Wei Rong, Qi Guoye, Zeng Zixin, Shen Ningning, Wang Ziyue, Shen Honghong, Gao Lifang, Song Chen, Ma Wenxia, Wang Chen
Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, Tai Yuan, 030000, ShanXi, China.
Department of Pathology, The Basic Medical College of ShanXi Medical University, Tai Yuan, ShanXi, China.
Cancer Cell Int. 2021 Nov 24;21(1):620. doi: 10.1186/s12935-021-02324-w.
Pancreatic cancer has been a threateningly lethal malignant tumor worldwide. Despite the promising survival improvement in other cancer types attributing to the fast development of molecular precise medicine, the current treatment situation of pancreatic cancer is still woefully challenging since its limited response to neither traditional radiotherapy and chemotherapy nor emerging immunotherapy. The study is to explore potential responsible genes during the development of pancreatic cancer, thus identifying promising gene indicators and probable drug targets.
Different bioinformatic analysis were used to interpret the genetic events in pancreatic cancer development. Firstly, based on multiple cDNA microarray profiles from Gene Expression Omnibus (GEO) database, the genes with differently mRNA expression in cancer comparing to normal pancreatic tissues were identified, followed by being grouped based on the difference level. Then, GO and KEGG were performed to separately interpret the multiple groups of genes, and further Kaplan-Meier survival and Cox Regression analysis assisted us to scale down the candidate genes and select the potential key genes. Further, the basic physicochemical properties, the association with immune cells infiltration, mutation or other types variations besides expression gap in pancreatic cancer comparing to normal tissues of the selected key genes were analyzed. Moreover, the aberrant changed expression of key genes was validated by immunohistochemistry (IHC) experiment using local hospital tissue microarray samples and the clinical significance was explored based on TCGA clinical data.
Firstly, a total of 22,491 genes were identified to express differently in cancer comparing to normal pancreatic tissues based on 5 cDNA expression profiles, and the difference of 487/22491 genes was over eightfold, and 55/487 genes were shared in multi profiles. Moreover, after genes interpretation which showed the > eightfold genes were mainly related to extracellular matrix structural constituent regulation, Kaplan-Meier survival and Cox-regression analysis were performed continually, and the result indicated that of the 55 extracellular locating genes, GPRC5A and IMUP were the only two independent prognostic indicators of pancreatic cancer. Further, detailed information of IMUP and GPRC5A were analyzed including their physicochemical properties, their expression and variation ratio and their association with immune cells infiltration in cancer, as well as the probable signaling pathways of genes regulation on pancreatic cancer development. Lastly, local IHC experiment performed on PAAD tissue array which was produced with 62 local hospital patients samples confirmed that GPRC5A and IMUP were abnormally up-regulated in pancreatic cancer, which directly associated with worse patients both overall (OS) and recurrence free survival (RFS).
Using multiple bioinformatic analysis as well as local hospital samples validation, we revealed that GPRC5A and IMUP expression were abnormally up-regulated in pancreatic cancer which associated statistical significantly with patients survival, and the genes' biological features and clinical significance were also explored. However, more detailed experiments and clinical trials are obligatory to support their further potential drug-target role in clinical medical treatment.
胰腺癌一直是全球范围内极具威胁的致命性恶性肿瘤。尽管分子精准医学的快速发展使其他癌症类型的生存率有了显著提高,但目前胰腺癌的治疗状况仍然极具挑战性,因为它对传统放疗、化疗以及新兴的免疫疗法的反应都很有限。本研究旨在探索胰腺癌发生发展过程中的潜在相关基因,从而确定有前景的基因指标和可能的药物靶点。
采用不同的生物信息学分析方法来解读胰腺癌发生发展过程中的基因事件。首先,基于基因表达综合数据库(GEO)中的多个cDNA微阵列图谱,识别出与正常胰腺组织相比在癌症中mRNA表达不同的基因,然后根据差异水平进行分组。接着,进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析,分别解读多组基因,进一步通过Kaplan-Meier生存分析和Cox回归分析来缩小候选基因范围并选择潜在的关键基因。此外,分析所选关键基因的基本理化性质、与免疫细胞浸润的关联、与正常组织相比在胰腺癌中的突变或其他类型变异(除表达差异外)。此外,使用当地医院组织微阵列样本通过免疫组织化学(IHC)实验验证关键基因的异常表达变化,并基于癌症基因组图谱(TCGA)临床数据探索其临床意义。
首先,基于5个cDNA表达图谱,共鉴定出22491个基因在癌症与正常胰腺组织中的表达存在差异,其中487/22491个基因的差异超过8倍,55/487个基因在多个图谱中共享。此外,在对显示差异超过8倍的基因进行解读后发现,这些基因主要与细胞外基质结构成分调节有关,随后继续进行Kaplan-Meier生存分析和Cox回归分析,结果表明在这55个细胞外定位基因中,G蛋白偶联受体C5A(GPRC5A)和免疫调节蛋白(IMUP)是胰腺癌仅有的两个独立预后指标。进一步分析了IMUP和GPRC5A的详细信息,包括它们的理化性质、表达和变异率、与癌症中免疫细胞浸润的关联,以及基因调控胰腺癌发生发展的可能信号通路。最后,对由62例当地医院患者样本制成的胰腺腺癌(PAAD)组织阵列进行的局部IHC实验证实,GPRC5A和IMUP在胰腺癌中异常上调,这与患者较差的总生存期(OS)和无复发生存期(RFS)直接相关。
通过多种生物信息学分析以及当地医院样本验证,我们发现GPRC5A和IMUP在胰腺癌中异常上调,与患者生存具有显著统计学关联,同时还探索了这些基因的生物学特征和临床意义。然而,需要更详细的实验和临床试验来支持它们在临床治疗中进一步作为潜在药物靶点的作用。