PARP Inhibitors in Melanoma-An Expanding Therapeutic Option?
Cancers(2021)SCI 2区SCI 3区
Abstract
Immunotherapy has transformed the treatment landscape of melanoma; however, despite improvements in patient outcomes, monotherapy can often lead to resistance and tumour escape. Therefore, there is a need for new therapies, combination strategies and biomarker-guided decision making to increase the subset of patients most likely to benefit from treatment. Poly (ADP-ribose) polymerase (PARP) inhibitors act by synthetic lethality to target tumour cells with homologous recombination deficiencies such as BRCA mutations. However, the application of PARP inhibitors could be extended to a broad range of BRCA-negative cancers with high rates of DNA damage repair pathway mutations, such as melanoma. Additionally, PARP inhibition has the potential to augment the therapeutic effect of immunotherapy through multi-faceted immune-priming capabilities. In this review, we detail the immunological role of PARP and rationale for combining PARP and immune checkpoint inhibitors, with a particular focus on a subset of melanoma with homologous recombination defects that may benefit most from this targeted approach. We summarise the biology supporting this combined regimen and discuss preclinical results as well as ongoing clinical trials in melanoma which may impact future treatment.
MoreTranslated text
Key words
melanoma,PARP inhibitor,immunotherapy,DNA damage response,homologous recombination,combination therapy
PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Prognostic Biomarkers in Uveal Melanoma: The Status Quo, Recent Advances and Future Directions
CANCERS 2022
被引用26
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK 2023
被引用1
CANCER RESEARCH 2023
被引用2
Germline Cancer Susceptibility in Individuals with Melanoma
JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY 2024
被引用0
Efficacy of PARP Inhibitor Therapy after Targeted BRAF/MEK Failure in Advanced Melanoma
npj Precision Oncology 2024
被引用0
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话