Dataset Information

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

ABSTRACT: Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31-33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications.

Significance

Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31-33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483.

SUBMITTER: Anurag M

PROVIDER: S-EPMC9627136 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Anurag Meenakshi M Jaehnig Eric J EJ Krug Karsten K Lei Jonathan T JT Bergstrom Erik J EJ Kim Beom-Jun BJ Vashist Tanmayi D TD Huynh Anh Minh Tran AMT Dou Yongchao Y Gou Xuxu X Huang Chen C Shi Zhiao Z Wen Bo B Korchina Viktoriya V Gibbs Richard A RA Muzny Donna M DM Doddapaneni Harshavardhan H Dobrolecki Lacey E LE Rodriguez Henry H Robles Ana I AI Hiltke Tara T Lewis Michael T MT Nangia Julie R JR Nemati Shafaee Maryam M Li Shunqiang S Hagemann Ian S IS Hoog Jeremy J Lim Bora B Osborne C Kent CK Mani D R DR Gillette Michael A MA Zhang Bing B Echeverria Gloria V GV Miles George G Rimawi Mothaffar F MF Carr Steven A SA Ademuyiwa Foluso O FO Satpathy Shankha S Ellis Matthew J MJ

Cancer discovery 20221101 11

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DN ...[more]

PMID: 36001024

Similar Datasets

Project description:Breast cancer represents the number one cause of cancer-associated mortality globally. The most aggressive molecular subtype is triple negative breast cancer (TNBC), of which limited therapeutic options are available. It is well known that breast cancer prognosis and tumor sensitivity toward immunotherapy are dictated by the tumor microenvironment. Breast cancer gene expression profiles were extracted from the METABRIC dataset and two TNBC clusters displaying unique immune features were identified. Activated immune cells formed a large proportion of cells in the high infiltration cluster, which correlated to a good prognosis. Differentially expressed genes (DEGs) extracted between two heterogeneous subtypes were used to further explore the underlying immune mechanism and to identify prognostic biomarkers. Functional enrichment analysis revealed that the DEGs were predominately related to some processes involved in activation and regulation of innate immune signaling. Using network analysis, we identified two modules in which genes were selected for further prognostic investigation. Validation by independent datasets revealed that CXCL9 and CXCL13 were good prognostic biomarkers for TNBC. We also performed comparisons between the above two genes and immune markers (CYT, APM, TILs, and TIS), as well as cell checkpoint marker expressions, and found a statistically significant correlation between them in both METABRIC and TCGA datasets. The potential of CXCL9 and CXCL13 to predict chemotherapy sensitivity was also evaluated. We found that the CXCL9 and CXCL13 were good predictors for chemotherapy and their expressions were higher in chemotherapy-responsive patients in contrast to those who were not responsive. In brief, immune infiltrate characterization on TNBC revealed heterogeneous subtypes with unique immune features allowed for the identification of informative and reliable characteristics representative of the local immune tumor microenvironment and were potential candidates to guide the management of TNBC patients.

Project description:BACKGROUND:Chemotherapy resistance is a great obstacle in effective treatment for metastatic triple negative breast cancer (TNBC). The ability to predict chemotherapy response would allow chemotherapy administration to be directed toward only those patients who would benefit, thus maximizing treatment efficiency. Differentially expressed plasma proteins may serve as putative biomarkers for predicting chemotherapy outcomes. PATIENTS AND METHODS:In this study, 26 plasma samples (10 samples with partial response (S) and 16 samples with progression disease (R)) from patients with metastatic TNBC were measured by Tandem Mass Tag (TMT)-based proteomics analysis to identify differentially expressed proteins between the S and R group. Potential proteinswere validated with enzyme-linked immunosorbent assay (ELISA) in another 67 plasma samples. RESULTS:A total of 320 plasma proteins were identified, and statistical analysis showed that 108 proteins were significantly dysregulated between R and S groups in the screening stage. Bioinformatics revealed relevant pathways and regulatory networks of the differentially expressed proteins. Three differentially expressed proteins were validated by ELISA with 67 samples from TNBC patients. The R group had significantly higher plasma CAMK2A level than the S group (P=0.0074). The ROC curve analysis showed an AUC of 0.708, with sensitivity 48.4% and specificity 86.1%. In multivariate logistic regression analysis, the level of plasma CAMK2A was also significant for chemotherapeutic response (P=0.009, OR=0.152). Furthermore, the patients with higher CAMK2A level had shorter OS than those with lower CAMK2A level, which amounted to 13.9 and 28.9 months, respectively (P=0.034). In the multivariate Cox regression analysis, CAMK2A level still had significant effect on OS (P=0.031, HR=1.865). CONCLUSION:TMT-based proteomic analysis was able to identify potential biomarkers in plasma that predicted chemotherapy resistance in the metastatic TNBC. The plasma of CAMK2A level may serve as apotential predictive and prognostic biomarker for chemotherapy in metastatic TNBC.

Project description:BackgroundThe persistence of residual tumour after neoadjuvant chemotherapy (NAC) in localised triple-negative breast cancer (TNBC) is known to have a negative prognostic value. However, different degrees of expression of some immunohistochemical markers may correlate with different prognoses.MethodsThe expression of biomarkers with a known prognostic value, i.e., cytokeratin 5/6 (CK5/6), androgen receptor (AR), epidermal growth factor receptor (EGFR) proliferation-related nuclear antigen Ki-67, human epidermal growth factor receptor 2 (HER2), protein 53 (p53), forkhead box protein 3 (FOXP3), and cluster differentiation 8 (CD8), was analysed by immunohistochemistry in 111 samples after NAC in non-metastatic TNBC patients addressed to Georges-François Leclerc Cancer Centre Dijon, France. Clinical and pathological variables were retrospectively collected. Cox regression was used to identify immunohistochemical (IHC) and clinicopathological predictors of event-free survival (EFS) (relapse or death).ResultsMedian age was 50.4 years (range 25.6-88.3), 55.9% (n = 62) were non-menopausal, 70 (63.1%) had stage IIA-IIB disease. NAC was mostly sequential anthracycline-taxanes (72.1%), and surgical intervention was principally conservative (51.3%). We found 65.7% ypT1, 47.2% lymph node involvement (ypN+), and 29.4% lymphovascular invasion (LVI). Most residual tumours were EGFR >110 (H-score) (60.5%, n = 66), AR ≥4% (53.2%, n = 58), p53-positive mutated (52.7%, n = 58), CD8 ≥26 (58.1%, n = 61), FOXP3 ≥7 (51.4%, n = 54), more than half in the stroma, and 52.3% (n = 58) HER2 score 0. After a median follow-up of 80.8 months, 48.6% had relapsed. Median EFS was 62.3 months (95% CI, 37.2-not reached (NR)). Factors independently associated with poor EFS were AR-low (p = 0.002), ypN+ (p < 0.001), and LVI (p = 0.001). Factors associated with lower overall survival (OS) were EGFR-low (p = 0.041), Ki-67 high (p = 0.024), and ypN+ (p < 0.001).ConclusionPost-NAC residual disease in TNBC showed biomarkers specific to a basal-like subtype and markers of lymphocyte infiltration mostly present in the stroma. Prognostic markers for EFS were AR, LVI, and ypN and warrant further validation in a prognostic model.

Dataset Information

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Significance

Publications

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets