Analysis of transcriptomics data from COVID-19 patients: a pilot research

During SARS-CoV-2 infection, the virus transforms the infected host cell into factories that produce new viral particles. As infection progresses, the infected cells undergo numerous changes in various pathways. One of these changes is the occurrence of a cytokine storm, which leads to severe symptoms. In this study, we examined the transcriptomic changes caused by COVID-19 by analyzing RNA-seq data obtained from COVID-19-positive patients as well as COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. We analyzed the first datasets, consisting of 96 samples to validate our methods. The objective of this publication is to report the pilot results. To explore potential biomarkers related to disease severity, we conducted a differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Given the large number of potential biomarkers we identified, we further performed pathway enrichment analysis with terms from Kyoto Encyclopedia of Genes and Genomics (KEGG) to obtain a more profound understanding of altered pathways. Our results indicate that pathways related to immune processes, response to infection, and multiple signaling pathways were affected. These findings align with several previous studies that also reported the influence of SARS-CoV-2 infection on these pathways.

Metatranscriptome Analysis of Nasopharyngeal Swabs across the Varying Severity of COVID-19 Disease Demonstrated Unprecedented Species Diversity

The recent global emergence of the SARS-CoV-2 pandemic has accelerated research in several areas of science whose valuable outputs and findings can help to address future health challenges in the event of emerging infectious agents. We conducted a comprehensive shotgun analysis targeting multiple aspects to compare differences in bacterial spectrum and viral presence through culture-independent RNA sequencing. We conducted a comparative analysis of the microbiome between healthy individuals and those with varying degrees of COVID-19 severity, including a total of 151 participants. Our findings revealed a noteworthy increase in microbial species diversity among patients with COVID-19, irrespective of disease severity. Specifically, our analysis revealed a significant difference in the abundance of bacterial phyla between healthy individuals and those infected with COVID-19. We found that Actinobacteria, among other bacterial phyla, showed a notably higher abundance in healthy individuals compared to infected individuals. Conversely, Bacteroides showed a lower abundance in the latter group. Infected people, regardless of severity and symptoms, have the same proportional representation of Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteriales. In addition to SARS-CoV-2 and numerous phage groups, we identified sequences of clinically significant viruses such as Human Herpes Virus 1, Human Mastadenovirus D, and Rhinovirus A in several samples. Analyses were performed retrospectively, therefore, in the case of SARS-CoV-2 various WHO variants such as Alpha (B.1.1.7), Delta (B.1.617.2), Omicron (B.1.1.529), and 20C strains are represented. Additionally, the presence of specific virus strains has a certain effect on the distribution of individual microbial taxa.

Abstract P5-11-04: Differentially expressed genes and their pathways in breast cancer patients with mesenchymal CTC

Background: Circulating tumor cells (CTC) with phenotype of epithelial-mesenchymal transition (CTC_EMT) represent novel subpopulation of CTC associated with inferior outcome in primary breast cancer (PBC). However, molecular characterization of primary tumors associated with this CTC subpopulation is lacking. The aim of this study was to identify signaling pathways associated with presence of CTC_EMT in PBC patients using a comprehensive genomics approach. Methods: This translational study included 17 patients with PBC and 5 donors of normal breast tissue. CTC_EMT were detected before surgery by quantitative RT-PCR assay for expression of epithelial-mesenchymal transition (EMT) genes (TWIST1, SNAIL1, SLUG, ZEB1). Total RNA was extracted, in parallel, from fresh frozen primary tumor and whole-trancriptome profiles were obtained using RNA sequencing and additionally mRNAs profiles by microarray. Genes expressions were further validated by qRT-PCR. Results: Analyzing RNA sequencing and microarray data, we found set of genes differentially expressed in absence or presence of CTC_EMT in PBC. We identified 157 genes differentially expressed in CTC_EMT phenotype compared to patients with non-detectable CTC. Namely, keratin family is represented by genes KRT5, KRT14, KRT17. Gene ontologies related to membrane structure or communication and immunology appears to be involved in CTC-related processes, pathways related to cell junction and various signaling pathways including PI3K and Ras-signaling appear to be significant in processes leading to CTC EMT presence. Conclusions: We suspect multiple genes of having a role in primary tumour processes leading to CTC EMT production in breast cancer patients. Data suggest, that PI3K & Ras-signalling and pathways related to cell junction are the key pathways for changes inside of primary tumour tissue between CTC EMT and CTC- phenotype of breast cancer patients. We propose, additional study with single-cell resolution is needed for better understanding of the processes.

Citation Format: Michal Mego, Dominik Hadzega, Gabriel Minarik, Andrea Soltysova, Petra Nemcova, Katarina Kalavska, Marian Karaba, Juraj Benca, Tatiana Sedlackova, Daniel Pindak, Lubos Klucar. Differentially expressed genes and their pathways in breast cancer patients with mesenchymal CTC [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-11-04.

Uncovering Microbial Composition in Human Breast Cancer Primary Tumour Tissue Using Transcriptomic RNA-seq

Recent research studies are showing breast tissues as a place where various species of microorganisms can thrive and cannot be considered sterile, as previously thought. We analysed the microbial composition of primary tumour tissue and normal breast tissue and found differences between them and between multiple breast cancer phenotypes. We sequenced the transcriptome of breast tumours and normal tissues (from cancer-free women) of 23 individuals from Slovakia and used bioinformatics tools to uncover differences in the microbial composition of tissues. To analyse our RNA-seq data (rRNA depleted), we used and tested Kraken2 and Metaphlan3 tools. Kraken2 has shown higher reliability for our data. Additionally, we analysed 91 samples obtained from SRA database, originated in China and submitted by Sichuan University. In breast tissue, the most enriched group were Proteobacteria, then Firmicutes and Actinobacteria for both datasets, in Slovak samples also Bacteroides, while in Chinese samples Cyanobacteria were more frequent. We have observed changes in the microbiome between cancerous and healthy tissues and also different phenotypes of diseases, based on the presence of circulating tumour cells and few other markers.