Compartmentalized PGRP expression along the dipteran Bactrocera dorsalis gut forms a zone of protection for symbiotic bacteria.

All metazoan guts are subject to opposing pressures wherein the immune system must eliminate pathogens while tolerating the presence of symbiotic microbiota. The Imd pathway is an essential defense against invading pathogens in insect guts, but tolerance mechanisms are less understood. Here, we find PGRP-LB and PGRP-SB express mainly in the anterior and middle midgut in a similar pattern to symbiotic Enterobacteriaceae bacteria along the Bactrocera dorsalis gut. Knockdown of PGRP-LB and PGRP-SB enhances the expression of antimicrobial peptide genes and reduces Enterobacteriaceae numbers while increasing abundance of opportunistic pathogens. Microbiota numbers recover to normal levels after the RNAi effect subsided. In contrast, high expression of PGRP-LC in the foregut allows increased antibacterial peptide production to efficiently filter the entry of pathogens, protecting the symbiotic bacteria. Our study describes a mechanism by which regional expression of PGRPs construct a protective zone for symbiotic microbiota while maintaining the ability to fight pathogens.

Artificial Intelligence for Detecting and Delineating Margins of Early ESCC Under WLI Endoscopy.

INTRODUCTION: Conventional white light imaging (WLI) endoscopy is the most common screening technique used for detecting early esophageal squamous cell carcinoma (ESCC). Nevertheless, it is difficult to detect and delineate margins of early ESCC using WLI endoscopy. This study aimed to develop an artificial intelligence (AI) model to detect and delineate margins of early ESCC under WLI endoscopy. METHODS: A total of 13,083 WLI images from 1,239 patients were used to train and test the AI model. To evaluate the detection performance of the model, 1,479 images and 563 images were used as internal and external validation data sets, respectively. For assessing the delineation performance of the model, 1,114 images and 211 images were used as internal and external validation data sets, respectively. In addition, 216 images were used to compare the delineation performance between the model and endoscopists. RESULTS: The model showed an accuracy of 85.7% and 84.5% in detecting lesions in internal and external validation, respectively. For delineating margins, the model achieved an accuracy of 93.4% and 95.7% in the internal and external validation, respectively, under an overlap ratio of 0.60. The accuracy of the model, senior endoscopists, and expert endoscopists in delineating margins were 98.1%, 78.6%, and 95.3%, respectively. The proposed model achieved similar delineating performance compared with that of expert endoscopists but superior to senior endoscopists. DISCUSSION: We successfully developed an AI model, which can be used to accurately detect early ESCC and delineate the margins of the lesions under WLI endoscopy.

Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.

BACKGROUND AND AIM: Diagnosis of esophageal squamous cell carcinoma (ESCC) is complicated and requires substantial expertise and experience. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC under multiple endoscopic imaging modalities. METHODS: Endoscopic images were retrospectively collected from West China Hospital, Sichuan University as a training dataset and an independent internal validation dataset. Images from other four hospitals were used as an external validation dataset. The AI system was compared with 11 experienced endoscopists. Furthermore, videos were collected to assess the performance of the AI system. RESULTS: A total of 53 933 images from 2621 patients and 142 videos from 19 patients were used to develop and validate the AI system. In the internal and external validation datasets, the performance of the AI system under all or different endoscopic imaging modalities was satisfactory, with sensitivity of 92.5-99.7%, specificity of 78.5-89.0%, and area under the receiver operating characteristic curves of 0.906-0.989. The AI system achieved comparable performance with experienced endoscopists. Regarding superficial ESCC confined to the epithelium, the AI system was more sensitive than experienced endoscopists on white-light imaging (90.8% vs 82.5%, P = 0.022). Moreover, the AI system exhibited good performance in videos, with sensitivity of 89.5-100% and specificity of 73.7-89.5%. CONCLUSIONS: We developed an AI system that showed comparable performance with experienced endoscopists in detecting superficial ESCC under multiple endoscopic imaging modalities and might provide valuable support for inexperienced endoscopists, despite requiring further evaluation.

The effects of TNF-α/TNFR2 in regulatory T cells on the microenvironment and progression of gastric cancer.

TNFR2+ regulatory T cells preferentially accumulate in the tumor microenvironment, express high levels of immunosuppressive molecules and possess strong suppressive activity. Our study aimed to explore the characteristics and role of TNFR2+ Tregs in the microenvironment and progression of gastric cancer via polychromatic immunofluorescence, single-cell RNA sequencing and flow cytometry assays. The TNFR2+ Treg infiltration level in the tumor microenvironment increased significantly as gastric cancer progressed and was demonstrated to be a prognostic marker. Single-cell RNA sequencing revealed high levels of TNFR2 in tumor-infiltrating Tregs. The TNF-α/TNFR2 signaling pathway was activated, accompanied by the upregulation of costimulatory molecules. Unlike blood Tregs, tumor-infiltrating Tregs existed in activated and effector states. In addition to expressing costimulatory molecules such as TNFR2, 4-1BB, OX40 and GITR, tumor-infiltrating Tregs were also characterized by high expression levels of immune checkpoints such as CTLA-4 and TIGIT and chemokines such as CCR6. In vitro studies showed that the TNF-α/TNFR2 pathway increased the Foxp3 expression in CD4+ CD25+ T cells and the latent TGF-ß production in Tregs as well as enhanced the immunosuppressive function of Tregs. In summary, our study revealed high infiltration levels of TNFR2+ Tregs that were in activated and effector states in the tumor microenvironment. The infiltration level of TNFR2+ Tregs is a prognostic marker and an independent risk factor for gastric cancer. Activation of the TNF-α/TNFR2 pathway promotes the immunosuppressive phenotype and function of Tregs. Our study provides a new theoretical basis for TNFR2+ Tregs as a therapeutic target in gastric cancer.

Immune-related adverse event profile of combination treatment of PD-(L)1 checkpoint inhibitors and bevacizumab in non-small cell lung cancer patients: data from the FDA adverse event reporting system.

BACKGROUND: Immune checkpoint inhibitors (ICIs) and bevacizumab-based therapy are a promising treatment approach to significantly improving overall survival (OS) of non-small cell lung cancer (NSCLC) patients. However, the incidence of adverse events induced by a combination treatment with programmed cell death-1 or programmed death ligand 1 [PD-(L)1] inhibitor and bevacizumab remains unknown. The current evidence from prospective studies is limited. Thus, efforts using real-world data to further improve our understanding of the potential adverse events will be necessary. METHODS: The present study included 15,872 participants with NSCLC in the FDA Adverse Event Reporting System (FAERS) database from April 2013 to September 2019. The definition of adverse events (AEs) relied on the Medical Dictionary for Regulatory Activities (MedDRA). Statistical analysis was performed, and odds ratio (ORs) with 95% confidence intervals (CIs) were calculated. RESULTS: Of the 15,872 participants with NSCLC, 15,463 cases were treated with the PD-(L)1 inhibitor monotherapy, while 409 cases were treated with both PD-(L)1 inhibitor and bevacizumab. Compared with monotherapy, combination therapy had lower risks of pneumonitis, respiratory failure, edema, disease progression, and death; however, combination therapy was also associated with significantly higher risks of pyrexia, general physical health deterioration, stomatitis, dehydration, thrombocytopenia, peripheral neuropathy, nephritis, bone marrow failure, immune thrombocytopenic purpura, neutropenia, and serious AEs. The results of the multivariate analysis suggested that combination therapy was the independent risk factor for pyrexia, neutropenia, nephritis, ITP, and the independent protective factor for respiratory failure. CONCLUSIONS: We observed that the spectrum and risk of irAEs differed widely between therapeutic regimens, and irAEs involved multiple organ systems both in monotherapy or combination therapy. Deepening our understanding of irAEs has a great clinical value for improving individualized clinical patient management and the safety of medication use.

Peroral endoscopic myotomy for the treatment of esophageal diverticulum: an experience in China.

BACKGROUND: With the development of minimally invasive endoscopic approaches for the esophagus in recent years, peroral endoscopic myotomy (POEM) in the treatment of esophageal diverticulum has been described recently in some reports due to its successful outcomes. The aim of this study is to report our experience with the use of diverticular POEM (D-POEM) technique in the management of esophageal diverticulum. METHODS: This retrospective study included consecutive patients with symptomatic esophageal diverticulum who visited our endoscopy center between April 2014 and January 2019. D-POEM was performed based on the principles of submucosal endoscopy. A new symptomatic scoring system was introduced to evaluate the severity of diverticular symptoms. RESULTS: A total of 10 patients with esophageal diverticulum (Zenker's 2, mid-esophagus 5, and epiphrenic 3) were included. The overall technical success rate of D-POEM was 100%, with a mean procedure time of 38.9 ± 20.5 (range 16-70) min. No serious complications occurred. Clinical improvement was achieved in 90% (9/10) of patients. The symptomatic score was significantly decreased from 2.5 (IQR 2.00-3.25) to 1.0 (IQR 0-1.25) (P = 0.007) during a median follow-up period of 11.0 (IQR 10.25-17.25) months. CONCLUSION: These findings suggested complete septotomy by D-POEM. Our preliminary data and experience put forwarded D-POEM as a safe and effective technique for esophageal diverticulum.

Romidepsin (FK228) regulates the expression of the immune checkpoint ligand PD-L1 and suppresses cellular immune functions in colon cancer.

Romidepsin (FK228), a histone deacetylase inhibitor (HDACi), has anti-tumor effects against several types of solid tumors. Studies have suggested that HDACi could upregulate PD-L1 expression in tumor cells and change the state of anti-tumor immune responses in vivo. However, the influence of enhanced PD-L1 expression in tumor cells induced by romidepsin on anti-tumor immune responses is still under debate. So, the purpose of this study was to explore the anti-tumor effects and influence on immune responses of romidepsin in colon cancer. The results indicated that romidepsin inhibited proliferation, induced G0/G1 cell cycle arrest and increased apoptosis in CT26 and MC38 cells. Romidepsin treatment increased PD-L1 expression in vivo and in vitro via increasing the acetylation levels of histones H3 and H4 and regulating the transcription factor BRD4. In subcutaneous transplant tumor mice and colitis-associated cancer (CAC) mice, romidepsin increased the percentage of FOXP3+ regulatory T cells (Tregs), decreased the ratio of Th1/Th2 cells and the percentage of IFN-γ+ CD8+ T cells in the peripheral blood and the tumor microenvironment. Upon combination with an anti-PD-1 antibody, the anti-tumor effects of romidepsin were enhanced and the influence on CD4+ and CD8+ T cells was partially reversed. Therefore, the combination of romidepsin and anti-PD-1 immunotherapy provides a more potential treatment for colon cancer.

Comparative genomics of Klebsiella michiganensis BD177 and related members of Klebsiella sp. reveal the symbiotic relationship with Bactrocera dorsalis.

BACKGROUND: Bactrocera dorsalis is a destructive polyphagous and highly invasive insect pest of tropical and subtropical species of fruit and vegetable crops. The sterile insect technique (SIT) has been used for decades to control insect pests of agricultural, veterinary, and human health importance. Irradiation of pupae in SIT can reduce the ecological fitness of the sterile insects. Our previous study has shown that a gut bacterial strain BD177 that could restore ecological fitness by promoting host food intake and metabolic activities. RESULTS: Using long-read sequence technologies, we assembled the complete genome of K. michiganensis BD177 strain. The complete genome of K. michiganensis BD177 comprises one circular chromosome and four plasmids with a GC content of 55.03%. The pan-genome analysis was performed on 119 genomes (strain BD177 genome and 118 out of 128 published Klebsiella sp. genomes since ten were discarded). The pan-genome includes a total of 49305 gene clusters, a small number of 858 core genes, and a high number of accessory (10566) genes. Pan-genome and average nucleotide identity (ANI) analysis showed that BD177 is more similar to the type strain K. michiganensis DSM2544, while away from the type strain K. oxytoca ATCC13182. Comparative genome analysis with 21 K. oxytoca and 12 K. michiganensis strains, identified 213 unique genes, several of them related to amino acid metabolism, metabolism of cofactors and vitamins, and xenobiotics biodegradation and metabolism in BD177 genome. CONCLUSIONS: Phylogenomics analysis reclassified strain BD177 as a member of the species K. michiganensis. Comparative genome analysis suggested that K. michiganensis BD177 has the strain-specific ability to provide three essential amino acids (phenylalanine, tryptophan and methionine) and two vitamins B (folate and riboflavin) to B. dorsalis. The clear classification status of BD177 strain and identification of unique genetic characteristics may contribute to expanding our understanding of the symbiotic relationship of gut microbiota and B. dorsalis.

A CT-based radiomics signature for evaluating tumor infiltrating Treg cells and outcome prediction of gastric cancer.

BACKGROUND: Tumor infiltrating regulatory T (TITreg) cells are highly infiltrated in gastric cancer (GC) and associated with worse prognosis of GC patients. We aim to develop and validate a radiomics signature for evaluation of TITreg cells and outcome prediction of GC patients. METHODS: A total of 165 GC patients from three independent cohorts were enrolled in this retrospective study. The abundance of TITreg cells were evaluated by using multispectral immunohistochemical analysis and CIBERSORT algorithm. The radiomics features were extracted by using PyRadiomics software and the radiomics signature was generated by using the least absolute shrinkage and selection operator (LASSO) logistic regression model. The receiver operator characteristic (ROC) curves were applied to assess the performance of radiomics signature for estimating TITreg cells. Univariable and multivariable Cox regression analysis were used for identifying risk factor of overall survival (OS). The prognostic value of the radiomics signature and the TITreg cells were evaluated by using the Kaplan-Meier method and log-rank test. RESULTS: Six robust features were selected for building the radiomics signature. The radiomics signature showed good ability for estimating TITreg in the training, validation and testing cohort, with area under the curve (AUC) of 0.884, 0.869 and 0.847, respectively. Multivariable Cox regression analysis showed that the radiomics signature was an independent risk factor of unfavorable OS of GC patients. CONCLUSIONS: The proposed CT-based radiomics signature is a promising non-invasive biomarker of TITreg cells and outcome prediction of GC patients.

Real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinoma using a deep learning model (with videos).

BACKGROUND AND AIMS: We developed a system for computer-assisted diagnosis (CAD) for real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinomas (ESCCs) to assist the diagnosis of esophageal cancer. METHODS: A total of 6473 narrow-band imaging (NBI) images, including precancerous lesions, early ESCCs, and noncancerous lesions, were used to train the CAD system. We validated the CAD system using both endoscopic images and video datasets. The receiver operating characteristic curve of the CAD system was generated based on image datasets. An artificial intelligence probability heat map was generated for each input of endoscopic images. The yellow color indicated high possibility of cancerous lesion, and the blue color indicated noncancerous lesions on the probability heat map. When the CAD system detected any precancerous lesion or early ESCCs, the lesion of interest was masked with color. RESULTS: The image datasets contained 1480 malignant NBI images from 59 consecutive cancerous cases (sensitivity, 98.04%) and 5191 noncancerous NBI images from 2004 cases (specificity, 95.03%). The area under curve was 0.989. The video datasets of precancerous lesions or early ESCCs included 27 nonmagnifying videos (per-frame sensitivity 60.8%, per-lesion sensitivity, 100%) and 20 magnifying videos (per-frame sensitivity 96.1%, per-lesion sensitivity, 100%). Unaltered full-range normal esophagus videos included 33 videos (per-frame specificity 99.9%, per-case specificity, 90.9%). CONCLUSIONS: A deep learning model demonstrated high sensitivity and specificity for both endoscopic images and video datasets. The real-time CAD system has a promising potential in the near future to assist endoscopists in diagnosing precancerous lesions and ESCCs.

Prognostic Value of the Neo-Immunoscore in Renal Cell Carcinoma.

Objective: This study evaluated the prognostic value of the newly-built Immunoscore (neo-Immunoscore) in patients with renal cell carcinoma (RCC). Methods: Eighty-two patients with RCC were enrolled in this study. Their 3- and 5-year survival rates and overall survival (OS) were evaluated. The clinicopathologic data of the 82 patients were collected and analyzed. CD3, CD4, CD8, CD45RO, Foxp3, tumor necrosis factor receptor type II (TNFR2), programmed death ligand-1 (PD-L1), CD68, programmed death-1 (PD-1), cytokeratin (CK), and indoleamine 2,3-dioxygenase (IDO) were separated into two panels and stained using multiplex fluorescent immunohistochemistry methods. An immunologic prediction model of RCC patients, the neo-Immunoscore (neo-IS), was constructed using a Cox regression model. For the prognostic prediction of RCC, the neo-IS with the immunoscore (IS) proposed by the Society for Immunotherapy of Cancer (SITC) were compared by receiver operator characteristic (ROC) curve analysis. Survivals between the neo-ISlow and neo-IShigh groups were analyzed using the Kaplan-Meier method. Multivariate Cox regression survival analysis was applied to analyze independent indicators. Results: The Cox regression model allowed the establishment of a neo-IS based on three features: CD 3 CT + , CD4+Foxp3+CD45RO CT + , and CD8+PD- 1 IM + . Compared to that of the IS proposed by the SITC, the neo-IS obtained a better prediction. The 3- and 5-year survival rates in neo-IShigh RCC patients were significantly higher than those in neo-ISlow RCC patients (94.7 vs. 77.4%, P = 0.035 and 94.7 vs. 64.5%, P = 0.002, respectively). The OS in the neo-ISlow group was significantly shorter than that in the neo-IShigh group (73 vs. 97 months, P = 0.000). In comparisons of the neo-IS with clinical pathological factors, we found that the risk stratification and neo-IS were independent factors for the prognosis of patients with RCC. Moreover, the OS rate of neo-IShigh RCC patients with low- and intermediate- risk was higher than that of neo-ISlow patients. Conclusion: The newly-constructed IS model more precisely predicted the survival of patients with RCC and may supplement the prognostic value of risk stratification.