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    Original Investigation
    Immunology
    April 7, 2020

    Association of Long Noncoding RNA Biomarkers With Clinical Immune Subtype and Prediction of Immunotherapy Response in Patients With Cancer

    Author Affiliations
    • 1Department of Medical Oncology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
    • 2Guangdong Medical University, Zhanjiang, China
    • 3Department of Medical Oncology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
    • 4Breast Tumor Centre, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
    JAMA Netw Open. 2020;3(4):e202149. doi:10.1001/jamanetworkopen.2020.2149
    Key Points español 中文 (chinese)

    Question  Are long noncoding RNAs (lncRNAs) associated with immune molecular classification and clinical outcomes of cancer immunotherapy?

    Findings  This cohort study of 348 patients with bladder cancer from the IMvigor210 trial and 71 patients with melanoma from The Cancer Genome Analysis identified 4 distinct classes with different immunotherapeutic overall survival and response. An lncRNA score was developed that also was associated with survival and immunotherapy response.

    Meaning  This study identifies novel lncRNA-based immune classes in cancer immunotherapy and provides an lncRNA score for integration into multiomic panels for precision immunotherapy.

    Abstract

    Importance  Long noncoding RNAs (lncRNAs) are involved in innate and adaptive immunity in cancer by mediating the functional state of immunologic cells, pathways, and genes. However, whether lncRNAs are associated with immune molecular classification and clinical outcomes of cancer immunotherapy is largely unknown.

    Objectives  To explore lncRNA-based immune subtypes associated with survival and response to cancer immunotherapy and to present a novel lncRNA score for immunotherapy prediction using computational algorithms.

    Design, Setting, and Participants  In this cohort study, an individual patient analysis based on a phase 2, single-arm clinical trial and multicohort was performed from June 25 through September 30, 2019. Data are from the phase 2 IMvigor210 trial and from The Cancer Genome Atlas (TCGA). The study analyzed lncRNA and genomic data of 348 patients with bladder cancer from the IMvigor210 trial and 71 patients with melanoma from TCGA who were treated with immunotherapy. In addition, a pancancer multicohort that included 2951 patients was obtained from TCGA.

    Main Outcomes and Measures  The primary end point was overall survival (OS).

    Results  Among 348 patients from the IMvigor210 trial (272 [78.2%] male) and 71 patients with melanoma from TCGA (mean [SD] age, 58.3 [13.4] years; 37 [52.1%] female), 4 distinct classes with statistically significant differences in OS (median months, not reached vs 9.6 vs 8.1 vs 6.7 months; P = .002) were identified. The greatest OS benefit was obtained in the immune-active class, as characterized by the immune-functional lncRNA signature and high CTL infiltration. Patients with low vs high lncRNA scores had statistically significantly longer OS (hazard ratio, 0.32; 95% CI, 0.24-0.42; P < .001) in the IMvigor210 trial and across various cancer types. The lncRNA score was associated with immunotherapeutic OS benefit in the IMvigor210 trial cohort (area under the curve [AUC], 0.79 at 12 months and 0.77 at 20 months) and in TCGA melanoma cohort (AUC, 0.87 at 24 months), superior tumor alteration burden, programmed cell death ligand 1 (PD-L1) expression, and cytotoxic T-lymphocyte (CTL) infiltration. Addition of the lncRNA score to the combination of tumor alteration burden, PD-L1 expression, and CTL infiltration to build a novel multiomics algorithm correlated more strongly with OS in the IMvigor210 trial cohort (AUC, 0.81 at 12 months and 0.80 at 20 months).

    Conclusions and Relevance  This study identifies novel lncRNA-based immune classes in cancer immunotherapy and recommends immunotherapy for patients in the immune-active class. In addition, the study recommends that the lncRNA score should be integrated into multiomic panels for precision immunotherapy.

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