Anti-PRKDC (aa 4078-4128) polyclonal antibody

Although the specific causes of colorectal cancer (CRC) are not known, a robust DNA repair capacity may decrease the risk of this malignancy. DNA repair capacity may be reduced by alterations of genes involved in DNA repair process. This may affect susceptibility to carcinogenesis. It is hypothesized that single nucleotide polymorphisms (SNPs) of several DNA repair genes may be a risk factor for CRC susceptibility and prognosis. Using PCR-RFLP method, we conducted a case-control study to genotype 291 patients with CRC and 140 healthy individuals to determine variants in thePRKDC,XPDandXRCC1genes. Results showed that the genotypes ofXRCC1c.580C>T polymorphism were associated with the risk of CRC. Compared with CC, CT (odds ratio (OR) = 5.35,P< 0.001) and CT/TT (OR = 4.74,P< 0.001) as well as T allele (OR = 4.95,P< 0.001) were overrepresented among the CRC patients. Variant genotype CC (OR = 2.37;P= 0.042) and C allele ofXPDc.2251A>C (OR = 1.37;P= 0.028) polymorphism, enhanced the risk of CRC cases. Compared with GG, positive association was also obtained for all genotypes (GT, TT, GT/TT) ofPRKDCrs7003908; 6721G>T polymorphism with CRC. Moreover, T allele ofPRKDCdemonstrated significant risk for CRC (OR = 5.61;P< 0.001). Besides, significant relevance of thePRKDCrs7003908; 6721G>T variations to smoking as well asXPDc.2251A>C variations to smoking and alcohol consumption in individuals with CRC was observed. Our findings indicated that genetic polymorphisms ofPRKDC,XRCC1,XPDgenes may influence susceptibility of CRC in the Iranian population.

Purpose: Glioblastoma multiforme (GBM) is a highly malignant tumor of the central nervous system. Although primary GBM patients receive extensive therapies, tumors may recur within months, and there is no objective and scientific method to predict prognosis. Adoptive immunotherapy holds great promise for GBM treatment. However, the expression profiles of the tumor-associated antigens (TAAs) and tumor immune microenvironment (TME) genes used in immunotherapy of GBM patients have not been fully described. The present study aimed to develop a predictive tool to evaluate patient survival based on full analysis of the expression levels of TAAs and TME genes. Methods: Expression profiles of a panel of 87 TAAs and 8 TME genes significantly correlated with poor prognosis were evaluated in 44 GBM patients and 10 normal brain tissues using quantitative real-time polymerase chain reaction (qRT-PCR). A linear formula (the LASSO algorithm based in the R package) weighted by regression coefficients was used to develop a multi-element expression score to predict prognosis; this formula was cross-validated by the leave-one-out method in different GBM cohorts. Results: After analysis of gene expression, clinical features, and overall survival (OS), a total of 8 TAAs (CHI3L1, EZH2, TRIOBP, PCNA, PIK3R1, PRKDC, SART3 and EPCAM), 1 TME gene (FOXP3) and 4 clinical features (neutrophil-to-lymphocyte (NLR), number of basophils (BAS), age and treatment with standard radiotherapy and chemotherapy) were included in the formula. There were significant differences between high and low scoring groups identified using the formula in different GBM cohorts (TCGA (n=732) and GEO databases (n=84)), implying poor and good prognosis, respectively. Conclusion: The multi-element expression score was significantly associated with OS of GBM patients. The improve understanding of TAAs and TMEs and well-defined formula could be implemented in immunotherapy for GBM to provide better care.