Inferring Potential Cancer Driving Synonymous Variants

Identification of cis-sQTL demonstrates genetic associations and functional implications of inflammatory processes in Nelore cattle muscle tissue

This study aimed to identify splicing quantitative trait loci (cis-sQTL) in Nelore cattle muscle tissue and explore the involvement of spliced genes (sGenes) in immune system-related biological processes. Genotypic data from 80 intact male Nelore cattle were obtained using SNP-Chip technology, while RNA-Seq analysis was performed to measure gene expression levels, enabling the integration of genomic and transcriptomic datasets. The normalized expression levels of spliced transcripts were associated with single nucleotide polymorphisms (SNPs) through an analysis of variance using an additive linear model with the MatrixEQTL package. A permutation analysis then assessed the significance of the best SNPs for each spliced transcript. Functional enrichment analysis was performed on the sGenes to investigate their roles in the immune system. In total, 3,187 variants were linked to 3,202 spliced transcripts, with 83 sGenes involved in immune system processes. Of these, 31 sGenes were enriched for five transcription factors. Most cis-sQTL effects were found in intronic regions, with 27 sQTL variants associated with disease susceptibility and resistance in cattle. Key sGenes identified, such as GSDMA, NLRP6, CASP6, GZMA, CASP4, CASP1, TREM2, NLRP1, and NAIP, were related to inflammasome formation and pyroptosis. Additionally, genes like PIDD1, OPTN, NFKBIB, STAT1, TNIP3, and TREM2 were involved in regulating the NF-kB pathway. These findings lay the groundwork for breeding disease-resistant cattle and enhance our understanding of genetic mechanisms in immune responses.

The theory of massively repeated evolution and full identifications of cancer-driving nucleotides (CDNs)

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size n=300-1000), point mutations may recur in i out of n patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reach i*=3, all mutations recurring at i≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if n increases to 100,000 for each cancer type. At present, only <10% of CDNs have been identified. When the full sets of CDNs are identified, the evolutionary mechanism of tumorigenesis in each case can be known and, importantly, gene targeted therapy will be far more effective in treatment and robust against drug resistance.

Therapeutic Potential of lncRNAs in Regulating Disulfidptosis for Cancer Treatment

Non-coding RNAs (lncRNAs) play critical roles in various cellular processes, including a novel form of regulated cell death known as disulfidptosis, characterized by accumulating protein disulfide bonds and severe endoplasmic reticulum stress. This review highlights the therapeutic potential of lncRNAs in regulating disulfidptosis for cancer treatment, emphasizing their influence on key pathway components such as GPX4, SLC7A11, and PDIA family members. Recent studies have demonstrated that targeting specific lncRNAs can sensitize cancer cells to disulfidptosis, offering a promising approach to cancer therapy. The regulation of disulfidptosis by lncRNAs involves various signaling pathways, including oxidative stress, ER stress, and calcium signaling. This review also discusses the molecular mechanisms underlying lncRNA regulation of disulfidptosis, the challenges of developing lncRNA-based therapies, and the future potential of this rapidly advancing field in cancer research.

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.