1.The Study Of Diagnosis And Prognosis Factors In Lung Cancer 2.Study Of The Prognosis Factor NCAPD2 In Triple Negative Breast Cancer

Part 1 The study of diagnosis and prognosis factors in lung cancerChapter 1 Discovering lung adenocaricinoma prognosis factor SMC4 through lung development dataBackground:Tumor is a complex network disease,it contains numerable mutated genes which have complicated functions and involved in dynamic biomolecular network network.The study of tumor is challenging attributes to its heterogeneity,disorder and hard-to-get precancerous stages.An increasing body of evidence have demonstrated that there are startling similarities between embryo developmemt process and tumorigenesis in gene expression patterns and cellular biological behaviors.Tumors can be regarded as special "organs" that undergo aberrant and poorly regulated organogenesis.Distinct from carcinogenesis,embryogenesis is a tightly regulated process with high conservatism and uniformity.In embryo developmental process,the molercular network is highly ordered;besides,the process between different individuals and the molecular change occurring in that process is highly uniform.Therefore,the re-examination of distinctive processes involved in normal development might help elucidate the intrinsic features of cancer that are significantly obscured by its heterogeneity and disorder.Aim:To explore the feasibility of discovering biomarkers in lung cancer through a comparative study between embryo developmental process and tumorigenesis.Materials and methods:First,we analysed the expression pattern of 1640 genes that were continuously upregulated or downregulated in 44 cases of lung development data in 69 cases of lung adenocarcinoma data.Then these genes were used to built a molecular co-expression network during lung development.Further by screening nodes with high connectivity and using Clique Percolation Method,we found a hub module during lung development.In this hub module,we selected structural maintenance of chromosome 4(SMC4)that has not been reported in lung adenocarcinoma for further study.The function of SMC4 in lung adenocarcinoma and lung development was studied using the gene expression profile data of 69 lung adenocarcinoma samples and 44 lung development samples by correlation analysis and Gene Ontology enrichment analysis.Finally,506 lung adenocarcinoma sequencing data with survival information downloaded from the TCGA(The Cancer Genome Atlas)database was used to evaluate the relationship between SMC4 gene expression and the prognosis of lung adenocarcinoma patients by log-rank test and Cox proportional hazards regression model.Results:Many of the genes continuously upregulated or downregulated during lung development showed opposite expression patterns in lung adenocarcinoma.There was a close interaction between these genes and they were mainly involved in cell cycle,cytoskeletal organization,DNA metabolism,cell death,and immune response.Co-expression network construction and module mining revealed that SMC4 was one of the key molecules in lung development.Gene expression profile data showed that the mRNA expression level of SMC4 was continuously down-regulated during lung development,but was highly expressed in lung adenocarcinoma compared with adult lung tissue(unpaired t-test,p = 0.0033)and corresponding adjacent lung tissue(paired t-test,p = 0.00024).And SMC4 played a very similar role in lung development and lung adenocarcinoma,involved in the cell cycle,RNA splicing,DNA metabolic process,cell death,cell adhesion and extracellular matrix organization.Survival analysis showed that high SMC4 expression was significantly associated with poor overall survival in lung adenocarcinoma patients(Log-rank test,p = 0.024)and was an independent poor prognostic factor for lung adenocarcinoma patients(multivariate cox regression,p = 0.0432).Conclusions:Lung development tissues and lung adenocarcinoma tissues have similar molecular expression patterns.SMC4,a pivotal gene in lung development which is exploited by embryogenesis model for studying tumorigenesis,plays a consistent function in lung development and lung adenocarcinomas;besides,it is significantly associated with the progression and prognosis of lung adenocarcinoma.Comparing research on tumors with molecular events related to embryonic development is an effective method for tapping potential tumor-related key genes and therapeutic targets,and helps elucidate the mechanism of tumorigenesis.Chapter 2 Analysis of gene expression profiles of peripheral blood leukocytes from lung cancer patients and identification of lung cancer-specific gene signatureBackground:Blood test is a routine method for disease detection.Blood circulates throughout the tissues and organs of the body,and there is a material exchange between them all the times.At the same time,various immune-related cells in the blood monitor the state of the body and respond to pathological changes in the body.The interaction between tumor tissues and the body’s immune system plays a very important role in the development of tumors.As an abnormal tissue,tumor antigens produced by tumor tissues cause the body’s anti-tumor immune response.At the same time,in order to evade the killing of the immune system,tumor tissues in turn act on immune cells to suppress the immune response and make the host loses its immune response to tumors.During the interaction between the tumor tissue and the host’s immune system,the expression of mRNA changes in various leukocytes,which are basic units for exercising immune functions.Blood is easy to get and is less traumatic to humans,therefore,it is a very attractive method to detect tumors by using tumor-specific gene signature in peripheral blood.Aim:The purpose of this study is to investigate the difference in gene expression profiles of peripheral blood leucocyte in patients with lung cancer and healthy people,and to screen out the lung cancer-specific peripheral blood gene expression signatures,which can be used to distinguish between lung cancer patients and healthy people.Methods and materials:In this part of the study,we collected 73 peripheral blood samples of lung cancer patients and 76 healthy peripheral blood samples,and tested the leukocyte expression profiles of these samples using second-generation sequencing technology.After data quality control and standardization,firstly,T-Distribution Stochastic Neighbour Embedding and unsupervised clustering algorithms were used to compare the samples based on the characteristics of the sample gene expression profiles.Next,we compared the gene expression profiles of peripheral blood leukocytes of patients with different pathological types of lung cancer by molecular distance analysis and KW test.Subsequently,the differential gene expression of peripheral blood leukocytes was identified in lung cancer patients and healthy individuals.Functional enrichment was used to annotate the biological functions of the differential genes,and these genes were used to construct a co-expression network,and then the core genes were identified.By analyzing the blood routine results of lung cancer patients and healthy people,the changes of the composition ratio of peripheral blood cells in the two are compared.The SVM-RFE algorithm was further used to identify the tumor-specific gene signature in peripheral blood and then a classification model was constructed.The prediction efficiency of the classification model was evaluated in an independent validation data set of 102 peripheral blood samples from patients with lung cancer and 63 healthy peripheral blood samples.Results:The comparison of gene expression profile showed that the gene expression profiles of peripheral blood leukocytes in lung cancer patients and healthy individuals are significantly different and they have different classification characteristics.There is also a difference in the expression profile of peripheral blood leukocytes between lung cancer patients.Further analysis showed that there was no significant difference in the gene expression profiles of peripheral blood leukocytes between lung adenocarcinoma,lung squamous cell carcinoma,and small cell lung cancer(One-way ANOVA,p=0.866).According to the characteristics of gene expression profiles,lung cancer patients can be divided into two categories,named Cancerl and Cancer2 respectively.There is no significant difference in pathological types between the two types of lung cancer(Chi square test,p=0.8572),but there are significant differences in TNM staging(Chi square test,p=0.004248).Cancerl group is mostly early stage lung cancer(70.6%),and Cancer2 group is mostly advanced stage lung cancer(75%).The biological function of differentially expressed genes between two types of lung cancer and healthy humans is significantly different.The number of peripheral blood leucocyte,peripheral blood neutrophil ratio and absolute value in Cancer2 group were significantly higher than that in Cancerl group and healthy people(One-way ANOVA,p<0.001),indicating that Cancer2 group may be in a relatively obvious inflammatory state.Based on the differentially expressed genes between lung cancer patients and healthy people,we identified a tumor-specific 22-gene signature by using SVM-RFE algorithm and constructed a classification model.We evaluated the prediction efficiency of this classification model using an independent validation data sets and the result showed that this model can distinguish lung cancer patients from healthy people with an accuracy of 90.0%,a sensitivity of 92.1%,and a specificity of 88.9%.Conclussions:The interaction between tumor and host immune system results in a significant change in the expression profile of leukocytes in peripheral blood of tumor patients.These changes not only provide clues as how tumors affect the body’s immune system,but also provide new candidate indicators for the research and development of tumor-associated diagnostic markers.Part 2 Study of the prognosis factor NCAPD2 in triple negative breast cancerBackground:In China,breast cancer is the most common cancer with highest incidence in women.The incidence and mortality of breast cancer are increasing year by year,among which triple-negative breast cancer accounts for 15-20%.Compared with other types of breast cancer,triple-negative breast cancer often relapses in a short time and has poor prognosis.Triple-negative breast cancer is refractory because of its aggressive phenotype,high molecular heterogeneity,and lacking in targeted therapies.Triple-negative breast cancer patients have a higher risk of local recurrence and distant metastasis,which leading to a poor prognosis.Therefore,it is important to study the molecular mechanism of triple negative breast cancer and to explore potential prognostic related markers and therapeutic targets for breast cancer.Non-SMC condensin I complex subunit D2(NCAPD2)is a key components of the condensin I complex,mediating the recruitment and localization of complex on chromatin,and is mainly involved in chromosomes condensation and segragationa during cell cycle.The studies on the relationship between NCAPD2 and human diseases were limited.In our study,we first reported the close relationship between NCAPD2 and triple negative breast cancer.Aim:To study the value of NCAPD2 as a prognostic factor for triple negative breast cancer and its biological function in promoting disease progressionMaterials and methods:Immunohistochemical staining was used to detect the expression of NCAPD2 in the tumor tissue of 179 triple-negative breast cancer patients.The relationship between the expression of NCAPD2 and clinical characteristics and prognosis was analyzed by chi-square test and log-rank test.To explore the biological function of NCAPD2 in triple-negative breast cancer,the mRNA expression profiles of 299 triple-negative breast cancer samples get from METABRIC were analysed by correlation analysis and function enrichment.The function of NCAPD2 known by data analysis was further verified by the NCAPD2 low expression cell model of triple negative breast cancer.The role of NCAPD2 in proliferation and invasion of triple negative breast cancer cells were detected by CCK-8 and transwell assays,respectively.Cell cycle and cell apoptosis were detected by flow cytometry.Results:Immunohistochemistry results showed that the protein expression of NCAPD2 was mainly localized in the cytoplasm of triple-negative breast cancer cells.Statistical analysis and survival analysis showed that positive NCAPD2 expression is significantly correlated with lymph node metastasis(Chi square test,p = 3.84E-06),and was an independent poor prognostic factor for triple negative breast cancer(Multivariate Cox regression,p = 0.025).It was significantly correlated with poor overall survival(Log-rank test,p = 0.0033)and progression-free survival(Log-rank test,p = 0.0013)of patients with triple negative breast cancer.Compared with negative NCAPD2 expression patients,the risk of triple-negative breast cancer-related death in patients with positive NCAPD2 expression was increased by 5-fold,and the risk of disease progression was increased by 4-fold.Gene expression profile data analysis showed that NCAPD2 is involved in many biological functions in triple negative breast cancer cells,including cell cycle,cell proliferation,cell division and invasion,and other malignant phenotypes.The NCAPD2 low expression cell model of triple negative breast cancer verified the effect of NCAPD2 on cell proliferation and invasive ability.We found that the inhibition of NCAPD2 attributed to G2/M arrest of the cell cycle,which makes some cells unable to successfully complete mitosis,leading to polyploid cells formation and cell apoptosis.Conclusions:We first report the close relationship between NCAPD2 and triple-negative breast cancer.Our results demonstrated that NCAPD2 played an important role in the triple negative breast cancer cell cycle,cell proliferation and invasion,and is closely related to the TNBC aggressive phenotype.Analysis of clinical features showed that the positive NCAPD2 expression is correlated with the lymph node metastasis in triple-negative breast cancer.More importantly,our results demonstrated that positive NCAPD2 expression was an independent predictor of TNBC poor prognosis.