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A predictive and prognostic 38-gene expression signature for metastatic relapse in breast cancer

ABSTRACT: Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis 252 breast cancer patients at diagnosis examined with spotted cDNA nylon membrane. Patient details: PACS01x are 2 parts of a clinical trial : PACS01A : patients had received 6 cycles of FEC100 PACS01B : patients had received 3 cycles of FEC100 then 3 cycles of Docetaxel CCRG are patients from our local cancer center (Cancer Center René Gauducheau) included with the same criteria as PACS01A (6 cycles of FEC100).

ORGANISM(S): Homo sapiens

SUBMITTER: Jézéquel P

PROVIDER: S-ECPF-GEOD-11264 | biostudies-other | 2009 Aug

REPOSITORIES: biostudies-other

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Project description:Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis 252 breast cancer patients at diagnosis examined with spotted cDNA nylon membrane. Patient details: PACS01x are 2 parts of a clinical trial : PACS01A : patients had received 6 cycles of FEC100 PACS01B : patients had received 3 cycles of FEC100 then 3 cycles of Docetaxel CCRG are patients from our local cancer center (Cancer Center René Gauducheau) included with the same criteria as PACS01A (6 cycles of FEC100).

Project description:Breast cancer (BC) is the most common type of malignancy among females worldwide. Histone modifications, which are the major post-translational modifications, have a significant role in cancer development and prognosis. However, whether histone family genes may serve as potential prognostic biomarkers for BC patients has remained elusive. In the present study, RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analysis was performed. As histone family genes have been reported to be associated with cervical cancer, the present study hypothesized that histone family genes are associated with gynecological tumors. Histone family genes, including histone cluster 1 H1A family member B (HIST1H1B), HIST1H2AJ, HIST1H2AM, HIST1H2BI, HIST1H2BO, HIST1H3B, HIST1H3F, HIST1H3H, HIST1H4C and HIST1H4D, were upregulated and identified as hub genes in the protein-protein interaction network. In addition, Oncomine and the Human Protein Atlas were used to further verify the expression levels of histone gene sets. The PrognoScan database was then used to investigate the association between expression and prognostic value regarding cancer patient survival. The present results indicated that higher expression of histone gene sets was associated with poor overall survival, relapse-free survival and distant metastasis-free survival of BC patients. The differential expression of histone family genes between BC and normal samples was validated by reverse transcription-quantitative PCR. Finally, to determine the clinical role of histone family genes in BC, the correlations between histone family genes expression and clinical characteristics were investigated through data collected from TCGA. Therefore, the present study indicates that histone gene sets may be used as prognostic factors for survival prediction for BC patients.

Project description:Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

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A predictive and prognostic 38-gene expression signature for metastatic relapse in breast cancer

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