Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden

Germline NGS targeted analysis in adult patients with sporadic adrenocortical carcinoma

BACKGROUND

Adrenocortical carcinoma (ACC) is a rare cancer that arises sporadically or due to hereditary syndromes. Data on germline variants (GVs) in sporadic ACC are limited. Our aim was to characterize GVs of genes potentially related to adrenal diseases in 150 adult patients with sporadic ACC.

METHODS

This was a retrospective analysis of stage I-IV ACC patients with sporadic ACC from two reference centers for ACC in Italy. Patients were included in the analysis if they had confirmed diagnosis of ACC, a frozen peripheral blood sample and complete clinical and follow-up data. Next generation sequencing technology was used to analyze the prevalence of GVs in a custom panel of 17 genes belonging to either cancer-predisposition genes or adrenocortical-differentiation genes categories.

RESULTS

We identified 18 GVs based on their frequency, enrichment and predicted functional characteristics. We found six pathogenic (P) or likely pathogenic (LP) variants in ARMC5, CTNNB1, MSH2, PDE11A and TP53 genes; and twelve variants lacking evidence of pathogenicity. New unique P/LP variants were identified in TP53 (p.G105D) and, for the first time, in ARMC5 (p.P731R). The presence of P/LP GVs was associated with reduced survival outcomes and had a significant and independent impact on both progression-free survival and overall survival.

CONCLUSIONS

GVs were present in 6.7 % of patients with sporadic ACC, and we identified novel variants of ARMC5 and TP53. These findings may improve understanding of ACC pathogenesis and enable genetic counseling of patients and their families.

Developing theragnostics for Alzheimer's disease: Insights from cancer treatment

The prevalence of Alzheimer's disease (AD) and its associated economic and societal burdens are on the rise, but there are no curative treatments for AD. Interestingly, this neurodegenerative disease shares several biological and pathophysiological features with cancer, including cell-cycle dysregulation, angiogenesis, mitochondrial dysfunction, protein misfolding, and DNA damage. However, the genetic factors contributing to the overlap in biological processes between cancer and AD have not been actively studied. In this review, we discuss the shared biological features of cancer and AD, the molecular targets of anticancer drugs, and therapeutic approaches. First, we outline the common biological features of cancer and AD. Second, we describe several anticancer drugs, their molecular targets, and their effects on AD pathology. Finally, we discuss how protein-protein interactions (PPIs), receptor inhibition, immunotherapy, and gene therapy can be exploited for the cure and management of both cancer and AD. Collectively, this review provides insights for the development of AD theragnostics based on cancer drugs and molecular targets.

Mutations, substitutions, and selection: Linking mutagenic processes to cancer using evolutionary theory

Cancers are the product of evolutionary events, where molecular variation occurs and accumulates in tissues and tumors. Sequencing of this molecular variation informs not only which variants are driving tumorigenesis, but also the mechanisms behind what is fueling mutagenesis. Both of these details are crucial for preventing premature deaths due to cancer, whether it is by targeting the variants driving the cancer phenotype or by measures to prevent exogenous mutations from contributing to somatic evolution. Here, we review tools to determine both molecular signatures and cancer drivers, and avenues by which these metrics may be linked.

Interpreting disease genome-wide association studies and polygenetic risk scores given eligibility and study design considerations

Genome-wide association studies (GWAS) have been helpful in identifying genetic variants predicting cancer risk and providing new insights into cancer biology. Increasing use of genetically informed care, as well as genetically informed prevention and treatment strategies, have also drawn attention to some of the inherent limitations of cancer genetic data. Specifically, genetic endowment is lifelong. However, those recruited into cancer studies tend to be middle-aged or older people, meaning the exposure most likely starts before recruitment, as opposed to exposure and recruitment aligning, as in a trial or a target trial. Studies in survivors can be biased as a result of depletion of the susceptibles, here specifically due to genetic vulnerability and the cancer of interest or a competing risk. In addition, including prevalent cases in a case-control study will make the genetics of survival with cancer look harmful (Neyman bias). Here, we describe ways of designing GWAS to maximize explanatory power and predictive utility, by reducing selection bias due to only recruiting survivors and reducing Neyman bias due to including prevalent cases alongside using other techniques, such as selection diagrams, age-stratification, and Mendelian randomization, to facilitate GWAS interpretability and utility.

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.

Tri©DB: an integrated platform of knowledgebase and reporting system for cancer precision medicine

BACKGROUND

With the development of cancer precision medicine, a huge amount of high-dimensional cancer information has rapidly accumulated regarding gene alterations, diseases, therapeutic interventions and various annotations. The information is highly fragmented across multiple different sources, making it highly challenging to effectively utilize and exchange the information. Therefore, it is essential to create a resource platform containing well-aggregated, carefully mined, and easily accessible data for effective knowledge sharing.

METHODS

In this study, we have developed "Consensus Cancer Core" (Tri©DB), a new integrative cancer precision medicine knowledgebase and reporting system by mining and harmonizing multifaceted cancer data sources, and presenting them in a centralized platform with enhanced functionalities for accessibility, annotation and analysis.

RESULTS

The knowledgebase provides the currently most comprehensive information on cancer precision medicine covering more than 40 annotation entities, many of which are novel and have never been explored previously. Tri©DB offers several unique features: (i) harmonizing the cancer-related information from more than 30 data sources into one integrative platform for easy access; (ii) utilizing a variety of data analysis and graphical tools for enhanced user interaction with the high-dimensional data; (iii) containing a newly developed reporting system for automated annotation and therapy matching for external patient genomic data. Benchmark test indicated that Tri©DB is able to annotate 46% more treatments than two officially recognized resources, oncoKB and MCG. Tri©DB was further shown to have achieved 94.9% concordance with administered treatments in a real clinical trial.

CONCLUSIONS

The novel features and rich functionalities of the new platform will facilitate full access to cancer precision medicine data in one single platform and accommodate the needs of a broad range of researchers not only in translational medicine, but also in basic biomedical research. We believe that it will help to promote knowledge sharing in cancer precision medicine. Tri©DB is freely available at www.biomeddb.org , and is hosted on a cutting-edge technology architecture supporting all major browsers and mobile handsets.

Selection bias as an explanation for the observed protective association of childhood adiposity with breast cancer

OBJECTIVES

Recalled childhood adiposity is inversely associated with breast cancer observationally, including in Mendelian randomization (MR) studies. Breast cancer studies recruited in adulthood only include survivors of childhood adiposity and breast cancer or a competing risk. We assessed recalled childhood adiposity on participant reported sibling and maternal breast cancer to ensure ascertainment of nonsurvivors.

STUDY DESIGN AND SETTING

We obtained independent strong genetic predictors of recalled childhood adiposity for women and their associations with participant reported own, sibling and maternal breast cancer from UK Biobank genome wide association studies.

RESULTS

Recalled childhood adiposity in women was inversely associated with own breast cancer using Mendelian randomization inverse variance weighting (odds ratio (OR) 0.66, 95% confidence interval (CI) 0.52-0.84) but less clearly related to participant reported sibling (OR 0.89, 95% CI 0.69-1.14) or maternal breast cancer (OR 0.84, 95% CI 0.67-1.05).

CONCLUSION

Weaker inverse associations of recalled childhood adiposity with breast cancer with more comprehensive ascertainment of cases before recruitment suggests the inverse association of recalled childhood adiposity with breast cancer could be partly selection bias from preferential selection of survivors. Greater consideration of survival bias in public health relevant causal inferences would be helpful.

Early-Onset Ovarian Cancer <30 Years: What Do We Know about Its Genetic Predisposition?

Ovarian cancer (OC) is one of the leading causes of cancer-related deaths in women. Most patients are diagnosed with advanced epithelial OC in their late 60s, and early-onset adult OC diagnosed ≤30 years is rare, accounting for less than 5% of all OC cases. The most significant risk factor for OC development are germline pathogenic/likely pathogenic variants (GPVs) in OC predisposition genes (including BRCA1, BRCA2, BRIP1, RAD51C, RAD51D, Lynch syndrome genes, or BRIP1), which contribute to the development of over 20% of all OC cases. GPVs in BRCA1/BRCA2 are the most prevalent. The presence of a GPV directs tailored cancer risk-reducing strategies for OC patients and their relatives. Identification of OC patients with GPVs can also have therapeutic consequences. Despite the general assumption that early cancer onset indicates higher involvement of hereditary cancer predisposition, the presence of GPVs in early-onset OC is rare (<10% of patients), and their heritability is uncertain. This review summarizes the current knowledge on the genetic predisposition to early-onset OC, with a special focus on epithelial OC, and suggests other alternative genetic factors (digenic, oligogenic, polygenic heritability, genetic mosaicism, imprinting, etc.) that may influence the development of early-onset OC in adult women lacking GPVs in known OC predisposition genes.

Neurodevelopmental disorders and cancer networks share pathways, but differ in mechanisms, signaling strength, and outcome

Epidemiological studies suggest that individuals with neurodevelopmental disorders (NDDs) are more prone to develop certain types of cancer. Notably, however, the case statistics can be impacted by late discovery of cancer in individuals afflicted with NDDs, such as intellectual disorders, autism, and schizophrenia, which may bias the numbers. As to NDD-associated mutations, in most cases, they are germline while cancer mutations are sporadic, emerging during life. However, somatic mosaicism can spur NDDs, and cancer-related mutations can be germline. NDDs and cancer share proteins, pathways, and mutations. Here we ask (i) exactly which features they share, and (ii) how, despite their commonalities, they differ in clinical outcomes. To tackle these questions, we employed a statistical framework followed by network analysis. Our thorough exploration of the mutations, reconstructed disease-specific networks, pathways, and transcriptome levels and profiles of autism spectrum disorder (ASD) and cancers, point to signaling strength as the key factor: strong signaling promotes cell proliferation in cancer, and weaker (moderate) signaling impacts differentiation in ASD. Thus, we suggest that signaling strength, not activating mutations, can decide clinical outcome.

FADS2 function at the major cancer hotspot 11q13 locus alters fatty acid metabolism in cancer

Dysregulation of fatty acid metabolism and de novo lipogenesis is a key driver of several cancer types through highly unsaturated fatty acid (HUFA) signaling precursors such as arachidonic acid. The human chromosome 11q13 locus has long been established as the most frequently amplified in a variety of human cancers. The fatty acid desaturase genes (FADS1, FADS2 and FADS3) responsible for HUFA biosynthesis localize to the 11q12-13.1 region. FADS2 activity is promiscuous, catalyzing biosynthesis of several unsaturated fatty acids by Δ6, Δ8, and Δ4 desaturation. Our main aim here is to review known and putative consequences of FADS2 dysregulation due to effects on the 11q13 locus potentially driving various cancer types. FADS2 silencing causes synthesis of sciadonic acid (5Z,11Z,14Z-20:3) in MCF7 cells and breast cancer in vivo. 5Z,11Z,14Z-20:3 is structurally identical to arachidonic acid (5Z,8Z,11Z,14Z-20:4) except it lacks the internal Δ8 double bond required for prostaglandin and leukotriene synthesis, among other eicosanoids. Palmitic acid has substrate specificity for both SCD and FADS2. Melanoma, prostate, liver and lung cancer cells insensitive to SCD inhibition show increased FADS2 activity and sapienic acid biosynthesis. Elevated serum mead acid levels found in hepatocellular carcinoma patients suggest an unsatisfied demand for arachidonic acid. FADS2 circular RNAs are at high levels in colorectal and lung cancer tissues. FADS2 circular RNAs are associated with shorter overall survival in colorectal cancer patients. The evidence thusfar supports an effort for future research on the role of FADS2 as a tumor suppressor in a range of neoplastic disorders.

Low mutation rate in epaulette sharks is consistent with a slow rate of evolution in sharks

Sharks occupy diverse ecological niches and play critical roles in marine ecosystems, often acting as apex predators. They are considered a slow-evolving lineage and have been suggested to exhibit exceptionally low cancer rates. These two features could be explained by a low nuclear mutation rate. Here, we provide a direct estimate of the nuclear mutation rate in the epaulette shark (Hemiscyllium ocellatum). We generate a high-quality reference genome, and resequence the whole genomes of parents and nine offspring to detect de novo mutations. Using stringent criteria, we estimate a mutation rate of 7×10-10 per base pair, per generation. This represents one of the lowest directly estimated mutation rates for any vertebrate clade, indicating that this basal vertebrate group is indeed a slowly evolving lineage whose ability to restore genetic diversity following a sustained population bottleneck may be hampered by a low mutation rate.

Prevalence and spectrum of cancer predisposition germline mutations in young patients with the common late-onset cancers

BACKGROUND

Pathogenic germline variants (PGVs) can play a vital role in the oncogenesis process in carriers. Previous studies have recognized that PGVs contribute to early onset of tumorigenesis in certain cancer types, for example, colorectal cancer and breast cancer. However, the reported prevalence data of cancer-associated PGVs were highly inconsistent due to nonuniform patient cohorts, sequencing methods, and prominent difficulties in pathogenicity interpretation of variants. In addition to the above difficulties, due to the rarity of cases, the prevalence of cancer PGV carriers in young cancer patients affected by late-onset cancer types has not been comprehensively evaluated to date.

METHODS

A total of 131 young cancer patients (1-29 years old at diagnosis) were enrolled in this study. The patients were affected by six common late-onset cancer types, namely, lung cancer, liver cancer, colorectal cancer, gastric cancer, renal cancer, and head-neck cancer. Cancer PGVs were identified and analyzed. based on NGS-based targeted sequencing followed by bioinformatic screening and strict further evaluations of variant pathogenicity.

RESULTS

Twenty-three cancer PGVs in 21 patients were identified, resulting in an overall PGV prevalence of 16.0% across the six included cancer types, which was approximately double the prevalence reported in a previous pancancer study. Nine of the 23 PGVs are novel, thus expanding the cancer PGV spectrum. Seven of the 23 (30.4%) PGVs are potential therapeutic targets of olaparib, with potential implications for clinical manipulation. Additionally, a small prevalence of somatic mutations of some classic cancer hallmark genes in young patients, in contrast to all-age patients, was revealed.

CONCLUSION

This study demonstrates the high prevalence of PGVs in young cancer patients with the common late-onset cancers and the potentially significant clinical implications of cancer PGVs, the findings highlight the value of PGV screening in young patients across lung cancer, liver cancer, colorectal cancer, gastric cancer, renal cancer, or head-neck cancer.

More than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome

Aging is a leading risk factor for cancer. While it is proposed that age-related accumulation of somatic mutations drives this relationship, it is likely not the full story. We show that aging and cancer share a common epigenetic replication signature, which we modeled using DNA methylation from extensively passaged immortalized human cells in vitro and tested on clinical tissues. This signature, termed CellDRIFT, increased with age across multiple tissues, distinguished tumor from normal tissue, was escalated in normal breast tissue from cancer patients, and was transiently reset upon reprogramming. In addition, within-person tissue differences were correlated with predicted lifetime tissue-specific stem cell divisions and tissue-specific cancer risk. Our findings suggest that age-related replication may drive epigenetic changes in cells and could push them toward a more tumorigenic state.

A polygenic two-hit hypothesis for prostate cancer

Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

The genetic era of childhood cancer: Identification of high-risk patients and germline sequencing approaches

Childhood cancer is a leading cause of death by disease in children ages 5-14, for which there are no preventive strategies. Due to early-age of diagnosis and short period of exposure to environmental factors, increasing evidence suggests childhood cancer could have strong association with germline alterations in predisposition cancer genes but, their frequency and distribution are largely unknown. Several efforts have been made to develop tools to identify children with increased risk of cancer who may benefit from genetic testing but their validation and application on a large scale is necessary. Research on genetic bases of childhood cancer is ongoing, in which several approaches for the identification of genetic variants related to cancer predisposition have been used. In this paper, we discuss the updated efforts, strategies, molecular mechanisms and clinical implications for germline predisposition gene alterations and the characterization of risk variants in childhood cancer.

Incidence of Hereditary Gastric Cancer May Be Much Higher than Reported

Hereditary gastric cancers (HGCs) are supposed to be rare and difficult to identify. Nonetheless, many cases of young patients with gastric cancer (GC) fulfill the clinical criteria for considering this diagnosis but do not present the defined pathogenic mutations necessary to meet a formal diagnosis of HGC. Moreover, GC in young people is a challenging medical situation due to the usual aggressiveness of such cases and the potential risk for their relatives when related to a germline variant. Aiming to identify additional germline alterations that might contribute to the early onset of GC, a complete exome sequence of blood samples from 95 GC patients under 50 and 94 blood samples from non-cancer patients was performed and compared in this study. The number of identified germline mutations in GC patients was found to be much higher than that from individuals without a cancer diagnosis. Specifically, the number of high functional impact mutations, including those affecting genes involved in medical diseases, cancer hallmark genes, and DNA replication and repair processes, was much higher, strengthening the hypothesis of the potential causal role of such mutations in hereditary cancers. Conversely, classically related HGC mutations were not found and the number of mutations in genes in the CDH1 pathway was not found to be relevant among the young GC patients, reinforcing the hypothesis that existing alternative germline contributions favor the early onset of GC. The LILRB1 gene variants, absent in the world's cancer datasets but present in high frequencies among the studied GC patients, may represent essential cancer variants specific to the Amerindian ancestry's contributions. Identifying non-reported GC variants, potentially originating from under-studied populations, may pave the way for additional discoveries and translations to clinical interventions for GC management. The newly proposed approaches may reduce the discrepancy between clinically suspected and molecularly proven hereditary GC and shed light on similar inconsistencies among other cancer types. Additionally, the results of this study may support the development of new blood tests for evaluating cancer risk that can be used in clinical practice, helping physicians make decisions about strategies for surveillance and risk-reduction interventions.

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.

Molecular differences between younger versus older ER-positive and HER2-negative breast cancers

The RxPONDER and TAILORx trials demonstrated benefit from adjuvant chemotherapy in patients age ≤ 50 with node-positive breast cancer and Recurrence Score (RS) 0-26, and in node-negative disease with RS 16-25, respectively, but no benefit in older women with the same clinical features. We analyzed transcriptomic and genomic data of ER+/HER2- breast cancers with in silico RS < 26 from TCGA (n = 530), two microarray cohorts (A: n = 865; B: n = 609), the METABRIC (n = 867), and the SCAN-B (n = 1636) datasets. There was no difference in proliferation-related gene expression between age groups. Older patients had higher mutation burden and more frequent ESR1 copy number gain, but lower frequency of GATA3 mutations. Younger patients had higher rate of ESR1 copy number loss. In all datasets, younger patients had significantly lower mRNA expression of ESR1 and ER-associated genes, and higher expression of immune-related genes. The ER- and immune-related gene signatures showed negative correlation and defined three subpopulations in younger women: immune-high/ER-low, immune-intermediate/ER-intermediate, and immune-low/ER-intermediate. We hypothesize that in immune-high cancers, the cytotoxic effect of chemotherapy may drive the benefit, whereas in immune-low/ER-intermediate cancers chemotherapy induced ovarian suppression may play important role.

Gene-Level Associations in Patients With and Without Pathogenic Germline Variants in CDKN2A and Pancreatic Cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a component of familial melanoma due to germline pathogenic variants (GPVs) in CDKN2A. However, it is unclear what role this gene or other genes play in its etiology.

MATERIALS AND METHODS

We analyzed 189 cancer predisposition genes using parametric rare-variant association (RVA) tests and nonparametric permutation tests to identify gene-level associations in PDAC for patients with (CDKN2A+) and without (CDKN2A-) GPV. Exome sequencing was performed on 84 patients with PDAC, 47 CDKN2A+ and 37 CDKN2A-. After variant filtering, various RVA tests and permutation tests were run separately by CDKN2A status. Genes with the strongest nominal associations were evaluated in patients with PDAC from The Cancer Genome Atlas and the UK Biobank (UKB). A secondary analysis including only GPV from UKB was also performed.

RESULTS

In RVA tests, ERCC4 and RET showed the most compelling evidence as plausible PDAC candidate genes for CDKN2A+ patients. In contrast, the findings in CDKN2A- patients provided evidence for HMBS, EPCAM, and MRE11 as potential new candidate genes and confirmed ATM, BRCA2, and PALB2 as PDAC genes, consistent with findings in The Cancer Genome Atlas and the UKB. As expected, CDKN2A- patients were more likely to harbor GPVs from the 189 genes investigated. When including only GPVs from UKB, significant associations with PDAC were seen for ATM, BRCA2, and CDKN2A.

CONCLUSION

These results suggest that variants in other genes likely play a role in PDAC in all patients and that PDAC in CDKN2A+ patients has a distinct etiology from PDAC in CDKN2A- 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.

New Drug Development and Clinical Trial Design by Applying Genomic Information Management

Depending on the patients’ genotype, the same drug may have different efficacies or side effects. With the cost of genomic analysis decreasing and reliability of analysis methods improving, vast amount of genomic information has been made available. Several studies in pharmacology have been based on genomic information to select the optimal drug, determine the dose, predict efficacy, and prevent side effects. This paper reviews the tissue specificity and genomic information of cancer. If the tissue specificity of cancer is low, cancer is induced in various organs based on a single gene mutation. Basket trials can be performed for carcinomas with low tissue specificity, confirming the efficacy of one drug for a single gene mutation in various carcinomas. Conversely, if the tissue specificity of cancer is high, cancer is induced in only one organ based on a single gene mutation. An umbrella trial can be performed for carcinomas with a high tissue specificity. Some drugs are effective for patients with a specific genotype. A companion diagnostic strategy that prescribes a specific drug for patients selected with a specific genotype is also reviewed. Genomic information is used in pharmacometrics to identify the relationship among pharmacokinetics, pharmacodynamics, and biomarkers of disease treatment effects. Utilizing genomic information, sophisticated clinical trials can be designed that will be better suited to the patients of specific genotypes. Genomic information also provides prospects for innovative drug development. Through proper genomic information management, factors relating to drug response and effects can be determined by selecting the appropriate data for analysis and by understanding the structure of the data. Selecting pre-processing and appropriate machine-learning libraries for use as machine-learning input features is also necessary. Professional curation of the output result is also required. Personalized medicine can be realized using a genome-based customized clinical trial design.

Cancer Relevance of Human Genes

BACKGROUND

We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional importance in cancer.

METHODS

We categorized 12 767 human genes into CCGs (n = 468), 1 (n = 5467), 2 (n = 5573), 3 (n = 915), and more than 3 steps (n = 416) removed from the nearest CCG in the Search Tool for the Retrieval of Interacting Genes/Proteins network. We estimated cancer-relevant functional importance in these neighborhood categories using 1) gene dependency score, which reflects the effect of a gene on cell viability after knockdown; 2) somatic mutation frequency in The Cancer Genome Atlas; 3) effect size that estimates to what extent a mutation in a gene enhances cell survival; and 4) negative selection pressure of germline protein-truncating variants in healthy populations.

RESULTS

Cancer biology-related functional importance of genes decreases as their distance from the CCGs increases. Genes closer to cancer genes show greater connectedness in the network, have greater importance in maintaining cancer cell viability, are under greater negative germline selection pressure, and have higher somatic mutation frequency in cancer. Based on these 4 metrics, we provide cancer relevance annotation to known human genes.

CONCLUSIONS

A large number of human genes are connected to CCGs and could influence cancer biology to various extent when dysregulated; any given mutation may be functionally important in one but not in another individual depending on genomic context.

Higher ATM expression in lymphoblastoid cell lines from centenarian compared with younger women

With increased life expectancies in developed countries, cancer rates are becoming more common among the elderly. Cancer is typically driven by a combination of germline and somatic mutations accumulating during an individual's lifetime. Yet, many centenarians reach exceptionally old age without experiencing cancer. It was suggested that centenarians have more robust DNA repair and mitochondrial function, allowing improved maintenance of DNA stability. In this study, we applied real-time quantitative PCR to examine the expression of ATM in lymphoblastoid cell lines (LCLs) from 15 healthy female centenarians and 24 younger female donors aged 21-88 years. We observed higher ATM mRNA expression of in LCLs from female centenarians compared with both women aged 21-48 years (FD = 2.0, p = .0016) and women aged 56-88 years (FD = 1.8, p = .0094. Positive correlation was found between ATM mRNA expression and donors age (p = .0028). Levels of hsa-miR-181a-5p, which targets ATM, were lower in LCLs from centenarians compared with younger women. Our findings suggest a role for ATM in protection from age-related diseases, possibly reflecting more effective DNA repair, thereby reducing somatic mutation accumulation during aging. Further studies are required for analyzing additional DNA repair pathways in biosamples from centenarians and younger age men and women.

Considering hormone-sensitive cancers as a single disease in the UK biobank reveals shared aetiology

Hormone-related cancers, including cancers of the breast, prostate, ovaries, uterine, and thyroid, globally contribute to the majority of cancer incidence. We hypothesize that hormone-sensitive cancers share common genetic risk factors that have rarely been investigated by previous genomic studies of site-specific cancers. Here, we show that considering hormone-sensitive cancers as a single disease in the UK Biobank reveals shared genetic aetiology. We observe that a significant proportion of variance in disease liability is explained by the genome-wide single nucleotide polymorphisms (SNPs), i.e., SNP-based heritability on the liability scale is estimated as 10.06% (SE 0.70%). Moreover, we find 55 genome-wide significant SNPs for the disease, using a genome-wide association study. Pair-wise analysis also estimates positive genetic correlations between some pairs of hormone-sensitive cancers although they are not statistically significant. Our finding suggests that heritable genetic factors may be a key driver in the mechanism of carcinogenesis shared by hormone-sensitive cancers.

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.

Role of IGF2 in the Study of Development and Evolution of Prostate Cancer

Prostate Cancer (PC) is commonly known as one of the most frequent tumors among males. A significant problem of this tumor is that in early stages most of the cases course as indolent forms, so an active surveillance will anticipate the appearance of aggressive stages. One of the main strategies in medical and biomedical research is to find non-invasive biomarkers for improving monitoring and performing a more precise follow-up of diseases like PC. Here we report the relevant role of IGF2 and miR-93-5p as non-invasive biomarker for PC. This event could improve current medical strategies in PC.

The insertion and dysregulation of transposable elements in osteosarcoma and their association with patient event-free survival

The dysregulation of transposable elements (TEs) has been explored in a variety of cancers. However, TE activities in osteosarcoma (OS) have not been extensively studied yet. By integrative analysis of RNA-seq, whole-genome sequencing (WGS), and methylation data, we showed aberrant TE activities associated with dysregulations of TEs in OS tumors. Specifically, expression levels of LINE-1 and Alu of different evolutionary ages, as well as subfamilies of SVA and HERV-K, were significantly up-regulated in OS tumors, accompanied by enhanced DNA repair responses. We verified the characteristics of LINE-1 mediated TE insertions, including target site duplication (TSD) length (centered around 15 bp) and preferential insertions into intergenic and AT-rich regions as well as intronic regions of longer genes. By filtering polymorphic TE insertions reported in 1000 genome project (1KGP), besides 148 tumor-specific somatic TE insertions, we found most OS patient-specific TE insertions (3175 out of 3326) are germline insertions, which are associated with genes involved in neuronal processes or with transcription factors important for cancer development. In addition to 68 TE-affected cancer genes, we found recurrent germline TE insertions in 72 non-cancer genes with high frequencies among patients. We also found that +/− 500 bps flanking regions of transcription start sites (TSS) of LINE-1 (young) and Alu showed lower methylation levels in OS tumor samples than controls. Interestingly, by incorporating patient clinical data and focusing on TE activities in OS tumors, our data analysis suggested that higher TE insertions in OS tumors are associated with a longer event-free survival time.

Recent Advances in Pediatric Cancer Research

Over the past few years, the field of pediatric cancer has experienced a shift in momentum, and this has led to new and exciting findings that have relevance beyond pediatric malignancies. Here we present the current status of key aspects of pediatric cancer research. We have focused on genetic and epigenetic drivers of disease, cellular origins of different pediatric cancers, disease models, the tumor microenvironment, and cellular immunotherapies.

Germline Sequencing Improves Tumor-Only Sequencing Interpretation in a Precision Genomic Study of Patients With Pediatric Solid Tumor

PURPOSE

Molecular tumor profiling is becoming a routine part of clinical cancer care, typically involving tumor-only panel testing without matched germline. We hypothesized that integrated germline sequencing could improve clinical interpretation and enhance the identification of germline variants with significant hereditary risks.

MATERIALS AND METHODS

Tumors from pediatric patients with high-risk, extracranial solid malignancies were sequenced with a targeted panel of cancer-associated genes. Later, germline DNA was analyzed for a subset of these genes. We performed a post hoc analysis to identify how an integrated analysis of tumor and germline data would improve clinical interpretation.

RESULTS

One hundred sixty participants with both tumor-only and germline sequencing reports were eligible for this analysis. Germline sequencing identified 38 pathogenic or likely pathogenic variants among 35 (22%) patients. Twenty-five (66%) of these were included in the tumor sequencing report. The remaining germline pathogenic or likely pathogenic variants were single-nucleotide variants filtered out of tumor-only analysis because of population frequency or copy-number variation masked by additional copy-number changes in the tumor. In tumor-only sequencing, 308 of 434 (71%) single-nucleotide variants reported were present in the germline, including 31% with suggested clinical utility. Finally, we provide further evidence that the variant allele fraction from tumor-only sequencing is insufficient to differentiate somatic from germline events.

CONCLUSION

A paired approach to analyzing tumor and germline sequencing data would be expected to improve the efficiency and accuracy of distinguishing somatic mutations and germline variants, thereby facilitating the process of variant curation and therapeutic interpretation for somatic reports, as well as the identification of variants associated with germline cancer predisposition.

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.

Individualized Proteogenomics Reveals the Mutational Landscape of Melanoma Patients in Response to Immunotherapy

Simple Summary

Melanoma is the most aggressive form of skin cancer, with a rapidly increasing incidence rate. Due to ineffective treatment options in the late stage melanoma, patients have an overall poor prognosis. Over the last decades, the role of the immune system in the control of tumor progression has been established and immune checkpoint inhibitors (ICi) have shown remarkable clinical activity. While current trials suggest durable responses in patient under ICi therapy, there is increasing evidence pointing towards existence of innate and acquired resistance to ICi therapy; and it is now clear that personalized medicine will be critical for effective patient therapy. Proteogenomics is a powerful tool to study the mode of action of disease-associated mutations at the genome, transcriptome, proteome and PTM level. Here, we applied a proteogenomic workflow to study melanoma samples from human tumors. Such workflow may be applicable to other patient-derived samples and different cancer types.

Abstract

Immune checkpoint inhibitors are used to restore or augment antitumor immune responses and show great promise in the treatment of melanoma and other types of cancers. However, only a small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by the accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development, tumor heterogeneity and resistance mechanisms. Using this approach, we characterized the mutational landscape of four clinical melanoma patients. This enabled the quantification of hundreds of sample-specific amino acid variants, among them many that were previously not reported in melanoma. Changes in abundance at the protein and phosphorylation site levels revealed patient-specific over-represented pathways, notably linked to melanoma development (MAPK1 activation) or immunotherapy (NLRP1 inflammasome). Personalized data integration resulted in the prediction of protein drug targets, such as the drugs vandetanib and bosutinib, which were experimentally validated and led to a reduction in the viability of tumor cells. Our study emphasizes the potential of proteogenomic approaches to study personalized mutational landscapes, signaling networks and therapy options.

Proteogenomics Reveals Perturbed Signaling Networks in Malignant Melanoma Cells Resistant to BRAF Inhibition

Analysis of nucleotide variants is a cornerstone of cancer medicine. Although only 2% of the genomic sequence is protein coding, mutations occurring in these regions have the potential to influence protein structure or modification status and may have severe impact on disease aetiology. Proteogenomics enables the analysis of sample-specific nonsynonymous nucleotide variants with regard to their effect at the proteome and phosphoproteome levels. Here, we developed a proof-of-concept proteogenomics workflow and applied it to the malignant melanoma cell line A375. Initially, we studied the resistance to serine/threonine-protein kinase B-raf (BRAF) inhibitor (BRAFi) vemurafenib in A375 cells. This allowed identification of several oncogenic nonsynonymous nucleotide variants, including a gain-of-function variant on aurora kinase A (AURKA) at F31I. We also detected significant changes in abundance among (phospho)proteins, which led to reactivation of the MAPK signaling pathway in BRAFi-resistant A375 cells. Upon reconstruction of the multiomic integrated signaling networks, we predicted drug therapies with the potential to disrupt BRAFi resistance mechanism in A375 cells. Notably, we showed that AURKA inhibition is effective and specific against BRAFi-resistant A375 cells. Subsequently, we investigated amino acid variants that interfere with protein posttranslational modification (PTM) status and potentially influence A375 cell signaling irrespective of BRAFi resistance. Mass spectrometry (MS) measurements confirmed variant-driven PTM changes in 12 proteins. Among them was the runt-related transcription factor 1 (RUNX1) displaying a variant on a known phosphorylation site S(Ph)276L. We confirmed the loss of phosphorylation site by MS and demonstrated the impact of this variant on RUNX1 interactome.

Machine-learning algorithms predict breast cancer patient survival from UK Biobank whole-exome sequencing data

Aim: We tested whether machine-learning algorithm could find biomarkers predicting overall survival in breast cancer patients using blood-based whole-exome sequencing data. Materials & methods: Whole-exome sequencing data derived from 1181 female breast cancer patients within the UK Biobank was collected. We found feature genes (n = 50) regarding total mutation burden using the long short-term memory model. Then, we developed the XGBoost survival model with selected feature genes. Results: The XGBoost survival model performed acceptably, with a concordance index of 0.75 and a scaled Brier score of 0.146 in terms of overall survival prediction. The high-mutation group exhibited inferior overall survival compared with the low-mutation group in patients ≥56 years (log-rank test, p = 0.042). Conclusion: We showed that machine-learning algorithms can be used to predict overall survival in breast cancer patients from blood-based whole-exome sequencing data.

Inferred Ancestral Origin of Cancer Cell Lines Associates with Differential Drug Response

Disparities between risk, treatment outcomes and survival rates in cancer patients across the world may be attributed to socioeconomic factors. In addition, the role of ancestry is frequently discussed. In preclinical studies, high-throughput drug screens in cancer cell lines have empowered the identification of clinically relevant molecular biomarkers of drug sensitivity; however, the genetic ancestry from tissue donors has been largely neglected in this setting. In order to address this, here, we show that the inferred ancestry of cancer cell lines is conserved and may impact drug response in patients as a predictive covariate in high-throughput drug screens. We found that there are differential drug responses between European and East Asian ancestries, especially when treated with PI3K/mTOR inhibitors. Our finding emphasizes a new angle in precision medicine, as cancer intervention strategies should consider the germline landscape, thereby reducing the failure rate of clinical trials.

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.

Evaluating the impact of age on immune checkpoint therapy biomarkers

Both tumors and aging alter the immune landscape of tissues. These interactions may play an important role in tumor progression among elderly patients and may suggest considerations for patient care. We leverage large-scale genomic and clinical databases to perform comprehensive comparative analysis of molecular and cellular markers of immune checkpoint blockade (ICB) response with patient age. These analyses demonstrate that aging is associated with increased tumor mutational burden, increased expression and decreased promoter methylation of immune checkpoint genes, and increased interferon gamma signaling in older patients in many cancer types studied, all of which are expected to promote ICB efficacy. Concurrently, we observe age-related alterations that might be expected to reduce ICB efficacy, such as decreases in T cell receptor diversity. Altogether, these changes suggest the capacity for robust ICB response in many older patients, which may warrant large-scale prospective study on ICB therapies among patients of advanced age.

Systems genetics analysis of oral squamous cell carcinoma susceptibility using the mouse model: current position and new perspective

Oral squamous cell carcinoma (OSCC) is one of the most common human malignancies with complex etiology and poor prognosis. Although environmental carcinogens and carcinogenic viruses are still considered the main etiologic factors for OSCC development, genetic factors obviously play a key role in the initiation and progression of this neoplasm, given that not all individuals exposed to carcinogens develop the same severity of the disease, if any. Identifying genetic loci modulating OSCC risk may have several important clinical implications, including early detection, prevention and developing new treatment strategies. Due to limitations in controlled and standardized genetic studies in humans, genetic components underlying susceptibility of OSCC development remain largely unknown. A combination of quantitative trait loci mapping in mice, with complementary association studies in humans, has the potential to discover novel cancer risk loci. As of today, a limited number of genetic analyses were applied on rodent models to locate novel genetic loci associated with human OSCC. Here, we discuss the current status of the mouse models use for dissecting the genetic basis of OSCC and highlight how systems genetics analysis using mouse models, may increase our understanding of human OSCC susceptibility.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

The Panorama of Cancer Genetics

Cancer, a disease of the genome, is caused by a combination of germline predisposing variants and acquired somatic mutations. A unified view of heritable and acquired genetic factors will improve our understanding of cancer occurrence and progression. Fanfani and colleagues provide new insight into heritable cancer risk through a computational method that identifies genes and loci that contribute strongly to cancer heritability; many of these loci also harbor somatic drivers. Beyond improving cancer clinical outcomes, these methods will also be valuable across complex disorders by identifying regions responsible for missing heritability.See related article by Fanfani et al., p. 2588.

Profiling Oncogenic Germline Mutations in Unselected Chinese Lung Cancer Patients

Introduction

Emerging evidence has suggested that inherited factors are also involved in lung cancer development. However, most studies focused on well-elucidated cancer predisposition genes, the majority of which are tumor suppressor genes. The profile of germline mutations in oncogenic driver genes remains unrevealed, which might also provide potential clinical implications for lung cancer management.

Methods

Sequencing data from 36,813 unselected lung cancer patients who underwent somatic mutation profiling were retrospectively reviewed. All recruited patients had matched white blood cell samples sequenced in parallel using a capture-based panel including eight key lung cancer driver genes (epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), MET proto-oncogene, receptor tyrosine kinase (MET), Kirsten rat sarcoma viral oncogene homolog (KRAS), Erb-B2 receptor tyrosine kinase 2(ERBB2), ROS proto-oncogene 1, receptor tyrosine kinase (ROS1), ret proto-oncogene (RET), and B-Raf proto-oncogene, serine/threonine kinase (BRAF)). Likely pathogenic/pathogenic (LP/P) variants were called according to the classification criteria of the American College of Medical Genetics and Genomics. Variants of uncertain significance (VUS) located in the kinase domains of driver genes and occurring recurrently (n ≥3) were also included for further analyses.

Results

Seven different LP/P variants in EGFR, MET, or RET were identified in 0.03% of lung cancer patients (n = 14) and 25 different VUS in the kinase domains of seven driver genes (except KRAS) were found with a prevalence of 0.3% (n = 117).Collectively, germline mutations were most frequently seen in ROS1 (n = 31, 0.084%), followed by MET (n = 23, 0.062%), EGFR (n = 22, 0.06%), ALK (n = 22, 0.06%) and RET (n = 17, 0.046%). LP/P variants and VUS fell the most commonly in EGFR (n = 10, 72%) and ROS1 (n = 31, 26%), respectively. Of the 10 patients with EGFR LP/P germline mutation, 70% also acquired somatic EGFR driver mutation exon21 p.L858R or exon19 deletion at baseline; while the three patients with pathogenic germline RET mutation displayed distinct baseline somatic profiles of rare EGFR mutation or KRAS exon2 p.G12C. We discovered 11 germline mutations that also occurred somatically, including four LP/P variants and seven VUS.

Conclusion

We present the first study to systemically characterize the germline mutation in oncogenic driver genes in a large cohort of unselected patients with lung cancers.

The Landscape of the Heritable Cancer Genome

Genome-wide association studies (GWAS) have found hundreds of single-nucleotide polymorphisms (SNP) associated with increased risk of cancer. However, the amount of heritable risk explained by SNPs is limited, leaving most of the cancer heritability unexplained. Tumor sequencing projects have shown that causal mutations are enriched in genic regions. We hypothesized that SNPs located in protein coding genes and nearby regulatory regions could explain a significant proportion of the heritable risk of cancer. To perform gene-level heritability analysis, we developed a new method, called Bayesian Gene Heritability Analysis (BAGHERA), to estimate the heritability explained by all genotyped SNPs and by those located in genic regions using GWAS summary statistics. BAGHERA was specifically designed for low heritability traits such as cancer and provides robust heritability estimates under different genetic architectures. BAGHERA-based analysis of 38 cancers reported in the UK Biobank showed that SNPs explain at least 10% of the heritable risk for 14 of them, including late onset malignancies. We then identified 1,146 genes, called cancer heritability genes (CHG), explaining a significant proportion of cancer heritability. CHGs were involved in hallmark processes controlling the transformation from normal to cancerous cells. Importantly, 60 of them also harbored somatic driver mutations, and 27 are tumor suppressors. Our results suggest that germline and somatic mutation information could be exploited to identify subgroups of individuals at higher risk of cancer in the broader population and could prove useful to establish strategies for early detection and cancer surveillance. SIGNIFICANCE: This study describes a new statistical method to identify genes associated with cancer heritability in the broader population, creating a map of the heritable cancer genome with gene-level resolution.See related commentary by Bader, p. 2586.

Interpreting Sequence Variation in PDAC-Predisposing Genes Using a Multi-Tier Annotation Approach Performed at the Gene, Patient, and Cohort Level

We investigated germline variation in pancreatic ductal adenocarcinoma (PDAC) predisposition genes in 535 patients, using a custom-built panel and a new complementary bioinformatic approach. Our panel assessed genes belonging to DNA repair, cell cycle checkpoints, migration, and preneoplastic pancreatic conditions. Our bioinformatics approach integrated annotations of variants by using data derived from both germline and somatic references. This integrated approach with expanded evidence enabled us to consider patterns even among private mutations, supporting a functional role for certain alleles, which we believe enhances individualized medicine beyond classic gene-centric approaches. Concurrent evaluation of three levels of evidence, at the gene, sample, and cohort level, has not been previously done. Overall, we identified in PDAC patient germline samples, 12% with mutations previously observed in pancreatic cancers, 23% with mutations previously discovered by sequencing other human tumors, and 46% with mutations with germline associations to cancer. Non-polymorphic protein-coding pathogenic variants were found in 18.4% of patient samples. Moreover, among patients with metastatic PDAC, 16% carried at least one pathogenic variant, and this subgroup was found to have an improved overall survival (22.0 months versus 9.8; p=0.008) despite a higher pre-treatment CA19-9 level (p=0.02). Genetic alterations in DNA damage repair genes were associated with longer overall survival among patients who underwent resection surgery (92 months vs. 46; p=0.06). ATM alterations were associated with more frequent metastatic stage (p = 0.04) while patients with BRCA1 or BRCA2 alterations had improved overall survival (79 months vs. 39; p=0.05). We found that mutations in genes associated with chronic pancreatitis were more common in non-white patients (p<0.001) and associated with longer overall survival (52 months vs. 26; p=0.004), indicating the need for greater study of the relationship among these factors. More than 90% of patients were found to have variants of uncertain significance, which is higher than previously reported. Furthermore, we generated 3D models for selected mutant proteins, which suggested distinct mechanisms underlying their dysfunction, likely caused by genetic alterations. Notably, this type of information is not predictable from sequence alone, underscoring the value of structural bioinformatics to improve genomic interpretation. In conclusion, the variation in PDAC predisposition genes appears to be more extensive than anticipated. This information adds to the growing body of literature on the genomic landscape of PDAC and brings us closer to a more widespread use of precision medicine for this challenging disease.

Pathogenic germline variants are associated with poor survival in stage III/IV melanoma patients

Patients with late stage resected cutaneous melanoma have poor overall survival (OS) and experience irreversible adverse events from systemic therapy. There is a clinical need to identify biomarkers to predict outcome. Performing germline/tumour whole-exome sequencing of 44 stage III/IV melanoma patients we identified pathogenic germline mutations in CDKN2A, CDK4, ATM, POLH, MRE11A, RECQL4 and XPC, affecting 7/44 patients. These mutations were associated with poor OS (p = 0.0082). We confirmed our findings in The Cancer Genome Atlas (TCGA) human skin cutaneous melanoma cohort where we identified pathogenic variants in 40/455 patients (p = 0.0203). Combining these cohorts (n = 499) further strengthened these findings showing germline carriers had worse OS (p = 0.0009). Additionally, we determined whether tumour mutation burden (TMB) or BRAF status were prognostic markers of survival. Low TMB rate (< 20 Mut/Mb; p = 0.0034) and BRAF p.V600 mutation (p = 0.0355) were associated with worse progression-free survival. Combining these biomarkers indicated that V600 mutant patients had significantly lower TMB (p = 0.0155). This was confirmed in the TCGA (n = 443, p = 0.0007). Integrative analysis showed germline mutation status conferred the highest risk (HR 5.2, 95% CI 1.72–15.7). Stage IV (HR 2.5, 0.74–8.6) and low TMB (HR 2.3, 0.57–9.4) were similar, whereas BRAF V600 status was the weakest prognostic biomarker (HR 1.5, 95% CI 0.44–5.2).