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Copy number alteration fingerprint predicts the clinical response of oxaliplatin-based chemotherapy in metastatic colorectal cancer
  • Published: 10 March 2026

Copy number alteration fingerprint predicts the clinical response of oxaliplatin-based chemotherapy in metastatic colorectal cancer

  • Junyong Weng1,
  • Jinyu Wang2,
  • Ziyu Tao2,
  • Tao Wu2,3,
  • Kaixuan Diao2,
  • Jiexuan Wang4,
  • Nan Wang2,
  • Zilan Ye1,
  • Ruoxin Zhang1,
  • Jiayu Shen2,
  • Xiangyu Zhao2,
  • XinXing Li4,
  • Xinxiang Li1 &
  • …
  • Xue-Song Liu2,5 

, Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Oxaliplatin-based chemotherapy is a standard treatment for metastatic colorectal cancer (mCRC), yet accurate biomarkers to identify responders remain lacking. In this study, we developed and validated a genomic copy number alteration (CNA)-based biomarker to predict clinical response to oxaliplatin-based chemotherapy. A total of 297 samples were collected, and shallow sequencing was employed to extract CNA features. The resulting model named “CNA fingerprint” is an XGBoost model trained using 7 CNA features. The model was validated across three independent test cohorts from two centers, achieving area under the receiver operating characteristic curve (AUC) of 0.87, 0.87, and 0.85, respectively. The primary predictor was the number of DNA segments with high absolute copy numbers. Our findings suggest that the CNA fingerprint could be used as biomarker for oxaliplatin-based chemotherapy response prediction in mCRC. Further prospective clinical trials are warranted to evaluate CNA fingerprint’s performance in clinical applications.

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References

  1. Sung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca-a Cancer J. Clin. 71, 209–249 (2021).

    Google Scholar 

  2. SEER. Cancer Stat Facts: Colorectal Cancer, https://seer.cancer.gov/statfacts/html/colorect.html (2024).

  3. Kahi, C. J. et al. Colonoscopy surveillance after colorectal cancer resection: recommendations of the US multi-society task force on colorectal cancer. Gastroenterology 150, 758–768 (2016).

    Google Scholar 

  4. Alese, O. B. et al. Update on emerging therapies for advanced colorectal cancer. Am. Soc. Clin. Oncol. Educ. Book, e389574, https://doi.org/10.1200/edbk_389574 (2023).

  5. Kawai, S. et al. Comparison of irinotecan and oxaliplatin as the first-line therapies for metastatic colorectal cancer: a meta-analysis. BMC Cancer 21, 116 (2021).

    Google Scholar 

  6. Bahrami, A. et al. Genetic variants as potential predictive biomarkers in advanced colorectal cancer patients treated with oxaliplatin-based chemotherapy. J. Cell. Physiol. 233, 2193–2201 (2018).

    Google Scholar 

  7. Chen, L. J. et al. Machine learning predicts oxaliplatin benefit in early colon cancer. J. Clin. Oncol. 42, 1520–1530 (2024).

    Google Scholar 

  8. Yin, M. et al. ERCC1 and ERCC2 polymorphisms predict clinical outcomes of oxaliplatin-based chemotherapies in gastric and colorectal cancer: a systemic review and meta-analysis. Clin. Cancer Res. 17, 1632–1640 (2011).

    Google Scholar 

  9. Abraham, J. P. et al. Clinical validation of a machine-learning-derived signature predictive of outcomes from first-line oxaliplatin-based chemotherapy in advanced colorectal cancer. Clin. Cancer Res. 27, 1174–1183 (2021).

    Google Scholar 

  10. Russo, V. et al. Artificial intelligence predictive models of response to cytotoxic chemotherapy alone or combined to targeted therapy for metastatic colorectal cancer patients: a systematic review and meta-analysis. Cancers 14, 4012 (2022).

    Google Scholar 

  11. Yi, K. & Ju, Y. S. Patterns and mechanisms of structural variations in human cancer. Exp. Mol. Med. 50, 98 (2018).

    Google Scholar 

  12. Tao, Z. Y. et al. The repertoire of copy number alteration signatures in human cancer. Brief. Bioinform. 24, bbad053 (2023).

    Google Scholar 

  13. Wang, S. X. et al. Copy number signature analysis tool and its application in prostate cancer reveals distinct mutational processes and clinical outcomes. PLoS Genet. 17, e1009557 (2021).

    Google Scholar 

  14. McShane, L. M. et al. Reporting recommendations for tumor marker prognostic studies (REMARK). Natl. Cancer Inst. 97, 1180–1184 (2005).

    Google Scholar 

  15. Haan, J. C. et al. Genomic landscape of metastatic colorectal cancer. Nat. Commun. 5, https://doi.org/10.1038/ncomms6457 (2014).

  16. Malla, S. B. et al. In-depth clinical and biological exploration of dna damage immune response as a biomarker for oxaliplatin use in colorectal cancer. Clin. Cancer Res. 27, 288–300 (2021).

    Google Scholar 

  17. Replogle, J. M. et al. Aneuploidy increases resistance to chemotherapeutics by antagonizing cell division. Proc. Natl. Acad. Sci. USA 117, 30566–30576 (2020).

    Google Scholar 

  18. Shukla, A. et al. Chromosome arm aneuploidies shape tumour evolution and drug response. Nat. Commun. 11, 449 (2020).

    Google Scholar 

  19. Baran, B. et al. Difference between left-sided and right-sided colorectal cancer: a focused review of literature. 11, https://doi.org/10.14740/gr1062w (2018).

  20. Watson, R. G. et al. Amplification of thymidylate synthetase in metastatic colorectal cancer patients pretreated with 5-fluorouracil-based chemotherapy. Eur. J. Cancer 46, 3358–3364 (2010).

    Google Scholar 

  21. Buess, M. et al. STRAP is a strong predictive marker of adjuvant chemotherapy benefit in colorectal cancer. Neoplasia 6, 813–820 (2004).

    Google Scholar 

  22. Fujita, Y. et al. aCGH analysis of predictive biomarkers for response to bevacizumab plus oxaliplatin- or irinotecan-based chemotherapy in patients with metastatic colorectal cancer. Oncologist 24, 327–337 (2019).

    Google Scholar 

  23. Wu, Z. Y. et al. Copy number amplification of DNA damage repair pathways potentiates therapeutic resistance in cancer. Theranostics 10, 3939–3951 (2020).

    Google Scholar 

  24. Ippolito, M. R. et al. Gene copy-number changes and chromosomal instability induced by aneuploidy confer resistance to chemotherapy. Dev. Cell 56, 2440–244 (2021).

    Google Scholar 

  25. Galofré, C. et al. Tetraploidy-associated genetic heterogeneity confers chemo-radiotherapy resistance to colorectal cancer cells. Cancers 12, 1118 (2020).

    Google Scholar 

  26. Jardim, D. L., Rodrigues, C. A., Novis, Y. A. S., Rocha, V. G. & Hoff, P. M. Oxaliplatin-related thrombocytopenia. Ann. Oncol. 23, 1937–1942 (2012).

    Google Scholar 

  27. Arango, D. et al. Molecular mechanisms of action and prediction of response to oxaliplatin in colorectal cancer cells. Br. J. Cancer 91, 1931–1946 (2004).

    Google Scholar 

  28. Bencardino, K. et al. Oxaliplatin immune-induced syndrome occurs with cumulative administration and rechallenge: single institution series and systematic review study. Clin. Colorectal Cancer 15, 213–221 (2016).

    Google Scholar 

  29. Wang, S. & Liu, X. -s The UCSCXenaTools R package: a toolkit for accessing genomics data from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq. J. Open Source Softw. 4, 1627 (2019).

    Google Scholar 

  30. Chen, S. F. Ultrafast one-pass FASTQ data preprocessing, quality control, and deduplication using fastp. Imeta 2, e107 (2023).

    Google Scholar 

  31. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM, https://doi.org/10.48550/arXiv.1303.3997 (2013).

  32. Scheinin, I. et al. DNA copy number analysis of fresh and formalin-fixed specimens by shallow whole-genome sequencing with identification and exclusion of problematic regions in the genome assembly. Genome Res. 24, 2022–2032 (2014).

    Google Scholar 

  33. Poell, J. B. et al. ACE: absolute copy number estimation from low-coverage whole-genome sequencing data. Bioinformatics 35, 2847–2849 (2019).

    Google Scholar 

  34. Wu, C. X. et al. Single-cell copy number alteration signature analysis reveals masked patterns and potential biomarkers for cancer. Commun. Biol. 8, https://doi.org/10.1038/s42003-025-08994-w (2025).

  35. Hieronymus, H. et al. Tumor copy number alteration burden is a pan-cancer prognostic factor associated with recurrence and death. Elife 7, e37294 (2018).

    Google Scholar 

  36. Drews, R. M. et al. A pan-cancer compendium of chromosomal instability. Nature 606, 976–983 (2022).

    Google Scholar 

  37. Lang., M. et al. mlr3: a modern object-oriented machine learning framework in R. J. Open Source Softw., https://doi.org/10.21105/joss.01903 (2019).

  38. Yao, H. Z. et al. Copy number alteration features in pan-cancer homologous recombination deficiency prediction and biology. Commun. Biol. 6, 527 (2023).

    Google Scholar 

  39. Sztupinszki, Z. et al. Migrating the SNP array-based homologous recombination deficiency measures to next generation sequencing data of breast cancer. npj Breast Cancer 4, 16 (2018).

    Google Scholar 

  40. Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. 28, 1–26 (2008).

    Google Scholar 

  41. Robin, X. et al. pROC: an open-source package for R and S plus to analyze and compare ROC curves. BMC Bioinform. 12, 77 (2011).

    Google Scholar 

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Acknowledgements

We thank ShanghaiTech University High Performance Computing Public Service Platform for computing services. We thank multi-omics facility, molecular and cell biology core facility of ShanghaiTech University for technical help. This work is supported by National Natural Science Foundation of China (82373149), Shanghai Science and Technology Commission (24J22800700), cross disciplinary Research Fund of Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine (JYJC202227), open project fund of the National Health Commission’s key laboratory of individualized diagnosis and treatment of nasopharyngeal cancer (2023NPCCK02) and startup funding from ShanghaiTech University.

Author information

Authors and Affiliations

  1. Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China

    Junyong Weng, Zilan Ye, Ruoxin Zhang & Xinxiang Li

  2. School of Life Science and Technology, ShanghaiTech University, Shanghai, China

    Jinyu Wang, Ziyu Tao, Tao Wu, Kaixuan Diao, Nan Wang, Jiayu Shen, Xiangyu Zhao & Xue-Song Liu

  3. Department of Dermatology, Yangjiang People’s Hospital affiliated to Guangdong Medical University, Yangjiang, China

    Tao Wu

  4. Department of General Surgery, Tongji hospital, Tongji University School of Medicine, Shanghai, China

    Jiexuan Wang & XinXing Li

  5. Shanghai Clinical Research and Trial Center, Shanghai, China

    Xue-Song Liu

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  1. Junyong Weng
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Contributions

J.W., J.W., Z.T., and T.W. contributed equally to this work as joint first authors. X.L., X.L., and X.S.L contributed equally to this work as joint senior authors. X.S.L were responsible for overall study design. J.W., J.W., Z.T., and T.W. accessed and verified the underlying data. J.W., J.W., Z.T., T.W., K.D., J.W., N.W., Z.Y., R.Z., J.S., and X.Z. were responsible for analysis and interpretation of data. J.W., Z.T., T.W., and X.S.L. were responsible for writing, review, and/or revision of the manuscript. X.L., X.L., and X.S.L. were study supervisions and guarantors. All the authors have read, discussed, and unanimously approved the final version of the manuscript. All authors had full access to the data and had the final responsibility for the decision to submit for publication.

Corresponding authors

Correspondence to XinXing Li, Xinxiang Li or Xue-Song Liu.

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Weng, J., Wang, J., Tao, Z. et al. Copy number alteration fingerprint predicts the clinical response of oxaliplatin-based chemotherapy in metastatic colorectal cancer. npj Precis. Onc. (2026). https://doi.org/10.1038/s41698-026-01354-9

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  • Received: 26 May 2025

  • Accepted: 23 February 2026

  • Published: 10 March 2026

  • DOI: https://doi.org/10.1038/s41698-026-01354-9

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