bims-meluca Biomed News
on Metabolism of non-small cell lung carcinoma
Issue of 2024–04–07
two papers selected by
the Muñoz-Pinedo/Nadal (PReTT) lab, L’Institut d’Investigació Biomèdica de Bellvitge



  1. Front Oncol. 2024 ;14 1277206
       Background: Metabolic reprogramming plays a significant role in the advancement of lung adenocarcinoma (LUAD), yet the precise metabolic changes remain incompletely understood. This study aims to uncover metabolic indicators associated with the progression of LUAD.
    Methods: A total of 1083 subjects were recruited, including 670 LUAD, 135 benign lung nodules (BLN) and 278 healthy controls (HC). Gas chromatography-mass spectrometry (GC/MS) was used to identify and quantify plasma metabolites. Odds ratios (ORs) were calculated to determine LUAD risk factors, and machine learning algorithms were utilized to differentiate LUAD from BLN.
    Results: High levels of oxalate, glycolate, glycine, glyceric acid, aminomalonic acid, and creatinine were identified as risk factors for LUAD (adjusted ORs>1.2, P<0.03). Remarkably, oxalate emerged as a distinctive metabolic risk factor exhibiting a strong correlation with the progression of LUAD (adjusted OR=5.107, P<0.001; advanced-stage vs. early-stage). The Random Forest (RF) model demonstrated a high degree of efficacy in distinguishing between LUAD and BLN (accuracy = 1.00 and 0.73, F1-score= 1.00 and 0.79, and AUC = 1.00 and 0.76 in the training and validation sets, respectively). TCGA and GTEx gene expression data have shown that lactate dehydrogenase A (LDHA), a crucial enzyme involved in oxalate metabolism, is increasingly expressed in the progression of LUAD. High LDHA expression levels in LUAD patients are also linked to poor prognoses (HR=1.66, 95% CI=1.34-2.07, P<0.001).
    Conclusions: This study reveals risk factors associated with LUAD.
    Keywords:  LDHA; LUAD; metabolomics; oxalate; risk factor
    DOI:  https://doi.org/10.3389/fonc.2024.1277206
  2. Eur Rev Med Pharmacol Sci. 2024 Mar;pii: 35741. [Epub ahead of print]28(6): 2340-2350
       OBJECTIVE: The relationship between inflammatory markers and survival in many cancers has been investigated previously. Inflammatory markers may also offer the possibility of predicting surveillance in patients with malignant mesothelioma. Our study seeks to enhance comprehension of how variables such as the nutritional status and inflammation indices of malignant mesothelioma patients impact the disease's progression and prognosis.
    PATIENTS AND METHODS: This study included patients who were treated at the Erciyes University Medical Oncology Clinic between 2010 and 2022 and diagnosed with malignant mesothelioma. This is a retrospective single-center cohort study. Receiver Operating Characteristic (ROC) analysis was applied to determine the inflammation markers' optimal cut-off values with high sensitivity and specificity. Patients were categorized based on these values. The differences in overall survival (OS) and progression-free survival (PFS) between categorized groups were assessed using Log-rank curves and Kaplan-Meier tests. Multivariate analysis was performed using Cox regression analysis on statistically significant data. The relationship between inflammation markers and malignant mesothelioma survival was evaluated.
    RESULTS: There are 115 patients in this study. Pre-treatment high neutrophil to lymphocyte ratio (NLR) (HR: 1.34, 95% CI: 1.12-2.83, p=0.04), high pan-immune inflammation value (PIIV) (HR: 2.01, 95% CI: 1.32-4.79, p=0.03), and high systemic inflammation response index (SIRI) (HR: 1.34, 95% CI: 1.2-2.78, p=0.04) were associated with poor OS. Conversely, high advanced lung cancer inflammation index (ALI) (HR: 0.73, 95% CI: 0.53-0.84, p=0.03) and high hemoglobin-albumin-lymphocyte and platelet (HALP) (HR: 0.67, 95% CI: 0.23-0.78, p=0.02) were associated with favorable survival.
    CONCLUSIONS: Our study investigated the prognostic value of various inflammation markers in malignant mesothelioma patients and suggests that composite formulas like NLR, PIIV, SIRI, ALI, and HALP that incorporate CBC cells and nutritional parameters like albumin, height, and weight could more consistently and accurately predict malignant mesothelioma prognosis.
    DOI:  https://doi.org/10.26355/eurrev_202403_35741