Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

A Quantitative Proteome Map of the Human Body.

Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.

A mutation in the low-complexity domain of splicing factor hnRNPA1 linked to amyotrophic lateral sclerosis disrupts distinct neuronal RNA splicing networks.

Amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative disease characterized by loss of motor neurons. Human genetic studies have linked mutations in RNA-binding proteins as causative for this disease. The hnRNPA1 protein, a known pre-mRNA splicing factor, is mutated in some ALS patients. Here, two human cell models were generated to investigate how a mutation in the C-terminal low-complexity domain (LCD) of hnRNPA1 can cause splicing changes of thousands of transcripts that collectively are linked to the DNA damage response, cilium organization, and translation. We show that the hnRNPA1 D262V mutant protein binds to new binding sites on differentially spliced transcripts from genes that are linked to ALS. We demonstrate that this ALS-linked hnRNPA1 mutation alters normal RNA-dependent protein-protein interactions. Furthermore, cells expressing this hnRNPA1 mutant exhibit a cell aggregation phenotype, markedly reduced growth rates, changes in stress granule kinetics, and aberrant growth of neuronal processes. This study provides insight into how a single amino acid mutation in a splicing factor can alter RNA splicing networks of genes linked to ALS.

Global mitochondrial protein import proteomics reveal distinct regulation by translation and translocation machinery.

Most mitochondrial proteins are translated in the cytosol and imported into mitochondria. Mutations in the mitochondrial protein import machinery cause human pathologies. However, a lack of suitable tools to measure protein uptake across the mitochondrial proteome has prevented the identification of specific proteins affected by import perturbation. Here, we introduce mePRODmt, a pulsed-SILAC based proteomics approach that includes a booster signal to increase the sensitivity for mitochondrial proteins selectively, enabling global dynamic analysis of endogenous mitochondrial protein uptake in cells. We applied mePRODmt to determine protein uptake kinetics and examined how inhibitors of mitochondrial import machineries affect protein uptake. Monitoring changes in translation and uptake upon mitochondrial membrane depolarization revealed that protein uptake was extensively modulated by the import and translation machineries via activation of the integrated stress response. Strikingly, uptake changes were not uniform, with subsets of proteins being unaffected or decreased due to changes in translation or import capacity.

Growth Factor Receptor Signaling Inhibition Prevents SARS-CoV-2 Replication.

SARS-CoV-2 infections are rapidly spreading around the globe. The rapid development of therapies is of major importance. However, our lack of understanding of the molecular processes and host cell signaling events underlying SARS-CoV-2 infection hinders therapy development. We use a SARS-CoV-2 infection system in permissible human cells to study signaling changes by phosphoproteomics. We identify viral protein phosphorylation and define phosphorylation-driven host cell signaling changes upon infection. Growth factor receptor (GFR) signaling and downstream pathways are activated. Drug-protein network analyses revealed GFR signaling as key pathways targetable by approved drugs. The inhibition of GFR downstream signaling by five compounds prevents SARS-CoV-2 replication in cells, assessed by cytopathic effect, viral dsRNA production, and viral RNA release into the supernatant. This study describes host cell signaling events upon SARS-CoV-2 infection and reveals GFR signaling as a central pathway essential for SARS-CoV-2 replication. It provides novel strategies for COVID-19 treatment.

Functional Translatome Proteomics Reveal Converging and Dose-Dependent Regulation by mTORC1 and eIF2α.

Regulation of translation is essential during stress. However, the precise sets of proteins regulated by the key translational stress responses-the integrated stress response (ISR) and mTORC1-remain elusive. We developed multiplexed enhanced protein dynamics (mePROD) proteomics, adding signal amplification to dynamic-SILAC and multiplexing, to enable measuring acute changes in protein synthesis. Treating cells with ISR/mTORC1-modulating stressors, we showed extensive translatome modulation with ∼20% of proteins synthesized at highly reduced rates. Comparing translation-deficient sub-proteomes revealed an extensive overlap demonstrating that target specificity is achieved on protein level and not by pathway activation. Titrating cap-dependent translation inhibition confirmed that synthesis of individual proteins is controlled by intrinsic properties responding to global translation attenuation. This study reports a highly sensitive method to measure relative translation at the nascent chain level and provides insight into how the ISR and mTORC1, two key cellular pathways, regulate the translatome to guide cellular survival upon stress.

Multi-omics analysis reveals the potential pathogenesis and therapeutic targets of diabetic kidney disease.

Clinicians have long been interested in understanding the molecular basis of diabetic kidney disease (DKD)and its potential treatment targets. Its pathophysiology involves protein phosphorylation, one of the most recognizable post-transcriptional modifications, that can take part in many cellular functions and control different metabolic processes. In order to recognize the molecular and protein changes of DKD kidney, this study applied Tandem liquid chromatography-mass spectrometry (LC-MS/MS) and Next-Generation Sequencing, along with Tandem Mass Tags (TMT) labeling techniques to evaluate the mRNA, protein and modified phosphorylation sites between DKD mice and model ones. Based on Gene Ontology (GO) and KEGG pathway analyses of transcriptome and proteome, The molecular changes of DKD include accumulation of extracellular matrix, abnormally activated inflammatory microenvironment, oxidative stress and lipid metabolism disorders, leading to glomerulosclerosis and tubulointerstitial fibrosis. Oxidative stress has been emphasized as an important factor in DKD and progression to ESKD, which is directly related to podocyte injury, albuminuria and renal tubulointerstitial fibrosis. A histological study of phosphorylation further revealed that kinases were crucial. Three groups of studies have found that RAS signaling pathway, RAP1 signaling pathway, AMPK signaling pathway, PPAR signaling pathway and HIF-1 signaling pathway were crucial for the pathogenesis of DKD. Through this approach, it was discovered that targeting specific molecules, proteins, kinases and critical pathways could be a promising approach for treating DKD.

A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics.

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

Dissecting Detergent-Insoluble Proteome in Alzheimer's Disease by TMTc-Corrected Quantitative Mass Spectrometry.

Protein aggregation of amyloid-ß peptides and tau are pathological hallmarks of Alzheimer's disease (AD), which are often resistant to detergent extraction and thus enriched in the insoluble proteome. However, additional proteins that coaccumulate in the detergent-insoluble AD brain proteome remain understudied. Here, we comprehensively characterized key proteins and pathways in the detergent-insoluble proteome from human AD brain samples using differential extraction, tandem mass tag (TMT) labeling, and two-dimensional LC-tandem mass spectrometry. To improve quantification accuracy of the TMT method, we developed a complement TMT-based strategy to correct for ratio compression. Through the meta-analysis of two independent detergent-insoluble AD proteome datasets (8914 and 8917 proteins), we identified 190 differentially expressed proteins in AD compared with control brains, highlighting the pathways of amyloid cascade, RNA splicing, endocytosis/exocytosis, protein degradation, and synaptic activity. To differentiate the truly detergent-insoluble proteins from copurified background during protein extraction, we analyzed the fold of enrichment for each protein by comparing the detergent-insoluble proteome with the whole proteome from the same AD samples. Among the 190 differentially expressed proteins, 84 (51%) proteins of the upregulated proteins (n = 165) were enriched in the insoluble proteome, whereas all downregulated proteins (n = 25) were not enriched, indicating that they were copurified components. The vast majority of these enriched 84 proteins harbor low-complexity regions in their sequences, including amyloid-ß, Tau, TARDBP/TAR DNA-binding protein 43, SNRNP70/U1-70K, MDK, PTN, NTN1, NTN3, and SMOC1. Moreover, many of the enriched proteins in AD were validated in the detergent-insoluble proteome by five steps of differential extraction, proteomic analysis, or immunoblotting. Our study reveals a resource list of proteins and pathways that are exclusively present in the detergent-insoluble proteome, providing novel molecular insights to the formation of protein pathology in AD.

Multitissue Circadian Proteome Atlas of WT and Per1-/-/Per2-/- Mice.

The molecular basis of circadian rhythm, driven by core clock genes such as Per1/2, has been investigated on the transcriptome level, but not comprehensively on the proteome level. Here we quantified over 11,000 proteins expressed in eight types of tissues over 46 h with an interval of 2 h, using WT and Per1/Per2 double knockout mouse models. The multitissue circadian proteome landscape of WT mice shows tissue-specific patterns and reflects circadian anticipatory phenomena, which are less obvious on the transcript level. In most peripheral tissues of double knockout mice, reduced protein cyclers are identified when compared with those in WT mice. In addition, PER1/2 contributes to controlling the anticipation of the circadian rhythm, modulating tissue-specific cyclers as well as key pathways including nucleotide excision repair. Severe intertissue temporal dissonance of circadian proteome has been observed in the absence of Per1 and Per2. The γ-aminobutyric acid might modulate some of these temporally correlated cyclers in WT mice. Our study deepens our understanding of rhythmic proteins across multiple tissues and provides valuable insights into chronochemotherapy. The data are accessible at https://prot-rhythm.prottalks.com/.

Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays.

Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standard─which is commercially available but may also be assembled in-lab─and establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species.

Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples.

Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.

Comparative Hippocampal Proteome and Phosphoproteome in a Niemann-Pick, Type C1 Mouse Model Reveal Insights into Disease Mechanisms.

Niemann-Pick disease, type C (NPC) is a neurodegenerative, lysosomal storage disorder in individuals carrying two mutated copies of either the NPC1 or NPC2 gene. Consequently, impaired cholesterol recycling and an array of downstream events occur. Interestingly, in NPC, the hippocampus displays lysosomal lipid storage but does not succumb to progressive neurodegeneration as significantly as other brain regions. Since defining the neurodegeneration mechanisms in this disease is still an active area of research, we use mass spectrometry to analyze the overall proteome and phosphorylation pattern changes in the hippocampal region of a murine model of NPC. Using 3 week old mice representing an early disease time point, we observed changes in the expression of 47 proteins, many of which are consistent with the previous literature. New to this study, changes in members of the SNARE complex, including STX7, VTI1B, and VAMP7, were identified. Furthermore, we identified that phosphorylation of T286 on CaMKIIα and S1303 on NR2B increased in mutant animals, even at the late stage of the disease. These phosphosites are crucial to learning and memory and can trigger neuronal death by altering protein-protein interactions.

Photochemically Controlled Release of the Glucose Transporter 1 Inhibitor for Glucose Deprivation Responses and Cancer Suppression Research.

Cancer cells need a greater supply of glucose mainly due to their aerobic glycolysis, known as the Warburg effect. Glucose transport by glucose transporter 1 (GLUT1) is the rate-limiting step for glucose uptake, making it a potential cancer therapeutic target. However, GLUT1 is widely expressed and performs crucial functions in a variety of cells, and its indiscriminate inhibition will cause serious side effects. In this study, we designed and synthesized a photocaged GLUT1 inhibitor WZB117-PPG to suppress the growth of cancer cells in a spatiotemporally controllable manner. WZB117-PPG exhibited remarkable photolysis efficiency and substantial cytotoxicity toward cancer cells under visible light illumination with minimal side effects, ensuring its safety as a potential cancer therapy. Furthermore, our quantitative proteomics data delineated a comprehensive portrait of responses in cancer cells under glucose deprivation, underlining the mechanism of cell death via necrosis rather than apoptosis. We reason that our study provides a potentially reliable cancer treatment strategy and can be used as a spatiotemporally controllable trigger for studying nutrient deprivation-related stress responses.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Analysis of Protein Cysteine Acylation Using a Modified Suspension Trap (Acyl-Trap).

Proteins undergo reversible S-acylation via a thioester linkage in vivo. S-palmitoylation, modification by C16:0 fatty acid, is a common S-acylation that mediates critical protein-membrane and protein-protein interactions. The most widely used S-acylation assays, including acyl-biotin exchange and acyl resin-assisted capture, utilize blocking of free Cys thiols, hydroxylamine-dependent cleavage of the thioester and subsequent labeling of nascent thiol. These assays generally require >500 µg of protein input material per sample and numerous reagent removal and washing steps, making them laborious and ill-suited for high throughput and low input applications. To overcome these limitations, we devised "Acyl-Trap", a suspension trap-based assay that utilizes a thiol-reactive quartz to enable buffer exchange and hydroxylamine-mediated S-acyl enrichment. We show that the method is compatible with protein-level detection of S-acylated proteins (e.g., H-Ras) as well as S-acyl site identification and quantification using "on trap" isobaric labeling and LC-MS/MS from as little as 20 µg of protein input. In mouse brain, Acyl-Trap identified 279 reported sites of S-acylation and 1298 previously unreported putative sites. Also described are conditions for long-term hydroxylamine storage, which streamline the assay. More generally, Acyl-Trap serves as a proof-of-concept for PTM-tailored suspension traps suitable for both traditional protein detection and chemoproteomic workflows.

Comparative proteomics in tall fescue to reveal underlying mechanisms for improving Photosystem II thermotolerance during heat stress memory.

BACKGROUND: The escalating impacts of global warming intensify the detrimental effects of heat stress on crop growth and yield. Among the earliest and most vulnerable sites of damage is Photosystem II (PSII). Plants exposed to recurring high temperatures develop heat stress memory, a phenomenon that enables them to retain information from previous stress events to better cope with subsequent one. Understanding the components and regulatory networks associated with heat stress memory is crucial for the development of heat-resistant crops. RESULTS: Physiological assays revealed that heat priming (HP) enabled tall fescue to possess higher Photosystem II photochemical activity when subjected to trigger stress. To investigate the underlying mechanisms of heat stress memory, we performed comparative proteomic analyses on tall fescue leaves at S0 (control), R4 (primed), and S5 (triggering), using an integrated approach of Tandem Mass Tag (TMT) labeling and Liquid Chromatography-Mass Spectrometry. A total of 3,851 proteins were detected, with quantitative information available for 3,835 proteins. Among these, we identified 1,423 differentially abundant proteins (DAPs), including 526 proteins that were classified as Heat Stress Memory Proteins (HSMPs). GO and KEGG enrichment analyses revealed that the HSMPs were primarily associated with the "autophagy" in R4 and with "PSII repair", "HSP binding", and "peptidase activity" in S5. Notably, we identified 7 chloroplast-localized HSMPs (HSP21, DJC77, EGY3, LHCA4, LQY1, PSBR and DEGP8, R4/S0 > 1.2, S5/S0 > 1.2), which were considered to be effectors linked to PSII heat stress memory, predominantly in cluster 4. Protein-protein interaction (PPI) analysis indicated that the ubiquitin-proteasome system, with key nodes at UPL3, RAD23b, and UCH3, might play a role in the selective retention of memory effectors in the R4 stage. Furthermore, we conducted RT-qPCR validation on 12 genes, and the results showed that in comparison to the S5 stage, the R4 stage exhibited reduced consistency between transcript and protein levels, providing additional evidence for post-transcriptional regulation in R4. CONCLUSIONS: These findings provide valuable insights into the establishment of heat stress memory under recurring high-temperature episodes and offer a conceptual framework for breeding thermotolerant crops with improved PSII functionality.

An interim exploratory proteomics biomarker analysis of a phase 2 clinical trial to assess the impact of CT1812 in Alzheimer's disease.

CT1812 is a novel, brain penetrant small molecule modulator of the sigma-2 receptor (S2R) that is currently in clinical development for the treatment of Alzheimer's disease (AD). Preclinical and early clinical data show that, through S2R, CT1812 selectively prevents and displaces binding of amyloid beta (Aß) oligomers from neuronal synapses and improves cognitive function in animal models of AD. SHINE is an ongoing phase 2 randomized, double-blind, placebo-controlled clinical trial (COG0201) in participants with mild to moderate AD, designed to assess the safety and efficacy of 6 months of CT1812 treatment. To elucidate the mechanism of action in AD patients and pharmacodynamic biomarkers of CT1812, the present study reports exploratory cerebrospinal fluid (CSF) biomarker data from 18 participants in an interim analysis of the first set of patients in SHINE (part A). Untargeted mass spectrometry-based discovery proteomics detects >2000 proteins in patient CSF and has documented utility in accelerating the identification of novel AD biomarkers reflective of diverse pathophysiologies beyond amyloid and tau, and enabling identification of pharmacodynamic biomarkers in longitudinal interventional trials. We leveraged this technique to analyze CSF samples taken at baseline and after 6 months of CT1812 treatment. Proteome-wide protein levels were detected using tandem mass tag-mass spectrometry (TMT-MS), change from baseline was calculated for each participant, and differential abundance analysis by treatment group was performed. This analysis revealed a set of proteins significantly impacted by CT1812, including pathway engagement biomarkers (i.e., biomarkers tied to S2R biology) and disease modification biomarkers (i.e., biomarkers with altered levels in AD vs. healthy control CSF but normalized by CT1812, and biomarkers correlated with favorable trends in ADAS-Cog11 scores). Brain network mapping, Gene Ontology, and pathway analyses revealed an impact of CT1812 on synapses, lipoprotein and amyloid beta biology, and neuroinflammation. Collectively, the findings highlight the utility of this method in pharmacodynamic biomarker identification and providing mechanistic insights for CT1812, which may facilitate the clinical development of CT1812 and enable appropriate pre-specification of biomarkers in upcoming clinical trials of CT1812.

Multi-omics in MECP2 duplication syndrome patients and carriers.

MECP2 duplication syndrome (MDS) is an X-linked neurodevelopmental disorder caused by the gain of dose of at least the genes MECP2 and IRAK1 and is characterised by intellectual disability (ID), developmental delay, hypotonia, epilepsy and recurrent infections. It mainly affects males, and females can be affected or asymptomatic carriers. Rett syndrome (RTT) is mainly triggered by loss of function mutations in MECP2 and is a well described syndrome that presents ID, epilepsy, lack of purposeful hand use and impaired speech, among others. As a result of implementing omics technology, altered biological pathways in human RTT samples have been reported, but such molecular characterisation has not been performed in patients with MDS. We gathered human skin fibroblasts from 17 patients with MDS, 10 MECP2 duplication carrier mothers and 21 patients with RTT, and performed multi-omics (RNAseq and proteomics) analysis. Here, we provide a thorough description and compare the shared and specific dysregulated biological processes between the cohorts. We also highlight the genes TMOD2, SRGAP1, COPS2, CNPY2, IGF2BP1, MOB2, VASP, FZD7, ECSIT and KIF3B as biomarker and therapeutic target candidates due to their implication in neuronal functions. Defining the RNA and protein profiles has shown that our four cohorts are less alike than expected by their shared phenotypes.

Proteomics of prostate cancer serum and plasma using low and high throughput approaches.

Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.