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Charting the metabolic biogeography of the colorectum in cancer: challenging the right sided versus left sided classification
Molecular Cancer ( IF 27.7 ) Pub Date : 2024-09-28 , DOI: 10.1186/s12943-024-02133-5
Abhishek Jain, Montana T. Morris, Domenica Berardi, Trisha Arora, Xavier Domingo-Almenara, Philip B. Paty, Nicholas J. W. Rattray, Daniel Kerekes, Lingeng Lu, Sajid A. Khan, Caroline H. Johnson

Colorectal cancer (CRC) is conventionally classified as right sided, left sided, and rectal cancer. Clinicopathological, molecular features and risk factors do not change abruptly along the colorectum, and variations exist even within the refined subsites, which may contribute to inconsistencies in the identification of clinically relevant CRC biomarkers. We generated a CRC metabolome map to describe the association between metabolites, diagnostic and survival heterogeneity in cancers of different subsites of the colorectum. Utilizing 372 patient-matched tumor and normal mucosa tissues, liquid chromatography-mass spectrometry was applied to examine metabolomic profiles along seven subsites of the colorectum: cecum (n = 63), ascending colon (n = 44), transverse colon (n = 32), descending colon (n = 28), sigmoid colon (n = 75), rectosigmoid colon (n = 38), and rectum (n = 92). 39 and 70 significantly altered metabolites (including bile acids, lysophosphatidylcholines and lysophosphatidylethanolamines) among tumors and normal mucosa, respectively, showed inter-subsite metabolic heterogeneity between CRC subsites. Gradual changes in metabolite abundances with significantly linear trends from cecum to rectum were observed: 23 tumor-specific metabolites, 30 normal mucosa-specific metabolites, and 15 metabolites in both tumor and normal mucosa, had concentration gradients across the colorectum, and is disease status dependent. The metabolites that showed a linear trend included bile acids, amino acids, lysophosphatidylcholines, and lysophosphatidylethanolamines. Comparison of tumors to patient-matched normal mucosa revealed metabolite changes exclusive to each subsite, thereby further highlighting differences in cancer metabolism across the 7 subsites of the colorectum. Furthermore, metabolites associated with survival were different and unique to each subsite. Finally, an interactive and publicly accessible CRC metabolome database was designed to enable access and utilization of this rich data resource ( https://colorectal-cancer-metabolome.com/yale-university ). Gradual changes exist in metabolite abundances from the cecum to the rectum. The association between patient survival and distinct metabolites with anatomic subsite of the colorectum, reveals differences between cancers across the colorectum. These inter-subsite metabolic heterogeneities enrich the current understanding and substantiate previous studies that have challenged the conventional classification of right-sided, left-sided, and rectal cancers, by identifying specific metabolites that offer new biological insights into CRC subsite heterogeneity. The database designed in this study will enable researchers to delve into granular information on the CRC metabolome, which until now has not been available.

中文翻译:


绘制癌症结直肠代谢生物地理学图:挑战右侧与左侧分类



结直肠癌(CRC)通常分为右侧癌、左侧癌和直肠癌。临床病理学、分子特征和危险因素不会沿着结直肠突然改变,甚至在细化的亚位点内也存在变化,这可能导致临床相关结直肠癌生物标志物鉴定的不一致。我们生成了 CRC 代谢组图来描述结直肠不同亚位点癌症中代谢物、诊断和生存异质性之间的关联。利用 372 例患者匹配的肿瘤和正常粘膜组织,采用液相色谱-质谱法检查结肠直肠七个亚位点的代谢组学特征:盲肠 (n = 63)、升结肠 (n = 44)、横结肠 (n = 32) )、降结肠(n = 28)、乙状结肠(n = 75)、直肠乙状结肠(n = 38)和直肠(n = 92)。 39 和 70 分别在肿瘤和正常粘膜中显着改变的代谢物(包括胆汁酸、溶血磷脂酰胆碱和溶血磷脂酰乙醇胺),显示出 CRC 亚位点之间的亚位点间代谢异质性。观察到从盲肠到直肠代谢物丰度的逐渐变化,具有显着线性趋势:23种肿瘤特异性代谢物、30种正常粘膜特异性代谢物以及肿瘤和正常粘膜中的15种代谢物,在整个结直肠中具有浓度梯度,并且是疾病状态依赖。显示线性趋势的代谢物包括胆汁酸、氨基酸、溶血磷脂酰胆碱和溶血磷脂酰乙醇胺。将肿瘤与患者匹配的正常粘膜进行比较,揭示了每个亚位点独有的代谢变化,从而进一步突出了结直肠 7 个亚位点的癌症代谢差异。 此外,与生存相关的代谢物对于每个亚位点来说都是不同且独特的。最后,设计了一个交互式且可公开访问的 CRC 代谢组数据库,以便能够访问和利用这一丰富的数据资源 (https://colorectal-cancer-metabolome.com/yale-university)。从盲肠到直肠,代谢物丰度存在逐渐变化。患者生存率和不同代谢物与结直肠解剖亚位点之间的关联揭示了结直肠癌症之间的差异。这些子位点间代谢异质性丰富了当前的理解,并证实了之前的研究,这些研究挑战了右侧、左侧和直肠癌的传统分类,通过识别特定的代谢物,为CRC亚位点异质性提供了新的生物学见解。本研究设计的数据库将使研究人员能够深入研究 CRC 代谢组的详细信息,而这些信息迄今为止尚未获得。
更新日期:2024-09-28
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