Risk Assessment and Preventive Treatment for Peritoneal Recurrence Following Radical Resection for Gastric Cancer.
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ABSTRACT:
SUBMITTER: Xiang L
PROVIDER: S-EPMC8763009 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe incidence of stage pN3b gastric cancer (GC) is low, and the clinical prognosis is poor, with a high rate of postoperative recurrence. Machine learning (ML) methods can predict the recurrence of GC after surgery. However, the prognostic significance for pN3b remains unclear. Therefore, we aimed to predict the recurrence of pN3b through ML models.MethodsThis retrospective study included 336 patients with pN3b GC who underwent radical surgery. A 3-fold cross-validation was used to partition the participants into training and test cohorts. Linear combinations of new variable features were constructed using principal component analysis (PCA). Various ML algorithms, including random forest, support vector machine (SVM), logistic regression, multilayer perceptron (MLP), extreme gradient boosting (XGBoost), and Gaussian naive Bayes (GNB), were utilized to establish a recurrence prediction model. Model performance was evaluated using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Python was used for the analysis of ML algorithms.ResultsNine principal components with a cumulative variance interpretation rate of 90.71% were identified. The output results of the test set showed that random forests had the highest AUC (0.927) for predicting overall recurrence with an accuracy rate of 80.5%. Random forests had the highest AUC (0.940) for predicting regional recurrence with an accuracy of 89.7%. For predicting distant recurrence, random forests had the highest AUC (0.896) with an accuracy of 84.3%. For peritoneal recurrence, random forests had the highest AUC (0.923) with an accuracy of 83.3%.ConclusionsML can personalize the prediction of postoperative recurrence in patients with GC with stage pN3b.
| S-EPMC11009806 | biostudies-literature
Project description:BackgroundHepatic resection is the preferred treatment for huge hepatocellular carcinoma (>10 cm in diameter; H-HCC). However, the patients with H-HCC suffer from poor prognosis due to the early recurrence/metastasis. The underlying mechanism of H-HCC's early recurrence/metastasis is currently not well understood.ResultsHere, we describe an Isobaric Tags for relative and absolute quantification (iTRAQ)-based quantitative proteomics approach to analyze the early recurrence/metastasis related proteins of H-HCC after radical resection through multidimensional chromatography coupled with tandem mass spectrometry (2DLC-MS/MS). The different protein expression profiles between the early recurrence/metastasis within 6 months(R/M≤6months) and late recurrence/metastasis within 6-12 months after surgery (R/M6-12months) were confirmed and might reveal different underlying molecular mechanisms. We identified 44 and 49 significantly differentially expressed proteins in the R/M≤6months group and the R/M6-12months group compared to the group who had no recurrence within 2 years post surgery (the NR/M group), respectively. Moreover, among those proteins, S100A12 and AMACR were down regulated in the R/M≤6months group but up-regulated in the R/M6-12months group; and this regulation was further confirmed in mRNA and protein level by Q-PCR, Western-Blot and Immunohistochemistry (IHC).ConclusionsThis current study presents the first proteomic profile of the early recurrence/metastasis of H-HCC. The results suggest that S100A12 and AMACR might be potential prognostic markers for predicting the early recurrence/metastasis of H-HCC after hepatectomy.
| S-EPMC4023177 | biostudies-literature
Project description:BACKGROUND:The association of obesity at diagnosis with prostate cancer progression is uncertain. This study aimed to examine the relationship between body mass index (BMI; 18.5-<25, 25-<30, 30-<35, ?35 kg/m2) and prognostic risk at diagnosis, compare the concordance between prognostic risk assessed at diagnostic biopsy versus pathologic risk assessed at surgery across BMI categories, and investigate the association between obesity and prostate cancer recurrence and all-cause death. METHODS:We examined men enrolled in CaPSURE who underwent radical prostatectomy between 1995 and 2017. Multiple imputation methods were used to handle missing data and reported along with complete case findings. RESULTS:Participants (n = 5,200) were followed for a median of 4.5 years; 685 experienced recurrence. Obesity was associated with higher prognostic risk at time of diagnosis (ORobese = 1.5; ORvery obese = 1.7) and upward reclassification of disease between biopsy and surgery, driven by change in tumor stage (ORobese = 1.3; ORvery obese = 1.6). We observed an association between BMI and recurrence with adjustment for disease severity using diagnostic factors (HRvery obese = 1.7); this association disappeared when adjusting for disease severity factors obtained at surgery. CONCLUSIONS:Our findings suggest that residual confounding may partially explain the conflicting evidence regarding obesity's influence on prostate cancer progression. Assessing T-stage via digital rectal exam may be complicated in larger men, potentially affecting clinical treatment decisions. A strong association with all-cause mortality demonstrates healthier BMI at diagnosis may still improve overall survival. IMPACT:Patients with greater BMI are prone to more advanced disease at diagnosis and may be more likely to have their tumor stage underestimated at diagnosis.
| S-EPMC6825577 | biostudies-literature
Project description:Aiming to identify novel immunotargets for gastric cancer (GC), we retrospectively analyzed the formalin-fixed paraffin embedded (FFPE) samples of gastric cancer tissues from postoperative patients who relapsed or metastasized within (early recurrence, n=25) or after two years (late recurrence, n=23). RNA immune-oncology panel (RIOP) including 398 immune-related genes was used to detect the RNA expression level. Disease free survival (DFS) time in early and late recurrent group was 7.52±0.72 and 28.49±0.81 months, respectively. 18 genes were significantly different between the early and late recurrent groups, and the expression of ITK, EBI3, CX3CL1, MYC, EOMES, CA4, TAGAP, MMP2, HAVCR2, FCGR1 and SNAI2 were verified to be associated with the DFS time. We also found that 18 genes were differentially expressed in diffusal type and non-diffusal type of GC. Leukocyte-inhibition, Leukocyte-migration, and Lymphocyte-infiltrate signal/functional pathways were activated in diffusal type of GC by cluster analysis. Our data uncovered the gene set consisted of ITK, EBI3, and CX3CL1 as a potential tool for prediction of early recurrence or poor prognosis in GC, which could be used as novel immunotargets and prognostic markers for the management of GC.
| S-EPMC6959033 | biostudies-literature
Project description:ObjectiveAccurate prediction of postoperative recurrence risk of gastric cancer (GC) is critical for individualized precision therapy. We aimed to investigate whether a computed tomography (CT)-based radiomics nomogram can be used as a tool for predicting the local recurrence (LR) of GC after radical resection.Materials and methods342 patients (194 in the training cohort, 78 in the internal validation cohort, and 70 in the external validation cohort) with pathologically proven GC from two centers were included. Radiomics features were extracted from the preoperative CT imaging. The clinical model, radiomics signature, and radiomics nomogram, which incorporated the radiomics signature and independent clinical risk factors, were developed and verified. Furthermore, the performance of these three models was assessed by using the area under the curve (AUC) of receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA).ResultsThe radiomics signature, which was comprised of two selected radiomics features, namely, contrast_GLCM and dissimilarity_GLCM, showed better performance than the clinical model in predicting the LR of GC, with AUC values of 0.83 in the training cohort, 0.84 in the internal validation cohort, and 0.73 in the external cohort, respectively. By integrating the independent clinical risk factors (N stage, bile acid duodenogastric reflux and nodular or irregular outer layer of the gastric wall) into the radiomics signature, the radiomics nomogram achieved the highest accuracy in predicting LR, with AUC values of 0.89, 0.89 and 0.80 in the three cohorts, respectively. DCA in the validation cohort showed that radiomics nomogram added more net benefit than the clinical model within the range of 0.01-0.98.ConclusionThe CT-based radiomics nomogram has the potential to predict the LR of GC after radical resection.
| S-EPMC8445075 | biostudies-literature
Project description:Recurrence and distant metastases were main reasons of unfavorable outcomes for patients with pancreatic ductal adenocarcinoma (PDAC) after surgery. The aim of this study was to describe the patterns, timing, and predictors of recurrence or metastasis in PDAC patients after curative surgery. Patients with PDAC who underwent radical pancreatectomy were included. Associations between clinicopathological and radiological characteristics and specific pattern of progression were investigated. Least absolute shrinkage and selection operator (LASSO) and Cox regression were applied to assess the prognostic factors for overall survival (OS) and progression-free survival (PFS). A total of 302 patients were included into present study, and 173 patients were documented as recurrence after a median survival of 24.7 months. More than half of patients recurred after 12 months after surgery, and the liver was the most common metastatic site. Decreased time interval to progression, elevated carbohydrate antigen 19-9 (CA19-9) level, and lymph node (LN)16 metastasis were independent predictors for reduced OS. Independent prognostic factors for PFS included elevated carcinoembryonic antigen (CEA) level, local progression, liver or lung-only metastasis, local + distant progression, multiple metastases, LN16 metastasis, imaging tumor size, chemotherapy, and tumor-node-metastasis (TNM) stage. The predictive system showed valuable prediction performance with values of concordance indexes (C-indexes) and the area under the receiver operating characteristic curve (AUC) over 0.80. Different survival curves and predictive factors for specific patterns of disease progression suggested the biological heterogeneity, providing new versions into personal management of recurrence in PDAC patients after surgery.
| S-EPMC6861378 | biostudies-literature
Project description:Aims: TBX2 is related to tumor progression and drug resistance. However, the roles of TBX2 in gastric cancer (GC) remain unclear. Our study aims at investigating the clinical roles of TBX2 in GC. Methods: The protein expression levels of TBX2 in fresh GC tissue (n=20) were investigated with Western blotting analyses. The correlation between TBX2 expression and its prognostic significance was evaluated by immunohistochemical analyses of 401 patients. The survival benefit of postoperative adjuvant chemotherapy (PAC) for patients was evaluated. Results: The expression of TBX2 was increased in GC tissue compared with adjacent paracancerous tissue (p=0.020). Immunohistochemistry demonstrated that TBX2 expression was significantly associated with lymphovascular invasion (p=0.024) and lymph node metastasis (p=0.044). A high level of TBX2 expression was an independent indicator of unfavorable recurrence-free and overall survival (p=0.002 and p=0.033, respectively). The prognostic model incorporating TBX2 expression exhibited greater predictive accuracy than the primary model. More importantly, the benefit of PAC noted in stage II/III GC patients with low TBX2 expression was superior to high TBX2 expression. Conclusion: TBX2 may be not only a useful prognostic marker for GC but also a predictive biomarker of response to PAC in stage II/III GC patients. The current findings warrant further verification.
| S-EPMC7097955 | biostudies-literature
Project description:PurposeTo evaluate the prognostic significance of six epigenetic biomarkers (AIM1, CDH1, KIF1A, MT1G, PAK3, and RBM6 promoter hypermethlation) in a homogeneous group of prostate cancer patients, following radical prostatectomy (RP).Patients and methodsBiomarker analyses were performed retrospectively on tumors from 95 prostate cancer patients all with a Gleason score of 3 + 4 = 7 and a minimum follow-up period of 8 years. Using Quantitative Methylation Specific PCR (QMSP), we analyzed the promoter region of six genes in primary prostate tumor tissues. Time to any progression was the primary endpoint and development of metastatic disease and/or death from prostate cancer was a secondary endpoint. The association of clinicopathological and biomolecular risk factors to recurrence was performed using the Log-rank test and Cox proportional hazards model for multivariate analysis. To identify independent prognostic factors, a stepwise selection method was used.ResultsAt a median follow-up time of 10 years, 48 patients (50.5%) had evidence of recurrence: Biochemical/PSA relapse, metastases, or death from prostate cancer. In the final multivariate analysis for time to progression, the significant factors were: Older age, HR = 0.95 (95% CI: 0.91, 1.0) (P = 0.03), positive lymph nodes HR = 2.11 (95% CI: 1.05, 4.26) (P = 0.04), and decreased hypermethylation of AIM1 HR = 0.45 (95% CI: 0.2, 1.0) (P = 0.05).ConclusionsMethylation status of AIM1 in the prostate cancer specimen may predict for time to recurrence in Gleason 3 + 4 = 7 patients undergoing prostatectomy. These results should be validated in a larger and unselected cohort.
| S-EPMC3360823 | biostudies-literature
Project description:PurposeGastric cancer peritoneal carcinomatosis is fatal. Delay in detection of peritoneal metastases contributes to high mortality, highlighting the need to develop biomarkers that can help identify patients at high risk for peritoneal recurrence or metastasis.Experimental designWe performed a systematic discovery and validation for the identification of peritoneal recurrence prediction and peritoneal metastasis detection biomarkers by analyzing expression profiling datasets from 249 patients with gastric cancer, followed by analysis of 426 patients from three cohorts for clinical validation.ResultsGenome-wide expression profiling identified a 12-gene panel for robust prediction of peritoneal recurrence in patients with gastric cancer (AUC = 0.95), which was successfully validated in a second dataset (AUC = 0.86). Examination of 216 specimens from a training cohort allowed us to establish a six gene-based risk-prediction model [AUC = 0.72; 95% confidence interval (CI): 0.66-0.78], which was subsequently validated in an independent cohort of 111 patients with gastric cancer (AUC = 0.76; 95% CI: 0.67-0.83). In both cohorts, combining tumor morphology and depth of invasion further improved the predictive accuracy of the prediction model (AUC = 0.84). Thereafter, we evaluated the performance of the identical six-gene panel for its ability to detect peritoneal metastasis by analyzing 210 gastric cancer specimens (prior 111 patients plus additional 99 cases), which discriminated patients with and without peritoneal metastasis (AUC = 0.72). Finally, our biomarker panel was also remarkably effective for identifying peritoneal micrometastasis (AUC = 0.72), and its diagnostic accuracy was significantly enhanced when depth of invasion was included in the model (AUC = 0.85).ConclusionsOur novel transcriptomic signature for risk stratification and identification of high-risk patients with peritoneal carcinomatosis might serve as an important clinical decision making in patients with gastric cancer.
| S-EPMC8103893 | biostudies-literature
Project description:BackgroundThe aim of this study was to clarify whether a cancer stem cell marker could be an indicator of post-operative peritoneal recurrence of colon cancer.MethodsExpression of four putative markers (CD133, CD44 variant 6, aldehyde dehydrogenase-1 and leucine-rich repeating G-protein-coupled receptor-5 (LGR5)) was evaluated immunohistochemically in primary tumour samples from 292 patients who underwent curative resection for non-metastasised pT4 colon cancer at the University of Tokyo Hospital between 1997 and 2015.ResultsPeritoneal recurrence was significantly higher in LGR5-negative cases (5-year cumulative incidence: 27.5% vs. 14.4%, p = 0.037). Multivariable analysis confirmed that negative LGR5 expression was an independent risk factor for peritoneal recurrence (hazard ratio (HR) 2.79, p = 0.005) in addition to poor differentiation, positive lymph node metastasis, preoperative carcinoembryonic antigen > 5 ng/mL and anastomotic leakage. The addition of LGR5 significantly improved the predictive value of the multivariable model (net reclassification improvement: 0.186, p = 0.028: integrated discrimination improvement: 0.047, p = 0.008).ConclusionsNegative LGR5 expression was a significant predictor of peritoneal recurrence in patients with pT4 colon cancer. Therefore, LGR5 might be a promising biomarker to identify patients at high risk of post-operative peritoneal metastasis.
| S-EPMC6734652 | biostudies-literature