Clinical proteomics最新文献

Background: The diagnosis and treatment of colorectal cancer (CRC), especially metastatic colorectal cancer (mCRC), is a major priority and research challenge. We screened for expression differences in the plasma exosomal proteomes of patients with mCRC, those with CRC, and healthy controls (HCs) to discover potential biomarkers for mCRC.

Methods: Plasma samples from five patients with mCRC, five patients with CRC, and five HCs were collected and processed to isolate exosomes by ultracentrifugation. Exosomal protein concentrations were determined using the BCA kit, and liquid chromatography-mass spectrometry was utilized to identify and analyze the proteins.

Results: From the exosomes isolated from plasma samples, a total of 994 quantifiable proteins were detected, including 287 differentially expressed proteins identified by quantitative proteomics analyses. Totals of 965, 963 and 968 proteins were identified in mCRC patients, CRC patients, and HCs, respectively. The study identified 83 proteins with differential expression in the plasma exosomes of mCRC patients. The top 10 upregulated proteins in the mCRC group and CRC groups were ITGA4, GNAI1, SFTPA2, UGGT1, GRN, LBP, SMIM1, BMP1, HMGN5, and MFAP4, while the top 10 downregulated proteins were PSMB8, LCK, RAB35, PSMB4, CD81, CD63, GLIPR2, RAP1B, RAB30, and CES1. Western Blot validation data confirmed that ITGA4 and GNAI1 were unequivocally enriched in plasma-derived exosomes from mCRC patients.

Conclusions: These differential proteins offer potential new candidate molecules for further research on the pathogenesis of mCRC and the identification of therapeutic targets. This study sheds light on the potential significance of plasma exosome proteomics studies in our understanding and treatment of mCRC.

Background: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying proteoform sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

Methods: Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

Results: From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation. Data are available via ProteomeXchange with the identifier PXD051505.

Conclusion: By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Background: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder often misdiagnosed as Parkinson's Disease (PD) due to shared symptoms. PSP is characterized by the accumulation of tau protein in specific brain regions, leading to loss of balance, gaze impairment, and dementia. Diagnosing PSP is challenging, and there is a significant demand for reliable biomarkers. Existing biomarkers, including tau protein and neurofilament light chain (NfL) levels in cerebrospinal fluid (CSF), show inconsistencies in distinguishing PSP from other neurodegenerative disorders. Therefore, the development of new biomarkers for PSP is imperative.

Methods: We conducted an extensive proteome analysis of CSF samples from 40 PSP patients, 40 PD patients, and 40 healthy controls (HC) using tandem mass tag-based quantification. Mass spectrometry analysis of 120 CSF samples was performed across 13 batches of 11-plex TMT experiments, with data normalization to reduce batch effects. Pathway, interactome, cell-type-specific enrichment, and bootstrap receiver operating characteristic analyses were performed to identify key candidate biomarkers.

Results: We identified a total of 3,653 unique proteins. Our analysis revealed 190, 152, and 247 differentially expressed proteins in comparisons of PSP vs. HC, PSP vs. PD, and PSP vs. both PD and HC, respectively. Gene set enrichment and interactome analysis of the differentially expressed proteins in PSP CSF showed their involvement in cell adhesion, cholesterol metabolism, and glycan biosynthesis. Cell-type enrichment analysis indicated a predominance of neuronally-derived proteins among the differentially expressed proteins. The potential biomarker classification performance demonstrated that ATP6AP2 (reduced in PSP) had the highest AUC (0.922), followed by NEFM, EFEMP2, LAMP2, CHST12, FAT2, B4GALT1, LCAT, CBLN3, FSTL5, ATP6AP1, and GGH.

Conclusion: Biomarker candidate proteins ATP6AP2, NEFM, and CHI3L1 were identified as key differentiators of PSP from the other groups. This study represents the first large-scale use of mass spectrometry-based proteome analysis to identify cerebrospinal fluid (CSF) biomarkers specific to progressive supranuclear palsy (PSP) that can differentiate it from Parkinson's disease (PD) and healthy controls. Our findings lay a crucial foundation for the development and validation of reliable biomarkers, which will enhance diagnostic accuracy and facilitate early detection of PSP.

Background: Proteomics and metabolomics offer substantial potential for advancing kidney transplant research by providing versatile opportunities for gaining insights into the biomolecular processes occurring in donors, recipients, and grafts. To achieve this, adequate quality and numbers of biological samples are required. Whilst access to donor samples is facilitated by initiatives such as the QUOD biobank, an adequately powered biobank allowing exploration of recipient-related aspects in long-term transplant outcomes is missing. Rich, yet unverified resources of recipient material are the serum repositories present in the immunological laboratories of kidney transplant centers that prospectively collect recipient sera for immunological monitoring. However, it is yet unsure whether these samples are also suitable for -omics applications, since such clinical samples are collected and stored by individual centers using non-uniform protocols and undergo an undocumented number of freeze-thaw cycles. Whilst these handling and storage aspects may affect individual proteins and metabolites, it was reasoned that incidental handling/storage artifacts will have a limited effect on a theoretical network (pathway) analysis. To test the potential of such long-term stored clinical serum samples for pathway profiling, we submitted these samples to discovery proteomics and metabolomics.

Methods: A mass spectrometry-based shotgun discovery approach was used to obtain an overview of proteins and metabolites in clinical serum samples from the immunological laboratories of the Dutch PROCARE consortium. Parallel analyses were performed with material from the strictly protocolized QUOD biobank.

Results: Following metabolomics, more than 800 compounds could be identified in both sample groups, of which 163 endogenous metabolites were found in samples from both biorepositories. Proteomics yielded more than 600 proteins in both groups. Despite the higher prevalence of fragments in the clinical, non-uniformly collected samples compared to the biobanked ones (42.5% vs 26.5% of their proteomes, respectively), these fragments could still be connected to their parent proteins. Next, the proteomic and metabolomic profiles were successfully mapped onto theoretical pathways through integrated pathway analysis, which showed significant enrichment of 79 pathways.

Conclusions: This feasibility study demonstrated that long-term stored serum samples from clinical biorepositories can be used for qualitative proteomic and metabolomic pathway analysis, a notion with far-reaching implications for all biomedical, long-term outcome-dependent research questions and studies focusing on rare events.

Background: Mycosis fungoides (MF) is the most common type of cutaneous T cell lymphoma. As the early clinical manifestations of MF are non-specific (e.g., erythema or plaques), it is often misdiagnosed as inflammatory skin conditions (e.g., atopic dermatitis, psoriasis, and pityriasis rosea), resulting in delayed treatment. As there are no effective biological markers for the early detection and management of MF, the aim of the present study was to perform a proteomic analysis of urine samples (as a non-invasive protein source) to identify reliable MF biomarkers.

Methods: Thirteen patients with early-stage MF were administered a subcutaneous injection of interferon α-2a in combination with phototherapy for 6 months. The urine proteome of patients with early-stage MF before and after treatment was compared against that of healthy controls by liquid chromatography-tandem mass spectrometry. The differentially expressed proteins were subjected to Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Clusters of Orthologous Groups analyses. For validation, the levels of the selected proteins were evaluated by enzyme-linked immunosorbent assay (ELISA).

Results: We identified 41 differentially expressed proteins (11 overexpressed and 30 underexpressed) between untreated MF patients and healthy control subjects. The proteins were mainly enriched in focal adhesion, endocytosis, and the PI3K-Akt, phospholipase D, MAPK, and calcium signaling pathways. The ELISA results confirmed that the urine levels of Serpin B5, epidermal growth factor (EGF), and Ras homologous gene family member A (RhoA) of untreated MF patients were significantly lower than those of healthy controls. After 6 months of treatment, however, there was no significant difference in the urine levels of Serpin B5, EGF, and RhoA between MF patients and healthy control subjects. The area under the receiver operating characteristic curve values for Serpin B5, EGF, and RhoA were 0.817, 0.900, and 0.933, respectively.

Conclusions: This study showed that urine proteomics represents a valuable tool for the study of MF, as well as identified potential new biomarkers (Serpin B5, EGF, and RhoA), which could be used in its diagnosis and management.

Background: Tumor recurrence and metastatic progression remains the leading cause for breast cancer related mortalities. However, the proteomes of patient- matched primary breast cancer (BC) and metastatic lesions have not yet been identified, due to the lack of clinically annotated longitudinal samples. In this study, we evaluated the global-proteomic landscape of BC patients with and without distant metastasis as well as compared the proteome of distant metastatic disease with its corresponding primary BC, within the same patient.

Methods: We performed mass spectrometry-based proteome profiling of 73 serum samples from 51 BC patients. Among the 51 patients with BC, 29 remained metastasis-free (henceforth called non-progressors), and 22 developed metastases (henceforth called progressors). For the 22 progressors, we obtained two samples: one collected within a year of diagnosis, and the other collected within a year before the diagnosis of metastatic disease. MS data were analyzed using intensity-based absolute quantification and normalized before differential expression analysis. Significantly differentially expressed proteins (DEPs; absolute fold-change ≥ 1.5, P-value < 0.05 and 30% abundance per clinical group) were subjected to pathway analyses.

Results: We identified 967 proteins among 73 serum samples from patients with BC. Among these, 39 proteins were altered in serum samples at diagnosis, between progressors and non-progressors. Among these, 4 proteins were further altered when the progressors developed distant metastasis. In addition, within progressors, 20 proteins were altered in serum collected at diagnosis versus at the onset of metastasis. Pathway analysis showed that these proteins encoded pathways that describe metastasis, including epithelial-mesenchymal transition and focal adhesion that are hallmarks of metastatic cascade.

Conclusions: Our results highlight the importance of examining matched samples from distant metastasis with primary BC samples collected at diagnosis to unravel subset of proteins that could be involved in BC progression in serum. This study sets the foundation for additional future investigations that could position these proteins as non-invasive markers for clinically monitoring breast cancer progression in patients.

Background: The molecular mechanisms underlying development of posthemorrhagic hydrocephalus (PHH) following subarachnoid hemorrhage (SAH) remain incompletely understood. Consequently, treatment strategies tailored towards the individual patient remain limited. This study aimed to identify proteomic cerebrospinal fluid (CSF) biomarkers capable of predicting shunt dependency and functional outcome in patients with SAH in order to improve informed clinical decision making.

Methods: Ventricular CSF samples were collected twice from 23 patients with SAH who required external ventricular drain (EVD) insertion (12 patients with successful EVD weaning, 11 patients in need of permanent CSF shunting due to development of PHH). The paired CSF samples were collected acutely after ictus and later upon EVD removal. Cisternal CSF samples were collected from 10 healthy control subjects undergoing vascular clipping of an unruptured aneurysm. All CSF samples were subjected to mass spectrometry-based proteomics analysis. Proteomic biomarkers were quantified using area under the curve (AUC) estimates from a receiver operating curve (ROC).

Results: CSF from patients with SAH displayed a distinct proteomic profile in comparison to that of healthy control subjects. The CSF collected acutely after ictus from patients with SAH was moreover distinct from that collected weeks later but appeared similar in the weaned and shunted patient groups. Sixteen unique proteins were identified as potential predictors of shunt dependency, while three proteins were identified as potential predictors of functional outcome assessed six months after ictus with the modified Rankin Scale.

Conclusions: We here identified several potential proteomic biomarkers in CSF from patients with SAH capable of predicting (i) shunt dependency and thus development of PHH and (ii) the functional outcome assessed six months after ictus. These proteomic biomarkers may have the potential to aid clinical decision making by predicting shunt dependency and functional outcome following SAH.

Background: Estrogen receptor-positive (ER+) breast cancer accounts for two-thirds of all breast cancers, and its early and late recurrences still threaten patients' long-term survival and quality of life. Finding candidate tumor antigens and potential therapeutic targets is critical to addressing these unmet needs.

Method: The isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to identify the differentially expressed proteins (DEPs) between ER + breast cancer and corresponding adjacent normal tissue. Candidate DEPs were screened by bioinformatic analyses, and their expression was confirmed by immunohistochemical (IHC) staining and western blot. A series of in vitro experiments, including wound healing assay, colony formation, and cell cycle assay, were performed to reveal the functions of selected DEPs. Additionally, their clinical significances were further analyzed.

Result: A total of 369 DEPs (fold change ≥ 2.0 or ≤ 0.66, P < 0.05) were discovered. Compared with normal tissue, 358 proteins were up-regulated and 11 proteins were down-regulated in ER + breast cancer. GO and KEGG enrichment analysis showed that DEPs were closely associated with RNA regulation and metabolic pathways. STRING analysis found ESF1 and MIPEP were the hub genes in breast cancer, whose increased expressions were verified by the IHC staining and western blot. Knocking down ESF1 and MIPEP inhibited colony formation and increased cell apoptosis. Besides, knocking down ESF1 inhibited wound healing but not MIPEP. In addition, ESF1 and MIPEP expression were negatively associated with patient prognosis.

Conclusion: The upregulation of ESF1 and MIPEP promoted ER + breast cancer proliferation, which might provide novel targets for the development of new therapies.

Background: Characterization of the host response in cutaneous leishmaniasis (CL) through proteome profiling has gained limited insights into leishmaniasis research compared to that of the parasite. The primary objective of this study was to comprehensively analyze the proteomic profile of the skin lesions tissues in patients with CL, by mass spectrometry, and subsequent validation of these findings through immunohistochemical methods.

Methods: Eight lesion specimens from leishmaniasis-confirmed patients and eight control skin biopsies were processed for proteomic profiling by mass spectrometry. Formalin-fixed paraffin-embedded lesion specimens from thirty patients and six control skin specimens were used for Immunohistochemistry (IHC) staining. Statistical analyses were carried out using SPSS software. The chi-square test was used to assess the association between the degree of staining for each marker and the clinical and pathological features.

Results: Sixty-seven proteins exhibited significant differential expression between tissues of CL lesions and healthy controls (p < 0.01), representing numerous enriched biological processes within the lesion tissue, as evident by both the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Among these, the integrated endoplasmic reticulum stress response (IERSR) emerges as a pathway characterized by the up-regulated proteins in CL tissues compared to healthy skin. Expression of endoplasmic reticulum (ER) stress sensors, inositol-requiring enzyme-1 (IRE1), protein kinase RNA-like ER kinase (PERK) and activating transcription factor 6 (ATF6) in lesion tissue was validated by immunohistochemistry.

Conclusions: In conclusion, proteomic profiling of skin lesions carried out as a discovery phase study revealed a multitude of probable immunological and pathological mechanisms operating in patients with CL in Sri Lanka, which needs to be further elaborated using more in-depth and targeted investigations. Further research exploring the intricate interplay between ER stress and CL pathophysiology may offer promising avenues for the development of novel diagnostic tools and therapeutic strategies in combating this disease.