Quantitative Proteomics Profiling of Primary Lung Adenocarcinoma Tumors Reveals Functional Perturbations in Tumor Metabolism

In
this study, we have analyzed human primary lung adenocarcinoma
tumors using global mass spectrometry to elucidate the biological
mechanisms behind relapse post surgery. In total, we identified over
3000 proteins with high confidence. Supervised multivariate analysis
was used to select 132 proteins separating the prognostic groups.
Based on in-depth bioinformatics analysis, we hypothesized that the
tumors with poor prognosis had a higher glycolytic activity and HIF
activation. By measuring the bioenergetic cellular index of the tumors,
we could detect a higher dependency of glycolysis among the tumors
with poor prognosis. Further, we could also detect an up-regulation
of HIF1α mRNA expression in tumors with early relapse. Finally,
we selected three proteins that were upregulated in the poor prognosis
group (cathepsin D, ENO1, and VDAC1) to confirm that the proteins
indeed originated from the tumor and not from a stromal or inflammatory
component. Overall, these findings show how in-depth analysis of clinical
material can lead to an increased understanding of the molecular mechanisms
behind tumor progression.

在本项研究中，我们通过全球质谱分析对人类原发性肺腺癌肿瘤进行了深入研究，旨在阐明术后复发的生物学机制。总计，我们以高置信度鉴定出3000余种蛋白质。通过监督多元分析，我们选出了132种蛋白质，这些蛋白质能够区分预后组别。基于深入的生物信息学分析，我们提出假设，即预后不良的肿瘤具有更高的糖酵解活性和HIF激活。通过测量肿瘤的生物能量细胞指数，我们能够检测到预后不良肿瘤对糖酵解的更高依赖性。此外，我们还可以检测到早期复发肿瘤中HIF1α mRNA表达的上调。最终，我们从预后不良组中选择了三种上调的蛋白质（组织蛋白酶D、ENO1和VDAC1）以证实这些蛋白质确实源自肿瘤而非间质或炎症成分。总体而言，这些发现展示了深入分析临床材料如何有助于加深对肿瘤进展背后分子机制的理解。