The Role of Regulated Cell Death Genetic Signatures in Predicting Response to Targeted Therapy for Lung Cancer

سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 69

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شناسه ملی سند علمی:

ICGCS02_117

تاریخ نمایه سازی: 17 دی 1403

چکیده مقاله:

Lung cancer, especially lung adenocarcinoma (LUAD), is a leading cause of cancer-related mortality worldwide, with a median ۵-year survival rate of ۱۰–۲۰%. Predicting response to oncogene- and immune-targeted therapies for this cancer remains a challenge, as only a limited number of patients respond favorably to these therapeutic approaches. This is explained by the heterogenous nature of this tumor and the inevitable development of drug resistance in patients with lung cancer, highlighting the need for identifying response biomarkers. Recognizing the significant role of regulated cell death (RCD) in anti-cancer immunity, we aimed to review the genetic markers associated with RCD that may serve as predictors for targeted therapy response. RCD represents a genetically regulated form of cell death encompassing various mechanisms such as apoptosis, necroptosis, ferroptosis, pyroptosis, and others. . The implications of different RCD modalities in both treatment response and resistance in lung cancer have been widely explored. Recent studies have utilized large-scale genomic data as well as machine learning algorithms to develop and optimize predictive models, leading to the development of RCD indexes. These indexes consolidate expression data from key differentially expressed RCD-related genes to efficiently predict patient prognosis and treatment response. Furthermore, the performance of these signatures has been validated through clinical datasets and in-vitro investigations. One notable advancement is the introduction of a programmed cell death index (PCDI), which includes ۱۰ genes such as CHEK۲, KRT۱۸, and GAPDH. Elevated PCDI values are linked to poor clinical outcomes and an unfavorable anti-tumor immune profile characterized by diminished CD۸+ T cells, CD۴+ memory T cells, and myeloid dendritic cells. High PCDI scores also correlate with resistance to immune checkpoint inhibitors like anti-PD-L۱ and standard chemotherapeutic agents, while indicating potential sensitivity to oncogene-targeted therapies, including MET and EGFR inhibitors. Additionally, a cell death risk signature (CDRSig) comprising ۸ genes has been associated with reduced CD۸+ T cell infiltration during radiotherapy and anti-PD-L۱ treatment, suggesting lower sensitivity. Moreover, an RCD signature (RCD.Sig) was developed using seven machine learning algorithms across ۱۸ immune checkpoint inhibitor cohorts and further refined into a novel RCD survival-related signature (RCD.Sur.Sig) for predicting overall survival. The integration of cell death genetic signatures into clinical practice holds significant promise in moving towards personalized treatment approach and improving patient outcomes in lung cancer. These signatures serve as valuable prognostic indicators in guiding treatment decisions and provide valuable insights into resistance mechanisms, offering potential therapeutic targets.

نویسندگان

Sama Jabbaripour

Tehran University of Medical Sciences