Cancer Genomics & Proteomics[JOURNAL]
Sun
200 papers
Time-Enduring Proteomic Fidelity in Over 30-Year-Old FFPE Tissues: Distinct Proteomic Signatures of Hepatocellular Carcinoma and Adjacent Non-Tumor Liver Tissue.
Adachi Y, Ishii M, Noguchi R … +5 more , Hiraoka N, Yokoo H, Yoshimatsu Y, Ohtsuki S, Kondo T
Proteomics · 2026 Jan · PMID 41450324 · Publisher ↗
Formalin-fixed paraffin-embedded (FFPE) tissues are crucial clinical archives linked with long-term follow-up data, yet the suitability of deep proteomic analysis on samples stored over 30 years remains largely unexplore...
Formalin-fixed paraffin-embedded (FFPE) tissues are crucial clinical archives linked with long-term follow-up data, yet the suitability of deep proteomic analysis on samples stored over 30 years remains largely unexplored. This study aimed to verify the feasibility of deep proteomic analysis on extremely long-term stored FFPE samples. We employed adaptive focused acoustics (AFA) technology for efficient protein extraction, combined with SP3 cleanup and data-independent acquisition (DIA) mass spectrometry using a ZenoTOF 7600, to analyze FFPE samples of hepatocellular carcinoma (HCC) and adjacent non-tumor liver (NTL) tissues from 19 HCC patients from 1988 to 1992. Our workflow identified and quantified approximately 7000 proteins, with excellent reproducibility. Proteomic profiles clearly distinguished HCC from NTL tissues. We identified 630 differentially expressed proteins (467 upregulated in HCC, 163 upregulated in NTL). Pathway analysis revealed expected biological differences: HCC showed enrichment in proliferation/genomic maintenance pathways (e.g., ribosome biogenesis, DNA replication), while NTL showed enrichment in metabolic pathways (e.g., cytochrome P450), consistent with known biology and validated by COSMIC database. Comprehensive, biologically relevant proteomic data can be obtained from FFPE archives over 30 years old. Our validated workflow unlocks the potential of these historically invaluable specimens for powerful retrospective studies, contributing to our understanding of cancer such as HCC.
Middle-down proteomics: the pursuit for longer peptides.
Hovey OFJ, Lajoie GA, Cooper TT
Expert Rev Proteomics · 2025 · PMID 41399164 · Publisher ↗
INTRODUCTION: Middle-down proteomics (MDP) bridges bottom-up and top-down proteomics, analyzing 3-10 kDa peptides to enhance sequence coverage and post-translational modification (PTM) localization. This approach is cruc...
INTRODUCTION: Middle-down proteomics (MDP) bridges bottom-up and top-down proteomics, analyzing 3-10 kDa peptides to enhance sequence coverage and post-translational modification (PTM) localization. This approach is crucial for decoding complex proteoforms and PTM networks, advancing insights into biological and disease processes. However, its application to complex samples like cell lysates or biofluids remains largely underexplored. AREAS COVERED: This review examines MDP's potential in complex biological samples, focusing on sample preparation, chromatography, mass spectrometry, and bioinformatics. We explore sample lysis, protein precipitation, and alternative proteases (GluC, thermolysin), supported by analyses revealing peptide length and charge distribution as key limitations for current enzymes. Advanced chromatographic techniques, ion mobility (FAIMS, TIMS), and fragmentation methods (ETD, EThcD) are discussed. Experimental challenges include peptide solubility, ionization efficiency, and bioinformatic complexity from missed cleavages and promiscuous protease specificity. EXPERT OPINION: MDP offers significant potential to uncover the 'dark' proteome, including PTM-rich regions and proteoforms undetectable by traditional workflows. However, a focused effort on improving high-throughput workflows will require optimizations to enzyme selection, LC-MS parameters, peptide ionization, ion mobility, ion fragmentation, and tailored algorithms are essential to drive MDP's adoption. Only then will deeper proteomic insights and breakthroughs in biological research be obtained.
Discovery and targeted mass spectrometry-based proteomics of ovarian cancer.
Platzer NE, Hummon AB
Expert Rev Proteomics · 2025 · PMID 41367230 · Publisher ↗
INTRODUCTION: Ovarian cancer is the most lethal gynecologic malignancy and has seen little progress in early detection and treatment. Mass spectrometry-based proteomics is a powerful technique that can be used to underst...
INTRODUCTION: Ovarian cancer is the most lethal gynecologic malignancy and has seen little progress in early detection and treatment. Mass spectrometry-based proteomics is a powerful technique that can be used to understand tumor biology and identify novel biomarkers that could transform diagnosis, prognosis, and treatment. AREAS COVERED: This review highlights recent applications of proteomics in ovarian cancer research. Tissue studies have defined histotype-specific pathways and spatial proteomics focuses on intratumoral heterogeneity. Biofluid studies are growing with exciting potential for minimally invasive diagnostics. Post-translational modification profiling has explored signaling alterations and mechanisms of resistance. Proteogenomic integration has improved tumor classification, revealing protein-level alterations and regulatory mechanisms not captured by genomics. Literature was drawn mostly from studies of the past five years, with emphasis on translational applications. EXPERT OPINION: Proteomics has developed into a tool capable of providing clinically relevant, valuable insight. However, translation will depend on validation and standardization. Continued integration with other omics is critical for moving discoveries from the laboratory to the clinic. Importantly, there is an unmet need for proteomic analysis of less common subtypes, as seen by the bias of this review toward HGSOC.
Lunatin-1: A peptide derived from the venom of the Hadruroides lunatus scorpion modulates signaling pathways in HL60 tumor cells to induce cytotoxic effects.
Lima-Batista EM, Gómez-Mendoza DP, Moysés MN … +8 more , de Sousa Gomes K, Carvalho BC, de Lima ME, Souza-Fagundes EM, da Silva AM, Kjeldsen F, Verano-Braga T, Pimenta AMC
J Proteomics · 2026 Feb · PMID 41276073 · Publisher ↗
Lunatin-1 is a 13-residue cytotoxic peptide derived from the venom of the scorpion Hadruroides lunatus. This study investigated its early effects on cellular signaling in the human promyelocytic leukemia cell line HL-60...
Lunatin-1 is a 13-residue cytotoxic peptide derived from the venom of the scorpion Hadruroides lunatus. This study investigated its early effects on cellular signaling in the human promyelocytic leukemia cell line HL-60 using integrated proteomics and phosphoproteomics. Lunatin-1 regulated key mediators of apoptosis, such as caspase-2 (CASP2) and MEK1 (MAP2K1), and impacted major signaling pathways such as MAPK and PI3K/AKT. Lunatin-1 induced caspase-dependent and -independent apoptotic signaling, reduced AKT1 phosphorylation, and promoted BAX activation, consistent with mitochondrial apoptosis. These findings demonstrate that Lunatin-1 disrupts pro-survival signaling and activates multiple cell death pathways, highlighting its potential as a therapeutic candidate for hematologic malignancies. SIGNIFICANCE: This study provides a comprehensive analysis of the early molecular events triggered by Lunatin-1, a venom-derived peptide, in HL60 leukemia cells. Through integrated proteomic and phosphoproteomic approaches, we reveal that Lunatin-1 disrupts key survival pathways, notably MAPK and PI3K/AKT, and activates both caspase-dependent and -independent mechanisms of apoptosis. The peptide modulates proteins involved in DNA damage response, cell cycle regulation, and oxidative stress, offering insight into its multifaceted cytotoxic effects. These findings advance our understanding of venom-derived peptides as potential anticancer agents and underscore Lunatin-1's therapeutic promise for targeting resistant cancer cell populations.
Increased Serum Levels of LDHA and TPI1 in Patients With Polycystic Ovary Syndrome.
Wang W, Yan T, Sun M … +2 more , Li Y, Lou J
Proteomics Clin Appl · 2026 Jan · PMID 41273239 · Publisher ↗
BACKGROUND: Polycystic ovary syndrome (PCOS) is a metabolic disorder affecting women of reproductive age, and its etiology remains unclear. Therefore, it is crucial to identify biomarkers of the metabolic disturbances in...
BACKGROUND: Polycystic ovary syndrome (PCOS) is a metabolic disorder affecting women of reproductive age, and its etiology remains unclear. Therefore, it is crucial to identify biomarkers of the metabolic disturbances in PCOS. METHODS: A total of eight clinical PCOS samples and control group samples were analyzed using data-independent acquisition (DIA) proteomics. Clinical data were used to identify protein biomarkers, and enzyme-linked immunosorbent assay (ELISA) validation was performed on 27 PCOS and 23 control samples. RESULTS: In the PCOS samples, a total of 114 differentially expressed proteins were identified, with 37 upregulated and 77 downregulated. Further biofunctional analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed two differentially expressed proteins, lactate dehydrogenase A (LDHA) and triosephosphate isomerase 1 (TPI1), both of which were significantly upregulated in clinical PCOS samples. LDHA and TPI1 are involved in the glycolysis/gluconeogenesis metabolic pathway. Finally, ELISA was used to validate the high expression of LDHA and TPI1 in PCOS patients. CONCLUSION: DIA proteomics effectively identifies PCOS biomarkers. LDHA and TPI1 may serve as diagnostic biomarkers and could exert effects through glycolytic pathways.
Proteomics of Prostate Cancer Tissue Small Extracellular Vesicles Reveal Alteration of Metabolism.
Yu L, Ding T, Olofsson Bagge R … +2 more , Zheng L, Hao X
Proteomics · 2026 Feb · PMID 41243699 · Full text
Prostate cancer (PCa) is a leading male malignancy worldwide, with metabolic reprogramming being a critical hallmark of its progression. Extracellular vesicles (EVs) derived from tissues directly reflect the tumor microe...
Prostate cancer (PCa) is a leading male malignancy worldwide, with metabolic reprogramming being a critical hallmark of its progression. Extracellular vesicles (EVs) derived from tissues directly reflect the tumor microenvironment, offering unique insights into cancer pathophysiology that are unattainable through cell line or biofluid-derived EVs. However, the functional roles of tissue-derived EVs in PCa metabolism remain poorly understood. Leveraging our expertise in murine PCa model establishment and EV isolation from prostate tissue, this study aimed to characterize functional differences between PCa and normal prostate tissue via proteomic analysis of tissue-derived sEVs. We orthotopically implanted luciferase-labeled PCa cells into nude mice to establish an in situ PCa model, confirmed tumor formation via in vivo imaging, and harvested tissues after 4 weeks. sEVs were isolated using ultracentrifugation combined with an iodixanol density cushion and characterized by transmission electron microscopy, nanoparticle tracking analysis, and protein marker profiling. Proteomic analysis identified 28 upregulated and 24 downregulated proteins in PCa-derived sEVs compared to normal controls. Subcellular localization revealed enrichment in the cytoplasm, while pathway analysis highlighted significant involvement in metabolic processes, particularly glycolysis, amino acid biogenesis, carbon metabolism, and pyruvate metabolism. Our study establishes a robust method for isolating prostate tissue sEVs and provides the first evidence that PCa tissue-derived sEVs exhibit profound metabolic pathway alterations. These findings enhance our understanding of PCa progression mechanisms and may facilitate the development of novel diagnostic biomarkers and therapeutic strategies targeting metabolic dysregulation in PCa. SUMMARY: In this study, we created a method to isolate prostate tissue small EVs, based on our knowledge of the murine prostate cancer model building. Our data suggested that prostate tissue small EVs proteins significantly changed in many metabolism pathways, such as Glycolysis, Biogenesis of amino acids, Carbon metabolism and Pyruvate metabolism. In this study, we are the first to report prostate tissue-derived EVs proteins enriched in alterations of cancer metabolism. These differential proteins in PCa tissue EVs reflect metabolic changes in PCa and may provide insights into the development of early diagnostic biomarkers or novel therapeutic strategies.
The dynamics of ubiquitination and its role within the proteome of extracellular vesicles.
Morales-Tarré O, Popa-Navarro X, Paradela A … +4 more , Hernández-Ortiz M, Arrieta O, Corrales F, Encarnación-Guevara S
J Proteomics · 2026 Jan · PMID 41241127 · Publisher ↗
Ubiquitination is a multifaceted post-translational modification that plays a crucial role in regulating the degradation of unnecessary cellular proteins and is involved in various cellular processes, including protein e...
Ubiquitination is a multifaceted post-translational modification that plays a crucial role in regulating the degradation of unnecessary cellular proteins and is involved in various cellular processes, including protein export via extracellular vesicles. We investigate how alterations in the intracellular levels of ubiquitinated proteins affect vesicle protein content in BEAS-2B cells. We increased the intracellular levels of ubiquitinated proteins by inhibiting proteasomal degradation with MG-132 and by blocking deubiquitinating enzymes using PR-619. Using centrifugation and ultracentrifugation, were isolate various vesicle types, specifically the largest vesicles (enriched in plasma membrane-derived microvesicles) and the smallest vesicles (enriched in endosomal exosomes). High-resolution mass spectrometry-based proteomics was utilized to quantify their protein content. The content of extracellular vesicles changed in response to both treatments, reflecting cellular changes and the export of stress signals. The increase in intracellular levels of ubiquitinated proteins induced metabolic stress in the cells, generally leading to a reduction in protein translation, an enhanced response to oxidative stress, changes in membrane transport, and alterations in cell-microenvironment interactions. The modifications observed in the vesicular proteome suggest that ubiquitination plays a significant role in regulating protein export. This regulation can be mastered for diagnostic purposes and for describing cells and tissues through liquid biopsies. SIGNIFICANCE: Ubiquitination is one of the most abundant post-translational modifications in cells, and its role, beyond marking proteins for degradation, is not fully understood. Characterizing the effect of this modification on protein export to extracellular vesicles can shed light on how a cell selects its contents to influence its microenvironment, send signals to distant tissues, or interact with the immune system. This is particularly relevant in the context of pathologies such as cancer, which hijacks the cellular vesicle-producing machinery and adapts it to its needs to influence the remodeling of its surroundings. Understanding how a cell regulates the specific contents of its vesicles may point the way toward the development of treatments or superior diagnostic and classification tools.
Decoding spliceosome inhibition: Isobaric tag-based proteomic profiling of pladienolide B treated human cell lines.
Lopez XIH, Martinez-Perez K, Thakurta SG … +2 more , Levi BP, Paulo JA
J Proteomics · 2026 Jan · PMID 41224195 · Full text
Pladienolide B (Pla-B) is a potent splicing modulator that has shown promise in cancer treatment, but its cellular effects remain incompletely understood. We investigated the dose-associated effect of Pla-B on human cell...
Pladienolide B (Pla-B) is a potent splicing modulator that has shown promise in cancer treatment, but its cellular effects remain incompletely understood. We investigated the dose-associated effect of Pla-B on human cell lines using isobaric tag-based quantitative proteomics and phosphoproteomics techniques. We quantified over 10,000 proteins and 19,000 phosphorylation events in SH-SY5Y cells, revealing dose-associated changes in protein abundance and phosphorylation status. Low Pla-B concentrations induced significant alterations in nuclear proteins, specifically those involved in transcription and cell division. Higher concentrations led to more extensive proteome remodeling, affecting chromatin-associated proteins and transcription. Phosphoproteome analysis uncovered alterations in the phosphorylation states of proteins including the splicing factor subunit SF3B, suggesting complex regulation of signaling pathways. Our findings reveal the detailed proteomic landscape of Pla-B's effects, offering insights into its role in the global proteome, which may guide future therapeutic applications and rational drug design.
The protein cargo of extracellular vesicles. Recent advances in lung cancer research.
Morales-Tarré O, Navarro XP, Encarnación-Guevara S
J Proteomics · 2026 Jan · PMID 41207652 · Publisher ↗
Extracellular vesicles (EVs) are membranous microparticles produced by all living cells, from bacteria to humans. In recent years, interest in these vesicles has increased because they are linked to various biological fu...
Extracellular vesicles (EVs) are membranous microparticles produced by all living cells, from bacteria to humans. In recent years, interest in these vesicles has increased because they are linked to various biological functions, such as coagulation, the removal of undegraded proteins, intercellular signaling, stimulation and inactivation of T lymphocytes, and the transfer of antigens to APC. Since these vesicles carry specific characteristics of the parental cells, their characterization is a valuable opportunity to understand, through a liquid biopsy, the mechanisms involved in different pathologies, such as cancer. Lung cancer, is known to increase the production of extracellular vesicles, making their study particularly relevant in this group of diseases where biopsy collection is extremely difficult. Most research has centered on characterizing the nucleic acid content of vesicles due to their ability to alter gene expression in recipient cells. In contrast, the protein content of extracellular vesicles has been studied less extensively. Here, we describe the mechanisms of production for the main classes of extracellular vesicles and delve into their protein content. We also analyze recent progress in the proteomic characterization of extracellular vesicles in lung cancer research and explore their potential in diagnosis and the mechanisms underlying the disease's development. SIGNIFICANCE: This article highlights the advancements that the field of proteomics has brought to the characterization of extracellular vesicles derived from lung cancer. Given that lung cancer is the leading cause of cancer-related deaths, it is crucial to molecularly characterize this disease within the current landscape of biomedical research. We aim to draw the reader´s attention to the benefits of analyzing extracellular vesicles, as their protein content holds promise as an alternative liquid biopsy to achieve these objectives. By discussing existing findings and the challenges that remain, we hope to motivate researchers to utilize proteomics tools to develop new methodologies that can be consistently applied in clinical research and personalized patient care.
Decoding bladder cancer aggressiveness: A proteomic, phosphoproteomic and metabolomic approach.
Feng Z, Zhang B, Liu Y … +4 more , Yang F, Lei Y, Liao S, Hou X
J Proteomics · 2026 Jan · PMID 41187894 · Publisher ↗
BACKGROUND: Bladder cancer (BC) is the most common malignancy of the urinary system. However, the median survival of patients with metastatic bladder cancer remains limited. Thus, there is an urgent imperative to develop...
BACKGROUND: Bladder cancer (BC) is the most common malignancy of the urinary system. However, the median survival of patients with metastatic bladder cancer remains limited. Thus, there is an urgent imperative to develop novel biomarkers for BC-targeted therapies and to conduct in-depth investigations into BC pathogenesis leveraging multi-omics technologies. RESULTS: Our results revealed that proteins co-upregulated in both proteomic and phosphoproteomic analysis, such as SLC4A7 and MYO9B, demonstrated potential utility in distinguishing MIBC from NMIBC. Upregulation of CPT2 and palmitic acid in MIBC patients highlighted the dysregulation of physiological control mechanisms and enhanced pro-tumorigenic effects of lipid metabolic pathways. CONCLUSIONS: Integrated multi-omics analysis reveals that key regulatory proteins such as SLC4A7 and MYO9B play pivotal roles in mediating the aggressive phenotypes of MIBC. Aberrant upregulation of CPT2 protein and metabolites like palmitic acid may drive malignant transformation from NMIBC to MIBC by promoting lipid metabolic reprogramming. SIGNIFICANCE: This study utilized LC-MS/MS to systematically profile the proteomic, phosphoproteomic, and metabolomic characteristics of MIBC, NMIBC, and adjacent noncancerous tissues, with the aim of identifying key molecules and metabolites driving bladder cancer progression. Our findings indicate that aberrant phosphorylation of regulatory proteins such as SLC4A7 and MYO9B may play a critical role in mediating the invasive phenotype of MIBC. In parallel, the upregulation of CPT2 and its associated metabolites (e.g., palmitic acid) suggests that lipid metabolic reprogramming, including enhanced β-oxidation and membrane phospholipid synthesis, may contribute to the malignant transition from NMIBC to MIBC. Overall, this study not only reveals potential molecules and metabolites driving bladder cancer progression but also provides a valuable reference for further exploration of pathways associated with bladder cancer invasiveness.
Comparative quantitative proteomics of tumoral and peritumoral tissues for distinguishing human glioblastoma from low-grade astrocytoma.
Xiong Z, Li C, Han Q … +3 more , Su Y, Cheng L, Zeng HL
J Proteomics · 2026 Jan · PMID 41161534 · Publisher ↗
Glioblastoma multiforme (GBM) and low-grade astrocytoma (LGA) are diffuse gliomas with distinct biological features and prognoses. However, the molecular mechanisms driving their differences are not fully understood. In...
Glioblastoma multiforme (GBM) and low-grade astrocytoma (LGA) are diffuse gliomas with distinct biological features and prognoses. However, the molecular mechanisms driving their differences are not fully understood. In this study, we performed a multi-dataset analysis integrating in-house quantitative proteomics data with high-quality external datasets to identify GBM-specific proteomic alterations between tumoral and peritumoral tissues relative to LGA. Our analysis revealed more pronounced proteomic differences between intra- and peritumoral tissues in GBM than in LGA. Proteins specifically dysregulated in GBM were predominantly linked to upregulated RNA splicing and spliceosome signaling. Through multi-dataset integration, we identified 73 GBM-specific upregulated proteins enriched in processes such as transcriptional regulation, hypoxia and necrosis, cytoskeleton organization, extracellular matrix remodeling, and immune response. Conversely, the 129 GBM-specific downregulated proteins were mainly involved in tumor suppression, G-protein signaling, calcium signaling, and neuronal gap junctions. Using these signature proteins, we developed a risk model based on CDK2, HDAC1, IGFBP2, SLC6A1, and TNR, which significantly predicted overall survival in glioma patients. This study delineates the proteomic landscape of GBM in comparison to LGA and offers a valuable resource for future mechanistic and clinical investigations. SIGNIFICANCE: Diffuse gliomas are a heterogeneous brain tumor that include both low-grade and high-grade variants, each characterized by distinct morphological and biological features. Glioblastoma multiforme (GBM) is the most common primary high-grade and malignant brain tumor, with a median survival of less than 15 months despite aggressive treatment, including surgery, radiotherapy, and chemotherapy. In contrast, low-grade astrocytoma (LGA) exhibits indolent growth and a less aggressive clinical course, resulting in significantly longer patient survival compared to GBM. The molecular mechanisms underlying the biological differences between LGA and GBM are incompletely understood, and there is an urgent need for new molecular biomarkers to enhance diagnosis and therapeutic options. In this study, we conducted a comprehensive multi-dataset analysis by integrating our in-house quantitative proteomics data with several high-quality external datasets. We analyzed tumor and peritumoral tissue samples from human GBM and LGA, and further identified the GBM-specifically regulated proteomic signatures and signaling pathways, which is crucial for understanding the molecular mechanisms driving the aggressive behavior of GBM and could serve as a foundation for developing novel diagnostic biomarkers and therapeutic targets. Future research should focus on validating these GBM-specific proteins in larger cohorts and exploring their functional roles in GBM progression. Additionally, integrating multi-omics data (e.g., genomics, transcriptomics, and metabolomics) with proteomics could provide a more comprehensive understanding of the molecular mechanisms underlying GBM.
Toward real clinical utility: leveraging comprehensive cancer proteomic datasets for clinical insight.
Rodland KD, Zhang B
Expert Rev Proteomics · 2025 Oct · PMID 41159901 · Publisher ↗
INTRODUCTION: Recent advances in multi-omic technologies and computational tools have enabled comprehensive studies of cancer that integrate proteomics, genomics, transcriptomics, and metabolomics to improve disease unde...
INTRODUCTION: Recent advances in multi-omic technologies and computational tools have enabled comprehensive studies of cancer that integrate proteomics, genomics, transcriptomics, and metabolomics to improve disease understanding and outcomes. AREAS COVERED: 1. Recent improvements in throughput and decreasing sample mass requirements have enabled deep analysis of hundreds of human samples in multi-omic studies, increasing the statistical rigor of these studies and facilitating comparisons across clinical and demographic categories.2. Despite advances in statistical modeling, machine learning, and pathway-aware analysis, the principal outcome from these observational studies remains correlational-strong statistical associations between omic features and clinical characteristics, including clinical outcomes.3. Demonstration of causal relationships requires multi-pronged mechanistic experiments involving techniques in molecular and cellular biology that are distinct from the analytical and computational skills needed to generate these datasets. DATABASE USED: National Library of Medicine PubMed database. EXPERT OPINION: True clinical utility depends on the demonstration of causal relationships between candidate targets and the biomedical process of interest. Enhanced collaboration with molecular and cellular biologists skilled in the use of modern tools of genetic manipulation and engineered model systems is required to realize the full translational potential of even the most comprehensive multi-omic studies.
Proteomic Changes in Cancer Cell Lines as a Result of Bacterial Infection.
Ren B, Weke K, Hardie D … +5 more , Goncheva MI, Hupp T, Alfaro JA, Pětrošová H, Goodlett DR
Proteomics · 2025 Oct · PMID 41116249 · Publisher ↗
Bacterial infections have been implicated in shaping the tumor microenvironment (TME), but their effects on cancer cell proteomes remain unexplored. In this study, we analyzed proteomic changes in melanoma (A375) and ova...
Bacterial infections have been implicated in shaping the tumor microenvironment (TME), but their effects on cancer cell proteomes remain unexplored. In this study, we analyzed proteomic changes in melanoma (A375) and ovarian cancer (OVCAR3) cell line models following infection with Staphylococcus aureus strain USA300 or Salmonella enterica strain SL1344 using mass spectrometry-based label-free quantitative proteomics. Bacterial infection leads to widespread changes in host protein expression in the cancer cells, with levels of proteins involved in mitochondrial metabolism, RNA processing, and cellular stress response all increasing in relative abundance. In contrast, proteins involved in DNA repair, cytoskeletal structure, vesicle trafficking, and cell cycle regulation were consistently downregulated. The magnitude of the observed changes varied by the cancer cell type. Understanding these interactions may provide new directions for the role of bacteria in tumor progression and therapeutic resistance.
Proteomic exploration of the recently Re-classified forest cobra Naja species and the potential cytotoxic activity in cancer cell lines.
Motsa P, Muller B, Motadi LR … +2 more , Offor BC, Piater LA
J Proteomics · 2026 Jan · PMID 41115607 · Publisher ↗
The forest cobra (Naja melanoleuca) species represents one of the most widespread medically important elapid snakes across Africa. The immense tissue-damaging effect of cobra venoms is attributed to the cytotoxins (CTX),...
The forest cobra (Naja melanoleuca) species represents one of the most widespread medically important elapid snakes across Africa. The immense tissue-damaging effect of cobra venoms is attributed to the cytotoxins (CTX), which predominate in virtually all cobra venoms. In this study a bottom-up venomic approach was followed for deciphering the composition of the N. melanoleuca, N. subfulva, and N. savannula venom proteomes. The results revealed complex venoms that constituted predominantly of proteins belonging to the three-finger toxins (3FTxs) followed by phospholipase A (PLAs) and snake venom metalloproteinases (SVMPs). The cytotoxicity and selectivity of the crude venoms and fractions were evaluated against cancer and normal cell lines. The crude N. melanoleuca venom sample demonstrated weak/low cytotoxic activity across the different cell lines as corroborated by SI values of less than 2, thus highlighting its limited application against these cancer cells, while the N. subfulva venom demonstrated its highest cytotoxic activity against the HeLa cancer cell line with a moderate selectivity index of 2.04. It is crucial to emphasize that these findings are still in the preliminary stages, primarily based on in vitro studies, and there remains a significant gap to bridge before any therapeutic applications can be considered. SIGNIFICANCE: Biological significance: African forest cobra venom is a rich source of bioactive compounds such as cytotoxins, which cause tissue necrosis and descending paralysis. However, the venom has also been identified as a potential source of therapeutic agents, including anticancer agents. In this study, we evaluate the anticancer effects of the N. melanoleuca, N. subfulva, and N. savannula venoms and their fractions against the selected cell lines. The 3FTxs and PLAs, which are the most abundant protein families in the venoms, are predominantly responsible for the cytotoxic effects. In conclusion, this research study highlights the important role of forest cobra venoms as potential resources that researchers can further exploit to investigate the molecules responsible for the anticancer effect and investigate their mechanisms of action.
Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.
Müller J, Kuster B, The M
Proteomics · 2025 Nov · PMID 41108535 · Full text
Protein function is dynamically modulated by post-translational modifications (PTMs). Many different types of PTMs can nowadays be identified and quantified at a large scale using mass spectrometry. It is well known that...
Protein function is dynamically modulated by post-translational modifications (PTMs). Many different types of PTMs can nowadays be identified and quantified at a large scale using mass spectrometry. It is well known that many PTMs have an effect on protein function and cellular processes, and they should be studied not in isolation, but in the holistic context of cellular pathways. This is increasingly facilitated by a wide variety of computational efforts. This review aims to give a systematic overview of tools for pathway-centric analysis of PTM data and critically evaluate the state of play in this research field. Starting from databases that make up the foundational prior knowledge, we follow typical steps that an analytical workflow might contain, including pathway enrichment analysis, algorithms for pathway reconstruction, and the integration and visualization of results. We then reflect on common limitations of all existing tools and give our opinion on future directions that we think are currently most desirable.
Differential Proteomics of Large Extracellular Vesicles in Ovarian Cancer.
Suzuki K, Yamamoto Y, Kitagawa M … +4 more , Asano-Inami E, Yoshida K, Kajiyama H, Yokoi A
Proteomics · 2026 Feb · PMID 41039788 · Full text
Diverse extracellular vesicles (EVs) are present in all body fluids; however, knowledge of large EVs (lEVs) remains limited. Molecular EV profiles vary depending on EV size and the physiological circulatory system, even...
Diverse extracellular vesicles (EVs) are present in all body fluids; however, knowledge of large EVs (lEVs) remains limited. Molecular EV profiles vary depending on EV size and the physiological circulatory system, even within the same patient. In this study, we aimed to characterize the proteomic profile of IEVs in ovarian cancer patients and identify lEV-protein biomarkers. We collected tissue, serum, and ascites from patients with high-grade serous ovarian cancer and concurrently separated small EVs (sEVs) and lEVs through sequential multistep centrifugation. Proteomic analysis of tissues and EVs revealed distinct EV profiles in serum and ascites, identifying 11 lEV-specific proteins in serum and 14 in ascites that were absent in sEV. Of these, seven serum-specific and 10 ascites-specific proteins were further analyzed using transcriptomic databases, revealing candidate diagnostic and prognostic lEV-protein biomarkers. Our findings underscore the importance of size-based EV separation, as particle size influences biosynthetic mechanisms, in identifying lEV-specific proteins with potential diagnostic and prognostic values. SUMMARY: This study underscores the importance of distinguishing extracellular vesicle (EV) subtypes and considering body fluid specificity in biomarker discovery. By isolating EVs based on size and stepwise separation and analyzing their proteomic profiles in ovarian cancer, we identified potential large EV (lEV)-specific biomarkers that reflect disease pathology. These findings provide a foundation for lEV-protein-based liquid biopsy approaches that could enhance the accuracy of early detection and patient stratification. Further validation in clinical settings may pave the way for more precise and personalized ovarian cancer diagnostics.
Oncogenic H-Ras Reprograms Madin-Darby Canine Kidney (MDCK) Cell-Derived Midbody Remnant Proteome Following Epithelial-Mesenchymal Transition.
Shafiq A, Rai A, Xu R … +4 more , Chen M, Suwakulsiri W, Greening DW, Simpson RJ
Proteomics · 2026 Feb · PMID 41030230 · Full text
Epithelial-mesenchymal transition (EMT) is a fundamental, dynamic cellular process involved in embryonic development, metastasis, organ fibrosis, and tissue regeneration. To define the molecular landscape of secreted mid...
Epithelial-mesenchymal transition (EMT) is a fundamental, dynamic cellular process involved in embryonic development, metastasis, organ fibrosis, and tissue regeneration. To define the molecular landscape of secreted midbody remnants (MBRs) to the EMT process, a proteome analysis of MBRs released from Madin-Darby canine kidney (MDCK) cells and following oncogenic H-Ras transformation (21D1 cells) was performed. MBRs, a new class of membranous extracellular vesicle (EV) molecularly distinct from exosomes/small EVs, were purified using sequential centrifugation/buoyant density gradient centrifugation. Proteomic profiling revealed MDCK cell-MBRs reflect their epithelial origin (e.g., enriched CDH1, DSP, THBS1, OLCN, EPCAM proteins) and 21D1 cell-MBRs their oncogenic and mesenchymal phenotype (e.g., HRAS, VIM, MMP14, CDH2, WNT5A, and enriched invasive and cell motility protein networks). Validation of proteome cargo revealed key protein networks associated with the EMT process in MBRs, and conserved MBR proteome across different cell types. Prominent findings were the unique expression of the immune checkpoint protein NT5E/CD73 (ecto-5'-nucleotidase) and ser/thr kinases LIMK1/K2 in MBRs from mesenchymal cells following their oncogenic transformation, and enrichment in Wnt signaling network proteins. These data identify the core proteome of MBRs regulated during the dynamic process of EMT and cell transformation over other EV types in context of the EMT process. SUMMARY: Epithelial-to-mesenchymal transition (EMT) is a critical cell biological process that occurs during embryonic development and cancer progression. Our study describes sequential purification of secreted midbody remnants (MBRs) and exosomes/sEVs from the in vitro cell line EMT model Madin-Darby canine kidney (MDCK) cells and MDCK cells transformed with oncogenic H-Ras (21D1 cells): Proteomics identified the repertoire of enriched MDCK-MBR proteins following EMT. MBRs display a proteome profile distinct from sEVs that is enriched with factors of the centralspindlin complex (KIF23.1, KIF4A, INCENP, CEP55, PLK1) and further includes components of the mitochondrial network, cytokinesis, microtubule movement, and intercellular connection. In the context of EMT, our data reveal enriched EMT pathways in MBRs including signaling receptor binding, regulation of cell differentiation, and Wnt, VEGF, and PDGF signaling. We have validated these findings in the context of Wnt signaling in other EV types. We identify several mesenchymal-enriched networks in MBRs associated with focal adhesion, cell matrix, kinase activity, and cell shape/organization, while epithelial-derived MBRs show enriched networks predominantly associated with mitochondrial (processing/transport), midbody, and plasma membrane annotation. Our study sheds light on the proteome architecture of MBRs following oncogenic H-Ras-induced EMT in cell transformation: collectively, our data informs ongoing efforts to delineate oncogenic drivers of cancer initiation, progression, and metastasis.
Anisomelic acid promotes proteasomal degradation of HPV16 E6 via E3 ligase recruitment: A mass spectrometry-based interactome study.
Santos Silva M, Coelho-Rato LS, Delshad N … +5 more , Tarkhova T, Edman J, Paul P, Meinander A, Eriksson JE
J Proteomics · 2026 Jan · PMID 40967472 · Publisher ↗
Human papillomavirus (HPV) is a major driver of cervical and other epithelial cancers, with the viral oncoprotein E6 playing a central role in tumorigenesis by promoting degradation of the tumor suppressor p53. While pro...
Human papillomavirus (HPV) is a major driver of cervical and other epithelial cancers, with the viral oncoprotein E6 playing a central role in tumorigenesis by promoting degradation of the tumor suppressor p53. While prophylactic vaccines prevent infection, there remains a critical need for therapeutic strategies that eliminate established HPV-positive cells. Here, we identify anisomelic acid (AA), a natural diterpenoid, as a novel pharmacological principle that selectively induces the degradation of HPV16 E6. Using cellular thermal shift assay, we demonstrate that AA directly interacts with E6, likely triggering a conformational change that promotes its ubiquitination. Proteomic analysis of the E6 interactome in AA-treated cells revealed consistent enrichment of E3 ubiquitin ligases, including E6AP, UBR4, CDC20, and TRIP12, as well as proteasomal subunits. To our knowledge, this represents the first comprehensive proteomics framework of the HPV16 E6 interactome under small-molecule treatment conditions. These findings support a model in which AA facilitates proteasome-mediated elimination of E6, and the dataset itself provides a timely and valuable resource for HPV biology and therapeutic development.
Advances and applications of clinical proteomics in precision medicine.
Alshehri S, Vitorino R, Saleh O … +9 more , Al-Harthi S, Alahmadi A, Alotibi R, da Silva Rosa SC, Osama A, Magedeldin S, Alhattab D, Emwas AH, Jaremko M
Expert Rev Proteomics · 2025 Oct · PMID 40963397 · Publisher ↗
INTRODUCTION: Clinical proteomics has become a pivotal component of precision medicine, significantly advancing the understanding of disease mechanisms and informing therapeutic strategies. This review explores how clini...
INTRODUCTION: Clinical proteomics has become a pivotal component of precision medicine, significantly advancing the understanding of disease mechanisms and informing therapeutic strategies. This review explores how clinical proteomics is transforming diagnostic and therapeutic approaches across multiple fields. AREAS COVERED: This review highlights recent developments and applications of clinical proteomics in cardiovascular and neurological disorders, as well as its impact on drug development. Technologies such as mass spectrometry and protein microarrays have enhanced diagnostic precision, facilitated the discovery of novel biomarkers, and uncovered new therapeutic targets. In cardiovascular medicine, proteomics supports early disease detection and patient risk stratification, while in neurology, it helps identify disease-specific protein signatures that guide targeted interventions. The integration of proteomics with databases like Universal Protein Resource (UniProt) and the Human Protein Atlas, alongside the use of advanced bioinformatics tools, has streamlined data analysis and accelerated the design of personalized therapies. EXPERT OPINION: Clinical proteomics is rapidly evolving, offering unprecedented opportunities to refine diagnostics, personalize therapies, and improve patient outcomes. Overcoming current challenges in standardization and validation will be essential for its full integration into clinical practice.
Interpretable Machine Learning for Proteomics-Based Subtyping and Tumor Mutational Burden Prediction in Endometrial Cancer.
Luong TM, Bui XL, Tzeng CR … +1 more , Le NQK
Proteomics Clin Appl · 2025 Nov · PMID 40916623 · Publisher ↗
BACKGROUND: Endometrial carcinoma (EC) represents a significant clinical challenge due to its pronounced molecular heterogeneity, directly influencing prognosis and therapeutic responses. Accurate classification of molec...
BACKGROUND: Endometrial carcinoma (EC) represents a significant clinical challenge due to its pronounced molecular heterogeneity, directly influencing prognosis and therapeutic responses. Accurate classification of molecular subtypes (CNV-high, CNV-low, MSI-H, POLE) and precise tumor mutational burden (TMB) assessment is crucial for guiding personalized therapeutic interventions. Integrating proteomics data with advanced machine learning (ML) techniques offers a promising strategy for achieving precise, clinically actionable classification and biomarker discovery in EC. MATERIALS AND METHODS: Using proteomic data from 95 EC patients (83 endometrioid, 12 serous), sourced from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), we developed an ML pipeline integrating proteomic feature selection (Lasso-penalized logistic regression), classification modeling, and interpretability analysis. The dataset was divided into training (70%) and test (30%) sets, with synthetic minority oversampling (SMOTE) applied to address the class imbalance. Logistic regression models were trained for molecular subtypes classification, and the TMB prediction model performance was evaluated using accuracy, AUC, precision, recall, and F1-score. Model interpretability was enhanced using explainable AI (XAI) techniques: SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME). RESULTS: Feature selection reduced the proteomic dataset from 11,000 to eight key proteins. The proteomics-based ML model demonstrated robust predictive performance, accurately classifying EC molecular subtypes (accuracy: 82.8%; AUC: 0.990) and distinguishing high (≥10 mutations/Mb) versus low TMB (<10 mutations/Mb) cases (accuracy: 89.7%; AUC: 0.984). SHAP analysis highlighted clinically recognized biomarkers (MLH1, PMS2, STAT1) and identified novel protein candidates (MTHFD2, MAST4, RPL22L1, MX2, SEC16A). LIME analysis provided individualized prediction interpretations, clarifying each protein biomarker's influence on model decisions. CONCLUSION: Our proteomics-driven ML approach demonstrates high accuracy and interpretability in EC subtype classification and TMB prediction. By identifying validated and novel biomarkers, this strategy provides essential biological insights and a strong foundation for the future development of non-invasive diagnostics, personalized treatments, and precision medicine in EC.
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