CSF1R is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in the Gastric Cancer Microenvironment

Radiogenomic Profiling for Survival Analysis in Gastric Cancer: Integrating CT Imaging, Gene Expression, and Clinical Data

PURPOSE

This study aims to integrate CT (Computed Tomography) radiomic features, gene expression profiles, and clinical data to identify radiogenomic biomarkers and improve overall survival prediction in gastric cancer (GC) patients.

PROCEDURES

Quantitative radiomic analysis was performed on 37 GC CT images, alongside gene expression and clinical data, to identify biomarkers associated with overall survival. Tumor segmentation and radiomic feature extraction were followed by Pearson correlation for feature selection. Gene Set Enrichment Analysis (GSEA) identified pathways linking gene expression changes with radiomic features. Regression models were applied to explore the relationships between these pathways, radiomic features, and clinical data in survival prediction.

RESULTS

A total of 107 radiomic features were extracted, with 46 radiomic features, 1,032 genes, and one clinical feature (age) selected for further analysis. GSEA identified 29 significant KEGG pathways, mainly involving immune, signal transduction, and catabolism pathways. In survival analysis, the SVM model performed best, identifying age, genes CSF1R and CXCL12, and image features ShortRunHighGrayLevelEmphasis and Idn (Inverse Difference Normalized) as independent predictors.

CONCLUSION

This study highlights the potential of integrating imaging, genomics, and clinical data for prognosis in GC patients, with identified genes suggesting new radiogenomic biomarker candidates for future evaluation.

A Comprehensive Exploration of Agents Targeting Tumor Microenvironment: Challenges and Future Perspectives

The tumor microenvironment (TME) encompasses the complex and diverse surroundings in which tumors arise. Emerging insights highlight the TME's critical role in tumor development, progression, metastasis, and treatment response. Consequently, the TME has attracted significant research and clinical interest, leading to the identification of numerous novel therapeutic targets. Advances in molecular technologies now enable detailed genomic and transcriptional analysis of cancer cells and the TME and the integration of microenvironmental data to the tumor genomic landscape. This comprehensive review discusses current progress in targeting the TME for drug development, addressing associated challenges, strategies for modulating the pro-tumor microenvironment, and the discovery of new targets.

Molecular Mechanism for Malignant Progression of Gastric Cancer Within the Tumor Microenvironment

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of GC, and progress in the development of effective anti-GC drugs has been insufficient. The tumor microenvironment (TME) regulates various functions of tumor cells, and interactions between the cellular and molecular components of the TME-e.g., inflammatory cells, fibroblasts, vasculature cells, and innate and adaptive immune cells-promote the aggressiveness of cancer cells and dissemination to distant organs. This review summarizes the roles of various TME cells and molecules in regulating the malignant progression and metastasis of GC. We also address the important roles of signaling pathways in mediating the interaction between cancer cells and the different components of the GC TME. Finally, we discuss the implications of these molecular mechanisms for developing novel and effective therapies targeting molecular and cellular components of the GC TME to control the malignant progression of GC.

Narazaciclib, a novel multi-kinase inhibitor with potent activity against CSF1R, FLT3 and CDK6, shows strong anti-AML activity in defined preclinical models

CSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301's high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50 < 1.5 μM). In vivo pharmacology modeling of narazaciclib using five AML xenografts resulted in: inhibition of MV4-11 (FLT3-ITD) subcutaneous tumor growth and complete suppression of AM7577-PDX (FLT3-ITD/CSF1Rmed) systemic growth, likely due to the suppression of FLT3-ITD activity; complete suppression of AM8096-PDX (CSF1Rhi/wild-type FLT3) growth, likely due to the inhibition of CSF1R ("a putative driver"); and nonresponse of both AM5512-PDX and AM7407-PDX (wild-type FLT3/CSF1Rlo). Significant leukemia load reductions in bone marrow, where disease originated, were also achieved in both responders (AM7577/AM8096), implicating that HX301 might be a potentially more effective therapy than those only affecting peripheral leukemic cells. Altogether, narazaciclib can potentially be a candidate treatment for a subset of AML with CSF1Rhi and/or mutant FLT3-ITD variants, particularly second generation FLT3 inhibitor resistant variants.

Identification and characterization of CLEC11A and its derived immune signature in gastric cancer

Introduction

C-type lectin domain family 11 member A (CLEC11A) was characterized as a growth factor that mainly regulates hematopoietic function and differentiation of bone cells. However, the involvement of CLEC11A in gastric cancer (GC) is not well understood.

Methods

Transcriptomic data and clinical information pertaining to GC were obtained and analyzed from publicly available databases. The relationships between CLEC11A and prognoses, genetic alterations, tumor microenvironment (TME), and therapeutic responses in GC patients were analyzed by bioinformatics methods. A CLEC11A-derived immune signature was developed and validated, and its mutational landscapes, immunological characteristics as well as drug sensitivities were explored. A nomogram was established by combining CLEC11A-derived immune signature and clinical factors. The expression and carcinogenic effects of CLEC11A in GC were verified by qRT-PCR, cell migration, invasion, cell cycle analysis, and in vivo model analysis. Myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), M2 macrophages, and T cells in tumor samples extracted from mice were analyzed utilizing flow cytometry analysis.

Results

CLEC11A was over-expressed in GC, and the elevated CLEC11A expression indicated an unfavorable prognosis in GC patients. CLEC11A was involved in genomic alterations and associated with the TME in GC. Moreover, elevated CLEC11A was found to reduce the benefit of immunotherapy according to immunophenoscore (IPS) and the tumor immune dysfunction, exclusion (TIDE). After validation, the CLEC11A-derived immune signature demonstrated a consistent ability to predict the survival outcomes in GC patients. A nomogram that quantifies survival probability was constructed to improve the accuracy of prognosis prediction in GC patients. Using shRNA to suppress the expression of CLEC11A led to significant inhibitions of cell cycle progression, migration, and invasion, as well as a marked reduction of in vivo tumor growth. Moreover, the flow cytometry assay showed that the knock-down of CLEC11A increased the infiltration of cytotoxic CD8+ T cells and helper CD4+ T into tumors while decreasing the percentage of M2 macrophages, MDSCs, and Tregs.

Conclusion

Collectively, our findings revealed that CLEC11A could be a prognostic and immunological biomarker in GC, and CLEC11A-derived immune signature might serve as a new option for clinicians to predict outcomes and formulate personalized treatment plans for GC patients.

Integrated analysis of Helicobacter pylori-related prognostic gene modification patterns in the tumour microenvironment of gastric cancer

BACKGROUND

Helicobacter pylori (HP) infection is one of the leading causes of gastric cancer (GC). However, the interaction between HP and the TME, and its carcinogenic mechanism remains unknown.

METHODS

The HP-related prognostic genes were identified based on HP infection-related gene markers and HP infection sample datasets by risk method and NMF algorithm. Principal component analysis (PCA) algorithm was used to constructed the HPscore system. The "limma" R package was employed to determine differentially expressed genes. In addition, the R packages, such as "xCell" and "GSVA", was used to analyze the relationship between the HPscore and tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to verify the expression levels of 28 HP-related prognostic genes in tissues.

RESULTS

We successfully identified 28 HP-related prognostic genes that accurately classified the GC population. There are significant differences in survival between different subgroups (high-, low-risk and cluster_1,2). Thereafter, the HPscore system was constructed to evaluate the signatures of the 28 HP-related prognostic genes. The overall survival rate in the high-HPscore group was poor and immunological surveillance was reduced, whereas the low-HPscore group had a survival advantage and was related to the inflammatory response. HPscore was also strongly correlated with the tumour stage, TME cell infiltration and stemness. The qRT-PCR results showed that DOCK4 expression level of 28 HP-related prognostic genes was higher in gastric cancer tissues than in adjacent tissues.

CONCLUSIONS

HP signatures play a crucial role in the TME and tumourigenesis. HPscore evaluation of a single tumour sample can help identify the TME characteristics and the carcinogenic mechanism of GC patients infected with HP, based on which personalized treatment can be administered.

High Expression of CSF-1R Predicts Poor Prognosis and CSF-1Rhigh Tumor-Associated Macrophages Inhibit Anti-Tumor Immunity in Colon Adenocarcinoma

Background

Colony stimulating factor 1 receptor (CSF-1R) is a single channel III transmembrane receptor tyrosine kinase (RTK) and plays an important role in immune regulation and the development of various cancer types. The expression of CSF-1R in colon adenocarcinoma (COAD) and its prognostic value remain incompletely understood. Therefore, we aim to explore the prognostic value of CSF-1R in COAD and its relationship with tumor immunity.

Methods

CSF-1R expression in a COAD cohort containing 103 patients was examined using immunohistochemistry (IHC). The relationship between CSF-1R expression and clinicopathological parameters and prognosis was evaluated. Dual immunofluorescence staining was conducted to determine the localization of CSF-1R in COAD tissues. Univariate and multivariate Cox regression analysis were performed to evaluate independent prognostic factors. Transcriptomic profiles of CSF-1R^high and CSF-1R^low tumor-associated macrophages (TAMs) were investigated. Gene enrichment analysis was used to explore the signal pathways related to CSF-1R. In addition, the relationship between CSF-1R in tumor microenvironment (TME) and tumor immunity was also studied.

Results

IHC analysis showed that CSF-1R was overexpressed in COAD, and higher expression was associated with shorter overall survival (OS). Immunofluorescence staining showed that CSF-1R was co-localized with macrophage marker CD68. Univariate and multivariate Cox regression analysis showed that CSF-1R was an independent prognostic factor for COAD. The results of gene enrichment analysis showed that CSF-1R was involved in tumor immune response and regulation of TME. In addition, CSF-1R was significantly correlated with TME, immune cell infiltration, TMB, MSI, Neoantigen, and immune checkpoint molecules.

Conclusion

CSF-1R can serve as an independent prognostic factor of COAD and promising immunotherapeutic target of COAD.