Bioinformatic approaches to the investigation of the atavistic genes implicated in cancer
Accepted: 30 July 2021 Published: 30 August 2021
Introduction: Cancer is a widespread phenomenon occurring across multicellular organisms and represents a condition of atavism, wherein cells follow a path of reverse evolution that unlocks a toolkit of ancient pre-existing adaptations by disturbing hub genes of the human gene network. This results to a primitive cellular phenotype which resembles a unicellular life form. Methods: In the present study, we have employed bioinformatic approaches for the in-depth investigation of twelve atavistic hub genes (ACTG1, CTNNA1, CTNND1, CTTN, DSP, ILK, PKN2, PKP3, PLEC, RCC2, TLN1 and VASP), which exhibit highly disrupted interactions in diverse types of cancer and are associated with the formation of metastasis. To this end, phylogenetic analyses were conducted towards unravelling the evolutionary history of those hubs and tracing the origin of cancer in the Tree of Life. Results: Based on our results, most of those genes are of unicellular origin, and some of them can be traced back to the emergence of cellular life itself (atavistic theory). Our findings indicate how deep the evolutionary roots of cancer actually are, and may be exploited in the clinical setting for the design of novel therapeutic approaches and, particularly, in overcoming resistance to antineoplastic treatment.
Atavism; Cancer; Bioinformatics; Evolution; Phylogeny; Biological pathways; Unicellularity; Multicellularity
Cancer’s origin dates back to the emergence of multicellularity itself, about one billion years ago , since cancer and cancel-like phenomena have been observed in almost all species that exhibit either clonal or aggregative multicellularity , indicating that spontaneous tumor formation has deep evolutionary roots . Cancer is the result of the breakdown of complex molecular and cellular mechanisms, which are necessary to enable multicellular cooperation by regulating cell growth, cell differentiation, cell death and senescence, resulting in a more primitive cellular phenotype that resembles a unicellular life form . Each one of the hallmarks of cancer  is a direct “violation” of the principles of multicellular cooperation . In point of fact, the transition from unicellular to multicellular life was only possible when cooperating cells acquired a selective advantage over those who lived independently by inhibiting their own growth and replication .
From an evolutionary perspective, cancer is suggested to occur because early in the evolution of life, cells were ‘designed’ so as to maximize their replication capacity. However, cancer is actually uncommon because during the emergence of multicellularity, natural selection at the level of the individual led to the emergence of robust mechanisms to suppress it . Nevertheless, the paradox of cancer is that cancer cells, which initially disrupt the principles of multicellular cooperation, end up implementing those same principles [7, 8], especially in neoplasms of advanced stages ; as a consequence, tumors resemble more of an ecosystem than a simple aggregate of cells  or a rather “pseudomulticellular neotissue” . Cancer cells represent a lower level of organization of life, similar to our Cambrian ancestors, and as such are capable of transitioning from multicellularity to unicellularity, but can never adapt the phenotype of complex multicellularity .
Although healthy cells, of both unicellular and multicellular origin, exhibit a finely tuned coordination of expression of biological processes during carcinogenesis, this coordination is markedly disrupted, resulting in a characteristic up-regulation of genes of unicellular origin, detected in various human cancer types where cancer cells maintain control over cell cycle activity , as well as significant inactivation of genes which are associated with multicellularity and, therefore, have evolved more recently . This phenomenon of enhanced segregation of cellular processes with different evolutionary ages is called “mutual exclusivity” and is common among tumors, and is of particular importance for tumor development  and, ultimately, cancer progression.
For mutual exclusivity events to occur, certain fundamental alterations to the gene network need to take place. The human gene network consists of two main subnetworks comprised of genes of unicellular and multicellular origin, respectively. The “multicellular” network has been progressively built upon the “unicellular” one during billions of years of evolution, which led to the formation of an intricate network [12, 13], dedicated to maintain the complex phenotypes and cooperative growth required for multicellularity . Those subnetworks are interconnected in the human gene network through “hub” genes that appeared during the early metazoan life in order to enhance intercellular cooperation , and more precisely at the evolutionary boundary between unicellularity and multicellularity; as a result, they reflect key points in the evolutionary transition from unicellular to multicellular life . Those genes represent “points of vulnerability”, since mutual exclusivity occurs particularly due to the alteration of their interactions . Hence, only a limited amount of driver mutations is thought to be responsible for the transition of a normal cell to a malignant state [16, 17, 18], indicating that mutations in these hub genes result in widespread dysregulation of the gene network and are sufficient to initiate carcinogenesis, partially, through a process of de-differentiation . Particularly, since the “unicellular” subnetwork is denser and exhibits a higher inside/outside interaction ratio compared to the “multicellular” subnetwork, the former acts as an attractor that renders the cells of multicellular organisms vulnerable to carcinogenesis (principles of atavistic model for cancer evolution) .
The phenotype exhibited by cancer cells resembles that of a unicellular form of life because it is achieved through a process of de-differentiation, also referred to as “reverse evolution” . Through a series of consecutive reversionary transitions, cancer progression follows a similar pattern, but in reverse, that is, to the gradual transition from unicellularity to multicellularity . Particularly, the emergence of common characteristics among cancer cells, regardless of the tissue they originated from, indicates that the occurrence and progression of cancer may be a controlled transition from a complex multicellular phenotype to a primitive unicellular one . Through a small number of mutations in hub genes, mutual exclusivity events occur, and cancer cells activate pre-existing ancestral genes and pathways which render cancer cells remarkably robust. Besides, the mechanisms and genes involved in carcinogenesis are mainly evolutionarily ancient and highly conserved, mostly because they play a crucial role in vital cellular functions of a healthy cell .
Therefore, according to the “atavistic model” of cancer, cancer represents an atavism at the cellular level and cancer cells are not just “rogue” cells that were generated through a series of random mutations, but rather an ancient form of life that lies dormant within healthy metazoan cells . In other words, cancer cells do not construct a gene network ab intitio and acquire traits through random mutations and a few decades of internal Darwinian selection within the host’s body, but strategically take advantage of certain components of the existing gene networks . Characteristic examples include the healthy cells’ ability to multiply rapidly and migrate during wound healing , traits that at the same time render cells vulnerable to cancer . The same applies to rapid angiogenesis, which is necessary in wound healing to supply new cells with oxygen and nutrients , but also a hallmark of cancer , with cancer cells even utilizing the same angiogenic signaling pathways as the ones used by the healthy cells of a multicellular organism to develop the vascular system . Another example is the behavior of cells in the early developmental stages, such as the invasion of cells into adjacent developing tissues during gastrulation and the ability of some cells to transform from immotile epithelial cells into motile mesenchymal cells, a process termed “epithelial-mesenchymal transition” (EMT). If cells do not possess the necessary capabilities to perform these functions, growth cannot be achieved; however, these same cell capabilities enable cancer cells to metastasize .
The pathways of cell differentiation are initially identical to all organisms and then branch off in different taxonomic divisions . Accordingly, tracing the origin of emergence and evolutionary history of certain genes can be important, especially for the most ancient genes that play a crucial role in cancer progression compared to the more recently evolved ones, since the effects of inactivating the former tend to be more pronounced as they are more likely to lead to cell death .
In the present study, we investigated certain genes which have previously been proven to exhibit a highly disrupted number of interactions across multiple tumor types and contribute to the phenomenon of mutual exclusivity . More precisely, Trigos and colleagues  studied a pair of cellular processes, that is, chromosome organization and cellular junction organization. The co-expression of genes involved in those processes is highly important for the eukaryotic cells of a multicellular organism and the co-expression of those genes was strongly disrupted in tumors. Both of these processes involve genes of both unicellular and multicellular origin, and the dramatic change in the co-expression of those genes suggests that mutual exclusivity between these processes occurs during carcinogenesis and is actually advantageous to the development of different cancer stages such as early cancer, late cancer, and metastasis. A set of twelve atavistic genes, which represent the “hubs” between the unicellular and multicellular processes was identified: RCC1, TLN1, VASP, ACTG1, PLEC, CTTN, DSP, ILK, PKN2, CTNNA1, CTNND1 and PKP3. Those genes act as regulators of co-expression of the genes involved in the two aforementioned processes and their hubness was dramatically changed in seven different solid tumor types. Therefore, due to their central role in the human gene network, those genes represent fundamental points of vulnerability particularly regarding the phenomenon of mutual exclusivity and, consequently, carcinogenesis. To these data is added the fact that these 12 genes interact with genes associated with genomic instability, as well as genes associated with poor prognosis for cancer progression and metastasis . Moreover, these 12 genes play a critical role in regulatory networks associated with genomic instability and metastasis and are generally involved in key processes of carcinogenesis . Therefore, these genes can be considered as pan-cancer molecular markers or regulators of malignancy in diverse cancer tumors .
To this end, we have employed a bioinformatics approach to explore the involvement of those genes in various cancer types and performed phylostratigraphic analyses [14, 31], in an effort to elucidate the evolutionary trajectory of these genes aiming towards tracing the origin of cancer in the Tree of Life.
3. Materials and methods
3.1 Sequence database searching
In this study, we followed the evolutionary lineage of the contemporary human species since the organisms or taxonomic divisions under investigation represent important links of human evolution: Homo sapiens (human), Pan troglodytes (chimpanzee), Macaca mulatta (Rhesus monkey), Callithrix jacchus (marmoset), Mus musculus (mouse), Rattus norvegicus (rat), Canis lupus familiaris (dog), Equus caballus (horse), Sus scrofa (pig), Bos taurus (cattle), Tursiops truncatus (dolphin), Pteropus vampyrus (bat), Monodelphis domestica (opossum), Ornythorhynchus anatinus (platypus), Gallus gallus (chicken), Xenopus laevis (frog), Latimeria chalumnae (coelacanth), Danio rerio (zebrafish), Callorhinchus milii (shark), Petromyzon marinus (lamprey), Ciona intestinalis (vase tunicate), Strongylocentrotus purpuratus (sea urchin), Amphimedon queenslandica (sponge), Monosiga brevicollis (choanoflagellate), Saccharomyces cerevisiae (baker’s yeast), Schizosaccharomyces pombe (fission yeast), Actinobacteria, Chlamydiae, Cyanobacteria, Proteobacteria, Firmicutes, Bacteroidetes, Archaea.
The official names of the genes were initially retrieved from the HGNC database [32, 33] and then the accession numbers of the peptide sequences corresponding to the human genes were retrieved from the publicly available non-redundant NCBI Reference Sequence Database (RefSeq) . The amino acid sequences were used subsequently as probes in an extensive series of BLASTp  reciprocal searches in order to obtain the canonical homologous amino acid sequences corresponding to the species included in this study. This process was reiterated until no novel sequences could be detected, ensuring that a full representation of each gene’s family is obtained.
3.2 Alignment and phylogenetic analysis
To investigate the evolutionary history of each gene, we conducted comprehensive phylogenetic analysis using the entire length protein sequences of the species under study. The full-length amino acid sequences were aligned with MAFFT v.7 (https://mafft.cbrc.jp/alignment/server/) . The alignments were subsequently used to reconstruct phylogenetic trees by employing two separate methods, Maximum Likelihood, a method based on a heuristic approach for finding the optimal tree that fits the observed data, and Neighbor Joining, a method based on a hierarchical clustering algorithm , as implemented in the software package MEGA (https://www.megasoftware.net/), version 10 . Furthermore, MEGA v.10  was used to estimate the best-fit substitution model, which best describes the number of observed amino acid substitutions per position. For both methods of phylogenetic tree reconstruction, bootstrap analyses (150 pseudo-replicates) were conducted in order to evaluate the robustness and the statistical significance of the inferred reconstructed trees. Finally, the phylogenetic trees were visualized with MEGA v.10 .
3.3 Pathways identification
3.4 Differential gene expression analysis
RNA sequencing data for tumor and corresponding normal tissue samples from the TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) databases, respectively, were retrieved from the GEPIA2 website (http://gepia2.cancer-pku.cn/). The atavistic genes that are differentially expressed (DE) between tumor and normal samples were identified using ANOVA; threshold value for absolute log fold change logFC 2 and FDR-adjusted p-value (or q-value) 0.05.
3.5 Functional network of hubs
4.1 Atavistic genes’ association with cancer
By conducting a thorough and comprehensive review of studies published in PubMed (https://pubmed.ncbi.nlm.nih.gov/) and The Human Protein Atlas , we found those cancers each of the 12 genes is involved in; even different types of cancers that can affect the same organ (Table 1, Ref. [43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237]). In this context, certain genes have been shown to exhibit either oncogenic or tumor suppressive effects. In fact, both qualitative and quantitative modifications were identified in the genes under study which are associated with the development and progression of different cancers in different tissues. In particular, the types of alterations observed in those genes and/or their protein products, include aberrant, increased or decreased, expression (Table 2), epigenetic modifications, mutations, gene inactivation or amplification, copy number alterations, altered protein interactions and post-translational modifications, characteristic protein subcellular localization. Furthermore, these genes constitute diagnostic and prognostic biomarkers in cancer, regarding malignancy, disease stage, clinical subtypes, disease progression, metastasis, clinical outcome and survival and prediction of patients’ response to therapeutic treatments. In addition, each gene and/or its products constitute drug targets or are considered as novel potential drug targets for at least one type of cancer.
|Organ system||Types of cancer||Metastasis||Biomarker||Drug target||Type of alteration||Oncogenic (O) or tumor suppression (TS) effect||Reference|
|RCC2||Gene’s expression is regulated by p53, thus it plays an important role in metastasis|||
|It regulates apoptosis by blocking RAC1 signaling. The gene’s expression levels in tumor cells are used to predict response to chemotherapy.|||
|Brain and nervous system||Glioblastoma||+|||
|Breast||Breast Cancer||+||Wnt pathway|||
|Gastrointestinal||Gastric Cancer||Aberrant expression|||
|Genitourinary and gynecologic||Epithelial Ovarian Carcinoma||+||+|||
|Ovarian Cancer||+||RalA pathway|||
|Thoracic and respiratory||Lung Adenocarcinoma||+||Increased expression|||
|TLN1||Bone and muscle sarcoma||Malignant Fibrous Histiocytoma (MFH)||Mutations|||
|Ewing Sarcoma Family of Tumors (EFT)|
|Brain and nervous system||Glioblastoma||+|||
|Breast||Triple-negative Breast Cancer||+|||
|Endocrine system||Thyroid Cancer||+||Increased expression|||
|Gastrointestinal||Hepatocellular Carcinoma||+||+||Decreased expression||[58, 59]|
|Genitourinary and gynecologic||Prostate Cancer||+||+||Increased expression||[60, 61]|
|Ovarian Cancer||Increased expression|||
|Head and neck||Nasopharyngeal Carcinoma||+||Increased expression|||
|Oral Squamous Cell Carcinoma||+||+||Increased expression|||
|Hematopoietic||Chronic Myeloid Leukemia||Increased expression|||
|VASP||Bone and muscle sarcoma||Osteosarcoma||+|||
|Gastrointestinal||Hepatocellular Carcinoma||+||+||Increased expression||[43, 68]|
|Gastric (stomach) Cancer||+||PI3/AKT pathway|||
|Genitourinary and gynecologic||Renal Cell Carcinoma||+||+||Post-translational modifications (phosphorylation)||[43, 71]|
|Hematopoietic||Chronic Myeloid Leukemia||+||Aberrant expression|||
|Post-translational modifications (phosphorylation)|
|Thoracic and respiratory||Lung Adenocarcinoma||+||Increased expression|||
|ACTG1||Bone and muscle sarcoma||Osteosarcoma||+||+||Increased expression|||
|Breast||Breast Cancer||Increased expression|||
|Gastrointestinal||Alcohol related Hepatocellular Carcinoma||+||Increased expression||[77, 78]|
|Colorectal Cancer||+||+||[43, 79]|
|Genitourinary and gynecologic||Renal Cancer||+|||
|Cervical Cancer||+||Epigenetic modification (methylation)|||
|Hematopoietic||Acute Lymphoblastic Leukemia (children)||+||SNPs|||
|Skin||Skin Cancer||+||+||Increased expression|||
|Thoracic and respiratory||Non-small Cell Lung Cancer||+||+|||
|PLEC||Gastrointestinal||Hepatocellular Carcinoma||+||+||Decreased expression|||
|Pancreatic Ductal Adenocarcinoma||+||+|||
|Genitourinary and gynecologic||Renal Cancer||+|||
|Testicular Germ Cell Tumors||+|||
|Head and neck||Paranasal sinus carcinoma||Increased expression|||
|Oral Squamous Cell Carcinoma||+||Decreased expression|||
|Skin||Melanoma||+||Copy number alterations|||
|Thoracic and respiratory||Lung Cancer||+|||
|CTTN||CTTN is a well-established oncogene, associated with advanced disease stage and poor prognosis.|||
|Bone and muscle sarcoma||Osteosarcoma||+||Increased expression|||
|Brain and nervous system||Glioma||Increased expression|||
|Breast||Breast Cancer||Post-translational modification (phosphorylation)|||
|Endocrine system||Thyroid Cancer||+||+||Increased expression|||
|Hepatocellular Carcinoma||+||+||Increased expression||[98, 99]|
|Colorectal Cancer||+||Increased expression||[100, 101]|
|Genitourinary and gynecologic||Bladder Cancer||+|||
|Ovarian Epithelial Cancer||+||Increased expression|||
|Prostate Cancer||+||Increased expression|||
|Renal Clear Cell Carcinoma||+|||
|Head and neck||Head and Neck Squamous Cell Carcinomas||+||+||[91, 106]|
|Esophageal Squamous Cell Carcinoma||+||+||+||Increased expression||[107, 108]|
|Oral Squamous Cell Carcinoma||+||+||+||Gene amplification||[109, 110]|
|Pharyngolaryngeal Squamous Cell Carcinomas||+||+||Gene amplification|||
|Oropharynx Squamous Cell Carcinoma||+||Gene amplification|||
|Laryngeal Cancer||+||[111, 112]|
|Hematopoietic||B-cell Acute Lymphoblastic Leukemia||+||+||Increased expression|||
|Cutaneous Squamous Cell Carcinoma||+||Post-translational modification (phosphorylation)|||
|Thoracic and respiratory||Non-small Cell Lung Cancer||+||Increased expression|||
|DSP||Breast||Breast Cancer||+||Decreased expression|||
|Gastric Cancer||Decreased expression|||
|Hepatocellular Carcinoma||+||Decreased expression|||
|Genitourinary and gynecologic||Ovarian Cancer||+||+||Increased expression|||
|High-grade Serous Ovarian Cancer||+||Characteristic expression profile|||
|Head and neck||Oral Squamous Cell Carcinoma||+||Decreased expression|||
|Oropharyngeal Squamous Cell Carcinomas||+||+||Decreased expression|||
|Thoracic and respiratory||Lung Adenocarcinoma||Characteristic expression profiles|||
|Lung Squamous Cell Carcinoma||Characteristic subcellular localization|
|Non-small Cell Lung Cancer||+||Decreased expression due to epigenetic modification (methylation)|||
|ILK||Increased expression is associated with an aggressive phenotype and metastasis in many types of cancer.|||
|Brain and nervous system||Neuroblastoma||+||LIMS1/ILK pathway|||
|Breast||Breast Cancer||+||+||+||Increased expression||[130, 131, 132]|
|Endocrine system||Thyroid Cancer||+||+||Aberrant expression|||
|Gastrointestinal||Colorectal Cancer||+||+||Increased expression|||
|Pancreatic Ductal Adenocarcinoma||+||+||Increased expression|||
|Hepatocellular Carcinoma||Increased expression|||
|Gallbladder Squamous Cell Carcinoma||+||+||+||Increased expression|||
|Adenosquamous Gallbladder Carcinomas|
|Pancreatic Cancer||+||+||+||KRAS-ILK regulatory feedback loop|||
|Gastric Cancer||+||+||Increased expression|||
|Genitourinary and gynecologic||Ovarian Epithelial Cancer||+||+||Increased expression||[140, 141]|
|Bladder Cancer||+||+||+||ILK/PI3K/Akt pathway|||
|Renal Clear Cell Carcinoma||+||+||[43, 143]|
|Prostate Cancer||+||Cell cycle regulation|||
|Head and neck||Salivary Adenoid Cystic Carcinoma||+||+||Increased expression|||
|Laryngeal Squamous Cell Carcinoma||+||+||+||Increased expression|||
|Esophageal Squamous Cell Carcinoma||+||Increased expression|||
|Hematopoietic||Chronic Myeloid Leukemia||+|||
|Acute Myeloid Leukemia|
|Skin||Melanoma||Impaired post-translational modification (phosphorylation)|||
|Thoracic and respiratory||Non-small Cell Lung Cancer||+||+|||
|PKN2||Breast||Triple-negative Breast Cancer||+||+||Increased expression||TS||[151, 152]|
|Head and Neck||Oral Squamous Cell Carcinoma (smokers)||+||+||Increased expression|||
|Post-translational modification (hyperphosphorylation)|
|Gastrointestinal||Colon Cancer||+||+||Decreased expression||TS||[43, 154]|
|Genitourinary and gynecologic||Prostate Cancer||+||Increased expression||[155, 156]|
|Bladder Cancer||+||Increased expression|||
|CTNNA1||CTNNA1 is generally considered as a tumor suppressor|
|Brain and nervous system||Glioblastoma||Increased expression|||
|Breast||Luminal Breast Cancer||Increased expression|||
|Triple-negative Breast Cancer (basal-like)||NF-kB pathway||TS|||
|Lobular Type Breast Carcinoma||+||Aberrant expression|||
|Endocrine system||Differentiated Thyroid Carcinoma||+||+||Decreased expression|||
|Gastrointestinal||Colorectal Cancer||+||+||Pseudogene CTNNAP1||[162, 163, 164]|
|Cell cycle regulation|
|Gastric Cancer||+||Deleterious variants|||
|Pancreatic Ductal Adenocarcinoma||+||+||Inactivation||[166, 167, 168]|
|Impaired epigenetic modification (methylation)|
|Hepatocellular Carcinoma||+||Decreased expression|||
|Genitourinary and gynecologic||Bladder Cancer||+||Protein interactions|||
|Ovarian Cancer||+||Epigenetic modification (methylation)|||
|Renal Cell Carcinoma||Decreased expression||[43, 173]|
|Head and neck||Oral Squamous Cell Carcinoma||+||Decrease protein levels|||
|Characteristic subcellular localization|
|Esophageal Cancer||+||Decreased expression|||
|Hematopoietic||Myelodysplastic Syndromes||+||Chromosome 5q deletion|||
|Acute Myeloid Leukemia||Epigenetic modifications (methylation and histone deacetylation of the promoter)|
|Immune system||Thymoma||+||Characteristic expression profile|||
|Thoracic and respiratory||Non-small Cell Lung Cancer||+||Decreased expression||[180, 181, 182]|
|CTNND1||In fact, p120 catenin appears to have both pro-oncogenic and anti-oncogenic effects, depending on the localization and the specific function of p120 catenin in each cell compartment.|||
|Loss, downregulation or mislocalization of p120 catenin is observed in most human cancers.|||
|Bone and muscle sarcoma||Osteosarcoma||+||Increased expression|||
|Brain and nervous system||Astrocytoma||+||Abnormal post-translational modification (hyperphosphorylation)|||
|Breast||Breast Cancer||+||+||Increased expression||[190, 191]|
|Isomorphs (basal-like and luminal subtypes)|
|Characteristic subcellular localization|
|Breast Invasive Lobular Carcinoma||+||Decreased expression||[191, 192]|
|Characteristic subcellular localization|
|Endocrine-resistant Breast Cancer||+||Decreased expression|||
|Characteristic subcellular localization|
|Triple-negative Breast Cancer (basal like)||Decreased expression||[191, 193]|
|Characteristic subcellular localization|
|Gastrointestinal||Colorectal Cancer||+||+||+||Increased expression||[194, 195, 196]|
|Gastric Cancer||+||+||Increased expression||[197, 198, 199]|
|Characteristic subcellular localization|
|Hepatocellular Carcinoma||Increased expression||O||[200, 201]|
|Pancreatic Ductal Adenocarcinoma||+||+||+||Decreased expression||TS||[202, 203, 204]|
|Characteristic subcellular localization|
|Solid Pseudopapillary Tumors of the Pancreas||+||Decreased expression||[203, 205]|
|Characteristic subcellular localization|
|Genitourinary and gynecologic||Bladder Cancer||+||Decreased expression|||
|Characteristic subcellular localization|
|Cervical Cancer||+||Aberrant expression|||
|Endometrial Cancer||Decreased expression|||
|Prostatic Adenocarcinoma||+||+||Decreased expression|||
|Renal Cancer||+||+||+||Isophorm Increased expression||[43, 210]|
|Ovarian Cancer||+||Characteristic subcellular localization|||
|Head and neck||Head and Neck Squamous Cell Carcinomas||+||Decreased expression|||
|Esophageal Squamous Cell Carcinoma||+||Decreased expression||TS|||
|Characteristic subcellular localization|
|Hematopoietic||Acute Lymphoblastic Leukemia||+||Increased expression|||
|Skin||Skin Squamous Cell Carcinoma||Decreased expression||[215, 216]|
|Characteristic subcellular localization|
|Characteristic subcellular localization|
|Thoracic and respiratory||Lung Cancer||+||Increased expression||O|||
|Characteristic subcellular localization|
|Lung Adenocarcinoma||+||Decreased expression|||
|Lung Squamous Cell Carcinoma|
|Non-small Cell Lung Cancer||Decreased expression|||
|PKP3||Downregulation of PKP3 leads to tumor formation, a decrease in cell adhesion, promotion of EMT and metastasis||[220, 221, 222]|
|Breast||Breast Cancer||+||Increased expression|||
|Gastrointestinal||Gastric Adenocarcinoma||Decreased expression|||
|Gastrointestinal Cancer||+||+||Increased expression|||
|Genitourinary and gynecologic||Ovarian Cancer||+||+||+||Increased expression||O||[121, 226, 227]|
|Bladder Cancer||+||Increased expression|||
|Characteristic subcellular localization|
|Prostatic Adenocarcinoma||+||Increased expression||[229, 230]|
|Uterine Carcinosarcoma||+||Epigenetic modification (methylation)|||
|Head and neck||Oropharynx Squamous Cell Carcinoma||+||+||Decreased expression|||
|Nasopharyngeal Carcinoma||+||Decreased expression (DNP carcinogen factor)|||
|Skin||Melanoma||+||+||+||Immune response||[121, 234]|
|Thoracic and respiratory||Lung Adenocarcinoma||+||+||Increased expression|||
|Non-small Cell Lung Cancer||+||Aberrant expression|||
|CTTN||OV, LAML, UCS||Down|
|DSP||CESC, COAD, LUAD, LUSC, OV, THYM, TGCT, UCEC,UCS, READ||Up|
|PKP3||UCS, LUSC, OV, THYM, STAD, UCEC, PAAD, READ, CESC, COAD||Up|
|RCC1||GBM, THYM, DLBC||Up|
|Up, up-regulation; Down, down-regulation.|
The critical role of these genes and their corresponding products in carcinogenesis is highlighted by the fact that they are all involved in cancer-relevant pathways and processes, usually more than one (Table 3). More specifically, the identified cancer signaling pathways include the Wnt pathway (RCC2, DSP, CTNND1), the MAPK pathway (TLN1, CTTN, PKP3), the VEGF pathway (TLN1, CTNNA1, CTNND1), the PI3K-Akt pathway (VASP, ILK, PKN2), the Hippo pathway (ACTG1, CTNNA1), the PPAR pathway (ILK) and the Rap1 pathway (VASP, CTNND1, ACTG1, TLN1). Moreover, particularly vital processes of the cell, which also play a role in carcinogenesis, are eukaryotic cell cycle regulation and mitosis (RCC2, ILK, CTNNA1, CTNND1), apoptosis (ACTG1, PLEC, DSP, CTTN, CTNND1), immune system processes (TLN1, VASP, ACTG1, DSP, PKP3) and interaction with proteoglycans in cancer (ACTG1, CTTN). Finally, the proteins that constitute the adherens junctions (ACTG1, CTNNA1, CTNND1) and contribute to focal adhesions (VASP, TLN1, ACTG1) play a critical role especially in metastasis.
|Cell cycle regulation and mitosis||+||+||+||+|
|Immune system processes||+||+||+||+||+|
|Interaction with proteoglycans in cancer||+||+|
Of note, based on the STRING database analysis, the most significantly enriched pathway of the 12 gene/proteins is ‘cell junction assembly’ (GO: 0034329; FDR = 4.10 10). In this network (Fig. 1), ten hub genes/gene products appear to interact either physically or functionally in the process of cell juction organization, having an integral role in EMT which is essential in cancer progression and metastasis .
Therefore, the importance of the examined genes is enhanced by their involvement in pathways related to carcinogenesis and the progression of the disease in various types of cancer.
4.2 Phylogenetic analysis
In terms of overall topology, there is congruence between the phylogenetic trees that were generated with both methods. The trees constructed with the maximum likelihood method are considered more accurate and reliable and they display higher bootstrap values (Figs. 2,3,4, 5,6,7,8,9,10,11,12). These high bootstrap values indicate that the tree nodes are statistically significant and the inferred topology is biologically significant. The trees generated with the neighbor-joining method can be found at the Supplementary material.
The ILK, CTNNA1, CTNND1 and PKP3 genes are detected exclusively in multicellular Animals as shown in the phylogenetic trees in Figs. 2,3,4, respectively. Therefore, those genes most likely first appeared in a eukaryotic multicellular organism which was the common ancestor of Metazoa.
Catenins A (CTNNA) and catenins D (CTNND) are members of the catenin superfamily (Fig. 3). CTNNA1, CTNNA2, CTNNA3, CTNND1, CTNND2 genes are paralogs which probably occurred through a series of gene duplication events. The corresponding orthologous proteins of each gene form distinct clades, and as a result the phylogenetic tree is divided into two major subtrees, comprised of protein sequences encoded by CTNNA and CTNND genes, respectively. The subtree of CTNNA includes the protein sequences encoded by CTNNA1, CTNNA2 and CTNNA3. CTNNA2 appears to be the primordial gene as it was first detected in Amphimedon queenslandica, thus it probably first emerged in an ancestor of Porifera after their divergence from Choanoflagellates, since an ortholog was not found in Monosiga brevicollis. On the other hand, CTNNA1 and CTNNA3 were detected for the first time in Callorhinchus milli, and thus, they appeared later in evolution and probably occurred due to duplication events of the CTNNA2 gene, as they most likely first appeared in an ancestor of Chondrichthyes after their divergence from Tunicates, since orthologs were not detected in Ciona intestinalis and in fact they demonstrate high similarity to each other. The subtree of catenins D includes the protein sequences encoded by CTNND1 and CTNND2. CTNND2 is apparently the primordial gene as it was first detected in Amphimedon queenslandica, and thus it probably first arose in an ancestor of Porifera after their divergence from Choanoflagellates, since an ortholog was not detected in Monosiga brevicollis. On the other hand, CTNND1 appeared later in evolution and probably occurred due to CTNND2 gene duplication, as it was detected for the first time in Ciona intestinalis. Therefore, CTNND1 might have arisen in an ancestor of Tunicates after their divergence from Echinodermata, given that CTNND1 orthologs were not detected in Strongylocentrotus purpuratus.
The PKP1, PKP2, PKP3, PKP4 genes are likely paralogs (Fig. 4) which probably occurred through a series of gene duplication events of an ancestral PKP gene. The corresponding orthologs of each gene form distinct clades. All PKP genes were detected for the first time in Callorhinchus milli, suggesting that they probably appeared in an ancestor of Chondrichthyes after their divergence from Tunicates, since PKP orthologs were not detected in Ciona intestinalis. Based on the inferred phylogenetic tree, however, PKP1 and PKP2 exhibit the highest similarity, followed by PKP3. We could speculate that PKP4 is the primordial gene of this family, since it is basal to PKP1, PKP2 and PKP3. PKP3 appeared later in evolution, probably due to PKP4 gene duplication, while PKP1 and PKP2 have emerged even more recently through another series of duplication events in a chondrichthyan PKP1/2 gene and have not accumulated a large number of mutations.
VASP and Enah/Vasp-Like are likely paralogs (Fig. 5). In Monosiga brevicollis, Strongylocentrotus purpuratus, Ciona intestinalis and Callorhinchus milli the corresponding detected genes were annotated as VASP-like in RefSeq, but display high similarity to the VASP genes of the rest of Metazoa.
The PLEC and TLN1 genes were detected in unicellular and multicellular organisms, as shown in Figs. 8,9, respectively, and they probably first appeared in a eukaryotic unicellular organism that was the common ancestor of Animalia and Fungi.
PLEC homologs were found in Animalia as well as in Fungi (SAC6 in Saccharomyces cerevisiae and FM1 in Schizosaccharomyces pombe) (Fig. 8).
The TLN1 and TLN2 genes are likely paralogs (Fig. 9), and their corresponding orthologous protein sequences form distinct clades. TLN1/2 is probably the primordial gene of this family, since it was first detected in Amphimedon queenslandica, Monosiga brevicollis, Ciona intestinalis and Strongylocentrotus purpuratus which gave rise to TLN1 and TLN2 after successive gene duplications. Talin homologs were also identified in Fungi, that is, SLA2P in Saccharomyces cerevisiae and END4 in Schizosaccharomyces pombe, as also confirmed in literature [239, 240]. Therefore, although members of the TLN1 gene family were found only in Metazoa, it has deep evolutionary roots in some ancient unicellular eukaryotic organism, which is the common ancestor of Animalia and Fungi.
The characteristically long clade corresponding to Monosiga brevicollis, as shown in Figs. 5,6,7,8,9, is due to the evolutionary course of the organism, as it evolved for many millions of years separately from the rest of the Metazoa.
The evolutionary origin of ACTG1, RCC2 and PKN2 genes can be traced to a universal common ancestor, namely an ancient prokaryotic unicellular organism, that is the common ancestor of Animalia, Bacteria and Archaea as illustrated in Figs. 10,11,12, respectively.
The ACTA1, ACTA2, ACTB, ACTC1, ACTG1, ACTG2 genes are likely paralogs (Fig. 10), the orthologs of which cluster together in distinct clades. The phylogenetic tree is divided into two major subtrees, one comprised of protein sequences encoded by genes of different types of cytoplasmic actins and the other includes sequences encoded by genes of different types of muscle actins.
The subtree of cytoplasmic actins harbors the protein sequences encoded by ACTG1 (Actin cytoplasmic 2), ACTB (Actin cytoplasmic 1) as well as various other actin genes. ACTG1 is apparently the ancestral gene of this family as it was detected in Animalia, Bacteria (Microbacterium arborescens (Actinobacteria), Chlamydia trachomatis (Chlamydiae), Leptolyngbya sp. PCC 7376 (Cyanobacteria), Kangiella spongicola (Proteobacteria), Staphylococcus aureus (Firmicutes)), as well as Archaea (Candidatus Heimdallarchaeota (Archaea), Candidatus Lokiarchaeota (Archaea)). The sequences detected in bacteria do not cluster together, but are rather scattered among those corresponding to genes that encode the two types of cytoplasmic actins in Metazoa. This is indicative of high similarity among the aforementioned genes, since the encoded protein sequences appear to be highly conserved. Additionally, Actin genes found in Fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe) exhibit high similarity to Actin genes found in Archaea, which encode cytoplasmic actin 2.
On the other hand, the ACTB gene likely appeared later in evolution and probably occurred due to a duplication event of the ACTG1 gene, as it was detected for the first time in Petromyzon marinus. Also, in Ciona intestinalis, a cytoplasmic actin gene and a muscle actin gene were identified, and in fact the gene encoding the cytoplasmic actin shows high similarity to the only ACTIN gene detected in Monosiga brevicollis. Finally, Actin-85C-Like gene found in Amphimedon queenslandica also demonstrates high similarity to types of cytoplasmic actin.
The subtree of muscle actins, includes the protein sequences encoded by ACTA1 (Actin alpha 1, skeletal muscle), ACTA2 (Actin alpha 2, smooth muscle), ACTC1 (Actin alpha cardiac muscle 1) and ACTG2 (Actin gamma 2, enteric smooth muscle). Muscle actin genes appear to be the primordial genes of all muscle actin encoding genes as they were first identified in Strongylocentrotus purpuratus and Ciona intestinalis; thus, the gene probably first appeared in a common ancestor of Echinodermata and Chordata after their divergence from Porifera, since an ortholog was not detected in Amphimedon queenslandica. ACTA2 and ACTC1 genes were first detected in Callorhinchus milli, ACTA1 in Danio rerio, and ACTG2 in Latimeria chalumnae, respectively. We would expect to find the ACTA1 and ACTG2 genes in Callorhinchus milli, as it is the first organism in this study to have differentiated organs, but the sequences were not detected using BLAST. In any case, we believe that these genes occurred through a series of gene duplication events yielding four paralogs that probably first appeared in an ancestor of the Chondrichthyes after their divergence from Echinodermata and Tunicates.
In summary, those genes encoding different types of cytoplasmic actins are evolutionarily older, since those genes that encode different types of muscle actins appeared later in evolution. Specifically, ACTG1 is the ancestral gene of the entire family, since it is the evolutionarily older out of all paralogs found in Metazoa.
The RCC1 and RCC2 genes are likely paralogs, and their corresponding orthologous protein sequences form distinct clades (Fig. 11). RCC1 is probably the primordial gene of this family as it was detected in Metazoa, Bacteria Bifidobacterium asteroides (Actinobacteria), Parachlamydia sp. C2 (Chlamydiae), Synechococcus sp. WH 8103 (Cyanobacteria), Myxococcus xanthus (Proteobacteria), Cohnella sp. CAU 1483 (Firmicutes), Hymenobacter chitinivorans (Bacteroidetes) and Methanocella conradii (Archaea). RCC1 and RCC2 homologs have also been identified in Fungi, that is, SRM1 in Saccharomyces cerevisiae and PIM1 in Schizosaccharomyces pombe, as confirmed in literature [241, 242]. Furthermore, although the corresponding gene in Monosiga brevicollis and Amphimedon queenslandica is annotated as RCC in RefSeq, it displays high similarity to the RCC1 gene. Thus, RCC1 probably first appeared in a common ancestor of Eukaryotes, Bacteria and Archaea. RCC2 on the other hand, might have appeared later in evolution, as it was detected for the first time in Strongylocentrotus purpuratus, and probably occurred due to duplication of the RCC1 gene in an ancestor of Echinodermata after their divergence from the phylum of Porifera, since an RCC2 ortholog was not detected in Amphimedon queenslandica. Therefore, although RCC2 is found only in Metazoa, its ancestor is traced to some ancient prokaryotic unicellular organism, that is, the common ancestor of Eukaryotes, Bacteria and Archaea.
The PKN1, PKN2, PKN3, PKN, PKC genes are likely paralogs, the orthologs of which cluster together in distinct clades (Fig. 12). PKN was detected in Amphimedon queenslandica, in the unicellular Choanoflagellate Monosiga brevicollis, in Bacteria Streptomyces seoulensis (Actinobacteria), Chlamydia ibidis (Chlamydiae), Chloracidobacterium thermophilum (Cyanobacteria), Escherichia coli (Proteobacteria), Paenibacillus donghaensis (Firmicutes), Spirosoma panaciterrae (Bacteroidetes) and in Archaea (Methanoregula boonei and Thermococcus thioreducens) and is likely the primordial gene of this family and precursor of the PKN1, PKN2 and PKN3 genes which probably occurred through a series of PKN gene duplication events. The PKC gene was also detected in Petromyzon marinus, as well as in Fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe). PKN2 is apparently the oldest one as it was first detected in Ciona intestinalis and Strongylocentrotus purpuratus, so it probably first appeared in a common ancestor of Tunicates and Echinodermata after their divergence from Choanoflagellates, since an PKN2 ortholog was not detected in Monosiga brevicollis. PKN1 most likely emerged later as it was first detected in Callorhinchus milli; it probably first appeared in an ancestor of Chondrichthyes after their divergence from Tunicates, since an PKN1 ortholog was not detected in Ciona intestinalis. PKN3 was detected for the first time in Latimeria chalumnae, so it probably first emerged in an ancestor of Actinists after their divergence from Osteichthyes, since an PKN3 ortholog was not detected in Danio rerio. Therefore, although PKN2 was found exclusively in Metazoa, it has very deep evolutionary roots found in some ancient prokaryotic unicellular organism, that is the common ancestor of Animalia, Bacteria and Archaea.
According to the findings of this in silico study, three different types of genes were identified within the 12 ‘hub’ genes, in terms of their evolutionary age. Fırst and foremost, genes of unicellular origin that are in fact associated with the emergence of the first cellular life forms. In particular, ACTG1, RCC2 and PKN2 were detected in all domains of life, namely the empire Eukaryota (Animal and Fungi kingdoms) and the empire Prokaryota (Eubacteria and Archaebacteria kingdoms). Second, genes of unicellular origin that are associated with the emergence of the first eukaryotic life forms, namely the VASP, DSP, CTTN, PLEC and TLN1 genes. Third, genes of multicellular origin that are in fact associated with the evolution of multicellularity in the Animal kingdom. In particular, the ILK, CTNNA1, CTNND1 and PKP3 genes were detected exclusively in Metazoa; hence, they could be considered as genes of multicellular origin. Therefore, these are highly conserved genes of unicellular origin, which are in fact associated with the emergence of the first cellular life forms. Consequently, the investigated genes are considered to have deep evolutionary roots, with the most recently evolved ones being linked to the emergence of Metazoa and the most ancient ones having an evolutionary age of billions of years, thereby coinciding with the emergence of the first cellular life forms (Fig. 13).
In addition to their evolutionary age, the genes are involved in multiple cancer-related pathways and processes, and are associated with various forms of cancer, especially metastasis. Furthermore, they are characterized as hub genes and hold a particular position in the human gene network, on the boundary of unicellularity and multicellularity, and thus, contribute to the phenomenon of mutual exclusivity. Of particular note, all 12 genes have been linked to the most aggressive trait of cancer, that is, metastasis, in various types of cancers.
To further support the theory of “atavistic reversion” of cancer, the emerging model of the germ-and-soma life cycle  shows that cancer, uses not only first cellular, first eukaryotic, and Metzaoa I genes, but also genes of the late evolved unicellular organisms, respectively stemness and differentiation genes, as well as genome repair genes, including their own mechanisms of cancer stem cell production.
The findings of the present study can be applied on the design of therapeutic strategies, since the investigated genes and their products, as well as the processes and pathways in which they participate, could represent candidate pan-cancer biomarkers and potential targets for the development of a new class of pan-cancer treatment protocols that can be applied to any type of cancer. The development of therapeutic strategies based on the analysis of the configuration of the human gene network itself have been proposed. These approaches entail the cellular processes of a specific evolutionary age to be used as targets, and especially the genes of unicellular or multicellular origin that are highly interconnected and contribute to the phenomenon of mutual exclusivity, rendering them vulnerable and also potential drug targets .
Although the concept that cancer is linked with evolution was first proposed almost a century ago, laying in this way the foundation for the atavistic model of cancer [244, 245, 246], the application of evolutionary biology approaches to the study of neoplasms’ formation and progression is a recent endeavor. Comparative oncology is a novel and highly promising field of cancer research that can lead to a deeper understanding of cancer and contribute to the discovery of novel biomarkers and clinical therapeutic strategies.
Several other possible evolutionary approaches to cancer treatment and prevention have been proposed, mainly to address the problem of cancer cells’ remarkable resistance to therapeutic regimens. Given the resilience and diversity of different forms of cancer, the key lies in the common characteristics of all cancer cells, regardless of tumor type. The pathways and genes involved, in particular, can be utilized to the design of drugs that target cancer cells selectively and are effective against any cancer cell .
Another very promising approach concerns neoplasm ecology. In particular, the therapeutic approaches that have been proposed include the use of a combination of drugs , alteration of the competition between healthy and cancer cells by enhancing the adaptability of the former , selection of cells sensitive to chemotherapy  or cells exhibiting genetic stability  and, above all, treatments aiming at preventing the survival of resistant cells which lead to disease recurrence and recession after treatment .
Apart from the type of treatment, the manner in which it is administered is also important, as it can influence the evolutionary dynamics of tumor cells . Chemotherapy, for example, has different effect on cell competition when administered in large individual doses instead of small continuous doses , since the latter strategy diminishes the likelihood of creating resistant clones in the neoplasm population .
Herein, we have made an effort to track the emergence of twelve important hub cancer genes in the evolutionary history by phylostratigraphy. Based on our analyses, those genes that have been proven to play a crucial role in several aspects of cancer biology, as being part of an intricate regulatory network, are evolutionarily ancient, with a high fraction of them (67%) being of unicellular origin and existing well before humans emerged and evolved. The fact that most of the hub genes are of unicellular origin adds further support to the atavistic model of cancer, according to which the biological origin of cancer is believed to date before the emergence of multicellular animals, approximately 600 million years ago. In the light of evolution, cancer arises as a phenomenon that is inextricably linked with multicellularity itself, and therefore this should be taken into consideration, in order to deeply understand and efficiently tackle probably one of the oldest chronic diseases on the planet. In this way, anti-neoplastic therapeutic strategies could be developed tailored to the atavistic model, by targeting the most recently evolved key innovations (i.e., the so-called weaknesses) that have lost their ancestral functionality in cancer.
7. Author contributions
AGG conceived the study; AL and AP designed and run the in silico experiments; AL, IT and AP analyzed the data; AL, IT, AP and AGG wrote the manuscript.
8. Ethics approval and consent to participate
Işıl Takan acknowledges the YÖK (Yükseköğretim Kurulu) scholarship.
This research received no external funding.
11. Conflict of interest
The authors declare no conflict of interest.
Supplementary material associated with this article can be found, in the online version, at https://www.fbscience.com/Landmark/articles/10.52586/4944.
CESC, Cervical squamous cell carcinoma and endocervical adenocarcinoma; COAD, Colon adenocarcinoma; DLBC, Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; GBM, Glioblastoma multiforme; LAML, Acute Myeloid Leukemia; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; OV, Ovarian serous cystadenocarcinoma; PAAD, Pancreatic adenocarcinoma; READ, Rectum adenocarcinoma; SKCM, Skin Cutaneous Melanoma; STAD, Stomach adenocarcinoma; TGCT, Testicular Germ Cell Tumors; THYM, Thymoma; UCEC, Uterine Corpus Endometrial Carcinoma; UCS, Uterine Carcinosarcoma.
-  Aktipis CA, Nesse RM. Evolutionary foundations for cancer biology. Evolutionary Applications. 2013; 6: 144–159.
-  Aktipis CA, Boddy AM, Jansen G, Hibner U, Hochberg ME, Maley CC, et al. Cancer across the tree of life: cooperation and cheating in multicellularity. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences. 2015; 370: 20140219.
-  Domazet-Lošo T, Klimovich A, Anokhin B, Anton-Erxleben F, Hamm MJ, Lange C, et al. Naturally occurring tumours in the basal metazoan Hydra. Nature Communications. 2014; 5: 4222.
-  Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors. Proceedings of the National Academy of Sciences. 2017; 114: 6406–6411.
-  Hanahan D, Weinberg R. Hallmarks of Cancer: the next Generation. Cell. 2011; 144: 646–674.
-  Maynard Smith J, Szathmary E. The Major Transitions in Evolution. Oxford: Oxford University Press. 1997.
-  Cleary AS, Leonard TL, Gestl SA, Gunther EJ. Tumour cell heterogeneity maintained by cooperating subclones in Wnt-driven mammary cancers. Nature. 2014; 508: 113–117.
-  Marusyk A, Tabassum DP, Altrock PM, Almendro V, Michor F, Polyak K. Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature. 2014; 514: 54–58.
-  Jézéquel P, Campone M. Comment on ‘how the evolution of multicellularity set the stage for cancer’. British Journal of Cancer. 2018; 119: 133–134.
-  Niculescu VF. Is Cancer Cell Reversion to Normalcy Possible? Un Update. Novel Approaches in Cancer Study. 2020; 5: 500–503.
-  Vinogradov AE, Anatskaya OV. Cell-cycle dependence of transcriptome gene modules: comparison of regression lines. FEBS Journal. 2020; 287: 4427–4439.
-  Chen C, Ho A, Huang H, Juan H, Huang H. Dissecting the human protein-protein interaction network via phylogenetic decomposition. Scientific Reports. 2014; 4: 7153.
-  Schmitz JF, Zimmer F, Bornberg-Bauer E. Mechanisms of transcription factor evolution in Metazoa. Nucleic Acids Research. 2016; 44: 6287–6297.
-  Domazet-Loso T, Tautz D. Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa. BMC Biology. 2010; 8: 66.
-  Trigos AS, Pearson RB, Papenfuss AT, Goode DL. How the evolution of multicellularity set the stage for cancer. British Journal of Cancer. 2018; 118: 145–152.
-  Martincorena I, Raine KM, Gerstung M, Dawson KJ, Haase K, Van Loo P, et al. Universal Patterns of Selection in Cancer and Somatic Tissues. Cell. 2017; 171: 1029–1041.e21.
-  Schinzel AC, Hahn WC. Oncogenic transformation and experimental models of human cancer. Frontiers in Bioscience. 2008; 13: 71–84.
-  Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature. 2009; 458: 719–724.
-  Trigos AS, Pearson RB, Papenfuss AT, Goode DL. Somatic mutations in early metazoan genes disrupt regulatory links between unicellular and multicellular genes in cancer. Elife. 2019;8: e40947.
-  Vinogradov AE, Anatskaya OV. Evolutionary framework of the human interactome: Unicellular and multicellular giant clusters. Biosystems. 2019; 181: 82–87.
-  Chen H, Lin F, Xing K, He X. The reverse evolution from multicellularity to unicellularity during carcinogenesis. Nature Communications. 2015; 6: 6367.
-  Lineweaver CH, Bussey KJ, Blackburn AC, Davies PCW. Cancer progression as a sequence of atavistic reversions. BioEssays. 2021; 43: 2000305.
-  Weinberg RA. Oncogenes and the molecular biology of cancer. Journal of Cell Biology. 1983; 97: 1661–1662.
-  Davies PCW, Lineweaver CH. Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestors. Physical Biology. 2011; 8: 015001.
-  Guo S, Dipietro LA. Factors affecting wound healing. Journal of Dental Research. 2010; 89: 219–229.
-  Hofman P, Vouret-Craviari V. Microbes-induced EMT at the crossroad of inflammation and cancer. Gut Microbes. 2012; 3: 176–185.
-  Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000; 100: 57–70.
-  Papetti M, Herman IM. Mechanisms of normal and tumor-derived angiogenesis. American Journal of Physiology. Cell Physiology. 2002; 282: C947–C970.
-  Sulston JE, Horvitz HR. Post-embryonic cell lineages of the nematode, Caenorhabditis elegans. Developmental Biology. 1977; 56: 110–156.
-  Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nature Genetics. 2006; 38: 1043–1048.
-  Domazet-Loso T, Brajković J, Tautz D. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends in Genetics. 2007; 23: 533–539.
-  Bruford EA, Lush MJ, Wright MW, Sneddon TP, Povey S, Birney E. The HGNC Database in 2008: a resource for the human genome. Nucleic Acids Research. 2008; 36: D445–D448.
-  Eyre TA, Ducluzeau F, Sneddon TP, Povey S, Bruford EA, Lush MJ. The HUGO Gene Nomenclature Database, 2006 updates. Nucleic Acids Research. 2006; 34: D319–D321.
-  O’Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Research. 2016; 44: D733–D745.
-  Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. Journal of Molecular Biology. 1990; 215: 403–410.
-  Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Research. 2002; 30: 3059–3066.
-  Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution. 1987; 4: 406–425.
-  Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution. 2018; 35: 1547–1549.
-  Jassal B, Matthews L, Viteri G, Gong C, Lorente P, Fabregat A, et al. The reactome pathway knowledgebase. Nucleic Acids Research. 2020; 48: D498–D503.
-  Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Research. 2000; 28: 27–30.
-  Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Science. 2019; 28: 1947–1951.
-  Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Research. 2021; 49: D605–D612.
-  Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. A pathology atlas of the human cancer transcriptome. Science. 2017; 357: eaan2507.
-  Song C, Liang L, Jin Y, Li Y, Liu Y, Guo L, et al. RCC2 is a novel p53 target in suppressing metastasis. Oncogene. 2018; 37: 8–17.
-  Wu N, Ren D, Li S, Ma W, Hu S, Jin Y, et al. RCC2 over-expression in tumor cells alters apoptosis and drug sensitivity by regulating Rac1 activation. BMC Cancer. 2018; 18: 67.
-  Yu H, Zhang S, Ibrahim AN, Wang J, Deng Z, Wang M. RCC2 promotes proliferation and radio-resistance in glioblastoma via activating transcription of DNMT1. Biochemical and Biophysical Research Communications. 2019; 516: 999–1006.
-  Chen Z, Wu W, Huang Y, Xie L, Li Y, Chen H, et al. RCC2 promotes breast cancer progression through regulation of Wnt signaling and inducing EMT. Journal of Cancer. 2019; 10: 6837–6847.
-  Matsuo M, Nakada C, Tsukamoto Y, Noguchi T, Uchida T, Hijiya N, et al. MiR-29c is downregulated in gastric carcinomas and regulates cell proliferation by targeting RCC2. Molecular Cancer. 2013; 12: 15.
-  Bruun J, Kolberg M, Ahlquist TC, Røyrvik EC, Nome T, Leithe E, et al. Regulator of Chromosome Condensation 2 Identifies High-Risk Patients within both Major Phenotypes of Colorectal Cancer. Clinical Cancer Research. 2015; 21: 3759–3770.
-  Yi JM, Kang E, Kwon H, Bae J, Kang K, Ahuja N, et al. Epigenetically altered miR-1247 functions as a tumor suppressor in pancreatic cancer. Oncotarget. 2017; 8: 26600–26612.
-  Buranjiang G, Kuerban R, Abuduwanke A, Li X, Kuerban G. MicroRNA-331-3p inhibits proliferation and metastasis of ovarian cancer by targeting RCC2. Archives of Medical Science. 2019; 15: 1520–1529.
-  Gong S, Chen Y, Meng F, Zhang Y, Wu H, Li C, et al. RCC2, a regulator of the RalA signaling pathway, is identified as a novel therapeutic target in cisplatin-resistant ovarian cancer. FASEB Journal. 2019; 33: 5350–5365.
-  Pang B, Wu N, Guan R, Pang L, Li X, Li S, et al. Overexpression of RCC2 Enhances Cell Motility and Promotes Tumor Metastasis in Lung Adenocarcinoma by Inducing Epithelial-Mesenchymal Transition. Clinical Cancer Research. 2017; 23: 5598–5610.
-  Sarhadi VK, Lahti L, Scheinin I, Ellonen P, Kettunen E, Serra M, et al. Copy number alterations and neoplasia-specific mutations in MELK, PDCD1LG2, TLN1, and PAX5 at 9p in different neoplasias. Genes, Chromosomes & Cancer. 2014; 53: 579–588.
-  Kang W, Kim SH, Cho HJ, Jin J, Lee J, Joo KM, et al. Talin1 targeting potentiates anti-angiogenic therapy by attenuating invasion and stem-like features of glioblastoma multiforme. Oncotarget. 2015; 6: 27239–27251.
-  Singel SM, Cornelius C, Batten K, Fasciani G, Wright WE, Lum L, et al. A targeted RNAi screen of the breast cancer genome identifies KIF14 and TLN1 as genes that modulate docetaxel chemosensitivity in triple-negative breast cancer. Clinical Cancer Research. 2013; 19: 2061–2070.
-  Luo D, Zhan S, Xia W, Huang L, Ge W, Wang T. Proteomics study of serum exosomes from papillary thyroid cancer patients. Endocrine-Related Cancer. 2018; 25: 879–891.
-  Chen P, Lei L, Wang J, Zou X, Zhang D, Deng L, et al. Downregulation of Talin1 promotes hepatocellular carcinoma progression through activation of the ERK1/2 pathway. Cancer Science. 2017; 108: 1157–1168.
-  Chen P, Zheng X, Zhou Y, Xu Y, Zhu L, Qian Y. Talin-1 interaction network promotes hepatocellular carcinoma progression. Oncotarget. 2017; 8: 13003–13014.
-  Xu N, Chen H, Chen S, Xue X, Chen H, Zheng Q, et al. Upregulation of Talin-1 expression associates with advanced pathological features and predicts lymph node metastases and biochemical recurrence of prostate cancer. Medicine. 2016; 95: e4326.
-  Jin J, Tien P, Cheng C, Song JH, Huang C, Lin S, et al. Talin1 phosphorylation activates 1 integrins: a novel mechanism to promote prostate cancer bone metastasis. Oncogene. 2015; 34: 1811–1821.
-  Tang H, Yao L, Tao X, Yu Y, Chen M, Zhang R, et al. MiR-9 functions as a tumor suppressor in ovarian serous carcinoma by targeting TLN1. International Journal of Molecular Medicine. 2013; 32: 381–388.
-  Wang Z, Zhu Z, Lin Z, Luo Y, Liang Z, Zhang C, et al. MiR-429 suppresses cell proliferation, migration and invasion in nasopharyngeal carcinoma by downregulation of TLN1. Cancer Cell International. 2019; 19: 115.
-  Lai M, Hua C, Tsai M, Wan L, Lin Y, Chen C, et al. Talin-1 overexpression defines high risk for aggressive oral squamous cell carcinoma and promotes cancer metastasis. Journal of Pathology. 2011; 224: 367–376.
-  Halder A, Nayak KB, Chakraborty S. Ecotopic viral integration site 1 (EVI1) transcriptionally targets talin1 (TLN1) and upregulates its expression in chronic myeloid leukemia. Leukemia & Lymphoma. 2018; 59: 2008–2010.
-  Wu G, Wei L, Yu A, Zhang M, Qi B, Su K, et al. Vasodilator-stimulated phosphoprotein regulates osteosarcoma cell migration. Oncology Reports. 2011; 26: 1609–1615.
-  Tian Y, Xu L, He Y, Xu X, Li K, Ma Y, et al. Knockdown of RAC1 and VASP gene expression inhibits breast cancer cell migration. Oncology Letters. 2018; 16: 2151–2160.
-  Liu Z, Wang Y, Dou C, Xu M, Sun L, Wang L, et al. Hypoxia-induced up-regulation of VASP promotes invasiveness and metastasis of hepatocellular carcinoma. Theranostics. 2018; 8: 4649–4663.
-  Pitari GM, Cotzia P, Ali M, Birbe R, Rizzo W, Bombonati A, et al. Vasodilator-Stimulated Phosphoprotein Biomarkers are Associated with Invasion and Metastasis in Colorectal Cancer. Biomarkers in Cancer. 2020; 10: 1179299X18774551.
-  Chen H, Dai G, Cai Y, Gong Q, Wu W, Gao M, et al. Vasodilator-stimulated phosphoprotein (VASP), a novel target of miR-4455, promotes gastric cancer cell proliferation, migration, and invasion, through activating the PI3K/AKT signaling pathway. Cancer Cell International. 2018; 18: 97.
-  Zhao T, Liang X, Chen J, Bao Y, Wang A, Gan X, et al. ANGPTL3 inhibits renal cell carcinoma metastasis by inhibiting VASP phosphorylation. Biochemical and Biophysical Research Communications. 2019; 516: 880–887.
-  Bernusso VA, Machado-Neto JA, Pericole FV, Vieira KP, Duarte ASS, Traina F, et al. Imatinib restores VASP activity and its interaction with Zyxin in BCR-ABL leukemic cells. Biochimica et Biophysica Acta. 2015; 1853: 388–395.
-  Tokuo H, Bhawan J, Coluccio LM. Myosin X is required for efficient melanoblast migration and melanoma initiation and metastasis. Scientific Reports. 2018; 8: 10449.
-  Dertsiz L, Ozbilim G, Kayisli Y, Gokhan GA, Demircan A, Kayisli UA. Differential expression of VASP in normal lung tissue and lung adenocarcinomas. Thorax. 2005; 60: 576–581.
-  Li Y, Liang Q, Wen Y, Chen L, Wang L, Liu Y, et al. Comparative proteomics analysis of human osteosarcomas and benign tumor of bone. Cancer Genetics and Cytogenetics. 2010; 198: 97–106.
-  Huang S, Cai M, Zheng Y, Zhou L, Wang Q, Chen L. MiR-888 in MCF-7 Side Population Sphere Cells Directly Targets E-cadherin. Journal of Genetics and Genomics. 2014; 41: 35–42.
-  Yan Y, Xu H, Zhang L, Zhou X, Qian X, Zhou J, et al. RRAD suppresses the Warburg effect by downregulating ACTG1 in hepatocellular carcinoma. OncoTargets and Therapy. 2019; 12: 1691–1703.
-  Gao B, Li S, Tan Z, Ma L, Liu J. ACTG1 and TLR3 are biomarkers for alcohol-associated hepatocellular carcinoma. Oncology Letters. 2019; 17: 1714–1722.
-  Liu Y, Zhang Y, Wu H, Li Y, Zhang Y, Liu M, et al. MiR-10a suppresses colorectal cancer metastasis by modulating the epithelial-to-mesenchymal transition and anoikis. Cell Death & Disease. 2017; 8: e2739.
-  Wang J, Su Y, Tian Y, Ding Y, Wang X. Characterization of DNA hydroxymethylation profile in cervical cancer. Artificial Cells, Nanomedicine, and Biotechnology. 2019; 47: 2706–2714.
-  Ceppi F, Langlois-Pelletier C, Gagné V, Rousseau J, Ciolino C, De Lorenzo S, et al. Polymorphisms of the vincristine pathway and response to treatment in children with childhood acute lymphoblastic leukemia. Pharmacogenomics. 2014; 15: 1105–1116.
-  Dong X, Han Y, Sun Z, Xu J. Actin Gamma 1, a new skin cancer pathogenic gene, identified by the biological feature-based classification. Journal of Cellular Biochemistry. 2018; 119: 1406–1419.
-  Gan T, Xie Z, Tang R, Zhang T, Li D, Li Z, et al. Clinical value of miR-145-5p in NSCLC and potential molecular mechanism exploration: a retrospective study based on GEO, qRT-PCR, and TCGA data. Tumour Biology. 2017; 39: 1010428317691683.
-  Cheng C, Chao W, Liao C, Tseng Y, Lai YC, Lai Y, et al. Plectin deficiency in liver cancer cells promotes cell migration and sensitivity to sorafenib treatment. Cell Adhesion & Migration. 2018; 12: 19–27.
-  McInroy L, Määttä A. Plectin regulates invasiveness of SW480 colon carcinoma cells and is targeted to podosome-like adhesions in an isoform-specific manner. Experimental Cell Research. 2011; 317: 2468–2478.
-  Bausch D, Thomas S, Mino-Kenudson M, Fernández-del CC, Bauer TW, Williams M, et al. Plectin-1 as a Novel Biomarker for Pancreatic Cancer. Clinical Cancer Research. 2011; 17: 302–309.
-  Paumard-Hernández B, Calvete O, Inglada Pérez L, Tejero H, Al-Shahrour F, Pita G, et al. Whole exome sequencing identifies PLEC, EXO5 and DNAH7 as novel susceptibility genes in testicular cancer. International Journal of Cancer. 2018; 143: 1954–1962.
-  Yang Z, Zhang Y, Wang X, Huang J, Guo W, Wei P, et al. Putative biomarkers of malignant transformation of sinonasal inverted papilloma into squamous cell carcinoma. Journal of International Medical Research. 2019; 47: 2371–2380.
-  Rikardsen OG, Magnussen SN, Svineng G, Hadler-Olsen E, Uhlin-Hansen L, Steigen SE. Plectin as a prognostic marker in non-metastatic oral squamous cell carcinoma. BMC Oral Health. 2015; 15: 98.
-  Koroknai V, Ecsedi S, Vízkeleti L, Kiss T, Szász I, Lukács A, et al. Genomic profiling of invasive melanoma cell lines by array comparative genomic hybridization. Melanoma Research. 2016; 26: 100–107.
-  Hermida-Prado F, Menéndez ST, Albornoz-Afanasiev P, Granda-Diaz R, Álvarez-Teijeiro S, Villaronga MÁ, et al. Distinctive Expression and Amplification of Genes at 11q13 in Relation to HPV Status with Impact on Survival in Head and Neck Cancer Patients. Journal of Clinical Medicine. 2018; 7: 501.
-  Folio C, Zalacain M, Zandueta C, Ormazábal C, Sierrasesúmaga L, San Julián M, et al. Cortactin (CTTN) overexpression in osteosarcoma correlates with advanced stage and reduced survival. Cancer Biomarkers. 2011; 10: 35–41.
-  Su H-Y, Lin Z-Y, Peng W-C, Guan F, Zhu G-T, Mao B-B, et al. MiR-448 downregulates CTTN to inhibit cell proliferation and promote apoptosis in glioma. European Review for Medical and Pharmacological Sciences. 2018; 22: 3847–3854.
-  Zhang S, Qi Q. MTSS1 suppresses cell migration and invasion by targeting CTTN in glioblastoma. Journal of Neuro-Oncology. 2015; 121: 425–431.
-  Lang L, Hou Y, Chen Y, Tu G, Tao J, Yang D, et al. ATM-Mediated Phosphorylation of Cortactin Involved in Actin Polymerization Promotes Breast Cancer Cells Migration and Invasion. Cellular Physiology and Biochemistry. 2018; 51: 2972–2988.
-  Watkins RJ, Imruetaicharoenchoke W, Read ML, Sharma N, Poole VL, Gentilin E, et al. Pro-invasive Effect of Proto-oncogene PBF is Modulated by an Interaction with Cortactin. Journal of Clinical Endocrinology and Metabolism. 2016; 101: 4551–4563.
-  Kim DY, Lee JH, Kim KY, Kang DB, Park WC, Chae SC, et al. Association between genetic polymorphisms in cortactin and susceptibility to gastric cancer. Annals of Surgical Treatment and Research. 2015; 89: 74–80.
-  Gang Z, Ya-Lin K, Dong-Qing W, Yu L, Li R, Hong-Yi Z. Combining cortactin and CTTN detection with clinicopathologic features increases effectiveness of survival predictions for patients with resectable hepatocellular carcinoma. Clinical Laboratory. 2013; 59: 1343–1352.
-  Li Y, Fu Y, Hu X, Sun L, Tang D, Li N, et al. The HBx–CTTN interaction promotes cell proliferation and migration of hepatocellular carcinoma via CREB1. Cell Death & Disease. 2019; 10: 405.
-  Long H, Gao X, Lei C, Zhu B, Li L, Zeng C, et al. MiR-542-3p inhibits the growth and invasion of colorectal cancer cells through targeted regulation of cortactin. International Journal of Molecular Medicine. 2016; 37: 1112–1118.
-  Zhang X, Liu K, Zhang T, Wang Z, Qin X, Jing X, et al. Cortactin promotes colorectal cancer cell proliferation by activating the EGFR-MAPK pathway. Oncotarget. 2017; 8: 1541–1554.
-  Tokui N, Yoneyama MS, Hatakeyama S, Yamamoto H, Koie T, Saitoh H, et al. Extravasation during bladder cancer metastasis requires cortactin-mediated invadopodia formation. Molecular Medicine Reports. 2014; 9: 1142–1146.
-  Li A, Zhang L, Zhang X, Jin W, Ren Y. Expression and clinical significance of cortactin protein in ovarian neoplasms. Clinical & Translational Oncology. 2016; 18: 220–227.
-  Nakane K, Fujita Y, Terazawa R, Atsumi Y, Kato T, Nozawa Y, et al. Inhibition of cortactin and SIRT1 expression attenuates migration and invasion of prostate cancer DU145 cells. International Journal of Urology. 2012; 19: 71–79.
-  Shen H, Liu Q, Yang P, Tian Y. Protein interactions of cortactin in relation to invadopodia formation in metastatic renal clear cell carcinoma. Tumour Biology. 2015; 36: 3417–3422.
-  Ramos-García P, González-Moles MÁ, Ayén Á, González-Ruiz L, Ruiz-Ávila I, Gil-Montoya JA. Prognostic and clinicopathological significance of CTTN/cortactin alterations in head and neck squamous cell carcinoma: Systematic review and meta-analysis. Head & Neck. 2019; 41: 1963–1978.
-  Lu P, Qiao J, He W, Wang J, Jia Y, Sun Y, et al. Genome-wide gene expression profile analyses identify CTTN as a potential prognostic marker in esophageal cancer. PLoS ONE. 2014; 9: e88918.
-  Luo M, Shen X, Zhang Y, Wei F, Xu X, Cai Y, et al. Amplification and overexpression of CTTN (EMS1) contribute to the metastasis of esophageal squamous cell carcinoma by promoting cell migration and anoikis resistance. Cancer Research. 2006; 66: 11690–11699.
-  Horn D, Gross M, Dyckhoff G, Fuchs J, Grabe N, Weichert W, et al. Cortactin expression: Association with disease progression and survival in oral squamous cell carcinoma. Head & Neck. 2018; 40: 2685–2694.
-  Ramos-García P, González-Moles MÁ, González-Ruiz L, Ayén Á, Ruiz-Ávila I, Navarro-Triviño FJ, et al. An update of knowledge on cortactin as a metastatic driver and potential therapeutic target in oral squamous cell carcinoma. Oral Diseases. 2019; 25: 949–971.
-  Rodrigo JP, Álvarez-Alija G, Menéndez ST, Mancebo G, Allonca E, García-Carracedo D, et al. Cortactin and focal adhesion kinase as predictors of cancer risk in patients with laryngeal premalignancy. Cancer Prevention Research. 2011; 4: 1333–1341.
-  Villaronga MÁ, Hermida-Prado F, Granda-Díaz R, Menéndez ST, Álvarez-Teijeiro S, Quer M, et al. Immunohistochemical Expression of Cortactin and Focal Adhesion Kinase Predicts Recurrence Risk and Laryngeal Cancer Risk beyond Histologic Grading. Cancer Epidemiology, Biomarkers & Prevention. 2018; 27: 805–813.
-  Velázquez-Avila M, Balandrán JC, Ramírez-Ramírez D, Velázquez-Avila M, Sandoval A, Felipe-López A, et al. High cortactin expression in B-cell acute lymphoblastic leukemia is associated with increased transendothelial migration and bone marrow relapse. Leukemia. 2019; 33: 1337–1348.
-  Wei C, Zhu M, Yang Y, Zhang P, Yang X, Peng R, et al. Downregulation of RNF128 activates Wnt/-catenin signaling to induce cellular EMT and stemness via CD44 and CTTN ubiquitination in melanoma. Journal of Hematology & Oncology. 2019; 12: 21.
-  Zhu L, Cho E, Zhao G, Roh MR, Zheng Z. The Pathogenic Effect of Cortactin Tyrosine Phosphorylation in Cutaneous Squamous Cell Carcinoma. In Vivo. 2019; 33: 393–400.
-  Li Y, Zhang H, Gong H, Yuan Y, Li Y, Wang C, et al. MiR-182 suppresses invadopodia formation and metastasis in non-small cell lung cancer by targeting cortactin gene. Journal of Experimental & Clinical Cancer Research. 2018; 37: 141.
-  Davies EL, Gee JM, Cochrane RA, Jiang WG, Sharma AK, Nicholson RI, et al. The immunohistochemical expression of desmoplakin and its role in vivo in the progression and metastasis of breast cancer. European Journal of Cancer. 1999; 35: 902–907.
-  Palaniappan A, Ramar K, Ramalingam S. Computational Identification of Novel Stage-Specific Biomarkers in Colorectal Cancer Progression. PLoS ONE. 2016; 11: e0156665.
-  Wang H, Wu M, Lu Y, He K, Cai X, Yu X, et al. LncRNA MIR4435-2HG targets desmoplakin and promotes growth and metastasis of gastric cancer by activating Wnt/-catenin signaling. Aging. 2019; 11: 6657–6673.
-  Lee CF, Ling ZQ, Zhao T, Fang SH, Chang WC, Lee SC, et al. Genomic-wide analysis of lymphatic metastasis-associated genes in human hepatocellular carcinoma. World Journal of Gastroenterology. 2009; 15: 356–365.
-  Salerno EP, Bedognetti D, Mauldin IS, Deacon DH, Shea SM, Pinczewski J, et al. Human melanomas and ovarian cancers overexpressing mechanical barrier molecule genes lack immune signatures and have increased patient mortality risk. Oncoimmunology. 2016; 5: e1240857.
-  Xie H, Xu H, Hou Y, Cai Y, Rong Z, Song W, et al. Integrative prognostic subtype discovery in high-grade serous ovarian cancer. Journal of Cellular Biochemistry. 2019; 120: 18659–18666.
-  Hiraki A, Shinohara M, Ikebe T, Nakamura S, Kurahara S, Garrod DR. Immunohistochemical staining of desmosomal components in oral squamous cell carcinomas and its association with tumour behaviour. British Journal of Cancer. 1996; 73: 1491–1497.
-  Papagerakis S, Shabana A, Pollock BH, Papagerakis P, Depondt J, Berdal A. Altered desmoplakin expression at transcriptional and protein levels provides prognostic information in human oropharyngeal cancer. Human Pathology. 2009; 40: 1320–1329.
-  Young GD, Winokur TS, Cerfolio RJ, Van Tine BA, Chow LT, Okoh V, et al. Differential expression and biodistribution of cytokeratin 18 and desmoplakins in non-small cell lung carcinoma subtypes. Lung Cancer. 2002; 36: 133–141.
-  Yang L, Chen Y, Cui T, Knösel T, Zhang Q, Albring KF, et al. Desmoplakin acts as a tumor suppressor by inhibition of the Wnt/-catenin signaling pathway in human lung cancer. Carcinogenesis. 2012; 33: 1863–1870.
-  Canel M, Serrels A, Frame MC, Brunton VG. E-cadherin-integrin crosstalk in cancer invasion and metastasis. Journal of Cell Science. 2013; 126: 393–401.
-  Saeki N, Saito A, Sugaya Y, Amemiya M, Ono H, Komatsuzaki R, et al. Chromatin Immunoprecipitation and DNA Sequencing Identified a LIMS1/ILK Pathway Regulated by LMO1 in Neuroblastoma. Cancer Genomics & Proteomics. 2018; 15: 165–174.
-  Hausmann C, Temme A, Cordes N, Eke I. ILKAP, ILK and PINCH1 control cell survival of p53-wildtype glioblastoma cells after irradiation. Oncotarget. 2015; 6: 34592–34605.
-  Akrida I, Nikou S, Gyftopoulos K, Argentou M, Kounelis S, Zolota V, et al. Expression of EMT inducers integrin-linked kinase (ILK) and ZEB1 in phyllodes breast tumors is associated with aggressive phenotype. Histology & Histopathology. 2018; 33: 937–949.
-  Qu Y, Hao C, Xu J, Cheng Z, Wang W, Liu H. ILK promotes cell proliferation in breast cancer cells by activating the PI3K/Akt pathway. Molecular Medicine Reports. 2017; 16: 5036–5042.
-  Yang J, Hou Y, Zhou M, Wen S, Zhou J, Xu L, et al. Twist induces epithelial-mesenchymal transition and cell motility in breast cancer via ITGB1-FAK/ILK signaling axis and its associated downstream network. International Journal of Biochemistry & Cell Biology. 2016; 71: 62–71.
-  Shirley LA, McCarty S, Yang M, Saji M, Zhang X, Phay J, et al. Integrin-linked kinase affects signaling pathways and migration in thyroid cancer cells and is a potential therapeutic target. Surgery. 2016; 159: 163–170.
-  Tsoumas D, Nikou S, Giannopoulou E, Champeris Tsaniras S, Sirinian C, Maroulis I, et al. ILK Expression in Colorectal Cancer is Associated with EMT, Cancer Stem Cell Markers and Chemoresistance. Cancer Genomics & Proteomics. 2018; 15: 127–141.
-  Zhang K, Yao H, Yang Z, Li D, Yang L, Zou Q, et al. Comparison of ILK and ERP29 expressions in benign and malignant pancreatic lesions and their clinicopathological significances in pancreatic ductal adenocarcinomas. Clinical & Translational Oncology. 2016; 18: 352–359.
-  Peroukides S, Bravou V, Varakis J, Alexopoulos A, Kalofonos H, Papadaki H. ILK overexpression in human hepatocellular carcinoma and liver cirrhosis correlates with activation of Akt. Oncology Reports. 2008; 20: 1337–1344.
-  Li J, Yang Z, Ren X, Zou Q, Yuan Y, Liang L, et al. ILK and PRDX1 are prognostic markers in squamous cell/adenosquamous carcinomas and adenocarcinoma of gallbladder. Tumour Biology. 2013; 34: 359–368.
-  Chu P, Kulp SK, Bekaii-Saab T, Chen C. Targeting integrin-linked kinase to suppress oncogenic KRAS signaling in pancreatic cancer. Small GTPases. 2018; 9: 452–456.
-  Gu X, Xing X, Yang W, Hu J, Dai D. High expression of integrin-linked kinase predicts aggressiveness and poor prognosis in patients with gastric cancer. Acta Histochemica. 2014; 116: 758–762.
-  Choi YP, Kim BG, Gao M, Kang S, Cho NH. Targeting ILK and 4 integrin abrogates the invasive potential of ovarian cancer. Biochemical and Biophysical Research Communications. 2012; 427: 642–648.
-  Lu J, Xu Y, Zhao Z, Ke X, Wei X, Kang J, et al. Emodin suppresses proliferation, migration and invasion in ovarian cancer cells by down regulating ILK in vitro and in vivo. OncoTargets and Therapy. 2017; 10: 3579–3589.
-  Zhuang X, Lv M, Zhong Z, Zhang L, Jiang R, Chen J. Interplay between intergrin-linked kinase and ribonuclease inhibitor affects growth and metastasis of bladder cancer through signaling ILK pathways. Journal of Experimental & Clinical Cancer Research. 2016; 35: 130.
-  Khan MI, Dębski KJ, Dabrowski M, Czarnecka AM, Szczylik C. Gene set enrichment analysis and ingenuity pathway analysis of metastatic clear cell renal cell carcinoma cell line. American Journal of Physiology-Renal Physiology. 2016; 311: F424–F436.
-  Persad S, Attwell S, Gray V, Delcommenne M, Troussard A, Sanghera J, et al. Inhibition of integrin-linked kinase (ILK) suppresses activation of protein kinase B/Akt and induces cell cycle arrest and apoptosis of PTEN-mutant prostate cancer cells. Proceedings of the National Academy of Sciences. 2000; 97: 3207–3212.
-  Chen D, Zhang B, Kang J, Ma X, Lu Y, Gong L. Expression and clinical significance of FAK, ILK, and PTEN in salivary adenoid cystic carcinoma. Acta Oto-Laryngologica. 2013; 133: 203–208.
-  Wu P-A, Xie L-L, Zhao D-Y, Li S-S, Tang Q-L, Wang S-H, et al. Integrin-linked kinase is overexpressed in laryngeal squamous cell carcinoma and correlates with tumor proliferation, migration and invasion. European Review for Medical and Pharmacological Sciences. 2018; 22: 8740–8748.
-  Ma X-L, Yao H, Wang X, Wei Y, Cao L-Y, Zhang Q, et al. ILK predicts the efficacy of chemoradiotherapy and the prognosis of patients with esophageal squamous cell carcinoma. Oncology Letters. 2019; 18: 4114–4125.
-  de la Puente P, Weisberg E, Muz B, Nonami A, Luderer M, Stone RM, et al. Identification of ILK as a novel therapeutic target for acute and chronic myeloid leukemia. Leukemia Research. 2015; 39: 1299-1308.
-  El Kharbili M, Robert C, Witkowski T, Danty-Berger E, Barbollat-Boutrand L, Masse I, et al. Tetraspanin 8 is a novel regulator of ILK-driven 1 integrin adhesion and signaling in invasive melanoma cells. Oncotarget. 2017; 8: 17140–17155.
-  Chen D, Zhang Y, Zhang X, Li J, Han B, Liu S, et al. Overexpression of integrin-linked kinase correlates with malignant phenotype in non-small cell lung cancer and promotes lung cancer cell invasion and migration via regulating epithelial–mesenchymal transition (EMT)-related genes. Acta Histochemica. 2013; 115: 128–136.
-  Lin W, Huang J, Yuan Z, Feng S, Xie Y, Ma W. Protein kinase C inhibitor chelerythrine selectively inhibits proliferation of triple-negative breast cancer cells. Scientific Reports. 2017; 7: 2022.
-  Morais-Rodrigues F, Silv́erio-Machado R, Kato RB, Rodrigues DLN, Valdez-Baez J, Fonseca V, et al. Analysis of the microarray gene expression for breast cancer progression after the application modified logistic regression. Gene. 2020; 726: 144168.
-  Rajagopalan P, Nanjappa V, Patel K, Jain AP, Mangalaparthi KK, Patil AH, et al. Role of protein kinase N2 (PKN2) in cigarette smoke-mediated oncogenic transformation of oral cells. Journal of Cell Communication and Signaling. 2018; 12: 709–721.
-  Cheng Y, Zhu Y, Xu J, Yang M, Chen P, Xu W, et al. PKN2 in colon cancer cells inhibits M2 phenotype polarization of tumor-associated macrophages via regulating DUSP6-Erk1/2 pathway. Molecular Cancer. 2018; 17: 13.
-  Lachmann S, Jevons A, De Rycker M, Casamassima A, Radtke S, Collazos A, et al. Regulatory domain selectivity in the cell-type specific PKN-dependence of cell migration. PLoS ONE 2011; 6: e21732.
-  Yang C, Melhuish TA, Spencer A, Ni L, Hao Y, Jividen K, et al. The protein kinase C super-family member PKN is regulated by mTOR and influences differentiation during prostate cancer progression. Prostate. 2017; 77: 1452–1467.
-  Shinoura N, Paradies NE, Warnick RE, Chen H, Larson JJ, Tew JJ, et al. Expression of N-cadherin and alpha-catenin in astrocytomas and glioblastomas. British Journal of Cancer. 1995; 72: 627–633.
-  Hu X, Xiang D, Xie Y, Tao L, Zhang Y, Jin Y, et al. LSD1 suppresses invasion, migration and metastasis of luminal breast cancer cells via activation of GATA3 and repression of TRIM37 expression. Oncogene. 2019; 38: 7017–7034.
-  Piao H, Yuan Y, Wang M, Sun Y, Liang H, Ma L. Α-catenin acts as a tumour suppressor in E-cadherin-negative basal-like breast cancer by inhibiting NF-κB signalling. Nature Cell Biology. 2014; 16: 245–254.
-  Nakopoulou L, Gakiopoulou H, Keramopoulos A, Giannopoulou I, Athanassiadou P, Mavrommatis J, et al. C-met tyrosine kinase receptor expression is associated with abnormal beta-catenin expression and favourable prognostic factors in invasive breast carcinoma. Histopathology. 2000; 36: 313–325.
-  Böhm J, Niskanen L, Kiraly K, Kellokoski J, Eskelinen M, Hollmen S, et al. Expression and prognostic value of alpha-, beta-, and gamma-catenins indifferentiated thyroid carcinoma. Journal of Clinical Endocrinology and Metabolism. 2000; 85: 4806–4811.
-  Chen X, Zhu H, Wu X, Xie X, Huang G, Xu X, et al. Downregulated pseudogene CTNNAP1 promote tumor growth in human cancer by downregulating its cognate gene CTNNA1 expression. Oncotarget. 2016; 7: 55518–55528.
-  Raftopoulos I, Davaris P, Karatzas G, Karayannacos P, Kouraklis G. Level of alpha-catenin expression in colorectal cancer correlates with invasiveness, metastatic potential, and survival. Journal of Surgical Oncology. 1998; 68: 92–99.
-  Ikeguchi M, Makino M, Kaibara N. Clinical significance of E-cadherin-catenin complex expression in metastatic foci of colorectal carcinoma. Journal of Surgical Oncology. 2001; 77: 201–207.
-  Weren RDA, van der Post RS, Vogelaar IP, van Krieken JH, Spruijt L, Lubinski J, et al. Role of germline aberrations affecting CTNNA1, MAP3K6 and MYD88 in gastric cancer susceptibility. Journal of Medical Genetics. 2018; 55: 669–674.
-  Li Y, Meng Y, Ji X. Relationship between expressions of E-cadherin and alpha-catenin and biological behaviors of human pancreatic cancer. Hepatobiliary & Pancreatic Diseases International. 2003; 2: 471–477.
-  Niu N, Lu P, Yang Y, He R, Zhang L, Shi J, et al. Loss of Setd2 promotes Kras-induced acinar-to-ductal metaplasia and epithelia-mesenchymal transition during pancreatic carcinogenesis. Gut. 2020; 69: 715–726.
-  Joo Y, Rew J, Park C, Kim S. Expression of E-cadherin, alpha-and beta-catenins in patients with pancreatic adenocarcinoma. Pancreatology. 2002; 2: 129–137.
-  Kozyraki R, Scoazec JY, Flejou JF, D’Errico A, Bedossa P, Terris B, et al. Expression of cadherins and alpha-catenin in primary epithelial tumors of the liver. Gastroenterology. 1996; 110: 1137–1149.
-  Ashida K, Terada T, Kitamura Y, Kaibara N. Expression of E-cadherin, alpha-catenin, beta-catenin, and CD44 (standard and variant isoforms) in human cholangiocarcinoma: an immunohistochemical study. Hepatology 1998; 27: 974–982.
-  Kumari N, Saxena S, Agrawal U. Exosomal protein interactors as emerging therapeutic targets in urothelial bladder cancer. Journal of the Egyptian National Cancer Institute. 2015; 27: 51–58.
-  Chang P, Liao Y, Wang H, Chen Y, Huang R, Wang Y, et al. An epigenetic signature of adhesion molecules predicts poor prognosis of ovarian cancer patients. Oncotarget. 2017; 8: 53432–53449.
-  Aaltomaa S, Lipponen P, Kärjä V, Lundstedt S, Lappi J, Kosma V. The expression and prognostic value of alpha-, beta- and gamma-catenins in renal cell carcinoma. Anticancer Research. 2004; 24: 2407–2413.
-  Isaacs WB, Bova GS, Morton RA, Bussemakers MJ, Brooks JD, Ewing CM. Genetic alterations in prostate cancer. Cold Spring Harbor Symposia on Quantitative Biology. 1994; 59: 653–659.
-  Williams HK, Sanders DS, Jankowski JA, Landini G, Brown AM. Expression of cadherins and catenins in oral epithelial dysplasia and squamous cell carcinoma. Journal of Oral Pathology & Medicine. 1998; 27: 308–317.
-  Kadowaki T, Shiozaki H, Inoue M, Tamura S, Oka H, Doki Y, et al. E-cadherin and alpha-catenin expression in human esophageal cancer. Cancer Research. 1994; 54: 291–296.
-  Liu TX, Becker MW, Jelinek J, Wu W, Deng M, Mikhalkevich N, et al. Chromosome 5q deletion and epigenetic suppression of the gene encoding alpha-catenin (CTNNA1) in myeloid cell transformation. Nature Medicine. 2007; 13: 78–83.
-  Vodicka P, Krskova L, Odintsov I, Krizova L, Sedlackova E, Schutzner J, et al. Expression of molecules of the Wnt pathway and of E-cadherin in the etiopathogenesis of human thymomas. Oncology Letters. 2020; 19: 2413–2421.
-  Zhang XD, Hersey P. Expression of catenins and p120cas in melanocytic nevi and cutaneous melanoma: deficient alpha-catenin expression is associated with melanoma progression. Pathology. 1999; 31: 239–246.
-  Lee Y, Wu C, Chen C, Hsu H, Chang Y. The significance of E-cadherin and alpha-, beta-, and gamma-catenin expression in surgically treated non-small cell lung cancers of 3 cm or less in size. Journal of Thoracic and Cardiovascular Surgery. 2002; 123: 502–507.
-  Pirinen RT, Hirvikoski P, Johansson RT, Hollmén S, Kosma VM. Reduced expression of alpha-catenin, beta-catenin, and gamma-catenin is associated with high cell proliferative activity and poor differentiation in non-small cell lung cancer. Journal of Clinical Pathology. 2001; 54: 391–395.
-  Srivastava M, Khurana P, Sugadev R. Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data. BMC Research Notes. 2012; 5: 617.
-  Schackmann RCJ, Tenhagen M, van de Ven RAH, Derksen PWB. P120-catenin in cancer - mechanisms, models and opportunities for intervention. Journal of Cell Science. 2014; 126: 3515–3525.
-  Peglion F, Etienne-Manneville S. P120catenin alteration in cancer and its role in tumour invasion. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences. 2013; 368: 20130015.
-  Wu S, Du X, Wu M, Du H, Shi X, Zhang T. MicroRNA-409-3p inhibits osteosarcoma cell migration and invasion by targeting catenin-δ1. Gene. 2016; 584: 83–89.
-  Sato H, Hasegawa T, Kanai Y, Tsutsumi Y, Osamura Y, Abe Y, et al. Expression of cadherins and their undercoat proteins (alpha-, beta-, and gamma-catenins and p120) and accumulation of beta-catenin with no gene mutations in synovial sarcoma. Virchows Archiv. 2001; 438: 23–30.
-  Yang J, Bassuk AG, Merl-Pham J, Hsu C, Colgan DF, Li X, et al. Catenin delta-1 (CTNND1) phosphorylation controls the mesenchymal to epithelial transition in astrocytic tumors. Human Molecular Genetics. 2016; 25: 4201–4210.
-  Han L, Li Z, Jiang Y, Jiang Z, Tang L. SNHG29 regulates miR-223-3p/CTNND1 axis to promote glioblastoma progression via Wnt/-catenin signaling pathway. Cancer Cell International. 2019; 19: 345.
-  Ohno H, Uemura K, Shintani-Ishida K, Nakamura M, Inomata M, Yoshida K. Ischemia promotes calpain-mediated degradation of p120-catenin in SH-SY5Y cells. Biochemical and Biophysical Research Communications. 2007; 353: 547–552.
-  Gao X, Zhang Y, Zhang Z, Guo S, Chen X, Guo Y. MicroRNA-96-5p represses breast cancer proliferation and invasion through Wnt/-catenin signaling via targeting CTNND1. Scientific Reports. 2020; 10: 44.
-  Zhao W, Hoadley KA, Parker JS, Perou CM. Identification of mRNA isoform switching in breast cancer. BMC Genomics. 2016; 17: 181.
-  Vermeulen JF, van de Ven RAH, Ercan C, van der Groep P, van der Wall E, Bult P, et al. Nuclear Kaiso expression is associated with high grade and triple-negative invasive breast cancer. PLoS ONE. 2012; 7: e37864.
-  Pham TND, Perez White BE, Zhao H, Mortazavi F, Tonetti DA. Protein kinase C enhances migration of breast cancer cells through FOXC2-mediated repression of p120-catenin. BMC Cancer. 2017; 17: 832.
-  Ding X, Du J, Mao K, Wang X, Ding Y, Wang F. MicroRNA-143-3p suppresses tumorigenesis by targeting catenin-δ1 in colorectal cancer. OncoTargets and Therapy. 2019; 12: 3255–3265.
-  Gold JS, Reynolds AB, Rimm DL. Loss of p120ctn in human colorectal cancer predicts metastasis and poor survival. Cancer Letters. 1998; 132: 193–201.
-  Skoudy A, Gomez S, Fabre M, Garcia de Herreros A. P120-catenin expression in human colorectal cancer. International Journal of Cancer. 1996; 68: 14–20.
-  Karatzas G, Karayiannakis AJ, Syrigos KN, Chatzigianni E, Papanikolaou S, Simatos G, et al. Expression patterns of the E-cadherin-catenin cell-cell adhesion complex in gastric cancer. Hepato-Gastroenterology. 2000; 47: 1465–1469.
-  Wang Y, Liu C, Luo M, Zhang Z, Gong J, Li J, et al. Chemotherapy-Induced miRNA-29c/Catenin-δ Signaling Suppresses Metastasis in Gastric Cancer. Cancer Research. 2015; 75: 1332–1344.
-  Xing A, Wang Y, Su Z, Shi D, Wang B, Gao P. Catenin-δ1, negatively regulated by miR-145, promotes tumour aggressiveness in gastric cancer. Journal of Pathology. 2015; 236: 53–64.
-  Cao N, Mu L, Yang W, Liu L, Liang L, Zhang H. MicroRNA-298 represses hepatocellular carcinoma progression by inhibiting CTNND1-mediated Wnt/-catenin signaling. Biomedicine & Pharmacotherapy. 2018; 106: 483–490.
-  Tang B, Tang F, Wang Z, Qi G, Liang X, Li B, et al. Overexpression of CTNND1 in hepatocellular carcinoma promotes carcinous characters through activation of Wnt/-catenin signaling. Journal of Experimental & Clinical Cancer Research. 2016; 35: 82.
-  Hamada S, Satoh K, Miura S, Hirota M, Kanno A, Masamune A, et al. MiR-197 induces epithelial-mesenchymal transition in pancreatic cancer cells by targeting p120 catenin. Journal of Cellular Physiology. 2013; 228: 1255–1263.
-  Hendley AM, Wang YJ, Polireddy K, Alsina J, Ahmed I, Lafaro KJ, et al. P120 Catenin Suppresses Basal Epithelial Cell Extrusion in Invasive Pancreatic Neoplasia. Cancer Research. 2016; 76: 3351–3363.
-  Taniuchi K, Nakagawa H, Hosokawa M, Nakamura T, Eguchi H, Ohigashi H, et al. Overexpressed P-cadherin/CDH3 promotes motility of pancreatic cancer cells by interacting with p120ctn and activating rho-family GTPases. Cancer Research. 2005; 65: 3092–3099.
-  Chetty R, Jain D, Serra S. P120 catenin reduction and cytoplasmic relocalization leads to dysregulation of E-cadherin in solid pseudopapillary tumors of the pancreas. American Journal of Clinical Pathology. 2008; 130: 71–76.
-  Syrigos KN, Karayiannakis A, Syrigou EI, Harrington K, Pignatelli M. Abnormal expression of p120 correlates with poor survival in patients with bladder cancer. European Journal of Cancer. 1998; 34: 2037–2040.
-  Noordhuis MG, Fehrmann RSN, Wisman GBA, Nijhuis ER, van Zanden JJ, Moerland PD, et al. Involvement of the TGF-beta and beta-catenin pathways in pelvic lymph node metastasis in early-stage cervical cancer. Clinical Cancer Research. 2011; 17: 1317–1330.
-  Moreno-Bueno G, Hardisson D, Sarrió D, Sánchez C, Cassia R, Prat J, et al. Abnormalities of E- and P-cadherin and catenin (beta-, gamma-catenin, and p120ctn) expression in endometrial cancer and endometrial atypical hyperplasia. Journal of Pathology. 2003; 199: 471–478.
-  Kallakury BV, Sheehan CE, Ross JS. Co-downregulation of cell adhesion proteins alpha- and beta-catenins, p120CTN, E-cadherin, and CD44 in prostatic adenocarcinomas. Human Pathology. 2001; 32: 849–855.
-  Yanagisawa M, Huveldt D, Kreinest P, Lohse CM, Cheville JC, Parker AS, et al. A p120 catenin isoform switch affects Rho activity, induces tumor cell invasion, and predicts metastatic disease. Journal of Biological Chemistry. 2008; 283: 18344–18354.
-  Cheung LWT, Leung PCK, Wong AST. Cadherin switching and activation of p120 catenin signaling are mediators of gonadotropin-releasing hormone to promote tumor cell migration and invasion in ovarian cancer. Oncogene. 2010; 29: 2427–2440.
-  Kidacki M, Lehman HL, Green MV, Warrick JI, Stairs DB. P120-Catenin Downregulation and PIK3CA Mutations Cooperate to Induce Invasion through MMP1 in HNSCC. Molecular Cancer Research. 2017; 15: 1398–1409.
-  Chung Y, Lam AKY, Luk JM, Law S, Chan K, Lee P, et al. Altered E-cadherin expression and p120 catenin localization in esophageal squamous cell carcinoma. Annals of Surgical Oncology. 2007; 14: 3260–3267.
-  Juric D, Lacayo NJ, Ramsey MC, Racevskis J, Wiernik PH, Rowe JM, et al. Differential gene expression patterns and interaction networks in BCR-ABL-positive and -negative adult acute lymphoblastic leukemias. Journal of Clinical Oncology. 2007; 25: 1341–1349.
-  Ishizaki Y, Omori Y, Momiyama M, Nishikawa Y, Tokairin T, Manabe M, et al. Reduced expression and aberrant localization of p120catenin in human squamous cell carcinoma of the skin. Journal of Dermatological Science. 2004; 34: 99–108.
-  Perez-Moreno M, Song W, Pasolli HA, Williams SE, Fuchs E. Loss of p120 catenin and links to mitotic alterations, inflammation, and skin cancer. Proceedings of the National Academy of Sciences of the United States of America. 2008; 105: 15399–15404.
-  Castillo SD, Angulo B, Suarez-Gauthier A, Melchor L, Medina PP, Sanchez-Verde L, et al. Gene amplification of the transcription factor DP1 and CTNND1 in human lung cancer. Journal of Pathology. 2010; 222: 89–98.
-  Liu Y, Li Q, Miao Y, Xu H, Dai S, Wei Q, et al. Ablation of p120-catenin enhances invasion and metastasis of human lung cancer cells. Cancer Science. 2009; 100: 441–448.
-  Mortazavi F, An J, Dubinett S, Rettig M. P120-Catenin is Transcriptionally Downregulated by FOXC2 in Non–Small Cell Lung Cancer Cells. Molecular Cancer Research. 2010; 8: 762–774.
-  Aigner K, Descovich L, Mikula M, Sultan A, Dampier B, Bonné S, et al. The transcription factor ZEB1 (deltaEF1) represses Plakophilin 3 during human cancer progression. FEBS Letters. 2007; 581: 1617–1624.
-  Basu S, Chaudhary N, Shah S, Braggs C, Sawant A, Vaz S, et al. Plakophilin3 loss leads to an increase in lipocalin2 expression, which is required for tumour formation. Experimental Cell Research. 2018; 369: 251–265.
-  Kundu ST, Gosavi P, Khapare N, Patel R, Hosing AS, Maru GB, et al. Plakophilin3 downregulation leads to a decrease in cell adhesion and promotes metastasis. International Journal of Cancer. 2008; 123: 2303–2314.
-  Demirag GG, Sullu Y, Yucel I. Expression of Plakophilins (PKP1, PKP2, and PKP3) in breast cancers. Medical Oncology. 2012; 29: 1518–1522.
-  Demirag GG, Sullu Y, Gurgenyatagi D, Okumus NO, Yucel I. Expression of plakophilins (PKP1, PKP2, and PKP3) in gastric cancers. Diagnostic Pathology. 2011; 6: 1.
-  Valladares-Ayerbes M, Díaz-Prado S, Reboredo M, Medina V, Lorenzo-Patiño MJ, Iglesias-Díaz P, et al. Evaluation of plakophilin-3 mRNA as a biomarker for detection of circulating tumor cells in gastrointestinal cancer patients. Cancer Epidemiology, Biomarkers & Prevention. 2010; 19: 1432–1440.
-  Lim V, Zhu H, Diao S, Hu L, Hu J. PKP3 interactions with MAPK-JNK-ERK1/2-mTOR pathway regulates autophagy and invasion in ovarian cancer. Biochemical and Biophysical Research Communications. 2019; 508: 646–653.
-  Qian H, Yuan D, Bao J, Liu F, Zhang W, Yang X, et al. Increased expression of plakophilin 3 is associated with poor prognosis in ovarian cancer. Medicine. 2019; 98: e14608.
-  Takahashi H, Nakatsuji H, Takahashi M, Avirmed S, Fukawa T, Takemura M, et al. Up-regulation of plakophilin-2 and down-regulation of plakophilin-3 are correlated with invasiveness in bladder cancer. Urology. 2012; 79: 240.e1–240.e8.
-  Yang C, Ströbel P, Marx A, Hofmann I. Plakophilin-associated RNA-binding proteins in prostate cancer and their implications in tumor progression and metastasis. Virchows Archiv. 2013; 463: 379–390.
-  Breuninger S, Reidenbach S, Georg Sauer C, Ströbel P, Pfitzenmaier J, Trojan L, et al. Desmosomal Plakophilins in the Prostate and Prostatic Adenocarcinomas. American Journal of Pathology. 2010; 176: 2509–2519.
-  Li J, Xing X, Li D, Zhang B, Mutch DG, Hagemann IS, et al. Whole-Genome DNA Methylation Profiling Identifies Epigenetic Signatures of Uterine Carcinosarcoma. Neoplasia. 2017; 19: 100–111.
-  Papagerakis S, Shabana A, Depondt J, Gehanno P, Forest N. Immunohistochemical localization of plakophilins (PKP1, PKP2, PKP3, and p0071) in primary oropharyngeal tumors: correlation with clinical parameters. Human Pathology. 2003; 34: 565–572.
-  Li Y, Ju K, Wang W, Liu Z, Xie H, Jiang Y, et al. Dinitrosopiperazine-decreased PKP3 through upregulating miR-149 participates in nasopharyngeal carcinoma metastasis. Molecular Carcinogenesis. 2018; 57: 1763–1779.
-  Wang L-X, Li Y, Chen G-Z. Network-based co-expression analysis for exploring the potential diagnostic biomarkers of metastatic melanoma. PLoS ONE. 2018; 13: e0190447.
-  Furukawa C, Daigo Y, Ishikawa N, Kato T, Ito T, Tsuchiya E, et al. Plakophilin 3 oncogene as prognostic marker and therapeutic target for lung cancer. Cancer Research. 2005; 65: 7102–7110.
-  Mašić S, Brčić L, Krušlin B, Šepac A, Pigac B, Stančić-Rokotov D, et al. Expression of plakophilin 3 in diffuse malignant pleural mesothelioma. Histology and Histopathology. 2018; 33: 995–1004.
-  Kim H, Roh MS, Son CH, Kim AJ, Jee HJ, Song N, et al. Loss of Med1/TRAP220 promotes the invasion and metastasis of human non-small-cell lung cancer cells by modulating the expression of metastasis-related genes. Cancer Letters. 2012; 321: 195–202.
-  Knights AJ, Funnell APW, Crossley M, Pearson RCM. Holding Tight: Cell Junctions and Cancer Spread. Trends in Cancer Research. 2012; 8: 61–69.
-  Baggett JJ, D’Aquino KE, Wendland B. The Sla2p talin domain plays a role in endocytosis in Saccharomyces cerevisiae. Genetics. 2003; 165: 1661–1674.
-  Wesp A, Hicke L, Palecek J, Lombardi R, Aust T, Munn AL, et al. End4p/Sla2p Interacts with Actin-associated Proteins for Endocytosis in Saccharomyces cerevisiae. Molecular Biology of the Cell. 1997; 8: 2291–2306.
-  Clark KL, Ohtsubo M, Nishimoto T, Goebl M, Sprague GF. The yeast SRM1 protein and human RCC1 protein share analogous functions. Cell Regulation. 1991; 2: 781–792.
-  Kirkpatrick D, Solomon F. Overexpression of yeast homologs of the mammalian checkpoint gene RCC1 suppresses the class of alpha-tubulin mutations that arrest with excess microtubules. Genetics. 1994; 137: 381–392.
-  Niculescu VF. Germline Evolution in Cancer as Explained by the Germ and Soma Theory of Dual Cell Systems. Journal of Clinical & Anatomic Pathology. 2021; 6: 1–9.
-  Snow H. A Treatise, Practical and Theoretic, on Cancers and the Cancer-Process. American Journal of the Medical Sciences. 1893; 107: 311–312.
-  Ravenel MP. Malignancy and Evolution: a Biological Inquiry into the Nature and Causes of Cancer. American Journal of Public Health. 1926; 16: 1238–1238.
-  Nowell PC. The clonal evolution of tumor cell populations. Science. 1976; 194: 23–28.
-  Chabner BA, Roberts TG. Timeline: Chemotherapy and the war on cancer. Nature Reviews Cancer. 2005; 5: 65–72.
-  Maley CC, Reid BJ, Forrest S. Cancer prevention strategies that address the evolutionary dynamics of neoplastic cells: simulating benign cell boosters and selection for chemosensitivity. Cancer Epidemiology, Biomarkers & Prevention. 2004; 13: 1375–1384.
-  Komarova NL, Wodarz D. Evolutionary dynamics of mutator phenotypes in cancer: implications for chemotherapy. Cancer Research. 2003; 63: 6635–6642.
-  Merlo LMF, Pepper JW, Reid BJ, Maley CC. Cancer as an evolutionary and ecological process. Nature Reviews Cancer. 2006; 6: 924–935.
-  Suiter AM, Bänziger O, Dean AM. Fitness consequences of a regulatory polymorphism in a seasonal environment. Proceedings of the National Academy of Sciences of the United States of America. 2003; 100: 12782–12786.