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      Prognostic Risk Model and Tumor Immune Environment Modulation of m5C-Related LncRNAs in Pancreatic Ductal Adenocarcinoma

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          Abstract

          RNA methylation modification is a key process in epigenetics that regulates posttranscriptional gene expression. With advances in next-generation sequencing technology, 5-methylcytosine (m5C) modification has also been found in multiple RNAs. Long non-coding RNAs (lncRNAs) were proved to have a key role in cancer progression and closely related to the tumor immune microenvironment. Thus, based on the PDAC patients’ clinical information and genetic transcriptome data from the TCGA database, we performed a detailed bioinformatic analysis to establish a m5C-related lncRNA prognostic risk model for PDAC patients and discovered the relationship between the risk model and PDAC immune microenvironment. Pearson correlation coefficient analysis was applied to conduct a m5C regulatory gene and m5C-related lncRNA co-expression network. Expression of m5C-related lncRNAs screened by univariate regression analysis with prognostic value showed a significant difference between pancreatic cancer and normal tissues. The least absolute shrinkage and selection operator (LASSO) Cox regression method was applied to determine an 8-m5C-related lncRNA prognostic risk model. We used principal component analysis to indicate that the risk model could distinguish all the samples clearly. The clinical nomogram also accurately predicted 1-, 1.5-, 2-, and 3-year survival time among PDAC patients. Additionally, this risk model was validated in the entire group and sub-test groups using KM analysis and ROC analysis. Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the survival of PDAC patients. Furthermore, the association between the risk model and tumor immune microenvironment was evaluated via the ESTIMATE R package and CIBERSORT method. Consequently, the results indicated that immune cells were associated with m5C-related lncRNA risk model scores and had different distribution in the high- and low-risk groups. Based on all these analyses, the m5C-related lncRNA risk model could be a reliable prognostic tool and therapeutic target for PDAC patients.

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          Most cited references43

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          Cancer Statistics, 2021

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.
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            Functional Classification and Experimental Dissection of Long Noncoding RNAs

            Over the last decade, it has been increasingly demonstrated that the genomes of many species are pervasively transcribed, resulting in the production of numerous long noncoding RNAs (lncRNAs). At the same time, it is now appreciated that many types of DNA regulatory elements, such as enhancers and promoters, regularly initiate bidirectional transcription. Thus, discerning functional noncoding transcripts from a vast transcriptome is a paramount priority, and challenge, for the lncRNA field. In this review, we aim to provide a conceptual and experimental framework for classifying and elucidating lncRNA function. We categorize lncRNA loci into those that regulate gene expression in cis versus those that perform functions in trans , and propose an experimental approach to dissect lncRNA activity based on these classifications. These strategies to further understand lncRNAs promise to reveal new and unanticipated biology, with great potential to advance our understanding of normal physiology and disease.
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              The Tumor Microenvironment Innately Modulates Cancer Progression

              Cancer development and progression occurs in concert with alterations in the surrounding stroma. Cancer cells can functionally sculpt their microenvironment through the secretion of various cytokines, chemokines, and other factors. This results in a reprogramming of the surrounding cells, enabling them to play a determinative role in tumor survival and progression. Immune cells are important constituents of the tumor stroma and critically take part in this process. Growing evidence suggests that the innate immune cells (macrophages, neutrophils, dendritic cells, innate lymphoid cells, myeloid-derived suppressor cells, and NK cells) as well as adaptive immune cells (T cells and B cells) contribute to tumor progression when present in the tumor microenvironment (TME). Crosstalk between cancer cells and the proximal immune cells ultimately results in an environment that fosters tumor growth and metastasis. Understanding the nature of this dialog will allow for improved therapeutics that simultaneously target multiple components of the TME, increasing the likelihood of favorable patient outcomes.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                08 December 2021
                2021
                : 12
                : 800268
                Affiliations
                [1] 1 Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University , Nanjing, China
                [2] 2 Pancreas Institute, Nanjing Medical University , Nanjing, China
                [3] 3 Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University , Nanjing, China
                Author notes

                Edited by: Yunfei Xu, Shandong University, China

                Reviewed by: Ning Pu, Fudan University, China; Yongsong Chen, Shantou University, China

                *Correspondence: Kuirong Jiang, jiangkuirong@ 123456njmu.edu.cn ; Bin Xiao, xiaobin@ 123456jsph.org.cn

                †These authors have contributed equally to this work

                This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2021.800268
                8692582
                34956238
                30dafbae-f2ac-43d3-b0f0-0373f21a1ce0
                Copyright © 2021 Yuan, Liu, Zhao, Wu, Chen, Chen, Shen, Yang, Fan, Xiao and Jiang

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 October 2021
                : 19 November 2021
                Page count
                Figures: 7, Tables: 1, Equations: 0, References: 43, Pages: 12, Words: 6043
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 82072706, 81871980
                Categories
                Immunology
                Original Research

                Immunology
                lncrna,m5c methylation,tumor immune microenvironment,pdac,prognostic model
                Immunology
                lncrna, m5c methylation, tumor immune microenvironment, pdac, prognostic model

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