Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

ABSTRACT: Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

PROVIDER: PRJNA688546 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

Project description:Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

| PRJNA688545 | ENA

Characterizing advanced breast cancer heterogeneity and treatment resistance through serial biopsies and comprehensive analytics.

Project description:Molecular heterogeneity in metastatic breast cancer presents multiple clinical challenges in accurately characterizing and treating the disease. Current diagnostic approaches offer limited ability to assess heterogeneity that exists among multiple metastatic lesions throughout the treatment course. We developed a precision oncology platform that combines serial biopsies, multi-omic analysis, longitudinal patient monitoring, and molecular tumor boards, with the goal of improving cancer management through enhanced understanding of the entire cancer ecosystem within each patient. We describe this integrative approach using comprehensive analytics generated from serial-biopsied lesions in a metastatic breast cancer patient. The serial biopsies identified remarkable heterogeneity among metastatic lesions that presented clinically as discordance in receptor status and genomic alterations with mixed treatment response. Based on our study, we highlight clinical scenarios, such as rapid progression or mixed response, that indicate consideration for repeat biopsies to evaluate intermetastatic heterogeneity (IMH), with the objective of refining targeted therapy. We present a framework for understanding the clinical significance of heterogeneity in breast cancer between metastatic lesions utilizing multi-omic analyses of serial biopsies and its implication for effective personalized treatment.

| S-EPMC7997873 | biostudies-literature

Serial gene expression analysis in locally advanced breast cancer patients who failed to respond to neoadjuvant chemotherapy

2015-06-12 | GSE32603 | GEO

CRISPR-Analytics

Project description:CRISPR-Analytics (CRISPR-A): a platform for precise analytics and simulations for gene editing

| PRJEB53901 | ENA

Serial gene expression analysis in locally advanced breast cancer patients who failed to respond to neoadjuvant chemotherapy

Project description:To elucidate candidate genes and pathways associated with poor response, we retrospectively analyzed gene expression profiles in serial biopsies from women with locally advanced breast cancer who failed to respond to anthracycline-based chemo followed by taxane in the I-SPY Of the 221 patients who completed neoadjuvant chemotherapy, 215 patients had surgery with 73% not achieving a pathologic complete response (pathCR). In these patients, cDNA microarray expression profiles from pretreatment biopsy (T1) were compared to those biopsy specimens obtained 24-72 hours after initiation of treatment (T2) or in tumors surgically removed after chemotherapy (TS). Paired expression data for T1vsT2 and T1vsTS were available for 29 and 39 patients with no pathCR, respectively. Paired differential expression analyses were performed via Significance Analysis of Microarrays (SAM) and differentially expressed genes were subjected to Ingenuity Pathway Analysis

2015-06-12 | E-GEOD-32603 | biostudies-arrayexpress

Differential activity of treatment with protein kinase inhibitors on tumor phosphotyrosine profiles in patients with advanced cancer

Project description:Mass spectrometry-based phosphoproteomics of tumor tissue lysates provides a potential personalized medicine approach based on its ability to identify activated signaling pathways and novel drug targets. We performed a pilot study (NCT01636908) to determine the effect of protein kinase inhibitors (PKIs) on tyrosine-(pTyr)-phosphoproteomic profiles of serial tumor biopsies in patients with advanced cancer. Tumor needle biopsies were analyzed from 31 patients with advanced cancer before and after 2 weeks treatment with sorafenib (SOR), erlotinib (ERL), dasatinib (DAS), vemurafenib (VEM), sunitinib (SUN) or everolimus (EVE). pTyr-Phosphoproteomics of pre- and on-treatment biopsies was performed by phosphotyrosine immunoprecipitation followed by LC-MS/MS.

2019-04-18 | PXD008032 | Pride

Gene expression data from serial samples of follicular lymphoma (FLSB - follicular lymphoma serial biopsies)

Project description:Transformation of follicular lymphoma (FL) to a more aggressive disease is associated with rapid progression and death. Existing molecular markers for transformation are few and their clinical impact is limited. Here, we report on a whole-genome study of DNA copy numbers and gene expression profiles in serial FL biopsies. We identified 698 genes with high correlation between gene expression and copy number and the molecular network most enriched for these cis-associated genes. This network includes 14 cis-associated genes directly related to the NFκB pathway. For each of these 14 genes, the correlated NFκB target genes were identified and corresponding expression scores defined. The scores for six of the cis-associated NFκB pathway genes (BTK, IGBP1, IRAK1, ROCK1, TMED7-TICAM2 and TRIM37) were significantly associated with transformation. The results suggest that genes regulating B-cell survival and activation are involved in transformation of FL Expression profiles were obtained from 81 biopsies origniating from 41 patients diagnosed with follicular lymphoma using Affymetrix HG U133 Plus 2.0 Gene Chip. Of these, 49 biopsies were from 24 patients with subsequent transformation to higher-grade lymphoma (DLBCL) (43 with histological diagnosis FL and 6 with DLBCL) and 32 biopsies were from 17 patients without any signs transformation

2014-01-07 | E-GEOD-53820 | biostudies-arrayexpress

Stable gene expression of serial skin biopsies defines patient subsets in diffuse cutaneous systemic sclerosis

Project description:Systemic sclerosis (SSc) shows complex clinical manifestations including progressive skin and internal organ fibrosis. SSc can be divided into 'intrinsic subsets' by gene expression suggesting patient-specific heterogeneity in pathogenesis or temporal evolution of disease. Here we validate these subsets using an independent patient population, and test whether the genes vary over time with patients changing subsets as disease progresses, or if the genes are a stable feature of the patients within each subset. Skin biopsies were analyzed from 13 dSSc patients enrolled in an open label study of rituximab, 9 dSSc patients not treated with rituximab, and 9 healthy controls. These data recapitulate the patient 'intrinsic subsets' described previously with gene expression associated with cell proliferation, inflammatory processes, and a normal-like group. Serial skin biopsies showed consistent and non-progressing gene expression. We were unable to detect significant differences in gene expression before and after rituximab treatment, consistent with an apparent lack of clinical response. Serial biopsies from each patient stayed within the same gene expression subset regardless of treatment regimen or the time point at which they were taken. This demonstrates the intrinsic subsets are an inherent, reproducible and stable feature of SSc that is independent of disease duration.

2012-03-23 | GSE32413 | GEO

RNA-sequencing of serial biopsies from 3 patients treated with Capivasertib (AZD5363)

Project description:RNA-sequencing of serial biopsies from 3 patients treated with Capivasertib (AZD5363)

| PRJNA609909 | ENA

Gene expression data from serial samples of follicular lymphoma (FLSB - follicular lymphoma serial biopsies)

2014-01-07 | GSE53820 | GEO