@article{SeufferleinLausserSteinetal.2024, author = {Seufferlein, Thomas and Lausser, Ludwig and Stein, Alexander and Arnold, Dirk and Prager, Gerald and Kasper-Virchow, Stefan and Niedermeier, Michael and M{\"u}ller, Lothar and Kubicka, Stefan and K{\"o}nig, Alexander and B{\"u}chner-Steudel, Petra and Wille, Kai and Berger, Andreas W. and Kestler, Angelika M. R. and Kraus, Johann M. and Werle, Silke D. and Perkhofer, Lukas and Ettrich, Thomas J. and Kestler, Hans A.}, title = {Prediction of resistance to bevacizumab plus FOLFOX in metastatic colorectal cancer—Results of the prospective multicenter PERMAD trial}, volume = {19}, pages = {e0304324}, journal = {PLOS ONE}, number = {6}, publisher = {PLOS}, address = {San Francisco}, issn = {1932-6203}, doi = {https://doi.org/10.1371/journal.pone.0304324}, year = {2024}, abstract = {Background Anti-vascular endothelial growth factor (VEGF) monoclonal antibodies (mAbs) are widely used for tumor treatment, including metastatic colorectal cancer (mCRC). So far, there are no biomarkers that reliably predict resistance to anti-VEGF mAbs like bevacizumab. A biomarker-guided strategy for early and accurate assessment of resistance could avoid the use of non-effective treatment and improve patient outcomes. We hypothesized that repeated analysis of multiple cytokines and angiogenic growth factors (CAFs) before and during treatment using machine learning could provide an accurate and earlier, i.e., 100 days before conventional radiologic staging, prediction of resistance to first-line mCRC treatment with FOLFOX plus bevacizumab. Patients and methods 15 German and Austrian centers prospectively recruited 50 mCRC patients receiving FOLFOX plus bevacizumab as first-line treatment. Plasma samples were collected every two weeks until radiologic progression (RECIST 1.1) as determined by CT scans performed every 2 months. 102 pre-selected CAFs were centrally analyzed using a cytokine multiplex assay (Luminex, Myriad RBM). Results Using random forests, we developed a predictive machine learning model that discriminated between the situations of "no progress within 100 days before radiological progress" and "progress within 100 days before radiological progress". We could further identify a combination of ten out of the 102 CAF markers, which fulfilled this task with 78.2\% accuracy, 71.8\% sensitivity, and 82.5\% specificity. Conclusions We identified a CAF marker combination that indicates treatment resistance to FOLFOX plus bevacizumab in patients with mCRC within 100 days prior to radiologic progress.}, language = {en} } @article{BuchholzLausserSchenketal.2024, author = {Buchholz, Malte and Lausser, Ludwig and Schenk, Miriam and Earl, Julie and Lawlor, Rita T. and Scarpa, Aldo and Sanjuanbenito, Alfonso and Carrato, Alfredo and Malats, Nuria and Tjaden, Christine and Giese, Nathalia A. and B{\"u}chler, Markus and Hackert, Thilo and Kestler, Hans A. and Gress, Thomas M.}, title = {Combined analysis of a serum mRNA/miRNA marker signature and CA 19-9 for timely and accurate diagnosis of recurrence after resection of pancreatic ductal adenocarcinoma: A prospective multicenter cohort study}, volume = {13}, journal = {United European Gastroenterology Journal}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {2050-6414}, doi = {https://doi.org/10.1002/ueg2.12676}, pages = {353 -- 363}, year = {2024}, abstract = {Background and Aims Timely and accurate detection of tumor recurrence in pancreatic ductal adenocarcinoma (PDAC) patients is an urgent and unmet medical need. This study aimed to develop a noninvasive molecular diagnostic procedure for the detection of recurrence after PDAC resection based on quantification of circulating mRNA and miRNA biomarkers in serum samples. Methods In a multicentric study, serum samples from a total of 146 patients were prospectively collected after resection. Samples were classified into a "No Evidence of Disease" and a "Recurrence" group based on clinical follow-up data. A multianalyte biomarker panel was composed of mRNAs and miRNA markers and simultaneously analyzed in serum samples using custom microfluidic qPCR arrays (TaqMan array cards). A diagnostic algorithm was developed combining a 7-gene marker signature with CA19-9 data. Results The best-performing marker combination achieved 90\% diagnostic accuracy in predicting the presence of tumor recurrence (98\% sensitivity; 84\% specificity), clearly outperforming the singular CA 19-9 analysis. Moreover, time series data obtained by analyzing successively collected samples from 5 patients during extended follow-up suggested that molecular diagnosis has the potential to detect recurrence earlier than routine clinical procedures. Conclusions TaqMan array card measurements were found to be biologically valid and technically reproducible. The BioPac multianalyte marker panel is capable of sensitive and accurate detection of recurrence in patients resected for PDAC using a simple blood test. This could allow a closer follow-up using shorter time intervals than currently used for imaging, thus potentially prompting an earlier work-up with additional modalities to allow for earlier therapeutic intervention. This study provides a promising approach for improved postoperative monitoring of resected PDAC patients, which is an urgent and unmet clinical need.}, language = {en} }