1b48214a-9065-4160-9be3-af722f53cc51 - samples
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ABSTRACT:
PROVIDER: EGAD00001009414 | EGA |
REPOSITORIES: EGA
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Project description:Divergent estrogen receptor (ER) and HER2 status with breast cancer disease progression has important consequences for clinical management and long-term survival. Molecular subtype expression is dynamic and influenced by therapeutic intervention and the metastatic environment. HER2 status, ER expression levels and global DNA methylation was assessed in pre-treatment biopsies, in post-treatment samples in patients with residual disease and, where relevant, in metastatic tumour samples. Mapping of the methylation landscape revealed global gains in hypomethylation following treatment (n=7 matched tumours, 16 samples) in contrast to hypermethylation on metastasis (n=5 matched tumours, 14 samples). Differential methylation of key signalling pathways, including estrogen response, epithelial to mesenchymal transition and PI3K/AKT/mTOR, is conserved between post-treatment and metastasis. However, where core pathway genes were hypomethylated following treatment, there was a shift to hypermethylation on metastasis, facilitating alterations in the tumour phenotype. This study unlocks DNA methylation as a key process in breast cancer progression providing vital insights into the effects of targeted HER2 treatment. This work provides a clear rationale to develop combined HER2 inhibitor and endocrine therapeutic strategies to enhance long-term survival in HER2 positive patients.
2024-12-16 | GSE283272 | GEO
Project description:Clinical data for KATHERINE: Clinical data include Treatment Arm, Invasive Disease Free Survival (IDFS), Clinical Stage at Presentation, Hormone Receptor Status, Preoperative HER2 Directed Therapy, Pathological Node.
| EGAD00001008785 | EGA
Project description:The I-SPY2-990 mRNA/RPPA Data Resource contains gene expression and clinical data for 987 patients from 10 arms of the neoadjuvant I-SPY2 TRIAL for aggressive early stage breast cancer [210 Control (Ctr); 71 veliparib/carboplatin (VC); 114 neratinib (N); 93 MK2206; 106 ganitumab; 93 ganetespib; 134 trebananib; 52 TDM1/pertuzumab(P); 44 H/P; 69 pembrolizumab (pembro)]. All 987 patients have pretreatment full transcriptome expression data on over ~19,000 genes assayed on Agilent 44K. Clinical data includes HR, HER2 and MP status, response (pCR or no pCR), and treatment arm. The ISPY2-990 mRNA/RPPA Data Resource also includes normalized pre-treatment LCM-RPPA data for 139 key signaling proteins/phosphoproteins in cancer for 736 patients (see companion GEO record GSE196093 for data and details).
2022-05-25 | GSE194040 | GEO
Project description:The I-SPY2-990 mRNA/RPPA data resource contains gene expression, protein/phosphoprotein and clinical data for ~990 patients from the first 10 completed arms of the I-SPY 2 platform trial for aggressive, early stage breast cancer. Experimental treatments include pan-HER2 inhibitors and anti-HER2 agents, PARP inhibitor/DNA damaging agent combinations, an AKT inhibitor, immunotherapy, and ANG1/2, IGF1R and HSP90 inhibitors added to standard of care chemotherapy. All patients have pretreatment full transcriptome expression data on over ~19,000 genes assayed on Agilent 44K. 736 patients (all arms except ganitumab and ganetespib) have normalized LCM-RPPA data for 139 key signaling proteins/phosphoproteins in cancer. Clinical data includes HR, HER2 and MP status, response (pCR or no pCR), and treatment arm. This SuperSeries is composed of the mRNA and RPPA SubSeries listed below.
2022-05-25 | GSE196096 | GEO
Project description:In this publication, researchers investigated the intricate relationship between breast cancers and their microenvironment, specifically focusing on predicting treatment responses using multi-omic machine learning model. They collected diverse data types including clinical, genomic, transcriptomic, and digital pathology profiles from pre-treatment biopsies of breast tumors. Leveraging this comprehensive multi-omic dataset, the team developed ensemble machine learning models using different algorithms (Logistic Regression, SVM and Random Forest). These predictive models identifies patients likely to achieve a pathological complete response (pCR) to therapy, showcasing their potential to enhance treatment selection.
Please note that the authors also have an interactive dashboard to apply the fully-integrated NAT response model on new (or any desired) data. The user can find its link in their GitHub repository: https://github.com/micrisor/NAT-ML
For more information and clarification, please refer to the ReadMe_NAT-ML document in the files section.
2023-08-28 | BIOMD0000001075 | BioModels
Project description:The RPPA component of the I-SPY2-990 mRNA/RPPA Data Resource contains protein/phosphoprotein data from pre-treatment laser capture microdissected (LCM) tumor biopsies for 139 key signaling proteins/phosphoproteins in cancer for 736 patients from 8 arms of the neoadjuvant I-SPY2 TRIAL (NCT01042379) for aggressive early stage breast cancer [194 Control (Ctr); 63 veliparib/carboplatin (VC); 105 neratinib (N); 87 MK2206; 128 trebananib; 49 TDM1/pertuzumab(P); 43 H/P; and 67 pembrolizumab (pembro)]. This record also contains clinical data for these patients, including HR, HER2 and MP status, response (pCR or no pCR), and treatment arm. RPPA endpoints assayed are from hormone receptor (n=4), HER family (n=14), cell cycle/proliferation (n=20), immune (n=18), DNA repair deficiency (DDR; n=15), AKT/mTOR/PI3K (n=7), apoptosis/autophagy (n=10), IGF1R (n=6), TIE/ANG (n=4), growth/survival/metabolism (n=22) and RTK (n=19) pathways. For gene expresson data for all 736 patients with RPPA data, plus an additional 150 patients for a total 987 patients from 10 arms of I-SPY2 (mRNA component of the I-SPY2-990 Data Resource), see the companion GEO record/subseries GSE194040.
2022-05-25 | GSE196093 | GEO
Project description:The AKT inhibitor MK2206 (M) was one of the experimental agents evaluated in I-SPY 2, a neoadjuvant platform trial for high risk, early stage breast cancer, and graduated in the HER2+, HR-, and HR-HER2+ signatures. Based on the hypotheses that since MK2206 is an enzymatic inhibitor of AKT, response to MK2206 may be predicted by the relative pre-treatment levels of AKT kinase substrates, in pre-defined analyses we assessed 10 genes in the HER-AKT-mTOR pathway to test their association with pCR (complete pathologic response) in the MK2206 arm, in both HER2+ and HER2- subsets. We also tested 9 genes genes previously associated with response to MK2206 in vitro and in the HER2+ metastatic setting, and performed exploratory association analyses using whole-transcriptome data to identify additional predictive signals outside the HER-AKT-mTOR pathway.
2020-09-20 | GSE149322 | GEO
Project description:HER2-targeted therapies including antibody drug conjugates have shown great efficacy in HER2-positive breast cancer. However, resistance to treatment in part due to pre-existing HER2 heterogeneity (HET) is a significant clinical challenge and requires the use of rationally-designed combination therapies. Here we describe transcriptomic profiling of 287 biopsies from 129 patients in a phase II neoadjuvant clinical trial using a combination of T-DM1 and pertuzumab for early-stage HER2-positive breast cancer, we investigated the mechanisms driving T-DM1 resistance. In pre-treatment tumors from patients without a complete response (pCR), distinct molecular features were identified: HER2 HET tumors retained PI3K pathway activation and a basal-like phenotype, while HER2 Non-HET tumors exhibited lower PI3K pathway enrichment. T-DM1 treatment universally reduced HER2 protein expression and copy number heterogeneity while increasing PI3K pathway enrichment and luminal identity in residual tumors. Importantly, HER2 HET tumors showed minimal transcriptomic response compared to HER2 Non-HET tumors, in line with the lesser clinical response. The response to T-DM1 was not associated with hotspot PIK3CA/ERBB2 mutations but rather correlated with immune infiltration. HER2 Non-HET tumors exhibited less effective immune surveillance at baseline but became immune activated with T-DM1 treatment, while HER2 HET tumors exhibited a more immune suppressed microenvironment upon treatment. Our study highlights the multifaceted nature of T-DM1 resistance driven by HER2 heterogeneity and provides essential evidence for optimizing therapeutic strategies for these patients.
2024-02-29 | GSE243375 | GEO
Project description:Clinical data from IMblaze370: Clinical data include disease, treatment arm, MSI status, KRAS oncogenic mutation status, sex, and overall survival (1=dead, 0=alive)
| EGAD00001008551 | EGA
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