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BackgroundTherapeutic management of stage II colon cancer remains difficult regarding the decision whether adjuvant chemotherapy should be administered or not. Low rates of recurrence are opposed to chemotherapy induced toxicity and current clinical features are limited in predicting disease relapse. Predictive biomarkers are urgently needed and we hypothesise that the spatial tissue composition of relapsed and non-relapsed colon cancer stage II patients reveals relevant biomarkers.MethodsThe spatial tissue composition of stage II colon cancer patients was examined by in situ sequencing technology with sub-cellular resolution. A panel of 175 genes was designed investigating specific cancer-associated processes and components of the tumour microenvironment. We identified a tumour gene signature to subclassify tissue into neoplastic and non-neoplastic tissue compartments based on spatial expression patterns generated by in situ sequencing (GTC-tool – Genes-To-Count).ResultsThe GTC-tool automatically identified tissue compartments that were used to quantify gene expression of biological processes upregulated within the neoplastic tissue in comparison to non-neoplastic tissue and within relapsed versus non-relapsed stage II colon patients. Three differentially expressed genes (FGFR2, MMP11 and OTOP2) in the neoplastic tissue compartments of relapsed patients in comparison to non-relapsed patients were identified predicting recurrence in stage II colon cancer.ConclusionsIn depth spatial in situ sequencing revealed novel potential predictive biomarkers for disease relapse in colon cancer stage II patients. Our developed open-access GTC-tool allows to accurately capture the tumour compartment and quantify spatial gene expression in colon cancer tissue.

Background Assessment of liver quality during machine perfusion (MP) is under intensive investigation. Gold standard methods either are of limited validity or evaluation is time-consuming. Hence, herein we investigate a novel real-time method to estimate liver function during sub-normothermic MP. Methods Three healthy porcine livers and one non-allocable human liver were subjected to 24h of SNMP with either Custodiol® or Custodiol MP as perfusate. Additional to liver enzymes, Flavin mononucleotide (FMN) and High-mobility group box 1 (HMGB-1) as well-established markers of liver quality, a novel 13C-Methacetin based method was evaluated. Readouts of ϭ13CO2 plots generated by the 13CORLab Prototype were calculated and compared to established parameters. Results The newly established method mirrored the pathological findings as well as the increasing changes in liver enzymes, HMGB-1 and FMN levels bearing the advantage of being a real-time, non-invasive test which is applicable on site. Conclusion This novel method is an easy to implement and reliable tool for quick on-site estimation of liver function during liver SNMP.

Cholangiocarcinoma (CCA) are characterized by their desmoplastic and hypervascularized tumor microenvironment (TME), which is mainly composed of tumor cells and cancer-associated fibroblasts (CAFs). CAFs play a pivotal role in general and CCA tumor progression, angiogenesis, metastasis, and the development of treatment resistance. To our knowledge, no continuous human in vivo-like co-culture model is available for research. Therefore, we aimed to establish a new model system (called MUG CCArly) that mimics the desmoplastic microenvironment typically seen in CCA. Proteomic data comparing the new CCA tumor cell line with our co-culture tumor model (CCTM) indicated a higher gene expression correlation of the CCTM with physiological CCA characteristics. A pro-angiogenic TME that is typically observed in CCA could also be better simulated in the CCTM group. Further analysis of secreted proteins revealed CAFs to be the main source of these angiogenic factors. Our CCTM MUG CCArly represents a new, reproducible, and easy-to-handle 3D CCA model for preclinical studies focusing on CCA-stromal crosstalk, tumor angiogenesis, and invasion, as well as the immunosuppressive microenvironment and the involvement of CAFs in the way that drug resistance develops.

Granulomatous and abscessing testicular inflammations are important differential diagnoses of testicular tumors. Infectious orchitis should always be considered in unclear testicular masses with negative tumor markers. We report the case of a 45-year-old man with abscessing orchitis due to early syphilis diagnosed after orchiectomy with the suspicion of a seminoma.Granulomatöse und abszedierende Orchitiden sind wichtige Differenzialdiagnosen von Hodenkarzinomen. Eine infektiöse Orchitis sollte bei unklaren testikulären Raumforderungen mit negativen Tumormarkern immer bedacht werden. Im vorliegenden Beitrag wird über den Fall eines 45-jährigen Mannes mit abszedierender Orchitis bedingt durch eine Frühsyphilis berichtet. Die Diagnose konnte erst nach Orchiektomie bei Verdacht auf ein Seminom gestellt werden.

Metastasis is responsible for the majority of cancer‐related deaths. Particularly, challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue of origin (TOO) remains undetermined even after extensive investigations and whose therapy is rather unspecific and poorly effective. Molecular approaches to identify the most probable TOO of CUPs can overcome some of these issues. In this study, we applied a predetermined set of 89 microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. The miRNA expression was assessed with droplet digital PCR in 159 samples, including primary tumors from 17 tumor classes (reference set) and metastases of known and unknown origin (test set). We combined two different statistical models for class prediction to obtain the most probable TOOs: the nearest shrunken centroids approach of Prediction Analysis of Microarrays (PAMR) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successful for all formalin‐fixed paraffin‐embedded samples and provided a TOO identification within 1 week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast, lung, and bile duct. The assay was applied also to multiple metastases from the same CUP, collected from different metastatic sites: The predictions showed a strong agreement, intrinsically validating our assay. The final CUPs' TOO prediction was compared with the clinicopathological hypothesis of primary site. Moreover, a panel of 13 miRNAs proved to have prognostic value and be associated with overall survival in CUP patients. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indications about the possible primary site, thereby supporting treatment decisions., Cancer of unknown primary site (CUP) patients suffer the burden of a metastatic disease whose site of origin is unidentifiable, even after intensive clinical investigations. The lack of a recognized primary site limits patients' treatment options. In this manuscript, we present a molecular assay, based on digital miRNA profiling, that allowed the prediction of the primary site of 53 CUPs.

Metastasis is responsible for the majority of cancer-related deaths. Particularly challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue-of-origin (TOO) remains undetermined even after expensive investigations. CUP therapy is rather unspecific and poorly effective. Molecular approaches developed to identify CUPs’ potential tissue-of-origin, can overcome some of these issues. In this study, we applied a pre-determined set of microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. We designed a molecular assay to quantify 89 miRNAs at the copy number level, using EvaGreen-based Droplet Digital PCR. We assessed miRNA expression in 159 samples including primary tumors from 17 tumor classes (reference set), metastases of known and unknown origin. We applied two different statistical models for class prediction to obtain CUP’s most probable TOOs. Specifically, we used the shrunken centroids using PAMR (Prediction Analysis of Microarrays for R) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successfully applied to FFPE samples and provided a site-of-origin identification within one-week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast and lung. The assay was applied to multiple metastases from the same CUP, collected from different metastatic sites: the molecular prediction revealed an impressive agreement in site-of-origin prediction, intrinsically validating our assay. The final prediction was compared with the clinico-pathological hypothesis of primary site. Moreover, a panel of 14 miRNAs proved to have prognostic value and being associated with overall survival. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on-request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indication about the possible primary site, thereby supporting treatment decisions.