{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T05:52:05Z","timestamp":1776664325333,"version":"3.51.2"},"reference-count":101,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Multiple myeloma (MM) typically evolves from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Its progression is accompanied by significant tumor heterogeneity and immune microenvironment remodeling, and MM remains largely incurable despite therapeutic advances. Elucidating cellular heterogeneity and regulatory mechanisms involved in disease progression is critical for understanding MM pathogenesis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Single-cell RNA sequencing (scRNA-seq) provides important support for systematically elucidating the molecular mechanisms and immune regulatory pathways associated with the progression of MM. The scRNA-seq datasets from healthy donors (HD), MGUS, SMM, and MM patients were obtained from the GEO database to analyze plasma cell transcriptional heterogeneity within the bone marrow microenvironment. Plasma cell differentiation trajectories were inferred using pseudotime analysis, and intercellular communication and transcription factor regulatory networks were predicted using CellChat and SCENIC analyses. In addition, functional validation of\n                      <jats:italic>ELK3<\/jats:italic>\n                      was performed\n                      <jats:italic>in vitro<\/jats:italic>\n                      using MM cell lines RPMI 8226 and U266.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this work, we used scRNA-seq to thoroughly evaluate the heterogeneity of MM. We identified a tumor-associated plasma cell subtype, C4\n                      <jats:italic>TTN+<\/jats:italic>\n                      plasma cell subtype, which was predominant in SMM and MM and was significantly enriched throughout the intermediate and final phases of differentiation. We hypothesized that C4\n                      <jats:italic>TTN+<\/jats:italic>\n                      plasma cell subtype may be associated with the progression of MM. We also found that the TGFb signaling pathway played a key role in the interaction between C4\n                      <jats:italic>TTN+<\/jats:italic>\n                      plasma cell subtype and various cell types within the TME. Furthermore,\n                      <jats:italic>in vitro<\/jats:italic>\n                      experiments validated the positive regulatory effects of ELK3 on plasma cell proliferation, migration, and cell viability in MM.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      In summary, this study, based on scRNA-seq analysis, identified a C4\n                      <jats:italic>TTN+<\/jats:italic>\n                      plasma cell subtype potentially associated with\n                      <jats:italic>ELK3<\/jats:italic>\n                      . This subtype may be associated with progression and immune evasion in MM, thereby providing a potential new direction for targeted immunotherapeutic strategies in MM.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1793391","type":"journal-article","created":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T05:23:23Z","timestamp":1776662603000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Single-cell RNA sequencing analysis revealed a potential association between ELK3 expression and the progression of multiple myeloma"],"prefix":"10.3389","volume":"17","author":[{"given":"Chengcheng","family":"Song","sequence":"first","affiliation":[{"name":"School of Acupuncture and Tuina, Shandong University of Traditional Chinese Medicine","place":["Jinan, 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China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cuicui","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Hematology, The First Affiliated Hospital of USTC (West District), Anhui Provincial Cancer Hospital, University of Science and Technology of China","place":["Hefei, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanchen","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Affiliated Hospital of Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3390\/cells11152308","article-title":"Bone disease in multiple myeloma: Biologic and clinical 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