Breast Heterogeneity Validation
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ABSTRACT:
PROVIDER: EGAS00001001972 | EGA |
REPOSITORIES: EGA
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Project description:Purpose Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with no targeted treatment available. Our previous study identified 38 TNBC-specific genes with altered expression in tumour samples compared to normal samples. This study aimed to identify whether DNA methylation contributed to these gene expression changes in the same breast cancer cohort. Additionally, we aimed to identify a whole genome methylation profile that contributes to the progression from primary breast tumour to lymph node metastasis. Methods We used the DNA of 23 primary TNBC samples, 12 matched lymph node metastases, and 11 matched normal adjacent tissues to perform 450K Illumina methylation arrays. The results were validated in an independent cohort of 70 primary TNBC samples. Results The gene expression of 16/38 TNBC-specific genes was associated with significantly altered methylation. Furthermore, altered methylation of 18 genes associated with lymph node metastasis was identified and validated in an independent cohort. Additionally, novel methylation changes between primary tumours and lymph node metastases, as well as those associated with survival were identified. Conclusion This study has shown that DNA methylation plays an important role in altered gene expression patterns of TNBC-specific genes and is the first study to perform whole genome DNA methylation analysis that includes matched lymph node metastases in this breast cancer subtype. This novel insight into the progression of TNBC to secondary cancers may provide potential prognostic indicators for this hard-to-treat breast cancer subtype. Validation cohort (70 IDC TNBC samples)
2017-02-10 | GSE78754 | GEO
Project description:Validation of point mutations and small insertions and deletions in primary and associated metastatic breast cancer samples with matched normal tissues.
| EGAS00001001968 | EGA
Project description:In our early study (PMID: 21939527), we have created a ClinicoMolecular Triad Classification (CMTC) to improve prediction and prognostication of breast cancer by using a training cohort contained 161 breast cancer patients (2003 to 2008). Here, a supplemental internal validation cohort contained 340 breast cancer patients was collected (2008 to 2010) for development of the CMTC.
2014-06-19 | GSE45725 | GEO
Project description:This is an observational case-control study to train and validate a genome-wide methylome enrichment platform to detect multiple cancer types and to differentiate amongst cancer types. The cancers included in this study are brain, breast, bladder, cervical, colorectal, endometrial, esophageal, gastric, head and neck, hepatobiliary, leukemia, lung, lymphoma, multiple myeloma, ovarian, pancreatic, prostate, renal, sarcoma, and thyroid. These cancers were selected based on their prevalence and mortality to maximize impact on clinical care.
Additionally, the ability of the whole-genome methylome enrichment platform to detect minimal residual disease after completion of cancer treatment and to detect relapse prior to clinical presentation will be evaluated in four cancer types (breast, colorectal, lung, prostate). These cancers were selected based on the existing clinical landscape and treatment availability.
| 2727212 | ecrin-mdr-crc
Project description:6 samples of FFPE breast cancer tissue, whole genome amplification methods tested for fidelity: 3 samples amplified by two techniques (SCOMP and DOP) and compaed to non amplified control, 3 samples amplified additionally by the better performing technique (SCOMP) Keywords: Pre-clinical method validation, whole genome amplification for use with aCGH
2008-02-10 | GSE10456 | GEO
Project description:Validation of pooled whole-genome re-sequencing in Arabidopsis lyrata
| PRJEB8335 | ENA
Project description:In our early study ([GEO Accession: GSE16987], [PMID: 21939527]), we have created a ClinicoMolecular Triad Classification (CMTC) to improve prediction and prognostication of breast cancer by using a training cohort contained 161 breast cancer patients (2003 to 2008). Here, a supplemental internal validation cohort contained 340 breast cancer patients was collected (2008 to 2010) for development of the CMTC. Total 340 fine-needle aspirates (FNA) specimens from breast tumors without replicate were collected and prepared for microarray examination. Finally, 284 invasive breast cancers were used in this study.
2014-06-19 | E-GEOD-45725 | biostudies-arrayexpress
Project description:Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.
| EGAS00001000403 | EGA
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
2007-01-05 | E-SMDB-3830 | biostudies-arrayexpress
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
2006-12-10 | E-SMDB-3831 | biostudies-arrayexpress