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Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a molecular imaging technology uniquely capable of untargeted measurement of proteins, lipids, and metabolites while retaining spatial information about their location in situ. This powerful combination of capabilities has the potential to bring a wealth of knowledge to the field of molecular histology. Translation of this innovative research tool into clinical laboratories requires the development of reliable sample preparation protocols for the analysis of proteins from formalin-fixed paraffin-embedded (FFPE) tissues, the standard preservation process in clinical pathology. Although ideal for stained tissue analysis by microscopy, the FFPE process cross-links, disrupts, or can remove proteins from the tissue, making analysis of the protein content challenging. To date, reported approaches differ widely in process and efficacy. This tutorial presents a strategy derived from systematic testing and optimization of key parameters, for reproducible in situ tryptic digestion of proteins in FFPE tissue and subsequent MALDI IMS analysis. The approach describes a generalized method for FFPE tissues originating from virtually any source.
© 2019 John Wiley & Sons, Ltd.
The emerging phenomenon of cellular heterogeneity in tissue requires single-cell resolution studies. A specific challenge for suspension-based single-cell analysis is the preservation of intact cell states when single cells are isolated from tissue contexts, in order to enable downstream analyses to extract accurate, native information. We have developed DISSECT (Disaggregation for Intracellular Signaling in Single Epithelial Cells from Tissue) coupled to mass cytometry (CyTOF: Cytometry by Time-of-Flight), an experimental approach for profiling intact signaling states of single cells from epithelial tissue specimens. We have previously applied DISSECT-CyTOF to fresh mouse intestinal samples and to Formalin-Fixed, Paraffin-Embedded (FFPE) human colorectal cancer specimens. Here, we present detailed protocols for each of these procedures, as well as a new method for applying DISSECT to cryopreserved tissue slices. We present example data for using DISSECT on a cryopreserved specimen of the human colon to profile its immune and epithelial composition. These techniques can be used for high-resolution studies for monitoring disease-related alternations in different cellular compartments using specimens stored in cryopreserved or FFPE tissue banks.
BACKGROUND - Triple negative breast cancer (TNBC) is a heterogeneous disease that lacks unifying molecular alterations that can guide therapy decisions. We previously identified distinct molecular subtypes of TNBC (TNBCtype) using gene expression data generated on a microarray platform using frozen tumor specimens. Tumors and cell lines representing the identified subtypes have distinct enrichment in biologically relevant transcripts with differing sensitivity to standard chemotherapies and targeted agents. Since our initial discoveries, RNA-sequencing (RNA-seq) has evolved as a sensitive and quantitative tool to measure transcript abundance.
METHODS - To demonstrate that TNBC subtypes were similar between platforms, we compared gene expression from matched specimens profiled by both microarray and RNA-seq from The Cancer Genome Atlas (TCGA). In the clinical care of patients with TNBC, tumor specimens collected for diagnostic purposes are processed by formalin fixation and paraffin-embedding (FFPE). Thus, for TNBCtype to eventually have broad and practical clinical utility we performed RNA-seq gene expression and molecular classification comparison between fresh-frozen (FF) and FFPE tumor specimens.
RESULTS - Analysis of TCGA showed consistent subtype calls between 91% of evaluable samples demonstrating conservation of TNBC subtypes across microarray and RNA-seq platforms. We compared RNA-seq performed on 21-paired FF and FFPE TNBC specimens and evaluated genome alignment, transcript coverage, differential transcript enrichment and concordance of TNBC molecular subtype calls. We demonstrate that subtype accuracy between matched FF and FFPE samples increases with sequencing depth and correlation strength to an individual TNBC subtype.
CONCLUSIONS - TNBC subtypes were reliably identified from FFPE samples, with highest accuracy if the samples were less than 4 years old and reproducible subtyping increased with sequencing depth. To reproducibly subtype tumors using gene expression, it is critical to select genes that do not vary due to platform type, tissue processing or RNA isolation method. The majority of differentially expressed transcripts between matched FF and FFPE samples could be attributed to transcripts selected for by RNA enrichment method. While differentially expressed transcripts did not impact TNBC subtyping, they will provide guidance on determining which transcripts to avoid when implementing a gene set size reduction strategy.
TRIAL REGISTRATION - NCT00930930 07/01/2009.
The construction of tissue microarrays (TMAs) with cores from a large number of paraffin-embedded tissues (donors) into a single paraffin block (recipient) is an effective method of analyzing samples from many patient specimens simultaneously. For the TMA to be successful, the cores within it must capture the correct histologic areas from the donor blocks (technical accuracy) and maintain concordance with the tissue of origin (analytical accuracy). This can be particularly challenging for tissues with small histological features such as small islands of carcinoma in situ (CIS), thin layers of normal urothelial lining of the bladder, or cancers that exhibit intratumor heterogeneity. In an effort to create a comprehensive TMA of a bladder cancer patient cohort that accurately represents the tumor heterogeneity and captures the small features of normal and CIS, we determined how core size (0.6 vs 1.0 mm) impacted the technical and analytical accuracy of the TMA. The larger 1.0 mm core exhibited better technical accuracy for all tissue types at 80.9% (normal), 94.2% (tumor), and 71.4% (CIS) compared with 58.6%, 85.9%, and 63.8% for 0.6 mm cores. Although the 1.0 mm core provided better tissue capture, increasing the number of replicates from two to three allowed with the 0.6 mm core compensated for this reduced technical accuracy. However, quantitative image analysis of proliferation using both Ki67+ immunofluorescence counts and manual mitotic counts demonstrated that the 1.0 mm core size also exhibited significantly greater analytical accuracy (P=0.004 and 0.035, respectively, r=0.979 and 0.669, respectively). Ultimately, our findings demonstrate that capturing two or more 1.0 mm cores for TMA construction provides superior technical and analytical accuracy over the smaller 0.6 mm cores, especially for tissues harboring small histological features or substantial heterogeneity.
Cellular heterogeneity poses a substantial challenge to understanding tissue-level phenotypes and confounds conventional bulk analyses. To analyze signaling at the single-cell level in human tissues, we applied mass cytometry using cytometry time of flight to formalin-fixed, paraffin-embedded (FFPE) normal and diseased intestinal specimens. This technique, called FFPE-DISSECT (disaggregation for intracellular signaling in single epithelial cells from tissue), is a single-cell approach to characterizing signaling states in embedded tissue samples. We applied FFPE-DISSECT coupled to mass cytometry and found differential signaling by tumor necrosis factor-α in intestinal enterocytes, goblet cells, and enteroendocrine cells, implicating the downstream RAS-RAF-MEK pathway in determining goblet cell identity. Application of this technique and computational analyses to human colon specimens confirmed the reduced differentiation in colorectal cancer (CRC) compared to normal colon and revealed increased intratissue and intertissue heterogeneity in CRC with quantitative changes in the regulation of signaling pathways. Specifically, coregulation of the kinases p38 and ERK, the translation regulator 4EBP1, and the transcription factor CREB in proliferating normal colon cells was lost in CRC. Our data suggest that this single-cell approach, applied in conjunction with genomic annotation, enables the rapid and detailed characterization of cellular heterogeneity from clinical repositories of embedded human tissues. This technique can be used to derive cellular landscapes from archived patient samples (beyond CRC) and as a high-resolution tool for disease characterization and subtyping.
Copyright © 2016, American Association for the Advancement of Science.
Defining molecular features that can predict the recurrence of colorectal cancer (CRC) for stage II-III patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed, Paraffin-Embedded (FFPE). NanoString nCounter® and Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) are the two platforms marketed for high-throughput gene expression profiling for FFPE samples. In this study, to evaluate the gene expression of frozen tissue-derived prognostic signatures in FFPE CRC samples, we evaluated the expression of 516 genes from published frozen tissue-derived prognostic signatures in 42 FFPE CRC samples measured by both platforms. Based on HTA platform-derived data, we identified both gene (99 individual genes, FDR < 0.05) and gene set (four of the six reported multi-gene signatures with sufficient information for evaluation, P < 0.05) expression differences associated with survival outcomes. Using nCounter platform-derived data, one of the six multi-gene signatures (P < 0.05) but no individual gene was associated with survival outcomes. Our study indicated that sufficiently high quality RNA could be obtained from FFPE tumor tissues to detect frozen tissue-derived prognostic gene expression signatures for CRC patients.
The prognosis of colorectal cancer (CRC) stage II and III patients remains a challenge due to the difficulties of finding robust biomarkers suitable for testing clinical samples. The majority of published gene signatures of CRC have been generated on fresh frozen colorectal tissues. Because collection of frozen tissue is not practical for routine surgical pathology practice, a clinical test that improves prognostic capabilities beyond standard pathological staging of colon cancer will need to be designed for formalin-fixed paraffin-embedded (FFPE) tissues. The NanoString nCounter® platform is a gene expression analysis tool developed for use with FFPE-derived samples. We designed a custom nCounter® codeset based on elements from multiple published fresh frozen tissue microarray-based prognostic gene signatures for colon cancer, and we used this platform to systematically compare gene expression data from FFPE with matched microarray array data from frozen tissues. Our results show moderate correlation of gene expression between two platforms and discovery of a small subset of genes as candidate biomarkers for colon cancer prognosis that are detectable and quantifiable in FFPE tissue sections.
Herein we present a simple, reproducible and versatile approach for in situ protein digestion and identification on formalin-fixed and paraffin-embedded (FFPE) tissues. This adaptation is based on the use of an enzyme delivery platform (hydrogel discs) that can be positioned on the surface of a tissue section. By simultaneous deposition of multiple hydrogels over select regions of interest within the same tissue section, multiple peptide extracts can be obtained from discrete histological areas. After enzymatic digestion, the hydrogel extracts are submitted for LC-MS/MS analysis followed by database inquiry for protein identification. Further, imaging mass spectrometry (IMS) is used to reveal the spatial distribution of the identified peptides within a serial tissue section. Optimization was achieved using cutaneous tissue from surgically excised pressure ulcers that were subdivided into two prime regions of interest: the wound bed and the adjacent dermal area. The robust display of tryptic peptides within these spectral analyses of histologically defined tissue regions suggests that LC-MS/MS in combination with IMS can serve as useful exploratory tools.
© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
BACKGROUND - Controversy exists regarding the impact of CYP2D6 genotype on tamoxifen responsiveness. We examined loss of heterozygosity (LOH) at the CYP2D6 locus and determined its impact on genotyping error when tumor tissue is used as a DNA source.
METHODS - Genomic tumor data from the adjuvant and metastatic settings (The Cancer Genome Atlas [TCGA] and Foundation Medicine [FM]) were analyzed to characterize the impact of CYP2D6 copy number alterations (CNAs) and LOH on Hardy Weinberg equilibrium (HWE). Additionally, we analyzed CYP2D6 *4 genotype from formalin-fixed paraffin-embedded (FFPE) tumor blocks containing nonmalignant tissue and buccal (germline) samples from patients on the North Central Cancer Treatment Group (NCCTG) 89-30-52 tamoxifen trial. All statistical tests were two-sided.
RESULTS - In TCGA samples (n =627), the CYP2D6 LOH rate was similar in estrogen receptor (ER)-positive (41.2%) and ER-negative (35.2%) but lower in HER2-positive tumors (15.1%) (P < .001). In FM ER+ samples (n = 290), similar LOH rates were observed (40.8%). In 190 NCCTG samples, the agreement between CYP2D6 genotypes derived from FFPE tumors and FFPE tumors containing nonmalignant tissue was moderate (weighted Kappa = 0.74; 95% CI = 0.63 to 0.84). Comparing CYP2D6 genotypes derived from buccal cells to FFPE tumor DNA, CYP2D6*4 genotype was discordant in six of 31(19.4%). In contrast, there was no disagreement between CYP2D6 genotypes derived from buccal cells with FFPE tumors containing nonmalignant tissue.
CONCLUSIONS - LOH at the CYP2D6 locus is common in breast cancer, resulting in potential misclassification of germline CYP2D6 genotypes. Tumor DNA should not be used to determine germline CYP2D6 genotype without sensitive techniques to detect low frequency alleles and quality control procedures appropriate for somatic DNA.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
INTRODUCTION - The aim of this study was to validate a molecular expression signature [cell cycle progression (CCP) score] that identifies patients with a higher risk of cancer-related death after surgical resection of early stage (I-II) lung adenocarcinoma in a large patient cohort and evaluate the effectiveness of combining CCP score and pathological stage for predicting lung cancer mortality.
METHODS - Formalin-fixed paraffin-embedded surgical tumor samples from 650 patients diagnosed with stage I and II adenocarcinoma who underwent definitive surgical treatment without adjuvant chemotherapy were analyzed for 31 proliferation genes by quantitative real-time polymerase chain reaction. The prognostic discrimination of the expression score was assessed by Cox proportional hazards analysis using 5-year lung cancer-specific death as primary outcome.
RESULTS - The CCP score was a significant predictor of lung cancer-specific mortality above clinical covariates [hazard ratio (HR) = 1.46 per interquartile range (95% confidence interval = 1.12-1.90; p = 0.0050)]. The prognostic score, a combination of CCP score and pathological stage, was a more significant indicator of lung cancer mortality risk than pathological stage in the full cohort (HR = 2.01; p = 2.8 × 10) and in stage I patients (HR = 1.67; p = 0.00027). Using the 85th percentile of the prognostic score as a threshold, there was a significant difference in lung cancer survival between low-risk and high-risk patient groups (p = 3.8 × 10).
CONCLUSIONS - This study validates the CCP score and the prognostic score as independent predictors of lung cancer death in patients with early stage lung adenocarcinoma treated with surgery alone. Patients with resected stage I lung adenocarcinoma and a high prognostic score may be candidates for adjuvant therapy to reduce cancer-related mortality.