Cheng Ting-Yuan David, Fu Dongtao Ann, Falzarano Sara M, Zhang Runzhi, Datta Susmita, Zhang Weizhou, Omilian Angela R, Aduse-Poku Livingstone, Bian Jiang, Irianto Jerome, Asirvatham Jaya Ruth, Campbell-Thompson Martha
Division of Cancer Prevention and Control, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH 43201, USA.
Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32611, USA.
Int J Mol Sci. 2024 Dec 14;25(24):13428. doi: 10.3390/ijms252413428.
This hypothesis-generating study aims to examine the extent to which computed tomography-assessed body composition phenotypes are associated with immune and phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathways in breast tumors. A total of 52 patients with newly diagnosed breast cancer were classified into four body composition types: adequate (lowest two tertiles of total adipose tissue [TAT]) and highest two tertiles of total skeletal muscle [TSM] areas); high adiposity (highest tertile of TAT and highest two tertiles of TSM); low muscle (lowest tertile of TSM and lowest two tertiles of TAT); and high adiposity with low muscle (highest tertile of TAT and lowest tertile of TSM). Immune and PI3K/AKT pathway proteins were profiled in tumor epithelium and the leukocyte-enriched stromal microenvironment using GeoMx (NanoString). Linear mixed models were used to compare log2-transformed protein levels. Compared with the normal type, the low muscle type was associated with higher expression of INPP4B (log2-fold change = 1.14, = 0.0003, false discovery rate = 0.028). Other significant associations included low muscle type with increased CTLA4 and decreased pan-AKT expression in tumor epithelium, and high adiposity with increased CD3, CD8, CD20, and CD45RO expression in stroma ( < 0.05; false discovery rate > 0.2). With confirmation, body composition can be associated with signaling pathways in distinct components of breast tumors, highlighting the potential utility of body composition in informing tumor biology and therapy efficacies.
这项产生假设的研究旨在探讨计算机断层扫描评估的身体成分表型与乳腺肿瘤中的免疫和磷酸肌醇3激酶（PI3K）/蛋白激酶B（AKT）信号通路之间的关联程度。共有52例新诊断的乳腺癌患者被分为四种身体成分类型：正常型（总脂肪组织[TAT]最低的两个三分位数和总骨骼肌[TSM]面积最高的两个三分位数）；高肥胖型（TAT最高的三分位数和TSM最高的两个三分位数）；低肌肉型（TSM最低的三分位数和TAT最低的两个三分位数）；以及高肥胖伴低肌肉型（TAT最高的三分位数和TSM最低的三分位数）。使用GeoMx（NanoString）对肿瘤上皮和富含白细胞的基质微环境中的免疫和PI3K/AKT通路蛋白进行分析。采用线性混合模型比较log2转换后的蛋白水平。与正常型相比，低肌肉型与INPP4B的高表达相关（log2倍变化=1.14，P=0.0003，错误发现率=0.028）。其他显著关联包括低肌肉型与肿瘤上皮中CTLA4增加和泛AKT表达降低相关，以及高肥胖型与基质中CD3、CD8、CD20和CD45RO表达增加相关（P<0.05；错误发现率>0.2）。经证实，身体成分可能与乳腺肿瘤不同成分中的信号通路相关，这突出了身体成分在了解肿瘤生物学和治疗疗效方面的潜在效用。
