Download This Paper
Preprints with The Lancet is a collaboration between The Lancet Group of journals and SSRN to facilitate the open sharing of preprints for early engagement, community comment, and collaboration. Preprints available here are not Lancet publications or necessarily under review with a Lancet journal. These preprints are early-stage research papers that have not been peer-reviewed. The usual SSRN checks and a Lancet-specific check for appropriateness and transparency have been applied. The findings should not be used for clinical or public health decision-making or presented without highlighting these facts. For more information, please see the FAQs.
Robust Immunoscore Model to Predict the Response to Anti-PD1 Therapy in Melanoma
24 Pages Posted: 20 Sep 2019
More...Abstract
Background: Anti-PD1 therapy translates tremendous clinical gains in treatment of melanoma. However, only a subset of patients with melanoma derives benefit from PD1 inhibitors. This study therefore aimed to construct predictors to identify responders to anti-PD1 therapy.
Methods: CIBERSORT method was applied to establish the fraction of 22 immune cell types from GEO and TCGA datasets. We used a least absolute shrinkage and selection operator (LASSO) logistic regression to construct an immunoscore based on the fraction of immune subsets and adopted gene set enrichment analysis (GSEA) to analyze the biological pathways associated with the immunoscore.
Findings: Using LASSO regression, an immunoscore consisting of eight immune subsets was generated to predict the anti-PD1 response. It achieved an overall accuracy of AUC = 0*77, 0*80 and 0*73 in the training cohort, validation cohort and on-anti-PD1 cohort. Patients with high-immunoscore had significantly higher objective response rates (ORRs) than those with low-immunoscore (ORR: 53*8% vs 17*7%, P < 0*001 for entire pre-anti-PD1 cohort; 42*1% vs 15*1%, P = 0*022 for on-anti-PD1 cohort; 66*7% vs 16*7%, P = 0*038 for neoadjuvant anti-PD1 cohort). Prolonged survival trends were observed in the high-immunoscore group (1-year PFS: 42*4% vs 14*3%, P = 0*059; 3-year OS: 41*5% vs 31*6%, P = 0*057). Furthermore, high-immunoscore group exhibited higher fractions of tumor-infiltrating lymphocytes and an increased IFN-γ response. Analysis of GSEA indicated a significant enrichment of antitumor immunity pathways in the high-immunoscore group.
Interpretation: This study indicated that we constructed a robust immunoscore model to predict the anti-PD1 response of melanoma.
Funding Statement: The authors declared: "This study was not funded."
Declaration of Interests: The authors declare that they have no competing interests.
Keywords: melanoma, PD1, immunoscore, response, CIBERSORT
Suggested Citation: Suggested Citation