Transcription profiling of breast carcinomas and correlation with clinical outcome
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Sørlie T
PROVIDER: S-ECPF-SMDB-579 | biostudies-other | 2001 Sep
REPOSITORIES: biostudies-other
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Project description:The purpose of this study was to explore the possibility of classifying breast carcinomas based upon variations in gene expression patterns derived from cDNA microarrays, and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing tumor and normal breast tissues from 78 individuals were analyzed by hierarchical-clustering. As reported previously, we identified a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized lluminal epithelial/ER-positiven group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets; first, a set of 456 cDNA clones previously selected to reflect the lintrinsicn properties of the tumors and, second, a gene set identified that highly correlated with patient outcome. Survival analyses on the sub-cohort of 51 patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
2005-06-28 | E-SMDB-579 | biostudies-arrayexpress
Project description:BackgroundTumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in routine pathology is hampered due to the use of several slightly different assessment systems, a time-consuming manual counting process and a high inter-observer variability. Hence, we established and validated an automatic image processing approach to reliably quantify tumor budding in immunohistochemically (IHC) stained sections of CRC samples.MethodsThis approach combines classical segmentation methods (like morphological operations) and machine learning techniques (k-means and hierarchical clustering, convolutional neural networks) to reliably detect tumor buds in colorectal carcinoma samples immunohistochemically stained for pan-cytokeratin. As a possible application, we tested it on whole-slide images as well as on tissue microarrays (TMA) from a clinically well-annotated CRC cohort.ResultsOur automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86). Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. However, the number of spatial clusters of tumor buds (budding hotspots) significantly correlated to the nodal status (p-value = 0.003 for N0 vs. N1/N2). TMAs were not feasible for tumor budding evaluation, as the spatial relationship of tumor buds (especially hotspots) was not preserved.ConclusionsAutomatic image processing is a feasible and valid assessment tool for tumor budding in CRC on whole-slide images. Interestingly, only the spatial clustering of the tumor buds in hotspots (and especially the number of hotspots) and not the absolute number of tumor buds showed a clinically relevant correlation with patient outcome in our data.
| S-EPMC6114534 | biostudies-literature
Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes’. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform. 16 IDC samples analyzed with the U133 Plus 2.0 array compared to 4 normal control samples.
| S-ECPF-GEOD-22544 | biostudies-other
Project description:tumor microenviroment facilitates metastatic spread by eliciting reversible changes in the phenotypes of cancer cells Experiment Overall Design: expression array of stromal samples prepared from 15 normal/DCIS and 7 IDC tumor specimans
| S-ECPF-GEOD-8977 | biostudies-other
Project description:The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents. Keywords: Gene expression profiling; correlation with outcome in clinical trials of the proteasome inhibitor bortezomib
2007-12-06 | GSE9782 | GEO
Project description:97 triple negative tumors were selected from the fresh-frozen tissue bank of the Netherlands Cancer Institute and gene expression profiles were generated using 35K oligonucleotide microarrays. Human breast carcinomas were snap frozen in liquid nitrogen within one hour after surgery and stored in the fresh-frozen tissue bank of the Netherlands Cancer Institute. RNA from a pool of more than 100 unselected fresh frozen breast carcinomas were isolated and pooled to form the reference to which each individual breast carcinoma is hybridized.
| S-ECPF-NCMF-2 | biostudies-other
Project description:The genetic program that drives tumor metastasis and the mode and timing of its initiation are of great practical significance to clinical management. Modern technical advances open new opportunities for gaining useful relevant information. Gene expression profiles of histologically-verified viable tissue from lymph node metastases were compared with those of matched primary breast cancers from 10 different patients, among samples from over 400 cases, using high-throughput oligonucleotide arrays comprising probes for 22,000 genes. It was observed that metastases have very similar expression signatures to their parent tumors. However, detailed computational analysis revealed that a small number of genes were consistently differentially expressed between 100% of tumors and metastases, suggesting that these are mechanistically important. Lists of such candidate genes, of potential clinical interest, are provided. We interpret these results in the framework of a meta-analysis of previous investigations by others and ourselves and of existing clinical knowledge on the behavior of human tumors. The collective data show that metastases resemble their primary tumors but the signatures obtained in different studies are not sufficiently reproducible or informative to be prognostically useful, although they do give valuable insights into the pathogenesis and biology of human tumor metastasis. The findings indicate that the genetic program encoding metastasis is implemented progressively over time although, occasionally, this evolution can occur rapidly, early in the life of the neoplasm. The important clinical significance of this deduction is that, in most patients, early detection provides time for appropriate therapeutic intervention to be effective in obstructing metastasis.
| S-EPMC5543892 | biostudies-literature
Project description:BackgroundWe report here for the first time, a comprehensive characterization of biological and clinical features of early-stage triple negative Invasive Lobular Carcinomas(TN-ILCs) METHODS: We analyzed all consecutive patients with early-stage TN-ILC operated at two reference cancer-centers between 1994 and 2012. Primary objective was to assess the invasive disease-free survival(iDFS). Co-primary objective was to assess biological features of TN-ILCs, including molecular intrinsic subtypes based on PAM-50 assay, expression of androgen receptor (AR) and mutational status of ERBB2-gene. Additionally, DNA mutational status of an independent cohort of 45 TN-ILCs from three databases were analyzed, to confirm mutations in ERBB2-gene and to identify other recurrently mutated genes.ResultsAmong 4152 ILCs, 74(1.8%) were TN and were analyzed. The iDFS at 5 and 10 years of FUP were 50.4%(95%CI,38.0-61.6) and 37.2%(95%CI,25.5-48.8), respectively. The molecular subtype was defined through PAM50-classifier for 31 out of 74 TN-ILCs: 48% were Luminal-A(15/31), 3% luminal-B(1/31), 32% HER2-enriched (10/31), and only 16% basal-like(5/31). Luminal tumors expressed AR more frequently than non-luminal tumors (AR≥1% in 94% of luminal tumors versus 53% in non-luminal tumors; p-value = 0.001). 20% of TN-ILCs analyzed(7/35), harbored a pathogenetic and actionable mutation in the ERBB2-gene. Analysis of the independent cohort of 45 TN-ILCs from three different databases, confirmed similar percentage of pathogenetic and actionable mutations in ERBB2-gene(20%; 9/45). Among the top 10 molecular pathways significantly enriched for recurrently mutated genes in TN-ILCs(FDR<0.05), there were ErbB-signaling and DNA-damage-response pathways.ConclusionsTN-ILCs are rare tumors with poor prognosis. Their specific biological features require newly defined targeted therapeutic strategies.
| S-EPMC8261657 | biostudies-literature
Project description:BACKGROUND: Ion channels play a critical role in a wide variety of biological processes, including the development of human cancer. However, the overall impact of ion channels on tumorigenicity in breast cancer remains controversial. METHODS: We conduct microarray meta-analysis on 280 ion channel genes. We identify candidate ion channels that are implicated in breast cancer based on gene expression profiling. We test the relationship between the expression of ion channel genes and p53 mutation status, ER status, and histological tumor grade in the discovery cohort. A molecular signature consisting of ion channel genes (IC30) is identified by Spearman's rank correlation test conducted between tumor grade and gene expression. A risk scoring system is developed based on IC30. We test the prognostic power of IC30 in the discovery and seven validation cohorts by both Cox proportional hazard regression and log-rank test. RESULTS: 22, 24, and 30 ion channel genes are found to be differentially expressed with a change in p53 mutation status, ER status, and tumor histological grade in the discovery cohort. We assign the 30 tumor grade associated ion channel genes as the IC30 gene signature. We find that IC30 risk score predicts clinical outcome (P < 0.05) in the discovery cohort and 6 out of 7 validation cohorts. Multivariate and univariate tests conducted in two validation cohorts indicate that IC30 is a robust prognostic biomarker, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node status, tumor size, tumor grade, estrogen and progesterone receptor status, and p53 mutation status. CONCLUSIONS: We identified a molecular gene signature IC30, which represents a promising diagnostic and prognostic biomarker in breast cancer. Our results indicate that information regarding the expression of ion channels in tumor pathology could provide new targets for therapy in human cancers.
| S-EPMC3849355 | biostudies-literature
Project description:BackgroundOvarian cancer (OCA), the fifth leading deaths cancer to women, is famous for its low survival rate in epithelial ovarian cancer cases, which is very complicated and hard to be diagnosed from asymptomatic nature in the early stage. Thus, it is urgent to develop an effective genetic prognostic strategy.MethodsCurrent study using the Database for Annotation, Visualization and Integrated Discovery tool for the generation and analysis of quantitative gene expression profiles; all the annotated gene and biochemical pathway membership realized according to shared categorical data from Pathway and Kyoto Encyclopedia of Genes and Genomes; correlation networks based on current gene screening actualize by Weighted correlation network analysis to identify therapeutic targets gene and candidate bio-markers.Results3095 differentially expressed genes were collected from genome expression profiles of OCA patients (n = 53, 35 advanced, 8 early and 10 normal). By pathway enrichment, most genes showed contribution to cell cycle and chromosome maintenance.1073 differentially expression genes involved in the 4 dominant network modules are further generated for prognostic pattern establish, we divided a dataset with random OCA cases (n = 80) into 3 groups efficiently (p = 0.0323, 95% CIs in Kaplan-Meier). Finally, 6 prognosis related genes were selected out by COX regression analysis, TFCP2L1 related to cancer-stem cell, probably contributes to chemotherapy efficiency.ConclusionsOur study presents an integrated original model of the differentially expression genes related to ovarian cancer progressing, providing the identification of genes relevant for its pathological physiology which can potentially be new clinical markers.
| S-EPMC4521463 | biostudies-literature