With the development of materials science and biomedicine, the application of nanomaterials in the medical field is further promoted. In the process of the diagnosis and treatment of diseases, a variety of drugs need to be used. It is an ideal state to make these drugs arrive at a specific location at a specific time and release at a specific speed, which can improve the bioavailability of drugs and reduce the adverse effects of drugs on normal tissues. Traditional drug delivery methods such as tablets, capsules, syrups, and ointments have certain limitations. The emergence of a new nano-drug delivery system further improves the accuracy of drug delivery and the efficacy of drugs. It is well known that the development of the cancer of the stomach is the most serious consequence for the infection of Helicobacter pylori. For the patients who are suffering from gastric cancer, the treatments are mainly surgery, chemotherapy, targeted and immune therapy, and other comprehensive treatments. Although great progress has been made, the diagnosis and prognosis of gastric cancer are still poor with patients usually diagnosed with cancer at an advanced stage. Current treatments are of limited benefits for patients, resulting in a poor 5-year survival rate. Nanomaterials may play a critical role in early diagnosis. A nano-drug delivery system can significantly improve the chemotherapy, targeted therapy, and immunotherapy of advanced gastric cancer, reduce the side effects of the original treatment plan and provide patients with better benefits. It is a promising treatment for gastric cancer. This article introduces the application of nanomaterials in the diagnosis and treatment of H. pylori and gastric cancer.

The ANLN gene encodes anillin, a protein that binds to actin. Recent research has identified ANLN’s function in the initiation and advancement of different cancers. However, its impact on gallbladder cancer (GBC) remains unexplored. This study aimed to elucidate its possible molecular mechanisms in GBC. ANLN expression was assessed using quantitative real-time polymerase chain reaction (QRT-PCR), Western blotting (WB), and immunohistochemistry (IHC), revealing elevated levels in GBC tissues. ANLN knockdown resulted in the inhibition of cell proliferation and migration, leading to apoptosis and cell cycle arrest. Conversely, ANLN overexpression had the opposite effects on GBC cells. In vivo experiments confirmed that ANLN knockdown inhibited GBC cell growth. RNA-seq and bioinformatics analysis revealed ANLN’s function in activating the PI3K/AKT signaling pathway. We further confirmed that ANLN could upregulate STRA6 expression, which activated PI3K/AKT signaling to enhance the growth and movement of GBC cells. These findings demonstrate ANLN’s involvement in GBC initiation and progression, suggesting its potential as a novel target for GBC.

Background: Long non-coding RNAs (lncRNAs) are crucial factors affecting the occurrence, progression, and prognosis of gastric carcinoma (GC). The accumulation of disulfide bonds to excessive levels in cells expressing high SLC7A11 triggers disulfidptosis, which functions as a regulated form of cellular death. Research has demonstrated that upregulated SLC7A11 is common in human cancers, but the effect of disulfidptosis on GC remains unclear. Identifying lncRNAs associated with disulfidptosis (drlncRNAs) and establishing a prognostic risk profile holds considerable importance for advancing GC research and treatment. Methods: Clinical records and transcriptomic datasets from individuals with GC were acquired from The Cancer Genome Atlas (TCGA) repository. A three-drlncRNA risk model was built using three common regression analysis methods. Then we used receiver operating characteristic (ROC) curves, independent prognostic analysis, and additional statistical approaches to assess the precision of the model. This investigation additionally encompassed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, immune cell infiltration evaluation, and pharmacological sensitivity predictions. To further investigate immunotherapy response disparities between patient cohorts with elevated- and reduced-risk scores, analyses of tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and microsatellite instability (MSI) were implemented. Results: We constructed a unique model composed of three drlncRNAs (AC107021.2, AC016394.2, and AC129507.1). Its independent prognostic capability for GC patients was validated through both single-variable and multivariable Cox regression analyses. GO and KEGG pathway assessments revealed predominant enrichment within the elevated-risk cohort, particularly in pathways involving sulfur compound interactions, traditional Wnt signaling mechanisms, cell-substrate adherens junctions, and cAMP signaling cascades, among others. Tumor microenvironment (TME) evaluation demonstrated elevated ImmuneScores, StromalScores, and ESTIMATEScores within the high-risk patient population. Concurrently, this elevated-risk cohort exhibited enhanced immune cell infiltration patterns, whereas the reduced-risk group displayed superior expression of immune checkpoints (ICPs). Additional investigations revealed that patients categorized into the reduced-risk classification possessed greater tumor mutational burden, increased MSI-high proportions, and diminished tumor immune dysfunction and exclusion scores compared to their high-risk counterparts. Pharmacological sensitivity assessments confirmed the superior efficacy of several therapeutic agents, including gemcitabine and veliparib (ABT.888), in patients with lower risk classifications. Conclusions: Our established risk stratification system demonstrates independent prognostic predictive capacity while offering personalized clinical intervention guidance for individuals diagnosed with GC.