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Abstract
Background Ipilimumab improved outcomes for high-risk melanoma patients compared to interferon-α2b in phase III adjuvant trial E1609 (NCT01274338) to which patients provided IRB-approved consent at participating institutions.1 We hypothesized that a superior predictive biomarker signature could be generated by combining specific immune biomarkers in both tumor and circulating blood based on a common systems immunobiology.
Methods We analyzed baseline tumor microarray (Affymetrix GeneChips) gene expression data from patients treated with ipilimumab (471) and interferon (248). We used multicolor flow cytometry to compare cellular marker expression on thawed PBMC and multiplex Luminex to measure serum biomarkers vs. patient-matched biospecimens collected at baseline (210 ipilimumab, 119 interferon). Expression levels of 31 genes and 40 circulating candidate biomarkers were correlated to survival outcomes. We then developed 2 separate multivariate Lasso-Cox regression models followed by an integrative modeling of risk prediction using the prioritized biomarkers.
Results In patient blood, an enriched population of CTLA4+Treg (CD3+/CD4+/CD25hi+/CD152+) and monocytic (M)-MDSC (Lin-CD33+/HLA-Drlo/CD14+/CD15+) were associated with the worst OS and RFS, while an enriched population of CXCR3+/CD4+ T cells, CXCR3+/CD8+ T cells, CTLA4+/INFg+/CD8+ T cells, and higher levels of CCL3 and CXCL11 were associated with significantly improved OS and RFS. In tumors, we identified CXCL9, CD8A, CXCL10, INPP5D as Tier-1 (P<0.05) and IDO1, IGKC, IL2RB as Tier-2 (P<0.1) biomarkers of improved outcomes. Next, we generated risk scores based on the prioritized circulating (L-IPI3) and tumor (L-IPI-7) biomarkers, respectively to assess their predictive power. Through an integrative comparison between the circulating biomarker model compared to the tumoral biomarker model, we found 23.4% of patients could be consistently predicted as high risk (above median risk score) and 29.1% of patients could be consistently predicted as low risk (below median risk score) based on the 2 risk scores. A multivariate survival analysis with a multiplicative interaction between the two risk models identified an improved categorization of patient risk (figure 1). Overall, ~50% of the risk groups defined by circulating and tumor biomarker models did not overlap, indicating complementary features of defining risk groups in ipilimumab-treated patients, but not in interferon-treated patients.
Conclusions Integrating candidate blood and tumor immune-related biomarkers generated a baseline signature that maximizes prediction of immunotherapeutic benefits in melanoma patients in reference to the compartmental biomarker signatures. Our integrated signature supports the presence of tumor infiltrating and circulating immune cells with limited levels of immunosuppressive cells as an optimal environment for favorable prognosis after treatment with adjuvant ipilimumab.
Acknowledgements We are grateful to our patients who participated in E1609 and their family members. We also would like to thank E1609 investigators and research coordinators and our funding sources.
Trial Registration Clinicaltrials.gov NCT01274338
Reference
Tarhini AA, Lee SJ, Hodi FS, Rao UNM, Cohen GI, Hamid O, Hutchins LF, Sosman JA, Kluger HM, Eroglu Z, Koon HB, Lawrence DP, Kendra KL, Minor DR, Lee CB, Albertini MR, Flaherty LE, Petrella TM, Streicher H, Sondak VK, Kirkwood JM. Phase III Study of Adjuvant Ipilimumab (3 or 10 mg/kg) Versus High-Dose Interferon Alfa-2b for Resected High-Risk Melanoma: North American Intergroup E1609. J Clin Oncol. 2020 Feb 20;38(6):567–575. PMID: 31880964.
Ethics Approval Patients participating in the ECOG-ACRIN E1609 trial and included in this study provided an IRB-approved informed consent at their participating institutions.
Consent Patients participating in the ECOG-ACRIN E1609 trial and included in this study provided an IRB-approved informed consent at their participating institutions.
A multivariate survival analysis with a multiplicative interaction between blood and tumor biomarkers risk models. The integrated signature supports improved categorization of patient risk with adjuvant ipilimumab.
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