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Autoimmune hepatitis episodes have been described following SARS-CoV-2 infection and vaccination but their pathophysiology remains unclear. Herein, we report the case of a 52-year-old male, presenting with bimodal episodes of acute hepatitis, each occurring 2-3 weeks after BNT162b2 mRNA vaccination. We sought to identify the underlying immune correlates. The patient received oral budesonide, relapsed, but achieved remission under systemic steroids.Imaging mass cytometry for spatial immune profiling was performed on liver biopsy tissue. Flow cytometry was performed to dissect CD8 T-cell phenotypes and identify SARS-CoV-2-specific and EBV-specific T cells longitudinally. Vaccine-induced antibodies were determined by ELISA. Data were correlated with clinical laboratory results.Analysis of the hepatic tissue revealed an immune infiltrate quantitatively dominated by activated cytotoxic CD8 T cells with panlobular distribution. An enrichment of CD4 T cells, B cells, plasma cells and myeloid cells was also observed compared to controls. The intrahepatic infiltrate showed enrichment for CD8 T cells with SARS-CoV-2-specificity compared to the peripheral blood. Notably, hepatitis severity correlated longitudinally with an activated cytotoxic phenotype of peripheral SARS-CoV-2-specific, but not EBV-specific, CD8+ T cells or vaccine-induced immunoglobulins.COVID-19 vaccination can elicit a distinct T cell-dominant immune-mediated hepatitis with a unique pathomechanism associated with vaccination-induced antigen-specific tissue-resident immunity requiring systemic immunosuppression.Liver inflammation is observed during SARS-CoV-2 infection but can also occur in some individuals after vaccination and shares some typical features with autoimmune liver disease. In this report, we show that highly activated T cells accumulate and are evenly distributed in the different areas of the liver in a patient with liver inflammation following SARS-CoV-2 vaccination. Moreover, within the population of these liver-infiltrating T cells, we observed an enrichment of T cells that are reactive to SARS-CoV-2, suggesting that these vaccine-induced cells can contribute to liver inflammation in this context.

Despite recent translation of immunotherapies into clinical practice, the immunobiology of hepatocellular carcinoma (HCC), in particular the role and clinical relevance of exhausted and liver-resident T cells remain unclear. We therefore dissected the landscape of exhausted and resident T cell responses in the peripheral blood and tumor microenvironment of patients with HCC.Lymphocytes were isolated from the blood, tumor and tumor-surrounding liver tissue of patients with HCC (n = 40, n = 10 treated with anti-PD-1 therapy). Phenotype, function and response to anti-PD-1 were analyzed by mass and flow cytometry ex vivo and in vitro, tissue residence was further assessed by immunohistochemistry and imaging mass cytometry. Gene signatures were analyzed in silico.We identified significant enrichment of heterogeneous populations of exhausted CD8+ T cells (TEX) in the tumor microenvironment. Strong enrichment of severely exhausted CD8 T cells expressing multiple immune checkpoints in addition to PD-1 was linked to poor progression-free and overall survival. In contrast, PD-1 was also expressed on a subset of more functional and metabolically active CD103+ tissue-resident memory T cells (TRM) that expressed few additional immune checkpoints and were associated with better survival. TEX enrichment was independent of BCLC stage, alpha-fetoprotein levels or age as a variable for progression-free survival in our cohort. These findings were in line with in silico gene signature analysis of HCC tumor transcriptomes from The Cancer Genome Atlas. A higher baseline TRM/TEX ratio was associated with disease control in anti-PD-1-treated patients.Our data provide information on the role of peripheral and intratumoral TEX-TRM dynamics in determining outcomes in patients with HCC. The dynamics between exhausted and liver-resident T cells have implications for immune-based diagnostics, rational patient selection and monitoring during HCC immunotherapies.The role of the immune response in hepatocellular carcinoma (HCC) remains unclear. T cells can mediate protection against tumor cells but are frequently dysfunctional and exhausted in cancer. We found that patients with a predominance of exhausted CD8+ T cells (TEX) had poor survival compared to patients with a predominance of tissue-resident memory T cells (TRM). This correlated with the molecular profile, metabolic and functional status of these cell populations. The enrichment of TEX was independently associated with prognosis in addition to disease stage, age and tumor markers. A high TRM proportion was also associated with better outcomes following checkpoint therapy. Thus, these T-cell populations are novel biomarkers with relevance in HCC.

Protein expression is a primary area of interest for routine histological diagnostics and tissue-based research projects, but the limitations of its post-mortem applicability remain largely unclear. On the other hand, tissue specimens obtained during autopsies can provide unique insight into advanced disease states, especially in cancer research. Therefore, we aimed to identify the maximum post-mortem interval (PMI) which is still suitable for characterizing protein expression patterns, to explore organ-specific differences in protein degradation, and to investigate whether certain proteins follow specific degradation kinetics. Therefore, the proteome of human tissue samples obtained during routine autopsies of deceased patients with accurate PMI (6, 12, 18, 24, 48, 72, 96 h) and without specific diseases that significantly affect tissue preservation, from lungs, kidneys and livers, was analyzed by liquid chromatography–tandem mass spectrometry (LC–MS/MS). For the kidney and liver, significant protein degradation became apparent at 48 h. For the lung, the proteome composition was rather static for up to 48 h and substantial protein degradation was detected only at 72 h suggesting that degradation kinetics appear to be organ specific. More detailed analyses suggested that proteins with similar post-mortem kinetics are not primarily shared in their biological functions. The overrepresentation of protein families with analogous structural motifs in the kidney indicates that structural features may be a common factor in determining similar postmortem stability. Our study demonstrates that a longer post-mortem period may have a significant impact on proteome composition, but sampling within 24 h may be appropriate, as degradation is within acceptable limits even in organs with faster autolysis.

Zusammenfassung Hintergrund Das prostataspezifische Membranantigen (PSMA) ist für Mammakarzinompatientinnen ein vielversprechendes Protein. Es wurde bisher nicht nur beim Prostatakarzinom nachgewiesen, sondern wird auch von den Tumor- sowie Endothelzellen der Tumorgefäße des Mammakarzinoms exprimiert. Das PSMA hat eine Rolle bei der Tumorprogression und Neubildung von Gefäßen. Deshalb wurden bereits viele PSMA-gerichtete diagnostische und therapeutische Verfahren entwickelt. Methode Diese Arbeit ist eine allgemeine und gegliederte Übersicht über das PSMA und dessen onkogenetisches Potenzial, mit dem Fokus auf dessen Rolle beim Mammakarzinom. Für dieses narrative Review wurde eine selektive Literaturrecherche via PubMed und der Bibliothek des Universitätsklinikums Freiburg angefertigt. Hierbei wurden folgende Schlüsselwörter verwendet: „PSMA“, „PSMA and breast cancer“, „PSMA PET/CT“, „PSMA tumor progression“. Relevante Artikel wurden explizit durchgelesen, bearbeitet und zusammengefasst. Schlussfolgerung Das PSMA könnte, insbesondere beim triple-negativen Mammakarzinom, eine neue diagnostische und therapeutische Alternative darstellen. Es scheint ein möglicher prädiktiver und prognostischer Marker zu sein.

Background/Aim: To investigate whether quantitative analysis of diffusion weighted images allows for improved risk stratification of transition zone lesions in prostate magnetic resonance imaging (MRI) evaluated according to PI-RADSv2.1 [Prostate Imaging Reporting and Data System, target variable: clinically significant prostate cancer (csPCa)]. Patients and Methods: Consecutive patients with transition zone lesions in 3T prostate MRI were enrolled in the study. All lesions on MRI were histopathologically verified by transperineal MRI-TRUS fusion biopsy. Two blinded radiologists re-evaluated all lesions according to PI-RADSv2.1. A consensus reading was performed after reading of all cases. Additionally, mean apparent diffusion coefficient values (mADC) were derived from blinded lesion segmentation. ROC analysis was performed for PI-RADS categories and PI-RADS categories with separate subcategories and diffusion coefficient values (ADC). Data were examined for optimal mADC cut-off values that improve stratification of csPCa and benign lesions. Results: Among 85 patients (mean age=66.2 years), 98 transition zone lesions were detected. Biopsy confirmed csPCa in 24/98 cases. Area under the curve (AUC) was 0.89/0.90 for reader 1, 0.92/0.91 for reader 2 and 0.92/0.91 for the consensus reading (5 category analysis/analysis with subcategories separately). Inter-reader agreement was substantial, with lower PI-RADS categories assigned by the more experienced reader (p

Supplementary Figure 3: Association of chemokine expression with a T cell-inflamed phenotype was validated in a second independent PDAC patient cohort

This file contains the legends to all Supplementary Figures

Supplementary Table 1: Top 99 genes associating with CD8+ TIL counts in primary resected cases

Supplementary Table 3: Summary statistics for cellularity in 4-chemokinehi and 4-chemokinelo groups in primary resections

H3K9me3 levels increase upon treatment with QC6352. Changes in H3K9me3 levels are depicted according to genomic location.

Supplementary Figure 6: Immune phenotypes were not impacted by cellularity in metastases

Treatment with QC6352 inhibits xenograft tumor growth of a second breast cancer stem cell line (BCSC2).

Supplementary Table 2: Top 100 upregulated genes in 4-chemokinehi and 4-chemokinelo patients

Purpose:The molecular drivers of antitumor immunity in pancreatic ductal adenocarcinoma (PDAC) are poorly understood, posing a major obstacle for the identification of patients potentially amenable for immune-checkpoint blockade or other novel strategies. Here, we explore the association of chemokine expression with effector T-cell infiltration in PDAC.Experimental Design:Discovery cohorts comprised 113 primary resected PDAC and 107 PDAC liver metastases. Validation cohorts comprised 182 PDAC from The Cancer Genome Atlas and 92 PDACs from the Australian International Cancer Genome Consortium. We explored associations between immune cell counts by immunohistochemistry, chemokine expression, and transcriptional hallmarks of antitumor immunity by RNA sequencing (RNA-seq), and mutational burden by whole-genome sequencing.Results:Among all known human chemokines, a coregulated set of four (CCL4, CCL5, CXCL9, and CXCL10) was strongly associated with CD8+ T-cell infiltration (P < 0.001). Expression of this “4-chemokine signature” positively correlated with transcriptional metrics of T-cell activation (ZAP70, ITK, and IL2RB), cytolytic activity (GZMA and PRF1), and immunosuppression (PDL1, PD1, CTLA4, TIM3, TIGIT, LAG3, FASLG, and IDO1). Furthermore, the 4-chemokine signature marked tumors with increased T-cell activation scores (MHC I presentation, T-cell/APC costimulation) and elevated expression of innate immune sensing pathways involved in T-cell priming (STING and NLRP3 inflammasome pathways, BATF3-driven dendritic cells). Importantly, expression of this 4-chemokine signature was consistently indicative of a T-cell–inflamed phenotype across primary PDAC and PDAC liver metastases.Conclusions:A conserved 4-chemokine signature marks resectable and metastatic PDAC tumors with an active antitumor phenotype. This could have implications for the appropriate selection of PDAC patients in immunotherapy trials.

QC6352 strongly decreases proliferation and sphere formation of a second breast cancer stem cell line (BCSC2). Other breast cancer-targeting agents like QC6688 and paclitaxel are unable to abolish secondary sphere formation in BCSC1 or BCSC2.

KDM4B, C, or D do not control proliferation and xenograft tumor growth of BCSC1.

Supplementary Table 4: Summary statistics for cellularity between 4-chemokinehi and 4-chemokinelo groups in liver metastases

Supplementary Figure 5: The 4-chemokine signature identified an antitumor phenotype in liver metastases, independent of mutational burden

Supplementary Figure 2: Transcriptomic subtypes versus 4-chemokinehi and 4-chemokinelo in both primary and metastatic tumours

Additional evidence showing control of EGFR expression by QC6352 is presented here. The specific EGFR inhibitor erlotinib diminishes proliferation and sphere formation in BCSC1 and BCSC2.

Characterization of the breast cancer stem cell line BCSC2 in vitro and in vivo. Like BCSC1 in Figure 1, BCSC2-derived xenografts also recapitulate the original patient tumor.

Supplementary Figure 1: Overview of methodology and cohorts

Traditional treatments for breast cancer fail to address therapy-resistant cancer stem–like cells that have been characterized by changes in epigenetic regulators such as the lysine demethylase KDM4. Here, we describe an orally available, selective and potent KDM4 inhibitor (QC6352) with unique preclinical characteristics. To assess the antitumor properties of QC6352, we established a method to isolate and propagate breast cancer stem–like cells (BCSC) from individual triple-negative tumors resected from patients after neoadjuvant chemotherapy. Limiting-dilution orthotopic xenografts of these BCSCs regenerated original patient tumor histology and gene expression. QC6352 blocked BCSC proliferation, sphere formation, and xenograft tumor formation. QC6352 also abrogated expression of EGFR, which drives the growth of therapy-resistant triple-negative breast cancer cells. Our findings validate a unique BCSC culture system for drug screening and offer preclinical proof of concept for KDM4 inhibition as a new strategy to treat triple-negative breast cancer. Cancer Res; 77(21); 5900–12. ©2017 AACR.

Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa. ispartof: Int J Radiat Oncol Biol Phys vol:116 issue:3 pages:503-520 ispartof: location:United States status: published

Pancreatic ductal adenocarcinoma (PDAC) represents one of the most aggressive and lethal malignancies worldwide with an urgent need for new diagnostic and therapeutic strategies. One major risk factor for PDAC is the pre-indication of chronic pancreatitis (CP), which represents highly inflammatory pancreatic tissue. Kallikreins (KLKs) are secreted serine proteases that play an important role in various cancers as components of the tumor microenvironment. Previous studies of KLKs in solid tumors largely relied on either transcriptomics or immunodetection. We present one of the first targeted mass spectrometry profiling of kallikrein proteases in PDAC, CP, and normal pancreas. We show that KLK6 and KLK10 are significantly upregulated in PDAC (n=14) but not in CP (n=7) when compared to normal pancreas (n=21), highlighting their specific intertwining with malignancy. Additional explorative proteome profiling identified 5936 proteins in our pancreatic cohort and observed disease-specific proteome rearrangements in PDAC and CP. As such, PDAC features an enriched proteome motif for extracellular matrix (ECM) and cell adhesion while there is depletion of mitochondrial energy metabolism proteins, reminiscent of the Warburg effect. Although often regarded as a PDAC hallmark, the ECM fingerprint was also observed in CP, alongside with a prototypical inflammatory proteome motif as well as with an increased wound healing process and proteolytic activity, thereby possibly illustrating tissue autolysis. Proteogenomic analysis based on publicly accessible data sources identified 112 PDAC-specific and 32 CP-specific single amino acid variants, which among others affect KRAS and ANKHD1. Our study emphasizes the diagnostic potential of kallikreins and provides novel insights into proteomic characteristics of PDAC and CP.

SummaryRecent advances in digital pathology have led to an explosion in high-content multidimensional imaging approaches. Yet, our ability to gainfully process, visualize, integrate and mine the resulting mass of bioimaging data remains a challenge. We have developed Hourglass, an open access user-friendly software that streamlines complex biology-driven post-processing and visualization of multiparametric data. Directed at datasets derived from tissue microarrays or imaging methods that analyze multiple regions of interest per patient specimen, Hourglass systematically organizes observations across spatial and global levels as well as within patient subgroups. Application of Hourglass to our large and complex pancreatic cancer bioimaging dataset (540,617 datapoints derived from 26 bioimaging analyses applied to 596 specimens from 165 patients) consolidated a breadth of known IL-6 functions in a well-annotated human pancreatic cancer cohort and uncovered new unprecedented insights into a sex-linked Interleukin-6 (IL-6) association with immune phenotypes. Specifically, regional effects of IL-6 on the intratumoral T cell response were restricted to male patients only. In conclusion, Hourglass facilitates multi-layered knowledge extraction from complex multiparametric bioimaging datasets and provides tailored analytical means to productively harness heterogeneity at the sample and patient level.

Soft tissue sarcomas (STS) are rare tumors of mesenchymal origin with high mortality. After curative resection, about one third of patients suffer from distant metastases. Tumor follow-up only covers a portion of recurrences and is associated with high cost and radiation burden. For metastasized STS, only limited inferences can be drawn from imaging data regarding therapy response. To date there are no established and evidence-based diagnostic biomarkers for STS due to their rarity and diversity. In a proof-of-concept study, circulating tumor DNA (ctDNA) was quantified in (n = 25) plasma samples obtained from (n = 3) patients with complex karyotype STS collected over three years. Genotyping of tumor tissue was performed by exome sequencing. Patient-individual mini-panels for targeted next-generation sequencing were designed encompassing up to 30 mutated regions of interest. Circulating free DNA (cfDNA) was purified from plasma and ctDNA quantified therein. ctDNA values were correlated with clinical parameters. ctDNA concentrations correlated with the tumor burden. In case of full remission, no ctDNA was detectable. Patients with a recurrence at a later stage showed low levels of ctDNA during clinical remission, indicating minimal residual disease. In active disease (primary tumor or metastatic disease), ctDNA was highly elevated. We observed direct response to treatment, with a ctDNA decline after tumor resections, radiotherapy, and chemotherapy. Quantification of ctDNA allows for the early detection of recurrence or metastases and can be used to monitor treatment response in STS. Therapeutic decisions can be made earlier, such as the continuation of a targeted adjuvant therapy or the implementation of extended imaging to detect recurrences. In metastatic disease, therapy can be adjusted promptly in case of no response. These advantages may lead to a survival benefit for patients in the future.

Background: Adenosquamous carcinoma of the pancreas (ASCP) is a rare malignancy and its pathophysiology is poorly understood. Sparse clinical data suggest that clinical outcome and overall survival is worse in comparison to common pancreatic ductal adenocarcinoma (PDAC). Methods: We evaluated clinical outcome and prognostic factors for overall survival of patients with ASCP in comparison to patients with PDAC recorded between 2000 and 2019 in 17 population-based clinical cancer registries at certified cancer centers within the Association of German Tumor Centers (ADT). Results: We identified 278 (0.5%) patients with ASCP in the entire cohort of 52,518 patients with pancreatic cancer. Significantly, more patients underwent surgical resection in the cohort of ASCP patients in comparison to patients with PDAC (p < 0.001). In the cohort of 142 surgically resected patients with ASCP, the majority of patients was treated by pancreatoduodenectomy (44.4%). However, compared to the cohort of PDAC patients, significantly more patients underwent distal pancreatectomy (p < 0.001), suggesting that a significantly higher proportion of ASCP tumors was located in the pancreatic body/tail. ASCPs were significantly more often poorly differentiated (G3) (p < 0.001) and blood vessel invasion (V1) was detected more frequently (p = 0.01) in comparison with PDAC. Median overall survival was 6.13 months (95% CI 5.20–7.06) for ASCP and 8.10 months (95% CI 7.93–8.22) for PDAC patients, respectively (p = 0.094). However, when comparing only those patients who underwent surgical resection, overall survival of ASCP patients was significantly shorter (11.80; 95% CI 8.20–15.40 months) compared to PDAC patients (16.17; 95% CI 15.78–16.55 months) (p = 0.007). ASCP was a highly significant prognostic factor for overall survival in univariable regression analysis (p = 0.007) as well as in multivariable Cox regression analysis (HR 1.303; 95% CI 1.013–1.677; p = 0.039). Conclusions: In conclusion, ASCP showed poorer differentiation and higher frequency of blood vessel invasion indicative of a more aggressive tumor biology. ASCP was a significant prognostic factor for overall survival in a multivariable analysis. Overall survival of resected ASCP patients was significantly shorter compared to resected PDAC patients. However, surgical resection still improved survival significantly.

Raman spectroscopy offers label-free assessment of bladder tissue for in vivo and ex vivo intraoperative applications. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates. Raman microspectroscopic images were collected from whole tissue samples in a closed chamber at 785 nm laser excitation using a 20× objective lens and 250 µm step size. Without further preprocessing, Raman images were decomposed by the hyperspectral unmixing algorithm vertex component analysis into endmember spectra and their abundancies. Hierarchical cluster analysis distinguished endmember Raman spectra that were assigned to normal bladder, bladder cancer, necrosis, epithelium and lipid inclusions. Interestingly, Raman spectra of microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. In conclusion, our Raman workflow and data processing protocol with minimal user interference offers advantages for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices.

Background Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset. Methods Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. Results Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. Conclusion Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.

Introduction Primary prostate cancer (PCa) can be visualized on prostate-specific membrane antigen positron emission tomography (PSMA-PET) with high accuracy. However, intraprostatic lesions may be missed by visual PSMA-PET interpretation. In this work, we quantified and characterized the intraprostatic lesions which have been missed by visual PSMA-PET image interpretation. In addition, we investigated whether PSMA-PET-derived radiomics features (RFs) could detect these lesions. Methodology This study consists of two cohorts of primary PCa patients: a prospective training cohort (n = 20) and an external validation cohort (n = 52). All patients underwent 68Ga-PSMA-11 PET/CT and histology sections were obtained after surgery. PCa lesions missed by visual PET image interpretation were counted and their International Society of Urological Pathology score (ISUP) was obtained. Finally, 154 RFs were derived from the PET images and the discriminative power to differentiate between prostates with or without visually undetectable lesions was assessed and areas under the receiver-operating curve (ROC-AUC) as well as sensitivities/specificities were calculated. Results In the training cohort, visual PET image interpretation missed 134 tumor lesions in 60% (12/20) of the patients, and of these patients, 75% had clinically significant (ISUP > 1) PCa. The median diameter of the missed lesions was 2.2 mm (range: 1–6). Standard clinical parameters like the NCCN risk group were equally distributed between patients with and without visually missed lesions (p U: p Conclusion Visual PSMA-PET image interpretation may miss small but clinically significant PCa in a relevant number of patients and RFs can be implemented to uncover them. This could be used for guiding personalized treatments.

Background Aim of the pilot study was the histologic classification of the inflamed peri-implant soft tissue around ceramic implants (CI) in comparison with titanium implants (TI). Methods Peri-implant tissue were retrieved from 15 patients (aged 34 to 88 years, seven males/eight females) with severe peri-implantitis (eight CI, seven TI). The peri-implant soft tissue samples were retrieved from the sites during scheduled removal of the implant and prepared for immunohistochemical analysis. Monoclonal antibodies (targeting CD3, CD20, CD138, and CD68) were used to identify T- and B-cells, plasma cells and macrophages. Quantitative assessment was performed by one histologically trained investigator. Linear mixed regression models were used. Results A similar numerical distribution of the cell population was found in peri-implantitis around CI compared with TI. CD3 (TI, 17% to 85% versus CI, 20% to 70% of total cell number) and CD138 (TI, 1% to 73% versus CI, 12% to 69% of total cell number) were predominantly expressed. Notably, patient-individual differences of numerical cell distribution were detected. Co-localization of B- and T-lymphocytes was observed. Conclusions Peri-implantitis around CI in comparison with TI seems to have a similar histological appearance. Differences in cellular composition of peri-implantitis lesions might also depend on the patient's specific immune status and not only on the material used.

Motivation Mass spectrometry imaging (MSI) characterizes the molecular composition of tissues at spatial resolution, and has a strong potential for distinguishing tissue types, or disease states. This can be achieved by supervised classification, which takes as input MSI spectra, and assigns class labels to subtissue locations. Unfortunately, developing such classifiers is hindered by the limited availability of training sets with subtissue labels as the ground truth. Subtissue labeling is prohibitively expensive, and only rough annotations of the entire tissues are typically available. Classifiers trained on data with approximate labels have sub-optimal performance. Results To alleviate this challenge, we contribute a semi-supervised approach mi-CNN. mi-CNN implements multiple instance learning with a convolutional neural network (CNN). The multiple instance aspect enables weak supervision from tissue-level annotations when classifying subtissue locations. The convolutional architecture of the CNN captures contextual dependencies between the spectral features. Evaluations on simulated and experimental datasets demonstrated that mi-CNN improved the subtissue classification as compared to traditional classifiers. We propose mi-CNN as an important step toward accurate subtissue classification in MSI, enabling rapid distinction between tissue types and disease states. Availability and implementation The data and code are available at https://github.com/Vitek-Lab/mi-CNN_MSI.

Introduction The gastrin-releasing peptide receptor is overexpressed in breast cancer (BC) tissue and can be visualized by positron emission tomography (PET) using the GRPR antagonist [68Ga]Ga-RM2. This study assessed tumor binding of RM2 before and after neoadjuvant chemotherapy (NAC) in primary BC with reference to residual tumor size in the resected specimen. Materials and methods In this retrospective study, five female patients with biopsy-confirmed estrogen receptor (ER)-positive primary BC (one with bilateral tumors) underwent [68Ga]Ga-RM2 PET/CT before and after NAC. PET/CT was acquired 1 h after injection of 143–224 MBq [68Ga]Ga-RM2. Time from pre-NAC PET to beginning of NAC was 23 ± 4.9 days, from end of NAC to post-NAC PET 18.7 ± 6.3 days, and from post-NAC PET to surgery 9.5 ± 10.8 days. In vivo tumor uptake of [68Ga]Ga-RM2 was assessed before and after NAC and correlated with histopathological response. Results All tumors (6/6) showed strongly increased [68Ga]Ga-RM2 uptake compared to normal breast tissue on pre-NAC PET (mean SUVmax 13.2 ± 7.3; mean SUVpeak 9.4 ± 4.4). [68Ga]Ga-RM2 uptake was significantly reduced on post-NAC PET in all primary tumors (mean SUVmax 2.3 ± 0.8, −79 ± 11%; p = 0.0125; mean SUVpeak 1.6 ± 0.4, −79 ± 10%; p = 0.0096). Residual tumor size in resected specimens correlated well with SUVmax (r = 0.91, p = 0.0057) and SUVpeak (r = 0.88, p = 0.0196) on [68Ga]Ga-RM2 PET/CT after NAC. Conclusion and implications for patient care In this pilot study, residual uptake of [68Ga]Ga-RM2 in ER-positive primary BC correlated well with residual vital tumor size after NAC. This suggests that [68Ga]Ga-RM2 PET/CT merits further investigation for response assessment to NAC in patients with ER-positive BC.

Accurate determination of resection margins in breast specimens is important as complete removal of malignancy is a prerequisite for patients’ outcome. Mammography (DM) as 2D-technique provides only limited value in margin assessment. Therefore, we investigated whether cone-beam computed tomography (CBCT) or digital breast tomosynthesis (DBT) has incremental value in assessing margins to microcalcifications. Three independent readers investigated breast specimens for presence of microcalcifications and the smallest distance to margins. Histopathology served as gold standard. Microcalcifications were detected in 15 out of 21 included specimens (71%). Pooled sensitivity for DM, DBT and CBCT for microcalcifications compared to preoperative DM was 0.98 (CI 0.94–0.99), 0.83 (CI 0.73–0.94) and 0.94 (CI 0.87–0.99), pooled specificity was 0.99 (CI 0.99–0.99), 0.73 (CI 0.51–0.96) and 0.60 (CI 0.35–0.85). Mean measurement error for margin determination for DM, DBT and CBCT was 10 mm, 14 mm and 6 mm (p = 0.002) with significant difference between CBCT and the other devices (p p

Accurate detection and segmentation of the intraprostatic gross tumor volume (GTV) is pivotal for radiotherapy (RT) in primary prostate cancer (PCa) since it influences focal therapy target volumes and the patients' cT stage. The study aimed to compare the performance of multiparametric resonance imaging (mpMRI) with [In total, 93 patients from two German University Hospitals with [In the Freiburg cohort (Intraprostatic GTV segmentation based on [18F] PSMA-1007 PET results in more and larger GTVs compared to mpMRI. This influences focal RT target volumes and cT stage definition, but not the NCCN risk group.

Background Response to metabolic surgery is heterogeneous and the metabolic states that underpin weight loss and metabolic improvement are still unclear. In this study, we investigate parameters of post-bariatric fasting glucoregulation and leverage artificial intelligence-assisted whole-slide image analyses to characterize associated immunohistologic features of the pancreas. Materials and Methods We performed either loop duodeno-jejunostomy (DJOS) with exclusion of 1/3 of total intestinal length, loop duodeno-ileostomy with exclusion of 2/3 of total intestinal length (DiOS), or a sham operation on 8-week-old male obese ZDF rats. Six months post-operative, we measured blood metabolites and hormones. Subsequently, pancreatic and intestinal tissue was removed, formalin fixed, and paraffin embedded. Immunohistologic (IHC) analyses included proliferating cell nuclear antigen (PCNA) to visualize the proliferation fraction and pancreatic and duodenal homeobox 1 (PDX 1) as a measure of pancreatic cell differentiation. For IHC quantification, all slides were digitalized and analyzed using QuPath. All analyzed slides were reviewed by two independent pathologists for correctness. Results DJOS and DiOS were associated with preserved fasting insulin production compared to sham. Histopathologic evaluation showed significantly higher numbers of beta cells and specifically of clustered cell organization in DJOS and DiOS compared to sham. Cell proliferation (PCNA) was significantly elevated in DJOS and DiOS compared to sham. Conclusion In this interventional model of bariatric surgery in severe genetic diabetes, we demonstrate post-operative histologic and immunohistologic features of the pancreas associated with improved fasting glucose homeostasis. Graphical abstract

We describe a sequential multistaining protocol for immunohistochemistry, immunofluorescence and CyTOF imaging for formalin-fixed, paraffin-embedded specimens (FFPE) in the formalin gas-phase (FOLGAS), enabling sequential multistaining, independent from the primary and secondary antibodies and retrieval. Histomorphologic details are preserved, and crossreactivity and loss of signal intensity are not detectable. Combined with a DAB-based hydrophobic masking of metal-labeled primary antibodies, FOLGAS allows the extended use of CyTOF imaging in FFPE sections.

Micronuclei are DNA-containing structures separate from the nucleus found in cancer cells. Micronuclei are recognized by the immune sensor axis cGAS/STING, driving cancer metastasis. The mitochondrial apoptosis apparatus can be experimentally triggered to a non-apoptotic level, and this can drive the appearance of micronuclei through the Caspase-activated DNAse (CAD). We tested whether spontaneously appearing micronuclei in cancer cells are linked to sub-lethal apoptotic signals. Inhibition of mitochondrial apoptosis or of CAD reduced the number of micronuclei in tumor cell lines as well as the number of chromosomal misalignments in tumor cells and intestinal organoids. Blockade of mitochondrial apoptosis or deletion of CAD reduced, while experimental activation CAD, STING-dependently, enhanced aggressive growth of tumor cells in vitro. Deletion of CAD from human cancer cells reduced metastasis in xenograft models. CAD-deficient cells displayed a substantially altered gene-expression profile, and a CAD-associated gene expression ‘signature’ strongly predicted survival in cancer patients. Thus, low-level activity in the mitochondrial apoptosis apparatus operates through CAD-dependent gene-induction and STING-activation and has substantial impact on metastasis in cancer.

The bacterium Helicobacter pylori induces gastric inflammation and predisposes to cancer. H. pylori-infected epithelial cells secrete cytokines and chemokines and undergo DNA-damage. We show that the host cell’s mitochondrial apoptosis system contributes to cytokine secretion and DNA-damage in the absence of cell death. H. pylori induced secretion of cytokines/chemokines from epithelial cells, dependent on the mitochondrial apoptosis machinery. A signalling step was identified in the release of mitochondrial Smac/DIABLO, which was required for alternative NF-κB-activation and contributed to chemokine secretion. The bacterial cag-pathogenicity island and bacterial muropeptide triggered mitochondrial host cell signals through the pattern recognition receptor NOD1. H. pylori-induced DNA-damage depended on mitochondrial apoptosis signals and the caspase-activated DNAse. In biopsies from H. pylori-positive patients, we observed a correlation of Smac-levels and inflammation. Non-apoptotic cells in these samples showed evidence of caspase-3-activation, correlating with phosphorylation of the DNA-damage response kinase ATM. Thus, H. pylori activates the mitochondrial apoptosis pathway to a sub-lethal level. During infection, Smac has a cytosolic, pro-inflammatory role in the absence of apoptosis. Further, DNA-damage through sub-lethal mitochondrial signals is likely to contribute to mutagenesis and cancer development.

Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis-promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.

Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis-promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.

Introduction/Background* Patients with high-grade endometrial carcinoma (EC) have an increased risk of lymph node metastasis (LNM). Preoperative serum CA125 and imaging findings have been incorporated in multiple risk stratification models to predict LNM and advanced disease in EC and are widely used in clinical practice. However, data on their predictive value in high-grade EC are limited. We therefore aim to determine the predictive value of CA125 combined with preoperative computed tomography (CT) imaging in high-grade EC for LNM. Methodology Retrospective multicentre cohort study including patients (n=334) with preoperative high-grade EC and available CA125. Clinical data including imaging results, primary surgical treatment and final International Federation of Gynaecology and Obstetrics (FIGO) stage were recorded. CA125 was considered elevated at >35 IU/L. Result(s)* Patients with high-grade EC (n=334) and elevated CA125 more often presented with advanced FIGO stage (III-IV), 64.2% (95/148) versus 18.8% (35/186) in patients with normal CA125 (p Multivariate analysis (table 2) showed that elevated CA125, histological deep (>50%) myometrial invasion, and cervical involvement independently predict histological LNM (p Conclusion* This study demonstrates that elevated CA125 in patients with high-grade EC is an important prognostic marker for the predication of LNM and advanced stage disease. In patients with preoperative normal CA125, the additional value of CT imaging was limited with respect to the prediction of LNM. We therefore recommend to incorporate CA125 in routine preoperative work-up for risk stratification in high-grade EC.

An overwhelming number of proteomics software tools and algorithms have been published for different steps of Data Independent Acquisition analysis of clinical samples. Nonetheless, there is still a lack of comprehensive benchmark studies evaluating which combinations of those isolated components perform best.Here, we used 92 lymph nodes from distinct patients to create a unique benchmark dataset representing real-world inter-individual heterogeneity. The publicly available dataset comprises 118 LC-MS/MS runs with > 12 million MS2 spectra and allowed us to objectively evaluate how well different combinations of spectral libraries, DIA software, sparsity reduction, normalization and statistical tests can detect differentially abundant proteins, while also taking sample size into account.Evaluation of 2 million data analysis workflows showed that a gas phase fractionation refined spectral library in combination with DIA-NN and Significance Analysis of Microarrays reliably detected differentially abundant proteins. Furthermore, DIA-NN and Spectronaut robustly avoided the false detection of truly absent proteins.*KF and EB share first authorship. CK and OS share last authorship.

Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best.