Association Between DCE-MRI Perfusion Histogram Parameters and EGFR and VEGF Expressions in Different Lauren Classifications of Advanced Gastric Cancer

Overexpression of ELF1 combined with MMP9 is associated with prognosis and tumor microenvironment in gastric cancer

Gastric cancer (GC) is a prevalent malignancy of the digestive system. E74-like factor 1 (ELF1) is a transcription factor that is specific to T cells and belongs to the Ets family. They are typically expressed in numerous tumor cells, such as pancreatic cancer, oral squamous cell, endometrial carcinoma, nasopharyngeal carcinoma and prostate and colorectal cancer, where they can promote cell invasion and migration. MMP9 is an important protease of the MMP family, since it serves a vital role in tumor progression and prognostic evaluation in colorectal cancer, uveal melanoma and clear cell renal cell carcinoma. The present study aimed to investigate the expression, correlation with MMP9 and clinical significance of ELF1 in GC. In addition, it aimed to explore the possible mechanisms. The ELF1 mRNA expression profile was first assessed using the GEPIA database and R4.2.1 software (Limma package). Reverse transcription-quantitative PCR (RT-qPCR) was used then to validate ELF1 mRNA expression levels in fresh GC samples from 40 patients. The clinical diagnostic value of ELF1 was also assessed using RT-qPCR. Tissue microarray immunohistochemistry (TMA-IHC) was utilized to examine the expression levels of ELF1 and MMP9 proteins in 355 paraffin-embedded GC samples. Subsequently, the present study further investigated the relationship between ELF1 and MMP9 and their possible effects on the clinicopathological features and prognosis of patients with GC. Gene correlation analysis was conducted using the GEPIA database and complemented with Tumor Immune Estimation Resource (TIMER) and CIBERSORT analyses to explore associations with immune infiltration. A significantly higher expression of ELF1 mRNA was found in GC tissues compared with that in adjacent normal tissues (P<0.05). High ELF1 expression in GC tumor cells was found to distinguish GC tissues from adjacent normal tissues with a sensitivity of 87.5% and specificity of 77.5%. ELF1 and MMP9 proteins also showed higher expression in 355 GC compared with adjacent normal tissues, where they were significantly positively correlated (P<0.001). The two were closely associated with various clinicopathological features, including infiltration depth, lymph node involvement, metastasis, TNM staging, microscopic venous invasion, lymphatic invasion and blood serum carcinoembryonic antigen levels in GC. Furthermore, ELF1 and MMP9 expression levels were negatively associated with the overall survival of patients with GC. Prognostic analysis using the Cox proportional hazards model identified high ELF1 expression [hazards ratio (HR), 2.555; 95% CI, 1.546-4.224; P=0.002], high MMP9 expression (HR, 3.813; 95% CI, 2.406-6.041; P<0.001), advanced TNM stage (P=0.001) and advanced N stage (P=0.011) to be independent prognostic factors for patients with GC. Correlation analysis results from the GEPIA database indicated significant associations of ELF1 expression with various GC-related genes, including MutL homolog 1, erythroblastic leukemia viral oncogene homolog 2, PI3K catalytic subunit α, and tumor suppressor protein 53, MMP-9, Cadherin 1, TIMP1, growth factor A and kinase insert domain receptor. In addition, immune infiltration correlation analysis on TIMER and CIBERSORT revealed ELF1 positive relationship with specific infiltrating immune cell types, including naive B, memory-activated CD4+ and gamma delta T cells, and activated NK cells (P<0.05). This observation was further confirmed using immunohistochemistry, showing that ELF1 was associated with CD19 (B-cells) (P<0.001) and CD4 (CD4+ T cells, P=0.002). In conclusion, results from the present study suggest that ELF1 is overexpressed in GC. ELF1 combined with MMP9 can serve as a predictor of malignant biological behavior in GC and therefore a prognostic indicator for patients, due to its association with the tumor microenvironment.

Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging in Magnetic Resonance in the Assessment of Peritoneal Recurrence of Ovarian Cancer in Patients with or Without BRCA Mutation

BACKGROUND

The aim of this study was to determine the differences in diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE) parameters between patients with peritoneal high-grade serous ovarian cancer (HGSOC) recurrence with BRCA mutations (BRCAmut) or BRCA wild type (BRCAwt).

MATERIALS AND METHODS

We retrospectively analyzed the abdominal and pelvic magnetic resonance (MR) images of 43 patients suspected of having recurrent HGSOC, of whom 18 had BRCA1/2 gene mutations. Patients underwent MRI examination via a 1.5 T MRI scanner, and the analyzed parameters were as follows: apparent diffusion coefficient (ADC), time to peak (TTP) and perfusion maximum enhancement (Perf. Max. En.).

RESULTS

The mean ADC in patients with BRCAwt was lower than that in patients with BRCAmut: 788.7 (SD: 139.5) vs. 977.3 (SD: 103), p-value = 0.00002. The average TTP value for patients with BRCAwt was greater than that for patients with mutations: 256.3 (SD: 50) vs. 160.6 (SD: 35.5), p-value < 0.01. The Perf. Max. En. value was lower in the BRCAwt group: 148.6 (SD: 12.3) vs. 233.6 (SD: 29.2), p-value < 0.01.

CONCLUSION

Our study revealed a statistically significant correlation between DWI and DCE parameters in examinations of peritoneal metastasis in patients with BRCA1/2 mutations. Adding DCE perfusion to the MRI protocol for ovarian cancer recurrence in patients with BRCAmut may be a valuable tool.

Fructose-1, 6-Bisphosphate Aldolase B Suppresses Glycolysis and Tumor Progression of Gastric Cancer

OBJECTIVE

Gastric cancer (GC) is believed to be one of the most common digestive tract malignant tumors. However, mounting evidence indicates a link between the glycolysis and tumorigenesis, including gastric cancer.

METHODS

Our research identified 5508 differently expressed mRNAs in gastric cancer. Then, the genes highly associated with tumorigenesis were identified through weighted correlation network analysis (WGCNA). Bioinformatics analysis observed that these hub genes were significantly linked to the regulation of cell cycle, drug metabolism, and glycolysis. Among these hub genes, there is a critical gene involved in glycolysis regulation, namely fructose-bisphosphate B (ALDOB).

RESULTS

Analysis based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets revealed that ALDOB was significantly downregulated in GC compared with normal tissues. In addition, cell viability assay confirmed that ALDOB acted as a tumor suppressor. Finally, drug sensitivity analysis revealed that ALDOB increased the sensitivity of gastric cancer cells to most antitumor drugs, especially talazoparib, XAV939, and FTI-277. Our results showed that the expression of ALDOB was significantly lower in GC tissues than in normal tissues. And ALDOB significantly inhibited proliferation and migration, delayed glycolysis in GC cells. Consequently, our study suggests that ALDOB may be a potential target for the clinical treatment of gastric cancer.

Correlation of MRI quantitative perfusion parameters with EGFR, VEGF and EGFR gene mutations in non-small cell cancer

To explore the relationship between quantitative perfusion histogram parameters of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with the expression of tumor tissue epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF) and EGFR gene mutations in non-small cell lung cancer (NSCLC). A total of 44 consecutive patients with known NSCLC were recruited from March 2018 to August 2021. Histogram parameters (mean, uniformity, skewness, energy, kurtosis, entropy, percentile) of each (Ktrans, Kep, Ve, Vp, Fp) were obtained by Omni Kinetics software. Immunohistochemistry staining was used in the detection of the expression of VEGF and EGFR protein, and the mutation of EGFR gene was detected by PCR. Corresponding statistical test was performed to compare the parameters and protein expression between squamous cell carcinoma (SCC) and adenocarcinoma (AC), as well as EGFR mutations and wild-type. Correlation analysis was used to evaluate the correlation between parameters with the expression of VEGF and EGFR protein. Fp (skewness, kurtosis, energy) were statistically significant between SCC and AC, and the area under the ROC curve were 0.733, 0.700 and 0.675, respectively. The expression of VEGF in AC was higher than in SCC. Fp (skewness, kurtosis, energy) were negatively correlated with VEGF (r =  - 0.527, - 0.428, - 0.342); Ktrans (Q50) was positively correlated with VEGF (r = 0.32); Kep (energy), Ktrans (skewness, kurtosis) were positively correlated with EGFR (r = 0.622, r = 0.375, 0.358), some histogram parameters of Kep, Ktrans (uniformity, entropy) and Ve (kurtosis) were negatively correlated with EGFR (r =  - 0.312 to - 0.644). Some perfusion histogram parameters were statistically significant between EGFR mutations and wild-type, they were higher in wild-type than mutated (P < 0.05). Quantitative perfusion histogram parameters of DCE-MRI have a certain value in the differential diagnosis of NSCLC, which have the potential to non-invasively evaluate the expression of cell signaling pathway-related protein.

Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in gastric cancer patients

Background: We explored whether a model based on contrast-enhanced computed tomography radiomics features and clinicopathological factors can evaluate preoperative lymphovascular invasion (LVI) in patients with gastric cancer (GC) with Lauren classification. Methods: Based on clinical and radiomic characteristics, we established three models: Clinical + Arterial phase_Radcore, Clinical + Venous phase_Radcore and a combined model. The relationship between Lauren classification and LVI was analyzed using a histogram. Results: We retrospectively analyzed 495 patients with GC. The areas under the curve of the combined model were 0.8629 and 0.8343 in the training and testing datasets, respectively. The combined model showed a superior performance to the other models. Conclusion: CECT-based radiomics models can effectively predict preoperative LVI in GC patients with Lauren classification.

Association between radiomics features of DCE-MRI and CD8+ and CD4+ TILs in advanced gastric cancer

Objective: The aim of this investigation was to explore the correlation between the levels of tumor-infiltrating CD8⁺ and CD4⁺ T cells and the quantitative pharmacokinetic parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced gastric cancer. Methods: We retrospectively analyzed the data of 103 patients with histopathologically confirmed advanced gastric cancer (AGC). Three pharmacokinetic parameters, K_ep, K^trans, and V_e, and their radiomics characteristics were obtained by Omni Kinetics software. Immunohistochemical staining was used to determine CD4⁺ and CD8⁺ TILs. Statistical analysis was subsequently performed to assess the correlation between radiomics characteristics and CD4⁺ and CD8⁺ TIL density. Results: All patients included in this study were finally divided into either a CD8⁺ TILs low-density group (n = 51) (CD8⁺ TILs < 138) or a high-density group (n = 52) (CD8⁺ TILs ≥ 138), and a CD4⁺ TILs low-density group (n = 51) (CD4⁺ TILs < 87) or a high-density group (n = 52) (CD4⁺ TILs ≥ 87). ClusterShade and Skewness based on K_ep and Skewness based on K^trans both showed moderate negative correlation with CD8⁺ TIL levels (r = 0.630-0.349, p < 0.001), with ClusterShade based on K_ep having the highest negative correlation (r = -0.630, p < 0.001). Inertia-based K_ep showed a moderate positive correlation with the CD4⁺ TIL level (r = 0.549, p < 0.001), and the Correlation based on K_ep showed a moderate negative correlation with the CD4⁺ TIL level, which also had the highest correlation coefficient (r = -0.616, p < 0.001). The diagnostic efficacy of the above features was assessed by ROC curves. For CD8⁺ TILs, ClusterShade of K_ep had the highest mean area under the curve (AUC) (0.863). For CD4⁺ TILs, the Correlation of K_ep had the highest mean AUC (0.856). Conclusion: The radiomics features of DCE-MRI are associated with the expression of tumor-infiltrating CD8⁺ and CD4⁺ T cells in AGC, which have the potential to noninvasively evaluate the expression of CD8⁺ and CD4⁺ TILs in AGC patients.