A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

Latest guideline of endoscopic submucosal dissection of early gastric cancer may not be suitable for Chinese patients: retrospective study findings from two centers

BACKGROUND

To analyze the diagnostic efficiency of the four absolute endoscopic submucosal dissection (ESD) indications for lymph node metastasis (LNM) of Chinese patients with early gastric cancer (EGC).

METHODS

We retrospectively analyzed EGC patients who underwent radical D2 gastrectomy from January 2019 to December 2022. We evaluated the rate of LNM, false-negative rate, and negative predictive value of the four ESD indications.

RESULTS

Of enrolled 2722 EGC patients, 388 (14.3%) patients presented LNM. Tumor size > 2 cm, ulceration, submucosal invasion, undifferentiated type, and lymphovascular invasion were independent risk factors of LNM in patients with EGC. 1062 (39%) cases of EGC conformed to the four EDS indications; however, 4% of them had LNM. 451 cases were fully in accord with the fourth ESD indication (undifferentiated intramucosal carcinoma without ulceration and a maximum lesion diameter of ≤ 2 cm), and 35 of them had LNM, with a false-negative rate (FNR) of 9.02% and a negative predictive value (NPV) of 92.24%. There was significant difference among the four indications in terms of the rate of LNM (1.0% vs 1.5% vs 1.3% vs 7.8%, P < 0.001), FNR (1.03% vs 0.52% vs 0.26% vs 9.02%, P < 0.001), and NPV (98.99% vs 98.53% vs 98.75% vs 92.24%, P < 0.001).

CONCLUSION

Overall, the fourth ESD indication was associated with a high rate of LNM compared to the other three indications. Thus, it might not be safe to classify it as an absolute indication in Chinese patients with EGC.

A thirty-three gene-based signature predicts lymph node metastasis and prognosis in patients with gastric cancer

Recently, several studies have indicated the great potential of gene expression signature of the primary tumor in predicting lymph node metastasis; however, few current gene biomarkers can predict lymph node status and prognosis in gastric cancer (GC). Thus, we used the RNA-seq data from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes between pathological lymph node-negative (pN0) and positive (pN+) patients and to establish a gene signature that could predict lymph node metastasis. Meanwhile, the robustness of identified gene signatures was validated in an independent dataset Asian Cancer Research Group (n = 300). In this study, our thirty-three gene-based signature was highly correlated with lymph node metastasis and could successfully discriminate pN + patients in the training set (Area under the receiver operating characteristic curve = 0.951). Moreover, Disease-free survival (P = 0.0029) and overall survival (P = 0.026) were significantly worse in high-risk compared with low-risk patients overall and when confined to pN0 patients only (P < 0.0001). Of note, this gene signature also proved useful in predicting lymph node status and survival in the validation cohort. The present study suggests a thirty-three gene-based signature that could effectively predict lymph node metastasis and prognosis in GC.

Novel, alternative splicing signature to detect lymph node metastasis in prostate adenocarcinoma with machine learning

Background

The presence of lymph node metastasis leads to a poor prognosis for prostate cancer (Pca). Recently, many studies have indicated that gene signatures may be able to predict the status of lymph nodes. The purpose of this study is to probe and validate a new tool to predict lymph node metastasis (LNM) based on alternative splicing (AS).

Methods

Gene expression profiles and clinical information of prostate adenocarcinoma cohort were retrieved from The Cancer Genome Atlas (TCGA) database, and the corresponding RNA-seq splicing events profiles were obtained from the TCGA SpliceSeq. Limma package was used to identify the differentially expressed alternative splicing (DEAS) events between LNM and non-LNM groups. Eight machine learning classifiers were built to train with stratified five-fold cross-validation. SHAP values was used to explain the model.

Results

333 differentially expressed alternative splicing (DEAS) events were identified. Using correlation filter and the least absolute shrinkage and selection operator (LASSO) method, a 96 AS signature was identified that had favorable discrimination in the training set and validated in the validation set. The linear discriminant analysis (LDA) was the best classifier after 100 iterations of training. The LDA classifier was able to distinguish between LNM and non-LNM with an area under the receiver operating curve of 0.962 ± 0.026 in the training set (D1 = 351) and 0.953 in the validation set (D2 = 62). The decision curve analysis plot proved the clinical application of the AS-based model.

Conclusion

Machine learning combined with AS data could robustly distinguish between LNM and non-LNM in Pca.

Clinicopathological Characteristics and Survival Predictions for Adenocarcinoma of the Esophagogastric Junction: A SEER Population-Based Retrospective Study

Objective

Adenocarcinoma of the esophagogastric junction (AEJ) is a relatively rare malignancy in Western countries whose specific clinicopathological characteristics and associated prognosis have not been comprehensively described.

Methods

Data on patients with AEJ between 2005 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were extracted, evaluated, and compared with patients with gastric cancer (GC) in general. Overall survival (OS) was evaluated using the Kaplan–Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards regression model to identify risk factors predictive for OS, and the results were used to construct a nomogram to predict 1-, 3-, and 5-year OS among patients with AEJ.

Results

A total of 8013 patients diagnosed with AEJ were identified from the records of 30,179 patients with GC. The mean age was 65.4 (SD = 12.0) years, 79.5% were men, 87.2% were Caucasian, 91.5% were moderately-to-poorly differentiated, 34.4% had AJCC stage I AEJ, and 28.8% had stage IV. The median OS was 18 months, and the 5-year OS was 25.8% (95% CI: 24.8–26.8%). Fewer patients with AEJ had undergone surgical resection, fewer had T+ and N+ (N2~N3) disease (P < 0.001), and fewer had distant metastases compared to the patients with GC (P < 0.05). In the univariate and multivariate analyses, age, race, summary stage, N stage, M stage, and surgery were identified as independent risk factors. The nomogram had a calibration index of 0.726.

Conclusion

AEJ was found to have distinct clinicopathological characteristics. Age, race, summary stage, N stage, M stage, and surgery were independently associated with OS. The nomogram accurately predicted 1-, 3-, and 5-year OS rates.

Effect of Combining Early Chemotherapy with Zhipu Liujunzi Decoction under the Concept of Strengthening and Consolidating Body Resistance for Gastric Cancer Patients and Nursing Strategy

Objective

To explore the clinical efficacy of combining early chemotherapy with Zhipu Liujunzi decoction under the concept of strengthening and consolidating body resistance for gastric cancer patients and nursing strategy.

Methods

The clinical data of 100 patients undergoing radical gastrectomy in our hospital from July 2019 to July 2020 were selected for the retrospective analysis, and the patients were divided into the control group and experimental group according to different treatment methods, with 50 cases in each group. Early chemotherapy after surgery was given to patients in the control group, and on the basis of the aforesaid treatment and under the concept of strengthening and consolidating body resistance, patients in the experimental group took Zhipu Liujunzi decoction and received the nursing strategy, so as to compare their effective rate, adverse reaction rate (ARR), immune function indicators, KPS scores, and nursing satisfaction scores.

Results

After treatment, the experimental group obtained significantly higher objective remission rate (ORR) and disease control rate (DCR) (P < 0.05), lower carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) levels (P < 0.001), higher immune parameters levels (P < 0.001), higher KPS scores and lower TCM symptom scores (P < 0.001), lower PSQI scores, SAS scores, and SDS scores (P < 0.001) and higher nursing satisfaction scores (P < 0.001), and lower total accidence rate of toxic side effects (P < 0.05) than the control group.

Conclusion

Under the concept of strengthening and consolidating body resistance, combining early chemotherapy with Zhipu Liujunzi decoction is a reliable method for improving the immune function and quality of life for gastric cancer patients with higher safety. Such a strategy greatly reduces the tumor marker levels in patients. Further research will be conducive to establishing a better solution for gastric cancer patients.