Research On Multiple Genes For Diagnosis Of Prostate Cancer

Prostate cancer (PCa) is frequently diagnosed in elder men, and its risk is associated with increase of age.75% newly diagnosed PCa are patients with an age of more than 65 years old. The incidence and mortality rates all present an index number growth when men beyond 50 years old. In clinical, the prostate-specific antigen (PSA) has been widely used in screening for prostate cancer. Since PSA elevation is also associated with prostatitis and benign prostatic hyperplasia (BPH), elevated PSA levels do not always indicate the presence of Pca because of its insufficent specificity. In particularly, it is dificult to distinguish PCa between BPH when an individual gets PSA between 4.0 ng/ml and 10.0 ng/ml. And the PSA test can't give the inherent nature of PCa, so not to guide the clinical tumor classification and not to provide the decision-making information of treatment and prognosis. PCa is a multi-gene imbalance in the complex process of gradual change, and diffent clinical PCa may have different gene imbalance and associated with different signal systems, so virtually it is impossible to diagnosis PCa accurately by using a single biomarker. Recent years, a number of genes are reveaed that which expression changes with PCa progression. Forward study these result on clinical pathology; there are promice to develop some bettor biomarkers than PSA for early diagnosis and type of PCa.Thus, the objective of our research is the identification of more specific and predictive biomarkers for improving clinical management by studing multi-gene expression profile of clinical PCa samples. Harnessing the current research results on gene expression of PCa, target genes are selected by data mining methods, and then the genes'primer and sequence are designed according to FQ-PCR's requirement. FQ-PCR with SYBR Green I are carried out to detect the mRNA expression levels of these genes in clinical samples.First, to study gene expression, we pre-choose 9 genes (KLK3/PSA,KLK2,KLK11,pim-1,hepsin,PSMA,AR,p27,IGF-1) as a biomarker combination to advance clinical trial on PCa tests. The results showed the PCa and BPH samples can be classified by the 9 genes expression profile, and among the 9 genes, pim-1, KLK2, AR and PSMA have the core contribution to classification. Second, to study gene expression ratio,12 genes (trmp-2,RPS16,TMPRSS2,KLK11,Ki-67,PCNA,HER2,MYC,NFKBIA,SREBF2,PSMA,GSTP1) are selected. The expression ratio result showed the 12 genes expression profile can provide useful imformation for PCa diagonosis, and among the 12 genes, TMPRSS2,KLK11,Ki-67,PCNA,NFKBIA,SREBF2 would be the most potential biomarker combinations. Howerver, HER2/MYC is the non-special gene combination in PCa, its overexpression may contribute to the early detection of PCa.