上次我们简单的介绍了一下肿瘤TNM分期系统。今天我们来用R获取感兴趣的癌症的临床信息，其中就可以找到我们上次讲到的TNM分期信息。
#加载TCGAbiolinks包
library(TCGAbiolinks)
#下载TCGA-CHOL这个项目相关的临床信息，这个项目是胆管癌
clinical <- GDCquery_clinic(project = "TCGA-CHOL", type = "clinical")
#将下载到的临床信息写入到clinical.csv文件中
write.csv(file="clinical.csv",clinical)
> dim(clinical)
[1] 51 158
一共得到51个样本的临床信息，一共有158条临床信息，他们分别是
> names(clinical)
[1] "submitter_id"
[2] "year_of_diagnosis"
[3] "classification_of_tumor"
[4] "last_known_disease_status"
[5] "updated_datetime"
[6] "primary_diagnosis"
[7] "tumor_stage"
[8] "age_at_diagnosis"
[9] "morphology"
[10] "days_to_last_known_disease_status"
[11] "created_datetime"
[12] "prior_treatment"
[13] "ajcc_pathologic_n"
[14] "ajcc_pathologic_m"
[15] "state"
[16] "days_to_last_follow_up"
[17] "days_to_recurrence"
[18] "diagnosis_id"
[19] "tumor_grade"
[20] "icd_10_code"
[21] "days_to_diagnosis"
[22] "tissue_or_organ_of_origin"
[23] "progression_or_recurrence"
[24] "prior_malignancy"
[25] "ajcc_staging_system_edition"
[26] "ajcc_pathologic_stage"
[27] "synchronous_malignancy"
[28] "site_of_resection_or_biopsy"
[29] "ajcc_pathologic_t"
[30] "vascular_invasion_type"
[31] "method_of_diagnosis"
[32] "laterality"
[33] "ann_arbor_pathologic_stage"
[34] "inrg_stage"
[35] "metastasis_at_diagnosis"
[36] "cog_rhabdomyosarcoma_risk_group"
[37] "irs_group"
[38] "weiss_assessment_score"
[39] "enneking_msts_metastasis"
[40] "esophageal_columnar_dysplasia_degree"
[41] "lymph_nodes_tested"
[42] "ishak_fibrosis_score"
[43] "lymphatic_invasion_present"
[44] "supratentorial_localization"
[45] "igcccg_stage"
[46] "gastric_esophageal_junction_involvement"
[47] "goblet_cells_columnar_mucosa_present"
[48] "iss_stage"
[49] "enneking_msts_tumor_site"
[50] "tumor_regression_grade"
[51] "gross_tumor_weight"
[52] "ajcc_clinical_stage"
[53] "ann_arbor_b_symptoms"
[54] "cog_neuroblastoma_risk_group"
[55] "days_to_best_overall_response"
[56] "enneking_msts_grade"
[57] "tumor_largest_dimension_diameter"
[58] "figo_stage"
[59] "child_pugh_classification"
[60] "peripancreatic_lymph_nodes_positive"
[61] "circumferential_resection_margin"
[62] "lymph_nodes_positive"
[63] "inss_stage"
[64] "inpc_histologic_group"
[65] "secondary_gleason_grade"
[66] "residual_disease"
[67] "anaplasia_present"
[68] "ann_arbor_clinical_stage"
[69] "tumor_confined_to_organ_of_origin"
[70] "perineural_invasion_present"
[71] "tumor_focality"
[72] "wilms_tumor_histologic_subtype"
[73] "ajcc_clinical_t"
[74] "ajcc_clinical_n"
[75] "ajcc_clinical_m"
[76] "irs_stage"
[77] "first_symptom_prior_to_diagnosis"
[78] "cog_liver_stage"
[79] "enneking_msts_stage"
[80] "inpc_grade"
[81] "burkitt_lymphoma_clinical_variant"
[82] "ann_arbor_extranodal_involvement"
[83] "peripancreatic_lymph_nodes_tested"
[84] "masaoka_stage"
[85] "mitosis_karyorrhexis_index"
[86] "esophageal_columnar_metaplasia_present"
[87] "best_overall_response"
[88] "vascular_invasion_present"
[89] "micropapillary_features"
[90] "primary_gleason_grade"
[91] "anaplasia_present_type"
[92] "medulloblastoma_molecular_classification"
[93] "cog_renal_stage"
[94] "metastasis_at_diagnosis_site"
[95] "gleason_grade_group"
[96] "NA."
[97] "cigarettes_per_day"
[98] "weight"
[99] "alcohol_history"
[100] "alcohol_intensity"
[101] "bmi"
[102] "years_smoked"
[103] "exposure_id"
[104] "height"
[105] "environmental_tobacco_smoke_exposure"
[106] "tobacco_smoking_status"
[107] "pack_years_smoked"
[108] "respirable_crystalline_silica_exposure"
[109] "coal_dust_exposure"
[110] "asbestos_exposure"
[111] "type_of_tobacco_used"
[112] "tobacco_smoking_onset_year"
[113] "smoking_frequency"
[114] "tobacco_smoking_quit_year"
[115] "type_of_smoke_exposure"
[116] "alcohol_days_per_week"
[117] "time_between_waking_and_first_smoke"
[118] "radon_exposure"
[119] "alcohol_drinks_per_day"
[120] "gender"
[121] "year_of_birth"
[122] "race"
[123] "days_to_birth"
[124] "ethnicity"
[125] "vital_status"
[126] "demographic_id"
[127] "age_at_index"
[128] "year_of_death"
[129] "days_to_death"
[130] "cause_of_death"
[131] "weeks_gestation_at_birth"
[132] "premature_at_birth"
[133] "treatments_pharmaceutical_days_to_treatment_start"
[134] "treatments_pharmaceutical_treatment_effect"
[135] "treatments_pharmaceutical_initial_disease_status"
[136] "treatments_pharmaceutical_treatment_type"
[137] "treatments_pharmaceutical_treatment_id"
[138] "treatments_pharmaceutical_therapeutic_agents"
[139] "treatments_pharmaceutical_regimen_or_line_of_therapy"
[140] "treatments_pharmaceutical_treatment_intent_type"
[141] "treatments_pharmaceutical_treatment_anatomic_site"
[142] "treatments_pharmaceutical_treatment_outcome"
[143] "treatments_pharmaceutical_days_to_treatment_end"
[144] "treatments_pharmaceutical_treatment_or_therapy"
[145] "treatments_radiation_days_to_treatment_start"
[146] "treatments_radiation_treatment_effect"
[147] "treatments_radiation_initial_disease_status"
[148] "treatments_radiation_treatment_type"
[149] "treatments_radiation_treatment_id"
[150] "treatments_radiation_therapeutic_agents"
[151] "treatments_radiation_regimen_or_line_of_therapy"
[152] "treatments_radiation_treatment_intent_type"
[153] "treatments_radiation_treatment_anatomic_site"
[154] "treatments_radiation_treatment_outcome"
[155] "treatments_radiation_days_to_treatment_end"
[156] "treatments_radiation_treatment_or_therapy"
[157] "bcr_patient_barcode"
[158] "disease"
我们上次提到的TNM分期信息在这里的名字分别叫
"ajcc_pathologic_t", "ajcc_pathologic_n"和"ajcc_pathologic_m" 。
这个文件也保存到本地了，我们可以直接用Excel打开查看，并找到这三列。
