Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors.
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ABSTRACT:
SUBMITTER: Sayaman RW
PROVIDER: S-EPMC9772839 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
Publications
Analytic pipelines to assess the relationship between immune response and germline genetics in human tumors.
Sayaman Rosalyn W RW Saad Mohamad M Heimann Carolina C Hu Donglei D Kunji Khalid K Roelands Jessica J Wolf Denise M DM Huntsman Scott S Ceccarelli Michele M Thorsson Vésteinn V Ziv Elad E Bedognetti Davide D
STAR protocols 20221214 4
Germline genetic variants modulate human immune response. We present analytical pipelines for assessing the contribution of hosts' genetic background to the immune landscape of solid tumors using harmonized data from more than 9,000 patients in The Cancer Genome Atlas (TCGA). These include protocols for heritability, genome-wide association studies (GWAS), colocalization, and rare variant analyses. These workflows are developed around the structure of TCGA but can be adapted to explore other rep ...[more]
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Project description:BackgroundBenchmarking the performance of complex analytical pipelines is an essential part of developing Lab Developed Tests (LDT). Reference samples and benchmark calls published by Genome in a Bottle (GIAB) consortium have enabled the evaluation of analytical methods. The performance of such methods is not uniform across the different genomic regions of interest and variant types. Several benchmarking methods such as hap.py, vcfeval, and vcflib are available to assess the analytical performance characteristics of variant calling algorithms. However, assessing the performance characteristics of an overall LDT assay still requires stringing together several such methods and experienced bioinformaticians to interpret the results. In addition, these methods are dependent on the hardware, operating system and other software libraries, making it impossible to reliably repeat the analytical assessment, when any of the underlying dependencies change in the assay. Here we present a scalable and reproducible, cloud-based benchmarking workflow that is independent of the laboratory and the technician executing the workflow, or the underlying compute hardware used to rapidly and continually assess the performance of LDT assays, across their regions of interest and reportable range, using a broad set of benchmarking samples.ResultsThe benchmarking workflow was used to evaluate the performance characteristics for secondary analysis pipelines commonly used by Clinical Genomics laboratories in their LDT assays such as the GATK HaplotypeCaller v3.7 and the SpeedSeq workflow based on FreeBayes v0.9.10. Five reference sample truth sets generated by Genome in a Bottle (GIAB) consortium, six samples from the Personal Genome Project (PGP) and several samples with validated clinically relevant variants from the Centers for Disease Control were used in this work. The performance characteristics were evaluated and compared for multiple reportable ranges, such as whole exome and the clinical exome.ConclusionsWe have implemented a benchmarking workflow for clinical diagnostic laboratories that generates metrics such as specificity, precision and sensitivity for germline SNPs and InDels within a reportable range using whole exome or genome sequencing data. Combining these benchmarking results with validation using known variants of clinical significance in publicly available cell lines, we were able to establish the performance of variant calling pipelines in a clinical setting.
| S-EPMC7903625 | biostudies-literature
Project description:The outbreak of coronavirus disease 2019 (COVID-19) was caused by the newly emerged corona virus (2019-nCoV alias SARS-CoV-2) that resembles the severe acute respiratory syndrome virus (SARS-CoV). SARS-CoV-2, which was first identified in Wuhan (China) has spread globally, resulting in a high mortality worldwide reaching ~4 million deaths to date. As of first week of July 2021, ~181 million cases of COVID-19 have been reported. SARS-CoV-2 infection is mediated by the binding of virus spike protein to Angiotensin Converting Enzyme 2 (ACE2). ACE2 is expressed on many human tissues; however, the major entry point is probably pneumocytes, which are responsible for synthesis of alveolar surfactant in lungs. Viral infection of pneumocytes impairs immune responses and leads to, apart from severe hypoxia resulting from gas exchange, diseases with serious complications. During viral infection, gene products (e.g. ACE2) that mediate viral entry, antigen presentation, and cellular immunity are of crucial importance. Human leukocyte antigens (HLA) I and II present antigens to the CD8+ and CD4+ T lymphocytes, which are crucial for immune defence against pathogens including viruses. HLA gene variants affect the recognition and presentation of viral antigenic peptides to T-cells, and cytokine secretion. Additionally, endoplasmic reticulum aminopeptidases (ERAP) trim antigenic precursor peptides to fit into the binding groove of MHC class I molecules. Polymorphisms in ERAP genes leading to aberrations in ERAP's can alter antigen presentation by HLA class I molecules resulting in aberrant T-cell responses, which may affect susceptibility to infection and/or activation of immune response. Polymorphisms from these genes are associated, in global genetic association studies, with various phenotype traits/disorders many of which are related to the pathogenesis and progression of COVID-19; polymorphisms from various genes are annotated in genotype-tissue expression data as regulating the expression of ACE2, HLA's and ERAP's. We review such polymorphisms and illustrate variations in their allele frequencies in global populations. These reported findings highlight the roles of genetic modulators (e.g. genotype changes in ACE2, HLA's and ERAP's leading to aberrations in the expressed gene products or genotype changes at other genes regulating the expression levels of these genes) in the pathogenesis of viral infection.
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Project description:BACKGROUND:After decades of identifying risk factors using array-based genome-wide association studies (GWAS), genetic research of complex diseases has shifted to sequencing-based rare variants discovery. This requires large sample sizes for statistical power and has brought up questions about whether the current variant calling practices are adequate for large cohorts. It is well-known that there are discrepancies between variants called by different pipelines, and that using a single pipeline always misses true variants exclusively identifiable by other pipelines. Nonetheless, it is common practice today to call variants by one pipeline due to computational cost and assume that false negative calls are a small percent of total. RESULTS:We analyzed 10,000 exomes from the Alzheimer's Disease Sequencing Project (ADSP) using multiple analytic pipelines consisting of different read aligners and variant calling strategies. We compared variants identified by using two aligners in 50,100, 200, 500, 1000, and 1952 samples; and compared variants identified by adding single-sample genotyping to the default multi-sample joint genotyping in 50,100, 500, 2000, 5000 and 10,000 samples. We found that using a single pipeline missed increasing numbers of high-quality variants correlated with sample sizes. By combining two read aligners and two variant calling strategies, we rescued 30% of pass-QC variants at sample size of 2000, and 56% at 10,000 samples. The rescued variants had higher proportions of low frequency (minor allele frequency [MAF] 1-5%) and rare (MAF < 1%) variants, which are the very type of variants of interest. In 660 Alzheimer's disease cases with earlier onset ages of ≤65, 4 out of 13 (31%) previously-published rare pathogenic and protective mutations in APP, PSEN1, and PSEN2 genes were undetected by the default one-pipeline approach but recovered by the multi-pipeline approach. CONCLUSIONS:Identification of the complete variant set from sequencing data is the prerequisite of genetic association analyses. The current analytic practice of calling genetic variants from sequencing data using a single bioinformatics pipeline is no longer adequate with the increasingly large projects. The number and percentage of quality variants that passed quality filters but are missed by the one-pipeline approach rapidly increased with sample size.
| S-EPMC5902939 | biostudies-literature
Project description:Gastrointestinal Stromal Tumors (GISTs) represent a paradigmatic model of oncogene addiction. Despite the well-known impact of the mutational status on clinical outcomes, we need to expand our knowledge to other factors that influence behavior heterogeneity in GIST patients. A growing body of studies has revealed that the tumor microenvironment (TME), mostly populated by tumor-associated macrophages (TAMs) and lymphocytes (TILs), and stromal differentiation (SD) have a significant impact on prognosis and response to treatment. Interestingly, even though the current knowledge of the role of immune response in this setting is still limited, recent pre-clinical and clinical data have highlighted the relevance of the TME in GISTs, with possible implications for clinical practice in the near future. Moreover, the expression of immune checkpoints, such as PD-L1, PD-1, and CTLA-4, and their relationship to the clinical phenotype in GIST are emerging as potential prognostic biomarkers. Looking forward, these variables related to the underlying tumoral microenvironment in GIST, though limited to still-ongoing trials, might lead to the potential use of immunotherapy, alone or in combination with targeted therapy, in advanced TKI-refractory GISTs. This review aims to deepen understanding of the potential link between mutational status and the immune microenvironment in GIST.
| S-EPMC9818806 | biostudies-literature
Project description:The immune composition of the tumor microenvironment influences response and resistance to immunotherapies. While numerous studies have identified somatic correlates of immune infiltration, germline features that associate with immune infiltrates in cancers remain incompletely characterized. We analyze seven million autosomal germline variants in the TCGA cohort and test for association with established immune-related phenotypes that describe the tumor immune microenvironment. We identify one SNP associated with the amount of infiltrating follicular helper T cells; 23 candidate genes, some of which are involved in cytokine-mediated signaling and others containing cancer-risk SNPs; and networks with genes that are part of the DNA repair and transcription elongation pathways. In addition, we find a positive association between polygenic risk for rheumatoid arthritis and amount of infiltrating CD8+ T cells. Overall, we identify multiple germline genetic features associated with tumor-immune phenotypes and develop a framework for probing inherited features that contribute to differences in immune infiltration.
| S-EPMC7082123 | biostudies-literature
Project description:The imbalance of immune response plays a crucial role in the development of diseases, including glioblastoma. It is essential to comprehend how the innate immune system detects tumors and pathogens. Endosomal and cytoplasmic sensors can identify diverse cancer cell antigens, triggering the production of type I interferon and pro-inflammatory cytokines. This, in turn, stimulates interferon stimulating genes, enhancing the presentation of cancer antigens, and promoting T cell recognition and destruction of cancer cells. While RNA and DNA sensing of tumors and pathogens typically involve different receptors and adapters, their interaction can activate adaptive immune response mechanisms. This review highlights the similarity in RNA and DNA sensing mechanisms in the innate immunity of both tumors and pathogens. The aim is to enhance the anti-tumor innate immune response, identify regions of the tumor that are not responsive to treatment, and explore new targets to improve the response to conventional tumor therapy and immunotherapy.
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Project description:ObjectiveObservational studies have identified a dual effect of circulating inflammatory proteins and immune cells on cancer progression. However, the specific mechanisms of action have not been clarified in the exacerbation of cutaneous-origin tumors. Therefore, this study aims to investigate whether the causal relationship between circulating inflammatory factors and basal cell carcinoma (BCC), cutaneous malignant melanoma (SKCM), and cutaneous squamous cell carcinoma (cSCC) is regulated by immune cells.MethodsThis study employed the Two-Sample Mendelian Randomization (TSMR) approach to investigate the causal relationships between 91 circulating inflammatory factors and three prevalent types of skin cancer from a genetic perspective. Bayesian Weighted Mendelian Randomization (BWMR) was also used to validate correlation and reverse MR to assess inverse relationships. Subsequent sensitivity analyses were conducted to limit the impact of heterogeneity and pleiotropy. Finally, the two-step Mendelian Randomization (two-step MR) method was utilized to ascertain the mediating effects of specific immune cell traits in the causal pathways linking circulating inflammatory factors with BCC, SKCM, and cSCC.ResultsThe Inverse Variance Weighted (IVW) method and the Bayesian Weighted Algorithm collectively identified nine inflammatory factors causally associated with BCC, SKCM, and cSCC. The results from Cochran's Q test, mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and MR-Egger intercept were not statistically significant (p < 0.05). Additionally, the proportions mediated by CD4+ CD8dim T cell %leukocyte, CD4-CD8-Natural Killer T %T cell, and CD20 on IgD-CD38-B cell for FIt3L, CCL4, and OSM were 9.26%, 8.96%, and 10.16%, respectively.ConclusionImmune cell levels potentially play a role in the modulation process between circulating inflammatory proteins and cutaneous-origin exacerbated tumors. This finding offers a new perspective for the in-depth exploration of cutaneous malignancies.
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Project description:BackgroundRCSD1 is a cytoskeletal regulator that has been confirmed to undergo genetic mutations in hematological tumors, but the mechanisms of RCSD1 in pan-cancer and its impact on patient prognosis have not been studied.MethodsUsing TCGA, GEPIA, UALCAN, Kaplan-Meier plotters, Linkedomics, String, cBioPortal, TISIDB, TCIA and TIMER database methods, we investigated the expression of RCSD1 in human tumors and its relationship to clinical prognosis, functional analysis of co-expression networks, mutation status, and immune infiltration in cancers, especially lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).ResultsThe expression of RCSD1 is low in most tumors compared with normal tissues, and its high expression is associated with good patient survival. The RCSD1 co-expression network is mainly involved in the regulation of immune response. In human cancer, RCSD1 plays an important role in the tumor microenvironment (TME) and is significantly associated with the expression of immune infiltrating cells (TIL) in lung cancer.ConclusionsAs a prognostic biomarker of generalized cancer, RCSD1 is associated with immune infiltration.
| S-EPMC9606721 | biostudies-literature
Project description:We describe open, reproducible pipelines that create an integrated genomic profile of a cancer and use the profile to find mutations associated with disease and potentially useful drugs. These pipelines analyze high-throughput cancer exome and transcriptome sequence data together with public databases to find relevant mutations and drugs. The three pipelines that we have developed are: (1) an exome analysis pipeline, which uses whole or targeted tumor exome sequence data to produce a list of putative variants (no matched normal data are needed); (2) a transcriptome analysis pipeline that processes whole tumor transcriptome sequence (RNA-seq) data to compute gene expression and find potential gene fusions; and (3) an integrated variant analysis pipeline that uses the tumor variants from the exome pipeline and tumor gene expression from the transcriptome pipeline to identify deleterious and druggable mutations in all genes and in highly expressed genes. These pipelines are integrated into the popular Web platform Galaxy at http://usegalaxy.org/cancer to make them accessible and reproducible, thereby providing an approach for doing standardized, distributed analyses in clinical studies. We have used our pipeline to identify similarities and differences between pancreatic adenocarcinoma cancer cell lines and primary tumors.
| S-EPMC4380965 | biostudies-literature
Project description:In the past two years, the world has faced the pandemic caused by the severe acute respiratory syndrome 2 coronavirus (SARS-CoV-2), which by August of 2022 has infected around 619 million people and caused the death of 6.55 million individuals globally. Although SARS-CoV-2 mainly affects the respiratory tract level, there are several reports, indicating that other organs such as the heart, kidney, pancreas, and brain can also be damaged. A characteristic observed in blood serum samples of patients suffering COVID-19 disease in moderate and severe stages, is a significant increase in proinflammatory cytokines such as interferon-α (IFN-α), interleukin-1β (IL-1β), interleukin-2 (IL-2), interleukin-6 (IL-6) and interleukin-18 (IL-18), as well as the presence of autoantibodies against interferon-α (IFN-α), interferon-λ (IFN-λ), C-C motif chemokine ligand 26 (CCL26), CXC motif chemokine ligand 12 (CXCL12), family with sequence similarity 19 (chemokine (C-C motif)-like) member A4 (FAM19A4), and C-C motif chemokine ligand 1 (CCL1). Interestingly, it has been described that the chronic cytokinemia is related to alterations of blood-brain barrier (BBB) permeability and induction of neurotoxicity. Furthermore, the generation of autoantibodies affects processes such as neurogenesis, neuronal repair, chemotaxis and the optimal microglia function. These observations support the notion that COVID-19 patients who survived the disease present neurological sequelae and neuropsychiatric disorders. The goal of this review is to explore the relationship between inflammatory and humoral immune markers and the major neurological damage manifested in post-COVID-19 patients.
| S-EPMC9800881 | biostudies-literature