David A. Nix

Patients with advanced melanoma who progress on standard-dose ipilimumab (Ipi) + nivolumab continue to have poor prognosis. Studies support a dose–response activity of Ipi, and one promising combination is Ipi 10 mg/kg (Ipi10) + temozolomide (TMZ). We performed a retrospective cohort analysis of patients with advanced melanoma treated with Ipi10 + TMZ in the immunotherapy refractory/resistant setting (n = 6, all progressed after prior Ipi + nivolumab), using similar patients treated with Ipi3 + TMZ (n = 6) as comparison. Molecular profiling by whole-exome sequencing (WES) and RNA-sequencing (RNA-seq) of tumors harvested through one responder’s treatment was performed. With a median follow up of 119 days, patients treated with Ipi10 + TMZ had a statistically significant longer median progression-free survival of 144.5 days (range 27–219) vs. 44 (26–75) in Ipi 3 mg/kg (Ipi3) + TMZ, p = 0.04, and a trend of longer median overall survival of 154.5 days (27–537) vs. 89.5 (26–548). Two patients in the Ipi10 + TMZ cohort had a partial response, and both responders had BRAF V600E mutant melanoma. RNA-seq showed enrichment of inflammatory signatures, including interferon responses in metastases after Ipi10 + TMZ compared to the primary tumor, and downregulated negative immune regulators. Ipi10 + TMZ demonstrated efficacy, including dramatic responses in patients refractory to prior Ipi + anti-PD1. Molecular data suggest a potential threshold of Ipi dose for activation of sufficient anti-tumor immune response, and higher doses are required for some patients.

In the past decade, defective DNA repair has been increasingly linked with cancer progression. Human tumors with markers of defective DNA repair and increased replication stress exhibit genomic instability and poor survival rates across tumor types. Seminal studies have demonstrated that genomic instability develops following inactivation of BRCA1, BRCA2, or BRCA-related genes. However, it is recognized that many tumors exhibit genomic instability but lack BRCA inactivation. We sought to identify a pan-cancer mechanism that underpins genomic instability and cancer progression in BRCA-wildtype tumors. Methods: Using multi-omics data from two independent consortia, we analyzed data from dozens of tumor types to identify patient cohorts characterized by poor outcomes, genomic instability, and wildtype BRCA genes. We developed several novel metrics to identify the genetic underpinnings of genomic instability in tumors with wildtype BRCA. Associated clinical data was mined to analyze patient responses to standard of care therapies and potential differences in metastatic dissemination. Results: Systematic analysis of the DNA repair landscape revealed that defective single-strand break repair, translesion synthesis, and non-homologous end-joining effectors drive genomic instability in tumors with wildtype BRCA and BRCA-related genes. Importantly, we find that loss of these effectors promotes replication stress, therapy resistance, and increased primary carcinoma to brain metastasis. Conclusions: Our results have defined a new pan-cancer class of tumors characterized by replicative instability (RIN). RIN is defined by the accumulation of intra-chromosomal, gene-level gain and loss events at replication stress sensitive (RSS) genome sites. We find that RIN accelerates cancer progression by driving copy number alterations and transcriptional program rewiring that promote tumor evolution. Clinically, we find that RIN drives therapy resistance and distant metastases across multiple tumor types.

Patient-Derived Xenografts (PDXs) are tumor-in-mouse models for cancer. PDX collections, such as those supported by the NCI PDXNet program, are powerful resources for preclinical therapeutic testing. However, variations in experimental design and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three pre-validated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers (PDTCs) using independently selected SOPs. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. Here we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-seq and RNA-Seq analysis and for evaluating growth.

With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data.

High throughput signature sequencing holds many promises, one of which is the ready identification of in vivo transcription factor binding sites, histone modifications, changes in chromatin structure and patterns of DNA methylation across entire genomes. In these experiments, chromatin immunoprecipitation is used to enrich for particular DNA sequences of interest and signature sequencing is used to map the regions to the genome (ChIP-Seq). Elucidation of these sites of DNA-protein binding/modification are proving instrumental in reconstructing networks of gene regulation and chromatin remodelling that direct development, response to cellular perturbation, and neoplastic transformation. Here we present a package of algorithms and software that makes use of control input data to reduce false positives and estimate confidence in ChIP-Seq peaks. Several different methods were compared using two simulated spike-in datasets. Use of control input data and a normalized difference score were found to more than double the recovery of ChIP-Seq peaks at a 5% false discovery rate (FDR). Moreover, both a binomial p-value/q-value and an empirical FDR were found to predict the true FDR within 2–3 fold and are more reliable estimators of confidence than a global Poisson p-value. These methods were then used to reanalyze Johnson et al.'s neuron-restrictive silencer factor (NRSF) ChIP-Seq data without relying on extensive qPCR validated NRSF sites and the presence of NRSF binding motifs for setting thresholds. The methods developed and tested here show considerable promise for reducing false positives and estimating confidence in ChIP-Seq data without any prior knowledge of the chIP target. They are part of a larger open source package freely available from http://useq.sourceforge.net/ .