Abstract
Autophagy is an important bioprocess throughout the occurrence and development of cancer. However, the role of autophagy-related lncRNAs in pancreatic cancer (PC) remains obscure. In the study, we identified the autophagy-related lncRNAs (ARlncRNAs) and divided the PC patients from The Cancer Genome Atlas into training and validation set. Firstly, we constructed a signature in the training set by the least absolute shrinkage and selection operator penalized cox regression analysis and the multivariate cox regression analysis. Then, we validated the independent prognostic role of the risk signature in both training and validation set with survival analysis, receiver operating characteristic analysis, and Cox regression. The nomogram was established to demonstrate the predictive power of the signature. Moreover, high risk scores were significantly correlated to worse outcomes and severe clinical characteristics. The Pearson’s analysis between risk scores with immune cells infiltration, tumor mutation burden, and the expression level of chemotherapy target molecules indicated that the signature could predict efficacy of immunotherapy and targeted therapy. Next, we constructed an lncRNA–miRNA–mRNA regulatory network and identified several potential small molecule drugs in the Connectivity Map (CMap). What’s more, quantitative real-time PCR (qRT-PCR) analysis showed that serum LINC01559 could serve as a diagnostic biomarker. In vitro analysis showed inhibition of LINC01559 suppressed PC cell proliferation, migration, and invasion. Additionally, silencing LINC01559 suppressed gemcitabine-induced autophagy and promoted the sensitivity of PC cells to gemcitabine. In conclusion, we identified a novel ARlncRNAs signature with valuable clinical utility for reliable prognostic prediction and personalized treatment of PC patients. And inhibition of LINC01559 might be a novel strategy to overcome chemoresistance.
Highlights
MATERIALS AND METHODSPancreatic cancer (PC) is one of the most lethal malignancies with a rising incidence and an extremely poor prognosis
A total of 13,482 Long non-coding RNA (lncRNA) was extracted from the The Cancer Genome Atlas (TCGA) dataset, 825 of which were identified as ARlncRNAs by the Pearson correlation analysis (|R| > 0.5, p < 0.01)
Accumulated evidence showed that autophagy got involved in tumor development and treatment resistance in PC (Piffoux et al, 2020)
Summary
MATERIALS AND METHODSPancreatic cancer (PC) is one of the most lethal malignancies with a rising incidence and an extremely poor prognosis. There is an urgent need to identify reliable biomarkers for the prognostic prediction and develop effective therapeutic strategies for PC patients. Long non-coding RNA (lncRNA) is a gene transcription composed of more than 200 nucleotides, which has been reported to be aberrantly expressed and abnormally regulated in multiple cancers (Li et al, 2016; Castro-Oropeza et al, 2018). Several lncRNAs have been identified as tumor biomarkers, such as HOTAIR, MALAT1, and H19. Iyer et al (2015) curated a total of 7,256 RNA-seq libraries and identified 7,942 cancer-associated lncRNAs that could potentially be biomarkers for specific cancer types. Better understanding of the role of lncRNAs in cancer is helpful to identify novel diagnostic biomarkers and develop potential therapeutic targets
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