AI-powered genomic mutation signature for predicting immune checkpoint inhibitor therapy outcomes in gastroesophageal cancer: a multi-cohort analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have significantly transformed the treatment of gastroesophageal cancer (GEC). However, the lack of reliable prognostic biomarkers hinders the ability to predict patient response to ICI therapy. METHODS: In this study, we engineered and validated a genomic mutation signature (GMS) utilizing an innovative artificial intelligence (AI) algorithm to forecast ICI therapy outcomes in GEC patients. We further explored immune profiles across subtypes through comprehensive multiomics analysis. Our investigation of drug sensitivity data from the Genomics of Drug Sensitivity in Cancer (GDSC) database led to the identification of trametinib as a potential therapeutic agent. We subsequently evaluated trametinib's efficacy in AGS and MKN45 cell lines using Cell Counting Kit-8 (CCK8) assays and clonogenic experiments. RESULTS: We developed a GMS by integrating 297 algorithms, enabling autonomous prognosis prediction for GEC patients. The GMS demonstrated consistent performance across three public cohorts, exhibiting high sensitivity and specificity for overall survival (OS) at 6, 12, and 18 months, as shown by Receiver Operator Characteristic Curve (ROC) analysis. Notably, the GMS surpassed traditional clinical and molecular features, including tumor mutational burden (TMB), programmed death-ligand 1 (PD-L1) expression, and microsatellite instability (MSI), in predictive accuracy. Low-risk samples exhibited elevated levels of cytolytic immune cells and heightened immunogenic potential compared to high-risk samples. Our investigation identified trametinib as a potential therapeutic agent. An inverse correlation was observed between GMS and trametinib IC50. Moreover, the high-risk-derived AGS cell line showed increased sensitivity to trametinib compared to the low-risk-derived MKN45 cell line. CONCLUSION: The GMS utilized in this study successfully demonstrated the ability to reliably predict the survival advantage for patients with GECs undergoing ICI therapy.

PPM1G promotes autophagy and progression of pancreatic cancer via upregulating HMGB1.

Pancreatic cancer remains one of the most aggressive and lethal malignancies worldwide, with a dismal 5-year relative survival rates of only 12%. Therefore, it is urgent to discover the key molecular markers to improve the therapeutic outcomes in pancreatic cancer. Herein, we first demonstrated that PPM1G is upregulated in pancreatic cancer and that PPM1G depletion decreases pancreatic cancer cell growth in vitro and in vivo. High PPM1G expression was linked to short overall survival of pancreatic cancer patients, which was further validated in the TCGA database. Moreover, by detecting Beclin 1, LC3-II, and SQSTM1/p62 expressions and observing autolysosome under transmission electron microscope, we discovered that PPM1G is a novel positive regulator of macroautophagy/autophagy. Furthermore, by using immunoprecipitation-mass spectrometry (IP-MS) analysis and following systemic molecular biology experiment, we demonstrated PPM1G promotes the autophagy and proliferation of pancreatic cancer by directly upregulating HMGB1. Additionally, patients with both high PPM1G and high HMGB1 exhibited poorer prognosis in our cohort. This study preliminarily investigated the possibility of PPM1G as a potential therapeutic target and prognostic biomarker in pancreatic cancer patients.

Analysis of white-light imaging-based features predictive for determination of lesion depths of superficial flat esophageal squamous cell carcinoma: a retrospective multicenter study from China.

OBJECTIVES: Endoscopic diagnosis of invasion depth of superficial esophageal squamous cell carcinoma (SESCC) by white-light imaging (WLI) modality remains difficult. This study aims to clarify WLI-based features which are predictive for invasion depth of SESCC. METHODS: A two-phase study was performed by enrolling 1288 patients with 1396 SESCC lesions. Endoscopic appearances, clinical characteristics and post-operative pathological outcomes were collected and reviewed. The association between lesion features and invasion depth were analyzed. A predictive nomogram was constructed for prediction of invasion depth. RESULTS: Among 1396 lesions in derivation and validation cohort, 1139 (81.6%), 194 (13.9%) and 63 (4.5%) lesions were diagnosed as lesions confined into the intraepithelium or the lamina propria mucosa (T1a-EP/LPM), lesions invading the muscularis mucosa (T1a-MM) or superficial submucosa (T1b-SM1) and tumor with moderate invasion into the submucosa or deeper submucosal invasion (≥ T1b-SM2), respectively. Lesion length > 2 cm (p < 0.001), wider circumferential extension (p < 0.001, 0.002 and 0.048 for > 3/4, 1/2-3/4 and 1/4-1/2 circumferential extension, respectively), surface unevenness (p < 0.001 for both type 0-IIa/0-IIc lesions and mixed type lesions), spontaneous bleeding (p < 0.001), granularity (p < 0.001) and nodules (p < 0.001) were identified as significant factors predictive for lesion depth. A nomogram based on these factors was constructed and the values of area under the Receiver Operating Characteristics curve were 0.89 and 0.90 in the internal and external patient cohort. CONCLUSIONS: Our study provides six WLI-based morphological features predicting for lesion depth of SESCC. Our findings will make endoscopic evaluation of invasion depth for SESCC more convenient by assessing these profiles.

Artificial intelligence assisted detection of superficial esophageal squamous cell carcinoma in white-light endoscopic images by using a generalized system.

BACKGROUND: The use of artificial intelligence (AI) assisted white light imaging (WLI) detection systems for superficial esophageal squamous cell carcinoma (SESCC) is limited by training with images from one specific endoscopy platform. METHODS: In this study, we developed an AI system with a convolutional neural network (CNN) model using WLI images from Olympus and Fujifilm endoscopy platforms. The training dataset consisted of 5892 WLI images from 1283 patients, and the validation dataset included 4529 images from 1224 patients. We assessed the diagnostic performance of the AI system and compared it with that of endoscopists. We analyzed the system's ability to identify cancerous imaging characteristics and investigated the efficacy of the AI system as an assistant in diagnosis. RESULTS: In the internal validation set, the AI system's per-image analysis had a sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of 96.64%, 95.35%, 91.75%, 90.91%, and 98.33%, respectively. In patient-based analysis, these values were 90.17%, 94.34%, 88.38%, 89.50%, and 94.72%, respectively. The diagnostic results in the external validation set were also favorable. The CNN model's diagnostic performance in recognizing cancerous imaging characteristics was comparable to that of expert endoscopists and significantly higher than that of mid-level and junior endoscopists. This model was competent in localizing SESCC lesions. Manual diagnostic performances were significantly improved with the assistance by AI system, especially in terms of accuracy (75.12% vs. 84.95%, p = 0.008), specificity (63.29% vs. 76.59%, p = 0.017) and PPV (64.95% vs. 75.23%, p = 0.006). CONCLUSIONS: The results of this study demonstrate that the developed AI system is highly effective in automatically recognizing SESCC, displaying impressive diagnostic performance, and exhibiting strong generalizability. Furthermore, when used as an assistant in the diagnosis process, the system improved manual diagnostic performance.

Endothelin receptor B enhances liver injury and pro-inflammatory responses by increasing G-protein-coupled receptor kinase-2 expression in primary biliary cholangitis.

Severe diseases like cirrhosis and liver failure can be developed from primary biliary cholangitis (PBC). Endothelin-2 (EDN2) and endothelin receptor B (EDNRB) are related to the pathogenesis of PBC. However, the roles of EDN2 and EDNRB in PBC-related liver injury and inflammation along with molecular mechanisms are poorly defined. In this study, histopathologic alterations of liver tissues were assessed through hematoxylin-eosin staining. Alanine transaminase (ALT), alkaline phosphatase (ALP), aspartate transaminase (AST), and γ-Glutamyltranspetidase (GGT) (4 liver function indexes) serum levels were detected with corresponding activity assay kits. Also, we determined the levels of M2 subtype anti-mitochondrial antibody (AMA-M2), interferon-gamma (IFN-γ), and tumor-necrosis factor alpha (TNFα) in serum with ELISA assay. Later, RT-qPCR assay was used to measure the expression of genes at mRNA levels, while western blotting and immunohistochemical techniques were used to detect protein levels of genes. Our results showed that the liver tissues of PBC patients and mice presented with severe hepatocyte injury and inflammatory cell infiltration as well as destruction of intrahepatic small bile ducts. ALP, AST, ALT, GGT, AMA-M2, IFN-γ, and TNF-α serum levels were higher in PBC patients and mice. Besides, EDN2 and EDNRB were highly expressed in serums and livers of PBC patients and mice. EDNRB potentiated PBC-related liver injury and pro-inflammatory responses, as evidenced by observation of serious liver pathologic injury and increased serum levels of ALP, AST, ALT, AMA-M2, IFN-γ, and TNF-α in PBC mice following EDNRB overexpression. EDNRB overexpression or activation via its agonist IRL-1620 TFA triggered liver injury and pro-inflammatory responses, increased GRK2 expression and induced NF-κB expression and activation in wild-type mice. EDNRB knockdown or inhibition by Bosentan alleviated liver damage and inflammation, reduced GRK2 expression, and inhibited NF-κB in PBC mice. These findings suggested EDNRB loss or inhibition weakened liver injury and pro-inflammatory responses by down-regulating GRK2 and inhibiting the NF-κB pathway in PBC mice.

Study protocol for artificial intelligence-assisted sponge cytology as pre-endoscopy screening for early esophegeal squmaous epithelial lesions in China.

BACKGROUND: Endoscopic screening is the widely accepted screening strategy for esophageal squmaous cell carcinoma (ESCC). However, massive endoscopic screening is expensive and not cost-efficient, and novel pre-endoscopy detection used as a preliminary screening method arouses new concerns. We are planning to launch an artificial intelligence (AI) assisted sponge cytology for detecting esophageal squmaous high-grade intraepithelial neoplasia (HGIN) and above lesions. The aim of this trail is to investigate the efficiency of AI-assisted sponge cytology in population-based screening of early esophageal squmaous epithelial lesions. METHODS: The study will be prospectively conducted in five regions with a high prevalence of ESCC. AI-assisted sponge cytology and endoscopic examination will be sequentially performed. Based on our previous data, at least 864 patients with esophageal HGIN and above lesions are needed to achieve enough statistical power. And, a calculated 112,500 individuals with high risks of ESCC will be recruited. In the first stage, each 24,000 participants who meet the inclusion criteria will be recruited on a voluntary basis. Setting pathological results as standard reference, diagnostic threshold and according performance of AI-assisted detection will be evaluated. A prediction model will be constructed by co-analyzing cytological results and relevant risk factors. Then, an external validation cohort will be used for validation of the model efficiency. Also, cost-efficiency analysis will be performed. This study protocol was registered on chineseclinicaltrial.gov (ChiCTR1900028524). DISCUSSION: Our study will determine whether this AI-assisted sponge cytology can be used as an effective pre-endoscopy detection tool for large-scale screening for ESCC in high-risk areas.

Expression profile, clinical significance and biological functions of IGF2BP2 in esophageal squamous cell carcinoma.

The ectopic expression of insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) has been demonstrated to facilitate tumorigenesis and induce proliferation in a various types of cancer. However, the role of IGF2BP2 in esophageal squamous cell carcinoma (ESCC) has yet been fully elucidated. In this regard, the current study assessed the expression patterns and clinical significance of IGF2BP2 in 94 Chinese patients diagnosed with ESCC. Immunohistochemistry and reverse transcription-quantitative PCR assays were employed to assess IGF2BP2 expression in ESCC tissues compared with adjacent healthy tissues. The results revealed that the protein expression of IGF2BP2 was substantially upregulated in ESCC tissues compared with adjacent ESCC tissues. More specifically, higher IGF2BP2 expression strongly associated with tumor node metastasis stage, lymphatic infiltration and lymph node metastasis. Using two ESCC cell lines (TE-1 and TE-10), the inhibition of IGF2BP2 expression by small interfering RNA was proven to induce apoptosis and suppress proliferation, migration and cell cycle progression in vitro. Collectively, the present findings indicated that IGF2BP2 may serve a major role in the development of ESCC carcinogenesis. The present study may be helpful in the design of potential drug targets in the treatment of ESCC.

A multicenter retrospective study of endoscopic submucosal tunnel dissection for large lesser gastric curvature superficial neoplasms.

BACKGROUND AND AIM: Endoscopic submucosal tunnel dissection (ESTD) has been used for dissection of esophageal and gastric lesions. However, outcomes of ESTD for large lesions in the lesser gastric curvature had not been acknowledged because previous reports had the limitations of being single-center studies. We aimed to clarify the outcomes of ESTD for large lesser gastric curvature superficial neoplasms and provide our experience to accelerate its application. METHODS: Between July 2014 and July 2016, 87 patients with early cancer in the lesser gastric curvature treated at six Chinese institutions were enrolled. Our primary outcome was dissection speed. Moreover, both efficacy and safety clinical data were collected and analyzed retrospectively. RESULTS: All of the 87 patients were found to successfully undergo ESTD or ESD. Of these, 32 underwent ESTD and 55 underwent endoscopic submucosal dissection (ESD). The ESTD group had a higher dissection speed (18.0 mm2/min vs. 7.8 mm2/min, p < 0.01) and was associated with higher en bloc resection rate (100% vs. 87.3%, p = 0.035) and curative resection rate (100% vs. 85.5%, p = 0.024) compared with the ESD group. No perforation or muscular injury occurred in the ESTD group and its intraprocedural bleeding rate was lower (59.4% vs. 100%, p < 0.01) than that of the ESD group. CONCLUSIONS: In this multicenter retrospective study, outcomes of ESTD were excellent with a higher dissection speed and radical curative rate compared with ESD.

MiR-26b regulates 5-FU-resistance in human colorectal cancer via down-regulation of Pgp.

Chemotherapy resistance frequently drives tumor progression. However, the underlying molecular mechanisms remain unclear. In this study, we found that the expression level of miR-26b was down-regulated in the human colorectal cancer tissues and the resistant cells strains: HT-29/5-FU and LOVO/5-FU cells. Meanwhile, we showed that miR-26b improved sensibility of colorectal cancer cells to 5-FU in vitro and enhanced the potency of 5-FU in the inhibition of tumor growth in vivo. We further demonstrated that the tumor suppressive role of miR-26b was mediated by negatively regulating P-glycoprotein (Pgp) protein expression. Furthermore, studies of colorectal cancer specimens indicated that the expression of miR-26b and Pgp had inverse correlation. Importantly, we found that CpG islands in the miR-26b promoter region were hypermethylated in 5-FU resistant cells. Our study is the first to identify the tumor suppressive role of over-expressed miR-26b in chemo-sensitivity. Identification of a novel miRNA-mediated pathway that regulates chemo-sensitivity in colorectal cancer will facilitate the development of novel therapeutic strategies in the future.

[Value of non-invasive continuous hemodynamic monitoring system in the differential diagnosis of the patients with dyspnea].

OBJECTIVE: To evaluate non-invasive continuous hemodynamic (IQ System) monitoring in the differential diagnosis of dyspnea. METHODS: According to the diagnosis on discharge, 48 patients diagnosed as pulmonary dyspnea were enrolled in control group and 38 patients with cardiac dyspnea were in heart failure group. Each patient underwent IQ monitoring on admission and after recovery. The difference in the diagnosis on admission and on discharge, and the difference in IQ index were analyzed. RESULTS: (1) Clinical diagnosis: 7 patients in heart failure group were missed on admission as 5 were diagnosed as pneumonia and 2 were diagnosed as chronic obstructive pulmonary disease (COPD). One patient with pneumothorax in control group was misdiagnosed as heart failure. (2) Indexes of cardiac function: base impedance (Zo), maximum value of dz/dt (dz/dt max) and Heather index (HI) of heart failure group were markedly lower than those of control group (all P<0.001). The respective values were (19.0+/-3.5) Omega vs. (28.8+/-5.5) Omega, (0.76+/-0.42) Omega/s vs. (1.40+/-0.72) Omega/s, and (7.04+/-4.25) Omega/s2 vs. (13.60+/-6.36) Omega/s2. If Zo value of patients with dyspnea was 22 omicron or less, the sensitivity in diagnosing heart failure was 79 percent, and its specificity was 94 percent. If Zo value was 18.0 omicron or less, the sensitivity in diagnosing heart failure was 47 percent, and its specificity was 100 percent. (3) Comparison within groups: Indexes of cardiac function of control group did not change obviously and Zo, dz/dt max, HI, stroke volume (SV) and acceleration contraction index (ACI) values of heart failure group rose significantly after recovery. (4) Pre-ejection period (PEP) and left ventricular ejection time (VET) in both groups had no statistical significance in differences. CONCLUSION: IQ System was valuable in differential diagnosis to judge if dyspnea is caused by heart failure. Zo, dz/dt max and HI, especially Zo, are reliable.