Comparison of Patient Susceptibility Genes Across Breast Cancer: Implications for Prognosis and Therapeutic Outcomes

Insights into the Oncogenic, Prognostic, and Immunological Role of BRIP1 in Pan-Cancer: A Comprehensive Data-Mining-Based Study

Background

BRCA1 interacting helicase 1 (BRIP1), an ATP-dependent DNA helicase which belongs to an Iron-Sulfur (Fe-S) helicase cluster family with a DEAH domain, plays a key role in DNA damage and repair, Fanconi anemia, and development of several cancers including breast and ovarian cancer. However, its role in pan-cancer remains largely unknown.

Methods

BRIP1 expression data of tumor and normal tissues were downloaded from the Cancer Genome Atlas, Genotype-Tissue Expression, and Human Protein Atlas databases. Correlation between BRIP1 and prognosis, genomic alterations, and copy number variation (CNV) as well as methylation in pan-cancer were further analyzed. Protein-protein interaction (PPI) and gene set enrichment and variation analysis (GSEA and GSVA) were performed to identify the potential pathways and functions of BRIP1. Besides, BRIP1 correlations with tumor microenvironment (TME), immune infiltration, immune-related genes, tumor mutation burden (TMB), microsatellite instability (MSI), and immunotherapy as well as antitumor drugs were explored in pan-cancer.

Results

Differential analyses showed an increased expression of BRIP1 in 28 cancer types and its aberrant expression could be an indicator for prognosis in most cancers. Among the various mutation types of BRIP1 in pan-cancer, amplification was the most common type. BRIP1 expression had a significant correlation with CNV and DNA methylation in 23 tumor types and 16 tumor types, respectively. PPI, GSEA, and GSVA results validated the association between BRIP1 and DNA damage and repair, cell cycle, and metabolism. In addition, the expression of BRIP1 and its correlation with TME, immune-infiltrating cells, immune-related genes, TMB, and MSI as well as a variety of antitumor drugs and immunotherapy were confirmed.

Conclusions

Our study indicates that BRIP1 plays an imperative role in the tumorigenesis and immunity of various tumors. It may not only serve as a diagnostic and prognostic biomarker but also can be a predictor for drug sensitivity and immunoreaction during antitumor treatment in pan-cancer.

Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer

Identifying pathogenic missense variants in hereditary cancer is critical to the efforts of patient surveillance and risk-reduction strategies. For this purpose, many different gene panels consisting of different number and/or set of genes are available and we are particularly interested in a panel of 26 genes with a varying degree of hereditary cancer risk consisting of ABRAXAS1, ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MEN1, MLH1, MRE11, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, and XRCC2. In this study, we have compiled a collection of the missense variations reported in any of these 26 genes. More than a thousand missense variants were collected from ClinVar and the targeted screen of a breast cancer cohort of 355 patients which contributed to this set with 160 novel missense variations. We analyzed the impact of the missense variations on protein stability by five different predictors including both sequence- (SAAF2EC and MUpro) and structure-based (Maestro, mCSM, CUPSAT) predictors. For the structure-based tools, we have utilized the AlphaFold (AF2) protein structures which comprise the first structural analysis of this hereditary cancer proteins. Our results agreed with the recent benchmarks that computed the power of stability predictors in discriminating the pathogenic variants. Overall, we reported a low-to-medium-level performance for the stability predictors in discriminating pathogenic variants, except MUpro which had an AUROC of 0.534 (95% CI [0.499-0.570]). The AUROC values ranged between 0.614-0.719 for the total set and 0.596-0.682 for the set with high AF2 confidence regions. Furthermore, our findings revealed that the confidence score for a given variant in the AF2 structure could alone predict pathogenicity more robustly than any of the tested stability predictors with an AUROC of 0.852. Altogether, this study represents the first structural analysis of the 26 hereditary cancer genes underscoring 1) the thermodynamic stability predicted from AF2 structures as a moderate and 2) the confidence score of AF2 as a strong descriptor for variant pathogenicity.

A Large Case-Control Study Performed in Spanish Population Suggests That RECQL5 Is the Only RECQ Helicase Involved in Breast Cancer Susceptibility

Simple Summary

Around 50% of the familial breast cancer (BC) cases are estimated to be caused by variants in low-, moderate-, and high-risk susceptibility genes; however, the other half is of unknown origin. The finding of new susceptibility genes is key to improve diagnosis, take preventive measures, and identify new therapies. In this context, previous studies have discussed whether the genes encoding for the RECQ helicase family could play a role in BC susceptibility, without very conclusive results. To clarify this, in this study, we sequenced the whole coding sequence of the RECQL1, BLM, WRN, RECQL4, and RECQL5 genes in 1993 Spanish BC familial cases and compared it with controls from gnomAD. No association was found for RECQL1, BLM, WRN, and RECQL4; however, we did find an association between RECQL5 and breast cancer as a moderate-risk gene, making it a perfect candidate for further studies.

Abstract

Around 50% of the familial breast cancer (BC) cases are estimated to be caused by germline variants in known low-, moderate-, and high-risk susceptibility genes, while the other half is of unknown genetic origin. In the present study, we wanted to evaluate the role of the RECQ helicases, some of which have been studied in the past as candidates, with unclear results about their role in the disease. Using next-generation sequencing (NGS) technology, we analyzed the whole coding sequence of BLM, RECQL1, RECQL4, RECQL5, and WRN in almost 2000 index cases from BC Spanish families that had previously tested negative for the known BC susceptibility genes (BRCAX) and compared the results with the controls extracted from gnomAD. Our results suggest that BLM, RECQL1, RECQL4, and WRN do not play a major role in BC susceptibility. However, in the combined analysis, joining the present results with those previously reported in a series of 1334 BC Spanish patients and controls, we found a statistically significant association between Loss of Function (LoF) variants in RECQL5 and BC risk, with an OR of 2.56 (p = 0.009; 95% CI, 1.18–4.98). Our findings support our previous work and places the RECQL5 gene as a new moderate-risk BC gene.

Functions of Breast Cancer Predisposition Genes: Implications for Clinical Management

Approximately 5–10% of all breast cancer (BC) cases are caused by germline pathogenic variants (GPVs) in various cancer predisposition genes (CPGs). The most common contributors to hereditary BC are BRCA1 and BRCA2, which are associated with hereditary breast and ovarian cancer (HBOC). ATM, BARD1, CHEK2, PALB2, RAD51C, and RAD51D have also been recognized as CPGs with a high to moderate risk of BC. Primary and secondary cancer prevention strategies have been established for HBOC patients; however, optimal preventive strategies for most hereditary BCs have not yet been established. Most BC-associated CPGs participate in DNA damage repair pathways and cell cycle checkpoint mechanisms, and function jointly in such cascades; therefore, a fundamental understanding of the disease drivers in such cascades can facilitate the accurate estimation of the genetic risk of developing BC and the selection of appropriate preventive and therapeutic strategies to manage hereditary BCs. Herein, we review the functions of key BC-associated CPGs and strategies for the clinical management in individuals harboring the GPVs of such genes.

An integrative pan-cancer analysis reveals the oncogenic role of mutS homolog 6 (MSH6) in human tumors

There are three most important mismatch repair genes in the mismatch repair system, MSH6 is one of them and it plays an essential role in DNA mismatch repair. Several emerging cell- or animal-based studies have verified that MSH6 mutations are closely linked to the occurrence, progression or metastasis of cancer, but there is still no practicable pan-cancer analysis. On account of the available datasets of the cancer genome atlas (TCGA) and Gene expression omnibus (GEO), a comprehensive analysis of the potential carcinogenic effects of the MSH6 gene was conducted in 33 human cancers. MSH6 was highly expressed in most cancers, and the high expression of MSH6 was associated with poor overall survival prognosis of patients with multiple cancers, such as adrenocortical carcinoma. MSH6 mutations occurred in most cancers and were closely related to the prognosis of cancer patients. Increased phosphorylation levels of S227 and S830 were noted in several tumors, including breast cancer and colon cancer. MSH6 expression was also observed to be correlated with cancer-associated fibroblasts and CD8⁺ T-cells infiltration levels in various cancer types, e. g. pancreatic adenocarcinoma or testicular germ cell tumors. Furthermore, pathway enrichment analysis demonstrated that the main biological activities of MSH6 were related to ATPase activity, mismatch repair, and DNA metabolism-related functions. Altogether, our pan-cancer research has suggested that the MSH6 expression level was closely related to the carcinogenesis and prognosis of certain tumors, which helps to know the effect of MSH6 in tumorigenesis from the point of view of clinical tumor samples.

Role of Splicing Regulatory Elements and In Silico Tools Usage in the Identification of Deep Intronic Splicing Variants in Hereditary Breast/Ovarian Cancer Genes

Simple Summary

There is a significant percentage of hereditary breast and ovarian cancer (HBOC) cases that remain undiagnosed, because no pathogenic variant is detected through massively parallel sequencing of coding exons and exon-intron boundaries of high-moderate susceptibility risk genes. Deep intronic regions may contain variants affecting RNA splicing, leading ultimately to disease, and hence they may explain several cases where the genetic cause of HBOC is unknown. This study aims to characterize intronic regions to identify a landscape of “exonizable” zones and test the efficiency of two in silico tools to detect deep intronic variants affecting the mRNA splicing process.

Abstract

The contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.