Abstract：
OBJECTIVE: The prevalence of microsatellite instability (MSI) subtype among all colon cancers in India is about 30 %, approximately two times more than that of western population suggesting different molecular pathogeneses.
METHODS: A NanoString analysis-based Pan cancer differential expression (DE) profile was determined in a primary cohort of early-stage CRC (tumor=10, normal=7), and correlated against MSI status. Using RT-PCR, tumor-specific DE genes were validated in another cohort of MSI-high CRC (n=15).
RESULTS: Among the most differentially expressed genes, AXIN2, ETV4, and RNF43 were tumor cell-specific signals, while a set of genes including COL11A1, COMP, INHBA, SPP1, MMP3, TLR2, and others were immune cell-specific signals, that had a differential expression between MSI and MSS groups. When overlapped with The Cancer Genome Atlas (TCGA) studies using the Tumor immune estimation resource tool (TIMER), and protein-protein interaction analysis by STRING.db, these genes were segregated to representative tumor cells and immune cells. On validation, the tumor-specific gene signals were inversely associated with TLR4 expression.
CONCLUSIONS: The differential expression distribution of AXIN2, ETV4, and RNF43 among tumor and immune cells, suggests more than one pathological subset in the MSI-H subgroup of early-stage CRC in the Indian population.
METHODS: A NanoString analysis-based Pan cancer differential expression (DE) profile was determined in a primary cohort of early-stage CRC (tumor=10, normal=7), and correlated against MSI status. Using RT-PCR, tumor-specific DE genes were validated in another cohort of MSI-high CRC (n=15).
RESULTS: Among the most differentially expressed genes, AXIN2, ETV4, and RNF43 were tumor cell-specific signals, while a set of genes including COL11A1, COMP, INHBA, SPP1, MMP3, TLR2, and others were immune cell-specific signals, that had a differential expression between MSI and MSS groups. When overlapped with The Cancer Genome Atlas (TCGA) studies using the Tumor immune estimation resource tool (TIMER), and protein-protein interaction analysis by STRING.db, these genes were segregated to representative tumor cells and immune cells. On validation, the tumor-specific gene signals were inversely associated with TLR4 expression.
CONCLUSIONS: The differential expression distribution of AXIN2, ETV4, and RNF43 among tumor and immune cells, suggests more than one pathological subset in the MSI-H subgroup of early-stage CRC in the Indian population.
摘要：
目的：在印度所有结肠癌中，微卫星不稳定性（MSI）亚型的患病率约为30％，大约是西方人口的两倍，表明有不同的分子病因。
方法：在早期CRC（肿瘤=10，正常=7）的主要队列中确定了基于NanoString分析的泛癌差异表达（DE）谱，并与MSI状态相关。使用RT-PCR，在另一个MSI高CRC队列中验证了肿瘤特异性DE基因(n=15).
结果：在差异表达最多的基因中，AXIN2，ETV4和RNF43是肿瘤细胞特异性信号，而一组基因包括COL11A1，COMP，INHBA,SPP1、MMP3、TLR2等为免疫细胞特异性信号,MSI和MSS组之间有差异表达。当与使用肿瘤免疫评估资源工具（TIMER）的癌症基因组图谱（TCGA）研究重叠时，用STRING进行蛋白质-蛋白质相互作用分析。db,这些基因被分离为代表性的肿瘤细胞和免疫细胞。在验证时，肿瘤特异性基因信号与TLR4表达呈负相关。
结论：AXIN2，ETV4和RNF43在肿瘤和免疫细胞中的差异表达分布，提示印度人群早期CRC的MSI-H亚组中不止一个病理子集。
方法：在早期CRC（肿瘤=10，正常=7）的主要队列中确定了基于NanoString分析的泛癌差异表达（DE）谱，并与MSI状态相关。使用RT-PCR，在另一个MSI高CRC队列中验证了肿瘤特异性DE基因(n=15).
结果：在差异表达最多的基因中，AXIN2，ETV4和RNF43是肿瘤细胞特异性信号，而一组基因包括COL11A1，COMP，INHBA,SPP1、MMP3、TLR2等为免疫细胞特异性信号,MSI和MSS组之间有差异表达。当与使用肿瘤免疫评估资源工具（TIMER）的癌症基因组图谱（TCGA）研究重叠时，用STRING进行蛋白质-蛋白质相互作用分析。db,这些基因被分离为代表性的肿瘤细胞和免疫细胞。在验证时，肿瘤特异性基因信号与TLR4表达呈负相关。
结论：AXIN2，ETV4和RNF43在肿瘤和免疫细胞中的差异表达分布，提示印度人群早期CRC的MSI-H亚组中不止一个病理子集。
