A Hitchhiker's guide to high-dimensional tissue imaging with multiplexed ion beam imaging.

Advancements in multiplexed tissue imaging technologies are vital in shaping our understanding of tissue microenvironmental influences in disease contexts. These technologies now allow us to relate the phenotype of individual cells to their higher-order roles in tissue organization and function. Multiplexed Ion Beam Imaging (MIBI) is one of such technologies, which uses metal isotope-labeled antibodies and secondary ion mass spectrometry (SIMS) to image more than 40 protein markers simultaneously within a single tissue section. Here, we describe an optimized MIBI workflow for high-plex analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues following antigen retrieval, metal isotope-conjugated antibody staining, imaging using the MIBI instrument, and subsequent data processing and analysis. While this workflow is focused on imaging human FFPE samples using the MIBI, this workflow can be easily extended to model systems, biological questions, and multiplexed imaging modalities.

Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues.

The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.

DNA flow cytometry for detection of genomic instability as a cancer precursor in the gastrointestinal tract.

One of the earliest applications of flow cytometry was the measurement of DNA content in cells. This method is based on the ability to stain DNA in a stoichiometric manner (i.e., the amount of stain is directly proportional to the amount of DNA within the cell). For more than 40years, a number of studies have consistently demonstrated the utility of DNA flow cytometry as a potential diagnostic and/or prognostic tool in patients with most epithelial tumors, including pre-invasive lesions (such as dysplasia) in the gastrointestinal tract. However, its availability as a clinical test has been limited to few medical centers due to the requirement for fresh tissue in earlier studies and perceived technical demands. However, more recent studies have successfully utilized formalin-fixed paraffin-embedded (FFPE) tissue to generate high-quality DNA content histograms, demonstrating the feasibility of this methodology. This review summarizes step-by-step methods on how to perform DNA flow cytometry using FFPE tissue and analyze DNA content histograms based on the published consensus guidelines in order to assist in the diagnosis and/or risk stratification of many different epithelial tumors, with particular emphasis on dysplasia associated with Barrett's esophagus and inflammatory bowel disease.

Quantitative performance assessment of Ultivue multiplex panels in formalin-fixed, paraffin-embedded human and murine tumor specimens.

We present a rigorous validation strategy to evaluate the performance of Ultivue multiplex immunofluorescence panels. We have quantified the accuracy and precision of four different multiplex panels (three human and one mouse) in tumor specimens with varying levels of T cell density. Our results show that Ultivue panels are typically accurate wherein the relative difference in cell proportion between a multiplex image and a 1-plex image is less than 20% for a given biomarker. Ultivue panels exhibited relatively high intra-run precision (CV ≤ 25%) and relatively low inter-run precision (CV >> 25%) which can be remedied by using local intensity thresholding to gate biomarker positivity. We also evaluated the reproducibility of cell-cell distance estimates measured from multiplex images which show high intra- and inter-run precision. We introduce a new metric, multiplex labeling efficiency, which can be used to benchmark the overall fidelity of the multiplex data across multiple batch runs. Taken together our results provide a comprehensive characterization of Ultivue panels and offer practical guidelines for analyzing multiplex images.

Virtual formalin-fixed and paraffin-embedded staining of fresh brain tissue via stimulated Raman CycleGAN model.

Intraoperative histology is essential for surgical guidance and decision-making. However, frozen-sectioned hematoxylin and eosin (H&E) staining suffers from degraded accuracy, whereas the gold-standard formalin-fixed and paraffin-embedded (FFPE) H&E is too lengthy for intraoperative use. Stimulated Raman scattering (SRS) microscopy has shown rapid histology of brain tissue with lipid/protein contrast but is challenging to yield images identical to nucleic acid-/protein-based FFPE stains interpretable to pathologists. Here, we report the development of a semi-supervised stimulated Raman CycleGAN model to convert fresh-tissue SRS images to H&E stains using unpaired training data. Within 3 minutes, stimulated Raman virtual histology (SRVH) results that matched perfectly with true H&E could be generated. A blind validation indicated that board-certified neuropathologists are able to differentiate histologic subtypes of human glioma on SRVH but hardly on conventional SRS images. SRVH may provide intraoperative diagnosis superior to frozen H&E in both speed and accuracy, extendable to other types of solid tumors.

Extracting high-quality RNA from formaldehyde-fixed naturally aged neuromusculoskeletal tissues.

Modern approaches to discovering molecular mechanisms and validating treatments for age-related neuromusculoskeletal dysfunction typically rely on high-throughput transcriptome analysis. Previously harvested and fixed tissues offer an incredible reservoir of untapped molecular information. However, obtaining RNA from such formaldehyde-fixed neuromusculoskeletal tissues, especially fibrotic aged tissues, is technically challenging and often results in RNA degradation, chemical modification and yield reduction, prohibiting further analysis. Therefore, we developed a protocol to extract high-quality RNA from formaldehyde-fixed brain, cartilage, muscle and peripheral nerve isolated from naturally aged mice. Isolated RNA produced reliable gene expression data comparable to fresh and flash-frozen tissues and was sensitive enough to detect age-related changes, making our protocol valuable to researchers in the field of aging.

High-Resolution Genotyping of Formalin-Fixed Tissue Accurately Estimates Polygenic Risk Scores in Human Diseases.

Formalin-fixed paraffin-embedded (FFPE) tissues stored in biobanks and pathology archives are a vast but underutilized source for molecular studies on different diseases. Beyond being the "gold standard" for preservation of diagnostic human tissues, FFPE samples retain similar genetic information as matching blood samples, which could make FFPE samples an ideal resource for genomic analysis. However, research on this resource has been hindered by the perception that DNA extracted from FFPE samples is of poor quality. Here, we show that germline disease-predisposing variants and polygenic risk scores (PRS) can be identified from FFPE normal tissue (FFPE-NT) DNA with high accuracy. We optimized the performance of FFPE-NT DNA on a genome-wide array containing 657,675 variants. Via a series of testing and validation phases, we established a protocol for FFPE-NT genotyping with results comparable with blood genotyping. The median call rate of FFPE-NT samples in the validation phase was 99.85% (range 98.26%-99.94%) and median concordance with matching blood samples was 99.79% (range 98.85%-99.9%). We also demonstrated that a rare pathogenic PALB2 genetic variant predisposing to cancer can be correctly identified in FFPE-NT samples. We further imputed the FFPE-NT genotype data and calculated the FFPE-NT genome-wide PRS in 3 diseases and 4 disease risk variables. In all cases, FFPE-NT and matching blood PRS were highly concordant (all Pearson's r > 0.95). The ability to precisely genotype FFPE-NT on a genome-wide array enables translational genomics applications of archived FFPE-NT samples with the possibility to link to corresponding phenotypes and longitudinal health data.

Evaluation of Seegene Anyplex II Performance for Detection of Human Papillomavirus Genotypes in Formalin-Fixed, Paraffin-Embedded Cervical Cancer Specimens.

CONTEXT.­: Detection of human papillomavirus (HPV) in formalin-fixed, paraffin-embedded (FFPE) tissues may identify the cause of lesions and has value for the development of new diagnostic assays and epidemiologic studies. Seegene Anyplex II assays are widely used for HPV screening, but their performance using FFPE samples has not been fully explored. OBJECTIVE.­: To validate Anyplex II HPV HR Detection (Anyplex II, Seegene) using FFPE samples. DESIGN.­: We used 248 stored DNA extracts from cervical cancer FFPE samples collected during 2005-2015 that tested HPV positive using the RHA kit HPV SPF10-LiPA25, v1 (SPF10, Labo Biomedical Products) HPV genotyping assay, manufacturer-validated for FFPE samples. RESULTS.­: Of the selected 248 samples, 243 were used in our analysis. Consistent with SPF10 genotyping results, Anyplex II detected all 12 oncogenic types and had an overall HPV detection rate of 86.4% (210 of 243 samples). Anyplex II and SPF10 showed very high agreement for the detection of the 2 most important oncogenic genotypes: HPV 16 (219 of 226; 96.9%; 95% CI, 93.7-98.75) and HPV 18 (221 of 226; 97.8%; 95% CI, 94.9-99.3). CONCLUSIONS.­: Overall results showed that both platforms produced comparable HPV genotyping results, indicating the suitability of Anyplex II for FFPE samples. The Anyplex II assay has the added convenience of being an efficient, single-well semiquantitative polymerase chain reaction assay. Further optimization of Anyplex II may enhance its performance using FFPE samples by improving the detection limit.

Formalin-Fixed Paraffin-Embedded Proteomics of Malignant Mesothelioma and New Candidate Biomarkers Thioredoxin and Superoxide Dismutase 2 for Immunohistochemistry.

The pathogenesis of malignant mesothelioma (MM) has been extensively investigated, focusing on stress derived from reactive oxygen species. We aimed to identify diagnostic biomarkers of MM by analyzing proteins in formalin-fixed paraffin-embedded specimens using liquid chromatography-mass spectrometry. We extracted proteins from formalin-fixed paraffin-embedded sections of MM tissues (n = 7) and compared their profiles with those of benign mesothelial tissues (n = 4) and alveolar tissue (n = 1). Proteomic data were statistically assessed and profiled using principal component analysis. We were successful in the classification of MM and healthy tissue. The levels of superoxide dismutase 2 (SOD2), an enzyme that converts superoxide anion into oxygen and hydrogen peroxide, and thioredoxin (TXN), which plays a crucial role in reducing disulfide bonds in proteins, primarily contributed to the classification. Other redox-related proteins, such as pyruvate dehydrogenase subunit X, and ceruloplasmin also contributed to the classification. Protein-protein interaction analysis demonstrated that these proteins play essential roles in MM pathogenesis. Immunohistochemistry revealed that TXN levels were significantly lower, whereas SOD2 levels were significantly higher in MM and lung cancer tissues than in controls. Proteomic profiling suggested that MM tissues experienced increased exposure to hydrogen peroxide and other reactive oxygen species. Combining immunohistochemistry for TXN and SOD2 allows for differentiation among MM, lung cancer, and control tissues; hence, TXN and SOD2 may be promising MM biomarkers and therapeutic targets.

Spatial transcriptomics and the anatomical pathologist: Molecular meets morphology.

In recent years anatomical pathology has been revolutionised by the incorporation of molecular findings into routine diagnostic practice, and in some diseases the presence of specific molecular alterations are now essential for diagnosis. Spatial transcriptomics describes a group of technologies that provide up to transcriptome-wide expression profiling while preserving the spatial origin of the data, with many of these technologies able to provide these data using a single tissue section. Spatial transcriptomics allows expression profiling of highly specific areas within a tissue section potentially to subcellular resolution, and allows correlation of expression data with morphology, tissue type and location relative to other structures. While largely still research laboratory-based, several spatial transcriptomics methods have now achieved compatibility with formalin-fixed paraffin-embedded tissue (FFPE), allowing their use in diagnostic tissue samples, and with further development potentially leading to their incorporation in routine anatomical pathology practice. This mini review provides an overview of spatial transcriptomics methods, with an emphasis on platforms compatible with FFPE tissue, approaches to assess the data and potential applications in anatomical pathology practice.

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes.

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

FFPE++: Improving the quality of formalin-fixed paraffin-embedded tissue imaging via contrastive unpaired image-to-image translation.

Formalin-fixation and paraffin-embedding (FFPE) is a technique for preparing and preserving tissue specimens that has been utilized in histopathology since the late 19th century. This process is further complicated by FFPE preparation steps such as fixation, processing, embedding, microtomy, staining, and coverslipping, which often results in artifacts due to the complex histological and cytological characteristics of a tissue specimen. The term "artifacts" includes, but is not limited to, staining inconsistencies, tissue folds, chattering, pen marks, blurring, air bubbles, and contamination. The presence of artifacts may interfere with pathological diagnosis in disease detection, subtyping, grading, and choice of therapy. In this study, we propose FFPE++, an unpaired image-to-image translation method based on contrastive learning with a mixed channel-spatial attention module and self-regularization loss that drastically corrects the aforementioned artifacts in FFPE tissue sections. Turing tests were performed by 10 board-certified pathologists with more than 10 years of experience. These tests which were performed for ovarian carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, and papillary thyroid carcinoma, demonstrate the clear superiority of the proposed method in many clinical aspects compared with standard FFPE images. Based on the qualitative experiments and feedback from the Turing tests, we believe that FFPE++ can contribute to substantial diagnostic and prognostic accuracy in clinical pathology in the future and can also improve the performance of AI tools in digital pathology. The code and dataset are publicly available at https://github.com/DeepMIALab/FFPEPlus.

Identification of Metabolomic Markers in Frozen or Formalin-Fixed and Paraffin-Embedded Samples of Diffuse Glioma from Adults.

The aim of this study was to identify metabolomic signatures associated with the gliomagenesis pathway (IDH-mutant or IDH-wt) and tumor grade of diffuse gliomas (DGs) according to the 2021 WHO classification on frozen samples and to evaluate the diagnostic performances of these signatures in tumor samples that are formalin-fixed and paraffin-embedded (FFPE). An untargeted metabolomic study was performed using liquid chromatography/mass spectrometry on a cohort of 213 DG samples. Logistic regression with LASSO penalization was used on the frozen samples to build classification models in order to identify IDH-mutant vs. IDH-wildtype DG and high-grade vs low-grade DG samples. 2-Hydroxyglutarate (2HG) was a metabolite of interest to predict IDH mutational status and aminoadipic acid (AAA) and guanidinoacetic acid (GAA) were significantly associated with grade. The diagnostic performances of the models were 82.6% AUC, 70.6% sensitivity and 80.4% specificity for 2HG to predict IDH status and 84.7% AUC, 78.1% sensitivity and 73.4% specificity for AAA and GAA to predict grade from FFPE samples. Thus, this study showed that AAA and GAA are two novel metabolites of interest in DG and that metabolomic data can be useful in the classification of DG, both in frozen and FFPE samples.

Quality and Quantity of Nucleic Acids Extracted from Formalin-Fixed Paraffin-Embedded Lymphoma Biopsies from Nigerian Archived Biopsy.

BACKGROUND: Integrity of nucleic acids derived from archived formalin-fixed paraffin-embedded (FFPE) cancer specimens affects diagnosis, prognosis, and therapy. Several factors affect the quality and quantity of extracted nucleic acids and one of such factors is storage period. AIM: We investigated the impact of storage duration on the quality and quantity of nucleic acids extracted from archived FFPE lymphoma biopsies in Nigeria. MATERIALS AND METHODS: A total of 53 FFPE biopsies diagnosed as lymphoma stored over several years (2008-2019) were analyzed. They were 22 chronic lymphocytic leukemia (CLL) cases, 17 Hodgkin lymphoma (HL) cases, and 14 diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS). DNA was extracted from all the lymphoma samples which were analyzed for integrity and amplifiability using the four pairs of control genes polymerase chain reaction (PCR) primers of BIOMED-2 protocol, whereas RNA extraction was from 6 CLL cases used for qPCR analysis of RNU43. RESULTS: For CLL, the mean DNA yield was 193.6 ng/µl (range: 3.0-533.0 ng/µl), whereas the mean A260/A280 ratio was 1.7 (1.2-1.9). For DLBCL, NOS, and HL, 255.5 ng/µl (range: 32.9-605.4 ng/µl), 1.8 (1.5-2.0) and 242.7 ng/µl (range: 1.3-886.0 ng/µl), and 1.7 (0.9-1.8), respectively. The extracted DNA gave amplifiable products of at least 200bp, whereas the RNA analysis showed CT values of <38 in all the samples. The mean RNA yield was 462.2 ng/µl (range: 74.7-1082.1), whereas the mean A260/A280 was 1.7 (1.5-1.8). CONCLUSION: Quantity and quality of nucleic acids from FFPE tissues stored for different time periods showed no significant difference in yield and quality.

A comprehensive assessment of exome capture methods for RNA sequencing of formalin-fixed and paraffin-embedded samples.

RNA-Seq analysis of Formalin-Fixed and Paraffin-Embedded (FFPE) samples has emerged as a highly effective approach and is increasingly being used in clinical research and drug development. However, the processing and storage of FFPE samples are known to cause extensive degradation of RNAs, which limits the discovery of gene expression or gene fusion-based biomarkers using RNA sequencing, particularly methods reliant on Poly(A) enrichment. Recently, researchers have developed an exome targeted RNA-Seq methodology that utilizes biotinylated oligonucleotide probes to enrich RNA transcripts of interest, which could overcome these limitations. Nevertheless, the standardization of this experimental framework, including probe designs, sample multiplexing, sequencing read length, and bioinformatic pipelines, remains an essential requirement. In this study, we conducted a comprehensive comparison of three main commercially available exome capture kits and evaluated key experimental parameters, to provide the overview of the advantages and limitations associated with the selection of library preparation protocols and sequencing platforms. The results provide valuable insights into the best practices for obtaining high-quality data from FFPE samples.

A region-resolved proteomic map of the human brain enabled by high-throughput proteomics.

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).

Routine Workflow of Spatial Proteomics on Micro-formalin-Fixed Paraffin-Embedded Tissues.

In the era of single-cell biology, spatial proteomics has emerged as an important frontier. However, it still faces several challenges in technology. Formalin-fixed paraffin-embedded (FFPE) tissues are an important material in spatial proteomics, in which fixed tissues are excised using laser capture microdissection (LCM), followed by protein identification with mass spectrometry. For a satisfied spatial proteomics upon FFPE tissues, the excision area is expected to be as small as possible, and the identified proteins are countered upon as much as possible. For a general laboratory for spatial proteomics, a routine workflow is required, not relying on any special device, and is easily operating. In view of these challenges in technology, we initiated a technology evaluation throughout the entire procedure of proteomic analysis with micro-FFPE tissues. In contrast to the protocols reported previously, several innovations in technology were proposed and conducted, such as removal of destaining, decross-linking with "hang-down", solution simplification for peptide generation and balancing to excision area, and capture rate of micro-FFPE tissues. After optimization of all the necessary steps, a routine workflow was established, in which the minimized area for protein identification was 0.002 mm2, while the excision area for a consistent proteomic analysis was 0.05 mm2. Using the developed workflow and collecting the micro-FFPE tissues continuously, for the first time, a spatial proteomic atlas of mouse brain was preliminarily constructed, which exhibited the typical characteristics of spatial-dependent protein abundance and functional enrichment.

Influence of formalin fixation duration on RNA quality and quantity from formalin-fixed paraffin-embedded hepatocellular carcinoma tissues.

Analyzing RNA samples from formalin-fixed paraffin-embedded (FFPE) tissues is essential for precision medicine. We investigated RNA quantity and quality from FFPE tumor tissues fixed in formalin for various times and compared sequencing metrics from next-generation sequencing (NGS). Hepatocellular carcinoma (HCC) tissues were fixed in 10% neutral buffered formalin (1-240 h) and FFPE blocks were prepared. Total RNA was extracted, and the quantity and quality were assessed using the NanoDrop, Qubit and Bioanalyzer. After preparing sequencing libraries, NGS was performed on the Oncomine Dx Multi-CDx system. Total RNA yields of all samples met the threshold required for NGS, but longer fixation times resulted in decreased total RNA and long RNA fragment (>200 nt) yields. NGS analysis showed fewer sequencing reads of internal control genes from RNA with longer fixation times. RNA extracted from FFPE blocks stored for 500 days had reduced RNA yield and quality compared with RNA obtained from FFPE blocks prepared immediately. In conclusion, short and over-fixation should be avoided because of their negative impact on sequencing quality. Fixation process should be finished promptly within recommended guidelines (6-72 h) for cancer patients.

RNA-seq RNAaccess identified as the preferred method for gene expression analysis of low quality FFPE samples.

Clinical tumor tissues that are preserved as formalin-fixed paraffin-embedded (FFPE) samples result in extensive cross-linking, fragmentation, and chemical modification of RNA, posing significant challenges for RNA-seq-based gene expression profiling. This study sought to define an optimal RNA-seq protocol for FFPE samples. We employed a common RNA extraction method and then compared RNA-seq library preparation protocols including RNAaccess, RiboZero and PolyA in terms of sequencing quality and concordance of gene expression using FFPE and case-matched fresh-frozen (FF) triple-negative breast cancer (TNBC) tissues. We found that RNAaccess, a method based on exome capture, produced the most concordant results. Applying RNAaccess to FFPE gastric cancer tissues, we established a minimum RNA DV200 requirement of 10% and a RNA input amount of 10ng that generated highly reproducible gene expression data. Lastly, we demonstrated that RNAaccess and NanoString platforms produced highly concordant expression profiles from FFPE samples for shared genes; however, RNA-seq may be preferred for clinical biomarker discovery work because of the broader coverage of the transcriptome. Taken together, these results support the selection of RNA-seq RNAaccess method for gene expression profiling of FFPE samples. The minimum requirements for RNA quality and input established here may allow for inclusion of clinical FFPE samples of sub-optimal quality in gene expression analyses and ultimately increasing the statistical power of such analyses.