Pachimatla Akhil Goud, Gee Kaylan, Hsiao Hua-Hsin, Yendamuri Sai, Rosario Spencer
Department of Thoracic Surgery, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA.
Ann Surg Oncol. 2025 Mar;32(3):1628-1634. doi: 10.1245/s10434-024-16402-6. Epub 2024 Dec 13.
Studies suggest that the obesity paradox in non-small cell lung cancer (NSCLC) results from the use of body mass index (BMI) as a measure of obesity. However, the mechanistic basis linking body fat and lung cancer behavior remains unclear. We examined the association of image-based measures of obesity with tumor gene expression to identify transcriptional signatures concordant with adiposity and their underlying biology.
RNA-sequencing data for 143 NSCLC tumor samples generated by the ORIEN consortium was compiled with image-based measurements of total fat. Total fat area (TFA) was quantified at the third lumbar vertebra level using computed tomography images and the SliceOmatic software. Differential gene expression analysis was conducted between patients in the highest and lowest TFA tertiles. Utilizing a validated metabolic analysis pipeline, these differences in gene expression were used to enrich dysregulated metabolic pathways crucial in carcinogenesis.
We identified 1154 gene transcripts as differentially expressed (p ≤ 0.05 and log fold change ≥ 0.58) in metabolic pathways of normal physiology as well as cancer growth. Utilizing the metabolic pipeline, we found 58/114 metabolic pathways were significantly enriched (p ≤ 0.05) in the high TFA individuals, some of which are expected in obese individuals (lipids metabolism), and some were novel. Gene set enrichment analysis (GSEA) identified transcriptional alterations to inflammatory mediation, cell-signaling, and cellular respiration pathways based on TFA.
Image-based measures of adiposity correlate with significant gene expression changes in NSCLC tumors. We have identified altered biological processes associated with obesity, including metabolic vulnerabilities, that can be leveraged in developing new treatment strategies.
研究表明，非小细胞肺癌（NSCLC）中的肥胖悖论是由于使用体重指数（BMI）作为肥胖的衡量指标所致。然而，将体脂与肺癌行为联系起来的机制基础仍不清楚。我们研究了基于图像的肥胖测量指标与肿瘤基因表达之间的关联，以确定与肥胖及其潜在生物学特性一致的转录特征。
将ORIEN联盟生成的143例NSCLC肿瘤样本的RNA测序数据与基于图像的总脂肪测量数据进行整合。使用计算机断层扫描图像和SliceOmatic软件在第三腰椎水平对总脂肪面积（TFA）进行量化。对TFA三分位数最高和最低的患者进行差异基因表达分析。利用经过验证的代谢分析流程，这些基因表达差异被用于富集在致癌过程中起关键作用的失调代谢途径。
我们在正常生理以及癌症生长的代谢途径中鉴定出1154个基因转录本差异表达（p≤0.05且对数变化倍数≥0.58）。利用代谢流程，我们发现58/114条代谢途径在高TFA个体中显著富集（p≤0.05），其中一些在肥胖个体中是预期的（脂质代谢），还有一些是新发现的。基因集富集分析（GSEA）基于TFA确定了炎症介导、细胞信号传导和细胞呼吸途径的转录改变。
基于图像的肥胖测量指标与NSCLC肿瘤中显著的基因表达变化相关。我们已经确定了与肥胖相关的生物学过程改变，包括代谢脆弱性，这可用于开发新的治疗策略。
