Project description:The study aim was to identify novel serum markers of prostate cancer diagnosis compared to benign prostate hyperplasia and healthy controls
Project description:Although an increased level of the prostate-specific antigen can be an indication for prostate cancer, other reasons often lead to a high rate of false positive results. Therefore, an additional serological screening of autoantibodies in patients’ sera could improve the detection of prostate cancer. We performed protein macroarray screening with sera from 49 prostate cancer patients, 70 patients with benign prostatic hyperplasia and 28 healthy controls and compared the autoimmune response in those groups. We were able to distinguish prostate cancer patients from normal controls with an accuracy of 83.2%, patients with benign prostatic hyperplasia from normal controls with an accuracy of 86.0% and prostate cancer patients from patients with benign prostatic hyperplasia with an accuracy of 70.3%. Combining seroreactivity pattern with a PSA level of higher than 4.0 ng/ml this classification could be improved to an accuracy of 84.1%. For selected proteins we were able to confirm the differential expression by using Lluminex on 84 samples. We provide a minimally invasive serological method to reduce false positive results in detection of prostate cancer and according to PSA screening to distinguish men with prostate cancer from men with benign prostatic hyperplasia.
Project description:Despite its low incidence, the aggressive nature and high metastatic potential of canine prostate cancer (PC) make it a serious problem in veterinary medicine. However, knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is still limited. We used RNAseq to identify diffentially expressed genes between PC (n=2) and benign prostate hyperplasia (BPH, n=3) samples. Based on these results, we chose 26 genes for validation on a larger patient cohorts. We used Nanosting nCounter technology for the comparative analysis of gene expression profiles in PC (n=14) and BPH (n=7) tissue samples. Finally the results for voltage-dependent calcium channel α2δ1 subunit were validated using Western blotting and immunohistochemistry.
Project description:Despite its low incidence, the aggressive nature and high metastatic potential of canine prostate cancer (PC) make it a serious problem in veterinary medicine. However, knowledge of the molecular mechanisms and regulatory networks underlying the development and progression of canine PC is still limited. We used RNAseq to identify diffentially expressed genes between PC (n=2) and benign prostate hyperplasia (BPH, n=3) samples. Based on these results, we chose 26 genes for validation on a larger patient cohorts. We used Nanosting nCounter technology for the comparative analysis of gene expression profiles in PC (n=14) and BPH (n=7) tissue samples. Finally the results for voltage-dependent calcium channel α2δ1 subunit were validated using Western blotting and immunohistochemistry.
Project description:Proteomic sequencing was performed on 5 prostate cancer patient tissues and 5 benign prostatic hyperplasia patient tissues collected from Beijing Tongren Hospital Affiliated to Capital Medical University. Differential genes related to the prognosis of prostate cancer were identified, and enrichment analysis was conducted on prostate cancer patients based on these genes to clarify the biological functions in prostate cancer cells that significantly affect cancer cell progression. Lactylation modification proteomic sequencing revealed the sites in prostate cancer that promote prostate cancer progression due to lactylation modification, providing potential therapeutic methods for the treatment of prostate cancer.
Project description:There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants with a diagnosis of PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model was able to separate PCa from controls with sensitivity of 0.82 and specificity of 0.95, adding BPH resulted in a statistically significant decline in specificity for prostate cancer to 0.76, with half of BPH cases being misclassified by the model as PCa. A small number of biomarkers differentiating between BPH and prostate cancer were identified, including proteins in MAP Kinase pathways, as well as in lipids containing oleic acid; these may offer a route to greater specificity. These results highlight, however, that whilst there are opportunities for machine learning, these will only be achieved by use of appropriate training sets that include confounding comorbidities, especially when calculating the specificity of a test.