Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer

The Germline and Somatic Origins of Prostate Cancer Heterogeneity

SIGNIFICANCE

This study uncovered 223 recurrently mutated driver regions using the largest cohort of prostate tumors to date. It reveals associations between germline SNPs, somatic drivers, and tumor aggression, offering significant insights into how prostate tumor evolution is shaped by germline factors and the timing of somatic mutations.

Characterizing somatic mutations in ovarian cancer germline risk regions

Epithelial ovarian cancer (EOC) genetics research has been focused on germline or somatic mutations independently. Emerging evidence suggests that the somatic mutational landscape can be shaped by the germline genetic background. In this study, we aim to unravel the role of somatic alterations within EOC germline susceptibility regions by incorporating functional annotations. We investigate somatic events, including mutational signatures, point mutations, copy number alterations, and transcription factor binding disruptions, within 33 EOC germline susceptibility regions. Our analysis identifies significant associations between candidate germline susceptibility genes and somatic mutational signatures known to be key risk factors for EOC, such as mismatch repair deficiency, age-related mutagenesis, and homologous recombination deficiency. In addition, we find somatic point mutations and copy number alterations are significantly enriched in histotype-specific active enhancers and promoters within EOC risk loci. Furthermore, we examine the impact of germline variants and somatic mutations on transcription factor binding sites, identifying cancer developmental transcription factor motifs frequently affected by both types of mutations. Overall, our study highlights the importance of integrating germline and somatic mutations with regulatory and epigenomic data to gain insights into the genetic basis of EOC.

Integrative Computational Analysis of Common EXO5 Haplotypes: Impact on Protein Dynamics, Genome Stability, and Cancer Progression

Understanding the impact of common germline variants on protein structure, function, and disease progression is crucial in cancer research. This study presents a comprehensive analysis of the EXO5 gene, which encodes a DNA exonuclease involved in DNA repair that was previously associated with cancer susceptibility. We employed an integrated approach combining genomic and clinical data analysis, deep learning variant effect prediction, and molecular dynamics (MD) simulations to investigate the effects of common EXO5 haplotypes on protein structure, dynamics, and cancer outcomes. We characterized the haplotype structure of EXO5 across diverse human populations, identifying five common haplotypes, and studied their impact on the EXO5 protein. Extensive, all-atom MD simulations revealed significant structural and dynamic differences among the EXO5 protein variants, particularly in their catalytic region. The L151P EXO5 protein variant exhibited the most substantial conformational changes, potentially disruptive for EXO5's function and nuclear localization. Analysis of The Cancer Genome Atlas data showed that cancer patients carrying L151P EXO5 had significantly shorter progression-free survival in prostate and pancreatic cancers and exhibited increased genomic instability. This study highlights the strength of our methodology in uncovering the effects of common genetic variants on protein function and their implications for disease outcomes.

FaMMily Affairs: Dissecting inherited contributions to multiple myeloma risk

Etiological links to multiple myeloma (MM) remain poorly understood, though emerging evidence suggests a significant hereditary component. This review integrates current literature on inherited factors contributing to MM risk, synthesizing both epidemiologic and genomic data. We examine familial clustering patterns, assess genome-wide association studies (GWAS) that reveal common genetic variants linked to MM, and explore rare, high-penetrance variants in key susceptibility genes. Additionally, we advocate for routine germline screening in high-risk MM populations, particularly those with a strong family history of cancer, a personal history of cancer, or early-onset disease. By elucidating the inherited influences on MM predisposition, this review seeks to inform future research and refine risk assessment strategies in this population.

Identifying somatic fingerprints of cancers defined by germline and environmental risk factors

Numerous studies over the past generation have identified germline variants that increase specific cancer risks. Simultaneously, a revolution in sequencing technology has permitted high-throughput annotations of somatic genomes characterizing individual tumors. However, examining the relationship between germline variants and somatic alteration patterns is hugely challenged by the large numbers of variants in a typical tumor, the rarity of most individual variants, and the heterogeneity of tumor somatic fingerprints. In this article, we propose statistical methodology that frames the investigation of germline-somatic relationships in an interpretable manner. The method uses meta-features embodying biological contexts of individual somatic alterations to implicitly group rare mutations. Our team has used this technique previously through a multilevel regression model to diagnose with high accuracy tumor site of origin. Herein, we further leverage topic models from computational linguistics to achieve interpretable lower-dimensional embeddings of the meta-features. We demonstrate how the method can identify distinctive somatic profiles linked to specific germline variants or environmental risk factors. We illustrate the method using The Cancer Genome Atlas whole-exome sequencing data to characterize somatic tumor fingerprints in breast cancer patients with germline BRCA1/2 mutations and in head and neck cancer patients exposed to human papillomavirus.

Genetic and clinical characteristics of genetic tumor syndromes in the central nervous system cancers: Implications for clinical practice

Recognizing individuals with Genetic tumor syndromes (GTS) in the primary central nervous system (CNS) tumors is crucial for optimizing proper genetic counseling and improving therapeutics and clinical care. We retrospectively analyzed the GTS in a Chinese CNS tumor cohort and examined the molecular characteristics and their clinical significance for diagnostic and therapeutic purposes. Our study identified 34 categories of GTS in 258 patients with CNS tumors. The gene with the highest germline pathogenic or likely pathogenic mutation frequency was TP53, followed by MSH2, NF1, and BRCA2. The top five GTS in CNS tumors showed high genetic heterogeneity GTS analysis reclassifies CNS tumors as "NEC." 53.88% of patients diagnosed with GTS harbor potential precision oncology therapy target mutations. The results of our study deepen our understanding of CNS tumors, provide a reference direction for the future design of clinical trials, and further expect to improve disease entire process management in CNS tumors.

Clinical and Functional Analyses of an African-ancestry Gain-of-function HOXB13 Variant Implicated in Aggressive Prostate Cancer

BACKGROUND

Recent reports have uncovered a HOXB13 variant (X285K) predisposing to prostate cancer in men of West African ancestry. The clinical relevance and protein function associated with this inherited variant are unknown.

OBJECTIVE

To determine the clinical relevance of HOXB13 (X285K) in comparison with HOXB13 (G84E) and BRCA2 pathogenic/likely pathogenic (P/LP) variants, and to elucidate the oncogenic mechanisms of the X285K protein.

DESIGN, SETTING, AND PARTICIPANTS

Real-world data were collected from 21,393 men with prostate cancer undergoing genetic testing from 2019 to 2022, and in vitro cell-line models were established for the evaluation of oncogenic functions associated with the X285K protein.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Genetic testing results were compared among patient groups according to self-reported race/ethnicity, Gleason scores, and American Joint Committee on Cancer stages using the exact test. Oncogenic functions of X285K were evaluated by RNA sequencing, chromatin immunoprecipitation sequencing, and Western blot analyses.

RESULTS AND LIMITATIONS

HOXB13 (X285K) was significantly enriched in self-reported Black (1.01%) versus White (0.01%) patients. We observed a trend of more aggressive disease in the HOXB13 (X285K) and BRCA2 P/LP carriers than in the HOXB13 (G84E) carriers. Replacement of the wild-type HOXB13 protein with the X285K protein resulted in a gain of an E2F/MYC signature, validated by the elevated expression of cyclin B1 and c-Myc, without affecting the androgen response signature. Elevated expression of cyclin B1 and c-Myc was explained by enhanced binding of the X285K protein to the promoters and enhancers of these genes. The limitations of the study are the lack of complete clinical outcome data for all patients studied and the use of a single cell line in the functional analysis.

CONCLUSIONS

HOXB13 (X285K) is significantly enriched in self-reported Black patients, and X285K carriers detected in the real-world clinical setting have aggressive prostate cancer features similar to the BRCA2 carriers. Functional studies revealed a unique gain-of-function oncogenic mechanism of X285K protein in regulating E2F/MYC signatures.

PATIENT SUMMARY

The HOXB13 (X285K) variant is clinically and functionally linked to aggressive prostate cancer, supporting genetic testing for X285K in Black men and early disease screening of carriers of this variant.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

BACKGROUND

The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.

RESULTS

We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.

CONCLUSION

We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

Inflammatory memory in psoriasis: From remission to recurrence

The routine use of targeted systemic immunomodulatory therapies has transformed outcomes for people with severe psoriasis, with skin clearance (clinical remission) rates up to 60% at 1 year of biologic treatment. However, psoriasis may recur following drug withdrawal, and as a result, patients tend to continue receiving costly treatment indefinitely. Here, we review research into the "inflammatory memory" in resolved psoriasis skin and the potential mechanisms leading to psoriasis recurrence following drug withdrawal. Research has implicated immune cells such as tissue resident memory T cells, Langerhans cells, and dermal dendritic cells, and there is growing interest in keratinocytes and fibroblasts. A better understanding of the interactions between these cell populations, enabled by single cell technologies, will help to elucidate the events underpinning the shift from remission to recurrence. This may inform the development of personalized strategies for sustaining remission while reducing long-term drug burden.

James German and the Quest to Understand Human RECQ Helicase Deficiencies

James German's work to establish the natural history and cancer risk associated with Bloom syndrome (BS) has had a strong influence on the generation of scientists and clinicians working to understand other RECQ deficiencies and heritable cancer predisposition syndromes. I summarize work by us and others below, inspired by James German's precedents with BS, to understand and compare BS with the other heritable RECQ deficiency syndromes with a focus on Werner syndrome (WS). What we know, unanswered questions and new opportunities are discussed, as are potential ways to treat or modify WS-associated disease mechanisms and pathways.

Germline variants alter immune surveillance

Germline-derived epitopes shape tumor development through immunoediting.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Tumors with the same diagnosis can have different molecular profiles and response to treatment. It remains unclear when and why these differences arise. Somatic genomic aberrations occur within the context of a highly variable germline genome. Interrogating 5870 breast cancer lesions, we demonstrated that germline-derived epitopes in recurrently amplified genes influence somatic evolution by mediating immunoediting. Individuals with a high germline-epitope burden in human epidermal growth factor receptor 2 (HER2/ERBB2) are less likely to develop HER2-positive breast cancer compared with other subtypes. The same holds true for recurrent amplicons defining three aggressive estrogen receptor (ER)-positive subgroups. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show that the germline genome plays a role in dictating somatic evolution.

Germline determinants of aberrant signaling pathways in cancer

Cancer is a complex disease influenced by a heterogeneous landscape of both germline genetic variants and somatic aberrations. While there is growing evidence suggesting an interplay between germline and somatic variants, and a substantial number of somatic aberrations in specific pathways are now recognized as hallmarks in many well-known forms of cancer, the interaction landscape between germline variants and the aberration of those pathways in cancer remains largely unexplored. Utilizing over 8500 human samples across 33 cancer types characterized by TCGA and considering binary traits defined using a large collection of somatic aberration profiles across ten well-known oncogenic signaling pathways, we conducted a series of GWAS and identified genome-wide and suggestive associations involving 276 SNPs. Among these, 94 SNPs revealed cis-eQTL links with cancer-related genes or with genes functionally correlated with the corresponding traits' oncogenic pathways. GWAS summary statistics for all tested traits were then used to construct a set of polygenic scores employing a customized computational strategy. Polygenic scores for 24 traits demonstrated significant performance and were validated using data from PCAWG and CCLE datasets. These scores showed prognostic value for clinical variables and exhibited significant effectiveness in classifying patients into specific cancer subtypes or stratifying patients with cancer-specific aggressive phenotypes. Overall, we demonstrate that germline genetics can describe patients' genetic liability to develop specific cancer molecular and clinical profiles.

A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

A Multiethnic Germline-Somatic Association Database Deciphers Multilayered and Interconnected Genetic Mutations in Cancer

Inherited germline and acquired somatic alterations can both promote human tumor development. Elucidating the cooperation between somatic and germline genetic alterations that drive tumorigenesis could help inform precision cancer prevention and treatment strategies. Here, leveraging genomic genotyping and sequencing data from 9,029 patients with cancer with European, East Asian, and African ancestry, we performed a pan-cancer analysis to evaluate the associations between germline SNPs and somatic alterations, including single-nucleotide variant and small insertion/deletion mutations, copy-number variation, tumor mutational burden, and mutational signatures. Genome-wide significant germline-somatic pairs were abundant, and most of the associations were observed in one cancer type and one ancestry group. A user-friendly interactive Multiethnic Germline-Somatic Association (MGSA) database (http://wanglab-hkust.cn:3838/MGSA/) was developed, which can be used to query, browse, and download the results of the association analyses. Moreover, the MGSA database offers additional survival analysis and functional annotation. Together, this work provides a resource for uncovering the clinical and biological roles of associations between germline variants and somatic alterations in human cancer.

SIGNIFICANCE

Comprehensive analysis of connections between germline variants and somatic events in cancer offers a resource for investigating the functional significance of genetic mutations and exploring genetic factors contributing to racial disparities.

Investigation of pathogenic germline variants in gastric cancer and development of "GasCanBase" database

BACKGROUND

Gastric cancer, which is also known as stomach cancer, can be influenced by both germline and somatic mutations. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) in germline have long been reported to play a pivotal role in cancer progression.

AIM

The aim of this study is to examine the nsSNP in GC-associated genes. The study also aims to develop a database with extensive information regarding the nsSNPs in the GC-associated genes and their impacts.

METHODS AND RESULTS

A total of 34,588 nsSNPs from 1,493,460 SNPs of the 40 genes were extracted from the available SNP database. Drug binding and energy minimization were examined by molecular docking and YASARA. To validate the existence of the germline CDH1 gene mutation (rs34466743) in the isolated blood DNA of gastric cancer (GC) patients, polymerase chain reaction (PCR) and DNA sequencing were performed. According to the results of the gene network analysis, 17 genes may interact with other types of cancer. A total of 11,363 nsSNPs were detected within the 40 GC genes. Among these, 474 nsSNPs were predicted to be damaging and 40 to be the most damaging. The SNPs in domain regions were thought to be strong candidates that alter protein functions. Our findings proposed that most of the selected nsSNPs were within the domains or motif regions. Free Energy Deviation calculation of protein structure pointed toward noteworthy changes in the structure of each protein that can demolish its natural function. Subsequently, drug binding confirmed the structural variation and the ineffectiveness of the drug against the mutant model in individuals with these germline variants. Furthermore, in vitro analysis of the rs34466743 germline variant from the CDH1 gene confirmed the strength and robustness of the pipeline that could expand the somatic alteration for causing cancer. In addition, a comprehensive gastric cancer polymorphism database named "GasCanBase" was developed to make data available to researchers.

CONCLUSION

The findings of this study and the "GasCanBase" database may greatly contribute to our understanding of molecular epidemiology and the development of precise therapeutics for gastric cancer. GasCanBase is available at: https://www.gascanbase.com/.

Data-adaptive and pathway-based tests for association studies between somatic mutations and germline variations in human cancers

Cancer is a disease driven by a combination of inherited genetic variants and somatic mutations. Recently available large-scale sequencing data of cancer genomes have provided an unprecedented opportunity to study the interactions between them. However, previous studies on this topic have been limited by simple, low statistical power tests such as Fisher's exact test. In this paper, we design data-adaptive and pathway-based tests based on the score statistic for association studies between somatic mutations and germline variations. Previous research has shown that two single-nucleotide polymorphism (SNP)-set-based association tests, adaptive sum of powered score (aSPU) and data-adaptive pathway-based (aSPUpath) tests, increase the power in genome-wide association studies (GWASs) with a single disease trait in a case-control study. We extend aSPU and aSPUpath to multi-traits, that is, somatic mutations of multiple genes in a cohort study, allowing extensive information aggregation at both SNP and gene levels.p $p$ -values from different parameters assuming varying genetic architecture are combined to yield data-adaptive tests for somatic mutations and germline variations. Extensive simulations show that, in comparison with some commonly used methods, our data-adaptive somatic mutations/germline variations tests can be applied to multiple germline SNPs/genes/pathways, and generally have much higher statistical powers while maintaining the appropriate type I error. The proposed tests are applied to a large-scale real-world International Cancer Genome Consortium whole genome sequencing data set of 2583 subjects, detecting more significant and biologically relevant associations compared with the other existing methods on both gene and pathway levels. Our study has systematically identified the associations between various germline variations and somatic mutations across different cancer types, which potentially provides valuable utility for cancer risk prediction, prognosis, and therapeutics.

Profiling the Somatic Mutational Landscape of Breast Tumors from Hispanic/Latina Women Reveals Conserved and Unique Characteristics

Somatic mutational profiling is increasingly being used to identify potential targets for breast cancer. However, limited tumor-sequencing data from Hispanic/Latinas (H/L) are available to guide treatment. To address this gap, we performed whole-exome sequencing (WES) and RNA sequencing on 146 tumors and WES of matched germline DNA from 140 H/L women in California. Tumor intrinsic subtype, somatic mutations, copy-number alterations, and expression profiles of the tumors were characterized and compared with data from tumors of non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Eight genes were significantly mutated in the H/L tumors including PIK3CA, TP53, GATA3, MAP3K1, CDH1, CBFB, PTEN, and RUNX1; the prevalence of mutations in these genes was similar to that observed in White women in TCGA. Four previously reported Catalogue of Somatic Mutations in Cancer (COSMIC) mutation signatures (1, 2, 3, 13) were found in the H/L dataset, along with signature 16 that has not been previously reported in other breast cancer datasets. Recurrent amplifications were observed in breast cancer drivers including MYC, FGFR1, CCND1, and ERBB2, as well as a recurrent amplification in 17q11.2 associated with high KIAA0100 gene expression that has been implicated in breast cancer aggressiveness. In conclusion, this study identified a higher prevalence of COSMIC signature 16 and a recurrent copy-number amplification affecting expression of KIAA0100 in breast tumors from H/L compared with White women. These results highlight the necessity of studying underrepresented populations.

SIGNIFICANCE

Comprehensive characterization of genomic and transcriptomic alterations in breast tumors from Hispanic/Latina patients reveals distinct genetic alterations and signatures, demonstrating the importance of inclusive studies to ensure equitable care for patients. See related commentary by Schmit et al., p. 2443.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

Mutational landscape of primary spinal cord astrocytoma

Primary spinal cord astrocytoma (SCA) is a rare disease. Knowledge about the molecular profiles of SCAs mostly comes from intracranial glioma; the pattern of genetic alterations of SCAs is not well understood. Herein, we describe genome-sequencing analyses of primary SCAs, aiming to characterize the mutational landscape of primary SCAs. We utilized whole exome sequencing (WES) to analyze somatic nucleotide variants (SNVs) and copy number variants (CNVs) among 51 primary SCAs. Driver genes were searched using four algorithms. GISTIC2 was used to detect significant CNVs. Additionally, recurrently mutated pathways were also summarized. A total of 12 driver genes were identified. Of those, H3F3A (47.1%), TP53 (29.4%), NF1 (19.6%), ATRX (17.6%), and PPM1D (17.6%) were the most frequently mutated genes. Furthermore, three novel driver genes seldom reported in glioma were identified: HNRNPC, SYNE1, and RBM10. Several germline mutations, including three variants (SLC16A8 rs2235573, LMF1 rs3751667, FAM20C rs774848096) that were associated with risk of brain glioma, were frequently observed in SCAs. Moreover, 12q14.1 (13.7%) encompassing the oncogene CDK4 was recurrently amplified and negatively affected patient prognosis. Besides frequently mutated RTK/RAS pathway and PI3K pathway, the cell cycle pathway controlling the phosphorylation of retinoblastoma protein (RB) was mutated in 39.2% of patients. Overall, a considerable degree of the somatic mutation landscape is shared between SCAs and brainstem glioma. Our work provides a key insight into the molecular profiling of primary SCAs, which might represent candidate drug targets and complement the molecular atlas of glioma. © 2023 The Pathological Society of Great Britain and Ireland.

Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations

Somatic mutations drive cancer development and are relevant to patient responses to treatment. Emerging evidence shows that variations in the somatic genome can be influenced by the germline genetic background. However, the mechanisms underlying these germline-somatic associations remain largely obscure. We hypothesized that germline variants can influence somatic mutations in a nearby cancer gene ("local impact") or a set of recurrently mutated cancer genes across the genome ("global impact") through their regulatory effect on gene expression. To test this hypothesis, tumor targeted sequencing data from 12,413 patients across 11 cancer types in the Dana-Farber Profile cohort were integrated with germline cancer gene expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression Project. Variants that upregulate ATM expression were associated with a decreased risk of somatic ATM mutations across 8 cancer types. GLI2, WRN, and CBFB eQTL were associated with global tumor mutational burden of cancer genes in ovarian cancer, glioma, and esophagogastric carcinoma, respectively. An EPHA5 eQTL was associated with mutations in cancer genes specific to colorectal cancer, and eQTL related to expression of APC, WRN, GLI1, FANCA, and TP53 were associated with mutations in genes specific to endometrial cancer. These findings provide evidence that germline-somatic associations are mediated through expression of specific cancer genes, opening new avenues for research on the underlying biological processes.

SIGNIFICANCE

Analysis of associations between the germline genetic background and somatic mutations in patients with cancer suggests that germline variants can influence local and global tumor mutations by altering expression of cancer-related genes. See related commentary by Kar, p. 1165.

A New Frontier for Cancer Genetics: Identification of Germline-Somatic Associations

Studies of the inherited or germline genome have identified rare mutations with large effects and common polymorphisms of more modest effect sizes that are associated with cancer risk. This research has substantially illuminated the etiology and development of cancer, with particular relevance to cancer prevention. In parallel, studies of the somatic or tumor genome have been instrumental in identifying the key drivers of cancer progression, significantly informing modern cancer therapy. While these studies have thus far largely been performed separately, integrative studies where the germline and somatic genomes are mapped in the same individuals have the potential to yield novel and holistic insights into cancer biology. In this issue of Cancer Research, Liu and colleagues report the results of integrative germline-somatic analyses in over 12,000 patients with cancer and 11 cancer types, identifying several associations where inherited variants that regulate the expression of a nearby gene in normal tissues are associated with tumor mutations in the same gene or with genome-wide somatic traits such as the tumor mutational burden. Although considerable follow-up work is required, the study is an important contribution to an emerging body of evidence that is demonstrating that the germline has a vital role in shaping the tumor genome. See related article by Liu et al., p. 1191.

Genetic variants of SOS2, MAP2K1 and RASGRF2 in the RAS pathway genes predict survival of HBV-related hepatocellular carcinoma patients

The RAS pathway participates in the cascade of proliferation and cell division process, and the activated RAS pathway can lead to tumorigenesis including hepatocellular carcinoma (HCC). However, few studies have explored the effects of genetic variants in the RAS pathway-related genes on the survival of patients with HBV-related HCC. In the present study, we assessed the associations between 11,658 single-nucleotide polymorphisms (SNPs) in 62 RAS pathway genes and the overall survival (OS) of 866 HBV-related HCC individuals, which were randomly split (1:1) into discovery and validation datasets. As a result, three potentially functional SNPs were identified, based on multivariable cox proportional hazards regression analyses, in SOS Ras/Rho guanine nucleotide exchange factor 2 (SOS2, rs4632055 A > G), Ras protein-specific guanine nucleotide releasing factor 2 (RASGRF2, rs26418A > G) and mitogen-activated protein kinase 1 (MAP2K1,rs57120695 C > T), which were significantly and independently associated with OS of HBV-related HCC patients [adjusted hazards ratios (HRs) of 1.42, 1.32 and 1.50, respectively; 95% confidence intervals (CI), 1.14 to 1.76, 1.15 to 1.53 and 1.15 to 1.97, respectively; P = 0.001, < 0.001 and 0.003, respectively]. Additionally, the joint effects as the unfavorable genotypes of these three SNPs showed a significant association with the poor survival of HCC (trend test P < 0.001). The expression quantitative trait loci (eQTL) analysis further revealed that the rs4632055 G allele and the rs26418 A allele were associated with lower mRNA expression levels of SOS2 and RASGRF2, respectively. Collectively, these potentially functional SNPs of RASGRF2, SOS2 and M2PAK1 may become potential prognostic biomarkers for HBV-related HCC after hepatectomy.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual's germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

Stromal Interaction Molecule 1 (STIM1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Solid Tumors

Increasing evidence has shown that stromal interaction molecule 1 (STIM1), a key subunit of store-operated Ca2+ entry (SOCE), is closely associated with tumor growth, development, and metastasis. However, there is no report of a comprehensive assessment of STIM1 in pan-cancer. This study aimed to perform a general analysis of STIM1 in human tumors, including its molecular characteristics, functional mechanisms, clinical significance, and immune infiltrates correlation based on pan-cancer data from The Cancer Genome Atlas (TCGA). Gene expression analysis was investigated using TCGA RNA-seq data, the Tumor Immune Estimation Resource (TIMER). Phosphorylation analysis was undertaken using the Clinical Proteomic Tumor Analysis Consortium (CP-TAC) and the PhosphoNET database. Genetic alterations of STIM1 were analyzed using cBioPortal. Prognostic analysis was via the R package "survival" function and the Kaplan-Meier plotter. Functional enrichment analysis was via by the R package "cluster Profiler" function. The association between STIM1 and tumor-infiltrating immune cells and immune markers was by the R package "GSVA" function and TIMER. STIM1 was differentially expressed and associated with distinct clinical stages in multiple tumors. The phosphorylation of STIM1 at S673 is highly expressed in clear cell renal carcinoma and lung adenocarcinoma tumors compared to normal tissues. STIM1 genetic alterations correlate with poor prognosis in several tumors, including ovarian cancer and lung squamous cell carcinomas. High STIM1 expression is associated with good or poor prognosis across diverse tumors. Overall survival (OS) analysis indicated that STIM1 is a favorable prognostic factor for patients with BRCA, KIRC, LIHC, LUAD, OV, SARC, and UCEC, and is a risk prognostic factor for BLCA, KIRP, STAD, and UVM. There is a close correlation between STIM1 expression and immune cell infiltration, immune-regulated genes, chemokines, and immune checkpoints in a variety of tumors. STIM1 functions differently in diverse tumors, playing an oncogenic or antitumor role. Moreover, It may serve as a prognostic biomarker and an immunotherapy target across multiple tumors.

Common Germline Risk Variants Impact Somatic Alterations and Clinical Features across Cancers

Aggregation of genome-wide common risk variants, such as polygenic risk score (PRS), can measure genetic susceptibility to cancer. A better understanding of how common germline variants associate with somatic alterations and clinical features could facilitate personalized cancer prevention and early detection. We constructed PRSs from 14 genome-wide association studies (median n = 64,905) for 12 cancer types by multiple methods and calibrated them using the UK Biobank resources (n = 335,048). Meta-analyses across cancer types in The Cancer Genome Atlas (n = 7,965) revealed that higher PRS values were associated with earlier cancer onset and lower burden of somatic alterations, including total mutations, chromosome/arm somatic copy-number alterations (SCNA), and focal SCNAs. This contrasts with rare germline pathogenic variants (e.g., BRCA1/2 variants), showing heterogeneous associations with somatic alterations. Our results suggest that common germline cancer risk variants allow early tumor development before the accumulation of many somatic alterations characteristic of later stages of carcinogenesis.

SIGNIFICANCE

Meta-analyses across cancers show that common germline risk variants affect not only cancer predisposition but the age of cancer onset and burden of somatic alterations, including total mutations and copy-number alterations.

Comparative Genomics Provides Etiologic and Biological Insight into Melanoma Subtypes

Melanoma is a cancer of melanocytes, with multiple subtypes based on body site location. Cutaneous melanoma is associated with skin exposed to ultraviolet radiation; uveal melanoma occurs in the eyes; mucosal melanoma occurs in internal mucous membranes; and acral melanoma occurs on the palms, soles, and nail beds. Here, we present the largest whole-genome sequencing study of melanoma to date, with 570 tumors profiled, as well as methylation and RNA sequencing for subsets of tumors. Uveal melanoma is genomically distinct from other melanoma subtypes, harboring the lowest tumor mutation burden and with significantly mutated genes in the G-protein signaling pathway. Most cutaneous, acral, and mucosal melanomas share alterations in components of the MAPK, PI3K, p53, p16, and telomere pathways. However, the mechanism by which these pathways are activated or inactivated varies between melanoma subtypes. Additionally, we identify potential novel germline predisposition genes for some of the less common melanoma subtypes.

SIGNIFICANCE

This is the largest whole-genome analysis of melanoma to date, comprehensively comparing the genomics of the four major melanoma subtypes. This study highlights both similarities and differences between the subtypes, providing insights into the etiology and biology of melanoma. This article is highlighted in the In This Issue feature, p. 2711.

Epidemiological characteristics and genetic alterations in adult diffuse glioma in East Asian populations

Understanding the racial specificities of diseases-such as adult diffuse glioma, the most common primary malignant tumor of the central nervous system-is a critical step toward precision medicine. Here, we comprehensively review studies of gliomas in East Asian populations and other ancestry groups to clarify the racial differences in terms of epidemiology and genomic characteristics. Overall, we observed a lower glioma incidence in East Asians than in Whites; notably, patients with glioblastoma had significantly younger ages of onset and longer overall survival than the Whites. Multiple genome-wide association studies of various cohorts have revealed single nucleotide polymorphisms associated with overall and subtype-specific glioma susceptibility. Notably, only 3 risk loci-5p15.33, 11q23.3, and 20q13.33-were shared between patients with East Asian and White ancestry, whereas other loci predominated only in particular populations. For instance, risk loci 12p11.23, 15q15-21.1, and 19p13.12 were reported in East Asians, whereas risk loci 8q24.21, 1p31.3, and 1q32.1 were reported in studies in White patients. Although the somatic mutational profiles of gliomas between East Asians and non-East Asians were broadly consistent, a lower incidence of EGFR amplification in glioblastoma and a higher incidence of 1p19q-IDH-TERT triple-negative low-grade glioma were observed in East Asian cohorts. By summarizing large-scale disease surveillance, germline, and somatic genomic studies, this review reveals the unique characteristics of adult diffuse glioma among East Asians, to guide clinical management and policy design focused on patients with East Asian ancestry.

Predicting cancer evolution for patient benefit: Renal cell carcinoma paradigm

Evolutionary features of cancer have important clinical implications, but their evaluation in the clinic is currently limited. Here, we review current approaches to reconstruct tumour subclonal structure and discuss tumour sampling method and experimental design influence. We describe clear-cell renal cell carcinoma (ccRCC) as an exemplar for understanding and predicting cancer evolutionary dynamics. Finally, we discuss how understanding cancer evolution can benefit patients.

Genomic crossroads between non-Hodgkin's lymphoma and common variable immunodeficiency

Common variable immunodeficiency (CVID) represents the largest group of primary immunodeficiencies that may manifest with infections, inflammation, autoimmunity, and cancer, mainly B-cell non-Hodgkin's lymphoma (NHL). Indeed, NHL may result from chronic or recurrent infections and has, therefore, been recognized as a clinical phenotype of CVID, although rare. The more one delves into the mechanisms involved in CVID and cancer, the stronger the idea that both pathologies can be a reflection of the same primer events observed from different angles. The potential effects of germline variants on specific somatic modifications in malignancies suggest that it might be possible to anticipate critical events during tumor development. In the same way, a somatic alteration in NHL could be conditioning a similar response at the transcriptional level in the shared signaling pathways with genetic germline alterations in CVID. We aimed to explore the genomic substrate shared between these entities to better characterize the CVID phenotype immunodeficiency in NHL. By means of an in-silico approach, we interrogated the large, publicly available datasets contained in cBioPortal for the presence of genes associated with genetic pathogenic variants in a panel of 50 genes recurrently altered in CVID and previously described as causative or disease-modifying. We found that 323 (25%) of the 1,309 NHL samples available for analysis harbored variants of the CVID spectrum, with the most recurrent alteration presented in NHL occurring in PIK3CD (6%) and STAT3 (4%). Pathway analysis of common gene alterations showed enrichment in inflammatory, immune surveillance, and defective DNA repair mechanisms similar to those affected in CVID, with PIK3R1 appearing as a central node in the protein interaction network. The co-occurrence of gene alterations was a frequent phenomenon. This study represents an attempt to identify common genomic grounds between CVID and NHL. Further prospective studies are required to better know the role of genetic variants associated with CVID and their reflection on the somatic pathogenic variants responsible for cancer, as well as to characterize the CVID-like phenotype in NHL, with the potential to influence early CVID detection and therapeutic management.

Role of germline variants in the metastasis of breast carcinomas

Most cancer-related deaths in breast cancer patients are associated with metastasis, a multistep, intricate process that requires the cooperation of tumour cells, tumour microenvironment and metastasis target tissues. It is accepted that metastasis does not depend on the tumour characteristics but the host’s genetic makeup. However, there has been limited success in determining the germline genetic variants that influence metastasis development, mainly because of the limitations of traditional genome-wide association studies to detect the relevant genetic polymorphisms underlying complex phenotypes. In this work, we leveraged the extreme discordant phenotypes approach and the epistasis networks to analyse the genotypes of 97 breast cancer patients. We found that the host’s genetic makeup facilitates metastases by the dysregulation of gene expression that can promote the dispersion of metastatic seeds and help establish the metastatic niche—providing a congenial soil for the metastatic seeds.

Association between germline variants and somatic mutations in colorectal cancer

Colorectal cancer (CRC) is a heterogeneous disease with evidence of distinct tumor types that develop through different somatically altered pathways. To better understand the impact of the host genome on somatically mutated genes and pathways, we assessed associations of germline variations with somatic events via two complementary approaches. We first analyzed the association between individual germline genetic variants and the presence of non-silent somatic mutations in genes in 1375 CRC cases with genome-wide SNPs data and a tumor sequencing panel targeting 205 genes. In the second analysis, we tested if germline variants located within previously identified regions of somatic allelic imbalance were associated with overall CRC risk using summary statistics from a recent large scale GWAS (n≃125 k CRC cases and controls). The first analysis revealed that a variant (rs78963230) located within a CNA region associated with TLR3 was also associated with a non-silent mutation within gene FBXW7. In the secondary analysis, the variant rs2302274 located in CDX1/PDGFRB frequently gained/lost in colorectal tumors was associated with overall CRC risk (OR = 0.96, p = 7.50e-7). In summary, we demonstrate that an integrative analysis of somatic and germline variation can lead to new insights about CRC.

Coming of Age: Human Genomics and the Cancer-Immune Set Point

Cancer is largely a disease of the tumor cell genome. As a result, the majority of genetics research in oncology has concentrated on the role of tumor somatic mutations, as well as inherited risk variants, in disease susceptibility and response to targeted treatments. The advent and success of cancer immunotherapies, however, have opened new perspectives for the investigation of the role of inherited genetic variation in codetermining outcome and safety. It is increasingly likely that the entirety of germline genetic variation involved in regulating immune responses accounts for a significant fraction of the observed variability in responses to cancer immunotherapies. Although germline genetic data from patients treated with cancer immunotherapies are still scarce, this line of research benefits from a vast body of knowledge derived from studies into autoimmune and infectious disease phenotypes, thus not requiring a start from a blank slate. Here, we discuss how a thorough investigation of genomic variation relevant for individuals' variability in (auto)immune responses can contribute to the discovery of novel treatment approaches and drug targets, and yield predictive biomarkers to stratify cancer patient populations in precision and personalized medicine settings.

Enhancer RNA Transcription Is Essential for a Novel CSF1 Enhancer in Triple-Negative Breast Cancer

Enhancers are critical regulatory elements in the genome that help orchestrate spatiotemporal patterns of gene expression during development and normal physiology. In cancer, enhancers are often rewired by various genetic and epigenetic mechanisms for the activation of oncogenes that lead to initiation and progression. A key feature of active enhancers is the production of non-coding RNA molecules called enhancer RNAs, whose functions remain unknown but can be used to specify active enhancers de novo. Using a combination of eRNA transcription and chromatin modifications, we have identified a novel enhancer located 30 kb upstream of Colony Stimulating Factor 1 (CSF1). Notably, CSF1 is implicated in the progression of breast cancer, is overexpressed in triple-negative breast cancer (TNBC) cell lines, and its enhancer is primarily active in TNBC patient tumors. Genomic deletion of the enhancer (via CRISPR/Cas9) enabled us to validate this regulatory element as a bona fide enhancer of CSF1 and subsequent cell-based assays revealed profound effects on cancer cell proliferation, colony formation, and migration. Epigenetic silencing of the enhancer via CRISPR-interference assays (dCas9-KRAB) coupled to RNA-sequencing, enabled unbiased identification of additional target genes, such as RSAD2, that are predictive of clinical outcome. Additionally, we repurposed the RNA-guided RNA-targeting CRISPR-Cas13 machinery to specifically degrade the eRNAs transcripts produced at this enhancer to determine the consequences on CSF1 mRNA expression, suggesting a post-transcriptional role for these non-coding transcripts. Finally, we test our eRNA-dependent model of CSF1 enhancer function and demonstrate that our results are extensible to other forms of cancer. Collectively, this work describes a novel enhancer that is active in the TNBC subtype, which is associated with cellular growth, and requires eRNA transcripts for proper enhancer function. These results demonstrate the significant impact of enhancers in cancer biology and highlight their potential as tractable targets for therapeutic intervention.

Somatic mutational profiles and germline polygenic risk scores in human cancer

BACKGROUND

The mutational profile of cancer reflects the activity of the mutagenic processes which have been operative throughout the lineage of the cancer cell. These processes leave characteristic profiles of somatic mutations called mutational signatures. Mutational signatures, including single-base substitution (SBS) signatures, may reflect the effects of exogenous or endogenous exposures.

METHODS

We used polygenic risk scores (PRS) to summarize common germline variation associated with cancer risk and other cancer-related traits and examined the association between somatic mutational profiles and germline PRS in 12 cancer types from The Cancer Genome Atlas. Somatic mutational profiles were constructed from whole-exome sequencing data of primary tumors. PRS were calculated for the 12 selected cancer types and 9 non-cancer traits, including cancer risk determinants, hormonal factors, and immune-mediated inflammatory diseases, using germline genetic data and published summary statistics from genome-wide association studies.

RESULTS

We found 17 statistically significant associations between somatic mutational profiles and germline PRS after Bonferroni correction (p < 3.15 × 10^-5), including positive associations between germline inflammatory bowel disease PRS and number of somatic mutations attributed to signature SBS1 in prostate cancer and APOBEC-related signatures in breast cancer. Positive associations were also found between age at menarche PRS and mutation counts of SBS1 in overall and estrogen receptor-positive breast cancer. Consistent with prior studies that found an inverse association between the pubertal development PRS and risk of prostate cancer, likely reflecting hormone-related mechanisms, we found an inverse association between age at menarche PRS and mutation counts of SBS1 in prostate cancer. Inverse associations were also found between several cancer PRS and tumor mutation counts.

CONCLUSIONS

Our analysis suggests that there are robust associations between tumor somatic mutational profiles and germline PRS. These may reflect the mechanisms through hormone regulation and immune responses that contribute to cancer etiology and drive cancer progression.

Overview of Research on Germline Genetic Variation in Immune Genes and Cancer Outcomes

Since the late 19th century, the immune system has been known to play a role in cancer risk, initiation, and progression. Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for autoimmune and inflammatory diseases, yet the connection between human genetic variation and immune-mediated response to cancer treatments remains less well-explored. Understanding inherited genetic variation, with respect to germline genetic polymorphisms that affect immune system pathways, could lead to greater insights about how these processes may best be harnessed to successfully treat cancer. Our goal in this manuscript was to understand progress and challenges in assessing the role of inherited genetic variation in response to cancer treatments. Overall, the 39 studies reviewed here suggest that germline genetic variation in immune system related genes may potentially affect responses to cancer treatments. Although further research is needed, considering information on germline immune genetic variation may help, in some cases, to optimize cancer treatment.

OUP accepted manuscript

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.

MicroRNAs in Genetic Etiology of Human Diseases

Since their first discovery more than 20 years ago, miRNAs have been subject to deliberate research and analysis for revealing their physiological or pathological involvement. Regulatory roles of miRNAs in signal transduction, gene expression, and cellular processes in development, differentiation, proliferation, apoptosis, and homeostasis also imply their critical role in disease pathogenesis. Their roles in cancer, neurodegenerative diseases, and other systemic diseases have been studied broadly. In these regulatory pathways, their mutations and target sequence variations play critical roles to determine their functional repertoire. In this chapter, we summarize studies that investigated the role of mutations, polymorphisms, and other variations of miRNAs in respect to pathological processes.

Constructing germline research cohorts from the discarded reads of clinical tumor sequences

Background

Hundreds of thousands of cancer patients have had targeted (panel) tumor sequencing to identify clinically meaningful mutations. In addition to improving patient outcomes, this activity has led to significant discoveries in basic and translational domains. However, the targeted nature of clinical tumor sequencing has a limited scope, especially for germline genetics. In this work, we assess the utility of discarded, off-target reads from tumor-only panel sequencing for the recovery of genome-wide germline genotypes through imputation.

Methods

We developed a framework for inference of germline variants from tumor panel sequencing, including imputation, quality control, inference of genetic ancestry, germline polygenic risk scores, and HLA alleles. We benchmarked our framework on 833 individuals with tumor sequencing and matched germline SNP array data. We then applied our approach to a prospectively collected panel sequencing cohort of 25,889 tumors.

Results

We demonstrate high to moderate accuracy of each inferred feature relative to direct germline SNP array genotyping: individual common variants were imputed with a mean accuracy (correlation) of 0.86, genetic ancestry was inferred with a correlation of > 0.98, polygenic risk scores were inferred with a correlation of > 0.90, and individual HLA alleles were inferred with a correlation of > 0.80. We demonstrate a minimal influence on the accuracy of somatic copy number alterations and other tumor features. We showcase the feasibility and utility of our framework by analyzing 25,889 tumors and identifying the relationships between genetic ancestry, polygenic risk, and tumor characteristics that could not be studied with conventional on-target tumor data.

Conclusions

We conclude that targeted tumor sequencing can be leveraged to build rich germline research cohorts from existing data and make our analysis pipeline publicly available to facilitate this effort.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00999-4.

Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations

BACKGROUND

Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The "rare variant hypothesis" proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale.

OBJECTIVES

In this study, we investigated associations between rare variants and 14 cancer types.

METHODS

We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG).

RESULTS

We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer).

CONCLUSIONS

Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.

Genomic Determinants of Homologous Recombination Deficiency across Human Cancers

Germline BRCA1/2 mutations associated with HRD are clinical biomarkers for sensitivity to poly-ADP ribose polymerase inhibitors (PARPi) treatment in breast, ovarian, pancreatic, and prostate cancers. However, it remains unclear whether other mutations may also lead to HRD and PARPi sensitivity across a broader range of cancer types. Our goal was to determine the germline or somatic alterations associated with the HRD phenotype that might therefore confer PARPi sensitivity. Using germline and somatic genomic data from over 9000 tumors representing 32 cancer types, we examined associations between HRD scores and pathogenic germline variants, somatic driver mutations, and copy number deletions in 30 candidate genes involved in homologous recombination. We identified several germline and somatic mutations (e.g., BRCA1/2, PALB2, ATM, and ATR mutations) associated with HRD phenotype in ovarian, breast, pancreatic, stomach, bladder, and lung cancer. The co-occurrence of germline BRCA1 variants and somatic TP53 mutations was significantly associated with increasing HRD in breast cancer. Notably, we also identified multiple somatic copy number deletions associated with HRD. Our study suggests that multiple cancer types include tumor subsets that show HRD phenotype and should be considered in the future clinical studies of PARPi and synthetic lethality strategies exploiting HRD, which can be caused by a large number of genomic alterations.

Somatic mutations provide important and unique insights into the biology of complex diseases

Somatic evolution of cells within the body is well known to lead to cancers. However, spread of somatic mutations within a tissue over time may also contribute to the pathogenesis of non-neoplastic diseases. Recent years have seen the publication of many studies aiming to characterize somatic evolution in healthy tissues. A logical next step is to extend such work to diseased conditions. As our understanding of the interplay between somatic mutations and non-neoplastic disease grows, opportunities for the joint study of germline and somatic variants will present themselves. Here, we present our thoughts on the utility of somatic mutations for understanding both the causes and consequences of common complex disease and the challenges that remain for the joint study of the soma and germline.

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.

Pathological Features of Tumors of the Nervous System in Hereditary Cancer Predisposition Syndromes: A Review

Hereditary cancer predisposition syndromes (HCS) become more recognizable as the knowledge about them expands, and genetic testing becomes more affordable. In this review, we discussed the known HCS that predispose to central and peripheral nervous system tumors. Different genetic phenomena were highlighted, and the important cellular biological alterations were summarized. Genetic mosaicism and germline mutations are features of HCS, and recently, they were described in normal population and as modifiers for the genetic landscape of sporadic tumors. Description of the tumors arising in these conditions was augmented by representative cases explaining the main pathological findings. Clinical spectrum of the syndromes and diagnostic criteria were tabled to outline their role in defining these disorders. Interestingly, precision medicine has found its way to help these groups of patients by offering targeted preventive measures. Understanding the signaling pathway alteration of mammalian target of rapamycin (mTOR) in tuberous sclerosis helped introducing mTOR inhibitors as a prophylactic treatment in these patients. More research to define the germline genetic alterations and resulting cellular signaling perturbations is needed for effective risk-reducing interventions beyond prophylactic surgeries.

Germline variants predictive of tumor mutational burden and immune checkpoint inhibitor efficacy

High tumor mutational burden (TMB) is associated with response to checkpoint blockade in several cancers. We identify pathogenic germline variants associated with increased TMB (GVITMB). GVITMB were found in 7 genes using a pan-cancer approach (APC, FANCL, SLC25A13, ERCC3, MSH6, PMS2, and TP53) and 38 gene sets (e.g., those involved in DNA repair and programmed cell death). GVITMB were also associated with mutational signatures related to the dysfunction of the gene carrying the variant, somatic mutations that further affect the gene or pathway with the variant, or transcriptomic changes concordant with the expected effect of the variant. In a validation cohort of 140 patients with cutaneous melanoma, we found that patients with GVITMB had prolonged progression-free survival (p = 0.0349, hazard ratio = 0.688) and responded favorably (p = 0.0341, odds = 1.842) when treated with immune checkpoint inhibitors. Our results suggest that germline variants can influence the molecular phenotypes of tumors and predict the response to immune checkpoint inhibitors.

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GVITMB were found in 7 genes and 38 gene sets

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GVITMB influence the somatic mutation and gene expression profiles of tumors

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GVITMB predict immune checkpoint inhibitory efficacy in SKCM

Genetic Ancestry Correlations with Driver Mutations Suggest Complex Interactions between Somatic and Germline Variation in Cancer

Carrot-Zhang and colleagues describe associations between Native American ancestry and the somatic mutational landscape in lung cancer, including tumor mutation burden and specific driver mutations in EGFR, KRAS, and STK11. Local ancestry analysis suggests that specific germline loci, and not environment, underlie these associations.See related article by Carrot-Zhang et al., p. 591.

Tumor Mutational Burden Is Polygenic and Genetically Associated with Complex Traits and Diseases

Tumor mutational burden (TMB) is an emerging biomarker of response to immunotherapy in solid tumors. However, the extent to which variation in TMB between patients is attributable to germline genetic variation remains elusive. Here, using 7,004 unrelated patients of European descent across 33 cancer types from The Cancer Genome Atlas, we show that pan-cancer TMB is polygenic with approximately 13% of its variation explained by approximately 1.1 million common variants altogether. We identify germline variants that affect TMB in stomach adenocarcinoma through altering the expression levels of BAG5 and KLC1. Further analyses provide evidence that TMB is genetically associated with complex traits and diseases, such as smoking, rheumatoid arthritis, height, and cancers, and some of the associations are likely causal. Overall, these results provide new insights into the genetic basis of somatic mutations in tumors and may inform future efforts to use genetic variants to stratify patients for immunotherapy. SIGNIFICANCE: This study provides evidence for a polygenic architecture of tumor mutational burden and opens an avenue for the use of whole-genome germline genetic variations to stratify patients with cancer for immunotherapy.

Global Autozygosity Is Associated with Cancer Risk, Mutational Signature and Prognosis

Simple Summary

Global autozygosity in the form of runs of homozygosity is associated with various diseases. Heterozygosity ratio, an alternative measure of global autozygosity, is used to assess cancer risk in this study. Our analysis shows strong and consistent associations between heterozygosity ratios and various cancer types. Further analysis reveals the heterozygosity ratio’s potential connections to mutational signatures and cancer prognosis.

Abstract

Global autozygosity quantifies the genome-wide levels of homozygous and heterozygous variants. It is the signature of non-random reproduction, though it can also be driven by other factors, and has been used to assess risk in various diseases. However, the association between global autozygosity and cancer risk has not been studied. From 4057 cancer subjects and 1668 healthy controls, we found strong associations between global autozygosity and risk in ten different cancer types. For example, the heterozygosity ratio was found to be significantly associated with breast invasive carcinoma in Blacks and with male skin cutaneous melanoma in Caucasians. We also discovered eleven associations between global autozygosity and mutational signatures which can explain a portion of the etiology. Furthermore, four significant associations for heterozygosity ratio were revealed in disease-specific survival analyses. This study demonstrates that global autozygosity is effective for cancer risk assessment.