Inferring Potential Cancer Driving Synonymous Variants

Targeted Next Generation Sequencing molecular profiling and its clinical application in adrenocortical cancer

OBJECTIVE

Adrenal cortical carcinoma (ACC) is a rare malignancy with a generally poor but heterogeneous prognosis, especially depending on the tumour stage at diagnosis. Identification of somatic gene alterations combined with clinical/histopathological evaluation of the tumour can help improve prognostication. We applied a simplified targeted-Next-Generation Sequencing (NGS) panel to characterise the mutational profiles of ACCs, providing potentially relevant information for better patient management.

DESIGN AND METHODS

Thirty frozen tumour specimens from a local ACC series were retrospectively analysed by a custom-NGS panel (CDKN2A, CTNNB1, DAXX, MED12, NF1, PRKAR1A, RB1, TERT, TP53, ZNRF3) to detect somatic prioritised single-nucleotide variants. This cohort was integrated with 86 patients from the ACC-TCGA series bearing point-mutations in the same genes and their combinations identified by our panel. Primary endpoints of the analysis on the total cohort (113 patients) were overall survival (OS) and progression-free survival (PFS), and hazard ratio (HR) for the different alterations grouped by the signalling pathways/combinations affected.

RESULTS

Different PFS, OS, and HR were associated to the different pathways/combinations, being NF1 + TP53 and Wnt/β-catenin + Rb/p53 combined mutations the most deleterious, with a statistical significance for progression HR which is retained only in low-(I/II) stages-NF1 + TP53 combination: HR = 2.96[1.01-8.69] and HR = 13.23[3.15-55.61], all and low stages, respectively; Wnt/β-catenin + Rb/p53 combined pathways: HR = 6.47[2.54-16.49] and HR = 16.24[3.87-68.00], all and low-stages, respectively.

CONCLUSIONS

A simplified targeted-NGS approach seems the best routinely applicable first step towards somatic genetic characterisation of ACC for prognostic assessment. This approach proved to be particularly promising in low-stage cases, suggesting the need for more stringent surveillance and personalised treatment.

Oncogenes and tumor suppressor genes: functions and roles in cancers

Cancer, being the most formidable ailment, has had a profound impact on the human health. The disease is primarily associated with genetic mutations that impact oncogenes and tumor suppressor genes (TSGs). Recently, growing evidence have shown that X-linked TSGs have specific role in cancer progression and metastasis as well. Interestingly, our genome harbors around substantial portion of genes that function as tumor suppressors, and the X chromosome alone harbors a considerable number of TSGs. The scenario becomes even more compelling as X-linked TSGs are adaptive to key epigenetic processes such as X chromosome inactivation. Therefore, delineating the new paradigm related to X-linked TSGs, for instance, their crosstalk with autosome and involvement in cancer initiation, progression, and metastasis becomes utmost importance. Considering this, herein, we present a comprehensive discussion of X-linked TSG dysregulation in various cancers as a consequence of genetic variations and epigenetic alterations. In addition, the dynamic role of X-linked TSGs in sex chromosome-autosome crosstalk in cancer genome remodeling is being explored thoroughly. Besides, the functional roles of ncRNAs, role of X-linked TSG in immunomodulation and in gender-based cancer disparities has also been highlighted. Overall, the focal idea of the present article is to recapitulate the findings on X-linked TSG regulation in the cancer landscape and to redefine their role toward improving cancer treatment strategies.

Incorporating mutational heterogeneity to identify genes that are enriched for synonymous mutations in cancer

BACKGROUND

Synonymous mutations, which change the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations might be enriched in cancer has been explored in several recent studies. However, none of these studies control for all three types of mutational heterogeneity (patient, histology, and gene) that are known to affect the accurate identification of non-synonymous cancer-associated genes. Our goal is to adopt the current standard for non-synonymous mutations in an investigation of synonymous mutations.

RESULTS

Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify cancer-associated genes that are enriched for synonymous mutations based on a non-coding background model that takes into account the mutational heterogeneity across these levels. Using MutSigCVsyn, we first analyzed 2572 cancer whole-genome samples from the Pan-cancer Analysis of Whole Genomes (PCAWG) to identify non-synonymous cancer drivers as a quality control. Indicative of the algorithm accuracy we find that 58.6% of these candidate genes were also found in Cancer Census Gene (CGC) list, and 66.2% were found within the PCAWG cancer driver list. We then applied it to identify 30 putative cancer-associated genes that are enriched for synonymous mutations within the same samples. One of the promising gene candidates is the B cell lymphoma 2 (BCL-2) gene. BCL-2 regulates apoptosis by antagonizing the action of proapoptotic BCL-2 family member proteins. The synonymous mutations in BCL2 are enriched in its anti-apoptotic domain and likely play a role in cancer cell proliferation.

CONCLUSION

Our study introduces MutSigCVsyn, an algorithm that accounts for mutational heterogeneity at patient, histology, and gene levels, to identify cancer-associated genes that are enriched for synonymous mutations using whole genome sequencing data. We identified 30 putative candidate genes that will benefit from future experimental studies on the role of synonymous mutations in cancer biology.