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 … Show more
“…[ 8 9 10 ] Increasing studies have found that lncRNAs exist abnormal expression and related to prognosis in BC. [ 11 12 13 ] However, there are few studies on the prognostic value of uniting biomarkers and other clinical indicators.…”
“…[ 8 9 10 ] Increasing studies have found that lncRNAs exist abnormal expression and related to prognosis in BC. [ 11 12 13 ] However, there are few studies on the prognostic value of uniting biomarkers and other clinical indicators.…”
“…Moreover, lncRNAs not only participate in the process of chemoresistance, but can also be used for predicting the response to neoadjuvant chemotherapy in TNBC. Zheng et al 110 systematically compared gene expression between TNBC patients with pathological complete response and those without a complete response to neoadjuvant chemotherapy and ultimately developed a gene signature of 2 coding genes and 3 lncRNAs to predict the response to neoadjuvant chemotherapy of TNBC patients.…”
Triple‐negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with negativity for oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2). Non‐coding RNAs (ncRNAs) make up most of the transcriptome and are widely present in eukaryotic cells. In recent years, emerging evidence suggests that ncRNAs, mainly microRNAs (miRNAs), long ncRNAs (lncRNAs) and circular RNAs (circRNAs), play prominent roles in the tumorigenesis and development of TNBC, but the functions of most ncRNAs have not been fully described. In this review, we systematically elucidate the general characteristics and biogenesis of miRNAs, lncRNAs and circRNAs, discuss the emerging functions of these ncRNAs in TNBC and present future perspectives in clinical practice.
“…13 Recently, plenty of gene signatures have become biomarkers for guiding treatment in various cancers. [14][15][16] Multigene prognostic sets can predict the tumor prognosis more accurately than a single gene, which enable more effective treatment of cancer patients. 17,18 Identifying the hallmark gene signature is important for clinical application and precision medicine of cancers.…”
Background: Glioma is one of the most prevalent tumors in the central nervous system of adults and shows a poor prognosis. This study aimed to develop a DNA damage repair (DDR)-related gene signature to evaluate the prognosis of glioma patients. Methods: Differentially expressed genes (DEGs) were extracted based on 276 DDR genes. Then, a gene signature was developed for the survival prediction in glioma patients by means of univariate, multivariate Cox, and least absolute shrinkage and selector operation (Lasso) analyses. After analyzing the clinical parameters, a nomogram was constructed and assessed. A total of 693 gliomas from the Chinese Glioma Genome Atlas (CGGA) were used for external validation. In addition, we used glioma tumor tissues for qPCR experiment to verify. Results: A 12-DDR-related gene signature was identified from the 75 DEGs to stratify the survival risk of glioma patients. The overall survival of high-risk group was significantly shorter than that of low-risk group (P < 0.001). Besides, according to the risk score assessment, patients in high-or low-risk group also had significant correlations with clinicopathological parameters, including age (P < 0.01), grade (P < 0.001), IDH status (P < 0.001) and 1p19q codeletion status (P < 0.001). The nomogram provided favorable C-index and calibration plots. The C-index of training set and verification set was 0.761 and 0.746, respectively, and the calibration curve also showed that both training set and verification set were close to the standard curve. The qPCR results showed that there were significant differences in the expression of some typical DDRrelated genes in tumor tissues and paracancer tissues (P (WEE1) =0.0002, P (RECQL) =0.0117, P (RPA1) =0.021, P (RRM1) =0.0035, P (PARP4) =0.0006, P (ELOA) =0.0023).
Conclusion:Our study developed a novel 12 DDR-related gene signature as a practical prognostic predictor for glioma patients. A nomogram combining the signature and clinical parameters was established as an individual clinical prediction tool.
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