Inferences of individual drug responses across diverse cancer types using a novel competing endogenous RNA network

Abstract

Differences in individual drug responses are an obstacle to progression in cancer treatment, and predicting responses would help to plan treatment. The accumulation of cancer molecular profiling and drug response data provides opportunities and challenges to identify novel molecular signatures and mechanisms of tumor responsiveness to drugs. This study evaluated drug responses with a competing endogenous RNA (ceRNA) system that depended on competition between diverse RNA species. We identified drug response‐related ceRNA (DRCEs) by combining the sequence and expression data of long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA), and the survival data of cancer patients treated with drugs. We constructed a patient–drug two‐layer integrated network and used a linear weighting method to predict individual drug responses. DRCEs were found to be significantly enriched in known cancer and drug‐associated data resources, involved in biological processes known to mediate drug responses, and correlated to drug activity in cancer cell lines. The dysregulation of DRCE expression influenced drug response‐associated functions and pathways, suggesting DRCEs as potential therapeutic targets affecting drug responses. A further case study in breast invasive carcinoma (BRCA) found that DRCE expression was consistent with the drug response pattern and the aberrant expression of the two NEAT1‐related DRCEs may lead to poor response to tamoxifen therapy for patients with TP53 mutations. In summary, this study provides a framework for ceRNA‐based evaluation of clinical drug responses across multiple cancer types. Understanding the underlying molecular mechanisms of drug responses will allow improved response to chemotherapy and outcomes of cancer treatment.

Noncoding RNA:RNA Regulatory Networks in Cancer

“…Interestingly, a recent study also exploited ceRNA networks as a tool to predict drug responses across different cancers [ 179 ]. Analysis of sequence, expression and survival data of cancer patients treated with drugs were used to identify drug-response related ceRNAs (DRCEs).…”

“…The functional diversity of various classes of ncRNAs and the plasticity of their interactions add to the multilayered regulatory circuitry that could be derailed in malignancies. Given that ceRNA interactions generated by bioinformatics analyses have shown promising diagnostic and prognostic potential, as well as drug response predictions, this approach could be further harnessed to predict therapy resistance of specific cancers with different mutational load [ 174 , 175 , 176 , 177 , 178 , 179 ]. Comprehensive studies integrating computational analysis and new experimental platforms could be key to providing new insights into these complex networks.…”

Identification of a competing endogenous RNA network associated with prognosis of pancreatic adenocarcinoma

“…During the occurrence and development of diseases, multiple interacting RNAs could be changed. So figuring out the mechanism of RNA interactions would help us to understand pathogenesis of diseases [10]. In recent years, many papers have studied and reported the interaction between non-coding RNA and mRNA based on the ceRNA hypothesis.…”

Human Plasma-Derived 3D Cultures Model Breast Cancer Treatment Responses and Predict Clinically Effective Drug Treatment Concentrations

“…When a patient is initially diagnosed, physicians have an arsenal of treatment regimens to choose from. However, a standard clinical treatment is used in BCa patients despite the fact that the BCa population is highly heterogeneous [6][7][8]. The main molecular subtypes of breast cancer are luminal A, luminal B, HER2 positive, and basal-like (triple negative).…”