{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T06:04:52Z","timestamp":1789538692913,"version":"build-2803163510"},"reference-count":52,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"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>Mechanical stimulation is a key biomechanical characteristic of the tumor microenvironment and is involved in tumor progression, immune microenvironment remodeling, and therapy resistance. This study aimed to develop a mechanical stimulation-related gene (MSRG)-based prognostic signature for survival prediction and to explore its association with the tumor immune microenvironment in lung adenocarcinoma (LUAD).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We used a multifaceted approach to analyze MSRGs in LUAD. The AUCell algorithm was used to calculate mechanical stimulation scores at the single-cell level, while CellChat and NicheNet analyses were applied to reveal cell\u2013cell communication and ligand-target regulatory patterns under high mechanical stimulation. Mechanical stimulation activity in TCGA-LUAD samples was quantified by ssGSEA, and WGCNA was then performed to identify key gene modules associated with this trait. An integrated machine learning framework was then used to develop a prognostic risk model. Immune infiltration, stromal and immune scores, immune checkpoint-related features, and immune evasion potential were further evaluated. Finally, the selected key gene,\n                      <jats:italic>COL22A1<\/jats:italic>\n                      , was validated using multiple approaches.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Analysis of scRNA-seq data demonstrated that mechanical stimulation (MS) scores varied considerably across different cell types. The high-MS subgroup showed enhanced intercellular communication, suggesting active tumor microenvironment remodeling. Furthermore, a prognostic model for LUAD with robust predictive performance was constructed using WGCNA and machine learning algorithms. Notably, the high-risk group showed reduced immune infiltration, higher tumor purity, elevated\n                      <jats:italic>CD276<\/jats:italic>\n                      expression, and increased TIDE scores, suggesting an immune-cold and immune-evasive microenvironment.\n                      <jats:italic>In vitro<\/jats:italic>\n                      experiments further showed that\n                      <jats:italic>COL22A1<\/jats:italic>\n                      enhanced the malignant behavior of LUAD cells, indicating its potential as a therapeutic target.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      We established an MSRG-based prognostic signature that not only predicts survival in LUAD but also reflects tumor immune microenvironment remodeling and potential immune escape. Our preliminary findings also suggest that\n                      <jats:italic>COL22A1<\/jats:italic>\n                      is involved in LUAD progression and may have potential as a therapeutic target.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1918878","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T05:32:14Z","timestamp":1789536734000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A mechanical stimulation-related gene signature predicts prognosis, reflects immune microenvironment remodeling, and identifies COL22A1 as a potential therapeutic target in lung adenocarcinoma"],"prefix":"10.3389","volume":"17","author":[{"given":"Weihao","family":"Zhang","sequence":"first","affiliation":[{"name":"Graduate School, Chengde Medical University","place":["Chengde, Hebei, 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