The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing

STAT5 and STAT3 balance shapes dendritic cell function and tumour immunity

Immune checkpoint blockade (ICB) has transformed cancer therapy1,2. The efficacy of immunotherapy depends on dendritic cell-mediated tumour antigen presentation, T cell priming and activation3,4. However, the relationship between the key transcription factors in dendritic cells and ICB efficacy remains unknown. Here we found that ICB reprograms the interplay between the STAT3 and STAT5 transcriptional pathways in dendritic cells, thereby activating T cell immunity and enabling ICB efficacy. Mechanistically, STAT3 restrained the JAK2 and STAT5 transcriptional pathway, determining the fate of dendritic cell function. As STAT3 is often activated in the tumour microenvironment5, we developed two distinct PROTAC (proteolysis-targeting chimera) degraders of STAT3, SD-36 and SD-2301. STAT3 degraders effectively degraded STAT3 in dendritic cells and reprogrammed the dendritic cell-transcriptional network towards immunogenicity. Furthermore, STAT3 degrader monotherapy was efficacious in treatment of advanced tumours and ICB-resistant tumours without toxicity in mice. Thus, the crosstalk between STAT3 and STAT5 transcriptional pathways determines the dendritic cell phenotype in the tumour microenvironment and STAT3 degraders hold promise for cancer immunotherapy.

Androgen receptor-regulated lncRNA PRCAT71 promotes AR signaling through the interaction with KHSRP in prostate cancer

Mounting evidence indicates that long noncoding RNAs (lncRNAs) play vital roles in tumorigenesis and progression of cancers. However, the functions and regulatory mechanisms of lncRNAs in prostate cancer (PCa) are still largely unknown. In this study, we found an lncRNA, PCa-associated transcript 71 (PRCAT71), highly expressed in metastatic and primary PCa compared to benign prostate tissues. Silencing PRCAT71 inhibited cancerous properties of PCa cells and androgen receptor (AR) signaling. Mechanistically, PRCAT71 acts as a scaffold to recruit K homology (KH)-type splicing regulatory protein (KHSRP) to AR messenger RNA (mRNA) and stabilize AR mRNA, leading to activated AR signaling. KHSRP plays a critical role in PCa progression. PRCAT71 is transcriptionally regulated by AR-driven enhancers, forming a positive regulatory loop between AR and PRCAT71 in PCa. Our study demonstrates a coordinated regulation of AR mRNA by lncRNA PRCAT71 and RNA binding protein KHSRP and provides insight that the PRCAT71-KHSRP-AR axis is a promising therapeutic target for treating PCa.

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.

Laser-capture microdissection for spatial transcriptomics of immunohistochemically detected neurons

We developed a versatile 'IHC/LCM-Seq' method for spatial transcriptomics of immunohistochemically detected neurons collected with laser-capture microdissection (LCM). IHC/LCM-Seq uses aluminon and polyvinyl sulfonic acid for inventive RNA-preserving strategies to maintain RNA integrity in free-floating sections of 4% formaldehyde-fixed brains. To validate IHC/LCM-Seq, we first immunostained and harvested striatal cholinergic interneurons with LCM. RNA preparations were subjected to random primer-based cDNA library preparation and bulk sequencing on the NextSeq Illumina platform. IHC/LCM-Seq detected ∼16,000 transcripts, reaching the sensitivity of a reference 'LCM-Seq method' developed for fluorescently tagged neurons microdissected from lightly formaldehyde-fixed and slide-mounted brain sections of transgenic mice. We successfully used the new IHC/LCM-Seq approach to provide unprecedented insight into the transcriptome of immunohistochemically detected gonadotropin-releasing hormone (GnRH) neurons regulating reproduction. The ∼13,000 to 14,000 transcripts identified in GnRH neurons of adult male rats and mice encoded 28 proteins implicated previously in human infertility, 35 neuropeptides, 34 nuclear receptors, and 164 G protein-coupled receptors. Functional experiments using slice electrophysiology established that the heavy Ntsr2 expression conveys a strong excitatory action of neurotensin on GnRH neurons. As an unexpected species difference, we found that GnRH neurons exclusively expressed estrogen receptor-β in rats and against the current consensus, the alpha estrogen receptor isoform in mice. The IHC/LCM-Seq technique we are reporting is a highly sensitive and accurate bulk sequencing approach to characterize the transcriptome landscape of immunohistochemically labeled neurons, including neuroendocrine GnRH cells. This method is readily applicable to any species, opening new perspectives also for future studies of the post mortem human brain.

Genomic Landscape of Superficial Malignant Peripheral Nerve Sheath Tumor

Superficial malignant peripheral nerve sheath tumors (SF-MPNSTs) are rare cancers and can be difficult to distinguish from spindle cell (SCM) or desmoplastic (DM) melanomas. Their biology is poorly understood. We performed whole-exome sequencing and RNA sequencing (RNA-seq) on SF-MPNST (n = 8) and compared them with cases of SCM (n = 7), DM (n = 8), and deep MPNST (D-MPNST, n = 8). Immunohistochemical staining for H3K27me3 and PRAME was also performed. SF-MPNST demonstrated intermediate features between D-MPNST and melanoma. Patients were younger than those with melanoma and older than those with D-MPNST; the outcome was worse and better, respectively. SF-MPNST tumor mutational burden (TMB) was higher than D-MPNST and lower than melanoma; differences were significant only between SF-MPNST and SCM (P = .0454) and between D-MPNST and SCM (P = .001, Dunn's Kruskal-Wallis post hoc test). Despite having an overlapping mutational profile in some common cancer-associated genes, the COSMIC mutational signatures clustered DM and SCM together with UV light exposure signatures (SBS7a, 7b), and SF- and D-MPNST together with defective DNA base excision repair (SBS30, 36). RNA-seq revealed differentially expressed genes between SF-MPNST and SCM (1670 genes), DM (831 genes), and D-MPNST (614 genes), some of which hold promise for development as immunohistochemical markers (SOX8 and PLCH1) or aids (MLPH, CALB2, SOX11, and TBX4). H3K27me3 immunoreactivity was diffusely lost in most D-MPNSTs (7/8, 88%) but showed variable and patchy loss in SF-MPNSTs (2/8, 25%). PRAME was entirely negative in the majority (0+ in 20/31, 65%), including 11/15 melanomas, and showed no significant difference between groups (P = .105, Kruskal-Wallis test). Expression of immune cell transcripts was upregulated in melanomas relative to MPNSTs. Next-generation sequencing revealed multiple differential features between SF- MPNST, D-MPNST, SCM, and DM, including tumor mutation burden, mutational signatures, and differentially expressed genes. These findings help advance our understanding of disease pathogenesis and improve diagnostic modalities.

Robust Cluster Prediction Across Data Types Validates Association of Sex and Therapy Response in GBM

BACKGROUND

Previous studies have described sex-specific patient subtyping in glioblastoma. The cluster labels associated with these "legacy data" were used to train a predictive model capable of recapitulating this clustering in contemporary contexts.

METHODS

We used robust ensemble machine learning to train a model using gene microarray data to perform multi-platform predictions including RNA-seq and potentially scRNA-seq.

RESULTS

The engineered feature set was composed of many previously reported genes that are associated with patient prognosis. Interestingly, these well-known genes formed a predictive signature only for female patients, and the application of the predictive signature to male patients produced unexpected results.

CONCLUSIONS

This work demonstrates how annotated "legacy data" can be used to build robust predictive models capable of multi-target predictions across multiple platforms.

Analysis of the Pattern of RNA Expression in the Skin of TR-Deficient Mice By RNA-seq

RNA-sequencing (RNA-seq) has become the method of choice for whole transcriptome analysis, as it enables profiling of a wide range of RNA molecules and the always evolving bioinformatic pipelines allow the extraction of diverse biological information from a single sample. However, there is not a gold-standard RNA-seq protocol nor an optimal bioinformatic pipeline defined, which can challenge new users. The aim of this chapter is to describe the basic RNA-sequencing pipeline, from RNA extraction and library preparation to the bioinformatic preprocessing and downstream analyses. The steps are oriented to the transcriptome analysis of the skin of TR-deficient mice, but the protocol can be easily translated to other tissue types or organisms.

Phase II trial of multi-tyrosine kinase inhibitor ESK981 in combination with PD-1 inhibitor nivolumab in patients with metastatic castration-resistant prostate cancer

Increasing the response rates of immune checkpoint inhibitors in patients with metastatic castration-resistant prostate cancer (mCRPC) presents a significant challenge. ESK981 is a multi-tyrosine kinase and PIKfyve lipid kinase inhibitor that augments immunotherapeutic responses. In this phase II study, ESK981 was combined with the PD-1 blocking monoclonal antibody nivolumab to test for potentially improved response rates in patients with mCRPC who have progressed on androgen receptor (AR)-targeted agents and chemotherapy. Eligible patients received ESK981 orally once daily for five consecutive days, followed by a two-day break. Patients were also treated with nivolumab intravenously on Day 1 of each 28-day cycle. The primary endpoints were a 50% reduction in prostate-specific antigen (PSA50), and safety. Secondary endpoints included radiographic progression free survival (rPFS) and overall survival (OS). Additional investigations included whole exome sequencing in patients. Ten patients were enrolled. The maximum PSA decline from baseline of 14% was achieved in only one patient. Grade 3 treatment-related adverse events (AEs) included fatigue, anemia, and lymphopenia. There were no Grade 4 events. The median rPFS was 3.7 months (95% CI, 1.6-8.4). The median OS was 9.6 months (95% CI, 1.8-22.4). The study was terminated due to futility after 10 patients. Whole exome sequencing identified AR amplification in 63% of patients (5/8). ESK981 + nivolumab showed no antitumor activity in patients with AR-positive (AR+) mCRPC. Further evaluation of ESK981 combined with the PD-1 inhibitor nivolumab in AR + mCRPC patients is not warranted. (Trial registration: ClinicalTrials.gov NCT04159896. Registration date: November 12, 2019.).

Case report: A case of giant malignant solitary fibrous tumor of the pleura with Doege-Potter's syndrome and review of the literature

The solitary fibrous tumor of the pleura (SFTP) is a rare intrathoracic neoplasm that commonly originates from the subpleural mesenchymal cells of the visceral pleura and accounts for less than 5% of all pleural tumors. We reported a case of a 54-year-old man with a two-week history of hypoglycemia, a six-month history of productive cough and fatigue, and chronic right chest pain. Radiological techniques revealed a giant intra-thoracic mass with hypervascularization, and pathological staining was carried out to make a definitive diagnosis of SFTP. Interventional embolization was conducted to block the main feeding vessels before the surgery, and an anterolateral thoracotomy combined with a transverse sternotomy was performed to achieve a complete resection, which demonstrates significant potential for further application in patients with unilateral giant SFTP. The postoperative course was uneventful, with no signs of hypoglycemia observed during the follow-up. Additionally, we reviewed and prospected the research progress on SFTP. The aim of this study is to enhance clinicians' understanding of SFTP through our case and to provide a detailed review of the current research.

Phase II trial of multi-kinase inhibitor ESK981 in patients with metastatic castration-resistant prostate cancer

ESK981 is a potent tyrosine kinase and PIKfyve lipid kinase inhibitor. This phase II trial evaluated the efficacy of ESK981 as a single agent in patients with androgen receptor-positive (AR +) metastatic castration-resistant prostate cancer (mCRPC). Eligible patients had mCRPC with progression on AR-targeted agents and without prior chemotherapy treatment. Each patient received 160 mg ESK981 once daily for 5 days per week for 4 weeks per cycle (except for an adverse event (AE) occurrence). The primary endpoints were a 50% reduction in prostate-specific antigen (PSA50), and safety. Secondary endpoints included the time and the duration of PSA response, PSA progression rates, PSA progression free survival (PFS) and overall survival (OS). Exploratory investigations included whole exome sequencing in patients before treatment, and morphological evaluation of biopsy samples pre- and post-treatment. PSA was evaluated in 13 patients. Only one patient (7.7% two-sided 95% Wilson CI (0.4%, 33.3%)) experienced a reduction in their PSA levels by 50% or more. The most common grade 3 treatment-related AEs were cardiac disorders, diarrhea, hypertension, alanine transaminase and aspartate transaminase elevations. No grade 4-5 events occurred. Median PFS was 1.8 months, and median OS was 12.1 months. Peripheral immune cells showed increased T cell activation and cytokine production in two patients who received 12-weeks of ESK981. Although relatively well tolerated, ESK981 alone showed no anti-tumor activity in patients with AR + mCRPC and its further evaluation as a single agent in AR + mCRPC is not warranted. (Trial registration: ClinicalTrials.gov, NCT03456804. Registration date: March 7, 2018).

Evaluating Immune Checkpoint Blockade in Metastatic Castration-Resistant Prostate Cancers with Deleterious CDK12 Alterations in the Phase 2 IMPACT Trial

PURPOSE

CDK12 inactivation in metastatic castration-resistant prostate cancer (mCRPC) may predict immunotherapy responses. This phase 2 trial evaluated the efficacy of immune checkpoint inhibitor (ICI) therapy in patients with CDK12-altered mCRPC.

PATIENTS AND METHODS

Eligible patients had mCRPC with deleterious CDK12 alterations and any prior therapies except ICI. Cohort A received ipilimumab (1 mg/kg) with nivolumab (3 mg/kg) every 3 weeks for up to four cycles, followed by nivolumab 480 mg every 4 weeks. Cohort C received nivolumab alone 480 mg every 4 weeks. Patients with CDK12-altered nonprostate tumors were enrolled in cohort B and not reported. The primary endpoint was a 50% reduction in PSA (PSA50). Key secondary endpoints included PSA progression-free survival, overall survival, objective response rate, and safety.

RESULTS

PSA was evaluable in 23 patients in cohort A and 14 in cohort C. Median lines of prior therapy were two in cohorts A and C, including any prior novel hormonal agent (74% and 79%) and chemotherapy (57% and 36%). The PSA50 rate was 9% [95% confidence interval (CI), 1%-28%] in cohort A with two responders; neither had microsatellite instability or a tumor mutational burden >10 mutations/megabase. No PSA50 responses occurred in cohort C. Median PSA progression-free survival was 7.0 months (95% CI, 3.6-11.4) in cohort A and 4.5 months (95% CI, 3.4-13.8) in cohort C. Median overall survival was 9.0 months (95% CI, 6.2-12.3) in cohort A and 13.8 months (95% CI, 3.6-not reached) in cohort C.

CONCLUSIONS

There was minimal activity with ICI therapy in patients with CDK12-altered mCRPC.

PIKfyve controls dendritic cell function and tumor immunity

The modern armamentarium for cancer treatment includes immunotherapy and targeted therapy, such as protein kinase inhibitors. However, the mechanisms that allow cancer-targeting drugs to effectively mobilize dendritic cells (DCs) and affect immunotherapy are poorly understood. Here, we report that among shared gene targets of clinically relevant protein kinase inhibitors, high PIKFYVE expression was least predictive of complete response in patients who received immune checkpoint blockade (ICB). In immune cells, high PIKFYVE expression in DCs was associated with worse response to ICB. Genetic and pharmacological studies demonstrated that PIKfyve ablation enhanced DC function via selectively altering the alternate/non-canonical NF-κB pathway. Both loss of Pikfyve in DCs and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively controls DCs, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

PIKfyve, expressed by CD11c-positive cells, controls tumor immunity

Cancer treatment continues to shift from utilizing traditional therapies to targeted ones, such as protein kinase inhibitors and immunotherapy. Mobilizing dendritic cells (DC) and other myeloid cells with antigen presenting and cancer cell killing capacities is an attractive but not fully exploited approach. Here, we show that PIKFYVE is a shared gene target of clinically relevant protein kinase inhibitors and high expression of this gene in DCs is associated with poor patient response to immune checkpoint blockade (ICB) therapy. Genetic and pharmacological studies demonstrate that PIKfyve ablation enhances the function of CD11c+ cells (predominantly dendritic cells) via selectively altering the non-canonical NF-κB pathway. Both loss of Pikfyve in CD11c+ cells and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively regulates the function of CD11c+ cells, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

Comparison of RNA-Sequencing Methods for Degraded RNA

RNA sequencing (RNA-Seq) is a powerful technique and is increasingly being used in clinical research and drug development. Currently, several RNA-Seq methods have been developed. However, the relative advantage of each method for degraded RNA and low-input RNA, such as RNA samples collected in the field of clinical setting, has remained unknown. The Standard method of RNA-Seq captures mRNA by poly(A) capturing using Oligo dT beads, which is not suitable for degraded RNA. Here, we used three commercially available RNA-Seq library preparation kits (SMART-Seq, xGen Broad-range, and RamDA-Seq) using random primer instead of Oligo dT beads. To evaluate the performance of these methods, we compared the correlation, the number of detected expressing genes, and the expression levels with the Standard RNA-Seq method. Although the performance of RamDA-Seq was similar to that of Standard RNA-Seq, the performance for low-input RNA and degraded RNA has decreased. The performance of SMART-Seq was better than xGen and RamDA-Seq in low-input RNA and degraded RNA. Furthermore, the depletion of ribosomal RNA (rRNA) improved the performance of SMART-Seq and xGen due to increased expression levels. SMART-Seq with rRNA depletion has relative advantages for RNA-Seq using low-input and degraded RNA.

Broad Next-Generation Integrated Sequencing of Myelofibrosis Identifies Disease-Specific and Age-Related Genomic Alterations

PURPOSE

Myeloproliferative neoplasms (MPN) are characterized by the overproduction of differentiated myeloid cells. Mutations in JAK2, CALR, and MPL are considered drivers of Bcr-Abl-ve MPN, including essential thrombocythemia (ET), polycythemia vera (PV), prefibrotic primary myelofibrosis (prePMF), and overt myelofibrosis (MF). However, how these driver mutations lead to phenotypically distinct and/or overlapping diseases is unclear.

EXPERIMENTAL DESIGN

To compare the genetic landscape of MF to ET/PV/PrePMF, we sequenced 1,711 genes for mutations along with whole transcriptome RNA sequencing of 137 patients with MPN.

RESULTS

In addition to driver mutations, 234 and 74 genes were found to be mutated in overt MF (N = 106) and ET/PV/PrePMF (N = 31), respectively. Overt MF had more mutations compared with ET/PV/prePMF (5 vs. 4 per subject, P = 0.006). Genes frequently mutated in MF included high-risk genes (ASXL1, SRSF2, EZH2, IDH1/2, and U2AF1) and Ras pathway genes. Mutations in NRAS, KRAS, SRSF2, EZH2, IDH2, and NF1 were exclusive to MF. Advancing age, higher DIPSS, and poor overall survival (OS) correlated with increased variants in MF. Ras mutations were associated with higher leukocytes and platelets and poor OS. The comparison of gene expression showed upregulation of proliferation and inflammatory pathways in MF. Notably, ADGRL4, DNASE1L3, PLEKHGB4, HSPG2, MAMDC2, and DPYSL3 were differentially expressed in hematopoietic stem and differentiated cells.

CONCLUSIONS

Our results illustrate that evolution of MF from ET/PV/PrePMF likely advances with age, accumulation of mutations, and activation of proliferative pathways. The genes and pathways identified by integrated genomics approach provide insight into disease transformation and progression and potential targets for therapeutic intervention.

Discovery and Validation of a 15-Gene Prognostic Signature for Clear Cell Renal Cell Carcinoma

PURPOSE

Develop and validate gene expression-based biomarker associated with recurrent disease to facilitate risk stratification of clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

We retrospectively identified 110 patients who underwent radical nephrectomy for ccRCC (discovery cohort). Patients who recurred were matched on the basis of grade/stage to patients without recurrence. Capture whole-transcriptome sequencing was performed on RNA isolated from archival tissue using the Illumina platform. We developed a gene-expression signature to predict recurrence-free survival/disease-free survival (DFS) using a 15-fold lasso and elastic-net regularized linear Cox model. We derived the 31-gene cell cycle progression (mxCCP) score using RNA-seq data for each patient. Kaplan-Meier (KM) curves and multivariable Cox proportional hazard testing were used to validate the independent prognostic impact of the gene-expression signature on DFS, disease-specific survival (DSS), and overall survival (OS) in two validation data sets (combined n = 761).

RESULTS

After quality control, the discovery cohort comprised 50 patients with recurrence and 41 patients without, with a median follow-up of 26 and 36 months, respectively. We developed a 15-gene (15G) signature, which was independently associated with worse DFS and DSS (DFS: hazard ratio [HR], 11.08 [95% CI, 4.9 to 25.1]; DSS: HR, 9.67 [95% CI, 3.4 to 27.7]) in a multivariable model adjusting for clinicopathologic parameters (including stage, size, grade, and necrosis [SSIGN] score and Memorial Sloan Kettering Cancer Center nomogram) and mxCCP score. The 15G signature was also independently associated with worse DFS and DSS in both validation data sets (Validation A [n = 382], DFS: HR, 2.6 [95% CI, 1.6 to 4.3]; DSS: HR, 3 [95% CI, 1.4 to 6.1] and Validation B (n = 379), DFS: HR, 2.1 [95% CI, 1.2 to 3.6]; OS: HR, 3 [95% CI, 1.6 to 5.7]) adjusting for clinicopathologic variables and mxCCP score.

CONCLUSION

We developed and validated a novel 15G prognostic signature to improve risk stratification of patients with ccRCC. Pending further validation, this signature has the potential to facilitate optimal treatment allocation.

Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data

With the increased use of gene expression profiling for personalized oncology, optimized RNA sequencing (RNA-seq) protocols and algorithms are necessary to provide comparable expression measurements between exome capture (EC)-based and poly-A RNA-seq. Here, we developed and optimized an EC-based protocol for processing formalin-fixed, paraffin-embedded samples and a machine-learning algorithm, Procrustes, to overcome batch effects across RNA-seq data obtained using different sample preparation protocols like EC-based or poly-A RNA-seq protocols. Applying Procrustes to samples processed using EC and poly-A RNA-seq protocols showed the expression of 61% of genes (N = 20,062) to correlate across both protocols (concordance correlation coefficient > 0.8, versus 26% before transformation by Procrustes), including 84% of cancer-specific and cancer microenvironment-related genes (versus 36% before applying Procrustes; N = 1,438). Benchmarking analyses also showed Procrustes to outperform other batch correction methods. Finally, we showed that Procrustes can project RNA-seq data for a single sample to a larger cohort of RNA-seq data. Future application of Procrustes will enable direct gene expression analysis for single tumor samples to support gene expression-based treatment decisions.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.

Molecular characterization of large cell calcifying sertoli cell tumors: A multi-institutional study of 6 benign and 2 malignant tumors

Large cell calcifying Sertoli cell tumors (LCCSCTs) are rare testicular tumors, representing <1 % of all testicular neoplasms. Almost 40 % of patients with LCCSCTs will present in the context of the inherited tumor predisposition syndrome, the Carney complex. While most LCCSCTs are benign, 10-20 % have malignant behavior. The aim of our study was to analyze LCCSCTs for novel molecular alterations in addition to PRKAR1A mutations and to identify potential drivers for malignant progression. Eight LCCSCTs diagnosed at two institutions were included. Two patients had the Carney complex confirmed on subsequent genetic testing, and two tumors had several adverse pathological findings. One patient presented with metastatic disease at the time of initial diagnosis. Targeted next-generation sequencing detected PRKAR1A alterations in all cases, with heterozygous PRKAR1A mutations in 5 tumors, germline Carney-complex-associated PRKAR1A mutation in 2 patients, and PRKAR1A fusion in 1 tumor. Additionally, sequencing the metastatic case identified CDKN1B and TERT promoter gene mutations. All tumors showed a low tumoral mutational burden and unremarkable copy number alterations except for frequent LOH of 17q24 encompassing the PRKAR1A locus. RNA expression analysis showed increased expression of several markers including novel PRUNE2, and usual markers like inhibin and calretinin. Our study showed that while LCCSCTs have been reported in the setting of cancer predisposition syndromes, the majority of these tumors occur sporadically. PRKAR1A alterations were present in all cases and appear to be the major driver in LCCSCTs. It remains to be determined whether malignant progression may be caused by additional driver mutations.

Transcriptome Sequencing Allows Comprehensive Genomic Characterization of Pediatric B-Acute Lymphoblastic Leukemia in an Academic Clinical Laboratory

Studies have shown the power of transcriptome sequencing [RNA sequencing (RNA-Seq)] in identifying known and novel oncogenic drivers and molecular subtypes of B-acute lymphoblastic leukemia (B-ALL). The current study investigated whether the clinically validated RNA-Seq assay, coupled with a custom analysis pipeline, could be used for a comprehensive B-ALL classification. Following comprehensive clinical testing, RNA-Seq was performed on 76 retrospective B-ALL cases, 28 of which had known and 48 had undetermined subtype. Subtypes were accurately identified in all 28 known cases, and in 38 of 48 unknown cases (79%). The subtypes of the unknown cases included the following: PAX5alt (n = 12), DUX4-rearranged (n = 6), Philadelphia chromosome-like (n = 5), low hyperdiploid (n = 4), ETV6::RUNX1-like (n = 3), MEF2D-rearranged (n = 2), PAX5 P80R (n = 2), ZEB2/CEBP (n = 1), NUTM1-rearranged (n = 1), ZNF384-rearranged (n = 1), and TCF3::PBX1 (n = 1). In 15 of 38 cases (39%), classification based on expression profile was corroborated by detection of subtype-defining oncogenic drivers missed by clinical testing. RNA-Seq analysis also detected large copy number abnormalities, oncogenic hot-spot sequence variants, and intragenic IKZF1 deletions. This pilot study confirms the feasibility of implementing an RNA-Seq workflow for clinical diagnosis of molecular subtypes in pediatric B-ALL, reinforcing that RNA-Seq represents a promising global genomic assay for this heterogeneous leukemia.

Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy

Despite the remarkable clinical success of immunotherapies in a subset of cancer patients, many fail to respond to treatment and exhibit resistance. Here, we found that genetic or pharmacologic inhibition of the lipid kinase PIKfyve, a regulator of autophagic flux and lysosomal biogenesis, upregulated surface expression of major histocompatibility complex class I (MHC-I) in cancer cells via impairing autophagic flux, resulting in enhanced cancer cell killing mediated by CD8+ T cells. Genetic depletion or pharmacologic inhibition of PIKfyve elevated tumor-specific MHC-I surface expression, increased intratumoral functional CD8+ T cells, and slowed tumor progression in multiple syngeneic mouse models. Importantly, enhanced antitumor responses by Pikfyve-depletion were CD8+ T cell- and MHC-I-dependent, as CD8+ T cell depletion or B2m knockout rescued tumor growth. Furthermore, PIKfyve inhibition improved response to immune checkpoint blockade (ICB), adoptive cell therapy, and a therapeutic vaccine. High expression of PIKFYVE was also predictive of poor response to ICB and prognostic of poor survival in ICB-treated cohorts. Collectively, our findings show that targeting PIKfyve enhances immunotherapies by elevating surface expression of MHC-I in cancer cells, and PIKfyve inhibitors have potential as agents to increase immunotherapy response in cancer patients.

Clonal expansion of intra-epithelial T cells in breast cancer revealed by spatial transcriptomics

The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of tumor microenvironment. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse and more clonal than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top 10 dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

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.

Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.

Characterization of Intercalated Cell Markers KIT and LINC01187 in Chromophobe Renal Cell Carcinoma and Other Renal Neoplasms

Introduction. Chromophobe renal cell carcinoma (chromophobe RCC) is the third major subcategory of renal tumors after clear cell RCC and papillary RCC, accounting for approximately 5% of all RCC subtypes. Other oncocytic neoplasms seen commonly in surgical pathology practice include the eosinophilic variant of chromophobe RCC, renal oncocytoma, and low-grade oncocytic unclassified RCC. Methods. In our recent next-generation sequencing based study, we nominated a lineage-specific novel biomarker LINC01187 (long intergenic non-protein coding RNA 1187) which was found to be enriched in chromophobe RCC. Like KIT (cluster of differentiation 117; CD117), a clinically utilized chromophobe RCC related biomarker, LINC01187 is expressed in intercalated cells of the nephron. In this follow-up study, we performed KIT immunohistochemistry and LINC01187 RNA in situ hybridization (RNA-ISH) on a cohort of chromophobe RCC and other renal neoplasms, characterized the expression patterns, and quantified the expression signals of the two biomarkers in both primary and metastatic settings. Results. LINC01187, in comparison to KIT, exhibits stronger and more uniform expression within tumors while maintaining temporal and spatial consistency. LINC01187 also is devoid of intra-tumoral heterogeneous expression pattern, a phenomenon commonly noted with KIT. Conclusions. LINC01187 expression can augment the currently utilized KIT assay and help facilitate easy microscopic analyses in routine surgical pathology practice.

Validation of a Transcriptome-Based Assay for Classifying Cancers of Unknown Primary Origin

INTRODUCTION

Cancers assume a variety of distinct histologies, and may originate from a myriad of sites including solid organs, hematopoietic cells, and connective tissue. Clinical decision-making based on consensus guidelines such as the National Comprehensive Cancer Network (NCCN) is often predicated on a specific histologic and anatomic diagnosis, supported by clinical features and pathologist interpretation of morphology and immunohistochemical (IHC) staining patterns. However, in patients with nonspecific morphologic and IHC findings-in addition to ambiguous clinical presentations such as recurrence versus new primary-a definitive diagnosis may not be possible, resulting in the patient being categorized as having a cancer of unknown primary (CUP). Therapeutic options and clinical outcomes are poor for patients with CUP, with a median survival of 8-11 months.

METHODS

Here, we describe and validate the Tempus Tumor Origin (Tempus TO) assay, an RNA-sequencing-based machine learning classifier capable of discriminating between 68 clinically relevant cancer subtypes. Model accuracy was assessed using primary and/or metastatic samples with known subtype.

RESULTS

We show that the Tempus TO model is 91% accurate when assessed on both a retrospectively held out cohort and a set of samples sequenced after model freeze that collectively contained 9210 total samples with known diagnoses. When evaluated on a cohort of CUPs, the model recapitulated established associations between genomic alterations and cancer subtype.

DISCUSSION

Combining diagnostic prediction tests (e.g., Tempus TO) with sequencing-based variant reporting (e.g., Tempus xT) may expand therapeutic options for patients with cancers of unknown primary or uncertain histology.

The peptide woods are lovely, dark and deep: Hunting for novel cancer antigens

Harnessing the patient's immune system to control a tumor is a proven avenue for cancer therapy. T cell therapies as well as therapeutic vaccines, which target specific antigens of interest, are being explored as treatments in conjunction with immune checkpoint blockade. For these therapies, selecting the best suited antigens is crucial. Most of the focus has thus far been on neoantigens that arise from tumor-specific somatic mutations. Although there is clear evidence that T-cell responses against mutated neoantigens are protective, the large majority of these mutations are not immunogenic. In addition, most somatic mutations are unique to each individual patient and their targeting requires the development of individualized approaches. Therefore, novel antigen types are needed to broaden the scope of such treatments. We review high throughput approaches for discovering novel tumor antigens and some of the key challenges associated with their detection, and discuss considerations when selecting tumor antigens to target in the clinic.

Circular RNAs Could Encode Unique Proteins and Affect Cancer Pathways

circRNAs constitute a novel class of RNA, generally considered as non-coding RNAs; nonetheless, their coding potential has been under scrutiny. In this work, we systematically explored the predicted proteins of more than 160,000 circRNAs detected by exome capture RNA-sequencing and collected in the MiOncoCirc pan-cancer compendium, including normal and cancer samples from different types of tissues. For the functional evaluation, we compared their primary structure and domain composition with those derived from the same linear mRNAs. Among the 4362 circRNAs potentially encoding proteins with a unique primary structure and 1179 encoding proteins with a novel domain composition, 183 were differentially expressed in cancer. In particular, eight were associated with prognosis in acute myeloid leukemia. The functional classification of the dysregulated circRNA-encoded polypeptides showed an enrichment in the heme and cancer signaling, DNA-binding, and phosphorylation processes, and disclosed the roles of some circRNA-based effectors in cancer.

Intron-capture RNA-seq reveals the landscape of intronic RNAs in Arabidopsis

Intronic RNAs have been overlooked for a long time: They are functional, but treated as "junk." In this work, we designed a new sequencing strategy to investigate intronic RNAs. By using intron-capture RNA-seq, we systematically analyzed the intronic RNAs in Arabidopsis by zooming into the intronic regions an order of magnitude deeper than in previous work. Our key findings include: (1) Intron-capture RNA-seq is a much more efficient approach to analyze intronic RNAs than total RNA-seq and mRNA-seq. (2) We identified three types of intronic RNAs, and found that the GC pattern differs significantly between the introns with and without intronic RNAs. (3) We detected many hidden elements in introns, including circular RNAs, splice junctions, and transcripts that have previously been overlooked. (4) The expression of these intronic RNAs varies during the time course of pathogen infection, which indicates that an unknown mechanism may exist for these RNAs. (5) We also demonstrated that most of intronic RNAs are detectable in both Arabidopsis and rice, suggesting that these non-coding molecules are conserved. Taken together, this work proposes an efficient strategy to analyze intronic RNAs, and provides an unprecedented view of this essential component in biological pathways.

RNA Extraction Method Impacts Quality Metrics and Sequencing Results in Formalin-Fixed, Paraffin-Embedded Tissue Samples

Archived formalin-fixed, paraffin-embedded (FFPE) tissue samples are being increasingly used in molecular cancer research. Compared with fresh-frozen tissue, the nucleic acid analysis of FFPE tissue is technically more challenging. This study aimed to compare the impact of 3 different RNA extraction methods on yield, quality, and sequencing-based gene expression results in FFPE samples. RNA extraction was performed in 16 FFPE tumor specimens from patients with diffuse large B-cell lymphoma and in reference FFPE material from microsatellite-stable and microsatellite-instable cell lines (3 replicates each) using 2 silica-based procedures (A, miRNeasy FFPE; C, iCatcher FFPE Tissue RNA) and 1 isotachophoresis-based procedure (B, Ionic FFPE to Pure RNA). The RNA yield; RNA integrity, as reflected by the distribution value 200; and RNA purity, as reflected by the 260/280 and the 260/230 nm absorbance ratios, were determined. The RNA was sequenced on the NovaSeq 6000 instrument using the TruSeq RNA Exome and SMARTer Stranded Total RNA-Seq Pico v3 library preparations kits. Our results highlight the impact of RNA extraction methodology on both preanalytical and sequencing-based gene expression results. Overall, methods B and C outperformed method A because these showed significantly higher fractions of uniquely mapped reads, an increased number of detectable genes, a lower fraction of duplicated reads, and better representation of the B-cell receptor repertoire. Differences among the extraction methods were generally more explicit for the total RNA sequencing method than for the exome-capture sequencing method. Importantly, the predicative value of quality metrics varies among extraction kits, and caution should be applied when comparing and interpreting results obtained using different methods.

Quality control recommendations for RNASeq using FFPE samples based on pre-sequencing lab metrics and post-sequencing bioinformatics metrics

Background

Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.

Methods

We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.

Results

Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with TPM > 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples.

Conclusions

We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01355-0.

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.

The genetic heterogeneity and drug resistance mechanisms of relapsed refractory multiple myeloma

Multiple myeloma is the second most common hematological malignancy. Despite significant advances in treatment, relapse is common and carries a poor prognosis. Thus, it is critical to elucidate the genetic factors contributing to disease progression and drug resistance. Here, we carry out integrative clinical sequencing of 511 relapsed, refractory multiple myeloma (RRMM) patients to define the disease’s molecular alterations landscape. The NF-κB and RAS/MAPK pathways are more commonly altered than previously reported, with a prevalence of 45–65% each. In the RAS/MAPK pathway, there is a long tail of variants associated with the RASopathies. By comparing our RRMM cases with untreated patients, we identify a diverse set of alterations conferring resistance to three main classes of targeted therapy in 22% of our cohort. Activating mutations in IL6ST are also enriched in RRMM. Taken together, our study serves as a resource for future investigations of RRMM biology and potentially informs clinical management.

The genetic factors involved in disease progression and drug resistance in multiple myeloma (MM) are varied and complex. Here, genomic and transcriptomic profiling of 511 relapsed and refractory MM patients reveals genetic alterations in several oncogenic pathways contributing to progression and resistance to MM therapies.

The transcript integrity index (TII) provides a standard measure of sperm RNA

Standardizing RNA quality is key to interpreting RNA-seq data as a compromised sample can mask the underlying biology. The challenge remains when evaluating RNA quality in samples with high RNA fragmentation. For example, programmed fragmentation and cytoplasmic expulsion, integral to sperm maturation, is a prime example of the complexities of interpreting RNA-seq data, given that fragmentation can be random and\or targeted. To meet this challenge, we developed an algorithm that accurately measures RNA quality in samples with high fragmentation, such as spermatozoa. The integrity of 1,000 previously identified abundant sperm transcripts were independently visualized and evaluated using the Transcript Integrity Index (TII) algorithm to identify intact transcripts. Full-length transcripts from visual and the TII algorithm were evaluated for testis preference in humans using the GTEx tissues database. Samples were then filtered by the Interquartile Range (IQR), identifying those in which the greatest number of transcripts failed to pass the visual or TII thresholds. Transcript lists were overlapped, forming the set of intact transcripts used as TII standards. Each sample was re-evaluated as a function of this TII set of intact transcripts, with poor quality samples identified as those failing in the largest number of transcripts. While ontologically enriched in roles related to spermatogenesis and/or fertilization, samples did not segregate based on birth outcome. The TII algorithm proved an effective means to identify samples of similar quality from sperm, a cell type enriched in biologically fragmented RNAs. The algorithm should facilitate other studies using samples compromised by high levels of RNA fragmentation, such as Formalin-Fixed Paraffin-Embedded samples. Requisite to assessing male health, TII provides a solution to the long-sought-after standard that identifies samples of similar quality.

Comparison of Two Illumina Whole Transcriptome RNA Sequencing Library Preparation Methods Using Human Cancer FFPE Specimens

Objective: RNA extraction and library preparation from formalin-fixed, paraffin-embedded (FFPE) samples are crucial pre-analytical steps towards achieving optimal downstream RNA sequencing (RNASeq) results. In this study, we assessed 2 Illumina library preparation methods for RNA-Seq analysis using archived FFPE samples from human cancer indications at 2 independent vendors. Methods: Twenty-five FFPE samples from 5 indications (non-small cell lung cancer, colorectal cancer, renal carcinoma, breast cancer, and hepatocellular carcinoma) were included, covering a wide range of sample storage durations (3-25 years-old), sample qualities, and specimen types (resection vs core needle biopsy). Each sample was processed independently by both vendors. Total RNA was isolated using the Qiagen miRNeasy FFPE kit followed by library construction using either TruSeq Stranded Total RNA library preparation kit with Ribo-Zero Gold, or TruSeq RNA Access library preparation kit. Libraries were normalized to 20 pM and sequenced on an Illumina HiSeq 2500 using V3 chemistry in paired-end mode with a read length of 2 × 50 bp. The data were processed through a standard RNASeq pipeline to produce counts and transcripts per millions for each gene in each sample to compare 2 library kits at 2 different vendors. Results: Our data showed that TruSeq RNA Access libraries yield over 80% exonic reads across different quality samples, indicating higher selectivity of the exome pull down by the capture approach compared to the random priming of the TruSeq Stranded Total kit. The overall QC data for FFPE RNA extraction, library preparation, and sequencing generated by the 2 vendors are comparable, and downstream gene expression quantification results show high concordance as well. With the TruSeq Stranded Total kit, the mean Spearman correlation between vendors was 0.87 and the mean Pearson correlation was 0.76. With the TruSeq RNA Access kit, the mean Spearman correlation between vendors was 0.89 and the mean Pearson correlation was 0.73. Interestingly, examination of the cross-vendor correlations compared to various common QC statistics suggested that library concentration is better correlated with consistency between vendors than is the RNA quantity. Conclusions: Our analyses provide evidence to guide selection of sequencing methods for FFPE samples in which the sample quality may be severely compromised.

A method for simultaneous detection of small and long RNA biotypes by ribodepleted RNA-Seq

RNA sequencing offers unprecedented access to the transcriptome. Key to this is the identification and quantification of many different species of RNA from the same sample at the same time. In this study we describe a novel protocol for simultaneous detection of coding and non-coding transcripts using modifications to the Ion Total RNA-Seq kit v2 protocol, with integration of QIASeq FastSelect rRNA removal kit. We report highly consistent sequencing libraries can be produced from both frozen high integrity mouse hippocampal tissue and the more challenging post-mortem human tissue. Removal of rRNA using FastSelect was extremely efficient, resulting in less than 1.5% rRNA content in the final library. We identified > 30,000 unique transcripts from all samples, including protein-coding genes and many species of non-coding RNA, in biologically-relevant proportions. Furthermore, the normalized sequencing read count for select genes significantly negatively correlated with Ct values from qRT-PCR analysis from the same samples. These results indicate that this protocol accurately and consistently identifies and quantifies a wide variety of transcripts simultaneously. The highly efficient rRNA depletion, coupled with minimized sample handling and without complicated and high-loss size selection protocols, makes this protocol useful to researchers wishing to investigate whole transcriptomes.

Association of Complement and MAPK Activation With SARS-CoV-2-Associated Myocardial Inflammation

Question

What is the cardiac phenotype of patients with SARS-CoV-2 infection compared with viral and immune-mediated myocarditis and noninflammatory cardiomyopathy?

Findings

In this case series of 19 patients undergoing endomyocardial biopsies, cardiac specimens of patients with SARS-CoV-2 infection had a higher abundance of complement-associated factors and serine/threonine protein kinases, with mitogen-activated protein kinase–associated pathways having the highest abundance. Similarities in the cardiac immune signature were found among those with SARS-CoV-2 infection and viral myocarditis.

Meaning

In this study, the exploratory data, which characterized myocardial inflammation by deep phenotyping, have implications for the development of treatment strategies to reduce SARS-CoV-2–mediated tissue injury; these findings require confirmation in a prospective and extended cohort of patients.

Importance

Myocardial injury is a common feature of patients with SARS-CoV-2 infection. However, the cardiac inflammatory processes associated with SARS-CoV-2 infection are not completely understood.

Objective

To investigate the inflammatory cardiac phenotype associated with SARS-CoV-2 infection compared with viral myocarditis, immune-mediated myocarditis, and noninflammatory cardiomyopathy by integrating histologic, transcriptomic, and proteomic profiling.

Design, Setting, and Participants

This case series was a cooperative study between the Ludwig Maximilian University Hospital Munich and the Cardiopathology Referral Center at the University of Tübingen in Germany. A cohort of 19 patients with suspected myocarditis was examined; of those, 5 patients were hospitalized with SARS-CoV-2 infection between March and May 2020. Cardiac tissue specimens from those 5 patients were compared with specimens from 5 patients with immune-mediated myocarditis, 4 patients with non–SARS-CoV-2 viral myocarditis, and 5 patients with noninflammatory cardiomyopathy, collected from January to August 2019.

Exposures

Endomyocardial biopsy.

Main Outcomes and Measures

The inflammatory cardiac phenotypes were measured by immunohistologic analysis, RNA exome capture sequencing, and mass spectrometry–based proteomic analysis of endomyocardial biopsy specimens.

Results

Among 19 participants, the median age was 58 years (range, 37-76 years), and 15 individuals (79%) were male. Data on race and ethnicity were not collected. The abundance of CD163+ macrophages was generally higher in the cardiac tissue of patients with myocarditis, whereas lymphocyte counts were lower in the tissue of patients with SARS-CoV-2 infection vs patients with non–SARS-CoV-2 virus-associated and immune-mediated myocarditis. Among those with SARS-CoV-2 infection, components of the complement cascade, including C1q subunits (transcriptomic analysis: 2.5-fold to 3.6-fold increase; proteomic analysis: 2.0-fold to 3.4-fold increase) and serine/cysteine proteinase inhibitor clade G member 1 (transcriptomic analysis: 1.7-fold increase; proteomic analysis: 2.6-fold increase), belonged to the most commonly upregulated transcripts and differentially abundant proteins. In cardiac macrophages, the abundance of C1q was highest in SARS-CoV-2 infection. Assessment of important signaling cascades identified an upregulation of the serine/threonine mitogen-activated protein kinase pathways.

Conclusions and Relevance

This case series found that the cardiac immune signature varied in inflammatory conditions with different etiologic characteristics. Future studies are needed to examine the role of these immune pathways in myocardial inflammation.

Genome-wide spatial expression profiling in formalin-fixed tissues

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3' end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.

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.

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.

Clinical Implications of a Targeted RNA-Sequencing Panel in the Detection of Gene Fusions in Solid Tumors

The detection of recurrent gene fusions can help confirm diagnoses in solid tumors, particularly when the morphology and staining are unusual or nonspecific, and can guide therapeutic decisions. Although fluorescence in situ hybridization and PCR are often used to identify fusions, the rearrangement must be suspected, with only a few prioritized probes run. We hypothesized that the Illumina TruSight RNA Fusion Panel, which detects fusions of 507 genes and their partners, would uncover fusions with greater sensitivity than other approaches, leading to changes in diagnosis, prognosis, or therapy. Targeted RNA sequencing was performed on formalin-fixed, paraffin-embedded sarcoma and carcinoma cases in which fluorescence in situ hybridization, RT-PCR, or DNA-based sequencing was conducted during the diagnostic workup. Of 153 cases, 138 (90%) were sequenced with adequate quality control metrics. A total of 101 of 138 (73%) cases were concordant by RNA sequencing and the prior test method. RNA sequencing identified an additional 30 cases (22%) with fusions that were not detected by conventional methods. In seven cases (5%), the additional fusion information provided by RNA sequencing would have altered the diagnosis and management. A total of 19 novel fusion pairs (not previously described in the literature) were discovered (14%). Overall, the findings show that a targeted RNA-sequencing method can detect gene fusions in formalin-fixed, paraffin-embedded specimens with high sensitivity.

Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity among samples. Mixed allelic frequencies along the 20kb ORF1ab gene in one sample, suggested the presence of a defective viral RNA species subpopulation maintained in mixture with functional RNA in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

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.

Clinical cancer genomic profiling

Technological innovation and rapid reduction in sequencing costs have enabled the genomic profiling of hundreds of cancer-associated genes as a component of routine cancer care. Tumour genomic profiling can refine cancer subtype classification, identify which patients are most likely to benefit from systemic therapies and screen for germline variants that influence heritable cancer risk. Here, we discuss ongoing efforts to enhance the clinical utility of tumour genomic profiling by integrating tumour and germline analyses, characterizing allelic context and identifying mutational signatures that influence therapy response. We also discuss the potential clinical utility of more comprehensive whole-genome and whole-transcriptome sequencing and ultra-sensitive cell-free DNA profiling platforms, which allow for minimally invasive, serial analyses of tumour-derived DNA in blood.

Enrichment of low abundance DNA/RNA by oligonucleotide-clicked iron oxide nanoparticles

Detection of low abundance target DNA/RNA for clinical or research purposes is challenging because the target sequences can be hidden under a large background of human genomic or non-human metagenomic sequences. We describe a probe-based capture method to enrich for target sequences with DNA-clicked iron oxide nanoparticles. Our method was tested against commercial capture assays using streptavidin beads, on a set of probes derived from a common genotype of the hepatitis C virus. We showed that our method is more specific and sensitive, most likely due to the combination of an inert silica coating and a high density of DNA probes clicked to the nanoparticles. This facilitates target capture below the limits of detection for TaqMan qPCR, and we believe that this method has the potential to transform management of infectious diseases.

A Scalable Strand-Specific Protocol Enabling Full-Length Total RNA Sequencing From Single Cells

RNA sequencing (RNAseq) has been widely used to generate bulk gene expression measurements collected from pools of cells. Only relatively recently have single-cell RNAseq (scRNAseq) methods provided opportunities for gene expression analyses at the single-cell level, allowing researchers to study heterogeneous mixtures of cells at unprecedented resolution. Tumors tend to be composed of heterogeneous cellular mixtures and are frequently the subjects of such analyses. Extensive method developments have led to several protocols for scRNAseq but, owing to the small amounts of RNA in single cells, technical constraints have required compromises. For example, the majority of scRNAseq methods are limited to sequencing only the 3' or 5' termini of transcripts. Other protocols that facilitate full-length transcript profiling tend to capture only polyadenylated mRNAs and are generally limited to processing only 96 cells at a time. Here, we address these limitations and present a novel protocol that allows for the high-throughput sequencing of full-length, total RNA at single-cell resolution. We demonstrate that our method produced strand-specific sequencing data for both polyadenylated and non-polyadenylated transcripts, enabled the profiling of transcript regions beyond only transcript termini, and yielded data rich enough to allow identification of cell types from heterogeneous biological samples.

Randomized phase II study of the Bruton tyrosine kinase inhibitor acalabrutinib, alone or with pembrolizumab in patients with advanced pancreatic cancer

Background

The immunosuppressive desmoplastic stroma of pancreatic cancer represents a major hurdle to developing an effective immune response. Preclinical studies in pancreatic cancer have demonstrated promising anti-tumor activity with Bruton tyrosine kinase (BTK) inhibition combined with programmed cell death receptor-1 (PD-1) blockade.

Methods

This was a phase II, multicenter, open-label, randomized (1:1) clinical trial evaluating the BTK inhibitor acalabrutinib, alone (monotherapy) or in combination with the anti-PD-1 antibody pembrolizumab (combination therapy). Eligible patients were adults with histologically confirmed metastatic or locally advanced unresectable pancreatic ductal adenocarcinoma with an Eastern Cooperative Oncology Group Performance Status (ECOG PS) ≤1 who had received at least one prior systemic therapy. Oral acalabrutinib 100 mg twice daily was administered with or without intravenous pembrolizumab 200 mg on day 1 of each 3-week cycle. Peripheral blood was analyzed for changes in immune markers, and tumors from exceptional responders were molecularly analyzed.

Results

A total of 77 patients were enrolled (37 monotherapy; 40 combination therapy) with a median age of 64 years; 77% had an ECOG PS of 1. The median number of prior therapies was 3 (range 1–6). Grade 3–4 treatment-related adverse events were seen in 14.3% of patients in the monotherapy arm and 15.8% of those in the combination therapy arm. The overall response rate and disease control rate were 0% and 14.3% with monotherapy and 7.9% and 21.1% with combination therapy, respectively. Median progression-free survival was 1.4 months in both arms. Peripheral blood flow analysis demonstrated consistent reductions in granulocytic (CD15+) myeloid-derived suppressor cells (MDSCs) over time. Two exceptional responders were found to be microsatellite stable with low tumor mutation burden, low neoantigen load and no defects in the homologous DNA repair pathway.

Conclusions

The combination of acalabrutinib and pembrolizumab was well tolerated, but limited clinical activity was seen with either acalabrutinib monotherapy or combination therapy. Peripheral reductions in MDSCs were seen. Efforts to understand and target the pancreatic tumor microenvironment should continue.

Trial registration number

NCT02362048.

Combined VEGFR and MAPK pathway inhibition in angiosarcoma

Angiosarcoma is an aggressive malignancy of endothelial cells that carries a high mortality rate. Cytotoxic chemotherapy can elicit clinical responses, but the duration of response is limited. Sequencing reveals multiple mutations in angiogenesis pathways in angiosarcomas, particularly in vascular endothelial growth factor (VEGFR) and mitogen-activated protein kinase (MAPK) signaling. We aimed to determine the biological relevance of these pathways in angiosarcoma. Tissue microarray consisting of clinical formalin-fixed paraffin embedded tissue archival samples were stained for phospho- extracellular signal-regulated kinase (p-ERK) with immunohistochemistry. Angiosarcoma cell lines were treated with the mitogen-activated protein kinase kinase (MEK) inhibitor trametinib, pan-VEGFR inhibitor cediranib, or combined trametinib and cediranib and viability was assessed. Reverse phase protein array (RPPA) was performed to assess multiple oncogenic protein pathways. SVR angiosarcoma cells were grown in vivo and gene expression effects of treatment were assessed with whole exome RNA sequencing. MAPK signaling was found active in over half of clinical angiosarcoma samples. Inhibition of MAPK signaling with the MEK inhibitor trametinib decreased the viability of angiosarcoma cells. Combined inhibition of the VEGF and MAPK pathways with cediranib and trametinib had an additive effect in in vitro models, and a combinatorial effect in an in vivo model. Combined treatment led to smaller tumors than treatment with either agent alone. RNA-seq demonstrated distinct expression signatures between the trametinib treated tumors and those treated with both trametinib and cediranib. These results indicate a clinical study of combined VEGFR and MEK inhibition in angiosarcoma is warranted.

Integrated genomic and transcriptomic analysis suggests KRT18 mutation and MTAP are key genetic alterations related to the prognosis between astrocytoma and glioblastoma

Background

Astrocytoma and glioblastoma (GBM) are the two main subtypes of glioma, with the 2016 World Health Organization Classification of Tumors of the Central Nervous System (CNS WHO) classifying them into different grades. GBM is the most malignant among all CNS tumors with a 5-year survival rate of less than 5%. Although the prognosis of patients with astrocytoma is better than that of GBM in general, patients with anaplastic astrocytoma (AA) and isocitrate dehydrogenase (IDH) wild type have a similar prognosis as GBM and entail a high risk of progression. Exploring the molecular driving force behind the malignant phenotype of astrocytoma and GBM will help explain the diversity of glioma and discover new drug targets.

Methods

We enrolled 12 patients with astrocytoma and 12 patients with GBM and performed whole-exome sequencing (WES) and RNA sequencing analysis on tumor samples from the patients.

Results

We found that the somatic mutation of KRT18, which is associated with cell apoptosis and adhesion by interacting with receptor 1-associated protein (TRADD) and pinin, was significantly enriched in astrocytoma, but rare in GBM. Copy number loss of MTAP, which is closely related to a poor prognosis of glioma, was found to be significantly enriched in GBM. In addition, different somatic copy number alteration (SCNA), gene expression, and immune cell infiltration patterns between astrocytoma and GBM were found.

Conclusions

This study revealed the distinct characteristics of astrocytoma and GBM at the DNA and RNA level. Somatic mutation of KRT18 and copy number loss of MTAP, two key genetic alterative genes in astrocytoma and GBM, have the potential to become therapeutic targets in glioma.