Implication of an Immune Score in Molecular Subtypes and Distant Metastasis of Breast Cancer: Comparison between Western and Chinese Han Patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE87377 | GEO | 2016/10/10
SECONDARY ACCESSION(S): PRJNA344563
REPOSITORIES: GEO
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Project description:Analysis of 104 breast cancer biopsies (removed prior to any treatment with tamoxifen or chemotherapeutic agents) from patients aged between 31 years and 89 years at the time of diagnosis (mean age = 58 years). Twenty were less than 50 years and seventy-seven women were 50 years, or older, at diagnosis. The size of the tumours ranged between 0.6 cm and 8.0 cm (mean = 2.79 cm). Eighteen tumours were T1 (<2 cm) in maximal dimension; 83 were T2 (2M-bM-^@M-^S5 cm) and 3 tumours were T3 (>5 cm). Eighty-two were invasive ductal carcinoma, 17 were invasive lobular and five were tumours of special type (two tubular and three mucinous). Eleven tumours were grade 1; 40 were grade 2; and 53 were grade 3. Sixty-seven tumours were oestrogen receptor (ER) positive and 34 were ER negative (ER status was determined by Enzyme Immuno-Assay (EIA); a positive result was defined as more than 200 fmol/g protein). ER status was not available for 3 patients. Forty-five tumours had no axillary metastases and 59 tumours had metastasised to axillary lymph nodes. Sixty-nine women were treated with post-operative tamoxifen; 26 did not receive tamoxifen. Fifty patients were treated with adjuvant systemic chemotherapy (CMF +/M-bM-^HM-^R adriamycin); 45 patients did not receive chemotherapy. Details regarding tamoxifen and systemic chemotherapy were not available for 9 patients. Maximal follow-up was 3,026 days with a mean follow-up of 1,887 days. 17 normal breast tissues were also assayed. Gene expression profiling of 104 breast cancer and 17 normal breast biopsies.
2013-05-26 | E-GEOD-42568 | biostudies-arrayexpress
Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.
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Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.
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Project description:Analysis of 104 breast cancer biopsies (removed prior to any treatment with tamoxifen or chemotherapeutic agents) from patients aged between 31 years and 89 years at the time of diagnosis (mean age = 58 years). Twenty were less than 50 years and seventy-seven women were 50 years, or older, at diagnosis. The size of the tumours ranged between 0.6 cm and 8.0 cm (mean = 2.79 cm). Eighteen tumours were T1 (<2 cm) in maximal dimension; 83 were T2 (2–5 cm) and 3 tumours were T3 (>5 cm). Eighty-two were invasive ductal carcinoma, 17 were invasive lobular and five were tumours of special type (two tubular and three mucinous). Eleven tumours were grade 1; 40 were grade 2; and 53 were grade 3. Sixty-seven tumours were oestrogen receptor (ER) positive and 34 were ER negative (ER status was determined by Enzyme Immuno-Assay (EIA); a positive result was defined as more than 200 fmol/g protein). ER status was not available for 3 patients. Forty-five tumours had no axillary metastases and 59 tumours had metastasised to axillary lymph nodes. Sixty-nine women were treated with post-operative tamoxifen; 26 did not receive tamoxifen. Fifty patients were treated with adjuvant systemic chemotherapy (CMF +/− adriamycin); 45 patients did not receive chemotherapy. Details regarding tamoxifen and systemic chemotherapy were not available for 9 patients. Maximal follow-up was 3,026 days with a mean follow-up of 1,887 days. 17 normal breast tissues were also assayed.
2013-05-26 | GSE42568 | GEO
Project description:This is Phase II Trial of 4courses of 5-fluorouracil, doxorubicin and cyclophosphamide follwed by 4 additional courses of weekly docetaxel and capecitabine administered as Preoperative Therapy for Patients with Locally Advanced Breast Cancer, Stages II and III by US oncology (PROTOCOL 02-103) We performed gene set analysis (GSA) using functionally annotated gene sets corresponding to almost all known biological processes in ER-positive/HER2negative and ER-negative/HER2-negative breast cancer, respectively.
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Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.
2014-01-07 | GSE48390 | GEO
Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.
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