Rabbit Anti-Human TUBA1B Polyclonal antibody

Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, three pairs of NC-treated and NC-untreated HCC xenograft tumour tissues were collected for circRNA sequencing analysis. In total, 297 circRNAs were differently expressed between the two groups, with 188 upregulated and 109 downregulated, among which hsa_circ_0088364 and hsa_circ_0090049 were validated by real-time quantitative polymerase chain reaction. The in vitro experiments showed that the two circRNAs inhibited the malignant biological behaviour of HCC, suggesting that they may play important roles in the development of HCC. To elucidate whether the two circRNAs function as "miRNA sponges" in HCC, we identified circRNA-miRNA and miRNA-mRNA interactions by using the CircInteractome and miRwalk, respectively. Subsequently, 857 miRNA-associated differently expressed genes in HCC were selected for weighted gene co-expression network analysis. Module Eigengene turquoise with 423 genes was found to be significantly related to the survival time, pathology grade and TNM stage of HCC patients. Gene functional enrichment analysis showed that the 423 genes mainly functioned in DNA replication- and cell cycle-related biological processes and signalling cascades. Eighteen hubgenes (SMARCD1, CBX1, HCFC1, RBM12B, RCC2, NUP205, ECT2, PRIM2, RBM28, COPS7B, PRRC2A, GPR107, ANKRD52, TUBA1B, ATXN7L3, FUS, MCM8 and RACGAP1) associated with clinical outcomes of HCC patients were then identified. These findings showed that the crosstalk between hsa_circ_0088364 and hsa_circ_0090049 and their competing mRNAs may play important roles in HCC, providing interesting clues into the potential of circRNAs as therapeutic targets of NC in HCC.

Background and aims Several clinical factors have an impact on prognosis in stage II colorectal cancer (CRC), but as yet they are inadequate for risk assessment. The present study aimed to develop a gene expression classifier for improved risk stratification of patients with stage II CRC. Methods 315 CRC samples were included in the study. Gene expression measurements from 207 CRC samples (stage I-IV) from two independent Norwegian clinical series were obtained using Affymetrix exon-level microarrays. Differentially expressed genes between stage I and stage IV samples from the test series were identified and used as input for L1 (lasso) penalised Cox proportional hazards analyses of patients with stage II CRC from the same series. A second validation was performed in 108 stage II CRC samples from other populations (USA and Australia). Results An optimal 13-gene expression classifier (PIGR, CXCL13, MMP3, TUBA1B, SESN1, AZGP1, KLK6, EPHA7, SEMA3A, DSC3, CXCL10, ENPP3, BNIP3) for prediction of relapse among patients with stage II CRC was developed using a consecutive Norwegian test series from patients treated according to current standard protocols (n=44, p<0.001, HR=18.2), and its predictive value was successfully validated for patients with stage II CRC in a second Norwegian CRC series collected two decades previously (n-52, p-0.02, HR-3.6). Further validation of the classifier was obtained in a recent external dataset of patients with stage II CRC from other populations (n=108, p=0.001, HR=6.5). Multivariate Cox regression analyses, including all three sample series and various clinicopathological variables, confirmed the independent prognostic value of the classifier (p <= 0.004). The classifier was shown to be specific to stage II CRC and does not provide prognostic stratification of patients with stage III CRC. Conclusion This study presents the development and validation of a 13-gene expression classifier, ColoGuideEx, for prognosis prediction specific to patients with stage II CRC. The robustness was shown across patient series, populations and different microarray versions.