CT-detected extramural venous invasion-related gene signature for the overall survival prediction in patients with gastric cancer

Extramural venous invasion in gastric cancer: 9.4T magnetic resonance imaging assessment and circular RNA functional analysis

BACKGROUND

Extramural venous invasion (EMVI) is a critical prognostic factor in gastric cancer (GC); however, its detection and underlying molecular mechanisms remain underexplored.

AIM

To investigate the relationship between EMVI and expression of the circular RNA hsa_circ_0097977 in orthotopic GC mouse models.

METHODS

A retrospective analysis was conducted in addition to a preclinical animal study, involving 13 GC patients and 24 orthotopic GC mouse models, respectively. EMVI was assessed using axial T2-weighted fat suppression sequences on a 9.4T magnetic resonance imaging (MRI) with histopathological confirmation as the gold standard for EMVI. The impact of hsa_circ_0097977 on EMVI and GC cell function was evaluated. Statistical analyses comprised consistency, area under the curve analysis, correlation, χ 2/Fisher exact, and Mann-Whitney U/t-tests, with significance set at P < 0.05.

RESULTS

EMVI was accurately detected using 9.4T MRI in orthotopic mouse models with an area under the curve of 0.843 (sensitivity 78.6%, specificity 90.0%). MRI detected EMVI was the only imaging factor associated with distant metastasis (P = 0.04). Furthermore, knockdown of hsa_circ_0097977 was the only factor associated with EMVI (P = 0.043, 0.038) and led to reduced invasion and increased apoptosis in GC cells.

CONCLUSION

EMVI, a risk factor for distant metastasis in GC, is detectable by 9.4T MRI and regulated by hsa_circ_0097977, making it a potential therapeutic target.

CT-based scores for extramural vascular invasion and occult peritoneal metastasis correlate with gastric cancer survival

OBJECTIVE

To assess the feasibility of scoring extragastric vascular invasion and occult peritoneal metastasis using preoperative computed tomography (CT) images of gastric cancer (GC) and to explore the correlation between these scores and patient prognosis.

METHODS

587 GC patients with CT scans from two centers, all confirmed by pathology, were retrospectively evaluated. Scores for CT-detected blood vessel invasion (ctBVI), lymphatic invasion (ctLVI), and occult peritoneal metastasis (ctOPM) were assigned based on preoperative CT images. The patients' follow-up provided data on overall and disease-free survival. Cox proportional hazard models were used to analyze prognostic factors.

RESULTS

The inter-group and intra-group consistency of ctBVL, ctLVI, and ctOPM scores were all > 0.70. Log-rank analysis demonstrated a statistically significant difference in survival curves (p < 0.001). CtBVL, ctLVI, and ctOPM scores were related to overall survival (OS) and disease-free survival (DFS). Univariate and multivariate Cox regression analyses identified ctBVL, ctLVI, ctOPM scores as independent risk factors for GC prognosis. In multivariate analysis, the three sign scores were related to DFS (p < 0.05), with ctBVL (hazard ratio (HR) = 1.980, 95% CI: 1.336-2.933), ctLVI (HR = 1.502, 95% CI: 1.336-2.933), and ctOPM (HR = 1.182, 95% CI: 0.886-1.578). The three scores were also correlated with OS (p < 0.05), ctBVL (HR = 2.003, 95% CI: 1.278-3.139), ctLVI (HR = 1.523, 95% CI:1.055-2.200) and ctOPM (HR = 1.289, 95% CI: 1.013-1.770).

CONCLUSION

CtBVL, ctLVI, and ctOPM scores are valuable prognostic indicators in gastric cancer, influencing both OS and DFS.

KEY POINTS

Question To study whether the ctBVL, ctLVI, and ctOPM scores assessed by preoperative enhanced CT imaging can predict the survival outcomes of patients. Findings CtBVL, ctLVI, and ctOPM scores, assessed via preoperative enhanced CT imaging, are associated with worse survival outcomes when elevated. Clinical relevance CtBVL, ctLVI, and ctOPM scores may help guide personalized follow-up plans. Patients with higher scores might require closer monitoring and more aggressive treatment.

Imaging genomics of cancer: a bibliometric analysis and review

BACKGROUND

Imaging genomics is a burgeoning field that seeks to connections between medical imaging and genomic features. It has been widely applied to explore heterogeneity and predict responsiveness and disease progression in cancer. This review aims to assess current applications and advancements of imaging genomics in cancer.

METHODS

Literature on imaging genomics in cancer was retrieved and selected from PubMed, Web of Science, and Embase before July 2024. Detail information of articles, such as systems and imaging features, were extracted and analyzed. Citation information was extracted from Web of Science and Scopus. Additionally, a bibliometric analysis of the included studies was conducted using the Bibliometrix R package and VOSviewer.

RESULTS

A total of 370 articles were included in the study. The annual growth rate of articles on imaging genomics in cancer is 24.88%. China (133) and the USA (107) were the most productive countries. The top 2 keywords plus were "survival" and "classification". The current research mainly focuses on the central nervous system (121) and the genitourinary system (110, including 44 breast cancer articles). Despite different systems utilizing different imaging modalities, more than half of the studies in each system employed radiomics features.

CONCLUSIONS

Publication databases provide data support for imaging genomics research. The development of artificial intelligence algorithms, especially in feature extraction and model construction, has significantly advanced this field. It is conducive to enhancing the related-models' interpretability. Nonetheless, challenges such as the sample size and the standardization of feature extraction and model construction must overcome. And the research trends revealed in this study will guide the development of imaging genomics in the future and contribute to more accurate cancer diagnosis and treatment in the clinic.

Overall survival prediction of gastric cancer using the gene signature of CT-detected extramural venous invasion combined with M2 macrophages infiltration

BACKGROUND

CT-detected Extramural venous invasion (EMVI) is known as an independent risk factor for distant metastasis in patients with advanced gastric cancer (GC). However, the molecular basis is not clear. In colorectal cancer, M2 macrophages plays a vital role in determining EMVI. This study aimed to investigate the relationship between CT-detected EMVI and the M2 macrophages as well as prognosis predictionusing a radiogenomic approach.

METHOD

We utilized EMVI-related genes (from mRNA sequencing of 13 GC samples correlated with EMVI score by spearman analysis, P < 0.01) to overlap the co-expression genes of WGCNA module and M2 macrophages related genes (from mRNA data of 371 GC patients in TCGA database), generating a total of 136 genes. An EMVI-M2-prognosis-related hub gene signature was constructed by COX and least absolute shrinkage and selection operator (LASSO) analysis from a training cohort TCGA database (n = 371) and validated it in a validation cohort from GEO database (n = 357). High- and low-risk groups were divided by hub gene (EGFLAM and GNG11) signature-derived risk scores. We assessed its predictive ability through Kaplan-Meier (K-M) curve and COX analysis. Furthermore, we utilized ESTIMATE to detect tumor mutation burden (TMB) and evaluate sensitivity to immune checkpoint inhibitors (ICIs). Expression of hub genes was tested using western blotting and immunohistochemistry (IHC) analysis.

RESULTS

The overall survival (OS) was significantly reduced in the high-risk group (Training/Validation: AUC = 0.701/0.620; P < 0.001/0.003). Furthermore, the risk score was identified as an independent predictor of OS in multivariate COX regression analyses (Training/Validation: HR = 1.909/1.928; 95% CI: 1.225-2.974/1.308-2.844). The low-risk group exhibited significantly higher TMB levels (P = 1.6e- 07) and greater sensitivity to ICIs. Significant higher expression of hub-genes was identified on multiple GC cell lines and original samples. Hub-genes knockdown in gastric cancer cell lines inhibited their proliferation, metastatic and invasive capacity to varying degrees. In vivo experiments indicate that EGFLAM, as one of the hub genes, its high expression can serve as a biomarker for low response to immunotherapy.

CONCLUSION

Our study demonstrated EMVI-M2 gene signature could effectively predict the prognosis of GC tissue, reflecting the relationship between EMVI and M2 macrophages.

Non-Coding RNA as Biomarkers and Their Role in the Pathogenesis of Gastric Cancer-A Narrative Review

Non-coding RNAs (ncRNAs) represent a broad family of molecules that regulate gene expression, including microRNAs, long non-coding RNAs and circular RNAs, amongst others. Dysregulated expression of ncRNAs alters gene expression, which is implicated in the pathogenesis of several malignancies and inflammatory diseases. Gastric cancer is the fifth most frequently diagnosed cancer and the fourth most common cause of cancer-related death. Studies have found that altered expression of ncRNAs may contribute to tumourigenesis through regulating proliferation, apoptosis, drug resistance and metastasis. This review describes the potential use of ncRNAs as diagnostic and prognostic biomarkers. Moreover, we discuss the involvement of ncRNAs in the pathogenesis of gastric cancer, including their interactions with the members of major signalling pathways.

Study on the diagnostic value of MDCT extramural vascular invasion in preoperative N staging of gastric cancer patients

BACKGROUND

To explore the diagnostic value of multidetector computed tomography (MDCT) extramural vascular invasion (EMVI) in preoperative N Staging of gastric cancer patients.

METHODS

According to the MR-defined EMVI scoring standard of rectal cancer, we developed a 5-point scale scoring system to evaluate the status of CT-detected extramural vascular invasion(ctEMVI), 0-2 points were ctEMVI-negative status, and 3-4 points were positive status for ctEMVI. Patients were divided into ctEMVI positive group and ctEMVI negative group. The correlation between ctEMVI and clinical features was analyzed. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of ctEMVI for pathological metastatic lymph nodes and N staging, The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of pathological N staging using ctEMVI and short-axis diameter were generated and compared.

RESULTS

The occurrence rate of lymphovascular invasion (LVI) and proportion of tumors with a greatest diameter > 6 cm in the ctEMVI positive group was higher than that in the ctEMVI negative group (P < 0.05). Spearman correlation analysis showed a positive correlation between ctEMVI and LVI, N stage, and tumor size (P < 0.05). For ctEMVI scores ≥ 3,The AUC of ctEMVI for diagnosing lymph node metastasis, N stage ≥ N2, and N3 stage were 0.857, 0.802, and 0.758, respectively. The sensitivity, NPV and accuracy of ctEMVI for diagnosing N stage ≥ N2 were superior to those of short-axis diameter (P < 0.05), while sensitivity, specificity, PPV, NPV, and accuracy of ctEMVI for diagnosing N3 stage were superior to those of short-axis diameter (P < 0.05).

CONCLUSION

ctEMVI has important value in diagnosing metastatic lymph nodes and advanced N staging. As an important imaging marker, ctEMVI can be included in the preoperative imaging evaluation of patients, providing important assistance for clinical guidance and treatment.

Analysis of enhanced CT imaging signs and clinicopathological prognostic factors in hepatoid adenocarcinoma of stomach patients with radical surgery: a retrospective study

BACKGROUND

To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS).

METHODS

Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic (ROC) curve. Survival curves between model-defined risk groups was compared using Kaplan-Meier method.

RESULTS

24(49.0%) patients developed disease recurrence. Multivariate logistic analysis results showed elevated serum CEA level, peritumoral fatty space invasion and positive pathological vascular tumor thrombus were independent factors for disease recurrence. Odds ratios were 10.87 (95%CI, 1.14-103.66), 6.83 (95%CI, 1.08-43.08) and 42.67 (95%CI, 3.66-496.85), respectively. The constructed model showed an area under ROC of 0.912 (95%CI,0.825-0.999). The model-defined high-risk group showed poorer overall survival and recurrence-free survival than the low-risk group (both P < 0.001).

CONCLUSIONS

Preoperative CT appearance of peritumoral fatty space invasion, elevated serum CEA level, and pathological vascular tumor thrombus indicated poor prognosis of HAS patients.

Computed tomography-detected extramural venous invasion-related gene signature: a potential negative biomarker of immune checkpoint inhibitor treatment in patients with gastric cancer

BACKGROUND

To investigate the association between computed tomography (CT)-detected extramural venous invasion (EMVI)-related genes and immunotherapy resistance and immune escape in patients with gastric cancer (GC).

METHODS

Thirteen patients with pathologically proven locally advanced GC who had undergone preoperative abdominal contrast-enhanced CT and radical resection surgery were included in this study. Transcriptome sequencing was multidetector performed on the cancerous tissue obtained during surgery, and EMVI-related genes (P value for association < 0.001) were selected. A single-sample gene set enrichment analysis algorithm was also used to divide all GC samples (n = 377) in The Cancer Genome Atlas (TCGA) database into high and low EMVI-immune related groups based on immune-related differential genes. Cluster analysis was used to classify EMVI-immune-related genotypes, and survival among patients was validated in TCGA and Gene Expression Omnibus (GEO) cohorts. The EMVI scores were calculated using principal component analysis (PCA), and GC samples were divided into high and low EMVI score groups. Microsatellite instability (MSI) status, tumor mutation burden (TMB), response rate to immune checkpoint inhibitors (ICIs), immune escape were compared between the high and low EMVI score groups. Hub gene of the model in pan-cancer analysis was also performed.

RESULTS

There were 17 EMVI-immune-related genes used for cluster analysis. PCA identified 8 genes (PCH17, SEMA6B, GJA4, CD34, ACVRL1, SOX17, CXCL12, DYSF) that were used to calculate EMVI scores. High EMVI score groups had lower MSI, TMB and response rate of ICIs, status but higher immune escape status. Among the 8 genes used for EMVI scores, CXCL12 and SOX17 were at the core of the protein-protein interaction (PPI) network and had a higher priority in pan-cancer analysis. Immunohistochemical analysis showed that the expression of CXCL12 and SOX17 was significantly higher in CT-detected EMVI-positive samples than in EMVI-negative samples (P < 0.0001).

CONCLUSION

A CT-detected EMVI gene signature could be a potential negative biomarker for ICIs treatment, as the signature is negatively correlated with TMB, and MSI, resulting in poorer prognosis.

Effects of tRNA-derived fragments and microRNAs regulatory network on pancreatic acinar intracellular trypsinogen activation

Acute pancreatitis (AP) is a common gastrointestinal disease with substantial morbidity and mortality. Pancreatic acinar intracellular trypsinogen activation (PAITA) is an important event in the early stage of AP. The present study aimed to investigate the effects of tRNA-derived fragments (tRFs) and the microRNA regulatory network on pancreatic acinar intracellular trypsinogen activation (PAITA) and identify novel key targets in AP. Taurolithocholic acid 3-sulfate (TLC-S)-treated AR42J cells were used to establish a PAITA model. Twenty differentially expressed tRFs and 35 DE microRNAs were identified in PAITA through gene sequencing. Based on these genes, we established the tRF-mRNA and microRNA-mRNA regulatory networks by using bioinformatics methods. The networks revealed 29 hub microRNAs (e.g., Let-7 family, miR-21-3p.) and 19 hub tRFs (e.g., tRF3-Thr-AGT, i-tRF-Met-CAT) in PAITA. GO analysis showed that the functions of the two networks were similar and mainly enriched in RNA splicing, mRNA processing, and so on. tRF3-Thr-AGT, targeting Btg2, Cd44, Zbp1, etc., was significantly decreased in PAITA. Moreover, the trypsinogen activation level was increased significantly in the tRF3-Thr-AGT deficiency groups, but rescued by tRF3-Thr-AGT mimics. The results revealed that downregulated tRF3-Thr-AGT was involved in PAITA. This study provides potential novel targets for researching the underlying mechanisms of AP.

CT-detected extramural venous invasion-related gene signature for the overall survival prediction in patients with gastric cancer

Background

Computed tomography (CT)‐detected extramural venous invasion (EMVI) has been identified as an independent factor that can be used for risk stratification and prediction of prognosis in patients with gastric cancer (GC). Overall survival (OS) is identified as the most important prognostic indicator for GC patients. However, the molecular mechanism of EMVI development and its potential relationship with OS in GC are not fully understood. In this radiogenomics‐based study, we sought to investigate the molecular mechanism underlying CT‐detected EMVI in patients with GC, and aimed to construct a genomic signature based on EMVI‐related genes with the goal of using this signature to predict the OS.

Materials and Methods

Whole mRNA genome sequencing of frozen tumor samples from 13 locally advanced GC patients was performed to identify EMVI‐related genes. EMVI‐prognostic hub genes were selected based on overlapping EMVI‐related differentially expressed genes and OS‐related genes, using a training cohort of 176 GC patients who were included in The Cancer Genome Atlas database. Another 174 GC patients from this database comprised the external validation cohort. A risk stratification model using a seven‐gene signature was constructed through the use of a least absolute shrinkage and selection operator Cox regression model.

Results

Patients with high risk score showed significantly reduced OS (training cohort, p = 1.143e‐04; validation cohort, p = 2.429e‐02). Risk score was an independent predictor of OS in multivariate Cox regression analyses (training cohort, HR = 2.758; 95% CI: 1.825–4.169; validation cohort, HR = 2.173; 95% CI: 1.347–3.505; p < 0.001 for both). Gene functions/pathways of the seven‐gene signature mainly included cell proliferation, cell adhesion, regulation of metal ion transport, and epithelial to mesenchymal transition.

Conclusions

A CT‐detected EMVI‐related gene model could be used to predict the prognosis in GC patients, potentially providing clinicians with additional information regarding appropriate therapeutic strategy and medical decision‐making.