CLINICAL PROTEOMICS – Cancer Diseases
Mass spectrometry-based proteomics
Improved diagnostics through protein biomarkers
In the competence area of medical proteome analysis, another research focus is on the identification and verification of potential protein biomarkers that can be of additional help to pathologists in the day-to-day diagnosis of the respective types of cancer. Furthermore, tumour-relevant signalling pathways of the cells are investigated with the aim of elucidating tumourigenesis at the protein level. This method of mass spectrometry-based proteomics allows investigations on the smallest sample quantities, as protein quantities of 100-200 ng are sufficient for the identification phase. A major advantage of the methodology is therefore that it is possible to work with small quantities of isolated tumour-relevant cells by means of laser microdissection, which often originate from the automated procedures of the biospectroscopy competence area. This means that the subsequent analysis concentrates only on disease-relevant cells and thus also increases the chance of finding promising biomarkers. Due to the promising results, we have also extended our methodology to other cancers, such as pancreatic cancer, urachal carcinoma and skin cancer. Furthermore, we are establishing new methods to improve clinical protein analysis. In particular, further quantification methods are being developed to increase protein coverage from a sample. Special focus is also placed on functional analyses of tumour-relevant proteins in order to decipher their function in the signalling pathways of cancer development and thus to identify suitable drug targets for patients in the future, in addition to promising biomarkers. In addition, the methodology also enables research into therapy resistance, e.g. to chemotherapeutic agents, on the one hand to elucidate potential resistance mechanisms and, on the other hand, to identify possible biomarker candidates for stratifying patients who respond well or less well to the therapy under investigation.
Types of cancer
Colorectal cancer, or more specifically colorectal carcinoma, is one of the leading causes of cancer-related deaths worldwide. Treatment methods include tumour removal, radiation and chemotherapy and, in advanced stages, patient- or tumour-specific antibody or inhibitor therapies. A decisive factor for successful treatment is early and specific diagnosis. In cooperation with the clinics of the Ruhr University Bochum and the other areas of expertise, a study was therefore conducted to differentiate colorectal carcinoma from healthy colorectal crypts. A successful establishment of an automatic annotation of the different tissue types (carcinoma, healthy crypts) on the part of the competence area biospectroscopy could be confirmed by means of subsequent mass spectrometric proteome analysis of the automatically laser-microdissected tissue cells. Furthermore, the prognostic aspect of both subgroups will also be investigated.
Bladder cancer / prostate carcinoma
Prostate and bladder cancer are the two most common cancers of the genitourinary tract and especially bladder cancer is on the one hand one of the most expensive cancers to treat due to the frequency of screening low grade tumours and on the other hand it is often very difficult to differentiate between a simple inflammation of the bladder, a low grade carcinoma and a non-invasive high grade carcinoma (carcinoma in situ, CIS) due to the histology. This diagnosis often determines whether the bladder has to be removed, which is why the differential diagnosis of the tumour grade is essential. In collaboration with the clinics of the Ruhr University Bochum and the competence area of biospectroscopy, an automated characterisation of bladder tumours using IR imaging has already been established and a potential new biomarker (AHNAK2) for the diagnosis of CIS has been identified (Witzke et al. Am J Pathol. 2019). This approach will also be extended to prostate carcinoma in the coming years, where the exact determination of the tumour grade is the therapy-deciding factor. In the future, this differential diagnosis will be simplified and improved by our combined approach.
Lung cancer is the most common cause of death among all cancers, with smoking as the main cause for its development. Due to frequent very late initial diagnoses, the average survival rate is rather low, which is why biomarkers for the early detection of lung cancer are urgently needed. The risk prognosis for the development of lung adenocarcinoma in COPD (chronic obstructive pulmonary disease) patients is also very important, as they are basically at increased risk for lung cancer. Therefore, we are investigating not only laser microdissected tissue sections, but also plasma samples from patients with lung adenocarcinoma, COPD or both diagnoses and control patient samples with the primary aim of identifying potential early diagnostic and prognostic biomarkers for lung cancer and COPD. Preliminary work has been done in this regard in collaboration with the Biospectroscopy Competence Area, where the first automated detection of lung adenocarcinoma subtypes and laser microdissection based on this was used to successfully perform a proteomic analysis to identify new and known biomarker candidates (Großerueschkamp et al. Sci Rep. 2017). Through this combined approach of automated annotation and laser microdissection to sample generation for proteomics, it is now possible to generate samples for tissue analysis with unprecedented accuracy.