Identification Of Cancer-associated Genes Research Articles

Essentiality, protein–protein interactions and evolutionary properties are key predictors for identifying cancer-associated genes using machine learning

The distinctive nature of cancer as a disease prompts an exploration of the special characteristics the genes implicated in cancer exhibit. The identification of cancer-associated genes and their characteristics is crucial to further our understanding of this disease and enhanced likelihood of therapeutic drug targets success. However, the rate at which cancer genes are being identified experimentally is slow. Applying predictive analysis techniques, through the building of accurate machine learning models, is potentially a useful approach in enhancing the identification rate of these genes and their characteristics. Here, we investigated gene essentiality scores and found that they tend to be higher for cancer-associated genes compared to other protein-coding human genes. We built a dataset of extended gene properties linked to essentiality and used it to train a machine-learning model; this model reached 89% accuracy and > 0.85 for the Area Under Curve (AUC). The model showed that essentiality, evolutionary-related properties, and properties arising from protein–protein interaction networks are particularly effective in predicting cancer-associated genes. We were able to use the model to identify potential candidate genes that have not been previously linked to cancer. Prioritising genes that score highly by our methods could aid scientists in their cancer genes research.

TGF-β downregulates CAIII expression via MAPK and PI3K signaling pathways in colon carcinoma and osteosarcoma cells

Identification of cancer-associated genes is critical for developing effective treatments of colorectal cancer (CRC). A limited number of studies have examined the mechanisms and genes underlying CRC. Abnormal transforming growth factor beta (TGF-?) expression was observed at different stages of carcinoma. We examined the effect of cancer-related cytokine TGF-? on carbonic anhydrase (CA) III gene expression in colon cancer HT-29 cells. TGF-? (500 U/mL) downregulated CAIII gene expression at both the mRNA and protein levels. Transient transfection experiments indicated that different CAIII promoter constructs were active in HT-29 cells. TGF-? reduced transcriptional activity of all promoter constructs, indicating that the potential response element for TGF-?-directed transcription lies within the -108/+86 region of the CAIII promoter. According to the non-Smad pathway inhibitory assay, TGF-? downregulated the CAIII gene through mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) and phosphoinositide-3-kinase (PI3K) pathways. The same decreasing effect was determined in the Saos-2, osteosarcoma cell line, indicating that the effect of TGF-? on CAIII was not tissue-specific. However, examination of PI3K and MAPK/ERK signaling pathways with suitable inhibitors revealed that the PI3K but not the MAPK/ERK pathway was responsible for TGF-? downregulation.

Analysis of mutations in CDC27, CTBP2, HYDIN and KMT5A genes in carotid paragangliomas

Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors that arise from paraganglionic tissue of the carotid body localizing at the bifurcation of carotid artery. These tumors are slowly growing, but occasionally they become aggressive and metastatic. Surgical treatment remains high-risk and extremely challenging; radiation and chemotherapy are poorly effective. The study of molecular pathogenesis of CPGLs will allow developing novel therapeutic approaches and revealing biomarkers. Previously, we performed the exome sequencing of 52 CPGLs and estimated mutational load (ML). Paired histologically normal tissues or blood were unavailable, so potentially germline mutations were excluded from the analysis with strong filtering conditions using 1000 Genomes Project and ExAC databases. In this work, ten genes (ZNF717, CDC27, FRG2C, FAM104B, CTBP2, HLA-DRB1, HYDIN, KMT5A, MUC3A, and PRSS3) characterized by the highest level of mutational load were analyzed. Using several prediction algorithms (SIFT, PolyPhen-2, MutationTaster, and LRT), potentially pathogenic mutations were identified in four genes (CDC27, CTBP2, HYDIN, and KMT5A). Many of these mutations occurred in the majority of cases, and their mutation type was checked using exome sequencing data of blood prepared with the same exome enrichment kit that was used for preparation of exome libraries from CPGLs. The majority of the mutations were germline that can apparently be associated with annotation errors in 1000 Genomes Pro ject and ExAC. However, part of the mutations identified in CDC27, CTBP2, HYDIN, and KMT5A remain potentially pathogenic, and there is a large body of data on the involvement of these genes in the formation and progression of other tumors. This allows considering CDC27, CTBP2, HYDIN, and KMT5A genes as potentially associated with CPGL pathogenesis and requires taking them into account in further investigations. Thus, there is a necessity to improve the methods for identification of cancer-asso ciated genes as well as pathogenic mutations.

Characterization and Prognostic Significance of Methylthioadenosine Phosphorylase Deficiency in Nasopharyngeal Carcinoma.

Identification of cancer-associated genes by genomic profiling contributes to the elucidation of tumor development and progression. The methylthioadenosine phosphorylase (MTAP) gene, located at chromosome 9p21, plays a critical role in tumorigenicity and disease progression in a wide variety of cancers. However, the prognostic impact of MTAP in patients with nasopharyngeal carcinoma (NPC) remains obscured. Through data mining from published transcriptomic database, MTAP was first identified as a differentially downregulated gene in NPC. In this study, our aim was to evaluate the expression of MTAP in NPC and to clarify its prognostic significance.MTAP immunohistochemistry was retrospectively performed and analyzed in biopsy specimens from 124 NPC patients who received standard treatment without distant metastasis at initial diagnosis. The immunoexpression status was correlated with the clinicopathological variables, disease-specific survival (DSS), distant metastasis-free survival (DMFS), and local recurrence-free survival (LRFS). Real-time quantitative polymerase chain reaction (PCR) was used to measure MTAP gene dosage. In some cases, we also performed methylation-specific PCR and pyrosequencing to assess the status of promoter methylation.MTAP deficiency was significantly associated with advanced tumor stages (P = 0.023) and univariately predictive of adverse outcomes for DSS, DMFS, and LRFS. In the multivariate comparison, MTAP deficiency still remained prognostically independent to portend worse DSS (P = 0.021, hazard ratio = 1.870) and DMFS (P = 0.009, hazard ratio = 2.154), together with advanced AJCC stages III to IV. Homozygous deletion or promoter methylation of MTAP gene were identified to be significantly associated with MTAP protein deficiency (P < 0.001).MTAP deficiency was correlated with an aggressive phenotype and independently predictive of worse DSS and DMFS, suggesting its role in disease progression and as an independent prognostic biomarker of NPC, which potentially offers new strategy of targeted treatment for patients lacking MTAP expression.

Gene amplification: mechanisms and involvement in cancer.

Gene amplification was recognized as a physiological process during the development of Drosophila melanogaster. Intriguingly, mammalian cells use this mechanism to overexpress particular genes for survival under stress, such as during exposure to cytotoxic drugs. One well-known example is the amplification of the dihydrofolate reductase gene observed in methotrexate-resistant cells. Four models have been proposed for the generation of amplifications: extrareplication and recombination, the breakage-fusion-bridge cycle, double rolling-circle replication, and replication fork stalling and template switching. Gene amplification is a typical genetic alteration in cancer, and historically many oncogenes have been identified in the amplified regions. In this regard, novel cancer-associated genes may remain to be identified in the amplified regions. Recent comprehensive approaches have further revealed that co-amplified genes also contribute to tumorigenesis in concert with known oncogenes in the same amplicons. Considering that cancer develops through the alteration of multiple genes, gene amplification is an effective acceleration machinery to promote tumorigenesis. Identification of cancer-associated genes could provide novel and effective therapeutic targets.

Oncogenes and pathway identification using filter-based approaches between various carcinoma types in lung.

Lung cancer accounts for the most cancer-related deaths. The identification of cancer-associated genes and the related pathways are essential to prevent many types of cancer. In this paper, a more systematic approach is considered. First, we did pathway analysis using Hyper Geometric Distribution (HGD) and significantly overrepresented sets of reactions were identified. Second, feature-selection-based Particle Swarm Optimisation (PSO), Information Gain (IG) and the Biomarker Identifier (BMI) for the identification of different types of lung cancer were used. We also evaluated PSO and developed a new method to determine the BMI thresholds to prioritize genes. We were able to identify sets of key genes that can be found in several pathways. Experimental results show that our method simplifies features effectively and obtains higher classification accuracy than the other methods from the literature.

Osteopontin Expression Correlates with Melanoma Invasion

Melanoma is one of the most aggressive cancers affecting humans. Although early melanomas are curable with surgical excision, metastatic melanomas are associated with high mortality. The mechanism of melanoma development, progression, and metastasis is largely unknown. In order to uncover genes unique to melanoma cells, we used high-density DNA microarrays to examine the gene expression profiles of metastatic melanoma nodules using benign nevi as controls. Over 190 genes were significantly overexpressed in metastatic melanomas compared with normal nevi by at least 2-fold. One of the most abundantly expressed genes in metastatic melanoma nodules is osteopontin (OPN). Immunohistochemistry staining on tissue microarrays and individual skin biopsies representing different stages of melanoma progression revealed that OPN expression is first acquired at the step of melanoma tissue invasion. In addition, blocking of OPN expression by RNA interference reduced melanoma cell numbers in vitro. Our observations suggest that OPN may be acquired early in melanoma development and progression, and may enhance tumor cell growth in invasive melanoma.