Meta-analysis of host transcriptional responses to SARS-CoV-2 infection reveals their manifestation in human tumors.

A deeper understanding of the molecular biology of SARS-CoV-2 infection, including the host response to the virus, is urgently needed. Commonalities exist between the host immune response to viral infections and cancer. Here, we defined transcriptional signatures of SARS-CoV-2 infection involving hundreds of genes common across lung adenocarcinoma cell lines (A549, Calu-3) and normal human bronchial epithelial cells (NHBE), with additional signatures being specific to one or both adenocarcinoma lines. Cross-examining eight transcriptomic databases, we found that host transcriptional responses of lung adenocarcinoma cells to SARS-CoV-2 infection shared broad similarities with host responses to multiple viruses across different model systems and patient samples. Furthermore, these SARS-CoV-2 transcriptional signatures were manifested within specific subsets of human cancer, involving ~ 20% of cases across a wide range of histopathological types. These cancer subsets show immune cell infiltration and inflammation and involve pathways linked to the SARS-CoV-2 response, such as immune checkpoint, IL-6, type II interferon signaling, and NF-κB. The cell line data represented immune responses activated specifically within the cancer cells of the tumor. Common genes and pathways implicated as part of the viral host response point to therapeutic strategies that may apply to both SARS-CoV-2 and cancer.

Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals.

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity among samples. Mixed allelic frequencies along the 20kb ORF1ab gene in one sample, suggested the presence of a defective viral RNA species subpopulation maintained in mixture with functional RNA in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.