Cancer progression in COVID-19: integrating the roles of renin angiotensin aldosterone system, angiopoietin-2, heat shock protein-27 and epithelial mesenchymal transition

Oncogenic potential of SARS-CoV-2-targeting hallmarks of cancer pathways

The 2019 outbreak of SARS-CoV-2 has caused a major worldwide health crisis with high rates of morbidity and death. Interestingly, it has also been linked to cancer, which begs the issue of whether it plays a role in carcinogenesis. Recent studies have revealed various mechanisms by which SARS-CoV-2 can influence oncogenic pathways, potentially promoting cancer development. The virus encodes several proteins that alter key signaling pathways associated with cancer hallmarks. Unlike classical oncogenic viruses, which transform cells through viral oncogenes or by activating host oncogenes, SARS-CoV-2 appears to promote tumorigenesis by inhibiting tumor suppressor genes and pathways while activating survival, proliferation, and inflammation-associated signaling cascades. Bioinformatic analyses and experimental studies have identified numerous interactions between SARS-CoV-2 proteins and cellular components involved in cancer-related processes. This review explores the intricate relationship between SARS-CoV-2 infection and cancer, focusing on the regulation of key hallmarks driving initiation, promotion and progression of cancer by viral proteins. By elucidating the underlying mechanisms driving cellular transformation, the potential of SARS-CoV-2 as an oncovirus is highlighted. Comprehending these interplays is essential to enhance our understanding of COVID-19 and cancer biology and further formulating strategies to alleviate SARS-CoV-2 influence on cancer consequences.

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.

The alternative renin-angiotensin-system (RAS) signalling pathway in prostate cancer and its link to the current COVID-19 pandemic

BACKGROUND

The renin-angiotensin system is known to maintain blood pressure and body fluids. However, it has been found to consist of at least two major constituents, the classic and the alternative pathway, balancing and supporting each other's signalling in a very intricate way. Current research has shown that the renin-angiotensin system is involved in a broad range of biological processes and diseases, such as cancer and infectious diseases.

METHODS AND RESULTS

We conducted a literature review on the interaction of the renin-angiotensin system and prostate cancer and explored the research on the possible impact of the SARS-CoV-2 virus in this context. This review provides an update on contemporary knowledge into the alternative renin-angiotensin system, its role in cancer, specifically prostate cancer, and the implications of the current COVID-19 pandemic on cancer and cancer care.

CONCLUSION

In this work, we aim to demonstrate how shifting the RAS signalling pathway from the classic to the alternative axis seems to be a viable option in supporting treatment of specific cancers and at the same time demonstrating beneficial properties in supportive care. It however seems to be the case that the infection with SARS-CoV-2 and subsequent impairment of the renin-angiotensin-system could exhibit serious deleterious long-term effects even in oncology.

COVID-19 vs. Cancer Immunosurveillance: A Game of Thrones within an Inflamed Microenviroment

The COVID-19 pandemic accounts for more than 500 million confirmed infections and over 6 million deaths worldwide in the last 2 years. SARS-CoV-2 causes a highly complex form of inflammation that affects the human organism both acutely and chronically. In the same line, cancer as an inflammation-induced and immune-editing disease appears to cross-react with immune system at different levels including early interactions during carcinogenesis and later cross-talks within the tumor microenvironment. With all that in mind, a reasonable question one might address is whether the SARS-CoV-2 infection and the derived "long lasting inflammatory status" that is frequently observed in patients, might affect the cancer immunosurveillance mechanisms and consequently their risk of developing cancer, as well as the tumor and immune cell behaviors within the inflamed microenvironment. On this context, this review intends to outline and discuss the existing knowledge on SARS-CoV-2-mediated immunomodulation under the prism of changes that might be able to interfere with cancer cell immunoescape and the overall tumor progression and response to conventional therapeutics. Our goal is to highlight a potential interplay between the COVID-19 immunopathology and cancer immune-microenvironment that may pave the way for thorough investigation in the future.

Host cell stress response as a predictor of COVID-19 infectivity and disease progression

The coronavirus disease (COVID-19) caused by a coronavirus identified in December 2019 has caused a global pandemic. COVID-19 was declared a pandemic in March 2020 and has led to more than 6.3 million deaths. The pandemic has disrupted world travel, economies, and lifestyles worldwide. Although vaccination has been an effective tool to reduce the severity and spread of the disease there is a need for more concerted approaches to fighting the disease. COVID-19 is characterised as a severe acute respiratory syndrome . The severity of the disease is associated with a battery of comorbidities such as cardiovascular diseases, cancer, chronic lung disease, and renal disease. These underlying diseases are associated with general cellular stress. Thus, COVID-19 exacerbates outcomes of the underlying conditions. Consequently, coronavirus infection and the various underlying conditions converge to present a combined strain on the cellular response. While the host response to the stress is primarily intended to be of benefit, the outcomes are occasionally unpredictable because the cellular stress response is a function of complex factors. This review discusses the role of the host stress response as a convergent point for COVID-19 and several non-communicable diseases. We further discuss the merits of targeting the host stress response to manage the clinical outcomes of COVID-19.

SARS-CoV-2 and cancer: the intriguing and informative cross-talk

The COVID-19 pandemic caused by the SARS-CoV-2 virus has significantly disrupted and burdened the diagnostic workup and delivery of care, including transfusion, to cancer patients across the globe. Furthermore, cancer patients suffering from solid tumors or hematologic malignancies were more prone to the infection and had higher morbidity and mortality than the rest of the population. Major signaling pathways have been identified at the intersection of SARS-CoV-2 and cancer cells, often leading to tumor progression or alteration of the tumor response to therapy. The reactivation of oncogenic viruses has also been alluded to in the context and following COVID-19. Paradoxically, certain tumors responded better following the profound infection-induced immune modulation. Unveiling the mechanisms of the virus-tumor cell interactions will lead to a better understanding of the pathophysiology of both cancer progression and virus propagation. It would be challenging to monitor, through the different cancer registries, retrospectively, the response of patients who have been previously exposed to the virus in contrast to those who have not contracted the infection.

On the origin of metastases: Induction of pro-metastatic states after impending cell death via ER stress, reprogramming, and a cytokine storm

How metastatic cells arise is unclear. Here, we search for the induction of recently characterized pro-metastatic states as a surrogate for the origin of metastasis. Since cell-death-inducing therapies can paradoxically promote metastasis, we ask if such treatments induce pro-metastatic states in human colon cancer cells. We find that post-near-death cells acquire pro-metastatic states (PAMEs) and form distant metastases in vivo. These PAME ("let's go" in Greek) cells exhibit a multifactorial cytokine storm as well as signs of enhanced endoplasmic reticulum (ER) stress and nuclear reprogramming, requiring CXCL8, INSL4, IL32, PERK-CHOP, and NANOG. PAMEs induce neighboring tumor cells to become PAME-induced migratory cells (PIMs): highly migratory cells that re-enact the storm and enhance PAME migration. Metastases are thus proposed to originate from the induction of pro-metastatic states through intrinsic and extrinsic cues in a pro-metastatic tumoral ecosystem, driven by an impending cell-death experience involving ER stress modulation, metastatic reprogramming, and paracrine recruitment via a cytokine storm.

ARID1A knockdown enhances carcinogenesis features and aggressiveness of Caco-2 colon cancer cells: An in vitro cellular mechanism study

Loss of ARID1A, a tumor suppressor gene, is associated with the higher grade of colorectal cancer (CRC). However, molecular and cellular mechanisms underlying the progression and aggressiveness of CRC induced by the loss of ARID1A remain poorly understood. Herein, we evaluated cellular mechanisms underlying the effects of ARID1A knockdown on the carcinogenesis features and aggressiveness of CRC cells. A human CRC cell line (Caco-2) was transfected with small interfering RNA (siRNA) specific to ARID1A (siARID1A) or scrambled (non-specific) siRNA (siControl). Cell death, proliferation, senescence, chemoresistance and invasion were then evaluated. In addition, formation of polyploid giant cancer cells (PGCCs), self-aggregation (multicellular spheroid) and secretion of an angiogenic factor, vascular endothelial growth factor (VEGF), were examined. The results showed that ARID1A knockdown led to significant decreases in cell death and senescence. On the other hand, ARID1A knockdown enhanced cell proliferation, chemoresistance and invasion. The siARID1A-transfected cells also had greater number of PGCCs and larger spheroid size and secreted greater level of VEGF compared with the siControl-transfected cells. These data, at least in part, explain the cellular mechanisms of ARID1A deficiency in carcinogenesis and aggressiveness features of CRC.

COVID-19 patients' sera induce epithelial mesenchymal transition in cancer cells

Covid-19 Pneumonia of SARS-CoV-2 pandemic infection, persists to have high disease burden especially in cancer patients. Increased inflammation and thromboembolic processes are blamed to influence cancer patients more than the others but due to lack of knowledge regarding the pathophysiology of the both the virus itself and the response of the host, more basic and translational disease modeling research is needed to understand Cancer-Covid-19 interaction. In this study, serum samples from the patients, who were hospitalized due to Covid-19 pneumonia, applied to different cancer cells and cytotoxicity, motility, proliferation and gene expression analysis were performed. Serum samples derived from healthy volunteers and the fetal bovine serum that is used regularly in cell culture experiments used as controls. Hospitalized Covid-19 patients who had also cancer, were retrospectively screened, and their clinical course were recorded. Overall 12 Patient (PS) and 4 healthy serums (CS) were included in the experiments. PS applied cells showed increased motility in A549 cells as well as lost cell to cell connection in MCF7 and HCT116 cells, and induced expression of VIM, ZEB1 and SNAIL2 mRNA levels. Eight cancer diagnosed patients who were hospitalized due to Covid-19 between April and September 2020 were also reviewed retrospectively, which 5 of them were dead during SARS-CoV-2 infection. Thorax CT images of the 2 patients showed increased metastatic nodules in the lungs as of January 2021. The results of the study indicate that metastasis may be one of the prolonged consequences of COVID-19 pandemic in cancer sufferers.

Machine Learning Assisted Prediction of Prognostic Biomarkers Associated With COVID-19, Using Clinical and Proteomics Data

With the availability of COVID-19-related clinical data, healthcare researchers can now explore the potential of computational technologies such as artificial intelligence (AI) and machine learning (ML) to discover biomarkers for accurate detection, early diagnosis, and prognosis for the management of COVID-19. However, the identification of biomarkers associated with survival and deaths remains a major challenge for early prognosis. In the present study, we have evaluated and developed AI-based prediction algorithms for predicting a COVID-19 patient's survival or death based on a publicly available dataset consisting of clinical parameters and protein profile data of hospital-admitted COVID-19 patients. The best classification model based on clinical parameters achieved a maximum accuracy of 89.47% for predicting survival or death of COVID-19 patients, with a sensitivity and specificity of 85.71 and 92.45%, respectively. The classification model based on normalized protein expression values of 45 proteins achieved a maximum accuracy of 89.01% for predicting the survival or death, with a sensitivity and specificity of 92.68 and 86%, respectively. Interestingly, we identified 9 clinical and 45 protein-based putative biomarkers associated with the survival/death of COVID-19 patients. Based on our findings, few clinical features and proteins correlate significantly with the literature and reaffirm their role in the COVID-19 disease progression at the molecular level. The machine learning-based models developed in the present study have the potential to predict the survival chances of COVID-19 positive patients in the early stages of the disease or at the time of hospitalization. However, this has to be verified on a larger cohort of patients before it can be put to actual clinical practice. We have also developed a webserver CovidPrognosis, where clinical information can be uploaded to predict the survival chances of a COVID-19 patient. The webserver is available at http://14.139.62.220/covidprognosis/.