Virus expression detection reveals RNA-sequencing contamination in TCGA

Are There More Human Cancer Viruses Left to Be Found?

Of the thousands of viruses infecting humans, only seven cause cancer in the general population. Tumor sequencing is now a common cancer medicine procedure, and so it seems likely that more human cancer viruses already would have been found if they exist. Here, we review cancer characteristics that can inform a dedicated search for new cancer viruses, focusing on Kaposi sarcoma herpesvirus and Merkel cell polyomavirus as the most recent examples of successful genomic and transcriptomic searches. We emphasize the importance of epidemiology in determining which cancers to examine and describe approaches to virus discovery. Barriers to virus discovery, such as novel genomes and viral suppression of messenger RNA expression, may exist that prevent virus discovery using existing approaches. Optimally virus hunting should be performed in such a way that if no virus is found, the tumor can be reasonably excluded from having an infectious etiology and new information about the biology of the tumor can be found.

Three Modes of Viral Adaption by the Heart

Viruses elicit long-term adaptive responses in the tissues they infect. Understanding viral adaptions in humans is difficult in organs such as the heart, where primary infected material is not routinely collected. In search of asymptomatic infections with accompanying host adaptions, we mined for cardio-pathogenic viruses in the unaligned reads of nearly one thousand human hearts profiled by RNA sequencing. Among virus-positive cases (~20%), we identified three robust adaptions in the host transcriptome related to inflammatory NFκB signaling and post-transcriptional regulation by the p38-MK2 pathway. The adaptions are not determined by the infecting virus, and they recur in infections of human or animal hearts and cultured cardiomyocytes. Adaptions switch states when NFκB or p38-MK2 are perturbed in cells engineered for chronic infection by the cardio-pathogenic virus, coxsackievirus B3. Stratifying viral responses into reversible adaptions adds a targetable systems-level simplification for infections of the heart and perhaps other organs.

Nivolumab plus ipilimumab in advanced salivary gland cancer: a phase 2 trial

Salivary gland cancers (SGCs) are rare, aggressive cancers without effective treatments when metastasized. We conducted a phase 2 trial evaluating nivolumab (nivo, anti-PD-1) and ipilimumab (ipi, anti-CTLA-4) in 64 patients with metastatic SGC enrolled in two histology-based cohorts (32 patients each): adenoid cystic carcinoma (ACC; cohort 1) and other SGCs (cohort 2). The primary efficacy endpoint (≥4 objective responses) was met in cohort 2 (5/32, 16%) but not in cohort 1 (2/32, 6%). Treatment safety/tolerability and progression-free survival (PFS) were secondary endpoints. Treatment-related adverse events grade ≥3 occurred in 24 of 64 (38%) patients across both cohorts, and median PFS was 4.4 months (95% confidence interval (CI): 2.4, 8.3) and 2.2 months (95% CI: 1.8, 5.3) for cohorts 1 and 2, respectively. We present whole-exome, RNA and T cell receptor (TCR) sequencing data from pre-treatment and on-treatment tumors and immune cell flow cytometry and TCR sequencing from peripheral blood at serial timepoints. Responding tumors universally demonstrated clonal expansion of pre-existing T cells and mutational contraction. Responding ACCs harbored neoantigens, including fusion-derived neoepitopes, that induced T cell responses ex vivo. This study shows that nivo+ipi has limited efficacy in ACC, albeit with infrequent, exceptional responses, and that it could be promising for non-ACC SGCs, particularly salivary duct carcinomas. ClinicalTrials.gov identifier: NCT03172624 .

Profiling of Microbial Landscape in Lung of Chronic Obstructive Pulmonary Disease Patients Using RNA Sequencing

Purpose

The aim of the study was to use RNA sequencing (RNA-seq) data of lung from chronic obstructive pulmonary disease (COPD) patients to identify the bacteria that are most commonly detected. Additionally, the study sought to investigate the differences in these infections between normal lung tissues and those affected by COPD.

Patients and Methods

We re-analyzed RNA-seq data of lung from 99 COPD patients and 93 non-COPD smokers to determine the extent to which the metagenomes differed between the two groups and to assess the reliability of the metagenomes. We used unmapped reads in the RNA-seq data that were not aligned to the human reference genome to identify more common infections in COPD patients.

Results

We identified 18 bacteria that exhibited significant differences between the COPD and non-COPD smoker groups. Among these, Yersinia enterocolitica was found to be more than 30% more abundant in COPD. Additionally, we observed difference in detection rate based on smoking history. To ensure the accuracy of our findings and distinguish them from false positives, we double-check the metagenomic profile using Basic Local Alignment Search Tool (BLAST). We were able to identify and remove specific species that might have been misclassified as other species in Kraken2 but were actually Staphylococcus aureus, as identified by BLAST analysis.

Conclusion

This study highlighted the method of using unmapped reads, which were not typically used in sequencing data, to identify microorganisms present in patients with lung diseases such as COPD. This method expanded our understanding of the microbial landscape in COPD and provided insights into the potential role of microorganisms in disease development and progression.

Investigating Variability in Viral Presence and Abundance across Soybean Seed Development Stages Using Transcriptome Analysis

Plant transcriptomes offer a valuable resource for studying viral communities (viromes). In this study, we explore how plant transcriptome data can be applied to virome research. We analyzed 40 soybean transcriptomes across different growth stages and identified six viruses: broad bean wilt virus 2 (BBWV2), brassica yellow virus (BrYV), beet western yellow virus (BWYV), cucumber mosaic virus (CMV), milk vetch dwarf virus (MDV), and soybean mosaic virus (SMV). SMV was the predominant virus in both Glycine max (GM) and Glycine soja (GS) cultivars. Our analysis confirmed its abundance in both, while BBWV2 and CMV were more prevalent in GS than GM. The viral proportions varied across developmental stages, peaking in open flowers. Comparing viral abundance measured by viral reads and fragments per kilobase of transcript per million (FPKM) values revealed insights. SMV showed similar FPKM values in GM and GS, but BBWV2 and CMV displayed higher FPKM proportions in GS. Notably, the differences in viral abundance between GM and GS were generally insignificant based on the FPKM values across developmental stages, except for the apical bud stage in four GM cultivars. We also detected MDV, a multi-segmented virus, in two GM samples, with variable proportions of its segments. In conclusion, our study demonstrates the potential of plant transcriptomes for virome research, highlighting their strengths and limitations.

Detection of viral infection in cell lines using ViralCellDetector

Cell lines are commonly used in research to study biology, including gene expression regulation, cancer progression, and drug responses. However, cross-contaminations with bacteria, mycoplasma, and viruses are common issues in cell line experiments. Detection of bacteria and mycoplasma infections in cell lines is relatively easy but identifying viral infections in cell lines is difficult. Currently, there are no established methods or tools available for detecting viral infections in cell lines. To address this challenge, we developed a tool called ViralCellDetector that detects viruses through mapping RNA-seq data to a library of virus genome. Using this tool, we observed that around 10% of experiments with the MCF7 cell line were likely infected with viruses. Furthermore, to facilitate the detection of samples with unknown sources of viral infection, we identified the differentially expressed genes involved in viral infection from two different cell lines and used these genes in a machine learning approach to classify infected samples based on the host response gene expression biomarkers. Our model reclassifies the infected and non-infected samples with an AUC of 0.91 and an accuracy of 0.93. Overall, our mapping- and marker-based approaches can detect viral infections in any cell line simply based on readily accessible RNA-seq data, allowing researchers to avoid the use of unintentionally infected cell lines in their studies.

A multi-omics dataset of human transcriptome and proteome stable reference

The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine.

Design, execution, and interpretation of plant RNA-seq analyses

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

LENS: Landscape of Effective Neoantigens Software

MOTIVATION

Elimination of cancer cells by T cells is a critical mechanism of anti-tumor immunity and cancer immunotherapy response. T cells recognize cancer cells by engagement of T cell receptors with peptide epitopes presented by major histocompatibility complex molecules on the cancer cell surface. Peptide epitopes can be derived from antigen proteins coded for by multiple genomic sources. Bioinformatics tools used to identify tumor-specific epitopes via analysis of DNA and RNA-sequencing data have largely focused on epitopes derived from somatic variants, though a smaller number have evaluated potential antigens from other genomic sources.

RESULTS

We report here an open-source workflow utilizing the Nextflow DSL2 workflow manager, Landscape of Effective Neoantigens Software (LENS), which predicts tumor-specific and tumor-associated antigens from single nucleotide variants, insertions and deletions, fusion events, splice variants, cancer-testis antigens, overexpressed self-antigens, viruses, and endogenous retroviruses. The primary advantage of LENS is that it expands the breadth of genomic sources of discoverable tumor antigens using genomics data. Other advantages include modularity, extensibility, ease of use, and harmonization of relative expression level and immunogenicity prediction across multiple genomic sources. We present an analysis of 115 acute myeloid leukemia samples to demonstrate the utility of LENS. We expect LENS will be a valuable platform and resource for T cell epitope discovery bioinformatics, especially in cancers with few somatic variants where tumor-specific epitopes from alternative genomic sources are an elevated priority.

AVAILABILITY AND IMPLEMENTATION

More information about LENS, including code, workflow documentation, and instructions, can be found at (https://gitlab.com/landscape-of-effective-neoantigens-software).

An Automated Strategy to Handle Antigenic Variability in Immunisation Protocols, Part I: Nanopore Sequencing of Infectious Agent Variants

Infectious agents often challenge therapeutics, from antibiotics resistance to antigenic variability affecting inoculation measures. Over the last decades, genome sequencing arose as an important ally to address such challenges. In bacterial infection, whole-genome-sequencing (WGS) supports tracking pathogenic alterations affecting the human microbiome. In viral infection, the analysis of the relevant sequence of nucleotides helps with determining historical variants of a virus and elucidates details about infection clusters and their distribution. Additionally, genome sequencing is now an important step in inoculation protocols, isolating target genes to design more robust immunisation assays. Ultimately, genetic engineering has empowered repurposing at scale, allowing long-lasting repeating clinical trials to be automated within a much shorter time-frame, by adjusting existing protocols. This is particularly important during sanitary emergencies as the ones caused by the 2014 West African Ebola outbreak, the Zika virus rapid spread in both South and North America in 2015, followed by Asia in 2016, and the pandemic caused by the SARS-CoV-2, which has infected more than 187 million people and caused more than 4 million deaths, worldwide, as per July 2021 statistics. In this scenery, this chapter presents a novel fully automated strategy to handle antigenic variability in immunisation protocols. The methodology comprises of two major steps (1) nanopore sequencing of infectious agent variants - the focus is on the SARS-CoV-2 and its variants; followed by (2) mRNA vector design for immunotherapy. This chapter presents the nanopore sequencing step and Chapter 17 introduces a protocol for mRNA vector design.

Forensic Analysis of Novel SARS2r-CoV Identified in Game Animal Datasets in China Shows Evolutionary Relationship to Pangolin GX CoV Clade and Apparent Genetic Experimentation

Pangolins are the only animals other than bats proposed to have been infected with SARS-CoV-2 related coronaviruses (SARS2r-CoVs) prior to the COVID-19 pandemic. Here, we examine the novel SARS2r-CoV we previously identified in game animal metatranscriptomic datasets sequenced by the Nanjing Agricultural University in 2022, and find that sections of the partial genome phylogenetically group with Guangxi pangolin CoVs (GX PCoVs), while the full RdRp sequence groups with bat-SL-CoVZC45. While the novel SARS2r-CoV is found in 6 pangolin datasets, it is also found in 10 additional NGS datasets from 5 separate mammalian species and is likely related to contamination by a laboratory researched virus. Absence of bat mitochondrial sequences from the datasets, the fragmentary nature of the virus sequence and the presence of a partial sequence of a cloning vector attached to a SARS2r-CoV read suggests that it has been cloned. We find that NGS datasets containing the novel SARS2r-CoV are contaminated with significant Homo sapiens genetic material, and numerous viruses not associated with the host animals sampled. We further identify the dominant human haplogroup of the contaminating H. sapiens genetic material to be F1c1a1, which is of East Asian provenance. The association of this novel SARS2r-CoV with both bat CoV and the GX PCoV clades is an important step towards identifying the origin of the GX PCoVs.

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

Simple Summary

DNA repair pathways have been implicated in hepatocellular carcinoma outcomes. We found that hepatocellular carcinomas (HCC) could be separated into two groups (high and low) based on the overall expression of genes involved in DNA repair. Among the low repair group, there were three subgroups, one of which shared features of the high repair group. Given the important role of liver in metabolism and detoxification and its regenerative capacity, proliferation and DNA damage responses are critical in subdividing major biological categories of liver tumors. High repair samples showed more proliferative and regenerative signatures and had poorer outcomes versus the low repair that were more associated with the genes involved in normal liver biology. These biological groups suggest that dysregulation in endogenous liver processes promotes a pro-tumorigenic microenvironment that may facilitate tumor progression or identify tumors that require more substantial clinical intervention.

Abstract

DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

Virus finding tools: current solutions and limitations

MOTIVATION

The study of the Human Virome remains challenging nowadays. Viral metagenomics, through high-throughput sequencing data, is the best choice for virus discovery. The metagenomics approach is culture-independent and sequence-independent, helping search for either known or novel viruses. Though it is estimated that more than 40% of the viruses found in metagenomics analysis are not recognizable, we decided to analyze several tools to identify and discover viruses in RNA-seq samples.

RESULTS

We have analyzed eight Virus Tools for the identification of viruses in RNA-seq data. These tools were compared using a synthetic dataset of 30 viruses and a real one. Our analysis shows that no tool succeeds in recognizing all the viruses in the datasets. So we can conclude that each of these tools has pros and cons, and their choice depends on the application domain.

AVAILABILITY

Synthetic data used through the review and raw results of their analysis can be found at https://zenodo.org/record/6426147. FASTQ files of real data can be found in GEO (https://www.ncbi.nlm.nih.gov/gds) or ENA (https://www.ebi.ac.uk/ena/browser/home). Raw results of their analysis can be downloaded from https://zenodo.org/record/6425917.

Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets

The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.

Injection site vaccinology of a recombinant vaccinia-based vector reveals diverse innate immune signatures

Poxvirus systems have been extensively used as vaccine vectors. Herein a RNA-Seq analysis of intramuscular injection sites provided detailed insights into host innate immune responses, as well as expression of vector and recombinant immunogen genes, after vaccination with a new multiplication defective, vaccinia-based vector, Sementis Copenhagen Vector. Chikungunya and Zika virus immunogen mRNA and protein expression was associated with necrosing skeletal muscle cells surrounded by mixed cellular infiltrates. The multiple adjuvant signatures at 12 hours post-vaccination were dominated by TLR3, 4 and 9, STING, MAVS, PKR and the inflammasome. Th1 cytokine signatures were dominated by IFNγ, TNF and IL1β, and chemokine signatures by CCL5 and CXCL12. Multiple signatures associated with dendritic cell stimulation were evident. By day seven, vaccine transcripts were absent, and cell death, neutrophil, macrophage and inflammation annotations had abated. No compelling arthritis signatures were identified. Such injection site vaccinology approaches should inform refinements in poxvirus-based vector design.

Poxvirus vector systems have been widely developed for vaccine applications. Despite considerable progress, so far only one recombinant poxvirus vectored vaccine has to date been licensed for human use, with ongoing efforts seeking to enhance immunogenicity whilst minimizing reactogenicity. The latter two characteristics are often determined by early post-vaccination events at the injection site. We therefore undertook an injection site vaccinology approach to analyzing gene expression at the vaccination site after intramuscular inoculation with a recombinant, multiplication defective, vaccinia-based vaccine. This provided detailed insights into inter alia expression of vector-encoded immunoregulatory genes, as well as host innate and adaptive immune responses. We propose that such injection site vaccinology can inform rational vaccine vector design, and we discuss how the information and approach elucidated herein might be used to improve immunogenicity and limit reactogenicity of poxvirus-based vaccine vector systems.

Infection of human Nasal Epithelial Cells with SARS-CoV-2 and a 382-nt deletion isolate lacking ORF8 reveals similar viral kinetics and host transcriptional profiles

The novel coronavirus SARS-CoV-2 is the causative agent of Coronavirus Disease 2019 (COVID-19), a global healthcare and economic catastrophe. Understanding of the host immune response to SARS-CoV-2 is still in its infancy. A 382-nt deletion strain lacking ORF8 (Δ382 herein) was isolated in Singapore in March 2020. Infection with Δ382 was associated with less severe disease in patients, compared to infection with wild-type SARS-CoV-2. Here, we established Nasal Epithelial cells (NECs) differentiated from healthy nasal-tissue derived stem cells as a suitable model for the ex-vivo study of SARS-CoV-2 mediated pathogenesis. Infection of NECs with either SARS-CoV-2 or Δ382 resulted in virus particles released exclusively from the apical side, with similar replication kinetics. Screening of a panel of 49 cytokines for basolateral secretion from infected NECs identified CXCL10 as the only cytokine significantly induced upon infection, at comparable levels in both wild-type and Δ382 infected cells. Transcriptome analysis revealed the temporal up-regulation of distinct gene subsets during infection, with anti-viral signaling pathways only detected at late time-points (72 hours post-infection, hpi). This immune response to SARS-CoV-2 was significantly attenuated when compared to infection with an influenza strain, H3N2, which elicited an inflammatory response within 8 hpi, and a greater magnitude of anti-viral gene up-regulation at late time-points. Remarkably, Δ382 induced a host transcriptional response nearly identical to that of wild-type SARS-CoV-2 at every post-infection time-point examined. In accordance with previous results, Δ382 infected cells showed an absence of transcripts mapping to ORF8, and conserved expression of other SARS-CoV-2 genes. Our findings shed light on the airway epithelial response to SARS-CoV-2 infection, and demonstrate a non-essential role for ORF8 in modulating host gene expression and cytokine production from infected cells.

Sequencing of Historical Isolates, K-mer Mining and High Serological Cross-Reactivity with Ross River Virus Argue against the Presence of Getah Virus in Australia

Getah virus (GETV) is a mosquito-transmitted alphavirus primarily associated with disease in horses and pigs in Asia. GETV was also reported to have been isolated from mosquitoes in Australia in 1961; however, retrieval and sequencing of the original isolates (N544 and N554), illustrated that these viruses were virtually identical to the 1955 GETV_MM2021 isolate from Malaysia. K-mer mining of the >40,000 terabases of sequence data in the Sequence Read Archive followed by BLASTn confirmation identified multiple GETV sequences in biosamples from Asia (often as contaminants), but not in biosamples from Australia. In contrast, sequence reads aligning to the Australian Ross River virus (RRV) were readily identified in Australian biosamples. To explore the serological relationship between GETV and other alphaviruses, an adult wild-type mouse model of GETV was established. High levels of cross-reactivity and cross-protection were evident for convalescent sera from mice infected with GETV or RRV, highlighting the difficulties associated with the interpretation of early serosurveys reporting GETV antibodies in Australian cattle and pigs. The evidence that GETV circulates in Australia is thus not compelling.

Clinical-Forensic Autopsy Findings to Defeat COVID-19 Disease: A Literature Review

The severe acute respiratory syndrome (SARS)-CoV-2 was identified for the first time in China, in December 2019. Confirmed cases of COVID-19 have been reported around the world; indeed, this infection has been declared a pandemic. Consequently, the scientific community is working hard to gain useful information about the history of this virus, its transmission, diagnosis, clinical features, radiological findings, research and development of candidate therapeutics as well as vaccines. This review aims to analyze the diagnostic techniques used to ascertain the COVID-19 infection, critically reviewing positive points and criticism for forensic implications, obviously including autopsy. Finally, this review proposes a practical workflow to be applied in the management of corpses during this outbreak of the COVID-19 infection, which could be useful in cases of future infectious disease emergencies. Analyzing the diagnostic methods, to date, virus nucleic acid RT-PCR represents the standard method used to ascertain the COVID-19 infection in living subjects and corpses, even if this technique has several criticisms: mainly, the staff should be highly specialized, working in high-throughput settings, able to handle high workloads and aware of health risks and the importance of the results. Thus, IgG/IgM serological tests have been developed, overcoming RT-qPCR duration, costs, and management, not requiring highly trained personnel. Nevertheless, serological tests present problems; the WHO recommends the use of these new point-of-care immunodiagnostic tests only in research settings. Furthermore, nothing has yet been published regarding the possibility of applying these methods during post-mortem investigations. In light of this scenario, in this review, we suggest a flow chart for the pathologist called on to ascertain the cause of death of a subject with historical and clinical findings of COVID-19 status or without any anamnestic, diagnostic, or exposure information. Indeed, the literature data confirmed the analytical vulnerabilities of the kits used for laboratory diagnosis of COVID-19, particularly during postmortem examinations. For these reasons, autopsy remains the gold standard method to ascertain the exact cause of death (from or with COVID-19 infection, or other causes), to consequently provide real data for statistical evaluations and to take necessary measures to contain the risks of the infection. Moreover, performing autopsies could provide information on the pathogenesis of the COVID-19 infection with obvious therapeutic implications.