BMC Cancer (Jan 2023)

Clinical features and lipid metabolism genes as potential biomarkers in advanced lung cancer

  • María Merino Salvador,
  • Lara Paula Fernández,
  • Juan Moreno-Rubio,
  • Gonzalo Colmenarejo,
  • Enrique Casado,
  • Ana Ramírez de Molina,
  • María Sereno

DOI
https://doi.org/10.1186/s12885-023-10509-x
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 10

Abstract

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Abstract Background Lung cancer is one of the most lethal tumors with a poor survival rate even in those patients receiving new therapies. Metabolism is considered one of the hallmarks in carcinogenesis and lipid metabolism is emerging as a significant contributor to tumor metabolic reprogramming. We previously described a profile of some lipid metabolism related genes with potential prognostic value in advanced lung cancer. Aim To analyze clinical and pathological characteristics related to a specific metabolic lipid genomic signature from patients with advanced lung cancer and to define differential outcome. Methods Ninety samples from NSCLC (non-small cell lung cancer) and 61 from SCLC (small cell lung cancer) patients were obtained. We performed a survival analysis based on lipid metabolic genes expression and clinical characteristics. The primary end point of the study was the correlation between gene expression, clinical characteristics and survival. Results Clinical variables associated with overall survival (OS) in NSCLC patients were clinical stage, adenocarcinoma histology, Eastern Cooperative Oncology Group (ECOG), number and site of metastasis, plasma albumin levels and first-line treatment with platinum. As for SCLC patients, clinical variables that impacted OS were ECOG, number of metastasis locations, second-line treatment administration and Diabetes Mellitus (DM). None of them was associated with gene expression, indicating that alterations in lipid metabolism are independent molecular variables providing complementary information of lung cancer patient outcome. Conclusions Specific clinical features as well as the expression of lipid metabolism-related genes might be potential biomarkers with differential outcomes.

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