SARS-CoV-2 infection and cancer: Evidence for and against a role of SARS-CoV-2 in cancer onset

IGSF1: a biomarker for predicting prognosis, immunotherapy response, and drug candidates in COVID-19 combined hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor prognosis and a common cause of cancer-related death worldwide, and despite ongoing therapeutic breakthroughs, patient survival benefits are limited. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19) and poses a major threat to humanity worldwide. As the epidemic continues to develop, more and more people are infected with SARS-CoV-2, including patients with HCC. However, the relationship between COVID-19 and HCC has not yet been fully elucidated. Our study aimed to identify the shared genetic characteristics and molecular mechanisms between COVID-19 and HCC. The data involved in this study come from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression(GTEx), and Cancer Cell Line Encyclopedia(CCLE) databases. We used differentially expressed genes to perform enrichment analysis to reveal the biological landscape of COVID-19 combined with HCC. In addition, weighted gene co-expression network analysis (WGCNA) was used to study the co-expression network related to COVID-19 and HCC. We then combined the validation datasets to screen out immunoglobulin superfamily member 1 (IGSF1) as the most important core gene. Finally, we extensively studied the functional expression of IGSF1 in tumor samples, normal tissues, and cancer cell lines. The molecular mechanisms related to COVID-19 and HCC are rarely studied. Our study identifies IGSF1 as a potential therapeutic target and immune-related biomarker for patients with COVID-19 and HCC.

A Tiny Viral Protein, SARS-CoV-2-ORF7b: Functional Molecular Mechanisms

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein-protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose.

Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways

The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.

Coronavirus disease 2019 and lung cancer: where are we?

Oncology patients are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection due to hospital contact and an immunological system that can be compromised by antineoplastic therapy and supportive treatments. Certain similarities have been described in the physiopathology of coronavirus disease 2019 (COVID-19) and lung cancer (LC) that may explain the higher probability of these patients of developing a more serious disease with more frequent hospitalizations and even death, especially with the addition of smoking, cardiovascular and respiratory comorbidities, old age and corticosteroids use. Pre-existing lesions and cancer therapies change the normal architecture of the lungs, so diagnostic scales such as COVID-19 Reporting and Data System (CO-RADS) are of vital importance for a correct diagnosis and patient homogenization, with a high inter-observer correlation. Moreover, anticancer treatments have required an adaptation to reduce the number of visits to the hospital [hypofractionated radiotherapy (RT), larger intervals between chemotherapy cycles, delay in follow-up tests, among others]. In a way, this has also caused a delay in the diagnosis of new cancers. On the other hand, vaccination has had a positive impact on the mortality of these patients, who maintain a similar seroprevalence to the rest of the population, with a similar impact in mortality.

Possible cancer-causing capacity of COVID-19: Is SARS-CoV-2 an oncogenic agent?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown diverse life-threatening effects, most of which are considered short-term. In addition to its short-term effects, which has claimed many millions of lives since 2019, the long-term complications of this virus are still under investigation. Similar to many oncogenic viruses, it has been hypothesized that SARS-CoV-2 employs various strategies to cause cancer in different organs. These include leveraging the renin angiotensin system, altering tumor suppressing pathways by means of its nonstructural proteins, and triggering inflammatory cascades by enhancing cytokine production in the form of a "cytokine storm" paving the way for the emergence of cancer stem cells in target organs. Since infection with SARS-CoV-2 occurs in several organs either directly or indirectly, it is expected that cancer stem cells may develop in multiple organs. Thus, we have reviewed the impact of coronavirus disease 2019 (COVID-19) on the vulnerability and susceptibility of specific organs to cancer development. It is important to note that the cancer-related effects of SARS-CoV-2 proposed in this article are based on the ability of the virus and its proteins to cause cancer but that the long-term consequences of this infection will only be illustrated in the long run.

Characterizing the key genes of COVID-19 that regulate tumor immune microenvironment and prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a highly heterogeneous malignant tumor associated with a poor prognosis, is a common cause of cancer-related deaths worldwide, with a limited survival benefit for patients despite ongoing therapeutic breakthroughs. Coronavirus disease 2019 (COVID-19), a severe infectious disease caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), is a global pandemic and a serious threat to human health. The increased susceptibility to SARS-CoV-2 infection and a poor prognosis in patients with cancer necessitate the exploration of the potential link between the two. No studies have investigated the relationship of COVID-19 genes with the prognosis and tumor development in patients with HCC. We screened prognosis-related COVID-19 genes in HCC, performed molecular typing, developed a stable and reliable COVID-19 genes signature for predicting survival, characterized the immune microenvironment in HCC patients, and explored new molecular therapeutic targets. Datasets of HCC patients, including RNA sequencing data and clinical information, were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Prognosis-related COVID-19 genes were identified by univariate Cox analysis. Molecular typing of HCC was performed using the consensus non-negative matrix factorization method (cNMF), followed by the analysis of survival, tumor microenvironment, and pathway enrichment for each subtype. Prognostic signatures were constructed using LASSO-Cox regression models, and receiver operating characteristic (ROC) curves were used to validate the predictive performance of the signature. The same approach was used for the test and external validation sets. Seven software packages were applied to determine the abundance of immune infiltration in HCC patients and investigate its relationship with the risk scores. Gene set enrichment analysis (GSEA) was used to explore the potential mechanisms by which the COVID-19 genes affect hepatocarcinogenesis and prognosis. Three types of machine learning methods were combined to identify the most critical genes in the signature and localize their expression at the single cell level. We identified 53 prognosis-related COVID-19 genes and classified HCC into two molecular subtypes (C1, C2) by using the NMF method. The prognosis of C2 was significantly better than that of C1, and the two subtypes differed remarkably in terms of the tumor immune microenvironment and biological functions. The 17 COVID-19 genes were screened using the LASSO regression method to develop a 17 COVID-19 genes signature, which demonstrated a good predictive performance for 1-, 2- and 3-year OS of patients with HCC. The risk score as an independent prognostic factor for HCC has better predictive accuracy than traditional clinical variables. Patients in the TCGA cohort were categorized by risk score into the high- and low-risk groups, with the high-risk group mainly enriched in the immune modulation-related pathways and the low-risk group mainly enriched in the metabolism-related pathways, suggesting that the COVID-19 genes may affect disease progression and prognosis by regulating the tumor immune microenvironment and metabolism in HCC. NOL10 was identified as the most critical gene in the signature and hypothesized to be a potential therapeutic target for HCC. Objectively, the COVID-19 genes signature developed in this study, as an independent prognostic factor in HCC patients, is closely associated with the prognosis and tumor immune microenvironment of HCC patients and indicates that they may regulate the development of HCC in multiple ways, providing us with new perspectives for understanding the molecular mechanisms of HCC and finding effective therapeutic targets.

Deciphering the Relationship between SARS-CoV-2 and Cancer

Some viruses are known to be associated with the onset of specific cancers. These microorganisms, oncogenic viruses or oncoviruses, can convert normal cells into cancer cells by modulating the central metabolic pathways or hampering genomic integrity mechanisms, consequently inhibiting the apoptotic machinery and/or enhancing cell proliferation. Seven oncogenic viruses are known to promote tumorigenesis in humans: human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV), Epstein-Barr virus (EBV), human T-cell leukemia virus 1 (HTLV-1), Kaposi sarcoma-associated herpesvirus (KSHV), and Merkel cell polyomavirus (MCPyV). Recent research indicates that SARS-CoV-2 infection and COVID-19 progression may predispose recovered patients to cancer onset and accelerate cancer development. This hypothesis is based on the growing evidence regarding the ability of SARS-CoV-2 to modulate oncogenic pathways, promoting chronic low-grade inflammation and causing tissue damage. Herein, we summarize the main relationships known to date between virus infection and cancer, providing a summary of the proposed biochemical mechanisms behind the cellular transformation. Mechanistically, DNA viruses (such as HPV, HBV, EBV, and MCPyV) encode their virus oncogenes. In contrast, RNA viruses (like HCV, HTLV-1) may encode oncogenes or trigger host oncogenes through cis-/-trans activation leading to different types of cancer. As for SARS-CoV-2, its role as an oncogenic virus seems to occur through the inhibition of oncosuppressors or controlling the metabolic and autophagy pathways in the infected cells. However, these effects could be significant in particular scenarios like those linked to severe COVID-19 or long COVID. On the other hand, looking at the SARS-CoV-2─cancer relationship from an opposite perspective, oncolytic effects and anti-tumor immune response were triggered by SARS-CoV-2 infection in some cases. In summary, our work aims to recall comprehensive attention from the scientific community to elucidate the effects of SARS-CoV-2 and, more in general, β-coronavirus infection on cancer susceptibility for cancer prevention or supporting therapeutic approaches.

Innate Immune Recognition, Integrated Stress Response, Infection, and Tumorigenesis

Engagement of PRRs in recognition of PAMPs or DAMPs is one of the processes that initiates cellular stress. These sensors are involved in signaling pathways leading to induction of innate immune processes. Signaling initiated by PRRs is associated with the activation of MyD88-dependent signaling pathways and myddosome formation. MyD88 downstream signaling depends upon the context of signaling initiation, the cell (sub)type and the microenvironment of signal initiation. Recognition of PAMPs or DAMPs through PRRs activates the cellular autonomous defence mechanism, which orchestrates the cell responses to resolve specific insults at the single cell level. In general, stressed endoplasmic reticulum is directly linked with the induction of autophagy and initiation of mitochondrial stress. These processes are regulated by the release of Ca2+ from ER stores accepted by mitochondria, which respond through membrane depolarization and the production of reactive oxygen species generating signals leading to inflammasome activation. In parallel, signaling from PRRs initiates the accumulation of misfolded or inappropriately post-translationally modified proteins in the ER and triggers a group of conserved emergency rescue pathways known as unfolded protein response. The cell-autonomous effector mechanisms have evolutionarily ancient roots and were gradually specialized for the defence of specific cell (sub)types. All of these processes are common to the innate immune recognition of microbial pathogens and tumorigenesis as well. PRRs are active in both cases. Downstream are activated signaling pathways initiated by myddosomes, translated by the cellular autonomous defence mechanism, and finalized by inflammasomes.

Should We Expect an Increase in the Number of Cancer Cases in People with Long COVID?

The relationship between viral infections and the risk of developing cancer is well known. Multiple mechanisms participate in and determine this process. The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in the deaths of millions of people worldwide. Although the effects of COVID-19 are limited for most people, a large number of people continue to show symptoms for a long period of time (long COVID). Several studies have suggested that cancer could also be a potential long-term complication of the virus; however, the causes of this risk are not yet well understood. In this review, we investigated arguments that could support or reject this possibility.

PHEVIR: an artificial intelligence algorithm that predicts the molecular role of pathogens in complex human diseases

Infectious diseases are known to cause a wide variety of post-infection complications. However, it's been challenging to identify which diseases are most associated with a given pathogen infection. Using the recently developed LeMeDISCO approach that predicts comorbid diseases associated with a given set of putative mode of action (MOA) proteins and pathogen-human protein interactomes, we developed PHEVIR, an algorithm which predicts the corresponding human disease comorbidities of 312 viruses and 57 bacteria. These predictions provide an understanding of the molecular bases of complications and means of identifying appropriate drug targets to treat them. As an illustration of its power, PHEVIR is applied to identify putative driver pathogens and corresponding human MOA proteins for Type 2 diabetes, atherosclerosis, Alzheimer's disease, and inflammatory bowel disease. Additionally, we explore the origins of the oncogenicity/oncolyticity of certain pathogens and the relationship between heart disease and influenza. The full PHEVIR database is available at https://sites.gatech.edu/cssb/phevir/ .

An improved Fuzzy based GWO algorithm for predicting the potential host receptor of COVID-19 infection

Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has infected millions worldwide. SARS-CoV-2 spike protein uses Angiotensin-converting enzyme 2 (ACE2) and Transmembrane serine protease 2 (TMPRSS2) for entering and fusing the host cell membrane. However, interaction with spike protein receptors and protease processing are not the only factors determining coronaviruses' entry. Several proteases mediate the entry of SARS-CoV-2 virus into the host cell. Identifying receptor factors helps understand tropism, transmission, and pathogenesis of COVID-19 infection in humans. The paper aims to identify novel viral receptor or membrane proteins that are transcriptionally and biologically similar to ACE2 and TMPRSS2 through a fuzzy clustering technique that employs the Grey wolf optimizer (GWO) algorithm for finding the optimal cluster center. The exploratory and exploitation capability of GWO algorithm is improved by hybridizing mutation and crossover operators of the evolutionary algorithm. Also, the genetic diversity of the grey wolf population is enhanced by eliminating weak individuals from the population. The proposed clustering algorithm's effectiveness is shown by detecting novel viral receptors and membrane proteins associated with the pathogenesis of SARS-CoV-2 infection. The expression profiles of ACE2 protein and its co-receptor factor are analyzed and compared with single-cell transcriptomics profiling using the Seurat R toolkit, mass spectrometry (MS), and immunohistochemistry (IHC). Our advanced clustering method infers that cell that expresses high ACE2 level are more affected by SARS-CoV-infection. So, SARS-CoV-2 virus affects lung, intestine, testis, heart, kidney, and liver more severely than brain, bone marrow, skin, spleen, etc. We have identified 58 novel viral receptors and 816 membrane proteins, and their role in the pathogenicity mechanism of SARS-CoV-2 infection has been studied. Besides, our study confirmed that Neuropilins (NRP1), G protein-coupled receptor 78 (GPR78), C-type lectin domain family 4 member M (CLEC4M), Kringle containing transmembrane protein 1 (KREMEN1), Asialoglycoprotein receptor 1 (ASGR1), A Disintegrin and metalloprotease 17 (ADAM17), Furin, Neuregulin-1,(NRG1), Basigin or CD147 and Poliovirus receptor (PVR) are the potential co-receptors of SARS-CoV-2 virus. A significant finding is that heparin derivative glycosaminoglycans could block the replication of SARS-CoV-2 virus inside the host cytoplasm. The membrane protein N-Deacetylase/N-Sulfotransferase-2 (NDST2), Extostosin protein (EXT1, EXT2, and EXT3), Glucuronic acid epimerase (GLCE), and Xylosyltransferase I, II (XYLT1, XYLT2) could act as the therapeutic target for inhibiting the spread of SARS-CoV-2 infection. Drugs such as carboplatin and gemcitabine are effective in such situations.

Immune mechanisms in cancer patients that lead to poor outcomes of SARS-CoV-2 infection

Patients with cancers have been severely affected by the COVID-19 pandemic. This is highlighted by the adverse outcomes in cancer patients with COVID-19 as well as by the impact of the COVID-19 pandemic on cancer care. Patients with cancer constitute a heterogeneous population that exhibits distinct mechanisms of immune dysfunction, associated with distinct systemic features of hot (T-cell-inflamed/infiltrated) and cold (Non-T-cell-inflamed and/or infiltrated) tumors. The former show hyper immune activated cells and a highly inflammatory environment while, contrastingly, the latter show the profile of a senescent and/or quiescent immune system. Thus, the evolution of SARS-CoV-2 infection in different types of cancers can show distinct trajectories which could lead to a variety of clinical and pathophysiological outcomes. The altered immunological environment including cytokines that characterizes hot and cold tumors will lead to different mechanisms of immune dysfunction, which will result in downstream effects on the course of SARS-CoV-2 infection. This review will focus on defining the known contributions of soluble pro- and anti-inflammatory mediators on immune function including altered T-cells and B-cells responses and as well on how these factors modulate the expression of SARS-CoV-2 receptor ACE2, TMPRSS2 expression, and lymph node fibrosis in cancer patients. We will propose immune mechanisms that underlie the distinct courses of SARS-CoV-2 infection in cancer patients and impact on the success of immune based therapies that have significantly improved cancer outcomes. Better understanding of the immune mechanisms prevalent in cancer patients that are associated to the outcomes of SARS-CoV-2 infection will help to identify the high-risk cancer patients and develop immune-based approaches to prevent significant adverse outcomes by targeting these pathways.

Therapeutic benefits of Salvia species: A focus on cancer and viral infection

Man is increasingly being faced with many health conditions, including viral infection, some of which increases the risk to cancer. These infectious agents contribute to the large number of persons with cancer and the worrisome number that die from the diseases. A good range of drugs are currently in place for treating patients infected with viruses, however, some of the drugs' effectiveness are limited by the emergence of drug-resistant strains of the viruses, as well as adverse effects of the drugs. Similarly, the inability of many anticancer drugs to selectively kill cancer cells while sparing hosts' normal cells limit their use. This warrants more research for newer drugs, especially from chemicals naturally encrypted in plants with anticancer and antiviral activities. In response to infection with cancer-inducing viruses, plants such as Salvia species synthesize and store secondary metabolites to protect themselves and kill these viruses as well as inhibit their ability to induce carcinogenesis. Hence, this review presented a discussion on the potential application of Salvia species in the prevention and management of cancer and viral infection. The study also discusses the cellular mechanisms of action of these herbal products against cancer cells and viruses, where available and provided suggestions on future research directions. The study is believed to spur more research on how to exploit Salvia phytochemicals as candidates for the development of nutraceuticals and drugs for managing cancers and viral infection.

Charting the Unknown Association of COVID-19 with Thyroid Cancer, Focusing on Differentiated Thyroid Cancer: A Call for Caution

BACKGROUND

Conceived of as the "silver lining" of the dark cloud of the coronavirus disease 2019 (COVID-19) pandemic, lessons taught by this catastrophe should be leveraged by medical authorities and policy makers to optimize health care globally. A major lesson is that resilient health systems should absorb sudden shocks incited by overwhelming health emergencies without compromising the continuum of care of chronic diseases, especially of cancer.

METHODS

The present review dissects the association between COVID-19 and thyroid cancer (TC), especially with differentiated TC (DTC), focusing on available data, knowledge gaps, current challenges, and future perspectives.

RESULTS

Obesity has been incriminated in terms of both COVID-19 severity and a rising incidence of TC, especially of DTC. The current conceptualization of the pathophysiological landscape of COVID-19-(D)TC association implicates an interplay between obesity, inflammation, immunity, and oxidative stress. Whether COVID-19 could aggravate the health burden posed by (D)TC or vice versa has yet to be clarified. Improved understanding and harnessing of the pathophysiological landscape of the COVID-19-(D)TC association will empower a mechanism-guided, safe, evidence-based, and risk-stratified management of (D)TC in the COVID-19 era and beyond.

CONCLUSION

A multidisciplinary patient-centered decision-making will ensure high-quality (D)TC care for patients, with or without COVID-19.

SARS-CoV-2 Exposed Mesenchymal Stromal Cell from Congenital Pulmonary Airway Malformations: Transcriptomic Analysis and the Expression of Immunomodulatory Genes

The inflammatory response plays a central role in the complications of congenital pulmonary airway malformations (CPAM) and severe coronavirus disease 2019 (COVID-19). The aim of this study was to evaluate the transcriptional changes induced by SARS-CoV-2 exposure in pediatric MSCs derived from pediatric lung (MSCs-lung) and CPAM tissues (MSCs-CPAM) in order to elucidate potential pathways involved in SARS-CoV-2 infection in a condition of exacerbated inflammatory response. MSCs-lung and MSCs-CPAM do not express angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TRMPSS2). SARS-CoV-2 appears to be unable to replicate in MSCs-CPAM and MSCs-lung. MSCs-lung and MSCs-CPAM maintained the expression of stemness markers MSCs-lung show an inflammatory response (IL6, IL1B, CXCL8, and CXCL10), and the activation of Notch3 non-canonical pathway; this route appears silent in MSCs-CPAM, and cytokine genes expression is reduced. Decreased value of p21 in MSCs-lung suggested no cell cycle block, and cells did not undergo apoptosis. MSCs-lung appears to increase genes associated with immunomodulatory function but could contribute to inflammation, while MSCs-CPAM keeps stable or reduce the immunomodulatory receptors expression, but they also reduce their cytokines expression. These data indicated that, independently from their perilesional or cystic origin, the MSCs populations already present in a patient affected with CPAM are not permissive for SARS-CoV-2 entry, and they will not spread the disease in case of infection. Moreover, these MSCs will not undergo apoptosis when they come in contact with SARS-CoV-2; on the contrary, they maintain their staminality profile.