A Comparison of RNA-Seq Results from Paired Formalin-Fixed Paraffin-Embedded and Fresh-Frozen Glioblastoma Tissue Samples

Transcriptomics and epigenomics datasets of primary brain cancers in formalin-fixed paraffin embedded format

The access of public omics-based datasets is of paramount importance in brain cancer research as allows the proposal and validation of both biomarkers and therapeutic targets in gliomas, especially in the most prevalent and aggressive glioblastomas. Taking profit of current advances in next generation sequencing and DNA methylation profiling, we have created datasets from approximately 150 formalin-fixed paraffin embedded (FFPE) tumours. These datasets enable for the first time integrative transcriptional and epigenetics studies in a context that consider the degradation and fixation-derived chemical alterations of the most extended archiving format in hospitals, and provide an independent cohort from current public databases for further validation of putative novel biomarkers. Alongside with the most profusely known glioblastomas, astrocytomas and oligodendrogliomas, we have also included for comparison purposes few examples of rare tumours that are often neglected in brain cancer research. Taken together, we provide a valuable tool to explore combined gene expression and DNA methylation patterns in the study of gliomas and glioneuronal tumours.

Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets

Molecular subtypes, such as defined by The Cancer Genome Atlas (TCGA), delineate a cancer's underlying biology, bringing hope to inform a patient's prognosis and treatment plan. However, most approaches used in the discovery of subtypes are not suitable for assigning subtype labels to new cancer specimens from other studies or clinical trials. Here, we address this barrier by applying five different machine learning approaches to multi-omic data from 8,791 TCGA tumor samples comprising 106 subtypes from 26 different cancer cohorts to build models based upon small numbers of features that can classify new samples into previously defined TCGA molecular subtypes-a step toward molecular subtype application in the clinic. We validate select classifiers using external datasets. Predictive performance and classifier-selected features yield insight into the different machine-learning approaches and genomic data platforms. For each cancer and data type we provide containerized versions of the top-performing models as a public resource.

The Potential of Single-Transcription Factor Gene Expression by RT-qPCR for Subtyping Small Cell Lung Cancer

Complex RNA-seq signatures involving the transcription factors ASCL1, NEUROD1, and POU2F3 classify Small Cell Lung Cancer (SCLC) into four subtypes: SCLC-A, SCLC-N, SCLC-P, and SCLC-I (triple negative or inflamed). Preliminary studies suggest that identifying these subtypes can guide targeted therapies and potentially improve outcomes. This study aims to evaluate whether the expression levels of these three key transcription factors can effectively classify SCLC subtypes, comparable to the use of individual antibodies in immunohistochemical (IHC) analysis of formalin-fixed, paraffin-embedded (FFPE) tumor samples. We analyzed preclinical models of increasing complexity, including eleven human and five mouse SCLC cell lines, six patient-derived xenografts (PDXs), and two circulating tumor cell (CTC)-derived xenografts (CDXs) generated in our laboratory. RT-qPCR conditions were established to detect the expression levels of ASCL1, NEUROD1, and POU2F3. Additionally, protein-level analysis was performed using Western blot for cell lines and IHC for FFPE samples of PDX and CDX tumors, following our experience with patient tumor samples from the CANTABRICO trial (NCT04712903). We found that the analyzed SCLC cell line models predominantly expressed ASCL1, NEUROD1, and POU2F3, or showed no expression, as identified by RT-qPCR, consistently matching the previously assigned subtypes for each cell line. The classification of PDX and CDX models demonstrated consistency between RT-qPCR and IHC analyses of the transcription factors. Our results show that single-gene analysis by RT-qPCR from FFPE-extracted RNA simplifies SCLC subtype classification. This approach provides a cost-effective alternative to IHC staining or expensive multi-gene RNA sequencing panels, making SCLC subtyping more accessible for both preclinical research and clinical applications.

RNAscope Multiplex FISH Signal Assessment in FFPE and Fresh Frozen Tissues: The Effect of Archival Duration on RNA Expression

Formalin-fixed paraffin-embedded tissue (FFPET), which is the most widely used pathology archive, usually has low-quality DNA and RNA due to extensive nucleic acid crosslinking. RNA fluorescence in situ hybridization (RNA-FISH) has been increasingly utilized in research and clinical settings to diagnose disease pathology. In this study, the effect of RNA degradation over archival time on RNA-FISH signals in FFPET and fresh frozen tissue (FFT) was systematically assessed. RNAscope multiplex fluorescent assay with the four house-keeping-gene (HKG) probes UBC, PPIB, POLR2A, and HPRT1 was performed on 62 archived breast cancer samples (30 FFPETs and 32 FFTs). As expected, the number of RNAscope signals in FFPETs is lower than in FFTs in an archival duration-dependent fashion. The RNA degradation in FFPETs is most pronounced in high-expressor HKGs, UBC and PPIB, than in low-to-moderate expressors POLR2A and HPRT1 (p<0.0001). Analysis of RNA expression over time showed that PPIB, which has the highest signal, was the most degraded in both adjusted transcript and H-score quantification methods (R2 = 0.35 and R2 = 0.33, respectively). This proves that although the RNAscope probes are designed to detect fragmented RNA, performing a sample quality check using HKGs is strongly recommended to ensure accurate results.

A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues

Consensus Molecular Subtype (CMS) classification of colorectal cancer (CRC) tissues is complicated by RNA degradation upon formalin-fixed paraffin-embedded (FFPE) preservation. Here, we present an FFPE-curated CMS classifier. The CMSFFPE classifier was developed using genes with a high transcript integrity in FFPE-derived RNA. We evaluated the classification accuracy in two FFPE-RNA datasets with matched fresh-frozen (FF) RNA data, and an FF-derived RNA set. An FFPE-RNA application cohort of metastatic CRC patients was established, partly treated with anti-EGFR therapy. Key characteristics per CMS were assessed. Cross-referenced with matched benchmark FF CMS calls, the CMSFFPE classifier strongly improved classification accuracy in two FFPE datasets compared with the original CMSClassifier (63.6% versus 40.9% and 83.3% versus 66.7%, respectively). We recovered CMS-specific recurrence-free survival patterns (CMS4 versus CMS2: hazard ratio 1.75, 95% CI 1.24-2.46). Key molecular and clinical associations of the CMSs were confirmed. In particular, we demonstrated the predictive value of CMS2 and CMS3 for anti-EGFR therapy response (CMS2&3: odds ratio 5.48, 95% CI 1.10-27.27). The CMSFFPE classifier is an optimized FFPE-curated research tool for CMS classification of clinical CRC samples.

Effect of Different Staining Methods on Brain Cryosections

Staining frozen sections is often required to distinguish cell types for spatial transcriptomic studies of the brain. The impact of the staining methods on the RNA integrity of the cells becomes one of the limitations of spatial transcriptome technology with microdissection. However, there is a lack of systematic comparisons of different staining modalities for the pretreatment of frozen sections of brain tissue as well as their effects on transcriptome sequencing results. In this study, four different staining methods were analyzed for their effect on RNA integrity in frozen sections of brain tissue. Subsequently, differences in RNA quality in frozen sections under different staining conditions and their impact on transcriptome sequencing results were assessed by RNA-seq. As one of the most commonly used methods for staining pathological sections, HE staining seriously affects the RNA quality of frozen sections of brain tissue. In contrast, the homemade cresyl violet staining method developed in this study has the advantages of short staining time, low cost, and less RNA degradation. The homemade cresyl violet staining proposed in this study can be applied instead of HE staining as an advance staining step for transcriptome studies in frozen sections of brain tissue. In the future, this staining method may be suitable for wide application in brain-related studies of frozen tissue sections. Moreover, it is expected to become a routine step for staining cells before sampling in brain science.

snRNAs from Radical Prostatectomy Specimens Have the Potential to Serve as Prognostic Factors for Clinical Recurrence after Biochemical Recurrence in Patients with High-Risk Prostate Cancer

In patients with high-risk prostate cancer (HRPC) after radical prostatectomy (RP), biochemical recurrence (BCR) increases the risk of distant metastasis. Accordingly, additional prognostic biomarkers are required to identify the subpopulation of patients with HRPC who develop clinical recurrence (CR) after BCR. The objective of this study was to identify biomarkers in formalin-fixed paraffin-embedded (FFPE) RP samples that are prognostic for CR in patients with HRPC who experience BCR after RP (post-RP BCR). First, we performed a preliminary RNA sequencing analysis to comprehensively profile RNA expression in FFPE RP samples obtained from patients with HRPC who developed CR after post-RP BCR and found that many snRNAs were very abundant in preserved FFPE samples. Subsequently, we used quantitative polymerase chain reaction (qPCR) to compare the expression levels of highly abundant snRNAs in FFPE RP samples from patients with HRPC with and without CR after post-RP BCR (21 CR patients and 46 non-CR patients who had more than 5 years of follow-up after BCR). The qPCR analysis revealed that the expression levels of snRNA RNU1-1/1-2 and RNU4-1 were significantly higher in patients with CR than in patients without CR. These snRNAs were significantly correlated with clinical recurrence-free survival (RFS) in patients with HRPC who experienced post-RP BCR. Furthermore, snRNA RNU1-1/1-2 could serve as an independent prognostic factor for clinical RFS in post-RP BCR of HRPC cases where known prognostic factors (e.g., Gleason score) cannot distinguish between CR and non-CR patients. Our findings provide new insights into the involvement of snRNAs in prostate cancer progression.

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

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

Comparison of LIRADS 5 Image Guided Core Biopsy Derived From Formalin Fixed and Frozen Tissue Cores for Radiogenomics and Radioproteomics Analysis in Well, Moderate and Poorly Differentiated Hepatocellular Carcinoma

The aim of this pilot study is to evaluate and compare the quality of the genomics and proteomics data obtained from paired Formalin Fixed Paraffin Embedded (FFPE) and frozen (FF) tissue percutaneous core biopsies of Liver Imaging Reporting and Data System 5 (LIRADS 5) hepatocellular carcinoma (HCC) of varying histological grades. The preliminary data identified differentially expressed proteins and genes in poor, moderate and well differentiated HCC biopsies, with a greater efficacy in fresh frozen samples. The data offered valuable insights into the characteristics and suitability of samples for future studies.

Optimization of FFPE preparation and identification of gene attributes associated with RNA degradation

Formalin-fixed paraffin-embedded (FFPE) tissues are widely available specimens for clinical studies. However, RNA degradation in FFPE tissues often restricts their utility. In this study, we determined optimal FFPE preparation conditions, including tissue ischemia at 4°C (<48 h) or 25°C for a short time (0.5 h), 48-h fixation at 25°C and sampling from FFPE scrolls instead of sections. Notably, we observed an increase in intronic reads and a significant change in gene rank based on expression level in the FFPE as opposed to fresh-frozen (FF) samples. Additionally, we found that more reads were mapped to genes associated with chemical stimulus in FFPE samples. Furthermore, we demonstrated that more degraded genes in FFPE samples were enriched in genes with short transcripts and high free energy. Besides, we found 40 housekeeping genes exhibited stable expression in FF and FFPE samples across various tissues. Moreover, our study showed that FFPE samples yielded comparable results to FF samples in dimensionality reduction and pathway analyses between case and control samples. Our study established the optimal conditions for FFPE preparation and identified gene attributes associated with degradation, which would provide useful clues for the utility of FFPE tissues in clinical practice and research.

Chromogenic in situ hybridization reveals specific expression pattern of long non-coding RNA DRAIC in formalin-fixed paraffin-embedded specimen

Long non-coding RNA (lncRNA) plays an important role in the regulation of gene expression in normal and cancer cells. We previously discovered a novel tumor-suppressive lncRNA, DRAIC, in prostate cancer cells. Subsequent studies have demonstrated that DRAIC is dysregulated in various malignancies and exhibits a tumor-suppressive or pro-oncogenic function. However, details regarding its expression pattern in normal and cancerous tissues remain largely unknown. In this study, we performed chromogenic in situ hybridization (CISH) using RNAscope technology to assess DRAIC expression in formalin-fixed paraffin-embedded (FFPE) specimens. In the neuroendocrine-differentiated cancer cell line VMRC-LCD, CISH revealed a diffuse localization of DRAIC in the cytoplasm as well as specific accumulation in the nuclear compartment. DRAIC expression was comprehensively analyzed using tissue microarrays containing 89 normal and 155 tumor tissue samples. DRAIC was weakly expressed in normal epithelial cells of the colon, bronchiole, kidney, prostate, and testis. Conversely, DRAIC was moderately to highly expressed in some cancer tissues, including prostate adenocarcinoma, invasive ductal carcinoma of the breast, neuroendocrine carcinoma of the esophagus, lung adenocarcinoma, and small cell lung carcinoma. While DRAIC knockdown did not affect VMRC-LCD cellular viability and invasive ability, gene expression related to the neuroendocrine and cancer-related pathways was altered. Our expression analysis revealed the specific expression pattern of DRAIC in normal and cancerous FFPE tissues. The results presented here may lead to the elucidation of additional novel functions of DRAIC.

A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups

Surgical resection represents the standard of care for people with newly diagnosed diffuse gliomas, and the neuropathological and molecular profile of the resected tissue guides clinical management and forms the basis for research. The Response Assessment in Neuro-Oncology (RANO) consortium is an international, multidisciplinary effort that aims to standardise research practice in neuro-oncology. These recommendations represent a multidisciplinary consensus from the four RANO groups: RANO resect, RANO recurrent glioblastoma, RANO radiotherapy, and RANO/PET for a standardised workflow to achieve a representative tumour evaluation in a disease characterised by intratumoural heterogeneity, including recommendations on which tumour regions should be surgically sampled, how to define those regions on the basis of preoperative imaging, and the optimal sample volume. Practical recommendations for tissue sampling are given for people with low-grade and high-grade gliomas, as well as for people with newly diagnosed and recurrent disease. Sampling of liquid biopsies is also addressed. A standardised workflow for subsequent handling of the resected tissue is proposed to avoid information loss due to decreasing tissue quality or insufficient clinical information. The recommendations offer a framework for prospective biobanking studies.

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

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

Quantitative analysis of lncRNA in formalin-fixed paraffin-embedded tissues of oral squamous cell carcinoma

The study evaluated expression profiles of few regulatory lncRNAs in oral squamous cell carcinoma and normal mucosa adjacent to oral cancer using paired fresh frozen and formalin-fixed paraffin-embedded (FFPE) tissues stored at a different duration of time (1-5 years) using real-time quantitative PCR. The quantity and quality of total RNA isolated from FFPE tissues was less compared with that of fresh frozen tissues, which resulted in a noncorrelation of quantification cycle values. Following normalization, the expression of lncRNAs in the paired tissues did not differ significantly. The differential expression of the lncRNAs in the study was consistent with The Cancer Genome Atlas head and neck squamous cell carcinoma database. The study findings demonstrate the possibility of performing accurate quantitative analysis of lncRNAs using short amplicons and standardized real-time quantitative PCR assays in oral squamous cell carcinoma FFPE samples.

Multi-omic approach identifies hypoxic tumor-associated myeloid cells that drive immunobiology of high-risk pediatric ependymoma

Ependymoma (EPN) is a devastating childhood brain tumor. Single-cell analyses have illustrated the cellular heterogeneity of EPN tumors, identifying multiple neoplastic cell states including a mesenchymal-differentiated subpopulation which characterizes the PFA1 subtype. Here, we characterize the EPN immune environment, in the context of both tumor subtypes and tumor cell subpopulations using single-cell sequencing (scRNAseq, n = 27), deconvolution of bulk tumor gene expression (n = 299), spatial proteomics (n = 54), and single-cell cytokine release assays (n = 12). We identify eight distinct myeloid-derived subpopulations from which a group of cells, termed hypoxia myeloid cells, demonstrate features of myeloid-derived suppressor cells, including IL6/STAT3 pathway activation and wound healing ontologies. In PFA tumors, hypoxia myeloid cells colocalize with mesenchymal-differentiated cells in necrotic and perivascular niches and secrete IL-8, which we hypothesize amplifies the EPN immunosuppressive microenvironment. This myeloid cell-driven immunosuppression will need to be targeted for immunotherapy to be effective in this difficult-to-cure childhood brain tumor.

The impact of mutational clonality in predicting the response to immune checkpoint inhibitors in advanced urothelial cancer

Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment and can result in complete remissions even at advanced stages of the disease. However, only a small fraction of patients respond to the treatment. To better understand which factors drive clinical benefit, we have generated whole exome and RNA sequencing data from 27 advanced urothelial carcinoma patients treated with anti-PD-(L)1 monoclonal antibodies. We assessed the influence on the response of non-synonymous mutations (tumor mutational burden or TMB), clonal and subclonal mutations, neoantigen load and various gene expression markers. We found that although TMB is significantly associated with response, this effect can be mostly explained by clonal mutations, present in all cancer cells. This trend was validated in an additional cohort. Additionally, we found that responders with few clonal mutations had abnormally high levels of T and B cell immune markers, suggesting that a high immune cell infiltration signature could be a better predictive biomarker for this subset of patients. Our results support the idea that highly clonal cancers are more likely to respond to ICI and suggest that non-additive effects of different signatures should be considered for predictive models.

Survivin Expression in Luminal Breast Cancer and Adjacent Normal Tissue for Immuno-Oncology Applications

Survivin (BIRC5) is a tumor-associated antigen (TAA) overexpressed in various tumors but present at low to undetectable levels in normal tissue. Survivin is known to have a high expression in breast cancer (e.g., Ductal Carcinoma in situ (DCIS) and triple negative breast cancer). Previous studies have not compared survivin expression levels in DCIS tumor samples to levels in adjacent, normal breast tissue from the same patient. To ensure the effective use of survivin as a target for T cell immunotherapy of breast cancer, it is essential to ascertain the varying levels of survivin expression between DCIS tumor tissue samples and the adjacent normal breast tissue taken from the same patient simultaneously. Next-generation sequencing of RNA (RNA-seq) in normal breast tissue and tumor breast tissue from five women presenting with DCIS for lumpectomy was used to identify sequence variation and expression levels of survivin. The identity of both tumor and adjacent normal tissue samples were corroborated by histopathology. Survivin was overexpressed in human breast tissue tumor samples relative to the corresponding adjacent human normal breast tissue. Wild-type survivin transcripts were the predominant species identified in all tumor tissue sequenced. This study demonstrates upregulated expression of wild type survivin in DCIS tumor tissue versus normal breast tissue taken from the same patient at the same time, and provides evidence that developing selective cytotoxic T lymphocyte (CTL) immunotherapy for DCIS targeting survivin warrants further study.

Next-generation sequencing reveals mitogenome diversity in plasma extracellular vesicles from colorectal cancer patients

BACKGROUND

Recent reports have demonstrated that the entire mitochondrial genome can be secreted in extracellular vesicles (EVs), but the biological attributes of this cell-free mitochondrial DNA (mtDNA) remain insufficiently understood. We used next-generation sequencing to compare plasma EV-derived mtDNA to that of whole blood (WB), peripheral blood mononuclear cells (PBMCs), and formalin-fixed paraffin-embedded (FFPE) tumor tissue from eight rectal cancer patients and WB and fresh-frozen (FF) tumor tissue from eight colon cancer patients.

METHODS

Total DNA was isolated before the mtDNA was enriched by PCR with either two primer sets generating two long products or multiple primer sets (for the FFPE tumors), prior to the sequencing. mtDNA diversity was assessed as the total variant number, level of heteroplasmy (mutant mtDNA copies mixed with wild-type copies), variant distribution within the protein-coding genes, and the predicted functional effect of the variants in the different sample types. Differences between groups were compared by paired Student's t-test or ANOVA with Dunnett's multiple comparison tests when comparing matched samples from patients. Mann-Whitney U test was used when comparing differences between the cancer types and patient groups. Pearson correlation analysis was performed.

RESULTS

In both cancer types, EV mtDNA presented twice as many variants and had significantly more low-level heteroplasmy than WB mtDNA. The EV mtDNA variants were clustered in the coding regions, and the proportion of EV mtDNA variants that were missense mutations (i.e., estimated to moderately affect the mitochondrial protein function) was significantly higher than in WB and tumor tissues. Nonsense mutations (i.e., estimated to highly affect the mitochondrial protein function) were only observed in the tumor tissues and EVs.

CONCLUSION

Taken together, plasma EV mtDNA in CRC patients exhibits a high degree of diversity.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01816607 . Registered 22 March 2013.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

Multiomics technologies for comprehensive tumor microenvironment analysis in triple-negative breast cancer under neoadjuvant chemotherapy

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes and is characterized by abundant infiltrating immune cells within the microenvironment. As standard care, chemotherapy remains the fundamental neoadjuvant treatment in TNBC, and there is increasing evidence that supplementation with immune checkpoint inhibitors may potentiate the therapeutic efficiency of neoadjuvant chemotherapy (NAC). However, 20-60% of TNBC patients still have residual tumor burden after NAC and require additional chemotherapy; therefore, it is critical to understand the dynamic change in the tumor microenvironment (TME) during treatment to help improve the rate of complete pathological response and long-term prognosis. Traditional methods, including immunohistochemistry, bulk tumor sequencing, and flow cytometry, have been applied to elucidate the TME of breast cancer, but the low resolution and throughput may overlook key information. With the development of diverse high-throughput technologies, recent reports have provided new insights into TME alterations during NAC in four fields, including tissue imaging, cytometry, next-generation sequencing, and spatial omics. In this review, we discuss the traditional methods and the latest advances in high-throughput techniques to decipher the TME of TNBC and the prospect of translating these techniques to clinical practice.

Diagnostic classification of childhood cancer using multiscale transcriptomics

The causes of pediatric cancers' distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types.

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

The use of fresh tissue for molecular studies is preferred but often impossible. Instead, frozen or formalin-fixed, paraffin-embedded (FFPE) tissues are widely used and constitute valuable resources for retrospective studies. We assessed the utility of cardiac tissue stored in different ways for gene expression analyses by whole transcriptome sequencing of paired fresh, frozen, and FFPE tissues. RNA extracted from FFPE was highly degraded. Sequencing of RNA from FFPE tissues yielded higher proportions of intronic and intergenic reads compared to RNA from fresh and frozen tissues. The global gene expression profiles varied with the storage conditions, particularly mitochondrial and long non-coding RNAs. However, we observed high correlations among protein-coding transcripts (ρ > 0.94) with the various storage conditions. We did not observe any significant storage effect on the allele-specific gene expression. However, FFPE had statistically significantly (p < 0.05) more discordant variant calls compared to fresh and frozen tissue. In conclusion, we found that frozen and FFPE tissues can be used for reliable gene expression analyses, provided that proper quality control is performed and caution regarding the technical variability is withheld.

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.

Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases

Neurodegenerative diseases affect millions of people worldwide and there are currently no cures. Two types of common neurodegenerative diseases are Alzheimer's (AD) and Parkinson's disease (PD). Single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq) have become powerful tools to elucidate the inherent complexity and dynamics of the central nervous system at cellular resolution. This technology has allowed the identification of cell types and states, providing new insights into cellular susceptibilities and molecular mechanisms underlying neurodegenerative conditions. Exciting research using high throughput scRNA-seq and snRNA-seq technologies to study AD and PD is emerging. Herein we review the recent progress in understanding these neurodegenerative diseases using these state-of-the-art technologies. We discuss the fundamental principles and implications of single-cell sequencing of the human brain. Moreover, we review some examples of the computational and analytical tools required to interpret the extensive amount of data generated from these assays. We conclude by highlighting challenges and limitations in the application of these technologies in the study of AD and PD.

Exosome based analysis for Space Associated Neuro-Ocular Syndrome and health risks in space exploration

Molecular profiling to characterize the effects of environmental exposures is important from the human health and performance as well as the occupational medicine perspective in space exploration. We have developed a novel exosome-based platform that allows profiling of biological processes in the body from a variety of body fluids. The technology is suitable for diagnostic applications as well as studying the pathophysiology of the Space Associated Neuro-Ocular Syndrome in astronauts and monitoring patients with chronically impaired cerebrospinal fluid drainage or elevated intracranial pressure. In this proof-of-concept, we demonstrate that: (a) exosomes from different biofluids contain a specific population of RNA transcripts; (b) urine collection hardware aboard the ISS is compatible with exosome gene expression technology; (c) cDNA libraries from exosomal RNA can be stored in dry form and at room temperature, representing an interesting option for the creation of longitudinal molecular catalogs that can be stored as a repository for retrospective analysis.

Profiling cell-type specific gene expression in post-mortem human brain samples through laser capture microdissection

The transcriptome of a cell constitutes an essential piece of cellular identity and contributes to the multifaceted complexity and heterogeneity of cell-types within the mammalian brain. Thus, while a wealth of studies have investigated transcriptomic alterations underlying the pathophysiology of diseases of the brain, their use of bulk-tissue homogenates makes it difficult to tease apart whether observed differences are explained by disease state or cellular composition. Cell-type-specific enrichment strategies are, therefore, crucial in the context of gene expression profiling. Laser capture microdissection (LCM) is one such strategy that allows for the capture of specific cell-types, or regions of interest, under microscopic visualization. In this review, we focus on using LCM for cell-type specific gene expression profiling in post-mortem human brain samples. We begin with a discussion of various LCM systems, followed by a walk-through of each step in the LCM to gene expression profiling workflow and a description of some of the limitations associated with LCM. Throughout the review, we highlight important considerations when using LCM with post-mortem human brain samples. Whenever applicable, commercially available kits that have proven successful in the context of LCM with post-mortem human brain samples are described.

In silico validation of RNA-Seq results can identify gene fusions with oncogenic potential in glioblastoma

RNA-Sequencing (RNA-Seq) can identify gene fusions in tumors, but not all these fusions have functional consequences. Using multiple data bases, we have performed an in silico analysis of fusions detected by RNA-Seq in tumor samples from 139 newly diagnosed glioblastoma patients to identify in-frame fusions with predictable oncogenic potential. Among 61 samples with fusions, there were 103 different fusions, involving 167 different genes, including 20 known oncogenes or tumor suppressor genes (TSGs), 16 associated with cancer but not oncogenes or TSGs, and 32 not associated with cancer but previously shown to be involved in fusions in gliomas. After selecting in-frame fusions able to produce a protein product and running Oncofuse, we identified 30 fusions with predictable oncogenic potential and classified them into four non-overlapping categories: six previously described in cancer; six involving an oncogene or TSG; four predicted by Oncofuse to have oncogenic potential; and 14 other in-frame fusions. Only 24 patients harbored one or more of these 30 fusions, and only two fusions were present in more than one patient: FGFR3::TACC3 and EGFR::SEPTIN14. This in silico study provides a good starting point for the identification of gene fusions with functional consequences in the pathogenesis or treatment of glioblastoma.

Consensus Recommendations to Optimize Testing for New Targetable Alterations in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) has historically been associated with a poor prognosis and low 5-year survival, but the use of targeted therapies in NSCLC has improved patient outcomes over the past 10 years. The pace of development of new targeted therapies is accelerating, with the associated need for molecular testing of new targetable alterations. As the complexity of biomarker testing in NSCLC increases, there is a need for guidance on how to manage the fluid standard-of-care in NSCLC, identify pragmatic molecular testing requirements, and optimize result reporting. An expert multidisciplinary working group with representation from medical oncology, pathology, and clinical genetics convened via virtual meetings to create consensus recommendations for testing of new targetable alterations in NSCLC. The importance of accurate and timely testing of all targetable alterations to optimize disease management using targeted therapies was emphasized by the working group. Therefore, the panel of experts recommends that all targetable alterations be tested reflexively at NSCLC diagnosis as part of a comprehensive panel, using methods that can detect all relevant targetable alterations. In addition, comprehensive biomarker testing should be performed at the request of the treating clinician upon development of resistance to targeted therapy. The expert multidisciplinary working group also made recommendations for reporting to improve clarity and ease of interpretation of results by treating clinicians and to accommodate the rapid evolution in clinical actionability of these alterations. Molecular testing of all targetable alterations in NSCLC is the key for treatment decision-making and access to new therapies. These consensus recommendations are intended as a guide to further optimize molecular testing of new targetable alterations.

RNA Instant Quality Check: Alignment-Free RNA-Degradation Detection

With the constant increase of large-scale genomic data projects, automated and high-throughput quality assessment becomes a crucial component of any analysis. Whereas small projects often have a more homogeneous design and a manageable structure allowing for a manual per-sample analysis of quality, large-scale studies tend to be much more heterogeneous and complex. Many quality metrics have been developed to assess the quality of an individual sample on the raw read level. Degradation effects are typically assessed based on the RNA integrity (RIN) score, or on postalignment data. In this study, we show that single commonly used quality criteria such as the RIN score alone are not sufficient to ensure RNA sample quality. We developed a new approach and provide an efficient tool that estimates RNA sample degradation by computing the 5'/3' bias based on all genes in an alignment-free manner. That enables degradation assessment right after data generation and not during the analysis procedure allowing for early intervention in the sample handling process. Our analysis shows that this strategy is fast, robust to annotation and differences in library size, and provides complementary quality information to RIN scores enabling the accurate identification of degraded samples.

Urinary extracellular vesicles contain mature transcriptome enriched in circular and long noncoding RNAs with functional significance in prostate cancer

Long noncoding (lnc)RNAs modulate gene expression alongside presenting unexpected source of neoantigens. Despite their immense interest, their ability to be transferred and control adjacent cells is unknown. Extracellular Vesicles (EVs) offer a protective environment for nucleic acids, with pro and antitumourigenic functions by controlling the immune response. In contrast to extracellular nonvesicular RNA, few studies have addressed the full RNA content within human fluids' EVs and have compared them with their tissue of origin. Here, we performed Total RNA-Sequencing on six Formalin-Fixed-Paraffin-Embedded (FFPE) prostate cancer (PCa) tumour tissues and their paired urinary (u)EVs to provide the first whole transcriptome comparison from the same patients. UEVs contain simplified transcriptome with intron-free cytoplasmic transcripts and enriched lnc/circular (circ)RNAs, strikingly common to an independent 20 patients' urinary cohort. Our full cellular and EVs transcriptome comparison within three PCa cell lines identified a set of overlapping 14 uEV-circRNAs characterized as essential for prostate cell proliferation in vitro and 28 uEV-lncRNAs belonging to the cancer-related lncRNA census (CLC2). In addition, we found 15 uEV-lncRNAs, predicted to encode 768 high-affinity neoantigens, and for which three of the encoded-ORF produced detectable unmodified peptides by mass spectrometry. Our dual analysis of EVs-lnc/circRNAs both in urines' and in vitro's EVs provides a fundamental resource for future uEV-lnc/circRNAs phenotypic characterization involved in PCa.

Evaluation of 41 single nucleotide polymorphisms in canine diffuse large B-cell lymphomas using MassARRAY

Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of lymphoma in dogs with a multicentric form. This study aimed to assemble 41 variants of the previously reported genes and to investigate these variants in canine DLBCL using the Agena MassARRAY platform. These variants were chosen based on the high prevalence observed in canine B- and T-cell lymphomas, their significance for target therapy, and compatibility for multiplex PCR amplification. Lymph node biopsy was performed from 60 dogs with B-cell lymphoma comprising 47 purebred and 13 crossbred dogs. All dogs presented single nucleotide polymorphisms (SNPs) at HYAL4 and SATB1 genes. The lesser mutual SNPs were observed at SEL1L, excluding a cocker spaniel, and c-Kit, with the exception of a pug and a French bulldog. Even though no statistical association was noted between each SNP and dog breed, purebreds were 3.88 times more likely to have a SNP at FLT3 rs852342480 (95%CI 0.50–45.03, p = 0.26), 3.64 times at TRAF3 F306X (95%CI 0.58–42.50, p = 0.43) and 2.66 times at TRAF3 E303EX (95%CI 0.56–13.12, p = 0.31). Also, DLBCL dogs (CHOP-based treatment) with c-Kit T425= had a poorer prognosis with shorter median overall survival times (OST) than dogs with the wild type. Dogs treated with COP chemotherapy and contained 3–5 variants at SEL1L were associated with decreased median OST. Therefore, this SNP’s lymphoma panel provides valuable information that we can use to outline a prognosis and develop a treatment plan for the targeted therapy of each dog.

Transcriptional Heterogeneity and the Microbiome of Cutaneous T-Cell Lymphoma

Cutaneous T-Cell Lymphomas (CTCL) presents with substantial clinical variability and transcriptional heterogeneity. In the recent years, several studies paved the way to elucidate aetiology and pathogenesis of CTCL using sequencing methods. Several T-cell subtypes were suggested as the source of disease thereby explaining clinical and transcriptional heterogeneity of CTCL entities. Several differentially expressed pathways could explain disease progression. However, exogenous triggers in the skin microenvironment also seem to affect CTCL status. Especially Staphylococcus aureus was shown to contribute to disease progression. Only little is known about the complex microbiome patterns involved in CTCL and how microbial shifts might impact this malignancy. Nevertheless, first hints indicate that the microbiome might at least in part explain transcriptional heterogeneity and that microbial approaches could serve in diagnosis and prognosis. Shaping the microbiome could be a treatment option to maintain stable disease. Here, we review current knowledge of transcriptional heterogeneity of and microbial influences on CTCL. We discuss potential benefits of microbial applications and microbial directed therapies to aid patients with CTCL burden.

RNA-Seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq™ 2.0 assay

Whole transcriptome sequencing (RNA-Seq) has gained prominence for the detection of fusions in solid tumors. Here, we describe the development and validation of an in-house RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, in formalin-fixed paraffin-embedded (FFPE) specimens, using seventy tumor samples with varying fusion status. Conditions were optimized for RNA input of 50 ng, shown to be adequate to call known fusions at as low as 20% neoplastic content. Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. Performance analysis of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility. This clinically developed and validated RNA-Seq-based approach for fusion detection in FPPE samples was shown to be on par if not superior to off-the-shelf commercially offered assays. With gene fusions implicated in a variety of cancer types, offering high-quality, low-cost molecular testing services for FFPE specimens will serve to best benefit the patient and the advancement of precision medicine in molecular oncology. KEY MESSAGES: A custom RNA-Seq-based test system (FusionSeq™ 2.0) for the detection of clinically actionable gene fusions, Evaluation of assay performance between FFPE and fresh-frozen (FF) tissues exhibited little to no difference in fusion calling capability. The assay can be performed with low RNA input and neoplastic content. Performance characteristics of the assay validation data determined 100% accuracy, sensitivity, specificity, and reproducibility.

Application of the 3' mRNA-Seq using unique molecular identifiers in highly degraded RNA derived from formalin-fixed, paraffin-embedded tissue

Background

Archival formalin-fixed, paraffin-embedded (FFPE) tissue samples with clinical and histological data are a singularly valuable resource for developing new molecular biomarkers. However, transcriptome analysis remains challenging with standard mRNA-seq methods as FFPE derived-RNA samples are often highly modified and fragmented. The recently developed 3′ mRNA-seq method sequences the 3′ region of mRNA using unique molecular identifiers (UMI), thus generating gene expression data with minimal PCR bias. In this study, we evaluated the performance of 3′ mRNA-Seq using Lexogen QuantSeq 3′ mRNA-Seq Library Prep Kit FWD with UMI, comparing with TruSeq Stranded mRNA-Seq and RNA Exome Capture kit. The fresh-frozen (FF) and FFPE tissues yielded nucleotide sizes range from 13 to > 70% of DV200 values; input amounts ranged from 1 ng to 100 ng for validation.

Results

The total mapped reads of QuantSeq 3′ mRNA-Seq to the reference genome ranged from 99 to 74% across all samples. After PCR bias correction, 3 to 56% of total sequenced reads were retained. QuantSeq 3′ mRNA-Seq data showed highly reproducible data across replicates in Universal Human Reference RNA (UHR, R > 0.94) at input amounts from 1 ng to 100 ng, and FF and FFPE paired samples (R = 0.92) at 10 ng. Severely degraded FFPE RNA with ≤30% of DV200 value showed good concordance (R > 0.87) with 100 ng input. A moderate correlation was observed when directly comparing QuantSeq 3′ mRNA-Seq data with TruSeq Stranded mRNA-Seq (R = 0.78) and RNA Exome Capture data (R > 0.67).

Conclusion

In this study, QuantSeq 3′ mRNA-Seq with PCR bias correction using UMI is shown to be a suitable method for gene quantification in both FF and FFPE RNAs. 3′ mRNA-Seq with UMI may be applied to severely degraded RNA from FFPE tissues generating high-quality sequencing data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08068-1.

Comprehensive analysis of oncogenic fusions in mismatch repair deficient colorectal carcinomas by sequential DNA and RNA next generation sequencing

Background

Colorectal carcinoma (CRC) harboring oncogenic fusions has been reported to be highly enriched in mismatch repair deficient (dMMR) tumors with MLH1 hypermethylation (MLH1^me+) and wild-type BRAF and RAS. In this study, dMMR CRCs were screened for oncogene fusions using sequential DNA and RNA next generation sequencing (NGS).

Results

Comprehensive analysis of fusion variants, genetic profiles and clinicopathological features in fusion-positive dMMR CRCs was performed. Among 193 consecutive dMMR CRCs, 39 cases were identified as MLH1^me+BRAF/RAS wild-type. Eighteen fusion-positive cases were detected by DNA NGS, all of which were MLH1^me+ and BRAF/RAS wild-type. RNA NGS was sequentially conducted in the remaining 21 MLH1^me+BRAF/RAS wild-type cases lacking oncogenic fusions by DNA NGS, and revealed four additional fusions, increasing the proportion of fusion-positive tumors from 46% (18/39) to 56% (22/39) in MLH1^me+BRAF/RAS wild-type dMMR cases. All 22 fusions were found to involve RTK-RAS pathway. Most fusions affected targetable receptor tyrosine kinases, including NTRK1(9/22, 41%), NTRK3(5/22, 23%), ALK(3/22, 14%), RET(2/22, 9%) and MET(1/22, 5%), whilst only two fusions affected mitogen-activated protein kinase cascade components BRAF and MAPK1, respectively. RNF43 was identified as the most frequently mutated genes, followed by APC, TGFBR2, ATM, BRCA2 and FBXW7. The vast majority (19/22, 86%) displayed alterations in key WNT pathway components, whereas none harbored additional mutations in RTK-RAS pathway. In addition, fusion-positive tumors were typically diagnosed in elder patients and predominantly right-sided, and showed a significantly higher preponderance of hepatic flexure localization (P < 0.001) and poor differentiation (P = 0.019), compared to fusion-negative MLH1^me+ CRCs.

Conclusions

We proved that sequential DNA and RNA NGS was highly effective for fusion detection in dMMR CRCs, and proposed an optimized practical fusion screening strategy. We further revealed that dMMR CRCs harboring oncogenic fusion was a genetically and clinicopathologically distinctive subgroup, and justified more precise molecular subtyping for personalized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03108-6.

Transcriptome sequencing of archived lymphoma specimens is feasible and clinically relevant using exome capture technology

Formalin-fixed, paraffin-embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture-based RNA-sequencing protocol to explore global gene expression in paired fresh-frozen (FF) and FFPE samples from 16 diffuse large B-cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome (r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell-of-origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell-of-origin classification of DLBCL samples.

Safety and efficacy of depatuxizumab mafodotin in Japanese patients with malignant glioma: A nonrandomized, phase 1/2 trial

INTELLANCE‐J was a phase 1/2 study of a potent antibody‐drug conjugate targeting epidermal growth factor receptor (EGFR), depatuxizumab mafodotin (Depatux‐M), as a second‐ or first‐line therapy, alone or combined with chemotherapy or chemoradiotherapy in 53 Japanese patients with World Health Organization (WHO) grade III/IV glioma. In second‐line arms, patients with EGFR‐amplified recurrent WHO grade III/IV glioma received Depatux‐M plus chemotherapy (temozolomide) or Depatux‐M alone regardless of EGFR status. In first‐line arms, patients with newly diagnosed WHO grade III/IV glioma received Depatux‐M plus chemoradiotherapy. The study was halted following lack of survival benefit with first‐line Depatux‐M in the global trial INTELLANCE‐1. The primary endpoint was 6‐month progression‐free survival (PFS) in patients with EGFR‐amplified tumors receiving second‐line Depatux‐M plus chemotherapy. Common nonocular treatment‐emergent adverse events (TEAEs) with both second‐line and first‐line Depatux‐M included lymphopenia (42%, 33%, respectively), thrombocytopenia (39%, 47%), alanine aminotransferase increase (29%, 47%), and aspartate aminotransferase increase (24%, 60%); incidence of grade ≥3 TEAEs was 66% and 53%, respectively. Ocular side effects (OSEs) occurred in 93% of patients receiving second‐line Depatux‐M plus chemotherapy and all patients receiving second‐line Depatux‐M alone or first‐line Depatux‐M plus chemoradiotherapy. Most OSEs were manageable with dose modifications and concomitant medications. The 6‐month PFS estimate was 25.6% (95% confidence interval [CI] 11.4‒42.6), and median PFS was 2.1 months (95% CI 1.9‒3.9) with second‐line Depatux‐M plus chemotherapy in the EGFR‐amplified subgroup. This study showed acceptable safety profile of Depatux‐M alone or plus chemotherapy/chemoradiotherapy in Japanese patients with WHO grade III/IV glioma. The study was registered at ClinicalTrials.gov (NCT02590263).

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.

Effect of high variation in transcript expression on identifying differentially expressed genes in RNA-seq analysis

Great efforts have been made on the algorithms that deal with RNA-seq data to enhance the accuracy and efficiency of differential expression (DE) analysis. However, no consensus has been reached on the proper threshold values of fold change and adjusted p-value for filtering differentially expressed genes (DEGs). It is generally believed that the more stringent the filtering threshold, the more reliable the result of a DE analysis. Nevertheless, by analyzing the impact of both adjusted p-value and fold change thresholds on DE analyses, with RNA-seq data obtained for three different cancer types from the Cancer Genome Atlas (TCGA) database, we found that, for a given sample size, the reproducibility of DE results became poorer when more stringent thresholds were applied. No matter which threshold level was applied, the overlap rates of DEGs were generally lower for small sample sizes than for large sample sizes. The raw read count analysis demonstrated that the transcript expression of the same gene in different samples, whether in tumor groups or in normal groups, showed high variations, which resulted in a drastic fluctuation in fold change values and adjustedp-values when different sets of samples were used. Overall, more stringent thresholds did not yield more reliable DEGs due to high variations in transcript expression; the reliability of DEGs obtained with small sample sizes was more susceptible to these variations. Therefore, less stringent thresholds are recommended for screening DEGs. Moreover, large sample sizes should be considered in RNA-seq experimental designs to reduce the interfering effect of variations in transcript expression on DEG identification.

FFPE samples from cavitational ultrasonic surgical aspirates are suitable for RNA profiling of gliomas

During surgical procedures for gliomas, tissue material obtained from cavitational ultrasonic surgical aspirators (CUSAs) is generally discarded but can actually exceed the amount and quality of certain tumour core resections (TCRs). Despite reports indicating the suitability of CUSA-derived material for diagnosis and research, its use is still marginal. We extended these conclusions to formalin-fixed, paraffin-embedded (FFPE) samples, the most common format for archival tumour tissue in anatomical pathology departments, by conducting for the first time RNA-seq analysis in CUSA aspirates. We compared the molecular diagnosis of somatic mutations used in the clinical routine and the gene expression profiles of fixed solid material from CUSA aspirates and TCRs from the same patients in selected gliomas encompassing grades II to IV. Despite the characteristic heterogeneity of gliomas, we found substantial similarities between the corresponding aspirates and TCRs that included transcriptional signatures associated with glioma subtypes. Based on these results, we confirmed that CUSA-fixed biomaterials from glioma surgeries are appropriate for downstream applications and biomarkers screening.

Tumor mutational burden and purity adjustment before and after treatment with temozolomide in 27 paired samples of glioblastoma: a prospective study

Treatment of glioblastoma (GBM) remains a challenging task, with limited treatment options, none offering a cure. Immune therapy has proven effective across different cancers with remarkable response rates. Tumor mutational burden (TMB) is a marker of response, but technical and methodological differences in TMB estimates have made a proper assessment and comparison challenging. Here, we analyzed a prospective collection of paired samples from 35 patients with newly diagnosed GBM, all of whom were wild‐type (WT) for isocitrate dehydrogenase, before and after treatment with radiotherapy and temozolomide. Seven patients (20%) had O6‐methylguanine‐DNA methyltransferase‐methylated tumors. Six patients (17%) had two relapse surgeries, and tissue from all three surgeries was collected. We found that accurate evaluation of TMB was confounded by high variability in the cancer cell fraction of relapse samples. To ameliorate this, we developed a model to adjust for tumor purity based on the relative density distribution of variant allele frequencies in each primary–relapse pair. Additionally, we examined the mutation spectra of shared and private mutations. After tumor purity adjustment, we found TMB comparison reliable in tumors with tumor purity between 15% and 40%, resulting in 27/35 patients (77.1%). TMB remained unchanged from 0.65 mutations per megabase (Mb) to 0.67/Mb before and after treatment, respectively. Examination of the mutation spectra revealed a dominance of C > T transitions at CpG sites in both shared and relapse‐private mutations, consistent with cytosine deamination and the clock‐like mutational signature 1. We present and apply a cellularity correction approach that enables more accurate assessment of TMB in paired tumor samples. We did not find a significant increase in TMB after correcting for cancer cell fraction. Our study raises significant concerns when determining TMB. Although a small sample size, corrected TMB can have a clinical significance when stratifying patients to experimental treatment, for example, immune checkpoint therapy.

"Zooming in" on Glioblastoma: Understanding Tumor Heterogeneity and its Clinical Implications in the Era of Single-Cell Ribonucleic Acid Sequencing

Glioblastoma (GBM) is the most common primary brain malignancy in adults and one of the most aggressive of all human cancers. It is highly recurrent and treatment-resistant, in large part due to its infiltrative nature and inter- and intratumoral heterogeneity. This heterogeneity entails varying genomic landscapes and cell types within and between tumors and the tumor microenvironment (TME). In GBM, heterogeneity is a driver of treatment resistance, recurrence, and poor prognosis, representing a substantial impediment to personalized medicine. Over the last decade, sequencing technologies have facilitated deeper understanding of GBM heterogeneity by "zooming in" progressively further on tumor genomics and transcriptomics. Initial efforts employed bulk ribonucleic acid (RNA) sequencing, which examines composite gene expression of whole tumor specimens. While groundbreaking at the time, this bulk RNAseq masks the crucial contributions of distinct tumor subpopulations to overall gene expression. This work progressed to the use of bulk RNA sequencing in anatomically and spatially distinct tumor subsections, which demonstrated previously underappreciated genomic complexity of GBM. A revolutionary next step forward has been the advent of single-cell RNA sequencing (scRNAseq), which examines gene expression at the single-cell level. scRNAseq has enabled us to understand GBM heterogeneity in unprecedented detail. We review seminal studies in our progression of understanding GBM heterogeneity, with a focus on scRNAseq and the insights that it has provided into understanding the GBM tumor mass, peritumoral space, and TME. We highlight preclinical and clinical implications of this work and consider its potential to impact neuro-oncology and to improve patient outcomes via personalized medicine.

High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

BACKGROUND

RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible.

RESULTS

Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis.

CONCLUSIONS

High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

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.

Transcriptional Differences between Canine Cutaneous Epitheliotropic Lymphoma and Immune-Mediated Dermatoses

Canine cutaneous epitheliotropic T-cell lymphoma (CETL) and immune-mediated T-cell predominant dermatoses (IMD) share several clinical and histopathological features, but differ substantially in prognosis. The discrimination of ambiguous cases may be challenging, as diagnostic tests are limited and may prove equivocal. This study aimed to investigate transcriptional differences between CETL and IMD, as a basis for further research on discriminating diagnostic biomarkers. We performed 100bp single-end sequencing on RNA extracted from formalin-fixed and paraffin-embedded skin biopsies from dogs with CETL and IMD, respectively. DESeq2 was used for principal component analysis (PCA) and differential gene expression analysis. Genes with significantly different expression were analyzed for enriched pathways using two different tools. The expression of selected genes and their proteins was validated by RT-qPCR and immunohistochemistry. PCA demonstrated the distinct gene expression profiles of CETL and IMD. In total, 503 genes were upregulated, while 4986 were downregulated in CETL compared to IMD. RT-qPCR confirmed the sequencing results for 5/6 selected genes tested, while the protein expression detected by immunohistochemistry was not entirely consistent. Our study revealed transcriptional differences between canine CETL and IMD, with similarities to human cutaneous lymphoma. Differentially expressed genes are potential discriminatory markers, but require further validation on larger sample collections.

The Mutational Concordance of Fixed Formalin Paraffin Embedded and Fresh Frozen Gastro-Oesophageal Tumours Using Whole Exome Sequencing

1.

BACKGROUND

The application of massively parallel sequencing has led to the identification of aberrant druggable pathways and somatic mutations within therapeutically relevant genes in gastro-oesophageal cancer. Given the widespread use of formalin-fixed paraffin-embedded (FFPE) samples in the study of this disease, it would be beneficial, especially for the purposes of biomarker evaluation, to assess the concordance between comprehensive exome-wide sequencing data from archival FFPE samples originating from a prospective clinical study and those derived from fresh-frozen material. 2.

METHODS

We analysed whole-exome sequencing data to define the mutational concordance of 16 matched fresh-frozen and FFPE gastro-oesophageal tumours (N = 32) from a prospective clinical study. We assessed DNA integrity prior to sequencing and then identified coding mutations in genes that have previously been implicated in other cancers. In addition, we calculated the mutant-allele heterogeneity (MATH) for these samples. 3.

RESULTS

Although there was increased degradation of DNA in FFPE samples compared with frozen samples, sequencing data from only two FFPE samples failed to reach an adequate mapping quality threshold. Using a filtering threshold of mutant read counts of at least ten and a minimum of 5% variant allele frequency (VAF) we found that there was a high median mutational concordance of 97% (range 80.1-98.68%) between fresh-frozen and FFPE gastro-oesophageal tumour-derived exomes. However, the majority of FFPE tumours had higher mutant-allele heterogeneity (MATH) scores when compared with corresponding frozen tumours (p < 0.001), suggesting that FFPE-based exome sequencing is likely to over-represent tumour heterogeneity in FFPE samples compared to fresh-frozen samples. Furthermore, we identified coding mutations in 120 cancer-related genes, including those associated with chromatin remodelling and Wnt/β-catenin and Receptor Tyrosine Kinase signalling. 4.

CONCLUSIONS

These data suggest that comprehensive genomic data can be generated from exome sequencing of selected DNA samples extracted from archival FFPE gastro-oesophageal tumour tissues within the context of prospective clinical trials.

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.