Fig 1: Support the correlations between ANGPTL2/SPP1 and CAFs/macrophages in CRC tissues based on bulk RNA-seq. (A) The correlations between ANGPTL2 expression and the purity of CRC tissue and the infiltrated level of CAFs based on the TCGA CRC cohort. (B) The correlations between ANGPTL2 expression and the infiltrated level of CAFs based on the GSE49355 dataset. (C) The correlations between ANGPTL2 expression and the infiltrated level of CAFs based on the GSE81558 dataset. (D) The correlations between SPP1 expression and the purity of CRC tissue and the infiltrated level of macrophages based on the TCGA CRC cohort. (E) The correlations between SPP1 expression and the infiltrated level of macrophages based on the GSE49355 dataset. (F) The correlations between SPP1 expression and the infiltrated level of macrophages based on the GSE81558 dataset. *, p<0.05; **, p<0.01; ***, p<0.001.
Fig 2: Identify the characteristic DEGs of LM-CRC. (A) Identify the characteristic DEGs of LM-CRC through the “LASSO” algorithm based on the GSE49355 dataset. (B) Identify the characteristic DEGs of LM-CRC through the “LASSO” algorithm based on the GSE81558 dataset. (C) Overlap the characteristic DEGs in two datasets to select the common DEGs of LM-CRC. (D) The ROC curves of SPP1, CAV1, ANGPTL2, COLEC11, and their combination to differentiate LM-CRC from primary CRC based on the GSE49355 dataset. (E) The ROC curves of SPP1, CAV1, ANGPTL2, COLEC11, and their combination to differentiate LM-CRC from primary CRC based on the GSE81558 dataset. (F) The ROC curves of SPP1, CAV1, ANGPTL2, COLEC11, and their combination to differentiate LM-CRC from primary CRC based on the GSE178120 and GSE159216 datasets.
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