Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector

Wnt/β-catenin activation by mutually exclusive FBXW11 and CTNNB1 hotspot mutations drives salivary basal cell adenoma

Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) of the salivary gland are rare tumours that can be difficult to distinguish from each other and other salivary gland tumour subtypes. Using next-generation sequencing, we identify a recurrent FBXW11 missense mutation (p.F517S) in BCA that is mutually exclusive with the previously reported CTNNB1 p.I35T gain-of-function (GoF) mutation with these mutations collectively accounting for 94% of BCAs. In vitro, mutant FBXW11 is characterised by defective binding to β-catenin and higher protein levels within the nucleus. This is consistent with the increased nuclear expression of β-catenin and activation of the Wnt/β-catenin pathway. The genomic profiles of BCAC are distinct from BCA, with hotspot DICER1 and HRAS mutations and putative driver mutations affecting PI3K/AKT and NF-κB signalling pathway genes. These findings have important implications for the diagnosis and treatment of BCA and BCAC, which, despite histopathologic overlap, may be unrelated entities.

Effective Utilization of a Customized Targeted Hybrid Capture RNA Sequencing in the Routine Molecular Categorization of Adolescent and Adult B-Lineage Acute Lymphoblastic Leukemia: A Real-World Experience

INTRODUCTION

Recent World Health Organization (WHO) and International Consensus Classifications have introduced numerous molecular entities in B-lineage acute lymphoblastic leukemia (B-ALL), necessitating comprehensive genomic characterization by detecting gene fusions, expression, mutations, and exon deletions. While whole-genome plus transcriptome sequencing is the ideal strategy, it remains cost-prohibitive for routine use. This study reports a cost-effective and reasonably efficient alternate approach integrating a customized targeted hybrid capture RNA sequencing (RNAseq) into the routine workup.

METHODOLOGY

A total of 95 consecutive adolescent/adult B-ALL cases negative for common chimeric gene fusions (CGF) (BCR::ABL1, KMT2A::AFF1, TCF3::PBX1, and ETV6::RUNX1) were analyzed using a customized 69-gene targeted RNAseq panel. In total, three fusion detection pipelines, the Trinity Cancer Transcriptome Analysis Toolkit (CTAT) Mutations pipeline, and the Toblerone alignment tool were employed, and the results were compared with fluorescence in situ hybridization (FISH)/multiplex ligation-dependent probe amplification (MLPA) testing.

RESULTS

RNAseq identified fusions in 43% of cases (including BCR::ABL1-like: 15.8% and IGH::DUX4: 10.5%), demonstrating superior detection of cryptic intrachromosomal rearrangements. Somatic variants were detected in 30% of cases (including rat sarcoma (RAS) pathway and Janus kinase (JAK)-signal transducers and activators of transcription (STAT) variants in 18% and 5.3% respectively), and IKZF1 deletions were detected in 25% (77% concordance with MLPA). The integration of targeted RNAseq and comprehensive bioinformatic analysis with flow-cytometry-based ploidy analysis and FISH-based IGH rearrangements helped categorize 79% of common CGF-negative B-ALL. The BCR::ABL1/BCR::ABL1-like group showed a higher frequency of pathogenic IKZF1 deletions (50% versus 21.7%; p = 0.011), measurable residual disease (92% versus 51%; p = 0.009), and poorer overall survival (8.6 versus 22.8 months; p = 0.07).

DISCUSSION AND CONCLUSIONS

Effective utilization of RNAseq data by comprehensive bioinformatic analysis to test fusions, mutations, and deletions, supported by only minimal supplementary FISH testing, provides a practical, cost-effective solution for the molecular characterization of B-ALL in real-world scenarios until a single alternative and cost-effective test is available.

Benchmarking mouse contamination removing protocols in patient-derived xenografts genomic profiling

Patient-derived xenograft (PDX) models are widely used in cancer research. Genomic and transcriptomic profiling of PDXs are inevitably contaminated by sequencing reads originated from mouse cells. Here, we examine the impact of mouse read contamination on RNA sequencing (RNAseq), Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS) data of 21 PDXs. We also systematically benchmark the performance of 12 computational protocols for removing mouse reads from PDXs. We find that mouse read contamination increases expression of immune and stromal related genes, and inflates the number of somatic mutations. However, detection of gene fusions and copy number alterations is minimally affected by mouse read contamination. Using gold standard datasets, we find that pseudo-alignment protocols often demonstrate better prediction performance and computing efficiency. The best performing tool is a relatively new tool Xengsort. Our results emphasize the importance of removing mouse reads from PDXs and the need to adopt new tools in PDX genomic studies.

Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics and prognostics and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short-read sequences. Recent advances in long-read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single-cell samples. Here, we developed a new computational tool, CTAT-LR-Fusion, to detect fusion transcripts from long-read RNA-seq with or without companion short reads, with applications to bulk or single-cell transcriptomes. We demonstrate that CTAT-LR-Fusion exceeds the fusion detection accuracy of alternative methods as benchmarked with simulated and genuine long-read RNA-seq. Using short- and long-read RNA-seq, we further apply CTAT-LR-Fusion to bulk transcriptomes of nine tumor cell lines and to tumor single cells derived from a melanoma sample and three metastatic high-grade serous ovarian carcinoma samples. In both bulk and single-cell RNA-seq, long isoform reads yield higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-Fusion, we are able to further maximize the detection of fusion splicing isoforms and fusion-expressing tumor cells.

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.

Comparative analysis of RNA expression in a single institution cohort of pediatric cancer patients

With the low incidence of mutations in pediatric cancers, alternate genomic approaches are needed to identify therapeutic targets. Our study, the Comparative Analysis of RNA Expression to Improve Pediatric and Young Adult Cancer Treatment, was conducted by the UC Santa Cruz Treehouse Childhood Cancer Initiative and Stanford University School of Medicine. RNA sequencing data from 33 children and young adults with a relapsed, refractory or rare cancer underwent CARE analysis to reveal activated cancer driver pathways and nominate treatments. We compare our pipeline to other gene expression outlier detection approaches and discuss challenges for clinical implementation. Of our 33 patients, 31 (94%) had findings of potential clinical significance. Findings were implemented in 5 patients, 3 of which had defined clinical benefit. We demonstrate that comparator cohort composition determines which outliers are detected. This study highlights the clinical utility and challenges of implementing comparative RNA sequencing analysis in the clinic.

Frequent lncRNA-derived fusions in pediatric neuroblastoma identified by LncFusion : potential biomarker and therapeutic implications

Despite growing interest in the onco-fusion proteins and long noncoding RNAs (lncRNAs) in cancers, lncRNA-derived fusion transcripts in pediatric cancers remain understudied. To address this gap, we first developed LncFusion , a novel computational pipeline that systematically detects lncRNA-derived fusion transcripts from RNA-seq data. Leveraging our previously published Flnc (for comprehensive lncRNA identification) as a foundation and applying LncFusion , we identified over 900 high-confidence lncRNA-derived fusions (lnc-fusions) in pediatric neuroblastoma by analyzing the transcriptomics datasets from three major pediatric cancer cohorts-TARGET, Gabriella Miller Kids First, and St. Jude Cloud. The number of lnc-fusions exceeds the number of mRNA-derived fusions (mRNA-fusions) in neuroblastoma. Whole genome sequencing analyses revealed that approximately 40% of these lnc-fusions result from chromosomal rearrangements, while over 60% may arise from aberrant splicing events. Among these high-confidence lnc-fusions, 61 are enriched in pediatric neuroblastoma compared to healthy controls; and 20s exhibit subtype-specific expressions in pediatric neuroblastoma patients, which would be categorized into three groups: MYCN-amplified patients, c-MYC-highly expressed patients and the remaining (MYCN-unamplified and c-MYC not high expression). Subtype-specific enrichment of certain lnc-fusions, particularly in MYCN-amplified and c-MYC-high subgroups, underscores distinct oncogenic roles. Further functional studies implicated lnc-fusions in key pathways related to neuron development, translation, and energy metabolism, suggesting potential contributions to neuroblastoma pathogenesis. Additionally, We found several novel fusions might serve as potential diagnostic or prognostic biomarkers in neuroblastoma. A few candidates correlate with either favorable histology and lower-risk patient subsets, or poorer survival outcomes, indicating strong prognostic biomarker potential. Experiments in cell line further confirmed the presence of a few key lnc-fusions discovered from patient samples. Our findings provide the first comprehensive insight into lncRNA-derived fusions in pediatric neuroblastoma, providing the promise of lnc-fusions as novel biomarkers and therapeutic targets. The LncFusion tool developed can also be applied to explore lnc-fusions in other pediatric and adult cancers.

Comprehensive genomic characterization of early-stage bladder cancer

Understanding the molecular landscape of nonmuscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and treatment regimens. We performed a comprehensive genomic analysis of patients with NMIBC using whole-exome sequencing (n = 438), shallow whole-genome sequencing (n = 362) and total RNA sequencing (n = 414). A large genomic variation within NMIBC was observed and correlated with different molecular subtypes. Frequent loss of heterozygosity in FGFR3 and 17p (affecting TP53) was found in tumors with mutations in FGFR3 and TP53, respectively. Whole-genome doubling (WGD) was observed in 15% of the tumors and was associated with worse outcomes. Tumors with WGD were genomically unstable, with alterations in cell-cycle-related genes and an altered immune composition. Finally, integrative clustering of multi-omics data highlighted the important role of genomic instability and immune cell exhaustion in disease aggressiveness. These findings advance our understanding of genomic differences associated with disease aggressiveness in NMIBC and may ultimately improve patient stratification.

The contribution of the novel CLTC-VMP1 fusion gene to autophagy regulation and energy metabolism in cisplatin-resistant osteosarcoma

Osteosarcoma (OS) is a highly malignant tumor, and chemotherapy resistance is a major challenge in the treatment of this disease. This study aims to explore the role of the CLTC-VMP1 gene fusion in the mechanism of chemotherapy resistance in OS and investigate its molecular mechanisms in mediating energy metabolism reprogramming by regulating autophagy and apoptosis balance. Using single-cell transcriptome analysis, the heterogeneity of OS cells and their correlation with resistance to platinum drugs were revealed. Cisplatin-resistant cell lines were established in human OS cell lines for subsequent experiments. Based on transcriptomic analysis, the importance of VMP1 in chemotherapy resistance was confirmed. Lentiviral vectors overexpressing or interfering with VMP1 were used, and it was observed that inhibiting VMP1 could reverse cisplatin resistance, promote cell apoptosis, and inhibit autophagy, and mitochondrial respiration and glycolysis. Furthermore, the presence of CLTC-VMP1 gene fusion was validated, and its ability to regulate autophagy and apoptosis balance, promote mitochondrial respiration, and glycolysis was demonstrated. Mouse model experiments further confirmed the promoting effect of CLTC-VMP1 on tumor growth and chemotherapy resistance. In summary, the CLTC-VMP1 gene fusion mediates energy metabolism reprogramming by regulating autophagy and apoptosis balance, which promotes chemotherapy resistance in OS.NEW & NOTEWORTHY This study identifies the CLTC-VMP1 gene fusion as a key driver of chemotherapy resistance in osteosarcoma by regulating autophagy and reprogramming cellular energy metabolism. Through single-cell transcriptomics, the research reveals the heterogeneity of tumor cells and the role of VMP1 in promoting resistance to cisplatin. The findings suggest that targeting the CLTC-VMP1 fusion gene may offer new therapeutic strategies to overcome chemotherapy resistance in osteosarcoma.

CTAT-LR-fusion: accurate fusion transcript identification from long and short read isoform sequencing at bulk or single cell resolution

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.