{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:08:18Z","timestamp":1788739698145,"version":"build-2803163510"},"reference-count":45,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100018904","name":"Beijing Xisike Clinical Oncology Research Foundation","doi-asserted-by":"publisher","award":["Y\u20102024AZ(BTK)MS\u20100047"],"award-info":[{"award-number":["Y\u20102024AZ(BTK)MS\u20100047"]}],"id":[{"id":"10.13039\/100018904","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018904","name":"Beijing Xisike Clinical Oncology Research Foundation","doi-asserted-by":"publisher","award":["Y\u2010SYBLD2022RWR\u20100013"],"award-info":[{"award-number":["Y\u2010SYBLD2022RWR\u20100013"]}],"id":[{"id":"10.13039\/100018904","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82470186"],"award-info":[{"award-number":["82470186"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82570256"],"award-info":[{"award-number":["82570256"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20232039"],"award-info":[{"award-number":["BK20232039"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>The immune microenvironment contributes substantially to the biological and clinical heterogeneity of multiple myeloma (MM), yet immune\u2010related molecular biomarkers with reproducible prognostic value remain limited. Here, we developed a 12\u2010gene immune\u2010related gene signature (IRGS) using an integrative machine\u2010learning framework and evaluated its prognostic performance across multiple MM cohorts. The IRGS consistently stratified overall survival and remained independently associated with outcome after adjustment for established clinical covariates. Its prognostic discrimination was comparable to that of IFM15 and generally exceeded that of MRCIX6 and a mitophagy\u2010related signature across the evaluated validation datasets. Single\u2010cell RNA sequencing further revealed marked cell type\u2010dependent variation in the activity of the 12\u2010gene module, with comparatively low activity in plasma cells and higher activity in several non\u2010plasma compartments, indicating that the bulk\u2010derived IRGS reflects a multicellular bone marrow transcriptional context rather than an exclusively malignant plasma cell intrinsic program. Somatic mutation analysis identified distinct mutational patterns between IRGS\u2010defined groups, including relative enrichment of DIS3 mutations in the low\u2010IRGS group and MUC16 mutations in the high\u2010IRGS group, together with a modestly higher tumor mutational burden in low\u2010IRGS patients. Transcriptome\u2010based drug\u2010response prediction further suggested differential therapeutic vulnerabilities, with high\u2010 and low\u2010IRGS groups showing distinct predicted sensitivity patterns across apoptosis\u2010, DNA damage\u2010, BET\u2010, checkpoint\u2010, and replication\u2010stress\u2010related agents. Collectively, these findings define the IRGS as a complementary immune\u2010associated molecular biomarker for prognostic stratification in MM and provide a framework linking prognosis with multicellular transcriptional context, somatic mutational characteristics, and candidate therapeutic vulnerabilities.<\/jats:p>","DOI":"10.1111\/cas.70523","type":"journal-article","created":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T23:51:27Z","timestamp":1788738687000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning\u2010Derived Immune Gene Signature Predicts Prognosis and Therapeutic Vulnerabilities in Multiple Myeloma"],"prefix":"10.1111","author":[{"given":"Kai","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Hematology The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital  Nanjing China"},{"name":"Jiangsu Province Engineering Research Center 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Medical University, Jiangsu Province Hospital  Nanjing China"},{"name":"Jiangsu Province Engineering Research Center of Cell and Gene Therapy for Hematologic and Lymphoid Diseases  Nanjing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Orthopedics The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital  Nanjing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0863-5417","authenticated-orcid":false,"given":"Xiaoyan","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Hematology The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital  Nanjing China"},{"name":"Jiangsu Province Engineering Research Center of Cell and Gene Therapy for Hematologic and Lymphoid Diseases  Nanjing 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