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The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomarkers are imperfect. Here, we used an end-to-end deep learning algorithm to identify risk factors for lymph node metastasis (LNM) status in digitized histopathology slides of the primary CRC and its surrounding tissue. In two large population-based cohorts, we show that this system can predict the presence of more than one LNM in pT2 CRC patients with an area under the receiver operating curve (AUROC) of 0.733 (0.67-0.758) and patients with any LNM with an AUROC of 0.711 (0.597-0.797). Similarly, in pT1 CRC patients, the presence of more than one LNM or any LNM was predictable with an AUROC of 0.733 (0.644-0.778) and 0.567 (0.542-0.597), respectively. Based on these findings, we used the deep learning system to guide human pathology experts towards highly predictive regions for LNM in the whole slide images. This hybrid human observer and deep learning approach identified inflamed adipose tissue as the highest predictive feature for LNM presence. Our study is a first proof of concept that artificial intelligence (AI) systems may be able to discover potentially new biological mechanisms in cancer progression. Our deep learning algorithm is publicly available and can be used for biomarker discovery in any disease setting. © 2021 The Pathological Society of Great Britain and Ireland. Published by John WileySons, Ltd.

Background While a certain degree of tumor infiltration of the portal vein is common in patients with perihilar cholangiocarcinoma (pCCA) scheduled for surgery, complete tumor-associated portal vein occlusion (PVO) is less frequently observed. Here, we analyzed the impact of PVO on perioperative and oncological outcomes in pCCA patients. Methods Between 2010 and 2019, 127 patients with pCCA underwent surgery in curative intent at our department of which 17.3% (22/127) presented with PVO. Extensive group comparisons were conducted and the association of cancer-specific (CSS) and disease-free survival (DFS) with PVO and other clinico-pathological characteristics were assessed using Cox regression models. Results Patients without PVO showed a median CSS of 65 months (3-year-CSS = 64%, 5-year-CSS = 53%) compared to 31 months (3-year-CSS = 43%, 5-year-CSS = 17%) in patients with PVO (p = 0.025 log rank). Patients with PVO did also display significant perioperative mortality (22.7%, 5/22) compared to patients without PVO (14.3%, 15/105, p = 0.323). Further, PVO (CSS: HR = 5.25, p = 0.001; DFS: HR = 5.53, p = 0.001) was identified as independent predictors of oncological outcome. Conclusions PVO has been identified as an important prognostic marker playing a role in inferior oncological outcome in patients with pCCA. As PVO is also associated with notable perioperative mortality, surgical therapy should be considered carefully in pCCA patients.

Langenbeck's archives of surgery (2022). doi:10.1007/s00423-022-02545-1, Published by Springer, Berlin ; Heidelberg

HPB : official jouarnal of The International Hepato-Pancreato-Biliary 24(9), 1433-1442 (2022). doi:10.1016/j.hpb.2022.01.009, Published by Elsevier, [London]

The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. Site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the image characteristics constituting this site-specific digital histology signature. We demonstrate that these site-specific signatures lead to biased accuracy for prediction of features including survival, genomic mutations, and tumor stage. Furthermore, ethnicity can also be inferred from site-specific signatures, which must be accounted for to ensure equitable application of DL. These site-specific signatures can lead to overoptimistic estimates of model performance, and we propose a quadratic programming method that abrogates this bias by ensuring models are not trained and validated on samples from the same site., Deep learning models have been trained on The Cancer Genome Atlas to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. Here, the authors demonstrate that site-specific histologic signatures can lead to biased estimates of accuracy for such models, and propose a method to minimize such bias.

Oncogene : including Oncogene reviews 40(5), 899-908 (2021). doi:10.1038/s41388-020-01578-4, Published by Springer Nature, London

Background The majority of patients with pancreatic cancer develops cachexia. The mechanisms underlying cancer cachexia development and progression remain elusive, although tumour‐derived factors are considered to play a major role. Pancreatic tumour organoids are in vitro three‐dimensional organ‐like structures that retain many pathophysiological characteristics of the in vivo tumour. We aimed to establish a pancreatic tumour organoid biobank from well‐phenotyped cachectic and non‐cachectic patients to enable identification of tumour‐derived factors driving cancer cachexia. Methods Organoids were generated from tumour tissue of eight pancreatic cancer patients. A comprehensive pre‐operative patient assessment of cachexia‐related parameters including nutritional status, physical performance, body composition, and inflammation was performed. Tumour‐related and cachexia‐related characteristics of the organoids were analysed using histological stainings, targeted sequencing, and real‐time–quantitative PCR. Cachexia‐related factors present in the circulation of the patients and in the tumour organoid secretome were analysed by enzyme‐linked immunosorbent assay. Results The established human pancreatic tumour organoids presented typical features of malignancy corresponding to the primary tumour (i.e. nuclear enlargement, multiple nucleoli, mitosis, apoptosis, and mutated KRAS and/or TP53). These tumour organoids also expressed variable levels of many known cachexia‐related genes including interleukin‐6 (IL‐6), TNF‐α, IL‐8, IL‐1α, IL‐1β, Mcp‐1, GDF15, and LIF. mRNA expression of IL‐1α and IL‐1β was significantly reduced in organoids from cachectic vs. non‐cachectic patients (IL‐1α: −3.8‐fold, P = 0.009, and IL‐1β: −4.7‐fold, P = 0.004). LIF, IL‐8, and GDF15 mRNA expression levels were significantly higher in organoids from cachectic vs. non‐cachectic patients (LIF: 1.6‐fold, P = 0.003; IL‐8: 1.4‐fold, P = 0.01; GDF15: 2.3‐fold, P

Background The presence of lymph node metastasis (LNmets) is a poor prognostic factor in oesophageal cancer (OeC) patients treated with neoadjuvant chemoradiotherapy (nCRT) followed by surgery. Tumour regression grade (TRG) in LNmets has been suggested as a predictor for survival. The aim of this study was to investigate whether TRG in LNmets is related to their location within the radiotherapy (RT) field. Methods Histopathological TRG was retrospectively classified in 2565 lymph nodes (LNs) from 117 OeC patients treated with nCRT and surgery as: (A) no tumour, no signs of regression; (B) tumour without regression; (C) viable tumour and regression; and (D) complete response. Multivariate survival analysis was used to investigate the relationship between LN location within the RT field, pathological TRG of the LN and TRG of the primary tumour. Results In 63 (54%) patients, viable tumour cells or signs of regression were seen in 264 (10.2%) LNs which were classified as TRG-B (n = 56), C (n = 104) or D (n = 104) LNs. 73% of B, C and D LNs were located within the RT field. There was a trend towards a relationship between LN response and anatomical LN location with respect to the RT field (p = 0.052). Multivariate analysis showed that only the presence of LNmets within the RT field with TRG-B is related to poor overall survival. Conclusion Patients have the best survival if all LNmets show tumour regression, even if LNmets are located outside the RT field. Response in LNmets to nCRT is heterogeneous which warrants further studies to better understand underlying mechanisms.

BACKGROUND: Pancreatic tumors are frequently diagnosed in a locally advanced stage with poor prognosis if untreated. This study assesses the safety and oncological outcomes of pancreatic surgery with arterial en-bloc resection.METHODS: We retrospectively reviewed a prospectively maintained database of patients who underwent a pancreatic resection with arterial resection between 2011 and 2020. Univariable analyses were used to assess prognostic factors for survival.RESULTS: Forty consecutive patients (22 female; 18 male) undergoing arterial resections were included. Surgical procedures consisted of 19 pancreatoduodenectomies (PD, 48%), 16 distal splenopancreatectomy (DSP, 40%), and 5 total pancreatectomies (TP, 12%). Arterial resection included hepatic arteries (HA, N = 23), coeliac trunk (TC, N = 15) and superior mesenteric artery (SMA, N = 2). Neoadjuvant therapy was applied in 22 patients (58%). Major complications after surgery were observed in 15% of cases. 90-day mortality was 5%. Median disease-free survival and median overall survival were for the R0/CRM- group 22.8 months and 27.9 months, 9.5 and 19.8 months for the R0/CRM+ group, and 10.1 and 13.1 months for the R1 group, respectively.CONCLUSION: In highly selected patients, arterial en-bloc resection can be performed with acceptable mortality and morbidity rates and beneficial oncological outcome.

Cancers 14(2), 438 (2022). doi:10.3390/cancers14020438 special issue: "Special Issue "Perihilar Cholangiocarcinoma" / Special Issue Editors: Dr. Bas Groot Koerkamp, Guest Editor; r. Stefan Büttner, Guest Editor; Dr. Pim B. Olthof, Guest Editor", Published by MDPI, Basel

The journal of pathology 256(1), 50-60 (2022). doi:10.1002/path.5800, Published by Wiley, Bognor Regis [u.a.]

Scientific reports 11(1), 17936 (2021). doi:10.1038/s41598-021-97442-w, Published by Macmillan Publishers Limited, part of Springer Nature, [London]

Activation of the mechanistic target of rapamycin (mTOR) pathway is frequently found in cancer, but mTOR inhibitors have thus far failed to demonstrate significant antiproliferative efficacy in the majority of cancer types. Besides cancer cell-intrinsic resistance mechanisms, it is conceivable that mTOR inhibitors impact on non-malignant host cells in a manner that ultimately supports resistance of cancer cells. Against this background, we sought to analyze the functional consequences of mTOR inhibition in hepatocytes for the growth of metastatic colon cancer. To this end, we established liver epithelial cell (LEC)-specific knockout (KO) of mTOR (mTOR(LEC)) mice. We used these mice to characterize the growth of colorectal liver metastases with or without partial hepatectomy to model different clinical settings. Although the LEC-specific loss of mTOR remained without effect on metastasis growth in intact liver, partial liver resection resulted in the formation of larger metastases in mTOR(LEC) mice compared with wildtype controls. This was accompanied by significantly enhanced inflammatory activity in LEC-specific mTOR KO livers after partial liver resection. Analysis of NF-kappa B target gene expression and immunohistochemistry of p65 displayed a significant activation of NF-kappa B in mTOR(LEC) mice, suggesting a functional importance of this pathway for the observed inflammatory phenotype. Taken together, we show an unexpected acceleration of liver metastases upon deletion of mTOR in LECs. Our results support the notion that non-malignant host cells can contribute to resistance against mTOR inhibitors and encourage testing whether anti-inflammatory drugs are able to improve the efficacy of mTOR inhibitors for cancer therapy. (c) 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Cancers 13(15), 3661 (2021). doi:10.3390/cancers13153661, Published by MDPI, Basel

Surgery for intrahepatic cholangiocarcinoma (iCCA) is associated with a high rate of recurrence even after complete resection. To achieve acceptable results, preoperative patient selection is crucial. Hence, we aimed to identify preoperative characteristics with prognostic value focusing on certain radiological features. Patients who underwent hepatectomy for iCCA between 2010 and 2020 at University Hospital, RWTH Aachen were included. Kaplan–Meier and Cox regressions were applied for survival analysis and associations of overall survival (OS) and recurrence-free survival (RFS) with clinical/radiological characteristics, respectively. Based on radiological features patients were stratified into three groups: single nodule ≤ 3 cm, single nodule &gt, 3 cm, and ≥ 2 nodules. Analysis of 139 patients revealed a mean OS of 142 months for those with a single nodule ≤ 3 cm, median OS of 28 months with a single nodule &gt, 3 cm, and 19 months with ≥ 2 nodules, respectively. Multivariable analyses based on preoperative characteristics showed the radiological stratification to be independently associated with OS (HR (hazard ratio) = 4.25 (1 nodule, &gt, 3 cm), HR = 5.97 (≥ 2 nodules), p = 0.011), RFS (HR = 4.18 (1 nodule, &gt, 3 cm), and HR = 11.07 (≥2 nodules), p = 0.001). In conclusion, patients with single iCCA ≤ 3 cm show compelling OS and RFS. Basic radiological features (e.g., nodule size, number) are prognostic for patients undergoing surgery and useful in preoperative patient selection.

Cancer & metabolism 9, 26 (2021). doi:10.1186/s40170-021-00262-9, Published by Biomed Central, London

Liver cancer 10(3), 260-274 (2021). doi:10.1159/000515303, Published by Karger, Basel

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5‐year survival rate of, What's new? While several transcriptomic classifications of pancreatic adenocarcinoma (PDAC) have been proposed, a unified classification would be valuable to inform future treatment strategies. Through an integrative meta‐analysis of 353 patients from four different studies, the authors found that the greatest prognostic value in independent cohorts could be achieved through stratification by gene expression signatures associated with tumour‐infiltrating immune cells across different pancreatic cancer subtypes. Recognising the existence of different tumour escape mechanisms (and indeed phenotypes) in pancreatic cancer may guide immunotherapeutic treatment plans and improve patient stratification for maximization of therapeutics.

Introduction:Although advances in understanding the molecular basis of cholangiocarcinoma (CCA) have been made, surgery is the only curative therapy option and the overall prognosis of patients suffering from the disease remains poor. Therefore, estimation of prognosis based on known and novel biomarkers is essential for therapy guidance of CCA in both, curative and palliative settings.Areas covered:An extensive literature search on biomarkers for CCA with special emphasis on prognosis was performed. Based on this, prognostic biomarkers from serum, tumor tissue and other compartments that are currently in use or under evaluation for CCA were summarized in this review. Furthermore, an overview of new biomarkers was provided including those determined from extracellular vesicles (EVs), metabolites and nucleic acids. Finally, prognostic markers associated with potential new therapy options for the treatment of CCA were summed up.Expert opinion:So far, an optimal prognostic biomarker for CCA has not been described. However, based on the increasing knowledge about the molecular basis of CCA but also due to novel, innovative technologies, a plethora of novel prognostic biomarkers is currently under evaluation and will be available for CCA in future.

Simple Summary Pancreatic cancer has the worst survival of any human cancer. Checkpoint blockade has not yielded much benefit in pancreatic cancer. We explored immune cell phenotypes with this disease to identify new targets for checkpoint blockade therapy. We created a checkpoint-focused panel to analyse immune cells from eight pancreatic cancer patients. This showed us the majority of T-cells are senescent. Further T-cell investigation demonstrated the majority of cytotoxic T-cells have intermediate to low PD1 expression suggesting why PD1 may not work as a pancreatic cancer therapy strategy. Our data has also highlighted a regulatory T-cell population which is highly activated and can mediate immunosuppression. The checkpoints that are highly expressed on these cells are TIGIT, ICOS and CD39, suggesting inhibition of these may be a viable therapeutic strategy. Furthermore, we showed that Tregs were retained amongst the fibroblast stroma of the tumour. Our work suggests there are key checkpoints on Tregs that may help guide therapeutic strategies in pancreatic cancer. Abstract Pancreatic cancer has one of the worst prognoses of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies. In this study, we analysed 32 human pancreatic cancer patients from two independent cohorts. A multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment. Regulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8+ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset. These data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies multiple novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.

Journal of Clinical Medicine 10(3), 490 (2021). doi:10.3390/jcm10030490 special issue: "Special Issue "Pancreatic Cancer: Challenges and Breakthroughs" / Special Issue Editor: Dr. Maria Del Pilar Acedo Nunez, Guest Editor", Published by MDPI, Basel

BACKGROUND: Perihilar cholangiocarcinoma (pCCA) is a rare tumour that requires complex multidisciplinary management. All known data are almost exclusively derived from expert centres. This study aimed to analyse the outcomes of patients with pCCA in a nationwide cohort. METHODS: Data on all patients diagnosed with pCCA in the Netherlands between 2010 and 2018 were obtained from the Netherlands Cancer Registry. Data included type of hospital of diagnosis and the received treatment. Outcomes included the type of treatment and overall survival. RESULTS: A total of 2031 patients were included and the median overall survival for the overall cohort was 5.2 (95% CI 4.7-5.7) months. Three-hundred-ten (15%) patients underwent surgical resection, 271 (13%) underwent palliative systemic treatment, 21 (1%) palliative local anti-cancer treatment and 1429 (70%) underwent best supportive care. These treatments resulted in a median overall survival of 29.6 (95% CI 25.2-34.0), 12.2 (95% CI 11.0-13.3), 14.5 (95%CI 8.2-20.8) and 2.9 (95% CI 2.6-3.2) months respectively. Resection rate was 13% in patients who were diagnosed in non-academic and 32% in academic centres (P

Scientific reports 11(1), 2926 (2021). doi:10.1038/s41598-021-82378-y, Published by Macmillan Publishers Limited, part of Springer Nature, [London]

The lancet / Digital health 3(10), e654-e664 (2021). doi:10.1016/S2589-7500(21)00133-3, Published by The Lancet, London

Scientific reports 11, 13368 (2021). doi:10.1038/s41598-021-92798-5, Published by Macmillan Publishers Limited, part of Springer Nature, [London]

Introduction: Ampullary cancer is rare and as a result epidemiological data are scarce. The aim of this population-based study was to determine the trends in incidence, treatment and overall survival (OS) in patients with ampullary adenocarcinoma in the Netherlands between 1989 and 2016.Methods: Patients diagnosed with ampullary adenocarcinoma were identified from the Netherlands Cancer Registry. Incidence rates were age-adjusted to the European standard population. Trends in treatment and OS were studied over (7 years) period of diagnosis, using Kaplan-Meier and Cox regression analyses for OS and stratified by the presence of metastatic disease.Results: In total, 3840 patients with ampullary adenocarcinoma were diagnosed of whom, 55.0% were male and 87.1% had non-metastatic disease. The incidence increased from 0.59 per 100,000 in 1989-1995 to 0.68 per 100,000in 2010-2016. In non-metastatic disease, the resection rate increased from 49.5% in 1989-1995 to 63.9% in 2010-2016 (p < 0.001). The rate of adjuvant therapy increased from 3.1% to 7.9%. In non-metastatic disease, five-year OS (95% CI) increased from 19.8% (16.9-22.8) in 1989-1995 to 29.1% (26.0-31.2) in 2010e2016 (logrank p < 0.001). In patients with metastatic disease, median OS did not significantly improve (from 4.4 months (3.6-5.0) to 5.9 months (4.7-7.1); logrank p = 0.06). Cancer treatment was an independent prognostic factor for OS among all patients.Conclusion: Both incidence and OS of ampullary cancer increased from 1989 to 2016 which is most likely related to the observed increased resection rates and use of adjuvant therapy. (C) 2021 The Authors. Published by Elsevier Ltd.

INTRODUCTION: Major hepatectomy for perihilar and intrahepatic cholangiocarcinoma (CCA) is often associated with a significant intraoperative blood loss and the requirement for perioperative transfusion of blood products. The aim of this study was to investigate the oncological impact of fresh frozen plasma (FFP) transfusion during hospitalization in patients undergoing hepatectomy for CCA as adverse effects have been described in other malignancies.MATERIAL AND METHODS: Patients undergoing hepatectomy for CCA from 2010 to 2019 at a single institution were eligible for this study. Survival analysis was carried out according to Kaplan-Meier and the associations of cancer-specific (CSS) and recurrence-free survival (RFS) with in-hospital application of FFP and other clinico-pathological characteristics were assessed using Cox regression models. Perioperatively deceased patients were excluded from the analysis.RESULTS: A total of 219 CCA patients were included in this survival analysis of which 53.0% (116/219) received FFP during hospitalization. Patients receiving in-hospital FFP showed a median CCS of 33 months (3-year-CSS = 46%, 5-year-CSS = 29%) compared to 83 months (3-year-CSS = 55%, 5-year-CSS = 53%) in patients who did not receive in-hospital FFP (p = 0.006 log rank). Further, in-hospital FFP was identified as an independent predictor of oncological outcome in multivariable analysis (CSS: HR = 1.71, p = 0.016; RFS: HR = 1.89, p = 0.003).CONCLUSION: In a large European cohort of patients, in-hospital transfusion of FFP was identified as a novel independent prognostic marker in CCA patients undergoing curative-intent liver surgery. A restrictive transfusion policy is therefore recommended to improve long-term outcome in these patients.

Background Metabolic reprogramming is a common phenomenon in tumorigenesis and tumor progression. Amino acids are important mediators in cancer metabolism, and their kinetics in tumor tissue are far from being understood completely. Mass spectrometry imaging is capable to spatiotemporally trace important endogenous metabolites in biological tissue specimens. In this research, we studied L-[ring-13C6]-labeled phenylalanine and tyrosine kinetics in a human non-small cell lung carcinoma (NSCLC) xenografted mouse model using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FTICR-MSI). Methods We investigated the L-[ring-13C6]-Phenylalanine (13C6-Phe) and L-[ring-13C6]-Tyrosine (13C6-Tyr) kinetics at 10 min (n = 4), 30 min (n = 3), and 60 min (n = 4) after tracer injection and sham-treated group (n = 3) at 10 min in mouse-xenograft lung tumor tissues by MALDI-FTICR-MSI. Results The dynamic changes in the spatial distributions of 19 out of 20 standard amino acids are observed in the tumor tissue. The highest abundance of 13C6-Phe was detected in tumor tissue at 10 min after tracer injection and decreased progressively over time. The overall enrichment of 13C6-Tyr showed a delayed temporal trend compared to 13C6-Phe in tumor caused by the Phe-to-Tyr conversion process. Specifically, 13C6-Phe and 13C6-Tyr showed higher abundances in viable tumor regions compared to non-viable regions. Conclusions We demonstrated the spatiotemporal intra-tumoral distribution of the essential aromatic amino acid 13C6-Phe and its de-novo synthesized metabolite 13C6-Tyr by MALDI-FTICR-MSI. Our results explore for the first time local phenylalanine metabolism in the context of cancer tissue morphology. This opens a new way to understand amino acid metabolism within the tumor and its microenvironment. Supplementary Information The online version contains supplementary material available at 10.1186/s40170-021-00262-9.

The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. This site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the digital image characteristics constituting this histologic batch effect. As an example, we show that patient ethnicity within the TCGA breast cancer cohort can be inferred from histology due to site-level batch effect, which must be accounted for to ensure equitable application of DL. Batch effect also leads to overoptimistic estimates of model performance, and we propose a quadratic programming method to guide validation that abrogates this bias.

Background and Aims: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and cheaper than molecular assays. But clinical application of this technology requires high performance and multisite validation, which have not yet been performed. Methods: We collected hematoxylin and eosin-stained slides, and findings from molecular analyses for MSI and dMMR, from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning detector to identify samples with MSI from these slides; performance was assessed by cross-validation (n=6406 specimens) and validated in an external cohort (n=771 specimens). Prespecified endpoints were area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC). Results: The deep-learning detector identified specimens with dMMR or MSI with a mean AUROC curve of 0.92 (lower bound 0.91, upper bound 0.93) and an AUPRC of 0.63 (range, 0.59–0.65), or 67% specificity and 95% sensitivity, in the cross-validation development cohort. In the validation cohort, the classifier identified samples with dMMR with an AUROC curve of 0.95 (range, 0.92–0.96) without image-preprocessing and an AUROC curve of 0.96 (range, 0.93–0.98) after color normalization. Conclusions: We developed a deep-learning system that detects colorectal cancer specimens with dMMR or MSI using hematoxylin and eosin-stained slides; it detected tissues with dMMR with an AUROC of 0.96 in a large, international validation cohort. This system might be used for high-throughput, low-cost evaluation of colorectal tissue specimens.

Langenbeck's archives of surgery 406(1), 75-86 (2021). doi:10.1007/s00423-020-02052-1, Published by Springer, Heidelberg

BackgroundB cells and tertiary lymphoid structures (TLS) are reported to be important in the improvement of survival of cancer patients. These secondary lymphoid organs have been associated with the generation of an anti-tumor response. Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types and the stromal architecture shapes the intratumoral heterogeneity. The stroma of PDAC is a complex system in which crosstalk takes place between cancer-associated fibroblasts, immune cells, endothelial cells and the cancer cells. Besides immune cells and fibroblasts, there is some limited data about the influence of nerve fibers on cancer progression.Patients and methodsNerve Fiber Density (NFD) was analysed in our cohort of 188 patients with Pancreatic Ductal Adenocarcinoma who underwent pancreatic surgery. We used immunohistochemistry and multiplex imaging to phenotype the immune cell infiltrate. The cell detection classifier measured distance from immune cell to cancer gland and with a heat map we could count TLS. By using Machine learning we were able to define the spatial distribution and counting Tertiary Lymphoid Structures.ResultsHigh NFD is significantly associated with prolonged overall survival (HR 1.676 (95%CI 1.126,2.495) for low vs. high NFD, p-value 0.0109). The immune cells surrounding the nerve fibers were phenotyped in B cells, T cells and dendritic follicular cells, matching a TLS. Here we show that small nerve fibers are located at the TLS in Pancreatic Cancer and a high Nerve Fiber Density combined with more than 5 TLS is associated with a better survival (HR 0.388 (95%CI 0.218, 0.689).ConclusionThe co-localization of small nerve fibers with TLS is a new finding which has not been described before. However the precise roles of these TLS and nerve fibers remains unknown. These findings unravel future pathways and has the potential to reach new directions into already existing targeted therapy.

Activation of the mTOR pathway is frequently found in cancer, but mTOR inhibitors have thus far failed to demonstrate significant antiproliferative efficacy in the majority of cancer types. Besides cancer cell-intrinsic resistance mechanisms, it is conceivable that mTOR inhibitors impact on non-malignant host cells in a manner that ultimately supports resistance of cancer cells. Against this background, we sought to analyze the functional consequences of mTOR inhibition in hepatocytes for the growth of metastatic colon cancer. To this end, we established a liver epithelial cell (LEC)-specific knock-out (KO) of mTOR (mTORLEC mice). We used these mice to characterize the growth of colorectal liver metastases with and without partial hepatectomy to model different clinical settings. While the LEC-specific loss of mTOR remained without effect on metastasis growth in intact liver, partial liver resection resulted in the formation of larger metastases in mTORLEC mice compared to wildtype controls. This was accompanied by significantly enhanced inflammatory activity in LEC-specific mTOR KO livers after partial liver resection. Analysis of NF-κB target gene expression and immunohistochemistry of p65 displayed a significant activation of NF-κB in mTORLEC mice, suggesting a functional importance of this pathway for the observed inflammatory phenotype. Taken together, we show an unexpected acceleration of liver metastases upon deletion of mTOR in liver epithelial cells. Our results support the notion that non-malignant host cells can contribute to resistance against mTOR inhibitors and encourage to test if anti-inflammatory drugs are able to improve the efficacy of mTOR inhibitor for cancer therapy.

Molecular alterations in cancer can cause phenotypic changes in tumor cells and their microenvironment. Routine histopathology tissue slides, which are ubiquitously available, can reflect such morphological changes. Here, we show that deep learning can consistently infer a wide range of genetic mutations, molecular tumor subtypes, gene expression signatures and standard pathology biomarkers directly from routine histology. We developed, optimized, validated and publicly released a one-stop-shop workflow and applied it to tissue slides of more than 5,000 patients across multiple solid tumors. Our findings show that a single deep learning algorithm can be trained to predict a wide range of molecular alterations from routine, paraffin-embedded histology slides stained with hematoxylin and eosin. These predictions generalize to other populations and are spatially resolved. Our method can be implemented on mobile hardware, potentially enabling point-of-care diagnostics for personalized cancer treatment. More generally, this approach could elucidate and quantify genotype-phenotype links in cancer. Two papers by Kather and colleagues and Gerstung and colleagues develop workflows to predict a wide range of molecular alterations from pan-cancer digital pathology slides.

Pancreatic cancer has the worst prognosis of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies.In this study, we analysed 32 human pancreatic cancer patients from two independent cohorts. A multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment.Regulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8+ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset from additional 24 patients.These data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.

Chorioamnionitis can lead to inflammation and injury of the liver and gut, thereby predisposing patients to adverse outcomes such as necrotizing enterocolitis (NEC). In addition, intestinal bile acids (BAs) accumulation is causally linked to NEC development. Plant sterols are a promising intervention to prevent NEC development, considering their anti-inflammatory properties in the liver. Therefore, we investigated whether an intra-amniotic (IA) Ureaplasma parvum (UP) infection affected the liver and enterohepatic circulation (EHC) and evaluated whether an IA administered plant sterol mixture dissolved in &beta, cyclodextrin exerted prophylactic effects. An ovine chorioamnionitis model was used in which liver inflammation and the EHC were assessed following IA UP exposure in the presence or absence of IA prophylactic plant sterols (a mixture of &beta, sitosterol and campesterol dissolved in &beta, cyclodextrin (carrier)) or carrier alone. IA UP exposure caused an inflammatory reaction in the liver, histologically seen as clustered and conflated hepatic erythropoiesis in the parenchyma, which was partially prevented by IA administration of sterol + &beta, cyclodextrin, or &beta, cyclodextrin alone. In addition, IA administration of &beta, cyclodextrin prior to UP caused changes in the expression of several hepatic BAs transporters, without causing alterations in other aspects of the EHC. Thereby, the addition of plant sterols to the carrier &beta, cyclodextrin did not have additional effects.

Precision treatment of cancer relies on genetic alterations which are diagnosed by molecular biology assays.1 These tests can be a bottleneck in oncology workflows because of high turnaround time, tissue usage and costs.2 Here, we show that deep learning can predict point mutations, molecular tumor subtypes and immune-related gene expression signatures3,4 directly from routine histological images of tumor tissue. We developed and systematically optimized a one-stop-shop workflow and applied it to more than 4000 patients with breast5, colon and rectal6, head and neck7, lung8,9, pancreatic10, prostate11 cancer, melanoma12 and gastric13 cancer. Together, our findings show that a single deep learning algorithm can predict clinically actionable alterations from routine histology data. Our method can be implemented on mobile hardware14, potentially enabling point-of-care diagnostics for personalized cancer treatment in individual patients.

Painful peripheral neuropathy is a common, difficult-to-treat complication associated with a variety of diseases, including diabetes mellitus and sarcoidosis. It is caused by damage of small and autonomic nerve fibers, resulting in potentially debilitating symptoms of neuropathic pain and autonomic dysfunction. The limited efficacy of current treatment options dictates a rationalized design of novel compounds.The authors present the recent data from two Phase II clinical trials on ARA290, an erythropoietin derivative with tissue protective and healing properties that does not stimulate erythropoiesis. ARA 290 treatment was consistently associated with a significant improvement of neuropathic pain symptoms in sarcoidosis patients, evidenced by a decrease in pain scores on validated questionnaires. Moreover, ARA 290 treatment resulted in significant increases in corneal nerve fibers, improved sensory pain thresholds, improved quality of life and physical functioning.Current treatment modalities of neuropathy are based on a trial-and-error approach, have limited efficacy and come with significant side effects. Given the excellent safety profile while reducing neuropathy symptoms, the prospects of ARA 290 treatment in sarcoid neuropathy seem promising. The long-lasting beneficial effects of ARA 290 on both pain-related and non-pain-related symptoms in sarcoidosis patients prompt additional studies on potential disease-modifying properties of ARA 290.

Introduction: Sarcoidosis is a multi-system inflammatory disorder that may affect the peripheral nerves causing neuropathic pain. Chronic neuropathic pain is a debilitating disease and current treatment options are either of limited efficacy or are hampered by the development of serious side effects. A novel pharmacological treatment option is the non-hematopoietic erythropoietin analog ARA 290, a small peptide acting at the innate repair receptor, which is a heteromer of the erythropoietin receptor and β-common receptor. ARA 290 was recently granted designation as Orphan Drug Product by the FDA, for treatment of neuropathic pain in sarcoidosis patients. Areas covered: This report reviews the pathophysiology of sarcoidosis and, to understand the mechanistic pathway of ARA 290, the role of the innate repair receptor in inflammation and its natural and synthetic ligands, erythropoietin and ARA 290. The results of two proof-of-concept studies are presented that show the ability of ARA 290 to induce analgesia...

Small nerve fiber loss and damage (SNFLD) is a frequent complication of sarcoidosis that is associated with autonomic dysfunction and sensory abnormalities, including pain syndromes that severely degrade the quality of life. SNFLD is hypothesized to arise from the effects of immune dysregulation, an essential feature of sarcoidosis, on the peripheral and central nervous systems. Current therapy of sarcoidosis-associated SNFLD consists primarily of immune suppression and symptomatic treatment; however, this treatment is typically unsatisfactory. ARA 290 is a small peptide engineered to activate the innate repair receptor that antagonizes inflammatory processes and stimulates tissue repair. Here we show in a blinded, placebo-controlled trial that 28 d of daily subcutaneous administration of ARA 290 in a group of patients with documented SNFLD significantly improves neuropathic symptoms. In addition to improved patient-reported symptom-based outcomes, ARA 290 administration was also associated with a significant increase in corneal small nerve fiber density, changes in cutaneous temperature sensitivity, and an increased exercise capacity as assessed by the 6-minute walk test. On the basis of these results and of prior studies, ARA 290 is a potential disease-modifying agent for treatment of sarcoidosis-associated SNFLD.

ARA 290 (a peptide designed to activate the innate repair receptor that arrests injury and initiates cytoprotection, antiinflammation and healing) reduces allodynia in preclinical neuropathy models. We studied the safety and efficacy of ARA 290 to reduce symptoms of small fiber neuropathy (SFN) in patients with sarcoidosis. A total of 22 patients diagnosed with sarcoidosis and symptoms of SFN were enrolled in a double-blind, placebo-controlled exploratory trial consisting of three times weekly intravenous dosing of ARA 290 (2 mg; n = 12) or placebo (n = 10) for 4 wks. Inclusion criteria were a diagnosis of neuropathy and a spontaneous pain score of ≥5 (Brief Pain Inventory [BPI]). Endpoints assessed were changes in pain intensity and the small fiber neuropathy screening list (SFNSL) score, quality of life (SF-36), depressive symptoms (Inventory of Depressive Symptomatology [IDS]) and fatigue (Fatigue Assessment Scale [FAS]). No safety concerns were raised by clinical or laboratory assessments. The ARA 290 group showed significant (p < 0.05) improvement at wk 4 in SFNSL score compared with placebo (Δ -11.5 ± 3.04 versus Δ -2.9 ± 3.34 [standard error of the mean]). Additionally, the ARA 290 group showed a significant change from baseline in the pain and physical functioning dimensions of the SF-36 (Δ -23.4 ± 5.5 and Δ -14.6 ± 3.9, respectively). The mean BPI and FAS scores improved significantly but equivalently in both patient groups. No change was observed in the IDS. ARA 290 appears to be safe in patients with sarcoidosis and can reduce neuropathic symptoms.

Sarcoidosis is a chronic inflammatory illness and small-fiber neuropathy (SFN) is one of the disabling and often chronic manifestations of the disease. SFN presents with peripheral pain and symptoms of autonomic dysfunction. The character of the pain can be burning or shooting. Besides, allodynia and hyperesthesia can exist. Diagnosis is usually made on the basis of clinical features, in combination with abnormal specialized tests. The aim of treatment is often to reduce pain; however, total pain relieve is seldom achieved. The role of TNF-α in the pathogenesis of SFN in sarcoidosis appears interesting to explore. Novel therapeutic agents such as ARA 290, a nonhematopoietic erythropoietin analogue with potent anti-inflammatory and tissue protective properties, are interesting to explore in the treatment of SFN in sarcoidosis.