Update on proteomic studies of formalin-fixed paraffin-embedded tissues

Heart proteomic profiling discovers MYH6 and COX5B as biomarkers for sudden unexplained death

Sudden unexplained death (SUD) is not uncommon in forensic pathology. Yet, diagnosis of SUD remains challenging due to lack of specific biomarkers. This study aimed to screen differentially expressed proteins (DEPs) and validate their usefulness as diagnostic biomarkers for SUD cases. We designed a three-phase investigation, where in the discovery phase, formalin-fixed paraffin-embedded (FFPE) heart specimens were screened through label-free proteomic analysis of cases dying from SUD, mechanical injury and carbon monoxide (CO) intoxication. A total of 26 proteins were identified to be DEPs for the SUD cases after rigorous criterion. Bioinformatics and Adaboost-recursive feature elimination (RFE) analysis further revealed that three of the 26 proteins (MYH6, COX5B and TNNT2) were potential discriminative biomarkers. In the training phase, MYH6 and COX5B were verified to be true DEPs in cardiac tissues from 29 independent SUD cases as compared with a serial of control cases (n = 42). Receiver operating characteristic (ROC) analysis illustrated that combination of MYH6 and COX5B achieved optimal diagnostic sensitivity (89.7 %) and specificity (84.4 %), with area under the curve (AUC) being 0.91. A diagnostic software based on the logistic regression formula derived from the training phase was then constructed. In the validation phase, the diagnostic software was applied to eight authentic SUD cases, seven (87.5 %) of which were accurately recognized. Our study provides a valid strategy towards practical diagnosis of SUD by integrating cardiac MYH6 and COX5B as dual diagnostic biomarkers.

A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

Protein Profiling in Human Papillomavirus-Associated Cervical Carcinogenesis: Cornulin as a Biomarker for Disease Progression

Nearly 90% of cervical cancers are linked to human papillomavirus (HPV). Uncovering the protein signatures in each histological phase of cervical oncogenesis provides a path to biomarker discovery. The proteomes extracted from formalin-fixed paraffin-embedded tissues of the normal cervix, HPV16/18-associated squamous intraepithelial lesion (SIL), and squamous cell carcinoma (SCC) were compared using liquid chromatography-mass spectrometry (LC-MS). A total of 3597 proteins were identified, with 589, 550, and 1570 proteins unique to the normal cervix, SIL, and SCC groups, respectively, while 332 proteins overlapped between the three groups. In the transition from normal cervix to SIL, all 39 differentially expressed proteins were downregulated, while all 51 proteins discovered were upregulated in SIL to SCC. The binding process was the top molecular function, while chromatin silencing in the SIL vs. normal group, and nucleosome assembly in SCC vs. SIL groups was the top biological process. The PI3 kinase pathway appears crucial in initiating neoplastic transformation, while viral carcinogenesis and necroptosis are important for cell proliferation, migration, and metastasis in cervical cancer development. Annexin A2 and cornulin were selected for validation based on LC-MS results. The former was downregulated in the SIL vs. normal cervix and upregulated in the progression from SIL to SCC. In contrast, cornulin exhibited the highest expression in the normal cervix and lowest in SCC. Although other proteins, such as histones, collagen, and vimentin, were differentially expressed, their ubiquitous expression in most cells precluded further analysis. Immunohistochemical analysis of tissue microarrays found no significant difference in Annexin A2 expression between the groups. Conversely, cornulin exhibited the strongest expression in the normal cervix and lowest in SCC, supporting its role as a tumor suppressor and potential biomarker for disease progression.

From Bowen disease to cutaneous squamous cell carcinoma: eight markers were verified from transcriptomic and proteomic analyses

Background

Bowen's disease is a cutaneous squamous cell carcinoma (CSCC) in situ. If left untreated, BD may progress to invasive CSCC. CSCC is one of the most common cutaneous carcinoma in the elderly and the advanced, metastasis CSCC usually have a poor outcomes. However, the mechanisms of invasion and metastasis from Bowen’s disease to CSCC is complicated and still unclear.

Objectives

The aim of this study was to explore the biomarkers and molecular alterations in Bowen’s disease development process via analyzing the proteomics changes in tissues of CSCC, Bowen disease and healthy skin.

Methods

A total of 7 individuals with CSCC (5 for proteomics study and 2 for validation), 7 individuals with Bowen disease (5 for proteomics study and 2 for validation) and 7 healthy controls (5 for proteomics study and 2 for validation) presented to the Department of Dermatology, Yijishan Hospital, the First Affiliated Hospital of Wannan Medical College between January 2021 and December 2021 were enrolled. The proteomics analysis was performed to screen differentially expressed proteins/gens (DEPs/DEGs) in the lesions of CSCC, Bowen disease and healthy skin tissues. The transcriptomic data (GSE32628) of CSCC was selected and downloaded from the GEO database. The common DEGs in our proteomics results and GSE32628 between CSCC and healthy skin tissues were selected. And then, the common DEGs which significantly up or down-regulated between CSCC and Bowen disease in our proteomics results were further screened to identify using Western blot methods in the validation group. CSCC A431 cells were transfected with SERPINB1 small interfering RNA (si-SERPINB1) or small interfering RNA negative control (si-NC). To explore the effect of SERPINB1 silencing on migration and invasion ability of A431 cells.

Results

A total of 501 proteins were differentially expressed between the CSCC and healthy skin tissues, with 332 up-regulated and 169 down-regulated at least 1.5-fold with a P value < 0.05. These DEPs involved multiple biological functions such as protein binding process, immune, inflammation, ribosome, protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway and others. A total of 20 common DEGs (COL3A1, LUM, TNC, COL1A1, ALDH3A2, FSCN1, SERPINB4, SERPINB1, CD36, COL4A1, CSTB, GPX3, S100A7, ACTN1, SERPINB3, S100A8, RAB31, STAT1, SPRR1B, S100A9) between CSCC and healthy skin tissues in GSE32628 and our proteomics results were found. Besides, the proteins of TNC, FSCN1, SERPINB1, ACTN1 and RAB31 in CSCC were significantly up-regulated, while COL3A1, COL1A1 and CD36 were significantly down-regulated relative to Bowen disease in proteomics results. These proteins were mainly involved in multiple pathways, including Focal adhesion, ECM-receptor interaction, Human papillomavirus infection, PI3K-Akt signaling pathway, PPAR signaling pathway, AMPK signaling pathway and others. These eight proteins were selected for further validation. According to the Western blotting analysis, when compared with the Bowen disease and healthy skin tissues, we found that the relative expression levels of TNC, FSCN1, SERPINB1, ACTN1 and RAB31 in the CSCC were significantly increased, while COL1A1 and CD36 were significantly decreased, and the differences were statistically significant (P < 0.05). Furthermore, the relative expression levels of TNC, FSCN1, SERPINB1 in the Bowen disease were also significantly increased, while the COL3A1 were also significantly decreased relative to the healthy control. SERPINB1 siRNA inhibited the expression of SERPINB1 at mRNA and protein levels in the A431 cells. After interfering with the expression of SERPINB1, the migration and invasion ability in the A431 cells were significantly decreased (P < 0.05).

Conclusions

This study highlights that eight proteins, TNC, FSCN1, SERPINB1, ACTN1, RAB31, COL3A1, COL1A1, CD36, were significantly associated with the mechanisms of invasion and metastasis in Bowen’s disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03622-1.

A Pilot Study of Rare Renal Amyloidosis Based on FFPE Proteomics

Renal amyloidosis typically manifests albuminuria, nephrotic-range proteinuria, and ultimately progresses to end-stage renal failure if diagnosed late. Different types of renal amyloidosis have completely different treatments and outcomes. Therefore, amyloidosis typing is essential for disease prognosis, genetic counseling and treatment. Thirty-six distinct proteins currently known to cause amyloidosis that have been described as amyloidogenic precursors, immunohistochemistry (IHC) or immunofluorescence (IF), can be challenging for amyloidosis typing especially in rare or hereditary amyloidosis in clinical practice. We made a pilot study that optimized the proteomics pre-processing procedures for trace renal amyloidosis formalin-fixed paraffin-embedded (FFPE) tissue samples, combined with statistical and bioinformatics analysis to screen out the amyloidosis-related proteins to accurately type or subtype renal amyloidosis in order to achieve individual treatment. A sensitive, specific and reliable FFPE-based proteomics analysis for trace sample manipulation was developed for amyloidosis typing. Our results not only underlined the great promise of traditional proteomics and bioinformatics analysis using FFPE tissues for amyloidosis typing, but also proved that retrospective diagnosis and analysis of previous cases laid a solid foundation for personalized treatment.

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

Protein Extraction From FFPE Kidney Tissue Samples: A Review of the Literature and Characterization of Techniques

Most tissue biopsies from patients in hospital environments are formalin-fixed and paraffin-embedded (FFPE) for long-term storage. This fixation process produces a modification in the proteins called “crosslinks”, which improves protein stability necessary for their conservation. Currently, these samples are mainly used in clinical practice for performing immunohistochemical analysis, since these modifications do not suppose a drawback for this technique; however, crosslinks difficult the protein extraction process. Accordingly, these modifications make the development of a good protein extraction protocol necessary. Due to the specific characteristics of each tissue, the same extraction buffers or deparaffinization protocols are not equally effective in all cases. Therefore, it is necessary to obtain a specific protocol for each tissue. The present work aims to establish a deparaffinization and protein extraction protocol from FFPE kidney samples to obtain protein enough of high quality for the subsequent proteomic analysis. Different deparaffination, protocols and protein extraction buffers will be tested in FFPE kidney samples. The optimized conditions will be applied in the identification by LC-MS/MS analysis of proteins extracted from 5, 10, and 15 glomeruli obtained through the microdissection of FFPE renal samples.

Proteomics Landscape of Alzheimer's Disease

Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.

Molecular Features of Lymph Node Metastasis in T1/2 Colorectal Cancer from Formalin-Fixed Paraffin-Embedded Archival Specimens

Histological risk factors for lymph node metastasis (LNM) in early-stage colorectal cancers (CRC) have been described, although the predictive utility of these factors varies. Improved LNM risk assessment based on findings in endoscopic colon and rectal excisions is necessary for optimal surgical management of CRC patients with pathologic T1- /T2-staged invasive depth (i.e., tumor not invading beyond the muscularis propria layer); as the current system is overly conservative, and results in many unnecessary radical surgeries. To identify molecular features in early CRC with elevated LNM potential, we carried out proteomic and gene expression profiling to compare T1 lymph node (LN) negative with T1/2 LN positive CRC tumors from formalin-fixed paraffin-embedded (FFPE) specimens. Using a data-independent acquisition mass spectrometry workflow, we detected over 7400 proteins and quantified over 4400 in all 21 specimens. Proteins from tumors with LN metastasis were enriched with effectors of epithelial-mesenchymal transition (EMT) and gene expression profiling confirmed activation of key transcription factors, SNAI1 and ZEB1, as well as a reduction in E-cadherin expression. Toward an implementation pathway, we investigated immunohistochemistry assays targeting four EMT-related proteins. While MS could reliably discern twofold protein abundance changes, we found the semiquantitative nature of IHC scoring limited confirmation of this degree of protein expression difference. This study demonstrated that EMT effectors are associated with locoregional metastasis in T1/T2 CRC and could be used to augment metastatic risk assessment, although further developments are required to enable routine implementation.

Quantitative Proteomic Analysis Using Formalin-Fixed, Paraffin-Embedded (FFPE) Human Cardiac Tissue

Clinical tissue archives represent an invaluable source of biological information. Formalin-fixed, paraffin-embedded (FFPE) tissue can be used for retrospective investigation of biomarkers of diseases and prognosis.Recently, the number of studies using proteome profiling of samples from clinical archives has markedly increased. However, the application of conventional quantitative proteomics technologies remains a challenge mainly due to the harsh fixation process resulting in protein cross-linking and protein degradation. In the present chapter, we demonstrate a protocol for label-free proteomic analysis of FFPE tissue prepared from human cardiac autopsies. The data presented here highlight the applicability and suitability of FFPE heart tissue for understanding the molecular mechanism of cardiac injury using a proteomics approach.

Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

Novel Proteome Extraction Method Illustrates a Conserved Immunological Signature of MSI-H Colorectal Tumors

Using a simple, environment friendly proteome extraction (TOP), we were able to optimize the analysis of clinical samples. Using our TOP method we analyzed a clinical cohort of microsatellite stable (MSS) and unstable (MSI-H) colorectal carcinoma (CRC). We identified a tumor cell specific, STAT1-centered, immune signature expressed by the MSI-H tumor cells. We then showed that long, but not short, exposure to Interferon-γ induces a similar signature in vitro We identified 10 different temporal protein expression patterns, classifying the Interferon-γ protein temporal regulation in CRC. Our data sheds light on the changes that tumor cells undergo under long-term immunological pressure in vivo, the importance of STAT proteins in specific biological scenarios. The data generated could help find novel clinical biomarkers and therapeutic approaches.

Chronic Occupational Exposure to Ionizing Radiation Induces Alterations in the Structure and Metabolism of the Heart: A Proteomic Analysis of Human Formalin-Fixed Paraffin-Embedded (FFPE) Cardiac Tissue

Epidemiological studies on workers employed at the Mayak plutonium enrichment plant have demonstrated an association between external gamma ray exposure and an elevated risk of ischemic heart disease (IHD). In a previous study using fresh-frozen post mortem samples of the cardiac left ventricle of Mayak workers and non-irradiated controls, we observed radiation-induced alterations in the heart proteome, mainly downregulation of mitochondrial and structural proteins. As the control group available at that time was younger than the irradiated group, we could not exclude age as a confounding factor. To address this issue, we have now expanded our study to investigate additional samples using archival formalin-fixed paraffin-embedded (FFPE) tissue. Importantly, the control group studied here is older than the occupationally exposed (>500 mGy) group. Label-free quantitative proteomics analysis showed that proteins involved in the lipid metabolism, sirtuin signaling, mitochondrial function, cytoskeletal organization, and antioxidant defense were the most affected. A histopathological analysis elucidated large foci of fibrotic tissue, myocardial lipomatosis and lymphocytic infiltrations in the irradiated samples. These data highlight the suitability of FFPE material for proteomics analysis. The study confirms the previous results emphasizing the role of adverse metabolic changes in the radiation-associated IHD. Most importantly, it excludes age at the time of death as a confounding factor.

Prognostic significance of proteomics and multi-omics studies in renal carcinoma

INTRODUCTION

Renal carcinoma, and in particular its most common variant, the clear cell subtype, is often diagnosed incidentally through abdominal imaging and frequently, the tumor is discovered at an early stage. However, 20% to 40% of patients undergoing nephrectomy for clinically localized renal cancer, even after accurate histological and clinical classification, will develop metastasis or recurrence, justifying the associated mortality rate. Therefore, even if renal carcinoma is not among the most frequent nor deadly cancers, a better prognostication is needed.

AREAS COVERED

Recently proteomics or other omics combinations have been applied to both cancer tissues, on the neoplasia itself and surrounding microenvironment, cultured cells, and biological fluids (so-called liquid biopsy) generating a list of prognostic molecular tools that will be reviewed in the present paper.

EXPERT OPINION

Although promising, none of the approaches listed above has been yet translated in clinics. This is likely due to the peculiar genetic and phenotypic heterogeneity of this cancer, which makes nearly each tumor different from all the others. Attempts to overcome this issue will be also revised. In particular, we will discuss how the application of omics-integrated approaches could provide the determinants of response to the different targeted drugs.

RNA sequencing for research and diagnostics in clinical oncology

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.