CIDIE   24052
CENTRO DE INVESTIGACION Y DESARROLLO EN INMUNOLOGIA Y ENFERMEDADES INFECCIOSAS
Unidad Ejecutora - UE
artículos
Título:
Bioinformatic profiling of tumor immunity from patient biopsies to predict survival and response to immunotherapy.
Autor/es:
VEIGAS, FLORENCIA; ROCHA, DARIO; GIROTTI, MARIA ROMINA ROMINA; MAHMOUD, YAMIL DAMIAN; BALZARINI, MONICA; FERNANDEZ, ELMER; MERLO, JOAQUIN; RABINOVICH, GABRIEL ADRIAN
Revista:
JOURNAL OF CLINICAL ONCOLOGY
Editorial:
AMER SOC CLINICAL ONCOLOGY
Referencias:
Año: 2020 vol. 38
ISSN:
0732-183X
Resumen:
Background: Immunotherapies have revolutionized cancer treatment, but responses are not universal and patients who initially respond to therapy develop resistance. The accurate quantification of tumor-infiltrating immune cells holds the promise to reveal the role of the immune system in human cancers and its involvement in tumor escape mechanisms and response to therapy. We present MIXTURE, a new algorithm for tumor immune cell-type proportions deconvolution from transcriptomic data that overcomes competitive methods and revealed novel associations of immune cell types with patient survival and immunotherapy response. Methods: We applied MIXTURE to transcriptomic data from BRCA (n = 1095), LUAD (n = 506), SKCM (n = 472), HNSC (n = 499) and COAD (n = 521) cohorts from TCGA and five published datasets of melanoma patients treated with anti-PD-1/anti-CLTA-4. Results: The analysis of TCGA breast cancer biopsies showed high proportions of M2-macrophages associated with poor patient survival (p < 0.001). In contrast, we found that proportions of follicular T helper cells were associated with better outcome (p < 0.001). We observed a differential immune composition in biopsies of lung adenocarcinoma patients with mutations in TP53 (WT; n = 247; Mut; n = 259) and EGFR (WT, n = 438; Mut, n = 68) related with their different response to immunotherapy (p < 0.05). We found correlations between immune cells proportions and current biomarkers of response to immunotherapy such as TMB, intratumoral heterogeneity, MSI and PD-L1 expression in the TCGA cohorts (p < 0.05). The meta-analysis of melanoma patients treated with immunotherapy showed a distinct immune infiltrate in patients who responded to anti-PD-1 with an increase of immune effector cells such as CD8, CD4 memory activated and gamma-delta T cells, and a decrease in immunosuppressive M2-macrophages (p < 0.05; R = 81; NR = 107). According with the latest findings, we observed higher presence of B cells in responders to anti-PD-1 on-treatment (p = 0.033; R = 31; NR = 23) and in baseline of responders to anti-CTLA-4 (p = 0.028; R = 14; NR = 26). Interestingly, patients that previously progressed to anti-CTLA-4 showed a differential immune profile that was associated with response to anti-PD-1 (p < 0.05; Ipi-Prog = 59; Ipi-Naïve = 102). Conclusions: We demonstrated the potential of MIXTURE to understand the tumor immune microenvironment and its relationship with patient survival and response to immunotherapies. MIXTURE is available for the wider scientific community as web application and as packages for R and Python.