5-Fluorouracil enhances the chemosensitivity of gastric cancer to TRAIL via inhibition of the MAPK pathway

Combination therapies and novel delivery systems: a new frontier in overcoming TRAIL resistance in gastric cancer

Gastric cancer (GC) presents a formidable challenge in oncology, mainly due to its inherent resistance to therapies such as tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). This review delineates the multifaceted mechanisms underlying TRAIL resistance in GC, encompassing the deregulation of death receptors (DRs) and decoy receptors (DcRs), aberrant signaling pathways, and the influence of the tumor microenvironment (TME). Innovative strategies such as nanoparticle-based drug delivery systems and oncolytic viral therapies are being explored to counteract these challenges. Nanoparticles enhance TRAIL delivery and efficacy by exploiting the enhanced permeability and retention (EPR) effect, while oncolytic viruses can selectively target cancer cells and stimulate immune responses. Combination therapies, integrating TRAIL with conventional chemotherapeutics like paclitaxel, cisplatin, and 5-fluorouracil, have shown promise in overcoming resistance by modulating apoptotic pathways and downregulating multidrug resistance genes. Additionally, novel agents like cyclopamine, decitabine, and genistein have emerged as effective TRAIL sensitizers by modulating apoptotic pathways and enhancing DR5 expression. Furthermore, the integration of epigenetic modifiers can restore TRAIL sensitivity by demethylating DR4 and DR5 genes. This review emphasizes the need for a comprehensive understanding of the molecular underpinnings of TRAIL resistance and the potential of combination therapies and TRAIL delivery by nanoparticles and oncolytic viruses to enhance treatment outcomes in GC. Future research should focus on elucidating predictive biomarkers and optimizing therapeutic regimens to improve the clinical efficacy of TRAIL-based strategies in GC.

Patient-derived tumor xenograft animal model of gastric cancer in precision chemotherapy

This study aims to establish a patient-derived tumor xenograft (PDX) model for gastric cancer and apply it in pharmacodynamic studies for chemotherapeutic agents. So as to provide guidance for personalized treatment in gastric cancer patients. Fresh gastric cancer tissues were collected from surgical patients and transplanted into NOG mice to establish PDX model. Human source markers were identified by immunofluorescence and immunohistochemistry methods. Exon sequencing was used to verify the retention of humanized features in the PDX model. The efficacy of six chemotherapeutic drugs (oxaliplatin, cisplatin, paclitaxel, fluorouracil, Tegafur, capecitabine) and optimal dose of capecitabine were evaluated by the PDX model. The study has successfully established the PDX model of gastric cancer with transplantation success rates of P0 to P1 (45%), P1 to P2 (88.89%), and P2 to P3 (87.5%). Importantly, original tumor features were effectively preserved till P3. Drug screening results revealed notable antitumor effect of capecitabine in the PDX model of gastric cancer. The study has successfully established a gastric cancer PDX model, highlighting its potential for chemotherapy drug screening and personalized treatment. The transplantation success rates and preservation of original tumor features underscore the model's reliability and relevance for future studies. Findings from drug screening, especially capecitabine's effectiveness, suggest a promising avenue for precision treatment strategies in gastric cancer patients.

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiomics data of STAD patients in The Cancer Genome Atlas (TCGA)-STAD cohort, which included mRNA, microRNA, long non-coding RNA, somatic mutation, and DNA methylation data, from the sxdyc website. We synthesized the multiomics data of patients with STAD using 10 clustering methods, construct a consensus machine learning-driven signature (CMLS)-related prognostic models by combining 10 machine learning methods, and evaluated the prognosis models using the C-index. The prognostic relationship between CMLS and STAD was assessed using Kaplan-Meier curves, and the independent prognostic value of CMLS was determined by univariate and multivariate regression analyses. we also evaluated the immune characteristics, immunotherapy response, and drug sensitivity of different CMLS groups. The results of the multiomics analysis classified STAD into three subtypes, with CS1 resulting in the best survival outcome. In total, 10 hub genes (CES3, AHCYL2, APOD, EFEMP1, CYP1B1, ASPN, CPE, CLIP3, MAP1B, and DKK1) were screened and constructed the CMLS was significantly correlated with prognosis in patients with STAD and was an independent prognostic factor for patients with STAD. Using the CMLS risk score, all patients were divided into a high CMLS group and a low CMLS group. Patients in the low-CMLS group had better survival, more enriched immune cells, and higher tumor mutation load scores, suggesting better immunotherapy responsiveness and a possible "hot tumor" phenotype. Patients in the high-CMLS group had a significantly poorer prognosis and were less sensitive to immunotherapy but were likely to benefit more from chemotherapy and targeted therapy. In this study, 10 clustering methods and 10 machine learning methods were combined to analyze the multiomics of STAD, classify STAD into three subtypes, and constructed CMLS-related prognostic model features, which are important for accurate management and effective treatment of STAD.

Inhibition of PI3K/Akt/mTOR Signaling Pathway Suppresses 5-Fluorouracil Resistance in Gastric Cancer

BACKGROUND

At present, 5-Fluorouracil (5-FU) is a crucial anti-cancer drug and is widely used for the treatment of various carcinomas, including gastric cancer (GC). The resistance of GC cells to 5-FU is still a matter of great concern.

OBJECTIVE

To illustrate the role of PI3K/Akt/mTOR signaling in regulating the cell cycle progression and migration of 5-FU-resistant GC cells.

MATERIAL AND METHODS

After the establishment of drug-resistant GC cell lines, the effects of 5-FU and/or BEZ235 (the dual inhibitor of PI3K and mTOR) on the activity of parental or drug-resistant GC cells were explored. The viability and localization of GC cells (MKN-45 and MKN-74) and their drug-resistant cells (MKN-45/R and MKN-74/R) were assessed using MTT assays and immunofluorescence staining. The impacts of 5-FU and/or BEZ235 on GC cell cycle progression and cell migration were assessed via flow cytometry analyses and wound healing assays, respectively. GC tissues were collected from patients with GC sensitive or refractory to 5-FU chemotherapy. RT-qPCR and western blot were conducted to measure PI3K, AKT, and mTOR levels in GC cells or tissues.

RESULTS

After 5-FU treatment, GC cells displayed 5-FU resistance and the viability of drug-resistant cells (MKN-45/R and MKN-74/R) was higher than that of parental cells (MKN-45 and MKN-74). The IC50 values for MKN-45 and MKN-45/R were 8.93 ug/ml and 140 ug/ml, and the values for MKN-74 and MKN-74/R were 3.93 ug/ml and 114.29 ug/ml. Additionally, the PI3K/Akt/mTOR signaling pathway was activated in drug-resistant GC cells and tumor tissues of patients refractory to 5-FU chemotherapy, as evidenced by high PI3K, Akt, and mTOR levels in MKN-45/R, MKN-74/R, and GC tissues resistant to 5-FU. BEZ235 promoted cell cycle arrest and suppressed the migration of GC cells. Moreover, the combination of BEZ235 and 5-FU led to more effective suppressive influence on cell cycle progression and cell migration relative to the single 5-FU or BEZ235 treatment.

CONCLUSIONS

Silencing of the PI3K/Akt/mTOR signaling pathway suppressed the 5-FU resistance of GC cells.

Correlation between inflammatory cytokines and the likelihood of developing multiple types of digestive system cancers: A Mendelian randomization study

OBJECTIVE

Inflammatory cytokines have been linked to digestive system cancers, yet their exact causal connection remains uncertain. Consequently, we conducted a Mendelian randomization (MR) analysis to gauge how inflammatory cytokines are linked to the risk of five prevalent digestive system cancers (DSCs).

METHODS

We collected genetic variation data for 41 inflammatory cytokines from genome-wide association studies (GWAS), and the results data for five common diseases from the Finnish database. Our primary analytical approach involved employing the inverse-variance weighted, residual sum (IVW) method, complemented by the MR-Egger method, the weighted median method, simple mode analysis, and weighted mode analysis as supplementary analytical techniques. Furthermore, we conducted multiple sensitivity analyses.

RESULTS

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), macrophage colony-stimulating factor (M-CSF), and interleukin (IL)-18 showed a negative association with the risk of hepatocellular carcinoma. Conversely, TRAIL was inversely linked to the risk of gastric cancer, while IL-16 exhibited a positive correlation with gastric cancer risk. Stem cell factor (SCF) acted as a protective factor against pancreatic cancer. For colorectal cancer, IL-7, IL-9, IL-13, and vascular endothelial growth factor (VEGF) were identified as risk factors. Notably, our results did not indicate a significant correlation between inflammatory cytokines and the risk of esophageal cancer.

CONCLUSION

Our research unveils potential connections between 41 inflammatory cytokines and the risk of five common DSCs through a MR analysis. These associations offer valuable insights that could aid in the development of diagnostic biomarkers and the identification of novel therapeutic targets for DSCs.

ALDOC regulated the biological function and immune infiltration of gastric cancer cells

BACKGROUND

The role of ALDOC which is an important regulator involved in tumor metabolic reprogramming and immune microenvironment in GC remains unclear. Therefore, we investigated the feasibility of ALDOC as a prognostic marker and therapeutic target.

METHODS

We verified the expression of ALDOC in GC and its effect on the prognosis of GC patients by analyzing clinical data. The regulation of ALDOC on the biological behavior of GC cells was confirmed by experiments. The potential mechanism of miRNA regulating GC immune cell infiltration by inhibiting ALDOC was explored by experiments and bioinformatic analysis. We further analyzed the effect of ALDOC on somatic mutations in gastric cancer, and constructed a prognostic model based on ALDOC and related immune molecules.

RESULTS

ALDOC is overexpressed in GC cells and tissues, which promotes malignant biological behavior of GC cells and is an independent risk factor for poor prognosis of GC patients. MiR-19a-5p promotes the expression of ALDOC by down-regulating ETS1, leading to poor prognosis in GC patients. ALDOC is significantly associated with immune infiltration in GC, regulates macrophage differentiation and promotes the progression of GC. ALDOC is significantly correlated with TMB and MSI of gastric cancer, and affects somatic mutation of gastric cancer. The prognostic model has good predictive efficiency.

CONCLUSIONS

ALDOC is a potential prognostic marker and therapeutic target with abnormal immune-mediated effects. The prognostic model based on ALDOC provides a reference for prognosis prediction and individualized treatment of GC patients.

The Antigastric Cancer Effect of Triptolide is Associated With H19/NF-κB/FLIP Axis

Background and Objective: Triptolide (TP), one of the fat-soluble components extracted from the Chinese medicinal herb Tripterygium wilfordii Hook F. (TWHF), possesses strong antitumor bioactivities, but its dose-dependent side effects restrict its wide application. This study was designed to investigate whether inflammatory factors increased the antitumor effects of the nontoxic dose of TP on gastric cancer cells and tried to explore the possible molecular mechanisms.

Method: AGS and MKN45 cells were treated with different doses of TP and TNF-α. Cell viability and apoptosis were detected in vitro. In addition, NF-κB mediated prosurvival signals and cytoprotective proteins, especially FLICE-inhibitory protein (FLIP), were detected to determine their effects on TP/TNF-α–induced apoptosis. Moreover, the function of lncRNA H19/miR-204-5p/NF-κB/FLIP axis was investigated in vitro, and the antigastric cancer effect of TP plus TNF-α was proved in the mice xenograft model.

Result:In vitro experimental results showed that TP pretreatment promoted apoptosis in AGS and MKN45 cells upon TNF-α exposure. TP/TNF-α–mediated apoptosis was partly mediated by the inhibitory effect of NF-κB–mediated FLIP expression. Oncogene H19 lying in the upstream pathway of NF-κB played a vital role upon TNF-α exposure, and bioinformatics analysis proved that H19 participated in TP/TNF-α–induced apoptosis via binding of miR-204-5p. Lastly, a low dose of TP and TNF-α inhibited the tumor weight and tumor volume of AGS and MKN45 cells in vivo.

Conclusion: TP pretreatment increased apoptosis in TNF-α–stimulated gastric cancer cells, which are dependent on the disruption of the H19/miR-204-5p/NF-κB/FLIP axis. Cotreatment of TP and TNF-α is a better option for enhancing the anticancer effect and lowering the side effect of TP.