{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T21:59:40Z","timestamp":1774043980199,"version":"3.50.1"},"reference-count":13,"publisher":"BMJ","issue":"12","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"unspecified","delay-in-days":4,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Immunother Cancer"],"accepted":{"date-parts":[[2025,11,17]]},"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>\n                    While immune checkpoint inhibition (ICI) has revolutionized therapy across solid tumors, resistance remains an issue. Programmed death ligand-1 immunohistochemistry has limited clinical utility, whereas tumor mutation burden and microsatellite instability are only valuable for a minority of patients and leave room for improvement. Multiomic gene signatures have enhanced prediction of immune response by incorporating interferon-gamma signaling, T-cell dysfunction and exhaustion genes, and myeloid signatures. Single-cell RNA technology has been adopted to further optimize prediction of response to immunotherapy. A novel Immune Profile Score is presented by Zander et\n                    <jats:italic>al<\/jats:italic>\n                    that builds on prior immune signatures, using DNA and RNA profiling to predict outcomes across solid tumors receiving ICIs. While this assay is promising, further prospective validation and refinements will be necessary to realize its full potential in our quest to develop precision immuno-oncology. The incorporation of readily available clinical factors (eg, sites of metastasis), host genetics, orthogonal molecular platforms (microbiome, computational pathology, spatial transcriptomics, epigenetics, proteomics, radiomics) and investigating biomarkers to predict primary refractory disease and severe toxicities may further facilitate precision medicine.\n                  <\/jats:p>","DOI":"10.1136\/jitc-2025-013213","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T11:15:38Z","timestamp":1765278938000},"page":"e013213","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Toward a better pan-tumor predictive signature for unleashing precision immuno-oncology"],"prefix":"10.1136","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6225-7555","authenticated-orcid":false,"given":"Jason R.","family":"Brown","sequence":"first","affiliation":[{"name":"University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA"},{"name":"Case Western Reserve University, Cleveland, Ohio, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1010-9611","authenticated-orcid":false,"given":"Guru","family":"Sonpavde","sequence":"additional","affiliation":[{"name":"AdventHealth Cancer Institute, Orlando, Florida, USA"},{"name":"University of Central Florida, Orlando, Florida, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"239","published-online":{"date-parts":[[2025,12,9]]},"reference":[{"key":"2025120902350977000_13.12.e013213.1","doi-asserted-by":"crossref","first-page":"2352","DOI":"10.1002\/ijc.35347","article-title":"How many people in the US are eligible for and respond to checkpoint inhibitors: An empirical analysis","volume":"156","author":"Haslam","year":"2025","journal-title":"Int J Cancer"},{"key":"2025120902350977000_13.12.e013213.2","doi-asserted-by":"crossref","DOI":"10.1186\/s40425-019-0768-9","article-title":"The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors","volume":"7","author":"Davis","year":"2019","journal-title":"J Immunother Cancer"},{"key":"2025120902350977000_13.12.e013213.3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccell.2020.10.001"},{"key":"2025120902350977000_13.12.e013213.4","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1136\/jitc-2024-011363","article-title":"Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors","volume":"13","author":"Zander","year":"2025","journal-title":"J Immunother 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(UC)","volume":"43","author":"Brown","year":"2025","journal-title":"JCO"},{"key":"2025120902350977000_13.12.e013213.11","doi-asserted-by":"crossref","DOI":"10.1186\/s13073-022-01050-w","article-title":"Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response","volume":"14","author":"Zhang","year":"2022","journal-title":"Genome Med"},{"key":"2025120902350977000_13.12.e013213.12","doi-asserted-by":"crossref","DOI":"10.1016\/j.crmeth.2023.100643","article-title":"scCURE identifies cell types responding to immunotherapy and enables outcome prediction","volume":"3","author":"Zou","year":"2023","journal-title":"Cell Rep Methods"},{"key":"2025120902350977000_13.12.e013213.13","doi-asserted-by":"crossref","first-page":"8161","DOI":"10.1038\/s41467-025-63538-4","article-title":"Longitudinal liquid biopsy identifies an early predictive biomarker of immune checkpoint blockade response in head and neck squamous cell 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