{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T09:01:26Z","timestamp":1790240486742,"version":"4.1.0"},"reference-count":55,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: Automated assessment of mitotic activity may provide a reproducible marker of tumor proliferation, but computational mitosis recognition remains challenging because of cross-domain variability. We developed a transfer-learning framework to quantify mitotic activity in lung squamous cell carcinoma (LUSC) and investigated its clinical and molecular associations. Methods: A ResNet-34 classifier was trained using MIDOG source-domain data and adapted to TCGA-LUSC diagnostic whole-slide images. The target cohort included 478 patients and 512 whole-slide images. Tumor regions and mitotic figures were annotated by two pathologists, and 128 \u00d7 128-pixel patches at 40\u00d7 resolution were analyzed. After identifying patient overlap in the initial patch-level partition, we implemented patient-level stratified five-fold cross-validation to obtain leakage-mitigated performance estimates and out-of-fold predictions. Tumor-area mitosis proportion (TAMP) was defined as the proportion of evaluable tumor-region patches classified as mitosis-positive. Prognostic associations were evaluated using multivariable Cox proportional-hazards regression adjusted for age, sex, and pathological stage. Results: The classifier achieved an AUC of 0.972 (95% CI, 0.965\u20130.980) on the internal MIDOG test set. Direct application to TCGA-LUSC yielded an AUC of 0.81, whereas target-domain fine-tuning produced an initial patch-level AUC of 0.93. Patient tracing identified overlap in the original partitions, with 142 patients (29.7%) contributing patches to multiple subsets, including 67 patients (14.0%) represented in both training and test sets. Leakage-mitigated patient-level cross-validation yielded a mean AUC of 0.88 (95% CI, 0.86\u20130.90) and PR-AUC of 0.24. A patient-disjoint WSI holdout evaluation yielded an AUC of 0.87 (95% CI, 0.84\u20130.90) and PR-AUC of 0.22. High TAMP was associated with poorer overall survival (log-rank p=0.017; HR = 1.73, 95% CI, 1.12\u20132.68) and remained significant after adjustment for age, sex, and pathological stage (adjusted HR = 1.62, 95% CI, 1.03\u20132.54; p=0.036). High-TAMP tumors showed enrichment of proliferation- and growth-related transcriptional programs, whereas immune, genomic, and predicted drug-response associations were modest and hypothesis-generating. Conclusions: TAMP represents an image-derived measure of mitotic activity associated with survival and molecular characteristics in TCGA-LUSC. The findings support further investigation of computational mitotic phenotyping, but external multicenter validation and prospective clinical assessment are required before clinical translation.<\/jats:p>","DOI":"10.3390\/cancers18193098","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T16:10:31Z","timestamp":1790179831000},"page":"3098","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Transfer Learning-Based Quantification of Mitotic Activity and Its Prognostic and Molecular Associations in Lung Squamous Cell Carcinoma"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3487-7721","authenticated-orcid":false,"given":"Gulcin","family":"Yilmaz Gunes","sequence":"first","affiliation":[{"name":"Department of Pulmonology, Band\u0131rma Training and Research Hospital, Band\u0131rma 10200, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"conceptualization","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6439-8826","authenticated-orcid":false,"given":"Mehmet Akif","family":"Cifci","sequence":"additional","affiliation":[{"name":"Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam"},{"name":"School of Engineering and Technology, Duy Tan University, Da Nang 550000, Vietnam"},{"name":"Department of Computer Engineering, Band\u0131rma Onyedi Eyl\u00fcl University, Bal\u0131kesir 10200, T\u00fcrkiye"},{"name":"Engineering and Informatics Department, Klaip\u0117dos Valstybin\u0117 Kolegija\/Higher Education Institution, 92294 Klaipeda, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"ref_1","first-page":"e70090","article-title":"Global cancer statistics 2024: GLOBOCAN estimates of incidence and mortality worldwide for 34 cancers in 186 countries","volume":"76","author":"Sung","year":"2026","journal-title":"CA Cancer J. 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