Sense and anti-sense: Role of FAM83A and FAM83A-AS1 in Wnt, EGFR, PI3K, EMT pathways and tumor progression

Zhao, Chenshu; Li, Xiaowen; Zhang, Rui; Lyu, Hao; Xiao, Shuai; Guo, Dong; Ali, Declan William; Michalak, Marek; Chen, Xing-Zhen; Zhou, Cefan; Tang, Jingfeng

doi:10.1016/j.biopha.2024.116372

Cited by 6 publications

(1 citation statement)

References 110 publications

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“…FAM83A, found on chromosome 8q24 and overexpressed in various cancers, impacts lung adenocarcinoma through the Wnt/β-catenin signaling pathway and is linked to PD-L1 expression, affecting immune responses in cancer therapy 42 . Additionally, FAM83A’s expression is further promoted by the antisense RNA FAM83A-AS1, enhancing lung cancer cell growth 43 . KRT6A, a type II keratin involved in the epidermalization of squamous epithelium, plays a critical role in cell migration and cancer metastasis.…”

Section: Discussionmentioning

confidence: 99%

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures

Sui,

Liu,

Zhong

et al. 2024

Sci Rep

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In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model’s utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

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Section: Discussionmentioning

confidence: 99%