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Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin

Abstract

The accurate and early diagnosis and classification of cancer origin from either tissue or liquid biopsy is crucial for selecting the appropriate treatment and reducing cancer-related mortality. Here, we established the CAncer Cell-of-Origin (CACO) methylation panel using the methylation data of the 28 types of cancer in The Cancer Genome Atlas (7950 patients and 707 normal controls) as well as healthy whole blood samples (95 subjects). We showed that the CACO methylation panel had high diagnostic potential with high sensitivity and specificity in the discovery (maximum AUC = 0.998) and validation (maximum AUC = 1.000) cohorts. Moreover, we confirmed that the CACO methylation panel could identify the cancer cell type of origin using the methylation profile from liquid as well as tissue biopsy, including primary, metastatic, and multiregional cancer samples and cancer of unknown primary, independent of the methylation analysis platform and specimen preparation method. Together, the CACO methylation panel can be a powerful tool for the classification and diagnosis of cancer.

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Fig. 1: CACO (CAncer Cell-of Origin) methylation panel can differentiate different cancer types and healthy whole blood from each other.
Fig. 2: CACO methylation panel demonstrated high diagnostic potential.
Fig. 3: CACO methylation panels can identify the cancer tissue of origin among breast, colorectal, and gastric cancer using the methylation signature from the EPIC platform.
Fig. 4: CACO methylation panel can identify COADREAD using both primary and metastatic tumor methylation signatures, which were measured by whole-genome bisulfite sequencing using a TACS ligation-mediated post-bisulfite adaptor tagging (tPBAT) method.
Fig. 5: CACO methylation panels can identify colorectal cancer using any region of the tissue.
Fig. 6: CACO methylation panels can identify the cancer of origin using ctDNA methylation.

Code availability

Custom R scripts used to analyze microarray and NGS data are available from the corresponding authors upon reasonable request.

Data availability

Microarray data (IDAT files) have been deposited into the DDBJ Genomic Expression Archive (GEA). GEA accession: E-GEAD-396. tPBAT data (fastq files) have been deposited into the DDBJ Sequence Read Archive (DRA). DRA accession: DRA010902. All other raw data that are not found in the supplementary information are available from the corresponding authors upon reasonable request.

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Acknowledgements

The images in Fig. 1a and Supplementary Fig. S1b are from TogoTV (© 2016 DBCLS TogoTV) and Pintarest.

Funding

D.S. was supported by JSPS KAKENHI Grant Number 19K16868. K.M. received funding from the Platform Project for Supporting Drug Discovery, Life Science Research (Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS)) from AMED under Grant Number JP20am0101103 (support number 0958), P-CREATE from AMED (20cm0106475h0001(e-Rad ID: 20317791)), JSPS KAKENHI (20H05039, 19H03715, 19K09220), Grant-in-Aid for Scientific Research on Innovative Areas (15H05912), Priority Issue on Post-K computer (hp170227, hp160219), the Project for Cancer Research and Therapeutic Evolution (19cm0106504h0004), Research Grant of the Princess Takamatsu Cancer Research, and SRL, Miraka Research Institute and Takeda Science Foundation. K.T. was supported by the Kobayashi Foundation, Takeda Science Foundation and JSPS KAKENHI Grant Number (21H02758 and 21K19402).

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Contributions

D.S. and K.T. conceived and designed the research. D.S. performed most of the bioinformatics analysis with assistance from K.T., Y.M., H.H., M.S., and A.N. M.F., K.S., Y.M., Y.K., M.S., and H.B. collected, analyzed, and interpreted the clinical data. K.T., S.T., and A.K. performed the microarray experiments. H.A., F.M., and T.I. performed the PBAT analysis. Y.K., A.K., Y.Y., K.S., T.S., S.I., T.M., M.S., H.B., N.A., and Y.K. provided guidance and scientific input. D.S., K.T., and K.M. wrote the paper.

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Correspondence to Dai Shimizu or Kenzui Taniue.

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K.T., S.T., and A.K. were employees of Genomedia Inc. The remaining authors declare no competing interests.

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Shimizu, D., Taniue, K., Matsui, Y. et al. Pan-cancer methylome analysis for cancer diagnosis and classification of cancer cell of origin. Cancer Gene Ther 29, 428–436 (2022). https://doi.org/10.1038/s41417-021-00401-w

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