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Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer
Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes...
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| Published in: | Biochemical genetics 2024-02, Vol.62 (1), p.504-529 |
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| container_end_page | 529 |
| container_issue | 1 |
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| container_title | Biochemical genetics |
| container_volume | 62 |
| creator | Zhai, Jiabao Nie, Chuang Wang, Wanyu Liu, Chang Liu, Tianyu Sun, Lishuang Li, Wei Wang, Wentong Ren, Xiyun Han, Xu Zhou, Haibo Li, Xin Tian, Wenjing |
| description | Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients. |
| doi_str_mv | 10.1007/s10528-023-10436-3 |
| format | article |
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In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.</description><identifier>ISSN: 0006-2928</identifier><identifier>EISSN: 1573-4927</identifier><identifier>DOI: 10.1007/s10528-023-10436-3</identifier><identifier>PMID: 37386336</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Biochemistry ; Biomedical and Life Sciences ; Biomedicine ; Cancer ; Cluster Analysis ; Clustering ; DNA microarrays ; Drug delivery ; drug therapy ; Gastric cancer ; Gene expression ; Genes ; Human Genetics ; Humans ; Immune checkpoint ; Immune system ; Immunomodulation ; Immunomodulators ; Immunosuppressive agents ; Immunotherapy ; Lymphocytes ; Lymphocytes T ; Medical Microbiology ; Medical prognosis ; microarray technology ; nomogram ; Nomograms ; Original Article ; Patients ; Polymerase chain reaction ; Prognosis ; quantitative polymerase chain reaction ; risk ; Risk groups ; RNA-Seq ; sequence analysis ; stomach neoplasms ; Stomach Neoplasms - genetics ; Stomach Neoplasms - therapy ; T-Lymphocytes ; Tumor-infiltrating lymphocytes ; Tumors ; Zoology</subject><ispartof>Biochemical genetics, 2024-02, Vol.62 (1), p.504-529</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-69504d40777c660ce1e55d9e56bbec4a4ba71f4e90adf9beed0cd761ee09e0583</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37386336$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhai, Jiabao</creatorcontrib><creatorcontrib>Nie, Chuang</creatorcontrib><creatorcontrib>Wang, Wanyu</creatorcontrib><creatorcontrib>Liu, Chang</creatorcontrib><creatorcontrib>Liu, Tianyu</creatorcontrib><creatorcontrib>Sun, Lishuang</creatorcontrib><creatorcontrib>Li, Wei</creatorcontrib><creatorcontrib>Wang, Wentong</creatorcontrib><creatorcontrib>Ren, Xiyun</creatorcontrib><creatorcontrib>Han, Xu</creatorcontrib><creatorcontrib>Zhou, Haibo</creatorcontrib><creatorcontrib>Li, Xin</creatorcontrib><creatorcontrib>Tian, Wenjing</creatorcontrib><title>Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer</title><title>Biochemical genetics</title><addtitle>Biochem Genet</addtitle><addtitle>Biochem Genet</addtitle><description>Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.</description><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cancer</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>DNA microarrays</subject><subject>Drug delivery</subject><subject>drug therapy</subject><subject>Gastric cancer</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Immune checkpoint</subject><subject>Immune system</subject><subject>Immunomodulation</subject><subject>Immunomodulators</subject><subject>Immunosuppressive agents</subject><subject>Immunotherapy</subject><subject>Lymphocytes</subject><subject>Lymphocytes T</subject><subject>Medical Microbiology</subject><subject>Medical prognosis</subject><subject>microarray technology</subject><subject>nomogram</subject><subject>Nomograms</subject><subject>Original Article</subject><subject>Patients</subject><subject>Polymerase chain reaction</subject><subject>Prognosis</subject><subject>quantitative polymerase chain reaction</subject><subject>risk</subject><subject>Risk groups</subject><subject>RNA-Seq</subject><subject>sequence analysis</subject><subject>stomach neoplasms</subject><subject>Stomach Neoplasms - 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In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>37386336</pmid><doi>10.1007/s10528-023-10436-3</doi><tpages>26</tpages></addata></record> |
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| subjects | Biochemistry Biomedical and Life Sciences Biomedicine Cancer Cluster Analysis Clustering DNA microarrays Drug delivery drug therapy Gastric cancer Gene expression Genes Human Genetics Humans Immune checkpoint Immune system Immunomodulation Immunomodulators Immunosuppressive agents Immunotherapy Lymphocytes Lymphocytes T Medical Microbiology Medical prognosis microarray technology nomogram Nomograms Original Article Patients Polymerase chain reaction Prognosis quantitative polymerase chain reaction risk Risk groups RNA-Seq sequence analysis stomach neoplasms Stomach Neoplasms - genetics Stomach Neoplasms - therapy T-Lymphocytes Tumor-infiltrating lymphocytes Tumors Zoology |
| title | Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer |
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