{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T19:07:45Z","timestamp":1789153665966,"version":"build-2803163510"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1014747","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000}}],"reference-count":62,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Collective invasion is a key mechanism by which tumors disseminate and metastasize, involving coordinated migration of heterogeneous cell populations. Experimental studies in spheroid-based assays have identified specialized leader and follower cells that work together during this process, but the biophysical rules governing their interaction remain unclear. We present a mechanistic, cell-based computational model using the Cellular Potts framework to investigate how heterotypic adhesion, leader motility, and follower proliferation jointly shape invasion. Leader\u2013follower tumors were simulated across 13 310 parameter sets, and invasion was quantified by invasive and infiltrative areas, finger-like protrusions, solitary defectors, and detached clusters. From these simulations, we identified four distinct invasion phenotypes: non-invasive, bulk collective, single-cell, and multimodal. Multimodal invasion\u2013the coexistence of cohesive strands, solitary cells, and small clusters\u2013emerged as the most prevalent phenotype, particularly under moderate adhesion and high motility. Proliferation increased tumor bulk rather than determining invasion mode, which was governed primarily by adhesion and leader motility. Mapping outcomes across the parameter space revealed sharp transitions between invasion modes, underscoring trade-offs between adhesion and motility in shaping invasion complexity. Our results show that hybrid invasion behaviors, previously considered rare, arise robustly from simple mechanical rules and are favored in a broad region of the parameter space. This framework reconciles binary models of invasion with experimental observations of heterogeneity, providing predictive insights into how modulating adhesion and motility may modify invasive behavior.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1014747","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T18:02:49Z","timestamp":1788890569000},"page":"e1014747","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clusters, fingers, and singles: A mechanical landscape of tumor invasion"],"prefix":"10.1371","volume":"22","author":[{"given":"Sheriff","family":"Akeeb","sequence":"first","affiliation":[{"name":"Georgia State University","place":["Atlanta, Georgia, United States of America"],"department":["Department of Mathematics and Statistics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam 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