RNA Biomarkers May Shed Light on Cancer Immunotherapy Response

Medication Review


This study aimed to look at how long noncoding RNA’s (lncRNAs) are related to immune molecular classification and its clinical outcomes in terms of cancer immunotherapy. It is known that lncRNAs play a role in both the innate and adaptive immunity within cancer. The lncRNAs intervene and assist the functional of immunologic cells, their pathways, and their genes. While previous studies have looked at the interactions between a lncRNAs biology and immune microenvironment components, this study is the first, to their knowledge, to identify lncRNA-based immune subtypes that are linked to a response to clinical cancer immunotherapy.

An individual patient-level analysis was conducted on 3,370 patients between June and September in 2019 that used proven lncRNA and genomic data. From the analysis, a pan-cancer multicohort study consisted of 406 patients receiving immunotherapy for bladder cancer, 457 for melanoma, 513 for lung cancer, and 1,082 for breast cancer. The endpoints for this study was the overall survival of the patient and both the objective response rate and disease control rate. An R package clusterProfiler (an analysis module that “automates the process of biological-term classification and the enrichment of the analysis of gene clusters” [ncbi reference]) was used for gene ontology. Along with the R package clusterProfile, many other R packages were used to calculate gene set variation analysis (GSVA) enrichment scores, assess differences between GSVA enrichment scores and different lncRNA classes, and numerically estimate and rank the importance of lncRNAs.

A few discoveries were made as results were collected. First, two distinct lncRNA-based classes (immune functional and immune nonfunctional) were linked to significantly different overall survival rates. The immune functional class showed a higher probability of overall survival by about 15%-20%. The graph comparing this finding as well as the overall survival when comparing the nuclear factor-kB-interacting lncRNA (NKILA) is shown below. It was also found that patients who had lived longer experienced a reduced expression of immune cells, immune checkpoints, and human leukocyte antigen levels; the opposite was found for those that did not survive as long. As for the NKILA levels in the graph below, shows that low NKILA levels showed greater survivability. Four specific NKILAs were found to be especially important. These NKILAs were then further investigated how each of them compares against each other while still looking at overall survivability. The graph showing these comparisons is located on the top right-hand side of the following page.

The results of the graph to the right show that the immune-active class demonstrated the highest probability of survival and the immune-desert class revealed the lowest survival probability. By knowing what NKILAs are present can help a clinician plan how to fight the patient’s cancer. Many other variables are needed to be established before determining treatment but knowing more about how NKILAs are related to the patient’s ability to survive would be very helpful. A few other findings that were found in this study was that a patient’s overall survival rate increased with a functional immune response and high cytotoxic T lymphocytes (CTLs) infiltration, and patients who received a low lncRNA score had a greater overall survival probability.

Overall, the study was able to identify four different immune classes within clinical cancer immunotherapy. It is recommended that patients who show the immune-active class, immune-functional lncRNA signature, and dense CTL infiltration undergo immunotherapy. When giving the immunotherapy, panels checking tumor alteration burden, CTL infiltration, PD-L1 expression, and lncRNA scores will be good biomarkers as to the success of the immunotherapy.

All studies have their strength and weaknesses. For this study, one its strengths were its extensive research into all the different NKILAs once it was found to have an affect on overall survival. As for a weakness, the study acknowledges its heterogeneity of populations and its later affect on the different responses for high and low lncRNA scores.

Articles Cited:

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 Netw Open. 2020;3(4):e202149. doi:10.1001/jamanetworkopen.2020.2149

Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284-287. doi:10.1089/omi.2011.0118