Tumor size predicts survival in mucinous gastric carcinoma

Relationship between the deep features of the full-scan pathological map of mucinous gastric carcinoma and related genes based on deep learning

Background

Long-term differential expression of disease-associated genes is a crucial driver of pathological changes in mucinous gastric carcinoma. Therefore, there should be a correlation between depth features extracted from pathology-based full-scan images using deep learning and disease-associated gene expression. This study tried to provides preliminary evidence that long-term differentially expressed (disease-associated) genes lead to subtle changes in disease pathology by exploring their correlation, and offer a new ideas for precise analysis of pathomics and combined analysis of pathomics and genomics.

Methods

Full pathological scans, gene sequencing data, and clinical data of patients with mucinous gastric carcinoma were downloaded from TCGA data. The VGG-16 network architecture was used to construct a binary classification model to explore the potential of VGG-16 applications and extract the deep features of the pathology-based full-scan map. Differential gene expression analysis was performed and a protein-protein interaction network was constructed to screen disease-related core genes. Differential, Lasso regression, and extensive correlation analyses were used to screen for valuable deep features. Finally, a correlation analysis was used to determine whether there was a correlation between valuable deep features and disease-related core genes.

Result

The accuracy of the binary classification model was 0.775 ± 0.129. A total of 24 disease-related core genes were screened, including ASPM, AURKA, AURKB, BUB1, BUB1B, CCNA2, CCNB1, CCNB2, CDCA8, CDK1, CENPF, DLGAP5, KIF11, KIF20A, KIF2C, KIF4A, MELK, PBK, RRM2, TOP2A, TPX2, TTK, UBE2C, and ZWINT. In addition, differential, Lasso regression, and extensive correlation analyses were used to screen eight valuable deep features, including features 51, 106, 109, 118, 257, 282, 326, and 487. Finally, the results of the correlation analysis suggested that valuable deep features were either positively or negatively correlated with core gene expression.

Conclusion

The preliminary results of this study support our hypotheses. Deep learning may be an important bridge for the joint analysis of pathomics and genomics and provides preliminary evidence for long-term abnormal expression of genes leading to subtle changes in pathology.

Mucinous adenocarcinoma and non-mucinous adenocarcinoma: differing clinicopathological characteristics and computed tomography features in gastric cancer

Mucinous gastric carcinoma (MGC) is a rare histological subtype of gastric cancer. The clinicopathological characteristics and CT features of MGC remain controversial. This study aimed to determine the clinicopathological characteristics and CT features of MGC. We reviewed 62 patients with MGC and 104 patients with non-mucinous gastric carcinoma (NMGC), pathologically confirmed between 2003 and 2015. There are significant differences in some clinicopathological characteristics and CT features between MGC and NMGC. NMGC occurs preferentially in males and more frequently in the lower third of the stomach. Patients with MGC were characterized by larger tumor size, more advanced tumor stages (II and III) and fewer lymphatic invasions. Layered enhancement (83.3%) was the main pattern of MGC, while the most common pattern in NMGC was homogeneous enhancement (52.6%), followed by heterogonous enhancement (34.6%). The degree of enhancement of the inner layer in MGC was significantly higher than in NMGC (ΔCT of portal venous phase: 54.57 Hu vs. 47.19 Hu, P = 0.034), while the middle or outer layer in MGC was significantly less enhanced (ΔCT of portal venous phase: 19.07 Hu vs. 33.09 Hu, P <0.001). Calcifications were more common in MGC (P <0.001). ROC curves revealed that the most effective variables in distinguishing MGC and NMGC were ΔCT of the middle or outer layer in the arterial phase (AUC=0.774) and portal venous phase (AUC=0.774), followed by the attenuation value of the middle or outer layer in the unenhanced phase (AUC=0.763). Calcifications had a high specificity (98.7%) in the diagnosis of MGC. The accuracy (86.1%), sensitivity (83.3%) and specificity (87.2%) of layered enhancement in diagnosing MGC were all high. Therefore, MGC was more likely to have larger tumor size and more advanced tumor stage (II and III) than NMGC. The thicker gastric wall, layered enhancement pattern and calcification were highly suggestive CT features for differentiating MGC from NMGC.

The Clinicopathological Features and Long-Term Survival Outcomes of Mucinous Gastric Carcinoma: a Consecutive Series of 244 Cases from a Single Institute

BACKGROUND AND OBJECTIVES

Mucinous gastric carcinoma (MGC) is a rare kind of malignancy with unclear prognosis. This study aims to assess the clinicopathological features and prognosis of MGC.

METHODS

We retrospectively analyzed a consecutive series of 244 MGC patients who underwent radical gastrectomy with D2 lymphadenectomy, and compared the data with 260 gastric signet ring cell carcinoma (SRC) patients.

RESULTS

The univariate survival analysis showed that the surgical types, diameter of the primary tumor, the Borrmann type, pathological depth of tumor invasion (pT), pathological number of metastatic lymph node (pN), pathological tumor lymph metastasis (pTNM), and vascular invasion were all significant predictors of survival (all P < 0.05). The multivariate survival analysis revealed that the diameter of the tumor, the Borrmann type, pT, pTNM stage, and vascular invasion as an independent predictive factor of survival (all P < 0.05). Compared with the SRC group, the MGC group had more male patients, more elder patients, larger tumor diameter, more T3 and T4 invasion to the gastric wall, more patients with metastatic lymph nodes, more pTNM stage III, and less Borrmann type 1. The overall survival rate of patients with MGC was significantly lower than that of patients with SRC (P < 0.001).

CONCLUSIONS

MGC was an aggressive malignancy which had unique clinicopathological features.

Prognostic Significance of Tumor Size in 2405 Patients With Gastric Cancer: A Retrospective Cohort Study

The clinical prognostic significance of tumor size (Ts) in gastric cancer remains under debate. This study aims to evaluate the prognostic value of Ts in gastric cancer patients undergoing gastrectomy. A total of 2405 patients with gastric cancer, all having received radical resection, were enrolled in this retrospective study from 2000 to 2011. Patients were categorized by minimum P value from log-rank χ2 statistics using X-tile. The relationships between Ts and other clinicopathologic characteristics were analyzed, and the survival prediction accuracy was also compared between Ts and T stage. Patients were divided into 5 groups, according to which Ts stage and TsNM stage system were proposed. Ts, an independent prognostic factor identified by univariate and multivariate survival analysis, was significantly associated with sex, age, tumor location, macroscopic type, tumor diffferentiation, vessel invasion, perineural invasion, T stage, N stage, and TNM stage. Compared with T stage system, Ts stage system was found no superiorities in survival prediction. However, for patients with lymph node metastasis and patients with age ≥60, Ts stage system revealed a significant improvement of predictive accuracy in subgroup survival analysis. Furthermore, TsNM stage (c-index = 0.783) system was found to be superior to TNM stage (c-index = 0.743) system in prognostic prediction accuracy (P < 0.05). Ts is significantly correlated with gastric cancer progression, which can be regarded as a reliable prognostic factor, and the TsNM stage system may improve the prognostic prediction accuracy in gastric cancer patients.

The molecular background of mucinous carcinoma beyond MUC2

The increasing interest of the oncology community in tumour classification and prediction of outcome to targeted therapies has put emphasis on an improved identification of tumour types. Colorectal mucinous adenocarcinoma (MC) is a subtype that is characterized by the presence of abundant extracellular mucin that comprises at least 50% of the tumour volume and is found in 10–15% of colorectal cancer patients. MC development is poorly understood, however, the distinct clinical and pathological presentation of MC suggests a deviant development and molecular background. In this review we identify common molecular and genetic alterations in colorectal MC. MC is characterized by a high rate of MUC2 expression. Mutation rates in the therapeutically important RAS/RAF/MAPK and PI3K/AKT pathways are significantly higher in MC compared with non‐mucinous adenocarcinoma. Furthermore, mucinous adenocarcinoma shows higher rates of microsatellite instability and is more frequently of the CpG island methylator phenotype. Although the majority of MCs arise from the large intestine, this subtype also develops in other organs, such as the stomach, pancreas, biliary tract, ovary, breast and lung. We compared findings from colorectal MC with tumour characteristics of MCs from other organs. In these organs, MCs show different mutation rates in the RAS/RAF/MAPK and PI3K/AKT pathways as well, but a common mucinous pathway cannot be identified. Identification of conditions and molecular aberrations that are associated with MC generates insight into the aetiology of this subtype and improves understanding of resistance to therapies.