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The identification of early breast cancer patients who may benefit from adjuvant chemotherapy has evolved to include assessment of clinicopathologic features such as tumor size and nodal status, as well as several gene-expression profiles for ER-positive, HER2-negative cancers. However, these tools do not reliably identify patients at the greatest risk of recurrence. The mutation and copy-number landscape of triple-negative breast cancer (TNBC) subtypes defined by gene expression is also largely unknown, and elucidation of this landscape may shed light on novel therapeutic opportunities. The USO01062 phase III clinical trial of standard chemotherapy (with or without capecitabine) enrolled a cohort of putatively high-risk patients based on clinical features, yet only observed a 5-year disease-free survival event rate of 11.6%. In order to uncover genomic aberrations associated with recurrence, a targeted next-generation sequencing panel was used to compare tumor specimens from patients who had a recurrence event with a matched set who did not. The somatic mutation and copy-number alteration landscapes of high-risk early breast cancer patients were characterized and alterations associated with relapse were identified. Tumor mutational burden was evaluated but was not prognostic in this study, nor did it correlate with PDL1 or CD8 gene expression. However, TNBC subtypes had substantial genomic heterogeneity with a distinct pattern of genomic alterations and putative underlying driver mutations.Implications:The present study uncovers a compendium of genomic alterations with utility to more precisely identify high-risk patients for adjuvant trials of novel therapeutic agents.

Supplementary Figures

Supplemental Methods describing NGS and gene expression studies.

With only a fraction of patients responding to cancer immunotherapy, a better understanding of the entire tumor microenvironment is needed. Using single-cell transcriptomics, we chart the fibroblastic landscape during pancreatic ductal adenocarcinoma (PDAC) progression in animal models. We identify a population of carcinoma-associated fibroblasts (CAF) that are programmed by TGFβ and express the leucine-rich repeat containing 15 (LRRC15) protein. These LRRC15+ CAFs surround tumor islets and are absent from normal pancreatic tissue. The presence of LRRC15+ CAFs in human patients was confirmed in >80,000 single cells from 22 patients with PDAC as well as by using IHC on samples from 70 patients. Furthermore, immunotherapy clinical trials comprising more than 600 patients across six cancer types revealed elevated levels of the LRRC15+ CAF signature correlated with poor response to anti–PD-L1 therapy. This work has important implications for targeting nonimmune elements of the tumor microenvironment to boost responses of patients with cancer to immune checkpoint blockade therapy.Significance:This study describes the single-cell landscape of CAFs in pancreatic cancer during in vivo tumor evolution. A TGFβ-driven, LRRC15+ CAF lineage is associated with poor outcome in immunotherapy trial data comprising multiple solid-tumor entities and represents a target for combinatorial therapy.This article is highlighted in the In This Issue feature, p. 161

FoundationOne sequencing data for n=399 breast cancer population. Each sheet contains a distinct type of alteration. The clinical covariates used in our analysis are included.

Enriched Pathway Analysis.

Supplemental figures 1,2,4-8 as supporting figures to the manuscript.

Purpose: We sought to identify predictive biomarkers for a novel nicotinamide phosphoribosyltransferase (NAMPT) inhibitor.Experimental Design: We use a NAMPT inhibitor, GNE-617, to evaluate nicotinic acid rescue status in a panel of more than 400 cancer cell lines. Using correlative analysis and RNA interference (RNAi), we identify a specific biomarker for nicotinic acid rescue status. We next determine the mechanism of regulation of expression of the biomarker. Finally, we develop immunohistochemical (IHC) and DNA methylation assays and evaluate cancer tissue for prevalence of the biomarker across indications.Results: Nicotinate phosphoribosyltransferase (NAPRT1) is necessary for nicotinic acid rescue and its expression is the major determinant of rescue status. We demonstrate that NAPRT1 promoter methylation accounts for NAPRT1 deficiency in cancer cells, and NAPRT1 methylation is predictive of rescue status in cancer cell lines. Bisulfite next-generation sequencing mapping of the NAPRT1 promoter identified tumor-specific sites of NAPRT1 DNA methylation and enabled the development of a quantitative methylation-specific PCR (QMSP) assay suitable for use on archival formalin-fixed paraffin-embedded tumor tissue.Conclusions: Tumor-specific promoter hypermethylation of NAPRT1 inactivates one of two NAD salvage pathways, resulting in synthetic lethality with the coadministration of a NAMPT inhibitor. NAPRT1 expression is lost due to promoter hypermethylation in most cancer types evaluated at frequencies ranging from 5% to 65%. NAPRT1-specific immunohistochemical or DNA methylation assays can be used on archival formalin paraffin-embedded cancer tissue to identify patients likely to benefit from coadministration of a Nampt inhibitor and nicotinic acid. Clin Cancer Res; 19(24); 6912–23. ©2013 AACR.

XLSX file - 602KB, Supplementary Table 5. Cancer cell lines analyzed in this study. Supplementary Table 6. Tumor tissues analyzed in this study. Supplementary Table 7. List of 340 well characterized hotspot mutations interrogated by the amplicon libraries in this study. Variants also assayed by asPCR are indicated. Supplementary Table 8. Variants detected in 66 cancer cell lines, after applying post-processing filters. Note that indels and predicted deleterious SNVs are reported for all interrogated genes and transcripts. Supplementary Table 9. Variants detected in 73 FFPE endometrial tumor tissues, after applying post-processing filters. Note that indels and predicted deleterious SNVs are reported for all interrogated genes and transcripts. Supplementary Table 10. For cell line data, concordance with COSMIC somatic mutation annotation.

PDF file 122K, A) Chemical structure of GNE-617, B) cellular NAD and ATP levels in H522 cells after exposure to 4nM GNE-617, C) correlation of NAPRT1 mRNA and protein (n=32, spearman r= 0.88, p,0.0001)

PDF file - 731KB, Supplementary Figure 1. Schematic workflow of MMP-seq. Supplementary Figure 2. Examples of tiling and hotspot amplicon designs. Supplementary Figure 3. Consistent target enrichment and variant allele quantification in FF biological replicates. Supplementary Figure 4. Correlation between called variant frequencies in paired FF and FFPE samples. Supplementary Figure 5. UDG treatment improves sequencing specificity but has no impact on sensitivity. Supplementary Figure 6. PIK3R1 mutation profiles from TCGA endometrial cancer study. Supplementary Table 1. MMP-seq target genes. Supplementary Table 2. Latin Square Design. Supplementary Table 3. Latin square mutation read frequency detected when sequencing input cell lines for Latin square cross-dilutions. Supplementary Table 4. Pretreatment of FFPE DNA samples with uracil-DNA glycosylase (UDG) resulted in markedly reduction of false positives.

Purpose: Non–small cell lung cancers (NSCLC) comprise multiple distinct biologic groups with different prognoses. For example, patients with epithelial-like tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like tumors. Here, we test the hypothesis that epithelial-like NSCLCs can be distinguished from mesenchymal-like NSCLCs on the basis of global DNA methylation patterns.Experimental Design: To determine whether phenotypic subsets of NSCLCs can be defined on the basis of their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative reverse transcriptase PCR and methylation-specific PCR in formalin-fixed biopsies from patients with NSCLC who went on to fail front-line chemotherapy.Results: We show that patterns of methylation divide NSCLCs into epithelial-like and mesenchymal-like subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple differentially methylated regions, including one in ERBB2 and one in ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from patients with NSCLC who went on to fail front-line chemotherapy.Conclusions: Our data show that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used as a platform for predictive biomarker discovery and development. Clin Cancer Res; 18(8); 2360–73. ©2012 AACR.

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CCR Translation for This Article from DNA Methylation Profiling Defines Clinically Relevant Biological Subsets of Non–Small Cell Lung Cancer

PDF file 141K, Supplementary methods for NAD quantification and the QMSP assay. Table S1 GNE-617 IC50 and mRNA Levels of NAMPT and NAPRT1, Table S2 Cell Lines Not Rescued with 10uM NA, Table S3 Cell Lines with Low NAPRT1 Expression

Purpose: Tailoring cancer treatment to tumor molecular characteristics promises to make personalized medicine a reality. However, reliable genetic profiling of archived clinical specimens has been hindered by limited sensitivity and high false-positive rates. Here, we describe a novel methodology, MMP-seq, which enables sensitive and specific high-throughput, high-content genetic profiling in archived clinical samples.Experimental Design: We first validated the technical performance of MMP-seq in 66 cancer cell lines and a Latin square cross-dilution of known somatic mutations. We next characterized the performance of MMP-seq in 17 formalin-fixed paraffin-embedded (FFPE) clinical samples using matched fresh-frozen tissue from the same tumors as benchmarks. To demonstrate the potential clinical utility of our methodology, we profiled FFPE tumor samples from 73 patients with endometrial cancer.Results: We demonstrated that MMP-seq enabled rapid and simultaneous profiling of a panel of 88 cancer genes in 48 samples, and detected variants at frequencies as low as 0.4%. We identified DNA degradation and deamination as the main error sources and developed practical and robust strategies for mitigating these issues, and dramatically reduced the false-positive rate. Applying MMP-seq to a cohort of endometrial tumor samples identified extensive, potentially actionable alterations in the PI3K (phosphoinositide 3-kinase) and RAS pathways, including novel PIK3R1 hotspot mutations that may disrupt negative regulation of PIK3CA.Conclusions: MMP-seq provides a robust solution for comprehensive, reliable, and high-throughput genetic profiling of clinical tumor samples, paving the way for the incorporation of genomic-based testing into clinical investigation and practice. Clin Cancer Res; 20(8); 2080–91. ©2014 AACR.

XLSX file - 65K, Gene Ontology analysis of gene over-expressed and amplified in the tumour samples.

XLSX file - 39K, Gene copy number and ecpression (by Affymetrix and TaqMan) in cell lines used to screen for hits.

XLSX file - 37K, Supplementary materials and methods (cell lines, STR profiles, primers, antibodies, molecular reagents).

XLSX file - 419K, List of genes screened in the first and second round screens.

XLSX file - 112K, GISTIC analysis of tumour samples.

XLSX file - 29K, Analysis of expression (cancer versus normal) and association with outcome for PSMB4 and SHMT2.

Fibroblasts are non-haematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and have key roles in fibrosis, cancer, autoimmunity and wound healing1. Recent studies have described fibroblast heterogeneity within individual tissues1. However, the field lacks a characterization of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here we constructed fibroblast atlases by integrating single-cell transcriptomic data from about 230,000 fibroblasts across 17 tissues, 50 datasets, 11 disease states and 2 species. Mouse fibroblast atlases and a DptIRESCreERT2 knock-in mouse identified two universal fibroblast transcriptional subtypes across tissues. Our analysis suggests that these cells can serve as a reservoir that can yield specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts in disease. Comparison to an atlas of human fibroblasts from perturbed states showed that fibroblast transcriptional states are conserved between mice and humans, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In summary, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution has identified key organizing principles of the fibroblast lineage in health and disease. Single-cell and genetic tools are used to characterize the diversity of fibroblasts across healthy and perturbed tissues in mice and humans.

Fibroblastic reticular cells (FRCs) are specialized stromal cells that define tissue architecture and regulate lymphocyte compartmentalization, homeostasis, and innate and adaptive immunity in secondary lymphoid organs (SLOs). In the present study, we used single-cell RNA sequencing (scRNA-seq) of human and mouse lymph nodes (LNs) to identify a subset of T cell-zone FRCs defined by the expression of Gremlin1 (Grem1) in both species. Grem1-CreERT2 knock-in mice enabled localization, multi-omics characterization and genetic depletion of Grem1+ FRCs. Grem1+ FRCs primarily localize at T-B cell junctions of SLOs, neighboring pre-dendritic cells and conventional dendritic cells (cDCs). As such, their depletion resulted in preferential loss and decreased homeostatic proliferation and survival of resident cDCs and compromised T cell immunity. Trajectory analysis of human LN scRNA-seq data revealed expression similarities to murine FRCs, with GREM1+ cells marking the endpoint of both trajectories. These findings illuminate a new Grem1+ fibroblastic niche in LNs that functions to maintain the homeostasis of lymphoid tissue-resident cDCs.

With only a fraction of patients responding to cancer immunotherapy, a better understanding of the entire tumor microenvironment is needed. Using single-cell transcriptomics, we chart the fibroblastic landscape during pancreatic ductal adenocarcinoma (PDAC) progression in animal models. We identify a population of carcinoma-associated fibroblasts (CAF) that are programmed by TGFβ and express the leucine-rich repeat containing 15 (LRRC15) protein. These LRRC15+ CAFs surround tumor islets and are absent from normal pancreatic tissue. The presence of LRRC15+ CAFs in human patients was confirmed in >80,000 single cells from 22 patients with PDAC as well as by using IHC on samples from 70 patients. Furthermore, immunotherapy clinical trials comprising more than 600 patients across six cancer types revealed elevated levels of the LRRC15+ CAF signature correlated with poor response to anti–PD-L1 therapy. This work has important implications for targeting nonimmune elements of the tumor microenvironment to boost responses of patients with cancer to immune checkpoint blockade therapy. Significance: This study describes the single-cell landscape of CAFs in pancreatic cancer during in vivo tumor evolution. A TGFβ-driven, LRRC15+ CAF lineage is associated with poor outcome in immunotherapy trial data comprising multiple solid-tumor entities and represents a target for combinatorial therapy. This article is highlighted in the In This Issue feature, p. 161

BackgroundIndividualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types.MethodsWe combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting.ResultsBranching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. In colorectal, renal, and bladder cancer, most tumors had few globally clonal neoantigens. Prioritizing mutations with higher purity-adjusted and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases.ConclusionsWe show that tumor type, multilesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection, and may also be important factors to consider in the development of biomarker strategies.

Most colorectal (CRC) tumors are dependent on EGFR/KRAS/BRAF/MAPK signaling activation. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated CRC tumors. Here we show that anti-EGFR but not anti-VEGF treatment enriches for emerging ARID1A mutations in CRC patients. In addition, we find that patients with ARID1A mutations, at baseline, are associated with worse outcome when treated with cetuximab- but not bevacizumab-containing therapies; thus, this suggests that ARID1A mutations may provide both an acquired and intrinsic mechanism of resistance to anti-EGFR therapies. We find that, ARID1A and EGFR-pathway genetic alterations are mutually exclusive across lung and colorectal cancers, further supporting a functional connection between these pathways. Our results not only suggest that ARID1A could be potentially used as a predictive biomarker for cetuximab treatment decisions but also provide a rationale for exploring therapeutic MAPK inhibition in an unexpected but genetically defined segment of CRC patients.

The identification of early breast cancer patients who may benefit from adjuvant chemotherapy has evolved to include assessment of clinicopathologic features such as tumor size and nodal status, as well as several gene-expression profiles for ER-positive, HER2-negative cancers. However, these tools do not reliably identify patients at the greatest risk of recurrence. The mutation and copy-number landscape of triple-negative breast cancer (TNBC) subtypes defined by gene expression is also largely unknown, and elucidation of this landscape may shed light on novel therapeutic opportunities. The USO01062 phase III clinical trial of standard chemotherapy (with or without capecitabine) enrolled a cohort of putatively high-risk patients based on clinical features, yet only observed a 5-year disease-free survival event rate of 11.6%. In order to uncover genomic aberrations associated with recurrence, a targeted next-generation sequencing panel was used to compare tumor specimens from patients who had a recurrence event with a matched set who did not. The somatic mutation and copy-number alteration landscapes of high-risk early breast cancer patients were characterized and alterations associated with relapse were identified. Tumor mutational burden was evaluated but was not prognostic in this study, nor did it correlate with PDL1 or CD8 gene expression. However, TNBC subtypes had substantial genomic heterogeneity with a distinct pattern of genomic alterations and putative underlying driver mutations. Implications: The present study uncovers a compendium of genomic alterations with utility to more precisely identify high-risk patients for adjuvant trials of novel therapeutic agents.

Significance T cells recognize their targets via their T-cell receptors (TCRs), which in the case of CD8+ T cells bind to MHC-I:antigen complexes on the surface of target cells. Many cancer cells evade immune recognition and killing by down-regulating MHC-I AgPPM. Here, we show how the histone acetyl transferases p300/CBP together with NF-κB epigenetically regulate expression of MHC-I molecules, immunoproteasome subunits, and peptide transporter to enable proper MHC-I antigen presentation. Notably, this pathway is frequently disrupted in human cancers. We now show that certain chemotherapeutics can augment MHC-I antigen presentation via NF-κB and p300/CBP activation, thereby enhancing cancer cell recognition and killing by effector CD8+ CTLs., Many cancers evade immune rejection by suppressing major histocompatibility class I (MHC-I) antigen processing and presentation (AgPP). Such cancers do not respond to immune checkpoint inhibitor therapies (ICIT) such as PD-1/PD-L1 [PD-(L)1] blockade. Certain chemotherapeutic drugs augment tumor control by PD-(L)1 inhibitors through potentiation of T-cell priming but whether and how chemotherapy enhances MHC-I–dependent cancer cell recognition by cytotoxic T cells (CTLs) is not entirely clear. We now show that the lysine acetyl transferases p300/CREB binding protein (CBP) control MHC-I AgPPM expression and neoantigen amounts in human cancers. Moreover, we found that two distinct DNA damaging drugs, the platinoid oxaliplatin and the topoisomerase inhibitor mitoxantrone, strongly up-regulate MHC-I AgPP in a manner dependent on activation of nuclear factor kappa B (NF-κB), p300/CBP, and other transcription factors, but independently of autocrine IFNγ signaling. Accordingly, NF-κB and p300 ablations prevent chemotherapy-induced MHC-I AgPP and abrogate rejection of low MHC-I–expressing tumors by reinvigorated CD8+ CTLs. Drugs like oxaliplatin and mitoxantrone may be used to overcome resistance to PD-(L)1 inhibitors in tumors that had “epigenetically down-regulated,” but had not permanently lost MHC-I AgPP activity.

Fibroblasts are non-hematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and play key roles in fibrosis, cancer, autoimmunity and wound healing. Recent studies have described fibroblast heterogeneity within individual tissues. However, the field lacks a definition of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here, we integrated single-cell RNA transcriptomic data from ~150,000 fibroblast cells derived from 16 steady- and 11 perturbed-state mouse organs into fibroblast atlases. These data revealed two universal fibroblast cell subtypes, marked by expression of Pi16 or Col15a1, in all tissues; it also revealed discrete subsets of five specialized fibroblast subtypes in steady-state tissues and three activated fibroblast subtypes in perturbed or diseased tissues. These subsets were transcriptionally shaped by microenvironmental context rather than tissue-type alone. Inference of fibroblast lineage structure from the murine steady-state and perturbed-state fibroblast atlases suggested that specialized and activated subtypes are developmentally related to universal tissue-resident fibroblasts. Analysis of human samples revealed that fibroblast subtypes found in mice are conserved between species, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In sum, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution enabled us to define the organizing principles of the fibroblast lineage in health and disease.

Background Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC. Methods and findings We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions—stromal, proliferative and immune—that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study. Conclusions This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease’s unique biology.

Background We aimed to develop a gene expression–based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations. Methods Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as “ATE”), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net–selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts. Results NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P Conclusions The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma.