Somatic Mutational Profile of High-Grade Serous Ovarian Carcinoma and Triple-Negative Breast Carcinoma in Young and Elderly Patients: Similarities and Divergences

Background: Triple-negative breast cancer (TNBC) and High-Grade Serous Ovarian Cancer (HGSOC) are aggressive malignancies that share similarities; however, different ages of onset may reflect distinct tumor behaviors. Thus, our aim was to compare somatic mutations in potential driver genes in 109 TNBC and 81 HGSOC from young (Y ≤ 40 years) and elderly (E ≥ 75 years) patients. Methods: Open access mutational data (WGS or WES) were collected for TNBC and HGSOC patients. Potential driver genes were those that were present in the Cancer Gene Census—CGC, the Candidate Cancer Gene Database—CCGD, or OncoKB and those that were considered pathogenic in variant effect prediction tools. Results: Mutational signature 3 (homologous repair defects) was the only gene that was represented in all four subgroups. The median number of mutated CGCs per sample was similar in HGSOC (Y:3 vs. E:4), but it was higher in elderly TNBC than it was in young TNBC (Y:3 vs. E:6). At least 90% of the samples from TNBC and HGSOC from Y and E patients presented at least one known affected TSG. Besides TP53, which was mutated in 67–83% of the samples, the affected TSG in TP53 wild-type samples were NF1 (yHGSOC and yTNBC), PHF6 (eHGSOC and yTNBC), PTEN, PIK3R1 and ZHFX3 (yTNBC), KMT2C, ARID1B, TBX3, and ATM (eTNBC). A few samples only presented one affected oncogene (but no TSG): KRAS and TSHR in eHGSOC and RAC1 and PREX2 (a regulator of RAC1) in yTNBC. At least ⅔ of the tumors presented mutated oncogenes associated with tumor suppressor genes; the Ras and/or PIK3CA signaling pathways were altered in 15% HGSOC and 20–35% TNBC (Y vs. E); DNA repair genes were mutated in 19–33% of the HGSOC tumors but were more frequently mutated in E-TNBC (56%). However, in HGSOC, 9.5% and 3.3% of the young and elderly patients, respectively, did not present any tumors with an affected CGC nor did 4.65% and none of the young and elderly TNBC patients. Conclusion: Most HGSOC and TNBC from young and elderly patients present an affected TSG, mainly TP53, as well as mutational signature 3; however, a few tumors only present an affected oncogene or no affected cancer-causing genes.

Computational analysis of fused co-expression networks for the identification of candidate cancer gene biomarkers

The complexity of cancer has always been a huge issue in understanding the source of this disease. However, by appreciating its complexity, we can shed some light on crucial gene associations across and in specific cancer types. In this study, we develop a general framework to infer relevant gene biomarkers and their gene-to-gene associations using multiple gene co-expression networks for each cancer type. Specifically, we infer computationally and biologically interesting communities of genes from kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma data sets of The Cancer Genome Atlas (TCGA) database. The gene communities are extracted through a data-driven pipeline and then evaluated through both functional analyses and literature findings. Furthermore, we provide a computational validation of their relevance for each cancer type by comparing the performance of normal/cancer classification for our identified gene sets and other gene signatures, including the typically-used differentially expressed genes. The hallmark of this study is its approach based on gene co-expression networks from different similarity measures: using a combination of multiple gene networks and then fusing normal and cancer networks for each cancer type, we can have better insights on the overall structure of the cancer-type-specific network.

Profile of somatic mutations in young adults with pancreatic cancer.

e15790 Background: Most pancreatic carcinomas (PC) occur in older people, however a few cases are detected in young adults. In this age group, the carcinogenic process is less well understood. Our goal was to identify and to characterize cancer driver genes in early age onset PC. Methods: Somatic variants of individuals affected by PC aged ≤45 years were searched in the COSMIC and CBioPortal databases. The variants were annotated using Oncotator, excluding the silent and intronic variants. Implication in cancer causality was evaluated in the Cancer Gene Census (CGC) and the Candidate Cancer Gene Database (CCGD). The most frequently mutated genes were identified and investigated to determine if they configured FrequentLy mutAted GeneS (FLAGs). Results: Whole genome (4) or exome (29) sequencing was available from 33 individuals (14 females and 19 males). A median of 31 (7-102) alterations per tumor, mainly represented by C > T substitutions (median 16, 2-71), was detected. A median of 3 (0-11) truncated alterations, 4 (1-13) genes cataloged as CGC and 8 (1-22) genes cataloged as CCGD rank A or B was identified per tumor. The most frequently affected genes were those characteristic of tumor promotion in pancreatic cancer carcinogenesis, such as KRAS (79%), TP53 (64%), SMAD4 (18%), followed by RYR1 (15%) and TTN (12%) genes, the latter two classified as FLAGs and, finally, HERC2, GREB1 and DMBT1 (9%). Seventeen samples presented variants in both TP53 and KRAS (17/33), 9 and 4 presented only KRAS or TP53 variants, respectively. Three samples with mutations in neither of these genes presented mutations in genes such as BCLAF1, DCC, BRAF, CDH11 and CDKN2A, both CGCs. Three out of 9 samples carrying KRAS but not TP53 mutations presented variants in DNA homologous repair (HHR) genes. Among all the altered genes, the main biological processes were cell adhesion (139 genes involved) and anatomical structure formation involved in morphogenesis (127), while the most enriched pathways were Wnt (45) and Cadherin (30). Conclusions: TP53 and KRAS are the somatic mutations most frequently detected in PC. 10% of the samples showed no change in these genes, but showed changes in other CGCs. HERC2, GREB1 and DMBT1 are potential cancer drivers in young adult PCs.

Myeloid Translocation Gene Family Members Associate with T-Cell Factors (TCFs) and Influence TCF-Dependent Transcription

ABSTRACT Canonical Wnt signaling is mediated by a molecular “switch” that regulates the transcriptional properties of the T-cell factor (TCF) family of DNA-binding proteins. Members of the myeloid translocation gene (MTG) family of transcriptional corepressors are frequently disrupted by chromosomal translocations in acute myeloid leukemia, whereas MTG16 may be inactivated in up to 40% of breast cancer and MTG8 is a candidate cancer gene in colorectal carcinoma. Genetic studies imply that this corepressor family may function in stem cells. Given that mice lacking Myeloid Translocation Gene Related-1 (Mtgr1) fail to maintain the secretory lineage in the small intestine, we surveyed transcription factors that might recruit Mtgr1 in intestinal stem cells or progenitor cells and found that MTG family members associate specifically with TCF4. Coexpression of β-catenin disrupted the association between these corepressors and TCF4. Furthermore, when expressed in Xenopus embryos, MTG family members inhibited axis formation and impaired the ability of β-catenin and XLef-1 to induce axis duplication, indicating that MTG family members act downstream of β-catenin. Moreover, we found that c-Myc, a transcriptional target of the Wnt pathway, was overexpressed in the small intestines of mice lacking Mtgr1, thus linking inactivation of Mtgr1 to the activation of a potent oncogene.