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Introduction: The combination of neoadjuvant immunotherapy and chemotherapy (NICT) has become a common treatment regimen for locally advanced gastric cancer (LAGC). However, the safety and efficacy of radical gastrectomy following NICT (NICT-G) remain controversial. This study aimed to analyze the risk factors influencing postoperative complications (POCs) after NICT-G. Additionally, it aimed to construct a nomogram to provide a clinical reference for predicting POCs. Methods: This study included 177 patients who received NICT-G at the Chinese PLA General Hospital First Medical Center from January 2020 to January 2024. Univariable and multivariable logistic regression models were used to evaluate the risk factors influencing POCs, and a nomogram model was constructed. To evaluate the discrimination and accuracy of the nomogram model, the area under the receiver operating characteristic curve (AUC) and the calibration curve were measured. Results: In 177 patients who received NICT-G, the pathological complete response and major pathological response rates were 15.8% and 45.2%, respectively, whereas the rates of the overall and severe treatment-related adverse events were 71.8% and 15.8%, respectively. In addition, 43 (24.3%) patients developed overall POCs (Clavien-Dindo classification ≥ II). Univariable and multivariable logistic analyses showed that age ≥70 years, greater estimated blood loss, platelet/lymphocyte ratio (PLR) ≤196, neutrophil/lymphocyte ratio (NLR) >1.33, non-R0 resection, and body mass index (BMI) < 18.5 kg/m2 were independent risk factors for overall POCs (p < 0.05). The nomogram model developed using the abovementioned variables showed that the AUC (95% confidence interval [CI]) was 0.808 (95% CI): 0.731-0.885 in predicting the POC risk. The calibration curves showed that the prediction curve of the nomogram was a good fit for the actual POCs (Hosmer-Lemeshow test: χ2 = 5.76, P = 0.451). Conclusion: The independent risk factors for overall POCs in the NICT-G were age ≥ 70 years, greater estimated blood loss, PLR ≤ 196, NLR > 1.33, non-R0 resection, and BMI < 18.5 kg/m2. The nomogram model developed based on the abovementioned indicators showed better accuracy in predicting the POC risk.
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BACKGROUND: The metabolism of abnormal bile acids (BAs) is implicated in the initiation and development of gastrointestinal (GI) cancer. However, there was a lack of research on the molecular mechanisms of BAs metabolism in GI. METHODS: Genes involved in BAs metabolism were excavated from public databases of The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, and Molecular Signatures Database (MSigDB). ConsensusClusterPlus was used to classify molecular subtypes for GI. To develop a RiskScore model for predicting GI prognosis, univariate Cox analysis was performed on the genes in protein-protein interaction (PPI) network, followed by using Lasso regression and stepwise regression to refine the model and to determine the key prognostic genes. Tumor immune microenvironment in GI patients from different risk groups was assessed using the ESTIMATE algorithm and enrichment analysis. Reverse transcription-quantitative real-time PCR (RT-qPCR), Transwell assay, and wound healing assay were carried out to validate the expression and functions of the model genes. RESULTS: This study defined three molecular subtypes (C1, C2, and C3). Specifically, C1 had the best prognosis, while C3 had the worst prognosis with high immune checkpoint gene expression levels and TIDE scores. We selected nine key genes (AXIN2, ATOH1, CHST13, PNMA2, GYG2, MAGEA3, SNCG, HEYL, and RASSF10) that significantly affected the prognosis of GI and used them to develop a RiskScore model accordingly. Combining the verification results from a nomogram, the prediction of the model was proven to be accurate. The high RiskScore group was significantly enriched in tumor and immune-related pathways. Compared with normal gastric mucosal epithelial cells, the mRNA levels of the nine genes were differential in the gastric cancer cells. Inhibition of PNMA2 suppressed migration and invasion of the cancer cells. CONCLUSION: We distinguished three GI molecular subtypes with different prognosis based on the genes related to BAs metabolism and developed a RiskScore model, contributing to the diagnosis and treatment of patients with GI.
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Objective: Large-scale studies on the characteristics and management of abdominal trauma in megacities in China are lacking. The aim of this study was to analyze and present the clinical patterns and treatment status of abdominal trauma in regional medical centers. Methods: Cases of abdominal trauma treated at seven medical centers in Beijing from 2010 to 2021 were collected. Clinical information about age, sex, injury cause, geographic distribution, abbreviated injury scale/injury severity score (AIS/ISS) value, injury-hospital time, preoperative time, surgically identified organ injuries, type of surgery, causes of reoperation and 90-day mortality was included in this study. Clinical characteristics, treatment methods, and short-term prognoses (90-days survival) were compared between blunt abdominal trauma (BAT) and penetrating abdominal trauma (PAT) cases. Non-normally distributed data are described as medians (IQR), and the MannâWhitney U test was performed; qualitative data were analyzed using the X2 test. Univariate and multivariate survival analyses were performed by the Cox proportional hazards model. Results: A total of 553 patients (86.98% male) with a median age of 36.50 (27.00-48.00) years were included. The BAT group had a significantly higher proportion of serious injury (P=0.001), lower initial hemoglobin level (P=0.001), and a lower laparoscopy surgery rate (P=0.044) compared to the PAT group. Additionally, more BAT cases were from the area around Beijing (P=0.008) and a longer injury-regional hospital time (10.47 (5.18-22.51) hours vs. 7.00 (3.80-15.38) hours, P=0.001). In the hollow viscus injury subgroup, the BAT group had a significantly longer injury-regional hospital time and preoperative time compared to the PAT group (injury-regional hospital time: 10.23 (6.00-21.59) hours vs. 7.07 (3.99-13.85) hours, P=0.002; preoperative time: 3.02 (2.01-5.58) hours vs. 2.81 (1.85-3.63) hours, P=0.047). The overall 90-day mortality was 11.9%, and longer injury-regional hospital time (HR: 1.01, 95% CI: 1.00-1.02, P=0.008), receipt of ICU treatment (HR: 4.69, 95% CI: 2.54-8.65, P=0.001), and severe ISSs (ISS > 25 vs. ISS < 16, HR: 2.78, 95% CI: 1.38-5.601, P=0.004) had a worse impact on survival. Conclusion: More patients with BAT were transferred to higher-level hospital, leading to significantly longer prehospital and preoperation time. In the subgroup of hemodynamically stable individuals, more patients with BAT experienced hollow viscus injuries. For those patients, aggressive diagnostic laparoscopic exploration may be beneficial. Patients with longer injury-regional hospital intervals, the need for ICU care, and higher injury severity scores (ISSs) suffered from worse prognoses.
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Background: Homologous recombination is an important DNA repair mechanism, which deficiency is a common feature of many cancers. Defining homologous recombination deficiency (HRD) status can provide information for treatment decisions of cancer patients. HRD score is a widely accepted method to evaluate HRD status. This study aimed to explored HRD in gastric cancer (GC) patients' clinical outcomes with genes related to HRD score and HRD components score [HRD-loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (NtAI)]. Methods: Based on LOH, NtAI scores, LST, and integrated HRD scores-related genes, a risk model for stratifying 346 TCGA GC cases were developed by Cox regression analysis and LASSO Cox regression. The risk scores of 33 cancers in TCGA were calculated to analyze the relationship between risk scores of each cancer and HRD scores and 3 HRD component scores. Relationship between the risk model and patient survival, BRCA1, BRCA2 mutation, response to Cisplatin and Talazoparib treatment was analyzed by generating Kaplan-Meier curve, mutations waterfall map and conducting Pearson correlation analysis. Results: An gene signature was constructed based on 11 HRD scores-related gene (BEX2, C1QL2, DKK1, DRC1, GLUD2, HCAR1, IGFBP1, NXPH1, PROC, SERPINA5, and SLCA1A2). Risk groups were stratified by risk score. Prognosis of the high-risk score group was worse than the low-risk ones. Risk score was associated with BRCA2 mutation, and patients grouped according to BRCA2 mutation status had distinguishable risk score, NtAI score, HRD-LOH, LST, and HRD scores. The low-score group showed higher sensitivity to Cisplatin and Talazoparib. The risk score of adrenocortical carcinoma (ACC), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), sarcoma (SARC), prostate adenocarcinoma (PRAD), breast invasive carcinoma (BRCA) was significantly positively correlated with HRD score. Conclusion: We developed an 11 HRD scores-related genes risk model and revealed the potential association between HRD status and GC prognosis, gene mutations, patients' sensitivity to therapeutic drugs.
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Breast cancer is one of the most common life-threatening cancers, mainly because of its aggressiveness and metastasis. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) participate in the development and progression of breast cancer. Nevertheless, the function and expression level of lncRNAs in breast cancer are still not fully understood. Here, we demonstrated that lncRNA PCDHB17P was up-expressed in human breast cancer tissues and cell lines. Knockdown of PCDHB17P remarkably suppressed migration and invasion, as well as tube formation ability of breast cancer cells. MiR-145-3p was significantly decreased in breast cancer samples, which was negatively correlated to the expression of PCDHB17P. In addition, we identified that MELK was a direct target gene of miR-145-3p, which was higher expressed in breast cancer tissues than that in adjacent normal tissues. Mechanistic investigation indicated that PCDHB17P acted as a cancer-promoting competing endogenous RNA (ceRNA) by binding miR-145-3p and upregulating MELK. Interestingly, MELK could in turn increase the promoter activity and expression of PCDHB17P via NF-κB, thus forming a positive feedback loop that drives the metastasis and angiogenesis of breast cancer. Overall, the results demonstrated that the constitutive activation of PCDHB17P/miR-145-3p/MELK/NF-κB feedback loop promotes the metastasis and angiogenesis of breast cancer, suggesting that this lncRNA might be a promising prognostic biomarker and therapeutic target for breast cancer.