Read-through transcripts in lung: germline genetic regulation and correlation with the expression of other genes

Genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue

Emerging evidence suggests that the prognosis of patients with lung adenocarcinoma can be determined from germline variants and transcript levels in nontumoral lung tissue. Gene expression data from noninvolved lung tissue of 483 lung adenocarcinoma patients were tested for correlation with overall survival using multivariable Cox proportional hazard and multivariate machine learning models. For genes whose transcript levels are associated with survival, we used genotype data from 414 patients to identify germline variants acting as cis-expression quantitative trait loci (eQTLs). Associations of eQTL variant genotypes with gene expression and survival were tested. Levels of four transcripts were inversely associated with survival by Cox analysis (CLCF1, hazard ratio [HR] = 1.53; CNTNAP1, HR = 2.17; DUSP14, HR = 1.78; and MT1F: HR = 1.40). Machine learning analysis identified a signature of transcripts associated with lung adenocarcinoma outcome that was largely overlapping with the transcripts identified by Cox analysis, including the three most significant genes (CLCF1, CNTNAP1, and DUSP14). Pathway analysis indicated that the signature is enriched for ECM components. We identified 32 cis-eQTLs for CNTNAP1, including 6 with an inverse correlation and 26 with a direct correlation between the number of minor alleles and transcript levels. Of these, all but one were prognostic: the six with an inverse correlation were associated with better prognosis (HR < 1) while the others were associated with worse prognosis. Our findings provide supportive evidence that genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue.

Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases

Chimeric RNAs are transcripts that are generated by gene fusion and intergenic splicing events, thus comprising nucleotide sequences from different parental genes. In the past, Northern blot analysis and RT-PCR were used to detect chimeric RNAs. However, they are low-throughput and can be time-consuming, labor-intensive, and cost-prohibitive. With the development of RNA-seq and transcriptome analyses over the past decade, the number of chimeric RNAs in cancer as well as in rare inherited diseases has dramatically increased. Chimeric RNAs may be potential diagnostic biomarkers when they are specifically expressed in cancerous cells and/or tissues. Some chimeric RNAs can also play a role in cell proliferation and cancer development, acting as tools for cancer prognosis, and revealing new insights into the cell origin of tumors. Due to their abilities to characterize a whole transcriptome with a high sequencing depth and intergenically identify spliced chimeric RNAs produced with the absence of chromosomal rearrangement, RNA sequencing has not only enhanced our ability to diagnose genetic diseases, but also provided us with a deeper understanding of these diseases. Here, we reviewed the mechanisms of chimeric RNA formation and the utility of RNA sequencing for discovering chimeric RNAs in several types of cancer and rare inherited diseases. We also discussed the diagnostic, prognostic, and therapeutic values of chimeric RNAs.

Lung expression of genes putatively involved in SARS-CoV-2 infection is modulated in cis by germline variants

Germline variants in genes involved in SARS-CoV-2 cell entry and in host innate immune responses to viruses may influence the susceptibility to infection. This study used whole-genome analyses of lung tissue to identify polymorphisms acting as expression quantitative trait loci (eQTLs) for 60 genes of relevance to SARS-CoV-2 infection susceptibility. The expression of genes with confirmed or possible roles in viral entry-replication and in host antiviral responses was studied in the non-diseased lung tissue of 408 lung adenocarcinoma patients. No gene was differently expressed by sex, but APOBEC3H levels were higher and PARP12 levels lower in older individuals. A total of 125 cis-eQTLs (false discovery rate < 0.05) was found to modulate mRNA expression of 15 genes (ABO, ANPEP, AP2A2, APOBEC3D, APOBEC3G, BSG, CLEC4G, DDX58, DPP4, FURIN, FYCO1, RAB14, SERINC3, TRIM5, ZCRB1). eQTLs regulating ABO and FYCO1 were found in COVID-19 susceptibility loci. No trans-eQTLs were identified. Genetic control of the expression of these 15 genes, which encode putative virus receptors, proteins required for vesicle trafficking, enzymes that interfere with viral replication, and other restriction factors, may underlie interindividual differences in risk or severity of infection with SARS-CoV-2 or other viruses.