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The role of collagen and its receptor, discoidin domain receptor 1 (DDR1) in immune response of colorectal cancer (CRC) remains unclear. We identified DDR1 as a promising target of immunotherapy resistance using a pooled in vivo CRISPR/sgRNA screening in microsatellite stable (MSS) CRC mouse models. Our findings demonstrated that knockdown or inhibition of DDR1 could enhance infiltration of CD8+ T cells and sensitize MSS CRC to PD-1 blockade. Furthermore, DDR1 was found to facilitate kinase domain phosphorylation, upregulate EZH2, consequently elevating H3K27me3 levels at the CXCL10 promotor, which led to the suppression of CXCL10 transcription once bound to collagen in ECM. Lastly, DDR1 was found positively correlated with collagen I expression in MSS CRC specimens. These findings indicated that targeting DDR1 or its inhibitor 7rh might be potential strategy for overcoming immunotherapy resistance in MSS CRC. [ABSTRACT FROM AUTHOR]

Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single‐cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi‐omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer‐binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM. [ABSTRACT FROM AUTHOR]

Background: IDO1 and COX2 have emerged as promising immunotherapy targets. It is unclear whether IDO1 and COX2 expression levels in colorectal cancer (CRC) patients with liver oligometastases could be independent predictors of overall survival (OS) and progression-free survival (PFS). The purpose of this study was to investigate the correlation of IDO1 and COX2 expression levels with OS and PFS in CRC patients with liver oligometastases. Methods: The expression levels of IDO1 and COX2 were assessed by immunohistochemistry in 107 specimens from patients with liver oligometastases. The correlation between the expression of IDO1 and COX2 and the clinicopathological parameters and OS/PFS in patients was examined. Results: The expression level of IDO1/COX2 was significantly correlated with age and was not associated with gender, BMI, T stage, N stage, primary tumor size, liver metastasis size, CEA, CA19-9, CD3 TILs or CD8 TILs. In univariate analysis, we found that IDO1/COX2 expression, CEA and N stage all yielded significantly poor OS and PFS outcomes. In our multivariate Cox model, IDO1/COX2 coexpression, CEA and N stage were found to be significantly correlated with OS; IDO1/COX2 coexpression and CEA were significantly correlated with PFS. Conclusions: IDO1/COX2 coexpression plays a pivotal role and may act as a potential prognostic biomarker for survival in CRC patients with liver oligometastases. [ABSTRACT FROM AUTHOR]

The use of vaccines for cancer therapy is a promising immunotherapeutic strategy that has been shown to be effective against various cancers. Vaccines directly target tumors but their efficacy against glioblastoma multiforme (GBM) remains unclear. Immunotyping that classifies tumor samples is considered to be a biomarker for immunotherapy. This study aimed to identify potential GBM antigens suitable for vaccine development and develop a tool to predict the response of GBM patients to vaccination based on the immunotype. Gene Expression Profiling Interactive Analysis (GEPIA) was applied to evaluate the expression profile of GBM antigens and their influence on clinical prognosis, while the cBioPortal program was utilized to integrate and analyze genetic alterations. The correlation between antigens and antigen processing cells was assessed using TIMER. RNA-seq data of GBM samples and their corresponding clinical data were downloaded from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) for further clustering analysis. Six overexpressed and mutated tumor antigens (ARHGAP9, ARHGAP30, CLEC7A, MAN2B1, ARPC1B and PLB1) were highly correlated with the survival rate of GBM patients and the infiltration of antigen presenting cells in GBMs. With distinct cellular and molecular characteristics, three immune subtypes (IS1-IS3) of GBMs were identified and GBMs from IS3 subtype were more likely to benefit from vaccination. Through graph learning-based dimensional reduction, immune landscape was depicted and revealed the existence of heterogeneity among individual GBM patients. Finally, WGCNA can identify potential vaccination biomarkers by clustering immune related genes. In summary, the six tumor antigens are potential targets for developing anti-GBMs mRNA vaccine, and the immunotypes can be used for evaluating vaccination response. [ABSTRACT FROM AUTHOR]

Purpose: The anti-inflammatory environment of glioma reduces the efficacy of immunotherapies. Therefore, it is vital to transform the immunosuppressive microenvironment of glioma into a pro-inflammatory environment. Sialic acid-binding immunoglobulin-type lectins (Siglecs) can serve as immune checkpoint targets that enhance the anti-tumor immune response. However, the roles of Siglecs in the glioma microenvironment are unknown. This study was conducted to identify targets to inhibit the anti-inflammatory environment to improve therapeutic outcomes in patients with glioma. Methods: We analyzed the regulatory effect of prognosis-related Siglecs identified from data available in The Cancer Genome Atlas database (TCGA) and China Glioma Genome Atlas Data portal on the immunosuppressive microenvironment of glioma. The effects of prognosis-related Siglecs on the glioma microenvironment were investigated by determining the Pearson correlation coefficients of the Siglecs in transcriptome data from the TCGA database. Results: Siglec-1, -9, -10, and -14 were closely associated with the prognosis of patients with glioma. The expression of these four Siglecs was significantly increased in the high-risk group and positively correlated with anti-inflammatory cytokine levels in the glioma microenvironment. Conclusion: Our study provides insights into the effects of prognosis-related Siglecs in glioma immunotherapy, suggesting that targeted prognosis-related Siglecs can modify the microenvironment of glioma and improve the sensitivity of patients with glioma to immunotherapy. [ABSTRACT FROM AUTHOR]