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Over the past decade, three\u2010dimensional (3D) culture systems\u2014including spheroids, patient\u2010derived organoids (PDOs), tissue\u2010originated spheroids (CTOS), and collagen\u2010embedded models\u2014have revealed striking 2D vs. 3D discordance in proliferation, signaling, epithelial\u2010mesenchymal transition (EMT), plasticity, and sensitivity to standard chemo\u2010 and targeted therapies. This review synthesizes how 3D CRC models are used to decode mechanisms of primary and acquired resistance to anti\u2010CRC therapies, from metabolic phenotypes and ECM remodeling to EMT, polarity loss, and rare invasive trajectories identified by imaging and quantification of morphologic features of CRC cells grown in 3D. Parallel advances in PDO\u2010based functional precision oncology demonstrate that organoid drug screens can prospectively predict patient response in advanced CRC, while 3D combination screens uncover format\u2010specific synergies that are invisible in 2D. Building on this foundation, we highlight recent technical innovations and discuss how integrating morphometric, metabolic, and trajectory\u2010level readouts can move CRC drug discovery \u201cbeyond live\/dead.\u201d Rather than propose a single best model, we outline practical guidelines for matching 3D platform choice (cell lines vs. PDO\/CTOS, collagen vs. Matrigel, static vs. live\u2010imaging HTS) to mechanistic questions and therapeutic goals in CRC. We propose an integrated roadmap\u2014matrix\u2010embedded 3D cultures, high\u2010content morphological endpoints, trajectory analytics, and rigorous HTS validation\u2014to decode resistance mechanisms and prioritize clinically actionable combinations in CRC.<\/jats:p>","DOI":"10.1002\/cam4.72305","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T03:14:39Z","timestamp":1790824479000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Beyond the Monolayer: Leveraging\n                    <scp>3D<\/scp>\n                    Culture Systems to Decode Mechanisms of Drug Resistance and Therapeutic Vulnerabilities in Colorectal Cancer"],"prefix":"10.1002","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9967-5398","authenticated-orcid":false,"given":"Sarah J.","family":"Harmych","sequence":"first","affiliation":[{"name":"Department of Medicine Vanderbilt University Medical Center  Nashville Tennessee USA"},{"name":"Department of Cell and Developmental Biology Vanderbilt University  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1357-2158","authenticated-orcid":false,"given":"Bhuminder","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Medicine Vanderbilt University Medical Center  Nashville Tennessee USA"},{"name":"Epithelial Biology Center Vanderbilt University Medical Center  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,30]]},"reference":[{"issue":"3","key":"e_1_2_8_2_1","first-page":"233","article-title":"Colorectal Cancer Statistics, 2023","volume":"73","author":"Siegel R. 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