A potential lncRNA-based cancer algorithm
Abstract
How lncRNA are involved in regulating the immune system and how do they participate in tumors? To answer these questions, Li, Jiang and other authors[1] developed ImmLnc, an integrated algorithm that allows to identify correlations between regulatory lncRNAs and immune-related pathways. This work has obtained different types of data on the propagation of tumors and the possible use of lncRNAs as tumor biomarkers or to develop new immunotherapies against cancer and other diseases.
2020, China. A group of researchers from different universities published a fully computational research work on lncRNAs, their function in immune regulation and, being associated with proliferation, apoptosis and differentiation, they also seek the contribution of these molecules in tumors. Leveraging transcriptome big-data available in public databases they associated the presence of some lncRNAs to different types of tumor.
Long non-coding RNAs are non-coding RNAs longer than 200 base pairs. They are about as numerous as coding genes, but are usually less expressed. They lack catalytic activity and act as regulators of gene expression. The function of few lncRNA is known, which is why the authors of this research are looking for new innovative applications, in research fields in which they could be involved.
Li, Jiang et al. developed ImmLnc, an integrated algorithm that allows characterization of Immune Correlated (lncRNA ICs) and identifies different cancer subtypes (proliferative, intermediate, and immunological), which show distinct responses to chemotherapy. This is an interactive platform where the user can search for the immune pathway, sequences of biochemical reactions used by the body to regulate the immune system, or the lncRNA of interest and obtain in response data, such as: expression profiles of the lncRNA genes in different tumor samples, the correlations between the expression of lncRNA and immune cell infiltration, lncRNA expression perturbation data.
ImmLnc is developed in three steps: using data from the TCGA (The Cancer Genome Atlas, an international consortium that contains omics data of the gene expression sets of lncRNAs) the gene expression of lncRNAs is investigated in 11.000 samples, across 33 cancers.
Correlations between protein coding gene and lncRNA expressions, to built the IC lncrNA networks, are identified by partial correlation coefficient, that correlates genes to lncRNAs, through this you can predict a lncRNA function knowing the function of correlated protein coding gene. The correlation between coding and non-coding genes is calculated also taking into account tumor purity as a confusing factor: the data obtained therefore refer only to those pairs in which no other data brings randomness and to transport coding domain information to non-coding domain information.
For each lncRNA the activity in 17 immunologically relevant immune pathways is calculated considering if correlated protein coding genes are enriched in these pathways.
Considering all analysed data, the authors estimated the lncRNA activity in immune pathways and represented it as a network that connects lncRNA to 17 pathways. In particular focusing on the strongest 500 immune pathway-lncRNA pairs they obtained a regulatory network that includes 241 lncRNAs and 13 different immune pathways. Studying the different expressions of these 241 lncRNA, they found for example, MIAT, upregulated in 10 tumors and PVT-1 perturbed in 15 tumors. To validate the data obtained, the lncRNA-pathway pairs were reproduced with other independent data sets from the same tumor types, (collected from The International Cancer Genome Consortium and Gene Expression Omnibus).
The lncRNA-pathway pairs were re-identified by ImmLnc in each cancer type and significant lncRNA-pathway overlap was found for the same cancer type. In particular, a perturbation of lncRNAs expression was noted in cancers suitable for immunotherapy (such as lung cancer). Furthermore, cancers of similar tissue of origin have been found to significantly share immune-related lncRNAs, so that can be used as biomarkers, for early diagnosis or to identify precisely the disturbed expressions. The infiltration levels of six tumor-infiltrating immune cells (B cells, CD4 T cells, CD8 T cells, macrophages, neutrophils and dendritic cells) were then estimated in each patient, based on gene expression. The associations between immune infiltrates and lncRNA expression were evaluated by the Spearman correlation coefficient. In most cancers, a significantly higher percentage of immune-related lncRNAs are correlated with immune cell infiltration.
LncRNAs can also be used for molecular subtyping of the tumor, but how is it possible?
LncRNAs that regulate immune pathways in two types of lung cancer (LUAD and LUSC) were identified, then overlapped on those related to infiltration of 6 types of immune cells: there are in fact 28 highly expressed lncRNAs found in B and T cells. Based on the expression of these 28 common lncRNAs in pan-lung cancer, patients are classified into 3 categories: C1, C2, C3 . Most of these lncRNAs are highly expressed in C2 and C3 patients. In C1, the tumor showed a higher level of differentiation, hippo activity, proliferation rate, with increased stemness scores and poorer prognosis. A particularly significant difference between C1 and C2 concerns the number of surviving patients: after 4000 days it is approximately double in C2 compared to the number of patients alive in C1. C2 patients show significantly higher immune activity (CYT and MHC scores) than the other two categories. A higher percentage of C2 patients responded to chemotherapy. Therefore, ImmLnc identifies various cancer subtypes with significant molecular and immunological diversity, useful for improving personalized therapy management. It was thought to use lncRNAs as biomarkers because the IC lncRNAs identified by ImmLnc almost fully overlap with enriched lncRNAs in tumor tissues. Research is moving towards the study of new strategies to use lncRNAs as tumor biomarkers, despite the fact that a limited number of lncRNAs have been identified.
ImmLnc can also be applied to identify other regulators (such as transcription factors and microRNAs) of immune pathways.
LncRNAs seem to be a new frontier for better understanding how tumors spread in the body, but to do this, it is necessary to understand how these molecules influence gene expression, for example, if they act as signal molecules or as scaffolds.
Furthermore, the development of new RNA-based techniques, such as chromatin isolation, capture and analysis of hybridized RNAs, can help to better understand the functions of the nuclear lncRNA. The final aim is the development of new immunotherapies against cancer and other diseases.
References
- Li Y., et al. “Pan-Cancer Characterization of Immune-Related LncRNAs Identifies Potential Oncogenic Biomarkers.” Nature Communications, vol. 11, no. 1, 2020,
- Huarte, M. “The emerging role of lncRNAs in cancer”. Nat. Med. 21, 2015.
- Bhattacharya, S. et al. “ImmPort, toward repurposing of open access immunological assay data for translational and clinical research”. Sci. Data 5, 2018.