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Identification of Prognosis-Relevant Subgroups in Patients with Chemoresistant Triple Negative Breast Cancer

ABSTRACT: Triple-negative breast cancer (TNBC) patients with residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of chemoresistant TNBC patients with different prognosis. In this study, 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital) are chosen for study

ORGANISM(S): Homo sapiens

PROVIDER: GSE43502 | GEO | 2013/01/15

SECONDARY ACCESSION(S): PRJNA186609

REPOSITORIES: GEO

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Identification of Prognosis-Relevant Subgroups in Patients with Chemoresistant Triple Negative Breast Cancer

Project description:Triple-negative breast cancer (TNBC) patients with residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of chemoresistant TNBC patients with different prognosis. In this study, 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital) are chosen for study We used gene expression data of TNBC patients with residual disease and different prognosis to molecularly define the clinically relevant subgroups, and developed a 7-gene prognostic signature for chemoresistant TNBCs

2013-01-15 | E-GEOD-43502 | biostudies-arrayexpress

Targeting neddylation and sumoylation in chemoresistant triple negative breast cancer

Project description:Triple negative breast cancer (TNBC) accounts for 15-20% of breast cancer cases in the United States. Systemic neoadjuvant chemotherapy (NACT), with or without immunotherapy, is the current standard of care for patients with early-stage TNBC. However, up to 70% of TNBC patients have significant residual disease once NACT is completed, which is associated with a high risk of developing recurrence within two to three years of surgical resection. To identify targetable vulnerabilities in chemoresistant TNBC, we generated longitudinal patient-derived xenograft (PDX) models from TNBC tumors before and after patients received NACT. We then compiled transcriptomes and drug response profiles for all models. Transcriptomic analysis identified the enrichment of aberrant protein homeostasis pathways in models from post-NACT tumors relative to pre-NACT tumors. This observation correlated with increased sensitivity in vitro to inhibitors targeting the proteasome, heat shock proteins, and neddylation pathways. Pevonedistat, a drug annotated as a NEDD8-activating enzyme (NAE) inhibitor, was prioritized for validation in vivo and demonstrated efficacy as a single agent in multiple PDX models of TNBC. Pharmacotranscriptomic analysis identified a pathway-level correlation between pevonedistat activity and post-translational modification (PTM) machinery, particularly involving neddylation and sumoylation targets. Elevated levels of both NEDD8 and SUMO1 were observed in models exhibiting a favorable response to pevonedistat compared to those with a less favorable response in vivo. Moreover, a correlation emerged between the expression of neddylation-regulated pathways and tumor response to pevonedistat, indicating that targeting these PTM pathways may prove effective in combating chemoresistant TNBC.

2024-05-17 | GSE264252 | GEO

An immunological signature to predict outcome in patients with triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy

Project description:When triple-negative breast cancer (TNBC) patients have residual disease after neoadjuvant chemotherapy (NACT), they have a high risk of metastatic relapse. With immune infiltrate in TNBC being prognostic and predictive of response to treatment, our aim was to develop an immunologic transcriptomic signature using post NACT samples to predict relapse.

2022-09-20 | GSE185507 | GEO

Identification of Prognosis-Relevant Subgroups in Patients with Chemoresistant Triple Negative Breast Cancer

| S-ECPF-GEOD-43502 | biostudies-other

Identification of prognosis-relevant subgroups in patients with chemoresistant triple-negative breast cancer.

Project description:PurposePatients with triple-negative breast cancer (TNBC) and residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of patients with chemoresistant TNBC with different prognosis.Experimental designForty-nine chemoresistant cases from 111 patients with TNBC treated with neoadjuvant chemotherapy (M.D. Anderson Cancer Center, Houston, TX) constituted the discovery cohort, and 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital, Houston, TX) were chosen for validation. Extended validation was carried out in 269 operable TNBC predicted to be chemoresistant by expression pattern from published datasets.ResultsWe established a seven-gene prognostic signature using dChip and gene set enrichment analyses. In the independent validation cohort, the classifier predicted correctly with positive predictive value of 75.0% and negative predictive value (i.e., relapse-free survival; RFS) of 76.9% at 3 years. Those predicted to relapse had a HR of 4.67 [95% confidence interval (CI): 1.27-17.15] for relapse in 3 years. In extended validation, patients predicted not to relapse exhibited 3-year RFS of 78.9%, whereas the 3-year RFS was 48.5% for patients predicted to relapse, with HR of 2.61 (95% CI: 1.52-4.49). The TNBC subgroup that predicted to have relatively favorable prognosis was characterized by high expression of "luminal-like" genes [androgen-receptor (AR) and GATA3], whereas the subgroup with worse prognosis was characterized by expression of cancer stem-cell markers.ConclusionWe developed a clinically relevant signature for patients with chemoresistant TNBC. For these women, new therapeutic strategies like targeting AR activation or cancer stem cells may need to be developed.

| S-EPMC3655097 | biostudies-literature

ColXα1 and Tumor Infiltrating Lymphocytes: a Marker of Response to Neoadjuvant Therapy in Estrogen Receptor and Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer

Project description:This study focused on patients with estrogen receptor positive/human epidermal growth factor receptor 2 positive (ER+/HER2+) breast cancer treated with neoadjuvant chemotherapy and HER2-targeted therapy (NAC+H), and was designed to identify novel biomarkers by correlating gene expression, histology and immunohistochemistry with pathologic response. We performed gene expression profiling on 11 pre-treatment tumors samples: 5 who had no or minimal residual disease residual cancer burden (RCB) score of 0 or 1 and 6 who had significant residual disease (RCB score of 2 or 3). ER2/HER2 postive breast tumors biopsied before neoadjuvant chemotherapy were selected to identify potential biomarkers of pathological complete response (pCR)

2015-09-08 | E-GEOD-67982 | biostudies-arrayexpress

The chromatin landscape of high-grade serous ovarian cancer metastasis identifies potential regulatory drivers of chemoresistant tumour cells

Project description:Disease recurrence following chemotherapy is a major clinical challenge in ovarian cancer (OC) but little is known regarding how the tumour epigenome regulates transcriptional programs underpinning chemoresistance. We determined the single cell chromatin accessibility landscape of omental OC metastasis from treatment naïve and neoadjuvant chemotherapy-treated patients and defined the chromatin accessibility profiles of epithelial, fibroblast, myeloid and lymphoid cells. Epithelial tumour cells displayed open chromatin regions enriched with motifs for the oncogenic transcription factors MEIS and PBX. Chemotherapy drove profound tumour heterogeneity and selection for cells with accessible chromatin enriched for TP53, TP63 and resistance-pathway-activating TF motifs. Nuclear receptors RORa, NR2F6 and HNF4NG were identified as candidate transcriptional drivers of stress-associated chemotherapy resistance whilst closure of binding sites for E2F2 and E2F4 indicated low proliferative capacity of resistant tumour subsets. Delineation of the epigenetic landscape of chemoresistant ovarian cancer therefore reveals core transcriptional regulators of chemoresistance and identifies potential novel therapeutic approaches for improving clinical outcome.

2024-10-02 | GSE247982 | 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

Transcriptomic analysis of DOXO-Resistant cells compared to parental DOXO-Sensitive mda-mb-436 cell line

Project description:The major obstacle in successfully treating triple negative breast cancer (TNBC) is resistance to cytotoxic chemotherapy, the mainstay of treatment in this disease. Previous pre-clinical models of chemoresistance in TNBC have suffered from a lack of clinical relevance. Using a single high dose chemotherapy treatment, we developed a novel MDA-MB-436 cell-based model of chemoresistance characterized by a unique and complex morphological phenotype, which consists of polyploid giant cancer cells (PGCCs) giving rise to neuron-like mononuclear daughter cells filled with smaller but functional mitochondria and numerous lipid droplets. This resistant phenotype is associated with metabolic reprogramming with a shift to a greater dependence on fatty acids and oxidative phosphorylation. We validated both the molecular and histologic features of this model in a clinical cohort of primary chemoresistant TNBCs and identified several metabolic vulnerabilities including a dependence on PLIN4, a perilipin coating the observed lipid droplets, expressed both in the TNBC resistant cells and clinical chemoresistant tumors treated with neoadjuvant doxorubicin-based chemotherapy. These findings thus reveal a novel mechanism of chemotherapy resistance that has therapeutic implications in the treatment of drug resistant cancer.

2019-11-30 | GSE138233 | GEO

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Project description:Summary: There is a need for biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are unlikely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. A deep learning model (DLM) consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

2022-05-26 | ST002235 | MetabolomicsWorkbench

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