Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Epigenome analysis of pre- and post-neoadjuvant chemotherapy breast tumor samples

ABSTRACT: Epigenome analysis of pre- and post-neoadjuvant chemotherapy breast tumor samples

PROVIDER: PRJNA416463 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Epigenome analysis of pre- and post-neoadjuvant chemotherapy breast tumor samples

Project description:Methylome-wide DNA methylation profiling of spatially separated breast tumor samples pre- and post-neoadjuvant chemotherapy (NAC) to characterize methylation heterogeneity alteration by NAC. The Illumina Infinium HumanMethylation450K Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 485,000 CpGs in the 47 samples derived from 8 breast cancer patients.

2019-01-31 | GSE106360 | GEO

Transcriptomes of tumour-associated macrophages from high grade serous ovarian cancer pre- and post-platinum-based neoadjuvant chemotherapy.

Project description:The impact of platinum and taxol based neoadjuvant chemotherapy on tumour-associated macrophages (TAMs) was examined by analysis of TAMs extracted from high grade serous ovarian cancer (HGSOC) samples pre and post chemotherapy.

2021-04-20 | GSE158739 | GEO

Long noncoding RNA expression profile of breast cancer tissues pre- and post-neoadjuvant chemotherapy

Project description:Long noncoding RNA expression profile of breast cancer tissues pre- and post-neoadjuvant chemotherapy

| PRJNA912689 | ENA

Long noncoding RNA expression profile of breast cancer tissues pre- and post-neoadjuvant chemotherapy

Project description:To identify the differential expression of lncRNAs, we performed the lncRNA microarray analysis with three pairs of breast cancer tissues before and after neoadjuvant chemotherapy (NAC) from partially responded patients by Arraystar Human LncRNA Microarray V3.0.

2024-07-16 | GSE221061 | GEO

TMT-based Quantitative Proteomics Identifies Protein Markers of Resistance to Neoadjuvant Chemotherapy in Ovarian Cancer

Project description:The high rate of recurrence and chemoresistance necessitates in ovarian cancer warrants further research into tumor markers characterizing the resistant population. The proportion of drug-resistant tissue cells in residual lesions after neoadjuvant chemotherapy increases, and drug-resistant markers are enriched. However, there is a lack of comprehensive understanding of tumor marker predoninance pre- and post- neoadjuvant chemotherapy. Here we performed quantitative proteomic analysis of TMT in three patients with matched pretreatment biopsies and post-NACT ovarian cancer tissues. This study highlights a dominant molecular subpopulation that persists in the ovary after neoadjuvant chemotherapy exposure in order to elucidate how it is involved in mediating chemotherapy response, which will lay the foundation for the development.

2023-08-01 | PXD044243 |

Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance

Project description:When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identifiy biomarkers of response and resistance mechanims. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p=0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; 0=0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatmane sample (CDKN1B) or in the post-treatment sample(TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

2021-12-18 | GSE191127 | GEO

Proteomic Alterations Associated with Residual Disease in Neoadjuvant Chemotherapy Treated Ovarian Cancer Tissues

Project description:Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome in the management of high-grade serous ovarian cancer (HGSOC) patients. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) offers an alternate approach to management of HGSOC patients to achieve complete resection. This study assessed proteomic alterations in matched, chemotherapy naïve and NACT-treated patients tumors obtained from HGSOC patients with suboptimal (R1) versus optimal (R0) debulking at IDS. We describe distinct proteome profiles in pre- and post-NACT HGSOC tumors correlating with residual disease status providing prognostic biomarkers for residual disease at IDS as well as candidate proteins associated with NACT resistance warranting further pre-clinical investigation.

2022-10-05 | PXD031929 | Pride

Validation cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer

Project description:PURPOSE: To develop a predictive test for response and survival following neoadjuvant taxane-anthracycline chemotherapy for HER2-negative invasive breast cancer. METHODS: We developed a microarray-based gene expression test from pre-treatment tumor biopsies (310 patients) to predict favorable outcome based on estrogen receptor (ER) status,pathologic response to chemotherapy, 3-year disease outcomes, and sensitivity to endocrine therapy. Tumors were classified as treatment-sensitive if predicted to have pathologic response (and not resistance) to chemotherapy, or sensitive to endocrine therapy. We tested predictive accuracy, with 95% confidence interval (CI), for pathologic response (PPV, positive predictive value), distant relapse-free survival (DRFS), and absolute risk reduction at median follow-up in 198 other patients. Independence from clinical-pathologic factors was assessed in a multivariate Cox regression analysis based on the likelihood ratio test. Other evaluable, published response predictors (genomic grade index (GGI), intrinsic subtype (PAM50), pCR predictor (DLDA30)) were compared. Neoadjuvant validation cohort of 198 HER2-negative breast cancer cases treated with taxane-anthracycline chemotherapy pre-operatively and endocrine therapy if ER-positive. Response was assessed at the end of neoadjuvant treatment and distant-relapse-free survival was followed for at least 3 years post-surgery.

2011-05-11 | E-GEOD-25065 | biostudies-arrayexpress

Discovery cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer

Project description:PURPOSE: To develop a predictive test for response and survival following neoadjuvant taxane-anthracycline chemotherapy for HER2-negative invasive breast cancer. METHODS: We developed a microarray-based gene expression test from pre-treatment tumor biopsies (310 patients) to predict favorable outcome based on estrogen receptor (ER) status,pathologic response to chemotherapy, 3-year disease outcomes, and sensitivity to endocrine therapy. Tumors were classified as treatment-sensitive if predicted to have pathologic response (and not resistance) to chemotherapy, or sensitive to endocrine therapy. We tested predictive accuracy, with 95% confidence interval (CI), for pathologic response (PPV, positive predictive value), distant relapse-free survival (DRFS), and absolute risk reduction at median follow-up in 198 other patients. Independence from clinical-pathologic factors was assessed in a multivariate Cox regression analysis based on the likelihood ratio test. Other evaluable, published response predictors (genomic grade index (GGI), intrinsic subtype (PAM50), pCR predictor (DLDA30)) were compared. Neoadjuvant study of 310 HER2-negative breast cancer cases treated with taxane-anthracycline chemotherapy pre-operatively and endocrine therapy if ER-positive. Response was assessed at the end of neoadjuvant treatment and distant-relapse-free survival was followed for at least 3 years post-surgery.

2011-05-11 | E-GEOD-25055 | biostudies-arrayexpress

HER2-enriched tumor initiating cell (HTIC) genomic predictor of response following neoadjuvant trastuzumab-based chemotherapy in HER2+ breast cancer

Project description:We identified a 17-gene Her2-enriched tumor initiating cell (HTIC) signature in MMTV-Her2/Neu mouse mammary TICs. Here, we show that patients with HTICS+ HER2+:ERα− tumors are more likely to achieve a pathologic complete response to trastuzumab-based neoadjuvant chemotherapy compared with HER2+:ER+ tumors. Neoadjuvant study of 50 HER2-positive breast cancer cases treated with trastuzumab-based chemotherapy pre-operatively. Pre-treatment FNA from primary tumors were obtained and RNA extracted and hybridized to Affymetrix microarrays according to manufacturer protocol. Pathologic response was assessed at the end of neoadjuvant treatment.

2012-05-11 | E-GEOD-37946 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data