Cancer Biomarkers Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, United States.
Institute for Systems Biology, Seattle, Washington, United States.
J Proteome Res. 2020 May 1;19(5):1900-1912. doi: 10.1021/acs.jproteome.0c00021. Epub 2020 Apr 2.
A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of -dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.
美国国家癌症研究所(NCI)召开了一次智库会议,征求专家对多组学单细胞分析,特别是单细胞蛋白质组学的发展和应用的意见,以改善新一代癌症风险、早期检测、诊断和预后的生物标志物的开发,并讨论预防和治疗新靶点的发现。预计这些标志物和靶点将基于病变内和单个细胞内的细胞、亚细胞、分子和功能异常。单细胞蛋白质组学数据对于建立具有可搜索和可扩展功能的新工具至关重要,这些工具包括癌前和恶性病变的时空图谱。讨论中包括的挑战和潜在解决方案包括:(i)从新鲜和保存的组织中分析单细胞的最佳方法/途径;(ii)从单细胞,特别是从组织切片中检测和分析分泌分子;(iii)在癌前和早期癌症组织微环境中检测新的、以前未记录的细胞类型;(iv)多组学数据的整合,以支持和告知蛋白质组测量;(v)亚细胞细胞器-在单个癌前和恶性细胞内识别异常结构、功能、分布和位置;(vi)如何提高单细胞蛋白质组学测量的动态范围,以发现差异表达的蛋白质及其翻译后修饰(PTM);(vii)使用单细胞技术同时测量的深度;(viii)定量-绝对或半定量?(ix)单一方法或多重组合?(x)应用分析方法鉴定具有生物学意义的亚群;(xi)多维数据集的可视化;(xii)如何在癌前肿瘤微环境(TME)中的单个细胞内构建细胞间信号网络;(xiii)内在细胞过程与外在刺激之间的关联;(xiv)如何预测细胞对应激诱导刺激的反应;(xv)基于单个细胞内的时空变化,鉴定新的标志物,以预测从前体、良性和局部病变进展为浸润性癌症;(xvi)鉴定新的免疫预防或免疫治疗靶点-鉴定单个细胞内的新抗原和表面蛋白组。