BIBR1532 combined with radiotherapy induces ferroptosis in NSCLC cells and activates cGAS-STING pathway to promote anti-tumor immunity.

BACKGROUND: Telomerase, by safeguarding damaged telomeres and bolstering DNA damage repair, has the capacity to heighten the radioresistance of tumour cells. Thus, in turn, can compromise the efficacy of radiotherapy (RT) and radioimmunotherapy. Our previous studies have revealed that the highly selective telomerase inhibitor, BIBR1532, possesses the potential to enhance the radiosensitivity of Non-small cell lung cancer (NSCLC). In this study, we delve further into the impact of BIBR1532 on the immune activation induced by RT and elucidate the underlying mechanisms. METHODS: Biological information analyses, immunofluorescence assays, western blot assays, flow cytometry analysis were conducted to elucidate the functions of the combination of BIBR1532 with radiotherapy in NSCLC. Intracellular levels of lipid peroxides, glutathione, malondialdehyde, and Fe2+ were measured as indicators of ferroptosis status. Both in vitro and in vivo studies were conducted to examine the antitumor effects. RESULTS: Our findings indicate that the confluence of BIBR1532 with RT significantly augments the activation of the cGAS-STING pathway in both in vivo and in vitro settings, thereby fostering an effective anti-tumoral immune response. The effects can be ascribed to two key processes. Firstly, ionizing radiation, in precipitating DNA double-strand breaks (DSBs), prompts the release of tumour-derived double-stranded DNA (dsDNA) into the cytoplasm. Subsequently, BIBR1532 amplifies the activation of antigen-presenting cells by dsDNA post-RT and instigates the cGAS-STING pathway. Secondly, BIBR1532 enhances the ferroptosis response in NSCLC following RT, thereby promoting unrestrained lipid peroxidation and elevated levels of reactive oxygen species (ROS) within tumour cells. This ultimately leads to mitochondrial stress and the release of endogenous mitochondrial DNA (mtDNA) into the cytoplasm, thus facilitating the activation of the STING pathway and the induction of a type I interferon (IFN)-linked adaptive immune response. CONCLUSION: This study underscores the potential of BIBR1532 as an efficacious and safe radiosensitizer and radioimmunotherapy synergist, providing robust preclinical research evidence for the treatment of NSCLC.

Silencing PinX1 enhances radiosensitivity and antitumor-immunity of radiotherapy in non-small cell lung cancer.

BACKGROUND: We aimed to investigate the effects of PinX1 on non-small cell lung cancer(NSCLC) radiosensitivity and radiotherapy-associated tumor immune microenvironment and its mechanisms. METHODS: The effect of PinX1 silencing on radiosensitivity in NSCLC was assessed by colony formation and CCK8 assay, immunofluorescence detection of γ- H2AX and micronucleus assay. Western blot was used to assess the effect of PinX1 silencing on DNA damage repair pathway and cGAS-STING pathway. The nude mouse and Lewis lung cancer mouse model were used to assess the combined efficacy of PinX1 silencing and radiotherapy in vivo. Changes in the tumor immune microenvironment were assessed by flow cytometry for different treatment modalities in the Lewis luuse model. The interaction protein RBM10 was screened by immunoprecipitation-mass spectrometry. RESULTS: Silencing PinX1 enhanced radiosensitivity and activation of the cGAS-STING pathway while attenuating the DNA damage repair pathway. Silencing PinX1 further increases radiotherapy-stimulated CD8+ T cell infiltration and activation, enhances tumor control and improves survival in vivo; Moreover, PinX1 downregulation improves the anti-tumor efficacy of radioimmunotherapy, increases radioimmune-stimulated CD8+ T cell infiltration, and reprograms M2-type macrophages into M1-type macrophages in tumor tissues. The interaction of PinX1 and RBM10 may promote telomere maintenance by assisting telomerase localization to telomeres, thereby inhibiting the immunostimulatory effects of IR. CONCLUSIONS: In NSCLC, silencing PinX1 significantly contributed to the radiosensitivity and promoted the efficacy of radioimmunotherapy. Mechanistically, PinX1 may regulate the transport of telomerase to telomeres through interacting with RBM10, which promotes telomere maintenance and DNA stabilization. Our findings reveal that PinX1 is a potential target to enhance the efficacy of radioimmunotherapy in NSCLC patients.

Prognostic Implications of Novel Gene Signatures in Gastric Cancer Microenvironment.

BACKGROUND Increasing studies have shown the important clinical role of immune and stromal cells in gastric cancer microenvironment. Based on information of immune and stromal cells in The Cancer Genome Atlas, this study aimed to construct a prognostic risk assessment model for gastric cancer. MATERIAL AND METHODS Based on the immune/structural scores, differentially expressed genes (DEGs) were filtered and analyzed. Afterwards, DEGs associated with prognosis were screened and the risk assessment model was constructed in the training set. Moreover, the validity of the model was verified both in the testing set and the overall sample. RESULTS In this study, patients were divided into high-score and low-score groups based on immune/stromal score, and 919 DEGs were identified. By applying least absolute shrinkage and selection operator (LASSO) and Cox analysis, 10 mRNAs were selected to form a prognostic risk assessment model, risk score=(0.294*SLC17A9) + (-0.477*FERMT3) + (0.866*NRP1) + (0.350*MMRN1) + (0.381*RNASE1) + (0.189*TRIB3) + (0.230*PGAP3) + (0.087*MAGEA3) + (0.182*TACR2) + (0.368*CYP51A1). In the training set, the low-risk group divided by the model was found to have better overall survival, and the prediction efficiency of the model was demonstrated to be good. Multivariate Cox analysis indicated that the model could work as a prognostic factor independently. Similar results were shown in the testing group and overall patients cohort group. Finally, the risk assessment model and other clinical variables were integrated to construct a nomogram. CONCLUSIONS In general, this study constructs a prognostic risk assessment model for gastric cancer, which could improve the prognosis stratification of patients combined with other clinical indicators.

Identification and validation of an individualized autophagy-clinical prognostic index in gastric cancer patients.

BACKGROUND: The purpose of this study is to perform bioinformatics analysis of autophagy-related genes in gastric cancer, and to construct a multi-gene joint signature for predicting the prognosis of gastric cancer. METHODS: GO and KEGG analysis were applied for differentially expressed autophagy-related genes in gastric cancer, and PPI network was constructed in Cytoscape software. In order to optimize the prognosis evaluation system of gastric cancer, we established a prognosis model integrating autophagy-related genes. We used single factor Cox proportional risk regression analysis to screen genes related to prognosis from 204 autophagy-related genes in The Atlas Cancer Genome (TCGA) gastric cancer cohort. Then, the generated genes were applied to the Least Absolute Shrinkage and Selection Operator (LASSO). Finally, the selected genes were further included in the multivariate Cox proportional hazard regression analysis to establish the prognosis model. According to the median risk score, patients were divided into high-risk group and low-risk group, and survival analysis was conducted to evaluate the prognostic value of risk score. Finally, by combining clinic-pathological features and prognostic gene signatures, a nomogram was established to predict individual survival probability. RESULTS: GO analysis showed that the 28 differently expressed autophagy-related genes was enriched in cell growth, neuron death, and regulation of cell growth. KEGG analysis showed that the 28 differently expressed autophagy-related genes were related to platinum drug resistance, apoptosis and p53 signaling pathway. The risk score was constructed based on 4 genes (GRID2, ATG4D,GABARAPL2, CXCR4), and gastric cancer patients were significantly divided into high-risk and low-risk groups according to overall survival. In multivariate Cox regression analysis, risk score was still an independent prognostic factor (HR = 1.922, 95% CI = 1.573-2.349, P < 0.001). Cumulative curve showed that the survival time of patients with low-risk score was significantly longer than that of patients with high-risk score (P < 0.001). The external data GSE62254 proved that nomograph had a great ability to evaluate the prognosis of individual gastric cancer patients. CONCLUSIONS: This study provides a potential prognostic marker for predicting the prognosis of GC patients and the molecular biology of GC autophagy.

Identification of Hub Genes and Pathways in Gastric Adenocarcinoma Based on Bioinformatics Analysis.

BACKGROUND Gastric adenocarcinoma accounts for 95% of all gastric malignant tumors. The purpose of this research was to identify differentially expressed genes (DEGs) of gastric adenocarcinoma by use of bioinformatics methods. MATERIAL AND METHODS The gene microarray datasets of GSE103236, GSE79973, and GSE29998 were imported from the GEO database, containing 70 gastric adenocarcinoma samples and 68 matched normal samples. Gene ontology (GO) and KEGG analysis were applied to screened DEGs; Cytoscape software was used for constructing protein-protein interaction (PPI) networks and to perform module analysis of the DEGs. UALCAN was used for prognostic analysis. RESULTS We identified 2909 upregulated DEGs (uDEGs) and 7106 downregulated DEGs (dDEGs) of gastric adenocarcinoma. The GO analysis showed uDEGs were enriched in skeletal system development, cell adhesion, and biological adhesion. KEGG pathway analysis showed uDEGs were enriched in ECM-receptor interaction, focal adhesion, and Cytokine-cytokine receptor interaction. The top 10 hub genes - COL1A1, COL3A1, COL1A2, BGN, COL5A2, THBS2, TIMP1, SPP1, PDGFRB, and COL4A1 - were distinguished from the PPI network. These 10 hub genes were shown to be significantly upregulated in gastric adenocarcinoma tissues in GEPIA. Prognostic analysis of the 10 hub genes via UALCAN showed that the upregulated expression of COL3A1, COL1A2, BGN, and THBS2 significantly reduced the survival time of gastric adenocarcinoma patients. Module analysis revealed that gastric adenocarcinoma was related to 2 pathways: including focal adhesion signaling and ECM-receptor interaction. CONCLUSIONS This research distinguished hub genes and relevant signal pathways, which contributes to our understanding of the molecular mechanisms, and could be used as diagnostic indicators and therapeutic biomarkers for gastric adenocarcinoma.