Genome-wide identification of genes directly regulated by ChvI and a consensus sequence for ChvI binding in Sinorhizobium meliloti.

ExoS/ChvI two-component signaling in the nitrogen-fixing α-proteobacterium Sinorhizobium meliloti is required for symbiosis and regulates exopolysaccharide production, motility, cell envelope integrity and nutrient utilization in free-living bacteria. However, identification of many ExoS/ChvI direct transcriptional target genes has remained elusive. Here, we performed chromatin immunoprecipitation followed by microarray analysis (chIP-chip) to globally identify DNA regions bound by ChvI protein in S. meliloti. We then performed qRT-PCR with chvI mutant strains to test ChvI-dependent expression of genes downstream of the ChvI-bound DNA regions. We identified 64 direct target genes of ChvI, including exoY, rem and chvI itself. We also identified ChvI direct target candidates, like exoR, that are likely controlled by additional regulators. Analysis of upstream sequences from the 64 ChvI direct target genes identified a 15 bp-long consensus sequence. Using electrophoretic mobility shift assays and transcriptional fusions with exoY, SMb21440, SMc00084, SMc01580, chvI, and ropB1, we demonstrated this consensus sequence is important for ChvI binding to DNA and transcription of ChvI direct target genes. Thus, we have comprehensively identified ChvI regulon genes and a 'ChvI box' bound by ChvI. Many ChvI direct target genes may influence the cell envelope, consistent with the critical role of ExoS/ChvI in growth and microbe-host interactions.

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.

Functional landscapes of POLE and POLD1 mutations in checkpoint blockade-dependent antitumor immunity.

Defects in pathways governing genomic fidelity have been linked to improved response to immune checkpoint blockade therapy (ICB). Pathogenic POLE/POLD1 mutations can cause hypermutation, yet how diverse mutations in POLE/POLD1 influence antitumor immunity following ICB is unclear. Here, we comprehensively determined the effect of POLE/POLD1 mutations in ICB and elucidated the mechanistic impact of these mutations on tumor immunity. Murine syngeneic tumors harboring Pole/Pold1 functional mutations displayed enhanced antitumor immunity and were sensitive to ICB. Patients with POLE/POLD1 mutated tumors harboring telltale mutational signatures respond better to ICB than patients harboring wild-type or signature-negative tumors. A mutant POLE/D1 function-associated signature-based model outperformed several traditional approaches for identifying POLE/POLD1 mutated patients that benefit from ICB. Strikingly, the spectrum of mutational signatures correlates with the biochemical features of neoantigens. Alterations that cause POLE/POLD1 function-associated signatures generate T cell receptor (TCR)-contact residues with increased hydrophobicity, potentially facilitating T cell recognition. Altogether, the functional landscapes of POLE/POLD1 mutations shape immunotherapy efficacy.

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.

An Integrated Systems Biology Approach Identifies TRIM25 as a Key Determinant of Breast Cancer Metastasis.

At the root of most fatal malignancies are aberrantly activated transcriptional networks that drive metastatic dissemination. Although individual metastasis-associated genes have been described, the complex regulatory networks presiding over the initiation and maintenance of metastatic tumors are still poorly understood. There is untapped value in identifying therapeutic targets that broadly govern coordinated transcriptional modules dictating metastatic progression. Here, we reverse engineered and interrogated a breast cancer-specific transcriptional interaction network (interactome) to define transcriptional control structures causally responsible for regulating genetic programs underlying breast cancer metastasis in individual patients. Our analyses confirmed established pro-metastatic transcription factors, and they uncovered TRIM25 as a key regulator of metastasis-related transcriptional programs. Further, in vivo analyses established TRIM25 as a potent regulator of metastatic disease and poor survival outcome. Our findings suggest that identifying and targeting keystone proteins, like TRIM25, can effectively collapse transcriptional hierarchies necessary for metastasis formation, thus representing an innovative cancer intervention strategy.