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Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

ABSTRACT: The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026.

SUBMITTER: Budinska E

PROVIDER: S-EPMC3840702 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

Budinska Eva E Popovici Vlad V Tejpar Sabine S D'Ario Giovanni G Lapique Nicolas N Sikora Katarzyna Otylia KO Di Narzo Antonio Fabio AF Yan Pu P Hodgson John Graeme JG Weinrich Scott S Bosman Fred F Roth Arnaud A Delorenzi Mauro M

The Journal of pathology 20130708 1

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined ...[more]

PMID: 23836465

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Project description:ObjectiveTo examine the heterogeneity of global transcriptome patterns in systemic sclerosis (SSc) skin in a large sample of patients with SSc and control subjects.MethodsSkin biopsy specimens obtained from 61 patients enrolled in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort and 36 unaffected control subjects with a similar demographic background were examined by Illumina HumanHT-12 bead arrays. Followup experiments using quantitative polymerase chain reaction and immunohistochemical analysis were also performed.ResultsWe identified 2,754 differentially expressed transcripts in SSc patients compared with controls. Clustering analysis revealed 2 prominent transcriptomes in SSc patients: the keratin and fibroinflammatory signatures. Higher keratin transcript scores were associated with shorter disease duration and interstitial lung disease, while higher fibroinflammatory scores were associated with diffuse cutaneous involvement, a higher skin score at the biopsy site, and a higher modified Rodnan skin thickness score. A subgroup of patients with significantly longer disease duration had a normal-like transcript pattern. Analysis of cell type-specific signature scores revealed remarkable heterogeneity across patients. Significantly higher scores were calculated for fibroblasts (72% of patients), microvascular cells (61%), macrophages (54%), and dendritic cells (DCs) (49%). The majority of samples with significantly higher fibroblast scores (35 of 44 [80%]) had significantly increased macrophage and/or DC scores. Further analysis and immunohistochemical staining indicated that the keratin signature was not a general marker of keratinocyte activation but was in fact associated with an activation pattern in hair and adnexal structures.ConclusionProminent fibroinflammatory and keratin signatures are present in SSc skin. Expression profiles of SSc skin show significant heterogeneity, and this finding might be useful for stratifying patients for targeted therapies or predicting the response to immunosuppression.

Project description:Oral cancer (OC) ranked as eleventh malignancy worldwide, with the increasing incidence among young patients. Limited understanding of complications in cancer progression, its development system, and their interactions are major restrictions towards the progress of optimal and effective treatment strategies. The system-level approach has been designed to explore genetic complexity of the disease and to identify novel oral cancer related genes to detect genomic alterations at molecular level, through cDNA differential analysis. We analyzed 21 oral cancer-related cDNA datasets and listed 30 differentially expressed genes (DEGs). Among 30, we found 6 significant DEGs including CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13 and studied their functional role in OC. Our genomic and interactive analysis showed significant enrichment of xenobiotics metabolism, p53 signaling pathway and microRNA pathways, towards OC progression and development. We used human proteomic data for post-translational modifications to interpret disease mutations and inter-individual genetic variations. The mutational analysis revealed the sequence predicted disordered region of 14%, 12.5%, 10.5% for ADCY2, CYP1B1, and C7 respectively. The MiRNA target prediction showed functional molecular annotation including specific miRNA-targets hsa-miR-4282, hsa-miR-2052, hsa-miR-216a-3p, for CYP1B1, C7, and ADCY2 respectively associated with oral cancer. We constructed the system level network and found important gene signatures. The drug-gene interaction of OC source genes with seven FDA approved OC drugs help to design or identify new drug target or establishing novel biomedical linkages regarding disease pathophysiology. This investigation demonstrates the importance of system genetics for identifying 6 OC genes (CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13) as potential drugs targets. Our integrative network-based system-level approach would help to find the genetic variants of OC that can accelerate drug discovery outcomes to develop a better understanding regarding treatment strategies for many cancer types.

Dataset Information

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

Publications

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

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