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

Successive next-generation sequencing strategy for optimal fusion gene detection in non-small-cell lung cancer in clinical practice

Metastatic non-small-cell lung cancer (NSCLC) displays various molecular alterations in the RAS-MAPK pathway. In particular, NSCLCs show high rates of targetable gene fusion in ALK, RET, ROS1, NRG1 and NTRK, or MET exon 14 skipping. Rapid and accurate detection of gene fusion in EGFR/KRAS/BRAF mutations is important for treatment selection especially for first-line indications. RNA-based next-generation sequencing (NGS) panels appear to be the most appropriate as all targets are multiplexed in a single run. While comprehensive NGS panels remain costly for daily practice, optimal sequencing strategies using targeted DNA/RNA panel approaches need to be validated. Here, we describe our lung cancer screening strategy using DNA and RNA targeted approaches in a real-life cohort of 589 NSCLC patients assessed for molecular testing. Gene fusions were analysed in 174 patients negative for oncogene driver mutations or ALK immunohistochemistry in a two-step strategy. Targetable alterations were identified in 28% of contributive samples. Non-smokers had a 63.7% probability to have a targetable alteration as compared to 21.5% for smokers. Overall survival was significantly higher (p=0.03) for patients who received a molecularly matched therapy. Our study shows the feasibility in routine testing of NSCLC DNA/RNA molecular screening for all samples in a cost- and time-controlled manner. The significant high fusion detection rate in patients with wild-type RAS-MAPK tumours highlights the importance of amending testing strategies in NSCLC.

Validation of RNA Extraction Methods and Suitable Reference Genes for Gene Expression Studies in Developing Fetal Human Inner Ear Tissue

A comprehensive gene expression investigation requires high-quality RNA extraction, in sufficient amounts for real-time quantitative polymerase chain reaction and next-generation sequencing. In this work, we compared different RNA extraction methods and evaluated different reference genes for gene expression studies in the fetal human inner ear. We compared the RNA extracted from formalin-fixed paraffin-embedded tissue with fresh tissue stored at -80 °C in RNAlater solution and validated the expression stability of 12 reference genes (from gestational week 11 to 19). The RNA from fresh tissue in RNAlater resulted in higher amounts and a better quality of RNA than that from the paraffin-embedded tissue. The reference gene evaluation exhibited four stably expressed reference genes (B2M, HPRT1, GAPDH and GUSB). The selected reference genes were then used to examine the effect on the expression outcome of target genes (OTOF and TECTA), which are known to be regulated during inner ear development. The selected reference genes displayed no differences in the expression profile of OTOF and TECTA, which was confirmed by immunostaining. The results underline the importance of the choice of the RNA extraction method and reference genes used in gene expression studies.

Review of Molecular Technologies for Investigating Canine Cancer

Genetic molecular testing is starting to gain traction as part of standard clinical practice for dogs with cancer due to its multi-faceted benefits, such as potentially being able to provide diagnostic, prognostic and/or therapeutic information. However, the benefits and ultimate success of genomic analysis in the clinical setting are reliant on the robustness of the tools used to generate the results, which continually expand as new technologies are developed. To this end, we review the different materials from which tumour cells, DNA, RNA and the relevant proteins can be isolated and what methods are available for interrogating their molecular profile, including analysis of the genetic alterations (both somatic and germline), transcriptional changes and epigenetic modifications (including DNA methylation/acetylation and microRNAs). We also look to the future and the tools that are currently being developed, such as using artificial intelligence (AI) to identify genetic mutations from histomorphological criteria. In summary, we find that the molecular genetic characterisation of canine neoplasms has made a promising start. As we understand more of the genetics underlying these tumours and more targeted therapies become available, it will no doubt become a mainstay in the delivery of precision veterinary care to dogs with cancer.

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.

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.

Differentially expressed circRNAs in peripheral blood samples as potential biomarkers and therapeutic targets for acute angle-closure glaucoma

Glaucoma is the leading cause of irreversible blindness globally. Circular RNAs (circRNAs) play vital roles in various biological processes as microRNA (miRNA) sponges and, thus, have been investigated as potential biomarkers and therapeutic targets in numerous human diseases. However, the underlying mechanisms of circRNAs in the pathogenesis of glaucoma remain unclear. Therefore, transcriptome sequencing was performed to identify relevant circRNAs in peripheral blood samples from patients with primary angle-closure glaucoma. Bioinformatics analysis was performed to investigate the potential roles of differentially expressed circRNAs (DEcircRNAs) in the pathogenesis of glaucoma. In total, 481 differentially expressed genes in addition to 345 DEcircRNAs were identified in patients with glaucoma. Based on a public database, targeted gene analysis identified 11 DEcircRNAs that potentially regulate the expression of five genes as miRNA sponges in glaucoma. In addition, quantitative reverse transcription PCR analysis verified that expression of the circRNA hsa-circ-0000745 was positively correlated with the expression of NEAT1 as a potential target gene. These results suggest that DEcircRNAs are involved in a gene expression regulatory network related to immune cell function and progression of glaucoma. Thus, DEcircRNAs in peripheral blood are potential biomarkers and therapeutic targets for glaucoma.

Systems analyses of the Fabry kidney transcriptome and its response to enzyme replacement therapy identified and cross-validated enzyme replacement therapy-resistant targets amenable to drug repurposing

Fabry disease is a rare disorder caused by variations in the alpha-galactosidase gene. To a degree, Fabry disease is manageable via enzyme replacement therapy (ERT). By understanding the molecular basis of Fabry nephropathy (FN) and ERT's long-term impact, here we aimed to provide a framework for selection of potential disease biomarkers and drug targets. We obtained biopsies from eight control individuals and two independent FN cohorts comprising 16 individuals taken prior to and after up to ten years of ERT, and performed RNAseq analysis. Combining pathway-centered analyses with network-science allowed computation of transcriptional landscapes from four nephron compartments and their integration with existing proteome and drug-target interactome data. Comparing these transcriptional landscapes revealed high inter-cohort heterogeneity. Kidney compartment transcriptional landscapes comprehensively reflected differences in FN cohort characteristics. With exception of a few aspects, in particular arteries, early ERT in patients with classical Fabry could lastingly revert FN gene expression patterns to closely match that of control individuals. Pathways nonetheless consistently altered in both FN cohorts pre-ERT were mostly in glomeruli and arteries and related to the same biological themes. While keratinization-related processes in glomeruli were sensitive to ERT, a majority of alterations, such as transporter activity and responses to stimuli, remained dysregulated or reemerged despite ERT. Inferring an ERT-resistant genetic module of expressed genes identified 69 drugs for potential repurposing matching the proteins encoded by 12 genes. Thus, we identified and cross-validated ERT-resistant gene product modules that, when leveraged with external data, allowed estimating their suitability as biomarkers to potentially track disease course or treatment efficacy and potential targets for adjunct pharmaceutical treatment.

Diagnostic application of formalin fixed archived tissues for detection of foot-and-mouth disease

Early and definitive disease diagnosis is critical for effective disease control. 50% buffered glycerine is commonly used viral transport medium, which is not always available and required cold chain. Tissues samples archived in 10% neutral buffered formalin (NBF) can preserve nucleic acid that can be used in molecular studies and disease diagnosis. The present study's goal was to detect the foot-and-mouth disease (FMD) viral genome in formalin-fixed archived tissue which may avoid cold chain during transportation. This study used FMD suspected samples preserved in 10% neutral buffered formalin from 0 to 730 days post fixation (DPF). All archived tissues were positive for FMD viral genome by multiplex RT-PCR and RT-qPCR up to 30 DPF, whereas archived epithelium tissues and thigh muscle were positive for FMD vial genome up to 120 DPF. FMD viral genome was detected in cardiac muscle up to 60 DPF and 120 DPF, respectively. The findings suggest that 10% neutral buffered formalin could be used for sample preservation and transportation for timely and accurate FMD diagnosis. More samples need to be tested before implementing the use of 10% neutral buffered formalin as a preservative and transportation medium. The technique may add value in ensuring biosafety measures for creation during disease free zone as well.

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.

MultiomicsTracks96: A high throughput PIXUL-Matrix-based toolbox to profile frozen and FFPE tissues multiomes

Background

The multiome is an integrated assembly of distinct classes of molecules and molecular properties, or "omes," measured in the same biospecimen. Freezing and formalin-fixed paraffin-embedding (FFPE) are two common ways to store tissues, and these practices have generated vast biospecimen repositories. However, these biospecimens have been underutilized for multi-omic analysis due to the low throughput of current analytical technologies that impede large-scale studies.

Methods

Tissue sampling, preparation, and downstream analysis were integrated into a 96-well format multi-omics workflow, MultiomicsTracks96. Frozen mouse organs were sampled using the CryoGrid system, and matched FFPE samples were processed using a microtome. The 96-well format sonicator, PIXUL, was adapted to extract DNA, RNA, chromatin, and protein from tissues. The 96-well format analytical platform, Matrix, was used for chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), methylated RNA immunoprecipitation (MeRIP), and RNA reverse transcription (RT) assays followed by qPCR and sequencing. LC-MS/MS was used for protein analysis. The Segway genome segmentation algorithm was used to identify functional genomic regions, and linear regressors based on the multi-omics data were trained to predict protein expression.

Results

MultiomicsTracks96 was used to generate 8-dimensional datasets including RNA-seq measurements of mRNA expression; MeRIP-seq measurements of m6A and m5C; ChIP-seq measurements of H3K27Ac, H3K4m3, and Pol II; MeDIP-seq measurements of 5mC; and LC-MS/MS measurements of proteins. We observed high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles (ChIP-seq: H3K27Ac, H3K4m3, Pol II; MeDIP-seq: 5mC) was able to recapitulate and predict organ-specific super-enhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic expression profiles can be more accurately predicted by the full suite of multi-omics data, compared to using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

Conclusions

The MultiomicsTracks96 workflow is well suited for high dimensional multi-omics studies - for instance, multiorgan animal models of disease, drug toxicities, environmental exposure, and aging as well as large-scale clinical investigations involving the use of biospecimens from existing tissue repositories.

Molecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing

INTRODUCTION

RNA sequencing (RNAseq) analysis is emerging as a clinical research or diagnostic approach for cytologic samples, but there is need for formal comparison of different sample preparation methods in the cytology laboratory to identify which pre-analytic methods could provide alternatives to formalin-fixed paraffin-embedded (FFPE) sections.

MATERIALS AND METHODS

We prepared 13 malignant effusions (metastatic estrogen receptor-positive breast cancer) in the cytology laboratory using 6 routine cytologic methods: FFPE cell block, Carnoy's solution, 95% ethanol (EtOH), air-dried and Diff-Quik, ThinPrep, and SurePath preparations. Measurements of RNA quality, expression of 2 multigene expression signatures, molecular subtype, and 4 common activating mutation sites in each preparation were compared with fresh frozen (FF) cell pellet in RNA preservative using distribution of fragment length and concordance correlation coefficient (CCC).

RESULTS

The fraction of RNA fragments measuring 200 bases or more (DV200) were 24% higher from cytospins fixed in Carnoy's solution or 95% EtOH than DV200 from FFPE cell blocks. SurePath samples failed RNAseq quality control. There was high concordance of gene expression measurements with FF samples using cytospins fixed in Carnoy's solution, 95% EtOH, Diff-Quik (CCC = 0.829, 0.812, 0.760, respectively), or ThinPrep (CCC = 0.736), but lower using FFPE cell block (CCC = 0.564). The proportion of mutant transcripts was concordant between FF and any cytologic preparation methods.

CONCLUSIONS

Cytospin preparations fixed with Carnoy's or 95% ETOH then Papanicolaou stained produced RNAseq results that were equivalent to FF samples and superior to FFPE cell block sections.

Clinically relevant fusion oncogenes: detection and practical implications

Mechanistically, chimeric genes result from DNA rearrangements and include parts of preexisting normal genes combined at the genomic junction site. Some rearranged genes encode pathological proteins with altered molecular functions. Those which can aberrantly promote carcinogenesis are called fusion oncogenes. Their formation is not a rare event in human cancers, and many of them were documented in numerous study reports and in specific databases. They may have various molecular peculiarities like increased stability of an oncogenic part, self-activation of tyrosine kinase receptor moiety, and altered transcriptional regulation activities. Currently, tens of low molecular mass inhibitors are approved in cancers as the drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins, that is, including ALK, ABL, EGFR, FGFR1-3, NTRK1-3, MET, RET, ROS1 moieties. Therein, the presence of the respective RTK fusion in the cancer genome is the diagnostic biomarker for drug prescription. However, identification of such fusion oncogenes is challenging as the breakpoint may arise in multiple sites within the gene, and the exact fusion partner is generally unknown. There is no gold standard method for RTK fusion detection, and many alternative experimental techniques are employed nowadays to solve this issue. Among them, RNA-seq-based methods offer an advantage of unbiased high-throughput analysis of only transcribed RTK fusion genes, and of simultaneous finding both fusion partners in a single RNA-seq read. Here we focus on current knowledge of biology and clinical aspects of RTK fusion genes, related databases, and laboratory detection methods.

CODA: a combo-Seq data analysis workflow

The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA-miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA-miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA.

Reproducible and sensitive micro-tissue RNA sequencing from formalin-fixed paraffin-embedded tissues for spatial gene expression analysis

Spatial transcriptome analysis of formalin-fixed paraffin-embedded (FFPE) tissues using RNA-sequencing (RNA-seq) provides interactive information on morphology and gene expression, which is useful for clinical applications. However, despite the advantages of long-term storage at room temperature, FFPE tissues may be severely damaged by methylene crosslinking and provide less gene information than fresh-frozen tissues. In this study, we proposed a sensitive FFPE micro-tissue RNA-seq method that combines the punching of tissue sections (diameter: 100 μm) and the direct construction of RNA-seq libraries. We evaluated a method using mouse liver tissues at two years after fixation and embedding and detected approximately 7000 genes in micro-punched tissue-spots (thickness: 10 μm), similar to that detected with purified total RNA (2.5 ng) equivalent to the several dozen cells in the spot. We applied this method to clinical FFPE specimens of lung cancer that had been fixed and embedded 6 years prior, and found that it was possible to determine characteristic gene expression in the microenvironment containing tumor and non-tumor cells of different morphologies. This result indicates that spatial gene expression analysis of the tumor microenvironment is feasible using FFPE tissue sections stored for extensive periods in medical facilities.

Expert opinion on NSCLC small specimen biomarker testing - Part 1: Tissue collection and management

Biomarker testing is crucial for treatment selection in advanced non-small cell lung cancer (NSCLC). However, the quantity of available tissue often presents a key constraint for patients with advanced disease, where minimally invasive tissue biopsy typically returns small samples. In Part 1 of this two-part series, we summarise evidence-based recommendations relating to small sample processing for patients with NSCLC. Generally, tissue biopsy techniques that deliver the greatest quantity and quality of tissue with the least risk to the patient should be selected. Rapid on-site evaluation can help to ensure sufficient sample quality and quantity. Sample processing should be managed according to biomarker testing requirements, because tissue fixation methodology influences downstream nucleic acid, protein and morphological analyses. Accordingly, 10% neutral buffered formalin is recommended as an appropriate fixative, and the duration of fixation is recommended not to exceed 24–48 h. Tissue sparing techniques, including the ‘one biopsy per block’ approach and small sample cutting protocols, can help preserve tissue. Cytological material (formalin-fixed paraffin-embedded [FFPE] cytology blocks and non-FFPE samples such as smears and touch preparations) can be an excellent source of nucleic acid, providing either primary or supplementary patient material to complete morphological and molecular diagnoses. Considerations on biomarker testing, reporting and quality assessment are discussed in Part 2.

Impact of RNA degradation on next-generation sequencing transcriptome data

RNA sequencing is an innovative technology to study transcriptomes in both biological and clinical research. However, clinical specimens from patients undergoing surgical operations have a major challenge due to sample degradation. This study replicated the process of RNA degradation by maintaining cells at room temperature to achieve none, slight, middle, and high levels of RNA degradation with decreasing RNA integrity numbers (RIN) of approximately 9.8, 6.7, 4.4, and 2.5, respectively. Next, the differential expression of mRNA and long non-coding RNA (lncRNA) was analyzed in the four degradation groups along with pathway enrichment analysis. The results showed that the similarity of lncRNAs exhibited significant differences even for a slight level of RNA degradation compared with the non-degraded RNA sample. Also, the RNA degradation process was found to be universal, global, and random; the differentially expressed genes increased with an increase in degradation but the pathway enrichment phenomenon was not significantly observed.

A transcriptome-Based Deep Neural Network Classifier for Identifying the Site of Origin in Mucinous Cancer

Purpose:

There is a lack of tools for identifying the site of origin in mucinous cancer. This study aimed to evaluate the performance of a transcriptome-based classifier for identifying the site of origin in mucinous cancer.

Materials And Methods:

Transcriptomic data of 1878 non-mucinous and 82 mucinous cancer specimens, with 7 sites of origin, namely, the uterine cervix (CESC), colon (COAD), pancreas (PAAD), stomach (STAD), uterine endometrium (UCEC), uterine carcinosarcoma (UCS), and ovary (OV), obtained from The Cancer Genome Atlas, were used as the training and validation sets, respectively. Transcriptomic data of 14 mucinous cancer specimens from a tissue archive were used as the test set. For identifying the site of origin, a set of 100 differentially expressed genes for each site of origin was selected. After removing multiple iterations of the same gene, 427 genes were chosen, and their RNA expression profiles, at each site of origin, were used to train the deep neural network classifier. The performance of the classifier was estimated using the training, validation, and test sets.

Results:

The accuracy of the model in the training set was 0.998, while that in the validation set was 0.939 (77/82). In the test set which is newly sequenced from a tissue archive, the model showed an accuracy of 0.857 (12/14). t-SNE analysis revealed that samples in the test set were part of the clusters obtained for the training set.

Conclusion:

Although limited by small sample size, we showed that a transcriptome-based classifier could correctly identify the site of origin of mucinous cancer.

The lncRNA B3GALT5-AS1 Functions as an HCC Suppressor by Regulating the miR-934/UFM1 Axis

Accumulating evidence has demonstrated that long noncoding RNA (lncRNA) is importantly related to the occurrence and development of cancer. According to reports, the expression of B3GALT5-AS1 in hepatocellular carcinoma (HCC) is downregulated; however, the role of B3GALT5-AS1 in HCC is not yet clear. In this study, our purpose is to explore the biological function of B3GALT5-AS1 in HCC and its coupling mechanism with miR-934 and ubiquitin-fold modifier 1 (UFM1). We found that the B3GALT5-AS1 expression level was of significant reduction in both HCC tissues and cell lines; B3GALT5-AS1 overexpression (ov) may inhibit the malignant features of HCC. In addition, we demonstrated that miR-934 mimics could reverse the effect of B3GALT5-AS1 ov, which proved miR-934 was the downstream regulator of B3GALT5-AS1. Furthermore, si-UFM1 could reverse the effect of miR-934 inhibitor, which revealed the connection between them. Moreover, we found that B3GALT5-AS1 could keep down the PI3K/AKT pathway through UFM1. Our results demonstrated that B3GALT5-AS1 was an excellent HCC suppressant by regulating miR-934 and UFM1 to achieve negative regulation of HCC cell proliferation, invasion, and metastasis, indicating that B3GALT5-AS1 is a promising potential therapeutic target for HCC treatment.

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.

DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing

Targeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.

MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning

BACKGROUND

Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell lung cancer (NSCLC) MET exon 14 skipping was shown to be targetable.

METHODS

We constructed neural networks (NN/CNN) specifically designed to detect MET exon 14 skipping events using RNAseq data. Furthermore, for discovery purposes we also developed a sparsely connected autoencoder to identify uncharacterized MET isoforms.

RESULTS

The neural networks had a Met exon 14 skipping detection rate greater than 94% when tested on a manually curated set of 690 TCGA bronchus and lung samples. When globally applied to 2605 TCGA samples, we observed that the majority of false positives was characterized by a blurry coverage of exon 14, but interestingly they share a common coverage peak in the second intron and we speculate that this event could be the transcription signature of a LINE1 (Long Interspersed Nuclear Element 1)-MET (Mesenchymal Epithelial Transition receptor tyrosine kinase) fusion.

CONCLUSIONS

Taken together, our results indicate that neural networks can be an effective tool to provide a quick classification of pathological transcription events, and sparsely connected autoencoders could represent the basis for the development of an effective discovery tool.

Applications of single-cell and bulk RNA sequencing in onco-immunology

The rising interest for precise characterization of the tumour immune contexture has recently brought forward the high potential of RNA sequencing (RNA-seq) in identifying molecular mechanisms engaged in the response to immunotherapy. In this review, we provide an overview of the major principles of single-cell and conventional (bulk) RNA-seq applied to onco-immunology. We describe standard preprocessing and statistical analyses of data obtained from such techniques and highlight some computational challenges relative to the sequencing of individual cells. We notably provide examples of gene expression analyses such as differential expression analysis, dimensionality reduction, clustering and enrichment analysis. Additionally, we used public data sets to exemplify how deconvolution algorithms can identify and quantify multiple immune subpopulations from either bulk or single-cell RNA-seq. We give examples of machine and deep learning models used to predict patient outcomes and treatment effect from high-dimensional data. Finally, we balance the strengths and weaknesses of single-cell and bulk RNA-seq regarding their applications in the clinic.

Technical Validity of a Customized Assay of Sensitivity to Endocrine Therapy Using Sections from Fixed Breast Cancer Tissue

BACKGROUND

We translated a multigene expression index to predict sensitivity to endocrine therapy for Stage II-III breast cancer (SET2,3) to hybridization-based expression assays of formalin-fixed paraffin-embedded (FFPE) tissue sections. Here we report the technical validity with FFPE samples, including preanalytical and analytical performance.

METHODS

We calibrated SET2,3 from microarrays (Affymetrix U133A) of frozen samples to hybridization-based assays of FFPE tissue, using bead-based QuantiGene Plex (QGP) and slide-based NanoString (NS). The following preanalytical and analytical conditions were tested in controlled studies: replicates within and between frozen and fixed samples, age of paraffin blocks, homogenization of fixed sections versus extracted RNA, core biopsy versus surgically resected tumor, technical replicates, precision over 20 weeks, limiting dilution, linear range, and analytical sensitivity. Lin's concordance correlation coefficient (CCC) was used to measure concordance between measurements.

RESULTS

SET2,3 index was calibrated to use with QGP (CCC 0.94) and NS (CCC 0.93) technical platforms, and was validated in two cohorts of older fixed samples using QGP (CCC 0.72, 0.85) and NS (CCC 0.78, 0.78). QGP assay was concordant using direct homogenization of fixed sections versus purified RNA (CCC 0.97) and between core and surgical sample types (CCC 0.90), with 100% accuracy in technical replicates, 1-9% coefficient of variation over 20 weekly tests, linear range 3.0-11.5 (log2 counts), and analytical sensitivity ≥2.0 (log2 counts).

CONCLUSIONS

Measurement of the novel SET2,3 assay was technically valid from fixed tumor sections of biopsy or resection samples using simple, inexpensive, hybridization methods, without the need for RNA purification.

ESMO recommendations on the standard methods to detect RET fusions and mutations in daily practice and clinical research

Aberrant activation of RET is a critical driver of growth and proliferation in diverse solid tumours. Multikinase inhibitors (MKIs) showing anti-RET activities have been tested in RET-altered tumours with variable results. The low target specificity with consequent increase in side-effects and off-target toxicities resulting in dose reduction and drug discontinuation are some of the major issues with MKIs. To overcome these issues, new selective RET inhibitors such as pralsetinib (BLU-667) and selpercatinib (LOXO-292) have been developed in clinical trials, with selpercatinib recently approved by the Food and Drug Administration (FDA). The results of these trials showed marked and durable antitumour activity and manageable toxicity profiles in patients with RET-altered tumours. The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group (TR and PM WG) launched a collaborative project to review the available methods for the detection of RET gene alterations, their potential applications and strategies for the implementation of a rational approach for the detection of RET fusion genes and mutations in human malignancies. We present here recommendations for the routine clinical detection of targetable RET rearrangements and mutations.

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.

Stable gene expression for normalisation and single-sample scoring

Gene expression signatures have been critical in defining the molecular phenotypes of cells, tissues, and patient samples. Their most notable and widespread clinical application is stratification of breast cancer patients into molecular (PAM50) subtypes. The cost and relatively large amounts of fresh starting material required for whole-transcriptome sequencing has limited clinical application of thousands of existing gene signatures captured in repositories such as the Molecular Signature Database. We identified genes with stable expression across a range of abundances, and with a preserved relative ordering across thousands of samples, allowing signature scoring and supporting general data normalisation for transcriptomic data. Our new method, stingscore, quantifies and summarises relative expression levels of signature genes from individual samples through the inclusion of these ‘stably-expressed genes’. We show that our list of stable genes has better stability across cancer and normal tissue data than previously proposed gene sets. Additionally, we show that signature scores computed from targeted transcript measurements using stingscore can predict docetaxel response in breast cancer patients. This new approach to gene expression signature analysis will facilitate the development of panel-type tests for gene expression signatures, thus supporting clinical translation of the powerful insights gained from cancer transcriptomic studies.

A novel DNA damage response signature of IDH-mutant grade II and grade III astrocytoma at transcriptional level

PURPOSE

The WHO classification for IDH-mutant grade II and grade III astrocytoma may not be as prognostically meaningful as expected. We aimed to develop a novel classification system based on the DNA damage response signature.

METHODS

We developed the gene signature of DNA damage response with 115 samples from The Cancer Genome Atlas (TCGA) database. The dataset from Chinese Glioma Genome Atlas (CGGA) database with 41 samples was used as the validation set. Lasso Cox regression model was applied for selection of the best signature. Gene set enrichment analysis (GSEA) and gene ontology (GO) analysis were implemented to reveal its biological phenotype.

RESULTS

A two-gene DNA damage response signature (RAD18, MSH2) was developed using the lasso Cox regression model based on the TCGA dataset. Its prognostic efficiency was validated in the CGGA cohort. The result of Cox regression analysis showed that the signature has a better predictive accuracy than the WHO grade. The risk score was an independent prognostic factor for the overall survival of the IDH-mutant grade II and grade III astrocytoma. GSEA and GO analysis confirmed enhanced processes related to DNA damage response in high-risk group.

CONCLUSION

We developed a two-gene signature which can effectively predict the prognosis of patients with IDH-mutant grade II and grade III astrocytoma. It suggests a novel classification of astrocytoma with better prognostic accuracy based on the expression of DNA damage response genes.