Germline Variants That Affect Tumor Progression

Whole-exome sequencing reveals an association of rs112065068 in TGOLN2 gene with distant metastasis of non-small cell lung cancer

Early prediction and prevention of recurring illness is critical for improving the survival rates of patients with non-small cell lung cancer (NSCLC). Previously, we demonstrated that the presence of premalignant epithelial changes in the small bronchi distant to the primary tumor is associated with NSCLC progression: isolated basal cell hyperplasia (iBCH) indicates a high risk of distant metastasis, BCH combined with squamous metaplasia (BCHSM) - a high risk of locoregional recurrence. Here, we aimed to identify germline single nucleotide variants (SNVs) and insertions and deletions (InDels) associated with distant metastasis and locoregional recurrence in cases with iBCH and BCHSM using whole-exome sequencing of 172 NSCLC patients. The rs112065068 of the TGOLN2 gene was identified only in iBCH patients and was associated with a high risk of distant metastasis (P < .001) and worse metastasis-free survival (HR = 4.19 (95 %CI 1.97-8.93); P < .001). This variant was validated in a group of 109 NSCLC patients using real-time PCR and Sanger sequencing analyses. To our knowledge, this study is the first to identify a germline variant associated with NSCLC distant metastasis.

Meeting proceedings of the 43rd Indian Association for Cancer Research (IACR)

The 43rd Annual Conference of the Indian Association of Cancer Research (IACR) was held between 19th and 22nd January 2024 at the Indian Institute of Education and Research (IISER), Pune, India. Cancer is the second leading cause of death globally; efforts have been made to understand and treat this deadly disease for several decades. The 43rd IACR, organised by Mayurika Lahiri, Kundan Sengupta, Nagaraj Balasubramanian, Mridula Nambiar, Krishanpal Karmodiya, and Siddhesh Kamat, highlighted recent advances in cancer research, with implications in therapeutics at the forefront of the discussions. The meeting proved to be a promising platform for cancer researchers ranging from graduate and postdoctoral students to subject experts in varied aspects of cancer biology to showcase their research, ideate with their peers, and form collaborations.

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.

Serum micro-RNAs with mutation-targeted RNA modification: a potent cancer detection tool constructed using an optimized machine learning workflow

RNA modifications affect fundamental biological processes and diseases and are a research hotspot. Several micro-RNAs (miRNAs) exhibit genetic variant-targeted RNA modifications that can greatly alter their biofunctions and influence their effect on cancer. Therefore, the potential role of these miRNAs in cancer can be implicated in new prevention and treatment strategies. In this study, we determined whether RMvar-related miRNAs were closely associated with tumorigenesis and identified cancer-specific signatures based on these miRNAs with variants targeting RNA modifications using an optimized machine learning workflow. An effective machine learning workflow, combining least absolute shrinkage and selection operator analyses, recursive feature elimination, and nine types of machine learning algorithms, was used to screen candidate miRNAs from 504 serum RMvar-related miRNAs and construct a diagnostic signature for cancer detection based on 43,047 clinical samples (with an area under the curve value of 0.998, specificity of 93.1%, and sensitivity of 99.3% in the validation cohort). This signature demonstrated a satisfactory diagnostic performance for certain cancers and different conditions, including distinguishing early-stage tumors. Our study revealed the close relationship between RMvar-related miRNAs and tumors and proposed an effective cancer screening tool.

Exploring the Role of Non-synonymous and Deleterious Variants Identified in Colorectal Cancer: A Multi-dimensional Computational Scrutiny of Exomes

Introduction

Colorectal cancers are the world's third most commonly diagnosed type of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes of cancers reveals potential variation data that can be used for early disease prognosis.

Methods

By utilizing a comprehensive computational investigation, the present study aimed to reveal mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes were retrieved. Quality control assessments were performed using FastQC and MultiQC, gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous, start loss and stop gain mutations as well as marked them as possibly damaging, probably damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations and associated genes, for which the downstream multi-dimensional expression analyses were carried out.

Results

Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms bring about a functional alteration to the phenotype. The top variations associated with their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1, OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream analysis of all these genes in terms of gene expression profiling and analysis and differential gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed and overregulated genes in colorectal cancer.

Conclusion

Our work provides insights into the various alterations that might possibly lead to colorectal cancer and suggests the possibility of utilizing the most important genes identified for wet-lab experimentation.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Comparing variants related to chronic diseases from genome-wide association study (GWAS) and the cancer genome atlas (TCGA)

BACKGROUND

Several genome-wide association studies (GWAS) have been performed to identify variants related to chronic diseases. Somatic variants in cancer tissues are associated with cancer development and prognosis. Expression quantitative trait loci (eQTL) and methylation QTL (mQTL) analyses were performed on chronic disease-related variants in TCGA dataset.

METHODS

MuTect2 calling variants for 33 cancers from TCGA and 296 GWAS variants provided by LocusZoom were used. At least one mutation was found in TCGA 22 cancers and LocusZoom 23 studies. Differentially expressed genes (DEGs) and differentially methylated regions (DMRs) from the three cancers (TCGA-COAD, TCGA-STAD, and TCGA-UCEC). Variants were mapped to the world map using population locations of the 1000 Genomes Project (1GP) populations. Decision tree analysis was performed on the discovered features and survival analysis was performed according to the cluster.

RESULTS

Based on the DEGs and DMRs with clinical data, the decision tree model classified seven and three nodes in TCGA-COAD and TCGA-STAD, respectively. A total of 11 variants were commonly detected from TCGA and LocusZoom, and eight variants were selected from the 1GP variants, and the distribution patterns were visualized on the world map.

CONCLUSIONS

Variants related to tumors and chronic diseases were selected, and their geological regional 1GP-based proportions are presented. The variant distribution patterns could provide clues for regional clinical trial designs and personalized medicine.

Prevalence and Landscape of Pathogenic or Likely Pathogenic Germline Variants and Their Association With Somatic Phenotype in Unselected Chinese Patients With Gynecologic Cancers

Importance

Understanding germline and somatic status in patients with gynecologic cancers could improve risk assessment and guide therapeutic decision-making.

Objective

To evaluate the prevalence and landscape of germline pathogenic or likely pathogenic (P/LP) variants and explore whether these variants are associated with somatic phenotypes and cancer risk in unselected patients with gynecologic cancers.

Design, Setting, and Participants

This cross-sectional study retrospectively enrolled unselected patients in China with a gynecologic cancer, including ovarian, cervical, and endometrial, who underwent tumor-normal sequencing using a 520-gene panel from October 1, 2017, through May 31, 2021.

Exposure

Germline variants in gynecologic cancers.

Main Outcomes and Measures

The P/LP germline variant rates in 62 cancer predisposition genes were assessed using descriptive statistics. The associations of P/LP variant status with age, somatic profiles, and cancer risk were also investigated using the Fisher exact test or Student t test.

Results

A total of 1610 women (median [IQR] age, 54 [47-62] years; 1201 [74.6%] with stage III-IV disease) were included (945 with ovarian cancer, 307 with endometrial cancer, and 358 with cervical cancer). The prevalence of patients with P/LP variants was 20.5% (194 of 945) for ovarian cancer, 13.4% (41 of 307) for endometrial cancer, and 6.4% (23 of 358) for cervical cancer; 95.1% of the germline findings (n = 252) were potentially actionable, mainly in homologous recombination repair (HRR) and mismatch repair genes. Chinese patients with endometrial cancer had a higher rate of P/LP variants than a White population from The Cancer Genome Atlas (42 of 307 [13.7%] vs 24 of 367 [6.5%]; P = .003). In endometrial and cervical cancers, the prevalence of P/LP variants was 12.7% (30 of 237) and 4.8% (13 of 270), respectively, in patients diagnosed at age 45 years or older and increased to 25.0% (9 of 36; P = .09) and 12.0% (10 of 83; P = .04), respectively, for those with an onset age of less than 45 years. Mismatch repair P/LP variants were associated with a younger age at onset for ovarian cancer (46 vs 54 years; P = .02) and endometrial cancer (48 vs 57 years; P < .001), while HRR P/LP variants were associated with a younger age at onset for cervical cancer (46 vs 52 years; P = .04). Carriers of HRR P/LP variants had more prevalent somatic TP53 variants and less common somatic variants in oncogenic driver genes vs noncarriers. BRCA1/2 P/LP variants were also associated with moderate risks for endometrial and cervical cancer.

Conclusions and Relevance

This study delineates the landscape of germline P/LP variants in Chinese women with gynecologic cancers. The findings highlight the hereditary factor in cervical cancer that has long been neglected and suggest the importance of next-generation sequencing-based genetic testing with a large gene panel for gynecologic cancers.

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

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

SIGNIFICANCE

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

An integrated somatic and germline approach to aid interpretation of germline variants of uncertain significance in cancer susceptibility genes

Genomic profiles of tumors are often unique and represent characteristic mutational signatures defined by DNA damage or DNA repair response processes. The tumor-derived somatic information has been widely used in therapeutic applications, but it is grossly underutilized in the assessment of germline genetic variants. Here, we present a comprehensive approach for evaluating the pathogenicity of germline variants in cancer using an integrated interpretation of somatic and germline genomic data. We have previously demonstrated the utility of this integrated approach in the reassessment of pathogenic germline variants in selected cancer patients with unexpected or non-syndromic phenotypes. The application of this approach is presented in the assessment of rare variants of uncertain significance (VUS) in Lynch-related colon cancer, hereditary paraganglioma-pheochromocytoma syndrome, and Li-Fraumeni syndrome. Using this integrated method, germline VUS in PMS2, MSH6, SDHC, SHDA, and TP53 were assessed in 16 cancer patients after genetic evaluation. Comprehensive clinical criteria, somatic signature profiles, and tumor immunohistochemistry were used to re-classify VUS by upgrading or downgrading the variants to likely or unlikely actionable categories, respectively. Going forward, collation of such germline variants and creation of cross-institutional knowledgebase datasets that include integrated somatic and germline data will be crucial for the assessment of these variants in a larger cancer cohort.

Integrated bioinformatic pipeline using whole-exome and RNAseq data to identify germline variants correlated with cancer

Germline Variants (GVs) are effective in predicting cancer risk and may be relevant in predicting patient outcomes. Here we provide a bioinformatic pipeline to identify GVs from the TCGA lower grade glioma cohort in Genomics Data Commons. We integrate paired whole exome sequences from normal and tumor samples and RNA sequences from tumor samples to determine a patient’s GV status. We then identify the subset of GVs that are predictive of patient outcomes by Cox regression.

For complete details on the use and execution of this protocol, please refer to Chatrath et al. (2019) and Chatrath et al. (2020).

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Integration of whole-exome and RNA sequences to determine Germline Variants (GVs)

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Whole-exome and RNA sequences from tumors resolve low coverage issue in normal samples

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High correlation of GV allele frequencies between patient data and the GnomAD database

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GVs predict patient cancer outcome

Clinical application of liquid biopsy in cancer patients

Background

This study was to determine the prevalence and clinical significance of clonal hematopoiesis (CH)-related variants, and somatic and germline mutations in cancer patients and healthy individuals.

Methods

We performed next-generation sequencing of 275 cancer-related genes be-tween plasma and white blood cells in 92 cancer patients and 47 controls without cancer. Blood samples were recruited from May 2017 to July 2021, and blood cancer patients were excluded. For all statistical analysis in this study, p < 0.05 was considered statistically significant.

Results

Overall, 38.04% of patients and 46.81% of controls harbored at least one CH-related mutation in plasma cell-free DNA. Based on our results, older cancer patients exhibited a CH phenomenon more frequently than younger patients (p = 0.0024). A total of 39 somatic pathogenic (P)/likely pathogenic (LP) mutations were identified in 17 genes in 21 of 92 patients. We found that the presence of P/LP variants in cancer-related gene predicted shorter overall survival (OS) (p = 0.001). Multivariate analysis adjusted for CH-related mutations, germline mutations, and tumor stage, also indicated that somatic mutations correlated significantly with OS (p = 0.022). Moreover, the frequency of a germline P/LP variant was that of seven of 92 individuals in the cancer group and one of 42 individuals in the control group.

Conclusions

We characterized the CH-related variants, and somatic and germline mutations in cancer patients and healthy individuals, and the results have important clinical significance.

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

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

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.