Researchers Develop Long Noncoding RNA-Based Immune Classes and Scores for Immunotherapy

Article

A recent study determined 4 distinct long noncoding RNA-based immune classes for patients with cancer and provided scores for integration into multiomic panels for precision immunotherapy.

Immunotherapy is recommended for patients with bladder cancer that fall into the immune-active class, including 1 of the 4 distinct long noncoding RNA-based immune classes identified by trial researchers, according to a study published in JAMA Network Open.

The study also recommends that the long noncoding RNA score should be integrated into multiomic panels composed of tumor alteration burden, PD-L1 expression, cytotoxic T-lymphocyte (CTL) infiltration to act as a useful biomarker for precision immunotherapy.

“This study used signatures of (long noncoding RNAs) and CTL infiltration to identify 4 distinct immune classes in clinical cancer immunotherapy and recommends immunotherapy for patients in the immune-active class with both an immune-functional lncRNA signature and dense CTL infiltration,” wrote the researchers.

A total of 419 patients were analyzed, including 348 patients with bladder cancer from the IMvigor210 clinical trial and 71 patients with melanoma from The Cancer Genome Atlas. From these patients, 4 distinct classes with statistically significant differences in overall immunotherapeutic survival and response were distinguished.

The greatest overall survival benefit, which was characterized by “the immune-functional long noncoding RNA signature and high CTL infiltration,” was found in the immune-active class. Patients in the IMvigor210 trial and across cancer types who had low long noncoding RNA scores vs high scores saw longer overall survival (hazard ratio, 0.32; 95% CI, 0.24-0.42; P < .001).

The researchers first worked to characterize long noncoding RNA profiles to identify any overall survival advantages in the 2 classes: immune-functional class over the immune-nonfunctional class. Once they considered CTL infiltration, the researchers saw that patients in the immune-active class with both high density of CTLs and the immune-functional signature had the most favorable overall survival benefits.

Patients without these characteristics in the immune-desert class had worse clinical outcomes, with patients in the immune-dysfunctional class having high immune infiltration but poor overall survival benefits, which was even worse than patients in the immune-exclusion class.

“The 4 novel distinct classes identified in this study indicated that immune molecular classification of aspects of both immune exclusion and immune dysfunction could be informative for understanding patterns of immune escape (ie, cancers could escape immunologic destruction) and for selection of candidates for cancer immunotherapy,” wrote the researchers.

More, the long noncoding RNA score was associated with immunotherapeutic overall survival benefit in both the IMvigor210 trial cohort (area under the curve [AUC], 0.79 at 12 months and 0.77 at 20 months) and The Cancer Genome Atlas melanoma cohort (AUC, 0.87 at 24 months).

A limitation of the study is the heterogeneity of the populations and treatments across cancer types, which could explain small differences in the response between low vs high long noncoding RNA scores. More, some cohorts did not receive immunotherapy, resulting in only biomarker usefulness data being validated in these groups.

“The present study adds the long noncoding RNA score to this biomarker, potentially increasing and substantially improving the ability to predict immunotherapeutic benefit on overall survival, likely because of the additional information regarding immune dysfunction provided by the long noncoding RNA signature,” wrote the researchers.

Reference:

Yu Y, Zhang W, Li A, et al. Association of Long Noncoding RNA Biomarkers With Clinical Immune Subtype and Prediction of Immunotherapy Response in Patients With Cancer. JAMA Network Open. doi:10.1001/jamanetworkopen.2020.2149.

Related Videos
Thomas Marron, MD, PhD
PD-1 protein bound to PD-L1
cancer
Related Content