The Tumour Vasculature as a Target to Modulate Leucocyte Trafficking

Zhao, Yang; Ting, Ka Ka; Coleman, Paul R.; Qi, Yanfei; Chen, Jinbiao; Vadas, Mathew A.; Gamble, Jennifer R.

doi:10.3390/cancers13071724

Cited by 11 publications

(6 citation statements)

References 221 publications

(173 reference statements)

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“… 37–39 We found that OAd-MUC16-BiTE promotes the secretion of pro-inflammatory factors by T cells and decreases anti-inflammatory factors. The increase in chemokine levels 40 and the normalization of blood vessels 41 promote the transport of T cells to the tumor. In line with this, we found that after OAd-MUC16-BiTE treatment, tumors expressed higher levels of chemokines and lower angiogenesis factor, which promotes more CTL infiltration.…”

Section: Discussionmentioning

confidence: 99%

Oncolytic adenovirus with MUC16-BiTE shows enhanced antitumor immune response by reversing the tumor microenvironment in PDX model of ovarian cancer

Wang

et al. 2022

OncoImmunology

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The improved survival rate of ovarian cancer (OC) is related to the action of infiltrating cytotoxic T lymphocytes (CTLs). Recently, oncolytic adenoviruses (OAds) have emerged as a key player in treating solid tumors; however, the immunosuppressive tumor microenvironment (TME) and the body-mediated antiviral immune response limit their therapeutic effect. In this study, we tested the hypothesis that bispecific T-cell engagers (BiTEs) could activate and redirect CTLs to increase the anti-tumor effect of OAds. We modified the parental OAd to express a MUC16-targeting BiTE antibody (OAd-MUC16-BiTE), which retained its oncolytic properties and replication ability in vitro. This BiTE secreted from infected tumor cells into the microenvironment binds to MUC16 on target cells and cross‐links them to CD3 on T cells, leading to activation, proliferation, and toxicity of T cells against MUC16+ tumor cells. In cell coculture assays, OAd-MUC16-BiTE–mediated oncolysis enhanced T-cell–mediated tumor cell killing and bystander effect. In ex vivo tumor cultures freshly derived from OC patients, OAd-MUC16-BiTE overcame the suppressed immune TME, achieving stronger toxicity than the parental virus. Moreover, in the cell-derived xenograft and patient-derived xenograft model, OAd-MUC16-BiTE showed stronger antitumor activity and increased the number of CTLs, compared with the parental virus. Further, we demonstrated that the OAd-MUC16-BiTE-mediated anti-tumor activity is related to the reversal of the TME and improved MHC I antigen presentation. Overall, our results show how arming OAds with BiTE can overcome limitations in oncolytic virotherapy, yielding a potent therapy that is ready for clinical assessment.

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Section: Discussionmentioning

confidence: 99%

Oncolytic adenovirus with MUC16-BiTE shows enhanced antitumor immune response by reversing the tumor microenvironment in PDX model of ovarian cancer

Wang

et al. 2022

OncoImmunology

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“…Infiltration of immune cells into the TME is known to influence tumour progression ( 19 ). A systematic analysis of the relationship between tumour immune infiltration and hub genes can throw light on the mechanism of tumour immune escape and facilitate the development of new biomarkers and therapeutic strategies.…”

Section: Methodsmentioning

confidence: 99%

Construction and Validation of a m7G-Related Gene-Based Prognostic Model for Gastric Cancer

Wang

Chen

et al. 2022

Front. Oncol.

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BackgroundGastric cancer (GC) is one of the most common malignant tumors of the digestive system. Chinese cases of GC account for about 40% of the global rate, with approximately 1.66 million people succumbing to the disease each year. Despite the progress made in the treatment of GC, most patients are diagnosed at an advanced stage due to the lack of obvious clinical symptoms in the early stages of GC, and their prognosis is still very poor. The m7G modification is one of the most common forms of base modification in post-transcriptional regulation, and it is widely distributed in the 5′ cap region of tRNA, rRNA, and eukaryotic mRNA.MethodsRNA sequencing data of GC were downloaded from The Cancer Genome Atlas. The differentially expressed m7G-related genes in normal and tumour tissues were determined, and the expression and prognostic value of m7G-related genes were systematically analysed. We then built models using the selected m7G-related genes with the help of machine learning methods.The model was then validated for prognostic value by combining the receiver operating characteristic curve (ROC) and forest plots. The model was then validated on an external dataset. Finally, quantitative real-time PCR (qPCR) was performed to detect gene expression levels in clinical gastric cancer and paraneoplastic tissue.ResultsThe model is able to determine the prognosis of GC samples quantitatively and accurately. The ROC analysis of model has an AUC of 0.761 and 0.714 for the 3-year overall survival (OS) in the training and validation sets, respectively. We determined a correlation between risk scores and immune cell infiltration and concluded that immune cell infiltration affects the prognosis of GC patients. NUDT10, METTL1, NUDT4, GEMIN5, EIF4E1B, and DCPS were identified as prognostic hub genes and potential therapeutic agents were identified based on these genes.ConclusionThe m7G-related gene-based prognostic model showed good prognostic discrimination. Understanding how m7G modification affect the infiltration of the tumor microenvironment (TME) cells will enable us to better understand the TME’s anti-tumor immune response, and hopefully guide more effective immunotherapy methods.

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“…These pathways play important roles in the immune and inflammatory responses, cell migration, proliferation, and survival, and are critical in cancer progression and metastasis. 30 – 32 Certain chemokines like CCL20, PI3K/Akt, and Ras have been shown to be involved in the progression of GPLs. 33 – 35 Overall, these intersecting genes may be involved in LGIN to GC progression by regulating immune cell activity and cancer-related pathways.…”

Section: Discussionmentioning

confidence: 99%

Identification of Immune Infiltrating Cell-Related Biomarkers in Early Gastric Cancer Progression

Ji,

Cai,

Jin

et al. 2024

Technol Cancer Res Treat

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Objectives Gastric cancer (GC) is one of the most prevalent malignancies worldwide, and early detection is crucial for improving patient survival rates. We aimed to identify immune infiltrating cell-related biomarkers in early gastric cancer (EGC) progression. Methods The GSE55696 and GSE130823 datasets with low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and EGC samples were downloaded from the Gene Expression Omnibus database to perform an observational study. Immune infiltration analysis was performed by single sample gene set enrichment analysis and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data. Weighted gene co-expression network analysis was used to explore the co-expression modules and genes, and further enrichment analysis was performed on these genes. A protein-protein interaction (PPI) network of these genes was constructed to identify biomarkers associated with EGC progression. Screened hub genes were validated by the rank sum test and reverse transcription quantitative polymerase chain reaction. Results Immune scores were significantly elevated in EGC samples compared to LGIN and HGIN samples. The green-yellow module exhibited the strongest correlation with both immune score and disease progression. The 87 genes within this module were associated with the chemokine signaling pathways, the PI3K-Akt signaling pathways, leukocyte transendothelial migration, and Ras signaling pathways. Through PPI network analysis, the hub genes identified were protein tyrosine phosphatase receptor-type C (PTPRC), pleckstrin, CD53, CD48, lymphocyte cytosolic protein 1 (LCP1), hematopoietic cell-specific Lyn substrate 1, IKAROS Family Zinc Finger 1, Bruton tyrosine kinase, and Vav guanine nucleotide exchange factor 1. Notably, CD48, LCP1, and PTPRC showed high expression levels in EGC samples, with the remaining hub genes demonstrating a similar expression trend. Conclusion This study identified 9 immune cell-related biomarkers that may be actively involved in the progression of EGC and serve as potential targets for GC diagnosis and treatment.

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The Tumour Vasculature as a Target to Modulate Leucocyte Trafficking

Cited by 11 publications

References 221 publications

Oncolytic adenovirus with MUC16-BiTE shows enhanced antitumor immune response by reversing the tumor microenvironment in PDX model of ovarian cancer

Oncolytic adenovirus with MUC16-BiTE shows enhanced antitumor immune response by reversing the tumor microenvironment in PDX model of ovarian cancer

Construction and Validation of a m7G-Related Gene-Based Prognostic Model for Gastric Cancer

Identification of Immune Infiltrating Cell-Related Biomarkers in Early Gastric Cancer Progression

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