OBJECTIVE: To detect the expression level of T-complex polypeptide 1 (TCP1) in the bone marrow of newly diagnosed acute myeloid leukemia (AML) patients, and explore its correlation with clinical characteristics and prognosis. METHODS: The bone marrow samples from 80 newly diagnosed AML patients and 30 iron deficiency anemia (IDA) patients were collected, and real time fluorescence quantitative PCR was used to detect the expression level of TCP1 . The clinical data of AML patients were collected, and the correlation of TCP1 expression with clinical characteristics and prognosis of patients were analyzed. The impact of TCP1 on overall survival (OS) of AML patients was identified by using Kaplan-Meier curve analysis. Cox regression analysis was used to identify the factors affecting prognosis of AML patients. RESULTS: Compared with IDA patients, the expression of TCP1 was significantly increased in AML patients (P < 0.01). The high expression group of TCP1 showed a higher proportion of patients with ≥60 years and non-remission after treatment, more accompanied by TET2 mutation and poor prognosis but shorter OS compared to the low expression group (all P < 0.05). The results of multivariate Cox regression analysis showed that age, chromosomal abnormalities, therapeutic efficacy and TCP1 expression were independent risk factors affecting prognosis of AML patients (all P < 0.05). CONCLUSION TCP1 is significantly upregulated in AML patients, and its expression is associated with partial clinical features and poor prognosis. It can serve as a prognostic indicator and potential therapeutic target for AML patients.
Gene Expression Regulation, Leukemic ; Leukemia, Myeloid, Acute/metabolism* ; Humans ; Gene Expression Profiling ; Bone Marrow/metabolism* ; Anemia, Iron-Deficiency/metabolism* ; Polymerase Chain Reaction ; Prognosis ; Kaplan-Meier Estimate ; Proportional Hazards Models ; Multivariate Analysis ; Risk Factors ; Chaperonin Containing TCP-1

Testicular cancer seminoma is one of the most common types of cancer among men of reproductive age. Patients with this condition usually present reduced semen quality, even before initiating cancer therapy. However, the underlying mechanisms by which testicular cancer seminoma affects male fertility are largely unknown. The aim of this study was to investigate alterations in the sperm proteome of men with seminoma undergoing sperm banking before starting cancer therapy, in comparison to healthy proven fertile men (control group). A routine semen analysis was conducted before cryopreservation of the samples (n = 15 per group). Men with seminoma showed a decrease in sperm motility (P = 0.019), total motile count (P = 0.001), concentration (P = 0.003), and total sperm count (P = 0.001). Quantitative proteomic analysis identified 393 differentially expressed proteins between the study groups. Ten proteins involved in spermatogenesis, sperm function, binding of sperm to the oocyte, and fertilization were selected for validation by western blot. We confirmed the underexpression of heat shock-related 70 kDa protein 2 (P = 0.041), ubiquinol-cytochrome C reductase core protein 2 (P = 0.026), and testis-specific sodium/potassium-transporting ATPase subunit alpha-4 (P = 0.016), as well as the overexpression of angiotensin I converting enzyme (P = 0.005) in the seminoma group. The altered expression levels of these proteins are associated with spermatogenesis dysfunction, reduced sperm kinematics and motility, failure in capacitation and fertilization. The findings of this study may explain the decrease in the fertilizing ability of men with seminoma before starting cancer therapy.
Acrosin/metabolism* ; Adult ; Case-Control Studies ; Chaperonin Containing TCP-1/metabolism* ; Electron Transport Complex III/metabolism* ; HSP70 Heat-Shock Proteins/metabolism* ; Humans ; Male ; Peptidyl-Dipeptidase A/metabolism* ; Proteasome Endopeptidase Complex/metabolism* ; Proteomics ; Semen Analysis ; Seminoma/metabolism* ; Sodium-Potassium-Exchanging ATPase/metabolism* ; Sperm Count ; Sperm Motility ; Spermatozoa/metabolism* ; Testicular Neoplasms/metabolism*

PURPOSE: Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. MATERIALS AND METHODS: We used samples from five patients with transudative pleural effusions for internal standard, five patients with tuberculous pleurisy, and the same numbers of patients having malignant effusions were enrolled in the study. We analyzed the proteins in pleural fluid from patients using a technique that combined two-dimensional liquid-phase electrophoresis and matrix assisted laser desorption/ionization-time of flight-mass spectrometry. RESULTS: We identified a total of 10 proteins with statistical significance. Among 10 proteins, trasthyretin, haptoglobin, metastasis-associated protein 1, t-complex protein 1, and fibroblast growth factor-binding protein 1 were related with malignant pleural effusions and human ceruloplasmin, lysozyme precursor, gelsolin, clusterin C complement lysis inhibitor, and peroxirexdoxin 3 were expressed several times or more in tuberculous pleural effusions. CONCLUSION: Highly expressed proteins in malignant pleural effusion were associated with carcinogenesis and cell growth, and proteins associated with tuberculous pleural effusion played a role in the response to inflammation and fibrosis. These findings will aid in the development of novel diagnostic tools for tuberculous pleurisy and malignant pleural effusion of lung cancer.
Biomarkers* ; Carcinogenesis ; Ceruloplasmin ; Chaperonin Containing TCP-1 ; Clusterin ; Diagnosis ; Diagnosis, Differential ; Electrophoresis ; Fibroblasts ; Fibrosis ; Gelsolin ; Haptoglobins ; Humans ; Inflammation ; Lung Neoplasms ; Methods* ; Muramidase ; Pleural Effusion ; Pleural Effusion, Malignant ; Prevalence ; Proteomics ; Spectrum Analysis ; Tuberculosis ; Tuberculosis, Pleural