Gene expression signatures in breast cancer distinguish phenotype charact., histological subtypes, and tumor invasivness
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10810 | GEO | 2009/06/30
SECONDARY ACCESSION(S): PRJNA107401
REPOSITORIES: GEO
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Project description:Background. The development of reliable gene expression profiling technology is having an increasing impact on our understanding of breast cancer biology. Methods. In this study, microarray analysis was performed in order to establish gene signatures for different breast cancer phenotypes, determine differentially expressed gene sequences at different stages of the disease, and identify sequences with biological significance for tumor progression. Samples were taken from patients before their treatment. After microarray analysis, the expression level of 153 selected genes was studied by qPCR. Results. A number of gene sequences were differentially expressed in tumor versus control samples and were also associated with different breast cancer phenotypes, ER status, tumor histology, and grade of tumor differentiation. In N0 tumors were found a set of genes related to tumor differentiation grade. Conclusion. A number of differentially expressed gene sequences were found at different stages of the breast cancer disease. Key Words: Breast cancer, gene expression signature, tumor invasiveness, microarrays, qPCR In total, 58 samples were studied, 31 tumors and 27 controls. Some of the samples are paired
2009-06-30 | E-GEOD-10810 | biostudies-arrayexpress
Project description:PURPOSE The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. The present study aims to determine whether the phenotypic heterogeneity and genetic diversity of lung cancer are correlated. PATIENTS AND METHODS In this study, microarray analysis was performed in a set of 91 non-small cell lung cancer (NSCLC) samples in order to: establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas; determine differentially expressed gene sequences at different stages of the disease; and identify sequences with biological significance for tumor progression. After microarray analysis, the expression level of 92 selected genes was validated by qPCR in an independent set of 70 samples. RESULTS Gene sequences were differentially expressed as a function of tumor type, stage, and differentiation grade. High upregulation was observed for KRT15 and PKP1, which may be good markers to distinguish squamous cell carcinoma samples. High downregulation was observed for DSG3 in stage IA adenocarcinomas. CONCLUSION Expression signatures in NSCLC distinguish tumor type, stage, and differentiation grade. Keywords: Tumor vs control comparative genomics study
2010-10-01 | GSE18842 | GEO
Project description:PURPOSE The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. The present study aims to determine whether the phenotypic heterogeneity and genetic diversity of lung cancer are correlated. PATIENTS AND METHODS In this study, microarray analysis was performed in a set of 91 non-small cell lung cancer (NSCLC) samples in order to: establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas; determine differentially expressed gene sequences at different stages of the disease; and identify sequences with biological significance for tumor progression. After microarray analysis, the expression level of 92 selected genes was validated by qPCR in an independent set of 70 samples. RESULTS Gene sequences were differentially expressed as a function of tumor type, stage, and differentiation grade. High upregulation was observed for KRT15 and PKP1, which may be good markers to distinguish squamous cell carcinoma samples. High downregulation was observed for DSG3 in stage IA adenocarcinomas. CONCLUSION Expression signatures in NSCLC distinguish tumor type, stage, and differentiation grade. Keywords: Tumor vs control comparative genomics study 91 samples studied, 46 tumors and 45 controls. All samples are paired except three.
2010-10-01 | E-GEOD-18842 | biostudies-arrayexpress
Project description:Biological treatment of many cancers currently targets membrane bound receptors located on a cell surface. To identify novel membrane proteins associated with migration and metastasis of breast cancer cells, we selected and characterized a more migrating subpopulation of MDA-MB-231 breast cancer cells. We applied quantitative mass spectrometry with SILAC labeling to analyze their surfaceome and compared it with that of paternal MDA-MB-231 cells. Among 818 identified proteins (FDR < 0.01), 124 differentially abundant cell surface proteins with at least one transmembrane domain were found. Of these, (i) catechol-O-methyltransferase (COMT) was successfully verified as a protein associated with lymph node metastasis of triple negative breast cancer as well as tumor grade by targeted data extraction from the SWATH-MS data set of 96 breast cancer tissues, and (ii) desmocollin-1 (DSC1) was verified as a protein connected with lymph node status of luminal A breast cancer, tumor grade and Her-2 receptor by immunohistochemistry in the same set of patients. Kaplan-Meier analysis associated COMT and DSC1 with decreased overall survival in breast cancer subsets. Our findings indicate importance of both proteins for breast cancer development and metastasis
2019-10-23 | PXD013162 | Pride
Project description:Genomic Grade Index (GGI) is a 97-gene signature that improves histologic grade (HG) classification in invasive breast carcinoma. In this prospective study we sought to evaluate the feasibility of performing GGI in routine clinical practice and its impact on treatment recommendations. Patients with pT1pT2 or operable pT3, N0-3 invasive breast carcinoma were recruited from 8 centers in Belgium. Fresh surgical samples were sent at room temperature in the MapQuant DxM-bM-^DM-" PathKit for centralized genomic analysis. Genomic profiles were determined using Affymetrix U133 Plus 2.0 and GGI calculated using the MapQuant DxM-bM-^DM-" protocol, which defines tumors as low or high Genomic Grade (GG-1 and GG-3 respectively). 180 pts were recruited and 155 were eligible. The MapQuant test was performed in 142 cases and GGI was obtained in 78% of cases (n=111). Reasons for failures were 15 samples with <30% of invasive tumor cells (11%), 15 with insufficient RNA quality (10%), and 1 failed hybridization (<1%). For tumors with an available representative sample (M-bM-^IM-% 30% inv. tumor cells) (n=127), the success rate was 87.5 %. GGI reclassified 69% of the 54 HG2 tumors as GG-1 (54%) or GG-3 (46%). Changes in treatment recommendations occurred mainly in the subset of HG2 tumors reclassified into GG-3, with increased use of chemotherapy in this subset. The use of GGI is feasible in routine clinical practice and impacts treatment decisions in early-stage breast cancer. Total RNA was extracted from fresh tumor tissues comprising M-bM-^IM-%30% invasive tumor cells and hybridized on Affymetrix microarrays if the RIN was M-bM-^IM-% 7.
2013-06-03 | E-GEOD-43365 | biostudies-arrayexpress
Project description:Purpose: Presence of pelvic lymph node metastases is the main prognostic factor in early stage cervical cancer patients, primarily treated with surgery. Aim of this study was to identify cellular tumor pathways associated with pelvic lymph node metastasis in early stage cervical cancer. Experimental Design: Gene expression profiles (Affymetrix U133 plus 2.0) of 20 patients with negative (N0) and 19 with positive lymph nodes (N+), were compared with gene sets that represent all 285 presently available pathway signatures. Validation immunostaining of tumors of 274 consecutive early stage cervical cancer patients was performed for representatives of the identified pathways. Results: Analysis of 285 pathways resulted in identification of five pathways (TGF-β, NFAT, ALK, BAD, and PAR1) that were dysregulated in the N0, and two pathways (β-catenin and Glycosphingolipid Biosynthesis Neo Lactoseries) in the N+ group. Class comparison analysis revealed that five of 149 genes that were most significantly differentially expressed between N0 and N+ tumors (P<0.001) were involved in β-catenin signaling (TCF4, CTNNAL1, CTNND1/p120, DKK3 and WNT5a). Immunohistochemical validation of two well-known cellular tumor pathways (TGF-β and β-catenin) confirmed that the TGF-β pathway (positivity of Smad4) was related to N0 (OR:0.20, 95%CI:0.06-0.66) and the β-catenin pathway (p120 positivity) to N+ (OR:1.79, 95%CI:1.05-3.05). Conclusions: Our study provides new, validated insights in the molecular mechanism of lymph node metastasis in cervical cancer. Pathway analysis of the microarray expression profile suggested that the TGF-β and p120-associated non-canonical β-catenin pathways are important in pelvic lymph node metastasis in early stage cervical cancer. For the microarray experiment, we selected fresh frozen primary cervical cancer tissue, containing at least 80% tumor cells, of patients with histologically confirmed N0 (n=20) and of patients with N+ (n=19). The N0 and N+ groups were matched for age, FIGO stage and histology (all squamous cell carcinoma).
2011-02-15 | E-GEOD-26511 | biostudies-arrayexpress
Project description:Genomic Grade Index (GGI) is a 97-gene signature that improves histologic grade (HG) classification in invasive breast carcinoma. In this prospective study we sought to evaluate the feasibility of performing GGI in routine clinical practice and its impact on treatment recommendations. Patients with pT1pT2 or operable pT3, N0-3 invasive breast carcinoma were recruited from 8 centers in Belgium. Fresh surgical samples were sent at room temperature in the MapQuant Dx™ PathKit for centralized genomic analysis. Genomic profiles were determined using Affymetrix U133 Plus 2.0 and GGI calculated using the MapQuant Dx™ protocol, which defines tumors as low or high Genomic Grade (GG-1 and GG-3 respectively). 180 pts were recruited and 155 were eligible. The MapQuant test was performed in 142 cases and GGI was obtained in 78% of cases (n=111). Reasons for failures were 15 samples with <30% of invasive tumor cells (11%), 15 with insufficient RNA quality (10%), and 1 failed hybridization (<1%). For tumors with an available representative sample (≥ 30% inv. tumor cells) (n=127), the success rate was 87.5 %. GGI reclassified 69% of the 54 HG2 tumors as GG-1 (54%) or GG-3 (46%). Changes in treatment recommendations occurred mainly in the subset of HG2 tumors reclassified into GG-3, with increased use of chemotherapy in this subset. The use of GGI is feasible in routine clinical practice and impacts treatment decisions in early-stage breast cancer.
2013-06-03 | GSE43365 | GEO
Project description:Current prognostic factors are insufficient for precise risk-discrimination in breast cancer patients with low grade breast tumors, which, in disagreement with theoretical prognosis, occasionally form early lymph node metastasis. To identify markers for this group of patients, we employed iTRAQ-2DLC-MS/MS proteomics to 24 lymph node positive and 24 lymph node negative grade 1 luminal A primary breast tumors. Another group of 48 high-grade tumors (luminal B, triple negative, Her-2 subtypes) was also analyzed to investigate marker specificity for grade 1 luminal A tumors. From the total of 4405 proteins identified (FDR<5%), the top 65 differentially expressed together with 30 previously identified and control markers were analyzed also at transcript level. Increased levels of carboxypeptidase B1 (CPB1), PDZ and LIM domain protein 2 (PDLIM2) and ring finger protein 25 (RNF25) were associated specifically with lymph node positive grade 1 tumors, whereas stathmin 1 (STMN1) and thymosin beta 10 (TMSB10) associated with aggressive tumor phenotype also in high grade tumors at both protein and transcript level. For CPB1, these differences were also observed by immunohistochemical analysis on tissue microarrays. Upregulation of putative biomarkers in lymph node positive (vs. negative) luminal A tumors was validated by gene expression analysis of an independent published dataset (N=343) for CPB1 (p=0.00155), PDLIM2 (p=0.02027) and RELA (p=0.00015). Moreover, statistically significant connections with patient survival were identified in another public dataset (N=1678). Our findings indicate unique pro-metastatic mechanisms in grade 1 tumors that can include up-regulation of CPB1, activation of NF-κB pathway and changes in cell survival and cytoskeleton. These putative biomarkers have potential to identify the specific minor sub-population of breast cancer patients with low grade tumors who are at higher than expected risk of recurrence and who would benefit from more intensive follow-up and may require more personalized therapy.
2015-04-23 | PXD000029 | Pride
Project description:We explored whether lncRNA expression in primary tumor had nodal predicting value for HER-2 positive breast cancer who received neoadjuvant therapy. To explore the differentially expressed lncRNA, six HER2+ fresh core biopsies tissues before NAT were collected (3 tissues from ypT0N0 group and 3 tissues from ypT+N+ group) and subjected to lncRNA microarray. Different lncRNAs (POTEH-AS1, LncRNA-AL390243.1, and lncRNA-AC009975.1 ) were selected by microarray, validated by qPCR,
2021-11-13 | GSE188743 | GEO
Project description:Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Experiment Overall Design: 64 microarray experiments from primary breast tumors used as training set to identify genes differentially expressed in grade 1 and 3. Experiment Overall Design: 129 microarray experiments from primary breast tumors of untreated patients used as validation set to validate the list of genes and its correlation with survival. Experiment Overall Design: No replicate, no reference sample. **NOTE** There are some inconsistencies between the sample annotation provided by GEO for this experiment in the GSE2990_family.soft.gz file and the supplementary data file GSE2990_suppl_info.txt. ***
2008-06-13 | E-GEOD-2990 | biostudies-arrayexpress