The INSPECTOR study: enhanced feasibility for clinical translation of a multi-cancer early detection method based on enzyme-assisted high signal-to-noise ratio sequencing of methylated circulating tumor DNA

Hui-Yan Luo , Wei Wei , Pansong Li , Qi-Hua Zhang , Zhipeng Zhou , Liang Cui , Yong-Bin Lin , Hong Yang , Xianyu Zhong , Qingfeng Liu , Han Yang , Kong-Jia Luo , Hai-Bo Qiu , Shu-Qiang Yuan , Yuan-Fang Li , Zhi-Wei Zhou , Xiao-Jun Lin , Bo-Kang Cui , Rong-Xin Zhang , Wen-Hua Fan , He Huang , Chun-Yan Lan , Jun-Dong Li , Zhi-Qiang Wang , Bin-Kui Li , Rong-Ping Guo , Jun Tang , Xin Huang , Mian Xi , Yuying Liu , Chuanbo Xie , Shi Chen , Zhi-Hu Li , Yu-Hua Liu , Xiao-Ting Zhang , Qiang Zeng , Xin Yi , Rui-Hua Xu

Cancer Communications ›› 2025, Vol. 45 ›› Issue (12) : 1645 -1665.

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Cancer Communications ›› 2025, Vol. 45 ›› Issue (12) :1645 -1665. DOI: 10.1002/cac2.70071
ORIGINAL ARTICLE
The INSPECTOR study: enhanced feasibility for clinical translation of a multi-cancer early detection method based on enzyme-assisted high signal-to-noise ratio sequencing of methylated circulating tumor DNA
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Abstract

Background: Blood-based cell-free DNA (cfDNA) methylation testing has emerged as a promising approach for multi-cancer early detection (MCED), holding the potential to improve cancer survival rates. However, traditional bisulfite-based methods often encounter sensitivity limitations in detecting early-stage malignancies or certain cancer types. In the INSPECTOR study, we developed a MCED and cancer signal origin (CSO) system specifically designed for early-stage or hard-to-detect cancers, including those of the lung, breast, colorectum, liver, esophagus, stomach, pancreas, and ovary.

Methods: We established a comprehensive methylation marker discovery database (n = 6,342) by integrating public datasets (n = 4,699) and in-house samples (n = 1,643), all processed using human TET (hTET) enzyme-assisted whole-methylome sequencing (GM-seq). This enabled the design of a targeted panel encompassing 155,362 methylated CpG sites. Leveraging hTET-assisted high-depth next-generation sequencing (NGS), our blood test achieved a median unique depth of 1,093×. Multicenter case-control cohorts, including various pathological subtypes, were used for training, validation, and independent validation of MCED and CSO models, and to verify the clinical feasibility.

Results: Clinical validation was conducted across multi-center case-control cohorts, including 1,071 participants in the training set, 581 in the validation set, and 824 in the independent validation set. The MCED assay demonstrated robust performance with a specificity of 99.1% and sensitivity of 83.2% in the training set, 99.0% and 81.8% in the validation set, and comparable results in the independent validation set (99.0% specificity, 81.9% sensitivity). Notably, sensitivity reached 65.5% for stage I cancers, 79.7% for stage II, and 71.3% for stages I-II combined. The sensitivities for different cancer types were as follows: esophageal (79.2%), gastric (76.1%), colorectal (86.2%), pancreatic (66.7%), liver (100.0%), lung (72.9%), breast (88.9%), and ovarian (87.9%). The CSO model exhibited strong accuracy, with top-1 cancer origin prediction rates of 87.9% (validation) and 87.4% (independent validation), rising to 95.1% and 94.5% for top-2 predictions, respectively. For stage I cancers specifically, the top-1 accuracy was 85.5%.

Conclusions: These findings underscore the efficacy of the hTET-assisted cfDNA methylation sequencing system across diverse cancer types, particularly in early stages. Enzyme-assisted NGS test of methylated cfDNA thus enhances the clinical utility of non-invasive blood-based screening.

Keywords

cell-free DNA / cancer signal origin / multi-cancer early detection / methylation sequencing

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Hui-Yan Luo, Wei Wei, Pansong Li, Qi-Hua Zhang, Zhipeng Zhou, Liang Cui, Yong-Bin Lin, Hong Yang, Xianyu Zhong, Qingfeng Liu, Han Yang, Kong-Jia Luo, Hai-Bo Qiu, Shu-Qiang Yuan, Yuan-Fang Li, Zhi-Wei Zhou, Xiao-Jun Lin, Bo-Kang Cui, Rong-Xin Zhang, Wen-Hua Fan, He Huang, Chun-Yan Lan, Jun-Dong Li, Zhi-Qiang Wang, Bin-Kui Li, Rong-Ping Guo, Jun Tang, Xin Huang, Mian Xi, Yuying Liu, Chuanbo Xie, Shi Chen, Zhi-Hu Li, Yu-Hua Liu, Xiao-Ting Zhang, Qiang Zeng, Xin Yi, Rui-Hua Xu. The INSPECTOR study: enhanced feasibility for clinical translation of a multi-cancer early detection method based on enzyme-assisted high signal-to-noise ratio sequencing of methylated circulating tumor DNA. Cancer Communications, 2025, 45(12): 1645-1665 DOI:10.1002/cac2.70071

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References

[1]

Diao X, Guo C, Jin Y, Li B, Gao X, Du X, et al. Cancer situation in China: an analysis based on the global epidemiological data released in 2024. Cancer Commun (Lond). 2025;45(2):178-97.

[2]

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49.

[3]

Crosby D, Bhatia S, Brindle KM, Coussens LM, Dive C, Emberton M, et al. Early detection of cancer. Science. 2022;375(6586):eaay9040.

[4]

Force USPST, Nicholson WK, Silverstein M, Wong JB, Barry MJ, Chelmow D, et al. Screening for Breast Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2024;331(22):1918-30.

[5]

Force USPST, Curry SJ, Krist AH, Owens DK, Barry MJ, Caughey AB, et al. Screening for Cervical Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;320(7):674-86.

[6]

Force USPST, Davidson KW, Barry MJ, Mangione CM, Cabana M, Caughey AB, et al. Screening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021;325(19):1965-77.

[7]

Force USPST, Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, et al. Screening for Lung Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2021;325(10):962-70.

[8]

Force USPST, Grossman DC, Curry SJ, Owens DK, Bibbins-Domingo K, Caughey AB, et al. Screening for Prostate Cancer: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319(18):1901-13.

[9]

Imperiale TF, Ransohoff DF, Itzkowitz SH. Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med. 2014;371(2):187-8.

[10]

Lamb YN, Dhillon S. Epi proColon® 2.0 CE: A Blood-Based Screening Test for Colorectal Cancer. Mol Diagn Ther. 2017;21(2):225-32.

[11]

Barnell EK, Wurtzler EM, La Rocca J, Fitzgerald T, Petrone J, Hao Y, et al. Multitarget Stool RNA Test for Colorectal Cancer Screening. Jama. 2023;330(18):1760-8.

[12]

Connal S, Cameron JM, Sala A, Brennan PM, Palmer DS, Palmer JD, et al. Liquid biopsies: the future of cancer early detection. J Transl Med. 2023;21(1):118.

[13]

Jonas DE, Reuland DS, Reddy SM, Nagle M, Clark SD, Weber RP, et al. Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2021;325(10):971-87.

[14]

Zhao F, Bai P, Xu J, Li Z, Muhammad S, Li D, et al. Efficacy of cell-free DNA methylation-based blood test for colorectal cancer screening in high-risk population: a prospective cohort study. Mol Cancer. 2023;22(1):157.

[15]

Zhang K, Fu R, Liu R, Su Z. Circulating cell-free DNA-based multi-cancer early detection. Trends Cancer. 2024;10(2):161-74.

[16]

Braunstein GD, Ofman JJ. Criteria for Evaluating Multi-cancer Early Detection Tests. Oncol Haematol. 2021;17:3-6.

[17]

Dor Y, Cedar H. Principles of DNA methylation and their implications for biology and medicine. Lancet. 2018;392(10149):777-86.

[18]

Chen X, Gole J, Gore A, He Q, Lu M, Min J, et al. Non-invasive early detection of cancer four years before conventional diagnosis using a blood test. Nat Commun. 2020;11(1):3475.

[19]

Jamshidi A, Liu MC, Klein EA, Venn O, Hubbell E, Beausang JF, et al. Evaluation of cell-free DNA approaches for multi-cancer early detection. Cancer Cell. 2022;40(12):1537-49.e12.

[20]

Loyfer N, Magenheim J, Peretz A, Cann G, Bredno J, Klochendler A, et al. A DNA methylation atlas of normal human cell types. Nature. 2023;613(7943):355-64.

[21]

Liu MC, Oxnard GR, Klein EA, Swanton C, Seiden MV, Consortium C. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020;31(6):745-59.

[22]

Schrag D, Beer TM, McDonnell CH, Nadauld L, Dilaveri CA, Reid R, et al. Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study. Lancet. 2023;402(10409):1251-60.

[23]

Nicholson BD, Oke J, Virdee PS, Harris DA, O'Doherty C, Park JE, et al. Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study. Lancet Oncol. 2023;24(7):733-43.

[24]

Klein EA, Richards D, Cohn A, Tummala M, Lapham R, Cosgrove D, et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann Oncol. 2021;32(9):1167-77.

[25]

Gao Q, Lin YP, Li BS, Wang GQ, Dong LQ, Shen BY, et al. Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies. Ann Oncol. 2023;34(5):486-95.

[26]

Bie F, Wang Z, Li Y, Guo W, Hong Y, Han T, et al. Multimodal analysis of cell-free DNA whole-methylome sequencing for cancer detection and localization. Nat Commun. 2023;14(1):6042.

[27]

Huang A, Guo DZ, Su ZX, Zhong YS, Liu L, Xiong ZG, et al. GUIDE: a prospective cohort study for blood-based early detection of gastrointestinal cancers using targeted DNA methylation and fragmentomics sequencing. Mol Cancer. 2025;24(1):163.

[28]

Singer BD. A Practical Guide to the Measurement and Analysis of DNA Methylation. Am J Respir Cell Mol Biol. 2019;61(4):417-28.

[29]

Dai Q, Ye C, Irkliyenko I, Wang Y, Sun HL, Gao Y, et al. Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA. Nat Biotechnol. 2024;42(10):1559-1570.

[30]

Olova N, Krueger F, Andrews S, Oxley D, Berrens RV, Branco MR, et al. Comparison of whole-genome bisulfite sequencing library preparation strategies identifies sources of biases affecting DNA methylation data. Genome Biol. 2018;19(1):33.

[31]

Zheng RS, Chen R, Han BF, Wang SM, Li L, Sun KX, et al. [Cancer incidence and mortality in China, 2022]. Zhonghua Zhong Liu Za Zhi. 2024;46(3):221-31.

[32]

Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229-63.

[33]

Chen X, Liu J, Li J, Xie Y, Yu Z, Shen L, et al. Identification of DNA methylation and genetic alteration simultaneously from a single blood biopsy. Genes Genomics. 2023;45(5):627-35.

[34]

Flahault A, Cadilhac M, Thomas G. Sample size calculation should be performed for design accuracy in diagnostic test studies. J Clin Epidemiol. 2005;58(8):859-62.

[35]

Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884-i90.

[36]

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078-9.

[37]

Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, et al. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet. 2009;41(2):178-86.

[38]

Baca SC, Seo JH, Davidsohn MP, Fortunato B, Semaan K, Sotudian S, et al. Liquid biopsy epigenomic profiling for cancer subtyping. Nat Med. 2023;29(11):2737-41.

[39]

Li S, Zeng W, Ni X, Liu Q, Li W, Stackpole ML, et al. Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring. Proc Natl Acad Sci U S A. 2023;120(28):e2305236120.

[40]

Luo H, Zhao Q, Wei W, Zheng L, Yi S, Li G, et al. Circulating tumor DNA methylation profiles enable early diagnosis, prognosis prediction, and screening for colorectal cancer. Sci Transl Med. 2020;12(524).

[41]

Wu L, Yao H, Chen H, Wang A, Guo K, Gou W, et al. Landscape of somatic alterations in large-scale solid tumors from an Asian population. Nat Commun. 2022;13(1):4264.

[42]

Carrot-Zhang J, Chambwe N, Damrauer JS, Knijnenburg TA, Robertson AG, Yau C, et al. Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer. Cancer Cell. 2020;37(5):639-54.e6.

[43]

Guo S, Diep D, Plongthongkum N, Fung HL, Zhang K, Zhang K. Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA. Nat Genet. 2017;49(4):635-42.

[44]

Hao X, Luo H, Krawczyk M, Wei W, Wang W, Wang J, et al. DNA methylation markers for diagnosis and prognosis of common cancers. Proc Natl Acad Sci U S A. 2017;114(28):7414-9.

[45]

Kan Z, Ding Y, Kim J, Jung HH, Chung W, Lal S, et al. Multi-omics profiling of younger Asian breast cancers reveals distinctive molecular signatures. Nat Commun. 2018;9(1):1725.

[46]

Dai H, Yan Y, Wang P, Liu P, Cao Y, Xiong L, et al. Distribution of mammographic density and its influential factors among Chinese women. Int J Epidemiol. 2014;43(4):1240-51.

[47]

Fukuoka M, Wu YL, Thongprasert S, Sunpaweravong P, Leong SS, Sriuranpong V, et al. Biomarker analyses and final overall survival results from a phase III, randomized, open-label, first-line study of gefitinib versus carboplatin/paclitaxel in clinically selected patients with advanced non-small-cell lung cancer in Asia (IPASS). J Clin Oncol. 2011;29(21):2866-74.

[48]

Zhang JT, Liu SY, Gao W, Liu SM, Yan HH, Ji L, et al. Longitudinal Undetectable Molecular Residual Disease Defines Potentially Cured Population in Localized Non-Small Cell Lung Cancer. Cancer Discov. 2022;12(7):1690-701.

[49]

Mattox AK, Douville C, Wang Y, Popoli M, Ptak J, Silliman N, et al. The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer. Cancer Discov. 2023;13(10):2166-79.

[50]

Nagaraja AK, Kikuchi O, Bass AJ. Genomics and Targeted Therapies in Gastroesophageal Adenocarcinoma. Cancer Discov. 2019;9(12):1656-72.

[51]

Bao H, Yang S, Chen X, Dong G, Mao Y, Wu S, et al. Early detection of multiple cancer types using multidimensional cell-free DNA fragmentomics. Nat Med. 2025;31(8):2737-2745.

[52]

López-Otín C, Pietrocola F, Roiz-Valle D, Galluzzi L, Kroemer G. Meta-hallmarks of aging and cancer. Cell Metab. 2023;35(1):12-35.

[53]

Xu RH, Wei W, Krawczyk M, Wang W, Luo H, Flagg K, et al. Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma. Nat Mater. 2017;16(11):1155-61.

[54]

Etzioni R, Gulati R, Weiss NS. Multicancer Early Detection: Learning From the Past to Meet the Future. J Natl Cancer Inst. 2022;114(3):349-52.

[55]

Feng R, Su Q, Huang X, Basnet T, Xu X, Ye W. Cancer situation in China: what does the China cancer map indicate from the first national death survey to the latest cancer registration? Cancer Commun (Lond). 2023;43(1):75-86.

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