Project description:Gastric cancer (GC) is the world's third leading cause of cancer mortality. In spite of significant therapeutic improvement, the clinical outcome for patients with advanced GC is poor; thus, the identification and validation of novel targets is extremely important from a clinical point of view. We generated a wide, multi-level platform of GC models, comprising 100 Patient-derived xenografts (PDXs), primary cell lines and organoids. Samples were classified according to their histology, microsatellite stability (MS) and Epstein-Barr virus status, and molecular profile. This PDX platform is the widest in an academic institution and it includes all the GC histologic and molecular types identified by TCGA. PDX histopathological features were consistent with those of patients’ primary tumors and were maintained throughout passages in mice. Factors modulating grafting rate were histology, TNM stage, copy number variation of tyrosine kinases/KRAS genes and MSI status. PDX and PDX-derived cells/organoids demonstrated potential usefulness to study targeted therapy response. Finally, PDX transcriptomic analysis identified a cancer cell intrinsic MSI signature, which was efficiently exported to gastric cancer, allowing the identification -among MSS patients- of a subset of MSI-like tumors with common molecular assets and significant better prognosis. We generated a wide gastric cancer PDX platform, whose exploitation will help identify and validate novel 'druggable' targets and define the best therapeutic strategies. Moreover, transcriptomic analysis of GC PDXs allowed the identification of a cancer cell intrinsic MSI signature, recognizing a subset of MSS patients with MSI transcriptional traits, endowed with better prognosis.
Project description:mRNA assays were performed on 51 samples of human colorectal tumors using Affymetrix HuGeneFL arrays containing 7129 probe-sets. We compared 38 microsatelite stable (MSS) tumors with 13 microsatellite instable-high (MSI) tumors to form a list of genes differing between the two types. In order to identify molecular signatures characterizing MSI tumors, we examined only MSI-high cancers and not MSI-low ones. Keywords: disease state analysis
Project description:mRNA assays were performed on 51 samples of human colorectal tumors using Affymetrix HuGeneFL arrays containing 7129 probe-sets. We compared 38 microsatelite stable (MSS) tumors with 13 microsatellite instable-high (MSI) tumors to form a list of genes differing between the two types. In order to identify molecular signatures characterizing MSI tumors, we examined only MSI-high cancers and not MSI-low ones. Keywords: disease state analysis Human samples of 38 microsatellie stable and 13 microsatellite instable-high colorectal tumors, each from a separate patient, had mRNA assays performed using Affymetrix HuGeneFL arrays, with 7129 probe-sets. A supplementary Excel file (Colon_HuFL_logs.xls) is attached below that gives the log-transformed probe-set values. It also gives the p-values from T-tests comparing these values between MSS and MSI samples, as well as an estimated average fold-difference, for which the mathematical functions are explicitly given.
Project description:Samples were taken from colorectal cancers in surgically resected specimens from 74 patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. Our MSI/MSS classifer was applied to these samples. Experiment Overall Design: mRNA from 74 fresh-frozen primary colorectal tumour samples were extracted and hybridized to HG-U133Plus 2.0 expression arrays. The MAS5.0 procedure was used to make calls of expression. Data from each sample were quantile normalized with reference to a training set prior to application of our MSS/MSI classifier.
Project description:We compared the expression of genes related to inflammatory cytotoxic functions between MSI and MSS (HLA class I negative and positive) gastrointestinal adenocarcinomas (GIACs), seeking evidence of differences in inflammatory mediators and cytotoxic T-cell responses. Twenty-two GIACs were divided into three study groups as a function of HLA class I expression and MSI phenotype. Comparison between eight high-level MSI (MSI-H) and 8 MSS/HLA+ (control) cancers identified 2170 differentially expressed genes (p< 0.05) after microarray analysis on the Affymetrix HG-U133-Plus-PM plate. We grouped genes in Gene Ontology functional categories: apoptotic programme (119 genes, p=5.1·10-7), leukocyte activation (32 genes, p=0.01), T cell activation (20 genes, p= 0.01), and cytokine production (19 genes, p= 0.04). Real-time RT-PCR and immunohistochemical evaluation were used to confirm some microarray data, finding that increased mRNA levels of pro-inflammatory cytokines and cytotoxic mediators were associated with greater infiltration by CD8+ T lymphocytes in the MSI-H group (p<0.001). Finally, tumours with immunohistochemical HLA class I negative pattern were not grouped together but rather in accordance with features of the gene expression profile of MSI or MSS tumours. As expected, genes associated with antigen processing machinery and MHC class I molecules (TAP2, B2m) were downregulated in MSS/HLA-ABC negative CRCs. In conclusion, microarray and immunohistochemical data may be useful to comprehensively assess tumour-host interactions and differentiate MSI from MSS cancers. The two types of tumours, MSI/HLA- and MSS/HLA-, showed marked differences in the composition and intensity of infiltrating leukocytes, suggesting that their immune escape strategies involve distinct pathways. Case-control study. Samples were selected according to immunological criteria: those with total loss of HLA antigens and those without alterations in the expression of HLA molecules. In addition, the microsatellite instability genotype of all the samples was also analyzed, resulting in microsatellite stability (MSS) and microsatellite instability (MSI) samples. Therefore, three groups of samples were selected: MSS/HLA+, MSS/HLA-, and MSI. The MSS/HLA+ group was used as the control.
Project description:Goal: Microsatellite-instable (MSI) tumors are one of the few cancers that respond to immune checkpoint blockade (ICB); however, the mechanism of MSI status development is unclear. Here, we report that protein phosphatase 2A (PP2A) deletion or inactivation converted cold microsatellite-stable (MSS) into MSI tumors. Objectives: Using RNA sequencing data of three CT26-shppp2r1a data and a CT26-scr data, we demonstrate that these intestinal tumors display differential core driver pathways.
Project description:Early gastric cancers (EGC) precede advanced gastric cancers (AGC) with a favorable clinical outcome compared to advanced gastric cancers (AGC). To understand the progression mechanisms of EGC to AGC, it is required to disclose the EGC and AGC genomes in terms of the the mutational and evolutionary perspectives. In this study, we performed whole-exome sequencing and copy number profiling of nine microsatellite (MS)-unstable (MSI-H) (5 EGC and 4 AGC) and eight MS-stable (MSS) gastric cancers (4 EGC and 4 AGC). Unexpectedly, we observed no substantial differences in the number, sequence composition and functional consequences (potential driver mutations and affected pathways) of the mutations and CNAs between EGC and AGC genomes in both MSI-H and MSS cases.
Project description:Analysis of microRNA expression of tumoral and non-tumoral colonic tissues. The aim of this study was to analyze the global miRNA signatures in various groups of well-characterized CRCs based on the presence of microsatellite instability (MSI). Total RNA from formalin-fixed paraffin-embedded tissue blocks from 4 different groups (normal colonic mucosa, Lynch syndrome tumors, sporadic MSI tumors and MSS tumors) was isolated using the RecoverAll Total Nucleic Acid Isolation Kit (Ambion) according to manufacturer instructions. MiRNA expression profiles were analyzed using miRNA microarray platform.