JUNB mediates oxaliplatin resistance via the MAPK signaling pathway in gastric cancer by chromatin accessibility and transcriptomic analysis

PACSIN1 promotes immunosuppression in gastric cancer by degrading MHC-I

Gastric cancer (GC) is a common gastrointestinal system malignancy. PACSIN1 functions as an oncogene in various cancers. This study aims to investigate the potential of PACSIN1 as a target in GC treatment. Gene expression is determined by RT-qPCR, immunofluorescence staining, and immunohistochemistry assay. FISH is performed to determine the colocalization of PACSIN1 and the major histocompatibility complex (MHC-I). Cytokine release and cell functions are analyzed by flow cytometry. In vivo assays are also conducted. Histological analysis is performed using H&E staining. The results show that PACSIN1 is overexpressed in GC patients, especially in those with immunologically-cold tumors. A high level of PACSIN1 is associated with poor prognosis. PACSIN1 deficiency inhibits autophagy but increases antigen presentation in GC cells. Moreover, PACSIN1 deficiency inhibits the lysosomal fusion and selective autophagy of MHC-I, increases CD8 + T-cell infiltration, and suppresses tumor growth and liver metastasis in vivo. Additionally, PACSIN1 knockout enhances the chemosensitivity of cells to immune checkpoint blockade. In summary, PACSIN1 mediates lysosomal fusion and selective autophagy of MHC-I and suppresses antigen presentation and CD8 + T-cell infiltration, thus inhibiting antitumor immunity in GC.

Identification of neutrophil extracellular trap-driven gastric cancer heterogeneity and C5AR1 as a therapeutic target

Neutrophil extracellular traps (NETs) are implicated in gastric cancer (GC) growth, metastatic dissemination, cancer-associated thrombosis, etc. This work is conducted to elucidate the heterogeneity of NETs in GC. The transcriptome heterogeneity of NETs is investigated in TCGA-STAD via a consensus clustering algorithm, with subsequent external verification in the GSE88433 and GSE88437 cohorts. Clinical and molecular traits, the immune microenvironment, and drug response are characterized in the identified NET-based clusters. Based upon the feature genes of NETs, a classifier is built for estimating NET-based clusters via machine learning. Multiple experiments are utilized to verify the expressions and implications of the feature genes in GC. A novel NET-based classification system is proposed for reflecting the heterogeneity of NETs in GC. Two NET-based clusters have unique and heterogeneous clinical and molecular features, immune microenvironments, and responses to targeted therapy and immunotherapy. A logistic regression model reliably differentiates the NET-based clusters. The feature genes C5AR1, CSF1R, CSF2RB, CYBB, HCK, ITGB2, LILRB2, MNDA, MPEG1, PLEK, SRGN, and STAB1 are proven to be aberrantly expressed in GC cells. Specific knockdown of C5AR1 effectively hinders GC cell growth and elicits intracellular ROS accumulation. In addition, its suppression suppresses the aggressiveness and EMT phenotype of GC cells. In all, NETs are the main contributors to intratumoral heterogeneity and differential drug sensitivity in GC, and C5AR1 has been shown to trigger GC growth and metastatic spread. These findings collectively provide a theoretical basis for the use of anti-NETs in GC treatment.

UBA3 promotes the occurrence and metastasis of intrahepatic cholangiocarcinoma through MAPK signaling pathway

Intrahepatic cholangiocarcinoma (ICC) accounts for approximately 15% of primary liver cancers, and the incidence rate has been increasing in recent years. Surgical resection is the best treatment for ICC, but the 5-year survival rate is less than 30%. ICC signature genes are crucial for the early diagnosis of ICC, so it is especially important to identify signature genes. The aim of this study is to screen the signature genes of ICC and find the potential target for the treatment of ICC. We find that UBA3 is highly expressed in ICC, and knockdown of UBA3 inhibits ICC proliferation, invasion and migration. Mechanistic experiments show that UBA3 promotes ICC proliferation, invasion and migration by affecting ANXA2 through the MAPK signaling pathway. UBA3 is a target of bufalin, and bufalin targeting UBA3 inhibits ICC development and progression through the MAPK signaling pathway. In conclusion, our study shows that bufalin inhibits ICC by targeting UBA3, which has emerged as a new biomarker and potential therapeutic target for ICC.

Targeting PI3K/AKT/mTOR and MAPK Signaling Pathways in Gastric Cancer

Gastric cancer (GC) is the fourth leading cause of death worldwide, with more than 1 million cases diagnosed every year. Helicobacter pylori represents the main risk factor, being responsible for 78% of the cases. Increased amounts of salt, pickled food, red meat, alcohol, smoked food, and refined sugars negatively affect the stomach wall, contributing to GC development. Several gene mutations, including PIK3CA, TP53, ARID1A, CDH1, Ras, Raf, and ERBB3 are encountered in GC pathogenesis, leading to phosphatidylinositol 3-kinase (PI3K) protein kinase B (AKT)/mammalian target of rapamycin (mTOR)-PI3K/AKT/mTOR-and mitogen-activated protein kinase (MAPK) signaling pathway activation and promoting tumoral activity. Helicobacter pylori, growth factors, cytokines, hormones, and oxidative stress also activate both pathways, enhancing GC development. In clinical trials, promising results have come from monoclonal antibodies such as trastuzumab and ramucirumab. Dual inhibitors targeting the PI3K/AKT/mTOR and MAPK signaling pathways were used in vitro studies, also with promising results. The main aim of this review is to present GC incidence and risk factors and the dysregulations of the two protein kinase complexes together with their specific inhibitors.