Risk-stratification model to select conversion surgery for advanced gastric cancer patients

Objective: Conversion surgery is a surgery with a purpose of R0 resection in primary advanced gastric cancer(GC) that responded well to systemic chemotherapy. This study aimed to explore the efficacy of conversion surgery for advanced GC.Methods: A total of 618 advanced GC patients receiving systemic chemotherapy were stratified into low-,moderate-and high-risk groups based on a nomogram-predicted probability of overall survival. The survival of conversion surgery and chemotherapy alone groups was compared using the log-rank test and Cox regression analysis after propensity score matching(PSM).Results: A nomogram with good discrimination(concordance index: 0.65) and accurate calibration was constructed. After PSM, the median survival time(MST) of conversion surgery was 26.80 months, compared with16.60 months of chemotherapy alone(P<0.001). Conversion surgery was associated with a longer MST for patients in the low-risk group(30.40 months vs. 20.90 months, P=0.013), whereas it was not associated with prolonged survival in the moderate-and high-risk groups(P=0.221 and P=0.131, respectively).Conclusions: Conversion surgery was associated with longer survival, especially for low-risk population.

Photodynamic diagnostics of early gastric cancer:Complexity measures of gastric microcirculation and new model of metastatic adenocarcinoma of rat stomach

The detection of early gastric cancer that often develops asymptomatically is crucial for improving patient survival.The photodynamic diagnosis(PDD)of gastric cancer using 5-aminolevulinic acid/protoporphyrin IX(5-ALA/PpIX)has been reported in several studies.However,the selectivity of PDD of gastric tumor is poor with often false-positive results that require the development of new methods to improve PDD for early gastric cancer.Therefore,a measure of the complexity of gastric microcirculation(multi-scale entropy,MSE)and the detrendedfluctuation analysis(DFA)were applied as additional tools to detect early gastric cancer in rats.In this experimental study,we used our original model of metastatic adenocarcinoma in the stomach of a rat.To induce a gastric tumor,we used a long-term combination(for 9 months,which is 1/2 of the life of rats)of two natural factors,such as chronic stress(overpopulation being typical for modern cities)and the daily presence of nitrites in food and drinks,which are common ingredients added to processed meat andfish to help preserve food.Our results clearly show that both methods,namely,PDD using 5-ALA/PpIX and complexity/correlation analysis,can detect early gastric cancer,which was confirmed by histological analysis.Pre-cancerous areas in the stomach were detected as an intermediatefluorescent signal or MSE level between normal and malignant lesions of the stomach.However,in some cases,PDD with 5-ALA/PpIX produced a false-positivefluorescence of exogenousfluorophores due to its accumulation in benign and inflammatory areas of the mucosa.This fact indicates that the PDD itself is not sufficient for the correct diagnosis of gastric cancer,and the use of additional characteristics,e.g.,complexity measures or scaling exponents,can significantly improve the diagnostic accuracy of PDD of gastric cancer that should be confirmed in further clinical studies and applications.

SURVIVAL ANALYSIS OF GASTRIC CANCER PATIENTS BY COX REGRESSION MODEL

Mortality rate of gastric cancer is about 20.93/100000 which is the highest malignancy in China. The scientist of our country are at present interested in studying the postoperative survival model by multivariate analysis method just as stepwise regression model. The proportional hazard model initiated by Cox (1972) is more advanced than other regression method which is unneccessary to suppose the distribution of survival time and easy to analyse censoring data (the latter is difficult). This paper presented the first time application of Cox model in survival analysis of gastric cancer in China. The survival analysis system (SAS-Ⅰ) software complied by the author includes multivariate anlysis by Cox model, PV analysis and estimation of survival function which could provide useful information to surgeon for treatment of cancer patients.

Utilizing gastric cancer organoids to assess tumor biology and personalize medicine

While the incidence and mortality of gastric cancer (GC) have declined due to public health programs, it remains the third deadliest cancer worldwide. For patients with early disease, innovative endoscopic and complex surgical techniques have improved survival. However, for patients with advanced disease, there are limited treatment options and survival remains poor. Therefore, there is an urgent need for more effective therapies. Since novel therapies require extensive preclinical testing prior to human trials, it is important to identify methods to expedite this process. Traditional cancer models are restricted by the inability to accurately recapitulate the primary human tumor, exorbitant costs, and the requirement for extended periods of development time. An emerging in vitro model to study human disease is the patient-derived organoid, which is a three-dimensional system created from fresh surgical or biopsy tissues of a patient’s gastric tumor. Organoids are cultured in plastic wells and suspended in a gelatinous matrix, providing a substrate for extension and growth in all dimensions. They are rapid-growing and highly representative of the molecular landscape, histology, and morphology of the various subtypes of GC. Organoids uniquely model tumor initiation and growth, including steps taken by normal stomach cells to transform into invasive, intestinal-type tumor cells. Additionally, they provide ample material for biobanking and screening novel therapies. Lastly, organoids are a promising model for personalized therapy and warrant further investigation in drug sensitivity studies for GC patients.

E2F-1 overexpression inhibits human gastric cancer MGC-803 cell growth in vivo

AIM: To evaluate the influence of E2F-1 on the growth of human gastric cancer(GC) cells in vivo and the mechanism involved. METHODS: E2F-1 recombinant lentiviral vectors were injected into xenograft tumors of MGC-803 cells in nude mice, and then tumor growth was investigated. Overexpression of transcription factor E2F-1 was assessed by reverse transcription-polymerase chain reaction(RT-PCR) and Western blotting analysis. Apoptosis rates were determined using a terminal deoxynucleotidyl transferase-mediated d UTP-biotin nick end labeling(TUNEL) assay. Expression levels of certain cell cycle regulators and apoptosis-related proteins, such as Bax, survivin, Bcl-2, cyclin D1, S-phase kinaseassociated protein 2, and c-Myc were examined by Western blotting and RT-PCR. RESULTS: Xenograft tumors of MGC-803 cells in nude mice injected with E2F-1 recombinant lentiviral vectors stably overexpressed the E2F-1 gene as measured by semi-quantitative RT-PCR(relative m RNA expression: 0.10 ± 0.02 vs 0.05 ± 0.02 for control vector and 0.06 ± 0.03 for no infection; both P < 0.01) and Western blotting(relative protein expression: 1.90 ± 0.05 vs 1.10 ± 0.03 in control vector infected and 1.11 ± 0.02 for no infection; both P < 0.01). The growth-curve of tumor volumes revealed that infection with E2F-1 recombinant lentiviral vectors significantly inhibited the growth of human GC xenografts(2.81 ± 1.02 vs 6.18 ± 1.15 in control vector infected and 5.87 ± 1.23 with no infection; both P < 0.05) at 15 d after treatment. TUNEL analysis demonstrated that E2F-1 overexpression promoted tumor cell apoptosis(18.6% ± 2.3% vs 6.7% ± 1.2% in control vector infected 6.3% ± 1.2% for no infection; both P < 0.05). Furthermore, lentiviral vector-mediated E2F-1 overexpression increased theexpression of Bax and suppressed survivin, Bcl-2, cyclin D1, Skp2, and c-Myc expression in tumor tissue.CONCLUSION: E2F-1 inhibits growth of GC cells via regulating multiple signaling pathways, and may play an important role in targeted therapy for GC.

Reversal of multidrug resistance in gastric cancer cells by CDX2 downregulation

AIM: To explore the role of CDX2 in the multi-drug resistance (MDR) process of gastric cancer in vitro and in vivo . METHODS: A cisplatin-resistant gastric cancer cell line with stable downregulation of CDX2 was established. mRNA and protein expression levels of CDX2, survivin, cyclin D1, and c-Myc were detected by western blotting and semi-quantitative reverse-transcriptase polymerase chain reaction (RT-PCR). The influence of downregulation of CDX2 on MDR was assessed by measuring IC50 of SGC7901/DDP cells to cisplatin, doxorubicin, and 5-fluorouracil, rate of doxorubicin efflux, apoptosis, and cell cycle progression detected by flow cytometry. In addition, we determined the in vivo effects of CDX2 small interfering RNA (siRNA) on tumor size, and apoptotic cells in tumor tissues were detected by deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling and hematoxylin and eosin staining. RESULTS: CDX2 siRNA led to downregulation of endogenous CDX2 mRNA (0.31 ± 0.05 vs 1.10 ± 0.51, 0.31 ± 0.05 vs 1.05 ± 0.21, P = 0.003) and protein (0.12 ± 0.08 vs 0.51 ± 0.07, 0.12 ± 0.08 vs 0.55 ± 0.16, P = 2.57 × 10 -4) expression. It significantly promoted the sensitivity of SGC7901/DDP cells to cisplatin (0.12 ± 0.05 vs 0.33 ± 0.08, 0.12 ± 0.05 vs 0.39 ± 0.15, P = 0.001), doxorubicin (0.52 ± 0.13 vs 4.11 ± 1.25, 0.52 ± 0.13 vs 4.05 ± 1.44, P = 2.81 × 10-4), and 5-fluorouracil (0.82 ± 0.13 vs 2.81 ± 0.51, 0.82 ± 0.13 vs 3.28 ± 1.03, P = 1.71 × 10-4). Flow cytometry confirmed that the percentage of apoptotic cells increased after CDX2 downregulation (32.15% ± 2.15% vs 17.63% ± 3.16%, 32.15% ± 2.15% vs 19.3% ± 2.25%, P = 1.73 × 10-6). This notion was further supported by the observation that downregulation of CDX2 blocked entry into the S-phase of the cell cycle (31.53% ± 3.78% vs 65.05% ± 7.25%, 31.53% ± 3.78% vs 62.27% ± 5.02%, P = 7.55 × 10-7). Furthermore, downregulation of CDX2 significantly increased intracellular accumulation of doxorubicin (0.21 ± 0.06 vs 0.41 ± 0.11, 0.21 ± 0.06 vs 0.40 ± 0.08, P = 0.003). In molecular studies, semiquantitative RT-PCR and western blotting revealed that CDX2 downregulation could inhibit expression of c-Myc, survivin and cyclin D1. CONCLUSION: CDX2 may be involved in regulating multiple signaling pathways in reversing MDR, suggesting that CDX2 may represent a novel target for gastric cancer therapy.

Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting longterm survival of patients with gastric cancer

BACKGROUND Because of the powerful abilities of self-learning and handling complex biological information,artificial neural network(ANN)models have been widely applied to disease diagnosis,imaging analysis,and prognosis prediction.However,there has been no trained preoperative ANN(preope-ANN)model to preoperatively predict the prognosis of patients with gastric cancer(GC).AIM To establish a neural network model that can predict long-term survival of GC patients before surgery to evaluate the tumor condition before the operation.METHODS The clinicopathological data of 1608 GC patients treated from January 2011 to April 2015 at the Department of Gastric Surgery,Fujian Medical University Union Hospital were analyzed retrospectively.The patients were randomly divided into a training set(70%)for establishing a preope-ANN model and a testing set(30%).The prognostic evaluation ability of the preope-ANN model was compared with that of the American Joint Commission on Cancer(8th edition)clinical TNM(cTNM)and pathological TNM(pTNM)staging through the receiver operating characteristic curve,Akaike information criterion index,Harrell's C index,and likelihood ratio chi-square.RESULTS We used the variables that were statistically significant factors for the 3-year overall survival as input-layer variables to develop a preope-ANN in the training set.The survival curves within each score of the preope-ANN had good discrimination(P<0.05).Comparing the preope-ANN model,cTNM,and pTNM in both the training and testing sets,the preope-ANN model was superior to cTNM in predictive discrimination(C index),predictive homogeneity(likelihood ratio chi-square),and prediction accuracy(area under the curve).The prediction efficiency of the preope-ANN model is similar to that of pTNM.CONCLUSION The preope-ANN model can accurately predict the long-term survival of GC patients,and its predictive efficiency is not inferior to that of pTNM stage.

Intravoxel incoherent motion diffusion-weighted imaging for monitoring chemotherapeutic efficacy in gastric cancer

AIM: To assess intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for monitoring early efficacy of chemotherapy in a human gastric cancer mouse model.METHODS: IVIM-DWI was performed with 12 b-values (0-800 s/mm2) in 25 human gastric cancer-bearing nude mice at baseline (day 0), and then they were randomly divided into control and 1-, 3-, 5- and 7-d treatment groups (n = 5 per group). The control group underwent longitudinal MRI scans at days 1, 3, 5 and 7, and the treatment groups underwent subsequent MRI scans after a specified 5-fluorouracil/calcium folinate treatment. Together with tumor volumes (TV), the apparent diffusion coefficient (ADC) and IVIM parameters [true water molecular diffusion coefficient (D), perfusion fraction (f) and pseudo-related diffusion coefficient (D*)] were measured. The differences in those parameters from baseline to each measurement (ΔTV%, ΔADC%, ΔD%, Δf% and ΔD*%) were calculated. After image acquisition, tumor necrosis, microvessel density (MVD) and cellular apoptosis were evaluated by hematoxylin-eosin (HE), CD31 and terminal-deoxynucleotidyl transferase mediated nick end labeling (TUNEL) staining respectively, to confirm the imaging findings. Mann-Whitney test and Spearman’s correlation coefficient analysis were performed.RESULTS: The observed relative volume increase (ΔTV%) in the treatment group were significantly smaller than those in the control group at day 5 (ΔTVtreatment% = 19.63% ± 3.01% and ΔTVcontrol% = 83.60% ± 14.87%, P = 0.008) and day 7 (ΔTVtreatment% = 29.07% ± 10.01% and ΔTVcontrol% = 177.06% ± 63.00%, P = 0.008). The difference in ΔTV% between the treatment and the control groups was not significant at days 1 and 3 after a short duration of treatment. Increases in ADC in the treatment group (ΔADC%treatment, median, 30.10% ± 18.32%, 36.11% ± 21.82%, 45.22% ± 24.36%) were significantly higher compared with the control group (ΔADC%control, median, 4.98% ± 3.39%, 6.26% ± 3.08%, 9.24% ± 6.33%) at days 3, 5 and 7 (P = 0.008, P = 0.016, P = 0.008, respectively). Increases in D in the treatment group (ΔD%treatment, median 17.12% ± 8.20%, 24.16% ± 16.87%, 38.54% ± 19.36%) were higher than those in the control group (ΔD%control, median -0.13% ± 4.23%, 5.89% ± 4.56%, 5.54% ± 4.44%) at days 1, 3, and 5 (P = 0.032, P = 0.008, P = 0.016, respectively). Relative changes in f were significantly lower in the treatment group compared with the control group at days 1, 3, 5 and 7 follow-up (median, -34.13% ± 16.61% vs 1.68% ± 3.40%, P = 0.016; -50.64% ± 6.82% vs 3.01% ± 6.50%, P = 0.008; -49.93% ± 6.05% vs 0.97% ± 4.38%, P = 0.008, and -46.22% ± 7.75% vs 8.14% ± 6.75%, P = 0.008, respectively). D* in the treatment group decreased significantly compared to those in the control group at all time points (median, -32.10% ± 12.22% vs 1.85% ± 5.54%, P = 0.008; -44.14% ± 14.83% vs 2.29% ± 10.38%, P = 0.008; -59.06% ± 19.10% vs 3.86% ± 5.10%, P = 0.008 and -47.20% ± 20.48% vs 7.13% ± 9.88%, P = 0.016, respectively). Furthermore, histopathologic findings showed positive correlations with ADC and D and tumor necrosis (rs = 0.720, P < 0.001; rs = 0.522, P = 0.007, respectively). The cellular apoptosis of the tumor also showed positive correlations with ADC and D (rs = 0.626, P = 0.001; rs = 0.542, P = 0.005, respectively). Perfusion-related parameters (f and D*) were positively correlated to MVD (rs = 0.618, P = 0.001; rs = 0.538, P = 0.006, respectively), and negatively correlated to cellular apoptosis of the tumor (rs = -0.550, P = 0.004; rs = -0.692, P < 0.001, respectively).CONCLUSION: IVIM-DWI is potentially useful for predicting the early efficacy of chemotherapy in a human gastric cancer mouse model.

胃癌模型大鼠胃黏膜组织Cyclin D1、c-Myc、CKIT的表达意义及其与胃癌病变程度的相关性

目的探讨胃癌模型大鼠胃黏膜组织细胞周期蛋白D1(cyclinD1)、c-Myc、CKIT的表达意义及其与胃癌病变程度的相关性。方法选择48只健康成年雌性大鼠,按照随机数字表法将其分为对照组、研究1组、研究2组、研究3组,每组各12只。研究1组、研究2组、研究3组均制备成胃癌模型。对照组给予等量0.9%氯化钠溶液,第24周处死取材;研究1组、研究2组、研究3组制备成胃癌大鼠后分别于第8、16、24周取材。分析各组大鼠一般情况及胃黏膜组织病理切片,采用蛋白质印迹法检测胃黏膜组织Cyclin D1、c-Myc、CKIT蛋白的表达,采用逆转录聚合酶链式反应(RT-PCR)法测定胃黏膜组织Cyclin D1、c-Myc、CKIT mRNA的表达,采用Spearman分析法测定胃黏膜组织Cyclin D1、c-Myc、CKIT表达与胃癌病变程度相关性。结果对照组大鼠胃黏膜完整正常,外膜层、肌层、黏膜下层、黏膜层等结构清晰,且无炎症细胞浸润;研究1组大鼠胃黏膜组织与对照组大鼠接近,不存在炎症细胞,且黏膜腺体结构基本正常;研究2组大鼠胃黏膜组织存在破损,细胞核变大,基底部部分腺体细胞形态异常,存在轻度异型性,为早期胃癌;研究3组大鼠胃黏膜组织增加破损,核质比变大,细胞形态不规则,部分腺体存在扩张,黏膜下层及肌层存在炎症细胞浸润,为胃癌进展期。研究1组、研究2组、研究3组胃黏膜组织Cyclin D1、c-Myc、CKIT蛋白均呈显著高于对照组,差异均有统计学意义(P<0.05),胃黏膜组织Cyclin D1、c-Myc、CKIT蛋白在研究1组、研究2组、研究3组中逐渐升高趋势。研究1组、研究2组、研究3组胃黏膜组织Cyclin D1、c-Myc、CKIT mRNA均呈显著高于对照组,差异均有统计学意义(P<0.05),胃黏膜组织Cyclin D1、c-Myc、CKIT mRNA在研究1组、研究2组、研究3组中逐渐升高趋势。采用Spearman相关性结果分析显示,胃黏膜组织Cyclin D1、c-Myc、CKIT表达与胃癌病变程度呈正相关(r=0.382、0.781、0.993,均P<0.001)。结论胃癌模型大鼠胃黏膜组织Cyclin D1、c-Myc、CKIT呈高表达,其与胃癌病变程度密切相关。

营养支持链式管理在胃癌围术期患者中的应用

目的探讨围术期营养支持链式管理对胃癌患者术后营养状况及营养知信行水平的影响。方法将胃癌患者162例按住院时间分为对照组82例(2021年6—12月入院)、干预组80例(2022年1—6月入院)。对照组实施常规围术期营养管理,干预组实施营养支持链式管理,术后1个月比较2组患者的营养状况及营养知识知信行水平。结果干预组术后1个月总蛋白<60 g/L占比为5.00%,低于对照组的14.63%;干预组术后1个月白蛋白<35 g/L占比为3.75%,低于对照组的13.41%;干预组术后1个月体质量指数(BMI)正常范围者占比83.75%,高于对照组的59.75%,差异有统计学意义(P<0.05)。干预组术后1个月营养知识、支持态度、支持行为维度得分以及营养知信行总分均高于对照组,差异有统计学意义(P<0.05)。结论围术期实施营养支持链式管理能有效增加患者营养摄取量,改善胃癌患者术后营养状况,提升患者营养知信行水平和生活质量。

胃癌病人术后发生静脉血栓栓塞症危险因素分析以及预测模型的建立

目的 探讨影响胃癌病人术后发生静脉血栓栓塞症(VTE)的相关危险因素,并建立预测模型,验证该模型的预测价值。方法 纳入2019年1月~2021年6月我院接受根治性手术的胃癌病人160例作为建模组,167例作为验证组。收集病人临床病理资料,根据建模组胃癌病人术后6个月内VTE的发生情况将其分为VTE组和N-VTE组,对两组胃癌病人的临床病理因素进行单因素分析,再将单因素分析中有统计学意义的指标代入多因素Logistic回归模型进行多因素分析,得到影响胃癌病人术后发生VTE的独立危险因素,基于多因素分析结果得到的独立危险因素结合β值,根据列线图原理对独立危险因素进行赋分,构建列线图模型,并应用R软件绘制列线图,以Bootstrap法和校准曲线进行列线图模型的内外部验证,计算区分度评价指标C指数,并通过拟合优度(H-L)检验评价预测模型的校准能力。结果 建模组160例胃癌病人均接受胃癌根治手术,按术后6个月内是否发生VTE分为VTE组23例和N-VTE组137例,多因素分析结果显示,年龄≥60岁、病灶直径≥5 cm、糖尿病、TNM/T分期为T3~T4期、淋巴结转移5个指标为影响胃癌病人术后发生VTE的独立危险因素(P<0.05),构建列线图:P=1/(1+e^(-X)),X=1.885×年龄(≥60岁=1,<60岁=0)+2.051×糖尿病(是=1,否=0)+2.646×病灶直径(≥5 cm=1,<5 cm=0)+2.952×TNM/T分期(1~2期=0,3~4期=1)+0.694×淋巴结转移(是=1,否=0)-0.436,列线图模型的C指数分别为0.847(95%CI:0.784~0.932)和0.832(95%CI:0.772~0.910),H-L检验提示胃癌病人术后发生VTE的预测值与实际值符合度良好(P>0.05)。结论 本研究建立了关于预测胃癌病人术后发生VTE风险的列线图模型,该模型能够较为准确地预测胃癌病人术后的VTE发生风险。

胃癌术后辅助化疗期间恶心呕吐风险预测模型的建立及验证

目的探讨胃癌病人手术后化疗期间恶心呕吐的风险因素,并构建相应的风险预测模型。方法2020年2月~2021年2月收治的胃癌病人作为建模集组,用于探讨胃癌病人手术后化疗期间恶心呕吐的风险因素,并构建相应的风险预测模型,将2021年3月~2022年2月(第1年)、2022年3月~2023年2月(第2年)、2023年3月~2024年2月(第3年)作为验证集组用于验证建模集组构建的风险预测模型。统计建模集组病人化疗期间呕吐发生情况。采用单因素和多因素Logistic回归分析胃癌病人手术后化疗期间恶心呕吐风险因素,并构建相应的风险预测模型。采用受试者工作特征曲线(receiver operating characteristic curve,ROC)以2021年3月~2024年2月3年的验证集验证列线图预测模型的准确性。结果建模集组共纳入112例,其中75例未发生化疗相关性恶心呕吐,纳入对照组,37例病人发生了化疗相关性恶心呕吐,纳入观察组。单因素分析显示,年龄、性别、饮酒史、晕动病史、化疗次数、既往化疗相关性恶心呕吐史、妊吐史、匹茨堡睡眠质量指数(PSQI)、心理预期发生化疗后恶心呕吐等与病人发生化疗相关性恶心呕吐有关(P<0.05)。将单因素分析得到具有统计学意义的因素进行Logistic回归分析,结果显示,年龄、性别、晕动病史、化疗次数、妊吐史、PSQI、心理预期发生化疗后恶心呕吐是胃癌病人术后化疗期间恶心呕吐的危险因素(P<0.05)。根据Logistic回归得到具有统计学意义的因素构建风险预测模型。使用Bootstrap法对模型进行内部验证,第1年验证集组ROC曲线下面积(AUC)为0.71(95%CI:0.71~1.00),第2年验证集组0.69(95%CI:0.58~0.96),第3年验证集组0.66(95%CI:0.54~0.95)。结论年龄、性别、晕动病史、化疗次数、妊吐史、PSQI、心理预期发生化疗后恶心呕吐是胃癌病人术后化疗期间恶心呕吐的危险因素,上述因素构建的胃癌病人化疗期间恶心呕吐的风险预测模型具有较好的预测效能。

早期胃癌患者内镜黏膜下剥离术后疲劳预测模型的构建

目的探究早期胃癌患者胃内镜黏膜下剥离术后疲劳(POF)的危险因素,建立并验证早期胃癌POF风险预测模型。方法采用便利抽样法选取2020年10月-2022年12月于我院治疗的232例早期胃癌患者为研究对象,使用一般资料表、中文版多维度疲乏症状量表、阿姆斯特丹术前焦虑与信息需要量表、匹兹堡睡眠质量量表、艾森克人格问卷简式量表收集相关数据,通过单因素分析和二分类logistic回归分析发生术后疲劳的危险因素,并建立列线图预测模型,选取2023年1-6月在我院治疗的72例患者对模型进行验证。结果经检验,年龄、性别、睡眠障碍、病灶切除面积、气质类型、术后疼痛和胃肠功能紊乱是早期胃癌患者POF发生的独立危险因素,并以此建立早期胃癌患者POF的列线图模型,经验证该模型具有较好的准确度(H-L检验:χ^(2)=2.822,P=0.945)和区分度(AUC=0.0.909,95%CI:0.937~0.980,P<0.001),最大约登指数为0.648,灵敏度为0.832,特异度为0.813,截断值0.319,校准曲线为斜率近似于1的直线。结论该模型预测效果良好,可为医护人员对早期胃癌POF高风险人群筛查提供参考,及时采取预防性措施。

胃癌前病变病证结合动物模型研究进展

中医药在胃癌前病变(precancerous lesions of gastric cancer,PLGC)诊疗中发挥着重要作用,病证结合动物模型是进行PLGC相关实验研究的前提。文章从模型动物选择、胃癌前病变疾病模型和病证结合模型三方面,对近年来PLGC病证结合模型的制备方法进行了归纳分析,介绍了脾胃虚弱、胃阴不足、肝胃气滞、脾胃湿热和胃络瘀血5个常见PLGC病证结合模型的造模方法,并对当前模型制备中存在的问题提出了思考与展望。

胃癌根治术后奥沙利铂联合卡培他滨辅助化疗患者预后的影响因素分析及列线图模型构建

目的分析胃癌根治术后奥沙利铂联合卡培他滨辅助化疗患者预后的影响因素,并构建预后列线图模型。方法232例胃癌患者均行胃癌根治切除术及D2淋巴结清扫术,术后采用奥沙利铂联合卡培他滨化疗。对所有患者随访3年,根据随访期间的生存情况,将患者分为生存组和死亡组,比较两组患者的临床特征。采用Cox风险比例回归模型分析胃癌患者预后的影响因素并构建列线图预测模型,采用校正曲线、决策曲线验证列线图模型的预测效能及可靠性。结果死亡组(n=85)肿瘤大小≥5 cm、胃切除方式为全胃切除术、TNM分期为Ⅲ期、中性粒细胞与淋巴细胞比值(NLR)≥4、癌胚抗原(CEA)≥6 ng/ml、预后营养指数(PNI)﹤45患者比例均明显高于生存组(n=147),差异均有统计学意义(P﹤0.01)。Cox回归分析结果显示,肿瘤大小≥5 cm、胃切除方式为全胃切除术、TNM分期为Ⅲ期、NLR≥4、CEA≥6 ng/ml、PNI﹤45均是胃癌患者预后不良的危险因素(P﹤0.05)。该列线图模型预测胃癌患者预后的C指数为0.933(95%CI:0.901~0.964),该列线图模型的校准曲线在对患者预后风险的观测值和预测值之间表现出高度一致性。该列线图模型的阈值﹥0.04,其临床净收益显著高于肿瘤大小、胃切除方式、TNM分期、NLR、CEA、PNI单一预测因子。结论肿瘤大小≥5 cm、胃切除方式为全胃切除术、TNM分期为Ⅲ期、NLR≥4、CEA≥6 ng/ml、PNI﹤45均是胃癌根治术后奥沙利铂联合卡培他滨辅助化疗患者预后不良的危险因素,基于此构建的列线图预测模型预测价值较高,可为临床改善患者预后提供依据。

乳酸脱氢酶在胃癌诊治中的研究进展

我国是世界第一胃癌大国,胃癌发病率及死亡率在我国的各种恶性肿瘤中均居第三。研究发现肿瘤细胞有自身的能量代谢特点,即使在氧气充足的情况下,肿瘤细胞也更倾向于利用糖酵解产生能量,又称为“有氧糖酵解”。有氧糖酵解可导致乳酸增加,促进肿瘤细胞的增殖及侵袭,而驱动这种现象的关键酶是乳酸脱氢酶(Lactate dehydrogenase,LDH)。在胃癌患者中LDH水平显著升高,并且LDH可在许多方面促进胃癌的发生发展。本文将论述LDH在肿瘤糖酵解中的作用、与胃癌的相关性及临床应用价值,并讨论LDH在胃癌靶向治疗中的研究进展。

基于术前与术后中性粒细胞-淋巴细胞比值的组合预测胃癌患者的预后

目的:评估术前与术后中性粒细胞-淋巴细胞比值(neutrophil-lymphocyte ratio,NLR)的组合对胃癌患者的预后预测价值。方法:回顾性收集2015年1月1日至2018年4月1日贵州医科大学附属医院胃肠外科进行根治性手术的初诊胃癌患者133例。收集患者术前NLR和术后NLR,使用受试者工作特征曲线(receiver operating characteristic curve,ROC)来分析确定炎症指标的最佳截断值,根据最佳截断值将所有患者分为术前NLR和术后NLR均低组、术前NLR低或术后NLR低组以及术前NLR和术后NLR均高组,并使用Kaplan-Meier法分析患者总生存期(overall survival,OS)。采用Cox比例风险回归模型分析预后的独立危险因素。列线图模型由R Studio构建,并评估预测模型的效能。结果:术前NLR联合术后NLR对胃癌患者预后的预测效能(AUC=0.7068)优于单独术前NLR(AUC=0.6643)或术后NLR(AUC=0.5933)。术前NLR和术后NLR均低组的中位生存时间为61个月,5年生存率为62.07%;术前NLR低或术后NLR低组的中位生存时间为54个月,5年生存率为48.15%;术前NLR和术后NLR均高组的中位生存时间为12个月,5年生存率为22%。术前NLR和术后NLR均高组预后是最差的(P<0.001)。Cox回归分析显示手术方式(HR=0.465,P=0.001)、TNM分期(HR=3.387,P=0.006)及术前NLR联合术后NLR(HR=2.091,P=0.002)是胃癌患者预后的独立危险因素。结合独立危险因素构建列线图预测3年(AUC=0.8593)和5年(AUC=0.8852)预后,其预测效能优于单独术前NLR(AUC=0.6643)和术后NLR(AUC=0.5933)。校准曲线提示该模型具有较高的一致性,决策曲线显示该模型具有良好的临床获益。结论:术前NLR联合术后NLR是胃癌患者的重要预后因素。术前NLR和术后NLR均高组的患者预后不良。基于这两项炎症指标和临床病理特征的列线图模型可被用于评估胃癌患者预后,其预测能力优于单独术前NLR和术后NLR。

构建胃癌中CD8^(+)T细胞相关预后模型并筛选治疗药物

目的:胃癌是高度异质性的恶性肿瘤,其病死率高,患者就诊时多已处于晚期且预后差。CD8^(+)T细胞可识别和消灭肿瘤细胞,对癌症的进展有重要影响。本研究旨在构建CD8^(+)T细胞浸润相关预后模型,为胃癌患者预后评估提供新的生物标志物及其药物治疗提供客观依据。方法:从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中下载371例胃癌样本的数据为训练集。从基因表达综合(Gene Expression Omnibus,GEO)数据库中下载433例胃癌样本的数据为测试集。计算训练集胃癌样本中CD8^(+)T细胞相对含量,将样本分为CD8^(+)T细胞高含量组和CD8^(+)T细胞低含量组,采用Kaplan-Meier法分析和比较2组之间的生存关系;采用加权基因共表达网络(weighted gene co-expression network analysis,WGCNA)分析训练集数据,筛选出与CD8^(+)T细胞最具相关性的基因模块;对该模块基因进行单因素Cox回归分析、最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)回归分析及多因素Cox回归分析筛选出与预后相关的基因,构建预后风险评分模型。应用模型计算训练集和测试集患者的风险评分并分别将患者分为高风险组和低风险组,并对模型进行内部及外部测试。应用肿瘤免疫单细胞枢纽2(tumor immune single-cell hub 2,TISCH2)数据库及人类蛋白质图谱(The Human Protein Atlas,HPA)数据库对模型基因进行验证。结合模型进行临床病理特征分析、功能富集分析、免疫相关性分析及化学治疗药物敏感性分析。结果:生存分析显示CD8^(+)T细胞低含量组的预后更差。WGCNA分析筛选出与CD8^(+)T细胞最具相关性的基因模块为Ebisque4。单因素Cox回归分析、LASSO逻辑回归分析及多因素Cox回归分析最终筛选出9个独立预后基因并构建预后风险评分模型。模型内部及外部测试结果均表明该模型具有较强的预测能力。TISCH2数据库验证表明模型基因在肿瘤微环境中具有不同的表达模式;HPA数据库验证表明模型基因的表达情况与预后模型较一致。临床病理特征分析表明风险评分与组织浸润深度相关;功能富集分析表明高风险组富集于分子间相互作用的通路,而低风险组则富集于代谢相关通路;免疫相关性分析表明高、低风险组之间的多个免疫细胞、免疫功能和免疫检查点均有差异;化学治疗药物敏感性分析表明高风险组对帕唑帕尼的敏感性更高,低风险组对西妥昔单抗的敏感性更高。结论:肿瘤微环境中的CD8^(+)T细胞浸润对胃癌患者的预后有显著的影响。基于CD8^(+)T细胞相关基因构建的预后模型具有普适性和临床适用性,对胃癌患者的药物治疗有重要的提示作用。

基于SEER数据库的胃癌预后列线图模型的构建与验证

目的探讨胃癌患者的预后风险因素,构建一个列线图预后预测模型来预测胃癌患者的总生存期(overall survival,OS)。方法基于SEER数据库,对2010年至2015年诊断为胃癌患者数据进行回顾性分析。对纳入变量进行单因素和多因素Cox回归分析,筛选出影响胃癌患者生存的独立危险因素,利用Kaplan-Meier法绘制生存曲线。根据临床经验及统计学结果纳入危险因素,用于构建胃癌患者的预后模型并绘制列线图。采用C-index、ROC曲线和校准曲线评价临床预测模型。结果本研究共纳入3052例胃癌患者。构建了胃癌患者的1年、3年和5年预后预测模型。使用C-index评估列线图模型的准确性,训练集中C-index的结果为0.780(95%CI:0.769~0.793),验证集中C-index的结果为0.763(95%CI:0.743~0.783)。通过ROC曲线评估列线图模型。训练集ROC曲线的1年、3年和5年生存率AUC分别为0.844、0.852和0.858。验证集中ROC曲线的1年、3年和5年生存率AUC分别为0.824、0.829和0.842。训练集及验证集中的校准图也表明该模型具有较高的精度。结论构建的列线图预测模型可以有效预测胃癌患者的OS,有助于指导临床医师个性化预后评估和临床决策。

基于生物信息学分析泛凋亡基因对胃癌预后及肿瘤免疫微环境的影响

目的探讨泛凋亡相关基因对胃癌患者预后及免疫微环境的预测价值。方法基于TCGA、GEO数据库中胃癌患者PANoptosis差异基因表达谱,对胃癌患者进行聚类分析并构建预测模型,分析不同胃癌患者PANoptosis亚型及高、低风险组间肿瘤免疫微环境差异。结果胃癌患者可分为两个PANoptosis分子亚型,亚型间患者的临床特征、预后、信号通路和肿瘤微环境有显著差异。根据PANoptosis相关基因在胃癌组织中的表达水平,经Lasso回归分析、多因素Cox回归分析,鉴定出6个关键基因(IRF2、AKT3、UNC5B、CYCS、CASP5、TICAM1)用于构建风险评分体系。多组学分析发现,风险评分与微卫星不稳定性、肿瘤突变负荷和肿瘤干细胞指数呈负相关关系。基于PANoptosis风险评分和临床病理因素构建诺莫图,预测胃癌患者1、3、5年生存率的受试者操作特征曲线下面积值分别为0.702、0.736、0.744。实时定量聚合酶链式反应实验证实风险基因CYCS、CASP5、TICAM1在胃癌细胞系中高表达(P<0.01)。结论基于胃癌PANoptosis相关基因构建的预后模型有望成为独立预测胃癌患者预后的指标。