Cancer Genomics & Proteomics[JOURNAL]
Sun
200 papers
Proteomic and Phosphoproteomic analysis of thyroid papillary carcinoma: Identification of potential biomarkers for metastasis.
Peng L, Zhang Z, Du W … +2 more , Zhu J, Duan W
J Proteomics · 2024 Aug · PMID 39029786 · Publisher ↗
Thyroid cancer has emerged as the most rapidly proliferating solid neoplasm. In this study, we included a cohort of patients who underwent sonographic assessment and surgical intervention at the Sir Run Run Shaw Hospital...
Thyroid cancer has emerged as the most rapidly proliferating solid neoplasm. In this study, we included a cohort of patients who underwent sonographic assessment and surgical intervention at the Sir Run Run Shaw Hospital, associated with the School of Medicine at Zhejiang University, spanning from January 2019 to June 2020. Stratification of cases was based on a combination of preoperative ultrasonographic evaluations and postoperative histopathological diagnoses, resulting in three distinct groups: high-risk papillary thyroid carcinoma (PTC) labeled as C1, low-risk PTC designated as C2, and a control group (N) composed of benign thyroid tissue adjacent to the carcinoma. Proteomic and phosphoproteomic analyses were conducted on PTC specimens. The comparative assessment revealed that proteins up-regulated in the C1/N and C2/N groups were predominantly involved in functions such as amino acid binding, binding of phosphorylated compounds, and serine protease activity. Notably, proteins like NADH dehydrogenase, ATP synthase, oxidoreductases, and iron ion channels were significantly elevated in the C1 versus C2 comparative group. Through meticulous analysis of differential expression multiples, statistical significance, and involvement in metabolic pathways, this study identified eight potential biomarkers pertinent to PTC metastasis diagnostics, encompassing phosphorylated myosin 10, phosphorylated proline-directed protein kinase, leucine tRNA synthetase, 2-oxo-isovalerate dehydrogenase, succinic semialdehyde dehydrogenase, ADP/ATPtranslocase, pyruvate carboxylase, and fibrinogen. Therapeutic assays employing metformin, an AMP-activated protein kinase (AMPK) activator, alongside the phosphorylation-specific inhibitor ML-7 targeting Myosin10, demonstrated attenuated cellular proliferation, migration, and invasion capabilities in thyroid cancer cells, accompanied by a reduction in amino acid pools. Cellular colocalization and interaction studies elucidated that AMPK activation imposes an inhibitory influence on Myosin10 levels. The findings of this research corroborate the utility of proteomic and phosphoproteomic platforms in the identification of metastatic markers for PTC and suggest that modulation of AMPK activity, coupled with the inhibition of Myosin10 phosphorylation, may forge novel therapeutic avenues in the management of thyroid carcinoma. SIGNIFICANCE: The significance of our research lies in its potential to transform the current understanding and management of thyroid papillary carcinoma (PTC), particularly in its metastatic form. By integrating both proteomic and phosphoproteomic analyses, our study not only sheds light on the molecular alterations associated with PTC but also identifies eight novel biomarkers that could serve as indicators of metastatic potential.
Filling the gaps in peptide maps with a platform assay for top-down characterization of purified protein samples.
Bailey AO, Durbin KR, Robey MT … +2 more , Palmer LK, Russell WK
Proteomics · 2024 Nov · PMID 39004851 · Publisher ↗
Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as tr...
Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.
Plasma GPI and PGD are associated with vascular normalization and may serve as novel prognostic biomarkers for lung adenocarcinoma: Multi-omics and multi-dimensional analysis.
Liu Y, Wang Y, Meng Q … +15 more , Mao L, Hu Y, Zhao R, Zhang W, Xu H, Wu Y, Chu J, Chen Q, Tao X, Xu S, Zhang L, Tian T, Tian G, Cui J, Chu M
J Proteomics · 2024 Aug · PMID 38950696 · Publisher ↗
The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD case...
The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SIGNIFICANT: We identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.
Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics.
Ni M, Wan D, Wu J … +3 more , Gong W, Wang J, Zheng Z
J Proteomics · 2024 Jul · PMID 38925351 · Publisher ↗
High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC...
High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SIGNIFICANCE: OC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate.
Discovery and validation of combined biomarkers for the diagnosis of esophageal intraepithelial neoplasia and esophageal squamous cell carcinoma.
Zheng YQ, Huang HH, Chen SX … +9 more , Xu XE, Li ZM, Li YH, Chen SZ, Luo WX, Guo Y, Liu W, Li EM, Xu LY
J Proteomics · 2024 Jul · PMID 38925350 · Publisher ↗
Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial...
Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial neoplasia, IEN). Based on the proteomic and genomic data of esophageal tissue including previously reported data, up-regulated proteins with copy number amplification in esophageal cancer were screened as candidate biomarkers. Five proteins, including KDM2A, RAD9A, ECT2, CYHR1 and TONSL, were confirmed by immunohistochemistry on ESCC and normal esophagus (NE). Then, we investigated the expression of 5 proteins in 236 participants (60 NEs, 93 IENs and 83 ESCCs) which were randomly divided into training set and test set. When distinguishing ESCC from NE, the area under curve (AUC) of the multiprotein model was 0.940 in the training set, while the lowest AUC of a protein was 0.735. In the test set, the results were similar. When distinguishing ESCC from IEN or distinguishing IEN from NE, the diagnostic efficiency of the multi-protein models were also improved compared with that of single protein. Our findings suggest that combined detection of KDM2A, RAD9A, ECT2, CYHR1 and TONSL can be used as potential biomarkers for the early diagnosis of ESCC and precancerous lesion development prediction. SIGNIFICANCE: Candidate biomarkers including KDM2A, RAD9A, ECT2, CYHR1 and TONSL screened by integrating genomic and proteomic data from the esophagus can be used as potential biomarkers for the early diagnosis of esophageal squamous cell carcinoma and precancerous lesion development prediction.
Integrative proteome analysis of bone marrow interstitial fluid and serum reveals candidate signature for acute myeloid leukemia.
Jajula S, Naik V, Kalita B … +7 more , Yanamandra U, Sharma S, Chatterjee T, Bhanuse S, Bhavsar PP, Taunk K, Rapole S
J Proteomics · 2024 Jul · PMID 38866132 · Publisher ↗
Acute myeloid leukemia (AML) is an aggressive form of blood cancer and clinically highly heterogeneous characterized by the accumulation of clonally proliferative immature precursors of myeloid lineage leading to bone ma...
Acute myeloid leukemia (AML) is an aggressive form of blood cancer and clinically highly heterogeneous characterized by the accumulation of clonally proliferative immature precursors of myeloid lineage leading to bone marrow failure. Although, the current diagnostic methods for AML consist of cytogenetic and molecular assessment, there is a need for new markers that can serve as useful candidates in diagnosis, prognosis and understanding the pathophysiology of the disease. This study involves the investigation of alterations in the bone marrow interstitial fluid and serum proteome of AML patients compared to controls using label-free quantitative proteomic approach. A total of 201 differentially abundant proteins were identified in AML BMIF, while in the case of serum 123 differentially abundant proteins were identified. The bioinformatics analysis performed using IPA revealed several altered pathways including FAK signalling, IL-12 signalling and production of macrophages etc. Verification experiments were performed in a fresh independent cohort of samples using MRM assays led to the identification of a panel of three proteins viz., PPBP, APOH, ENOA which were further validated in a new cohort of serum samples by ELISA. The three-protein panel could be helpful in the diagnosis, prognosis and understanding of the pathophysiology of AML in the future. BIOLOGICAL SIGNIFICANCE: Acute Myeloid Leukemia (AML) is a type haematological malignancy which constitute one third of total leukemias and it is the most common acute leukemia in adults. In the current clinical practice, the evaluation of diagnosis and progression of AML is largely based on morphologic, immunophenotypic, cytogenetic and molecular assessment. There is a need for new markers/signatures which can serve as useful candidates in diagnosis and prognosis. The present study aims to identify and validate candidate biosignature for AML which can be useful in diagnosis, prognosis and understand the pathophysiology of the disease. Here, we identified 201 altered proteins in AML BMIF and 123 in serum. Among these altered proteins, a set of three proteins viz., pro-platelet basic protein (CXCL7), enolase 1 (ENO1) and beta-2-glycoprotein 1 (APOH) were significantly increased in AML BMIF and serum suggest that this panel of proteins could help in future AML disease management and thereby improving the survival expectancy of AML patients.
Extracellular vesicle proteins as breast cancer biomarkers: Mass spectrometry-based analysis.
Bandu R, Oh JW, Kim KP
Proteomics · 2024 Jun · PMID 38829178 · Publisher ↗
Extracellular vesicles (EVs) are membrane-surrounded vesicles released by various cell types into the extracellular microenvironment. Although EVs vary in size, biological function, and components, their importance in ca...
Extracellular vesicles (EVs) are membrane-surrounded vesicles released by various cell types into the extracellular microenvironment. Although EVs vary in size, biological function, and components, their importance in cancer progression and the potential use of EV molecular species to serve as novel cancer biomarkers have become increasingly evident. Cancer cells actively release EVs into surrounding tissues, which play vital roles in cancer progression and metastasis, including invasion and immune modulation. EVs released by cancer cells are usually chosen as a gateway in the search for biomarkers for cancer. In this review, we mainly focused on molecular profiling of EV protein constituents from breast cancer, emphasizing mass spectrometry (MS)-based proteomic approaches. To further investigate the potential use of EVs as a source of breast cancer biomarkers, we have discussed the use of these proteins as predictive marker candidates. Besides, we have also summarized the key characteristics of EVs as potential therapeutic targets in breast cancer and provided significant information on their implications in breast cancer development and progression. Information provided in this review may help understand the recent progress in understanding EV biology and their potential role as new noninvasive biomarkers as well as emerging therapeutic opportunities and associated challenges.
A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.
Duong VA, Enkhbayar A, Bhasin N … +11 more , Senavirathna L, Preisner EC, Hoffman KL, Shukla R, Jenq RR, Cheng K, Bronner MP, Figeys D, Britton RA, Pan S, Chen R
Proteomics · 2024 Nov · PMID 38824665 · Full text
The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are...
The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases.
Proteomics coupled transcriptomics reveals Slc34a1 and Slc34a3 downregulation as potential features of nephrotoxin-induced acute kidney injury.
Zhang J, Che T, Wang L … +12 more , Sun W, Zhao J, Chen J, Liu Y, Pu Q, Zhang Y, Li J, Li Z, Zhu Z, Fu Q, Wang X, Yuan J
J Proteomics · 2024 Jun · PMID 38782357 · Publisher ↗
Acute kidney injury (AKI) stands as a prevalent and economically burdensome condition worldwide, yet its complex molecular mechanisms remain incompletely understood. To address this gap, our study employs a multifaceted...
Acute kidney injury (AKI) stands as a prevalent and economically burdensome condition worldwide, yet its complex molecular mechanisms remain incompletely understood. To address this gap, our study employs a multifaceted approach, combining mass spectrometry and RNA sequencing technologies, to elucidate the intricate molecular landscape underlying nephrotoxin-induced AKI in mice by cisplatin- and LPS-induced. By examining the protein and RNA expression profiles, we aimed to uncover novel insights into the pathogenesis of AKI and identify potential diagnostic and therapeutic targets. Our results demonstrate significant down-regulation of Slc34a1 and Slc34a3, shedding light on their crucial roles in AKI pathology and highlighting their promise as actionable targets for diagnosis and treatment. This comprehensive analysis not only enhances our understanding of AKI pathophysiology but also offers valuable avenues for the development of targeted interventions to mitigate its clinical impact. SIGNIFICANCE: Nephrotoxicity acute kidney injury (AKI) is a common clinical condition whose pathogenesis is the process by which some drugs, chemicals or other factors cause damage to the kidneys, resulting in impaired kidney function. Although it has been proved that different nephrotoxic substances can affect the kidney through different pathways, whether they have a commonality has not been registered. Here, we combined transcriptomics and proteomics to study the molecular mechanism of LPS and cisplatin-induced nephrotoxic acute kidney injury finding that the down-regulation of Slc34a1 and Slc34a3 may be a critical link in nephrotoxic acute kidney injury, which can be used as a marker for its early diagnosis.
Quantitative proteomics revealed protein biomarkers to distinguish malignant pleural effusion from benign pleural effusion.
Dong T, Liang Y, Chen H … +3 more , Li Y, Li Z, Gao X
J Proteomics · 2024 Jun · PMID 38768894 · Publisher ↗
To identify protein biomarkers capable of early prediction regarding the distinguishing malignant pleural effusion (MPE) from benign pleural effusion (BPE) in patients with lung disease. A four-dimensional data independe...
To identify protein biomarkers capable of early prediction regarding the distinguishing malignant pleural effusion (MPE) from benign pleural effusion (BPE) in patients with lung disease. A four-dimensional data independent acquisition (4D-DIA) proteomic was performed to determine the differentially expressed proteins in samples from 20 lung adenocarcinoma MPE and 30 BPE. The significantly differential expressed proteins were selected for Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. Protein biomarkers with high capability to discriminate MPE from BPE patients were identified by Random Forest (RF) algorithm prediction model, whose diagnostic and prognostic efficacy in primary tumors were further explored in public datasets, and were validated by ELISA experiment. 50 important proteins (30 up-regulated and 20 down-regulated) were selected out as potential markers to distinguish the MPE from BPE group. GO analysis revealed that those proteins involving the most important cell component is extracellular space. KEGG analysis identified the involvement of cellular adhesion molecules pathway. Furthermore, the Area Under Curve (AUC) of these proteins were ranged from 0.717 to 1.000，with excellent diagnostic properties to distinguish the MPE. Finally, significant survival and gene and protein expression analysis demonstrated BPIFB1, DPP4, HPRT1 and ABI3BP had high discriminating values. SIGNIFICANCE: We performed a 4D-DIA proteomics to determine the differentially expressed proteins in pleural effusion samples from MPE and BPE. Some potential protein biomarkers were identified to distinguish the MPE from BPE patients., which may provide helpful diagnostic and therapeutic insights for lung cancer. This is significant because the median survival time of patients with MPE is usually 4-12 months, thus, it is particularly important to diagnose MPE early to start treatments promptly. The most common causes of MPE are lung cancers, while pneumonia and tuberculosis are the main causes of BPE. If more diagnostic markers could be identified periodically, there would be an important significance to clinical diagnose and treatment with drugs in lung cancer patients.
Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient.
Emery-Corbin SJ, Yousef JM, Adhikari S … +7 more , Sumardy F, Nhu D, van Delft MF, Lessene G, Dziekan J, Webb AI, Dagley LF
Proteomics · 2024 Aug · PMID 38766901 · Publisher ↗
Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and miss...
Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay "CETSA") workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.
Single-cell proteomics by mass spectrometry: Advances and implications in cancer research.
Tan YC, Low TY, Lee PY … +1 more , Lim LC
Proteomics · 2024 Jun · PMID 38727198 · Publisher ↗
Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively se...
Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively searching for information regarding the proteomics counterpart. Therefore recently, single-cell proteomics by mass spectrometry (SCP) has rapidly developed into state-of-the-art technology to cater the need. This review aims to summarize application of SCP in cancer research, while revealing current development progress of SCP technology. The review also aims to contribute ideas into research gaps and future directions, ultimately promoting the application of SCP in cancer research.
Methods and clinical biomarker discovery for targeted proteomics using Olink technology.
Wang H, Zhao T, Zeng J … +9 more , Zhang R, Pu L, Qian S, Xu S, Jiang Y, Pan L, Dai X, Guo X, Han L
Proteomics Clin Appl · 2024 Sep · PMID 38726756 · Publisher ↗
PURPOSE: This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment. EXPERIMENTAL DESIGN: We discusses the application...
PURPOSE: This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment. EXPERIMENTAL DESIGN: We discusses the application of Olink technology in oncology, cardiovascular, respiratory and immune-related diseases, and Outlines the advantages and limitations of Olink technology. RESULTS: Olink technology simplifies the search for therapeutic targets, advances proteomics research, reveals the pathogenesis of diseases, and ultimately helps patients develop precision treatments. CONCLUSIONS: Although proteomics technology has been rapidly developed in recent years, each method has its own disadvantages, so in the future research, more methods should be selected for combined application to verify each other.
Characterization of effective, simple, and low-cost precipitation methods for depleting abundant plasma proteins to enhance the depth and breadth of plasma proteomics.
Rice SJ, Belani CP
Proteomics · 2024 Aug · PMID 38700387 · Publisher ↗
Plasma is an abundant source of proteins and potential biomarkers to aid in the detection, diagnosis, and prognosis of human diseases. These proteins are often present at low levels in the blood and difficult to identify...
Plasma is an abundant source of proteins and potential biomarkers to aid in the detection, diagnosis, and prognosis of human diseases. These proteins are often present at low levels in the blood and difficult to identify and measure due to the large dynamic range of proteins. The goal of this work was to characterize and compare various protein precipitation methods related to how they affect the depth and breadth of plasma proteomic studies. Abundant protein precipitation with perchloric acid (PerCA) can increase protein identifications and depth of plasma proteomic studies. Three acid- and four solvent-based precipitation methods were evaluated. All methods tested provided excellent plasma proteomic coverage (>600 identified protein groups) and detected protein in the low pg/mL range. Functional enrichment analysis revealed subtle differences within and larger changes between the precipitant groups. Methanol-based precipitation outperformed the other methods based on identifications and reproducibility. The methods' performance was verified using eight lung cancer patient samples, where >700 protein groups were measured and proteins with an estimated plasma concentration of ∼10 pg/mL were detected. Various protein precipitation agents are amenable to extending the depth and breadth of plasma proteomes. These data can guide investigators to implement inexpensive, high-throughput methods for their plasma proteomic workflows.
From flesh to bones: Multi-omics approaches in forensic science.
Procopio N, Bonicelli A
Proteomics · 2024 Jun · PMID 38683823 · Publisher ↗
Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from p...
Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.
The tumour-derived extracellular vesicle proteome varies by endometrial cancer histology and is confounded by an obesogenic environment.
Artuyants A, Guo G, Flinterman M … +9 more , Middleditch M, Jacob B, Lee K, Vella L, Su H, Wilson M, Eva L, Shelling AN, Blenkiron C
Proteomics · 2024 Jun · PMID 38644352 · Publisher ↗
Endometrial cancer, the most common gynaecological cancer worldwide, is closely linked to obesity and metabolic diseases, particularly in younger women. New circulating biomarkers have the potential to improve diagnosis...
Endometrial cancer, the most common gynaecological cancer worldwide, is closely linked to obesity and metabolic diseases, particularly in younger women. New circulating biomarkers have the potential to improve diagnosis and treatment selections, which could significantly improve outcomes. Our approach focuses on extracellular vesicle (EV) biomarker discovery by directly profiling the proteome of EVs enriched from frozen biobanked endometrial tumours. We analysed nine tissue samples to compare three clinical subgroups-low BMI (Body Mass Index) Endometrioid, high BMI Endometrioid, and Serous (any BMI)-identifying proteins related to histological subtype, BMI, and shared secreted proteins. Using collagenase digestion and size exclusion chromatography, we successfully enriched generous quantities of EVs (range 204.8-1291.0 µg protein: 1.38 × 10-1.10 × 10 particles), characterised by their size (∼150 nm), expression of EV markers (CD63/81), and proposed endometrial cancer markers (L1CAM, ANXA2). Mass spectrometry-based proteomic profiling identified 2075 proteins present in at least one of the 18 samples. Compared to cell lysates, EVs were successfully depleted for mitochondrial and blood proteins and enriched for common EV markers and large secreted proteins. Further analysis highlighted significant differences in EV protein profiles between the high BMI subgroup and others, underlining the impact of comorbidities on the EV secretome. Interestingly, proteins differentially abundant in tissue subgroups were largely not also differential in matched EVs. This research identified secreted proteins known to be involved in endometrial cancer pathophysiology and proposed novel diagnostic biomarkers (EIF6, MUC16, PROM1, SLC26A2).
Shaping the future of oral cancer diagnosis: advances in salivary proteomics.
Barros O, D'Agostino VG, Lara Santos L … +2 more , Vitorino R, Ferreira R
Expert Rev Proteomics · 2024 Apr · PMID 38626289 · Publisher ↗
INTRODUCTION: Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for th...
INTRODUCTION: Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for the identification of oral cancer biomarkers. This is particularly important because oral cancer is often diagnosed at late stages with a poor prognosis. AREAS COVERED: The review addresses the evolution of the experimental approaches used in salivary proteomics studies of oral cancer over the years and outlines advantages and pitfalls related to each one. In addition, examines the current landscape of oral cancer biomarker discovery and translation focusing on salivary proteomic studies. This discussion is based on an extensive literature search (PubMed, Scopus and Google Scholar). EXPERT OPINION: The introduction of mass spectrometry has revolutionized the study of salivary proteomics. In the future, the focus will be on refining existing methods and introducing powerful experimental techniques such as mass spectrometry with selected reaction monitoring, which, despite their effectiveness, are still underutilized due to their high cost. In addition, conducting studies with larger cohorts and establishing standardized protocols for salivary proteomics are key challenges that need to be addressed in the coming years.
Differential expression of N-glycopeptides derived from serum glycoproteins in mild cognitive impairment (MCI) patients.
Gutierrez Reyes CD, Atashi M, Fowowe M … +4 more , Onigbinde S, Daramola O, Lubman DM, Mechref Y
Proteomics · 2024 Oct · PMID 38602241 · Full text
Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of mo...
Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of more complicated neurodegenerative diseases such as Alzheimer's. Therefore, accurate diagnosis and better understanding of the disease prognosis will facilitate prevention of neurodegeneration. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of the serum N-glycoproteome expression could represent an essential contributor to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using less invasive procedures. In this approach, we identified N-glycopeptides with different expressions between healthy and MCI patients from serum glycoproteins. Seven of the N-glycopeptides showed outstanding AUC values, among them the antithrombin-III Asn224 + 4-5-0-2 with an AUC value of 1.00 and a p value of 0.0004. According to proteomics and ingenuity pathway analysis (IPA), our data is in line with recent publications, and the glycoproteins carrying the identified N-sites play an important role in neurodegeneration.
Proteomic and metabolomic characterization of bone, liver, and lung metastases in plasma of breast cancer patients.
Ye H, Shen X, Li Y … +8 more , Zou W, Hassan SSU, Feng Y, Wang X, Tian J, Shao X, Tao Y, Zhu W
Proteomics Clin Appl · 2024 Sep · PMID 38571380 · Publisher ↗
BACKGROUND: Breast cancer (BC) is the second leading cause of cancer-related deaths among women, primarily due to metastases to other organs rather than the primary tumor. METHODS: In this study, a comprehensive analysis...
BACKGROUND: Breast cancer (BC) is the second leading cause of cancer-related deaths among women, primarily due to metastases to other organs rather than the primary tumor. METHODS: In this study, a comprehensive analysis of plasma proteomics and metabolomics was conducted on a cohort of 51 BC patients. Potential biomarkers were screened by the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithm. Additionally, enzyme-linked immunosorbent assay (ELISA) kits and untargeted metabolomics were utilized to validate the prognostic biomarkers in an independent cohort. RESULTS: In the study, extracellular matrix (ECM)-related functional enrichments were observed to be enriched in BC cases with bone metastases. Proteins dysregulated in retinol metabolism in liver metastases and leukocyte transendothelial migration in lung metastases were also identified. Machine learning models identified specific biomarker panels for each metastasis type, achieving high diagnostic accuracy with area under the curve (AUC) of 0.955 for bone, 0.941 for liver, and 0.989 for lung metastases. CONCLUSIONS: For bone metastasis, biomarkers such as leucyl-tryptophan, LysoPC(P-16:0/0:0), FN1, and HSPG2 have been validated. dUDP, LPE(18:1/0:0), and aspartylphenylalanine have been confirmed for liver metastasis. For lung metastasis, dUDP, testosterone sulfate, and PE(14:0/20:5) have been established.
Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer.
Perera CJ, Hosen SZ, Khan T … +9 more , Fang H, Mekapogu AR, Xu Z, Falasca M, Chari ST, Wilson JS, Pirola R, Greening DW, Apte MV
Proteomics · 2024 Jun · PMID 38570832 · Publisher ↗
Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) rec...
Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) records a very poor survival rate owing to its late diagnosis and several cancer cell-derived proteins have been reported as candidate biomarkers. However, given the pivotal role played by stellate cells (PSCs, which produce the collagenous stroma in PC), it is essential to also assess PSC-sEV cargo in biomarker discovery. Thus, this study aimed to isolate and characterise sEVs from mouse PC cells and PSCs cultured alone or as co-cultures and performed proteomic profiling and pathway analysis. Proteomics confirmed the enrichment of specific markers in the sEVs compared to their cells of origin as well as the proteins that are known to express in each of the culture types. Most importantly, for the first time it was revealed that PSC-sEVs are enriched in proteins (including G6PI, PGAM1, ENO1, ENO3, and LDHA) that mediate pathways related to development of diabetes, such as glucose metabolism and gluconeogenesis revealing a potential role of PSCs in pancreatic cancer-related diabetes (PCRD). PCRD is now considered a harbinger of PC and further research will enable to identify the role of these components in PCRD and may develop as novel candidate biomarkers of PC.
About
- Frequency
- Sun
- Papers found
- 200
- RSS feed
- Subscribe