Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection

Targeting the kynurenine pathway in gliomas: Insights into pathogenesis, therapeutic targets, and clinical advances

Gliomas, the most prevalent primary brain tumors, continue to present significant challenges in oncology due to poor patient prognosis despite advances in treatment such as immunotherapy and cancer vaccines. Recent research highlights the potential of targeting tryptophan metabolism, particularly the kynurenine pathway (KP) and combinatorial approaches with immunotherapies, as a promising strategy in cancer research. The key enzymes of the kynurenine pathway, such as IDO1, IDO2, and TDO, and metabolites like kynurenine, kynurenic acid, and quinolinic acid, are implicated in fostering an immunosuppressive tumor microenvironment and promoting glioma cell survival. In glioblastoma, a highly aggressive glioma subtype, elevated IDO and TDO expression correlates with reduced survival rates. KP metabolites, such as kynurenine (KYN), 3-hydroxykynurenine (3-HK), kynurenic acid (KYNA), and quinolinic acid (QUIN), are involved in modulating immune responses, oxidative stress, neuroprotection, and neurotoxicity. This review synthesizes recent findings on the kynurenine pathway involvement in glioma pathogenesis, examining potential therapeutic targets within this pathway and discussing ongoing clinical trials that draw attention to treatments based on this pathway. Furthermore, it highlights novel findings on the post-translational modifications of kynurenine pathway enzymes and their regulatory roles, presenting their potential as therapeutic targets in gliomas.

Proteomics in Diagnostic Evaluation and Treatment of Breast Cancer: A Scoping Review

Objectives: The aim of this scoping review was to delineate the current role and possible applications of proteomics in personalized breast cancer diagnostic evaluation and treatment. Methods: A comprehensive search in PubMed/MEDLINE and Scopus/EMBASE was conducted, according to the PRISMA-ScR guidelines. Inclusion criteria: proteomic studies of specimens from breast cancer patients, clinically relevant studies and clinical studies. Exclusion criteria: in silico, in vitro and studies in animal models, review articles, case reports, case series, comments, editorials, and articles in language other than English. The study protocol was registered in the Open Science Framework. Results: In total, 1093 records were identified, 170 papers were retrieved and 140 studies were selected for data extraction. Data analysis and synthesis of evidence showed that most proteomic analyses were conducted in breast tumor specimens (n = 77), followed by blood samples (n = 48), and less frequently in other biologic material taken from breast cancer patients (n = 19). The most commonly used methods were liquid chromatography-tandem mass spectrometry (LC-MS/MS), followed by Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF), Surface-Enhanced Laser Desorption/Ionization Time-of-Flight (SELDI-TOF) and Reverse Phase Protein Arrays (RPPA). Conclusions: The present review provides a thorough map of the published literature reporting clinically relevant results yielded from proteomic studies in various biological samples from different subgroups of breast cancer patients. This analysis shows that, although proteomic methods are not currently used in everyday practice to guide clinical decision-making, nevertheless numerous proteins identified by proteomics could be used as biomarkers for personalized diagnostic evaluation and treatment of breast cancer patients.

Mass Spectrometry-Based Proteomics for Next-Generation Precision Oncology

Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While the genomics-based testing has transformed modern medicine, the challenge of diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers and drug targets. Mass spectrometry (MS)-based clinical proteomics has illuminated the molecular features of cancers and facilitated discovery of biomarkers or therapeutic targets, paving the way for innovative strategies that enhance the precision of personalized treatment. In this article, we introduced the tools and current achievements of MS-based proteomics, choice of discovery and targeted MS from discovery to validation phases, profiling sensitivity from bulk samples to single-cell level and tissue to liquid biopsy specimens, current regulatory landscape of MS-based protein laboratory-developed tests (LDTs). The challenges, success and future perspectives in translating research MS assay into clinical applications are also discussed. With well-designed validation studies to demonstrate clinical benefits and meet the regulatory requirements for both analytical and clinical performance, the future of MS-based assays is promising with numerous opportunities to improve cancer diagnosis, treatment, and monitoring.

Proteomic profiles screening identified novel exosomal protein biomarkers for diagnosis of lung cancer

BACKGROUND

Exosomes play important role in biological functions, including both normal and disease process. Multiple cell types can secret exosomes, which act as message carriers. Increased evidences reveal that exosomes are promising diagnosis biomarkers in malignant tumors.

METHODS

In this study, we enrolled 78 participants, including 20 lung adenocarcinoma (LUAD), 18 lung squamous carcinoma (LUSC), 20 lung benign diseases (LUBN) and 20 healthy controls (NL) and we performed parallel reaction-monitoring (PRM)-mass spectrometry to screening the proteomic variation by label free analysis in exosomes from all groups, which has been widely used to quantify and detect target proteins.

RESULTS

Total 14 protein were identified as candidate biomarkers, complement components C9, apolipoprotein B (APOB), filamin A (FLNA), guanine nucleotide binding protein G subunit 2 (GNB2), fermitin family homolog 3 (FERMT3) showed significantly differentiation in total lung cancer (LUAD and LUSC together), we then obtained combination analysis of 5 proteins and the area under the curve (AUC), sensitivity (SN) and specificity (SP) were 63.0%, 65.0%, and 75.0%, respectively, in comparison to NL group. And the LUAD combination panel, peroxiredoxin 6 (PRDX6), integrin alpha-IIb (ITGA2B) and hemoglobin subunit delta (HBD) revealed AUC was 95.0%, SN was 90.0% and SP was 95.0% in comparison to NL controls. In LUSC analysis, combination analysis of fibronectin 1 (FN1), pregnancy zone protein (PZP) and complement C1q tumor necrosis factor related protein 3 (C1QTNF3) showed that AUC was 88.1%, SN was 75.0%, SP was 100% in paralleled with NL group. Finally C9, FLNA, PZP were overexpressed in lung cancer H1299 and A549 cell lines and the results indicated that C9 acted as oncogenic role by increasing proliferation, migration and invasion of lung cancer cells, while FLNA and PZP played tumor-suppression by inhibition biological functions of lung cancer cells.

CONCLUSION

Taken together, our study revealed multiple exosomal proteins which could be applied as candidate biomarkers in diagnosis of lung cancer.

Omics-Enhanced Nanomedicine for Cancer Therapy

Cancer nanomedicine has emerged as a promising approach to overcome the limitations of conventional cancer therapies, offering enhanced efficacy and safety in cancer management. However, the inherent heterogeneity of tumors presents increasing challenges for the application of cancer nanomedicine in both diagnosis and treatment. This heterogeneity necessitates the integration of advanced and high-throughput analytical techniques to tailor nanomedicine strategies to individual tumor profiles. Omics technologies, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and more, provide unparalleled insights into the molecular and cellular mechanisms underlying cancer. By dissecting tumor heterogeneity across multiple levels, these technologies offer robust support for the development of personalized and precise cancer nanomedicine strategies. In this review, the principles, techniques, and applications of key omics technologies are summarized. Especially, the synergistic integration of omics and nanomedicine in cancer therapy is explored, focusing on enhanced diagnostic accuracy, optimized therapeutic strategies and the assessment of nanomedicine-mediated biological responses. Moreover, this review addresses current challenges and outlines future directions in the field of omics-enhanced nanomedicine. By offering valuable insights and guidance, this review aims to advance the integration of omics with nanomedicine, ultimately driving improved diagnostic and therapeutic strategies for cancer.

A Proteomic Analysis of Nasopharyngeal Carcinoma in a Moroccan Subpopulation

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a distinct cancer of the head and neck that is highly prevalent in Southeast Asia and North Africa. Though an extensive analysis of environmental and genetic contributors has been performed, very little is known about the proteome of this disease. A proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissues can provide valuable information on protein expression and molecular patterns for both increasing our understanding of the disease and for biomarker discovery. To date, very few NPC proteomic studies have been performed, and none focused on patients from Morocco and North Africa.

METHODS

Label-free Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) was used to perform a proteomic analysis of FFPE tissue samples from a cohort of 41 NPC tumor samples of Morocco and North Africa origins. The LC-MS/MS data from this cohort were analyzed alongside 21 healthy controls using MaxQuant 2.4.2.0. A differential expression analysis was performed using the MSstats package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotations were carried out using the DAVID bioinformatic tool.

RESULTS

3341 proteins were identified across our NPC cases, revealing three main clusters and five DEPs with prognostic significance. The sex disparity of NPC was investigated from a proteomic perspective in which 59 DEPs were found between males and females, with significantly enriched terms associated with the immune response and gene expression. Furthermore, 26 DEPs were observed between patients with early and advanced stages of NPC with a significant cluster related to the immune response, implicating up-regulated DEPs such as IGHA, IGKC, and VAT1. Across both datasets, 6532 proteins were quantified between NPC patients and healthy controls. Among them, 1507 differentially expressed proteins (DEPs) were observed. GO and KEGG pathway analyses showed enriched terms of DEPs related to increased cellular activity, cell proliferation, and survival. PI3K and MAPK proteins as well as RAC1 BCL2 and PPIA were found to be overexpressed between cancer tissues and healthy controls. EBV infection was also one of the enriched pathways implicating its latent genes like LMP1 and LMP2 that activate several proteins and signaling pathways including NF-Kappa B, MAPK, and JAK-STAT pathways.

CONCLUSION

Our findings unveil the proteomic landscape of NPC for the first time in the Moroccan population. These studies additionally may provide a foundation for identifying potential biomarkers. Further research is still needed to help develop tools for the early diagnosis and treatment of NPC in Moroccan and North African populations.

Role of Filamin A in Growth and Migration of Breast Cancer-Review

Despite ongoing research in the field of breast cancer, the morbidity rates indicate that the disease remains a significant challenge. While patients with primary tumors have relatively high survival rates, these chances significantly decrease once metastasis begins. Thus, exploring alternative approaches, such as targeting proteins overexpressed in malignancies, remains significant. Filamin A (FLNa), an actin-binding protein (ABP), is involved in various cellular processes, including cell migration, adhesion, proliferation, and DNA repair. Overexpression of the protein was confirmed in samples from patients with numerous oncological diseases such as prostate, lung, gastric, colorectal, and pancreatic cancer, as well as breast cancer. Although most researchers concur on its role in promoting breast cancer progression and aggressiveness, discrepancies exist among studies. Moreover, the precise mechanisms through which FLNa affects cell migration, invasion, and even cancer progression remain unclear, highlighting the need for further research. To evaluate FLNa's potential as a therapeutic target, we have summarized its roles in breast cancer.

Talin mechanotransduction in disease

Talin protein (Talin 1/2) is a mechanosensitive cytoskeleton protein. The unique structure of the Talin plays a vital role in transmitting mechanical forces. Talin proteins connect the extracellular matrix to the cytoskeleton by linking to integrins and actin, thereby mediating the conversion of mechanical signals into biochemical signals and influencing disease progression as potential diagnostic indicators, therapeutic targets, and prognostic indicators of various diseases. Most studies in recent years have confirmed that mechanical forces also have a crucial role in the development of disease, and Talin has been found to play a role in several diseases. Still, more studies need to be done on how Talin is involved in mechanical signaling in disease. This review focuses on the mechanical signaling of Talin in disease, aiming to summarize the mechanisms by which Talin plays a role in disease and to provide references for further studies.

The Diversity of Liquid Biopsies and Their Potential in Breast Cancer Management

Analyzing blood as a so-called liquid biopsy in breast cancer (BC) patients has the potential to adapt therapy management. Circulating tumor cells (CTCs), extracellular vesicles (EVs), cell-free DNA (cfDNA) and other blood components mirror the tumoral heterogeneity and could support a range of clinical decisions. Multi-cancer early detection tests utilizing blood are advancing but are not part of any clinical routine yet. Liquid biopsy analysis in the course of neoadjuvant therapy has potential for therapy (de)escalation.Minimal residual disease detection via serial cfDNA analysis is currently on its way. The prognostic value of blood analytes in early and metastatic BC is undisputable, but the value of these prognostic biomarkers for clinical management is controversial. An interventional trial confirmed a significant outcome benefit when therapy was changed in case of newly emerging cfDNA mutations under treatment and thus showed the clinical utility of cfDNA analysis for therapy monitoring. The analysis of PIK3CA or ESR1 variants in plasma of metastatic BC patients to prescribe targeted therapy with alpesilib or elacestrant has already arrived in clinical practice with FDA-approved tests available and is recommended by ASCO. The translation of more liquid biopsy applications into clinical practice is still pending due to a lack of knowledge of the analytes' biology, lack of standards and difficulties in proving clinical utility.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70-80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of "6P" medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC-MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein-protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with "proteome point sampling" methods that allow for proteomic profiling by in vivo "proteome point characterization", or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC-MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

Isolation and identification of extracellular matrix proteins from oil-based CASPERized mouse brains for matrisomal analysis

The extracellular matrix (ECM) components present within all tissues and organs help to maintain the cytoskeletal architecture and tissue morphology. Although the ECM plays a role in cellular events and signaling pathways, it has not been well studied due its insolubility and complexity. Brain tissue has a higher cell density and weaker mechanical strength than other tissues in the body. When removing cells using a general decellularization method to produce scaffolds and obtain ECM proteins, various problems must be considered because tissues are easily damaged. To retain the brain shape and ECM components, we performed decellularization in combination with polymerization. We immersed mouse brains in oil for polymerization and decellularization via O-CASPER (Oil-based Clinically and Experimentally Applicable Acellular Tissue Scaffold Production for Tissue Engineering and Regenerative Medicine) and then isolated ECM components using sequential matrisome preparation reagents (SMPRs), namely, RIPA, PNGase F, and concanavalin A. Adult mouse brains were preserved with our decellularization method. Western blot and LC-MS/MS analyses revealed that ECM components, including collagen and laminin, were isolated efficiently from decellularized mouse brains using SMPRs. Our method will be useful to obtain matrisomal data and perform functional studies using adult mouse brains and other tissues.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography/mass spectrometry (LC/MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization, and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin-based depletion column followed by either protein In-Gel enzymatic digestion or protein In-Solution enzymatic digestion using a simple kit-based approach (i.e., using the PreOmics iST sample preparation kit), followed by analysis using one-dimensional reverse-phase chromatography (RPC) or high pH reversed-phase peptide fractionation.

Green Hydrogel Synthesis: Emphasis on Proteomics and Polymer Particle-Protein Interaction

The field of drug discovery has seen significant progress in recent years. These advances drive the development of new technologies for testing compound's effectiveness, as well as their adverse effects on organs and tissues. As an auxiliary tool for drug discovery, smart biomaterials and biopolymers produced from biodegradable monomers allow the manufacture of multifunctional polymeric devices capable of acting as biosensors, of incorporating bioactives and biomolecules, or even mimicking organs and tissues through self-association and organization between cells and biopolymers. This review discusses in detail the use of natural monomers for the synthesis of hydrogels via green routes. The physical, chemical and morphological characteristics of these polymers are described, in addition to emphasizing polymer-particle-protein interactions and their application in proteomics studies. To highlight the diversity of green synthesis methodologies and the properties of the final hydrogels, applications in the areas of drug delivery, antibody interactions, cancer therapy, imaging and biomarker analysis are also discussed, as well as the use of hydrogels for the discovery of antimicrobial and antiviral peptides with therapeutic potential.

Discovering biomarkers for hormone-dependent tumors: in silico study on signaling pathways implicated in cell cycle and cytoskeleton regulation

Malignancies dependent on hormone homeostasis include breast, ovary, cervical, prostate, testis and uterine tumors. Hormones are involved in signal transduction which orchestrate processes, such as apoptosis, proliferation, cell cycle or cytoskeleton organization. Currently, there is a need for novel biomarkers which would help to diagnose cancers efficiently. In this study, the genes implicated in signaling that is important in hormone-sensitive carcinogenesis were investigated regarding their prognostic significance. Data of seven cancer cohorts were collected from FireBrowse. 54 gene sets implicated in specific pathways were browsed through MSig database. Profiling was assessed via Monocle3, while gene ontology through PANTHER. For confirmation, correlation analysis was performed using WGCNA. Protein-protein networks were visualized via Cytoscape and impact of genes on survival, as well as cell cycle or cytoskeleton-related prognostic signatures, was tested. Several differences in expression profile were identified, some of them allowed to distinguish histology. Functional annotation revealed that various regulation of cell cycle, adhesion, migration, apoptosis and angiogenesis underlie these differences. Clinical traits, such as histological type or cancer staging, were found during evaluation of module-trait relationships. Of modules, the TopHubs (COL6A3, TNR, GTF2A1, NKX3-1) interacted directly with, e.g., PDGFB, ITGA10, SP1 or AKT3. Among TopHubs and interacting proteins, many showed an impact on hazard ratio and affected the cell cycle or cytoskeleton-related prognostic signatures, e.g., COL1A1 or PDGFB. In conclusion, this study laid the foundation for further hormone-sensitive carcinogenesis research through identification of genes which prove that crosstalk between cell cycle and cytoskeleton exists, opening avenues for future therapeutic strategies.

Separation of Serum and Plasma Proteins for In-Depth Proteomic Analysis

There are probably no biological samples that did more to spur interest in proteomics than serum and plasma. The belief was that comparing the proteomes of these samples obtained from healthy and disease-affected individuals would lead to biomarkers that could be used to diagnose conditions such as cancer. While the continuing development of mass spectrometers with greater sensitivity and resolution has been invaluable, the invention of strategic strategies to separate circulatory proteins has been just as critical. Novel and creative separation techniques were required because serum and plasma probably have the greatest dynamic range of protein concentration of any biological sample. The concentrations of circulating proteins can range over twelve orders of magnitude, making it a challenge to identify low-abundance proteins where the bulk of the useful biomarkers are believed to exist. The major goals of this article are to (i) provide an historical perspective on the rapid development of serum and plasma proteomics; (ii) describe various separation techniques that have made obtaining an in-depth view of the proteome of these biological samples possible; and (iii) describe applications where serum and plasma proteomics have been employed to discover potential biomarkers for pathological conditions.

Combinatorial Power of cfDNA, CTCs and EVs in Oncology

Liquid biopsy is a promising technique for clinical management of oncological patients. The diversity of analytes circulating in the blood useable for liquid biopsy testing is enormous. Circulating tumor cells (CTCs), cell-free DNA (cfDNA) and extracellular vesicles (EVs), as well as blood cells and other soluble components in the plasma, were shown as liquid biopsy analytes. A few studies directly comparing two liquid biopsy analytes showed a benefit of one analyte over the other, while most authors concluded the benefit of the additional analyte. Only three years ago, the first studies to examine the value of a characterization of more than two liquid biopsy analytes from the same sample were conducted. We attempt to reflect on the recent development of multimodal liquid biopsy testing in this review. Although the analytes and clinical purposes of the published multimodal studies differed significantly, the additive value of the analytes was concluded in almost all projects. Thus, the blood components, as liquid biopsy reservoirs, are complementary rather than competitive, and orthogonal data sets were even shown to harbor synergistic effects. The unmistakable potential of multimodal liquid biopsy testing, however, is dampened by its clinical utility, which is yet to be proven, the lack of methodical standardization and insufficiently mature reimbursement, logistics and data handling.

Proteomics and metabolomics approach in adult and pediatric glioma diagnostics

The diagnosis of glioma is mainly based on imaging methods that do not distinguish between stage and subtype prior to histopathological analysis. Patients with gliomas are generally diagnosed in the symptomatic stage of the disease. Additionally, healing scar tissue may be mistakenly identified based on magnetic resonance imaging (MRI) as a false positive tumor recurrence in postoperative patients. Current knowledge of molecular alterations underlying gliomagenesis and identification of tumoral biomarkers allow for their use as discriminators of the state of the organism. Moreover, a multiomics approach provides the greatest spectrum and the ability to track physiological changes and can serve as a minimally invasive method for diagnosing asymptomatic gliomas, preceding surgery and allowing for the initiation of prophylactic treatment. It is important to create a vast biomarker library for adults and pediatric patients due to their metabolic differences. This review focuses on the most promising proteomic, metabolomic and lipidomic glioma biomarkers, their pathways, the interactions, and correlations that can be considered characteristic of tumor grade or specific subtype.