Advances of DNA Damage Repair-Related Drugs and Combination With Immunotherapy in Tumor Treatment

Wang, Yumin; Duan, Meihan; Peng, Zhouying; Fan, Ruohao; He, Yuxiang; Zhang, Hua; Xiong, Wei; Jiang, Weihong

doi:10.3389/fimmu.2022.854730

Cited by 8 publications

(6 citation statements)

References 55 publications

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“…Meanwhile, the role of the DDR pathway in immunotherapy is being evidenced in increasing tumor types [39]. At present, although several reviews have demonstrated the influence of DDR on ICB and immune infiltration [16,[40][41][42][43][44], we illustrate this relationship using specific tumor microenvironment (TME) components. Hence, this work aims to identify, summarize and explore the existing mechanisms and effects of DDR on ICB, so as to facilitate an improved understanding of these specific interactions and the efficacy of related therapies.…”

Section: Introductionmentioning

confidence: 97%

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

Shi

Qin

Lin

et al. 2022

J Exp Clin Cancer Res

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As our understanding of the mechanisms of cancer treatment has increased, a growing number of studies demonstrate pathways through which DNA damage repair (DDR) affects the immune system. At the same time, the varied response of patients to immune checkpoint blockade (ICB) therapy has prompted the discovery of various predictive biomarkers and the study of combination therapy. Here, our investigation explores the interactions involved in combination therapy, accompanied by a review that summarizes currently identified and promising predictors of response to immune checkpoint inhibitors (ICIs) that are useful for classifying oncology patients. In addition, this work, which discusses immunogenicity and several components of the tumor immune microenvironment, serves to illustrate the mechanism by which higher response rates and improved efficacy of DDR inhibitors (DDRi) in combination with ICIs are achieved.

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Section: Introductionmentioning

confidence: 97%

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

Shi

Qin

Lin

et al. 2022

J Exp Clin Cancer Res

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“…Patients with hypermethylation may benefit more from a combination of targeted EMT therapy, such as inhibitors blocking upstream signaling pathways including TGFβ, EGFR, and ICI immunotherapy [ 35 ]. The combination of ICI immunotherapy and DNA damage repair-based drugs, such as temozolomide, polyadenosine diphosphate-ribose polymerase inhibitors, and cisplatin, may be more effective in patients with hypomethylation [ 36 ]. The methylation status of the PD-L1 promoter is a potential biomarker associated with immunotherapy response and therapy selection.…”

Section: Discussionmentioning

confidence: 99%

Analysis of PD-L1 promoter methylation combined with immunogenic context in pancreatic ductal adenocarcinoma

Chen,

Yu,

Chen

et al. 2024

Cancer Immunol Immunother

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Despite the successful application of programmed cell death ligand 1 (PD-L1)-blocking strategies in some types of cancers and well-established prognostic indicators in pancreatic ductal adenocarcinoma (PDAC), the biological and clinical implications of the methylation status of PD-L1/PD-L2 in PDAC remain largely unknown. Therefore, this study aimed to explore the biological role of PD-L1/PD-L2 methylation and its association with clinicopathological features, clinical outcomes, and the immune microenvironment by analyzing the data on PD-L1/PD-L2 methylation and mRNA expression in PDAC cohorts obtained from the Cancer Genome Atlas and International Cancer Genome Consortium. The correlation between PD-L1 promoter methylation and PD-L1 expression and survival was further validated in an independent validation cohort (Peking Union Medical College Hospital [PUMCH] cohort) using pyrosequencing and immunohistochemistry. These results demonstrated that hypomethylation of the PD-L1 promoter was strongly associated with upregulated PD-L1 expression and shorter overall survival in PDAC. Multivariate Cox regression analyses revealed that the PD-L1 promoter methylation was an independent prognostic factor. PD-L1 promoter hypomethylation and high expression were related to aggressive clinical phenotypes. Moreover, both PD-L1 and PD-L2 methylation correlated with immune cell infiltration and the expression of immune checkpoint genes. PD-L1 promoter methylation status was further validated as an independent prognostic biomarker in patients with PDAC using the PUMCH cohort. The prognostic significance of PD-L1 promoter methylation was more discriminative in tumors with perineural/lymphovascular invasion and distant metastasis than in those without perineural/lymphovascular invasion and distant metastasis. In summary, the methylation status of the PD-L1 promoter is a promising biomarker for survival outcomes, immune infiltration, and the potential immune benefits of immunotherapy in PDAC.

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“…This concept offers diverse patient populations, characterized by varying drug sensitivities, multiple opportunities to derive benefits from at least one drug. A thorough understanding of varied responses could reveal predictive indicators or biomarkers related to drug effects, allowing for more accurate utilization of current medications and leveraging the benefits of combined or synergistic effects.. [6]- [7] 1.1. Associated human genes/proteins X.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the research proposes that LncKRT16P6 might represent a promising treatment focus for managing tongue squamous cell carcinoma. [5][6][7][10][11][12] In the research conducted by D. Hu and D. V. Messadi, which explores the involvement of immune-related long non-coding RNA (lncRNA) signatures in tongue squamous cell carcinoma (TSCC), six immune-related signature lncRNAs, including FNDC1-IT1, were identified with prognostic significance in TSCC. The study determined that the risk score derived from the six-lncRNA model served as a crucial indicator of the survival rate.…”

Section: Introductionmentioning

confidence: 99%

“…Their survival is typically shortened due to a heightened risk of relapse following allogeneic transplantation. [5][6][7][18][19][20] The CASC18 gene shows heightened expression in tumors linked to tongue squamous cell carcinoma (TSCC), especially in instances where patients experience occult lymph node metastasis (OLNM). The study revealed a new regulatory axis, CASC18/miR-20a-3p/TGFB2 ceRNA, associated with OLNM in TSCC.…”

Section: Introductionmentioning

confidence: 99%

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Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol

Askari,

Kiaei,

Boush

et al. 2024

Preprint

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BackgroundTongue Neoplasms is a common form of malignancy, with squamous cell carcinoma of the tongue being the most frequently diagnosed type due to regular mechanical stimulation. Its prevalence remains on the rise among neoplastic cancer cases. Finding effective combinations of drugs to target the genetic and protein elements contributing to the development of Managing Tongue Neoplasms poses a difficulty owing to the intricate and varied nature of the ailment.MethodIn this research, we introduce a novel approach using Deep Modularity Networks (DMoN) to identify potential synergistic drug combinations for the condition, following the RAIN protocol. This procedure comprises three primary phases: First, employing Graph Neural Network (GNN) to propose drug combinations for treating the ailment by extracting embedding vectors of drugs and proteins from an extensive knowledge graph containing various biomedical data types, such as drug-protein interactions, gene expression, and drug-target interactions. Second, utilizing natural language processing to gather pertinent articles from clinical trials involving the previously recommended drugs. Finally, conducting network meta-analysis to evaluate the comparative efficacy of these drug combinations.ResultWe utilized our approach on a dataset containing drugs and genes as nodes, connected by edges indicating their associated p-values. Our DMoN model identified Cisplatin, Bleomycin, and Fluorouracil as the optimal drug combination for targeting the human genes/proteins associated with this cancer. Subsequent scrutiny of clinical trials and literature confirmed the validity of our findings. Additionally, network meta-analysis substantiated the efficacy of these medications concerning the pertinent genes.ConclusionThrough the utilization of DMoN as part of the RAIN protocol, our method introduces a fresh and effective way to suggest notable drug combinations for addressing proteins/genes linked to Tongue Neoplasms. This approach holds promise in assisting healthcare practitioners and researchers in pinpointing the best treatments for patients, as well as uncovering the fundamental mechanisms of the disease.HighlightsA new method using Deep Modularity Networks and the RAIN protocol can find the best drug combinations for treating Tongue Neoplasms, a common and deadly form of cancer.The method uses a Graph Neural Network to suggest drug pairings from a large knowledge graph of biomedical data, then searches for clinical trials and performs network meta-analysis to compare their effectiveness.The method discovered that Cisplatin, Bleomycin, and Fluorouracil are suitable drugs for targeting the genes/proteins involved in this cancer, and confirmed this finding with literature review and statistical analysis.The method offers a novel and powerful way to assist doctors and researchers in finding the optimal treatments for patients with Tongue Neoplasms, and to understand the underlying causes of the disease.Abstract Figure

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Advances of DNA Damage Repair-Related Drugs and Combination With Immunotherapy in Tumor Treatment

Cited by 8 publications

References 55 publications

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

Analysis of PD-L1 promoter methylation combined with immunogenic context in pancreatic ductal adenocarcinoma

Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol

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