Systematic discovery of germline cancer predisposition genes through the identification of somatic second hits

TCGEx: a powerful visual interface for exploring and analyzing cancer gene expression data

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr , providing an accessible tool to extract insights from cancer transcriptomics data.

Proteogenomic Profiling of Treatment-Naïve Metastatic Malignant Melanoma

BACKGROUND

Melanoma is a highly heterogeneous disease, and a deeper molecular classification is essential for improving patient stratification and treatment approaches. Here, we describe the histopathology-driven proteogenomic landscape of 142 treatment-naïve metastatic melanoma samples to uncover molecular subtypes and clinically relevant biomarkers.

METHODS

We performed an integrative proteogenomic analysis to identify proteomic subtypes, assess the impact of BRAF V600 mutations, and study the molecular profiles and cellular composition of the tumor microenvironment. Clinical and histopathological data were used to support findings related to tissue morphology, disease progression, and patient outcomes.

RESULTS

Our analysis revealed five distinct proteomic subtypes that integrate immune and stromal microenvironment components and correlate with clinical and histopathological parameters. We demonstrated that BRAF V600-mutated melanomas exhibit biological heterogeneity, where an oncogene-induced senescence-like phenotype is associated with improved survival. This led to a proposed mortality risk-based stratification that may contribute to more personalized treatment strategies. Furthermore, tumor microenvironment composition strongly correlated with disease progression and patient outcomes, highlighting a histopathological connective tissue-to-tumor ratio assessment as a potential decision-making tool. We identified a melanoma-associated SAAV signature linked to extracellular matrix remodeling and SAAV-derived neoantigens as potential targets for anti-tumor immune responses.

CONCLUSIONS

This study provides a comprehensive stratification of metastatic melanoma, integrating proteogenomic insights with histopathological features. The findings may aid in the development of tailored diagnostic and therapeutic strategies, improving patient management and outcomes.

Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver mutations

Cancer driver genes can undergo positive selection for various types of genetic alterations, including gain-of-function or loss-of-function mutations and copy number alterations (CNA). We investigated the landscape of different types of alterations affecting driver genes in 17,644 cancer exomes and genomes. We find that oncogenes may simultaneously exhibit signatures of positive selection and also negative selection in different gene segments, suggesting a method to identify additional tumor types where an oncogene is a driver or a vulnerability. Next, we characterize the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Similarly, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed regardless of the type of CNA and may signal new therapeutic opportunities. An analysis with focus on the somatic CNA two-hit events can help identify additional driver genes relevant to a tumor type. By a global inference of point mutation and CNA selection signatures and interactions thereof across genes and tissues, we identify 9 evolutionary archetypes of driver genes, representing different mechanisms of (in)activation by genetic alterations.

Systematic analysis of Mendelian disease-associated gene variants reveals new classes of cancer-predisposing genes

BACKGROUND

Despite the acceleration of somatic driver gene discovery facilitated by recent large-scale tumor sequencing data, the contribution of inherited variants remains largely unexplored, primarily focusing on previously known cancer predisposition genes (CPGs) due to the low statistical power associated with detecting rare pathogenic variant-phenotype associations.

METHODS

Here, we introduce a generalized log-regression model to measure the excess of pathogenic variants within genes in cancer patients compared to control samples. It aims to measure gene-level cancer risk enrichment by collapsing rare pathogenic variants after controlling the population differences across samples.

RESULTS

In this study, we investigate whether pathogenic variants in Mendelian disease-associated genes (OMIM genes) are enriched in cancer patients compared to controls. Utilizing data from PCAWG and the 1,000 Genomes Project, we identify 103 OMIM genes demonstrating significant enrichment of pathogenic variants in cancer samples (FDR 20%). Through an integrative approach considering three distinct properties, we classify these CPG-like OMIM genes into four clusters, indicating potential diverse mechanisms underlying tumor progression. Further, we explore the function of PAH (a key metabolic enzyme associated with Phenylketonuria), the gene exhibiting the highest prevalence of pathogenic variants in a pan-cancer (1.8%) compared to controls (0.6%).

CONCLUSIONS

Our findings suggest a possible cancer progression mechanism through metabolic profile alterations. Overall, our data indicates that pathogenic OMIM gene variants contribute to cancer progression and introduces new CPG classifications potentially underpinning diverse tumorigenesis mechanisms.

Comprehensive genomic profiling of breast cancers characterizes germline-somatic mutation interactions mediating therapeutic vulnerabilities

Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

Transmission ratio distortion detection by neutral genetic markers in the Pura Raza Española horse breed

Transmission Ratio Distortion (TRD) is a genetic phenomenon widely demonstrated in several livestock species, but barely in equine species. The TRD occurs when certain genotypes are over- or under-represented in the offspring of a particular mating and can be caused by a variety of factors during gamete formation or during embryonic development. For this study, 126 394 trios consisting of a stallion, mare, and offspring were genotyped using a panel of 17 neutral microsatellite markers recommended by the International Society for Animal Genetics for paternity tests and individual identification. The number of alleles available for each marker ranges from 13 to 18, been 268 the total number of alleles investigated. The TRDscan v.2.0 software was used with the biallelic procedure to identify regions with distorted segregation ratios. After completing the analysis, a total of 12 alleles (out of 11 microsatellites) were identified with decisive evidence for genotypic TRD; 3 and 9 with additive and heterosis patterns, respectively. In addition, 19 alleles (out of 10 microsatellites) were identified displaying allelic TRD. Among them, 14 and 5 were parent-unspecific and stallion-mare-specific TRD. Out of the TRD regions, 24 genes were identified and annotated, predominantly associated with cholesterol metabolism and homeostasis. These genes are often linked to non-specific symptoms like impaired fertility, stunted growth, and compromised overall health. The results suggest a significant impact on the inheritance of certain genetic traits in horses. Further analysis and validation are needed to better understand the TRD impact before the potential implementation in the horse breeding programme strategies.

Clonal Evolution in Healthy and Premalignant Tissues: Implications for Early Cancer Interception Strategies

Histologically normal human tissues accumulate significant mutational burden with age. The extent and spectra of mutagenesis are comparable both in rapidly proliferating and post-mitotic tissues and in stem cells compared with their differentiated progeny. Some of these mutations provide increased fitness, giving rise to clones which, at times, can replace the entire surface area of tissues. Compared with cancer, somatic mutations in histologically normal tissues are primarily single-nucleotide variations. Interestingly though, the presence of these mutations and positive clonal selection in isolation remains a poor indicator of potential future cancer transformation in solid tissues. Common clonally expanded mutations in histologically normal tissues also do not always represent the most frequent early mutations in cancers of corresponding tissues, indicating differences in selection pressures. Preliminary evidence implies that stroma and immune system co-evolve with age, which may impact selection dynamics. In this review, we will explore the mutational landscape of histologically normal and premalignant human somatic tissues in detail and discuss cell-intrinsic and environmental factors that can determine the fate of positively selected mutations within them. Precisely pinpointing these determinants of cancer transformation would aid development of early cancer interventional and prevention strategies.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

The impact of rare germline variants on human somatic mutation processes

Somatic mutations are an inevitable component of ageing and the most important cause of cancer. The rates and types of somatic mutation vary across individuals, but relatively few inherited influences on mutation processes are known. We perform a gene-based rare variant association study with diverse mutational processes, using human cancer genomes from over 11,000 individuals of European ancestry. By combining burden and variance tests, we identify 207 associations involving 15 somatic mutational phenotypes and 42 genes that replicated in an independent data set at a false discovery rate of 1%. We associate rare inherited deleterious variants in genes such as MSH3, EXO1, SETD2, and MTOR with two phenotypically different forms of DNA mismatch repair deficiency, and variants in genes such as EXO1, PAXIP1, RIF1, and WRN with deficiency in homologous recombination repair. In addition, we identify associations with other mutational processes, such as APEX1 with APOBEC-signature mutagenesis. Many of the genes interact with each other and with known mutator genes within cellular sub-networks. Considered collectively, damaging variants in the identified genes are prevalent in the population. We suggest that rare germline variation in diverse genes commonly impacts mutational processes in somatic cells.

Mutational signatures are markers of drug sensitivity of cancer cells

Genomic analyses have revealed mutational footprints associated with DNA maintenance gone awry, or with mutagen exposures. Because cancer therapeutics often target DNA synthesis or repair, we asked if mutational signatures make useful markers of drug sensitivity. We detect mutational signatures in cancer cell line exomes (where matched healthy tissues are not available) by adjusting for the confounding germline mutation spectra across ancestries. We identify robust associations between various mutational signatures and drug activity across cancer cell lines; these are as numerous as associations with established genetic markers such as driver gene alterations. Signatures of prior exposures to DNA damaging agents - including chemotherapy - tend to associate with drug resistance, while signatures of deficiencies in DNA repair tend to predict sensitivity towards particular therapeutics. Replication analyses across independent drug and CRISPR genetic screening data sets reveal hundreds of robust associations, which are provided as a resource for drug repurposing guided by mutational signature markers.

Germline Variants in Cancer Genes from Young Breast Cancer Mexican Patients

Breast cancer (BC) is one of the most frequent cancer types in women worldwide. About 7% is diagnosed in young women (YBC) less than 40 years old. In Mexico, however, YBC reaches 15% suggesting a higher genetic susceptibility. There have been some reports of germline variants in YBC across the world. However, there is only one report from a Mexican population, which is not restricted by age and limited to a panel of 143 genes resulting in 15% of patients carrying putatively pathogenic variants. Nevertheless, expanding the analysis to whole exome involves using more complex tools to determine which genes and variants could be pathogenic. We used germline whole exome sequencing combined with the PeCanPie tool to analyze exome variants in 115 YBC patients. Our results showed that we were able to identify 49 high likely pathogenic variants involving 40 genes on 34% of patients. We noted many genes already reported in BC and YBC worldwide, such as BRCA1, BRCA2, ATM, CHEK2, PALB2, and POLQ, but also others not commonly reported in YBC in Latin America, such as CLTCL1, DDX3X, ERCC6, FANCE, and NFKBIE. We show further supporting and controversial evidence for some of these genes. We conclude that exome sequencing combined with robust annotation tools and further analysis, can identify more genes and more patients affected by germline mutations in cancer.

Gain of Chromosome 6p Correlates with Severe Anaplasia, Cellular Hyperchromasia, and Extraocular Spread of Retinoblastoma

PURPOSE

Gain of chromosome 6p has been associated with poor ocular survival in retinoblastoma and histopathologic grading of anaplasia with increased risk of metastatic spread and death. This study examined the correlation between these factors and other chromosomal abnormalities as well as results of whole genome sequencing, digital morphometry, and progression-free survival.

DESIGN

Retrospective cohort study from 2 United States tertiary referral centers.

PARTICIPANTS

Forty-two children who had undergone enucleation for retinoblastoma from January 2000 through December 2017.

METHODS

Status of chromosomes 6p, 1q, 9q, and 16q was evaluated with fluorescence in situ hybridization, the degree of anaplasia and presence of histologic high-risk features were assessed by ocular pathologists, digital morphometry was performed on scanned tumor slides, and whole genome sequencing was performed on a subset of tumors. Progression-free survival was defined as absence of distant or local metastases or tumor growth beyond the cut end of the optic nerve.

MAIN OUTCOME MEASURES

Correlation between each of chromosomal abnormalities, anaplasia, morphometry and sequencing results, and survival.

RESULTS

Forty-one of 42 included patients underwent primary enucleation and 1 was treated first with intra-arterial chemotherapy. Seven tumors showed mild anaplasia, 19 showed moderate anaplasia, and 16 showed severe anaplasia. All tumors had gain of 1q, 18 tumors had gain of 6p, 6 tumors had gain of 9q, and 36 tumors had loss of 16q. Tumors with severe anaplasia were significantly more likely to harbor 6p gains than tumors with nonsevere anaplasia (P < 0.001). Further, the hematoxylin staining intensity was significantly greater and that of eosin staining significantly lower in tumors with severe anaplasia (P < 0.05). Neither severe anaplasia (P = 0.10) nor gain of 6p (P = 0.21) correlated with histologic high-risk features, and severe anaplasia did not correlate to RB1, CREBBP, NSD1, or BCOR mutations in a subset of 14 tumors (P > 0.5). Patients with gain of 6p showed significantly shorter progression-free survival (P = 0.03, Wilcoxon test).

CONCLUSIONS

Gain of chromosome 6p emerges as a strong prognostic biomarker in retinoblastoma because it correlates with severe anaplasia, quantifiable changes in tumor cell staining characteristics, and extraocular spread.

Potential Involvement of NSD1, KRT24 and ACACA in the Genetic Predisposition to Colorectal Cancer

Simple Summary

Methods used for the identification of hereditary cancer genes have evolved in parallel to technological progress; however, much of the genetic predisposition to cancer remains unexplained. A new in silico method based on Knudson’s two-hit hypothesis recently identified ~50 putative cancer predisposing genes, but their actual association with cancer has not yet been validated. In our study, we aimed to assess the involvement of these genes in familial/early-onset colorectal cancer (CRC) using different lines of evidence. Our results indicated that most of those genes were not associated with a genetic predisposition to CRC, but suggested a possible association for NSD1, KRT24 and ACACA.

Abstract

The ALFRED (Allelic Loss Featuring Rare Damaging) in silico method was developed to identify cancer predisposition genes through the identification of somatic second hits. By applying ALFRED to ~10,000 tumor exomes, 49 candidate genes were identified. We aimed to assess the causal association of the identified genes with colorectal cancer (CRC) predisposition. Of the 49 genes, NSD1, HDAC10, KRT24, ACACA and TP63 were selected based on specific criteria relevant for hereditary CRC genes. Gene sequencing was performed in 736 patients with familial/early onset CRC or polyposis without germline pathogenic variants in known genes. Twelve (predicted) damaging variants in 18 patients were identified. A gene-based burden test in 1596 familial/early-onset CRC patients, 271 polyposis patients, 543 TCGA CRC patients and >134,000 controls (gnomAD, non-cancer), revealed no clear association with CRC for any of the studied genes. Nevertheless, (non-significant) over-representation of disruptive variants in NSD1, KRT24 and ACACA in CRC patients compared to controls was observed. A somatic second hit was identified in one of 20 tumors tested, corresponding to an NSD1 carrier. In conclusion, most genes identified through the ALFRED in silico method were not relevant for CRC predisposition, although a possible association was detected for NSD1, KRT24 and ACACA.

Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers

The classic two-hit model posits that both alleles of a tumor suppressor gene (TSG) must be inactivated to cause cancer. In contrast, for some oncogenes and haploinsufficient TSGs, a single genetic alteration can suffice to increase tumor fitness. Here, by quantifying the interactions between mutations and copy number alterations (CNAs) across 10,000 tumors, we show that many cancer genes actually switch between acting as one-hit or two-hit drivers. Third order genetic interactions identify the causes of some of these switches in dominance and dosage sensitivity as mutations in other genes in the same biological pathway. The correct genetic model for a gene thus depends on the other mutations in a genome, with a second hit in the same gene or an alteration in a different gene in the same pathway sometimes representing alternative evolutionary paths to cancer.

A protein interaction landscape of breast cancer

[Figure: see text].

Clinical Quality in Cancer Research: Strategy to Assess Data Integrity of Germline Variants Inferred from Tumor-Only Testing Sequencing Data

In the majority of cancers, pathogenic variants are only found at the level of the tumor; however, an unusual number of cancers and/or diagnoses at an early age in a single family may suggest a genetic predisposition. Predisposition plays a major role in about 5-10% of adult cancers and in certain childhood tumors. As access to genomic testing for cancer patients continues to expand, the identification of potential germline pathogenic variants (PGPVs) through tumor-DNA sequencing is also increasing. Statistical methods have been developed to infer the presence of a PGPV without the need of a matched normal sample. These methods are mainly used for exploratory research, for example in real-world clinico-genomic databases/platforms (CGDB). These databases are being developed to support many applications, such as targeted drug development, clinical trial optimization, and postmarketing studies. To ensure the integrity of data used for research, a quality management system should be established, and quality oversight activities should be conducted to assess and mitigate clinical quality risks (for patient safety and data integrity). As opposed to well-defined 'good practice' quality guidelines (GxP) areas such as good clinical practice, there are no comprehensive instructions on how to assess the clinical quality of statistically derived variables from sequencing data such as PGPVs. In this article, we aim to share our strategy and propose a possible set of tactics to assess the PGPV quality and to ensure data integrity in exploratory research.

NSD1: A Lysine Methyltransferase between Developmental Disorders and Cancer

Recurrent epigenomic alterations associated with multiple human pathologies have increased the interest in the nuclear receptor binding SET domain protein 1 (NSD1) lysine methyltransferase. Here, we review the current knowledge about the biochemistry, cellular function and role of NSD1 in human diseases. Several studies have shown that NSD1 controls gene expression by methylation of lysine 36 of histone 3 (H3K36me1/2) in a complex crosstalk with de novo DNA methylation. Inactivation in flies and mice revealed that NSD1 is essential for normal development and that it regulates multiple cell type-specific functions by interfering with transcriptional master regulators. In humans, putative loss of function NSD1 mutations characterize developmental syndromes, such as SOTOS, as well as cancer from different organs. In pediatric hematological malignancies, a recurrent chromosomal translocation forms a NUP98-NSD1 fusion with SET-dependent leukemogenic activity, which seems targetable by small molecule inhibitors. To treat or prevent diseases driven by aberrant NSD1 activity, future research will need to pinpoint the mechanistic correlation between the NSD1 gene dosage and/or mutational status with development, homeostasis, and malignant transformation.

X-CNV: genome-wide prediction of the pathogenicity of copy number variations

Background

Gene copy number variations (CNVs) contribute to genetic diversity and disease prevalence across populations. Substantial efforts have been made to decipher the relationship between CNVs and pathogenesis but with limited success.

Results

We have developed a novel computational framework X-CNV (www.unimd.org/XCNV), to predict the pathogenicity of CNVs by integrating more than 30 informative features such as allele frequency (AF), CNV length, CNV type, and some deleterious scores. Notably, over 14 million CNVs across various ethnic groups, covering nearly 93% of the human genome, were unified to calculate the AF. X-CNV, which yielded area under curve (AUC) values of 0.96 and 0.94 in training and validation sets, was demonstrated to outperform other available tools in terms of CNV pathogenicity prediction. A meta-voting prediction (MVP) score was developed to quantitively measure the pathogenic effect, which is based on the probabilistic value generated from the XGBoost algorithm. The proposed MVP score demonstrated a high discriminative power in determining pathogenetic CNVs for inherited traits/diseases in different ethnic groups.

Conclusions

The ability of the X-CNV framework to quantitatively prioritize functional, deleterious, and disease-causing CNV on a genome-wide basis outperformed current CNV-annotation tools and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00945-4.

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

The characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.

Prevalence of cancer susceptibility variants in patients with multiple Lynch syndrome related cancers

Along with early-onset cancers, multiple primary cancers (MPCs) are likely resulting from increased genetic susceptibility; however, the associated predisposition genes or prevalence of the pathogenic variants genes in MPC patients are often unknown. We screened 71 patients with MPC of the stomach, colorectal, and endometrium, sequencing 65 cancer predisposition genes. A subset of 19 patients with early-onset MPC of stomach and colorectum were further evaluated for variants in cancer related genes using both normal and tumor whole exome sequencing. Among 71 patients with MPCs, variants classified to be pathogenic were observed in 15 (21.1%) patients and affected Lynch Syndrome (LS) genes: MLH1 (n = 10), MSH6 (n = 2), PMS2 (n = 2), and MSH2 (n = 1). All carriers had tumors with high microsatellite instability and 13 of them (86.7%) were early-onset, consistent with LS. In 19 patients with early-onset MPCs, loss of function (LoF) variants in RECQL5 were more prevalent in non-LS MPC than in matched sporadic cancer patients (OR = 31.6, 2.73–1700.6, p = 0.001). Additionally, there were high-confidence LoF variants at FANCG and CASP8 in two patients accompanied by somatic loss of heterozygosity in tumor, respectively. The results suggest that genetic screening should be considered for synchronous cancers and metachronous MPCs of the LS tumor spectrum, particularly in early-onset. Susceptibility variants in non-LS genes for MPC patients may exist, but evidence for their role is more elusive than for LS patients.

Comprehensive Study of Germline Mutations and Double-Hit Events in Esophageal Squamous Cell Cancer

Esophageal squamous cell cancer (ESCC) is the eighth most common cancer around the world. Several reports have focused on somatic mutations and common germline mutations in ESCC. However, the contributions of pathogenic germline alterations in cancer susceptibility genes (CSGs), highly frequently mutated CSGs, and pathogenically mutated CSG-related pathways in ESCC remain unclear. We obtained data on 571 ESCC cases from public databases and East Asian from the 1000 Genomes Project database and the China Metabolic Analytics Project database to characterize pathogenic mutations. We detected 157 mutations in 75 CSGs, accounting for 25.0% (143/571) of ESCC cases. Six genes had more than five mutations: TP53 (n = 15 mutations), GJB2 (n = 8), BRCA2 (n = 6), RECQL4 (n = 6), MUTYH (n = 6), and PMS2 (n = 5). Our results identified significant differences in pathogenic germline mutations of TP53, BRCA2, and RECQL4 between the ESCC and control cohorts. Moreover, we identified 84 double-hit events (16 germline/somatic double-hit events and 68 somatic/somatic double-hit events) occurring in 18 tumor suppressor genes from 83 patients. Patients who had ESCC with germline/somatic double-hit events were diagnosed at younger ages than patients with the somatic/somatic double-hit events, though the correlation was not significant. Fanconi anemia was the most enriched pathway of pathogenically mutated CSGs, and it appeared to be a primary pathway for ESCC predisposition. The results of this study identified the underlying roles that pathogenic germline mutations in CSGs play in ESCC pathogenesis, increased our awareness about the genetic basis of ESCC, and provided suggestions for using highly mutated CSGs and double-hit features in the early discovery, prevention, and genetic counseling of ESCC.

Detection of Rare Germline Variants in the Genomes of Patients with B-Cell Neoplasms

Simple Summary

The global importance of rare variants in tumorigenesis has been addressed by some pan-cancer analysis, revealing significant enrichments in protein-truncating variants affecting genes such as ATM, BRCA1/2, BRIP1, and MSH6. Germline variants can influence treatment response and contribute to the development of treatment-related second neoplasms, especially in childhood leukemia. We aimed to analyze the genomes of patients with B-cell lymphoproliferative disorders for the discovery of genes enriched in rare pathogenic variants. We discovered a significant enrichment for two genes in germline rare and dysfunctional variants. Additionally, we detected rare and likely pathogenic variants associated with disease prognosis and potential druggability, indicating a relevant role of these events in the variability of cancer phenotypes.

Abstract

There is growing evidence indicating the implication of germline variation in cancer predisposition and prognostication. Here, we describe an analysis of likely disruptive rare variants across the genomes of 726 patients with B-cell lymphoid neoplasms. We discovered a significant enrichment for two genes in rare dysfunctional variants, both of which participate in the regulation of oxidative stress pathways (CHMP6 and GSTA4). Additionally, we detected 1675 likely disrupting variants in genes associated with cancer, of which 44.75% were novel events and 7.88% were protein-truncating variants. Among these, the most frequently affected genes were ATM, BIRC6, CLTCL1A, and TSC2. Homozygous or germline double-hit variants were detected in 28 cases, and coexisting somatic events were observed in 17 patients, some of which affected key lymphoma drivers such as ATM, KMT2D, and MYC. Finally, we observed that variants in six different genes were independently associated with shorter survival in CLL. Our study results support an important role for rare germline variation in the pathogenesis and prognosis of B-cell lymphoid neoplasms.

Germline and Somatic Whole-Exome Sequencing Identifies New Candidate Genes Involved in Familial Predisposition to Serrated Polyposis Syndrome

The serrated polyposis syndrome (SPS) is the most common and yet underdiagnosed colorectal polyposis syndrome. It is characterized by multiple and/or large colonic serrated polyps and a higher associated risk for colorectal cancer (CRC). The main objective of this study was to identify new candidate genes involved in the germline predisposition to SPS/CRC. Thirty-nine SPS patients from 16 families (≥2 patients per family) were recruited without alterations in well-known hereditary CRC genes, and germline and somatic whole-exome sequencing were performed. Germline rare variants with plausible pathogenicity, located in genes involved in cancer development, senescence and epigenetic regulation were selected. Somatic mutational profiling and signature analysis was pursued in one sample per family, when possible. After data filtering, ANXA10, ASXL1, CFTR, DOT1L, HIC1, INO80, KLF3, MCM3AP, MCM8, PDLIM2, POLD1, TP53BP1, WNK2 and WRN were highlighted as the more promising candidate genes for SPS germline predisposition with potentially pathogenic variants shared within families. Somatic analysis characterized mutational profiles in advanced serrated polyps/tumors, revealing a high proportion of hypermutated samples, with a prevalence of clock-like mutational signatures in most samples and the presence of DNA mismatch repair-defective signatures in some cases. In conclusion, we identified new candidate genes to be involved in familial SPS. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.

Targeting RNA-binding proteins in acute and chronic leukemia

RNA-binding proteins (RBPs) play a crucial role in cellular physiology by regulating RNA processing, translation, and turnover. In neoplasms, RBP support of cancer-relevant expression of alternatively spliced, modified, and stabilized mRNA transcripts is essential to self-renewal, proliferation, and adaptation to stress. In this review, we assess the impact of key families of RBPs in leukemogenesis, review progress in targeting those proteins with small molecules, and discuss how multilevel composition of posttranscriptional regulation of gene expression could be used for potential therapies in acute and chronic leukemia.

How wide is the application of genetic big data in biomedicine

In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As countries around the world start to build their own gene banks, scientists study the data to explore the origins and migration of humans. Moreover, big data encourage the development of cancer therapy and bring good news to cancer patients. Big datum has been involved in the study of many diseases, and it has been found that analyzing diseases at the gene level can lead to more beneficial treatment options than ordinary treatments. This review will introduce the development of extensive data in medical research from the perspective of big data and tumor, neurological and psychiatric diseases, cardiovascular diseases, other applications and the development direction of big data in medicine.

Genetic control of tumor development in malformation syndromes

One of the questions that arises frequently when caring for an individual with a malformation syndrome, is whether some form of tumor surveillance is indicated. In some syndromes there is a highly variable increased risk to develop tumors, while in others this is not the case. The risks can be hard to predict and difficult to explain to affected individuals and their families, and often also to caregivers. The queries arise especially if syndrome causing mutations are also known to occur in tumors. It needs insight in the mechanisms to understand and explain differences of tumor occurrence, and to offer optimal care to individuals with syndromes. Here we provide a short overview of the major mechanisms of the control for tumor occurrences in malformation syndromes.

Mouse tumor susceptibility genes identify drug combinations for multiple myeloma

Long-term genetic studies utilizing backcross and congenic strain analyses coupled with positional cloning strategies and functional studies identified Cdkn2a, Mtor, and Mndal as mouse plasmacytoma susceptibility/resistance genes. Tumor incidence data in congenic strains carrying the resistance alleles of Cdkn2a and Mtor led us to hypothesize that drug combinations affecting these pathways are likely to have an additive, if not synergistic effect in inhibiting tumor cell growth. Traditional and novel systems-level genomic approaches were used to assess combination activity, disease specificity, and clinical potential of a drug combination involving rapamycin/everolimus, an Mtor inhibitor, with entinostat, an histone deacetylase inhibitor. The combination synergistically repressed oncogenic MYC and activated the Cdkn2a tumor suppressor. The identification of MYC as a primary upstream regulator led to the identification of small molecule binders of the G-quadruplex structure that forms in the NHEIII region of the MYC promoter. These studies highlight the importance of identifying drug combinations which simultaneously upregulate tumor suppressors and downregulate oncogenes.

Nuclear interacting SET domain protein 1 inactivation impairs GATA1-regulated erythroid differentiation and causes erythroleukemia

The nuclear receptor binding SET domain protein 1 (NSD1) is recurrently mutated in human cancers including acute leukemia. We show that NSD1 knockdown alters erythroid clonogenic growth of human CD34⁺ hematopoietic cells. Ablation of Nsd1 in the hematopoietic system of mice induces a transplantable erythroleukemia. In vitro differentiation of Nsd1^−/− erythroblasts is majorly impaired despite abundant expression of GATA1, the transcriptional master regulator of erythropoiesis, and associated with an impaired activation of GATA1-induced targets. Retroviral expression of wildtype NSD1, but not a catalytically-inactive NSD1^N1918Q SET-domain mutant induces terminal maturation of Nsd1^−/− erythroblasts. Despite similar GATA1 protein levels, exogenous NSD1 but not NSD^N1918Q significantly increases the occupancy of GATA1 at target genes and their expression. Notably, exogenous NSD1 reduces the association of GATA1 with the co-repressor SKI, and knockdown of SKI induces differentiation of Nsd1^−/− erythroblasts. Collectively, we identify the NSD1 methyltransferase as a regulator of GATA1-controlled erythroid differentiation and leukemogenesis.

Loss of function mutations of NSD1 occur in blood cancers. Here, the authors report that NSD1 loss blocks erythroid differentiation which leads to an erythroleukemia-like disease in mice by impairing GATA1-induced target gene activation.

Ancestry-specific predisposing germline variants in cancer

BACKGROUND

Distinct prevalence of inherited genetic predisposition may partially explain the difference of cancer risks across ancestries. Ancestry-specific analyses of germline genomes are required to inform cancer genetic risk and prognosis of diverse populations.

METHODS

We conducted analyses using germline and somatic sequencing data generated by The Cancer Genome Atlas. Collapsing pathogenic and likely pathogenic variants to cancer predisposition genes (CPG), we analyzed the association between CPGs and cancer types within ancestral groups. We also identified the predisposition-associated two-hit events and gene expression effects in tumors.

RESULTS

Genetic ancestry analysis classified the cohort of 9899 cancer cases into individuals of primarily European (N = 8184, 82.7%), African (N = 966, 9.8%), East Asian (N = 649, 6.6%), South Asian (N = 48, 0.5%), Native/Latin American (N = 41, 0.4%), and admixed (N = 11, 0.1%) ancestries. In the African ancestry, we discovered a potentially novel association of BRCA2 in lung squamous cell carcinoma (OR = 41.4 [95% CI, 6.1-275.6]; FDR = 0.002) previously identified in Europeans, along with a known association of BRCA2 in ovarian serous cystadenocarcinoma (OR = 8.5 [95% CI, 1.5-47.4]; FDR = 0.045). In the East Asian ancestry, we discovered one previously known association of BRIP1 in stomach adenocarcinoma (OR = 12.8 [95% CI, 1.8-90.8]; FDR = 0.038). Rare variant burden analysis further identified 7 suggestive associations in African ancestry individuals previously described in European ancestry, including SDHB in pheochromocytoma and paraganglioma, ATM in prostate adenocarcinoma, VHL in kidney renal clear cell carcinoma, FH in kidney renal papillary cell carcinoma, and PTEN in uterine corpus endometrial carcinoma. Most predisposing variants were found exclusively in one ancestry in the TCGA and gnomAD datasets. Loss of heterozygosity was identified for 7 out of the 15 African ancestry carriers of predisposing variants. Further, tumors from the SDHB or BRCA2 carriers showed simultaneous allelic-specific expression and low gene expression of their respective affected genes, and FH splice-site variant carriers showed mis-splicing of FH.

CONCLUSIONS

While several CPGs are shared across patients, many pathogenic variants are found to be ancestry-specific and trigger somatic effects. Studies using larger cohorts of diverse ancestries are required to pinpoint ancestry-specific genetic predisposition and inform genetic screening strategies.

Bioinformatic Analysis Reveals an Immune/Inflammatory-Related Risk Signature for Oral Cavity Squamous Cell Carcinoma

High-throughput gene expression profiling has recently emerged as a promising technique that provides insight into cancer subtype classification and improved prediction of prognoses. Immune/inflammatory-related mRNAs may potentially enrich genes to allow researchers to better illustrate cancer microenvironments. Oral cavity squamous cell carcinoma (OC-SCC) exhibits high morbidity and poor prognosis compared to that of other types of head and neck squamous cell carcinoma (HNSCC), and these differences may be partially due to differences within the tumor microenvironments. Based on this, we designed an immune-related signature to improve the prognostic prediction of OC-SCC. A cohort of 314 OC-SCC samples possessing whole genome expression data that were sourced from The Cancer Genome Atlas (TCGA) database was included for discovery. The GSE41613 database was used for validation. A risk score was established using immune/inflammatory signatures acquired from the training dataset. Principal components analysis, GO analysis, and gene set enrichment analysis were used to explore the bioinformatic implications. When grouped by the dichotomized risk score based on the signature, this classifier could successfully discriminate patients with distinct prognoses within the training and validation cohorts (P < 0.05 in both cohorts) and within different clinicopathological subgroups. Similar somatic mutation patterns were observed between high and low risk score groups, and different copy number variation patterns were also identified. Further bioinformatic analyses suggested that the lower risk score group was significantly correlated with immune/inflammatory-related biological processes, while the higher risk score group was highly associated with cell cycle-related processes. The analysis indicated that the risk score was a robust predictor of patient survival, and its functional annotation was well established. Therefore, this bioinformatic-based immune-related signature suggested that the microenvironment of OC-SCC could distinguish among patients with different underlying biological processes and clinical outcomes, and the use of this signature may shed light on future OC-SCC classification and therapeutic design.

Evolving Significance of Tumor-Normal Sequencing in Cancer Care

Molecular tests assist at various stages of cancer patient management, including providing diagnosis, predicting prognosis, identifying therapeutic targets, and determining hereditary cancer risk. The current testing paradigm involves germline testing in a subset of patients determined to be at high risk for having a hereditary cancer syndrome, and tumor-only sequencing for treatment decisions in advanced cancer patients. A major limitation of tumor-only sequencing is its inability to distinguish germline versus somatic mutations. Tumor-normal sequencing has emerged as a comprehensive analysis for both hereditary cancer predisposition and somatic profiling. Here, we review recent studies involving tumor-normal sequencing, discuss its benefits in clinical care, challenges for its implementation, and novel insights it has provided regarding tumor biology and germline contribution to cancer.

Potential genetic modifiers for somatic EGFR mutation in lung cancer: a meta-analysis and literature review

BACKGROUND

Accumulating evidence indicates inherited risk in the aetiology of lung cancer, although smoking exposure is the major attributing factor. Family history is a simple substitute for inherited susceptibility. Previous studies have shown some possible yet conflicting links between family history of cancer and EGFR mutation in lung cancer. As EGFR-mutated lung cancer favours female, never-smoker, adenocarcinoma and Asians, it may be argued that there may be some underlying genetic modifiers responsible for the pathogenesis of EGFR mutation.

METHODS

We searched four databases for all original articles on family history of malignancy and EGFR mutation status in lung cancer published up to July 2018. We performed a meta-analysis by using a random-effects model and odds ratio estimates. Heterogeneity and sensitivity were also investigated. Then we conducted a second literature research to curate case reports of familial lung cancers who studied both germline cancer predisposing genes and their somatic EGFR mutation status; and explored the possible links between cancer predisposing genes and EGFR mutation.

RESULTS

Eleven studies have been included in the meta-analysis. There is a significantly higher likelihood of EGFR mutation in lung cancer patients with family history of cancer than their counterparts without family history, preferentially in Asians (OR = 1.35[1.06-1.71], P = 0.01), those diagnosed with adenocarcinomas ((OR = 1.47[1.14-1.89], P = 0.003) and those with lung cancer-affected relatives (first and second-degree: OR = 1.53[1.18-1.99], P = 0.001; first-degree: OR = 1.76[1.36-2.28, P < 0.0001]). Familial lung cancers more likely have concurrent EGFR mutations along with mutations in their germline cancer predisposition genes including EGFR T790 M, BRCA2 and TP53. Certain mechanisms may contribute to the combination preferences between inherited mutations and somatic ones.

CONCLUSIONS

Potential genetic modifiers may contribute to somatic EGFR mutation in lung cancer, although current data is limited. Further studies on this topic are needed, which may help to unveil lung carcinogenesis pathways. However, caution is warranted in data interpretation due to limited cases available for the current study.

Risk factors predisposing to cardia gastric adenocarcinoma: Insights and new perspectives

Recent decades have seen an alarming increase in the incidence of cardia gastric adenocarcinoma (CGA) while noncardia gastric adenocarcinoma (NCGA) has decreased. In 2012, 260 000 CGA cases (age-standardised rate (ASR); 3.3/100 000) and 691 000 NCGA cases (ASR; 8.8/100 000) were reported worldwide. Compared with women, men had greater rates for both the subsites, especially for CGA. Recently, four molecular subtypes of GC have been proposed by the Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG); however, these classifications do not take into account predisposing germline variants and their possible interaction with somatic alterations in carcinogenesis. The etiology of adenocarcinoma of the cardia and the gastroesophageal junction (GEJ) is not known. It is thought that CGA is distinct from adenocarcinomas located in the esophagus or distal stomach, both epidemiologically and biologically. Moreover, CGA is often identified in the advanced stage having a poor prognosis. Therefore, understanding the risk and the role of predisposing factors in etiology of CGA can inform clinical practice and counseling for risk reduction. In this paper, we showed that GC family history, lifestyle, demographics, gastroesophageal reflux disease, Helicobacter pylori infection, and multiple genetic and epigenetic risk factors as well as several predisposing conditions may underlie susceptibility to CGA. However, several genome-wide association studies (GWASs) should be conducted to identify novel high-penetrance genes and pathways as well as causal germline variants predisposing to CGA. They must include different ethnic groups, especially from high-incidence countries for CGA, because some risk loci are ancestry-specific. In parallel, statistical methods can be developed to identify cancer predisposition genes (CPGs) from tumor sequencing data. It is also necessary to find novel long noncoding RNAs related to the risk of CGA. Taken altogether, new cancer risk prediction models, including all genetic and nongenetic factors influencing risk, should be developed to facilitate risk assessment, disease prevention, and early diagnosis and intervention of CGA in the future.

Substantial batch effects in TCGA exome sequences undermine pan-cancer analysis of germline variants

BACKGROUND

In recent years, research on cancer predisposition germline variants has emerged as a prominent field. The identity of somatic mutations is based on a reliable mapping of the patient germline variants. In addition, the statistics of germline variants frequencies in healthy individuals and cancer patients is the basis for seeking candidates for cancer predisposition genes. The Cancer Genome Atlas (TCGA) is one of the main sources of such data, providing a diverse collection of molecular data including deep sequencing for more than 30 types of cancer from > 10,000 patients.

METHODS

Our hypothesis in this study is that whole exome sequences from blood samples of cancer patients are not expected to show systematic differences among cancer types. To test this hypothesis, we analyzed common and rare germline variants across six cancer types, covering 2241 samples from TCGA. In our analysis we accounted for inherent variables in the data including the different variant calling protocols, sequencing platforms, and ethnicity.

RESULTS

We report on substantial batch effects in germline variants associated with cancer types. We attribute the effect to the specific sequencing centers that produced the data. Specifically, we measured 30% variability in the number of reported germline variants per sample across sequencing centers. The batch effect is further expressed in nucleotide composition and variant frequencies. Importantly, the batch effect causes substantial differences in germline variant distribution patterns across numerous genes, including prominent cancer predisposition genes such as BRCA1, RET, MAX, and KRAS. For most of known cancer predisposition genes, we found a distinct batch-dependent difference in germline variants.

CONCLUSION

TCGA germline data is exposed to strong batch effects with substantial variabilities among TCGA sequencing centers. We claim that those batch effects are consequential for numerous TCGA pan-cancer studies. In particular, these effects may compromise the reliability and the potency to detect new cancer predisposition genes. Furthermore, interpretation of pan-cancer analyses should be revisited in view of the source of the genomic data after accounting for the reported batch effects.

Systematic characterization of germline variants from the DiscovEHR study endometrial carcinoma population

Background

Endometrial cancer (EMCA) is the fifth most common cancer among women in the world. Identification of potentially pathogenic germline variants from individuals with EMCA will help characterize genetic features that underlie the disease and potentially predispose individuals to its pathogenesis.

Methods

The Geisinger Health System’s (GHS) DiscovEHR cohort includes exome sequencing on over 50,000 consenting patients, 297 of whom have evidence of an EMCA diagnosis in their electronic health record. Here, rare variants were annotated as potentially pathogenic.

Results

Eight genes were identified as having increased burden in the EMCA cohort relative to the non-cancer control cohort. None of the eight genes had an increased burden in the other hormone related cancer cohort from GHS, suggesting they can help characterize the underlying genetic variation that gives rise to EMCA. Comparing GHS to the cancer genome atlas (TCGA) EMCA germline data illustrated 34 genes with potentially pathogenic variation and eight unique potentially pathogenic variants that were present in both studies. Thus, similar germline variation among genes can be observed in unique EMCA cohorts and could help prioritize genes to investigate for future work.

Conclusion

In summary, this systematic characterization of potentially pathogenic germline variants describes the genetic underpinnings of EMCA through the use of data from a single hospital system.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0504-9) contains supplementary material, which is available to authorized users.

Germline Genetic Testing: What the Breast Surgeon Needs to Know

PURPOSE

The American Society of Breast Surgeons (ASBrS) sought to provide educational guidelines for breast surgeons on how to incorporate genetic information and genomics into their practice.

METHODS

A comprehensive nonsystematic review was performed of selected peer-reviewed literature. The Genetics Working Group of the ASBrS convened to develop guideline recommendations.

RESULTS

Clinical and educational guidelines were prepared to outline the essential knowledge for breast surgeons to perform germline genetic testing and to incorporate the findings into their practice, which have been approved by the ASBrS Board of Directors.

RECOMMENDATIONS

Thousands of women in the USA would potentially benefit from genetic testing for BRCA1, BRCA2, and other breast cancer genes that markedly increase their risk of developing breast cancer. As genetic testing is now becoming more widely available, women should be made aware of these tests and consider testing. Breast surgeons are well positioned to help facilitate this process. The areas where surgeons need to be knowledgeable include: (1) identification of patients for initial breast cancer-related genetic testing, (2) identification of patients who tested negative in the past but now need updated testing, (3) initial cancer genetic testing, (4) retesting of patients who need their genetic testing updated, (5) cancer genetic test interpretation, posttest counseling and management, (6) management of variants of uncertain significance, (7) cascade genetic testing, (8) interpretation of genetic tests other than clinical cancer panels and the counseling and management required, and (9) interpretation of somatic genetic tests and the counseling and management required.

Integrated Analysis of Germline and Tumor DNA Identifies New Candidate Genes Involved in Familial Colorectal Cancer

Colorectal cancer (CRC) shows aggregation in some families but no alterations in the known hereditary CRC genes. We aimed to identify new candidate genes which are potentially involved in germline predisposition to familial CRC. An integrated analysis of germline and tumor whole-exome sequencing data was performed in 18 unrelated CRC families. Deleterious single nucleotide variants (SNV), short insertions and deletions (indels), copy number variants (CNVs) and loss of heterozygosity (LOH) were assessed as candidates for first germline or second somatic hits. Candidate tumor suppressor genes were selected when alterations were detected in both germline and somatic DNA, fulfilling Knudson's two-hit hypothesis. Somatic mutational profiling and signature analysis were also performed. A series of germline-somatic variant pairs were detected. In all cases, the first hit was presented as a rare SNV/indel, whereas the second hit was either a different SNV (3 genes) or LOH affecting the same gene (141 genes). BRCA2, BLM, ERCC2, RECQL, REV3L and RIF1 were among the most promising candidate genes for germline CRC predisposition. The identification of new candidate genes involved in familial CRC could be achieved by our integrated analysis. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.

Global gene expression of histologically normal primary skin cells from BCNS subjects reveals "single-hit" effects that are influenced by rapamycin

Studies of dominantly heritable cancers enabled insights about tumor progression. BCNS is a dominantly inherited disorder that is characterized by developmental abnormalities and postnatal neoplasms, principally BCCs. We performed an exploratory gene expression profiling of primary cell cultures derived from clinically unaffected skin biopsies of BCNS gene-carriers (PTCH1^+/-) and normal individuals. PCA and HC of untreated keratinocytes or fibroblasts failed to clearly distinguish BCNS samples from controls. These results are presumably due to the common suppression of canonical HH signaling in vitro. We then used a relaxed threshold (p-value <0.05, no FDR cut-off; FC 1.3) that identified a total of 585 and 857 genes differentially expressed in BCNS keratinocytes and fibroblasts samples, respectively. A GSEA identified pancreatic β cell hallmark and mTOR signaling genes in BCNS keratinocytes, whereas analyses of BCNS fibroblasts identified gene signatures regulating pluripotency of stem cells, including WNT pathway. Significantly, rapamycin treatment (FDR<0.05), affected a total of 1411 and 4959 genes in BCNS keratinocytes and BCNS fibroblasts, respectively. In contrast, rapamycin treatment affected a total of 3214 and 4797 genes in normal keratinocytes and normal fibroblasts, respectively. The differential response of BCNS cells to rapamycin involved 599 and 1463 unique probe sets in keratinocytes and fibroblasts, respectively. An IPA of these genes in the presence of rapamycin pointed to hepatic fibrosis/stellate cell activation, and HIPPO signaling in BCNS keratinocytes, whereas mitochondrial dysfunction and AGRN expression were uniquely enriched in BCNS fibroblasts. The gene expression changes seen here are likely involved in the etiology of BCCs and they may represent biomarkers/targets for early intervention.

Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes

In its landmark paper about Standards and Guidelines for the Interpretation of Sequence Variants, the American College of Medical Genetics and Genomics (ACMG), and Association for Molecular Pathology (AMP) did not address how to use tumor data when assessing the pathogenicity of germline variants. The Clinical Genome Resource (ClinGen) established a multidisciplinary working group, the Germline/Somatic Variant Subcommittee (GSVS) with this focus. The GSVS implemented a survey to determine current practices of integrating somatic data when classifying germline variants in cancer predisposition genes. The GSVS then reviewed and analyzed available resources of relevant somatic data, and performed integrative germline variant curation exercises. The committee determined that somatic hotspots could be systematically integrated into moderate evidence of pathogenicity (PM1). Tumor RNA sequencing data showing altered splicing may be considered as strong evidence in support of germline pathogenicity (PVS1) and tumor phenotypic features such as mutational signatures be considered supporting evidence of pathogenicity (PP4). However, at present, somatic data such as focal loss of heterozygosity and mutations occurring on the alternative allele are not recommended to be systematically integrated, instead, incorporation of this type of data should take place under the advisement of multidisciplinary cancer center tumor-normal sequencing boards.