Department of Structural and Functional Biology, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, Brazil.
Molecular Genetics and Bioinformatics Laboratory - Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu, Brazil.
Cancer Genomics Proteomics. 2023 Sep-Oct;20(5):487-499. doi: 10.21873/cgp.20400.
BACKGROUND/AIM: Pancreatic cancer (PC) has one of the highest mortality rates, with an overall five-year survival rate of only 7%. When diagnosed, PC is limited to the pancreas in only 20% of patients, whereas in 50% it has already metastasized. This is due to its late diagnosis, which makes the treatments used, such as radiotherapy, difficult, and reduces survival rates. Therefore, the importance of this study in detecting genes that may become possible biomarkers for this type of tumor, especially regarding the human secretome, is highlighted. These genes participate in pathways that are responsible for tumor migration and resistance to therapies, along with other important factors.
To achieve these goals, the following online tools and platforms have been expanded to discover and validate these biomarkers: The Human Protein Atlas database, the Xena Browser platform, Gene Expression Omnibus, the EnrichR platform and the Kaplan-Meier Plotter platform.
Our study adopted a methodology that allows the identification of potential biomarkers related to the effectiveness of radiotherapy in PC. Inflammatory pathways were predominantly enriched, related to the regulation of biological processes, primarily in cytokine-derived proteins, which are responsible for tumor progression and other processes that contribute to the development of the disease.
Radiotherapy treatment demonstrated greater efficacy when used in conjunction with other forms of therapy since it decreased the expression of essential genes involved in several inflammatory pathways linked to tumor progression.
背景/目的：胰腺癌（PC）的死亡率最高之一，总体五年生存率仅为 7%。当诊断为 PC 时，只有 20%的患者局限于胰腺，而 50%的患者已经发生转移。这是由于其诊断较晚，使得使用的治疗方法（如放疗）变得困难，并降低了生存率。因此，本研究在检测可能成为此类肿瘤的潜在生物标志物的基因方面具有重要意义，特别是关于人类分泌组的基因。这些基因参与了负责肿瘤迁移和对治疗产生耐药性的途径，以及其他重要因素。
为了实现这些目标，已经扩展了以下在线工具和平台来发现和验证这些生物标志物：人类蛋白质图谱数据库、Xena 浏览器平台、基因表达综合数据库、EnrichR 平台和 Kaplan-Meier Plotter 平台。
我们的研究采用了一种方法，可以识别与 PC 放疗效果相关的潜在生物标志物。炎症途径主要富集，与生物过程的调节有关，主要涉及细胞因子衍生蛋白，这些蛋白负责肿瘤的进展和导致疾病发展的其他过程。
放疗与其他形式的治疗联合使用时显示出更大的疗效，因为它降低了与肿瘤进展相关的几个炎症途径中涉及的关键基因的表达。
