Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer

Understanding oncogenicity of cancer driver genes and mutations in the cancer genomics era

One of the key challenges of cancer biology is to catalogue and understand the somatic genomic alterations leading to cancer. Although alternative definitions and search methods have been developed to identify cancer driver genes and mutations, analyses of thousands of cancer genomes return a remarkably similar catalogue of around 300 genes that are mutated in at least one cancer type. Yet, many features of these genes and their role in cancer remain unclear, first and foremost when a somatic mutation is truly oncogenic. In this review, we first summarize some of the recent efforts in completing the catalogue of cancer driver genes. Then, we give an overview of different aspects that influence the oncogenicity of somatic mutations in the core cancer driver genes, including their interactions with the germline genome, other cancer driver mutations, the immune system, or their potential role in healthy tissues. In the coming years, this research holds promise to illuminate how, when, and why cancer driver genes and mutations are really drivers, and thereby move personalized cancer medicine and targeted therapies forward.

Germline Variants That Affect Tumor Progression

Germline variants have a rich history of being studied in the context of cancer risk. Emerging studies now suggest that germline variants contribute not only to cancer risk but to tumor progression as well. In this opinion article, we discuss the initial discoveries associating germline variants with patient outcome and the mechanisms by which germline variants affect molecular pathways. Germline variants affect molecular pathways through amino acid changes, alteration of splicing patterns or expression of genes, influencing the selection for somatic mutations, and causing genome-wide mutational enrichment. These molecular alterations can lead to tumor phenotypes that become clinically apparent such as metastasis, alterations to the immune microenvironment, and modulation of therapeutic response. Overall, the growing body of evidence suggests that germline variants play a larger role in tumor progression than has been previously appreciated and that germline variation holds substantial potential for improving personalized medicine and patient outcomes.

Sino-European Differences in the Genetic Landscape and Clinical Presentation of Pheochromocytoma and Paraganglioma

CONTEXT

Pheochromocytomas and paragangliomas (PPGLs) are characterized by distinct genotype-phenotype relationships according to studies largely restricted to Caucasian populations.

OBJECTIVE

To assess for possible differences in genetic landscapes and genotype-phenotype relationships of PPGLs in Chinese versus European populations.

DESIGN

Cross-sectional study.

SETTING

2 tertiary-care centers in China and 9 in Europe.

PARTICIPANTS

Patients with pathologically confirmed diagnosis of PPGL, including 719 Chinese and 919 Europeans.

MAIN OUTCOME MEASURES

Next-generation sequencing performed in tumor specimens with mutations confirmed by Sanger sequencing and tested in peripheral blood if available. Frequencies of mutations were examined according to tumor location and catecholamine biochemical phenotypes.

RESULTS

Among all patients, higher frequencies of HRAS, FGFR1, and EPAS1 mutations were observed in Chinese than Europeans, whereas the reverse was observed for NF1, VHL, RET, and SDHx. Among patients with apparently sporadic PPGLs, the most frequently mutated genes in Chinese were HRAS (16.5% [13.6-19.3] vs 9.8% [7.6-12.1]) and FGFR1 (9.8% [7.6-12.1] vs 2.2% [1.1-3.3]), whereas among Europeans the most frequently mutated genes were NF1 (15.9% [13.2-18.6] vs 6.6% [4.7-8.5]) and SDHx (10.7% [8.4-13.0] vs 4.2% [2.6-5.7]). Among Europeans, almost all paragangliomas lacked appreciable production of epinephrine and identified gene mutations were largely restricted to those leading to stabilization of hypoxia inducible factors. In contrast, among Chinese there was a larger proportion of epinephrine-producing paragangliomas, mostly due to HRAS and FGFR1 mutations.

CONCLUSIONS

This study establishes Sino-European differences in the genetic landscape and presentation of PPGLs, including ethnic differences in genotype-phenotype relationships indicating a paradigm shift in our understanding of the biology of these tumors.

Delineation of the Germline and Somatic Mutation Interaction Landscape in Triple-Negative and Non-Triple-Negative Breast Cancer

Background

Breast cancer development and progression involve both germline and somatic mutations. High-throughput genotyping and next-generation sequencing technologies have enabled discovery of genetic risk variants and acquired somatic mutations driving the disease. However, the possible oncogenic interactions between germline genetic risk variants and somatic mutations in triple-negative breast cancer (TNBC) and non-triple-negative breast cancer (non-TNBC) have not been characterized. Here, we delineated the possible oncogenic interactions between genes containing germline and somatic mutations in TNBC and non-TNBC and investigated whether there are differences in gene expression and mutation burden between the two types of breast cancer.

Methods

We addressed this problem by integrating germline mutation information from genome-wide association studies with somatic mutation information from next-generation sequencing using gene expression data as the intermediated phenotype. We performed network and pathway analyses to discover molecular networks and signalling pathways enriched for germline and somatic mutations.

Results

The investigation revealed signatures of differentially expressed and differentially somatic mutated genes between TNBC and non-TNBC. Network and pathway analyses revealed functionally related genes interacting in gene regulatory networks and multiple signalling pathways enriched for germline and somatic mutations for each type of breast cancer. Among the signalling pathways discovered included the DNA repair and Androgen and ATM signalling pathways for TNBC and the DNA damage response, molecular mechanisms of cancer, and ATM and GP6 signalling pathways for non-TNBC.

Conclusions

The results show that integrative genomics is a powerful approach for delineating oncogenic interactions between genes containing germline and genes containing somatic mutations in TNBC and non-TNBC and establishes putative functional bridges between genetic and somatic alterations and the pathways they control in the two types of breast cancer.

Cx43 in Neural Progenitors Promotes Glioma Invasion in a 3D Culture System

The environment that envelops the cancer cells intimately affects the malignancy of human cancers. In the case of glioma, an aggressive adult brain cancer, its high rate of recurrence after total resection is responsible for a poor prognosis. Connexin43 (Cx43) is a gap junction protein with a prominent presence in glioma-associated normal brain cells, specifically in the reactive astrocytes. We previously demonstrated that elimination of Cx43 in these astrocytes reduces glioma invasion in a syngeneic mouse model. To further our investigation in human glioma cells, we developed a scaffold-free 3D platform that takes into account both the tumor and its interaction with the surrounding tissue. Using cell-tracking dyes and 3D laser scanning confocal microscopy, we now report that the elimination of Cx43 protein in neural progenitor spheroids reduced the invasiveness of human brain tumor-initiating cells, confirming our earlier observation in an intact mouse brain. By investigating the glioma invasion in a defined multicellular system with a tumor boundary that mimics the intact brain environment, our findings strengthen Cx43 as a candidate target for glioma control.

Ancestry-specific predisposing germline variants in cancer

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Establishing a Framework for the Clinical Translation of Germline Findings in Precision Oncology

Inherited genetic variation has important implications for cancer screening, early diagnosis, and disease prognosis. A role for germline variation has also been described in shaping the molecular landscape, immune response, microenvironment, and treatment response of individual tumors. However, there is a lack of consensus on the handling and analysis of germline information that extends beyond known or suspected cancer susceptibility in large-scale cancer genomics initiatives. As part of the Personalized OncoGenomics program in British Columbia, we performed whole-genome and transcriptome sequencing in paired tumor and normal tissues from advanced cancer patients to characterize the molecular tumor landscape and identify putative targets for therapy. Overall, our experience supports a multidisciplinary and integrative approach to germline data management. This includes a need for broader definitions and standardized recommendations regarding primary and secondary germline findings in precision oncology. Here, we propose a framework for identifying, evaluating, and returning germline variants of potential clinical significance that may have indications for health management beyond cancer risk reduction or prevention in patients and their families.

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

Cancers harbor many somatic mutations and germline variants, we hypothesized that the combined effect of germline variants that alter the structure, expression, or function of protein-coding regions of cancer-biology related genes (gHFI) determines which and how many somatic mutations (sM) must occur for malignant transformation. We show that gHFI and sM affect overlapping genes and the average number of gHFI in cancer hallmark genes is higher in patients who develop cancer at a younger age (r = -0.77, P = 0.0051), while the average number of sM increases in increasing age groups (r = 0.92, P = 0.000073). A strong negative correlation exists between average gHFI and average sM burden in increasing age groups (r = -0.70, P = 0.017). In early-onset cancers, the larger gHFI burden in cancer genes suggests a greater contribution of germline alterations to the transformation process while late-onset cancers are more driven by somatic mutations.

Identification of host variants associated with overall survival of esophageal cancer patients receiving platinum-based therapy

Aim: Clinical features of esophageal cancer (EC) patients have poor prognostic power. Thus, it is paramount to discover biomarkers that can allow a more accurate survival prediction. Methods: To detect genetic variants associated with survival, DNA from 120 patients treated with cisplatin-based neoadjuvant therapy were genotyped using drug metabolism enzymes and transporters array. Results: We identified two variants: the rs2038067 in PPARD (p = 0.0004) and the rs683369 (F160L) in SLC22A1 (p = 0.001). Their prognostic power was greater than that of clinical stage alone (p = 0.017) and comparable to that of response to neoadjuvant therapy (p = 0.71). Interestingly, the prognostic accuracy of response models increased significantly when genetic variables were included (p = 0.003). Conclusion: Our data, though preliminary, strengthen the potential utility of germline variants for a better-tailored management of EC patients.

The pan-cancer landscape of prognostic germline variants in 10,582 patients

BACKGROUND

While clinical factors such as age, grade, stage, and histological subtype provide physicians with information about patient prognosis, genomic data can further improve these predictions. Previous studies have shown that germline variants in known cancer driver genes are predictive of patient outcome, but no study has systematically analyzed multiple cancers in an unbiased way to identify genetic loci that can improve patient outcome predictions made using clinical factors.

METHODS

We analyzed sequencing data from the over 10,000 cancer patients available through The Cancer Genome Atlas to identify germline variants associated with patient outcome using multivariate Cox regression models.

RESULTS

We identified 79 prognostic germline variants in individual cancers and 112 prognostic germline variants in groups of cancers. The germline variants identified in individual cancers provide additional predictive power about patient outcomes beyond clinical information currently in use and may therefore augment clinical decisions based on expected tumor aggressiveness. Molecularly, at least 12 of the germline variants are likely associated with patient outcome through perturbation of protein structure and at least five through association with gene expression differences. Almost half of these germline variants are in previously reported tumor suppressors, oncogenes or cancer driver genes with the other half pointing to genomic loci that should be further investigated for their roles in cancers.

CONCLUSIONS

Germline variants are predictive of outcome in cancer patients and specific germline variants can improve patient outcome predictions beyond predictions made using clinical factors alone. The germline variants also implicate new means by which known oncogenes, tumor suppressor genes, and driver genes are perturbed in cancer and suggest roles in cancer for other genes that have not been extensively studied in oncology. Further studies in other cancer cohorts are necessary to confirm that germline variation is associated with outcome in cancer patients as this is a proof-of-principle study.

Redefinition of familial intestinal gastric cancer: clinical and genetic perspectives

BACKGROUND

Familial intestinal gastric cancer (FIGC) remains genetically unexplained and without testing/clinical criteria. Herein, we characterised the age of onset and disease spectrum of 50 FIGC families and searched for genetic causes potentially underlying a monogenic or an oligogenic/polygenic inheritance pattern.

METHODS

Normal and tumour DNA from 50 FIGC probands were sequenced using Illumina custom panels on MiSeq, and their respective germline and somatic landscapes were compared with corresponding landscapes from sporadic intestinal gastric cancer (SIGC) and hereditary diffuse gastric cancer cohorts.

RESULTS

The most prevalent phenotype in FIGC families was gastric cancer, detected in 138 of 208 patients (50 intestinal gastric cancer probands and 88 unknown gastric cancer histology relatives), followed by colorectal and breast cancers. After excluding benign and intronic variants lacking impact in splicing, 12 rare high-quality variants were found exclusively in 11 FIGC probands. Only two probands carried potentially deleterious variants, but lacked somatic second-hits, weakly supporting the monogenic hypothesis for FIGC. However, FIGC probands developed gastric cancer at least 10 years earlier and carried more TP53 germline common variants than SIGC (p=4.5E-03); FIGC and SIGC could be distinguished by specific germline and somatic variant profiles; there was an excess of FIGC tumours presenting microsatellite instability (38%); and FIGC tumours displayed significantly more somatic common variants than SIGC tumours (p=4.2E-06).

CONCLUSION

This study proposed the first data-driven testing criteria for FIGC families, and supported FIGC as a genetically determined, likely polygenic, gastric cancer-predisposing disease, with earlier onset and distinct from patients with SIGC at the germline and somatic levels.

A protein-centric approach for exome variant aggregation enables sensitive association analysis with clinical outcomes

Somatic mutations are early drivers of tumorigenesis and tumor progression. However, the mutations typically occur at variable positions across different individuals, resulting in the data being too sparse to test meaningful associations between variants and phenotypes. To overcome this challenge, we devised a novel approach called Gene-to-Protein-to-Disease (GPD) which accumulates variants into new sequence units as the degree of genetic assault on structural or functional units of each protein. The variant frequencies in the sequence units were highly reproducible between two large cancer cohorts. Survival analysis identified 232 sequence units in which somatic mutations had deleterious effects on overall survival, including consensus driver mutations obtained from multiple calling algorithms. By contrast, around 76% of the survival predictive units had been undetected by conventional gene-level analysis. We demonstrate the ability of these signatures to separate patient groups according to overall survival, therefore, providing novel prognostic tools for various cancers. GPD also identified sequence units with somatic mutations whose impact on survival was modified by the occupancy of germline variants in the surrounding regions. The findings indicate that a patient's genetic predisposition interacts with the effect of somatic mutations on survival outcomes in some cancers.

Higher prevalence of homologous recombination deficiency in tumors from African Americans versus European Americans

To improve our understanding of longstanding disparities in incidence and mortality in lung cancer across ancestry, we performed a systematic comparative analysis of molecular features in tumors from African Americans (AAs) and European Americans (EAs). We find that lung squamous cell carcinoma tumors from AAs exhibit higher genomic instability-the proportion of non-diploid genome-aggressive molecular features such as chromothripsis and higher homologous recombination deficiency (HRD). In The Cancer Genome Atlas, we demonstrate that high genomic instability, HRD and chromothripsis among tumors from AAs is found across many cancer types. The prevalence of germline HRD (that is, the total number of pathogenic variants in homologous recombination genes) is higher in tumors from AAs, suggesting that the somatic differences observed have genetic ancestry origins. We also identify AA-specific copy-number-based arm-, focal- and gene-level recurrent features in lung cancer, including higher frequencies of PTEN deletion and KRAS amplification. These results highlight the importance of including under-represented populations in genomics research.

Systems Biology for Multiplatform Data Integration: An Overview

In this chapter, we consider some of the concepts behind multiplatform data integration. First, we examine the types of inferences that can be made using methods that integrate data types. Next, we discuss some broad considerations about methodologies. We conclude with the example of joint analyses of germ line genetic variation, gene expression and complex phenotypes. This chapter draws heavily from analyses that integrate datasets for inference on hereditary aspects of cancer susceptibility. However, these concepts should apply more broadly to other domains.

Integrating germline and somatic genetics to identify genes associated with lung cancer

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex traits. However, GWAS experience power issues, resulting in the failure to detect certain associated variants. Additionally, GWAS are often unable to parse the biological mechanisms of driving associations. An existing gene-based association test framework, Transcriptome-Wide Association Studies (TWAS), leverages expression quantitative trait loci data to increase the power of association tests and illuminate the biological mechanisms by which genetic variants modulate complex traits. We extend the TWAS methodology to incorporate somatic information from tumors. By integrating germline and somatic data we are able to leverage information from the nuanced somatic landscape of tumors. Thus we can augment the power of TWAS-type tests to detect germline genetic variants associated with cancer phenotypes. We use somatic and germline data on lung adenocarcinomas from The Cancer Genome Atlas in conjunction with a meta-analyzed lung cancer GWAS to identify novel genes associated with lung cancer.

Mapping the Germline and Somatic Mutation Interaction Landscape in Indolent and Aggressive Prostate Cancers

BACKGROUND

A majority of prostate cancers (PCas) are indolent and cause no harm even without treatment. However, a significant proportion of patients with PCa have aggressive tumors that progress rapidly to metastatic disease and are often lethal. PCa develops through somatic mutagenesis, but emerging evidence suggests that germline genetic variation can markedly contribute to tumorigenesis. However, the causal association between genetic susceptibility and tumorigenesis has not been well characterized. The objective of this study was to map the germline and somatic mutation interaction landscape in indolent and aggressive tumors and to discover signatures of mutated genes associated with each type and distinguishing the two types of PCa.

MATERIALS AND METHODS

We integrated germline mutation information from genome-wide association studies (GWAS) with somatic mutation information from The Cancer Genome Atlas (TCGA) using gene expression data from TCGA on indolent and aggressive PCas as the intermediate phenotypes. Germline and somatic mutated genes associated with each type of PCa were functionally characterized using network and pathway analysis.

RESULTS

We discovered gene signatures containing germline and somatic mutations associated with each type and distinguishing the two types of PCa. We discovered multiple gene regulatory networks and signaling pathways enriched with germline and somatic mutations including axon guidance, RAR, WINT, MSP-RON, STAT3, PI3K, TR/RxR, and molecular mechanisms of cancer, NF-kB, prostate cancer, GP6, androgen, and VEGF signaling pathways for indolent PCa and MSP-RON, axon guidance, RAR, adipogenesis, and molecular mechanisms of cancer and NF-kB signaling pathways for aggressive PCa.

CONCLUSION

The investigation revealed germline and somatic mutated genes associated with indolent and aggressive PCas and distinguishing the two types of PCa. The study revealed multiple gene regulatory networks and signaling pathways dysregulated by germline and somatic alterations. Integrative analysis combining germline and somatic mutations is a powerful approach to mapping germline and somatic mutation interaction landscape.

The prospect of discovering new biomarkers for ovarian cancer based on current knowledge of susceptibility loci and genetic variation (Review)

Ovarian cancer is the most lethal gynaecological malignancy. The cancer initially presents with non‑specific symptoms; thus, it is typically not discovered until the patient has reached the late, considerably more lethal, stages of the disease. Research focus is currently on finding novel biomarkers, especially for early detection and stratification of the disease. One promising approach has been to focus on mutations or variations in the genetic code that are associated with the risk of developing ovarian cancer. A certain heritable component is already known regarding genes such as BRCA1/2, TP53, MSH6, BRIP1 and RAD51C, yet these are estimated to only account for ~3.1% of the total risk. Recent advances in sequencing technologies have enabled the investigation of hundreds of thousands of genetic variants in genome‑wide association studies in tens of thousands of patients, which has led to the discovery of 108 (39 loci with P<5.0x10‑8) novel susceptibility loci for ovarian cancer, presented in this review. Using the published variants in a patient cohort screening, together with variants identified in our ongoing whole exome sequencing project, future aims are to ascertain whether certain of the novel variants could be used as biomarkers for early diagnosis and/or treatment decisions.

Clonal Evolution of TP53 c.375+1G>A Mutation in Pre- and Post- Neo-Adjuvant Chemotherapy (NACT) Tumor Samples in High-Grade Serous Ovarian Cancer (HGSOC)

Carboplatin/paclitaxel is the reference regimen in the treatment of advanced high-grade serous ovarian cancer (HGSOC) in neo-adjuvant chemotherapy (NACT) before interval debulking surgery (IDS). To identify new genetic markers of platinum-resistance, next-generation sequencing (NGS) analysis of 26 cancer-genes was performed on paired matched pre- and post-NACT tumor and blood samples in a patient with stage IV HGSOC treated with NACT-IDS, showing platinum-refractory/resistance and poor prognosis. Only the TP53 c.375+1G>A somatic mutation was identified in both tumor samples. This variant, associated with aberrant splicing, was in trans configuration with the 72Arg allele of the known germline polymorphism TP53 c.215C>G (p. Pro72Arg). In the post-NACT tumor sample we observed the complete expansion of the TP53 c.375+1G>A driver mutant clone with somatic loss of the treatment-sensitive 72Arg allele. NGS results were confirmed with Sanger method and immunostaining for p53, BRCA1, p16, WT1, and Ki-67 markers were evaluated. This study showed that (i) the splice mutation in TP53 was present as an early driver mutation at diagnosis; (ii) the mutational profile was shared in pre- and post-NACT tumor samples; (iii) the complete expansion of a single dominant mutant clone through loss of heterozygosity (LOH) had occurred, suggesting a possible mechanism of platinum-resistance in HGSOC under the pressure of NACT.

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

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

Polymorphisms of rs4787050 and rs8045980 are associated with lung cancer risk in northeast Chinese female nonsmokers

Aim: We studied the association between two single-nucleotide polymorphisms (SNPs: rs4787050 and rs8045980) in RBFOX1 and lung cancer risk, and explored the interaction between the two SNPs and exposure to cooking oil fume on lung cancer risk in northeast Chinese female nonsmokers. Methods: Northeast Chinese female nonsmokers were enrolled into the study (people with lung cancer, 647; people without lung cancer, 675). All statistical analyses were performed using SPSS software. Results: The SNPs rs4787050 and rs8045980 showed a significant association with susceptibility to lung cancer. Moreover, cooking oil fume exposure was found to increase the risk of lung cancer. However, no gene-environment interactions were discovered. Conclusion: The present study revealed that rs4787050 and rs8045980 in RBFOX1 may be meaningful as a novel biomarker for lung cancer susceptibility.

Rbfox1 up-regulation impairs BDNF-dependent hippocampal LTP by dysregulating TrkB isoform expression levels

Brain-derived neurotrophic factor (BDNF) is a potent modulator of brain synaptic plasticity. Signaling defects caused by dysregulation of its Ntrk2 (TrkB) kinase (TrkB.FL) and truncated receptors (TrkB.T1) have been linked to the pathophysiology of several neurological and neurodegenerative disorders. We found that upregulation of Rbfox1, an RNA binding protein associated with intellectual disability, epilepsy and autism, increases selectively hippocampal TrkB.T1 isoform expression. Physiologically, increased Rbfox1 impairs BDNF-dependent LTP which can be rescued by genetically restoring TrkB.T1 levels. RNA-seq analysis of hippocampi with upregulation of Rbfox1 in conjunction with the specific increase of TrkB.T1 isoform expression also shows that the genes affected by Rbfox1 gain of function are surprisingly different from those influenced by Rbfox1 deletion. These findings not only identify TrkB as a major target of Rbfox1 pathophysiology but also suggest that gain or loss of function of Rbfox1 regulate different genetic landscapes.

Somatic variants of potential clinical significance in the tumors of BRCA phenocopies

BACKGROUND

BRCA phenocopies are individuals with the same phenotype (i.e. cancer consistent with Hereditary Breast and Ovarian Cancer syndrome = HBOC) as their affected relatives, but not the same genotype as assessed by blood germline testing (i.e. they do not carry a germline BRCA1 or BRCA2 mutation). There is some evidence of increased risk for HBOC-related cancers in relatives of germline variant carriers even though they themselves test negative for the familial variant (BRCA non-carriers). At this time, BRCA phenocopies are recommended to undergo the same cancer surveillance as individuals in the general population. This raises the question of whether the increased cancer risk in BRCA non-carriers is due to alterations (germline, somatic or epigenetic) in other cancer-associated genes which were not analyzed during BRCA analysis.

METHODS

To assess the nature and potential clinical significance of somatic variants in BRCA phenocopy tumors, DNA from BRCA non-carrier tumor tissue was analyzed using next generation sequencing of 572 cancer genes. Tumor diagnoses of the 11 subjects included breast, ovarian, endometrial and primary peritoneal carcinoma. Variants were called using FreeBayes genetic variant detector. Variants were annotated for effect on protein sequence, predicted function, and frequency in different populations from the 1000 genomes project, and presence in variant databases COSMIC and ClinVar using Annovar.

RESULTS

None of the familial BRCA1/2 mutations were found in the tumor samples tested. The most frequently occurring somatic gene variants were ROS1(6/11 cases) and NUP98 (5/11 cases). BRCA2 somatic variants were found in 2/6 BRCA1 phenocopies, but 0/5 BRCA2 phenocopies. Variants of uncertain significance were found in other DNA repair genes (ERCC1, ERCC3, ERCC4, FANCD2, PALB2), one mismatch repair gene (PMS2), a DNA demethylation enzyme (TET2), and two histone modifiers (EZH2, SUZ12).

CONCLUSIONS

Although limited by a small sample size, these results support a role of selected somatic variants and epigenetic mechanisms in the development of tumors in BRCA phenocopies.

Rare variant phasing using paired tumor:normal sequence data

Background

In standard high throughput sequencing analysis, genetic variants are not assigned to a homologous chromosome of origin. This process, called haplotype phasing, can reveal information important for understanding the relationship between genetic variants and biological phenotypes. For example, in genes that carry multiple heterozygous missense variants, phasing resolves whether one or both gene copies are altered. Here, we present a novel approach to phasing variants that takes advantage of unique properties of paired tumor:normal sequencing data from cancer studies.

Results

VAF phasing uses changes in variant allele frequency (VAF) between tumor and normal samples in regions of somatic chromosomal gain or loss to phase germline variants. We apply VAF phasing to 6180 samples from the Cancer Genome Atlas (TCGA) and demonstrate that our method is highly concordant with other standard phasing methods, and can phase an average of 33% more variants than other read-backed phasing methods. Using variant annotation tools designed to score gene haplotypes, we find a suggestive association between carrying multiple missense variants in a single copy of a cancer predisposition gene and earlier age of cancer diagnosis.

Conclusions

VAF phasing exploits unique properties of tumor genomes to increase the number of germline variants that can be phased over standard read-backed methods in paired tumor:normal samples. Our phase-informed association testing results call attention to the need to develop more tools for assessing the joint effect of multiple genetic variants.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2753-1) contains supplementary material, which is available to authorized users.

Germline Variants Impact Somatic Events during Tumorigenesis

Cancer is characterized by diverse genetic alterations in both germline and somatic genomes that disrupt normal biology and provide a selective advantage to cells during tumorigenesis. Germline and somatic genomes have been extensively studied independently, leading to numerous biological insights. Analyses integrating data from both genomes have identified genetic variants impacting somatic events in tumors, including hotspot driver mutations. Interactions among specific germline variants and somatic events influence cancer subtypes, treatment response, and clinical outcomes. Investigation of these complex interactions is increasing our understanding of aberrant pathways in tumors that may uncover novel therapeutic targets. Here, we review the literature describing the role of germline genetic variants in promoting the selection and generation of specific mutations during tumorigenesis.

Germline Risk Contribution to Genomic Instability in Multiple Myeloma

Genomic instability, a well-established hallmark of human cancer, is also a driving force in the natural history of multiple myeloma (MM) - a difficult to treat and in most cases fatal neoplasm of immunoglobulin producing plasma cells that reside in the hematopoietic bone marrow. Long recognized manifestations of genomic instability in myeloma at the cytogenetic level include abnormal chromosome numbers (aneuploidy) caused by trisomy of odd-numbered chromosomes; recurrent oncogene-activating chromosomal translocations that involve immunoglobulin loci; and large-scale amplifications, inversions, and insertions/deletions (indels) of genetic material. Catastrophic genetic rearrangements that either shatter and illegitimately reassemble a single chromosome (chromotripsis) or lead to disordered segmental rearrangements of multiple chromosomes (chromoplexy) also occur. Genomic instability at the nucleotide level results in base substitution mutations and small indels that affect both the coding and non-coding genome. Sometimes this generates a distinctive signature of somatic mutations that can be attributed to defects in DNA repair pathways, the DNA damage response (DDR) or aberrant activity of mutator genes including members of the APOBEC family. In addition to myeloma development and progression, genomic instability promotes acquisition of drug resistance in patients with myeloma. Here we review recent findings on the genetic predisposition to myeloma, including newly identified candidate genes suggesting linkage of germline risk and compromised genomic stability control. The role of ethnic and familial risk factors for myeloma is highlighted. We address current research gaps that concern the lack of studies on the mechanism by which germline risk alleles promote genomic instability in myeloma, including the open question whether genetic modifiers of myeloma development act in tumor cells, the tumor microenvironment (TME), or in both. We conclude with a brief proposition for future research directions, which concentrate on the biological function of myeloma risk and genetic instability alleles, the potential links between the germline genome and somatic changes in myeloma, and the need to elucidate genetic modifiers in the TME.

Precision oncology of lung cancer: genetic and genomic differences in Chinese population

Knowledge of the lung cancer genome has experienced rapid growth over the past decade. Genome-wide association studies and sequencing studies have identified dozens of genetic variants and somatic mutations implicated in the development of lung cancer in both Chinese and Caucasian populations. With the accumulating evidence, heterogeneities in lung cancer susceptibility were observed in different ethnicities. In this review, the progress on germline-based genetic variants and somatic-based genomic mutations associated with lung cancer and the differences between Chinese and Caucasian populations were systematically summarized. In the analysis of the genetic predisposition to lung cancer, 6 susceptibility loci were shared by Chinese and Caucasian populations (3q28, 5p15, 6p21, 9p21.3, 12q13.13 and 15q25), 14 loci were specific to the Chinese population (1p36.32, 5q31.1, 5q32, 6p21.1, 6q22.2, 6p21.32, 7p15.3, 10p14, 10q25.2, 12q23.1, 13q22, 17q24.3, 20q13.2, and 22q12), and 12 loci were specific to the Caucasian population (1p31.1, 2q32.1, 6q27, 8p21.1, 8p12, 10q24.3, 11q23.3, 12p13.33, 13q13.1, 15q21.1, 20q13.33 and 22q12.1). In the analysis of genomic and somatic alterations, different mutation rates were observed for EGFR (Chinese: 39–59% vs. TCGA: 14%), KRAS (Chinese: 7–11% vs. TCGA: 31%), TP53 (Chinese: 44% vs. TCGA: 53%), CDKN2A (Chinese: 22% vs. TCGA: 15%), NFE2L2 (Chinese: 28% vs. TCGA: 17%), STK11 (Chinese: 4–7% vs. TCGA: 16%), KEAP1 (Chinese: 3–5% vs. TCGA: 18%), and NF1 (Chinese: <2% vs. TCGA: 12%). In addition, frequently amplified regions encompassing genes involved in cytoskeletal organization or focal adhesion were identified only in Chinese patients. These results provide a comprehensive description of the genetic and genomic differences in lung cancer susceptibility between Chinese and Caucasian populations and may contribute to the development of precision medicine for lung cancer treatment and prevention.

Context-dependent genetic interactions in cancer

Genetic co-dependencies have been found in many contexts, from processes during the development of organisms to many diseases in man, including cancer. Genetic interactions - and in particular synthetic lethal phenotypes - have provided fundamental insights into the genetic architecture of cells and identified potential new opportunities for therapeutic interventions. However, recent studies also demonstrated that genetic interactions are highly context dependent and synthetic lethal interactions in one tumor context might not be translatable to others. Therefore, to better define and understand contexts will be a key challenge for future studies to fully exploit genetic interaction networks for target identification and cancer therapy. In this review, we summarize recent developments in mapping context-specific genetic interaction networks with a particular focus on conceptual and experimental advances in the past years. We then discuss genetic and environmental contexts that influence genetic interaction networks. Finally, we outline challenges of putting genetic interaction networks into context and give an outlook on future directions.

Precision Radiotherapy and Radiation Risk Assessment: How Do We Overcome Radiogenomic Diversity?

Precision medicine is a rapidly developing area that aims to deliver targeted therapies based on individual patient characteristics. However, current radiation treatment is not yet personalized; consequently, there is a critical need for specific patient characteristics of both tumor and normal tissues to be fully incorporated into dose prescription. Furthermore, current risk assessment following environmental, occupational, or accidental exposures to radiation is based on population effects, and does not account for individual diversity underpinning radiosensitivity. The lack of personalized approaches in both radiotherapy and radiation risk assessment resulted in the current situation where a population-based model, effective dose, is being used. In this review article, to stimulate scientific discussion for precision medicine in both radiotherapy and radiation risk assessment, we propose a novel radiological concept and metric - the personalized dose and the personalized risk index - that incorporate individual physiological, lifestyle-related and genomic variations and radiosensitivity, outlining the potential clinical application for precision medicine. We also review on recent progress in both genomics and biobanking research, which is promising for providing novel insights into individual radiosensitivity, and for creating a novel conceptual framework of precision radiotherapy and radiation risk assessment.

A natural WNT signaling variant potently synergizes with Cdkn2ab loss in skin carcinogenesis

Cdkn2ab knockout mice, generated from 129P2 ES cells develop skin carcinomas. Here we show that the incidence of these carcinomas drops gradually in the course of backcrossing to the FVB/N background. Microsatellite analyses indicate that this cancer phenotype is linked to a 20 Mb region of 129P2 chromosome 15 harboring the Wnt7b gene, which is preferentially expressed from the 129P2 allele in skin carcinomas and derived cell lines. ChIPseq analysis shows enrichment of H3K27-Ac, a mark for active enhancers, in the 5' region of the Wnt7b 129P2 gene. The Wnt7b 129P2 allele appears sufficient to cause in vitro transformation of Cdkn2ab-deficient cell lines primarily through CDK6 activation. These results point to a critical role of the Cdkn2ab locus in keeping the oncogenic potential of physiological levels of WNT signaling in check and illustrate that GWAS-based searches for cancer predisposing allelic variants can be enhanced by including defined somatically acquired lesions as an additional input.

Integrating Germline and Somatic Mutation Information for the Discovery of Biomarkers in Triple-Negative Breast Cancer

Recent advances in high-throughput genotyping and the recent surge of next generation sequencing of the cancer genomes have enabled discovery of germline mutations associated with an increased risk of developing breast cancer and acquired somatic mutations driving the disease. Emerging evidence indicates that germline mutations may interact with somatic mutations to drive carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic alterations in triple-negative breast cancer (TNBC) have not been characterized. The objective of this study was to investigate the possible oncogenic interactions and cooperation between genes containing germline and somatic mutations in TNBC. Our working hypothesis was that genes containing germline mutations associated with an increased risk developing breast cancer also harbor somatic mutations acquired during tumorigenesis, and that these genes are functionally related. We further hypothesized that TNBC originates from a complex interplay among and between genes containing germline and somatic mutations, and that these complex array of interacting genetic factors affect entire molecular networks and biological pathways which in turn drive the disease. We tested this hypothesis by integrating germline mutation information from genome-wide association studies (GWAS) with somatic mutation information on TNBC from The Cancer Genome Atlas (TCGA) using gene expression data from 110 patients with TNBC and 113 controls. We discovered a signature of 237 functionally related genes containing both germline and somatic mutations. We discovered molecular networks and biological pathways enriched for germline and somatic mutations. The top pathways included the hereditary breast cancer and role of BRCA1 in DNA damage response signaling pathways. In conclusion, this is the first large-scale and comprehensive analysis delineating possible oncogenic interactions and cooperation among and between genes containing germline and somatic mutations in TNBC. Genetic and somatic mutations, along with the genes discovered in this study, will require experimental functional validation in different ethnic populations. Functionally validated genetic and somatic variants will have important implications for the development of novel precision prevention strategies and discovery of prognostic markers in TNBC.

Interactions between Germline and Somatic Mutated Genes in Aggressive Prostate Cancer

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the USA. Advances in high-throughput genotyping and next generation sequencing technologies have enabled discovery of germline genetic susceptibility variants and somatic mutations acquired during tumor formation. Emerging evidence indicates that germline variations may interact with somatic events in carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic variation and their role in aggressive PCa remain largely unexplored. Here we investigated the possible oncogenic interactions and cooperation between genes containing germline variation from genome-wide association studies (GWAS) and genes containing somatic mutations from tumor genomes of 305 men with aggressive tumors and 52 control samples from The Cancer Genome Atlas (TCGA). Network and pathway analysis were performed to identify molecular networks and biological pathways enriched for germline and somatic mutations. The analysis revealed 90 functionally related genes containing both germline and somatic mutations. Transcriptome analysis revealed a 61-gene signature containing both germline and somatic mutations. Network analysis revealed molecular networks of functionally related genes and biological pathways including P53, STAT3, NKX3-1, KLK3, and Androgen receptor signaling pathways enriched for germline and somatic mutations. The results show that integrative analysis is a powerful approach to uncovering the possible oncogenic interactions and cooperation between germline and somatic mutations and understanding the broader biological context in which they operate in aggressive PCa.

Integrating germline and somatic variation information using genomic data for the discovery of biomarkers in prostate cancer

BACKGROUND

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the United States. High-throughput genotyping has enabled discovery of germline genetic susceptibility variants (herein referred to as germline mutations) associated with an increased risk of developing PCa. However, germline mutation information has not been leveraged and integrated with information on acquired somatic mutations to link genetic susceptibility to tumorigenesis. The objective of this exploratory study was to address this knowledge gap.

METHODS

Germline mutations and associated gene information were derived from genome-wide association studies (GWAS) reports. Somatic mutation and gene expression data were derived from 495 tumors and 52 normal control samples obtained from The Cancer Genome Atlas (TCGA). We integrated germline and somatic mutation information using gene expression data. We performed enrichment analysis to discover molecular networks and biological pathways enriched for germline and somatic mutations.

RESULTS

We discovered a signature of 124 genes containing both germline and somatic mutations. Enrichment analysis revealed molecular networks and biological pathways enriched for germline and somatic mutations, including, the PDGF, P53, MYC, IGF-1, PTEN and Androgen receptor signaling pathways.

CONCLUSION

Integrative genomic analysis links genetic susceptibility to tumorigenesis in PCa and establishes putative functional bridges between the germline and somatic variation, and the biological pathways they control.

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients' response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439.

Germline genetic variants in somatically significantly mutated genes in tumors are associated with renal cell carcinoma risk and outcome

Genome-wide association studies (GWAS) have identified 13 susceptibility loci for renal cell carcinoma (RCC). Additional genetic loci of risk remain to be explored. Moreover, the role of germline genetic variants in predicting RCC recurrence and overall survival (OS) is less understood. In this study, we focused on 127 significantly mutated genes from The Cancer Genome Atlas (TCGA) Pan-Cancer Analysis across 12 major cancer sites to identify potential genetic variants predictive of RCC risk and clinical outcomes. In a three-phase design with a total of 2657 RCC cases and 5315 healthy controls, two single nucleotide polymorphisms (SNPs) that map to PIK3CG (rs6466135:A, ORmeta = 0.85, 95% CI = 0.77-0.94, Pmeta = 1.4 × 10-3) and ATM (rs611646:T, ORmeta = 1.17, 95% CI = 1.05-1.31, Pmeta = 3.5 × 10-3) were significantly associated with RCC risk. With respect to RCC recurrence and OS, two separate datasets with a total of 661 stages I-III RCC patients (discovery: 367; validation: 294) were analyzed. The most significant association was observed for rs10932384:C (ERBB4) with both outcomes (recurrence: HRmeta = 0.52, 95% CI = 0.39-0.68, Pmeta = 3.81 × 10-6; OS: HRmeta = 0.50, 95% CI = 0.37-0.67, Pmeta = 6.00 × 10-6). In addition, six SNPs were significantly associated with either RCC recurrence or OS but not both (Pmeta < 0.01). Rs10932384:C was significantly correlated with mutation frequency of ERBB4 in clear cell RCC (ccRCC) patients (P = 0.003, Fisher's exact test). Cis-eQTL was observed for several SNPs in blood/transformed fibroblasts but not in RCC tumor tissues. In summary, we identified promising genetic predictors of recurrence and OS among RCC patients with localized disease.

The Germline Variants rs61757955 and rs34988193 Are Predictive of Survival in Lower Grade Glioma Patients

Lower grade gliomas are invasive brain tumors that are difficult to completely resect neurosurgically. They often recur following resection and progress, resulting in death. Although previous studies have shown that specific germline variants increase the risk of tumor formation, no previous study has screened many germline variants to identify variants predictive of survival in patients with glioma. In this study, we present an approach to identify the small fraction of prognostic germline variants from the pool of over four million variants that we variant called in The Cancer Genome Atlas whole-exome sequencing and RNA sequencing datasets. We identified two germline variants that are predictive of poor patient outcomes by Cox regression, controlling for eleven covariates. rs61757955 is a germline variant found in the 3' UTR of GRB2 associated with increased KRAS signaling, CIC mutations, and 1p/19q codeletion. rs34988193 is a germline variant found in the tumor suppressor gene ANKDD1a that causes an amino acid change from lysine to glutamate. This variant was found to be predictive of poor prognosis in two independent lower grade glioma datasets and is predicted to be within the top 0.06% of deleterious mutations across the human genome. The wild-type residue is conserved in all 22 other species with a homologous protein. IMPLICATIONS: This is the first study presenting an approach to screening many germline variants to identify variants predictive of survival and our application of this methodology revealed the germline variants rs61757955 and rs34988193 as being predictive of survival in patients with lower grade glioma.

Time-resolved mapping of genetic interactions to model rewiring of signaling pathways

Context-dependent changes in genetic interactions are an important feature of cellular pathways and their varying responses under different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic interaction networks over time or in response to external stresses are largely lacking. To analyze the plasticity of genetic interactions, we performed a combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to end-point assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

Integrated Analysis of Genetic Ancestry and Genomic Alterations across Cancers

Disparities in cancer care have been a long-standing challenge. We estimated the genetic ancestry of The Cancer Genome Atlas patients, and performed a pan-cancer analysis on the influence of genetic ancestry on genomic alterations. Compared with European Americans, African Americans (AA) with breast, head and neck, and endometrial cancers exhibit a higher level of chromosomal instability, while a lower level of chromosomal instability was observed in AAs with kidney cancers. The frequencies of TP53 mutations and amplification of CCNE1 were increased in AAs in the cancer types showing higher levels of chromosomal instability. We observed lower frequencies of genomic alterations affecting genes in the PI3K pathway in AA patients across cancers. Our result provides insight into genomic contribution to cancer disparities.

Evolutionary Pressure against MHC Class II Binding Cancer Mutations

The anti-cancer immune response against mutated peptides of potential immunological relevance (neoantigens) is primarily attributed to MHC-I-restricted cytotoxic CD8+ T cell responses. MHC-II-restricted CD4+ T cells also drive anti-tumor responses, but their relation to neoantigen selection and tumor evolution has not been systematically studied. Modeling the potential of an individual's MHC-II genotype to present 1,018 driver mutations in 5,942 tumors, we demonstrate that the MHC-II genotype constrains the mutational landscape during tumorigenesis in a manner complementary to MHC-I. Mutations poorly bound to MHC-II are positively selected during tumorigenesis, even more than mutations poorly bound to MHC-I. This emphasizes the importance of CD4+ T cells in anti-tumor immunity. In addition, we observed less inter-patient variation in mutation presentation for MHC-II than for MHC-I. These differences were reflected by age at diagnosis, which was correlated with presentation by MHC-I only. Collectively, our results emphasize the central role of MHC-II presentation in tumor evolution.

Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer

Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations^1-6. cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas^7,8. We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification¹. This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology.

Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas

BACKGROUND

Cancer susceptibility germline variants generally require somatic alteration of the remaining allele to drive oncogenesis and, in some cases, tumor mutational profiles. Whether combined germline and somatic bi-allelic alterations are universally required for germline variation to influence tumor mutational profile is unclear. Here, we performed an exome-wide analysis of the frequency and functional effect of bi-allelic alterations in The Cancer Genome Atlas (TCGA).

METHODS

We integrated germline variant, somatic mutation, somatic methylation, and somatic copy number loss data from 7790 individuals from TCGA to identify germline and somatic bi-allelic alterations in all coding genes. We used linear models to test for association between mono- and bi-allelic alterations and somatic microsatellite instability (MSI) and somatic mutational signatures.

RESULTS

We discovered significant enrichment of bi-allelic alterations in mismatch repair (MMR) genes and identified six bi-allelic carriers with elevated MSI, consistent with Lynch syndrome. In contrast, we find little evidence of an effect of mono-allelic germline variation on MSI. Using MSI burden and bi-allelic alteration status, we reclassify two variants of unknown significance in MSH6 as potentially pathogenic for Lynch syndrome. Extending our analysis of MSI to a set of 127 DNA damage repair (DDR) genes, we identified a novel association between methylation of SHPRH and MSI burden.

CONCLUSIONS

We find that bi-allelic alterations are infrequent in TCGA but most frequently occur in BRCA1/2 and MMR genes. Our results support the idea that bi-allelic alteration is required for germline variation to influence tumor mutational profile. Overall, we demonstrate that integrating germline, somatic, and epigenetic alterations provides new understanding of somatic mutational profiles.

Cancer expression quantitative trait loci (eQTLs) can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity

Expression quantitative trait loci (eQTLs) identified using tumor gene expression data could affect gene expression in cancer cells, tumor-associated normal cells, or both. Here, we have demonstrated a method to identify eQTLs affecting expression in cancer cells by modeling the statistical interaction between genotype and tumor purity. Only one third of breast cancer risk variants, identified as eQTLs from a conventional analysis, could be confidently attributed to cancer cells. The remaining variants could affect cells of the tumor microenvironment, such as immune cells and fibroblasts. Deconvolution of tumor eQTLs will help determine how inherited polymorphisms influence cancer risk, development, and treatment response.

Germline genetic variants were interactively associated with somatic alterations in gastric cancer

Genome-wide association studies have identified several germline variants in gastric cancer. Meanwhile, sequencing studies have characterized extensive somatic alterations that arise during gastric carcinogenesis. However, the relationship between the germline variants and somatic alterations is still unclear in gastric cancer. A total of 11 susceptibility loci and 276 driver genes of gastric cancer were determined based on previous studies and publicly available database. An enrichment analysis was made to detect whether driver genes were enriched in susceptibility regions. Besides, we performed a pathway enrichment analysis to find common-enrich pathways of cancer driver genes and susceptibility genes. Finally, on the basis of the gastric cancer samples and data from TCGA STAD project, we evaluated the associations between susceptibility loci and somatic alterations. Enrichment analysis showed that gastric cancer susceptibility genes were more likely to be enriched in driver genes than in all the genes (P = .05). The susceptibility genes and driver genes were commonly enriched in 8 biological pathways. Gastric cancer susceptibility locus of rs2285947 was associated with truncation mutation within Signaling by PDGF pathway (OR = 0.26, 95%CI: 0.12-0.55, P = 3.93 × 10-4 ). The rs1679709 was connected with COSMIC Signature15 (P = .026). Moreover, rs1679709 was also associated with copy number values of RFC4 which is related to Signature15. These results provide evidence for the relationship between germline variants and somatic alterations, which facilitate understanding the interactive mechanism of germline variations with somatic alterations in gastric cancer development.

The Making of a PreCancer Atlas: Promises, Challenges, and Opportunities

Many cancers evolve from benign precancerous lesions and have a natural history of progression that provides a window of opportunity for intervention. The biological mechanisms underlying this evolutionary trajectory can only be truly understood through an extensive characterization of the molecular, cellular, and non-cellular properties of premalignant and malignant tumors, and must also recognize how the microenvironment (stromal cells, immune cells, and other types of cells) contributes to this evolution. We describe here the need to develop comprehensive molecular and cellular atlases for organ-specific premalignant lesions while capturing the spatial, structural, and functional changes over time that will provide a greater understanding of how premalignancy transitions to malignancy. The PreCancer Atlas (PCA) initiative, described in this Opinion, will address this need and aims to overcome the many challenges that currently plague the field. The hope is that PCAs will lead to the development of effective and timely interventions to prevent the development of invasive cancers.

Modelling glioma invasion using 3D bioprinting and scaffold-free 3D culture

Glioma is a highly aggressive form of brain cancer, with some subtypes having 5-year survival rates of less than 5%. Tumour cell invasion into the surrounding parenchyma seems to be the primary driver of these poor outcomes, as most gliomas recur within 2 cm of the original surgically-resected tumour. Many current approaches to the development of anticancer therapy attempt to target genetic weaknesses in a particular cancer, but may not take into account the microenvironment experienced by a tumour and the patient-specific genetic differences in susceptibility to treatment. Here we demonstrate the use of complementary approaches, 3D bioprinting and scaffold-free 3D tissue culture, to examine the invasion of glioma cells into neural-like tissue with 3D confocal microscopy. We found that, while both approaches were successful, the use of 3D tissue culture for organoid development offers the advantage of broad accessibility. As a proof-of-concept of our approach, we developed a system in which we could model the invasion of human glioma cells into mouse neural progenitor cell-derived spheroids. We show that we can follow invasion of human tumour cells using cell-tracking dyes and 3D laser scanning confocal microscopy, both in real time and in fixed samples. We validated these results using conventional cryosectioning. Our scaffold-free 3D approach has broad applicability, as we were easily able to examine invasion using different neural progenitor cell lines, thus mimicking differences that might be observed in patient brain tissue. These results, once applied to iPSC-derived cerebral organoids that incorporate the somatic genetic variability of patients, offer the promise of truly personalized treatments for brain cancer.

Genetic Modifiers of the Breast Tumor Microenvironment

Multiple nonmalignant cell types in the tumor microenvironment (TME) impact breast cancer risk, metastasis, and response to therapy, yet most heritable mechanisms that influence TME cell function and breast cancer outcomes are largely unknown. Breast cancer risk is ∼30% heritable and >170 genetic loci have been associated with breast cancer traits. However, the majority of candidate genes have poorly defined mechanistic roles in breast cancer biology. Research indicates that breast cancer risk modifiers directly impact cancer cells, yet it is equally plausible that some modifier alleles impact the nonmalignant TME. The objective of this review is to examine the list of current breast cancer candidate genes that may modify breast cancer risk and outcome through the TME.