Comparison of whole transcriptome sequencing of fresh, frozen, and formalin-fixed, paraffin-embedded cardiac tissue

Post-operative Crohn's Disease Recurrence and Infectious Complications: A Transcriptomic Analysis

BACKGROUND

Crohn's disease (CD) is a chronic inflammatory condition affecting the gastrointestinal tract, characterized by complications such as strictures, fistulas, and neoplasia. Despite medical advancements, a significant number of patients with Crohn's disease require surgery, and many experience post-operative complications and recurrence. Previous studies have analyzed gene expression to study recurrence and post-operative complications independently. This study aims to identify overlapping differentially expressed genes and pathways for recurrence and post-operative complications.

METHODS

A dataset including 45 patients with Crohn's disease, including gene expression from ileum and colon tissue, endoscopic recurrence, and intra-abdominal septic complications was analyzed. Gene set enrichment analysis was used to identify gene pathways associated with the outcomes. Finally, a multi-variable logistic regression model was created to assess whether gene pathways were independently associated with both outcomes.

RESULTS

In ileum tissue, several inflammatory pathways, including interferon alpha and gamma response were upregulated in patients with endoscopic recurrence and intra-abdominal septic complications. In addition, there was upregulation of the epithelial mesenchymal transition pathway. In colon tissue, metabolic processes, such as myogenesis and oxidative phosphorylation were downregulated in both outcomes. In a multivariate model, downregulation of myogenesis in colon tissue was significantly associated with both endoscopic recurrence and intra-abdominal septic complications.

CONCLUSION

These findings shed light on the underlying biology of these outcomes and suggest potential biomarkers or therapeutic targets to reduce their occurrence. Further validation and multi-institutional studies are warranted to confirm these results and improve post-operative outcomes for patients with Crohn's disease.

Genome-scale mutational signature analysis in fixed archived tissues

Mutation spectra and mutational signatures in cancerous and non-cancerous tissues can be identified by various established techniques of massively parallel sequencing (or next-generation sequencing) including whole-exome or whole-genome sequencing, and more recently by error-corrected/duplex sequencing. One rather underexplored area has been the genome-scale analysis of mutational signatures as markers of mutagenic exposures, and their impact on cancer driver events applied to formalin-fixed or alcohol-fixed paraffin embedded archived biospecimens. This review showcases successful applications of the next-generation sequencing methodologies in archived fixed tissues, including the delineation of the specific tissue fixation-related DNA damage manifesting as artifactual signatures, distinguishable from the true signatures that arise from biological mutagenic processes. Overall, we discuss and demonstrate how next-generation sequencing techniques applied to archived fixed biospecimens can enhance our understanding of cancer causes including mutagenic effects of extrinsic cancer risk agents, and the implications for prevention efforts aimed at reducing avoidable cancer-causing exposures.

LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue

Whole transcriptome analysis (WTA) using RNA extracted from Formalin Fixed Paraffin Embedded (FFPE) tissue is an invaluable tool to understand the molecular pathology of disease. RNA extracted from FFPE tissue is either degraded and/or in very low quantities hampering gene expression analysis. Earlier studies described protocols applied for cellular RNA using poly-A primer-based linear amplification. The current study describes a method, LINCATRA (LINear amplifiCAtion of RNA for whole TRAnscriptome analysis). It employs random nonamer primer based method which can amplify short, fragmented RNA with high fidelity from as low as 5 ng to obtain enough material for WTA. The two-cycle method significantly amplified RNA at ∼1000 folds (p < 0.0001) improving the mean read lengths (p < 0.05) in WTA. Overall, increased mean read length positively correlated with on-target reads (Pearson's r = 0.71, p < 0.0001) in both amplified and unamplified RNA-seq analysis. Gene expression analysis compared between unamplified and amplified group displayed substantial overlap of the differentially expressed genes (DEGs) (log2 fold change cut-off < -2 and >2, p < 0.05) identified between lung cancer and asthma cohorts validating the method developed. This method is applicable in clinical molecular pathology field for both diagnostics and elucidation of disease mechanisms.

Revealing intact neuronal circuitry in centimeter-sized formalin-fixed paraffin-embedded brain

Tissue-clearing and labeling techniques have revolutionized brain-wide imaging and analysis, yet their application to clinical formalin-fixed paraffin-embedded (FFPE) blocks remains challenging. We introduce HIF-Clear, a novel method for efficiently clearing and labeling centimeter-thick FFPE specimens using elevated temperature and concentrated detergents. HIF-Clear with multi-round immunolabeling reveals neuron circuitry regulating multiple neurotransmitter systems in a whole FFPE mouse brain and is able to be used as the evaluation of disease treatment efficiency. HIF-Clear also supports expansion microscopy and can be performed on a non-sectioned 15-year-old FFPE specimen, as well as a 3-month formalin-fixed mouse brain. Thus, HIF-Clear represents a feasible approach for researching archived FFPE specimens for future neuroscientific and 3D neuropathological analyses.

RNA sequencing of formalin fixed paraffin-embedded heart tissue provides transcriptomic information about chemotherapy-induced cardiotoxicity

Gene expression of formalin-fixed paraffin-embedded (FFPE) tissue may serve for molecular studies on cardiovascular diseases. Chemotherapeutics, such as doxorubicin (DOX) may cause heart injury, but the mechanisms of these side effects of DOX are not well understood. This study aimed to investigate whether DOX-induced gene expression in archival FFPE heart tissue in experimental rats would correlate with the gene expression in fresh-frozen heart tissue by applying RNA sequencing technology. The results showed RNA from FFPE samples was degraded, resulting in a lower number of uniquely mapped reads. However, DOX-induced differentially expressed genes in FFPE were related to molecular mechanisms of DOX-induced cardiotoxicity, such as inflammation, calcium binding, endothelial dysfunction, senescence, and cardiac hypertrophy signaling. Our data suggest that, despite the limitations, RNA sequencing of archival FFPE heart tissue supports utilizing FFPE tissues from retrospective studies on cardiovascular disorders, including DOX-induced cardiotoxicity.

Explore & actuate: the future of personalized medicine in oncology through emerging technologies

PURPOSE OF REVIEW

The future of medicine is aimed to equip the physician with tools to assess the individual health of the patient for the uniqueness of the disease that separates it from the rest. The integration of omics technologies into clinical practice, reviewed here, would open new avenues for addressing the spatial and temporal heterogeneity of cancer. The rising cancer burden patiently awaits the advent of such an approach to personalized medicine for routine clinical settings.

RECENT FINDINGS

To weigh the translational potential, multiple technologies were categorized based on the extractable information from the different types of samples used, to the various omic-levels of molecular information that each technology has been able to advance over the last 2 years. This review uses a multifaceted classification that helps to assess translational potential in a meaningful way toward clinical adaptation.

SUMMARY

The importance of distinguishing technologies based on the flow of information from exploration to actuation puts forth a framework that allows the clinicians to better adapt a chosen technology or use them in combination to enhance their goals toward personalized medicine.

Linking gene expression to clinical outcomes in pediatric Crohn's disease using machine learning

Pediatric Crohn's disease (CD) is characterized by a severe disease course with frequent complications. We sought to apply machine learning-based models to predict risk of developing future complications in pediatric CD using ileal and colonic gene expression. Gene expression data was generated from 101 formalin-fixed, paraffin-embedded (FFPE) ileal and colonic biopsies obtained from treatment-naïve CD patients and controls. Clinical outcomes including development of strictures or fistulas and progression to surgery were analyzed using differential expression and modeled using machine learning. Differential expression analysis revealed downregulation of pathways related to inflammation and extra-cellular matrix production in patients with strictures. Machine learning-based models were able to incorporate colonic gene expression and clinical characteristics to predict outcomes with high accuracy. Models showed an area under the receiver operating characteristic curve (AUROC) of 0.84 for strictures, 0.83 for remission, and 0.75 for surgery. Genes with potential prognostic importance for strictures (REG1A, MMP3, and DUOX2) were not identified in single gene differential analysis but were found to have strong contributions to predictive models. Our findings in FFPE tissue support the importance of colonic gene expression and the potential for machine learning-based models in predicting outcomes for pediatric CD.

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.

Fresh and frozen cardiac tissue are comparable in DNA methylation array β-values, but formalin-fixed, paraffin-embedded tissue may overestimate DNA methylation levels

Untreated fresh cardiac tissue is the optimal tissue material for investigating DNA methylation patterns of cardiac biology and diseases. However, fresh tissue is difficult to obtain. Therefore, tissue stored as frozen or formalin-fixed, paraffin-embedded (FFPE) is widely used for DNA methylation studies. It is unknown whether storage conditions alter the DNA methylation in cardiac tissue. In this study, we compared the DNA methylation patterns of fresh, frozen, and FFPE cardiac tissue to investigate if the storage method affected the DNA methylation results. We used the Infinium MethylationEPIC assay to obtain genome-wide methylation levels in fresh, frozen, and FFPE tissues from nine individuals. We found that the DNA methylation levels of 21.4% of the examined CpG sites were overestimated in the FFPE samples compared to that of fresh and frozen tissue, whereas 5.7% were underestimated. Duplicate analyses of the DNA methylation patterns showed high reproducibility (precision) for frozen and FFPE tissues. In conclusion, we found that frozen and FFPE tissues gave reproducible DNA methylation results and that frozen and fresh tissues gave similar results.

Epigenomic analysis of formalin-fixed paraffin-embedded samples by CUT&Tag

For more than a century, formalin-fixed paraffin-embedded (FFPE) sample preparation has been the preferred method for long-term preservation of biological material. However, the use of FFPE samples for epigenomic studies has been difficult because of chromatin damage from long exposure to high concentrations of formaldehyde. Previously, we introduced Cleavage Under Targeted Accessible Chromatin (CUTAC), an antibody-targeted chromatin accessibility mapping protocol based on CUT&Tag. Here we show that simple modifications of our CUTAC protocol either in single tubes or directly on slides produce high-resolution maps of paused RNA Polymerase II at enhancers and promoters using FFPE samples. We find that transcriptional regulatory element differences produced by FFPE-CUTAC distinguish between mouse brain tumors and identify and map regulatory element markers with high confidence and precision, including microRNAs not detectable by RNA-seq. Our simple workflows make possible affordable epigenomic profiling of archived biological samples for biomarker identification, clinical applications and retrospective studies.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.