ArticleAnnals of translational medicine2020
Myeloid cell leukemia-1 is an important predictor of survival and progression of small cell lung cancer.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors at 3 institutions in 1 country.
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Abstract
backgroundSmall cell lung cancer (SCLC) is the most fatal malignancy for which more effective therapies are urgently needed. Overexpression of myeloid cell leukemia-1 (Mcl-1) has been demonstrated to be one of the most common genetic alterations among different types of tumor/cancer, which induces resistance against various anti-cancer therapies including cisplatin. The study aimed to explore the role of Mcl-1 in the prognosis and resistance to anti-cancer therapy in patients with SCLC.
methodsPatients with SCLC were recruited from those enrolled/treated in Sun Yat-sen University Cancer Center. Their specimens were collected for immunohistochemical evaluation. We compared the baseline characteristics, response to chemotherapy and overall survival (OS) of the patients with different expression levels of Mcl-1.
resultsThe expression level of Mcl-1 was significantly lower in patients with limited stage SCLC than in those with extensive stage SCLC (P=0.014). Based on the median value of Mcl-1 expression level, the patients were divided into high and low Mcl-1 groups, respectively. Univariate analysis revealed that low Mcl-1 expression was associated with a significant improvement in OS, with a hazard ratio (HR) of 0.538. Multivariate analysis confirmed the independent prognostic value of Mcl-1 expression level (P=0.014). Moreover, we found a significantly close relationship between higher Mcl-1 expression level and shorter time to progression (TTP) of the patients received chemotherapy (P=0.040).
conclusionsOur findings demonstrated that Mcl-1 expression level was a prognostic biomarker for survival outcomes and cancer progression in the patients with SCLC. Thus, it could be used as a valuable biomarker in identifying those patients with high risk of treatment failure.
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