Cancer detection and biopsy classification using concurrent histopathological and metabolomic analysis of core biopsies.
Cancer detection and biopsy classification using concurrent histopathological and metabolomic analysis of core biopsies.
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DOI：
10.1186/gm332
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发表时间：
2012-04-30
期刊：
影响因子：
12.3
通讯作者：
Lawton KA
中科院分区：
文献类型：
--
作者：
Brown MV;McDunn JE;Gunst PR;Smith EM;Milburn MV;Troyer DA;Lawton KA
代谢组学，即对生物样本中小分子的非靶向询问，是识别诊断生物标记物的理想技术。目前的组织提取方案涉及销毁样本，排除了组织的额外用途。这对于可获得性有限的高价值样本来说尤其成问题，例如临床肿瘤活检需要结构保存来从组织学上诊断和衡量癌症的侵袭性。为了克服这一局限，增加从患者活检中获得的信息量，我们开发并表征了一种对同一活检样本进行代谢分析和组织学评估的工作流程。10个人体组织(肌肉、肾上腺、结肠、肺、胰腺、小肠、脾、胃、前列腺、肾脏)的活检标本被直接放置在甲醇溶液中，以回收代谢物、沉淀蛋白质和固定组织。孵育后，从溶液中取出活检组织并进行组织学检查。肾癌、前列腺癌、肿瘤及良性活检组织行苏木精-伊红染色，前列腺活检组织行PIN-4免疫组织化学染色。甲醇提取物在GC/MS和LC/MS平台上分析代谢物。使用包括峰鉴定和代谢物鉴定软件的信息系统自动提取原始质谱学数据文件。所有主要生化类别的代谢物(氨基酸、多肽、碳水化合物、脂类、核苷酸、辅因子、外源生物)都进行了测量。代谢物的数量(从前列腺的260到结肠的340)和同一性与目前需要30毫克研磨组织的方法获得的结果相当。比较代谢产物的相对水平，可以区分良性肾组织和前列腺癌组织中的肿瘤。苏木精-伊红染色和抗体结合(PIN-4，在前列腺中)的成功组织病理学分析表明，细胞构筑和免疫反应被保留。同时进行代谢物提取和完整活检的组织学分析是符合临床工作流程的。甲醇固定有效地保存了广泛的组织，并与化学染色和免疫组织化学相兼容。该方法提供了在同一组织样本中通过生物化学的定量测量来加强组织病理学诊断和肿瘤分类的机会。由于某些生物化学物质已被证明与疾病侵袭性相关，这种方法应该被证明是区分癌症侵袭性的一个有价值的辅助手段。
Metabolomics, the non-targeted interrogation of small molecules in a biological sample, is an ideal technology for identifying diagnostic biomarkers. Current tissue extraction protocols involve sample destruction, precluding additional uses of the tissue. This is particularly problematic for high value samples with limited availability, such as clinical tumor biopsies that require structural preservation to histologically diagnose and gauge cancer aggressiveness. To overcome this limitation and increase the amount of information obtained from patient biopsies, we developed and characterized a workflow to perform metabolomic analysis and histological evaluation on the same biopsy sample. Biopsies of ten human tissues (muscle, adrenal gland, colon, lung, pancreas, small intestine, spleen, stomach, prostate, kidney) were placed directly in a methanol solution to recover metabolites, precipitate proteins, and fix tissue. Following incubation, biopsies were removed from the solution and processed for histology. Kidney and prostate cancer tumor and benign biopsies were stained with hemotoxylin and eosin and prostate biopsies were subjected to PIN-4 immunohistochemistry. The methanolic extracts were analyzed for metabolites on GC/MS and LC/MS platforms. Raw mass spectrometry data files were automatically extracted using an informatics system that includes peak identification and metabolite identification software. Metabolites across all major biochemical classes (amino acids, peptides, carbohydrates, lipids, nucleotides, cofactors, xenobiotics) were measured. The number (ranging from 260 in prostate to 340 in colon) and identity of metabolites were comparable to results obtained with the current method requiring 30 mg ground tissue. Comparing relative levels of metabolites, cancer tumor from benign kidney and prostate biopsies could be distinguished. Successful histopathological analysis of biopsies by chemical staining (hematoxylin, eosin) and antibody binding (PIN-4, in prostate) showed cellular architecture and immunoreactivity were retained. Concurrent metabolite extraction and histological analysis of intact biopsies is amenable to the clinical workflow. Methanol fixation effectively preserves a wide range of tissues and is compatible with chemical staining and immunohistochemistry. The method offers an opportunity to augment histopathological diagnosis and tumor classification with quantitative measures of biochemicals in the same tissue sample. Since certain biochemicals have been shown to correlate with disease aggressiveness, this method should prove valuable as an adjunct to differentiate cancer aggressiveness.
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影响因子：
64.8
作者：
Sreekumar, Arun;Poisson, Laila M.;Rajendiran, Thekkelnaycke M.;Khan, Amjad P.;Cao, Qi;Yu, Jindan;Laxman, Bharathi;Mehra, Rohit;Lonigro, Robert J.;Li, Yong;Nyati, Mukesh K.;Ahsan, Aarif;Kalyana-Sundaram, Shanker;Han, Bo;Cao, Xuhong;Byun, Jaeman;Omenn, Gilbert S.;Ghosh, Debashis;Pennathur, Subramaniam;Alexander, Danny C.;Berger, Alvin;Shuster, Jeffrey R.;Wei, John T.;Varambally, Sooryanarayana;Beecher, Christopher;Chinnaiyan, Arul M.
通讯作者：
Chinnaiyan, Arul M.
影响因子：
37.3
作者：
Denkert C;Budczies J;Weichert W;Wohlgemuth G;Scholz M;Kind T;Niesporek S;Noske A;Buckendahl A;Dietel M;Fiehn O
通讯作者：
Fiehn O
影响因子：
2.6
作者：
Iczkowski, Kenneth A;Lucia, M Scott
通讯作者：
Lucia, M Scott
影响因子：
23.4
作者：
Cohen, Michael S.;Hanley, Robert S.;Libertino, John A.
通讯作者：
Libertino, John A.
影响因子：
3.7
作者：
Thysell E;Surowiec I;Hörnberg E;Crnalic S;Widmark A;Johansson AI;Stattin P;Bergh A;Moritz T;Antti H;Wikström P
通讯作者：
Wikström P