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      Single-cell and Bulk RNA-Seq reveal angiogenic heterogeneity and microenvironmental features to evaluate prognosis and therapeutic response in lung adenocarcinoma

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          Abstract

          Background

          Angiogenesis stands as a pivotal hallmark in lung adenocarcinoma (LUAD), intricately shaping the tumor microenvironment (TME) and influencing LUAD progression. It emerges as a promising therapeutic target for LUAD, affecting patients’ prognosis. However, its role in TME, LUAD prognosis, and its clinical applicability remain shrouded in mystery.

          Methods

          We employed integrated single-cell and bulk transcriptome sequencing to unravel the heterogeneity of angiogenesis within LUAD cells. Through “consensus clustering”, we delineated distinct angiogenic clusters and deciphered their TME features. “Monocle2” was used to unravel divergent trajectories within malignant cell subpopulations of LUAD. Additionally, regulon submodules and specific cellular communication patterns of cells in different angiogenic states were analyzed by “pyscenic” and “Cellchat” algorithms. The “univariate Cox” and “LASSO” algorithms were applied to build angiogenic prognostic models. Immunohistochemistry (IHC) on clinical samples validated the role of model factors in LUAD angiogenesis. We utilized CTRP 2.0 and PRISM databases for pinpointing sensitive drugs against lung adenocarcinoma.

          Results

          Two clusters for the activation of angiogenesis were identified, with Cluster 1 showing a poor prognosis and a pro-cancerous TME. Three differentiated states of malignant epithelial LUAD cells were identified, which had different degrees of angiogenic activation, were regulated by three different regulon submodules, and had completely different crosstalk from other cells in TME. The experiments validate that SLC2A1 promotes angiogenesis in LUAD. ARS (Angiogenesis related score) had a high prognostic value; low ARSs showed immunotherapy benefits, whereas high ARSs were sensitive to 15 chemotherapeutic agents.

          Conclusion

          The assessment of angiogenic clusters helps to determine the prognostic and TME characteristics of LUAD. Angiogenic prognostic models can be used to assess the prognosis, immunotherapeutic response, and chemotherapeutic drug sensitivity of LUAD.

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          Most cited references50

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              Understanding the tumor immune microenvironment (TIME) for effective therapy

              The clinical successes in immunotherapy have been both astounding and at the same time unsatisfactory. Countless patients with varied tumor types have seen pronounced clinical response with immunotherapeutic intervention; however, many more patients have experienced minimal or no clinical benefit when provided the same treatment. As technology has advanced, so has the understanding of the complexity and diversity of the immune context of the tumor microenvironment and its influence on response to therapy. It has been possible to identify different subclasses of immune environment that have an influence on tumor initiation and response and therapy; by parsing the unique classes and subclasses of tumor immune microenvironment (TIME) that exist within a patient’s tumor, the ability to predict and guide immunotherapeutic responsiveness will improve, and new therapeutic targets will be revealed.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/1799876Role: Role: Role: Role: Role: Role: Role: Role:
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                URI : https://loop.frontiersin.org/people/1535114Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2402171Role: Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2292131Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/1799822Role: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2612116Role: Role: Role: Role:
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                08 February 2024
                2024
                : 15
                : 1352893
                Affiliations
                [1] 1 Dalian Medical University , Dalian, China
                [2] 2 Department of Pathology, Affiliated Hospital of Nantong University , Nantong, China
                [3] 3 Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University , Suzhou, China
                [4] 4 Medical School of Nantong University , Nantong, China
                [5] 5 Suzhou Gene Pharma Co., Ltd , Suzhou, China
                Author notes

                Edited by: Hailin Tang, Sun Yat-sen University Cancer Center (SYSUCC), China

                Reviewed by: Jing-Sheng Cai, Peking University People’s Hospital, China

                Zhigang Zhou, First Affiliated Hospital of Jinan University, China

                Zijian Zhou, Fudan University, China

                *Correspondence: Weibiao Zeng, 18270881242@ 123456163.com ; Hao Ding, 353249221@ 123456qq.com ; Shu Pan, panshu@ 123456suda.edu.cn

                †These authors have contributed equally to this work

                Article
                10.3389/fimmu.2024.1352893
                10882092
                38390340
                e06341f6-1190-45a9-98bb-cbac30140510
                Copyright © 2024 Tang, Chen, Yang, Li, Wang, Mo, Zeng, Ding and Pan

                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
                : 09 December 2023
                : 23 January 2024
                Page count
                Figures: 9, Tables: 0, Equations: 0, References: 50, Pages: 18, Words: 7931
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Natural Science Foundation for the Youth of Jiangsu Province (No. BK20200196) and the Research Project of Gusu Health Talents in Suzhou (No. GSWS2021013).
                Categories
                Immunology
                Original Research
                Custom metadata
                Cancer Immunity and Immunotherapy

                Immunology
                angiogenesis,tumor microenvironment,immune infiltration,immune therapy,prognosis,lung adenocarcinoma

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