Chemokine expression predicts T cell-inflammation and improved survival with checkpoint inhibition across solid cancers

Autor: Joan Miguel Romero, Emma Titmuss, Yifan Wang, James Vafiadis, Alain Pacis, Gun Ho Jang, Amy Zhang, Bryn Golesworthy, Tatiana Lenko, Laura M. Williamson, Barbara Grünwald, Grainne M. O’Kane, Steven J. M. Jones, Marco. A. Marra, Julie M. Wilson, Steven Gallinger, Janessa Laskin, George Zogopoulos
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: npj Precision Oncology, Vol 7, Iss 1, Pp 1-14 (2023)
Druh dokumentu: article
ISSN: 2397-768X
DOI: 10.1038/s41698-023-00428-2
Popis: Abstract Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Scorehi) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Scorehi tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Scorehi tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22–0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.
Databáze: Directory of Open Access Journals