Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and is the one of the few cancers in which a continued increase in incidence has been observed over several years. HCC associated with chronic liver disease evolves from precancerous lesion and early HCC to overt cancer, and identifying key molecules contributing to early stage HCC is an urgent need. α-Fetoprotein (AFP) is the best serum biomarker for diagnosis of HCC, but sensitivity is low, particularly in detection of early-stage HCC. Therefore, novel and reliable diagnostic biomarkers to complement AFP are needed to improve HCC diagnosis. We aim to determine transcriptome-based molecular signature of multistep hepatocarcinogenesis, and to identify novel serum biomarkers to diagnose early stage HCC patient.
Project description:The aim of this study was to identify and evaluate exosomal miRNAs in serum as early diagnostic markers for gastric cancer (GC). Methods: Using next-generation sequencing (NGS) and bioinformatics, we identified candidate serum exosomal miRNA markers for early detection of GC in patients. The candidates were further validated by qRT-PCR in 50 newly recruited early-stage GC patients and matched healthy individuals. Results: NGS revealed that the average mappable reads in the RNA libraries were about 6.5 million per patient. A total of 66 up and 13 down-regulated exosomal miRNAs were found in the screened cohort after removal of log2 transformed read counts <5 and p >0.05. In the validation cohort, by comparing candidate exosomal miRNAs levels in early-stage GC patients and healthy individuals, higher levels of miR-92b-3p, let-7g-5p, miR-146b-5p and miR-9-5p were found to be significantly associated with GC. Diagnostic power of the combined panels of the exosomal miRNAs or the combination of exosomal miRNAs and CEA outperformed that of single exosomal miRNA marker for establishing a diagnosis of early-stage GC. In addition, serum levels of exosomal miR-92b-3p were significantly associated with low adhesion, let-7g-5p and miR-146b-5p were significantly correlated with nerve infiltration, and miR146b-5p was statistically correlated with tumor invasion depth in early-stage GC. Conclusions: Serum exosomal miR-92b-3p, -146b-5p, -9-5p, and let-7g-5p may serve as potential noninvasive biomarkers for early diagnosis of GC. Further validation of these candidate exosomal miRNAs in larger experimental cohorts are required in order to confirm the diagnostic values.
Project description:We aim to determine blood transcriptome-based molecular signature of acute coronary syndrome (ACS), and to identify novel serum biomarkers for early stage ST-segment-elevation myocardial infarction (STEMI)
Project description:This is the proteomics part of the above project. Purpose: No blood-based biomarkers to detect OPSCC early before symptoms develop or before clinically visible. Diagnosis is solely based on histology of a visible tumour. Most OPSCC patients are diagnosed at an advanced stage, which leads to significant morbidity and poor survival. If high-risk patients were identified with blood-based biomarkers before clear clinical manifestations, tumours could be detected and treated at an earlier stage. Causes of OPSCC include smoking, alcohol misuse, and human papillomavirus (HPV). Tumours are separated according to WHO recommendations into HPV+ OPSCC and HPV- OPSCC using the proxy histological marker p16. We additionally separated our patients into these groups to determine whether the serum glycopeptides would differ between HPV+ and HPV- tumours, as these are distinct clinical entities. Patients and Methods: Pre-treatment sera from 74 patients with OPSCC (including 26 p16- tumours and 48 p16+ tumours) and 12 controls were used, collected between the years 2012 and 2015 at the Department of Otorhinolaryngology – Head and Neck Surgery, Helsinki University Hospital, Helsinki, Finland. Samples were grouped as follows: early stage p16+ OPSCC (stage I only), early stage p16- OPSCC (stage I-II), p16+ (any stage), p16- (any stage), controls. In-parallel quantitative bulk serum proteomics and serum glycopeptidomics were performed. Results: We identified 78 bulk proteins in the serum, of which 33 significantly differed between early-stage p16- OPSCC and controls, 22 between early-stage p16+ OPSCC and controls, 1 between early-stage p16+ and early-stage p16- OPSCCs, and 30 between all p16+ and p16- OPSCCs. We identified glycopeptides from proteins including but not limited to alpha-1-antitrypsin, haptoglobin, and Immunoglobulin heavy constant alpha 1, and compared these with the protein expression levels in each comparison. Conclusions: We have identified novel serum glycopeptide biomarkers detect early-stage OPSCCs, to be evaluated further as a diagnostic panel to detect preclinical OPSCC in at-risk patients.
Project description:This is the glycopeptide part of the above project. Purpose: No blood-based biomarkers to detect OPSCC early before symptoms develop or before clinically visible. Diagnosis is solely based on histology of a visible tumour. Most OPSCC patients are diagnosed at an advanced stage, which leads to significant morbidity and poor survival. If high-risk patients were identified with blood-based biomarkers before clear clinical manifestations, tumours could be detected and treated at an earlier stage. Causes of OPSCC include smoking, alcohol misuse, and human papillomavirus (HPV). Tumours are separated according to WHO recommendations into HPV+ OPSCC and HPV- OPSCC using the proxy histological marker p16. We additionally separated our patients into these groups to determine whether the serum glycopeptides would differ between HPV+ and HPV- tumours, as these are distinct clinical entities. Patients and Methods: Pre-treatment sera from 74 patients with OPSCC (including 26 p16- tumours and 48 p16+ tumours) and 12 controls were used, collected between the years 2012 and 2015 at the Department of Otorhinolaryngology – Head and Neck Surgery, Helsinki University Hospital, Helsinki, Finland. Samples were grouped as follows: early stage p16+ OPSCC (stage I only), early stage p16- OPSCC (stage I-II), p16+ (any stage), p16- (any stage), controls. In-parallel quantitative bulk serum proteomics and serum glycopeptidomics were performed. Results: We identified 78 bulk proteins in the serum, of which 33 significantly differed between early-stage p16- OPSCC and controls, 22 between early-stage p16+ OPSCC and controls, 1 between early-stage p16+ and early-stage p16- OPSCCs, and 30 between all p16+ and p16- OPSCCs. We identified glycopeptides from proteins including but not limited to alpha-1-antitrypsin, haptoglobin, and Immunoglobulin heavy constant alpha 1, and compared these with the protein expression levels in each comparison. Conclusions: We have identified novel serum glycopeptide biomarkers detect early-stage OPSCCs, to be evaluated further as a diagnostic panel to detect preclinical OPSCC in at-risk patients.
Project description:Human serum samples from early-stage Parkinson's disease and non-diseased controls were probed onto human protein microarrays in order to identify differentially expressed autoantibody biomarkers that could be used as diagnostic indicators. Other neurodegenerative and non-neurodegenerative diseases were also used to help measure the specificity of the selected biomarkers.
Project description:We aim to determine blood transcriptome-based molecular signature of acute coronary syndrome (ACS), and to identify novel serum biomarkers for early stage ST-segment-elevation myocardial infarction (STEMI) We obtained peripheral blood from the patients with ACS who visited emergency department within 4 hours after the onset of chest pain: ST-elevation myocardial infarction (STEMI, n=7), Non-ST-elevation MI (NSTEMI, n=10) and unstable angina (UA, n=9), and normal control (n=7)
Project description:Colorectal cancer (CRC) is one of the most prevalent and lethal cancer diseases worldwide. Here, we aimed to identify and quantify CRC serum biomarkers by combining a robust label-free quantification procedure followed of two consecutive steps of targeted parallel reaction monitoring (PRM) for biomarker validation in a fully inclusive proteomic strategy. For the discovery phase pooled serum samples were used for shotgun proteomics and label-free quantification. On the identification phase, 116 potential biomarkers were selected based on their statistical significance and their relative expression in disease stages respect to healthy stage and their functional relation with cancer progression. Verification phase was conducted in 2 steps. In the first step, 318 peptides from 116 proteins were used for PRM verification giving place to 23 PRM-quantifiable, potential CRC biomarkers. In a second step, 7 peptides corresponding to CO9, APOC3, CRP, THSB1, ECM1 and IGF2 proteins were reproducibly confirmed by PRM in every CRC stage for these unfractionated samples. Finally, a different cohort composed by individual serum samples was used in the final validation phase. In individual serum samples, 5 peptides belonging to 4 proteins were consistently quantified and validated. ROC analyses indicated that peptides GWVTDGFSSLK and LCNNPTPQFGGK were suitable candidates for predicting the separation between control and CRC patients. Two assays for absolute quantification of significant peptides in serum samples were established using AQUA peptides. In conclusion, a set of serum peptides were validated by PRM as potential biomarkers for differentiating control from CRC patients.
Project description:MicroRNAs (miRNAs), which are stably present in serum, have been reported to be potentially useful for detecting cancer. In the present study, we examined the expression profiles of serum miRNAs in large cohorts to identify the miRNAs that can be used to detect breast cancer in the early stage. We comprehensively evaluated serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1,280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. Additionally, 2,836 serum samples were obtained from non-cancer controls and 514 from patients with other types of cancers or benign diseases. The samples were divided to a training cohort including non-cancer controls, other cancers and breast cancer and a test cohort including non-cancer controls and breast cancer. The training cohort was used to identify a combination of miRNAs that detect breast cancer, and the test cohort was used to validate that combination. miRNA expression was compared between breast cancer and non-breast cancer serum , and a combination of five miRNAs (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p, and miR-6875-5p) was found to detect breast cancer. This combination had a sensitivity of 97.3%, specificity of 82.9%, and accuracy of 89.7% for breast cancer in the test cohort Additionally, the combination could detect breast cancer in the early stage (sensitivity of 98.0% for T0).