Evaluation of automatic discrimination between benign and malignant prostate tissue in the era of high precision digital pathology.

BACKGROUND: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efficient diagnostic algorithms. METHODS: Retrospectively, 106 prostate tissue samples from 48 patients (mean age, [Formula: see text] years) were included in the study. Patients suffered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open-source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms. RESULTS: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of [Formula: see text], [Formula: see text], and [Formula: see text], respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02-0.06 for ERG and PIN-4. CONCLUSIONS: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classification. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classification methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.

Tumor-associated macrophages and Tregs influence and represent immune cell infiltration of muscle-invasive bladder cancer and predict prognosis.

INTRODUCTION AND OBJECTIVE: Muscle-invasive urothelial bladder cancer (MIBC) is associated with limited response rates to systemic therapy, risk of recurrence and death. Tumor infiltrating immune cells have been associated with outcome and response to chemo-and immunotherapy in MIBC. We aimed to profile the immune cells in the tumor microenvironment (TME) to predict prognosis in MIBC and responses to adjuvant chemotherapy. METHODS: We performed multiplex immunohistochemistry (IHC) profiling and quantification of immune and stromal cells (CD3, CD4, CD8, CD163, FoxP3, PD-1, and CD45, Vimentin, αSMA, PD-L1, Pan-Cytokeratin, Ki67) in 101 patients with MIBC receiving radical cystectomy. We used uni- and multivariate survival analyses to identify cell types predicting prognosis. Samples were subdivided using K-means clustering for Treg and macrophage infiltration resulting in 3 clusters, Cluster 1: Treg high, cluster 2: macrophage high, cluster 3: Treg and macrophage low. Routine CD68 and CD163 IHC were analyzed with QuPath in an extended cohort of 141 MIBC. RESULTS: High concentrations of macrophages were associated with increased risk of death (HR 10.9, 95% CI 2.8-40.5; p < 0.001) and high concentrations of Tregs were associated with decreased risk of death (HR 0.1, 95% CI 0.01-0.7; p = 0.03) in the multivariate Cox-regression model adjusting for adjuvant chemotherapy, tumor and lymph node stage. Patients in the macrophage rich cluster (2) showed the worst OS with and without adjuvant chemotherapy. The Treg rich cluster (1) showed high levels of effector and proliferating immune cells and had the best survival. Cluster 1 and 2 both were rich in PD-1 and PD-L1 expression on tumor and immune cells. CONCLUSION: Treg and macrophage concentrations in MIBC are independent predictors of prognosis and are important players in the TME. Standard IHC with CD163 for macrophages is feasible to predict prognosis but validation to use immune-cell infiltration, especially to predict response to systemic therapies, is required.

The age of the bone marrow microenvironment influences B-cell acute lymphoblastic leukemia progression via CXCR5-CXCL13.

B-cell acute lymphoblastic leukemia (B-ALL) occurs most commonly in children, whereas chronic myeloid leukemia is more frequent in adults. The myeloid bias of hematopoiesis in elderly individuals has been considered causative, but the age of the bone marrow microenvironment (BMM) may be contributory. Using various murine models of B-ALL in young vs old mice, we recapitulated B-ALL preponderance in children vs adults. We showed differential effects of young vs old BM macrophages on B-ALL cell function. Molecular profiling using RNA- and ATAC-sequencing revealed pronounced differences in young vs old BMM-derived macrophages and enrichment for gene sets associated with inflammation. In concordance with the role of C-X-C motif chemokine (CXCL) 13 for disease-associated B-cell chemoattraction, we found CXCL13 to be highly expressed in young macrophages on a translational compared with a transcriptional level. Inhibition of CXCL13 in BM macrophages impaired leukemia cell migration and decreased the proliferation of cocultured B-ALL cells, whereas recombinant CXCL13 increased pAKT and B-ALL cell expansion. Pretreatment of B-ALL-initiating cells with CXCL13 accelerated B-ALL progression. Deficiency of Cxcr5, the receptor for CXCL13, on B-ALL-initiating cells prolonged murine survival, whereas high expression of CXCR5 in pediatric B-ALL may predict central nervous system relapse. CXCL13 staining was increased in bone sections from pediatric compared with adult patients with B-ALL. Taken together, our study shows that the age of the BMM and, in particular, BM macrophages influence the leukemia phenotype. The CXCR5-CXCL13 axis may act as prognostic marker and an attractive novel target for the treatment of B-ALL.

Deep learning based on hematoxylin-eosin staining outperforms immunohistochemistry in predicting molecular subtypes of gastric adenocarcinoma.

In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond to chemotherapy or immunotherapy, according to the TCGA. In clinical practice, however, not every patient undergoes molecular testing. Many laboratories have used well-implemented in situ techniques (IHC and EBER-ISH) to determine the subclasses in their cohorts. Although multiple stains are used, we show that a staining approach is unable to correctly discriminate all subclasses. As an alternative, we trained an ensemble convolutional neuronal network using bagging that can predict the molecular subclass directly from hematoxylin-eosin histology. We also identified patients with predicted intra-tumoral heterogeneity or with features from multiple subclasses, which challenges the postulated TCGA-based decision tree for GC subtyping. In the future, deep learning may enable targeted testing for molecular subtypes and targeted therapy for a broader group of GC patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tumour cell characteristics and microenvironment composition correspond to clinical presentation in newly diagnosed nodular lymphocyte-predominant Hodgkin lymphoma.

Different studies have characterized the microenvironment and its prognostic impact in classic Hodgkin lymphoma whereas such analyses are pending for nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL). We thus investigated characteristics of tumour cells and microenvironment in NLPHL and evaluated possible correlations with the clinical presentation. Lymph node samples from 152 NLPHL patients who had first-line treatment within the randomized German Hodgkin Study Group HD16-HD18 trials were available and analysed with regard to IgD status and nuclear size of the tumour cells as well as presence of PD1-positive follicular T helper cells and CD163-positive macrophages in the microenvironment. While large tumour cell nuclei and high numbers of PD1-positive follicular T helper cells in the microenvironment were more common in patients presenting with early/intermediate stages than in patients with advanced-stage disease (p < 0.0001, unpaired t-test; p = 0.0022, Mann-Whitney test), no differences between risk groups were observed in terms of the IgD status of the tumour cells and the content of CD163-positive macrophages in the microenvironment. PD1-positive follicular T helper cells were present in both cases with typical and variant growth patterns and rosetting around the tumour cells was observed in 96% of patients, indicating an important role of PD1-positive follicular T helper cells in NLPHL.

Increased HRD score in cisplatin resistant penile cancer cells.

BACKGROUND/INTRODUCTION: Penile cancer is a rare disease in demand for new therapeutic options. Frequently used combination chemotherapy with 5 fluorouracil (5-FU) and cisplatin (CDDP) in patients with metastatic penile cancer mostly results in the development of acquired drug resistance. Availability of cell culture models with acquired resistance against standard therapy could help to understand molecular mechanisms underlying chemotherapy resistance and to identify candidate treatments for an efficient second line therapy. METHODS: We generated a cell line from a humanpapilloma virus (HPV) negative penile squamous cell carcinoma (UKF-PEC-1). This cell line was subject to chronic exposure to chemotherapy with CDDP and / or 5-FU to induce acquired resistance in the newly established chemo-resistant sublines (PEC-1rCDDP2500, adapted to 2500 ng/ml CDDP; UKF-PEC-1r5-FU500, adapted to 500 ng/ml 5- FU; UKF-PEC1rCDDP2500/r5-FU500, adapted to 2500 ng/ml CDDP and 500 ng/ml 5 -FU). Afterwards cell line pellets were formalin-fixed, paraffin embedded and subject to sequencing as well as testing for homologous recombination deficiency (HRD). Additionally, exemplary immunohistochemical stainings for p53 and gammaH2AX were applied for verification purposes. Finally, UKF-PEC-1rCDDP2500, UKF-PEC-1r5-FU500, UKF-PEC1rCDDP2500/r5-FU500, and UKF-PEC-3 (an alternative penis cancer cell line) were tested for sensitivity to paclitaxel, docetaxel, olaparib, and rucaparib. RESULTS AND CONCLUSIONS: The chemo-resistant sublines differed in their mutational landscapes. UKF-PEC-1rCDDP2500 was characterized by an increased HRD score, which is supposed to be associated with increased PARP inhibitor and immune checkpoint inhibitor sensitivity in cancer. However, UKF-PEC-1rCDDP2500 did not display sensitivity to PARP inhibitors.

The routine use of LCD-Array hybridisation technique for HPV subtyping in the diagnosis of penile carcinoma compared to other methods.

BACKGROUND: Routine human papillomavirus (HPV) testing is performed in cervival cancer and is required for classification of some head and neck cancers. In penile cancer a statement on HPV association of the carcinoma is required. In most cases p16 immunohistochemistry as a surrogate marker is applied in this setting. Since differing clinical outcomes for HPV positive and HPV negative tumors are described we await HPV testing to be requested more frequently by clinicians, also in the context of HPV vaccination, where other HPV subtypes are expected to emerge. METHOD: Therefore, a cohort of archived, formalin-fixed paraffin embedded (FFPE) penile neoplasias was stained for p16 and thereafter tested for HPV infection status via PCR based methods. Additionally to Sanger sequencing, we chose LCD-Array technique (HPV 3.5 LCD-Array Kit, Chipron; LCD-Array) for the detection of HPV in our probes expecting a less time consuming and sensitive HPV test for our probes. RESULTS: We found that LCD-Array is a sensitive and feasible method for HPV testing in routine diagnostics applicable to FFPE material in our cohort. Our cohort of penile carcinomas and carcinomas in situ was associated with HPV infection in 61% of cases. We detected no significant association between HPV infection status and histomorphological tumor characteristics as well as overall survival. CONCLUSIONS: We showed usability of molecular HPV testing on a cohort of archived penile carcinomas. To the best of our knowledge, this is the first study investigating LCD-Array technique on a cohort of penile neoplasias.

Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.

OBJECTIVES: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). METHODS: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. RESULTS: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. CONCLUSIONS: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance. KEY POINTS: • Quantitative imaging features differ between normal and malignant tissue of the peripheral zone in prostate cancer. • Radiomic feature analysis of clinical routine multiparametric MRI has the potential to improve the stratification of clinically significant versus insignificant prostate cancer lesions in the peripheral zone. • Certain combinations of standard multiparametric MRI reporting and assessment categories with feature subsets and machine learning algorithms reduced the diagnostic performance over standard clinical assessment categories alone.

Whole-exome sequencing of calcitonin-producing pancreatic neuroendocrine neoplasms indicates a unique molecular signature.

Introduction: Calcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs) are an extremely rare clinical entity, with approximately 60 cases reported worldwide. While CT-pNENs can mimic the clinical and diagnostic features of medullary thyroid carcinoma, their molecular profile is poorly understood. Methods: Whole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically validated calcitonin-positive CT-pNENs. cBioPortal analysis and DAVID gene enrichment analysis were performed to identify dysregulated candidate genes compared to control databases. Immunohistochemistry was used to detect the protein expression of MUC4 and MUC16 in CT-pNEN specimens. Results: Mutated genes known in the literature in pNENs like MEN1 (35% of cases), ATRX (18-20% of cases) and PIK3CA (1.4% of cases) were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not been described in CT- pNENs, yet. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in protein sequelae or clinical relevance. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 in two cases and MUC16 in one case, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low. Discussion: CT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, a major limitation of our study was the relative small number of only five cases. Therefore, our WES data should be interpreted with caution and the mutation landscape in CT-pNENs needs to be verified by a larger number of patients. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation and whole genome sequencing could be informative.

Overexpression of KMT9α Is Associated with Aggressive Basal-like Muscle-Invasive Bladder Cancer.

Muscle-invasive bladder cancer (MIBC) is associated with limited response rates to systemic therapy leading to a significant risk of recurrence and death. A recently discovered histone methyltransferase KMT9, acts as an epigenetic regulator of carcinogenesis in different tumor entities. In this study, we investigated the presence and association of histological and molecular subtypes and their impact on the survival of KMT9α in MIBC. We performed an immunohistochemical (IHC) analysis of KMT9α in 135 MIBC patients undergoing radical cystectomy. KMT9α was significantly overexpressed in the nucleus in MIBC compared to normal urothelium and low-grade urothelial cancer. Using the HTG transcriptome panel, we assessed mRNA expression profiles to determine molecular subtypes and identify differentially expressed genes. Patients with higher nuclear and nucleolar KMT9α expression showed basal/squamous urothelial cancer characteristics confirmed by IHC and differentially upregulated KRT14 expression. We identified a subset of patients with nucleolar expression of KMT9α, which was associated with an increased risk of death in uni- and multivariate analyses (HR 2.28, 95%CI 1.28-4.03, p = 0.005). In conclusion, basal-like MIBC and the squamous histological subtype are associated with high nuclear KMT9α expression. The association with poor survival makes it a potential target for the treatment of bladder cancer.

Transglutaminase 2 is associated with adverse colorectal cancer survival and represents a therapeutic target.

Molecular markers for predicting prognosis of colorectal cancer (CRC) patients are urgently needed for effective disease management. We reported previously that the multifunctional enzyme Transglutaminase 2 (TGM2) is essential for CRC cell survival by inactivation of the tumor suppressor p53. Based on these data, we determined the clinical relevance of TGM2 expression and explored its potential as prognostic marker and therapeutic target in CRC. We profiled TGM2 protein expression in tumor samples of 279 clinically characterized CRC patients using immunohistochemical staining. TGM2 expression was upregulated in matched tumor samples in comparison to normal tissue. A strong TGM2 expression was associated with advanced tumor stages and predicted worse prognosis regarding progression-free and overall-survival, even at early stages. Inhibition of TGM2 in CRC cell lines by the inhibitors LDN27219 and Tyrphostin resulted in a strong reduction of cancer cell proliferation and tumorsphere formation in vitro by induction of p53-mediated apoptosis. Primary patient-derived tumorsphere formation was significantly reduced by inhibition of TGM2. Treatment of mice with TGM2 inhibitors exhibited a significant deceleration of tumor progression. Our data indicate that high TGM2 expression in CRC is associated with worse prognosis and may serve as a therapeutic target in CRC patients with strong TGM2 expression.

Machine-Learning-Aided Prediction of Brain Metastases Development in Non-Small-Cell Lung Cancers.

PURPOSE: Non-small-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early detection is crucial to improve clinical prospects. We trained and validated classifier models to identify patients with a high risk of developing BM, as they could potentially benefit from surveillance brain MRI. METHODS: Consecutive patients with an initial diagnosis of NSCLC from January 2011 to April 2019 and an in-house chest-CT scan (staging) were retrospectively recruited at a German lung cancer center. Brain imaging was performed at initial diagnosis and in case of neurological symptoms (follow-up). Subjects lost to follow-up or still alive without BM at the data cut-off point (12/2020) were excluded. Covariates included clinical and/or 3D-radiomics-features of the primary tumor from staging chest-CT. Four machine learning models for prediction (80/20 training) were compared. Gini Importance and SHAP were used as measures of importance; sensitivity, specificity, area under the precision-recall curve, and Matthew's Correlation Coefficient as evaluation metrics. RESULTS: Three hundred and ninety-five patients compromised the clinical cohort. Predictive models based on clinical features offered the best performance (tuned to maximize recall: sensitivity∼70%, specificity∼60%). Radiomics features failed to provide sufficient information, likely due to the heterogeneity of imaging data. Adenocarcinoma histology, lymph node invasion, and histological tumor grade were positively correlated with the prediction of BM, age, and squamous cell carcinoma histology were negatively correlated. A subgroup discovery analysis identified 2 candidate patient subpopulations appearing to present a higher risk of BM (female patients + adenocarcinoma histology, adenocarcinoma patients + no other distant metastases). CONCLUSION: Analysis of the importance of input features suggests that the models are learning the relevant relationships between clinical features/development of BM. A higher number of samples is to be prioritized to improve performance. Employed prospectively at initial diagnosis, such models can help select high-risk subgroups for surveillance brain MRI.

CXCL1 and CXCL6 Are Potential Predictors for HCC Response to TACE.

Distinct immune patterns of hepatocellular carcinoma (HCC) may have prognostic implications in the response to transarterial chemoembolization (TACE). Thus, we aimed to exploratively analyze tumor tissue of HCC patients who do or do not respond to TACE, and to identify novel prognostic biomarkers predictive of response to TACE. We retrospectively included 15 HCC patients who had three consecutive TACE between January 2019 and November 2019. Eight patients had a response while seven patients had no response to TACE. All patients had measurable disease according to mRECIST. Corresponding tumor tissue samples were processed for differential expression profiling using NanoString nCounter® PanCancer immune profiling panel. Immune-related pathways were broadly upregulated in TACE responders. The top differentially regulated genes were the upregulated CXCL1 (log2fc 4.98, Benjamini-Hochberg (BH)-p < 0.001), CXCL6 (log2fc 4.43, BH-p = 0.016) and the downregulated MME (log2fc -4.33, BH-p 0.001). CD8/T-regs was highly increased in responders, whereas the relative number of T-regs to tumor-infiltrating lymphocytes (TIL) was highly decreased. We preliminary identified CXCL1 and CXCL6 as candidate genes that might have the potential to serve as therapeutically relevant biomarkers in HCC patients. This might pave the way to improve patient selection for TACE in HCC patients beyond expert consensus.

Active Autophagy Is Associated with Favorable Outcome in Patients with Surgically Resected Cholangiocarcinoma.

Data on the impact of autophagy in primary cholangiocarcinoma (CCA) remain scarce. Here, we therefore investigated the role of active autophagy and its impact on survival in CCA patients. All CCA patients who underwent surgical resection with curative intent between 08/2005 and 12/2021 at University Hospital Frankfurt were evaluated. Autophagic key proteins were studied by immunohistochemistry. iCCA processed for gene expression profiling of immune-exhaustion gene sets was used for an autophagy approach in silico. Active autophagy was present in 23.3% of the 172 CCA patients. Kaplan-Meier curves revealed median OS of 68.4 months (95% CI = 46.9-89.9 months) and 32.7 months (95% CI = 23.6-41.8 months) for active and non-active autophagy, respectively (p ≤ 0.001). In multivariate analysis, absence of active autophagy (HR = 2, 95% CI = 1.1-3.5, p = 0.015) was an independent risk factor for OS. Differential-expression profiling revealed significantly upregulated histone deacetylases (HDAC) mRNA in patients showing non-active autophagy. In line with this, pan-acetylated lysine was significantly more prominent in CCA patients with ongoing autophagy (p = 0.005). Our findings strengthen the role of active autophagy as a prognostically relevant marker and a potential therapeutic target.

Analytical Validation of an Immunohistochemical 7-Biomarker Prognostic Assay (immunoprint®) for Early-Stage Cutaneous Melanoma in Archival Tissue of Patients with AJCC v8 T2-T3 Disease.

Selected patients with early-stage melanoma have a "hidden high risk" of poor oncologic outcomes. They might benefit from clinical trials, and ultimately, if warranted by trial results, judicious everyday use of adjuvant therapy. A promising tool to identify these individuals is the immunoprint® assay. This immunohistochemical 7-biomarker prognostic test was clinically validated in three independent cohorts (N = 762) to classify early-stage patients as high-risk or low-risk regarding melanoma recurrence and mortality. Using College of American Pathologists (CAP) recommendations, we analytically validated this assay in primary melanoma specimens (N = 20 patients). We assessed assay precision by determining consistency of risk classification under repeated identical conditions (repeatability) or across varying conditions (reproducibility), involving separate assay runs, operators (laboratory scientists), and/or observers (e.g., dermatopathologists). Reference classification was followed by five analytical validation phases: intra-run/intra-operator, intra-observer, inter-run, inter-operator, and inter-observer. Concordance of classifications in each phase was assessed via Fleiss' kappa (primary endpoint) and percent agreement (secondary endpoint). Seven-marker signature classification demonstrated high consistency across validation categories (Fleiss' kappa 0.864-1.000; overall percent agreement 95-100%), in 9/10 cases, exceeding, and in 1/10 cases, closely approaching, CAP's recommended 0.9 level. The 7-marker assay has now been verified to provide excellent repeatability, reproducibility, and precision, besides having been clinically validated.

Impact of mesenchymal stromal cell-derived vesicular cargo on B-cell acute lymphoblastic leukemia progression.

Leukemia cells reciprocally interact with their surrounding bone marrow microenvironment (BMM), rendering it hospitable to leukemia cell survival, for instance through the release of small extracellular vesicles (sEVs). In contrast, we show here that BMM deficiency of pleckstrin homology domain family M member 1 (PLEKHM1), which serves as a hub between fusion and secretion of intracellular vesicles and is important for vesicular secretion in osteoclasts, accelerates murine BCR-ABL1+ B-cell acute lymphoblastic leukemia (B-ALL) via regulation of the cargo of sEVs released by BMM-derived mesenchymal stromal cells (MSCs). PLEKHM1-deficient MSCs and their sEVs carry increased amounts of syntenin and syndecan-1, resulting in a more immature B-cell phenotype and an increased number/function of leukemia-initiating cells (LICs) via focal adhesion kinase and AKT signaling in B-ALL cells. Ex vivo pretreatment of LICs with sEVs derived from PLEKHM1-deficient MSCs led to a strong trend toward acceleration of murine and human BCR-ABL1+ B-ALL. In turn, inflammatory mediators such as recombinant or B-ALL cell-derived tumor necrosis factor α or interleukin-1ß condition murine and human MSCs in vitro, decreasing PLEKHM1, while increasing syntenin and syndecan-1 in MSCs, thereby perpetuating the sEV-associated circuit. Consistently, human trephine biopsies of patients with B-ALL showed a reduced percentage of PLEKHM1+ MSCs. In summary, our data reveal an important role of BMM-derived sEVs for driving specifically BCR-ABL1+ B-ALL, possibly contributing to its worse prognosis compared with BCR-ABL1- B-ALL, and suggest that secretion of inflammatory cytokines by cancer cells in general may similarly modulate the tumor microenvironment.

CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients.

We aimed to identify hepatocellular carcinoma (HCC) patients who will respond to repetitive transarterial chemoembolization (TACE) to improve the treatment algorithm. Retrospectively, 61 patients (mean age, 65.3 years ± 10.0 [SD]; 49 men) with 94 HCC mRECIST target-lesions who had three consecutive TACE between 01/2012 and 01/2020 were included. Robust and non-redundant radiomics features were extracted from the 24 h post-embolization CT. Five different clinical TACE-scores were assessed. Seven different feature selection methods and machine learning models were used. Radiomics, clinical and combined models were built to predict response to TACE on a lesion-wise and patient-wise level as well as its impact on overall-survival prognostication. 29 target-lesions of 19 patients were evaluated in the test set. Response rates were 37.9% (11/29) on the lesion-level and 42.1% (8/19) on the patient-level. Radiomics top lesion-wise response prognostications was AUC 0.55-0.67. Clinical scores revealed top AUCs of 0.65-0.69. The best working model combined the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical score mHAP_II_score_group with AUC = 0.70, accuracy = 0.72. We transferred this model on a patient-level to achieve AUC = 0.62, CI = 0.41-0.83. The two radiomics-clinical features revealed overall-survival prognostication of C-index = 0.67. In conclusion, a random forest model using the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical mHAP-II-score-group seems promising for TACE response prognostication.

Metabolic reprogramming of hepatocytes by Schistosoma mansoni eggs.

Background & Aims: Schistosomiasis is a parasitic infection which affects more than 200 million people globally. Schistosome eggs, but not the adult worms, are mainly responsible for schistosomiasis-specific morbidity in the liver. It is unclear if S. mansoni eggs consume host metabolites, and how this compromises the host parenchyma. Methods: Metabolic reprogramming was analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging, liquid chromatography with high-resolution mass spectrometry, metabolite quantification, confocal laser scanning microscopy, live cell imaging, quantitative real-time PCR, western blotting, assessment of DNA damage, and immunohistology in hamster models and functional experiments in human cell lines. Major results were validated in human biopsies. Results: The infection with S. mansoni provokes hepatic exhaustion of neutral lipids and glycogen. Furthermore, the distribution of distinct lipid species and the regulation of rate-limiting metabolic enzymes is disrupted in the liver of S. mansoni infected animals. Notably, eggs mobilize, incorporate, and store host lipids, while the associated metabolic reprogramming causes oxidative stress-induced DNA damage in hepatocytes. Administration of reactive oxygen species scavengers ameliorates these deleterious effects. Conclusions: Our findings indicate that S. mansoni eggs completely reprogram lipid and carbohydrate metabolism via soluble factors, which results in oxidative stress-induced cell damage in the host parenchyma. Impact and implications: The authors demonstrate that soluble egg products of the parasite S. mansoni induce hepatocellular reprogramming, causing metabolic exhaustion and a strong redox imbalance. Notably, eggs mobilize, incorporate, and store host lipids, while the metabolic reprogramming causes oxidative stress-induced DNA damage in hepatocytes, independent of the host's immune response. S. mansoni eggs take advantage of the host environment through metabolic reprogramming of hepatocytes and enterocytes. By inducing DNA damage, this neglected tropical disease might promote hepatocellular damage and thus influence international health efforts.

Colorectal Cancer Organoid-Stroma Biobank Allows Subtype-Specific Assessment of Individualized Therapy Responses.

In colorectal cancers, the tumor microenvironment plays a key role in prognosis and therapy efficacy. Patient-derived tumor organoids (PDTO) show enormous potential for preclinical testing; however, cultured tumor cells lose important characteristics, including the consensus molecular subtypes (CMS). To better reflect the cellular heterogeneity, we established the colorectal cancer organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAF) from 30 patients. Context-specific phenotyping showed that xenotransplantation or coculture with CAFs improves the transcriptomic fidelity and instructs subtype-specific stromal gene expression. Furthermore, functional profiling in coculture exposed CMS4-specific therapeutic resistance to gefitinib and SN-38 and prognostic expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as a common target. Our results demonstrate that colorectal cancer phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for a faithful representation of molecular subtypes and therapy responses ex vivo. SIGNIFICANCE: Systematic characterization of the organoid-stroma biobank provides a resource for context dependency in colorectal cancer. We demonstrate a colorectal cancer subtype memory of PDTOs that is independent of specific driver mutations. Our data underscore the importance of functional profiling in cocultures for improved preclinical testing and identification of stromal resistance mechanisms. This article is featured in Selected Articles from This Issue, p. 2109.

Expression of MUC16/CA125 Is Associated with Impaired Survival in Patients with Surgically Resected Cholangiocarcinoma.

MUC16/CA125 is associated with cancer proliferation in several tumor entities. The data on MUC16 expression in cholangiocarcinoma (CCA) tissue are very limited. The aim of this study was to assess the MUC16 status and its impact on survival in CCA patients. All the patients with surgically resected CCA that were diagnosed between August 2005 and December 2021 at the University Hospital Frankfurt were retrospectively analyzed. A 7-Mucin biomarker panel was assessed by immunohistochemistry. For overall survival (OS), Kaplan−Meier curves and Cox-regression analyses were performed. Randomly selected intrahepatic cholangiocarcinoma (iCCA) were further processed for differential expression profiling. A total of 168 patients with CCA were classified as MUC16 (−) (66%, n = 111) and MUC16 (+) (34%, n = 57). Subgroup analyses revealed a median OS of 56.1 months (95% CI = 42.4−69.9 months) and 27.4 months (95% CI = 15.8−39.1 months) for MUC16 (−) and MUC16 (+), respectively (p < 0.001). In multivariate analysis, MUC16 (+) (HR = 1.6, 95% CI = 1−2.6, p = 0.032) was an independent risk factor for poor prognosis. Prominently deregulated pathways have been identified following MUC16 expression, overrepresented in cell cycle and immune system exhaustion processes. These findings suggest including MUC16 in clinical routine diagnostics as well as studying its molecular pathways to identify further mechanistic key players.