Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients.

OBJECTIVE: In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE. METHODS: Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible. RESULTS: In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm. CONCLUSION: Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis. TRIAL REGISTRATION NUMBER AND DATE: BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .

Direct image to subtype prediction for brain tumors using deep learning.

Background: Deep Learning (DL) can predict molecular alterations of solid tumors directly from routine histopathology slides. Since the 2021 update of the World Health Organization (WHO) diagnostic criteria, the classification of brain tumors integrates both histopathological and molecular information. We hypothesize that DL can predict molecular alterations as well as WHO subtyping of brain tumors from hematoxylin and eosin-stained histopathology slides. Methods: We used weakly supervised DL and applied it to three large cohorts of brain tumor samples, comprising N = 2845 patients. Results: We found that the key molecular alterations for subtyping, IDH and ATRX, as well as 1p19q codeletion, were predictable from histology with an area under the receiver operating characteristic curve (AUROC) of 0.95, 0.90, and 0.80 in the training cohort, respectively. These findings were upheld in external validation cohorts with AUROCs of 0.90, 0.79, and 0.87 for prediction of IDH, ATRX, and 1p19q codeletion, respectively. Conclusions: In the future, such DL-based implementations could ease diagnostic workflows, particularly for situations in which advanced molecular testing is not readily available.

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology.

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

Detecting drug resistance in pancreatic cancer organoids guides optimized chemotherapy treatment.

Drug combination therapies for cancer treatment show high efficacy but often induce severe side effects, resulting in dose or cycle number reduction. We investigated the impact of neoadjuvant chemotherapy (neoCTx) adaptions on treatment outcome in 59 patients with pancreatic ductal adenocarcinoma (PDAC). Resections with tumor-free margins were significantly more frequent when full-dose neoCTx was applied. We determined if patient-derived organoids (PDOs) can be used to personalize poly-chemotherapy regimens by pharmacotyping of treatment-naïve and post-neoCTx PDAC PDOs. Five out of ten CTx-naïve PDO lines exhibited a differential response to either the FOLFIRINOX or the Gem/Pac regimen. NeoCTx PDOs showed a poor response to the neoadjuvant regimen that had been administered to the respective patient in 30% of cases. No significant difference in PDO response was noted when comparing modified treatments in which the least effective single drug was removed from the complete regimen. Drug testing of CTx-naïve PDAC PDOs and neoCTx PDOs may be useful to guide neoadjuvant and adjuvant regimen selection, respectively. Personalizing poly-chemotherapy regimens by omitting substances with low efficacy could potentially result in less severe side effects, thereby increasing the fraction of patients receiving a full course of neoadjuvant treatment. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background in over one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and several other tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlighting the importance of identifying SDHx mutations for patient management. Genetic variants of unknown significance, where implications for the patient and family members are unclear, are a problem for interpretation. For such cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB (SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatography-mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions provide an alternative method. Here, we compare SDHB-IHC with metabolite profiling in 189 tumours from 187 PPGL patients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to establish predictive models for interpreting metabolite data. Metabolite profiling showed higher diagnostic specificity compared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite profiles improved predictive ability over that of the SFR, in particular for hard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, the combination of metabolite profiling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classified all but one of the false negatives from metabolite profiling strategies, while metabolite profiling correctly classified all but one of the false negatives/positives from SDHB-IHC. From 186 tumours with confirmed status of SDHx variant pathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benefits of both strategies for patient management. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Novel 3D organotypic urothelial cell culture model for identification of new therapeutic approaches in urological infections.

PURPOSE: 3D organotypic cell cultures offer the possibility to study cell growth in a more in vivo like situation. To our knowledge no 3D culture of primary urothelial cells has been established yet. BK Polyomavirus (BKPyV), replicating in urothelial cells, may cause haemorrhagic cystitis in immunocompromised patients. PRIMARY ENDPOINTS OF THIS STUDY: Establishment of a 3D organotypic cell culture of primary urothelial cells and fibroblasts; use of this model as infection model for archetype BKPyV; description of first parts of viral life cycle with identification of therapeutic targets. METHODS: This is an experimental study. Primary urothelial cells were purchased from CellnTec, Bern, Switzerland; fibroblasts were isolated from the ureter of patients with no urothelial malignancy in their medical history. As main methods we used quantitative real-time PCR and immunohistochemistry. Outcomes were analysed using SPSS 23.0. RESULTS: We were able to develop a 3D organotypic culture for primary urothelium. An infection with archetype BKPyV was established in this model with virus replication rates up to 6.41 × 108 copies/ml on day 9 following Infection. Interestingly, proliferation rate of the urothelial cells is significantly (p = 0.049 at day 6 following infection) elevated while cells are losing differentiation under infection. Phosphorylated STAT3 is also significantly elevated (p < 0.0001) during infection. CONCLUSIONS: The established of urothelial 3D cultures is a new method to study several urothelial diseases. The archetype BKPyV infection model is novel and the first method to study archetype viral life cycle. The STAT3 pathway might be an interesting target for the development of a causal therapy.

Lack of P-glycoprotein Results in Impairment of Removal of Beta-Amyloid and Increased Intraparenchymal Cerebral Amyloid Angiopathy after Active Immunization in a Transgenic Mouse Model of Alzheimer's Disease.

BACKGROUND: Immunization against beta-amyloid (Aß) reduces cerebral Aß deposits and improves cognitive capacities in transgenic mouse models, and thus has been considered a promising disease- modifying therapeutic approach for Alzheimer's disease (AD). Although clinical trials in AD patients have yielded evidence for clearance of parenchymal Aß plaques, Aß increases in blood vessels of treated patients. We hypothesize that an age-related decline in the mechanisms that clear Aß from the brain might be at least in part responsible for the failure to purge and re-distribute Aß. The expulsion of Aß via the blood-brain barrier is mediated by specialized transport proteins such as P-glycoprotein (P-gp, ABCB1/MDR1). OBJECTIVE: The objective of this study is to investigate the influence of the absence of P-gp at the bloodbrain barrier on the effectiveness of Aß peptide immunization in APP/PS1+/- P-gp ko mice. METHODS: Male APP/PS1+/- P-gp wt (n = 8) and APP/PS1+/- P-gp ko (n = 8) mice were actively immunized with human Aß42. After behavioral testing animals were sacrificed at the age of 395 days (+/- 5 days) and antibody titres against Aß were measured. Brains were dissected and soluble/insoluble cerebral Aß was quantified, additionally the number of amyloid plaques and severity of amyloid angiopathy were evaluated. RESULTS: In immunized mice with intact P-gp, our results showed a significant reduction of soluble and insoluble Aß40 and Aß42. Furthermore, immunization significantly reduced Aß plaque burden. In contrast, immunized APP/PS1+/- P-gp ko mice lacking functional P-gp did not show a reduction of Aß40 or Aß42 accumulation in the brain except for the soluble form of Aß42. Furthermore, after active immunization these mice displayed a stronger intracerebral amyloid angiopathy. CONCLUSION: The results show that the absence of P-gp results in a significant disturbance of Aß removal from the brain and increased intraparenchymal cerebral amyloid angiopathy after immunization against Aß. Our data indicate that the selective up-regulation of P-gp could enhance the efficacy of Aß immunization in the treatment or prevention of AD.