Background: Gastrointestinal (GI) cancers represent a leading cause of cancer-related mortality worldwide, highlighting an urgent need for effective preventive approaches. While fatty acids (FAs) are implicated of carcinogenesis across multiple cancer types, their specific associations with GI cancer risk, and particularly their clinical utility as actionable biomarkers for risk stratification and personalized prevention within existing preventive frameworks, remain poorly understood. This study aimed to prospectively assess these associations and evaluate the clinical utility of plasma fatty acids for risk stratification and personalized prevention. Methods: This prospective cohort study included 91,239 cancer-free UK Biobank participants at baseline [2006-2010]. Plasma FAs were quantified using nuclear magnetic resonance (NMR) spectroscopy. Incident GI cancers [esophagus, stomach, colorectum, liver, bile duct, pancreas; International Classification of Diseases 10 (ICD-10) codes] were identified via national cancer registries through 2020. Multivariable Cox proportional hazards models estimated hazard ratios (HRs) for incident GI cancers, with comprehensive adjustment for sociodemographic, lifestyle, and clinical covariates. Results: During a median follow-up of 11.8 years, 1,519 incident GI cancer cases were documented. Compared to non-cases, cases were older (mean age 60.8 vs. 55.5 years) and had a higher proportion of males (58.2% vs. 45.8%). After comprehensive adjustment for sociodemographic factors [age, sex, family history, educational level, Townsend deprivation index (TDI)], lifestyle characteristics (smoking, alcohol consumption, lifestyle score), clinical covariates [body mass index (BMI), diabetes history], and mutual correction for FA classes, each one-standard-deviation increase in plasma polyunsaturated fatty acid (PUFA) levels was associated with a 21% reduced risk of overall GI cancer [hazard ratio (HR) per 1 standard deviation (1-SD) increase: 0.79; 95% confidence interval (CI): 0.71-0.87]. Cancer-specific analyses revealed significant risk reductions for esophageal (HR =0.68; 95% CI: 0.53-0.88), colorectal (HR =0.82; 95% CI: 0.70-0.95), and liver cancers (HR =0.66; 95% CI: 0.46-0.93). Subgroup analyses demonstrated stronger protective effects in males (HR =0.74), older adults (HR =0.73), and individuals with higher BMI (HR =0.81-0.82). Conversely, saturated fatty acids (SFAs) were positively associated with GI cancer risk. Conclusions: Elevated plasma PUFA levels are associated with reduced incidence of GI cancers, particularly in esophageal, colorectal, and liver cancers. These findings suggest that plasma PUFA measurements may facilitate the identification of high-risk subsets (e.g., males, older adults, individuals with obesity) and inform the development of biomarker-driven dietary guidelines for precision prevention. Randomized controlled trials are warranted to evaluate the efficacy of targeted PUFA supplementation in specific populations.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with an extremely poor prognosis, and current clinical treatment options are limited. Natural products, due to their multi-target and low-toxicity characteristics, have emerged as an important direction for the development of anti-tumor drugs. Palmaturbine (Pal), an isoquinoline alkaloid derived from Coptis chinensis and Berberis species, has shown anti-inflammatory and anti-tumor potential in preliminary studies; however, its mechanism of action in PDAC remains unclear. This study systematically evaluated the anti-tumor effects and molecular mechanisms of Pal on PDAC through in vitro and in vivo experiments. In vitro, Pal significantly inhibited PDAC cell proliferation, migration, and invasion, induced G2/M phase cell cycle arrest, and promoted apoptosis. Transcriptomic sequencing and Western blot analysis revealed that Pal suppressed the JAK2/STAT3 signaling pathway by inhibiting the phosphorylation of JAK2 and STAT3. Animal experiments further indicated that Pal significantly inhibited the growth of subcutaneous xenograft tumors in nude mice without causing obvious toxicity. In summary, Pal, as a natural JAK/STAT pathway inhibitor, exhibits favorable anti-tumor activity and safety in PDAC treatment, holding potential as a novel candidate drug for PDAC.

In pancreatic ductal adenocarcinoma (PDAC), the tumor immune microenvironment (TIME) is central to prognosis and therapeutic response, yet predictive biomarkers are still lacking. Here, we used PDAC patients from TCGA, CPTAC, and multiple centers to investigate and validate the relationship between the prognosis and tumor-infiltrating neutrophil-to-T-cell ratio (NTR) in the TIME, including the correlation of NTR with chemotherapy response in PDAC. We developed seven artificial intelligence models to evaluate NTR in the TIME, then evaluated their performance. The multi-modal ROI-model, designated PORCELAIN (Pancreatic Cancer Tumor-Infiltrating Neutrophil-to-T-Cell Ratio Evaluation with Artificial Intelligence), achieved superior external validation performance, demonstrating significant stratification of overall survival and recurrence-free survival. The NTR in the TIME is a potential biomarker for PDAC prognosis and treatment stratification. Importantly, PORCELAIN provides a noninvasive approach to assess NTR in the TIME, offering potential value for clinical management. Trial registration number: NCT06760234.

Biological matrices are rich in information related to life processes, serving as invaluable media for assessing an individual's overall physiological status and its dynamic fluctuations, as well as crucial foundations for disease diagnosis. However, the inherent complexity of these matrices, coupled with our incomplete understanding of their full composition, presents significant challenges for comprehensive analysis and accurate diagnostic interpretation. The advent of single-molecule technologies has revolutionized biomedical research, enabling the direct observation of life processes at the molecular scale. We have proposed an Intelligent Nano-Fingerprinting strategy based on single-molecule nanopore technology, designed to capture the global molecular fingerprints of complex plasma matrices. Furthermore, we developed an intelligent algorithmic model capable of achieving precise classification of plasma samples. This approach is characterized by its simplicity, efficiency, and considerable potential for large-scale adoption and transferable applications.

This article reports a rare case of extraosseous myxoid chondrosarcoma originating from the gallbladder. The patient, a 50-year-old female, presented with recurrent right upper quadrant abdominal pain for over two months, with worsening symptoms in the month prior to admission. Before hospitalization, enhanced computed tomography (CT) of the upper abdomen performed at a local hospital suggested a malignant gallbladder tumor (gallbladder cancer) with lymphadenopathy near the hepatic portal, as well as chronic cholecystitis with gallstones. Upon admission, whole-abdomen enhanced CT and liver-enhanced magnetic resonance imaging (MRI) confirmed uneven thickening of the gallbladder wall and multiple enlarged lymph nodes in the hepatic portal, further supporting the suspicion of gallbladder cancer. Tumor marker tests revealed elevated levels of carbohydrate antigen 19-9 (CA19-9) and cytokeratin 19 fragment. On 12 March 2020, the patient underwent extended radical resection for gallbladder cancer. The procedure included the removal of the gallbladder, hepatic lobe, right half of the colon, and greater omentum, along with extensive lymphadenectomy of the hepatic portal and posterior of the pancreatic head. Postoperative pathological examination confirmed the diagnosis of extraosseous myxoid chondrosarcoma, with the tumor involving the full thickness of the gallbladder, intrahepatic parenchyma, and the serosa to the muscular layer of the intestinal wall. Hematoxylin and eosin staining results supported this diagnosis. The patient recovered well postoperatively and did not receive any additional antitumor therapies, such as chemotherapy or radiotherapy. During a 36-month follow-up period after surgery, no tumor recurrence or metastasis was observed.

N6-Methyladenosine (m6A) modification is a prevalent alteration in RNA, influencing stability, localization, and translation. The m6A reader IGF2BP2 stabilizes various mRNA transcripts of oncogenic proteins and has been extensively implicated in various tumors. Intriguingly, in pancreatic ductal adenocarcinoma (PDAC), IGF2BP2 maintains its protein stability despite the elevated autophagic activity, suggesting the existence of regulatory mechanisms that counteract IGF2BP2 degradation in PDAC. Herein, we explore the crosstalk between m6A modification and protein homeostasis, particularly the protein stability of IGF2BP2 under excessive activation of autophagic flux. Mechanistically, we show that deubiquitinase USP7 acts on IGF2BP2, which enhances the stability of IGF2BP2 by reversing its K33-linked polyubiquitin chains, thereby preventing its degradation via the autophagy-lysosome pathway. Accumulated IGF2BP2 stabilizes PDGFA mRNA, activating myofibroblastic cancer-associated fibroblasts (myCAFs) through PDGFR interaction, which promotes resistance to gemcitabine. These findings uncover the USP7/IGF2BP2/PDGFA axis as a critical regulatory pathway in PDAC progression and chemoresistance.

Metabolic dysfunction-associated steatotic liver disease (MASLD), the most prevalent chronic liver condition globally, lacks adequate and effective therapeutic remedies in clinical practice. Recent studies have increasingly highlighted the close connection between the ubiquitin–proteasome system (UPS) and the progression of MASLD. This relationship is crucial for understanding the disease’s underlying mechanism. As a sophisticated process, the UPS govern protein stability and function, maintaining protein homeostasis, thus influencing a multitude of elements and biological events of eukaryotic cells. It comprises four enzyme families, namely, ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), ubiquitin-protein ligases (E3), and deubiquitinating enzymes (DUBs). This review aims to delve into the array of pathways and therapeutic targets implicated in the ubiquitination within the pathogenesis of MASLD. Therefore, this review unveils the role of ubiquitination in MASLD while spotlighting potential therapeutic targets within the context of this disease.

BACKGROUND:To explore the risk factors of post pancreatectomy diabetes mellitus (PPTDM)in pancreatic ductal carcinoma (PDAC) patients and the value of perioperative fasting blood glucose (FBG) level expression on the long-term survival after surgery. MATERIALS AND METHODS:Between December 2015 and December 2019, a cohort of 509 patients diagnosed with PDAC and undergoing resection at our hospital was analyzed. They were stratified into two groups, Control group (Control) and study group (PPTDM), depending on the onset of postoperative diabetes mellitus. We analyzed the survival rates at 6 months, 12 months and 24 months post-operation in the two groups. We use univariate and logostic multivariate regressions to analyze the risk factors for PPTDM. ROC curve analysis was conducted to assess the diagnostic significance of perioperative FBG levels regarding patients' long-term survival rates. The Kaplan-Meier method was employed to assess the impact of both preoperative and postoperative FBG levels on the survival rates within 24 months for each patient group. RESULTS:The comparison of general clinical data between the two groups shows marginal differences without statistical significance(P > 0.05); Patients in PPTDM group had significantly higher BMI, preoperative jaundice proportion, larger tumor diameter, higher TNM stage and higher proportion of distal pancreatectomy (DP), with P values of 0.023, 0.010, 0.040, 0.012 and 0.005, respectively. The levels of preoperative FBG and postoperative FBG in PPTDM patients exhibited statistically significant elevation compared to the control group (P < 0.05). There were no significant differences in surgery-related indicators between the two groups in operative time, number of dissected positive lymph nodes, total number of dissected lymph nodes, intraoperative blood loss and other related data (P > 0.05). Hospitalization duration of PPTDM patients was longer than control group (P = 0.047). PPTDM group had significantly higher expression concentrations of BUN, Cr, TG, LDL and Apo-B factors (P = 0.023, 0.024, 0.013, 0.045 and 0.017). 17 patients (5.03%) died in the PPTDM group and 4 patients (2.35%) in control group which had significantly difference (P = 0.020). In univariate and logostic multivariate regression analysis indicated tumor size, jaundice, BUN, Cr, TG, LDL, Apo-B concentrations and DP approach were significantly correlated to the risk for PPTDM (P < 0.05). ROC curve analysis results showed combining of preoperative and postoperation FBG showed the highest diagnostic efficacy, followed by postoperation FBG and preoperative FBG. The AUC areas of the three groups were 0.745, 0.623 and 0.588, respectively, and the critical values of the three groups were 9.81/9.95 mmol/L, 10.18 mmol/L and 10.23 mmol/L, respectively, with statistical significance (P < 0.05). Results were considered statistically significant if the p-value was less than 0.05. CONCLUSION:PPTDM stands as a significant postoperative complication following pancreatic cancer surgery, characterized by a high incidence and severity. Several risk factors have garnered considerable attention among clinical surgeon. PPTDM may be an influential factor in postoperative prognosis of pancreatic cancer. The expression levels of preoperative and postoperative blood glucose hold diagnostic value for the long-term prognosis of pancreatic cancer patients. Early regulation and intervention by surgeons concerning perioperative FBG could potentially mitigate the risk of PPTDM.

Elevated blood glucose levels may serve as an early indicator of underlying pancreatic cancer. Discriminating between pancreatic cancer-associated new-onset diabetes (PCAND) and new-onset type 2 diabetes mellitus (T2DM) holds promise for enabling an earlier diagnosis of pancreatic cancer. Nevertheless, the absence of effective biomarkers for distinguishing PCAND from the more prevalent new-onset T2DM persists, primarily because of the elusive pathogenesis of PCAND. In this study, the intricate intercellular communication is comprehensively elucidated through single-cell RNA sequencing. The findings identified Midkine (MDK) as a potential mediator of the interaction between tumor and beta cells. MDK, which originated from pancreatic ductal adenocarcinoma cells, exerted deleterious effects on paraneoplastic beta cells by binding to the SDC4 receptor on the beta cell surface and subsequently downregulating the Ras signaling pathway, thereby impairing insulin production and secretion. Notably, the plasma levels of MDK are higher in patients with PCAND than in those with T2DM. In conclusion, MDK has emerged as a pivotal driver of PCAND pathogenesis and may function as a blood-based biomarker for discriminating between PCAND and T2DM in populations with new-onset diabetes, thereby facilitating the advancement of early detection strategies for pancreatic cancer.

Gastrointestinal tumors are among the malignancies with the highest global incidence and mortality rates, and their diagnosis and treatment heavily rely on histopathological examination. However, traditional pathological assessment faces challenges such as strong subjectivity, heavy workload, and low diagnostic consistency. In recent years, with advancements in high-resolution digital slide scanning technology and the rapid development of deep learning algorithms, pathomics has emerged as a novel tool for the precise diagnosis and treatment of gastrointestinal tumors. By extracting high-throughput quantitative features from whole slide images and combining machine learning and deep learning techniques, pathomics enables automated tumor typing, prognosis prediction, and treatment response evaluation. This article reviews the research progress of pathomics in gastrointestinal tumors, focusing on its applications in gene mutation prediction, prognosis assessment, and treatment response prediction, while analyzing current challenges and future directions.

AbstractA rise in blood glucose is an early warning sign of underlying pancreatic cancer (PC) and may be an indicator of genetic events in PC progression. However, there is still a lack of mechanistic research on pancreatic cancer-associated new-onset diabetes (PCAND). In the present study, we identified a gene SRI, which possesses a SNP with the potential to distinguish PCAND and Type 2 diabetes mellitus (T2DM), by machine learning on the basis of the UK Biobank database. In vitro and in vivo, sorcin overexpression induced pancreatic β-cell dysfunction. Sorcin can form a positive feedback loop with STAT3 to increase the transcription of serpin E1 and CCL5, which may directly induce β-cell dysfunction. In 88 biopsies, the expression of sorcin was elevated in PC tissues, especially in PCAND samples. Furthermore, plasma serpin E1 levels are higher in peripheral blood samples from PCAND patients than in those from T2DM patients. In conclusion, sorcin may be the key driver in PCAND, and further study on the sorcin-STAT3-serpin E1/CCL5 signaling axis may help us better understand the pathogenesis of PCAND and identify potential biomarkers.

Congenital diaphragmatic hernias are primarily found in infants and have a high mortality rate due to neonatal respiratory distress. The most common type of congenital diaphragmatic hernia is Bochdalek hernia, which occurs in the posterolateral diaphragm, with the left side being the most commonly affected. However, congenital diaphragmatic hernias are extremely rare in adults and are often misdiagnosed due to their subtle symptoms. Therefore, we suggest that a contrast-enhanced CT scan should be used for early screening and diagnosis in all patients with sudden severe pain or recurrent ambiguous symptoms in the chest and abdomen. This case report presents a rare occurrence of Bochdalek hernia in an adult male. The patient experienced nonspecific abdominal symptoms after eating. The hernia resulted in the displacement of the left kidney, the transverse colon of the splenic flexure, and most of the stomach into the thoracic cavity. This displacement led to atelectasis of the left lung, which reached three-fifths of its capacity. The patient underwent successful treatment using a combination of laparoscopy and open surgery. Follow-up CT scans conducted two weeks, three months, and one year later revealed a stable condition with no complications.

Gastrointestinal stromal tumors (GISTs) are soft tissue sarcomas that originate from the mesenchymal cells of the gastrointestinal tract. Extra-GISTs (EGISTs) are caused by sites outside the gastrointestinal tract. We reported a case of EGIST of the pancreas in a 51-year-old woman. Enhanced CT scan showed a rounded, slightly hypointense focus in the head of the pancreas and the right pars compacta of the descending duodenum. Routine laboratory and endocrine tests were unremarkable. The patient underwent laparoscopic surgery. The diagnosis of EGIST was confirmed through histopathological and immunohistochemical examination. The tumor was found to be CD117+, CD34+, and DOG+ with a high risk of malignancy. No recurrence was observed during the nine-month postoperative follow-up.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer that often exhibits resistance to chemotherapy. Pancreatic stellate cells (PSCs) play a crucial role in regulating the tumor microenvironment (TME), including promoting chemoresistance. However, the specific mechanisms underlying this promotion remain unclear. We employed a multi-omics approach, including transcriptomics, proteomics, and metabolomics, to analyze human-derived PSCs and their treated samples. We identified the aberrantly activated arachidonic acid metabolic pathway and its key enzyme PTGS1 and LTC4S in activated PSCs. We constructed a prognostic model related to the arachidonic acid metabolic enzymes and identified the potential biomarker CAV2. In vitro experiments demonstrated that CAV2 was highly expressed in PSCs and its expression could be effectively suppressed by siRNA transfection. Compared to the control group, inhibiting CAV2 in PSCs significantly reduced the proliferation and chemoresistance of PCCs. Additionally, inhibiting CAV2 expression also decreased the expression of cyclooxygenase-1 (COX-1). These findings are clinically significant for further exploring the molecular mechanisms of CAV2-mediated pancreatic cancer proliferation and chemoresistance, as well as improving the prognosis of pancreatic cancer patients.

The traditional recognition of extracellular matrix (ECM) at tissue sections relies on the time-consuming immunofluorescence that could not meet the demand of rapid diagnosis. Herein, we introduce a thickness-resolved electrochemiluminescence (ECL) microscopy to image thin-layer ECM at tissue sections for fast histopathological analysis. The unique surface-confined ECL mechanism enables to unveil the diversity and complexity of multiple tissue structures with varying thicknesses. Notably, the short lifetimes and the limited diffusion of electrogenerated coreactant radicals combined with their chemical reactivity result in a 2-fold increase in ECL intensity on ECM structures compared to the remaining tissue, enabling ECM visualization without specific labeling. The further quantitation of the ECM localization within tissue sections furnishes crucial insights into tumor progression and, more importantly, differentiates carcinoma and paracancerous tissues from patients in less than 30 min. Moreover, the reported electrochemistry-based microscopy is a dynamic approach allowing to investigate the transport, tortuosity, and trafficking properties through the tissues. This thickness-resolved recognition strategy not only opens new avenues for imaging complex samples but also holds promise for expediting tissue pathologic diagnosis, offering a more automated protocol with enhanced quantitative data compared to current intraoperative pathology methods.

ABSTRACT Introduction Individuals who develop new‐onset diabetes have been identified as a high‐risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identifying high‐risk individuals among those with new‐onset diabetes. Methods Employing the UK Biobank cohort, we focused on those developing new‐onset diabetes during follow‐up. Genetic and clinical characteristics available at registration were considered as candidate predictors. We conducted univariate regression analysis to identify potential indicators and used a 5‐fold cross‐validation method to select optimal predictors for model development. Five machine learning algorithms were used for model development. Results Among 12,735 patients with new‐onset diabetes, 100 (0.8%) were diagnosed with PC within 2 years. The final model (area under the curve, 0.897; 95% confidence interval, 0.865–0.929) included 5 clinical predictors and 24 single nucleotide polymorphisms. Two threshold cut‐offs were established: 1.28% and 5.26%. The recommended 1.28% cut‐off, based on model performance, reduces definitive testing to 13% of the total population while capturing 76% of PC cases. The high‐risk threshold is 5.26%. Utilizing this threshold, only 2% of the population needs definitive testing, capturing nearly half of PC cases. Conclusions We, for the first time, combined clinical and genetic data to develop and validate a model to determine the risk of pancreatic cancer in patients with new‐onset diabetes using machine learning algorithms. By reducing the number of unnecessary tests while ensuring that a substantial proportion of high‐risk patients are identified, this tool has the potential to improve patient outcomes and optimize healthcare sources.

OBJECTIVES:The study aim to investigate whether elderly patients with resectable pancreatic ductal adenocarcinoma (PDAC) could benefit from postoperative chemotherapy.METHODS:This study selects the data of PDAC patients who were diagnosed between 2004 and 2014 from the Surveillance, Epidemiology, and End Results program. Median overall survival (mOS) is determined by Kaplan-Meier survival curves. Multivariate logistic regression analysis and hazard ratio are employed to assess the association among potential prognostic factors. Propensity score matching evaluation is used to reduce bias.RESULTS:In total, there are 11,865 PDAC patients selected from the Surveillance, Epidemiology, and End Results database. Elderly PDAC patients have poor prognoses compared with younger (mOS, 15 vs 21 months). The possible reason might be that the elderly patients are less likely to receive postoperative chemotherapy. After propensity score matching, it is found that, for those who receive postoperative chemotherapy, although the mOS of older group is not as good as that of the younger group (mOS, 20 vs 23 months; 18-month survival rate: 53.4% vs 61.3%), the mOS of older group prolonged by postoperative chemotherapy is similar to that of younger group (9 vs 9 months).CONCLUSIONS:Elderly PDAC patients (≥70 years) might benefit from the currently used postoperative chemotherapy regimens.

BackgroundImmune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC.MethodsWe comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients’ clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell’s concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms.ResultsSoluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes’ expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16).ConclusionFive soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

BackgroundHepatoid adenocarcinoma of the stomach (HAS) is a highly malignant subtype of gastric carcinoma with specific clinicopathological features and extremely poor prognosis. We present an exceedingly rare case of complete response after chemo-immunotherapy.Case DescriptionA 48-year-old woman with highly elevated serum alpha-fetoprotein (AFP) level was found to have HAS verified by pathological examination based on gastroscopy. Computed tomography scan was done and TNM staging of the tumor was T4aN3aMx. Programmed cell death ligand-1 (PD-L1) immunohistochemistry was performed, revealing a negative PD-L1 expression. Chemo-immunotherapy including oxaliplatin plus S-1 and PD-1 inhibitor terelizumab was given to this patient for 2 months until the serum AFP level decreased from 748.5 to 12.9 ng/mL and the tumor shrank. D2 radical gastrectomy was then performed and histopathology of the resected specimen revealed that the cancerous cells had disappeared. Pathologic complete response (pCR) was achieved and no evidence of recurrence has been found after 1 year of follow-up.ConclusionsWe, for the first time, reported an HAS patient with negative PD-L1 expression who achieved pCR from the combined chemotherapy and immunotherapy. Although no consensus has been reached regarding the therapy, it might provide a potential effective management strategy for HAS patient.

Background: The association between night shift work and gastrointestinal (GI) cancer has been controversial. The aim of this research was to investigate the association between current and past night shift work and GI cancer risk, as well as the interaction between night shift work and genetic vulnerability.Methods: This large-scale prospective cohort study included 274331 participants in paid employment or who were self-employed at baseline from the UK Biobank. Current night shift work, lifetime duration and average lifetime frequency of night shift information was obtained. Multivariable cox regression model was used to estimate the association of night shift work and GI cancer risk, which was further stratified by chronotype and Melatonin receptor 1B gene (MTNR1B) rs10830963 polymorphism. Weighted genetic risk score for GI cancer was calculated and assessed whether it could be modified by night shift work.Findings: Over an average follow-up of 7.81 years, a total of 2721 incident GI cancer cases were observed. Current night shift work did not increase overall GI cancer risk after adjustment for multiple confounders (Some night shifts: hazards ratios (HR) 1.06, [95% confidence interval (CI): 0.88-1.27]; Usual/permanent night shifts: HR 1.11 [95% CI: 0.91-1.35]). In stratified analysis, current night shift exposure might increase the risk of overall GI cancer risk in individuals with MTNR1B rs10830963 GG genotype (Shift but never/rarely night shifts: HR 1.49, [95% CI: 0.97-2.30]; Some night shifts: HR 1.85, [95% CI: 1.11-3.10]; Usual/permanent night shifts: HR 2.16, [95% CI: 1.25-3.74)]). No significant association was seen in the analysis involving average lifetime night shift frequency or lifetime duration of night shift work and genetic GI cancer predisposition was not modified by shift work exposure. Further, among night shift workers, compared with those with CC genotype, GG carriers had a significantly higher risk of GI cancer (P for trend=0.007, HR 1.52, [95% CI: 1.14-2.03]).PInterpretation: No association was found between night shift work and overall GI cancer risk regardless of genetic risk. However, night shift exposure might increase the risk of GI cancer in individuals carrying MTNR1B rs10830963 GG genotype.Funding: This work was supported by the National Natural Science Foundation of China under grants No.82272954 (Yulian Wu), National Key R&D Program of China under grant No. 2019YFC0118802 (Jian Wu), Zhejiang public welfare technology research project under grant No. LGF20F020013 (Jian Wu).Declaration of Interest: The authors declare no potential conflicts of interest.