Accurate RNA Sequencing From Formalin-Fixed Cancer Tissue To Represent High-Quality Transcriptome From Frozen Tissue

Pre-analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation

OBJECTIVES

To investigate the pre-analytics of the molecular testing of cytology specimens, we studied the effects of time in refrigerator storage (4°C) of malignant effusions on RNA sequencing (RNAseq) results.

METHODS

Ten effusion specimens were stored in a refrigerator (4°C) for different durations (day 0, 1, 4, and 7). All specimens were prepared as cytospins fixed in either Carnoy's solution or 95% ethanol (EtOH) and in an RNA preservative for a fresh frozen (FF) high-quality reference. Whole transcriptome (wt) and targeted (t)RNAseq of two multigene expression signatures were performed. We then compared transcript expression levels (including mutant allele fraction) according to pre-analytical variables using a concordance correlation coefficient (CCC) and a mixed effect model.

RESULTS

Sequencing results were mostly stable over increasing time in storage. Cytospins fixed in Carnoy's solution were more concordant with FF samples than cytospins fixed in 95% EtOH at all timepoints. This finding was consistent for both wtRNAseq (averages: day 0 CCC = 0.98 vs 0.91; day 7 CCC = 0.88 vs 0.78) and tRNAseq methods (averages: day 0 CCC = 0.98 vs 0.81; day 7 CCC = 0.98 vs 0.90). Cytospins fixed in Carnoy's solution did not show significant changes in expression over timepoints or between expression signatures, whereas 95% EtOH did.

CONCLUSION

RNAseq can be accurately performed on effusion specimens after prolonged refrigerator storage. RNA extracted from scraped cytospin slides fixed in Carnoy's solution was marginally superior to 95% EtOH fixation, but either method had comparable analytic performance to high-quality FF RNA samples.

Assessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing

BACKGROUND

Rather than surgical resection, cytologic specimens are often used as first-line clinical diagnostic procedures due to higher safety, speed, and cost-effectiveness. Archival diagnostic cytology slides containing cancer can be equivalent to tissue biopsies for DNA mutation testing, but the accuracy of transcriptomic profiling by RNA sequencing (RNA-seq) is less understood.

METHODS

This study compares the results from whole transcriptome RNA-seq and a targeted RNA-seq assay of stained cytology smears (CS) versus matched tumor tissue samples preserved fresh-frozen (FF) and processed as formalin-fixed paraffin-embedded (FFPE) sections. Cellular cytology scrapes from all 11 breast cancers were fixed and stained using three common protocols: Carnoy's (CS_C) or 95% ethanol (CS_E) fixation and then Papanicolaou stain or air-dried then methanol fixation and DiffQuik stain (CS_DQ). Agreement between samples was assessed using Lin's concordance correlation coefficient.

RESULTS

Library yield for CS_DQ was too low, therefore it was not sequenced. The distributions of concordance correlation coefficient of gene expression levels in comparison to FF were comparable between CS_C and CS_E, but expression of genes enriched in stroma was lower in cytosmear samples than in FF or FFPE. Six signatures showed similar concordance to FF for all methods and two were slightly worse in CS_C and CS_E. Genomic signatures were highly concordant using targeted RNA-seq. The allele fraction of selected mutations calculated on cytosmear specimens was highly correlated with FF tissues using both RNA-seq methods.

CONCLUSION

RNA can be reliably extracted from cytology smears and is suitable for transcriptome profiling or mutation detection, except for signatures of tumor stroma.

Dysregulation and Epigenetic Reprogramming of NRF2 Signaling Axis Promote Acquisition of Cisplatin Resistance and Metastasis in Head and Neck Squamous Cell Carcinoma

PURPOSE

Cisplatin (CDDP)-based chemotherapy is a first-line treatment for patients with advanced head and neck squamous cell carcinomas (HNSCC), despite a high rate of treatment failures, acquired resistance, and subsequent aggressive behavior. The purpose of this study was to study the mechanism of CDDP resistance and metastasis in HNSCC. We investigated the role of NRF2 pathway activation as a driven event for tumor progression and metastasis of HNSCC.

EXPERIMENTAL DESIGN

Human HNSCC cell lines that are highly resistant to CDDP were generated. Clonogenic survival assays and a mouse model of oral cancer were used to examine the impact of NRF2 activation in vitro and in vivo on CDDP sensitivity and development of metastasis. Western blotting, immunostaining, whole-exome sequencing, single-cell transcriptomic and epigenomic profiling platforms were performed to dissect clonal evolution and molecular mechanisms.

RESULTS

Implantation of CDDP-resistant HNSCC cells into the tongues of nude mice resulted in a very high rate of distant metastases. The CDDP-resistant cells had significantly higher expression of NRF2 pathway genes in the presence of newly acquired KEAP1 mutations, or via epigenomic activation of target genes. Knockdown of NRF2 or restoration of the wild-type KEAP1 genes resensitized resistant cells to CDDP and decreased distant metastasis (DM). Finally, treatment with inhibitor of glutaminase-1, a NRF2 target gene, alleviated CDDP resistance.

CONCLUSIONS

CDDP resistance and development of DM are associated with dysregulated and epigenetically reprogrammed KEAP1-NRF2 signaling pathway. A strategy targeting KEAP1/NRF2 pathway or glutamine metabolism deserves further clinical investigation in patients with CDDP-resistant head and neck tumors.

PIM1 and CD79B Mutation Status Impacts the Outcome of Primary Diffuse Large B-Cell Lymphoma of the CNS

Primary diffuse large B cell lymphoma of the central nervous system (CNS DLBCL) is a rare malignancy with a distinct genetic profile. The clinicopathological significance of the mutation patterns remains unknown. Forty cases of primary CNS DLBCL were subjected to targeted exome sequencing covering 413 genes, including MYD88, CD79B and PIM1. Mutational analysis recognized two groups. The CDP (including CD79B and/or PIM1mutations) group was identified in 27 cases (67.5%), and the non-CDP (without CD79B and PIM1 mutations) group was identified in 13 cases 32.5%). The CDP group tended to occur in older patients (median age 57.0 vs. 48.4 years, p=0.015). Patients in the CDP group had a significantly longer 2-year overall survival (OS) (76% and 40%, p=0.0372) than those in the non-CDP group. Multivariate analysis revealed that age less than 60 years, no MYC and BCL2 double expression, and CDP group were three independent risk factors indicating favorable OS. PyClone analysis revealed the subcloning heterogeneity between the groups. In addition, transcriptional sequencing was successfully performed in 8 cases. A total of 131 genes were significantly differentially expressed between these two groups. The major categories of biological processes that were significantly altered between these two groups related to intracellular metabolism mechanisms. We developed a new molecular classification to divide CNS DLBCL into CDP and non-CDP groups based on CD79B and PIM1 mutational status. Patients with PIM1 and/or CD79B mutations had favorable long-term survival after high-dose methotrexate-based polychemotherapy.

Functional comparison of exome capture-based methods for transcriptomic profiling of formalin-fixed paraffin-embedded tumors

The availability of fresh frozen (FF) tissue is a barrier for implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. We performed transcriptomic analysis of 32 FFPE tumor samples from 11 patients using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to the TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable gene transcripts, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). The Agilent and IDT assays detected all the clinically relevant fusions that were initially identified in FF-TruSeq. All FFPE exome capture-based methods had comparable performance and concordance with FF-TruSeq. Our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

The Role of lncRNA PCAT6 in Cancers

Long non-coding RNA (lncRNA) PCAT6 is a member of the Prostate Cancer Associated Transcripts family of molecules. In this review, we focus on the latest studies involving PCAT6 in the diagnosis, treatment, and prognosis of malignant tumors of the digestive, respiratory, urinary, reproductive, motion, and nervous systems. PCAT6 was found to be highly expressed in gastric cancer, colon cancer, hepatocellular carcinoma, lung cancer, bladder cancer, ovarian cancer, breast cancer, cervical cancer, osteosarcoma, glioblastoma, and other tumors. PCAT6 can promote the development and progression of different types of malignant tumors through various mechanisms. Overall, these findings suggest that PCAT6 may play an increasingly vital role in the clinical assessment of these malignant tumors. It can function as an oncogene and may be used as a potential new prognostic biomarker of these tumors.

Two novel qualitative transcriptional signatures robustly applicable to non-research-oriented colorectal cancer samples with low-quality RNA

Currently, due to the low quality of RNA caused by degradation or low abundance, the accuracy of gene expression measurements by transcriptome sequencing (RNA‐seq) is very challenging for non‐research‐oriented clinical samples, majority of which are preserved in hospitals or tissue banks worldwide with complete pathological information and follow‐up data. Molecular signatures consisting of several genes are rarely applied to such samples. To utilize these resources effectively, 45 stage II non‐research‐oriented samples which were formalin‐fixed paraffin‐embedded (FFPE) colorectal carcinoma samples (CRC) using RNA‐seq have been analysed. Our results showed that although gene expression measurements were significantly affected, most cancer features, based on the relative expression orderings (REOs) of gene pairs, were well preserved. We then developed two REO‐based signatures, which consisted of 136 gene pairs for early diagnosis of CRC, and 4500 gene pairs for predicting post‐surgery relapse risk of stage II and III CRC. The performance of our signatures, which included hundreds or thousands of gene pairs, was more robust for non‐research‐oriented clinical samples, compared to that of two published concise REO‐based signatures. In conclusion, REO‐based signatures with relatively more gene pairs could be robustly applied to non‐research‐oriented CRC samples.

Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples

BACKGROUND

Our objective was to assess whether modifications to a customized targeted RNA sequencing (RNAseq) assay to include unique molecular identifiers (UMIs) that collapse read counts to their source mRNA counts would improve quantification of transcripts from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. The assay (SET4) includes signatures that measure hormone receptor and PI3-kinase related transcriptional activity (SETER/PR and PI3Kges), and measures expression of selected activating point mutations and key breast cancer genes.

METHODS

Modifications included steps to introduce eight nucleotides-long UMIs during reverse transcription (RT) in bulk solution, followed by polymerase chain reaction (PCR) of labeled cDNA in droplets, with optimization of the polymerase enzyme and reaction conditions. We used Lin's concordance correlation coefficient (CCC) to measure concordance, including precision (Rho) and accuracy (Bias), and nonparametric tests (Wilcoxon, Levene's) to compare the modified (NEW) SET4 assay to the original (OLD) SET4 assay and to whole transcriptome RNAseq using RNA from matched fresh frozen (FF) and FFPE samples from 12 primary breast cancers.

RESULTS

The modified (NEW) SET4 assay measured single transcripts (p< 0.001) and SETER/PR (p=0.002) more reproducibly in technical replicates from FFPE samples. The modified SET4 assay was more precise for measuring single transcripts (Rho 0.966 vs 0.888, p< 0.01) but not multigene expression signatures SETER/PR (Rho 0.985 vs 0.968) or PI3Kges (Rho 0.985 vs 0.946) in FFPE, compared to FF samples. It was also more precise than wtRNAseq of FFPE for measuring transcripts (Rho 0.986 vs 0.934, p< 0.001) and SETER/PR (Rho 0.993 vs 0.915, p=0.004), but not PI3Kges (Rho 0.988 vs 0.945, p=0.051). Accuracy (Bias) was comparable between protocols. Two samples carried a PIK3CA mutation, and measurements of transcribed mutant allele fraction was similar in FF and FFPE samples and appeared more precise with the modified SET4 assay. Amplification efficiency (reads per UMI) was consistent in FF and FFPE samples, and close to the theoretically expected value, when the library size exceeded 400,000 aligned reads.

CONCLUSIONS

Modifications to the targeted RNAseq protocol for SET4 assay significantly increased the precision of UMI-based and reads-based measurements of individual transcripts, multi-gene signatures, and mutant transcript fraction, particularly with FFPE samples.

MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

Background

Transcriptional analysis is widely used to study the molecular biology of cancer and hold great biomarker potential for clinical patient stratification. Yet, accurate transcriptional profiling requires RNA of a high quality, which often cannot be retrieved from formalin-fixed, paraffin-embedded (FFPE) tumor tissue that is routinely collected and archived in clinical departments. To overcome this roadblock to clinical testing, we previously developed MethCORR, a method that infers gene expression from DNA methylation data, which is robustly retrieved from FFPE tissue. MethCORR was originally developed for colorectal cancer and with this study, we aim to: (1) extend the MethCORR method to 10 additional cancer types and (2) to illustrate that the inferred gene expression is accurate and clinically informative.

Results

Regression models to infer gene expression information from DNA methylation were developed for ten common cancer types using matched RNA sequencing and DNA methylation profiles (HumanMethylation450 BeadChip) from The Cancer Genome Atlas Project. Robust and accurate gene expression profiles were inferred for all cancer types: on average, the expression of 11,000 genes was modeled with good accuracy and an intra-sample correlation of R² = 0.90 between inferred and measured gene expression was observed. Molecular pathway analysis and transcriptional subtyping were performed for breast, prostate, and lung cancer samples to illustrate the general usability of the inferred gene expression profiles: overall, a high correlation of r = 0.96 (Pearson) in pathway enrichment scores and a 76% correspondence in molecular subtype calls were observed when using measured and inferred gene expression as input. Finally, inferred expression from FFPE tissue correlated better with RNA sequencing data from matched fresh-frozen tissue than did RNA sequencing data from FFPE tissue (P < 0.0001; Wilcoxon rank-sum test).

Conclusions

In all cancers investigated, MethCORR enabled DNA methylation-based transcriptional analysis, thus enabling future analysis of cancer in situations where high-quality DNA, but not RNA, is available. Here, we provide the framework and resources for MethCORR modeling of ten common cancer types, thereby widely expanding the possibilities for transcriptional studies of archival FFPE material.

Genetic Signatures From RNA Sequencing of Pediatric Localized Scleroderma Skin

The purpose of this study was to explore the skin transcriptional profile in pediatric localized scleroderma (LS) to provide a better understanding of the altered immune and fibrotic pathways promoting disease. LS is a progressive disease of the skin and underlying tissue that causes significant functional disability and disfigurement, especially in developing children. RNA sequencing (RNAseq) technology allows for improved understanding of relevant cellular expression through transcriptome analysis of phases during LS disease progression (more active/inflammatory vs. inactive/fibrotic) and also permits the use of RNA extracted from existing paraffin-embedded skin tissue, which is important in pediatrics. A strong correlation was observed between the comparison of genes expressed between fresh (RNAlater) and paraffinized skin in healthy and LS subjects, supporting the use of paraffinized tissue. LS gene signatures compared to healthy controls showed a distinct expression of an inflammatory response gene signature (IRGS) composed of IFNγ-, IFNα-, and TNFα-associated genes. GSEA^© enrichment analysis showed that the IRGS, including interferon-inducible chemokines such as CXCL9, CXCL10, CXCL11, and IFNγ itself, was more highly expressed in LS patients with more inflammatory lesions. The use of paraffinized skin for sequencing was proven to be an effective substitute for fresh skin by comparing gene expression profiles. The prevalence of the IFNγ signature in the lesion biopsies of active LS patients indicates that these genes reflect clinical activity parameters and may be the promoters of early, inflammatory disease.

Evaluation of clinical formalin-fixed paraffin-embedded tissue quality for targeted-bisulfite sequencing

Formalin-fixed paraffin-embedded (FFPE) tissues are promising biological resources for genetic research. Recent improvements in DNA extraction from FFPE samples allowed the use of these tissues for multiple sequencing methods. However, fundamental research addressing the application of FFPE-derived DNA for targeted-bisulfite sequencing (TB-seq) is lacking. Here, we evaluated the suitability of FFPE-derived DNA for TB-seq. We conducted TB-seq using FFPE-derived DNA and corresponding fresh frozen (FF) tissues of patients with kidney cancer and compared the quality of DNA, libraries, and TB-seq statistics between the two preservation methods. The approximately 600-bp average fragment size of the FFPE-derived DNA was significantly shorter than that of the FF-derived DNA. The sequencing libraries constructed using FFPE-derived DNA and the mapping ratio were approximately 10 times and 10% lower, respectively, than those constructed using FF-derived DNA. In the mapped data of FFPE-derived DNA, duplicated reads accounted for > 60% of the obtained sequence reads, with lower mean on-target coverage. Therefore, the standard TB-seq protocol is inadequate for obtaining high-quality data for epigenetic analysis from FFPE-derived DNA, and technical improvements are necessary for enabling the use of archived FFPE resources.

Ginsenoside ameliorated ventilator-induced lung injury in rats

Background

Ginsenosides have antioxidant and anti-inflammatory features. This study aimed to evaluate the biologic effects of ginsenoside Rb2 pretreatment on ventilator-induced lung injury (VILI) in rats.

Methods

Rats were divided into four groups with 12 rats per group: control; low tidal volume (TV), TV of 6 mL/kg, VILI, TV of 20 mL/kg, positive end-expiratory pressure of 5 cm H₂O, and respiratory rate of 60 breaths per minute for 3 h at an inspiratory oxygen fraction of 0.21; and ginsenosides, treated the same as the VILI group but with 20 mg/kg intraperitoneal ginsenoside pretreatment. Morphology was observed with a microscope to confirm the VILI model. Wet-to-dry weight ratios, protein concentrations, and pro-inflammatory cytokines in the bronchoalveolar lavage fluid were measured. RNA sequencing of the lung tissues was conducted to analyze gene expression.

Results

High TV histologically induced VILI with alveolar edema and infiltration of inflammatory cells. Ginsenosides pretreatment significantly reduced the histologic lung injury score compared to the VILI group. Wet-to-dry weight ratios, malondialdehyde, and TNF-α in bronchoalveolar lavage fluid were significantly higher in the VILI group and ginsenoside pretreatment mitigated these effects. In the immunohistochemistry assay, ginsenoside pretreatment attenuated the TNF-α upregulation induced by VILI. We identified 823 genes differentially presented in the VILI group compared to the control group. Of the 823 genes, only 13 genes (Arrdc2, Cygb, Exnef, Lcn2, Mroh7, Nsf, Rexo2, Srp9, Tead3, Ephb6, Mvd, Sytl4, and Ube2l6) recovered to control levels in the ginsenoside group.

Conclusions

Ginsenosides inhibited the inflammatory and oxidative stress response in VILI. Further studies are required on the 13 genes, including LCN2.

Gene expression analysis in formalin fixed paraffin embedded melanomas is associated with density of corresponding immune cells in those tissues

Immune cell infiltrates in melanoma have important prognostic value. Gene expression analysis may simultaneously quantify numbers and function of multiple immune cell subtypes in formalin-fixed paraffin-embedded (FFPE) tissues. Prior studies report single gene expression can represent individual immune cell subtypes, but this has not been shown in FFPE melanomas. We hypothesized that gene expression profiling of human melanomas using a new RNA expression technology in FFPE tissue would correlate with the same immune cells identified by immunohistochemistry (IHC). This retrospective study included melanoma specimens analyzed by IHC on tumor tissue microarray (TMA) cores and by gene expression profiling with EdgeSeq Immuno-Oncology Assay using qNPA technology on the corresponding tumors. Standardized gene expression levels were analyzed relative to enumerated cells by IHC using Spearman rank test to calculate r-values. Multivariate analysis was performed by Kruskal–Wallis test. 119 melanoma specimens had both IHC and gene expression information available. There were significant associations between the level of gene expression and its quantified IHC cell marker for CD45⁺, CD3⁺, CD8⁺, CD4⁺, and CD20⁺ cells (all p < 0.001). There were also significant associations with exhaustion markers FoxP3⁺, PD-1⁺, and PD-L1⁺ (all p ≤ 0.0001). This new qNPA technology is useful to quantify intratumoral immune cells on FFPE specimens through RNA gene expression in metastatic melanoma. As previous studies have shown on other solid human tumors, we also confirm that the expression level of a single gene may be used to represent a single IHC immune cell marker in melanoma.

Large scale, robust, and accurate whole transcriptome profiling from clinical formalin-fixed paraffin-embedded samples

Transcriptome profiling can provide information of great value in clinical decision-making, yet RNA from readily available formalin-fixed paraffin-embedded (FFPE) tissue is often too degraded for quality sequencing. To assess the clinical utility of FFPE-derived RNA, we performed ribo-deplete RNA extractions on > 3200 FFPE slide samples; 25 of these had direct FFPE vs. fresh frozen (FF) replicates, 57 were sequenced in 2 different labs, 87 underwent multiple library analyses, and 16 had direct microdissected vs. macrodissected replicates. Poly-A versus ribo-depletion RNA extraction methods were compared using transcriptomes of TCGA cohort and 3116 FFPE samples. Compared to FF, FFPE transcripts coding for nuclear/cytoplasmic proteins involved in DNA packaging, replication, and protein synthesis were detected at lower rates and zinc finger family transcripts were of poorer quality. The greatest difference in extraction methods was in histone transcripts which typically lack poly-A tails. Encouragingly, the overall sequencing success rate was 81%. Exome coverage was highly concordant in direct FFPE and FF replicates, with 98% agreement in coding exon coverage and a median correlation of whole transcriptome profiles of 0.95. We provide strong rationale for clinical use of FFPE-derived RNA based on the robustness, reproducibility, and consistency of whole transcriptome profiling.

Genomic, transcriptomic, and viral integration profiles associated with recurrent/metastatic progression in high-risk human papillomavirus cervical carcinomas

Acquisition of recurrent/metastatic potential by a tumor cell defines a critical step in malignant progression. However, understanding of metastatic progression at the molecular level is scarce for cervical carcinomas (CES). In this study, we performed genomic, transcriptomic, and viral profiling of five pairs of primary (CES‐P) and matched recurrent/metastatic tumors (CES‐R/M) with high risk human papillomavirus. Whole exome sequencing revealed mutation features of CES‐R/M including elevated mutation burdens and prevalent copy number alterations compared to their matched CES‐P. A relative deficit of APOBEC‐related mutation signatures accompanying the transcriptional downregulation of APOBEC3A was observed for CES‐R/M. Mutations in genes encoding epigenetic regulators were commonly observed as CES‐R/M‐specific alterations. Immunoprofiling and gene set analysis revealed CES‐Ps were enriched with transcripts representing activated anticancer immunity such as interferon‐gamma pathway, while CES‐R/M exhibited upregulation of genes involved in epithelial‐mesenchymal transition and angiogenesis. Viral capture sequencing revealed that integration sites remained enriched in viral E1 protein domain during malignant progression. Moreover, we found transcriptional upregulation of POSTN and downregulation of APOBEC3A were associated with unfavorable clinical outcomes in CES. Comprehensive genomic and transcriptomic profiling of a rare cohort including CES‐R/M identified metastases‐specific features to advance the molecular understanding into CES metastatic progression with potential clinical implications.

Target Enrichment Enables the Discovery of lncRNAs with Somatic Mutations or Altered Expression in Paraffin-Embedded Colorectal Cancer Samples

Simple Summary

Alterations in long noncoding RNAs and their mutations have been increasingly recognized in tumorogenesis and cancer progression awakening especial interest as potential novel cancer biomarkers and therapeutic targets. The use of adjuvant chemotherapy in stage II colorectal cancer patients is challenging, and new biomarkers are required to identify patients with high probability of relapse. We focused on translational potential of non-coding RNAs in colorectal cancer. In this study, we aim to validate a new tool which couples target enrichment and RNAseq for transcriptomics studies of lncRNAs in formalin-fixed paraffin embedded (FFPE) tissue samples. Our results show that this new approach efficiently detects lncRNAs and differences in their expression between healthy and tumor FFPE tissues, as well as somatic mutations in expressed lncRNAs, identifying novel lncRNAs as potential candidates for colorectal cancer. This new approach could represent a promising avenue that would reduce costs and enable more efficient translational research.

Abstract

Long non-coding RNAs (lncRNAs) play important roles in cancer and are potential new biomarkers or targets for therapy. However, given the low and tissue-specific expression of lncRNAs, linking these molecules to particular cancer types and processes through transcriptional profiling is challenging. Formalin-fixed, paraffin-embedded (FFPE) tissues are abundant resources for research but are prone to nucleic acid degradation, thereby complicating the study of lncRNAs. Here, we designed and validated a probe-based enrichment strategy to efficiently profile lncRNA expression in FFPE samples, and we applied it for the detection of lncRNAs associated with colorectal cancer (CRC). Our approach efficiently enriched targeted lncRNAs from FFPE samples, while preserving their relative abundance, and enabled the detection of tumor-specific mutations. We identified 379 lncRNAs differentially expressed between CRC tumors and matched healthy tissues and found tumor-specific lncRNA variants. Our results show that numerous lncRNAs are differentially expressed and/or accumulate variants in CRC tumors, thereby suggesting a role in CRC progression. More generally, our approach unlocks the study of lncRNAs in FFPE samples, thus enabling the retrospective use of abundant, well documented material available in hospital biobanks.

Advancing brain barriers RNA sequencing: guidelines from experimental design to publication

BACKGROUND

RNA sequencing (RNA-Seq) in its varied forms has become an indispensable tool for analyzing differential gene expression and thus characterization of specific tissues. Aiming to understand the brain barriers genetic signature, RNA seq has also been introduced in brain barriers research. This has led to availability of both, bulk and single-cell RNA-Seq datasets over the last few years. If appropriately performed, the RNA-Seq studies provide powerful datasets that allow for significant deepening of knowledge on the molecular mechanisms that establish the brain barriers. However, RNA-Seq studies comprise complex workflows that require to consider many options and variables before, during and after the proper sequencing process.

MAIN BODY

In the current manuscript, we build on the interdisciplinary experience of the European PhD Training Network BtRAIN ( https://www.btrain-2020.eu/ ) where bioinformaticians and brain barriers researchers collaborated to analyze and establish RNA-Seq datasets on vertebrate brain barriers. The obstacles BtRAIN has identified in this process have been integrated into the present manuscript. It provides guidelines along the entire workflow of brain barriers RNA-Seq studies starting from the overall experimental design to interpretation of results. Focusing on the vertebrate endothelial blood-brain barrier (BBB) and epithelial blood-cerebrospinal-fluid barrier (BCSFB) of the choroid plexus, we provide a step-by-step description of the workflow, highlighting the decisions to be made at each step of the workflow and explaining the strengths and weaknesses of individual choices made. Finally, we propose recommendations for accurate data interpretation and on the information to be included into a publication to ensure appropriate accessibility of the data and reproducibility of the observations by the scientific community.

CONCLUSION

Next generation transcriptomic profiling of the brain barriers provides a novel resource for understanding the development, function and pathology of these barrier cells, which is essential for understanding CNS homeostasis and disease. Continuous advancement and sophistication of RNA-Seq will require interdisciplinary approaches between brain barrier researchers and bioinformaticians as successfully performed in BtRAIN. The present guidelines are built on the BtRAIN interdisciplinary experience and aim to facilitate collaboration of brain barriers researchers with bioinformaticians to advance RNA-Seq study design in the brain barriers community.

Identification of non-cancer cells from cancer transcriptomic data

Interactions between cancer cells and non-cancer cells composing the tumour microenvironment play a primary role in determining cancer progression and shaping the response to therapy. The qualitative and quantitative characterisation of the different cell populations in the tumour microenvironment is therefore crucial to understand its role in cancer. In recent years, many experimental and computational approaches have been developed to identify the cell populations composing heterogeneous tissue samples, such as cancer. In this review, we describe the state-of-the-art approaches for the quantification of non-cancer cells from bulk and single-cell cancer transcriptomic data, with a focus on immune cells. We illustrate the main features of these approaches and highlight their applications for the analysis of the tumour microenvironment in solid cancers. We also discuss techniques that are complementary and alternative to RNA sequencing, particularly focusing on approaches that can provide spatial information on the distribution of the cells within the tumour in addition to their qualitative and quantitative measurements. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

MMP2 as an independent prognostic stratifier in oral cavity cancers

Background

Around 25% of oral cavity squamous cell carcinoma (OCSCC) are not controlled by the standard of care, but there is currently no validated biomarker to identify those patients. Our objective was to determine a robust biomarker for severe OCSCC, using a biology-driven strategy.

Patients and methods

Tumor and juxtatumor secretome were analyzed in a prospective discovery cohort of 37 OCSCC treated by primary surgery. Independent biomarker validation was performed by RTqPCR in a retrospective cohort of 145 patients with similar clinical features. An 18-gene signature (18 G) predictive of the response to PD-1 blockade was evaluated in the same cohort.

Results

Among 29 deregulated molecules identified in a secretome analysis, including chemokines, cytokines, growth factors, and molecules related to tumor growth and tissue remodeling, only soluble MMP2 was a prognostic biomarker. In our validation cohort, high levels of MMP2 and CD276, and low levels of CXCL10 and STAT1 mRNA were associated with poor prognosis in univariate analysis (Kaplan-Meier). MMP2 (p = .001) and extra-nodal extension (ENE) (p = .006) were independent biomarkers of disease-specific survival (DSS) in multivariate analysis and defined prognostic groups with 5-year DSS ranging from 36% (MMP2highENE+) to 88% (MMP2lowENE-). The expression of 18 G was similar in the different prognostic groups, suggesting comparable responsiveness to anti-PD-1.

Conclusion

High levels of MMP2 were an independent and validated prognostic biomarker, surpassing other molecules of a large panel of the tumor and immune-related processes, which may be used to select poor prognosis patients for intensified neoadjuvant or adjuvant regimens.

MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer

Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their methylation profiles. MethCORR is here applied to methylation profiles from 877 fresh-frozen/FFPE samples and comparative analysis identifies the same two subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicts relapse-free survival (HR = 2.66, 95%CI [1.67-4.22], P value < 0.001 (log-rank test)) than UICC tumor, node, metastasis (TNM) staging and microsatellite instability status are identified and validated using DNA methylation-specific PCR. The MethCORR approach is general, and may be similarly successful for other cancer types.

Ovarian Cancer Translational Activity of the Multicenter Italian Trial in Ovarian Cancer (MITO) Group: Lessons Learned in 10 Years of Experience

Ovarian cancer is the most lethal gynecological cancer, and despite years of research, with the exception of a BRCA mutation driving the use of PARP inhibitors, no new prognostic/predictive biomarkers are clinically available. Improvement in biomarker selection and validation may derive from the systematic inclusion of translational analyses into the design of clinical trials. In the era of personalized medicine, the prospective centralized collection of high-quality biological material, expert pathological revision, and association to well-controlled clinical data are important or even essential added values to clinical trials. Here, we present the academic experience of the MITO (Multicenter Italian Trial in Ovarian Cancer) group, including gynecologists, pathologists, oncologists, biostatisticians, and translational researchers, whose effort is dedicated to the care and basic/translational research of gynecologic cancer. In our ten years of experience, we have been able to collect and process, for translational analyses, formalin-fixed, paraffin-embedded blocks from more than one thousand ovarian cancer patients. Standard operating procedures for collection, shipping, and processing were developed and made available to MITO researchers through the coordinating center’s web-based platform. Clinical data were collected through dedicated electronic case report forms hosted in a web-based electronic platform and stored in a central database at the trial’s coordinating center, which performed all the analyses related to the proposed translational researches. During this time, we improved our strategies of block management from retrospective to prospective collection, up to the design of a prospective collection with a quality check for sample eligibility before patients’ accrual. The final aim of our work is to share our experience by suggesting a guideline for the process of centralized collection, revision processing, and storing of formalin-fixed, paraffin-embedded blocks for translational purposes.

RNA-seq from archival FFPE breast cancer samples: molecular pathway fidelity and novel discovery

BACKGROUND

Formalin-fixed, paraffin-embedded (FFPE) tissues for RNA-seq have advantages over fresh frozen tissue including abundance and availability, connection to rich clinical data, and association with patient outcomes. However, FFPE-derived RNA is highly degraded and chemically modified, which impacts its utility as a faithful source for biological inquiry.

METHODS

True archival FFPE breast cancer cases (n = 58), stored at room temperature for 2-23 years, were utilized to identify key steps in tissue selection, RNA isolation, and library choice. Gene expression fidelity was evaluated by comparing FFPE data to public data obtained from fresh tissues, and by employing single-gene, gene set and transcription network-based regulon analyses.

RESULTS

We report a single 10 μm section of breast tissue yields sufficient RNA for RNA-seq, and a relationship between RNA quality and block age that was not linear. We find single-gene analysis is limiting with FFPE tissues, while targeted gene set approaches effectively distinguish ER+ from ER- breast cancers. Novel utilization of regulon analysis identified the transcription factor KDM4B to associate with ER+ disease, with KDM4B regulon activity and gene expression having prognostic significance in an independent cohort of ER+ cases.

CONCLUSION

Our results, which outline a robust FFPE-RNA-seq pipeline for broad use, support utilizing FFPE tissues to address key questions in the breast cancer field, including the delineation between indolent and life-threatening disease, biological stratification and molecular mechanisms of treatment resistance.

The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues

Background

Utilization of RNA sequencing methods to measure gene expression from archival formalin-fixed paraffin-embedded (FFPE) tumor samples in translational research and clinical trials requires reliable interpretation of the impact of pre-analytical variables on the data obtained, particularly the methods used to preserve samples and to purify RNA.

Methods

Matched tissue samples from 12 breast cancers were fresh frozen (FF) and preserved in RNAlater or fixed in formalin and processed as FFPE tissue. Total RNA was extracted and purified from FF samples using the Qiagen RNeasy kit, and in duplicate from FFPE tissue sections using three different kits (Norgen, Qiagen and Roche). All RNA samples underwent whole transcriptome RNA sequencing (wtRNAseq) and targeted RNA sequencing for 31 transcripts included in a signature of sensitivity to endocrine therapy. We assessed the effect of RNA extraction kit on the reliability of gene expression levels using linear mixed-effects model analysis, concordance correlation coefficient (CCC) and differential analysis. All protein-coding genes in the wtRNAseq and three gene expression signatures for breast cancer were assessed for concordance.

Results

Despite variable quality of the RNA extracted from FFPE samples by different kits, all had similar concordance of overall gene expression from wtRNAseq between matched FF and FFPE samples (median CCC 0.63–0.66) and between technical replicates (median expression difference 0.13–0.22). More than half of genes were differentially expressed between FF and FFPE, but with low fold change (median |LFC| 0.31–0.34). Two out of three breast cancer signatures studied were highly robust in all samples using any kit, whereas the third signature was similarly discordant irrespective of the kit used. The targeted RNAseq assay was concordant between FFPE and FF samples using any of the kits (CCC 0.91–0.96).

Conclusions

The selection of kit to purify RNA from FFPE did not influence the overall quality of results from wtRNAseq, thus variable reproducibility of gene signatures probably relates to the reliability of individual gene selected and possibly to the algorithm. Targeted RNAseq showed promising performance for clinical deployment of quantitative assays in breast cancer from FFPE samples, although numerical scores were not identical to those from wtRNAseq and would require calibration.

A comparative analysis of RNA sequencing methods with ribosome RNA depletion for degraded and low-input total RNA from formalin-fixed and paraffin-embedded samples

Background

Formalin-fixed and paraffin-embedded (FFPE) blocks held in clinical laboratories are an invaluable resource for clinical research, especially in the era of personalized medicine. It is important to accurately quantitate gene expression with degraded and small amounts of total RNA from FFPE materials.

Results

High concordance in transcript quantifications were shown between FF and FFPE samples using the same kit. The gene expression using the TaKaRa kit showed a difference with other kits, which may be due to the different principle of rRNA depletion or the amount of input total RNA. For seriously degraded RNA from FFPE samples, libraries could be constructed with as low as 50 ng of total RNA, although there was residual rRNA in the libraries. Data analysis with HISAT demonstrated that the unique mapping ratio, percentage of exons in unique mapping reads and number of detected genes decreased along with the decreasing quality of input RNA.

Conclusions

The method of RNA library construction with rRNA depletion can be used for clinical FFPE samples. For degraded and low-input RNA samples, it is still possible to obtain repeatable RNA expression profiling but with a low unique mapping ratio and high residual rRNA.

Prospective Evaluation of Unprocessed Core Needle Biopsy DNA and RNA Yield from Lung, Liver, and Kidney Tumors: Implications for Cancer Genomics

Context

Targeted needle biopsies are increasingly performed for the genetic characterization of cancer. While the nucleic acid content of core needle biopsies after standard pathology processing (i.e., formalin fixation and paraffin embedding (FFPE)) has been previously reported, little is known about the potential yield for molecular analysis at the time of biopsy sample acquisition.

Objectives

Our objective was to improve the understanding of DNA and RNA yields from commonly used core needle biopsy techniques prior to sample processing.

Methods

We performed 552 ex vivo 18 and 20G core biopsies in the lungs, liver, and kidneys. DNA and RNA were extracted from fresh-frozen core samples and quantified for statistical comparisons based on needle gauge, biopsy site, and tissue type.

Results

Median tumor DNA yields from all 18G and 20G samples were 5880 ng and 2710 ng, respectively. Median tumor RNA yields from all 18G and 20G samples were 1100 ng and 230 ng, respectively. A wide range of DNA and RNA quantities (1060–13,390 ng and 370–6280 ng, respectively) were acquired. Median DNA and RNA yields from 18G needles were significantly greater than those from 20G needles across all organs (p < 0.001).

Conclusions

Core needle biopsy techniques for cancer diagnostics yield a broad range of DNA and RNA for molecular pathology, though quantities are greater than what has been reported for FFPE processed material. Since non-formalin-fixed DNA is advantageous for molecular studies, workflows that optimize core needle biopsy yield for molecular characterization should be explored.

Feasibility of developing reliable gene expression modules from FFPE derived RNA profiled on Affymetrix arrays

The reliability of differential gene expression analysis on formalin-fixed, paraffin-embedded (FFPE) expression profiles generated using Affymetrix arrays is questionable, due to the high range of percent-present values reported in studies which profiled FFPE samples using this technology. Moreover, the validity of gene-modules derived from external datasets in FFPE microarray expression profiles is unknown. By generating matched gene expression profiles using RNAs derived from fresh-frozen (FF) and FFPE preserved breast tumors with Affymetrix arrays and FF/FFPE RNA specific amplification-and-labeling kits, the reliability of differential expression analysis and the validity of gene modules derived from external datasets were investigated. Specifically, the reliability of differential expression analysis was investigated by developing de-novo ER/HER2 pathway gene-modules from the matched datasets and validating them on external FF/FFPE gene expression datasets using ROC analysis. Spearman's rank correlation coefficient of module scores between matched FFPE/frozen datasets was used to measure the reliability of gene-modules derived from external datasets in FFPE expression profiles. Independent of the array/amplification-kit/sample preservation method used, de-novo ER/HER2 gene-modules derived from all matched datasets showed similar prediction performance in the independent validation (AUC range in FFPE dataset; ER: 0.93-0.95, HER2: 0.85-0.91), except for the de-novo ER/HER2 gene-module derived from the FFPE dataset using the 3'IVT kit (AUC range in FFPE dataset; ER: 0.79-0.81, HER2: 0.78). Among the external gene modules considered, roughly ~50% gene modules showed high concordance between expression profiles derived from matching FF and FFPE RNA. The remaining discordant gene modules between FF and FFPE expression profiles showed high concordance within matching FF datasets and within matching FFPE datasets independently, implying that microarrays still require improved amplification-and-sample-preparation protocols for deriving 100% concordant expression profiles from matching FF and FFPE RNA.

RNA based individualized drug selection in breast cancer patients without patient-matched normal tissue

Background

While standard RNA expression tests stratify patients into risk groups, RNA-Seq can guide personalized drug selection based on expressed mutations, fusion genes, and differential expression (DE) between tumor and normal tissue. However, patient-matched normal tissue may be unavailable. Additionally, biological variability in normal tissue and technological biases may confound results. Therefore, we present normal expression reference data for two sequencing methods that are suitable for breast biopsies.

Results

We identified breast cancer related and drug related genes that are expressed uniformly across our normal samples. Large subsets of these genes are identical for formalin fixed paraffin embedded samples and fresh frozen samples. Adipocyte signatures were detected in frozen compared to formalin samples, prepared by surgeons and pathologists, respectively. Gene expression confounded by adipocytes was identified using fat tissue samples. Finally, immune repertoire statistics were obtained for healthy breast, tumor and fat tissues.

Conclusions

Our reference data can be used with patient tumor samples that are asservated and sequenced with a matching aforementioned method. Coefficients of variation are given for normal gene expression. Thus, potential drug selection can be based on confidently overexpressed genes and immune repertoire statistics.

Materials and Methods

Normal expression from formalin and frozen healthy breast tissue samples using Roche Kapa RiboErase (total RNA) (19 formalin, 9 frozen) and Illumina TruSeq RNA Access (targeted RNA-Seq, aka TruSeq RNA Exome) (11 formalin, 1 frozen), and fat tissue (6 frozen Access). Tumor DE using 10 formalin total RNA tumor samples and 1 frozen targeted RNA tumor sample.

Biological Validation of RNA Sequencing Data from Formalin-Fixed Paraffin-Embedded Primary Melanomas

PURPOSE

Initiatives such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) have generated high-quality, multi-platform molecular data from thousands of frozen tumor samples. While these initiatives have provided invaluable insight into cancer biology, a tremendous potential resource remains largely untapped in formalin-fixed, paraffin-embedded (FFPE) samples that are more readily available, but which can present technical challenges due to crosslinking of fragile molecules such as RNA.

MATERIALS AND METHODS

We extracted RNA from FFPE primary melanomas and assessed two gene expression platforms -- genome-wide RNA sequencing (RNA-seq) and targeted NanoString -- for their ability to generate coherent biological signals. To do so, we generated an improved approach to quantifying gene expression pathways, in which we refine pathway scores through correlation-guided gene subsetting. We also make comparisons to the TCGA and other publicly available melanoma datasets.

RESULTS

Comparison of the gene expression patterns to each other, to established biological modules, and to clinical and immunohistochemical data confirmed the fidelity of biological signals from both platforms using FFPE samples to known biology. Moreover, correlations with patient outcome data were consistent with previous frozen-tissue-based studies.

CONCLUSION

FFPE samples from previously difficult-to-access cancer types - such as small primary melanomas - represents a valuable and previously unexploited source of analyte for RNA-seq and NanoString platforms. This work provides an important step towards the use of such platforms to unlock novel molecular underpinnings and inform future biologically-driven clinical decisions.