From bottom-up to cell surface proteomics: detergents or no detergents, that is the question

Measuring the expression levels of membrane proteins (MPs) is crucial for understanding cell differentiation and tissue specificity, defining disease characteristics, identifying biomarkers, and developing therapeutics. While bottom-up proteomics addresses the need for accurately surveying the membrane proteome, the lower abundance and hydrophobic nature of MPs pose challenges in sample preparation. As MPs normally reside in the lipid bilayer, conventional extraction methods rely on detergents, introducing here a paradox - detergents prevent aggregation and facilitate protein processing, but themselves become contaminants that interfere with downstream analytical applications. Various detergent removal methods exist to mitigate this issue, including filter-aided sample preparation, SP3, suspension trapping, and membrane mimetics. This review delves into the fundamentals of each strategy, applications, merits, and limitations, providing insights into their effectiveness in MP research.

The intricate role of annexin A2 in kidney: a comprehensive review

Annexin A2 (Anxa2) is a calcium (Ca2+)-regulated phospholipid binding protein composed of a variable N-terminus and a conserved core domain. This protein has been widely found in many tissues and fluids, including tubule cells, glomerular epithelial cells, renal vessels, and urine. In acute kidney injury, the expression level of this protein is markedly elevated in response to acute stress. Moreover, Anxa2 is a novel biomarker and potential therapeutic target with prognostic value in chronic kidney disease. In addition, Anxa2 is associated not only with clear-cell renal cell carcinoma differentiation but also the formation of calcium-related nephrolithiasis. In this review, we discuss the characteristics and functions of Anxa2 and focus on recent reports on the role of Anxa2 in the kidney, which may be useful for future research.

Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell's immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.

Absolute quantitative proteomics using the total protein approach to identify novel clinical immunohistochemical markers in renal neoplasms

BACKGROUND

Renal neoplasms encompass a variety of malignant and benign tumors, including many with shared characteristics. The diagnosis of these renal neoplasms remains challenging with currently available tools. In this work, we demonstrate the total protein approach (TPA) based on high-resolution mass spectrometry (MS) as a tool to improve the accuracy of renal neoplasm diagnosis.

METHODS

Frozen tissue biopsies of human renal tissues [clear cell renal cell carcinoma (n = 7), papillary renal cell carcinoma (n = 5), chromophobe renal cell carcinoma (n = 5), and renal oncocytoma (n = 5)] were collected for proteome analysis. Normal adjacent renal tissue (NAT, n = 5) was used as a control. Proteins were extracted and digested using trypsin, and the digested proteomes were analyzed by label-free high-resolution MS (nanoLC-ESI-HR-MS/MS). Quantitative analysis was performed by comparison between protein abundances of tumors and NAT specimens, and the label-free and standard-free TPA was used to obtain absolute protein concentrations.

RESULTS

A total of 205 differentially expressed proteins with the potential to distinguish the renal neoplasms were found. Of these proteins, a TPA-based panel of 24, including known and new biomarkers, was selected as the best candidates to differentiate the neoplasms. As proof of concept, the diagnostic potential of PLIN2, TUBB3, LAMP1, and HK1 was validated using semi-quantitative immunohistochemistry with a total of 128 samples assessed on tissue micro-arrays.

CONCLUSIONS

We demonstrate the utility of combining high-resolution MS and the TPA as potential new diagnostic tool in the pathology of renal neoplasms. A similar TPA approach may be implemented in any cancer study with solid biopsies.

Quantitative Proteomics Identifies Secreted Diagnostic Biomarkers as well as Tumor-Dependent Prognostic Targets for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the third most common and most malignant urological cancer, with a 5-year survival rate of 10% for patients with advanced tumors. Here, we identified 10,160 unique proteins by in-depth quantitative proteomics, of which 955 proteins were significantly regulated between tumor and normal adjacent tissues. We verified four putatively secreted biomarker candidates, namely, PLOD2, FERMT3, SPARC, and SIRPα, as highly expressed proteins that are not affected by intratumor and intertumor heterogeneity. Moreover, SPARC displayed a significant increase in urine samples of patients with ccRCC, making it a promising marker for the detection of the disease in body fluids. Furthermore, based on molecular expression profiles, we propose a biomarker panel for the robust classification of ccRCC tumors into two main clusters, which significantly differed in patient outcome with an almost three times higher risk of death for cluster 1 tumors compared with cluster 2 tumors. Moreover, among the most significant clustering proteins, 13 were targets of repurposed inhibitory FDA-approved drugs. Our rigorous proteomics approach identified promising diagnostic and tumor-discriminative biomarker candidates which can serve as therapeutic targets for the treatment of ccRCC. IMPLICATIONS: Our in-depth quantitative proteomics analysis of ccRCC tissues identifies the putatively secreted protein SPARC as a promising urine biomarker and reveals two molecular tumor phenotypes.

Proteomic approaches for characterizing renal cell carcinoma

Renal cell carcinoma is among the top 15 most commonly diagnosed cancers worldwide, comprising multiple sub-histologies with distinct genomic, proteomic, and clinicopathological features. Proteomic methodologies enable the detection and quantitation of protein profiles associated with the disease state and have been explored to delineate the dysregulated cellular processes associated with renal cell carcinoma. In this review we highlight the reports that employed proteomic technologies to characterize tissue, blood, and urine samples obtained from renal cell carcinoma patients. We describe the proteomic approaches utilized and relate the results of studies in the larger context of renal cell carcinoma biology. Moreover, we discuss some unmet clinical needs and how emerging proteomic approaches can seek to address them. There has been significant progress to characterize the molecular features of renal cell carcinoma; however, despite the large-scale studies that have characterized the genomic and transcriptomic profiles, curative treatments are still elusive. Proteomics facilitates a direct evaluation of the functional modules that drive pathobiology, and the resulting protein profiles would have applications in diagnostics, patient stratification, and identification of novel therapeutic interventions.

Urinary Extracellular Vesicles and Salt-Losing Tubulopathies: A Proteomic Approach

Renal tubular cells release urinary extracellular vesicles (uEV) that are considered a promising source of molecular markers for renal dysfunction and injury. We investigated uEV proteomes of patients with hereditary salt-losing tubulopathies (SLTs), focusing on those caused by Gitelman and Bartter (BS) syndromes, to provide potential markers for differential diagnosis. Second morning urine was collected from patients with genetically proven SLTs and uEV were isolated by the ultracentrifugation-based protocol. The uEV proteome was run through a diagonal bidimensional electrophoresis (16BAC/SDS-PAGE), to improve hydrophobic protein resolution. Sixteen differential spots from the proteome of two variants (BS2 and BS3) were analysed by nLC-ESI-MS/MS after in-gel tryptic digestion. A total of 167 protein species were identified from 7 BS2 spots and 9 BS3 spot. Most of these proteins were membrane-associated proteins, in particular transmembrane proteins, and were related to typical renal functions. The differential content of some uEV was then validated by immunoblotting. Our work suggests that uEV proteomics represents a promising strategy for the identification of differential SLT proteins. This could play a role in understanding the pathophysiological disease mechanisms and may support the recognition of different syndromes.

Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer

Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.

Proteomics of liquid biopsies: Depicting RCC infiltration into the renal vein by MS analysis of urine and plasma

Liquid biopsies, as blood and urine, could offer an invaluable, easily accessible source of biomarkers, and evidences for elucidating the pathological processes. Only few studies integrated the proteomes driven by more than one biofluid. Furthermore, it is not clear which biofluid better mirrors the alterations triggered by disease. Venous infiltrating RCC(Renal Cell Carcinoma) could represent an advantageous model for exploring this aspect. Herein, we investigate how blood and urine "proteomically" reflect the changes occurring during RCC infiltration into renal vein(RV) by label-free nLC-ESI-MS/MS. We found 574 and 58 differentially expressed proteins(DEPs) in response to vascular involvement. To the augment of vascular involvement, the abundance of only three proteins in urine(UROM,RALA,CNDP1) and two in plasma(APOA1,K2C1) diminished while increased for twenty-six urinary proteins. 80 proteins were found both in urine and plasma, among which twenty-eight were DEPs. A huge overlap between the two biofluids was highlighted, as expected, being urine the filtrate of blood. However, this consistency decreases when RV-occlusion occurs suggesting alternative protein releases, and a loss of kidney architecture. Moreover, several proteomic and functional signatures were biofluid-specific. In conclusion, the complementarity between the specimens allowed to achieve a deeper level of molecular complexity of the RCC venous infiltration. SIGNIFICANCE: Although plasma and urine are strongly interconnected, only few proteomic studies investigated the complementarity of these fluids as bio-sources of information. Moreover, none of them was focused to their analysis and comparison in the context of vascular infiltration of renal cancer. Herein, new insights were gained regarding the impact into urinary and plasma proteome of the changes triggered by the ccRCC invasion into vascular system and renal vein. Furthermore, the integration of the information driven by the two liquid biopsies permits to unravel biological processes otherwise lost.

The proteomic landscape of renal tumors

INTRODUCTION

Renal cell carcinoma (RCC) is the most fatal of the common urologic cancers, with approximately 35% of patients dying within 5 years following diagnosis. Therefore, there is a need for non-invasive markers that are capable of detecting and determining the severity of small renal masses at an early stage in order to tailor treatment and follow-up. Proteomic studies have proved to be very useful in the study of tumors. Areas covered: In this review, we will detail the current knowledge obtained by the different proteomic approaches, focusing on MS-based strategies, used to investigate RCC biology in order to identify diagnostic, prognostic and predictive biomarkers on tissue, cultured cells and biological fluids. Expert commentary: Currently, no reliable biomarkers or targets for RCC have been translated into the clinical setting. Moreover, despite the efforts of proteomics and other -omics disciplines, only a small number of them have been observed as shared targets between the different analytical platforms and biological specimens. The difficulty to define a specific molecular pattern for RCC and its subtypes highlights a peculiar profile and a heterogeneity that must be taken into account in future studies.

Comparative proteomic profiling identifies potential prognostic factors for human clear cell renal cell carcinoma

The identification of markers for disease diagnostic, prognostic, or predictive purposes will have a great effect in improving patient management. Proteomic‑based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on four patients including clear cell renal cell carcinoma (ccRCC) and paired adjacent non‑cancerous renal tissues using label‑free quantitative proteomics and liquid chromatography‑tandem mass spectrometry (LC‑MS/MS) to identify differentially expressed proteins. Among 3,061 identified non‑redundant proteins, we found that 210 proteins were differentially expressed (83 overexpressed and 127 underexpressed) in ccRCC tissue when compared with normal kidney tissues. Two most significantly dysregulated proteins (PCK1 and SNRPF) were chosen to be confirmed by western blotting. Pathway analysis of 210 differentially expressed proteins showed that dysregulated proteins are related to many cancer‑related biological processes such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Online survival analysis indicated the prognostic value of these dysregulated proteins. In conclusion, we identified some potential diagnostic biomarkers for ccRCC and an in‑depth understanding of their involved biological pathways may help pave the way to discover new therapeutic strategies for ccRCC.

Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer

Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

Integral membrane proteins in proteomics. How to break open the black box?

Integral membrane proteins (IMPs) are coded by 20-30% of human genes and execute important functions - transmembrane transport, signal transduction, cell-cell communication, cell adhesion to the extracellular matrix, and many other processes. Due to their hydrophobicity, low expression and lack of trypsin cleavage sites in their transmembrane segments, IMPs have been generally under-represented in routine proteomic analyses. However, the field of membrane proteomics has changed markedly in the past decade, namely due to the introduction of filter assisted sample preparation (FASP), the establishment of cell surface capture (CSC) protocols, and the development of methods that enable analysis of the hydrophobic transmembrane segments. This review will summarize the recent developments in the field and outline the most successful strategies for the analysis of integral membrane proteins.

SIGNIFICANCE

Integral membrane proteins (IMPs) are attractive therapeutic targets mostly due to their many important functions. However, our knowledge of the membrane proteome is severely limited to effectively exploit their potential. This is mostly due to the lack of appropriate techniques or methods compatible with the typical features of IMPs, namely hydrophobicity, low expression and lack of trypsin cleavage sites. This review summarizes the most recent development in membrane proteomics and outlines the most successful strategies for their large-scale analysis.

Searching Missing Proteins Based on the Optimization of Membrane Protein Enrichment and Digestion Process

A membrane protein enrichment method composed of ultracentrifugation and detergent-based extraction was first developed based on MCF7 cell line. Then, in-solution digestion with detergents and eFASP (enhanced filter-aided sample preparation) with detergents were compared with the time-consuming in-gel digestion method. Among the in-solution digestion strategies, the eFASP combined with RapiGest identified 1125 membrane proteins. Similarly, the eFASP combined with sodium deoxycholate identified 1069 membrane proteins; however, the in-gel digestion characterized 1091 membrane proteins. Totally, with the five digestion methods, 1390 membrane proteins were identified with ≥1 unique peptides, among which 1345 membrane proteins contain unique peptides ≥2. This is the biggest membrane protein data set for MCF7 cell line and even breast cancer tissue samples. Interestingly, we identified 13 unique peptides belonging to 8 missing proteins (MPs). Finally, eight unique peptides were validated by synthesized peptides. Two proteins were confirmed as MPs, and another two proteins were candidate detections.