Prognostic factors for elderly gastric cancer patients who underwent gastrectomy

Background Patients with gastric cancer are aging in Japan. It is not clear which patients and which surgical procedures have survival benefits after gastrectomy. A multivariate analysis was performed. Methods The medical records of 166 patients aged ≥ 80 years who underwent gastrectomy without macroscopic residual tumors were retrospectively reviewed. Univariate and multivariate analyses using Cox proportional hazard models were performed to detect prognostic factors for overall survival. Results In univariate analyses, age (≥ 90 vs. ≥ 80, < 85), performance status (3 vs. 0), American Society of Anesthesiologists physical status (ASA-PS) (3, 4 vs. 1, 2), Onodera’s prognostic nutritional index (< 40 vs. ≥ 45), the physiological score of the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) (≥ 40 vs. ≥ 20, ≤ 29), surgical approach (laparoscopic vs. open), extent of gastrectomy (total, proximal vs. distal), extent of lymphadenectomy (D1 vs. ≥ D2), pathological stage (II–IV vs. I), and residual tumor (R1 vs. R0) were significantly correlated with worse overall survival. Multivariate analysis revealed that ASA-PS [3, 4 vs. 1, 2, hazard ratio (HR) 2.30, 95% confidence interval (CI) 1.24–4.24], extent of gastrectomy (total vs. distal, HR 2.17, 95% CI 1.10–4.31) (proximal vs. distal, HR 4.05, 95% CI 1.45–11.3), extent of lymphadenectomy (D0 vs. ≥ D2, HR 12.4, 95% CI 1.58–97.7), and pathological stage were independent risk factors for mortality. Conclusions ASA-PS was a useful predictor for postoperative mortality. Gastrectomy including cardia is best avoided.

Decreased Expression of KPNA2 in Hepatocellular Carcinoma Infers Favorable Prognosis and High Immune Infiltrating Level

BackgroundLiver hepatocellular carcinoma (LIHC) is an important pathological type of liver cancer. The immune infiltration of the tumor microenvironment is negatively correlated with the overall survival rate of LIHC. At present , the role and molecular mechanism of KPNA2 in LIHC have not been elucidated, and the prognostic correlation between the two and the immune infiltration of LIHC are still unclear. Our study evaluated the role of KPNA2 in LIHC through TCGA data.MethodGene expression profiling interactive analysis (GEPIA) is used to analyze the expression of KPNA2 in LIHC. We evaluated the impact of KPNA2 on the survival of LIHC patients through the survival module. Then, We downloaded the LIHC data set from TCGA. Logistic regression was used to analyze the correlation between clinical information and KPNA2 expression. Cox regression analysis was used to analyze the clinicopathological characteristics related to the overall survival rate of TCGA patients. In addition, we used the "correlation" modules of CIBERSORT and GEPIA to explore the correlation between KPNA2 and cancer immune infiltrate. Western blotting was used to detect the expression of KPNA2.ResultUsing logistic regression for univariate analysis, increased KPNA2 expression was significantly correlated with pathological stage, tumor status, and lymph node status. In addition, multivariate analysis showed that down-regulation of KPNA2 expression, negative pathological stage and distant metastasis are independent prognostic factors for good prognosis. Specifically, CIBERSORT analysis was used to establish a negative correlation between the up-regulated expression of KPNA2 and the level of immune infiltration of B cells, NK cells, mast cells, and T cells. In addition, we confirmed this in the "Association" module of GEPIA. The expression of KPNA2 in LIHC tissues was significantly lower than that in adjacent normal tissues by western blotting.ConclusionThe down-regulation of KPNA2 expression is associated with a good prognosis and an increase in the proportion of immune cells in LIHC. These conclusions indicate that KPNA2 is related to the level of immune infiltration of LIHC and can be used as a potential prognostic biomarker of LIHC and a potential target for clinical tumor treatment.

The Initial Application of MRI Based Prostate Volume-Adjusted Prostate-Specific Antigen In The Diagonosis of MRI-Positive Prostate Cancer Patients

Purpose: To identify the value of prostate-specific antigen density (PSAD) and prostate-specific antigen density of the transition zone (PSADTZ) in improving the sensitivity and specificity of the prostate multiparameter magnetic resonance imaging (mp-MRI), for the purpose of predicting prostate cancer (PCa) and grade reclassification in men with prostate-specific antigen (PSA) between 4 and 20 ng/mL to reduce unnecessary prostate biopsies. Patients and Methods: Between 2018 and 2020, we retrospectively identified 283 consecutive men in Shanghai Jiao Tong University Affiliated Sixth People’s Hospital who had mp-MRI and PSA test within 3 months before prostate biopsies. Total prostate volume (TPV) and transition zone volume (TZV) were measured on mp-MRI. PSA, PSAD, and PSADTZ were compared to improve the sensitivity and specificity of positive biopsy cores and pathological stage by univariate analyses and through the receiver operating curve (ROC). We were focused primarily on the MRI-positive patients with PSA levels of 4-20ng/ml who were most likely subjected to unnecessary repeated prostate biopsies. Results: Of the 283 patients, 138 (48.8%) had PCa and in 145 (51.2%) a benign prostate disease was diagnosed. PSA, PSAD, and PSADTZ were significantly related to biopsy, and equally able to predict higher pathological stage. The receiver operating curve (AUC) for predicting the presence of PCa in all patients was 58.06 for PSA, 72.13 for PSAD and 78.28 for PSADTZ. In addition, the AUC for predicting higher pathological stage in PCa patients was 65.71 for PSA, 65.46 for PSAD and 69.81 for PSADTZ. For 228 MRI-positive patients, the AUC for predicting the presence of PCa was 61.31 for PSA, 74.00 for PSAD and 80.13 for PSADTZ. No difference among the PSA, PSAD, and PSADTZ was found in 55 MRI-negative patients. Conclusion: The determination of PSADTZ had higher diagnostic accuracy for PCa than that based on PSA or PSAD. For MRI-positive patients, PSADTZ promote a more effective and simple method for PCa detection, and may be useful for decreasing the burden of surveillance prostate biopsies.

Prognostic Nomograms Based on Ground Glass Opacity and Subtype of Lung Adenocarcinoma for Patients with Pathological Stage IA Lung Adenocarcinoma

The value of lung adenocarcinoma (LUAD) subtypes and ground glass opacity (GGO) in pathological stage IA invasive adenocarcinoma (IAC) has been poorly understood, and reports of their association with each other have been limited. In the current study, we retrospectively reviewed 484 patients with pathological stage IA invasive adenocarcinoma (IAC) at Sun Yat-sen University Cancer Center from March 2011 to August 2018. Patients with at least 5% solid or micropapillary presence were categorized as high-risk subtypes. Independent indicators for disease-free survival (DFS) and overall survival (OS) were identified by multivariate Cox regression analysis. Based on these indicators, we developed prognostic nomograms of OS and DFS. The predictive performance of the two nomograms were assessed by calibration plots. A total of 412 patients were recognized as having the low-risk subtype, and 359 patients had a GGO. Patients with the low-risk subtype had a high rate of GGO nodules (p &lt; 0.001). Multivariate Cox regression analysis showed that the high-risk subtype and GGO components were independent prognostic factors for OS (LUAD subtype: p = 0.002; HR 3.624; 95% CI 1.263–10.397; GGO component: p = 0.001; HR 3.186; 95% CI 1.155–8.792) and DFS (LUAD subtype: p = 0.001; HR 2.284; 95% CI 1.448–5.509; GGO component: p = 0.003; HR 1.877; 95% CI 1.013–3.476). The C-indices of the nomogram based on the LUAD subtype and GGO components to predict OS and DFS were 0.866 (95% CI 0.841–0.891) and 0.667 (95% CI 0.586–0.748), respectively. Therefore, the high-risk subtype and GGO components were potential prognostic biomarkers for patients with stage IA IAC, and prognostic models based on these indicators showed good predictive performance and satisfactory agreement between observational and predicted survival.

Evaluation of Pre-operative Biopsy, Surgical Procedures and Oncologic Outcomes in Upper Tract Urothelial Carcinoma (UTUC)

Purpose: Discordance between pre-operative biopsy and final pathology for Upper Tract Urothelial Carcinoma (UTUC) is high and optimal management remains controversial. The aim of this study is to evaluate the accuracy of pre-operative biopsy, to identify prognostic factors and to evaluate the effect of adjuvant chemotherapy on survival and oncologic outcome in UTUC.Methods: We analyzed records of patients receiving surgical treatment for UTUC. Pathology of pre-operative biopsy was compared to surgical specimen. We used Kaplan-Meier method to estimate survival probabilities and Cox's proportional hazards models to estimate the association between covariates and event times. Primary endpoint was overall survival (OS). A matched-pair analysis was performed to evaluate the effect of adjuvant chemotherapy.Results: 151 patients underwent surgical treatment (28% open, 36% laparoscopic, 17% robotic radical nephroureterectomy; 14% segmental ureteral resections and 5% palliative nephrectomy) for UTUC and were included in the analysis. Upstaging from &lt;pT1 in endoscopic biopsy to ≥pT1 in final pathology occurred in 61% of patients and upgrading from low-grade to high-grade occurred in 30% of patients. Five-year OS was 59.5%. In the univariate Cox-regression model pathological stage, grade, lymphovascular invasion and positive surgical margins were associated with OS. Matched pair analysis for stage (&lt;pT3; ≥pT3; pN+) and age revealed a significant survival benefit for adjuvant chemotherapy (HR 0.40, 0.14–0.77, p &lt; 0.018) in this cohort.Conclusion: UTUC is often underestimated in pre-operative biopsy, and it is associated with significant mortality. Pathological stage and grade, lymphovascular invasion and lymph node metastases are predictors of oncologic outcome and survival.

Genomic Instability of Mutation-Derived Gene Prognostic Signatures for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the major cancer-related deaths worldwide. Genomic instability is correlated with the prognosis of cancers. A biomarker associated with genomic instability might be effective to predict the prognosis of HCC. In the present study, data of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used. A total of 370 HCC patients from the TCGA database were randomly classified into a training set and a test set. A prognostic signature of the training set based on nine overall survival (OS)–related genomic instability–derived genes (SLCO2A1, RPS6KA2, EPHB6, SLC2A5, PDZD4, CST2, MARVELD1, MAGEA6, and SEMA6A) was constructed, which was validated in the test and TCGA and ICGC sets. This prognostic signature showed more accurate prediction for prognosis of HCC compared with tumor grade, pathological stage, and four published signatures. Cox multivariate analysis revealed that the risk score could be an independent prognostic factor of HCC. A nomogram that combines pathological stage and risk score performed well compared with an ideal model. Ultimately, paired differential expression profiles of genes in the prognostic signature were validated at mRNA and protein level using HCC and paratumor tissues obtained from our institute. Taken together, we constructed and validated a genomic instability–derived gene prognostic signature, which can help to predict the OS of HCC and help us to explore the potential therapeutic targets of HCC.