Jamshid Motalebzadeh1, Elaheh Eskandari2. 1. Medical Informatics and Genetics Center (MedInfoGene), Tabnak St. Velenjak Region, P.O. Box: 1987124500, Tehran, Iran. motalebzade@gmail.com. 2. Medical Informatics and Genetics Center (MedInfoGene), Tabnak St. Velenjak Region, P.O. Box: 1987124500, Tehran, Iran.
Abstract
BACKGROUND: Deciphering new molecules related to the breast cancer subtypes is crucial for prognosis and determining a better strategy for targeted therapy. In this study, we aimed to model ceRNAs networks in luminal A and luminal B subtypes of breast cancer and then delve deeper into the role of two candidate lncRNAs in breast tumors. METHODS: We constructed two networks as a regulatory model based on our previously identified transcription factors (TFs) and miRNAs with associated lncRNAs. Then, we highlighted the role of some lncRNAs in luminal subtypes of breast cancer using available online databases. Furthermore, we empirically quantified the expression levels of two candidate lncRNAs (DRAIC and TP53TG1) in breast tumors and normal tissues. RESULTS: Here, we proposed a regulatory model for TFs-miRNAs-lncRNAs in luminal subtypes of breast cancer. We found 18 and 17 differentially expressed lncRNAs in luminal A and luminal B subtypes, respectively. Of these lncRNAs, 16 were associated with breast cancer patients' RFS and/or OS rates. Well-known lncRNAs like HOTAIR and MALAT1 were identified as central factors associated with patients' survival rates in both networks. Based on the results acquired from our comprehensive in-silico data analysis, we carried out clinical experiments on two less-known lncRNAs, DRAIC and TP53TG1, and found a significant association between them with luminal subtypes of breast cancer. Interestingly, we discovered a significant association between DRAIC and TP53TG1 lncRNAs with ER- and PR-positive samples and lymph-node invasion in breast cancer patients. CONCLUSION: According to the results, DRAIC and TP53TG1 lncRNAs are overexpressed in breast tumors and may play an oncogenic role with a moderate value of prognosis for luminal subtypes of breast cancer.
BACKGROUND: Deciphering new molecules related to the breast cancer subtypes is crucial for prognosis and determining a better strategy for targeted therapy. In this study, we aimed to model ceRNAs networks in luminal A and luminal B subtypes of breast cancer and then delve deeper into the role of two candidate lncRNAs in breast tumors. METHODS: We constructed two networks as a regulatory model based on our previously identified transcription factors (TFs) and miRNAs with associated lncRNAs. Then, we highlighted the role of some lncRNAs in luminal subtypes of breast cancer using available online databases. Furthermore, we empirically quantified the expression levels of two candidate lncRNAs (DRAIC and TP53TG1) in breast tumors and normal tissues. RESULTS: Here, we proposed a regulatory model for TFs-miRNAs-lncRNAs in luminal subtypes of breast cancer. We found 18 and 17 differentially expressed lncRNAs in luminal A and luminal B subtypes, respectively. Of these lncRNAs, 16 were associated with breast cancer patients' RFS and/or OS rates. Well-known lncRNAs like HOTAIR and MALAT1 were identified as central factors associated with patients' survival rates in both networks. Based on the results acquired from our comprehensive in-silico data analysis, we carried out clinical experiments on two less-known lncRNAs, DRAIC and TP53TG1, and found a significant association between them with luminal subtypes of breast cancer. Interestingly, we discovered a significant association between DRAIC and TP53TG1 lncRNAs with ER- and PR-positive samples and lymph-node invasion in breast cancer patients. CONCLUSION: According to the results, DRAIC and TP53TG1 lncRNAs are overexpressed in breast tumors and may play an oncogenic role with a moderate value of prognosis for luminal subtypes of breast cancer.
Authors: Bhupinder Pal; Yunshun Chen; François Vaillant; Bianca D Capaldo; Rachel Joyce; Xiaoyu Song; Vanessa L Bryant; Jocelyn S Penington; Leon Di Stefano; Nina Tubau Ribera; Stephen Wilcox; Gregory B Mann; Anthony T Papenfuss; Geoffrey J Lindeman; Gordon K Smyth; Jane E Visvader Journal: EMBO J Date: 2021-05-05 Impact factor: 11.598