Programmed death-ligand 1 (PD-L1) expression in primary gastric adenocarcinoma and matched metastases.

BACKGROUND: Combination of immunotherapy and chemotherapy is recommended for first line treatment of gastric adenocarcinoma (GC) patients with locally advanced unresectable disease or metastatic disease. However, data regarding the concordance rate between PD-L1 combined positive score (CPS) in primary GC and matched regional lymph node metastasis (LNmet) or matched distant metastasis (Dmet) is limited. METHODS: Tissue microarray sections from primary resected GC, LNmet and Dmet were immunohistochemically stained with anti-PD-L1 (clone SP263). PD-L1 expression was scored separately in tumour cells and immune cells and compared between matched primary GC, LNmet and/or Dmet. CPS was calculated and results for CPS cut-offs 1 and 5 were compared between matched samples. RESULTS: 275 PD-L1 stained GC were analysed. 189 primary GC had matched LNmet. CPS cut-off 1 concordance rate between primary GC and LNmet was 77%. 23 primary GC had matched Dmet but no matched LNmet, CPS cut-off 1 concordance rate was 70%. 63 primary GC had both matched LNmet and matched Dmet, CPS cut-off 1 concordance rate of 67%. CPS cut-off 5 results were similar. The proportion of PD-L1 positive tumour cells increased from primary GC (26%) to LNmet (42%) and was highest in Dmet (75%). CONCLUSION: Our study showed up to 33% discordance of PD-L1 CPS between primary GC and LNmet and/or Dmet suggesting that multiple biopsies of primary GC and metastatic sites might need to be tested before considering treatment options. Moreover, this is the first study that seems to suggest that tumour cells acquire PD-L1 expression during disease progression.

Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning.

BACKGROUND: Computational pathology uses deep learning (DL) to extract biomarkers from routine pathology slides. Large multicentric datasets improve performance, but such datasets are scarce for gastric cancer. This limitation could be overcome by Swarm Learning (SL). METHODS: Here, we report the results of a multicentric retrospective study of SL for prediction of molecular biomarkers in gastric cancer. We collected tissue samples with known microsatellite instability (MSI) and Epstein-Barr Virus (EBV) status from four patient cohorts from Switzerland, Germany, the UK and the USA, storing each dataset on a physically separate computer. RESULTS: On an external validation cohort, the SL-based classifier reached an area under the receiver operating curve (AUROC) of 0.8092 (± 0.0132) for MSI prediction and 0.8372 (± 0.0179) for EBV prediction. The centralized model, which was trained on all datasets on a single computer, reached a similar performance. CONCLUSIONS: Our findings demonstrate the feasibility of SL-based molecular biomarkers in gastric cancer. In the future, SL could be used for collaborative training and, thus, improve the performance of these biomarkers. This may ultimately result in clinical-grade performance and generalizability.

Surgical pathology of adenocarcinomas arising around or within the gastroesophageal junction.

Classification of adenocarcinomas (AC) arising around or within the gastroesophageal junction (GEJ) is hampered by major morphologic and phenotypic overlaps. We reviewed the surgical pathology of esophagectomy specimens of 115 primary resected AC of the esophagus as defined by the 5th edition of the WHO classification regarding the anatomical site of the tumor, with corresponding categorization according to the Siewert AEG Classification and the preceding 4th edition of the WHO (discriminating esophageal adenocarcinomas/EAC and adenocarcinomas of the gastroesophageal junction/AdGEJ), and further histology findings. In addition, immunohistochemistry (IHC) for CDX2, CK7, CK20, MUC2, MUC5AC and MUC6 was performed. Sixty-eight cases were Siewert AEG type I and 47 cases Siewert AEG type II. Out of the AEG I tumors, 26 were classified as AdGEJ. Regardless of the classification system, more proximally located tumors showed less aggressive behavior with lower rates of lymph node metastases, lymphatic, venous and perineural invasion, better histological differentiation (p < 0.05 each) and were more frequently associated with pre-neoplastic Barrett's mucosa (p < 0.001). Histologically, the tumors displayed intestinal morphology in the majority of cases. IHC showed non-conclusive patterns with a frequent CK7+/CK20+ immunophenotype in all tumors, but also a gastric MUC5AC+ and MUC6+ phenotype in some proximal tumors. In conclusion, histology of the tumors and IHC failed to distinguish reliably between more proximal and more distal tumors. The presence of Barrett's mucosa rather than location alone, however, may help to further differentiating adenocarcinomas arising in this region and may be indicative for a particular biologic type.

Adversarial attacks and adversarial robustness in computational pathology.

Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to quantify and mitigate this risk before widespread clinical use. Here, we show that convolutional neural networks (CNNs) are highly susceptible to white- and black-box adversarial attacks in clinically relevant weakly-supervised classification tasks. Adversarially robust training and dual batch normalization (DBN) are possible mitigation strategies but require precise knowledge of the type of attack used in the inference. We demonstrate that vision transformers (ViTs) perform equally well compared to CNNs at baseline, but are orders of magnitude more robust to white- and black-box attacks. At a mechanistic level, we show that this is associated with a more robust latent representation of clinically relevant categories in ViTs compared to CNNs. Our results are in line with previous theoretical studies and provide empirical evidence that ViTs are robust learners in computational pathology. This implies that large-scale rollout of AI models in computational pathology should rely on ViTs rather than CNN-based classifiers to provide inherent protection against perturbation of the input data, especially adversarial attacks.

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised: the ground truth is only known for the slide, not for every single tile. In classical weakly-supervised analysis pipelines, all tiles inherit the slide label while in multiple-instance learning (MIL), only bags of tiles inherit the label. However, it is still unclear how these widely used but markedly different approaches perform relative to each other. We implemented and systematically compared six methods in six clinically relevant end-to-end prediction tasks using data from N=2980 patients for training with rigorous external validation. We tested three classical weakly-supervised approaches with convolutional neural networks and vision transformers (ViT) and three MIL-based approaches with and without an additional attention module. Our results empirically demonstrate that histological tumor subtyping of renal cell carcinoma is an easy task in which all approaches achieve an area under the receiver operating curve (AUROC) of above 0.9. In contrast, we report significant performance differences for clinically relevant tasks of mutation prediction in colorectal, gastric, and bladder cancer. In these mutation prediction tasks, classical weakly-supervised workflows outperformed MIL-based weakly-supervised methods for mutation prediction, which is surprising given their simplicity. This shows that new end-to-end image analysis pipelines in computational pathology should be compared to classical weakly-supervised methods. Also, these findings motivate the development of new methods which combine the elegant assumptions of MIL with the empirically observed higher performance of classical weakly-supervised approaches. We make all source codes publicly available at https://github.com/KatherLab/HIA, allowing easy application of all methods to any similar task.

Interspatial Distribution of Tumor and Immune Cells in Correlation with PD-L1 in Molecular Subtypes of Gastric Cancers.

(1) Background: EBV-positive and mismatch repair-deficient (MMRd) gastric cancers (GCs) show higher levels of tumor-infiltrating lymphocytes (TILs) and PD-L1 expression and thus a more profound response to immunotherapy. However, the majority of GCs are EBV-negative (EBV−) and MMR proficient (MMRp). We analyzed PD-L1 expression and TILs in EBV-MMRpGCs in comparison to EBV-positive (EBV+) and MMRdGCs to identify an immunogenic phenotype susceptible to immunotherapy. (2) Methods: A next-generation tissue microarray of 409 primary resected GCs was analyzed by Epstein-Barr encoding region (EBER) in situ hybridization for MSH1, PMS2, MSH2, MSH6, PD-L1, and CD8 immunohistochemistry. PD-L1 positivity was defined as a combined positive score (CPS) of ≥1. CD8+ TILs and their proximity to cancer cells were digitally analyzed on the HALO™ image analysis platform. (3) Results: Eleven cases were EBV+, 49 cases MMRd, and 349 cases EBV-MMRpGCs. The highest rate of PD-L1 positivity was seen in EBV+GCs, followed by MMRdGCs and EBV-MMRpGCs (81.8%, 73.5%, and 27.8%, respectively). EBV+ and MMRdGCs also demonstrated increased numbers and proximity of CD8+ TILs to tumor cells compared to EBV-MMRpGCs (p < 0.001 each). PD-L1 status positively correlated with the total numbers of CD8+ TILs and their proximity to tumor cells in all subtypes, including EBV-MMRpGCs (p < 0.001 each). A total of 28.4% of EBV-MMRpGCs showed high CD8+ TILs independent of PD-L1. (4) Conclusions: PD-L1 and CD8 immunohistochemistry, supplemented by digital image analysis, may identify EBV-MMRpGCs with high immunoreactivity indices, indicating susceptibility to immunotherapy.

Metabolic tumor constitution is superior to tumor regression grading for evaluating response to neoadjuvant therapy of esophageal adenocarcinoma patients.

The response to neoadjuvant therapy can vary widely between individual patients. Histopathological tumor regression grading (TRG) is a strong factor for treatment response and survival prognosis of esophageal adenocarcinoma (EAC) patients following neoadjuvant treatment and surgery. However, TRG systems are usually based on the estimation of residual tumor but do not consider stromal or metabolic changes after treatment. Spatial metabolomics analysis is a powerful tool for molecular tissue phenotyping but has not been used so far in the context of neoadjuvant treatment of esophageal cancer. We used imaging mass spectrometry to assess the potential of spatial metabolomics on tumor and stroma tissue for evaluating therapy response of neoadjuvant-treated EAC patients. With an accuracy of 89.7%, the binary classifier trained on spatial tumor metabolite data proved to be superior for stratifying patients when compared with histopathological response assessment, which had an accuracy of 70.5%. Sensitivities and specificities for the poor and favorable survival patient groups ranged from 84.9% to 93.3% using the metabolic classifier and from 62.2% to 78.1% using TRG. The tumor classifier was the only significant prognostic factor (HR 3.38, 95% CI 1.40-8.12, p = 0.007) when adjusted for clinicopathological parameters such as TRG (HR 1.01, 95% CI 0.67-1.53, p = 0.968) or stromal classifier (HR 1.86, 95% CI 0.81-4.25, p = 0.143). The classifier even allowed us to further stratify patients within the TRG1-3 categories. The underlying mechanisms of response to treatment have been figured out through network analysis. In summary, metabolic response evaluation outperformed histopathological response evaluation in our study with regard to prognostic stratification. This finding indicates that the metabolic constitution of the tumor may have a greater impact on patient survival than the quantity of residual tumor cells or the stroma. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

An unusual pseudolymphoma in the context of necrotizing fasciitis: A case report.

RATIONALE: The diagnosis of lymphoma in routine diagnostics can be challenging due to clinical, morphological and immunphenotypical overlap with unusual reactive processes termed "pseudolymphomas." PATIENT CONCERNS: 45-year-old male that underwent surgical debridement for a necrotizing fasciitis of the thigh with concomitant excision of a regional lymph node. DIAGNOSES: The lymph node demonstrated an architecture-effacing activation and proliferation of lymphoblasts and was initially misdiagnosed as an aggressive lymphoma. Only in consideration of the clinical context and with the help of additional immunohistochemical and molecular analyses the final diagnosis of a reactive lymphadenopathy could be made. INTERVENTIONS: No further therapy was required after the final diagnosis of a reactive lymphadenopathy was made. OUTCOMES: The clinical follow-up was unremarkable, with no evidence of residual disease after 6 months. LESSONS: This case report adds the parafollicular activation and proliferation of blasts and plasmablasts in the drainage area of an active infection to the spectrum of "pseudolymphomas" and reiterizes the importance of placing histopathological findings in the proper context.

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study.

BACKGROUND: Response to immunotherapy in gastric cancer is associated with microsatellite instability (or mismatch repair deficiency) and Epstein-Barr virus (EBV) positivity. We therefore aimed to develop and validate deep learning-based classifiers to detect microsatellite instability and EBV status from routine histology slides. METHODS: In this retrospective, multicentre study, we collected tissue samples from ten cohorts of patients with gastric cancer from seven countries (South Korea, Switzerland, Japan, Italy, Germany, the UK and the USA). We trained a deep learning-based classifier to detect microsatellite instability and EBV positivity from digitised, haematoxylin and eosin stained resection slides without annotating tumour containing regions. The performance of the classifier was assessed by within-cohort cross-validation in all ten cohorts and by external validation, for which we split the cohorts into a five-cohort training dataset and a five-cohort test dataset. We measured the area under the receiver operating curve (AUROC) for detection of microsatellite instability and EBV status. Microsatellite instability and EBV status were determined to be detectable if the lower bound of the 95% CI for the AUROC was above 0·5. FINDINGS: Across the ten cohorts, our analysis included 2823 patients with known microsatellite instability status and 2685 patients with known EBV status. In the within-cohort cross-validation, the deep learning-based classifier could detect microsatellite instability status in nine of ten cohorts, with AUROCs ranging from 0·597 (95% CI 0·522-0·737) to 0·836 (0·795-0·880) and EBV status in five of eight cohorts, with AUROCs ranging from 0·819 (0·752-0·841) to 0·897 (0·513-0·966). Training a classifier on the pooled training dataset and testing it on the five remaining cohorts resulted in high classification performance with AUROCs ranging from 0·723 (95% CI 0·676-0·794) to 0·863 (0·747-0·969) for detection of microsatellite instability and from 0·672 (0·403-0·989) to 0·859 (0·823-0·919) for detection of EBV status. INTERPRETATION: Classifiers became increasingly robust when trained on pooled cohorts. After prospective validation, this deep learning-based tissue classification system could be used as an inexpensive predictive biomarker for immunotherapy in gastric cancer. FUNDING: German Cancer Aid and German Federal Ministry of Health.

Loss of Furin in ß-Cells Induces an mTORC1-ATF4 Anabolic Pathway That Leads to ß-Cell Dysfunction.

FURIN is a proprotein convertase (PC) responsible for proteolytic activation of a wide array of precursor proteins within the secretory pathway. It maps to the PRC1 locus, a type 2 diabetes susceptibility locus, but its specific role in pancreatic ß-cells is largely unknown. The aim of this study was to determine the role of FURIN in glucose homeostasis. We show that FURIN is highly expressed in human islets, whereas PCs that potentially could provide redundancy are expressed at considerably lower levels. ß-cell-specific Furin knockout (ßFurKO) mice are glucose intolerant as a result of smaller islets with lower insulin content and abnormal dense-core secretory granule morphology. mRNA expression analysis and differential proteomics on ßFurKO islets revealed activation of activating transcription factor 4 (ATF4), which was mediated by mammalian target of rapamycin C1 (mTORC1). ßFurKO cells show impaired cleavage or shedding of vacuolar-type ATPase (V-ATPase) subunits Ac45 and prorenin receptor, respectively, and impaired lysosomal acidification. Blocking V-ATPase pharmacologically in ß-cells increased mTORC1 activity, suggesting involvement of the V-ATPase proton pump in the phenotype. Taken together, these results suggest a model of mTORC1-ATF4 hyperactivation and impaired lysosomal acidification in ß-cells lacking Furin, causing ß-cell dysfunction.

Favourable long-term survival of patients with esophageal cancer treated with extended transhiatal esophagectomy combined with en bloc lymphadenectomy: results from a retrospective observational cohort study.

BACKGROUND: Although considered complex and challenging, esophagectomy remains the best potentially curable treatment option for resectable esophageal and esophagogastric junction (AEG) carcinomas. The optimal surgical approach and technique as well as the extent of lymphadenectomy, particularly regarding quality of life and short- and long-term outcomes, are still a matter of debate. To lower perioperative morbidity, we combined the advantages of a one-cavity approach with extended lymph node dissection (usually achieved by only a two-cavity approach) and developed a modified single-cavity transhiatal approach for esophagectomy. METHODS: The aim of this study was to evaluate the outcome of an extended transhiatal esophageal resection with radical bilateral mediastinal en bloc lymphadenectomy (eTHE). A prospective database of 166 patients with resectable cancers of the esophagus (including adenocarcinomas of the AEG types I and II) were analyzed. Patients were treated between 2001 and 2017 with eTHE at a tertiary care university center. Relevant patient characteristics and outcome parameters were collected and analyzed. The primary endpoint was 5-year overall survival. Secondary outcomes included short-term morbidity, mortality, radicalness of en bloc resection and oncologic efficacy. RESULTS: The overall survival rates at 1, 3 and 5 years were 84, 70, and 61.0%, respectively. The in-hospital mortality rate after eTHE was 1.2%. Complications with a Clavien-Dindo score of III/IV occurred in 31 cases (18.6%). A total of 25 patients (15.1%) had a major pulmonary complication. The median hospital stay was 17 days (interquartile range (IQR) 12). Most patients (n = 144; 86.7%) received neoadjuvant treatment. The median number of lymph nodes resected was 25 (IQR 17). The R0 resection rate was 97%. CONCLUSION: In patients with esophageal cancer, eTHE without thoracotomy resulted in excellent long-term survival, an above average number of resected lymph nodes and an acceptable postoperative morbidity and mortality.

Significance of tumour regression in lymph node metastases of gastric and gastro-oesophageal junction adenocarcinomas.

The presence of lymph node (LN) metastases is one of the most important negative prognostic factors in upper gastrointestinal carcinomas. Tumour regression similar to that in primary tumours can be observed in LN metastases after neoadjuvant therapy. We evaluated the prognostic impact of histological regression in LNs in 480 adenocarcinomas of the stomach and gastro-oesophageal junction after neoadjuvant chemotherapy. Regressive changes in LNs (nodular and/or hyaline fibrosis, sheets of foamy histiocytes or acellular mucin) were assessed by histology. In total, regressive changes were observed in 128 of 480 patients. LNs were categorised according to the absence or presence of both residual tumour and regressive changes (LN-/+ and Reg-/+). 139 cases were LN-/Reg-, 28 cases without viable LN metastases revealed regressive changes (LN-/Reg+), 100 of 313 cases with LN metastases showed regressive changes (LN+/Reg+), and 213 of 313 metastatic LN had no signs of regression (LN+/Reg-). Overall, LN/Reg categorisation correlated with overall survival with the best prognosis for LN-/Reg- and the worst prognosis for LN+/Reg- (p < 0.001). LN-/Reg+ cases had a nearly significant better outcome than LN+/Reg+ (p = 0.054) and the latter had a significantly better prognosis than LN+/Reg- (p = 0.01). The LN/Reg categorisation was also an independent prognostic factor in multivariate analysis (HR = 1.23; 95% CI 1.1-1.38; p < 0.001). We conclude that the presence of regressive changes after neoadjuvant treatment in LNs and LN metastases of gastric and gastro-oesophageal junction cancers is a relevant prognostic factor.

Mouse brain proteomics establishes MDGA1 and CACHD1 as in vivo substrates of the Alzheimer protease BACE1.

The protease beta-site APP cleaving enzyme 1 (BACE1) has fundamental functions in the nervous system. Its inhibition is a major therapeutic approach in Alzheimer's disease, because BACE1 cleaves the amyloid precursor protein (APP), thereby catalyzing the first step in the generation of the pathogenic amyloid beta (Aß) peptide. Yet, BACE1 cleaves numerous additional membrane proteins besides APP. Most of these substrates have been identified in vitro, but only few were further validated or characterized in vivo. To identify BACE1 substrates with in vivo relevance, we used isotope label-based quantitative proteomics of wild type and BACE1-deficient (BACE1 KO) mouse brains. This approach identified known BACE1 substrates, including Close homolog of L1 and contactin-2, which were found to be enriched in the membrane fraction of BACE1 KO brains. VWFA and cache domain-containing protein 1 (CACHD)1 and MAM domain-containing glycosylphosphatidylinositol anchor protein 1 (MDGA1), which have functions in synaptic transmission, were identified and validated as new BACE1 substrates in vivo by immunoblots using primary neurons and mouse brains. Inhibition or deletion of BACE1 from primary neurons resulted in a pronounced inhibition of substrate cleavage and a concomitant increase in full-length protein levels of CACHD1 and MDGA1. The BACE1 cleavage site in both proteins was determined to be located within the juxtamembrane domain. In summary, this study identifies and validates CACHD1 and MDGA1 as novel in vivo substrates for BACE1, suggesting that cleavage of both proteins may contribute to the numerous functions of BACE1 in the nervous system.

Preservation of Epstein-Barr virus status and mismatch repair protein status along the metastatic course of gastric cancer.

AIMS: Epstein-Barr virus (EBV) in-situ hybridisation and mismatch repair (MMR) protein immunohistochemistry identifies two subgroups of gastric cancer (GC) with high immunogenicity and likelihood for response to immune check-point inhibition. As tumour biology may change during the metastatic course, which can negatively influence the success of therapeutic decisions made on primary tissue, we investigated the consistency of GC EBV and MMR status within primary tumours and metastases. METHODS AND RESULTS: We investigated a cohort of 415 primary resected GC, including 111 cases with corresponding distant metastases and 297 cases with lymph node metastases. Tumours were analysed by EBV in-situ hybridisation and MLH1, PMS2, MSH2 and MSH6 immunohistochemistry using tissue microarray technique. Primary tumours were grouped as EBV-positive MMR-proficient, EBV-negative MMR-deficient and EBV-negative MMR-proficient. Eleven of 415 (2.7%) of primary tumours were EBV-positive MMR-proficient, whereas 49 of 415 (11.8%) of tumours were EBV-negative MMR-deficient. EBV and MMR protein status showed full concordance with that of the primary tumours. MMR-deficient tumours were of lower pT-category (P < 0.001), had fewer lymph node metastases [24 of 49 (49%) versus 273 of 361 (75.6%) cases; P < 0.001] and a lower rate of distant metastases [six of 49 (12.2%) versus 105 of 366 (28.7%) cases; P = 0.015]. CONCLUSION: We demonstrate a strong correlation of EBV and MMR status between primary tumours, lymph node and distant metastases in a large series of primary resected GC. The cases showed the expected frequency of EBV-positive MMR-deficient and EBV-negative MMR-proficient tumours. We conclude that tissue testing for molecular subtyping for therapeutic decision-making can be reliably performed on primary tumours and metastases in GC.

Chlamydia-induced curvature of the host-cell plasma membrane is required for infection.

During invasion of host cells, Chlamydia pneumoniae secretes the effector protein CPn0678, which facilitates internalization of the pathogen by remodeling the target cell's plasma membrane and recruiting sorting nexin 9 (SNX9), a central multifunctional endocytic scaffold protein. We show here that the strongly amphipathic N-terminal helix of CPn0678 mediates binding to phospholipids in both the plasma membrane and synthetic membranes, and is sufficient to induce extensive membrane tubulations. CPn0678 interacts via its conserved C-terminal polyproline sequence with the Src homology 3 domain of SNX9. Thus, SNX9 is found at bacterial entry sites, where C. pneumoniae is internalized via EGFR-mediated endocytosis. Moreover, depletion of human SNX9 significantly reduces internalization, whereas ectopic overexpression of CPn0678-GFP results in a dominant-negative effect on endocytotic processes in general, leading to the uptake of fewer chlamydial elementary bodies and diminished turnover of EGFR. Thus, CPn0678 is an early effector involved in regulating the endocytosis of C. pneumoniae in an EGFR- and SNX9-dependent manner.

Correction: A specific expression profile of LC3B and p62 is associated with nonresponse to neoadjuvant chemotherapy in esophageal adenocarcinomas.

[This corrects the article DOI: 10.1371/journal.pone.0197610.].

Stromal PD-1/PD-L1 Expression Predicts Outcome in Colon Cancer Patients.

INTRODUCTION: The programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) axis plays an important role in controlling immune suppression by down-regulating T effector cell activities, enabling tumor cells to escape from the host's antitumor immunsurveillance. While only a small part of colon cancer cells express PD-L1, we sought to evaluate the differential impact of stromal and epithelial PD-L1 expression of primary tumors and liver metastasis on overall survival (OS) in colon cancer patients. PATIENTS AND METHODS: Using a next-generation tissue microarray approach, we assessed both epithelial and stromal PD-L1 expression levels in primary tumors (n = 279) and corresponding liver metastases (n = 14) of colon cancer patients. PD-L1 positivity was graded according to the percentage (0.1%-1%, > 1%, > 5%, > 50%) of tumor cells with membranous PD-L1 expression or as the percentage of positive stroma cells and associated inflammatory infiltrates. We also assessed the interplay between stromal PD-1/PD-L1 and both intratumoral and stromal CD8 count and their impact on outcome. The primary end point was OS. RESULTS: Stromal PD-L1 and PD-1 expression were both associated with less aggressive tumor behavior in colon cancer patients, which translated into better OS and disease-free survival, respectively. Conversely, PD-L1 staining in the tumor cells was less frequent than stromal staining and was associated with features of aggressive tumor biology, although without impact on outcome. Interestingly, the PD-L1 staining pattern remained similar between primary tumors and corresponding liver metastases. Stromal PD-1 expression correlated significantly with stromal PD-L1 staining and both intratumoral and stromal CD8 expression. CONCLUSION: Stromal PD-1/PD-L1 expression might serve as a prognostic marker in colon cancer patients.

Her2-Targeted Therapy Induces Autophagy in Esophageal Adenocarcinoma Cells.

Esophageal adenocarcinoma (EAC) is a highly lethal cancer type with an overall poor survival rate. Twenty to thirty percent of EAC overexpress the human epidermal growth factor receptor 2 (Her2), a transmembrane receptor tyrosine kinase promoting cell growth and proliferation. Patients with Her2 overexpressing breast and gastroesophageal cancer may benefit from Her2 inhibitors. Therapy resistance, however, is well documented. Since autophagy, a lysosome-dependent catabolic process, is implicated in cancer resistance mechanisms, we tested whether autophagy modulation influences Her2 inhibitor sensitivity in EAC. Her2-positive OE19 EAC cells showed an induction in autophagic flux upon treatment with the small molecule Her2 inhibitor Lapatinib. Newly generated Lapatinib-resistant OE19 (OE19 LR) cells showed increased basal autophagic flux compared to parental OE19 (OE19 P) cells. Based on these results, we tested if combining Lapatinib with autophagy inhibitors might be beneficial. OE19 P showed significantly reduced cell viability upon double treatment, while OE19 LR were already sensitive to autophagy inhibition alone. Additionally, Her2 status and autophagy marker expression (LC3B and p62) were investigated in a treatment-naïve EAC patient cohort (n = 112) using immunohistochemistry. Here, no significant correlation between Her2 status and expression of LC3B and p62 was found. Our data show that resistance to Her2-directed therapy is associated with a higher basal autophagy level, which is not per se associated with Her2 status. Therefore, we propose that autophagy may contribute to acquired resistance to Her2-targeted therapy in EAC, and that combining Her2 and autophagy inhibition might be beneficial for EAC patients.

Risk factors for esophageal cancer: emphasis on infectious agents.

Risk factors for esophageal cancer include genetic factors (such as tylosis) and infectious agents. A variety of organisms have been implicated in esophageal carcinogenesis, either directly or indirectly. In this review, we explore the normal esophageal flora and how it may be controlled, and also the variety of organisms that may affect esophageal carcinogenesis, either directly or indirectly. The organisms with potential direct effects in squamous cell carcinoma include human papillomavirus (HPV), Epstein-Barr virus, and polyoma viruses. Interestingly, HPV is now implicated in esophageal adenocarcinoma (EAC), not in its initiation but in the development of dysplasia, in which HPV33 in particular has been associated. Indirectly, Helicobacter pylori has been associated with EAC by, initially, causing increased acid secretion that increases acid reflux, and by reducing lower esophageal sphincter pressure, which increases gastroesophageal reflux; the latter increases the risk of Barrett's esophagus, and hence EAC. Conversely, subsequent atrophic gastritis may normalize that risk.