Anchored random reverse primer sequencing for quantitative detection of novel gene fusions

anchored-random-reverse-primer-sequencing-for-quantitative-detection-of-novel-gene-fusions
Anchored random reverse primer sequencing for quantitative detection of novel gene fusions
  • Gao, Q. et al. Driver fusions and their implications in the development and treatment of human cancers. Cell Rep. 23, 227–238.e3 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Su, X. et al. Challenges and prospects in utilizing technologies for gene fusion analysis in cancer diagnostics. Med-X 2, 14 (2024).

    Article  CAS  Google Scholar 

  • Burke, B. A. & Carroll, M. BCR-ABL: a multi-faceted promoter of DNA mutation in chronic myelogeneous leukemia. Leukemia 24, 1105–1112 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yuan, L. et al. Recurrent FGFR3-TACC3 fusion gene in nasopharyngeal carcinoma. Cancer Biol. Ther. 15, 1613–1621 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tamura, R. et al. Novel therapeutic strategy for cervical cancer harboring FGFR3-TACC3 fusions. Oncogenesis 7, 4 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Lasorella, A., Sanson, M. & Iavarone, A. FGFR-TACC gene fusions in human glioma. Neuro Oncol. 19, 475–483 (2016).

    PubMed Central  Google Scholar 

  • Singh, D. et al. Transforming fusions of FGFR and TACC genes in human glioblastoma. Science 337, 1231–1235 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Weinstein, J. N. et al. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature 507, 315–322 (2014).

    Article  CAS  Google Scholar 

  • Carneiro, B. A. et al. FGFR3–TACC3: a novel gene fusion in cervical cancer. Gynecol. Oncol. Rep. 13, 53–56 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Ren, R. Mechanisms of BCR–ABL in the pathogenesis of chronic myelogenous leukaemia. Nat. Rev. Cancer 5, 172–183 (2005).

    Article  CAS  PubMed  Google Scholar 

  • An, X. et al. BCR-ABL tyrosine kinase inhibitors in the treatment of Philadelphia chromosome positive chronic myeloid leukemia: a review. Leuk. Res. 34, 1255–1268 (2010).

    Article  CAS  PubMed  Google Scholar 

  • Peters, S. et al. Alectinib versus crizotinib in untreated ALK-positive non–small-cell lung cancer. N. Engl. J. Med. 377, 829–838 (2017).

    Article  CAS  PubMed  Google Scholar 

  • Abou-Alfa, G. K. et al. Pemigatinib for previously treated, locally advanced or metastatic cholangiocarcinoma: a multicentre, open-label, phase 2 study. Lancet Oncol. 21, 671–684 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kang, C. Infigratinib: first approval. Drugs 81, 1355–1360 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li, Z. et al. Efficacy of crizotinib among different types of ROS1 fusion partners in patients with ROS1-rearranged non-small cell lung cancer. J. Thorac. Oncol. 13, 987–995 (2018).

    Article  PubMed  Google Scholar 

  • Lin, J. J. et al. Impact of EML4-ALK variant on resistance mechanisms and clinical outcomes in ALK-positive lung cancer. J. Clin. Oncol. 36, 1199–1206 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Huber, D., Voith von Voithenberg, L. & Kaigala, G. V. Fluorescence in situ hybridization (FISH): history, limitations and what to expect from micro-scale FISH?. Micro Nano Eng. 1, 15–24 (2018).

    Article  Google Scholar 

  • Schröck, E. et al. Multicolor spectral karyotyping of human chromosomes. Science 273, 494–497 (1996).

    Article  PubMed  Google Scholar 

  • Volpi, E. V. & Bridger, J. M. FISH glossary: an overview of the fluorescence in situ hybridization technique. BioTechniques 45, 385–409 (2008).

    Article  CAS  PubMed  Google Scholar 

  • Xie, N. G. et al. Designing highly multiplex PCR primer sets with Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE). Nat. Commun. 13, 1881 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mohajeri, A. et al. Comprehensive genetic analysis identifies a pathognomonic NAB2/STAT6 fusion gene, nonrandom secondary genomic imbalances, and a characteristic gene expression profile in solitary fibrous tumor. Genes Chromosomes Cancer 52, 873–886 (2013).

    Article  CAS  PubMed  Google Scholar 

  • Weber, D. et al. Accurate detection of tumor-specific gene fusions reveals strongly immunogenic personal neo-antigens. Nat. Biotechnol. 40, 1276–1284 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Haas, B. J. et al. Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods. Genome Biol. 20, 213 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  • Wu, Y. et al. Enhanced detection of novel low-frequency gene fusions via high-yield ligation and multiplexed enrichment sequencing. Angew. Chem. Int. Ed. Engl. 63, e202316484 (2024).

    Article  CAS  PubMed  Google Scholar 

  • Zheng, Z. et al. Anchored multiplex PCR for targeted next-generation sequencing. Nat. Med. 20, 1479–1484 (2014).

    Article  CAS  PubMed  Google Scholar 

  • Peng, Q. et al. Targeted single primer enrichment sequencing with single end duplex-UMI. Sci. Rep. 9, 4810 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  • Heydt, C. et al. Detection of gene fusions using targeted next-generation sequencing: a comparative evaluation. BMC Med. Genom. 14, 62 (2021).

    Article  CAS  Google Scholar 

  • Song, P. et al. Selective multiplexed enrichment for the detection and quantitation of low-fraction DNA variants via low-depth sequencing. Nat. Biomed. Eng. 5, 690–701 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li, L. et al. High efficiency hydrodynamic DNA fragmentation in a bubbling system. Sci. Rep. 7, 40745 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Aigrain, L., Gu, Y. & Quail, M. A. Quantitation of next generation sequencing library preparation protocol efficiencies using droplet digital PCR assays – a systematic comparison of DNA library preparation kits for Illumina sequencing. BMC Genom. 17, 458 (2016).

    Article  Google Scholar 

  • Wang, L. et al. 3′ Branch ligation: a novel method to ligate non-complementary DNA to recessed or internal 3’OH ends in DNA or RNA. DNA Res. 26, 45–53 (2019).

    Article  PubMed  Google Scholar 

  • Song, P. et al. Limitations and opportunities of technologies for the analysis of cell-free DNA in cancer diagnostics. Nat. Biomed. Eng. 6, 232–245 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Park, H. J., Baek, I., Cheang, G., Solomon, J. P. & Song, W. Comparison of RNA-based next-generation sequencing assays for the detection of NTRK gene fusions. J. Mol. Diagn. 23, 1443–1451 (2021).

    Article  CAS  PubMed  Google Scholar 

  • Sohn, J. et al. Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets. Nat. Biomed. Eng. 7, 853–866 (2023).

  • Carstensen, B., Simpson, J. & Gurrin, L. C. Statistical models for assessing agreement in method comparison studies with replicate measurements. Int. J. Biostat. 4, 16 (2008).

  • Cunningham, F. et al. Ensembl 2022. Nucleic Acids Res. 50, D988–D995 (2022).

    Article  CAS  PubMed  Google Scholar 

  • Bergeron, D. et al. RNA-seq for the detection of gene fusions in solid tumors: development and validation of the JAX FusionSeq 2.0 assay. J. Mol. Med. 100, 323–335 (2022).

    Article  CAS  PubMed  Google Scholar 

  • Palomares, M.-A. et al. Systematic analysis of TruSeq, SMARTer and SMARTer Ultra-Low RNA-seq kits for standard, low and ultra-low quantity samples. Sci. Rep. 9, 7550 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  • Kerbs, P. et al. Gene fusion detection by RNA-seq in acute myeloid leukemia (AML). Blood 134, 4655 (2019).

    Article  Google Scholar 

  • Benelli, M. et al. Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript. Bioinformatics 28, 3232–3239 (2012).

    Article  CAS  PubMed  Google Scholar 

  • Haas, B. J. et al. STAR-Fusion: fast and accurate fusion transcript detection from RNA-seq. Preprint at bioRxiv https://doi.org/10.1101/120295 (2017).

  • Nicorici, D. et al. FusionCatcher – a tool for finding somatic fusion genes in paired-end RNA-sequencing data. Preprint at bioRxiv https://doi.org/10.1101/011650 (2014).

  • Uhrig, S. et al. Accurate and efficient detection of gene fusions from RNA sequencing data. Genome Res. 31, 448–460 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Si, Y. et al. Extended enrichment for ultrasensitive detection of low-frequency mutations by long blocker displacement amplification. Angew. Chem. Int. Ed. Engl. 63, e202400551 (2024).

    Article  CAS  PubMed  Google Scholar 

  • Kivioja, T. et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72–74 (2012).

    Article  CAS  Google Scholar 

  • Shiroguchi, K., Jia, T. Z., Sims, P. A. & Xie, X. S. Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes. Proc. Natl Acad. Sci. USA 109, 1347–1352 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Stoler, N. & Nekrutenko, A. Sequencing error profiles of Illumina sequencing instruments. NAR Genom. Bioinform. 3, lqab019 (2021).

  • Lu, B., Jiang, R., Xie, B., Wu, W. & Zhao, Y. Fusion genes in gynecologic tumors: the occurrence, molecular mechanism and prospect for therapy. Cell Death Dis. 12, 783 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Liu, S. et al. Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data. Nucleic Acids Res. 44, e47 (2016).

    Article  PubMed  Google Scholar 

  • Dehghannasiri, R. et al. Improved detection of gene fusions by applying statistical methods reveals oncogenic RNA cancer drivers. Proc. Natl Acad. Sci. USA 116, 15524–15533 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Heyer, E. E. et al. Diagnosis of fusion genes using targeted RNA sequencing. Nat. Commun. 10, 1388 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cappellen, D. et al. Frequent activating mutations of FGFR3 in human bladder and cervix carcinomas. Nat. Genet. 23, 18–20 (1999).

    Article  CAS  PubMed  Google Scholar 

  • Choi, C. H., Chung, J.-Y., Kim, J.-H., Kim, B.-G. & Hewitt, S. M. Expression of fibroblast growth factor receptor family members is associated with prognosis in early stage cervical cancer patients. J. Transl. Med. 14, 124 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Hiranuma, K. et al. Rare FGFR fusion genes in cervical cancer and transcriptome-based subgrouping of patients with a poor prognosis. Cancer Med. 12, 17835–17848 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Loeb, S. & Catalona, W. J. Prostate-specific antigen in clinical practice. Cancer Lett. 249, 30–39 (2007).

    Article  CAS  PubMed  Google Scholar 

  • Schatteman, P. H., Hoekx, L., Wyndaele, J. J., Jeuris, W. & van Marck, E. Inflammation in prostate biopsies of men without prostatic malignancy or clinical prostatitis: correlation with total serum PSA and PSA density. Eur. Urol. 37, 404–412 (2000).

    Article  CAS  PubMed  Google Scholar 

  • Kumar-Sinha, C., Tomlins, S. A. & Chinnaiyan, A. M. Recurrent gene fusions in prostate cancer. Nat. Rev. Cancer 8, 497–511 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Attard, G. et al. Prostate cancer. Lancet 387, 70–82 (2016).

    Article  PubMed  Google Scholar 

  • Huang, L. et al. FPIA: a database for gene fusion profiling and interactive analyses. Int. J. Cancer 150, 1504–1511 (2022).

    Article  CAS  PubMed  Google Scholar 

  • Luo, J. H. et al. Discovery and classification of fusion transcripts in prostate cancer and normal prostate tissue. Am. J. Pathol. 185, 1834–1845 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kong, D. P. et al. Prevalence and clinical application of TMPRSS2-ERG fusion in Asian prostate cancer patients: a large-sample study in Chinese people and a systematic review. Asian J. Androl. 22, 200–207 (2020).

    Article  PubMed  Google Scholar 

  • Ren, S. et al. RNA-seq analysis of prostate cancer in the Chinese population identifies recurrent gene fusions, cancer-associated long noncoding RNAs and aberrant alternative splicings. Cell Res. 22, 806–821 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pettersson, A. et al. The TMPRSS2:ERG rearrangement, ERG expression, and prostate cancer outcomes: a cohort study and meta-analysis. Cancer Epidemiol. Biomark. Prev. 21, 1497–1509 (2012).

    Article  Google Scholar 

  • Soller, M. J. et al. Confirmation of the high frequency of the TMPRSS2/ERG fusion gene in prostate cancer. Genes Chromosomes Cancer 45, 717–719 (2006).

    Article  CAS  PubMed  Google Scholar 

  • Tomlins, S. A. et al. Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA. Sci. Transl. Med. 3, 94ra72 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Qu, X., Yeung, C., Coleman, I., Nelson, P. S. & Fang, M. Comparison of four next generation sequencing platforms for fusion detection: Oncomine by ThermoFisher, AmpliSeq by illumina, FusionPlex by ArcherDX, and QIAseq by QIAGEN. Cancer Genet. 243, 11–18 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang, J.-T. et al. Longitudinal undetectable molecular residual disease defines potentially cured population in localized non-small cell lung cancer. Cancer Discov. 12, 1690–1701 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Romano, G. et al. A preexisting rare PIK3CA(E545K) subpopulation confers clinical resistance to MEK plus CDK4/6 inhibition in NRAS melanoma and is dependent on S6K1 signaling. Cancer Discov. 8, 556–567 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Song, P. et al. Programming bulk enzyme heterojunctions for biosensor development with tetrahedral DNA framework. Nat. Commun. 11, 838 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhao, H. et al. Programming super DNA-enzyme molecules for on-demand enzyme activity modulation. Angew. Chem. Int. Ed. Engl. 62, e202214450 (2023).

    Article  CAS  PubMed  Google Scholar 

  • Shao, L. et al. CMTM5 exhibits tumor suppressor activities and is frequently silenced by methylation in carcinoma cell lines. Clin. Cancer Res. 13, 5756–5762 (2007).

    Article  CAS  PubMed  Google Scholar 

  • Bueno, R. et al. Comprehensive genomic analysis of malignant pleural mesothelioma identifies recurrent mutations, gene fusions and splicing alterations. Nat. Genet. 48, 407–416 (2016).

    Article  CAS  PubMed  Google Scholar 

  • Sondka, Z. et al. The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers. Nat. Rev. Cancer 18, 696–705 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kim, P. et al. FusionGDB 2.0: fusion gene annotation updates aided by deep learning. Nucleic Acids Res. 50, D1221–d1230 (2022).

    Article  CAS  PubMed  Google Scholar 

  • Hu, X. et al. TumorFusions: an integrative resource for cancer-associated transcript fusions. Nucleic Acids Res. 46, D1144–d1149 (2018).

    Article  CAS  PubMed  Google Scholar 

  • Zhang, J. X. et al. A deep learning model for predicting next-generation sequencing depth from DNA sequence. Nat. Commun. 12, 4387 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lebedev, A. V. et al. Hot Start PCR with heat-activatable primers: a novel approach for improved PCR performance. Nucleic Acids Res. 36, e131 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  • Dobosy, J. R. et al. RNase H-dependent PCR (rhPCR): improved specificity and single nucleotide polymorphism detection using blocked cleavable primers. BMC Biotechnol. 11, 80 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Boratyn, G. M. et al. BLAST: a more efficient report with usability improvements. Nucleic Acids Res. 41, W29–W33 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • Chen, T. et al. The Genome Sequence Archive Family: toward explosive data growth and diverse data types. Genomics Proteomics Bioinformatics 19, 578–583 (2021).

  • CNCB-NGDC Members and Partners. Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025. Nucleic Acids Res. 53, D30–d44 (2025).

    Article  Google Scholar 

  • Xiu, X. et al. Anchored random reverse primer sequencing for quantitative detection of novel gene fusions. Datasets. figshare https://figshare.com/articles/dataset/Source_Data/29492369 (2025).

  • Xiu, X. et al. Anchored random reverse primer sequencing for quantitative detection of novel gene fusions. GitHub https://github.com/NABMElab/ARRP-seq (2025).