Prognostic analysis of gastric signet ring cell carcinoma and mucinous carcinoma: a propensity score-matched study and competing risk analysis

Comparison of Clinicopathological Features and Prognosis of Mucinous Gastric Carcinoma and other Gastric Cancers: A Retrospective Study of 4,417 Patients

BACKGROUND

Mucinous gastric carcinoma (MGC) is a distinct histologic subtype of gastric cancer (GC) that is often diagnosed at an advanced stage. The clinicopathological characteristics and prognosis of MGC, when compared to adenocarcinoma and signet-ring cell carcinoma (SRCC), are currently subjects of debate and require further investigation.

METHODS

In this study, we conducted an investigation on 4,417 patients who were hospitalized with GC at Zhejiang Cancer Hospital between April 2008 and December 2019. The objective was to compare the prognosis and clinicopathological characteristics of MGC with other types of GC.

RESULTS

In comparison to adenocarcinoma, MGC patients exhibited more advanced tumor infiltration (p < 0.001), lower tumor differentiation (p < 0.001), and higher rates of preoperative tumor marker positivity (except for AFP and CA125) (all p < 0.05). However, after propensity score matching (PSM) to eliminate confounding factors, MGC patients surprisingly exhibited a better prognosis than adenocarcinoma patients (p = 0.008), and the results in multifactorial COX regression were similar (HR = 0.792, 95% CI 0.629-0.997, p = 0.047). Among patients with MGC, age, pN stage, as well as preoperative levels of CA125 and CA724 (all p < 0.05), emerged as independent prognostic markers. While overall survival did not significantly differ between MGC and SRCC (p = 0.196), significant survival disparities emerged in advanced-stage patients (p = 0.009), with MGC showing better survival rates. Furthermore, a nomogram was developed to predict 1-, 3-, and 5-year survival in gastric cancer patients based on various factors, achieving a C-index of 0.772 (95% CI: 0.745-0.799).

CONCLUSIONS

While the poorer prognosis associated with MGC may be linked to its advanced stage and lower degree of differentiation, its biological behavior could contribute to improved survival.

Clinical Features of Gastric Signet Ring Cell Cancer: Results from a Systematic Review and Meta-Analysis

BACKGROUND

Conflicting results about the prognostic relevance of signet ring cell histology in gastric cancer have been reported. We aimed to perform a meta-analysis focusing on the clinicopathological features and prognosis of this subgroup of cancer compared with other histologies.

METHODS

A systematic literature search in the PubMed database was conducted, including all publications up to 1 October 2021. A meta-analysis comparing the results of the studies was performed.

RESULTS

A total of 2062 studies referring to gastric cancer with signet ring cell histology were identified, of which 262 studies reported on its relationship with clinical information. Of these, 74 were suitable to be included in the meta-analysis. A slightly lower risk of developing nodal metastases in signet ring cell tumours compared to other histotypes was found (especially to undifferentiated/poorly differentiated/mucinous and mixed histotypes); the lower risk was more evident in early and slightly increased in advanced gastric cancer. Survival tended to be better in early stage signet ring cell cancer compared to other histotypes; no differences were shown in advanced stages, and survival was poorer in metastatic patients. In the subgroup analysis, survival in signet ring cell cancer was slightly worse compared to non-signet ring cell cancer and differentiated/well-to-moderately differentiated adenocarcinoma.

CONCLUSIONS

Most of the conflicting results in signet ring cell gastric cancer literature could be derived from the lack of standardisation in their classification and the comparison with the different subtypes of gastric cancer. There is a critical need to strive for a standardised classification system for gastric cancer, fostering clarity and coherence in the forthcoming research and clinical applications.

Comparative analysis of tumor biology and prognosis in mucinous and signet-ring cell colon cancers versus classical adenocarcinoma

Background: Limited information is currently available on the natural history and prognosis of two distinct histological subtypes of adenocarcinoma (AC) in the colon: mucinous adenocarcinoma (MAC) and signet-ring cell carcinoma (SRCC). Therefore, the aim of this study is to examine the clinicopathological characteristics of colon MAC and SRCC, comparing them to classical AC, using a large cohort of cases from the United States. Methods: Patients diagnosed with colon AC, MAC, or SRCC from the SEER database between 2000 and 2018 were included in our study. Incidence trends, patient demographics, tumor characteristics, treatment, and survival were analyzed. Results: In our study, we analyzed a total of 310,813 patients with colon cancers, including 271,382 cases of classical AC, 34,750 cases of MAC, and 4,681 cases of SRCC. Over the study period, we observed a decline in the age-adjusted incidence rates of colon AC, MAC, and SRCC. Notably, the MAC and SRCC cohorts differed significantly from AC in terms of patient characteristics, tumor locations, and treatment patterns. Patients with MAC and SRCC had poorer survival outcomes compared to those with AC. Factors associated with worse survival included older age, male sex, poorly differentiated tumors, advanced stage, and the presence of MAC or SRCC histology. On the other hand, surgical intervention was associated with improved survival. Conclusion: Our study underscores the significance of recognizing the distinct features and outcomes associated with different histological subtypes of colon cancer. Further research is warranted to delve into the underlying biological traits that contribute to these differences and to develop more tailored treatment strategies.

Survival Outcome of Gastric Signet Ring Cell Carcinoma Based on the Optimal Number of Examined Lymph Nodes: A Nomogram- and Machine-Learning-Based Approach

The optimal number of examined lymph nodes (ELNs) for gastric signet ring cell carcinoma recommended by National Comprehensive Cancer Network guidelines remains unclear. This study aimed to determine the optimal number of ELNs and investigate its prognostic significance. In this study, we included 1723 patients diagnosed with gastric signet ring cell carcinoma in the Surveillance, Epidemiology, and End Results database. X-tile software was used to calculate the cutoff value of ELNs, and the optimal number of ELNs was found to be 32 for adequate nodal staging. In addition, we performed propensity score matching (PSM) analysis to compare the 1-, 3-, and 5-year survival rates; 1-, 3-, and 5-year survival rates for total examined lymph nodes (ELNs < 32 vs. ELNs ≥ 32) were 71.7% vs. 80.1% (p = 0.008), 41.8% vs. 51.2% (p = 0.009), and 27% vs. 30.2% (p = 0.032), respectively. Furthermore, a predictive model based on 32 ELNs was developed and displayed as a nomogram. The model showed good predictive ability performance, and machine learning validated the importance of the optimal number of ELNs in predicting prognosis.

Application of preoperative CT texture analysis in papillary gastric adenocarcinoma

Background

This study aimed to analyze the ability of computed tomography (CT) texture analysis to discriminate papillary gastric adenocarcinoma (PGC) and to explore the diagnostic efficacy of multivariate models integrating clinical information and CT texture parameters for discriminating PGCs.

Methods

This retrospective study included 20 patients with PGC and 80 patients with tubular adenocarcinoma (TAC). The clinical data and CT texture parameters based on the arterial phase (AP) and venous phase (VP) of all patients were collected and analyzed. Two CT signatures based on the AP and VP were built with the optimum features selected by the least absolute shrinkage and selection operator method. The performance of CT signatures was tested by regression analysis. Multivariate models based on regression analysis and the support vector machine (SVM) algorithm were established. The diagnostic performance of the established nomogram based on regression analysis was evaluated by receiver operating characteristic curve analysis.

Results

Thirty-two and fifteen CT texture parameters extracted from AP and VP CT images, respectively, differed significantly between PGCs and TACs (all p < 0.05). The diagnostic performance of CT signatures based on the AP and VP achieved AUCs of 0.873 and 0.859 in distinguishing PGCs. Multivariate models that integrated two CT signatures and age based on regression analysis and the SVM algorithm showed favorable performance in preoperatively predicting PGCs (AUC = 0.922 and 0.914, respectively).

Conclusion

CT texture analysis based multivariate models could preoperatively predict PGCs with satisfactory diagnostic efficacy.

Clinicopathological features and CT findings of papillary gastric adenocarcinoma

PURPOSE

This study aimed to analyze the clinicopathological and computed tomography (CT) findings of papillary gastric adenocarcinoma and to evaluate the feasibility of the multivariate model based on clinical information and CT findings for discriminating papillary gastric adenocarcinomas.

METHODS

This retrospective study included 22 patients with papillary gastric adenocarcinoma and 88 patients with tubular adenocarcinoma. The demographic data, tumor markers, histopathological information, CT morphological characteristics, and CT value-related parameters of all patients were collected and analyzed. The multivariate model based on regression analysis was performed to improve the diagnostic efficacy for discriminating papillary gastric adenocarcinomas preoperatively. The diagnostic performance of the established nomogram was evaluated by receiver operating characteristic curve analysis.

RESULTS

The distribution of age, carcinoembryonic antigen, differentiation degree, neural invasion, human epidermal growth factor receptor 2 overexpression, P53 mutation status, 4 CT morphological characteristics, and 10 CT valued-related parameters differed significantly between papillary gastric adenocarcinoma and tubular adenocarcinoma groups (all p < 0.05). The established multivariate model based on clinical information and CT findings for discriminating papillary gastric adenocarcinomas preoperatively achieved the area under the curve of 0.920.

CONCLUSION

There existed differences in clinicopathological features and CT findings between papillary gastric adenocarcinomas and tubular adenocarcinomas. The combination of demographic data, tumor markers, CT morphological characteristics, and CT value-related parameters could discriminate papillary gastric adenocarcinomas preoperatively with satisfactory diagnostic efficiency.

Predicting Overall Survival in Patients with Nonmetastatic Gastric Signet Ring Cell Carcinoma: A Machine Learning Approach

Background and Aims

Accurate prediction is essential for the survival of patients with nonmetastatic gastric signet ring cell carcinoma (GSRC) and medical decision-making. Current models rely on prespecified variables, limiting their performance and not being suitable for individual patients. Our study is aimed at developing a more precise model for predicting 1-, 3-, and 5-year overall survival (OS) in patients with nonmetastatic GSRC based on a machine learning approach.

Methods

We selected 2127 GSRC patients diagnosed from 2004 to 2014 from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly partitioned them into a training and validation cohort. We compared the performance of several machine learning-based models and finally chose the eXtreme gradient boosting (XGBoost) model as the optimal method to predict the OS in patients with nonmetastatic GSRC. The model was assessed using the receiver operating characteristic curve (ROC).

Results

In the training cohort, for predicting OS rates at 1-, 3-, and 5-year, the AUCs of the XGBoost model were 0.842, 0.831, and 0.838, respectively, while in the testing cohort, the AUCs of 1-, 3-, and 5-year OS rates were 0.749, 0.823, and 0.829, respectively. Besides, the XGBoost model also performed better when compared with the American Joint Committee on Cancer (AJCC) stage. The performance for this model was stably maintained when stratified by age and ethnicity.

Conclusion

The XGBoost-based model accurately predicts the 1-, 3-, and 5-year OS in patients with nonmetastatic GSRC. Machine learning is a promising way to predict the survival outcomes of tumor patients.

A modified survival model for patients with esophageal squamous cell carcinoma based on lymph nodes: A study based on SEER database and external validation

Background

The counts of examined lymph nodes (ELNs) in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) is a controversial issue. We conducted a retrospective study to develop an ELNs-based model to individualize ESCC prognosis.

Methods

Patients with ESCC from the SEER database and our center were strictly screened. The optimal threshold value was determine by the X-tile software. A prognostic model for ESCC patients was developed and validated with R. The model’s efficacy was evaluated by C-index, ROC curve, and decision curve analysis (DCA).

Results

3,629 cases and 286 cases were screened from the SEER database and our center, respectively. The optimal cut-off value of ELNs was 10. Based on this, we constructed a model with a favorable C-index (training group: 0.708; external group 1: 0.687; external group 2: 0.652). The model performance evaluated with ROC curve is still reliable among the groups. 1-year AUC for nomogram in three groups (i.e., 0.753, 0.761, and 0.686) were superior to that of the TNM stage (P < 0.05). Similarly, the 3-year AUC and the 5-year AUC results for the model were also higher than that of the 8th TNM stage. By contrast, DCA showed the benefit of this model was better in the same follow-up period.

Conclusion

More than 10 ELNs are helpful to evaluate the survival of ESCC patients. Based on this, an improved model for predicting the prognosis of ESCC patients was proposed.

Clinicopathological Features and Prognostic-Related Risk Factors of Gastric Signet Ring Cell Carcinoma: A Meta-Analysis

Background

Gastric signet ring cell carcinoma (SRCC) has shown a growth growing trend worldwide, but its clinicopathological features and prognostic-related risk factors have not been systematically studied. This systematic review was devoted to this.

Method

PubMed, Embase, Cochrane Library, and Web of Science databases were retrieved, and retrospective cohort studies comparing clinicopathological features and related risk factors in SRCC patients were included.

Results

In SRCC patient population, males were more than females (male, OR = 1.38, 95% CI: 1.20-1.60); N3 patients were more than N0-2 patients (N0-2, OR = 3.19, 95% CI: 1.98-5.15); M1 patients were more than M0 patients (M0, OR = 3.30, 95% CI: 1.88-5.80); patients with tumor > 5 cm were more than those with tumor (≤5 cm, OR = 7.36, 95% CI: 1.33-40.60). Patients with age < 60 years (age ≥ 60 years, OR = 1.03, 95% CI: 1.01-1.05), lymphatic vessel invasion (no, OR = 1.74, 95% CI: 1.03-2.45), T2 (T1, OR = 1.17, 95% CI: 1.07-1.28) and T4 (T1, OR = 2.55, 95% CI: 2.30-2.81) stages, and N1 (N0, OR = 1.73, 95% CI: 1.08-2.38), N2 (N0, OR = 2.24, 95% CI: 1.12-3.36), and N3 (N0, OR = 3.45, 95% CI: 1.58-5.32) stages had higher hazard ratio (HR).

Conclusion

SRCC may occur frequently in male. Age, lymphatic vessel invasion, TN, and M stage may be risk factors for poor prognoses of SRCC patients.

Classification and Grading Systems in Gastric Adenocarcinomas

Gastric adenocarcinomas are lesions that raise important issues in clinical practice, due to their incidence and biological behavior. Over time, various systems have been used for classifying and grading of gastric adenocarcinomas, in the hope of increasing the diagnostic accuracy. In this study we statistically analyzed 112 cases of gastric adenocarcinomas in relation to different classification and grading systems, in order to identify their efficacy and concordance in the histopathological diagnosis. The results indicated a significant association of the Lauren and World Health Organization 2019 classifications and also between these and the three-tier and two-tier grading systems, which supports their practical utility in establishing the diagnosis and assessment of the tumor aggressiveness, for the differentiated therapy.

Comparison of Prognosis and Lymph Node Metastasis in T1-Stage Colonic and Rectal Carcinoma: A Retrospective Study

Background

Limited evidence and contradictory results have been reported regarding the impact of tumor site on lymph node metastasis (LNM) and prognosis in T1 stage adenocarcinoma (AC). We aimed to compare two anatomic locations in terms of LNM and prognosis using a comprehensive statistical analysis of a large population.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database and our center (First Affiliated Hospital of Nanchang University) were used to extract patient information. Univariate and multivariate logistic or Cox regression and propensity score matching were used to explore the association between LNM/survival and tumor site.

Results

Information for 12,404 patients, including 9655 colonic AC and 2749 rectal AC patients, was extracted from the SEER database. The 516 AC patients included 184 colonic and 332 rectal AC patients from our center. Multivariate logistic regression analysis revealed a correlation between LNM and tumor site (colon vs rectum, odds ratio [OR] =1.52, 95% CI, 1.349–1.714, P<0.001). Additionally, we found that younger age, T1b stage, poor differentiation, and lymphatic invasion were risk factors for LNM. After adjusting for confounding factors by PSM, we found that the location of the rectum remained a higher risk factor for LNM. However, we found that patients diagnosed with rectal AC had a prognosis similar to that of patients diagnosed with colonic AC, which was demonstrated by the analysis of SEER data and data from our center.

Conclusion

T1-stage rectal AC may have a higher risk of LNM than colonic AC, while rectal AC has a prognosis similar to that of colonic AC.

Higher Lymph Node Metastasis Rate and Poorer Prognosis of Intestinal-Type Gastric Cancer Compared to Diffuse-Type Gastric Cancer in Early-Onset Early-Stage Gastric Cancer: A Retrospective Study

Background: The incidence of early-onset gastric cancer (GC) that was diagnosed at <50 years is increasing, but there is a knowledge gap on early-onset early-stage GC (EEGC) that was defined as early-onset GC limited to the mucosa or submucosa. Therefore, we comprehensively analysed the clinical features based on Lauren type.

Methods: Logistic and Cox analyses were used to investigate risk factors for lymph node metastasis (LNM) and prognosis, respectively. Propensity score matching (PSM) was used to adjust confounding factors. Protein mass spectrometry analysis was used to explore the molecular mechanism of LNM.

Result: Our study included 581 patients with EEGC from the Surveillance, Epidemiology, and End Results (SEER) database and 226 patients with EEGC from our own centre. We identified intestinal type, T1b stage, and tumour size (>3 cm) as risk factors for LNM using SEER and our own data. We also found that the prognosis of patients with intestinal-type EEGC was poorer than patients with diffuse-type EEGC, and T1b stage and positive LNM were hazard factors for survival. After analysing the expression of proteins between positive and negative LNM in the intestinal or diffuse type, we found no similar proteins between these groups. The differentially expressed genes (DEGs) in the intestinal type functioned as epithelial cell signalling in Helicobacter pylori. The DEGs in the diffuse type functioned in the tricarboxylic acid cycle (TCA cycle) and oxidative phosphorylation.

Conclusion: For EEGC, our study was the first report to demonstrate that the intestinal type was a risk factor for LNM and survival compared to the diffuse type, and the oncogenic expression promoting the occurrence of LNM was different. These findings suggest that clinicians should pay more attention to intestinal-type EEGC than diffuse-type EEGC.

Prognosis and Biological Behavior of Gastric Signet-Ring Cell Carcinoma Better or Worse: A Meta-Analysis

BACKGROUND

The clinical pathology of gastric signet-ring cell carcinoma (SRC) is still unclear. This meta-analysis was performed to evaluate the difference in biological behavior and prognosis between SRC and non-signet ring cell carcinoma (NSRC).

METHODS

A total of 58 eligible studies were analyzed using RevMan and other auxiliary software. Biological behaviors were compared based on odds ratio (OR) and mean difference (MD). Hazards ratio (HR) was calculated for prognosis based on Kaplan-Meier curves.

RESULTS

Totally, 28,946 SRC patients were compared with 81,917 NSRC patients. Compared with NSRC patients, lower male: female ratio (OR = 0.53, P < 0.01), younger age (MD = -4.89, P < 0.01), more middle location (OR = 1.64, P < 0.01), more depressed type at early stage (OR = 1.31, P < 0.05), higher incidence of Borrmann type IV (OR = 1.96, P < 0.01), less lymph node metastasis at early stage (OR = 0.78, P < 0.05), better prognosis at early stage (HR = 0.59, P < 0.01), and worse prognosis at advanced stage (HR = 1.19, P < 0.01) were associated with SRC patients.

CONCLUSION

The prognosis of SRC at early stage is better than other types of gastric cancer, while that of SRC at advanced stage is relatively poorer.

Higher LNM rate and poorer prognosis of early-onset compared to late-onset T1 stage colorectal cancer: a large-population based study

As for T1 stage CRC, there is little knowledge of differences in lymph node metastasis (LNM) and prognosis between early-onset and late-onset CRC. To know that, we included 13,084 patients from the SEER database and 476 patients in T1 stage from our hospital to analyze difference of LNM and prognosis. Univariate and multivariate logistic analyses revealed that early-onset CRC was more likely than late-onset CRC to be positive for LNM. In addition, we found that T1b stage, poor differentiation and lymphatic invasion were risk factors for LNM. Specifically, we found that black race was a risk factor. Before propensity-score matching (PSM), we also found that early-onset CRC patients had better survival, as demonstrated by SEER data. After adjusting for confounding factors by PSM, we found that early onset remained a risk factor for LNM. Moreover, we found that patients diagnosed with early-onset CRC had a poorer prognosis than those diagnosed with late-onset CRC, which was demonstrated by analysis of SEER data and our own data. In conclusion, our study was the first to find that early-onset T1 stage CRC more frequently developed LNM, suggesting that endoscopic submucosal resection should be performed more carefully in these patients. Moreover, early-onset patients in the T1 stage also had poorer survival, suggesting that clinical doctors should pay more attention to early-onset patients.

Gastric Adenocarcinomas and Signet-Ring Cell Carcinoma: Unraveling Gastric Cancer Complexity through Microbiome Analysis-Deepening Heterogeneity for a Personalized Therapy

Gastric cancer (GC) is the fifth most prevalent cancer worldwide and the third leading cause of global cancer mortality. With the advances of the omic studies, a heterogeneous GC landscape has been revealed, with significant molecular diversity. Given the multifaceted nature of GC, identification of different patient subsets with prognostic and/or predictive outcomes is a key aspect to allow tailoring of specific treatments. Recently, the involvement of the microbiota in gastric carcinogenesis has been described. To deepen this aspect, we compared microbiota composition in signet-ring cell carcinoma (SRCC) and adenocarcinoma (ADC), two distinct GC subtypes. To this purpose, 10 ADC and 10 SRCC and their paired non-tumor (PNT) counterparts were evaluated for microbiota composition through 16S rRNA analysis. Weighted and unweighted UniFrac and Bray-Curtis dissimilarity showed significant community-level separation between ADC and SRCC. Through the LEfSe (linear discriminant analysis coupled with effect size) tool, we identified potential microbial biomarkers associated with GC subtypes. In particular, SRCCs were significantly enriched in the phyla Fusobacteria, Bacteroidetes, Patescibacteria, whereas in the ADC type, Proteobacteria and Acidobacteria phyla were found. Overall, our data add new insights into GC heterogeneity and may contribute to deepening the GC classification.