Recent advances in cancer fusion transcript detection

Detection of Circulating mRNA Variants in Hepatocellular Carcinoma Patients Using Targeted RNAseq

Introduction

Mutations in circulating nucleic acids can be used as biomarkers for the early detection and management of hepatocellular carcinoma (HCC). However, while circulating tumor DNA and microRNA have been extensively explored, circulating tumor mRNA and circulating mRNA mutants (ctmutRNA), which may provide advantages over other analytes, remain less well described. We previously reported the identification of 288 HCC selective ctmutRNA variants, called "candidates," from a small cohort of HCC patients using total RNAseq. The objective of the current study was to use targeted RNAseq to validate the specificity and sensitivity of these HCC selective variants in an independent cohort of patients with liver cirrhosis (LC).

Methods

Several methods to isolate small extracellular vesicles and amplify mRNA from the circulation were compared. RNA was isolated, and the primers and probes selective for the 288 regions of interest were used with RNA from HCC (N = 50) and LC and no HCC (N = 35) patients. HCC tumor tissues (N = 11), a normal liver tissue and 3 cell lines were also studied. cDNA synthesis was followed by library construction using QIAseq RNA Fusion XP panel. QC analysis was carried out with an Agilent Bioanalyzer before sequencing on a NextSeq 550 instrument. A GATK HaplotypeCaller was used for variant calling and annotation carried out using snpEff.

Results

Among the test panel of 288 ctmutRNA candidates in the original cohort, 75 were detected in the new cohort of plasma samples. Moreover, 388 other variants in proximity to the original lesions were also found in multiple HCC but not LC plasma samples. A subset of 36 HCC selective variants was able to identify all HCC patients. The most common tumor specific variants were Indels and SNPs. Novel mRNA fusion variants, corresponding to SENP7, HYI, SAR1A, RASA2, TUBA transcripts, etc., were identified in HCC and LC patients.

Conclusion

Circulating RNA could be a robust analyte for noninvasive early detection of HCC and circulating RNA panels could be powerful tools in the entire spectrum of clinical management.

Deciphering IGH rearrangement complexity and detection strategies in acute lymphoblastic leukaemia

Acute lymphoblastic leukaemia is a highly heterogeneous malignancy characterised by various genomic alterations that influence disease progression and therapeutic outcomes. Gene fusions involving the immunoglobulin heavy chain gene represent a complex and diverse category. These fusions often result in enhancer hijacking, upregulation of partner proto-oncogenes and contribute to leukemogenesis. This review highlights the mechanisms underlying IGH gene fusions, the critical role they play in ALL pathogenesis, and current detection technologies.

EcDNA-borne PVT1 fusion stabilizes oncogenic mRNAs

Extrachromosomal DNA (ecDNA) amplifications are prevalent drivers of human cancers. We show that ecDNAs exhibit elevated structural variants leading to gene fusions that produce oncogene fusion transcripts. The long noncoding RNA (lncRNA) gene PVT1 is the most recurrent structural variant across cancer genomes, with PVT1-MYC fusions arising most frequently on ecDNA. PVT1 exon 1 is the predominant 5' partner fused to MYC or other oncogenes on the 3' end. Mechanistic studies demonstrate that PVT1 exon 1 confers enhanced RNA stability for fusion transcripts, which requires PVT1 exon 1 interaction with SRSF1 protein. Genetic rescue of MYC-addicted cancer models and isoform-specific single-cell RNA sequencing of tumors reveal that PVT1-MYC better supports MYC dependency and better activates MYC target genes in vivo . Thus, the mutagenic landscape of ecDNA contributes to genome instability and generates chimeric fusions of lncRNA and mRNA genes, selecting PVT1 5' region as a stabilizer of oncogene mRNAs.

Integrating comprehensive genomic profiling in the management of oncology patients: applications and challenges in Taiwan

Comprehensive genomic profiling (CGP) refers to the detailed genomic analysis of cancers for oncology patients. With the rapid development of next-generation sequencing (NGS) technologies, CGP has been widely applied to clinical practice and managing oncology patients. CGP can be performed on the tumor DNA and RNA, as well as non-tumor tissues (e.g., blood, pleural effusion, and ascites). In this article, we review the current evidence supporting the use of CGP in the management of oncology patients, both in real-world practice and the bridging to clinical trials. We also discuss the role of the molecular tumor board on the application of CGP in oncology patients. We provide an overview of the current scheme of CGP reimbursement in Taiwan and the precision oncology branch of the National Biobank Consortium of Taiwan. Finally, we discuss about the potential barriers and challenges of applying CGP in managing oncology patients and the future perspectives of CGP in precision oncology.

Detection of mRNA Transcript Variants

Most eukaryotic genes express more than one mature mRNA, defined as transcript variants. This complex phenomenon arises from various mechanisms, such as using alternative transcription start sites and alternative post-transcriptional processing events. The resulting transcript variants can lead to synthesizing proteins that possess distinct functional domains or may even generate noncoding RNAs, each with unique roles in cellular processes. The generation of these transcript variants is not merely a random occurrence; it is cell-type specific and varies with developmental stages, aging processes, or pathogenesis of diseases. This highlights the biological significance of transcript variants in regulating gene expression and their potential impact on cellular functionality. Despite the biological importance, investigating transcript variants has been hampered by challenges associated with detecting their expression. This review article addresses the advancements in molecular techniques in detecting transcript variants. Traditional methods such as RT-PCR and RT-qPCR can easily detect known transcript variants using primers that target unique exons associated with the variants. Other techniques like RACE-PCR and hybridization-based methods, including Northern blotting, RNase protection assays, and microarrays, have also been utilized to detect transcript variants. Nevertheless, RNA sequencing (RNA-Seq) has emerged as a powerful technique for identifying transcript variants, especially those with previously unknown sequences. The effectiveness of RNA sequencing in transcript variant detection depends on the specific sequencing approach and the precision of data analysis. By understanding the strengths and weaknesses of each laboratory technique, researchers can develop more effective strategies for detecting mRNA transcript variants. This ability will be crucial for our comprehensive understanding of gene regulation and the implications of transcript diversity in various biological contexts.

The Intestinal Mucin Isoform Landscape Reveals Region-Specific Biomarker Panels for Inflammatory Bowel Disease Patient Stratification

BACKGROUND AND AIMS

Mucosal healing is considered a key therapeutic endpoint in inflammatory bowel diseases (IBD) and comprises endoscopic improvement of inflammation without taking barrier healing into account. Mucins are critical components of the mucosal barrier function that give rise to structurally diverse isoforms. Unraveling disease-associated mucin isoforms that could act as an indication for barrier function would greatly enhance IBD management.

METHODS

We present the intestinal mucin RNA isoform landscape in IBD and control patients using a targeted mucin isoform sequencing approach on a discovery cohort (n = 106). Random Forest modeling (n = 1683 samples) with external validation (n = 130 samples) identified unique mucin RNA isoform panels that accurately stratified IBD patients in multiple subpopulations based on inflammation, IBD subtype (Crohn's disease [CD], ulcerative colitis [UC]), and anatomical location of the intestinal tract (i.e. ileum, proximal colon, distal colon, and rectum).

RESULTS

Particularly, the mucin RNA isoform panels obtained from the inflamed UC and CD distal colon showed high performance in distinguishing inflamed biopsies from their control counterparts (AUC of 93.3% and 91.1% in the training, 95.0% and 96.0% in the test, and 89.5% and 78.3% in the external validation datasets, respectively). Furthermore, the differentially expressed MUC4 (PB.1238.363), MUC5AC (PB.2811.15), MUC16 (ENST00000397910.8), and MUC1 (ENST00000462317.5 and ENST00000620103.4) RNA isoforms frequently occurred throughout the different panels highlighting their role in IBD pathogenesis.

CONCLUSIONS

We unveiled region-specific mucin RNA isoform panels capturing the heterogeneity of the IBD patient population and showing great potential to indicate barrier function in IBD patients.

Fusion transcripts in plants: hidden layer of transcriptome complexity

In the realm of genetic information, fusion transcripts contribute to the intricate complexity of the transcriptome across various organisms. Recently, Cong et al. investigated these RNAs in rice, maize, soybean, and arabidopsis (Arabidopsis thaliana), revealing conserved characteristics. These findings enhance our understanding of the functional roles and evolutionary significance of these fusion transcripts.

Detection of chimeric alpha-defensin transcripts and peptides in mouse Paneth cells

Introduction

In mammals, Paneth cells, located in the crypts of the small intestine, produceantimicrobial peptides that serve to keep the intestinal microbiome under control. a-Defensins are the primary antimicrobial peptides produced by these cells.

Methods

We used 148 publicly available bulk RNA-seq samples on purified PCs, proteomics on enriched purified PC proteins and Defa peptide activity assays to detect all Defa transcrips, including potential chimeric transcrips.

Results

We identified 28 expressed Defa genes in mice, with up to 85% of Paneth cell RNA reads mapping to these genes. Chimeric mRNAs, involving sequences from two different Defa genes, were detected in most experiments. Despite their low abundance (less than 0.3%), mass spectrometry confirmed the presence of chimeric peptides. Synthetic versions of these peptides demonstrated antibacterial activity against multiple bacterial species.

Conclusion

We show the existence of chimeric Defa transcripts and peptides in mice that are biologically active. We propose a possible stochatic mechanism or that the activation of the UPR patway may play a role in their production.

Detection of fusion events by RNA sequencing in FFPE versus freshly frozen colorectal cancer tissue samples

Gene fusion events result in chimeric proteins that are frequently found in human cancers. Specific targeted therapies are available for several types of cancer fusions including receptor tyrosine kinase gene moieties. RNA sequencing (RNAseq) can directly be used for detection of gene rearrangements in a single test, along with multiple additional biomarkers. However, tumor biosamples are usually formalin-fixed paraffin-embedded (FFPE) tissue blocks where RNA is heavily degraded, which in theory may result in decreased efficiency of fusion detection. Here, for the first time, we compared the efficacy of gene fusion detection by RNAseq for matched pairs of freshly frozen in RNA stabilizing solution (FF) and FFPE tumor tissue samples obtained from 29 human colorectal cancer patients. We detected no statistically significant difference in the number of chimeric transcripts in FFPE and FF RNAseq profiles. The known fusion KANSL1-ARL17A/B occurred with a high frequency in 69% of the patients. We also detected 93 new fusion genes not mentioned in the literature or listed in the ChimerSeq database. Among them, 11 were found in two or more patients, suggesting their potential role in carcinogenesis. Most of the fusions detected most probably represented read-through, microdeletion or local duplication events. Finally, in one patient, we detected a potentially clinically actionable in-frame fusion of LRRFIP2 and ALK genes not previously described in colorectal cancer with an intact tyrosine kinase domain that can be potentially targeted by ALK inhibitors.

ChiTaRS 8.0: the comprehensive database of chimeric transcripts and RNA-seq data with applications in liquid biopsy

Gene fusions are nucleotide sequences formed due to errors in replication and transcription control. These errors, resulting from chromosomal translocation, transcriptional errors or trans-splicing, vary from cell to cell. The identification of fusions has become critical as key biomarkers for disease diagnosis and therapy in various cancers, significantly influencing modern medicine. Chimeric Transcripts and RNA-Sequencing database version 8.0 (ChiTaRS 8.0; http://biosrv.org/chitars) is a specialized repository for human chimeric transcripts, containing 47 445 curated RNA transcripts and over 100 000 chimeric sequences in humans. This updated database provides unique information on 1055 chimeric breakpoints derived from public datasets using chromosome conformation capture techniques (the Hi-C datasets). It also includes an expanded list of gene fusions that are potential drug targets, and chimeric breakpoints across 934 cell lines, positioning ChiTaRS 8.0 as a valuable resource for testing personalized cancer therapies. By utilizing text mining on a curated selection of disease-specific RNA-sequencing data from public datasets, as well as patient blood and plasma samples, we have identified novel chimeras-particularly in diseases such as oral squamous cell carcinoma and glioblastoma-now catalogued in ChiTaRS. Thus, ChiTaRS 8.0 serves as an enhanced fusion transcript repository that incorporates insights into the functional landscape of chimeras in cancers and other complex diseases, based on liquid biopsy results.

Architects and Partners: The Dual Roles of Non-coding RNAs in Gene Fusion Events

Extensive research into gene fusions in cancer and other diseases has led to the discovery of novel biomarkers and therapeutic targets. Concurrently, various bioinformatics tools have been developed for fusion detection in RNA sequencing data, which, in the age of increasing affordability of sequencing, have delivered a large-scale identification of transcriptomic abnormalities. Historically, the focus of fusion transcript research was predominantly on coding RNAs and their resultant proteins, often overlooking non-coding RNAs (ncRNAs). This chapter discusses how ncRNAs are integral players in the landscape of gene fusions, detailing their contributions to the formation of gene fusions and their presence in chimeric transcripts. We delve into both linear and the more recently identified circular fusion RNAs, providing a comprehensive overview of the computational methodologies used to detect ncRNA-involved gene fusions. Additionally, we examine the inherent biases and limitations of these bioinformatics approaches, offering insights into the challenges and future directions in this dynamic field.

Gene Fusion Detection in Long-Read Transcriptome Datasets from Multiple Cancer Cell Lines

BACKGROUND

Fusion genes are important biomarkers in cancer research because their expression can produce abnormal proteins with oncogenic properties. Long-read RNA sequencing (long-read RNA-seq), which can sequence full-length mRNA transcripts, facilitates the detection of such fusion genes. Several tools have been proposed for detecting fusion genes in long-read RNA-seq datasets derived from cancer cells. However, the high sequencing error rate in long-read RNA-seq makes fusion gene detection challenging.

METHODS

To address this issue, additional steps were incorporated into the fusion detection tool to improve detection accuracy. These steps include anchoring breakpoints to exon boundaries, realigning unaligned regions, and clustering breakpoints. To evaluate the accuracy of our tool in detecting fusion genes, we compared its detection accuracy with two representative existing tools, JAFFAL and FusionSeeker.

RESULTS

Our tool outperformed the two existing tools in detecting fusion genes, as demonstrated in long-read RNA-seq datasets. We also identified potentially novel fusion genes consistently detected across multiple tools or datasets.

CONCLUSIONS

The application of our tool to the detection of fusion genes in long-read RNA-seq datasets from two different cancer cell lines demonstrated the detection effectiveness of this tool.

The landscape of fusion transcripts in plants: a new insight into genome complexity

BACKGROUND

Fusion transcripts (FTs), generated by the fusion of genes at the DNA level or RNA-level splicing events significantly contribute to transcriptome diversity. FTs are usually considered unique features of neoplasia and serve as biomarkers and therapeutic targets for multiple cancers. The latest findings show the presence of FTs in normal human physiology. Several discrete reports mentioned the presence of fusion transcripts in planta, has important roles in stress responses, morphological alterations, or traits (e.g. seed size, etc.).

RESULTS

In this study, we identified 169,197 fusion transcripts in 2795 transcriptome datasets of Arabidopsis thaliana, Cicer arietinum, and Oryza sativa by using a combination of tools, and confirmed the translational activity of 150 fusion transcripts through proteomic datasets. Analysis of the FT junction sequences and their association with epigenetic factors, as revealed by ChIP-Seq datasets, demonstrated an organised process of fusion formation at the DNA level. We investigated the possible impact of three-dimensional chromatin conformation on intra-chromosomal fusion events by leveraging the Hi-C datasets with the incidence of fusion transcripts. We further utilised the long-read RNA-Seq datasets to validate the most reoccurring fusion transcripts in each plant species followed by further authentication through RT-PCR and Sanger sequencing.

CONCLUSIONS

Our findings suggest that a significant portion of fusion events may be attributed to alternative splicing during transcription, accounting for numerous fusion events without a proportional increase in the number of RNA pairs. Even non-nuclear DNA transcripts from mitochondria and chloroplasts can participate in intra- and inter-chromosomal fusion formation. Genes in close spatial proximity are more prone to undergoing fusion formation, especially in intra-chromosomal FTs. Most of the fusion transcripts may not undergo translation and serve as long non-coding RNAs. The low validation rate of FTs in plants indicated that the fusion transcripts are expressed at very low levels, like in the case of humans. FTs often originate from parental genes involved in essential biological processes, suggesting their relevance across diverse tissues and stress conditions. This study presents a comprehensive repository of fusion transcripts, offering valuable insights into their roles in vital physiological processes and stress responses.

Direct RNA sequencing in plants: Practical applications and future perspectives

The transcriptome serves as a bridge that links genomic variation to phenotypic diversity. A vast number of studies using next-generation RNA sequencing (RNA-seq) over the last 2 decades have emphasized the essential roles of the plant transcriptome in response to developmental and environmental conditions, providing numerous insights into the dynamic changes, evolutionary traces, and elaborate regulation of the plant transcriptome. With substantial improvement in accuracy and throughput, direct RNA sequencing (DRS) has emerged as a new and powerful sequencing platform for precise detection of native and full-length transcripts, overcoming many limitations such as read length and PCR bias that are inherent to short-read RNA-seq. Here, we review recent advances in dissecting the complexity and diversity of plant transcriptomes using DRS as the main technological approach, covering many aspects of RNA metabolism, including novel isoforms, poly(A) tails, and RNA modification, and we propose a comprehensive workflow for processing of plant DRS data. Many challenges to the application of DRS in plants, such as the need for machine learning tools tailored to plant transcriptomes, remain to be overcome, and together we outline future biological questions that can be addressed by DRS, such as allele-specific RNA modification. This technology provides convenient support on which the connection of distinct RNA features is tightly built, sustainably refining our understanding of the biological functions of the plant transcriptome.

PFusionDB: a comprehensive database of plant-specific fusion transcripts

Fusion transcripts (FTs) are well known cancer biomarkers, relatively understudied in plants. Here, we developed PFusionDB (www.nipgr.ac.in/PFusionDB), a novel plant-specific fusion-transcript database. It is a comprehensive repository of 80,170, 39,108, 83,330, and 11,500 unique fusions detected in 1280, 637, 697, and 181 RNA-Seq samples of Arabidopsis thaliana, Oryza sativa japonica, Oryza sativa indica, and Cicer arietinum respectively. Here, a total of 76,599 (Arabidopsis thaliana), 35,480 (Oryza sativa japonica), 72,099 (Oryza sativa indica), and 9524 (Cicer arietinum) fusion transcripts are non-recurrent i.e., only found in one sample. Identification of FTs was performed by using a total of five tools viz. EricScript-Plants, STAR-Fusion, TrinityFusion, SQUID, and MapSplice. At PFusionDB, available fundamental details of fusion events includes the information of parental genes, junction sequence, expression levels of fusion transcripts, breakpoint coordinates, strand information, tissue type, treatment information, fusion type, PFusionDB ID, and Sequence Read Archive (SRA) ID. Further, two search modules: 'Simple Search' and 'Advanced Search', along with a 'Browse' option to data download, are present for the ease of users. Three distinct modules viz. 'BLASTN', 'SW Align', and 'Mapping' are also available for efficient query sequence mapping and alignment to FTs. PFusionDB serves as a crucial resource for delving into the intricate world of fusion transcript in plants, providing researchers with a foundation for further exploration and analysis. Database URL: www.nipgr.ac.in/PFusionDB.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04132-1.

Clinical utility of circulating tumor DNA profiling in detecting targetable fusions in non-small cell lung cancer

Introduction

Numerous studies have suggested high concordance between tissue and circulating tumor DNA (ctDNA) comprehensive genomic profiling (CGP) tests but only few of them focused on fusions. In addition, atypical breakpoints occasionally detected from DNA-based fusion detection make interpretation difficult, and their clinical significance remains unclear. This study evaluated the clinical utility of ctDNA CGP for fusion detection.

Methods

The results of ctDNA CGP tests performed on patients with stage IV non-small cell lung cancer during routine clinical care were retrospectively reviewed. The concordance between ctDNA CGP and combined tissue test results was analyzed using CGP, immunohistochemistry, fluorescence in situ hybridization, and reverse transcription polymerase chain reaction. The clinical significance of fusions detected by ctDNA CGP, including those with atypical breakpoints at the DNA level, was assessed.

Results

In total, 264 patients were tested with ctDNA CGP. Fusions were detected in 27 patients (10.2%), and the fusion drivers were RET (n=12, 4.6%), ALK (n=9, 3.4%), ROS1 (n=4, 1.5%), and FGFR2 (n=2, 0.8%). The overall prevalence of fusion in tissue CGP was comparable to that in ctDNA CGP. A total of 371 ctDNA-tissue test pairs were available, and the overall positive and negative percent agreement rates were 92.9% (13/14) and 100.0% (357/357), respectively. One ALK IHC-positive and ctDNA CGP-negative case did not respond to ALK-targeted therapy. Response to targeted therapy was assessed in 16 patients, and a partial response was achieved in all patients, including four with atypical breakpoints.

Conclusion

Fusion detection using ctDNA CGP showed high concordance with tissue tests and accuracy in predicting therapeutic responses in patients with non-small cell lung cancer. ctDNA CGP may provide an important diagnostic tool for fusion detection.

Advances in long-read single-cell transcriptomics

Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.

Effective requesting method to detect fusion transcripts in chronic myelomonocytic leukemia RNA-seq

RNA sequencing technology combining short read and long read analysis can be used to detect chimeric RNAs in malignant cells. Here, we propose an integrated approach that uses k-mers to analyze indexed datasets. This approach is used to identify chimeric RNA in chronic myelomonocytic leukemia (CMML) cells, a myeloid malignancy that associates features of myelodysplastic and myeloproliferative neoplasms. In virtually every CMML patient, new generation sequencing identifies one or several somatic driver mutations, typically affecting epigenetic, splicing and signaling genes. In contrast, cytogenetic aberrations are currently detected in only one third of the cases. Nevertheless, chromosomal abnormalities contribute to patient stratification, some of them being associated with higher risk of poor outcome, e.g. through transformation into acute myeloid leukemia (AML). Our approach selects four chimeric RNAs that have been detected and validated in CMML cells. We further focus on NRIP1-MIR99AHG, as this fusion has also recently been detected in AML cells. We show that this fusion encodes three isoforms, including a novel one. Further studies will decipher the biological significance of such a fusion and its potential to improve disease stratification. Taken together, this report demonstrates the ability of a large-scale approach to detect chimeric RNAs in cancer cells.

Transcriptional determinism and stochasticity contribute to the complexity of autism-associated SHANK family genes

Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3-mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We apply an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in humans and mice. We unexpectedly discover an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts are altered in Shank3-mutant mice and postmortem brain tissues from individuals with autism spectrum disorder. The enhanced SHANK3 transcriptome significantly improves the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest that both deterministic and stochastic transcription of the genome is associated with SHANK family genes.

Readon: a novel algorithm to identify read-through transcripts with long-read sequencing data

MOTIVATION

There are many clustered transcriptionally active regions in the human genome, in which the transcription complex cannot immediately terminate transcription at the upstream gene termination site, but instead continues to transcribe intergenic regions and downstream genes, resulting in read-through transcripts. Several studies have demonstrated the regulatory roles of read-through transcripts in tumorigenesis and development. However, limited by the read length of next-generation sequencing, discovery of read-through transcripts has been slow. For long but also erroneous third-generation sequencing data, this study developed a novel minimizer sketch algorithm to accurately and quickly identify read-through transcripts.

RESULTS

Readon initially splits the reference sequence into distinct active regions. It employs a sliding window approach within each region, calculates minimizers, and constructs the specialized structured arrays for query indexing. Following initial alignment anchor screening of candidate read-through transcripts, further confirmation steps are executed. Comparative assessments against existing software reveal Readon's superior performance on both simulated and validated real data. Additionally, two downstream tools are provided: one for predicting whether a read-through transcript is likely to undergo nonsense-mediated decay or encodes a protein, and another for visualizing splicing patterns.

AVAILABILITY AND IMPLEMENTATION

Readon is freely available on GitHub (https://github.com/Bulabula45/Readon).

Transcriptome-wide gene expression outlier analysis pinpoints therapeutic vulnerabilities in colorectal cancer

Multiple strategies are continuously being explored to expand the drug target repertoire in solid tumors. We devised a novel computational workflow for transcriptome-wide gene expression outlier analysis that allows the systematic identification of both overexpression and underexpression events in cancer cells. Here, it was applied to expression values obtained through RNA sequencing in 226 colorectal cancer (CRC) cell lines that were also characterized by whole-exome sequencing and microarray-based DNA methylation profiling. We found cell models displaying an abnormally high or low expression level for 3533 and 965 genes, respectively. Gene expression abnormalities that have been previously associated with clinically relevant features of CRC cell lines were confirmed. Moreover, by integrating multi-omics data, we identified both genetic and epigenetic alternations underlying outlier expression values. Importantly, our atlas of CRC gene expression outliers can guide the discovery of novel drug targets and biomarkers. As a proof of concept, we found that CRC cell lines lacking expression of the MTAP gene are sensitive to treatment with a PRMT5-MTA inhibitor (MRTX1719). Finally, other tumor types may also benefit from this approach.

IFDlong: an isoform and fusion detector for accurate annotation and quantification of long-read RNA-seq data

Advancements in long-read transcriptome sequencing (long-RNA-seq) technology have revolutionized the study of isoform diversity. These full-length transcripts enhance the detection of various transcriptome structural variations, including novel isoforms, alternative splicing events, and fusion transcripts. By shifting the open reading frame or altering gene expressions, studies have proved that these transcript alterations can serve as crucial biomarkers for disease diagnosis and therapeutic targets. In this project, we proposed IFDlong, a bioinformatics and biostatistics tool to detect isoform and fusion transcripts using bulk or single-cell long-RNA-seq data. Specifically, the software performed gene and isoform annotation for each long-read, defined novel isoforms, quantified isoform expression by a novel expectation-maximization algorithm, and profiled the fusion transcripts. For evaluation, IFDlong pipeline achieved overall the best performance when compared with several existing tools in large-scale simulation studies. In both isoform and fusion transcript quantification, IFDlong is able to reach more than 0.8 Spearman's correlation with the truth, and more than 0.9 cosine similarity when distinguishing multiple alternative splicing events. In novel isoform simulation, IFDlong can successfully balance the sensitivity (higher than 90%) and specificity (higher than 90%). Furthermore, IFDlong has proved its accuracy and robustness in diverse in-house and public datasets on healthy tissues, cell lines and multiple types of diseases. Besides bulk long-RNA-seq, IFDlong pipeline has proved its compatibility to single-cell long-RNA-seq data. This new software may hold promise for significant impact on long-read transcriptome analysis. The IFDlong software is available at https://github.com/wenjiaking/IFDlong.

The Application of Long-Read Sequencing to Cancer

Cancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment.

Transcriptional Determinism and Stochasticity Contribute to the Complexity of Autism Associated SHANK Family Genes

Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3 mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We applied an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in human and mice. We unexpectedly discovered an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts were altered in Shank3 mutant mice and postmortem brains tissues from individuals with ASD. The enhanced SHANK3 transcriptome significantly improved the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest the stochastic transcription of genome associated with SHANK family genes.

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

Molecular pathology as basis for timely cancer diagnosis and therapy

Precision and personalized therapeutics have witnessed significant advancements in technology, revolutionizing the capabilities of laboratories to generate vast amounts of genetic data. Coupled with computational resources for analysis and interpretation, and integrated with various other types of data, including genomic data, electronic medical health (EMH) data, and clinical knowledge, these advancements support optimized health decisions. Among these technologies, next-generation sequencing (NGS) stands out as a transformative tool in the field of cancer treatment, playing a crucial role in precision oncology. NGS-based workflows are employed across a range of applications, including gene panels, exome sequencing, and whole-genome sequencing, supporting comprehensive analysis of the entire cancer genome, including mutations, copy number variations, gene expression profiles, and epigenetic modifications. By utilizing the power of NGS, these workflows contribute to enhancing our understanding of disease mechanisms, diagnosis confirmation, identifying therapeutic targets, and guiding personalized treatment decisions. This manuscript explores the diverse applications of NGS in cancer treatment, highlighting its significance in guiding diagnosis and treatment decisions, identifying therapeutic targets, monitoring disease progression, and improving patient outcomes.

Evaluation of potential prevalence of onconeural antibodies in women with breast cancer

OBJECTIVE

Aim: To analyse onconeural antibodies in the blood serum of breast cancer patients without neurological symptoms..

PATIENTS AND METHODS

Materials and Methods: The study included 48 women with breast cancer. Paraneoplastic Neurologic Syndromes 12 Ag (IgG) Euroline by EUROIMMUN test was used to determine onconeural antibodies: anti-Hu, anti-Yo, anti-Ri, anti-CV2, anti-Ma/anti-Ta, anti-amphiphysin, anti-recoverin, anti-SOX1, anti-tytin, anti-zic4, anti-GAD65 and anti-Tr (DNER).

RESULTS

Results: The conducted analysis revealed the presence of onconeural antibodies such as: anti-recoverin, anti-CV2, anti-Zic4, anti-SOX1, anti-MA2/Ta and antititin in blood serum of women with breast cancer.

CONCLUSION

Conclusions: Further analysis may allow the assessment of the possible clinical usefulness of these determinations.

An optimized workflow of full-length transcriptome sequencing for accurate fusion transcript identification

Next-generation sequencing has revolutionized cancer genomics by enabling high-throughput mutation screening yet detecting fusion genes reliably remains challenging. Long-read sequencing offers potential for accurate fusion transcript identification, though challenges persist. In this study, we present an optimized workflow using nanopore sequencing technology to precisely identify fusion transcripts. Our approach encompasses a tailored library preparation protocol, data processing, and fusion gene analysis pipeline. We evaluated the performance using Universal Human Reference RNA and human adenocarcinoma cell lines. Our optimized nanopore sequencing workflow generated high-quality full-length transcriptome data characterized by an extended length distribution and comprehensive transcript coverage. Validation experiments confirmed novel fusion events with potential clinical relevance. Our protocol aims to mitigate biases and enhance accuracy, facilitating increased adoption in clinical diagnostics. Continued advancements in long-read sequencing promise deeper insights into fusion gene biology and improved cancer diagnostics.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

The application of long-read sequencing in clinical settings

Long-read DNA sequencing technologies have been rapidly evolving in recent years, and their ability to assess large and complex regions of the genome makes them ideal for clinical applications in molecular diagnosis and therapy selection, thereby providing a valuable tool for precision medicine. In the third-generation sequencing duopoly, Oxford Nanopore Technologies and Pacific Biosciences work towards increasing the accuracy, throughput, and portability of long-read sequencing methods while trying to keep costs low. These trades have made long-read sequencing an attractive tool for use in research and clinical settings. This article provides an overview of current clinical applications and limitations of long-read sequencing and explores its potential for point-of-care testing and health care in remote settings.

Decoding Oncofusions: Unveiling Mechanisms, Clinical Impact, and Prospects for Personalized Cancer Therapies

Cancer-associated gene fusions, also known as oncofusions, have emerged as influential drivers of oncogenesis across a diverse range of cancer types. These genetic events occur via chromosomal translocations, deletions, and inversions, leading to the fusion of previously separate genes. Due to the drastic nature of these mutations, they often result in profound alterations of cellular behavior. The identification of oncofusions has revolutionized cancer research, with advancements in sequencing technologies facilitating the discovery of novel fusion events at an accelerated pace. Oncofusions exert their effects through the manipulation of critical cellular signaling pathways that regulate processes such as proliferation, differentiation, and survival. Extensive investigations have been conducted to understand the roles of oncofusions in solid tumors, leukemias, and lymphomas. Large-scale initiatives, including the Cancer Genome Atlas, have played a pivotal role in unraveling the landscape of oncofusions by characterizing a vast number of cancer samples across different tumor types. While validating the functional relevance of oncofusions remains a challenge, even non-driver mutations can hold significance in cancer treatment. Oncofusions have demonstrated potential value in the context of immunotherapy through the production of neoantigens. Their clinical importance has been observed in both treatment and diagnostic settings, with specific fusion events serving as therapeutic targets or diagnostic markers. However, despite the progress made, there is still considerable untapped potential within the field of oncofusions. Further research and validation efforts are necessary to understand their effects on a functional basis and to exploit the new targeted treatment avenues offered by oncofusions. Through further functional and clinical studies, oncofusions will enable the advancement of precision medicine and the drive towards more effective and specific treatments for cancer patients.

Revealing the History and Mystery of RNA-Seq

Advances in RNA-sequencing technologies have led to the development of intriguing experimental setups, a massive accumulation of data, and high demand for tools to analyze it. To answer this demand, computational scientists have developed a myriad of data analysis pipelines, but it is less often considered what the most appropriate one is. The RNA-sequencing data analysis pipeline can be divided into three major parts: data pre-processing, followed by the main and downstream analyses. Here, we present an overview of the tools used in both the bulk RNA-seq and at the single-cell level, with a particular focus on alternative splicing and active RNA synthesis analysis. A crucial part of data pre-processing is quality control, which defines the necessity of the next steps; adapter removal, trimming, and filtering. After pre-processing, the data are finally analyzed using a variety of tools: differential gene expression, alternative splicing, and assessment of active synthesis, the latter requiring dedicated sample preparation. In brief, we describe the commonly used tools in the sample preparation and analysis of RNA-seq data.

Case Report: Clinical response to anaplastic lymphoma kinase inhibitor-based targeted therapy in uterine inflammatory myofibroblastic tumor harboring ALK-IGFBP5 fusion

Background

An inflammatory myofibroblastic tumor (IMT) is a mesenchymal tumor with a prevalence ranging from 0.04% to 0.7% worldwide, in which the lung is the most common predilection site, accounting for 33% of cases, followed by the abdomen, pelvis, mesentery, and uterus. Approximately 50% of uterine IMTs present as anaplastic lymphoma kinase (ALK) positive along with ALK gene fusion, which lays a solid foundation for the development of ALK-based target therapy to optimize treatment strategies.

Case presentation

Herein we describe a 57-year-old woman who presented with a slow-growing mass in the uterus for over 10 years and then received surgical resection because of significant progressive enlargement of the mass during follow-up. She was diagnosed with uterine leiomyosarcoma (LMS) with no further interventions until recurrence. We revised the diagnosis to uterine IMT based on diffuse ALK expression, ALK-IGFBP5 gene fusion, and the morphologic features of the tumors by pathology consultation. Based on these, we recommended an ALK tyrosine kinase inhibitor (TKI) treatment, crizotinib (250 mg bid), and she achieved a complete response (CR) with at least 18 months of progression-free survival (PFS). We monitored the dynamics of target lesions and peripheral blood cells at regular intervals through CT scans and routine blood tests during the treatment process. We present patient responses to ALK inhibitor-based targeted therapy with uterine IMT harboring ALK-IGFBP5 fusion, and the neutrophil-to-lymphocyte ratio (NLR) may be an effective indicator to predict prognosis.