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      Identification of Immune Subtypes and Candidate mRNA Vaccine Antigens in Small Cell Lung Cancer

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          Abstract

          Background

          Immune checkpoint inhibitors (ICIs) have demonstrated promising outcomes in small cell lung cancer (SCLC), but not all patients benefit from it. Thus, developing precise treatments for SCLC is a particularly urgent need. In our study, we constructed a novel phenotype for SCLC based on immune signatures.

          Methods

          We clustered patients with SCLC hierarchically in 3 publicly available datasets according to the immune signatures. ESTIMATE and CIBERSORT algorithm were used to evaluate the components of the tumor microenvironment. Moreover, we identified potential mRNA vaccine antigens for patients with SCLC, and qRT-PCR were performed to detect the gene expression.

          Results

          We identified 2 SCLC subtypes and named Immunity High (Immunity_H) and Immunity Low (Immunity_L). Meanwhile, we obtained generally consistent results by analyzing different datasets, suggesting that this classification was reliable. Immunity_H contained the higher number of immune cells and a better prognosis compared to Immunity_L. Gene-set enrichment analysis revealed that several immune-related pathways such as cytokine-cytokine receptor interaction, programmed cell death-Ligand 1 expression and programmed cell death-1 checkpoint pathway in cancer were hyperactivated in the Immunity_H. However, most of the pathways enriched in the Immunity_L were not associated with immunity. Furthermore, we identified 5 potential mRNA vaccine antigens of SCLC (NEK2, NOL4, RALYL, SH3GL2, and ZIC2), and they were expressed higher in Immunity_L, it indicated that Immunity_L maybe more suitable for tumor vaccine development.

          Conclusions

          SCLC can be divided into Immunity_H and Immunity_L subtypes. Immunity_H may be more suitable for treatment with ICIs. NEK2, NOL4, RALYL, SH3GL2, and ZIC2 may be act as potential antigens for SCLC.

          Abstract

          Immune checkpoint inhibitors (ICIs) have shown promising outcomes in small cell lung cancer (SCLC), but not all patients benefit from ICIs therapy. Developing precise treatments for SCLC is a particularly urgent need. This article describes a novel phenotype for SCLC based on immune signatures.

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          Most cited references55

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            GSVA: gene set variation analysis for microarray and RNA-Seq data

            Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.
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              Elements of cancer immunity and the cancer–immune set point

              Immunotherapy is proving to be an effective therapeutic approach in a variety of cancers. But despite the clinical success of antibodies against the immune regulators CTLA4 and PD-L1/PD-1, only a subset of people exhibit durable responses, suggesting that a broader view of cancer immunity is
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                Author and article information

                Contributors
                Journal
                Oncologist
                Oncologist
                oncolo
                The Oncologist
                Oxford University Press (US )
                1083-7159
                1549-490X
                November 2023
                03 July 2023
                03 July 2023
                : 28
                : 11
                : e1052-e1064
                Affiliations
                Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Gastric Cancer Center, Division of Medical Oncology, Cancer Center, West China Hospital, Sichuan University , Chengdu, People’s Republic of China
                Author notes
                Corresponding author: Cheng Yi, Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu 610000, People’s Republic of China. Email: yicheng6834@ 123456126.com
                Corresponding author: Hongfeng Gou, Gastric Cancer Center, Division of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, People’s Republic of China. Email: gouhongfeng@ 123456yeah.net

                Yuanfeng Wei, Lingnan Zheng and Xi Yang Contributed equally.

                Author information
                https://orcid.org/0000-0002-5963-5751
                https://orcid.org/0000-0002-8610-1341
                Article
                oyad193
                10.1093/oncolo/oyad193
                10628581
                37399175
                d8323154-ed43-4064-9f6e-489bf0f19e8d
                © The Author(s) 2023. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.

                History
                : 09 November 2022
                : 12 June 2023
                Page count
                Pages: 13
                Funding
                Funded by: Sichuan Science and Technology Program;
                Award ID: 2019YFS0109
                Funded by: Science and Technology Plan Project of Sichuan Province;
                Award ID: 2020YFSY0025
                Categories
                Immuno-Oncology
                AcademicSubjects/MED00010
                Oncolo/15

                Oncology & Radiotherapy
                small cell lung cancer,immunogenomic,mrna vaccine antigens,tumor microenvironment,machine learning

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