Proteomics reveal serum biomarkers for early diagnosis in premature ovarian insufficiency
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ABSTRACT:
ORGANISM(S): Homo Sapiens (human)
SUBMITTER: Xiaomin Hu
PROVIDER: PXD078636 | JPOST Repository | Wed May 27 00:00:00 BST 2026
REPOSITORIES: jPOST
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Project description:Early diagnosis of biliary atresia (BA) is crucial for improving the chances of survival and preserving the liver function of children with BA. To explore potential biomarkers for early diagnosis of BA with other non-BA jaundice cases, we performed proteomic analysis with data-independent acquisition (DIA) and parallel reaction monitoring (PRM). With this approach we were able to detect and validate differential protein expression in plasma of patients. Bioinformatics analysis revealed the enrichment biological processes, characteristic of BA by identifying differential expression of specific proteins of which with 10 were up- and 23 down-regulated. Signaling pathway analysis demonstrated changes in protein expression associated with an alteration in immunoglobins levels, which is indicative immune dysfunction in BA. When polymeric immunoglobulin receptor (pIgR) expression was combined with an immunoglobulin lambda variable chain (IGL c2225_light_IGLV1-47_IGLJ2), revealed by machine learning, they provided a useful early diagnostic model for BA, which had a sensitivity of 0.8, specificity of 1, accuracy of 0.89, and AUC value of 0.944. Our study not only identified a possible effective plasma biomarker for the early diagnosis of BA but may also help to further elucidate the underlying mechanisms of BA.
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Project description:The present study explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide potential biomarkers for their use in non-invasive screening strategies for the early detection of lung cancer (LC). EBC was collected from 192 individuals (49 control volunteers, 49 risk factor-smoking volunteers, 46 chronic obstructive pulmonary disease patients and 48 LC patients). Using LC-MS/MS a total of 348 different proteins with a different pattern among the four groups were identified in EBC samples. Despite the great variability observed among individuals, significantly more proteins were identified in the EBC from LC patients compared to other groups. Furthermore, the average number of proteins identified per sample was significantly higher in LC patients and Receiver Operating Characteristic curve analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histone isoforms, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples and levels of KRT6A, KRT6B and KRT6C isoforms were significantly higher in samples from LC patients. Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC. Thus, this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer.
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Project description:Proteomics reveal serum biomarkers for early diagnosis in premature ovarian insufficiency
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Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Late presentation of disease at the time of diagnosis is one of the major reasons for dismal prognostic outcomes for PDAC patients. Currently, there is a lack of clinical biomarkers which can be used to diagnose PDAC patients at an early resectable stage. This study performed proteomic mass spectrometry to identify novel blood-based biomarkers for early diagnosis of PDAC.
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Project description:Background & Aims: Cholangiocarcinomas (CCAs), heterogeneous biliary tumors with dismal prognosis, lack accurate early-diagnostic methods, especially important for individuals at high-risk (i.e., primary sclerosing cholangitis (PSC)). Here, we searched for protein biomarkers in serum extracellular vesicles (EVs). Methods: EVs from patients with isolated PSC (n=45), concomitant PSC-CCA (n=42), PSC who developed CCA during follow-up (PSC to CCA; n=25), CCAs from non-PSC etiology (n=56), hepatocellular carcinoma (n=34) and healthy individuals (n=55) were characterized by mass-spectrometry. Diagnostic biomarkers of PSC-CCA, non-PSC CCA or CCAs regardless etiology (pan-CCAs) were defined, and their expression was evaluated in human organs/tissues and within CCA tumors at single-cell level. Prognostic EV-biomarkers for CCA were investigated. Results: High-throughput proteomics identified candidate diagnostic biomarkers for PSC-CCA, non-PSC CCA or pan-CCA, as well as and for differential diagnosis of intrahepatic CCA and HCC, that were cross-validated by ELISA using total serum. Machine learning logit modelling disclosed CRP/FRIL/Fibrinogen algorithm with diagnostic value for early-stage PSC-CCA vs isolated PSC (AUC=0.944; OR=82.0), overpowering CA19-9 (AUC=0.735; OR=9.3). An algorithm combining CRP/VWF/PIGR/ /Fibrinogen allowed the diagnosis of early-stage non-PSC CCAs compared to healthy individuals (AUC=0.999; OR=1115). Noteworthy, levels of Fibrinogen/CRP/PIGR/FRIL showed predictive capacity for CCA development in patients with PSC before clinical evidences of malignancy. Multi-organ transcriptomic analysis revealed that serum EV-biomarkers were mostly expressed in hepatobiliary tissues, and scRNA-seq and immunofluorescence analysis of CCA tumors showed their presence mainly in malignant cholangiocytes. Multivariable analysis unveiled EVprognostic biomarkers independent to clinical features, with COMP/GNAI2/CFAI and ACTN1/MYCT1/PF4V associated negatively or positively to patients’ survival, respectively. Conclusions: Serum EVs contain protein biomarkers for the prediction, early diagnosis and prognosis estimation of CCA, representing a novel tumor cell-derived liquid biopsy for personalized medicine.
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Project description:Background & Aims: Cholangiocarcinomas (CCAs), heterogeneous biliary tumors with dismal prognosis, lack accurate early-diagnostic methods, especially important for individuals at high-risk (i.e., primary sclerosing cholangitis (PSC)). Here, we searched for protein biomarkers in serum extracellular vesicles (EVs). Methods: EVs from patients with isolated PSC (n=45), concomitant PSC-CCA (n=42), PSC who developed CCA during follow-up (PSC to CCA; n=25), CCAs from non-PSC etiology (n=56), hepatocellular carcinoma (n=34) and healthy individuals (n=55) were characterized by mass-spectrometry. Diagnostic biomarkers of PSC-CCA, non-PSC CCA or CCAs regardless etiology (pan-CCAs) were defined, and their expression was evaluated in human organs/tissues and within CCA tumors at single-cell level. Prognostic EV-biomarkers for CCA were investigated. Results: High-throughput proteomics identified candidate diagnostic biomarkers for PSC-CCA, non-PSC CCA or pan-CCA, as well as and for differential diagnosis of intrahepatic CCA and HCC, that were cross-validated by ELISA using total serum. Machine learning logit modelling disclosed CRP/FRIL/Fibrinogen algorithm with diagnostic value for early-stage PSC-CCA vs isolated PSC (AUC=0.944; OR=82.0), overpowering CA19-9 (AUC=0.735; OR=9.3). An algorithm combining CRP/VWF/PIGR/ /Fibrinogen allowed the diagnosis of early-stage non-PSC CCAs compared to healthy individuals (AUC=0.999; OR=1115). Noteworthy, levels of Fibrinogen/CRP/PIGR/FRIL showed predictive capacity for CCA development in patients with PSC before clinical evidences of malignancy. Multi-organ transcriptomic analysis revealed that serum EV-biomarkers were mostly expressed in hepatobiliary tissues, and scRNA-seq and immunofluorescence analysis of CCA tumors showed their presence mainly in malignant cholangiocytes. Multivariable analysis unveiled EVprognostic biomarkers independent to clinical features, with COMP/GNAI2/CFAI and ACTN1/MYCT1/PF4V associated negatively or positively to patients’ survival, respectively. Conclusions: Serum EVs contain protein biomarkers for the prediction, early diagnosis and prognosis estimation of CCA, representing a novel tumor cell-derived liquid biopsy for personalized medicine.
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Project description:Hemophagocytic Lymphohistiocytosis (HLH) shares many clinical features with sepsis. To improve HLH diagnosis and its differential diagnosis with sepsis, serum proteomic analyses of healthy donors, HLH and septic patients were performed. In this study, 24 individuals were enrolled in a label free MS/MS spectrometry analysis. Proteomic results revealed 537 differentially expressed proteins (DEP) between HLH and sepsis, 471 DEP between HLH and healthy donors and 37 DEP between sepsis and healthy donors. After protein identification and quantification, results were subjected to functional analysis to study impaired processes in each condition. These functional analyses showed that, apart from inflammation and lipid metabolism, the proteostasis network was deeply impaired in HLH condition. Considering this information, each protein fold changes, their function, and other previously published related to DEP, six proteins were validated by ELISA in a larger cohort of patients and healthy donors. Our results revealed that sCD300a, sCD300b and sCD25 could be specific serum biomarkers for HLH diagnosis. SAA-1 and LRG1 might be useful biomarkers for differential diagnosis between sepsis and HLH, and PSMB1 showed promising results for HLH specific and differential diagnosis. In this sense, PSMB1 was an interesting biomarker and its elevation in HLH patients may reflect an intensified demand for protein turnover, possibly driven by a higher activation of immunoproteasome. These insights contribute to expand our understanding of HLH pathophysiology in new pathways and highlight innovative therapeutic intervention such as Bortezomib and other next-generation inhibitors designed to modulate immunoproteasome activity
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