Cancer Genomics & Proteomics[JOURNAL]
Sun
200 papers
Enabling Variant Proteogenomic Assay Development Through a Peptide Target Selection Pipeline and Web Application.
Blidjios C, Bhowmick P, Richard VR … +2 more , Mohammed Y, Borchers CH
Proteomics · 2026 May · PMID 42143580 · Publisher ↗
The quantification of key protein variants can guide precision oncology to enable better identification of driver mutations. Bottom-up assays infer parent protein levels through the quantification of surrogate peptides....
The quantification of key protein variants can guide precision oncology to enable better identification of driver mutations. Bottom-up assays infer parent protein levels through the quantification of surrogate peptides. Assay methods designed for absolute quantification of protein variants, such as multiple reaction monitoring mass spectrometry (MRM-MS), can achieve quantitation with high precision and specificity. Bottom-up approaches rely on proper selection of suitable surrogate proteogenotypic peptide targets to quantify protein variants of interest. To this end, we developed an R-based bioinformatics pipeline to predict and evaluate variant-specific peptides. The workflow generates variant protein sequences from wild-type sequences and mutations encoded in the Human Genome Variation Society (HGVS) recommended nomenclature, performs in-silico tryptic digestion, and identifies both variant and corresponding wild-type peptides. Each peptide is evaluated by 37 selection criteria to determine suitability as MRM targets. To assess the strictness of these criteria, we applied all protein-altering mutations from the NCI-Genomic Data Commons (GDC) and COSMIC to our pipeline. Of the peptides outputted, 5% satisfied all defined criteria, representing the highest confidence candidates for assay development. We developed a database and web application from NCI-GDC generated peptides for searching, filtering, and downloading. Another web application was developed to provide access to our pipeline.
iMPI: An Integrative Database for MicroProteins Encoded by Intron Retention in Tumors.
Hu J, Zheng Y, Huang X … +9 more , Liang Z, Di J, Cao B, Wang L, Li J, Fu Z, Li H, Cheng H, Liu ZX
Proteomics · 2026 May · PMID 42113741 · Publisher ↗
Research advancements made in the last decade have shed light on the dysregulation of cellular mechanisms that lead to aberrant and pathologic intron retention (IR). IR is not merely a mechanism of gene regulation but ma...
Research advancements made in the last decade have shed light on the dysregulation of cellular mechanisms that lead to aberrant and pathologic intron retention (IR). IR is not merely a mechanism of gene regulation but may also play a potential role in cancer pathogenesis and therapeutic resistance across various human cancers. Despite its potential significance, there remains a notable gap in comprehensive database resources for introns within tumors. Therefore, we investigated whether the retained introns contain undiscovered protein-coding ORFs and whether they can encode proteins. We conducted a genome-wide search for underlying translatable intron ORFs (iORFs) and validated them at the protein level via large-scale proteomic mass spectrometry (MS) data. Furthermore, we developed the first comprehensive resource, iMPI (an integrative database for MicroProteins encoded by introns), to provide an accessible source of iORF-encoded microproteins. Our genome-wide search identified 209,091 introns in the human GRCh38 genome, among which 15,975 were confirmed as candidates with strong coding potential. On the basis of the proteomic MS search, 4751 introns containing a total of 5823 iORFs across 27 cancer types were validated. Detailed annotations, including intron information, coding evidence, subcellular location and structures, were integrated. iMPI is a user-friendly web interface that is freely available at https://impi.omicsbio.info/, making it a valuable tool for researchers investigating the spectrum of IR in human cancers.
Machine learning-enhanced plasma proteomics discriminates pancreatic cancer-associated diabetes from type 2 diabetes mellitus.
Lazari LC, Donnarumma CDC, Matheus LHG … +10 more , D'Alpino Peixoto R, de Matos MR, Valerio HP, Rosa-Fernandes L, Oba-Shinjo SM, Machado MCC, Machado MAC, Marie SKN, Correa-Giannella ML, Palmisano G
J Proteomics · 2026 Jun · PMID 42069247 · Publisher ↗
Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type 2 diabetes (T2D) remains clinically challenging. We investigated whet...
Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type 2 diabetes (T2D) remains clinically challenging. We investigated whether plasma proteomic profiling combined with machine learning could discriminate these conditions. Plasma samples from individuals with PDAC (with and without DM), long-standing T2D, and controls were analyzed by MALDI-TOF mass spectrometry. Spectral features were processed through a nested cross-validation framework to prevent data leakage, and model interpretability was explored using SHAP values. In parallel, low-molecular-weight proteins were characterized by GeLC-MS followed by LC-MS/MS and differential abundance analysis. Machine learning models distinguished PDAC-associated DM from T2D with a balanced accuracy of 85%. Proteomic analyses identified distinct signatures in PDAC- associated DM, including downregulation of erythrocyte-related proteins and PPBP, and upregulation of acute-phase reactants such as FGA, CP, and SERPINA3. Treatment-naïve cases displayed increased circulating epithelial and keratin-associated proteins, which were attenuated after therapy, suggesting dynamic tumor-related remodeling. These findings demonstrate that integrating MALDI-TOF profiling with machine learning can capture plasma signatures associated with PDAC-associated DM. Although exploratory, this approach supports further validation in prospective cohorts aimed at improving PDAC risk stratification among individuals with NODM. SIGNIFICANCE: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a dismal 5-year survival rate, primarily due to late-stage diagnosis. The frequent occurrence of new-onset diabetes mellitus (NODM) as a paraneoplastic syndrome offers a critical window for early detection. However, the clinical challenge of distinguishing PDAC-associated diabetes (PDAC-DM) from type 2 diabetes mellitus (T2D) has hindered the implementation of effective screening strategies. This study addresses this significant clinical problem by leveraging a multi-faceted proteomics approach. We demonstrate that the integration of MALDI-TOF mass spectrometry peptide profiling with machine learning algorithms can accurately discriminate PDAC-DM from T2D with 85% accuracy. Furthermore, we used LC-MS/MS to identify specific low molecular weight proteins that are differentially regulated between these conditions, providing a molecular basis for the observed discrimination. Our work is significant as it presents a novel, high-throughput pipeline for biomarker discovery that combines the scalability of MALDI-TOF with the analytical power of LC-MS/MS and machine learning. The identified plasma signatures hold strong translational potential to improve risk stratification in patients with NODM, ultimately enabling earlier diagnosis of PDAC and improving patient survival prospects. This research directly contributes to the field of clinical proteomics by providing a robust methodological framework and candidate biomarkers for the early detection of one of oncology's most challenging diseases.
Proteomics-based approaches to neutrophil biology.
Pittaluga Villarreal JR, Nita-Lazar A
Expert Rev Proteomics · 2026 · PMID 42060268 · Publisher ↗
INTRODUCTION: Neutrophils are central effectors of innate immunity and key contributors to inflammation, host defense, and tissue injury across a wide range of physiological and pathological contexts. Due to their short...
INTRODUCTION: Neutrophils are central effectors of innate immunity and key contributors to inflammation, host defense, and tissue injury across a wide range of physiological and pathological contexts. Due to their short lifespan, rapid activation, and extensive post-translational regulation, comprehensive molecular characterization of neutrophil function requires approaches that go beyond transcriptomics or marker-based analyses. AREAS COVERED: This review summarizes how proteomic technologies have advanced the understanding of neutrophil biology by enabling unbiased, system-wide profiling of protein abundance, subcellular organization, post-translational modifications, and functional heterogeneity. We discuss global and subcellular proteomics, PTM-centric analyses, and emerging low-input and single-cell proteomic strategies, highlighting recent studies of infection, cancer, metabolic disorders, aging, autoimmune disease, and inflammation. The literature covered includes current large-scale quantitative proteomics, targeted PTMs, and integrative multi-omics studies in both human samples and relevant experimental models. EXPERT OPINION: Proteomics has established neutrophils as highly plastic and context-dependent cells whose functions are governed by coordinated remodeling of signaling, metabolism, and effector pathways. Future progress will depend on expanding neutrophil-specific PTM maps, improving low-input workflows, and integrating single-cell and spatial proteomics. Together, these advances are expected to redefine neutrophil functional states and accelerate translation toward clinically meaningful biomarkers and therapeutic strategies.
Urinary Peptidomic Signatures Predict Overall and Progression-Free Survival in Bladder Cancer.
Ahangar M, Mischak H, Moulavasilis N … +5 more , Stravodimos K, Mahjoubi F, Jankowski J, Frantzi M, Vlahou A
Proteomics · 2026 Jul · PMID 42046269 · Publisher ↗
Clinicopathologic calculators for bladder cancer (BC) provide only moderate prognostic accuracy and do not capture the underlying molecular phenotypes. Herein, we applied capillary electrophoresis-mass spectrometry (CE-M...
Clinicopathologic calculators for bladder cancer (BC) provide only moderate prognostic accuracy and do not capture the underlying molecular phenotypes. Herein, we applied capillary electrophoresis-mass spectrometry (CE-MS) to identify prognostic signatures in urine linked to BC outcome. In a discovery cohort (n = 131; mean follow-up 623 days), 114 survival-associated peptides were significant prognostic factors for overall survival (OS) and were integrated into, and optimized as a 110-peptide support vector machine (SVM) classifier (BC110). Validation of the BC110 classifier was performed in an independent cohort (n = 102; mean follow-up 1605 days), resulting in an AUC of 0.78 (p = 0.03). Functional enrichment analysis revealed that the BC110 peptide panel predominantly reflects extracellular matrix (ECM) remodeling and collagen-related pathways, alongside additional biological processes including coagulation, complement activation, oxidative stress, and RNA processing, consistent with active tumor-stroma crosstalk. This urine-based classifier enables non-invasive risk stratification and may complement guideline calculators by identifying high-risk patients for adjuvant therapy and low-risk groups for reduced surveillance, potentially lowering reliance on repeated cystoscopy.
Deciphering mitochondrial metabolic vulnerabilities in ovarian clear cell carcinoma with mass spectrometry-based clinical proteomics.
Barrios A, Thomas SN
Expert Rev Proteomics · 2026 · PMID 42026901 · Publisher ↗
INTRODUCTION: Ovarian clear cell carcinoma (OCCC) is a rare gynecologic malignancy with a high mortality rate and a lack of response to standard chemotherapy. Despite the functional association between the loss of ARID1A...
INTRODUCTION: Ovarian clear cell carcinoma (OCCC) is a rare gynecologic malignancy with a high mortality rate and a lack of response to standard chemotherapy. Despite the functional association between the loss of ARID1A and mitochondrial dependency, the clinical translation of mitochondria-targeted therapies in OCCC has been hindered by a substantial disconnect between biological insight and therapeutic application. There is an urgent, unmet need to identify novel, more specific and effective therapies targeting the mitochondria-related molecular vulnerabilities of ARID1A-mutant OCCC. AREAS COVERED: This critical perspective is informed by results from PubMed literature searches and recent webinars and presentations providing insight into opportunities for mass spectrometry (MS)-based proteomic approaches to enhance and accelerate the clinical translation of mitochondria-targeted therapies in OCCC. EXPERT OPINION: The MS-based proteomic analysis of clinically-relevant experimental models of OCCC will provide a unique opportunity to progress beyond simplified preclinical models and incorporate the full spectrum of patient-specific systemic and microenvironmental factors that may influence therapeutic response, including the adipocyte-related metabolic dependencies of OCCC. Targeted MS is a precise and robust approach that can be applied to verify these novel, mechanistic insights into how mitochondria-targeted therapies intersect with tumor metabolism in OCCC.
The proteomics analysis of mitochondria-enriched fractions reveals alteration of key mitochondrial pathways in breast cancer cell lines.
Vázquez-Narváez HD, Labra-Barrios ML, Ríos-Castro E … +8 more , Castañón-Sánchez CA, Uribe-Carvajal S, Hernández-Martínez E, Hernández-Hernández JM, León-Ávila G, Pérez-Rangel A, Ángeles-Morales EB, Luna-Arias JP
J Proteomics · 2026 Jun · PMID 42025918 · Publisher ↗
Breast cancer, the leading cause of death in women worldwide, shows significant heterogeneity that makes this disease extremely difficult to treat. Many reports point to metabolic shifts, mainly those carried out into mi...
Breast cancer, the leading cause of death in women worldwide, shows significant heterogeneity that makes this disease extremely difficult to treat. Many reports point to metabolic shifts, mainly those carried out into mitochondria, as key processes governing the behavior and heterogeneity of several types of breast cancer. In this study, we performed label-free proteomics analysis on mitochondria-enriched fractions from T47D and MDA-MB-231 breast cancer cell lines, which have distinct molecular classifications, using bioinformatics analyses to identify differentially expressed proteins compared to MCF-12F healthy breast cells. Cancer cells exhibited down-regulated protein levels of subunits from the respiratory chain's Complex I. However, both showed differentially abundant proteins involved in ligase and oxidoreductase activities, including enzymes of glycolysis, pyruvate metabolism, the Krebs cycle, and gluconeogenesis. Many of these enzymes also participate in other metabolic processes, such as mitochondrial localization, mitochondrial gene expression, and the metabolism of amino acids, fatty acids, purines, and pyrimidines. Gene Set Enrichment Analysis revealed that OXPHOS subunits are integrated as signatures of neurodegenerative disease pathways. A protein set with little or no evidence in breast cancer was identified, which could lead to future research in breast cancer mitochondrial metabolism. Data are available via ProteomeXchange with identifier PXD069883. SIGNIFICANCE: This manuscript determined the protein expression profiles of mitochondria-enriched fractions from T47D (Luminal A, stage IV) and MDA-MB-231 (triple negative, Stage IV) breast cancer cell lines compared to the MCF-12F healthy breast cell line. We found that breast cancer cell lines exhibited low expression levels of Complex I subunits from the respiratory chain. However, both breast cancer cell lines presented high expression levels of some proteins related to ligase and oxidoreductase activities, the latter on CH-OH groups in cellular respiration processes, such as some enzymes from glycolysis, pyruvate metabolism, Krebs cycle and gluconeogenesis. Moreover, many of these enzymes also participate in other metabolic processes, such as localization to the mitochondrion, mitochondrial gene expression, amino acid, fatty acid, purine, and pyrimidine metabolism. We also observed through Gene Set Enrichment Analysis that OXPHOS enzymes have a key role in many neurodegenerative disease pathways as well. Finally, we found a protein set with little or no evidence in breast cancer that could lead to future pivotal research in the mitochondrial metabolism of breast cancer.
Proteomic characterization of primary pancreatic fibroblasts derived from neoadjuvant chemotherapy treated versus treatment-naïve PDAC.
Amrutkar M, Finstadsveen AV, Labori KJ … +2 more , Verbeke CS, Gladhaug IP
J Proteomics · 2026 Jun · PMID 42025917 · Publisher ↗
Neoadjuvant chemotherapy (NAT) is increasingly used in the treatment of pancreatic ductal adenocarcinoma (PDAC). However, the actual molecular impact of NAT on the tumor remains unknown, particularly on the cancer-associ...
Neoadjuvant chemotherapy (NAT) is increasingly used in the treatment of pancreatic ductal adenocarcinoma (PDAC). However, the actual molecular impact of NAT on the tumor remains unknown, particularly on the cancer-associated fibroblasts (CAFs) remains largely unknown. Here, mass-spectrometry (MS)-based proteomic profiling of primary CAFs derived from treatment-naïve (TN) and NAT-treated resected PDAC (n = 10 in each group) was conducted to explore potential NAT-associated changes. Differentially abundant proteins (DAPs; p < 0.05) in NAT versus TN CAFs accounted for 10.6% of all 5438 proteins mapped by MS. According to gene ontology analysis, DAPs with higher abundance (273) in NAT versus TN were involved in protein transport and carbohydrate metabolism, while DAPs with lower abundance (305) were mainly related to RNA processing. Protein-protein interactions identified several cluster networks of closely linked DAPs. Exploring the correlation between DAPs abundance and survival identified a negative correlation for 30 of 42 DAPs in NAT group. In addition, several proteins were found to be differentially abundant among different NAT regimens. In conclusion, this exploratory study reveals significant NAT-associated changes in CAF proteome profiles, which are related to the fundamental biological processes of RNA processing and protein transport. Further validation of these preliminary findings using a large independent cohort is needed.
Urinary Collagen Peptides Predict Mortality.
Frantzi M, Keller F, Latosinska A … +13 more , Beige J, Mebazaa A, Caillard A, An D, Perco P, Schanstra JP, Catanese L, Wendt R, Rupprecht H, Staessen JA, Vlahou A, Mischak H, Siwy J
Proteomics · 2026 Jul · PMID 41954080 · Full text
Organ fibrosis caused by the presence of excessive extracellular matrix (ECM) is related to mortality. Urinary peptide signatures were reported to be predictive of death in SARS-CoV-2 and chronic kidney disease. Such sig...
Organ fibrosis caused by the presence of excessive extracellular matrix (ECM) is related to mortality. Urinary peptide signatures were reported to be predictive of death in SARS-CoV-2 and chronic kidney disease. Such signatures were composed for 68% of collagen fragments. In this study, we examined whether urinary collagen peptides, potentially representing organ fibrosis, could predict mortality in patients with critical and non-critical conditions. Urinary proteomic data from 1012 patients with follow-up information from the CRIT-COV-U study were investigated for the association of collagen peptides with short-term mortality. Independent datasets from 9193 patients were used for validation, including 1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (outside the ICU). A total of 607 collagen peptides were significantly associated with mortality. A classifier based on 210 collagen peptides (COL210) predicting mortality was developed and validated in patients in the ICU (ICU: 2.64; 95% CI:1.71-4.10; p<0.001) and outside the ICU (Non-ICU: 2.16 95% CI: 1.47-3.17; p<0.001), showing strong associations to mortality regardless underlying conditions. This study demonstrates a link between the presence of ECM fragments in urine, specifically collagens, and increased mortality risk. Such a non-invasive collagen-based predictor of mortality may serve as a basis for proteomics-guided targeted intervention.
Comparison of In-Gel and SP3 Based Sample Preparation Protocols for LC-MS/MS Based Proteomics.
Schwarzmüller L, Frey D, Zadora P … +3 more , Schneider M, Wiemann S, Helm D
Proteomics · 2026 Jul · PMID 41904654 · Full text
Sensitivity, robustness, and reproducibility of sample preparation are main determinants of data quality in bottom-up mass spectrometry-based proteomics. To this end, in-gel protein clean-up and digestion has been used f...
Sensitivity, robustness, and reproducibility of sample preparation are main determinants of data quality in bottom-up mass spectrometry-based proteomics. To this end, in-gel protein clean-up and digestion has been used for decades and is characterized by its robustness and compatibility with harsh lysis conditions. Single-pot solid-phase-enhanced sample preparation (SP3) has gained substantial popularity recently and has been widely adapted as a standard workflow often replacing in-gel digestion-based workflows. Noteworthy, until today no direct comparison between the two workflows has been conducted. Here, we performed a systematic comparison of in-gel and SP3 based sample preparation workflows assessing sensitivity, robustness, reproducibility, and fractionation possibilities on human cellular lysates and blood plasma. Both methods performed similarly regarding number of identified proteins, however, showed specific biases. SP3 outperformed the in-gel workflow regarding higher sensitivity when handling limited sample amounts, especially below 5 µg of input material. In contrast, in-gel sample preparation was superior in the identification of low molecular weight proteins. In conclusion, while SP3 is indeed the state-of-the-art proteomics sample preparation method, in-gel digestion can deliver competitive and complementary results and still has advantages in some applications, such as measurement of small proteins or when there is a need for protein-level separation, e. g. in plasma samples.
Proteomic Characterization of AS1411 Reveals ATP6AP1 as a Mediator of Triple-Negative Breast Cancer Progression.
Bae HS, Seo YJ, Kim EB … +4 more , Park HM, Liu IH, Lee JE, Kim JY
Proteomics · 2026 Jul · PMID 41894428 · Full text
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by high metastatic potential, poor prognosis, and limited effective therapeutic options. In this study, we investigated the mol...
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by high metastatic potential, poor prognosis, and limited effective therapeutic options. In this study, we investigated the molecular mechanisms underlying the anticancer effects of the nucleolin (NCL)-targeting DNA aptamer AS1411 using label-free quantitative proteomic profiling. AS1411 treatment significantly reduced TNBC cell viability and migration. To uncover the underlying mechanisms, we performed global proteomic analysis of AS1411-treated TNBC cells. Bioinformatic analysis of differentially expressed proteins (DEPs) revealed enrichment of tumor-associated signaling pathways and protein-protein interaction networks regulated by AS1411. Among the DEPs, ATPase H-transporting accessory protein 1 (ATP6AP1) was markedly downregulated in AS1411-treated TNBC cells. Functional studies demonstrated that ATP6AP1 knockdown suppressed TNBC cell proliferation and migration, whereas its overexpression enhanced tumorigenic phenotypes. Importantly, modulation of ATP6AP1 expression showed minimal effects on normal breast epithelial cells. Collectively, these findings identify ATP6AP1 as a key downstream mediator of AS1411 and support its potential as a therapeutic target in TNBC.
Small extracellular vesicles in clinical Cancer research - A quantitative proteomics perspective.
Pandey D, Tiwari V, Ghosh D
J Proteomics · 2026 Jun · PMID 41806951 · Publisher ↗
'Small extracellular vesicles (sEVs) are nanosized, membrane-enclosed sacs released by diverse cell types. They play a critical role in cell-cell communication through their cargo, which includes a wide range of proteins...
'Small extracellular vesicles (sEVs) are nanosized, membrane-enclosed sacs released by diverse cell types. They play a critical role in cell-cell communication through their cargo, which includes a wide range of proteins, lipids, and nucleic acids. Physiologically, sEVs circulate in various body fluids such as blood, urine, and saliva, making them accessible for diagnostic via non-invasive isolation techniques. Recent advances in high-throughput proteomics have significantly enhanced our ability to characterize the protein content of sEVs. Importantly, multiple studies on human fluids have identified specific protein markers across different cancer types, encompassing molecules involved in inflammation, cellular adhesion, immunity, and lipoprotein regulation. Interestingly, some of these proteins are consistently detected across multiple cancer types and sample sources, suggesting the existence of a shared "oncogenic signature" that may be transferred via sEVs. Among body fluids, urine and saliva are particularly promising for easy, non-invasive diagnostics. However, these sample types remain underexplored as compared to the serum, leaving substantial opportunities for future research. Taken together, these findings position sEVs as a powerful tool with significant potential for advancing precision cancer care. SIGNIFICANCE: Living cells release nanosized membrane-enclosed vesicles called small extracellular vesicles (sEVs) into the extracellular environment. sEVs contain protein cargo molecules that critically take part in cell-cell communications. Quantitative proteomics identified potential sEV associated biomarkers for early cancer diagnosis and therapy. sEV Proteins associated with cell adhesion and inflammation, lipoproteins and immunoglobulins are potential molecules that were majorly identified. Interestingly, some of these proteins such as APOA4, SAA4, ITIH4, SERPINC1 and VWF were consistently identified across multiple cancer types and sample sources, highlighting their potential as future biomarkers.
A Network-Based Association of IBD and Colorectal Cancer Using Proteomics Data.
Dhami J, Radhakrishnan SK, Russ D … +6 more , Mondal S, Alzarooni A, Merodio LB, Duggal NA, Gupta R, Acharjee A
Proteomics Clin Appl · 2026 Mar · PMID 41704020 · Full text
BACKGROUND: Colorectal cancer (CRC) is a major cause of morbidity and mortality, with chronic inflammation from inflammatory bowel disease (IBD) representing a well-established risk factor. Clarifying shared molecular me...
BACKGROUND: Colorectal cancer (CRC) is a major cause of morbidity and mortality, with chronic inflammation from inflammatory bowel disease (IBD) representing a well-established risk factor. Clarifying shared molecular mechanisms may facilitate early detection and prevention strategies. METHODS: Proteomic data from the UK Biobank were analysed using the Olink proximity extension assay for seven CRC-associated proteins (TFF3, TFF1, AHCY, RETN, LCN2, SELE and CEACAM5) previously identified via machine learning. Expression levels in CRC and IBD cases were compared with controls. Multilayer interaction networks, incorporating protein-protein, protein-metabolite and transcription factor-protein interactions, were generated using OmicsNet. Findings were validated in the Colonomics transcriptomic dataset. RESULTS: All seven proteins were significantly upregulated in CRC; six (excluding CEACAM5) were also elevated in IBD. Network analysis identified AHCY and LCN2 as central hubs linking inflammatory and metabolic pathways. NF-κB and GATA2 emerged as recurrent transcriptional regulators. Colonomics validation confirmed upregulation of AHCY, LCN2 and SELE in CRC tissues. CONCLUSIONS: This multi-omics network analysis reveals a shared molecular framework between IBD and CRC, with inflammation as a key driver of colorectal carcinogenesis.
Proteomic insights into infection in stomach cells, revealing host response and host-targeted therapeutics repurposing.
Shetty A, Lakshman T, Raju R … +1 more , Ramesh P
Expert Rev Proteomics · 2026 · PMID 41664315 · Publisher ↗
BACKGROUND: ( ) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and...
BACKGROUND: ( ) is a globally prevalent gastric pathogen strongly associated with chronic gastritis, peptic ulcers, and gastric cancer. While bacterial factors have been extensively studied, host proteomic responses and their therapeutic potential remain largely underexplored. RESEARCH DESIGN AND METHODS: Current analyses employed a systematic proteomics-based data integration and harmonization approach (retrospective qualitative cohort study) to identify important differentially regulated host proteins. Proteomic datasets were curated from in vitro studies and analyzed for functional enrichment, protein-protein interaction networks, and hub protein identification. To explore therapeutic repurposing, drug repositioning was performed using the DrugBank database. RESULTS: Data summation describing protein differential regulation in human gastric cells as a result of the infection revealed 1672 perturbed host proteins. Bioinformatics analysis revealed 11 proteins including CSK, MET, RELA, MARK2, GRB2, FTO, PLCG1, CRKL, RPS5, RPS9, and RPS27A to be ideal host targets for therapeutic repurposing. Clinically approved drugs such as Dasatinib (targeting CSK) and Crizotinib (targeting MET) emerged as promising candidates due to favorable pharmacokinetics and known bioactivity. CONCLUSIONS: Host-directed therapeutics could offer alternative strategies to conventional antibiotic therapy, addressing challenges such as resistance and infection recurrence, providing a foundation for future experimental validation and development of host-targeted interventions for infection control.
Prospective serial proteomic analysis uncovers mechanistic pathways of chemotherapy resistance in advanced non-small cell lung cancer.
Kuo WK, Chu HY, Ko YK … +1 more , Hsu PH
J Proteomics · 2026 Apr · PMID 41653971 · Publisher ↗
Predicting chemotherapy response in advanced non-small cell lung cancer (NSCLC) remains a clinical challenge, as baseline profiles often fail to capture dynamic molecular adaptations under treatment. This prospective stu...
Predicting chemotherapy response in advanced non-small cell lung cancer (NSCLC) remains a clinical challenge, as baseline profiles often fail to capture dynamic molecular adaptations under treatment. This prospective study employed serial plasma proteomics to identify mechanistic pathways associated with chemotherapy resistance in 44 patients with stage IV NSCLC receiving platinum-based doublet chemotherapy. By analyzing blood samples collected immediately before the first and second cycles using liquid chromatography-tandem mass spectrometry, we demonstrated that a ratio-based proteomic model (early-treatment/pre-treatment) yielded superior separation between controlled and uncontrolled disease (UCD) compared to baseline-only assessment. Among 159 quantified proteins, 13 showed significant differential abundance, with UCD patients exhibiting marked upregulation of tetranectin, coagulation factor XIII A chain, and complement factor H-related protein 2. Ingenuity Pathway Analysis revealed that therapeutic resistance was characterized by three dominant axes: the activation of complement-coagulation-acute-phase signaling, the induction of lipid-nuclear receptor activity (LXR/RXR and DHCR24 signaling), and the relative attenuation of immune-regulatory pathways such as IL-12 signaling. These findings highlight the potential of serial proteomic profiling to uncover treatment-induced molecular adaptations, providing insights for therapeutic monitoring and hypothesis generation in precision oncology. SIGNIFICANCE: This study demonstrates the added value of prospective serial plasma proteomic profiling, compared with baseline-only approaches, for capturing early treatment-associated molecular adaptations in advanced non-small cell lung cancer (NSCLC) receiving chemotherapy. By quantifying proteomic changes between pre-treatment and early-treatment time points, we identified coordinated alterations involving the complement-coagulation-acute-phase axis and lipid-nuclear receptor signaling programs, including LXR/RXR and DHCR24, alongside relative attenuation of immune-regulatory pathways. Rather than reflecting isolated protein effects, these findings highlight interconnected host-tumor response programs that emerge under therapeutic pressure and may contribute to early adaptive resistance. Importantly, this work moves beyond static baseline markers by emphasizing dynamic, pathway-level changes and provides a hypothesis-generating framework for longitudinal therapeutic monitoring. Candidate proteins such as tetranectin and coagulation factor XIII A chain are proposed as molecular features associated with treatment response, warranting further validation in larger, prospective cohorts before translational application.
Time-resolved proteomic and phosphoproteomic profiling of Angiotensin-(1-7) signaling in A549 cells.
Melo-Braga MN, Magalhães GC, Silva FA … +4 more , Kjeldsen F, Larsen MR, Santos RAS, Verano-Braga T
J Proteomics · 2026 Apr · PMID 41570893 · Publisher ↗
Angiotensin-(1-7) [Ang-(1-7)] is a heptapeptide of the renin-angiotensin system (RAS) with antitumoral effects reported in various tumoral cell lines, including the human lung adenocarcinoma A549 lineage. While previous...
Angiotensin-(1-7) [Ang-(1-7)] is a heptapeptide of the renin-angiotensin system (RAS) with antitumoral effects reported in various tumoral cell lines, including the human lung adenocarcinoma A549 lineage. While previous studies have shown that Ang-(1-7) modulates MAPK and PI3K-AKT signaling, the precise molecular mechanisms involved remain incompletely understood. To investigate the signaling events of Ang-(1-7) in lung cancer-derived cells, we employed an integrated proteomic and phosphoproteomic approach in A549 cells. We analyzed early (minutes) and late (hours) molecular responses to Ang-(1-7) treatment. The treatment resulted in time-dependent modulation of multiple signaling pathways, including significant alterations in the MAPK, PI3K-AKT, and mTOR pathways at both the protein and phosphorylation levels. Notably, widespread early dephosphorylation events were observed, similar to the effects seen with other RAS peptides with antitumoral effects. Additionally, Ang-(1-7) promoted a long-lasting nuclear accumulation (up to 24 h) of the transcription factor FOXO1 indicating its activation. FOXO1 is known to regulate genes involved in apoptosis, cell cycle arrest, and oxidative stress, suggesting a role in mediating the peptide's antitumoral effects. The study provides new insights into the molecular basis of Ang-(1-7)'s antitumoral activity in A549 cells and reinforce its therapeutic potential in lung cancer. Raw data are available via ProteomeXchange with identifier PXD066687. SIGNIFICANCE: This study provides the first comprehensive, time-resolved proteomic and phosphoproteomic analysis of Angiotensin-(1-7) signaling in the lung cancer cell line A549. By capturing both early and late molecular events in A549 cells, we reveal that Ang-(1-7) modulates critical pathways involved in tumor progression, including MAPK, PI3K-AKT, and mTOR signaling. Importantly, we demonstrate the nuclear accumulation of FOXO1, a key transcription factor associated with tumor suppression, as part of the Ang-(1-7) response in A549 cells.
Identifying Subcellular Structure Components in Escherichia Coli by Crosslinking and SEC-MS.
Victor RA, Lipinski A, Langlais PR … +1 more , Schwartz JC
Proteomics · 2026 May · PMID 41566810 · Full text
Cells are comprised of a broad spectrum of structures that compartmentalize biochemical and signaling mechanisms. These structures can be comprised of many biomolecules, but especially lipids, proteins, and nucleic acids...
Cells are comprised of a broad spectrum of structures that compartmentalize biochemical and signaling mechanisms. These structures can be comprised of many biomolecules, but especially lipids, proteins, and nucleic acids. Techniques are limited to quantify or discover new subcellular structures. We explored whether a proteomics approach using chemical crosslinking followed by size-exclusion chromatography and mass spectrometry (SEC-MS) of whole cell lysates can address this challenge. Formaldehyde crosslinking was used to preserve the weak molecular interactions responsible for many protein and nucleic acid assemblies. In this study, we perform the first formaldehyde crosslinking-assisted SEC-MS in a bacterial system. We demonstrate that when expressed ectopically in E. coli, large structures of a known assembly protein, FUS, can be detected through SEC-MS. We then show that E. coli proteins are enriched in particles of large or medium size due to formaldehyde crosslinking, which is the first analysis by formaldehyde and SEC-MS for a bacterial system. Last, analysis identified previously characterized E. coli protein assemblies and condensates, as well as potentially novel associations of prokaryote metabolism with large subcellular bodies. We propose this unbiased method can be used to stimulate or supplement targeted methods for discovery of new cellular bodies in a wide range of cell types.
Proteomic and Lipidomic Profiling of Immune Cell-Derived Subpopulations of Extracellular Vesicles.
Lischnig A, Karimi N, Larsson P … +4 more , Ekström K, Crescitelli R, Olin AC, Lässer C
Proteomics · 2026 Feb · PMID 41518059 · Full text
Extracellular vesicles (EVs) are heterogeneous and play important roles in intercellular communication, contributing to physiological and pathological processes. Since few markers currently exist to differentiate subtype...
Extracellular vesicles (EVs) are heterogeneous and play important roles in intercellular communication, contributing to physiological and pathological processes. Since few markers currently exist to differentiate subtypes of EVs, this study aimed to determine proteomic and lipidomic differences among four EV subpopulations. Large and small EVs (L-EVs and S-EVs) were isolated from human mast cells (HMC-1) and monocytes (THP-1) by differential ultracentrifugation and then further separated by density cushions into two different densities [low-density (LD) and high-density (HD)]. L-EVs were pelleted at 16,500 × g, and S-EVs were pelleted at 118,000 × g. LD EVs were collected at 1.079-1.146 g/mL, while HD EVs were collected at 1.146-1.185 g/mL. The morphology, size and yield of EVs were determined by TEM and western blot. The proteome and lipidome of the EV subpopulations were determined with mass spectrometry. A total of 5364 proteins were quantified, and L-EVs LD were enriched in mitochondrial proteins such as TIMM/TOMM and MICOS proteins, while L-EVs HD were enriched in cytoskeleton- and cytokinesis-associated proteins, such as KIF proteins. S-EVs LD were enriched in tetraspanins, ADAM10 and ESCRT machinery proteins, while S-EVs HD were enriched in proteins commonly viewed as contaminants, such as histones, complement factors and collagen. Proteins involved in membrane trafficking between the plasma membrane and organelles, such as adaptor protein complexes, the conserved oligomeric Golgi complex, the trafficking protein particle complex, sortin-nexins, TBC1 domain proteins and coatomer subunits, were expressed at similar levels across all EV subtypes. Furthermore, 107 lipids were quantified, and phosphatidylethanolamine (PE) was less abundant in L-EVs LD as compared to the other EV subtypes, while ceramides were enriched in L-EVs as compared to S-EVs.This study demonstrates that there is a core proteome and lipidome that is similar across all four EV subtypes, but importantly, it also shows that a portion of the proteome and lipidome differs in EV subpopulations separated based on size and density. We suggest that these could be important markers in future EV studies and that they may reflect a different biogenesis and EV function.
Proteomic signatures in triple-negative breast cancer.
Kashyap S, Patidar V, Kumar A … +5 more , Sahu P, Dhiman M, Garg P, Jain A, Munshi A
J Proteomics · 2026 Mar · PMID 41512917 · Publisher ↗
An aggressive and heterogeneous malignancy, referred to as triple-negative breast cancer, is characterised by the absence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Treatme...
An aggressive and heterogeneous malignancy, referred to as triple-negative breast cancer, is characterised by the absence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Treatment options remain limited, relying primarily on chemotherapy due to the lack of well-defined therapeutic targets, which is linked with poor prognosis and high recurrence rates. Proteomics and other high-throughput technologies have significantly advanced TNBC research by enabling the identification of protein-based biomarkers with potential applications in diagnosis, prognosis, and treatment. Through protein biomarkers that affect immune checkpoints, cell-surface glycoproteins, and regulators of tumor microenvironment interactions, key protein signatures from tumor tissue, serum, and exosomal proteomics have been found to have the potential to predict chemotherapy response and disease progression. To develop new therapeutic approaches, these biomarkers are being investigated. Combining proteomics with other omics technologies, such as transcriptomics and genomics, enables the development of precision medicine approaches and provides deeper insights into the pathophysiology of TNBC. Clinically validated and newly developed protein biomarkers for diagnosis, prognosis, and treatment interventions are described in this review. The molecular mechanistic aspects have also been discussed. These biomarkers have the potential to aid in the classification, risk stratification, and development of personalized treatment approaches for TNBC. SIGNIFICANCE STATEMENT: Triple-negative breast cancer (TNBC) remains a highly aggressive and heterogeneous form of breast cancer, with very few treatment strategies. This review synthesizes past discoveries, current clinical applications, and future opportunities of proteomics in TNBC, making it highly relevant to the theme of this Special Issue on "Past, Present and Future of Proteomics." By consolidating evidence from human and other preclinical studies, it highlights how proteomic signatures have already transformed our understanding of TNBC biology and subtype classification, while also outlining their growing impact as diagnostic, prognostic, and therapeutic markers. Importantly, the review emphasizes the translational shift enabled by next-generation proteomic technologies to redefine precision medicine for TNBC. It showcases how proteomics can facilitate personalized medicine, drug repurposing, and rational combination therapies, and describes novel avenues such as single-cell proteomics and integrative immunoproteogenomics that are driving the field forward. Thus, this work not only consolidates what has been achieved but also provides perspectives on emerging technologies and innovative applications that could revolutionize biomarker discovery and clinical management of TNBC. It highlights proteomics as a critical pillar in shaping the future of cancer diagnostics and therapeutics, directly aligning with the scope and intent of the special issue.
Combining information on degradomics and gene expression data in prospecting metastatic melanoma proteolytic signatures.
Salardani M, Chaves AFA, Cardili L … +4 more , Uno M, Serrano SMT, Chammas R, Zelanis A
J Proteomics · 2026 Mar · PMID 41482208 · Publisher ↗
Melanoma is an aggressive skin cancer with a high metastatic potential, influenced by both genetic and environmental factors. Proteases play a key role in shaping the tumor microenvironment and enabling transformed cells...
Melanoma is an aggressive skin cancer with a high metastatic potential, influenced by both genetic and environmental factors. Proteases play a key role in shaping the tumor microenvironment and enabling transformed cells to actively colonize distant sites (metastasis). We performed proteomic mapping of protease cleavage sites in formalin-fixed paraffin-embedded tissue samples and profiled potentially active proteases in samples from melanoma patients with distinct prognostic outcomes. Although protein abundance alone did not indicate potential markers of disease progression, the observed cleaved fragments may serve for monitoring potentially active proteases in patient samples in targeted proteomics analysis. The findings provide valuable insights into melanoma biology and potential therapeutic prospects.
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