Senescence of human pancreatic beta cells enhances functional maturation through chromatin reorganization and promotes interferon responsiveness

Senescent cells can influence the function of tissues in which they reside, and their propensity for disease. A portion of adult human pancreatic beta cells express the senescence marker p16, yet it is unclear whether they are in a senescent state, and how this affects insulin secretion. We analyzed single-cell transcriptome datasets of adult human beta cells, and found that p16-positive cells express senescence gene signatures, as well as elevated levels of beta-cell maturation genes, consistent with enhanced functionality. Senescent human beta-like cells in culture undergo chromatin reorganization that leads to activation of enhancers regulating functional maturation genes and acquisition of glucose-stimulated insulin secretion capacity. Strikingly, Interferon-stimulated genes are elevated in senescent human beta cells, but genes encoding senescence-associated secretory phenotype (SASP) cytokines are not. Senescent beta cells in culture and in human tissue show elevated levels of cytoplasmic DNA, contributing to their increased interferon responsiveness. Human beta-cell senescence thus involves chromatin-driven upregulation of a functional-maturation program, and increased responsiveness of interferon-stimulated genes, changes that could increase both insulin secretion and immune reactivity.

Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Spatial analysis of human lung cancer reveals organized immune hubs enriched for stem-like CD8 T cells and associated with immunotherapy response

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially-localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens, and found that they were associated with beneficial responses to PD-1-blockade. Immunity hubs were enriched for many interferon-stimulated genes, T cells in multiple differentiation states, and CXCL9/10/11 + macrophages that preferentially interact with CD8 T cells. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcomes, distinct from mature tertiary lymphoid structures, and enriched for stem-like TCF7+PD-1+ CD8 T cells and activated CCR7 + LAMP3 + dendritic cells, as well as chemokines that organize these cells. These results elucidate the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Efficacy and safety of metabolic interventions for the treatment of severe COVID-19: in vitro, observational, and non-randomized open-label interventional study

Background

Viral infection is associated with a significant rewire of the host metabolic pathways, presenting attractive metabolic targets for intervention.

Methods

We chart the metabolic response of lung epithelial cells to SARS-CoV-2 infection in primary cultures and COVID-19 patient samples and perform in vitro metabolism-focused drug screen on primary lung epithelial cells infected with different strains of the virus. We perform observational analysis of Israeli patients hospitalized due to COVID-19 and comparative epidemiological analysis from cohorts in Italy and the Veteran's Health Administration in the United States. In addition, we perform a prospective non-randomized interventional open-label study in which 15 patients hospitalized with severe COVID-19 were given 145 mg/day of nanocrystallized fenofibrate added to the standard of care.

Results

SARS-CoV-2 infection produced transcriptional changes associated with increased glycolysis and lipid accumulation. Metabolism-focused drug screen showed that fenofibrate reversed lipid accumulation and blocked SARS-CoV-2 replication through a PPARα-dependent mechanism in both alpha and delta variants. Analysis of 3233 Israeli patients hospitalized due to COVID-19 supported in vitro findings. Patients taking fibrates showed significantly lower markers of immunoinflammation and faster recovery. Additional corroboration was received by comparative epidemiological analysis from cohorts in Europe and the United States. A subsequent prospective non-randomized interventional open-label study was carried out on 15 patients hospitalized with severe COVID-19. The patients were treated with 145 mg/day of nanocrystallized fenofibrate in addition to standard-of-care. Patients receiving fenofibrate demonstrated a rapid reduction in inflammation and a significantly faster recovery compared to patients admitted during the same period.

Conclusions

Taken together, our data suggest that pharmacological modulation of PPARα should be strongly considered as a potential therapeutic approach for SARS-CoV-2 infection and emphasizes the need to complete the study of fenofibrate in large randomized controlled clinical trials.

Funding

Funding was provided by European Research Council Consolidator Grants OCLD (project no. 681870) and generous gifts from the Nikoh Foundation and the Sam and Rina Frankel Foundation (YN). The interventional study was supported by Abbott (project FENOC0003).

Clinical trial number

NCT04661930.

Multimodal single-cell and whole-genome sequencing of small, frozen clinical specimens

Single-cell genomics enables dissection of tumor heterogeneity and molecular underpinnings of drug response at an unprecedented resolution1-11. However, broad clinical application of these methods remains challenging, due to several practical and preanalytical challenges that are incompatible with typical clinical care workflows, namely the need for relatively large, fresh tissue inputs. In the present study, we show that multimodal, single-nucleus (sn)RNA/T cell receptor (TCR) sequencing, spatial transcriptomics and whole-genome sequencing (WGS) are feasible from small, frozen tissues that approximate routinely collected clinical specimens (for example, core needle biopsies). Compared with data from sample-matched fresh tissue, we find a similar quality in the biological outputs of snRNA/TCR-seq data, while reducing artifactual signals and compositional biases introduced by fresh tissue processing. Profiling sequentially collected melanoma samples from a patient treated in the KEYNOTE-001 trial12, we resolved cellular, genomic, spatial and clonotype dynamics that represent molecular patterns of heterogeneous intralesional evolution during anti-programmed cell death protein 1 therapy. To demonstrate applicability to banked biospecimens of rare diseases13, we generated a single-cell atlas of uveal melanoma liver metastasis with matched WGS data. These results show that single-cell genomics from archival, clinical specimens is feasible and provides a framework for translating these methods more broadly to the clinical arena.

Mouse fetal growth restriction through parental and fetal immune gene variation and intercellular communications cascade

Fetal growth restriction (FGR) affects 5-10% of pregnancies, and can have serious consequences for both mother and child. Prevention and treatment are limited because FGR pathogenesis is poorly understood. Genetic studies implicate KIR and HLA genes in FGR, however, linkage disequilibrium, genetic influence from both parents, and challenges with investigating human pregnancies make the risk alleles and their functional effects difficult to map. Here, we demonstrate that the interaction between the maternal KIR2DL1, expressed on uterine natural killer (NK) cells, and the paternally inherited HLA-C*0501, expressed on fetal trophoblast cells, leads to FGR in a humanized mouse model. We show that the KIR2DL1 and C*0501 interaction leads to pathogenic uterine arterial remodeling and modulation of uterine NK cell function. This initial effect cascades to altered transcriptional expression and intercellular communication at the maternal-fetal interface. These findings provide mechanistic insight into specific FGR risk alleles, and provide avenues of prevention and treatment.

641 Spatially organized multicellular immune hubs in MMRd and MMRp colorectal cancer

Background

Immune responses to cancer are highly variable, with DNA mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. Almost all tumors are infiltrated with immune cells, but the types of immune responses and their effects on tumor growth, metastasis and death, vary greatly between different cancers and individual tumors. Which of the numerous cell subsets in a tumor contribute to the response, how their interactions are regulated, and how they are spatially organized within tumors remains poorly understood.

Methods

To understand the rules governing these varied responses, we transcriptionally profiled 371,223 single cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd treatment-naive patients. We developed a systematic approach to discover cell types, their underlying gene programs, and cellular communities based on single cell RNA-seq (scRNAseq) profiles and applied it to study the distinguishing features of human MMRd and MMRp colorectal cancer. Cellular communities discovered from this analysis were spatially mapped in tissue sections using multiplex RNA in situ hybridization microscopy.

Results

To understand the basis for differential immune responses in CRC, we first determined and compared the immune cell composition of MMRd and MMRp CRC and normal colon tissue, finding dramatic remodeling between tumor and normal tissue and between MMRd and MMRp tumors, particularly within the myeloid, T cell, and stromal compartments. Among the clusters enriched in MMRd tumors were activated CXCL13+ CD8 T cells. Importantly, gene program co-variation analysis revealed multicellular networks. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage, and an MMRd-enriched immune hub within the tumor, with activated IFNG+ and CXCL13+ T cells together with malignant and myeloid cells expressing T-cell-attracting chemokines (figure 1).

Conclusions

Our study provides a rich dataset of cellular states, gene programs and their transformations in tumors across a relatively large cohort of patients with colorectal cancer. Our predictions of several multicellular hubs based on co-variation of gene expression programs, and subsequent spatial localization of two major immune-malignant hubs, organizes a large set of cell states and programs into a smaller number of coordinated networks of cells and processes. Understanding the molecular mechanisms underlying these hubs, and studying their temporal and spatial regulation upon treatment will be critical for advancing cancer therapy.

Ethics Approval

This study was approved by the DF-HCC institutional review board (protocols 03-189 and 02-240).

Abstract 641 Figure 1

A coordinated network of CXCL13+ T cells with myeloid and malignant cells expressing ISGs. Image shows a portion of formalin-fixed paraffin-embedded tissue from an MMRd CRC specimen stained with multiplex RNA ISH / IF for PanCK-IF, CD3E-ISH, CXCL10/CXCL11-ISH, CXCL13-ISH, and IFNG-ISH. Note IFNG+ and CXCL13+ cells in proximity to cells expressing the chemokines CXCL10/CXCL11

Implications of Intratumor Heterogeneity on Consensus Molecular Subtype (CMS) in Colorectal Cancer

The implications of intratumor heterogeneity on the four consensus molecular subtypes (CMS) of colorectal cancer (CRC) are not well known. Here, we use single-cell RNA sequencing (scRNASeq) to build an algorithm to assign CMS classification to individual cells, which we use to explore the distributions of CMSs in tumor and non-tumor cells. A dataset of colorectal tumors with bulk RNAseq (n = 3232) was used to identify CMS specific-marker gene sets. These gene sets were then applied to a discovery dataset of scRNASeq profiles (n = 10) to develop an algorithm for single-cell CMS (scCMS) assignment, which recapitulated the intrinsic biology of all four CMSs. The single-cell CMS assignment algorithm was used to explore the scRNASeq profiles of two prospective CRC tumors with mixed CMS via bulk sequencing. We find that every CRC tumor contains individual cells of each scCMS, as well as many individual cells that have enrichment for features of more than one scCMS (called mixed cells). scCMS4 and scCMS1 cells dominate stroma and immune cell clusters, respectively, but account for less than 3% epithelial cells. These data imply that CMS1 and CMS4 are driven by the transcriptomic contribution of immune and stromal cells, respectively, not tumor cells.

Spatially organized multicellular immune hubs in human colorectal cancer

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd individuals. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across tumors from affected individuals and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T cell-attracting chemokines. By identifying interacting cellular programs, we reveal the logic underlying spatially organized immune-malignant cell networks.

Multicellular immune hubs and their organization in MMRd and MMRp colorectal cancer

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd patients. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across patient tumors and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage, and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T-cell-attracting chemokines. By identifying interacting cellular programs, we thus reveal the logic underlying spatially organized immune-malignant cell networks.

A Distinct Transcriptional Program in Human CAR T Cells Bearing the 4-1BB Signaling Domain Revealed by scRNA-Seq

T cells engineered to express chimeric antigen receptors (CARs) targeting CD19 have produced impressive outcomes for the treatment of B cell malignancies, but different products vary in kinetics, persistence, and toxicity profiles based on the co-stimulatory domains included in the CAR. In this study, we performed transcriptional profiling of bulk CAR T cell populations and single cells to characterize the transcriptional states of human T cells transduced with CD3ζ, 4-1BB-CD3ζ (BBζ), or CD28-CD3ζ (28ζ) co-stimulatory domains at rest and after activation by triggering their CAR or their endogenous T cell receptor (TCR). We identified a transcriptional signature common across CARs with the CD3ζ signaling domain, as well as a distinct program associated with the 4-1BB co-stimulatory domain at rest and after activation. CAR T cells bearing BBζ had increased expression of human leukocyte antigen (HLA) class II genes, ENPP2, and interleukin (IL)-21 axis genes, and decreased PD1 compared to 28ζ CAR T cells. Similar to previous studies, we also found BBζ CAR CD8 T cells to be enriched in a central memory cell phenotype and fatty acid metabolism genes. Our data uncovered transcriptional signatures related to costimulatory domains and demonstrated that signaling domains included in CARs uniquely shape the transcriptional programs of T cells.

Abstract 5722: Acquired stemness by luminal cells

Rare cell types in the prostate are reported to have stem cell properties based on organ regeneration potential following castration. Here, we use single cell RNA-seq (scRNA-Seq) to characterize these populations from the murine and human prostate in hormonally intact and androgen deprived conditions. Prostate cells from hormonally intact mice partitioned into one large subset of basal epithelial cells, another large subset of luminal epithelial cells, which we designate luminal 1 and two rare luminal populations: luminal 2 and luminal 3. Luminal cells that persist following castration display enhanced organoid regeneration potential, particularly within 1-2 days of androgen addback, and contribute equipotently to prostatic regeneration as revealed by lineage tracing. This regeneration is mediated, in part, through the orchestrated expression of Nrg2, Igf1, Fgf10 and Rspo3 by distinct populations of androgen-responsive mesenchymal and smooth muscle cells. Thus, luminal cells that persist post-castration undergo a cell state change that primes a proliferative response to microenvironment signals, analogous to other models of tissue injury such as liver damage.

Citation Format: Wouter Karthaus, Matan Hofree, Danielle Choi, Eliot L. Linton, Mesruh Turkekul, Alborz Bejnood, Brett Carver, Anuhandra Gopalan, Vincent Laudone, Moshe Biton, Ojasvi Chaudhary, Ignas Masilionis, Linas Mazutis, Dana Pe'er, Aviv Regev, Charles Sawyers. Acquired stemness by luminal cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5722.

Emergence of a High-Plasticity Cell State during Lung Cancer Evolution

Tumor evolution from a single cell into a malignant, heterogeneous tissue remains poorly understood. Here, we profile single-cell transcriptomes of genetically engineered mouse lung tumors at seven stages, from pre-neoplastic hyperplasia to adenocarcinoma. The diversity of transcriptional states increases over time and is reproducible across tumors and mice. Cancer cells progressively adopt alternate lineage identities, computationally predicted to be mediated through a common transitional, high-plasticity cell state (HPCS). Accordingly, HPCS cells prospectively isolated from mouse tumors and human patient-derived xenografts display high capacity for differentiation and proliferation. The HPCS program is associated with poor survival across human cancers and demonstrates chemoresistance in mice. Our study reveals a central principle underpinning intra-tumoral heterogeneity and motivates therapeutic targeting of the HPCS.

Author Correction: A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Regenerative potential of prostate luminal cells revealed by single-cell analysis

Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1 ⁺ and Psca ⁺) and a large population of differentiated cells (Nkx3.1 ⁺, Pbsn ⁺). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells.

A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis

Genome-wide association studies (GWAS) have revealed risk alleles for ulcerative colitis (UC). To understand their cell type specificities and pathways of action, we generate an atlas of 366,650 cells from the colon mucosa of 18 UC patients and 12 healthy individuals, revealing 51 epithelial, stromal, and immune cell subsets, including BEST4⁺ enterocytes, microfold-like cells, and IL13RA2⁺IL11⁺ inflammatory fibroblasts, which we associate with resistance to anti-TNF treatment. Inflammatory fibroblasts, inflammatory monocytes, microfold-like cells, and T cells that co-express CD8 and IL-17 expand with disease, forming intercellular interaction hubs. Many UC risk genes are cell type specific and co-regulated within relatively few gene modules, suggesting convergence onto limited sets of cell types and pathways. Using this observation, we nominate and infer functions for specific risk genes across GWAS loci. Our work provides a framework for interrogating complex human diseases and mapping risk variants to cell types and pathways.

Abstract GS6-05: A joint atlas of single-cell and bulk RNA-seq in metastatic breast cancer allows inference of oncogenic and drug-resistant transcriptional programs in malignant cells and the tumor microenvironment

While recent studies have begun to elucidate the genomics of metastatic breast cancer (MBC), the transcriptional programs (progs) that drive the drug-resistant phenotype remain poorly understood.

We prospectively collected biopsies from patients with MBC with detailed clinicopathologic features, including treatment and response characteristics. We profiled 29 biopsies by single-cell RNA seq, as well as bulk RNA-seq and whole exome sequencing on an additional 207 biopsies (analyzed snapshot, ongoing study). We analyzed these data to generate an atlas, delineating the cell-types, cell-states, and transcriptional progs.

We profiled 100,470 single cell transcriptomes and generated a comprehensive MBC atlas of the tumor and tumor microenvironment (TME). We next inferred cell types and progs associated with clinicopathologic characteristics. For example, we found significant differences in the TME of liver metastases compared to other sites, consistent with immunosuppression in the hepatic space. In particular, liver metastases were depleted in activated B-cells (lower CD69, TCL1A, VPREB3, BCNP1, and several activation-related chemokines - CXCR4/5/6/7), and their infiltrating T-cells expressed lower levels of effector and cytotoxicity markers (table=T) including CD8, CD3, beta chemokines CCL4/CCL5, IFI16, PRF1, granzymes, and GNLY, and exceptionally low expression of antigen processing genes (T).

To increase our power to make clinically relevant associations, we performed a joint analysis of the single-cell and bulk RNA-Seq data, to identify malignant cell progs related to specific oncogenic mutations, with implications for metastatic and drug-resistance phenotypes. For example, we characterized the oncogenic prog associated with activating estrogen receptor mutation (ESR1-mut). As expected, ESR1-mut prog overlaps with many known ER and luminal B markers (T). ESR1-mut prog also included specific Interferon-stimulated genes (ISGs) - IFI6, ISG15, IFIT1, STAT1, which are associated with tamoxifen resistance (T) and ECM-mediated regulation of apoptosis (T). These ISGs are predictive of poor prognosis among endocrine-treated patients (HR=1.69. p=1e-04, n=929, kmplotter). The ESR1-mut prog also included genes associated with cell-migration (SOX9, AGR2, TXNIP and several S100 genes). This suggests a role for ESR1 mutation in pathogenicity, beyond ligand-independent activation of ER signaling. A second malignant cell prog was associated with RB-null. While most of these genes were highly correlated with cell-cycle (R=0.4), some do not (HINT1, RHOC, SNRPB, ANAPC11, TMEM208, POLR2J). In spite of decoupling from proliferation, these still predict of poor outcome across breast cancer (HR=1.41, p= 6.0e-10, n=3951, kmplotter). We characterized the prog of high-grade tumors in our cohort, and found a strong association with RB-null prog (T). Similarly, we recovered additional mutation-specific oncogenic progs, including for TP53, GATA3, FOXA1, HER2, and FGFR mutants, forming a compendium of in-vivo oncogenic signatures.

To the best of our knowledge these data represent the first integration of single cell and bulk RNA-seq data in MBC, resulting in a comprehensive single-cell-resolution transcriptional atlas, and a catalog of drug-resistance oncogenic progs with implications for immunotherapy and precision-oncology.

Single-cell In-vivo programComparison Gene setAssociationP-value(top genes)(MSigDB name, PubMed ID, when applicable)Odds-ratio(Fisher''''s Exact test, two-sided)Depleted in liver T-cellsEffectors-cells markers4.077.29E-07(compared to other metastatic site - Bone, Skin, Chest-wall, Lymph node, Breast-met)(PMID: 28052254)""Antigen processing markers32.17.26E-07(PMID: 28052254)ESR1-mutVANTVEER_BREAST_CANCER_ESR1_UP5.82.30E-11(Enriched in ESR1-mutatated)(PMID: 11823860)“SMID_BREAST_CANCER_LUMINAL_B_UP5.898.10E-12“”DOANE_BREAST_CANCER_ESR1_UP6.30812.10E-09""BOWIE_RESPONSE_TO_TAMOXIFEN10.360.00036(PMID 17016442)""BECKER_TAMOXIFEN_RESISTANCE_UP7.81.20E-06(PMID 15657362)""BOWIE_RESPONSE_TO_EXTRACELLULAR_MATRIX8.240.0028(PMID 17016442)Enriched in RB-nullEnriched in High-grade (from our study)23.97.50E-05

Citation Format: Ofir Cohen, Daniel Abravanel, Michal Slyper, Johanna Klughammer, Judit Jane-Valbuena, Karla Helvie, Laura Dellostritto, Allison Frangieh, Sebastien Vigneau, Jingyi Wu, Angie Mayorga, Julia Waldman, Lan Nguyen, Danielle Dionne, Orr Ashenberg, Matan Hofree, Mike Cuoco, Christopher Rodman, Eric P Winer, Nancy Lin, Bruce Johnson, Asaf Rotem, Orit Rozenblatt-Rosen, Aviv Regev, Nikhil Wagle. A joint atlas of single-cell and bulk RNA-seq in metastatic breast cancer allows inference of oncogenic and drug-resistant transcriptional programs in malignant cells and the tumor microenvironment [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr GS6-05.

Synthetic Essentiality of Metabolic Regulator PDHK1 in PTEN-Deficient Cells and Cancers

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is a tumor suppressor and bi-functional lipid and protein phosphatase. We report that the metabolic regulator pyruvate dehydrogenase kinase1 (PDHK1) is a synthetic-essential gene in PTEN-deficient cancer and normal cells. The PTEN protein phosphatase dephosphorylates nuclear factor κB (NF-κB)-activating protein (NKAP) and limits NFκB activation to suppress expression of PDHK1, a NF-κB target gene. Loss of the PTEN protein phosphatase upregulates PDHK1 to induce aerobic glycolysis and PDHK1 cellular dependence. PTEN-deficient human tumors harbor increased PDHK1, a biomarker of decreased patient survival. This study uncovers a PTEN-regulated signaling pathway and reveals PDHK1 as a potential target in PTEN-deficient cancers.

Intrinsic Resistance to Immune Checkpoint Blockade in a Mismatch Repair-Deficient Colorectal Cancer

Immunotherapy with checkpoint inhibitors, such as the programmed death-1 (PD-1) antibodies pembrolizumab and nivolumab, are effective in a variety of tumors, yet not all patients respond. Tumor microsatellite instability-high (MSI-H) has emerged as a biomarker of response to checkpoint blockade, leading to the tissue agnostic approval of pembrolizumab in MSI-H cancers. Here we describe a patient with MSI-H colorectal cancer that was treated with this immune checkpoint inhibitor and exhibited progression of disease. We examined this intrinsic resistance through genomic, transcriptional, and pathologic characterization of the patient's tumor and the associated immune microenvironment. The tumor had typical MSI-H molecular features, including a high neoantigen load. We also identified biallelic loss of the gene for β2-microglobulin (B2M), whose product is critical for antigen presentation. Immune infiltration deconvolution analysis of bulk transcriptome data from this anti-PD-1-resistant tumor and hundreds of other colorectal cancer specimens revealed a high natural killer cell and M2 macrophage infiltration in the patient's cancer. This was confirmed by single-cell transcriptome analysis and multiplex immunofluorescence. Our study provides insight into resistance in MSI-H tumors and suggests immunotherapeutic strategies in additional genomic contexts of colorectal cancer.

A Cellular Taxonomy of the Bone Marrow Stroma in Homeostasis and Leukemia

Stroma is a poorly defined non-parenchymal component of virtually every organ with key roles in organ development, homeostasis, and repair. Studies of the bone marrow stroma have defined individual populations in the stem cell niche regulating hematopoietic regeneration and capable of initiating leukemia. Here, we use single-cell RNA sequencing (scRNA-seq) to define a cellular taxonomy of the mouse bone marrow stroma and its perturbation by malignancy. We identified seventeen stromal subsets expressing distinct hematopoietic regulatory genes spanning new fibroblastic and osteoblastic subpopulations including distinct osteoblast differentiation trajectories. Emerging acute myeloid leukemia impaired mesenchymal osteogenic differentiation and reduced regulatory molecules necessary for normal hematopoiesis. These data suggest that tissue stroma responds to malignant cells by disadvantaging normal parenchymal cells. Our taxonomy of the stromal compartment provides a comprehensive bone marrow cell census and experimental support for cancer cell crosstalk with specific stromal elements to impair normal tissue function and thereby enable emergent cancer.

Rapid CLIP dissociation from MHC II promotes an unusual antigen presentation pathway in autoimmunity

Spontaneous CLIP dissociation from an autoimmunity-associated MHC II protein enhances presentation of peptides released by insulin-producing β cells. Presentation of such extracellular peptides does not require endosomal antigen processing and augments islet infiltration by CD4 T cells.

A number of autoimmunity-associated MHC class II proteins interact only weakly with the invariant chain–derived class II–associated invariant chain peptide (CLIP). CLIP dissociates rapidly from I-A^g7 even in the absence of DM, and this property is related to the type 1 diabetes–associated β57 polymorphism. We generated knock-in non-obese diabetic (NOD) mice with a single amino acid change in the CLIP segment of the invariant chain in order to moderately slow CLIP dissociation from I-A^g7. These knock-in mice had a significantly reduced incidence of spontaneous type 1 diabetes and diminished islet infiltration by CD4 T cells, in particular T cells specific for fusion peptides generated by covalent linkage of proteolytic fragments within β cell secretory granules. Rapid CLIP dissociation enhanced the presentation of such extracellular peptides, thus bypassing the conventional MHC class II antigen-processing pathway. Autoimmunity-associated MHC class II polymorphisms therefore not only modify binding of self-peptides, but also alter the biochemistry of peptide acquisition.

Abstract IA34: Targeting cellular heterogeneity in lung adenocarcinoma

Cancer arises from a single cell through a series of acquired mutations, and gradually develops into a complex tissue comprising phenotypically heterogeneous societies of cancer cells. The phenotype, or state, of each tumor cell is influenced by multiple cell-autonomous and cell-extrinsic factors; the diversity of these cellular states poses a challenge for effective cancer therapies. We characterized the evolution of transcriptomes at the single-cell level in genetically engineered murine lung tumors driven by oncogenic Kras. Tumor progression was accompanied by a dramatic increase in cellular heterogeneity, which was further exacerbated upon deletion of the p53 tumor suppressor, allowing tumor progression into advanced adenocarcinomas. This heterogeneity was manifested by the emergence of de-differentiated or transdifferentiated populations, the activation of latent developmental or regenerative programs, as well as heterogeneous activation of signaling pathways. Surprisingly, similar heterogeneous populations emerged in independent tumors irrespective of considerable intertumoral differences in genetic copy number alterations, suggesting a remarkable degree of convergence to achieve a common evolutionary endpoint. We used these data to computationally model cell-state transitions. Finally, treatment of the lung tumors with chemotherapy enabled the identification of cellular states associated with intrinsic sensitivity or resistance. These results associate tumor progression with increasing transcriptional heterogeneity. The identification of unique gene expression programs in cancer cell subpopulations provides a path towards reducing cellular heterogeneity in cancer.

Citation Format: Nemanja Marjanovic, Matan Hofree, David Canner, Marianna Trakala, Katherine Wu, Olivia Smith, Jonathan Kim, Angelika Amon, Aviv Regev, Tyler Jacks, Tuomas Tammela. Targeting cellular heterogeneity in lung adenocarcinoma [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA34.

Single-cell RNA-seq identifies the neuropeptide NMU as a novel regulator of ILC2 function

Type 2 innate lymphoid cells (ILC2s) are important for both mucosal homeostasis as well as for initiation and progression of allergy and asthma. Alarmin cytokines produced by damaged or stressed epithelial cells activate ILC2s, however, the role of other pathways regulating the homeostatic versus inflammatory functions of ILC2s remain poorly defined. We generated transcriptional profiles of thousands of lung-resident ILCs isolated from mice challenged with either PBS or the alarmin cytokines IL-25 or IL-33 using massively parallel droplet-based single-cell RNA sequencing (scRNA-seq). We found significant transcriptional heterogeneity within activated ILCs and identified differentially expressed genes as potential novel regulators of ILC function. One of the genes, neuromedin U receptor 1 (NMUR1), is a receptor for the neuropeptide neuromedin U (NMU) and is specifically expressed by ILC2s and not by other immune cells. Nmur1 is particularly expressed by ILC2s at steady-state and after IL-25 treatment. In vivo NMU synergized with IL-25 to induce more severe airway inflammation than was seen with either IL-25 or NMU alone and this effect was dependent on ILCs. Mechanistically, IL-25 + NMU expanded highly proliferative and inflammatory ILCs with distinct transcriptional profiles and increased expression of IL-5 and IL-13. We observed reduced ILC2 frequency and function in NMU- or NMUR1-deficient mice after allergen challenge and found that ILCs from these mice had a lower score for an inflammatory ILC2 gene signature. Our data therefore establish a novel neuro-immune pathway that amplifies ILC2-driven airway inflammation.

Anatomically and Functionally Distinct Lung Mesenchymal Populations Marked by Lgr5 and Lgr6

The diversity of mesenchymal cell types in the lung that influence epithelial homeostasis and regeneration is poorly defined. We used genetic lineage tracing, single-cell RNA sequencing, and organoid culture approaches to show that Lgr5 and Lgr6, well-known markers of stem cells in epithelial tissues, are markers of mesenchymal cells in the adult lung. Lgr6⁺ cells comprise a subpopulation of smooth muscle cells surrounding airway epithelia and promote airway differentiation of epithelial progenitors via Wnt-Fgf10 cooperation. Genetic ablation of Lgr6⁺ cells impairs airway injury repair in vivo. Distinct Lgr5⁺ cells are located in alveolar compartments and are sufficient to promote alveolar differentiation of epithelial progenitors through Wnt activation. Modulating Wnt activity altered differentiation outcomes specified by mesenchymal cells. This identification of region- and lineage-specific crosstalk between epithelium and their neighboring mesenchymal partners provides new understanding of how different cell types are maintained in the adult lung.

•

Lgr5 and Lgr6 mark mesenchymal cells in adult lungs

•

Single-cell transcriptome analysis defines mesenchymal heterogeneity

•

Distinct mesenchymal niches drive airway and alveolar differentiation

•

Wnt activity affects epithelial differentiation specified by mesenchymal cells

Exome Sequencing of African-American Prostate Cancer Reveals Loss-of-Function ERF Mutations

African-American men have the highest incidence of and mortality from prostate cancer. Whether a biological basis exists for this disparity remains unclear. Exome sequencing (n = 102) and targeted validation (n = 90) of localized primary hormone-naïve prostate cancer in African-American men identified several gene mutations not previously observed in this context, including recurrent loss-of-function mutations in ERF, an ETS transcriptional repressor, in 5% of cases. Analysis of existing prostate cancer cohorts revealed ERF deletions in 3% of primary prostate cancers and mutations or deletions in ERF in 3% to 5% of lethal castration-resistant prostate cancers. Knockdown of ERF confers increased anchorage-independent growth and generates a gene expression signature associated with oncogenic ETS activation and androgen signaling. Together, these results suggest that ERF is a prostate cancer tumor-suppressor gene. More generally, our findings support the application of systematic cancer genomic characterization in settings of broader ancestral diversity to enhance discovery and, eventually, therapeutic applications.Significance: Systematic genomic sequencing of prostate cancer in African-American men revealed new insights into prostate cancer, including the identification of ERF as a prostate cancer gene; somatic copy-number alteration differences; and uncommon PIK3CA and PTEN alterations. This study highlights the importance of inclusion of underrepresented minorities in cancer sequencing studies. Cancer Discov; 7(9); 973-83. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 920.

Massively parallel single-nucleus RNA-seq with DroNc-seq

Single nucleus RNA-seq (sNuc-seq) profiles RNA from tissues that are preserved or cannot be dissociated, but does not provide the throughput required to analyse many cells from complex tissues. Here, we develop DroNc-seq, massively parallel sNuc-Seq with droplet technology. We profile 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient and unbiased classification of cell types, paving the way for systematic charting of cell atlases.

Abstract AP23: A PLATINUM–RESISTANT SUBTYPE OF HIGH–GRADE SEROUS OVARIAN CANCER IDENTIFIED BY A NETWORK OF SOMATIC MUTATIONS

PURPOSE: Like many solid tumors, high grade serous ovarian carcinoma (HGSOC) is a heterogeneous entity with a widely variable clinical course even among patients of the same stage and histological subtype. Although most patients will achieve remission with platinum-based chemotherapy, approximately 20% will display primary platinum resistance. If it were possible to platinum resistance from the molecular profile of a tumor, patients with platinum resistant tumor could be identified for alternative therapy, however, currently no such biomarker exists.

METHODS: We have recently developed an analysis method called Network-based Stratification (NBS), which combines genome-scale somatic mutation profiles with genetic interaction networks. Briefly, somatic mutations for each patient are mapped onto a network, and then the influence of each mutation is propagated over its network neighborhood to give each gene a propagated mutation score (PM score). Unsupervised clustering is then used to assign the propagated networks into subtypes.

RESULTS: Using NBS a high risk subtype consisting of approximately 20% of the patients was identified in both TCGA (n=330) and the ICGC (n=92) HGSOC cohorts. The median overall survival (OS) for the high risk (HR) subtype was a year less than standard risk (SR) subtype (36 vs. 48 mo, Log rank p = 1.6x 10-5) in TCGA cohort and similarly shorter (22 mo vs. not-yet-reached, p = 3.6x10-4), see figure 1. These survival differences were independent of age, tumor stage and residual tumor after surgical resection. The PM scores of the HR tumors from TCGA and ICGC cohorts we remarkably correlated (Pearson r2 = 0.94, p < 0.001). In contrast, the correlation of PM scores from the full TCGA to ICGC cohorts was 0.58, and within the TCGA the correlation between HR and SR was only 0.18. The network of frequently mutated genes for the HR subtype was enriched for genes in the nucleoskeleton, caspase, and FGFR pathways.

We then built a classifier to identify molecularly matched cell line models for in vitro study. The three cell lines with mutation profiles match the HR subtype (Kuramochi,Ovkate, OAW28) were significantly more resistant to cisplatin relative to cell lines characteristic of SR tumors (COV318, TYK-NU, OVCAR4), (IC50 14.4 vs. 3.3 µM, p < 0.0001). There was no significant difference in sensitivity to paclitaxel. Figure 1.Kaplan-Meier plots of Overall Survival, A TCGA, B ICGCFigure 1. Kaplan-Meier plots of Overall Survival, A TCGA, B ICGC

CONCLUSIONS: NBS can be used to identify a molecular distinct subtype of HGSOC characterized by poor patient survival and primary platinum resistance.

Citation Format: John Paul Shen, Ana Bojorquez-Gomez, Justin Huang, Matan Hofree, Kristin Klepper, Alex Beckett, Cheryl Saenz, Jason Kreisberg, Trey Ideker. A PLATINUM–RESISTANT SUBTYPE OF HIGH–GRADE SEROUS OVARIAN CANCER IDENTIFIED BY A NETWORK OF SOMATIC MUTATIONS [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr AP23.

A platinum-resistant subtype of high-grade serous ovarian cancer identified by a network of somatic mutations

5561

Background: High-grade serous ovarian carcinoma (HGS-OvCa) is a heterogeneous entity with a widely variable clinical course even among patients of the same stage and histological subtype. Although most patients will achieve remission with platinum-based chemotherapy, ~20% will display primary platinum resistance. Currently no biomarker exists to identify these platinum resistant patients. Methods: We have recently developed a method called Network-based Stratification (NBS), which combines genome-scale somatic mutation profiles with genetic interaction networks and performs unsupervised clustering of patients into subtypes. Results: Using NBS HGSOC patients were stratified into subtype, in both TCGA (n = 330) and the ICGC (n = 92) a high-risk (HR) subtype consisting of ~20% of the patients was identified (see table). Propagated mutation scores of the HR tumors from TCGA and ICGC cohorts we remarkably correlated (Pearson r2 = 0.94, p < 0.001), relative to the correlation between HR and standard risk subtypes within TGCA cohort (r2 = 0.18). We then identified molecularly matched cell line models for in vitro study, finding that HR cell lines (Kuramochi, Ovkate, OAW28, 59M) were significantly more resistant to cisplatin relative standard risk cell lines (COV318, TYK-NU, OVCAR4), (IC50 14.4 vs. 3.3 µM, p < 0.0001). There was no significant difference in sensitivity to paclitaxel. A genome-wide knockout screen using CRISPR-Cas9 has identified several candidate genes mediating this observed platinum resistance. Conclusions: NBS can be used to identify a molecularly distinct subtype of HGSOC characterized by poor patient survival and primary platinum resistance. [Table: see text]

Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer

Recent studies have characterized the extensive somatic alterations that arise during cancer. However, the somatic evolution of a tumor may be significantly affected by inherited polymorphisms carried in the germline. Here, we analyze genomic data for 5,954 tumors to reveal and systematically validate 412 genetic interactions between germline polymorphisms and major somatic events, including tumor formation in specific tissues and alteration of specific cancer genes. Among germline-somatic interactions, we found germline variants in RBFOX1 that increased incidence of SF3B1 somatic mutation by 8-fold via functional alterations in RNA splicing. Similarly, 19p13.3 variants were associated with a 4-fold increased likelihood of somatic mutations in PTEN. In support of this association, we found that PTEN knockdown sensitizes the MTOR pathway to high expression of the 19p13.3 gene GNA11 Finally, we observed that stratifying patients by germline polymorphisms exposed distinct somatic mutation landscapes, implicating new cancer genes. This study creates a validated resource of inherited variants that govern where and how cancer develops, opening avenues for prevention research.Significance: This study systematically identifies germline variants that directly affect tumor evolution, either by dramatically increasing alteration frequency of specific cancer genes or by influencing the site where a tumor develops. Cancer Discovery; 7(4); 410-23. ©2017 AACR.See related commentary by Geeleher and Huang, p. 354This article is highlighted in the In This Issue feature, p. 339.

Inactivation of Capicua drives cancer metastasis

Metastasis is the leading cause of death in people with lung cancer, yet the molecular effectors underlying tumor dissemination remain poorly defined. Through the development of an in vivo spontaneous lung cancer metastasis model, we show that the developmentally regulated transcriptional repressor Capicua (CIC) suppresses invasion and metastasis. Inactivation of CIC relieves repression of its effector ETV4, driving ETV4-mediated upregulation of MMP24, which is necessary and sufficient for metastasis. Loss of CIC, or an increase in levels of its effectors ETV4 and MMP24, is a biomarker of tumor progression and worse outcomes in people with lung and/or gastric cancer. Our findings reveal CIC as a conserved metastasis suppressor, highlighting new anti-metastatic strategies that could potentially improve patient outcomes.

Network-driven plasma proteomics expose molecular changes in the Alzheimer's brain

Background

Biological pathways that significantly contribute to sporadic Alzheimer’s disease are largely unknown and cannot be observed directly. Cognitive symptoms appear only decades after the molecular disease onset, further complicating analyses. As a consequence, molecular research is often restricted to late-stage post-mortem studies of brain tissue. However, the disease process is expected to trigger numerous cellular signaling pathways and modulate the local and systemic environment, and resulting changes in secreted signaling molecules carry information about otherwise inaccessible pathological processes.

Results

To access this information we probed relative levels of close to 600 secreted signaling proteins from patients’ blood samples using antibody microarrays and mapped disease-specific molecular networks. Using these networks as seeds we then employed independent genome and transcriptome data sets to corroborate potential pathogenic pathways.

Conclusions

We identified Growth-Differentiation Factor (GDF) signaling as a novel Alzheimer’s disease-relevant pathway supported by in vivo and in vitro follow-up experiments, demonstrating the existence of a highly informative link between cellular pathology and changes in circulatory signaling proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s13024-016-0095-2) contains supplementary material, which is available to authorized users.

Integrated Proteomic and Genomic Analysis of Gastric Cancer Patient Tissues

V-erb-b2 erythroblastic leukemia viral oncogene homologue 2, known as ERBB2, is an important oncogene in the development of certain cancers. It can form a heterodimer with other epidermal growth factor receptor family members and activate kinase-mediated downstream signaling pathways. ERBB2 gene is located on chromosome 17 and is amplified in a subset of cancers, such as breast, gastric, and colon cancer. Of particular interest to the Chromosome-Centric Human Proteome Project (C-HPP) initiative is the amplification mechanism that typically results in overexpression of a set of genes adjacent to ERBB2, which provides evidence of a linkage between gene location and expression. In this report we studied patient samples from ERBB2-positive together with adjacent control nontumor tissues. In addition, non-ERBB2-expressing patient samples were selected as comparison to study the effect of expression of this oncogene. We detected 196 proteins in ERBB2-positive patient tumor samples that had minimal overlap (29 proteins) with the non-ERBB2 tumor samples. Interaction and pathway analysis identified extracellular signal regulated kinase (ERK) cascade and actin polymerization and actinmyosin assembly contraction as pathways of importance in ERBB2+ and ERBB2- gastric cancer samples, respectively. The raw data files are deposited at ProteomeXchange (identifier: PXD002674) as well as GPMDB.

Abstract AS02: Network-based stratification: combining genome-scale somatic mutation profiles with genetic interaction networks to identify clinically relevant subtypes in high grade serous ovarian carcinoma

Background: Like many solid tumors, high grade serous ovarian carcinoma (HGS-OvCa) is a heterogeneous entity with a widely variable clinical course even among patients of the same stage and histological subtype. We have recently developed a method called Network-based Stratification (NBS), which combines genome-scale somatic mutation profiles with genetic interaction networks and performs unsupervised clustering of patients into subtypes. Remarkably, patients in these subtypes display distinct biological and clinical characteristics.

Methods: Briefly, somatic mutations for each patient are represented as a profile of binary (1,0) states on genes, in which a ‘1’ indicates a mutated gene. For each patient we project mutation profiles onto a human gene interaction network, then apply network propagation to spread the influence of each subsampled mutation profile over its network neighborhood. These ‘network-smoothed’ profiles are then clustered into a predefined number of subtypes using the unsupervised technique of non-negative matrix factorization (NMF).

Results: Using the NBS technique four distinct subtypes were identified from the TCGA HGS-OvCa cohort of 330 exome sequenced and clinically-annotated tumors. The median overall survival (OS) in months for these four subtypes was 36, 48, 56, and not-yet-reached respectively, which was highly significant (Logrank p = 1.59 x 10-5). No significant differences between subtypes were found in age, tumor stage at presentation, or percentage of patients with an optimal surgical resection. Furthermore, the survival difference is significant when comparing a Cox proportional hazards model of NBS subtypes together with the above factors and mutation rate is compared to a model of these factors alone (Likelihood ratio test p = 3.3x10-4). Each subtype exhibits a distinct set frequently mutated pathways, with subtype 1 (which had the worst OS) enriched for mutation in the fibroblast growth factor receptor, caspase and nucleoskeleton pathways, subtype 2 enriched for ‘classic’ HGS-OvCa mutations including mutation in DNA damage response genes.

Recognizing that full exome sequencing is not yet standard of care, we have built a limited classifier that only requires as input the mutational status of 50 genes. This 50 gene classifier performed with 94% accuracy and 80% precision relative to full exome. Using this 50 gene classifier we have stratified an independent cohort of 93 Australian HGS-OvCa patients from the ICGC and found survival relationships similar to what was seen in the TCGA cohort (median OS of 22 months for subtype 1 vs. not-yet-reached for other subtypes, Logrank p = 3.6x10-4). The 50 gene NBS classifier was also applied to a panel of cell lines from The Genomics of Drug Sensitivity in Cancer Project. Cell lines classified as subtype 1 had significantly higher cisplatin IC50 relative to other subtypes, whereas there was no difference in docetaxel or paclitaxel IC50.

Citation Format: John Paul Shen, Matan Hofree, Ana Bojorquez-Gomez, Cheryl Saenz, Trey Ideker. Network-based stratification: combining genome-scale somatic mutation profiles with genetic interaction networks to identify clinically relevant subtypes in high grade serous ovarian carcinoma [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr AS02.

Functional genome-wide siRNA screen identifies KIAA0586 as mutated in Joubert syndrome

Defective primary ciliogenesis or cilium stability forms the basis of human ciliopathies, including Joubert syndrome (JS), with defective cerebellar vermis development. We performed a high-content genome-wide small interfering RNA (siRNA) screen to identify genes regulating ciliogenesis as candidates for JS. We analyzed results with a supervised-learning approach, using SYSCILIA gold standard, Cildb3.0, a centriole siRNA screen and the GTex project, identifying 591 likely candidates. Intersection of this data with whole exome results from 145 individuals with unexplained JS identified six families with predominantly compound heterozygous mutations in KIAA0586. A c.428del base deletion in 0.1% of the general population was found in trans with a second mutation in an additional set of 9 of 163 unexplained JS patients. KIAA0586 is an orthologue of chick Talpid3, required for ciliogenesis and Sonic hedgehog signaling. Our results uncover a relatively high frequency cause for JS and contribute a list of candidates for future gene discoveries in ciliopathies.

DOI:http://dx.doi.org/10.7554/eLife.06602.001

Joubert syndrome is a rare disorder that affects the brain and causes physical, mental, and sometimes visual impairments. In individuals with this condition, two parts of the brain called the cerebellar vermis and the brainstem do not develop properly. This is thought to be due to defects in the development and maintenance of tiny hair-like structures called cilia, which are found on the surface of cells.

Currently, mutations in 25 different genes are known to be able to cause Joubert syndrome. However, these mutations only account for around 50% of the cases that have been studied, and the ‘unexplained’ cases suggest that mutations in other genes may also cause the disease.

Here, Roosing et al. used a technique called a ‘genome-wide siRNA screen’ to identify other genes regulating the formation of cilia that might also be connected with Joubert syndrome. This approach identified almost 600 candidate genes. The data from the screen were combined with gene sequence data from 145 individuals with unexplained Joubert syndrome. Roosing et al. found that individuals with Joubert syndrome from 15 different families had mutations in a gene called KIAA0586. In chickens and mice, this gene—known as Talpid3—is required for the formation of cilia.

Roosing et al.'s findings reveal a new gene that is involved in Joubert syndrome and also provides a list of candidate genes for future studies of other conditions caused by defects in the formation of cilia. The next challenges are to find out what causes the remaining unexplained cases of the disease and to understand what roles the genes identified in this study play in cilia.

DOI:http://dx.doi.org/10.7554/eLife.06602.002

Multi-tiered genomic analysis of head and neck cancer ties TP53 mutation to 3p loss

Head and neck squamous cell carcinoma (HNSCC) is characterized by aggressive behavior with a propensity for metastasis and recurrence. Here we report a comprehensive analysis of the molecular and clinical features of HNSCC that govern patient survival. We find that TP53 mutation is frequently accompanied by loss of chromosome 3p, and that the combination of both events associates with a surprising decrease in survival rates (1.9 years versus >5 years for TP53 mutation alone). The TP53-3p interaction is specific to chromosome 3p, rather than a consequence of global genome instability, and validates in HNSCC and pan-cancer cohorts. In Human Papilloma Virus positive (HPV+) tumors, in which HPV inactivates TP53, 3p deletion is also common and associates with poor outcomes. The TP53-3p event is modified by mir-548k expression which decreases survival even further, while it is mutually exclusive with mutations to RAS signaling. Together, the identified markers underscore the molecular heterogeneity of HNSCC and enable a new multi-tiered classification of this disease.

Exome sequencing links corticospinal motor neuron disease to common neurodegenerative disorders

Hereditary spastic paraplegias (HSPs) are neurodegenerative motor neuron diseases characterized by progressive age-dependent loss of corticospinal motor tract function. Although the genetic basis is partly understood, only a fraction of cases can receive a genetic diagnosis, and a global view of HSP is lacking. By using whole-exome sequencing in combination with network analysis, we identified 18 previously unknown putative HSP genes and validated nearly all of these genes functionally or genetically. The pathways highlighted by these mutations link HSP to cellular transport, nucleotide metabolism, and synapse and axon development. Network analysis revealed a host of further candidate genes, of which three were mutated in our cohort. Our analysis links HSP to other neurodegenerative disorders and can facilitate gene discovery and mechanistic understanding of disease.

Genotype to phenotype via network analysis

A prime objective of genomic medicine is the identification of disease-causing mutations and the mechanisms by which such events result in disease. As most disease phenotypes arise not from single genes and proteins but from a complex network of molecular interactions, a priori knowledge about the molecular network serves as a framework for biological inference and data mining. Here we review recent developments at the interface of biological networks and mutation analysis. We examine how mutations may be treated as a perturbation of the molecular interaction network and what insights may be gained from taking this perspective. We review work that aims to transform static networks into rich context-dependent networks and recent attempts to integrate non-coding RNAs into such analysis. Finally, we conclude with an overview of the many challenges and opportunities that lie ahead.

Using functional signature ontology (FUSION) to identify mechanisms of action for natural products

A challenge for biomedical research is the development of pharmaceuticals that appropriately target disease mechanisms. Natural products can be a rich source of bioactive chemicals for medicinal applications but can act through unknown mechanisms and can be difficult to produce or obtain. To address these challenges, we developed a new marine-derived, renewable natural products resource and a method for linking bioactive derivatives of this library to the proteins and biological processes that they target in cells. We used cell-based screening and computational analysis to match gene expression signatures produced by natural products to those produced by small interfering RNA (siRNA) and synthetic microRNA (miRNA) libraries. With this strategy, we matched proteins and miRNAs with diverse biological processes and also identified putative protein targets and mechanisms of action for several previously undescribed marine-derived natural products. We confirmed mechanistic relationships for selected siRNAs, miRNAs, and compounds with functional roles in autophagy, chemotaxis mediated by discoidin domain receptor 2, or activation of the kinase AKT. Thus, this approach may be an effective method for screening new drugs while simultaneously identifying their targets.

Abstract A14: Network-based stratification: Combining genome-scale somatic mutation profiles with genetic interaction networks to identify clinically relevant subtypes in high grade serous ovarian carcinoma

Background: Recent technological advances have drastically reduced the cost and increased the speed of DNA sequencing, developments that have been heralded as the beginning of a new era of personalized medicine. However, there still remains a pressing need to translate improved knowledge of cancer genomics into better clinical outcomes. Like many solid tumors, high grade serous ovarian carcinoma (HGS-OvCa) is a heterogeneous entity with a widely variable clinical course even among patients of the same stage and histological subtype.

Most prior attempts to stratify tumors into clinically meaningful subtypes have utilized gene expression profiles; however as a whole such methods have not reliably discovered subtypes with significant differences in survival or response to chemotherapy. There has been much effort to stratify tumors based on their somatic mutations; however this has proved difficult due to the great heterogeneity and sparseness of somatic mutations in most solid tumors. For example, in the TCGA HGS-OvCa cohort the average tumor had 61 non-silent mutations spread out over the ~20,000 genes in the human genome; most genes were mutated in one tumor only. Standard consensus clustering approaches applied to this sparse mutational data have repeatedly failed to produce a clinically valuable stratification of patients.

Methods: The technique of Network-based Stratification (NBS) combines genome-scale somatic mutation profiles with a genetic interaction network to produce a subdivision of patients into subtypes. Briefly, somatic mutations for each patient are represented as a profile of binary (1,0) states on genes, in which a ‘1’ indicates a mutated gene. For each patient independently we project the mutation profiles onto a human gene interaction network obtained from public databases. Next the technique of network propagation is applied to spread the influence of each subsampled mutation profile over its network neighborhood, resulting in a ‘network-smoothed’ profile. Following this ‘network-smoothing’, profiles are clustered into a predefined number of subtypes using the unsupervised technique of non-negative matrix factorization (NMF). This procedure is repeated for 1000 different subsamples using the technique of consensus clustering to promote robust cluster assignments. This method was repeated with three difference sources of network data: STRING, HumanNet, and PathwayCommons.

Results: Using the NBS technique four distinct subtypes were identified from the TCGA HGS-OvCa cohort of 330 exome sequenced and clinically-annotated tumors. The median overall survival (OS) in months for these four subtypes was 36, 48, 56, and not-yet-reached respectively, which was highly significant (Logrank p = 1.59 x 10-5). Subtypes were also predictive of platinum free interval (PFI), (Logrank p = 0.046). No significant differences between subtypes were found in age, tumor stage at presentation, or percentage of patients with an optimal surgical resection, and a cox proportional hazards model was significant even after taking those factors into account (Likelihood ratio test p = 3.3x10-4).

Comparing each subtype against the other three, the network of mutated genes for subtype 1, which had the worst overall survival and shortest platinum free interval, was enriched for over 20 genes in the fibroblast growth pathway. The network for subtype 2 was enriched in DNA damage response genes including ATM, ATR, BRCA1/2, RAD51 and Chek2, and also contained the majority of patients with BRCA1/2 germline mutations (15/20 and 5/6, respectively).

Conclusions: Network-based Stratification (NBS) combines genome-scale somatic mutation profiles with a genetic interaction network to stratify a cohort of HGS-OvCa tumors into subtypes with significant differences is OS and PFI.

Citation Format: Matan Hofree, John Paul Shen, Hannah Carter, Andrew Gross, Trey Ideker. Network-based stratification: Combining genome-scale somatic mutation profiles with genetic interaction networks to identify clinically relevant subtypes in high grade serous ovarian carcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr A14.

Genome wide proteomics of ERBB2 and EGFR and other oncogenic pathways in inflammatory breast cancer

In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.

Association of methylation of genes in the taurine/hypotaurine pathway with worse prognosis in renal cell carcinoma

e15562

Background: Epigenetic silencing of genes associated with the taurine/hypotaurine pathway has been associated with worse outcome in several tumors such as CDO1 in breast cancer, and GAD1 in prostate cancer. Our objective was to assess the prognostic value of methylation status of genes in the taurine/hypotaurine pathway in patients with renal cell carcinoma (RCC). Methods: We performed an analysis of 283 RCC samples using data from The Cancer Genome Atlas (TCGA). Ten genes belonging to the taurine/hypotaurine metabolic were analyzed using principal component analysis to determine a composite methylation profile of the pathway. A Cox proportional-hazards regression model was then used to determine the association of the composite methylation profile with patient survival. Results: CDO1, GAD2, and GAD1 influenced the outcome of the composite gene the most. Increasing degree of methylation correlated with more advanced tumor stage, and was an independent predictor of overall patient survival. Among patients with localized and locally advanced disease (stages 1-3), high levels of methylation correlated with significantly worse OS (Table). No difference in outcome was noted in patients with metastatic disease. Conclusions: Silencing of genes in the taurine/hypotaurine pathway through methylation is predictive of poorer outcomes in patients with localized RCC. Increasing degree of methylation correlates with tumor stage. Among patients with localized disease and belonging to the same stage, higher degree of methylation correlated with with worse prognosis. Interestingly, this effect is not observed in patients with metastatic disease, indicating the possible activation of other pathways that override the role of the taurine/hypotaurine pathway. [Table: see text]

RepTar: a database of predicted cellular targets of host and viral miRNAs

Computational identification of putative microRNA (miRNA) targets is an important step towards elucidating miRNA functions. Several miRNA target-prediction algorithms have been developed followed by publicly available databases of these predictions. Here we present a new database offering miRNA target predictions of several binding types, identified by our recently developed modular algorithm RepTar. RepTar is based on identification of repetitive elements in 3'-UTRs and is independent of both evolutionary conservation and conventional binding patterns (i.e. Watson-Crick pairing of 'seed' regions). The modularity of RepTar enables the prediction of targets with conventional seed sites as well as rarer targets with non-conventional sites, such as sites with seed wobbles (G-U pairing in the seed region), 3'-compensatory sites and the newly discovered centered sites. Furthermore, RepTar's independence of conservation enables the prediction of cellular targets of the less evolutionarily conserved viral miRNAs. Thus, the RepTar database contains genome-wide predictions of human and mouse miRNAs as well as predictions of cellular targets of human and mouse viral miRNAs. These predictions are presented in a user-friendly database, which allows browsing through the putative sites as well as conducting simple and advanced queries including data intersections of various types. The RepTar database is available at http://reptar.ekmd.huji.ac.il.

A decade of systems biology

Systems biology provides a framework for assembling models of biological systems from systematic measurements. Since the field was first introduced a decade ago, considerable progress has been made in technologies for global cell measurement and in computational analyses of these data to map and model cell function. It has also greatly expanded into the translational sciences, with approaches pioneered in yeast now being applied to elucidate human development and disease. Here, we review the state of the field with a focus on four emerging applications of systems biology that are likely to be of particular importance during the decade to follow: (a) pathway-based biomarkers, (b) global genetic interaction maps, (c) systems approaches to identify disease genes, and (d) stem cell systems biology. We also cover recent advances in software tools that allow biologists to explore system-wide models and to formulate new hypotheses. The applications and methods covered in this review provide a set of prime exemplars useful to cell and developmental biologists wishing to apply systems approaches to areas of interest.