Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab.

The mechanisms by which immune checkpoint blockade modulates tumor evolution during therapy are unclear. We assessed genomic changes in tumors from 68 patients with advanced melanoma, who progressed on ipilimumab or were ipilimumab-naive, before and after nivolumab initiation (CA209-038 study). Tumors were analyzed by whole-exome, transcriptome, and/or T cell receptor (TCR) sequencing. In responding patients, mutation and neoantigen load were reduced from baseline, and analysis of intratumoral heterogeneity during therapy demonstrated differential clonal evolution within tumors and putative selection against neoantigenic mutations on-therapy. Transcriptome analyses before and during nivolumab therapy revealed increases in distinct immune cell subsets, activation of specific transcriptional networks, and upregulation of immune checkpoint genes that were more pronounced in patients with response. Temporal changes in intratumoral TCR repertoire revealed expansion of T cell clones in the setting of neoantigen loss. Comprehensive genomic profiling data in this study provide insight into nivolumab's mechanism of action.

Protein-Protein interactions uncover candidate 'core genes' within omnigenic disease networks.

Genome wide association studies (GWAS) of human diseases have generally identified many loci associated with risk with relatively small effect sizes. The omnigenic model attempts to explain this observation by suggesting that diseases can be thought of as networks, where genes with direct involvement in disease-relevant biological pathways are named 'core genes', while peripheral genes influence disease risk via their interactions or regulatory effects on core genes. Here, we demonstrate a method for identifying candidate core genes solely from genes in or near disease-associated SNPs (GWAS hits) in conjunction with protein-protein interaction network data. Applied to 1,381 GWAS studies from 5 ancestries, we identify a total of 1,865 candidate core genes in 343 GWAS studies. Our analysis identifies several well-known disease-related genes that are not identified by GWAS, including BRCA1 in Breast Cancer, Amyloid Precursor Protein (APP) in Alzheimer's Disease, INS in A1C measurement and Type 2 Diabetes, and PCSK9 in LDL cholesterol, amongst others. Notably candidate core genes are preferentially enriched for disease relevance over GWAS hits and are enriched for both Clinvar pathogenic variants and known drug targets-consistent with the predictions of the omnigenic model. We subsequently use parent term annotations provided by the GWAS catalog, to merge related GWAS studies and identify candidate core genes in over-arching disease processes such as cancer-where we identify 109 candidate core genes.

Exonuclease mutations in DNA polymerase epsilon reveal replication strand specific mutation patterns and human origins of replication.

Tumors with somatic mutations in the proofreading exonuclease domain of DNA polymerase epsilon (POLE-exo*) exhibit a novel mutator phenotype, with markedly elevated TCT→TAT and TCG→TTG mutations and overall mutation frequencies often exceeding 100 mutations/Mb. Here, we identify POLE-exo* tumors in numerous cancers and classify them into two groups, A and B, according to their mutational properties. Group A mutants are found only in POLE, whereas Group B mutants are found in POLE and POLD1 and appear to be nonfunctional. In Group A, cell-free polymerase assays confirm that mutations in the exonuclease domain result in high mutation frequencies with a preference for C→A mutation. We describe the patterns of amino acid substitutions caused by POLE-exo* and compare them to other tumor types. The nucleotide preference of POLE-exo* leads to increased frequencies of recurrent nonsense mutations in key tumor suppressors such as TP53, ATM, and PIK3R1. We further demonstrate that strand-specific mutation patterns arise from some of these POLE-exo* mutants during genome duplication. This is the first direct proof of leading strand-specific replication by human POLE, which has only been demonstrated in yeast so far. Taken together, the extremely high mutation frequency and strand specificity of mutations provide a unique identifier of eukaryotic origins of replication.

DNA methyltransferase 1 and DNA methylation patterning contribute to germinal center B-cell differentiation.

The phenotype of germinal center (GC) B cells includes the unique ability to tolerate rapid proliferation and the mutagenic actions of activation induced cytosine deaminase (AICDA). Given the importance of epigenetic patterning in determining cellular phenotypes, we examined DNA methylation and the role of DNA methyltransferases in the formation of GCs. DNA methylation profiling revealed a marked shift in DNA methylation patterning in GC B cells versus resting/naive B cells. This shift included significant differential methylation of 235 genes, with concordant inverse changes in gene expression affecting most notably genes of the NFkB and MAP kinase signaling pathways. GC B cells were predominantly hypomethylated compared with naive B cells and AICDA binding sites were highly overrepresented among hypomethylated loci. GC B cells also exhibited greater DNA methylation heterogeneity than naive B cells. Among DNA methyltransferases (DNMTs), only DNMT1 was significantly up-regulated in GC B cells. Dnmt1 hypomorphic mice displayed deficient GC formation and treatment of mice with the DNA methyltransferase inhibitor decitabine resulted in failure to form GCs after immune stimulation. Notably, the GC B cells of Dnmt1 hypomorphic animals showed evidence of increased DNA damage, suggesting dual roles for DNMT1 in DNA methylation and double strand DNA break repair.

A genome-wide association study of men with symptoms of testicular dysgenesis syndrome and its network biology interpretation.

BACKGROUND: Testicular dysgenesis syndrome (TDS) is a common disease that links testicular germ cell cancer, cryptorchidism and some cases of hypospadias and male infertility with impaired development of the testis. The incidence of these disorders has increased over the last few decades, and testicular cancer now affects 1% of the Danish and Norwegian male population. METHODS: To identify genetic variants that span the four TDS phenotypes, the authors performed a genome-wide association study (GWAS) using Affymetrix Human SNP Array 6.0 to screen 488 patients with symptoms of TDS and 439 selected controls with excellent reproductive health. Furthermore, they developed a novel integrative method that combines GWAS data with other TDS-relevant data types and identified additional TDS markers. The most significant findings were replicated in an independent cohort of 671 Nordic men. RESULTS: Markers located in the region of TGFBR3 and BMP7 showed association with all TDS phenotypes in both the discovery and replication cohorts. An immunohistochemistry investigation confirmed the presence of transforming growth factor ß receptor type III (TGFBR3) in peritubular and Leydig cells, in both fetal and adult testis. Single-nucleotide polymorphisms in the KITLG gene showed significant associations, but only with testicular cancer. CONCLUSIONS: The association of single-nucleotide polymorphisms in the TGFBR3 and BMP7 genes, which belong to the transforming growth factor ß signalling pathway, suggests a role for this pathway in the pathogenesis of TDS. Integrating data from multiple layers can highlight findings in GWAS that are biologically relevant despite having border significance at currently accepted statistical levels.

ChemProt: a disease chemical biology database.

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs). We assembled more than 700,000 unique chemicals with biological annotation for 30,578 proteins. We gathered over 2-million chemical-protein interactions, which were integrated in a quality scored human PPI network of 428,429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/.

Dynamic Mutational Landscape of Cerebrospinal Fluid Circulating Tumor DNA and Predictors of Survival after Proton Craniospinal Irradiation for Leptomeningeal Metastases.

PURPOSE: Proton craniospinal irradiation (pCSI) is a promising treatment for patients with solid tumor leptomeningeal metastasis (LM). We hypothesize that genetic characteristics before and changes resulting after pCSI will reflect clinical response to pCSI. We analyzed the cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) from patients receiving pCSI for LM and explored genetic variations associated with response. EXPERIMENTAL DESIGN: We subjected CSF from 14 patients with LM before and after pCSI to cell-free DNA sequencing using a targeted-sequencing panel. In parallel, plasma ctDNA and primary tumors were subjected to targeted sequencing. Variant allele frequency (VAF) and cancer cell fraction (CCF) were calculated; clonality of observed mutations was determined. Kaplan-Meier analysis was used to associate genomic changes with survival. RESULTS: The median overall survival (OS) for the cohort was 9 months [interquartile range (IQR), 5-21 months]. We showed clonal evolution between tumor and ctDNA of the CSF and plasma with unique mutations identified by compartment. Higher CSF ctDNA mean VAF before pCSI (VAFpre) had worse OS (6 months for VAFpre ≥ 0.32 vs. 9 months for VAFpre < 0.32; P = 0.05). Similarly, increased VAF after pCSI portended worse survival (6 vs. 18 months; P = 0.008). Higher mean CCF of subclonal mutations appearing after pCSI was associated with worse OS (8 vs. 17 months; P = 0.05). CONCLUSIONS: In patients with solid tumor LM undergoing pCSI, we found unique genomic profiles associated with pCSI through CSF ctDNA analyses. Patients with reduced genomic diversity within the leptomeningeal compartment demonstrated improved OS after pCSI suggesting that CSF ctDNA analysis may have use in predicting pCSI response.

Templated Insertions Are Associated Specifically with BRCA2 Deficiency and Overall Survival in Advanced Ovarian Cancer.

Cancer cells defective in homologous recombination (HR) are responsive to DNA-crosslinking chemotherapies, PARP inhibitors, and inhibitors of polymerase theta (Pol θ), a key mediator of the backup pathway alternative end-joining. Such cancers include those with pathogenic biallelic alterations in core HR genes and another cohort of cases that exhibit sensitivity to the same agents and harbor genomic hallmarks of HR deficiency (HRD). These HRD signatures include a single-base substitution pattern, large rearrangements, characteristic tandem duplications, and small deletions. Here, we used what is now known about the backup pathway alternative end-joining (Alt-EJ) through the key factor Pol θ to design and test novel signatures of polymerase theta-mediated (TMEJ) repair. We generated two novel signatures; a signature composed of small deletions with microhomology and another consisting of small, templated insertions (TINS). We find that TINS consistent with TMEJ repair are highly specific to tumors with pathogenic biallelic mutations in BRCA2 and that high TINS genomic signature content in advanced ovarian cancers associate with overall survival following treatment with platinum agents. In addition, the combination of TINS with other HRD metrics significantly improves the association of platinum sensitivity with survival compared with current state-of-the-art signatures. IMPLICATIONS: Small, templated insertions indicative of theta-mediated end-joining likely can be used in conjunction with other HRD mutational signatures as a prognostic tool for patient response to therapies targeting HR deficiency.

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types.

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose1. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.

Deciphering diseases and biological targets for environmental chemicals using toxicogenomics networks.

Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types.

p53-intact cancers escape tumor suppression through loss of long noncoding RNA Dino.

Many long noncoding RNA (lncRNA) genes exist near cancer-associated loci, yet evidence connecting lncRNA functions to recurrent genetic alterations in cancer are lacking. Here, we report that DINO, the lncRNA transcribed from the cancer-associated DINO/CDKN1A locus, suppresses tumor formation independent of p21, the protein encoded at the locus. Loss of one or two alleles of Dino impairs p53 signaling and apoptosis, resulting in a haplo-insufficient tumor suppressor phenotype in genetically defined mouse models of tumorigenesis. A discrete region of the DINO/CDKN1A locus is recurrently hypermethylated in human cancers, silencing DINO but not CDKN1A, the gene encoding p21. Hypermethylation silences DINO, impairs p53 signaling pathway in trans, and is mutually exclusive with TP53 alterations, indicating that DINO and TP53 comprise a common tumor suppressor module. Therefore, DINO encodes a lncRNA essential for tumor suppression that is recurrently silenced in human cancers as a mechanism to escape p53-dependent tumor suppression.

Local function conservation in sequence and structure space.

We assess the variability of protein function in protein sequence and structure space. Various regions in this space exhibit considerable difference in the local conservation of molecular function. We analyze and capture local function conservation by means of logistic curves. Based on this analysis, we propose a method for predicting molecular function of a query protein with known structure but unknown function. The prediction method is rigorously assessed and compared with a previously published function predictor. Furthermore, we apply the method to 500 functionally unannotated PDB structures and discuss selected examples. The proposed approach provides a simple yet consistent statistical model for the complex relations between protein sequence, structure, and function. The GOdot method is available online (http://godot.bioinf.mpi-inf.mpg.de).

Genetic diversity of tumors with mismatch repair deficiency influences anti-PD-1 immunotherapy response.

Tumors with mismatch repair deficiency (MMR-d) are characterized by sequence alterations in microsatellites and can accumulate thousands of mutations. This high mutational burden renders tumors immunogenic and sensitive to programmed cell death-1 (PD-1) immune checkpoint inhibitors. Yet, despite their tumor immunogenicity, patients with MMR-deficient tumors experience highly variable responses, and roughly half are refractory to treatment. We present experimental and clinical evidence showing that the degree of microsatellite instability (MSI) and resultant mutational load, in part, underlies the variable response to PD-1 blockade immunotherapy in MMR-d human and mouse tumors. The extent of response is particularly associated with the accumulation of insertion-deletion (indel) mutational load. This study provides a rationale for the genome-wide characterization of MSI intensity and mutational load to better profile responses to anti-PD-1 immunotherapy across MMR-deficient human cancers.

The impact of the protein interactome on the syntenic structure of mammalian genomes.

Conserved synteny denotes evolutionary preserved gene order across species. It is not well understood to which degree functional relationships between genes are preserved in syntenic blocks. Here we investigate whether protein-coding genes conserved in mammalian syntenic blocks encode gene products that serve the common functional purpose of interacting at protein level, i.e. connectivity. High connectivity among protein-protein interactions (PPIs) was only moderately associated with conserved synteny on a genome-wide scale. However, we observed a smaller subset of 3.6% of all syntenic blocks with high-confidence PPIs that had significantly higher connectivity than expected by random. Additionally, syntenic blocks with high-confidence PPIs contained significantly more chromatin loops than the remaining blocks, indicating functional preservation among these syntenic blocks. Conserved synteny is typically defined by sequence similarity. In this study, we also examined whether a functional relationship, here PPI connectivity, can identify syntenic blocks independently of orthology. While orthology-based syntenic blocks with high-confident PPIs and the connectivity-based syntenic blocks largely overlapped, the connectivity-based approach identified additional syntenic blocks that were not found by conventional sequence-based methods alone. Additionally, the connectivity-based approach enabled identification of potential orthologous genes between species. Our analyses demonstrate that subsets of syntenic blocks are associated with highly connected proteins, and that PPI connectivity can be used to detect conserved synteny even if sequence conservation drifts beyond what orthology algorithms normally can identify.

Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations.

Gene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies, gene and protein level alterations have fatal consequences. We used genome-wide protein-protein interaction data to identify chromosome-specific patterns of protein interactions. We found that some chromosomes encode proteins that interact infrequently with each other, chromosome 21 in particular. We combined the protein interaction data with transcriptome data from human brain tissue to investigate how this pattern of global interactions may affect cellular function. We identified highly connected proteins that also had coordinated gene expression. These proteins were associated with important neurological functions affecting the characteristic phenotypes for Down syndrome and have previously been validated in mouse knockout experiments. Our approach is general and applicable to other gene-dosage changes, such as arm-level amplifications in cancer.

Pan-cancer analysis of bi-allelic alterations in homologous recombination DNA repair genes.

BRCA1 and BRCA2 are involved in homologous recombination (HR) DNA repair and are germ-line cancer pre-disposition genes that result in a syndrome of hereditary breast and ovarian cancer (HBOC). Whether germ-line or somatic alterations in these genes or other members of the HR pathway and if mono- or bi-allelic alterations of HR-related genes have a phenotypic impact on other cancers remains to be fully elucidated. Here, we perform a pan-cancer analysis of The Cancer Genome Atlas (TCGA) data set and observe that bi-allelic pathogenic alterations in homologous recombination (HR) DNA repair-related genes are prevalent across many malignancies. These bi-allelic alterations often associate with genomic features of HR deficiency. Further, in ovarian, breast and prostate cancers, bi-allelic alterations are mutually exclusive of each other. The combination of these two properties facilitates reclassification of variants of unknown significance affecting DNA repair genes, and may help personalize HR directed therapies in the clinic.Germline mutations in homologous recombination (HR) DNA repair genes are linked to breast and ovarian cancer. Here, the authors show that mutually exclusive bi-allelic inactivation of HR genes are present in other cancer types and associated with genomic features of HR deficiency, expanding the potential use of HR-directed therapies.

Genomic landscape and evolution of metastatic chromophobe renal cell carcinoma.

Chromophobe renal cell carcinoma (chRCC) typically shows ~7 chromosome losses (1, 2, 6, 10, 13, 17, and 21) and ~31 exonic somatic mutations, yet carries ~5%-10% metastatic incidence. Since extensive chromosomal losses can generate proteotoxic stress and compromise cellular proliferation, it is intriguing how chRCC, a tumor with extensive chromosome losses and a low number of somatic mutations, can develop lethal metastases. Genomic features distinguishing metastatic from nonmetastatic chRCC are unknown. An integrated approach, including whole-genome sequencing (WGS), targeted ultradeep cancer gene sequencing, and chromosome analyses (FACETS, OncoScan, and FISH), was performed on 79 chRCC patients including 38 metastatic (M-chRCC) cases. We demonstrate that TP53 mutations (58%), PTEN mutations (24%), and imbalanced chromosome duplication (ICD, duplication of ≥ 3 chromosomes) (25%) were enriched in M-chRCC. Reconstruction of the subclonal composition of paired primary-metastatic chRCC tumors supports the role of TP53, PTEN, and ICD in metastatic evolution. Finally, the presence of these 3 genomic features in primary tumors of both The Cancer Genome Atlas kidney chromophobe (KICH) (n = 64) and M-chRCC (n = 35) cohorts was associated with worse survival. In summary, our study provides genomic insights into the metastatic progression of chRCC and identifies TP53 mutations, PTEN mutations, and ICD as high-risk features.

Genomic Biomarkers of a Randomized Trial Comparing First-line Everolimus and Sunitinib in Patients with Metastatic Renal Cell Carcinoma.

BACKGROUND: Metastatic renal cell carcinoma (RCC) patients are commonly treated with vascular endothelial growth factor (VEGF) inhibitors or mammalian target of rapamycin inhibitors. Correlations between somatic mutations and first-line targeted therapy outcomes have not been reported on a randomized trial. OBJECTIVE: To evaluate the relationship between tumor mutations and treatment outcomes in RECORD-3, a randomized trial comparing first-line everolimus (mTOR inhibitor) followed by sunitinib (VEGF inhibitor) at progression with the opposite sequence in 471 metastatic RCC patients. DESIGN, SETTING, AND PARTICIPANTS: Targeted sequencing of 341 cancer genes at ∼540× coverage was performed on available tumor samples from 258 patients; 220 with clear cell histology (ccRCC). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Associations between somatic mutations and median first-line progression free survival (PFS1L) and overall survival were determined in metastatic ccRCC using Cox proportional hazards models and log-rank tests. RESULTS AND LIMITATIONS: Prevalent mutations (≥ 10%) were VHL (75%), PBRM1 (46%), SETD2 (30%), BAP1 (19%), KDM5C (15%), and PTEN (12%). With first-line everolimus, PBRM1 and BAP1 mutations were associated with longer (median [95% confidence interval {CI}] 12.8 [8.1, 18.4] vs 5.5 [3.1, 8.4] mo) and shorter (median [95% CI] 4.9 [2.9, 8.1] vs 10.5 [7.3, 12.9] mo) PFS1L, respectively. With first-line sunitinib, KDM5C mutations were associated with longer PFS1L (median [95% CI] of 20.6 [12.4, 27.3] vs 8.3 [7.8, 11.0] mo). Molecular subgroups of metastatic ccRCC based on PBRM1, BAP1, and KDM5C mutations could have predictive values for patients treated with VEGF or mTOR inhibitors. Most tumor DNA was obtained from primary nephrectomy samples (94%), which could impact correlation statistics. CONCLUSIONS: PBRM1, BAP1, and KDM5C mutations impact outcomes of targeted therapies in metastatic ccRCC patients. PATIENT SUMMARY: Large-scale genomic kidney cancer studies reported novel mutations and heterogeneous features among individual tumors, which could contribute to varied clinical outcomes. We demonstrated correlations between somatic mutations and treatment outcomes in clear cell renal cell carcinoma, supporting the value of genomic classification in prospective studies.

The SWI/SNF Protein PBRM1 Restrains VHL-Loss-Driven Clear Cell Renal Cell Carcinoma.

PBRM1 is the second most commonly mutated gene after VHL in clear cell renal cell carcinoma (ccRCC). However, the biological consequences of PBRM1 mutations for kidney tumorigenesis are unknown. Here, we find that kidney-specific deletion of Vhl and Pbrm1, but not either gene alone, results in bilateral, multifocal, transplantable clear cell kidney cancers. PBRM1 loss amplified the transcriptional outputs of HIF1 and STAT3 incurred by Vhl deficiency. Analysis of mouse and human ccRCC revealed convergence on mTOR activation, representing the third driver event after genetic inactivation of VHL and PBRM1. Our study reports a physiological preclinical ccRCC mouse model that recapitulates somatic mutations in human ccRCC and provides mechanistic and therapeutic insights into PBRM1 mutated subtypes of human ccRCC.

Recurrent SERPINB3 and SERPINB4 mutations in patients who respond to anti-CTLA4 immunotherapy.

Immune checkpoint blockade has shown significant promise as an anticancer treatment, yet the determinants of response are not completely understood. Here we show that somatic mutations in SERPINB3 and SERPINB4 are associated with survival after anti-CTLA4 immunotherapy in two independent cohorts of patients with melanoma (n = 174). Interestingly, serpins are homologs of the well-known ovalbumin antigen and are associated with autoimmunity. Our findings have implications for the personalization of immunotherapy.