Institute of Biomedical Chemistry, Pogodinskaya, 10, 119121 Moscow, Russia.
Petersburg Institute of Nuclear Physics (PNPI) of National Research Center "Kurchatov Institute", 188300 Gatchina, Russia.
Int J Mol Sci. 2022 Sep 21;23(19):11113. doi: 10.3390/ijms231911113.
The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for "ideal" tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways-by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called "classical plasma proteins", may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of "classical plasma proteins". Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.
肿瘤标志物的应用有助于早期发现癌症复发和预后。人们希望它们也能用于癌症早期检测的筛查试验。在这里,找到理想的肿瘤标志物的问题,即应该具有敏感性、特异性和可靠性,是一个紧迫的问题。人血浆是最受欢迎的样本之一,因为它通常在临床上采集,并且可以对任何类型的疾病(包括癌症)进行非侵入性、快速分析。人们已经在寻找“理想”肿瘤标志物方面做出了很多努力,深入挖掘了血浆蛋白质组。在这个领域,情况可以通过两种方式得到改善——尝试寻找理想的单一肿瘤标志物或生成不同标志物的组合。在这两种情况下,蛋白质组学都肯定起着主要作用。有一条证据表明,最丰富的所谓“经典血浆蛋白”可用于生成肿瘤生物标志物谱。为了全面起见,这些图谱不仅应该包含蛋白质水平的信息,还应该包含每个蛋白质的蛋白形式分布信息。最初,应该生成这些蛋白质在正常情况下的图谱。在我们的工作中,我们收集了有关癌症与“经典血浆蛋白”水平之间联系的文献信息。此外,我们还展示了通过二维电泳结合质谱和免疫检测生成的这些蛋白质在正常情况下的蛋白形式图谱(2DE 图谱)。下一步,将生成代表不同癌症情况下血浆中蛋白质扰动的类似图谱。此外,基于这些信息,可以开发不同的测试系统。