The immune response to COVID-19 infection is variable. How COVID-19 influences clinical outcomes in hospitalized patients needs to be understood through readily obtainable biological materials, such as blood. We hypothesized that a high-density analysis of host (and pathogen) blood RNA in hospitalized patients with SARS-CoV-2 would provide mechanistic insights into the heterogeneity of response amongst COVID-19 patients when combined with advanced multidimensional bioinformatics for RNA. We enrolled 36 hospitalized COVID-19 patients (11 died) and 15 controls, collecting 74 blood PAXgene RNA tubes at multiple timepoints, one early and in 23 patients after treatment with various therapies. Total RNAseq was performed at high-density, with >160 million paired-end, 150 base pair reads per sample, representing the most sequenced bases per sample for any publicly deposited blood PAXgene tube study. There are 770 genes significantly altered in the blood of COVID-19 patients associated with antiviral defense, mitotic cell cycle, type I interferon signaling, and severe viral infections. Immune genes activated include those associated with neutrophil mechanisms, secretory granules, and neutrophil extracellular traps (NETs), along with decreased gene expression in lymphocytes and clonal expansion of the acquired immune response. Therapies such as convalescent serum and dexamethasone reduced many of the blood expression signatures of COVID-19. Severely ill or deceased patients are marked by various secondary infections, unique gene patterns, dysregulated innate response, and peripheral organ damage not otherwise found in the cohort. High-density transcriptomic data offers shared gene expression signatures, providing unique insights into the immune system and individualized signatures of patients that could be used to understand the patient’s clinical condition. Whole blood transcriptomics provides patient-level insights for immune activation, immune repertoire, and secondary infections that can further guide precision treatment.

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Next-generation sequencing (NGS) capabilities can affect therapeutic decisions in patients with complex, advanced, or refractory cancer. We report the feasibility of a tumor sequencing advisory board at a regional cancer center. Specimens were analyzed for approximately 2800 mutations in 50 genes. Outcomes of interest included tumor sequencing advisory board function and processes, timely discussion of results, and proportion of reports having potentially actionable mutations. NGS results were successfully generated for 15 patients, with median time from tissue processing to reporting of 11.6 days (range, 5 to 21 days), and presented at a biweekly multidisciplinary tumor sequencing advisory board. Attendance averaged 19 participants (range, 12 to 24) at 20 days after patient enrollment (range, 10 to 30 days). Twenty-seven (range, 1 to 4 per patient) potentially actionable mutations were detected in 11 of 15 patients: TP53 (n = 6), KRAS (n = 4), MET (n = 3), APC (n = 3), CDKN2A (n = 2), PTEN (n = 2), PIK3CA, FLT3, NRAS, VHL, BRAF, SMAD4, and ATM. The Hotspot Panel is now offered as a clinically available test at our institution. NGS results can be obtained by in-house high-throughput sequencing and reviewed in a multidisciplinary tumor sequencing advisory board in a clinically relevant manner. The essential components of a center for personalized cancer care can support clinical decisions outside the university.

We present Single-cell TOtal RNA Miniaturized sequencing (STORM-seq), a full-length single-cell ribo-reduced RNA sequencing protocol, optimized to profile thousands of cells per run. Using off-the-shelf reagents and random hexamer priming, STORM-seq recovers comprehensive RNA profiles from single cells with library complexity approaching that of bulk RNA-seq. STORM-seq identifies thousands of additional coding and non-coding transcripts not detected by existing methods, and recovers clinically relevant structural variants at the single-cell level. We apply STORM-seq to primary human Fallopian tube epithelium (FTE), a complex solid tissue, key to both human reproductive biology and ovarian carcinogenesis. In differentiation trajectory analyses, the improved resolution from STORM-seq reveals intermediate/transitional cell states, and a putative progenitor cell population. The results support a trajectory from a bipotent progenitor population to ciliated and secretory cell types in normal FTE. These findings are consistent across human subjects, sequencing depths, and platforms. Long intergenic non-coding RNAs (lincRNAs) appear as key driver genes in both ciliated and secretory lineage trajectories, underscoring the importance of both coding and non-coding RNA in this tissue. By capturing essentially complete individual cellular transcriptomes, STORM-seq sheds new light on the transcriptional programs that establish cellular state and fate in complex tissues.