scholarly journals Improving breast cancer sensitivity to paclitaxel by increasing aneuploidy

2019 ◽  
Vol 116 (47) ◽  
pp. 23691-23697 ◽  
Author(s):  
Sylvie Rodrigues-Ferreira ◽  
Anne Nehlig ◽  
Hadia Moindjie ◽  
Clarisse Monchecourt ◽  
Cynthia Seiler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Microtubule Assembly ◽  
Breast Cancer Cell Lines ◽  
Breast Cancer Patients ◽  
Multipolar Spindle ◽  
Mitotic Abnormalities

Predictive biomarkers for tumor response to neoadjuvant chemotherapy are needed in breast cancer. This study investigates the predictive value of 280 genes encoding proteins that regulate microtubule assembly and function. By analyzing 3 independent multicenter randomized cohorts of breast cancer patients, we identified 17 genes that are differentially regulated in tumors achieving pathological complete response (pCR) to neoadjuvant chemotherapy. We focused on the MTUS1 gene, whose major product, ATIP3, is a microtubule-associated protein down-regulated in aggressive breast tumors. We show here that low levels of ATIP3 are associated with an increased pCR rate, pointing to ATIP3 as a predictive biomarker of breast tumor chemosensitivity. Using preclinical models of patient-derived xenografts and 3-dimensional models of breast cancer cell lines, we show that low ATIP3 levels sensitize tumors to the effects of taxanes but not DNA-damaging agents. ATIP3 silencing improves the proapoptotic effects of paclitaxel and induces mitotic abnormalities, including centrosome amplification and multipolar spindle formation, which results in chromosome missegregation leading to aneuploidy. As shown by time-lapse video microscopy, ATIP3 depletion exacerbates cytokinesis failure and mitotic death induced by low doses of paclitaxel. Our results favor a mechanism by which the combination of ATIP3 deficiency and paclitaxel treatment induces excessive aneuploidy, which in turn results in elevated cell death. Together, these studies highlight ATIP3 as an important regulator of mitotic integrity and a useful predictive biomarker for a population of chemoresistant breast cancer patients.

Plasma miR-221 as a Predictive Biomarker for Chemoresistance in Breast Cancer Patients who Previously Received Neoadjuvant Chemotherapy

Onkologie ◽  
2011 ◽  
Vol 34 (12) ◽  
pp. 675-680 ◽  
Author(s):  
Ruihua Zhao ◽  
Jiannan Wu ◽  
Weijuan Jia ◽  
Chang Gong ◽  
Fengyan Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Predictive Biomarker ◽  
Breast Cancer Patients

scholarly journals Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Fengling Li ◽  
Yongquan Yang ◽  
Yani Wei ◽  
Ping He ◽  
Jie Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Pathological Complete Response ◽  
Predictive Biomarkers ◽  
Predictive Performance ◽  
Complete Response ◽  
Breast Cancer Patients ◽  
Histological Images

Abstract Background Pathological complete response (pCR) is considered a surrogate endpoint for favorable survival in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Predictive biomarkers of treatment response are crucial for guiding treatment decisions. With the hypothesis that histological information on tumor biopsy images could predict NAC response in breast cancer, we proposed a novel deep learning (DL)-based biomarker that predicts pCR from images of hematoxylin and eosin (H&E)-stained tissue and evaluated its predictive performance. Methods In total, 540 breast cancer patients receiving standard NAC were enrolled. Based on H&E-stained images, DL methods were employed to automatically identify tumor epithelium and predict pCR by scoring the identified tumor epithelium to produce a histopathological biomarker, the pCR-score. The predictive performance of the pCR-score was assessed and compared with that of conventional biomarkers including stromal tumor-infiltrating lymphocytes (sTILs) and subtype. Results The pCR-score derived from H&E staining achieved an area under the curve (AUC) of 0.847 in predicting pCR directly, and achieved accuracy, F1 score, and AUC of 0.853, 0.503, and 0.822 processed by the logistic regression method, respectively, higher than either sTILs or subtype; a prediction model of pCR constructed by integrating sTILs, subtype and pCR-score yielded a mean AUC of 0.890, outperforming the baseline sTIL-subtype model by 0.051 (0.839, P  =  0.001). Conclusion The DL-based pCR-score from histological images is predictive of pCR better than sTILs and subtype, and holds the great potentials for a more accurate stratification of patients for NAC.

scholarly journals Linc00665 Can Predict the Response to Cisplatin-Paclitaxel Neoadjuvant Chemotherapy for Breast Cancer Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Huijuan Dai ◽  
Xiaonan Sheng ◽  
Rui Sha ◽  
Jing Peng ◽  
Fan Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Univariate Analysis ◽  
Enrichment Analysis ◽  
Predictive Biomarker ◽  
Gene Set Enrichment Analysis ◽  
Her2 Status ◽  
Breast Cancer Patients ◽  
Kegg Analysis

ObjectiveLinc00665 is a novel long non-coding RNA that can promote the progression of breast cancer, but its value in predicting the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer has not been reported. We aim to analyze the correlation between Linc00665 expression and pathological complete response (pCR) in breast cancer patients.Materials and MethodsThe present study examined the predictive role of Linc00665 expression in pCR after NAC using both univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to evaluate the performance of Linc00665 in predicting pCR. The Kyoto Encyclopedia of Gene and Genome (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) were also conducted to determine the biological processes where Linc00665 may participate in.ResultsThe present study study totally enrolled 102 breast cancer patients. The univariate analysis showed that Linc00665 level, human epidermal growth factor receptor 2 (HER2) status and hormone receptor (HR) status were correlated with pCR. The multivariate analysis showed that Linc00665 expression was an independent predictor of pCR (OR = 0.351, 95% CI: 0.125–0.936, P = 0.040), especially in patients with HR-positive/HER2-negative subtype (OR = 0.272, 95% CI: 0.104–0.664, P = 0.005). The KEGG analysis indicated that Linc00665 may be involved in drug metabolism. The GSEA analysis revealed that Linc00665 is correlated to DNA damage repair.ConclusionLinc00665 may be a potential novel predictive biomarker for breast cancer in NAC, especially for HR-positive/HER2-negative patients.

Targeting PKM2 promotes chemosensitivity of breast cancer cells in vitro and in vivo

2021 ◽  
pp. 1-10
Author(s):  
Yu Wang ◽  
Han Zhao ◽  
Ping Zhao ◽  
Xingang Wang
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Poor Prognosis ◽  
Breast Cancer Cells ◽  
Breast Cancer Patients ◽  
Cancer Tissues

BACKGROUND: Pyruvate kinase M2 (PKM2) was overexpressed in many cancers, and high PKM2 expression was related with poor prognosis and chemoresistance. OBJECTIVE: We investigated the expression of PKM2 in breast cancer and analyzed the relation of PKM2 expression with chemotherapy resistance to the neoadjuvant chemotherapy (NAC). We also investigated whether PKM2 could reverse chemoresistance in breast cancer cells in vitro and in vivo. METHODS: Immunohistochemistry (IHC) was performed in 130 surgical resected breast cancer tissues. 78 core needle biopsies were collected from breast cancer patients before neoadjuvant chemotherapy. The relation of PKM2 expression and multi-drug resistance to NAC was compared. The effect of PKM2 silencing or overexpression on Doxorubicin (DOX) sensitivity in the MCF-7 cells in vitro and in vivo was compared. RESULTS: PKM2 was intensively expressed in breast cancer tissues compared to adjacent normal tissues. In addition, high expression of PKM2 was associated with poor prognosis in breast cancer patients. The NAC patients with high PKM2 expression had short survival. PKM2 was an independent prognostic predictor for surgical resected breast cancer and NAC patients. High PKM2 expression was correlated with neoadjuvant treatment resistance. High PKM2 expression significantly distinguished chemoresistant patients from chemosensitive patients. In vitro and in vivo knockdown of PKM2 expression decreases the resistance to DOX in breast cancer cells in vitro and tumors in vivo. CONCLUSION: PKM2 expression was associated with chemoresistance of breast cancers, and could be used to predict the chemosensitivity. Furthermore, targeting PKM2 could reverse chemoresistance, which provides an effective treatment methods for patients with breast cancer.

scholarly journals MAT2A Localization and Its Independently Prognostic Relevance in Breast Cancer Patients

2021 ◽  
Vol 22 (10) ◽  
pp. 5382
Author(s):  
Pei-Yi Chu ◽  
Hsing-Ju Wu ◽  
Shin-Mae Wang ◽  
Po-Ming Chen ◽  
Feng-Yao Tang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Survival Rate ◽  
Protein Expression ◽  
Cancer Patients ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Breast Cancer Cell Lines ◽  
Breast Cancer Patients ◽  
Expression Ratio

(1) Background: methionine cycle is not only essential for cancer cell proliferation but is also critical for metabolic reprogramming, a cancer hallmark. Hepatic and extrahepatic tissues methionine adenosyltransferases (MATs) are products of two genes, MAT1A and MAT2A that catalyze the formation of S-adenosylmethionine (SAM), the principal biological methyl donor. Glycine N-methyltransferase (GNMT) further utilizes SAM for sarcosine formation, thus it regulates the ratio of SAM:S-adenosylhomocysteine (SAH). (2) Methods: by analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that breast cancer patients with higher MAT2A had worse survival rate (p = 0.0057). Protein expression pattern of MAT1AA, MAT2A and GNMT were investigated in the tissue microarray in our own cohort (n = 252) by immunohistochemistry. MAT2A C/N expression ratio and cell invasion activity were further investigated in a panel of breast cancer cell lines. (3) Results: GNMT and MAT1A were detected in the cytoplasm, whereas MAT2A showed both cytoplasmic and nuclear immunoreactivity. Neither GNMT nor MAT1A protein expression was associated with patient survival rate in our cohort. Kaplan–Meier survival curves showed that a higher cytoplasmic/nuclear (C/N) MAT2A protein expression ratio correlated with poor overall survival (5 year survival rate: 93.7% vs. 83.3%, C/N ratio ≥ 1.0 vs. C/N ratio < 1.0, log-rank p = 0.004). Accordingly, a MAT2A C/N expression ratio ≥ 1.0 was determined as an independent risk factor by Cox regression analysis (hazard ratio = 2.771, p = 0.018, n = 252). In vitro studies found that breast cancer cell lines with a higher MAT2A C/N ratio were more invasive. (4) Conclusions: the subcellular localization of MAT2A may affect its functions, and elevated MAT2A C/N ratio in breast cancer cells is associated with increased invasiveness. MAT2A C/N expression ratio determined by IHC staining could serve as a novel independent prognostic marker for breast cancer.

scholarly journals Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xu Yang ◽  
Geng-Xi Cai ◽  
Bo-Wei Han ◽  
Zhi-Wei Guo ◽  
Ying-Song Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cell Receptor ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Plasma Dna ◽  
Transcription Start Sites ◽  
Response To Chemotherapy

AbstractGene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

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