scholarly journals A Minimal lncRNA-mRNA Signature Predicts Sensitivity to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

2018 ◽  
Vol 48 (6) ◽  
pp. 2539-2548 ◽  
Author(s):  
Qian Wang ◽  
Chunmei Li ◽  
Peipei Tang ◽  
Runyuan Ji ◽  
Song Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Characteristic Curve ◽  
Gene Expression Signature ◽  
Receiver Operator Characteristic Curve ◽  
Response Score

Background/Aims: Triple-negative breast cancer (TNBC) is a highly aggressive malignancy that responds in a diverse manner to neoadjuvant chemotherapy (NAC). This study was aimed to uncover an RNA signature in TNBC patients which predicts pathological complete responses (pCR) to NAC by analyzing long noncoding RNA (lncRNA) and coding gene expression. Methods: Microarray datasets from 26 TNBC patients receiving NAC including ten patients showing pCR were obtained from the Gene Expression Omnibus database. Results: A total of 172 coding genes and 84 lncRNAs were differentially expressed between patients achieving pCR and those who did not. Filtering based on the predictive efficacy of response to NAC using receiver operator characteristic curve (ROC) and area under the curve (AUC) shortlisted 23 lncRNAs and 15 coding genes from consideration. Finally, a response score consisting of 1 lncRNA and 2 coding genes was developed: response score = 2.595*BPESC1 – 1.09*WDR72 –1.428*GADD45A – 0.731. The response score had good predictive performance (AUC=0.931, p< 0.01) and at the cut-off of 0.545, the response score had sensitivity and specificity of 0.8 and 0.9, respectively. Conclusion: We propose a simple gene expression signature of only three RNA species could be employed clinically to predict pCR in TNBC patients receiving NAC.

scholarly journals A gene signature predicts response to neoadjuvant chemotherapy in triple-negative breast cancer patients

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Tianzhi Zheng ◽  
Zhiyuan Pang ◽  
Zhao Zhao
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Characteristic Curve ◽  
Complete Response ◽  
Gene Signature ◽  
Differentially Expressed ◽  
Breast Cancer Patients

Abstract Triple-negative breast cancer (TNBC) accounts for approximately 15% of all breast cancer cases. TNBC is highly aggressive and associated with poor prognosis. The present study aimed to compare gene expression between TNBC patients with pathological complete response (pCR) and those with not complete response (nCR) to neoadjuvant chemotherapy. Microarray data of 16 TNBC patients received neoadjuvant chemotherapy were identified from the Gene Expression Omnibus database and 10 patients of them had pCR. We found that 250 coding genes and 155 long noncoding RNAs (lncRNAs) were statistically differentially expressed between patients with pCR and nCR. Receiver operator characteristic curve and area under the curve (AUC) were calculated to assess predictive value of differentially expressed genes. A gene signature of three coding genes and two lncRNA was developed: 2.318*TCF3 + 7.349*CREB1 + 0.891*CEP44 + 0.091*NR_023392.1 + 1.424*NR_048561.1 − 106.682. The gene signature was further validated and had an AUC = 0.829. In summary, we profiled gene expression in pCR patients and developed a gene signature, which was effective to predict pCR among TNBC patients received neoadjuvant chemotherapy.

scholarly journals A New Gene Expression Signature for Triple-Negative Breast Cancer using Frozen Fresh Tissue before Neoadjuvant chemotherapy

2017 ◽  
Vol 23 (1) ◽  
pp. 101-111 ◽  
Author(s):  
Sandra K. Santuario-Facio ◽  
Servando Cardona-Huerta ◽  
Yadira X. Perez-Paramo ◽  
Victor Trevino ◽  
Francisco Hernandez-Cabrera ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Gene Expression Signature ◽  
Fresh Tissue ◽  
Expression Signature ◽  
New Gene

A novel three-long noncoding RNA risk score system for the prognostic prediction of triple-negative breast cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 43-55
Author(s):  
Chao Yuan ◽  
Hongjun Yuan ◽  
Li Chen ◽  
Miaomiao Sheng ◽  
Wenru Tang
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Triple Negative Breast Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Gene Expression Omnibus ◽  
Prognostic Prediction

Background: Triple-negative breast cancer (TNBC) is characterized by fast tumor increase, rapid recurrence and natural metastasis. We aimed to identify a genetic signature for predicting the prognosis of TNBC. Materials & methods: We conducted a weighted correlation network analysis of datasets from the Gene Expression Omnibus. Multivariate Cox regression was used to construct a risk score model. Results: The multi-factor risk scoring model was meaningfully associated with the prognosis of patients with TBNC. The predictive power of the model was demonstrated by the time-dependent receiver operating characteristic curve and Kaplan–Meier curve, and verified using a validation set. Conclusion: We established a long noncoding RNA-based model for the prognostic prediction of TNBC.

scholarly journals Interferon-beta represses cancer stem cell properties in triple-negative breast cancer

2017 ◽  
Vol 114 (52) ◽  
pp. 13792-13797 ◽  
Author(s):  
Mary R. Doherty ◽  
HyeonJoo Cheon ◽  
Damian J. Junk ◽  
Shaveta Vinayak ◽  
Vinay Varadan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Triple Negative ◽  
Mammary Epithelial Cells ◽  
Gene Expression Signature ◽  
Tumor Infiltrating Lymphocytes ◽  
Gene Signature ◽  
Mesenchymal Transition

Triple-negative breast cancer (TNBC), the deadliest form of this disease, lacks a targeted therapy. TNBC tumors that fail to respond to chemotherapy are characterized by a repressed IFN/signal transducer and activator of transcription (IFN/STAT) gene signature and are often enriched for cancer stem cells (CSCs). We have found that human mammary epithelial cells that undergo an epithelial-to-mesenchymal transition (EMT) following transformation acquire CSC properties. These mesenchymal/CSCs have a significantly repressed IFN/STAT gene expression signature and an enhanced ability to migrate and form tumor spheres. Treatment with IFN-beta (IFN-β) led to a less aggressive epithelial/non–CSC-like state, with repressed expression of mesenchymal proteins (VIMENTIN, SLUG), reduced migration and tumor sphere formation, and reexpression of CD24 (a surface marker for non-CSCs), concomitant with an epithelium-like morphology. The CSC-like properties were correlated with high levels of unphosphorylated IFN-stimulated gene factor 3 (U-ISGF3), which was previously linked to resistance to DNA damage. Inhibiting the expression of IRF9 (the DNA-binding component of U-ISGF3) reduced the migration of mesenchymal/CSCs. Here we report a positive translational role for IFN-β, as gene expression profiling of patient-derived TNBC tumors demonstrates that an IFN-β metagene signature correlates with improved patient survival, an immune response linked with tumor-infiltrating lymphocytes (TILs), and a repressed CSC metagene signature. Taken together, our findings indicate that repressed IFN signaling in TNBCs with CSC-like properties is due to high levels of U-ISGF3 and that treatment with IFN-β reduces CSC properties, suggesting a therapeutic strategy to treat drug-resistant, highly aggressive TNBC tumors.

scholarly journals Single-cell long noncoding RNA (lncRNA) transcriptome implicates MALAT1 in triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hibah Shaath ◽  
Radhakrishnan Vishnubalaji ◽  
Ramesh Elango ◽  
Shahryar Khattak ◽  
Nehad M. Alajez
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Triple Negative ◽  
Gene Selection ◽  
Single Cells ◽  
Reciprocal Relationship ◽  
Differential Analysis

AbstractCumulative evidence suggests added benefit for neoadjuvant chemotherapy (NAC) in a subset of triple-negative breast cancer (TNBC) patients. Herein we identified the long noncoding RNA (lncRNA) transcriptional landscape associated with TNBC resistance to NAC, employing 1758 single cells from three extinction and three persistence TNBC patients. Using Iterative Clustering and Guide-gene Selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis, we observed single cells derived from each patient to largely cluster together. Comparing the lncRNA transcriptome from single cells through the course of NAC treatment revealed minimal overlap based on lncRNA transcriptome, suggesting substantial effects of NAC on lncRNA transcription. The differential analysis revealed upregulation of 202 and downregulation of 19 lncRNAs in the persistence group, including upregulation of five different transcripts encoding for the MALAT1 lncRNA. CRISPR/Cas9-mediated MALAT1 promoter deletion in BT-549 TNBC model enhanced sensitivity to paclitaxel and doxorubicin, suggesting a role for MALAT1 in conferring resistance. Mechanistically, whole transcriptome analysis of MALAT1-KO cells revealed multiple affected mechanistic networks as well as oxidative phosphorylation canonical and angiogenesis functional category. Interestingly, lncRNA profiling of MALAT1-depleted TNBC also revealed a number of altered lncRNAs in response to MALAT1 deletion, suggesting a reciprocal relationship between MALAT1 and a number of lncRNAs, including NEAT1, USP3-AS1, and LINC-PINT, in TNBC. Elevated expression of MALAT1, USP3-AS1, and LINC-PINT correlated with worse clinical outcomes in BC patients. Our data revealed the lncRNA transactional portrait and highlighted a complex regulatory network orchestrated by MALAT1 in the context of TNBC resistance to NAC therapy.

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