MiR-375 promotes cisplatin sensitivity of lung adenocarcinoma

Du, Shuomeng; Qu, Han; Zhang, Ying; Zhu, Shihao; Wang, Yan; Zhang, Shuopeng; Wang, Zhao; Yang, Qian; Fu, Songbin; Dong, Kai

doi:10.1016/j.prp.2023.154765

Cited by 1 publication

(1 citation statement)

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“…showed that ASCL1 is expressed in 8% of lung adenocarcinomas, which plays a tumor-promoting role ( 39 ) and could partially explain the upregulation of miR-375 in the plasma of some NSCLC patients ( 34 ). Conversely, a recent paper showed that miR-375 is often downregulated in NSCLC tissues compared to adjacent tissues ( 40 ), and that the overexpression of this miRNA induces cisplatin sensitivity in lung adenocarcinoma cell lines ( 41 ).…”

Section: Discussionmentioning

confidence: 99%

A plasma miRNA-based classifier for small cell lung cancer diagnosis

Saviana,

Romano,

McElroy

et al. 2023

Front. Oncol.

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IntroductionSmall cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based classifier to assist in SCLC diagnoses.MethodsWe profiled deregulated circulating cell-free miRNAs in the plasma of SCLC patients. We tested selected miRNAs on a training cohort and created a classifier by integrating miRNA expression and patients’ clinical data. Finally, we applied the classifier on a validation dataset.ResultsWe determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group.DiscussionThis study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

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