Skip to main content

Advertisement

SpringerLink
Log in

DNA ploidy and stroma predicted the risk of recurrence in low-risk stage III colorectal cancer

  • Research Article
  • Published:
Clinical and Translational Oncology Aims and scope Submit manuscript

Abstract

Background

For clinically low-risk stage III colorectal cancer, the decision on cycles of adjuvant chemotherapy after surgery is disputed. The present study investigates the use of additional biomarkers of ploidy and stroma-ratio(PS) to stratify patients with low-risk stage III colorectal cancer, providing a basis for individualized treatment in the future.

Methods

This study retrospectively enrolled 198 patients with clinical-low-risk stage III colorectal cancer (T1-3N1M0) and analyzed the DNA ploidy and stroma ratio of FFPE tumor tissues. The patients were divided into PS-low-risk group (Diploidy or Low-stroma) and PS-high-risk group (Non-diploid and High-stroma). For survival analyses, Kaplan–Meier and Cox regression models were used.

Results

The results showed that the 5-year DFS of the PS-high-risk group was significantly lower than that in the PS-low-risk group (78.6 vs. 91.2%, HR = 2.606 [95% CI: 1.011–6.717], P = 0.039). Besides, in the PS-low-risk group, the 5 year OS (98.2 vs. 86.7%, P = 0.022; HR = 5.762 [95% CI: 1.281–25.920]) and DFS (95.6, vs 79.9%, P = 0.019; HR = 3.7 [95% CI: 1.24–11.04]) of patients received adjuvant chemotherapy for > 3 months were significantly higher than those received adjuvant chemotherapy for < 3 months. We also found that the PS could stratify the prognosis of patients with dMMR tumors. The 5-year OS (96.3 vs 71.4%, P = 0.037) and DFS (92.6 vs 57.1%, P = 0.015) were higher in the PS-low-risk dMMR patients than those in the PS-high-risk dMMR patients.

Conclusion

In this study, we found that PS can predict the prognosis of patients with stage III low-risk CRC. Besides, it may guide the decision on postoperative adjuvant chemotherapy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7–34. https://doi.org/10.3322/caac.21551.

    Article  Google Scholar 

  2. Chen W, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–32. https://doi.org/10.3322/caac.21338.

    Article  Google Scholar 

  3. Benson AB, et al. NCCN Guidelines Insights: colon cancer, version 2.2018. J Natl Compr Canc Netw. 2018;16:359–69. https://doi.org/10.6004/jnccn.2018.0021.

    Article  Google Scholar 

  4. Des Guetz G, Uzzan B, Morere JF, Perret G, Nicolas P. Duration of adjuvant chemotherapy for patients with non-metastatic colorectal cancer. Cochrane Database Syst Rev. 2010. https://doi.org/10.1002/14651858.CD007046.pub2.

    Article  Google Scholar 

  5. Grothey A, et al. Duration of adjuvant chemotherapy for stage III colon cancer. N Engl J Med. 2018;378:1177–88. https://doi.org/10.1056/NEJMoa1713709.

    Article  CAS  Google Scholar 

  6. Lieu C, et al. Duration of oxaliplatin-containing adjuvant therapy for stage III colon cancer: ASCO clinical practice guideline. J Clin Oncol. 2019;37:1436–47. https://doi.org/10.1200/JCO.19.00281.

    Article  CAS  Google Scholar 

  7. Danielsen HE, Pradhan M, Novelli M. Revisiting tumour aneuploidy - the place of ploidy assessment in the molecular era. Nat Rev Clin Oncol. 2016;13:291–304. https://doi.org/10.1038/nrclinonc.2015.208.

    Article  CAS  Google Scholar 

  8. Mesker WE, et al. The carcinoma-stromal ratio of colon carcinoma is an independent factor for survival compared to lymph node status and tumor stage. Cell Oncol. 2007;29:387–98. https://doi.org/10.1155/2007/175276.

    Article  Google Scholar 

  9. Wang K, et al. Tumor-stroma ratio is an independent predictor for survival in esophageal squamous cell carcinoma. J Thorac Oncol. 2012;7:1457–61. https://doi.org/10.1097/JTO.0b013e318260dfe8.

    Article  Google Scholar 

  10. Zhang XL, et al. The tumor-stroma ratio is an independent predictor for survival in nasopharyngeal cancer. Oncol Res Treat. 2014;37:480–4. https://doi.org/10.1159/000365165.

    Article  CAS  Google Scholar 

  11. Chen Y, Zhang L, Liu W, Liu X. Prognostic significance of the tumor-stroma ratio in epithelial ovarian cancer. Biomed Res Int. 2015;2015: 589301. https://doi.org/10.1155/2015/589301.

    Article  CAS  Google Scholar 

  12. Yang L, et al. Prognostic value of nucleotyping, DNA ploidy and stroma in high-risk stage II colon cancer. Br J Cancer. 2020;123:973–81. https://doi.org/10.1038/s41416-020-0974-8.

    Article  CAS  Google Scholar 

  13. Danielsen HE, et al. Prognostic markers for colorectal cancer: estimating ploidy and stroma. Ann Oncol. 2018;29:616–23. https://doi.org/10.1093/annonc/mdx794.

    Article  CAS  Google Scholar 

  14. Van Loo P, et al. Allele-specific copy number analysis of tumors. Proc Natl Acad Sci U S A. 2010;107:16910–5. https://doi.org/10.1073/pnas.1009843107.

    Article  Google Scholar 

  15. Argiles G, et al. Localised colon cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2020;31:1291–305. https://doi.org/10.1016/j.annonc.2020.06.022.

    Article  CAS  Google Scholar 

  16. Pages F, et al. International validation of the consensus immunoscore for the classification of colon cancer: a prognostic and accuracy study. Lancet. 2018;391:2128–39. https://doi.org/10.1016/S0140-6736(18)30789-X.

    Article  Google Scholar 

  17. Auslander N, Wolf YI, Koonin EV. Interplay between DNA damage repair and apoptosis shapes cancer evolution through aneuploidy and microsatellite instability. Nat Commun. 2020;11:1234. https://doi.org/10.1038/s41467-020-15094-2.

    Article  CAS  Google Scholar 

  18. Hveem TS, et al. Prognostic impact of genomic instability in colorectal cancer. Br J Cancer. 2014;110:2159–64. https://doi.org/10.1038/bjc.2014.133.

    Article  CAS  Google Scholar 

  19. Carvalho B, et al. Concurrent hypermethylation of gene promoters is associated with a MSI-H phenotype and diploidy in gastric carcinomas. Eur J Cancer. 2003;39:1222–7. https://doi.org/10.1016/s0959-8049(03)00177-1.

    Article  CAS  Google Scholar 

  20. Mouradov D, et al. Survival in stage II/III colorectal cancer is independently predicted by chromosomal and microsatellite instability, but not by specific driver mutations. Am J Gastroenterol. 2013;108:1785–93. https://doi.org/10.1038/ajg.2013.292.

    Article  CAS  Google Scholar 

  21. Sinicrope FA, et al. Prognostic impact of microsatellite instability and DNA ploidy in human colon carcinoma patients. Gastroenterology. 2006;131:729–37. https://doi.org/10.1053/j.gastro.2006.06.005.

    Article  CAS  Google Scholar 

  22. Vilar E, Gruber SB. Microsatellite instability in colorectal cancer-the stable evidence. Nat Rev Clin Oncol. 2010;7:153–62. https://doi.org/10.1038/nrclinonc.2009.237.

    Article  CAS  Google Scholar 

  23. Cohen R, et al. Microsatellite instability in patients with stage III colon cancer receiving fluoropyrimidine with or without oxaliplatin: an ACCENT pooled analysis of 12 adjuvant trials. J Clin Oncol. 2021;39:642–51. https://doi.org/10.1200/JCO.20.01600.

    Article  CAS  Google Scholar 

  24. Sargent DJ, et al. Defective mismatch repair as a predictive marker for lack of efficacy of fluorouracil-based adjuvant therapy in colon cancer. J Clin Oncol. 2010;28:3219–26. https://doi.org/10.1200/JCO.2009.27.1825.

    Article  CAS  Google Scholar 

  25. Roth AD, et al. Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60–00 trial. J Clin Oncol. 2010;28:466–74. https://doi.org/10.1200/JCO.2009.23.3452.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We deeply appreciate the help from all of our colleagues in the Department of Colorectal Surgery at Sun Yat-sen University Cancer Center who were involved in performing the treatments for the current study. Meanwhile, we wish to thank the timely help given by Mao Lijun and Wang Fei in article writing and basic experiment.

Funding

This work was supported by grants from the National Natural Science Foundation of China [grant numbers: 81871971, 82073159, 81772595]; Sun Yat-sen University Clinical Research 5010 Program [grant number: 2014013].

Author information

Author notes

  1. Yuan Li, Leen Liao and Lingheng Kong contributed equally to this work.

Authors and Affiliations

  1. Department of Colorectal Cancer, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, No. 651, Dongfeng Road East, Guangzhou, 510060, Guangdong, People’s Republic of China

    Yuan Li, Leen Liao, Lingheng Kong, Wu Jiang, Jinghua Tang, Kai Han, Zhenlin Hou, Chenzhi Zhang, Chi Zhou, Linjie Zhang, Qiaoqi Sui, Binyi Xiao, Weijian Mei, Yanbo Xu, Jiehai Yu, Zhigang Hong, Zhizhong Pan & Peirong Ding

Authors
  1. Yuan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Leen Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lingheng Kong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wu Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jinghua Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kai Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zhenlin Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chenzhi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Chi Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Linjie Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Qiaoqi Sui
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Binyi Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Weijian Mei
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yanbo Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Jiehai Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Zhigang Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Zhizhong Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Peirong Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YL, LL, ZP and PD: contributed to the conception of the study; BX, QS, YX, WM, JY and ZH: collected data; WJ, LK, JT: and KH: contributed significantly to analysis and manuscript preparation; ZH, CZ, CZ and LZ: designed table and figure; YL and LL: performed the data analyses and wrote the manuscript; ZP and PD: helped perform the analysis with constructive discussions and contributed to critical revision; All authors reviewed the manuscript.

Corresponding author

Correspondence to Peirong Ding.

Ethics declarations

Conflict of interest

All authors have no conflicts of interest or financial ties to disclose.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Research Ethics Committee of Sun Yat-sen University Cancer Center (approval number: B2019-109).

Inform consent

For this type of study, formal consent is not required.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Liao, L., Kong, L. et al. DNA ploidy and stroma predicted the risk of recurrence in low-risk stage III colorectal cancer. Clin Transl Oncol 25, 218–225 (2023). https://doi.org/10.1007/s12094-022-02930-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12094-022-02930-8

Keywords

Search

Navigation