| Breast cancer is a heterogenous disease whose behaviour is determined by the molecular characteristics of the tumour. In clinical practice, we rely on clinico-pathological features to predict tumour behaviour and patient outcome. A challenging problem for the treatment of breast cancer is how to accurately determine the prognosis of each patient, and then the individualized treatment can be implemented. With the application of molecular biology to the tumor area deeper and deeper, the treatment of breast cancer change from basing experience to evidence-based individualized treatment. But now the regime of clinical treatment of breast cancer are more based on some simple clinical and pathological features of the development, such as tumor size, axillary lymph nodes, tumor grade, etc., so the treatment results are unsatisfactory. Some research centers would combine clinical and pathological features of these simple combinations to evaluate prognosis, such as the Nottingham Prognostic Index (NPI), and Adjuvant! evaluation system. In this way, prognosis can be assessed, but there are still some disadvantages when using them.In recent years, large sample, high-throughput gene expression studies, such as 70 genes (Mammaprint) and 21 genes (Oncotype DX) show more predictive ability than the prognosis of prognostic index. But it is worth mentioning that, because mRNA expression microarray studies were mostly based specific training set, different scholars study the genes contained in gene expression profile, particularly mRNA expression profiles reflect only the transcription level, while achieving its function also includes a complex post-transcriptional regulation and translation. Especially in recent years on post-transcriptional regulation of microRNA is increasing apparently and the process of transcription and translation after the important information are needed for further study of multiple perspectives. In short, to understand the prognostic factors of breast cancer, more researches should be done based on current data.This study started with retrospective analysis on breast cancer database with 5023 cases in our site. Using survival analysis to screen prognosis factors of breast cancer-related biological markers, and then select positive biological marker for prognostic significance in breast cancer via Meta analysis. Through comprehensive literature collection, increase reliability of conclusions for prognostic factors. Finally, Biological markers associated with the microRNA were selected based on literature, and tests for the samples of paraffin-embedded tissues was completed to explore its prognostic value in breast cancer.In the first chapter, a retrospective study was designed to select related biological indicators form ER, PR, Her-2, P53, Bcl-2, nm-23, PGP based on our database containing 5023 subjects from January 1985 to December 2009. In this study, the subjects should meet the following criteria: (1) have results of ER, PR, Her-2, P53, Bcl-2, nm-23, PGP; (2) pathological type were invasive cancer, and the number of lymph node≥6; (3) preoperative neoadjuvant therapy were not adopted; (4) detailed follow-up address and clinical data. A total of 144 subjects met these criteria. Kaplan Meier method was used to estimate statistics, Log rank test was used for univariate analysis, and Cox regression model was used for multivariate analysis. Tumor size, axillary lymph node metastasis, adjuvant radiotherapy, adjuvant endocrine therapy, ER, PR, Her-2, and Bcl-2 affected DFS in the univariate analysis. In the COX model, 13 indicators including tumor size, clinical stage, axillary lymph node metastasis, adjuvant chemotherapy, adjuvant radiotherapy, adjuvant endocrine therapy, ER, PR, Her-2, P53, Bcl-2, nm-23, PGP were considered, and clinical stage, axillary lymph node metastasis, adjuvant radiotherapy, adjuvant endocrine therapy affected DFS. Bcl-2 is the only independent prognostic factors of biological markers for breast cancer in the factors affected DFS. The results suggest that, Bcl-2 is an independent prognostic factor of breast cancer.In the second chapter, prognostic factors selected in first chapter were validated by Meta analysis based on literatures. There are a lot of literatures on the analysis of biological markers with breast cancer, but most of them are retrospective and dispersive. Recently, when evaluate prognostic factors, more and more evidence classification methods are used. Meta analysis can summarize a number of research data together, and give results based on these studies, so the conclusions would be more reliability for the sample size is enlarged. We collected literatures on the analysis of biological markers with breast cancer between year 1994 and 2009, and summary the study with subjects more than 100, disease-free survival (DFS) and overall survival (OS), the relationship of Bcl-2 and breast cancer, and hazard ratio (HR) results by Meta analysis. Comprehensive meta analysis software package was used for the Meta analysis. Homogeneity test was used to detect the heterogeneity. According to the criteria, 9 studies were selected for DFS, and the HR was 1.814(95%CI 1.373-2.396) in random effect model; 10 studies were selected for OS, and the HR was 1.592(95%CI 1.190-2.130)in random effect model. This result showed Bcl-2 is an independent prognostic indicator of breast cancer.In the third chapter, evaluate the relationship between related microRNA (miRNA) and biological markers. MicroRNA is a non-coding small RNA, and can be found in plants and animals widely. MicroRNA has been shown extensively involved in various physiological and pathological processes, including tumorigenesis and development. Several studies confirmed the Bcl-2 regulated by microRNA miR-16, miR-15b, miR-15a, because these microRNA have similar sequence and were found several common target genes and pathways, so some scholars call them miR-16 family. The results of chapter 1 and 2 show that Bcl-2 is an independent prognostic indicator of breast cancer. So the microRNA which can regulate Bcl-2 may have prognostic significance. According to literature, three miRNAs of miR-16 family were selected to explore how their expression would affect the clinical characteristics and prognosis of breast cancer. Subjects admitted in our site and with invasive cancer, lymph node number≥6, 5 years after surgery and did not have full recurrence and metastasis, or less than 5 years after surgery, but recurrence and metastasis were confirmed in patients with sample of target lesion. The relative expression level of mir-16, mir-15b and mir-195 were detected by Taqman probe, and the relationship between expression level and disease-free survival were assessed. The results showed that tumor size, ER, Her-2, Bcl-2 were related to prognosis of patients; miR-16 is not associated with DFS, and the patients with high expression of miR-195 or miR-15b had shorter disease-free survival time, but compare to low expression group, the difference both were not statistically significant. The results suggest that miR-195 and miR-15b may be associated with poor prognosis of breast cancer, but still need to expand the sample size, and design a prospective trial to confirm.
|
PDF Full Text Request