Title:Prediction Model for Therapeutic Responses in Ovarian Cancer
Patients using Paclitaxel-resistant Immune-related lncRNAs
Volume: 31
Issue: 26
Author(s): Xin Li, Huiqiang Liu, Fanchen Wang, Jia Yuan, Wencai Guan and Guoxiong Xu*
Affiliation:
- Research Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Center
for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Shanghai, 201508, China
Keywords:
Biomarker, chemoresistance, DEir-lncRNAs, immunotherapy, non-coding RNA, predicting tool, scRNA- seq.
Abstract:
Background: Ovarian cancer (OC) is the deadliest malignant tumor in women with a
poor prognosis due to drug resistance and lack of prediction tools for therapeutic responses to anti-
cancer drugs.
Objective: The objective of this study was to launch a prediction model for therapeutic responses
in OC patients.
Methods: The RNA-seq technique was used to identify differentially expressed paclitaxel (PTX)-
resistant lncRNAs (DE-lncRNAs). The Cancer Genome Atlas (TCGA)-OV and ImmPort
database were used to obtain immune-related lncRNAs (ir-lncRNAs). Univariate, multivariate,
and LASSO Cox regression analyses were performed to construct the prediction model. Kaplan-
meier plotter, Principal Component Analysis (PCA), nomogram, immune function analysis,
and therapeutic response were applied with Genomics of Drug Sensitivity in Cancer (GDSC),
CIBERSORT, and TCGA databases. The biological functions were evaluated in the CCLE
database and OC cells.
Results: The RNA-seq defined 186 DE-lncRNAs between PTX-resistant A2780-PTX and PTXsensitive
A2780 cells. Through the analysis of the TCGA-OV database, 225 ir-lncRNAs were
identified. Analyzing 186 DE-lncRNAs and 225 ir-lncRNAs using univariate, multivariate, and
LASSO Cox regression analyses, 9 PTX-resistant immune-related lncRNAs (DEir-lncRNAs) acted
as biomarkers were discovered as potential biomarkers in the prediction model. Single-cell
RNA sequencing (scRNA-seq) data of OC confirmed the relevance of DEir-lncRNAs in immune
responsiveness. Patients with a low prediction score had a promising prognosis, whereas patients
with a high prediction score were more prone to evade immunotherapy and chemotherapy and had
poor prognosis.
Conclusion: The novel prediction model with 9 DEir-lncRNAs is a valuable tool for predicting
immunotherapeutic and chemotherapeutic responses and prognosis of patients with OC.
