F-Seq: a feature density estimator for high-throughput sequence tags

Summary: Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features, such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an accurate and interpretable signal, we developed F-Seq, a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser

Modeling Cancer Progression via Pathway Dependencies

Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain elusive. These genetic perturbations are most likely reflected by the altered expression of sets of genes or pathways, rather than individual genes, thus creating a need for models of deregulation of pathways to help provide an understanding of the mechanisms of tumorigenesis. We introduce an integrative hierarchical analysis of tumor progression that discovers which a priori defined pathways are relevant either throughout or in particular steps of progression. Pathway interaction networks are inferred for these relevant pathways over the steps in progression. This is followed by the refinement of the relevant pathways to those genes most differentially expressed in particular disease stages. The final analysis infers a gene interaction network for these refined pathways. We apply this approach to model progression in prostate cancer and melanoma, resulting in a deeper understanding of the mechanisms of tumorigenesis. Our analysis supports previous findings for the deregulation of several pathways involved in cell cycle control and proliferation in both cancer types. A novel finding of our analysis is a connection between ErbB4 and primary prostate cancer

Integrative analysis identifies candidate tumor microenvironment and intracellular signaling pathways that define tumor heterogeneity in NF1

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions

Relative contribution of clinicopathological variables, genomic markers, transcriptomic subtyping and microenvironment features for outcome prediction in stage II/III colorectal cancer

Background: It remains unknown to what extent consensus molecular subtype (CMS) groups and immune-stromal infiltration patterns improve our ability to predict outcomes over tumor-node-metastasis (TNM) staging and microsatellite instability (MSI) status in early-stage colorectal cancer (CRC). Patients and methods: We carried out a comprehensive retrospective biomarker analysis of prognostic markers in adjuvant chemotherapy-untreated (N = 1656) and treated (N = 980), stage II (N = 1799) and III (N = 837) CRCs. We defined CMS scores and estimated CD8+ cytotoxic lymphocytes (CytoLym) and cancer-associated fibroblasts (CAF) infiltration scores from bulk tumor tissue transcriptomes (CMSclassifier and MCPcounter R packages); constructed a stratified multivariable Cox model for disease-free survival (DFS); and calculated the relative proportion of explained variation by each marker (clinicopathological [ClinPath], genomics [Gen: MSI, BRAF and KRAS mutations], CMS scores [CMS] and microenvironment cells [MicroCells: CytoLym+CAF]). Results: In multivariable models, only ClinPath and MicroCells remained significant prognostic factors, with both CytoLym and CAF infiltration scores improving survival prediction beyond other markers. The explained variation for DFS models of ClinPath, MicroCells, Gen markers and CMS4 scores was 77%, 14%, 5.3% and 3.7%, respectively, in stage II; and 55.9%, 35.1%, 4.1% and 0.9%, respectively, in stage III. Patients whose tumors were CytoLym high/CAF low had better DFS than other strata [HR=0.71 (0.6-0.9); P = 0.004]. Microsatellite stable tumors had the strongest signal for improved outcomes with CytoLym high scores (interaction P = 0.04) and the poor prognosis linked to high CAF scores was limited to stage III disease (interaction P = 0.04). Conclusions: Our results confirm that tumor microenvironment infiltration patterns represent potent determinants of the risk for distant dissemination in early-stage CRC. Multivariable models suggest that the prognostic value of MSI and CMS groups is largely explained by CytoLym and CAF infiltration patterns

KRAS mutation and Consensus Molecular Subtypes 2 and 3 are independently associated with reduced immune infiltration and reactivity in colorectal cancer

Abstract Purpose: KRAS mutation is a common canonical mutation in colorectal cancer, found at differing frequencies in all consensus molecular subtypes (CMS). The independent immunobiological impacts of RAS mutation and CMS are unknown. Thus, we explored the immunobiological effects of KRAS mutation across the CMS spectrum. Experimental Design: Expression analysis of immune genes/signatures was performed using The Cancer Genome Atlas (TCGA) RNA-seq and the KFSYSCC microarray datasets. Multivariate analysis included KRAS status, CMS, tumor location, MSI status, and neoantigen load. Protein expression of STAT1, HLA-class II, and CXCL10 was analyzed by digital IHC. Results: The Th1-centric co-ordinate immune response cluster (CIRC) was significantly, albeit modestly, reduced in KRAS-mutant colorectal cancer in both datasets. Cytotoxic T cells, neutrophils, and the IFNγ pathway were suppressed in KRAS-mutant samples. The expressions of STAT1 and CXCL10 were reduced at the mRNA and protein levels. In multivariate analysis, KRAS mutation, CMS2, and CMS3 were independently predictive of reduced CIRC expression. Immune response was heterogeneous across KRAS-mutant colorectal cancer: KRAS-mutant CMS2 samples have the lowest CIRC expression, reduced expression of the IFNγ pathway, STAT1 and CXCL10, and reduced infiltration of cytotoxic cells and neutrophils relative to CMS1 and CMS4 and to KRAS wild-type CMS2 samples in the TCGA. These trends held in the KFSYSCC dataset. Conclusions: KRAS mutation is associated with suppressed Th1/cytotoxic immunity in colorectal cancer, the extent of the effect being modulated by CMS subtype. These results add a novel immunobiological dimension to the biological heterogeneity of colorectal cancer. Clin Cancer Res; 24(1); 224–33. ©2017 AACR.</jats:p

Tumour invasiveness, the local and systemic environment and the basis of staging systems in colorectal cancer

background: The present study aimed to examine the relationship between tumour invasiveness (T stage), the local and systemic environment and cancer-specific survival (CSS) of patients with primary operable colorectal cancer. methods: The tumour microenvironment was examined using measures of the inflammatory infiltrate (Klintrup-Makinen (KM) grade and Immunoscore), tumour stroma percentage (TSP) and tumour budding. The systemic inflammatory environment was examined using modified Glasgow Prognostic Score (mGPS) and neutrophil:lymphocyte ratio (NLR). A 5-year CSS was examined. results: A total of 331 patients were included. Increasing T stage was associated with colonic primary, N stage, poor differentiation, margin involvement and venous invasion (P&lt;0.05). T stage was significantly associated with KM grade (P=0.001), Immunoscore (P=0.016), TSP (P=0.006), tumour budding (P&lt;0.001), and elevated mGPS and NLR (both P&lt;0.05). In patients with T3 cancer, N stage stratified survival from 88 to 64%, whereas Immunoscore and budding stratified survival from 100 to 70% and from 91 to 56%, respectively. The Glasgow Microenvironment Score, a score based on KM grade and TSP, stratified survival from 93 to 58%. conclusions: Although associated with increasing T stage, local and systemic tumour environment characteristics, and in particular Immunoscore, budding, TSP and mGPS, are stage-independent determinants of survival and may be utilised in the staging of patients with primary operable colorectal cancer

Molecular profiling of signet ring cell colorectal cancer provides a strong rationale for genomic targeted and immune checkpoint inhibitor therapies

We would like to thank all patients whose samples were used in this study. We are also thankful to the Northern Ireland Biobank and Grampian Biorepository for providing us with tissue blocks and patient data; and Dr HG Coleman (Queen’s University Belfast) for her advice on statistical analyses. This work has been carried out with financial support from Cancer Research UK (grant: C11512/A18067), Experimental Cancer Medicine Centre Network (grant: C36697/A15590 from Cancer Research UK and the NI Health and Social Care Research and Development Division), the Sean Crummey Memorial Fund and the Tom Simms Memorial Fund. The Northern Ireland Biobank is funded by HSC Research and Development Division of the Public Health Agency in Northern Ireland and Cancer Research UK through the Belfast CRUK Centre and the Northern Ireland Experimental Cancer Medicine Centre; additional support was received from Friends of the Cancer Centre. The Northern Ireland Molecular Pathology Laboratory which is responsible for creating resources for the Northern Ireland Biobank has received funding from Cancer Research UK, Friends of the Cancer Centre and Sean Crummey Foundation.Peer reviewedPublisher PD

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume I—conceptual challenges

The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I-conceptual challenges and Volume II-practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting

Analysis of cell proliferation and tissue remodelling uncovers a KLF4 activity score associated with poor prognosis in colorectal cancer

Human cancers can be classified based on gene signatures quantifying the degree of cell proliferation and tissue remodelling (PR). However, the specific factors that drive the increased tissue remodelling in tumours are not fully understood. Here we address this question using colorectal cancer as a case study. We reanalysed a reported cohort of colorectal cancer patients. The patients were stratified based on gene signatures of cell proliferation and tissue remodelling. Putative transcription factors activity was inferred using gene expression profiles and annotations of transcription factor targets as input. We demonstrate that the PR classification performs better than the currently adopted consensus molecular subtyping (CMS). Although CMS classification differentiates patients with a mesenchymal signature, it cannot distinguish the remaining patients based on survival. We demonstrate that the missing factor is cell proliferation, which is indicative of good prognosis. We also uncover a KLF4 transcription factor activity score associated with the tissue remodelling gene signature. We further show that the KLF4 activity score is significantly higher in colorectal tumours with predicted infiltration of cells from the myeloid lineage. The KLF4 activity score is associated with tissue remodelling, myeloid cell infiltration and poor prognosis in colorectal cancer