Somatic Mutations In Cancer Research Articles

Editorial Comment.

No AccessJournal of UrologyAdult Urology1 May 2023Editorial CommentThis article comments on the following:Clinical Impact of a Rapid Genetic Testing Model for Advanced Prostate Cancer Patients Lindsey Byrne Lindsey ByrneLindsey Byrne Division of Human Genetics, The Ohio State University, Columbus, Ohio More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003186.01AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Comment." The Journal of Urology, 209(5), pp. 926–927 REFERENCES 1. National Comprehensive Cancer Network. Clinical Practice Guidelines in Oncology: Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic. Version 2.2023. Accessed January 21, 2023. https://www.nccn.org/professionals/physician_gls/pdf/genetics_bop.pdf. Google Scholar 2. . Projecting the supply and demand for certified genetic counselors: a workforce study. J Genet Couns. 2018; 27(1):16-20. Crossref, Medline, Google Scholar 3. Clinical impact of a rapid genetic testing model for advanced prostate cancer patients. J Urol. 2023; 209(5):918-927. Abstract, Google Scholar 4. . Germline and somatic mutations in prostate cancer for the clinician. J Natl Compr Canc Netw. 2019; 17(5):515-521. Crossref, Medline, Google Scholar © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsRelated articlesJournal of Urology28 Mar 2023Clinical Impact of a Rapid Genetic Testing Model for Advanced Prostate Cancer Patients Volume 209Issue 5May 2023Page: 926-927 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Lindsey Byrne Division of Human Genetics, The Ohio State University, Columbus, Ohio More articles by this author Expand All Advertisement PDF downloadLoading ...

Protein Arginine Methyltransferase 5 (PRMT5) Mutations in Cancer Cells.

Arginine methylation is a form of posttranslational modification that regulates many cellular functions such as development, DNA damage repair, inflammatory response, splicing, and signal transduction, among others. Protein arginine methyltransferase 5 (PRMT5) is one of nine identified methyltransferases, and it can methylate both histone and non-histone targets. It has pleiotropic functions, including recruitment of repair machinery to a chromosomal DNA double strand break (DSB) and coordinating the interplay between repair and checkpoint activation. Thus, PRMT5 has been actively studied as a cancer treatment target, and small molecule inhibitors of its enzymatic activity have already been developed. In this report, we analyzed all reported PRMT5 mutations appearing in cancer cells using data from the Catalogue of Somatic Mutations in Cancers (COSMIC). Our goal is to classify mutations as either drivers or passengers to understand which ones are likely to promote cellular transformation. Using gold standard artificial intelligence algorithms, we uncovered several key driver mutations in the active site of the enzyme (D306H, L315P, and N318K). In silico protein modeling shows that these mutations may affect the affinity of PRMT5 for S-adenosylmethionine (SAM), which is required as a methyl donor. Electrostatic analysis of the enzyme active site shows that one of these mutations creates a tunnel in the vicinity of the SAM binding site, which may allow interfering molecules to enter the enzyme active site and decrease its activity. We also identified several non-coding mutations that appear to affect PRMT5 splicing. Our analyses provide insights into the role of PRMT5 mutations in cancer cells. Additionally, since PRMT5 single molecule inhibitors have already been developed, this work may uncover future directions in how mutations can affect targeted inhibition.

Cell-free chromatin immunoprecipitation can determine tumor gene expression in lung cancer patients.

Cell-free DNA (cfDNA) in blood plasma can be bound to nucleosomes that contain post-translational modifications representing the epigenetic profile of the cell of origin. This includes histone H3 lysine 36 trimethylation (H3K36me3), a marker of active transcription. We hypothesised that cell-free chromatin immunoprecipitation (cfChIP) of H3K36me3-modified nucleosomes present in blood plasma can delineate tumour gene expression levels. H3K36me3 cfChIP followed by targeted NGS (cfChIP-seq) was performed on blood plasma samples from non-small-cell lung cancer (NSCLC) patients (NSCLC, n= 8), small-cell lung cancer (SCLC) patients (SCLC, n= 4) and healthy controls (n= 4). H3K36me3 cfChIP-seq demonstrated increased enrichment of mutated alleles compared with normal alleles in plasma from patients with known somatic cancer mutations. Additionally, genes identified to be differentially expressed in SCLC and NSCLC tumours had concordant H3K36me3 cfChIP enrichment profiles in NSCLC (sensitivity=0.80) and SCLC blood plasma (sensitivity=0.86). Findings here expand the utility of cfDNA in liquid biopsies to characterise treatment resistance, cancer subtyping and disease progression.

Genomic analysis of cervical carcinoma identifies Alpelisib as a therapeutic option for PIK3CA-mutant cervical carcinoma via the PI3K/AKT pathway.

Cervical carcinoma is a serious type of gynecological cancer that can affect women of all ages. Cervical carcinoma presents challenges for precision medicine, as not all tumors have specific gene mutations or alterations that can be targeted with existing drugs. Nonetheless, there are some promising targets in cervical carcinoma. Herein, genomic mutation data from the Cancer Genome Atlas (TCGA) and Catalogue of Somatic Mutations in Cancer (COSMIC) were used to identify genomic targets for cervical carcinoma. PIK3CA was the most mutant gene among the promising targets, especially in cervical squamous cell carcinoma, and the mutated genes of cervical carcinoma were enriched in the RTK/PI3K/MAPK and Hippo pathways. In vitro, PIK3CA-mutant cervical cancer cell lines showed higher sensitivity to Alpelisib than cancer cells without the PIK3CA mutation and the normal cells (HCerEpic). Protein-protein networks and co-immunoprecipitation of PIK3CA revealed reduced interaction between p110α and ATR in PIK3CA-mutant cervical cancer cells, which were sensitive to the combination of Alpelisib and cisplatin in vivo. Furthermore, Alpelisib significantly suppressed the proliferation and migration of PIK3CA-mutant cervical cancer cells via inhibition of the AKT/mTOR pathway. Overall, Alpelisib showed antitumor effects and enhance cisplatin efficacy in PIK3CA-mutant cervical cancer cells via PI3K/AKT pathways. Our study demonstrated the therapeutic potential of Alpelisib in PIK3CA-mutant cervical carcinoma, which provides insights into precision medicine in cervical carcinoma. This article is protected by copyright. All rights reserved.

Landscape of DNA damage response gene alterations in breast cancer: A comprehensive investigation.

DNA damage response (DDR) gene alterations are prevalent in breast cancer (BC) and important for treatment decisions. Intensive studies on DDR alterations in BC are still needed. The authors included 438 patients with metastatic breast cancer from their next-generation sequencing database and 1091 patients with early-stage breast cancer from The Cancer Genome Atlas (TCGA) database in the analysis to characterize molecular alterations in the DDR pathway. Germline DDR mutations were more prevalent in younger patients and those with HER2-negative cancers. Tumors with germline DDR mutations more commonly had somatic DDR mutations, especially those with germline Fanconi anemia (FA) pathway mutations. Notably, 66.67% (four of six) of patients with germline PALB2 mutations had tumors that harbored somatic PALB2 mutations. No differences in prognosis were observed in patients with germline or tumor somatic DDR mutations compared to patients and tumors that were wild-type. Compared to early BC, the frequency of somatic DDR mutations in metastatic cancers was significantly higher (24.89% vs. 16.02%, p<.001). Higher tumor mutation burdens were observed in cancers with somatic DDR mutations, but not in cancers with germline DDR mutations. Furthermore, tumors with somatic DDR mutations showed an abundance of anticancer immunological phenotypes. Somatic FA and mismatch repair pathway mutations were associated with increased expression of immune checkpoint molecules. Although most DDR genes were significantly positively associated with expression of proliferation-related genes, PARP3 expression was negatively correlated with MKI67 expression. Lower PARP3 expression was associated with a worse prognosis in TCGA database by multivariate Cox analysis. Patients with germline FA mutations more frequently have tumors with somatic DDR mutations. Somatic DDR mutations lead to anticancer immunological phenotypes in BC. No differences in prognosis according to germline or somatic DDR mutations were found.

The frequency of somatic mutations in cancer predicts the phenotypic relevance of germline mutations.

Genomic sequence mutations can be pathogenic in both germline and somatic cells. Several authors have observed that often the same genes are involved in cancer when mutated in somatic cells and in genetic diseases when mutated in the germline. Recent advances in high-throughput sequencing techniques have provided us with large databases of both types of mutations, allowing us to investigate this issue in a systematic way. Hence, we applied a machine learning based framework to this problem, comparing multiple models. The models achieved significant predictive power as shown by both cross-validation and their application to recently discovered gene/phenotype associations not used for training. We found that genes characterized by high frequency of somatic mutations in the most common cancers and ancient evolutionary age are most likely to be involved in abnormal phenotypes and diseases. These results suggest that the combination of tolerance for mutations at the cell viability level (measured by the frequency of somatic mutations in cancer) and functional relevance (demonstrated by evolutionary conservation) are the main predictors of disease genes. Our results thus confirm the deep relationship between pathogenic mutations in somatic and germline cells, provide new insight into the common origin of cancer and genetic diseases, and can be used to improve the identification of new disease genes.

Unravelling the instability of mutational signatures extraction via archetypal analysis.

The high cosine similarity between some single-base substitution mutational signatures and their characteristic flat profiles could suggest the presence of overfitting and mathematical artefacts. The newest version (v3.3) of the signature database available in the Catalogue Of Somatic Mutations In Cancer (COSMIC) provides a collection of 79 mutational signatures, which has more than doubled with respect to previous version (30 profiles available in COSMIC signatures v2), making more critical the associations between signatures and specific mutagenic processes. This study both provides a systematic assessment of the de novo extraction task through simulation scenarios based on the latest version of the COSMIC signatures and highlights, through a novel approach using archetypal analysis, which COSMIC signatures are redundant and more likely to be considered as mathematical artefacts. 29 archetypes were able to reconstruct the profile of all the COSMIC signatures with cosine similarity 0.8. Interestingly, these archetypes tend to group similar original signatures sharing either the same aetiology or similar biological processes. We believe that these findings will be useful to encourage the development of new de novo extraction methods avoiding the redundancy of information among the signatures while preserving the biological interpretation.

Profiling PIK3CA variants in disorders of somatic mosaicism

PurposeVariants in PIK3CA (encoding p110α; the catalytic subunit of PI3K) characterize some disorders of somatic mosaicism (DoSM) conditions with clinical features, including sporadic overgrowth and vascular malformations. Here, we profile PIK3CA variants in DoSM. MethodsWe applied a next-generation, sequencing-based, laboratory-developed test, using an average coverage of approximately 2000× for up to 37 genes associated with DoSM, on a cohort of 1197 patients with DoSM referred for clinical genomics services between 2013 and 2022. ResultsWe identified clinically reportable variants in 747 (62.4%) individuals in this cohort. Notably, 371 clinically reportable variants in PIK3CA were identified in 368 patients, constituting approximately 49.2% of all patients with reportable findings. Variants in the C2 domain of p110α are enriched in DoSM (this cohort) compared with those of cancer (Catalogue of Somatic Mutations in Cancer [COSMIC] database), highlighting the role of the C2 domain in driving uncontrolled cell proliferation in DoSM. Furthermore, we report 17 novel variants in PIK3CA that are not previously reported in DoSM and describe clinical presentation correlation for 4 novel variants. ConclusionOur findings from the largest single-center cohort of patients with DoSM expand the spectrum of variants in PIK3CA and shed light on the less-studied role of the C2 domain in the pathogenesis of DoSM.

Identification of KCNK1 as a potential prognostic biomarker and therapeutic target of breast cancer.

Breast cancer is the most common malignant cancer and is the second most common cause of cancer-related deaths among females worldwide. Thus, it warrants the urgent development of new therapeutic targets and strategies. Potassium channels are aberrantly expressed in various tumors and are related to tumor progression. However, studies on potassium channels in breast cancer remain limited. First, The Cancer Genome Atlas (TCGA) and Gene Set Enrichment Analysis (GSEA) were used to screen the differentially expressed potassium channels in breast cancer. Several other databases were utilized for further data analysis and visualization, including Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Human Protein Atlas (HPA), GeneMANIA, Tumor Immune Estimation Resource 2 (TIMER2), Catalog of Somatic Mutations in Cancer (COSMIC), cBioPortal, and UCSC Xena tool. Besides, cell proliferation was detected by cell counting kit-8 (CCK8) and 5-Ethynyl-20-deoxyuridine (EdU), and cell migration was detected by wound healing and Transwell assays after knocking down KCNK1. Furthermore, the effect of KCNK1 knockdown on the sensitivity of breast cancer cells to paclitaxel was also evaluated. KCNK1 was overexpressed in breast cancer. Higher KCNK1 expression predicted an unfavorable prognosis. Moreover, the abnormal expression of KCNK1 was attributed to promoter hypomethylation of KCNK1 in breast cancer. Besides, cell proliferation and migration were significantly inhibited post-KCNK1 silencing, while KCNK1 knockdown significantly increased breast cancer cell sensitivity to paclitaxel. Taken together, our findings demonstrated that KCNK1 is a potential prognostic biomarker and therapeutic target of breast cancer. Thus, targeting KCNK1 might help synergize with paclitaxel function in breast cancer treatment.

Mutational signature of mtDNA confers mechanistic insight into oxidative metabolism remodeling in colorectal cancer.

Rationale: Mitochondrial dysfunction caused by mitochondrial DNA (mtDNA) mutations and subsequent metabolic defects are closely involved in tumorigenesis and progression in a cancer-type specific manner. To date, the mutational pattern of mtDNA somatic mutations in colorectal cancer (CRC) tissues and its clinical implication are still not completely clear. Methods: In the present study, we generated a large mtDNA somatic mutation dataset from three CRC cohorts (432, 1,015, and 845 patients, respectively) and then most comprehensively characterized the CRC-specific evolutionary pattern and its clinical implication. Results: Our results showed that the mtDNA control region (mtCTR) with a high mutation density exhibited a distinct mutation spectrum characterizing a high enrichment of L-strand C > T mutations, which was contrary to the H-strand C > T mutational bias observed in the mtDNA coding region (mtCDR) (P < 0.001). Further analysis clearly confirmed the relaxed evolutionary selection of mtCTR mutations, which was mainly characterized by the similar distribution of hypervariable region (HVS) and non-HVS mutation density. Moreover, significant negative selection was identified in mutations of mtDNA complex V (ATP6/ATP8) and tRNA loop regions. Although our data showed that oxidative metabolism was commonly increased in CRC cells, mtDNA somatic mutations in CRC tissues were not closely associated with mitochondrial biogenesis, oxidative metabolism, and clinical progression, suggesting a cancer-type specific relationship between mtDNA mutations and mitochondrial metabolic functions in CRC cells. Conclusion: Our study identified the CRC-specific evolutionary mode of mtDNA mutations, which is possibly matched to specific mitochondrial metabolic remodeling and confers new mechanic insight into CRC tumorigenesis.

O47: Leveraging somatic cancer mutation data to predict the pathogenicity of germline missense variants*

O47: Leveraging somatic cancer mutation data to predict the pathogenicity of germline missense variants*

&lt;i&gt;PIK3CA&lt;/i&gt;-mutated breast cancer: from research to clinical practice

Mutation or amplification in the PIK3CA gene is one of the most frequent somatic mutations in hormone-dependent Her2neu-negative breast cancer (HR+ Her2neu- breast cancer) and is associated with an increased risk of relapse, progression or death. Understanding the mechanisms leading to hyperactivation of the PI3K-mediated signaling cascade has led to a new class of drugs aimed at inhibiting/suppressing it. Studies of the efficacy of the pan-PI3K inhibitor buparlisib and the beta isoform inhibitor taselisib were formally positive and reached their planned primary sites, but were discontinued due to high levels of toxicity. To date, the only phosphatidylinositol 3-kinase (PI3K) inhibitor approved in clinical practice is alpelsib, which selectively inhibits the alpha isoform of the enzyme's catalytic subunit. The efficacy and safety of alpelisib in combination with fulvestrant for the treatment of postmenopausal women and men with HR+ HER2- PIK3CA-mutated advanced or metastatic breast cancer after prior therapy with aromatase inhibitors was demonstrated in the SOLAR-1 study. The next step proving the efficacy of combination therapy in patients previously treated with endocrine therapy in combination with CDK4/6 inhibitors was the open, multicenter, noncomparative three-arm study BYLieve. The current accumulated clinical experience confirms and complements the findings. In this article, we review clinical cases of the use of alpelisib in patients who previously received hormone therapy, including CDK4/6 inhibitors.

Germline and somatic variants in ovarian carcinoma: A next-generation sequencing (NGS) analysis.

Germline BRCA1/2 mutations are identified in 13-15% of ovarian cancers, while an additional 5-7% of ovarian cancers harbor somatic BRCA1/2 mutations. Beyond these mutations, germline or somatic aberrations in genes of the homologous recombination (HR) pathway such as RAD51B/C/D, PALB2, ATM, BRIP1 may confer an HR deficiency in up to 50% of ovarian tumors. Next-generation sequencing (NGS) is a high-throughput massive parallel sequencing method that enables the simultaneous detection of several mutations in entire genomes. We performed NGS analysis in 86 patients with ovarian cancer treated in the Oncology Department of Alexandra University Hospital in order to identify the molecular landscape of germline and somatic mutations in ovarian cancer. The genes with the highest number of pathogenic somatic mutations in high grade serous carcinoma (HGSC) patients were TP53 [68%; 34/50] and BRCA1 [22%; 11/50] followed by somatic mutations in RB1 [2%; 1/50], NF1 [2%; 1/50], BRCA2 [2%; 1/50], AKT1 [2%; 1/50], RAD50 [2%; 1/50], PIK3CA [2%; 1/50] genes. Of note, the most common TP53 genetic polymorphism was c.524G>A p.Arg175His in exon 5. Variants of unknown significance (VUS) detected in HGSC included ROS1 [26%; 13/50], RAD50 [6%; 3/50], BRCA2 [6%; 3/50], NOTCH1 [6%; 3/50], TP53 [6%; 3/50], AR [6%; 3/50]. As for germline mutations, BRCA1 [8/30; 27%] and BRCA2 [4/30; 13%] were the most common genes bearing pathogenic alterations in HGSC, while VUS germline mutations commonly affected HRR-related genes, including ATM (c.7816A>G), BRIP (c.2327 C>A), CHEK2 (c.320-5T>A). Overall, genetic testing should be offered in most patients with ovarian cancer to identify mutations in HRR genes and determine the population that would be susceptible to poly ADP ribose polymerase (PARP) inhibitors.

BRAF V600E and Novel Somatic Mutations in Thyroid Cancer of Libyan Patients

Thyroid cancer (TC) is a common endocrine malignancy that frequently harbours the oncogenic V600E BRAF mutation. This mutation has received considerable attention in recent years for its potential utility in the risk stratification and management of TC. This study aims to investigate BRAF mutational status in thyroid cancer of Libyan patients and their association with clinicopathological factors. 44 thyroid tissue samples were analysed for mutations in exon 15 of the BRAF gene by performing polymerase chain reaction and Sanger sequencing. The results of BRAF mutation screening were correlated to clinical and pathological characteristics of the studied thyroid cancer patients. Statistical analyses were performed using SPSS. The BRAF exon 15 mutations were detected in 19 (43.2%) of the thyroid cancer cases. The V600E was the most frequent one found in 15/44 (34.1%) cases. We also detected 6 other variants in 7 patients (15.9%), the S616F, the W619R and the T599S. Three mutations were associated with V600E, the L584I, the D587Y and the synonymous L597L. None of these mutations were reported previously in thyroid cancers. No statistical association was found between BRAF mutations and clinicopathological factors except with papillary thyroid cancer type (p= 0,032). Novel BRAF mutations and V600E were frequently detected in thyroid cancer of Libyan patients; this suggests a potential role of these novel mutations in carcinogenesis and in anti-EGFR therapy resistance.

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers.

Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

Computed cancer interactome explains the effects of somatic mutations in cancers.

Protein-protein interactions (PPIs) are involved in almost all essential cellular processes. Perturbation of PPI networks plays critical roles in tumorigenesis, cancer progression, and metastasis. While numerous high-throughput experiments have produced a vast amount of data for PPIs, these data sets suffer from high false positive rates and exhibit a high degree of discrepancy. Coevolution of amino acid positions between protein pairs has proven to be useful in identifying interacting proteins and providing structural details of the interaction interfaces with the help of deep learning methods like AlphaFold (AF). In this study, we applied AF to investigate the cancer protein-protein interactome. We predicted 1,798 PPIs for cancer driver proteins involved in diverse cellular processes such as transcription regulation, signal transduction, DNA repair, and cell cycle. We modeled the spatial structures for the predicted binary protein complexes, 1,087 of which lacked previous 3D structure information. Our predictions offer novel structural insight into many cancer-related processes such as the MAP kinase cascade and Fanconi anemia pathway. We further investigated the cancer mutation landscape by mapping somatic missense mutations (SMMs) in cancer to the predicted PPI interfaces and performing enrichment and depletion analyses. Interfaces enriched or depleted with SMMs exhibit different preferences for functional categories. Interfaces enriched in mutations tend to function in pathways that are deregulated in cancers and they may help explain the molecular mechanisms of cancers in patients; interfaces lacking mutations appear to be essential for the survival of cancer cells and thus may be future targets for PPI modulating drugs.

Arcch: Improving the Performance of Clonal Hematopoiesis Variant Calling and Interpretation Using a Consensus Based Approach

Introduction: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion is known as clonal hematopoiesis (CH). CH is linked to a higher risk of hematologic malignancies and other adverse health outcomes. The prevalence of CH is dependent on sequencing technique. With ultra-high-depth sequencing, CH can be detected in most adults. However, CH variant calling at very low variant allele fractions (VAF) is challenging due to difficulty in distinguishing low frequency CH mutations from sequencing artifacts. Here we develop and validate a novel CH variant calling approach that combines ensemble based variant calling with advanced artifact filtering and outperforms commonly used somatic variant callers. Methods: We sequenced a tumor-normal dilution series from six AML patients and 27 technical controls with a targeted panel utilizing unique molecular indexes that included nine common CH genes (DNMT3A, TET2, ASXL1, TP53, PPM1D, JAK2, SF3B1, SRSF2) with a mean unique coverage of 18,268x. In total we identified 32 mutations in these six samples validated by an independent sequencing panel performed for the purpose of clinical testing. The variant allele fraction (VAF) in the resulting tumor-dilution samples ranged from 0.1%-50% VAF. Results: For higher VAF mutations (>5%), Mutect2, Lofreq, and Vardict showed reasonable sensitivity (range: 0.70-1.00) and positive predictive values (PPV) (range: 0.80-1.00). However, at lower VAF, PPV was poor; for mutations between 0.1-0.4% VAF, the PPV ranged between 0.01-0.22. We applied additional filters based on sequencing quality, depth, regional complexity, and an empiric estimate of sequencing error at the position of a given called variant using technical controls. Taking the consensus of three callers and including our additional filters, we not only retained sensitivity and PPV for higher VAF variants above 1% (0.92 sensitivity, 0.95 PPV) but improved the PPV with retained sensitivity for variants between 1-0.1% VAF (0.91 sensitivity, 0.83 PPV). Applying our consensus approach to blood samples drawn from 31 healthy individuals sequenced using the same targeted panel with variants validated using an orthogonal approach, we saw excellent sensitivity and PPV across a wide range of VAFs (Sensitivity 0.99 [>1% VAF], 0.92 [0.2-1% VAF], and 0.82 [0.1-0.2% VAF]; PPV 1.00 [>1% VAF], 0.98 [0.2-1% VAF], 0.97 [0.2-0.1% VAF]). We compared our consensus calling and advanced filtering approach to a machine learning model. A decision-tree-based ensemble machine learning algorithm, XGBoost, was trained on the tumor-dilution samples with validation using 31 blood samples with orthogonal sequencing. The variant caller output (allele counts, flags, etc.), additional false positive filtering metrics, and statistical results from the technical controls were used as features. Sensitivity and PPV was high for mutations above 1% VAF (0.97 sensitivity and 0.82 PPV) with the performance declining for lower VAF mutations (0.72 sensitivity and 0.65 PPV). Thus, a machine learning approach did not outperform consensus calling with advanced artifact filtering. Finally, we developed a custom annotation pipeline for CH variant pathogenicity classification incorporating previously reported CH mutations in large cohorts, cancer somatic mutation frequency databases and curated cancer driver knowledge databases. Conclusion: We developed ArCCH, an advanced artifact filtering and consensus CH calling pipeline that includes custom annotation features to facilitate CH pathogenicity determination. Our results show that our consensus approach with advanced error correction filters substantially improves the performance of CH variant calling beyond commonly used single variant callers. This end-to-end flexible workflow package is publicly available on Terra and will facilitate future CH studies.

Clinicogenomic characteristics and synthetic lethal implications of germline homologous recombination-deficient hepatocellular carcinoma.

We performed an in-depth examination of pathogenic germline variants (PGVs) and somatic variants in DNA damage response (DDR) genes in hepatocellular carcinoma (HCC) to explore their clinical and genomic impacts. We used a merged whole-exome or RNA sequencing data set derived from in-house ( n = 230) and The Cancer Genome Atlas ( n = 362) databases of multiethnic HCC samples. We also evaluated synthetic lethal approaches targeting mutations in homologous recombination (HR) genes using HCC cells selected from five genomic databases of cancer cell lines. A total of 110 PGVs in DDR pathways in 96 patients were selected. Of the PGV carriers, 44 were HR-altered and found to be independently associated with poorer disease-free survival after hepatectomy. The most frequently altered HR gene in both germline and somatic tissues was POLQ , and this variant was detected in 22.7% (10/44) and 23.8% (5/21) of all the corresponding carriers, respectively. PGVs in HR were significantly associated with upregulation of proliferation and replication-related genes and familial risk of HCC. Samples harboring PGVs in HR with loss of heterozygosity were most strongly correlated with the genomic footprints of deficient HR, such as mutation burden and denovoSig2 (analogous to Catalogue of Somatic Mutations in Cancer [COSMIC] 3), and poor outcome. Pharmacologic experiments with HCC cells defective in BRCA2 or POLQ suggested that tumors with this phenotype are synthetic lethal with poly(ADP-ribose) polymerase inhibitors. Our findings suggest that germline HR defects in HCC tend to confer a poor prognosis and result in distinctive genomic scarring. Tests of the clinical benefits of HR-directed treatments in the affected patients are needed.

VariantAlert: A web-based tool to notify updates in genetic variant annotations.

The reinterpretation of variants based on updated annotations is part of the routine work of research laboratories: the more data is collected about a specific variant, the higher the probability to reinterpret its classification. To support this task, we developed VariantAlert, a web-based tool to help researchers and clinicians to be constantly informed about changes in variant annotations extracted from multiple sources. VariantAlert provides daily re-annotation of variants using external resources accessed through application programming interface, such as MyVariant.info providing in turn links to gnomAD, catalogue of somatic mutations In cancer (COSMIC), ClinVar, CIViC, and many others. Researchers and clinicians can submit one or more lists of variants. If a change is detected for the annotation of a variant due to the upgrade of the underlying resource (e.g., change in gnomAD allele frequency, presence in COSMIC database, change in ClinVar classification) the user is notified by email and updated annotations are stored on the web-site. VariantAlert is freely available at https://github.com/next-crs4/VariantAlert. Installation and deployment are easy thanks to the use of the Docker platform. A Makefile allows you to easily bootstrap VariantAlert. VariantAlert is also available as a web service at https://variant-alert.crs4.it/.

Excerno: Using Mutational Signatures in Sequencing Data to Filter False Variants Caused by Clinical Archival.

The accurate detection of point mutations from pathology slides using sequencing data is of great importance in cancer genomics and precision oncology. Formalin-fixation paraffin-embedding (FFPE) is a widely used technique to preserve pathology tissues. The FFPE process introduces artificial C > T mutations in next-generation sequencing, so we set out to develop excerno, a method to score and filter such spurious variants. FFPE mutational artifacts follow a mutational signature. By using the FFPE signature and Bayes' formula, we can calculate the probability of a mutation resulting from the FFPE process and use this probability to filter FFPE variants. We implement this method as the excerno R package. We tested excerno by simulating mutations across all 60-baseline mutational signatures from the Catalog of Somatic Mutations in Cancer (COSMIC) and combining them with mutations following the FFPE mutational signature. The sensitivity and specificity of excerno are adversely affected by the cosine similarity between the baseline and FFPE signatures (). Higher percentages of FFPE mutations () result in increased sensitivity and reduced specificity. The specificity and sensitivity of excerno can be predicted as linear model with an interaction term using and , with an and 0.79, respectively. Finally, we tested excerno using six RNA sequencing cancer samples and observed concordant trends of specificity and sensitivity with respect to our simulated data. The excerno R package can be used to annotate and filter FFPE-induced mutations in cancer genomics. Our method is adversely affected by and .