Understanding the risk of cancer after SARS-CoV-2 infection

JGI Seed Corn Funded Project

Viral infections have the potential to alter cell’s DNA, activating carcinogenic processes and preventing the immune system from eliminating damaged cells. Since the COVID19 pandemic began there is an urge to understand the long-term health impact of SARS-CoV-2 and how it may increase the risk of cancer. 

Aims of the project

In this pilot study we used the graph database EpiGraphDB (Liu et al, Bioinformatics, 2020), an analytical platform to support research in population health data science, to link the recently mapped host-coronavirus protein interaction in SARS-CoV-2 infections with the existing knowledge of cancer biology and epidemiology. 

The main objectives of this project are: 

  • The integration of specialized data sources: the SARS-CoV-2 protein interaction map (Gordon et. al, Nature, 2020), genetic risk factors of critical illness in COVID-19 (Erola-Pairo, Nature,2021), and cancer genes (Lever et. al, Nature Methods, 2019). 
  • The reconstruction of an accessible network of plausible molecular interactions between viral targets, genetic risk factors, and known oncogenes, tumour suppressor genes and cancer drivers for relevant cancer types. 


Coronaviruses are known to target the respiratory system. We have reconstructed the molecular network for lung cancer risk, as many patients recovering from SARS-CoV-2 suffer from long-term symptoms due to damage of the walls and linings of the lungs. 

Network of the protein interactions between human gene preys targeted by SARS-CoV2, risk factors of critical illness, and known carcinogenic genes in lung cancer. 

We found 93 human genes targeted by SARS-CoV-2, represented in pink, which are oncogenic or interact with oncogenic genes. These were clustered based on high connectivity to enrich the network visualization, where each cluster is depicted as two columns, one for SARS-CoV2 interacting genes and one for cancer genes. Then we searched for molecular pathways that may be perturbed by each gene set. 

Our results suggest potential alterations in Wnt and hippo signalling pathways, two important pathways frequently linked to cancer due to their roles in cell proliferation, development and cell survival. The risk of perturbations in telomere maintenance and DNA replication may affect the integrity of the DNA favouring it’s degradation and preventing the repair of damaging events like gene fusions. There may also be a possible impact on gene function through changes in the mRNA splicing process, impeding translation into working proteins. 

We also integrated genetic risk factors of critical illness in COVID-19 into this network. Triangulating this evidence, we identified that genes IFNAR2 and TYK2 may interact with Interleukin 6 (IL6), an important gene in the regulation of host defence during infections. Also, the genetic risk factor NOTCH4 was linked to genes CCND1 and ERBB2, genes that participate in the regulation of the cell cycle and transcriptional regulation respectively, and have been associated with cancer metastasis and poor prognosis. 

Future plans for the project. 

This project highlights the potential molecular mechanisms underlying how SARS-CoV-2 may interact with cancer, especially in those patients suffering long-term and chronic illness. However, until now there is no clear evidence that SARS-CoV-2 has a causative role in cancer pathobiology. 

Future plans include extending the network with novel sources of evidence and comparing the molecular web of interactions with other oncogenic viruses, such as papillomaviruses, Epstein-Barr virus and hepatitis C, to elucidate any shared mechanisms. This knowledge will enable the development of novel therapies to target coronaviruses. 

The impact of COVID-19 on cancer incidence, both direct and on the decline of cancer care, is still unknown and further research is needed to improve our understanding about the disease and optimize cancer detection and treatment.  


This project was led by Dr Pau Erola, Professor Tom Gaunt and Professor Richard Martin. For more details about EpiGraphDB and the Integrative Cancer Epidemiology Programme programme please visit: