Steinbeis experts investigate the progression of SARS-CoV-2 infections in oncological patients as part of a consortium project
How can the oncological treatment of cancer patients with COVID-19 be optimized? This is the question posed by experts working on a project called COVID Cancer Vision, which combines world-class R&D in the field of technology with fundamental immunological research. A variety of scientific partners are pursuing a common goal for the flagship project: the Steinbeis Transfer Institute of Clinical Hematology-Oncology, the Chair of Animal Physiology and Immunology at the Technical University of Munich, the Fraunhofer Institute for Optronics, System Technology, and Image Exploitation (IOSB), and the Fraunhofer Institute for Cell Therapy and Immunology (IZI). All have joined forces with the Bavarian bioinformatics company BioVariance and the OnkoMedeor Group, a consortium of seven oncological day clinics, to work together under the auspices of Cancer Centers Dachau.
Between April 15 and 26, the team of experts carried out SARS-CoV-2 testing on all tumor patients at the day clinics. They were surprised that out of the just under 1,300 cancer patients tested for COVID-19, only 40 were positive and of these, only three showed symptoms. 37 of the 40 infected patients were thus asymptomatic carriers of COVID-19, even though most of them were currently undergoing regular chemotherapy. It was decided to continue chemotherapy treatment on all asymptomatic patients and this resulted in no unexpected complications.
To conduct experiments, experts working under Prof. Dr. med. Dirk Hempel at the Steinbeis Transfer Institute for Clinical Hematology-Oncology spent two weeks setting up an automated diagnostics line. The processing facility consists of extraction robots that automatically obtain COVID-19 viral RNA from swab samples and prepare a so-called master mix for subsequent real-time quantitative polymerase chain reactions (RT-qPCR). The line has also laid a foundation for single-cell gene sequencing immune cells. Such technology is a prerequisite for experimentation on humoral and cellular mediated immune responses with SARS-CoV-2 infections, and the aim is to examine more closely the causes of the unexpected course of the infection in tumor patients. This is based on the hypothesis that changes triggered by chemotherapy in humoral and cellular mediated immune responses could be responsible for the mild course of infection in cancer patients.
To optimize the care of cancer patients in the event of a second wave of the pandemic, it is important to identify biomarkers that allow the course of the COVID-19 infection to be predicted in cancer patients. The experts are assuming that biomarkers are developed as a result of an immunological response. As part of the project, the aim is to examine humoral and T cell mediated immune responses among COVID-19-positive cancer patients during the course of the infection. This will involve investigating anti-COVID-19 immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies, as well as immunologically relevant cellular subclasses during the course of the infection.
After conducting flow-cytrometric cell sorting, the immune cells can be further characterized using single-cell gene sequencing. This cutting-edge technology will undergo continual development during the project so that later, it can also be made available for use in other areas, such as cancer research (precision oncology). To evaluate the colossal volumes of data generated by the experiments, the partners working on the project are using bioinformatic algorithms capable of machine-learning. The aim is to acquire data for immunological signatures that could be used as predictive biomarkers for the course of the infection. This involves comparing epidemiological and clinical data with the immunological profiles of tumor patients and evaluating data using bioinformatics.