Midostaurin Modulates Tumor Microenvironment and Enhances Efficacy of Anti-PD-1 against Colon Cancer

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma

BACKGROUND

Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response.

METHODS

We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R-CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes.

RESULTS

200 glioma patients (mean age, 33 years ± 19 [standard deviation]) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas.

CONCLUSIONS

These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.

JAML inhibits colorectal carcinogenesis by modulating the tumor immune microenvironment

It is necessary to explore new targets for the treatment of colon adenocarcinoma (COAD) according to the tumor microenvironment. The expression levels of JAML and CXADR were analyzed by bioinformatics analysis and validation of clinical samples. JAML over-expression CD8+ T cell line was constructed, and the proliferation activity was detected by MTT. The production of inflammatory factors was detected by ELISA. The expression of immune checkpoint PD-1 and TIM-3 was detected by Western blot. The apoptosis level was detected by flow cytometry and apoptosis markers. The AOM/DSS mouse model of colorectal cancer was constructed. The expression levels of JAML, CXADR and PD-1 were detected by PCR and Western blot, and the proportion of CD8+ T cells and exhausted T cells were detected by flow cytometry. The expression levels of JAML and CXADR were significantly decreased in colon cancer tissues. Overexpression of JAML can promote the proliferation of T cells, secrete a variety of inflammatory factors. Overexpression of CXADR can reduce the proliferation of colorectal cancer cells, promote apoptosis, and down-regulate the migration and invasion ability of tumor cells. Both JAML agonists and PD-L1 inhibitors can effectively treat colorectal cancer, and the combined use of JAML agonists and PD-L1 inhibitors can enhance the effect. JAML can promote the proliferation and toxicity of CD8+ T cells and down-regulate the expression of immune checkpoints in colon cancer. CXADR can inhibit the proliferation of cancer cells and promote the apoptosis. JAML agonist can effectively treat colorectal cancer by regulating CD8+ T cells.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

The role of ARL4C in predicting prognosis and immunotherapy drug susceptibility in pan-cancer analysis

Background: ARLs, which are a class of small GTP-binding proteins, play a crucial role in facilitating tumor tumorigenesis and development. ARL4C, a vital member of the ARLs family, has been implicated in the progression of tumors, metastatic dissemination, and development of resistance to therapeutic drugs. Nevertheless, the precise functional mechanisms of ARL4C concerning tumor prognosis and immunotherapy drug susceptibility remain elusive. Methods: By combining the GTEx and TCGA databases, the presence of ARL4C was examined in 33 various types of cancer. Immunohistochemistry and immunofluorescence staining techniques were utilized to confirm the expression of ARL4C in particular tumor tissues. Furthermore, the ESTIMATE algorithm and TIMER2.0 database were utilized to analyze the tumor microenvironment and immune infiltration associated with ARL4C. The TISCH platform facilitated the utilization of single-cell RNA-seq datasets for further analysis. ARL4C-related immune escape was investigated using the TISMO tool. Lastly, drug sensitivity analysis was conducted to assess the sensitivity of different types of tumors to compounds based on the varying levels of ARL4C expression. Results: The study found that ARL4C was highly expressed in 23 different types of cancer. Moreover, the presence of high ARL4C expression was found to be associated with a poor prognosis in BLCA, COAD, KIRP, LGG, and UCEC. Notably, ARL4C was also expressed in immune cells, and its high expression was found to be correlated with cancer immune activation. Most importantly, the drug sensitivity analysis revealed a positive correlation between ARL4C expression and the heightened sensitivity of tumors to Staurosporine, Midostaurin, and Nelarabine. Conclusion: The findings from our study indicate that the expression level of ARL4C may exert an influence on cancer development, prognosis, and susceptibility to immunotherapy drugs. In addition, the involvement of ARL4C in the tumor immune microenvironment has expanded the concept of ARL4C-targeted immunotherapy.

cGAS-STING signaling pathway in intestinal homeostasis and diseases

The intestinal mucosa is constantly exposed to commensal microbes, opportunistic pathogens, toxins, luminal components and other environmental stimuli. The intestinal mucosa consists of multiple differentiated cellular and extracellular components that form a critical barrier, but is also equipped for efficient absorption of nutrients. Combination of genetic susceptibility and environmental factors are known as critical components involved in the pathogenesis of intestinal diseases. The innate immune system plays a critical role in the recognition and elimination of potential threats by detecting pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). This host defense is facilitated by pattern recognition receptors (PRRs), in which the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway has gained attention due to its role in sensing host and foreign double-stranded DNA (dsDNA) as well as cyclic dinucleotides (CDNs) produced by bacteria. Upon binding with dsDNA, cGAS converts ATP and GTP to cyclic GMP-AMP (cGAMP), which binds to STING and activates TANK binding kinase 1 (TBK1) and interferon regulatory factor 3 (IRF3), inducing type I interferon (IFN) and nuclear factor kappa B (NF-κB)-mediated pro-inflammatory cytokines, which have diverse effects on innate and adaptive immune cells and intestinal epithelial cells (IECs). However, opposite perspectives exist regarding the role of the cGAS-STING pathway in different intestinal diseases. Activation of cGAS-STING signaling is associated with worse clinical outcomes in inflammation-associated diseases, while it also plays a critical role in protection against tumorigenesis and certain infections. Therefore, understanding the context-dependent mechanisms of the cGAS-STING pathway in the physiopathology of the intestinal mucosa is crucial for developing therapeutic strategies targeting the cGAS-STING pathway. This review aims to provide insight into recent findings of the protective and detrimental roles of the cGAS-STING pathway in intestinal diseases.

The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer

The tumour microenvironment (TME) is vital to tumour development and influences the immunotherapy response. Abnormal nucleotide metabolism (NM) not only promotes tumour cell proliferation but also inhibits immune responses in the TME. Therefore, this study aimed to determine whether the combined signatures of NM and the TME could better predict the prognosis and treatment response in gastric cancer (GC). 97 NM-related genes and 22 TME cells were evaluated in TCGA-STAD samples, and predictive NM and TME characteristics were determined. Subsequent correlation analysis and single-cell data analysis illustrated a link between NM scores and TME cells. Thereafter, NM and TME characteristics were combined to construct an NM-TME classifier. Patients in the NMlow/TMEhigh group exhibited better clinical outcomes and treatment responses, which could be attributed to the differences in immune cell infiltration, immune checkpoint genes, tumour somatic mutations, immunophenoscore, immunotherapy response rate and proteomap. Additionally, the NMhigh/TMElow group benefited more from Imatinib, Midostaurin and Linsitinib, while patients in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin. Finally, a highly reliable nomogram was developed. In conclusion, the NM-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic responses, which may offer novel strategies for strategizing patients with optimal therapies.

TREX1 cytosolic DNA degradation correlates with autoimmune disease and cancer immunity

The N-terminal domain of Three Prime Repair Exonuclease 1 (TREX1) is catalytically active and can degrade dsDNA or ssDNA in the cytosol, whereas the C-terminal domain is primarily involved in protein localization. TREX1 deficiency induces cytosolic DNA accumulation as well as activation of the cGAS-STING-IFN signaling pathway, which results in tissue inflammation and autoimmune diseases. Furthermore, TREX1 expression in cancer immunity can be adaptively regulated to promote tumor proliferation, making it a promising therapeutic target.

A novel signature of cuproptosis-related lncRNAs predicts prognosis in glioma: Evidence from bioinformatic analysis and experiments

Background: Glioma patients often experience unfavorable outcomes and elevated mortality rates. Our study established a prognostic signature utilizing cuproptosis-associated long non-coding RNAs (CRLs) and identified novel prognostic biomarkers and therapeutic targets for glioma. Methods: The expression profiles and related data of glioma patients were obtained from The Cancer Genome Atlas, an accessible online database. We then constructed a prognostic signature using CRLs and evaluated the prognosis of glioma patients by means of Kaplan-Meier survival curves and receiver operating characteristic curves. A nomogram based on clinical features was employed to predict the individual survival probability of glioma patients. Functional enrichment analysis was conducted to identify crucial CRL-related enriched biological pathways. The role of LEF1-AS1 in glioma was validated in two glioma cell lines (T98 and U251). Results: We developed and validated a prognostic model for glioma with 9 CRLs. Patients with low-risk had a considerably longer overall survival (OS). The prognostic CRL signature may serve independently as an indicator of prognosis for glioma patients. In addition, functional enrichment analysis revealed significant enrichment of multiple immunological pathways. Notable differences were observed between the two risk groups in terms of immune cell infiltration, function, and immune checkpoints. We further identified four drugs based on their different IC50 values from the two risk groups. Subsequently, we discovered two molecular subtypes of glioma (cluster one and cluster two), with the cluster one subtype exhibiting a remarkably longer OS compared to the cluster two subtype. Finally, we observed that inhibition of LEF1-AS1 curbed the proliferation, migration, and invasion of glioma cells. Conclusion: The CRL signatures were confirmed as a reliable prognostic and therapy response indicator for glioma patients. Inhibition of LEF1-AS1 effectively suppressed the growth, migration, and invasion of gliomas; therefore, LEF1-AS1 presents itself as a promising prognostic biomarker and potential therapeutic target for glioma.

The stimulator of interferon genes (STING) agonists for treating acute myeloid leukemia (AML): current knowledge and future outlook

Acute myeloid leukemia (AML) is an aggressive hematologic cancer in adults. Some patients exhibit restricted T cell infiltration and do not respond to routine treatments. This may be prevented by enhancing adaptive immunity by stimulating innate immune cells inside the tumor microenvironment (TME). To activate the adaptive immunological reaction against tumors, type I interferons (IFNs) can promote the presentation of tumor-specific cytotoxic T lymphocyte (CTL) cell recruitment. During the activation of innate immunity, cyclic di-nucleotides (CDNs) bind to and stimulate the stimulator of interferon genes (STING), a protein localized inside the endoplasmic reticulum (ER) membrane, resulting in the expression of type I IFNs. The efficacy of STING agonists as effective stimulators of the anti-tumor response in AML is being investigated in numerous clinical studies. Therefore, the purpose of this investigation was to thoroughly review existing knowledge in this field and provide perspective into the clinical potential of STING agonists in AML.