Shared Immunogenic Poly-Epitope Frameshift Mutations in Microsatellite Unstable Tumors.

Microsatellite instability-high (MSI-H) tumors are characterized by high tumor mutation burden and responsiveness to checkpoint blockade. We identified tumor-specific frameshifts encoding multiple epitopes that originated from indel mutations shared among patients with MSI-H endometrial, colorectal, and stomach cancers. Epitopes derived from these shared frameshifts have high population occurrence rates, wide presence in many tumor subclones, and are predicted to bind to the most frequent MHC alleles in MSI-H patient cohorts. Neoantigens arising from these mutations are distinctly unlike self and viral antigens, signifying novel groups of potentially highly immunogenic tumor antigens. We further confirmed the immunogenicity of frameshift peptides in T cell stimulation experiments using blood mononuclear cells isolated from both healthy donors and MSI-H cancer patients. Our study uncovers the widespread occurrence and strong immunogenicity of tumor-specific antigens derived from shared frameshift mutations in MSI-H cancer and Lynch syndrome patients, suitable for the design of common "off-the-shelf" cancer vaccines.

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics.

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing.

Pathogenic Germline Variants in 10,389 Adult Cancers.

We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer.

Associations of Circulating Biomarkers with Disease Risks: A Two-Sample Mendelian Randomization Study.

Circulating biomarkers play a pivotal role in personalized medicine, offering potential for disease screening, prevention, and treatment. Despite established associations between numerous biomarkers and diseases, elucidating their causal relationships is challenging. Mendelian Randomization (MR) can address this issue by employing genetic instruments to discern causal links. Additionally, using multiple MR methods with overlapping results enhances the reliability of discovered relationships. Here, we report an MR study using multiple methods, including inverse variance weighted, simple mode, weighted mode, weighted median, and MR-Egger. We use the MR-base resource (v0.5.6) from Hemani et al. 2018 to evaluate causal relationships between 212 circulating biomarkers (curated from UK Biobank analyses by Neale lab and from Shin et al. 2014, Roederer et al. 2015, and Kettunen et al. 2016 and 99 complex diseases (curated from several consortia by MRC IEU and Biobank Japan). We report novel causal relationships found by four or more MR methods between glucose and bipolar disorder (Mean Effect Size estimate across methods: 0.39) and between cystatin C and bipolar disorder (Mean Effect Size: -0.31). Based on agreement in four or more methods, we also identify previously known links between urate with gout and creatine with chronic kidney disease, as well as biomarkers that may be causal of cardiovascular conditions: apolipoprotein B, cholesterol, LDL, lipoprotein A, and triglycerides in coronary heart disease, as well as lipoprotein A, LDL, cholesterol, and apolipoprotein B in myocardial infarction. This Mendelian Randomization study not only corroborates known causal relationships between circulating biomarkers and diseases but also uncovers two novel biomarkers associated with bipolar disorder that warrant further investigation. Our findings provide insight into understanding how biological processes reflecting circulating biomarkers and their associated effects may contribute to disease etiology, which can eventually help improve precision diagnostics and intervention.

Using EGFR amplification to stratify recurrent glioblastoma treated with immune checkpoint inhibitors.

PURPOSE: While immune checkpoint inhibitors (ICI) have had success with various malignancies, their efficacy in brain cancer is still unclear. Retrospective and prospective studies using PD-1 inhibitors for recurrent glioblastoma (GBM) have not established survival benefit. This study evaluated if ICI may be effective for select patients with recurrent GBM. METHODS: This was a single-center retrospective study of adult patients diagnosed with first recurrence GBM and received pembrolizumab or nivolumab with or without concurrent bevacizumab. Archival tissue was used for immunohistochemistry (IHC) and targeted DNA next-generation sequencing (NGS) analysis. RESULTS: Median overall survival (mOS) from initial diagnosis was 24.5 months (range 10-42). mOS from onset of ICI was 10 months (range 1-31) with 75% surviving > 6 months and 46% > 12 months. Additional IHC analysis on tumors from eight patients demonstrated a trend of longer survival after ICI for those with elevated PD-L1 expression. NGS of samples from 15 patients identified EGFR amplification at initial diagnosis and at any time point to be associated with worse survival after ICI (HR 12.2, 95% CI 1.37-108, p = 0.025 and HR 3.92, 95% CI 1.03-14.9, p = 0.045, respectively). This significance was corroborated with previously tested EGFR amplification via in situ hybridization. CONCLUSION: ICI did not extend overall survival for recurrent GBM. However, molecular sequencing identified EGFR amplification as associated with worse survival. Prospective studies can validate if EGFR amplification is a biomarker of ICI resistance and determine if its use can stratify responders from non-responders.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Functional analysis of BARD1 missense variants in homology-directed repair and damage sensitivity.

The BARD1 protein, which heterodimerizes with BRCA1, is encoded by a known breast cancer susceptibility gene. While several BARD1 variants have been identified as pathogenic, many more missense variants exist that do not occur frequently enough to assign a clinical risk. In this paper, whole exome sequencing of over 10,000 cancer samples from 33 cancer types identified from somatic mutations and loss of heterozygosity in tumors 76 potentially cancer-associated BARD1 missense and truncation variants. These variants were tested in a functional assay for homology-directed repair (HDR), as HDR deficiencies have been shown to correlate with clinical pathogenicity for BRCA1 variants. From these 76 variants, 4 in the ankyrin repeat domain and 5 in the BRCT domain were found to be non-functional in HDR. Two known benign variants were found to be functional in HDR, and three known pathogenic variants were non-functional, supporting the notion that the HDR assay can be used to predict the clinical risk of BARD1 variants. The identification of HDR-deficient variants in the ankyrin repeat domain indicates there are DNA repair functions associated with this domain that have not been closely examined. In order to examine whether BARD1-associated loss of HDR function results in DNA damage sensitivity, cells expressing non-functional BARD1 variants were treated with ionizing radiation or cisplatin. These cells were found to be more sensitive to DNA damage, and variations in the residual HDR function of non-functional variants did not correlate with variations in sensitivity. These findings improve the understanding of BARD1 functional domains in DNA repair and support that this functional assay is useful for predicting the cancer association of BARD1 variants.

Modeling COVID-19 dynamic using a two-strain model with vaccination.

Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number ( R c ) and the per day infection, death and recovery rates of each strain in the US pandemic. The model dynamics predicted the rise of the alpha variant and shed light on potential impact of the delta variant in 2021. We obtained the minimum percentage of fully vaccinated individuals to reduce the spread of the variants in combination with other intervention strategies to deaccelerate the rise of a multi-strain pandemic.

Cooperation Between Distinct Cancer Driver Genes Underlies Intertumor Heterogeneity in Hepatocellular Carcinoma.

BACKGROUND AND AIMS: The pattern of genetic alterations in cancer driver genes in patients with hepatocellular carcinoma (HCC) is highly diverse, which partially explains the low efficacy of available therapies. In spite of this, the existing mouse models only recapitulate a small portion of HCC inter-tumor heterogeneity, limiting the understanding of the disease and the nomination of personalized therapies. Here, we aimed at establishing a novel collection of HCC mouse models that captured human HCC diversity. METHODS: By performing hydrodynamic tail-vein injections, we tested the impact of altering a well-established HCC oncogene (either MYC or ß-catenin) in combination with an additional alteration in one of eleven other genes frequently mutated in HCC. Of the 23 unique pairs of genetic alterations that we interrogated, 9 were able to induce HCC. The established HCC mouse models were characterized at histopathological, immune, and transcriptomic level to identify the unique features of each model. Murine HCC cell lines were generated from each tumor model, characterized transcriptionally, and used to identify specific therapies that were validated in vivo. RESULTS: Cooperation between pairs of driver genes produced HCCs with diverse histopathology, immune microenvironments, transcriptomes, and drug responses. Interestingly, MYC expression levels strongly influenced ß-catenin activity, indicating that inter-tumor heterogeneity emerges not only from specific combinations of genetic alterations but also from the acquisition of expression-dependent phenotypes. CONCLUSIONS: This novel collection of murine HCC models and corresponding cell lines establishes the role of driver genes in diverse contexts and enables mechanistic and translational studies.

Regulated Phosphosignaling Associated with Breast Cancer Subtypes and Druggability.

Aberrant phospho-signaling is a hallmark of cancer. We investigated kinase-substrate regulation of 33,239 phosphorylation sites (phosphosites) in 77 breast tumors and 24 breast cancer xenografts. Our search discovered 2134 quantitatively correlated kinase-phosphosite pairs, enriching for and extending experimental or binding-motif predictions. Among the 91 kinases with auto-phosphorylation, elevated EGFR, ERBB2, PRKG1, and WNK1 phosphosignaling were enriched in basal, HER2-E, Luminal A, and Luminal B breast cancers, respectively, revealing subtype-specific regulation. CDKs, MAPKs, and ataxia-telangiectasia proteins were dominant, master regulators of substrate-phosphorylation, whose activities are not captured by genomic evidence. We unveiled phospho-signaling and druggable targets from 113 kinase-substrate pairs and cascades downstream of kinases, including AKT1, BRAF and EGFR. We further identified kinase-substrate-pairs associated with clinical or immune signatures and experimentally validated activated phosphosites of ERBB2, EIF4EBP1, and EGFR. Overall, kinase-substrate regulation revealed by the largest unbiased global phosphorylation data to date connects driver events to their signaling effects.

Genotype concordance and polygenic risk score estimation across consumer genetic testing data.

The consumer genomics industry is steadily growing and delivering genetic information to over 10 million individuals. Yet, the implications of using data from different services remain unclear. We investigated the genotyped sites, concordance, and genetic risk estimation using data from three consumer services-two single nucleotide polymorphism (SNP)-array based and one sequencing based. In an N-of-one setting, we found the three services genotyped predominantly distinct sets of sites. While there was a high concordance between overlapping sites of the two SNP-array services (99.6%), there was a lower concordance between these services and a low-pass whole-genome service (73.0%). The discrepancy between the three sets of data resulted in different APOE genotypes and genetic risk scores of Alzheimer's disease. Our results demonstrate genotype results across consumer genomics platforms may lead to different genetic risk estimates, highlighting the need for careful quality control and interpretation.

GenomeVIP: a cloud platform for genomic variant discovery and interpretation.

Identifying genomic variants is a fundamental first step toward the understanding of the role of inherited and acquired variation in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional "download and analyze" paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole-genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been used for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available data sets.

CharGer: clinical Characterization of Germline variants.

SUMMARY: CharGer (Characterization of Germline variants) is a software tool for interpreting and predicting clinical pathogenicity of germline variants. CharGer gathers evidence from databases and annotations, provided by local tools and files or via ReST APIs, and classifies variants according to ACMG guidelines for assessing variant pathogenicity. User-designed pathogenicity criteria can be incorporated into CharGer's flexible framework, thereby allowing users to create a customized classification protocol. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/ding-lab/CharGer and is distributed under the GNU GPL-v3.0 license. Software is also distributed through the Python Package Index (PyPI) repository. CharGer is implemented in Python 2.7 and is supported on Unix-based operating systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mannose Phosphate Isomerase and Mannose Regulate Hepatic Stellate Cell Activation and Fibrosis in Zebrafish and Humans.

The growing burden of liver fibrosis and lack of effective antifibrotic therapies highlight the need for identification of pathways and complementary model systems of hepatic fibrosis. A rare, monogenic disorder in which children with mutations in mannose phosphate isomerase (MPI) develop liver fibrosis led us to explore the function of MPI and mannose metabolism in liver development and adult liver diseases. Herein, analyses of transcriptomic data from three human liver cohorts demonstrate that MPI gene expression is down-regulated proportionate to fibrosis in chronic liver diseases, including nonalcoholic fatty liver disease and hepatitis B virus. Depletion of MPI in zebrafish liver in vivo and in human hepatic stellate cell (HSC) lines in culture activates fibrotic responses, indicating that loss of MPI promotes HSC activation. We further demonstrate that mannose supplementation can attenuate HSC activation, leading to reduced fibrogenic activation in zebrafish, culture-activated HSCs, and in ethanol-activated HSCs. Conclusion: These data indicate the prospect that modulation of mannose metabolism pathways could reduce HSC activation and improve hepatic fibrosis.

Framework for microRNA variant annotation and prioritization using human population and disease datasets.

MicroRNA (miRNA) expression is frequently deregulated in human disease, in contrast, disease-associated miRNA mutations are understudied. We developed Annotative Database of miRNA Elements, ADmiRE, which combines multiple existing and new biological annotations to aid prioritization of causal miRNA variation. We annotated 10,206 mature (3,257 within seed region) miRNA variants from multiple large sequencing datasets including gnomAD (15,496 genomes; 123,136 exomes). The pattern of miRNA variation closely resembles protein-coding exonic regions, with no difference between intragenic and intergenic miRNAs (P = 0.56), and high confidence miRNAs demonstrate higher sequence constraint (P < 0.001). Conservation analysis across 100 vertebrates identified 765 highly conserved miRNAs that also have limited genetic variation in gnomAD. We applied ADmiRE to the TCGA PanCancerAtlas WES dataset containing over 10,000 individuals across 33 adult cancers and annotated 1,267 germline (rare in gnomAD) and 1,492 somatic miRNA variants. Several miRNA families with deregulated gene expression in cancer have low levels of both somatic and germline variants, e.g., let-7 and miR-10. In addition to known somatic miR-142 mutations in hematologic cancers, we describe novel somatic miR-21 mutations in esophageal cancers impacting downstream miRNA targets. Through the development of ADmiRE, we present a framework for annotation and prioritization of miRNA variation in disease datasets.

Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers.

More than 20 genetic loci have been associated with risk for Alzheimer's disease (AD), but reported genome-wide significant loci do not account for all the estimated heritability and provide little information about underlying biological mechanisms. Genetic studies using intermediate quantitative traits such as biomarkers, or endophenotypes, benefit from increased statistical power to identify variants that may not pass the stringent multiple test correction in case-control studies. Endophenotypes also contain additional information helpful for identifying variants and genes associated with other aspects of disease, such as rate of progression or onset, and provide context to interpret the results from genome-wide association studies (GWAS). We conducted GWAS of amyloid beta (Aß42), tau, and phosphorylated tau (ptau181) levels in cerebrospinal fluid (CSF) from 3146 participants across nine studies to identify novel variants associated with AD. Five genome-wide significant loci (two novel) were associated with ptau181, including loci that have also been associated with AD risk or brain-related phenotypes. Two novel loci associated with Aß42 near GLIS1 on 1p32.3 (ß = -0.059, P = 2.08 × 10-8) and within SERPINB1 on 6p25 (ß = -0.025, P = 1.72 × 10-8) were also associated with AD risk (GLIS1: OR = 1.105, P = 3.43 × 10-2), disease progression (GLIS1: ß = 0.277, P = 1.92 × 10-2), and age at onset (SERPINB1: ß = 0.043, P = 4.62 × 10-3). Bioinformatics indicate that the intronic SERPINB1 variant (rs316341) affects expression of SERPINB1 in various tissues, including the hippocampus, suggesting that SERPINB1 influences AD through an Aß-associated mechanism. Analyses of known AD risk loci suggest CLU and FERMT2 may influence CSF Aß42 (P = 0.001 and P = 0.009, respectively) and the INPP5D locus may affect ptau181 levels (P = 0.009); larger studies are necessary to verify these results. Together the findings from this study can be used to inform future AD studies.

Chitinase-3-like 1 protein (CHI3L1) locus influences cerebrospinal fluid levels of YKL-40.

BACKGROUND: Alzheimer's disease (AD) pathology appears several years before clinical symptoms, so identifying ways to detect individuals in the preclinical stage is imperative. The cerebrospinal fluid (CSF) Tau/Aß42 ratio is currently the best known predictor of AD status and cognitive decline, and the ratio of CSF levels of chitinase-3-like 1 protein (CHI3L1, YKL-40) and amyloid beta (Aß42) were reported as predictive, but individual variability and group overlap inhibits their utility for individual diagnosis making it necessary to find ways to improve sensitivity of these biomarkers. METHODS: We used linear regression to identify genetic loci associated with CSF YKL-40 levels in 379 individuals (80 cognitively impaired and 299 cognitively normal) from the Charles F and Joanne Knight Alzheimer's Disease Research Center. We tested correlations between YKL-40 and CSF Tau/Aß42 ratio, Aß42, tau, and phosphorylated tau (ptau181). We used studentized residuals from a linear regression model of the log-transformed, standardized protein levels and the additive reference allele counts from the most significant locus to adjust YKL-40 values and tested the differences in correlations with CSF Tau/Aß42 ratio, Aß42, tau, and ptau181. RESULTS: We found that genetic variants on the CH13L1 locus were significantly associated with CSF YKL-40 levels, but not AD risk, age at onset, or disease progression. The most significant variant is a reported expression quantitative trait locus for CHI3L1, the gene which encodes YKL-40, and explained 12.74 % of the variance in CSF YKL-40 in our study. YKL-40 was positively correlated with ptau181 (r = 0.521) and the strength of the correlation significantly increased with the addition of genetic information (r = 0.573, p = 0.006). CONCLUSIONS: CSF YKL-40 levels are likely a biomarker for AD, but we found no evidence that they are an AD endophenotype. YKL-40 levels are highly regulated by genetic variation, and by including genetic information the strength of the correlation between YKL-40 and ptau181 levels is significantly improved. Our results suggest that studies of potential biomarkers may benefit from including genetic information.