PRL1 and PRL3 promote macropinocytosis via its lipid phosphatase activity.

PRL1 and PRL3, members of the protein tyrosine phosphatase family, have been associated with cancer metastasis and poor prognosis. Despite extensive research on their protein phosphatase activity, their potential role as lipid phosphatases remains elusive. Methods: We conducted comprehensive investigations to elucidate the lipid phosphatase activity of PRL1 and PRL3 using a combination of cellular assays, biochemical analyses, and protein interactome profiling. Functional studies were performed to delineate the impact of PRL1/3 on macropinocytosis and its implications in cancer biology. Results: Our study has identified PRL1 and PRL3 as lipid phosphatases that interact with phosphoinositide (PIP) lipids, converting PI(3,4)P2 and PI(3,5)P2 into PI(3)P on the cellular membranes. These enzymatic activities of PRLs promote the formation of membrane ruffles, membrane blebbing and subsequent macropinocytosis, facilitating nutrient extraction, cell migration, and invasion, thereby contributing to tumor development. These enzymatic activities of PRLs promote the formation of membrane ruffles, membrane blebbing and subsequent macropinocytosis. Additionally, we found a correlation between PRL1/3 expression and glioma development, suggesting their involvement in glioma progression. Conclusions: Combining with the knowledge that PRLs have been identified to be involved in mTOR, EGFR and autophagy, here we concluded the physiological role of PRL1/3 in orchestrating the nutrient sensing, absorbing and recycling via regulating macropinocytosis through its lipid phosphatase activity. This mechanism could be exploited by tumor cells facing a nutrient-depleted microenvironment, highlighting the potential therapeutic significance of targeting PRL1/3-mediated macropinocytosis in cancer treatment.

Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer.

BACKGROUND: Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality. METHODS: We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation. RESULTS: Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified. CONCLUSIONS: We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.

Development and evaluation of a risk prediction tool for risk-adapted screening of colorectal cancer in China.

Risk prediction tools for colorectal cancer (CRC) have potential to improve the efficiency of population-based screening by facilitating risk-adapted strategies. However, such an applicable tool has yet to be established in the Chinese population. In this study, a risk score was created using data from the China Kadoorie Biobank (CKB), a nationwide cohort study of 409,854 eligible participants. Diagnostic performance of the risk score was evaluated in an independent CRC screening programme, which included 91,575 participants who accepted colonoscopy at designed hospitals in Zhejiang Province, China. Over a median follow-up of 11.1 years, 3136 CRC cases were documented in the CKB. A risk score was created based on nine questionnaire-derived variables, showing moderate discrimination for 10-year CRC risk (C-statistic = 0.68, 95 % CI: 0.67-0.69). In the CRC screening programme, the detection rates of CRC were 0.25 %, 0.82 %, and 1.93 % in low-risk (score <6), intermediate-risk (score: 6-19), and high-risk (score >19) groups, respectively. The newly developed score exhibited a C-statistic of 0.65 (95 % CI: 0.63-0.66), surpassing the widely adopted tools such as the Asia-Pacific Colorectal Screening (APCS), modified APCS, and Korean Colorectal Screening scores (all C-statistics = 0.60). In conclusion, we developed a novel risk prediction tool that is useful to identify individuals at high risk of CRC. A user-friendly online calculator was also constructed to encourage broader adoption of the tool.

Development and validation of a deep learning model for predicting gastric cancer recurrence based on CT Imaging: a multicenter study.

INTRODUCTION: The postoperative recurrence of gastric cancer has a significant impact on the overall prognosis of patients. Therefore, accurately predicting the postoperative recurrence of gastric cancer is crucial. METHODS: This retrospective study gathered data from 2,813 gastric cancer patients who underwent radical surgery between 2011 and 2017 at two medical centers. Follow-up was extended until May 2023, and cases were categorized as recurrent or non-recurrent based on postoperative outcomes. Clinical pathological information and imaging data were collected for all patients. A new deep learning signature (DLS) was generated using pretreatment CT images, based on a pre-trained baseline (a customized Resnet50), for predicting postoperative recurrence. The deep learning fusion signature (DLFS) was created by combining the score of DLS with the weighted values of identified clinical features. The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. Survival curves were plotted to investigate the differences between DLFS and prognosis. RESULTS: In this study, 2813 patients with gastric cancer (GC) were recruited and allocated into training, internal validation, and external validation cohorts. The DLFS was developed and assessed for its capability in predicting the risk of postoperative recurrence. The DLFS exhibited excellent performance with AUCs of 0.833 (95% CI, 0.809-0.858) in the training set, 0.831 (95% CI, 0.792-0.871) in the internal validation set, and 0.859 (95% CI, 0.806-0.912) in the external validation set, along with satisfactory calibration across all cohorts (P>0.05). Furthermore, the DLFS model significantly outperformed both the clinical model and DLS (P<0.05). High-risk recurrent patients exhibit a significantly poorer prognosis compared to low-risk recurrent patients (P<0.05). CONCLUSIONS: The integrated model developed in this study, focusing on GC patients undergoing radical surgery, accurately identifies cases at high risk of postoperative recurrence and highlights the potential of DLFS as a prognostic factor for GC patients.

Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment.

Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.

Revolutionizing T3-4N0-2M0 gastric cancer staging with an innovative pathologic N classification system.

BACKGROUND: The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). METHODS: Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve. RESULTS: The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort. CONCLUSION: This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC.

Clinical significance of geriatric nutritional risk index in esophageal squamous cell carcinoma receiving neoadjuvant immunotherapy.

OBJECTIVE: The geriatric nutritional risk index (GNRI) is a novel nutrition-related indicator designed to predict the risk of clinical outcomes in various cancers. The clinical significance of risk assessment, therapeutic response, and prognostic prediction of GNRI in esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunochemotherapy (NICT), a hot point of treatment these days, have not been documented in any research. METHODS: Two hundred and twenty-four cases with ESCC who underwent radical resection after NICT were retrospectively recruited. Using the calculation formula of GNRI (1.489 × albumin (g/L) + 41.7 × current weight/ideal weight), the cases were split into two cohorts. Analysis was done on the connections between GNRI and clinical outcomes, such as clinical features, postoperative complications, and pathological complete response (pCR). Prognostic factors of overall survival (OS) and disease-free survival (DFS) were also performed. RESULTS: Patients were then categorized as low (n = 139) or high (n = 85) group based on the threshold. After radical surgery, 67 patients achieved pCR (29.9%). Higher pCR rates were attained by patients in the high GNRI group (41.2% vs. 23.0%, P = 0.004). Lower GNRI patients experienced a considerably higher severe morbidity (36.7% vs. 23.5%, P = 0.040), particularly in the case of respiratory complications (28.8% vs. 14.1%, P = 0.012). Compared to high GNRI patients, lower GNRI cases had inferior 3-year OS (68.5% vs. 87.3%, P = 0.003) and DFS (64.8% vs. 81.5%, P = 0.002). It was also discovered that GNRI was a significant independent variable of both DFS [hazard ratios (HR) = 0.436, P = 0.009] and OS (HR = 0.294, P = 0.012). CONCLUSION: The GNRI, based on nutrition-related indicators, was independently related to postoperative complications, pCR prediction, and prognostication in ESCC receiving NICT.

A retrospective study: exploring the optimal patient population for adjuvant chemotherapy after D2 gastrectomy.

BACKGROUND: Adjuvant chemotherapy (CT) constitutes the primary approach for treating resectable advanced gastric cancer (GC). However, the effectiveness of postoperative CT can differ across various patient groups. This retrospective study aimed to examine how variances in clinical and pathologic factors affect postoperative CT. METHODS: This study enrolled 2060 patients with GC who underwent curative gastrectomy at Zhejiang Cancer Hospital between January 2008 and December 2017, with 1277 receiving postoperative CT. This study used Kaplan-Meier to determine the effect of clinical and pathology factors on CT benefits. In addition, univariate and multivariate Cox regression analyses were used to identify independent prognosis risk factors. RESULTS: Both univariate and multivariate analyses demonstrated that the absence of postoperative CT is an independent factor associated with a poor prognosis in patients with GC. The Kaplan-Meier univariate analysis revealed that specific subgroups, including males, those with a normal body mass index (BMI), the elderly, individuals with gastric adenocarcinoma, cases of nerve invasion by the tumor, vascular invasion by the tumor, tumor size ≥ 5 cm, and Tumor, Node, Metastasis (TNM) stage III, exhibited improved treatment outcomes with the administration of postoperative CT. The creation of nomograms using Cox regression and the rms package holds significant clinical relevance. CONCLUSION: Postoperative CT is advantageous for prolonging the survival of advanced patients undergoing D2 gastrectomy, particularly in male patients, the elderly, individuals with a normal BMI score, those diagnosed with gastric adenocarcinoma, cases, in which the tumor invades nerves or blood vessels, patients with a tumor size of ≥5 cm, and those with a TNM stage of III, as it results in improved treatment outcomes within these subgroups.

Safety and efficacy of a programmed cell death 1 inhibitor combined with oxaliplatin plus S-1 in patients with Borrmann large type III and IV gastric cancers.

BACKGROUND: Gastric cancer (GC) is the fifth most common and the fourth most lethal malignant tumour in the world. Most patients are already in the advanced stage when they are diagnosed, which also leads to poor overall survival. The effect of postoperative adjuvant chemotherapy for advanced GC is unsatisfactory with a high rate of distant metastasis and local recurrence. AIM: To investigate the safety and efficacy of a programmed cell death 1 (PD-1) inhibitor combined with oxaliplatin and S-1 (SOX) in the treatment of Borrmann large type III and IV GCs. METHODS: A retrospective analysis (IRB-2022-371) was performed on 89 patients with Borrmann large type III and IV GCs who received neoadjuvant therapy (NAT) from January 2020 to December 2021. According to the different neoadjuvant treatment regimens, the patients were divided into the SOX group (61 patients) and the PD-1 + SOX (P-SOX) group (28 patients). RESULTS: The pathological response (tumor regression grade 0/1) in the P-SOX group was significantly higher than that in the SOX group (42.86% vs 18.03%, P = 0.013). The incidence of ypN0 in the P-SOX group was higher than that in the SOX group (39.29% vs 19.67%, P = 0.05). The use of PD-1 inhibitors was an independent factor affecting tumor regression grade. Meanwhile, the use of PD-1 did not increase postoperative complications or the adverse effects of NAT. CONCLUSION: A PD-1 inhibitor combined with SOX could significantly improve the rate of tumour regression during NAT for patients with Borrmann large type III and IV GCs.

Genomic and immune microenvironment features influencing chemoimmunotherapy response in gastric cancer with peritoneal metastasis: a retrospective cohort study.

BACKGROUND: Patients with peritoneal metastasis (PM) from gastric cancer (GC) exhibit poor prognosis. Chemoimmunotherapy offers promising clinical benefits; however, its efficacy and predictive biomarkers in a conversion therapy setting remain unclear. The authors aimed to retrospectively evaluate chemoimmunotherapy efficacy in a conversion therapy setting for GC patients with PM and establish a prediction model for assessing clinical benefits. MATERIALS AND METHODS: A retrospective evaluation of clinical outcomes encompassed 55 GC patients with PM who underwent chemoimmunotherapy in a conversion therapy setting. Baseline PM specimens were collected for genomic and transcriptomic profiling. Clinicopathological factors, gene signatures, and tumor immune microenvironment were evaluated to identify predictive markers and develop a prediction model. RESULTS: Chemoimmunotherapy achieved a 41.8% objective response rate and 72.4% R0 resection rate in GC patients with PM. Patients with conversion surgery showed better overall survival (OS) than those without the surgery (median OS: not reached vs 7.82 m, P <0.0001). Responders to chemoimmunotherapy showed higher ERBB2 and ERBB3 mutation frequencies, CTLA4 and HLA-DQB1 expression, and CD8+ T cell infiltration, but lower CDH1 mutation and naïve CD4+ T cell infiltration, compared to nonresponders. A prediction model was established integrating CDH1 and ERBB3 mutations, HLA-DQB1 expression, and naïve CD4+ T cell infiltration (AUC=0.918), which were further tested using an independent external cohort (AUC=0.785). CONCLUSION: This exploratory study comprehensively evaluated clinicopathological, genomic, and immune features and developed a novel prediction model, providing a rational basis for the selection of GC patients with PM for chemoimmunotherapy-involved conversion therapy.

Blocking Ubiquitin-Specific Protease 7 Induces Ferroptosis in Gastric Cancer via Targeting Stearoyl-CoA Desaturase.

Gastric cancer (GC) presents a formidable global health challenge, and conventional therapies face efficacy limitations. Ubiquitin-specific protease 7 (USP7) plays pivotal roles in GC development, immune response, and chemo-resistance, making it a promising target. Various USP7 inhibitors have shown selectivity and efficacy in preclinical studies. However, the mechanistic role of USP7 has not been fully elucidated, and currently, no USP7 inhibitors have been approved for clinical use. In this study, DHPO is identified as a potent USP7 inhibitor for GC treatment through in silico screening. DHPO demonstrates significant anti-tumor activity in vitro, inhibiting cell viability and clonogenic ability, and preventing tumor migration and invasion. In vivo studies using orthotopic gastric tumor mouse models validate DHPO's efficacy in suppressing tumor growth and metastasis without significant toxicity. Mechanistically, DHPO inhibition triggers ferroptosis, evidenced by mitochondrial alterations, lipid Reactive Oxygen Species (ROS), Malondialdehyde (MDA) accumulation, and iron overload. Further investigations unveil USP7's regulation of Stearoyl-CoA Desaturase (SCD) through deubiquitination, linking USP7 inhibition to SCD degradation and ferroptosis induction. Overall, this study identifies USP7 as a key player in ferroptosis of GC, elucidates DHPO's inhibitory mechanisms, and highlights its potential for GC treatment by inducing ferroptosis through SCD regulation.

Protein Tyrosine Phosphatase PRL-3: A Key Player in Cancer Signaling.

Protein phosphatases are primarily responsible for dephosphorylation modification within signal transduction pathways. Phosphatase of regenerating liver-3 (PRL-3) is a dual-specific phosphatase implicated in cancer pathogenesis. Understanding PRL-3's intricate functions and developing targeted therapies is crucial for advancing cancer treatment. This review highlights its regulatory mechanisms, expression patterns, and multifaceted roles in cancer progression. PRL-3's involvement in proliferation, migration, invasion, metastasis, angiogenesis, and drug resistance is discussed. Regulatory mechanisms encompass transcriptional control, alternative splicing, and post-translational modifications. PRL-3 exhibits selective expressions in specific cancer types, making it a potential target for therapy. Despite advances in small molecule inhibitors, further research is needed for clinical application. PRL-3-zumab, a humanized antibody, shows promise in preclinical studies and clinical trials. Our review summarizes the current understanding of the cancer-related cellular function of PRL-3, its prognostic value, and the research progress of therapeutic inhibitors.

A multicenter clinical AI system study for detection and diagnosis of focal liver lesions.

Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis. We developed and validated a fully automated diagnostic system named Liver Artificial Intelligence Diagnosis System (LiAIDS) based on a diverse sample of 12,610 patients from 18 hospitals, both retrospectively and prospectively. In this study, LiAIDS achieved an F1-score of 0.940 for benign and 0.692 for malignant lesions, outperforming junior radiologists (benign: 0.830-0.890, malignant: 0.230-0.360) and being on par with senior radiologists (benign: 0.920-0.950, malignant: 0.550-0.650). Furthermore, with the assistance of LiAIDS, the diagnostic accuracy of all radiologists improved. For benign and malignant lesions, junior radiologists' F1-scores improved to 0.936-0.946 and 0.667-0.680 respectively, while seniors improved to 0.950-0.961 and 0.679-0.753. Additionally, in a triage study of 13,192 consecutive patients, LiAIDS automatically classified 76.46% of patients as low risk with a high NPV of 99.0%. The evidence suggests that LiAIDS can serve as a routine diagnostic tool and enhance the diagnostic capabilities of radiologists for liver lesions.

Synthesis and evaluation of WK-X-34 derivatives as P-glycoprotein (P-gp/ABCB1) inhibitors for reversing multidrug resistance.

The emergence of multidrug resistance (MDR) in malignant tumors is one of the leading threats encountered currently by many chemotherapeutic agents. A proposed strategy to overcome MDR is to disable the efflux function of P-glycoprotein (P-gp/ABCB1), a critical member of the ABC transporter family that significantly increases the efflux of various anticancer drugs from tumor cells. In this study, structural modification of a third-generation P-gp inhibitor WK-X-34 based on bioisosteric and fragment-growing strategies led to the discovery of the adamantane derivative PID-9, which exhibited the best MDR reversal activity (IC50 = 0.1338 µM, RF = 78.6) in this series, exceeding those of the reported P-gp inhibitors verapamil and WK-X-34. In addition, compared with WK-X-34, PID-9 showed decreased toxicity to cells. Furthermore, the mechanism studies revealed that the reversal activity of adamantane derivatives PID-5, PID-7, and PID-9 stemmed from the inhibition of P-gp efflux. These results indicated that compound PID-9 is the most effective P-gp inhibitor among them with low toxicity and high MDR reversal activity, which provided a fundamental structural reference for further discovery of novel, effective, and non-toxic P-gp inhibitors.

The promise and challenges of combination therapies with antibody-drug conjugates in solid tumors.

Antibody-drug conjugates (ADCs) represent an important class of cancer therapies that have revolutionized the treatment paradigm of solid tumors. To date, many ongoing studies of ADC combinations with a variety of anticancer drugs, encompassing chemotherapy, molecularly targeted agents, and immunotherapy, are being rigorously conducted in both preclinical studies and clinical trial settings. Nevertheless, combination therapy does not always guarantee a synergistic or additive effect and may entail overlapping toxicity risks. Therefore, understanding the current status and underlying mechanisms of ADC combination therapy is urgently required. This comprehensive review analyzes existing evidence concerning the additive or synergistic effect of ADCs with other classes of oncology medicines. Here, we discuss the biological mechanisms of different ADC combination therapy strategies, provide prominent examples, and assess their benefits and challenges. Finally, we discuss future opportunities for ADC combination therapy in clinical practice.

Burdens of stomach and esophageal cancer from 1990 to 2019 and projection to 2030 in China: Findings from the 2019 Global Burden of Disease Study.

Background: Stomach and esophageal cancer exhibit high morbidity and mortality rate in China, resulting in substantial disease burdens. It is imperative to identify the temporal trends of stomach and esophageal cancer from 1990 to 2019 and project future trends until 2030, which can provide valuable information for planning effective management and prevention strategies. Methods: We collected and analysed data from the Global Burden of Disease (GBD) between 1990 and 2019, including incidence, mortality, disability-adjusted life years (DALYs), age-standardised incidence rate (ASIR), mortality rate (ASMR) and DALYs rate. We also calculated and reported the proportion of mortality and DALYs attributable to risk factors by sex in China and different regions. The Bayesian age-period-cohort model was applied to project future trends until 2030. Results: The new cases, deaths and DALYs of stomach and esophageal cancer increased from 1990 to 2019. However, the ASIR, ASMR and age-standardised DALYs rates for stomach and esophageal cancer all decreased during the same period. These changes may be related to risks, such as smoking and diet. Furthermore, we utilised the projection model to estimate that the ASIR and ASMR of stomach and esophageal cancer among females will likely follow steady downward trends, while the ASMR of stomach cancer among males is expected to exhibit a significant decline. However, the ASIR of stomach and esophageal cancer and the ASMR of esophageal cancer among males are projected to display slight upward trends until 2030. Conclusions: The analysis of stomach and esophageal cancer trends in China from 1990 to 2030 reveals a general decline. However, it is crucial to acknowledge the persistent high burden of both cancers in the country. Adopting healthy lifestyle practices, including the reduction of tobacco and alcohol intake, avoidance of moldy foods and increased consumption of fresh fruits and vegetables can contribute to mitigating the risk of stomach and esophageal cancer. Significantly, the formulation and implementation of well-founded and efficacious public health policies are imperative for alleviating the disease burden in China.

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study.

BACKGROUND: Our previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer. METHODS: We employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins. RESULTS: We measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort. CONCLUSIONS: We characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer. Video Abstract.

Development and validation of nomogram for predicting early recurrence after radical gastrectomy of gastric cancer.

BACKGROUND: After radical surgery, early detection of recurrence and metastasis is a crucial factor in enhancing the prognosis and survival of patients with gastric cancer (GC). Therefore, assessing the risk of recurrence in gastric cancer patients and determining the timing for postoperative recurrence is crucial. METHODS: The clinicopathological data of 521 patients with recurrent gastric cancer, who underwent radical gastrectomy at Zhejiang Cancer Hospital between January 2010 and January 2017, were retrospectively analyzed. These patients were randomly divided into two groups: a training group (n = 365) and a validation group (n = 156). In the training set, patients were further categorized into early recurrence (n = 263) and late recurrence (n = 102) groups based on a 2-year boundary. Comparative analyses of clinicopathological features and prognoses were conducted between these two groups. Subsequently, a nomogram for predicting early recurrence was developed and validated. RESULTS: In this study, the developed nomogram incorporated age, serous infiltration, lymph node metastasis, recurrence mode, and the tumour marker CA19-9. In the training cohort, the area under the curve (AUC value) was 0.739 (95% CI, 0.682-0.798), with a corresponding C-index of 0.739. This nomogram was subsequently validated in an independent validation cohort, yielding an AUC of 0.743 (95% CI, 0.652-0.833) and a C-index of 0.743. Furthermore, independent risk factors for prognosis were identified, including age, absence of postoperative chemotherapy, early recurrence, lymph node metastasis, abdominal metastasis, and vascular cancer embolus. CONCLUSION: Independent risk factors for gastric cancer recurrence following radical surgery were utilized to construct a nomogram for predicting early relapse. This nomogram effectively assesses the risk of recurrence, aids in treatment decision-making and follow-up planning in clinical settings, and demonstrated strong performance in the validation cohort.