The Clinical Proteomic Tumor Analysis Consortium Lung Adenocarcinoma Collection

<p>This collection contains subjects from the National Cancer Institute’s <u><a href="https://proteomics.cancer.gov/programs/cptac">Clinical Proteomic Tumor Analysis Consortium</a></u> Lung Adenocarcinoma (CPTAC-LUAD) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data.</p><p>Imaging from each cancer type will be contained in its own TCIA Collection, with the collection name "CPTAC-<em>cancertype</em>".  Radiology imaging is collected from standard of care imaging performed on patients immediately before the pathological diagnosis, and from follow-up scans where available.  For this reason the radiology image data sets are heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. Pathology imaging is collected as part of the CPTAC qualification workflow.  </p><p>All CPTAC cohorts are released as either a single combined cohort, or split into <em>Discovery</em> and <em>Confirmatory</em> where applicable.  There are two main types of proteomic studies: discovery proteomics and targeted proteomics. The term "discovery proteomics" is in reference to "untargeted" identification and quantification of a maximal number of proteins in a biological or clinical sample. The term “targeted proteomics” refers to quantitative measurements on a defined subset of total proteins in a biological or clinical sample, often following the completion of discovery proteomics studies to confirm interesting targets selected. Commonly used proteomic technologies and platforms are different types of mass spectrometry and protein microarrays depending on the needs, throughput and sample input requirement of an analysis, with further development on nanotechnologies and automation in the pipeline in order to improve the detection of low abundance proteins, increase throughput, and selectively reach a target protein <em>in vivo</em>.  Once the protein targets of interest are identified, high-throughput targeted assays are developed for confirmatory studies: tests to affirm that the initial tests were accurate. A summary of CPTAC imaging efforts can be found on the <u><a href="https://wiki.cancerimagingarchive.net/display/Public/CPTAC+Imaging+Proteomics">CPTAC Imaging Proteomics</a></u> page. </p><h3>CPTAC Imaging Special Interest Group</h3><p>You can join the <a href="https://groups.google.com/forum/#!forum/cptac-imaging-sig">CPTAC Imaging Special Interest Group </a>to be notified of webinars & data releases, collaborate on common data wrangling tasks and seek out partners to explore research hypotheses!  Artifacts from previous webinars such as slide decks and video recordings can be found on the <a href="https://wiki.cancerimagingarchive.net/display/Public/CPTAC+SIG+Webinars">CPTAC SIG Webinars</a> page.</p><p><iframe src="https://player.vimeo.com/video/441014255" frameborder="0" allowfullscreen="allowfullscreen"></iframe></p><p>On July 22, 2020 Shankha Satpathy presented about the consortium's proteogenomic analyses of CPTAC-LUAD.  This deep dive into the LUAD genomic and proteomic datasets will help researchers better understand how these can be correlated with features derived from the imaging data. (<strong><a href="/download/attachments/52763925/CPTAC_LUAD_SIG.pdf?version=2&modificationDate=1614364805610&api=v2" data-linked-resource-container-id="52763925" data-linked-resource-container-version="48" data-linked-resource-content-type="application/pdf" data-linked-resource-default-alias="CPTAC_LUAD_SIG.pdf" data-linked-resource-id="83592415" data-linked-resource-type="attachment" data-linked-resource-version="2" data-nice-type="PDF Document">Download the slides</a></strong>)</p>

本数据集收录了来自国家癌症研究所临床蛋白质组肿瘤分析联盟（Clinical Proteomic Tumor Analysis Consortium，简称CPTAC）肺腺癌（CPTAC-LUAD）队列的研究对象。CPTAC是一项国家级的项目，旨在通过大规模蛋白质组学和基因组学分析（或称蛋白质组学）的应用，加速对癌症分子基础的理解。来自CPTAC患者的放射学和病理学图像正被收集并由癌症成像档案（The Cancer Imaging Archive）公开提供，以使研究者能够调查可能与相应的蛋白质组、基因组及临床数据相关的癌症表型。各癌症类型的成像数据将包含在其各自的TCIA收藏中，收藏名称为“CPTAC-<em>肿瘤类型</em>”。放射学成像收集自患者病理诊断前进行的标准护理成像，以及可用的随访扫描。因此，放射学图像数据集在扫描器模式、制造商和采集协议方面存在异质性。病理学成像作为CPTAC资格流程的一部分被收集。所有CPTAC队列均以单个综合队列或根据适用性分为<em>探索性</em>和<em>验证性</em>两部分发布。蛋白质组学研究主要有两种类型：探索性蛋白质组学和靶向蛋白质组学。‘探索性蛋白质组学’一词指的是对生物或临床样本中最大数量的蛋白质进行非靶向的鉴定和定量。‘靶向蛋白质组学’则指对生物或临床样本中定义的蛋白质子集进行定量测量，通常在完成探索性蛋白质组学研究后，为了确认选定的有趣目标而进行。常用的蛋白质组学技术和平台根据分析的需求、通量和样本输入要求，采用不同类型的质谱和蛋白质微阵列，同时，在纳米技术和自动化方面的进一步发展也在进行中，以改善低丰度蛋白质的检测，提高通量，并选择性地在<em>体内</em>达到目标蛋白质。一旦确定感兴趣蛋白质的目标，将为验证性研究开发高通量靶向检测：验证初步测试准确性的测试。有关CPTAC成像努力的总结可在CPTAC成像蛋白质组页面找到。CPTAC成像特别兴趣小组（CPTAC Imaging Special Interest Group）允许加入，以获取网络研讨会和数据发布通知，共同协作处理常见的数据整理任务，并寻求合作伙伴以探索研究假设。往期网络研讨会如幻灯片和视频记录等资料可在CPTAC SIG网络研讨会页面找到。2020年7月22日，Shankha Satpathy介绍了联盟对CPTAC-LUAD的蛋白质组学分析。对LUAD基因组学和蛋白质组学数据集的深入探讨将有助于研究者更好地理解这些数据如何与成像数据推导出的特征相关联。可在此处下载幻灯片：<a href="/download/attachments/52763925/CPTAC_LUAD_SIG.pdf?version=2&modificationDate=1614364805610&api=v2">下载幻灯片</a>。

搜集汇总

背景与挑战

背景概述

该数据集是临床蛋白质组肿瘤分析联盟（CPTAC）肺腺癌队列的集合，专注于通过蛋白质组学和基因组学分析研究肺腺癌的分子机制。它包含放射学和病理学图像数据，这些数据与蛋白质组、基因组及临床信息相关联，旨在促进癌症表型与分子数据的相关性研究。数据集具有异质性的图像采集特点，并支持从发现性到靶向蛋白质组学的研究流程。