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LncRNA-LA16c-313D11.11,A Signature to Predict Endometrial Carcinoma Patients with a Better Survival

  • Gynecologic Oncology: Original Article
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Abstract

The aim of this study was to develop and internally validate a nomogram of the probability EC patients surviving longer than 5 years. Quantitative real-time PCR (qRT–PCR) was implemented to analyze the expression of lncRNA-LA16c-313D11.11 in 60 EC tissues. The clinicopathological characteristics and follow-up data were retrospectively gathered and analyzed. To establish the prediction model, multivariate logistic regression analysis was applied, and the discrimination, calibration, and clinical practicability of the prediction model were assessed with a concordance index (C-index), calibration chart, and decision curve analysis. Bootstrap validation was performed for internal validation. The prediction factors included the age of patients, myometrial invasion, lymphovascular space invasion, histological subtype, and the expression of lncRNA-LA16C-313D11.11. The model demonstrated good calibration and modest discrimination (C-index = 0.860, 95% confidence interval: 0.724–0.946). Moreover, the interval validation achieved a high C-index value of 0.778. This study revealed the predictive value of lncRNA-LA16C-313D11.11 and successfully developed a nomogram for predicting EC patients survival longer than 5 years, which may facilitate the institution of personalized treatment algorithms, surveillance strategies, and lifestyle interventions.

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References

  1. Straughn J, Huh W, Kelly F, Leath C, Kleinberg M, et al. Conservative management of stage i endometrial carcinoma after surgical staging. Gynecol Oncol. 2002;84:194–200.

    Article  PubMed  Google Scholar 

  2. Blake P, Swart A, Ortonet J, Kitcheneral H, Whelan T, et al. Adjuvant external beam radiotherapy in the treatment of endometrial cancer (MRC ASTEC and NCIC CTG EN.5 randomised trials): pooled trial results, systematic review, and meta-analysis. Lancet. 2009;373:137–46.

    Article  CAS  PubMed  Google Scholar 

  3. Nout RA, Smit VT, Putter H, Jürgenliemk-Schulz I, Jobsen J, et al. Vaginal brachytherapy versus pelvic external beam radiotherapy for patients with endometrial cancer of high-intermediate risk (PORTEC-2): an open-label, non-inferiority, randomised trial. Lancet. 2010;375:816–23.

    Article  CAS  PubMed  Google Scholar 

  4. Creutzberg C, Wárlám-Rodenhuis C, De Winter K, Koper P, Lybeert M, et al. Outcome of high-risk stage IC, grade 3, compared with stage I endometrial carcinoma patients: the postoperative radiation therapy in endometrial carcinoma Trial. J Clin Oncol. 2004;22:1234–41.

    Article  PubMed  Google Scholar 

  5. Morrow C, Bundy B, Kurman R, Creasman W, Heller P, et al. Relationship between surgical-pathological risk factors and outcome in clinical Stage I and II carcinoma of the endometrium: a gynecologic oncology group study. Gynecol Oncol. 1991;40:55–65.

    Article  CAS  PubMed  Google Scholar 

  6. Kasius J, Pijnenborg J, Lindemann K, Forsseet D, van Zwolal J, et al. Risk stratification of endometrial cancer patients: FIGO stage, biomarkers and molecular classification. Cancers. 2021;13:5848.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Sun LC, Xue HB, Jiang CH, Zhou H, Gu L, et al. LncRNA DQ786243 contributes to proliferation and metastasis of colorectal cancer both in vitro and in vivo. Biosci Rep. 2016;3:328.

    Google Scholar 

  8. Xu S, Yi XM, Tang CP, Ge JP, Zhang ZY, et al. Long non-coding RNA ATB promotes growth and epithelial-mesenchymal transition and predicts poor prognosis in human prostate carcinoma. Oncol Rep. 2016;36:10–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Grossman S, Lyle S, Resnick M, Lis R, Rosinha E, et al. p66 Shc tumor levels show a strong prognostic correlation with disease outcome in stage IIA colon cancer. Clin Cancer Res. 2007;13:5798–804.

    Article  CAS  PubMed  Google Scholar 

  10. Xin WJ, Liu XX, Ding JX, Zhao J, Zhou Y, et al. Long non-coding RNA derived miR-205-5p modulates human endometrial cancer by targeting PTEN. Am J Transl Res. 2015;7:2433–41.

  11. Xin WJ, Zhao ST, Hang XS, Yu H, Gao XD, et al. lncRNA LA16c‑313D11.11 modulates the development of endometrial cancer by binding to and inhibiting microRNA‑205‑5p function and indirectly increasing PTEN activity. Int J Oncol., 2020.57:355–63.

    Google Scholar 

  12. Pecorelli S. Revised FIGO staging for carcinoma of the vulva, cervix, and endometrium. Int J Gynaecol Obstet. 2009;105:103–4.

    Article  PubMed  Google Scholar 

  13. Scully R, WHO—histological typing of female genital-tract tumors. Ann Pathol, 1995. 4:296–297.

    Google Scholar 

  14. Huang YQ, Liang CH, He L, Tian J, Liang CS, et al. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol. 2016;34:2157–64.

    Article  PubMed  Google Scholar 

  15. Friedman J, Hastie T, Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw, 2010. 33:1–22.

    Google Scholar 

  16. Sauerbrei W, Royston P, Binder H. Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med. 2007;26:5512–28.

    Article  PubMed  Google Scholar 

  17. Iasonos A, Schrag D, Raj G, Panageas K. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;8:1364–70.

    Article  Google Scholar 

  18. Balachandran V, Gonen M, Smith J, DeMatteo R. Nomograms in oncology — more than meets the eye. Lancet Oncol. 2015;16:e173–80.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Huang WT, Macheret F, Gabriel R, Ohno-Machado L. A tutorial on calibration measurements and calibration models for clinical prediction models. Am Med Inform Assoc. 2020;27:621–33.

    Article  Google Scholar 

  20. Zhang MM, Tang WY, Wang YR, Peng PK, et al. JZWT. High Hepsin expression predicts poor prognosis in gastric cancer. Sci Rep. 2016;6:36902.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Song J, Wang L, Ng N, Zhao MF, Shi JY,et al. Development and validation of a machine learning model to explore tyrosine kinase inhibitor response in patients with stage IV EGFR variant-positive non-small cell lung cancer. JAMA Netw Open. 2020;12:e2030442.

    Article  Google Scholar 

  22. Alba A, Agoritsas T, Walsh M, Hanna S, Iorio A, et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. JAMA. 2017;318:1377–84.

    Article  PubMed  Google Scholar 

  23. Creasman W, Walsh M, Hanna S, Iorio A, Devereaux P, et al. Adenocarcinoma of the endometrium its metastatic lymph node potential A preliminary report. Gynecol Oncol. 1976;4:239–43.

    Article  CAS  PubMed  Google Scholar 

  24. Ballester M, Dubernard G, Lécuru F, Heitz D, Mathevet P, et al. Detection rate and diagnostic accuracy of sentinel-node biopsy in early stage endometrial cancer: a prospective multicentre study (SENTI-ENDO). Lancet Oncol. 2011;12:469–76.

    Article  PubMed  Google Scholar 

  25. Concin N, Matias-Guiu X, Vergote I, Creutzberg C, Mirza M, et al. ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma. Radiother Oncol. 2021;154:327–53.

    Article  PubMed  Google Scholar 

  26. Kandoth C, Schultz N, Cherniack A, Akbani R, Liu Y, et al. Integrated genomic characterization of endometrial carcinoma. Nature. 2013;497:67–73.

    Article  PubMed  Google Scholar 

  27. De Boer S, Powell M, Mileshkin L, Ledermann J, Khaw P, et al. Toxicity and quality of life after adjuvant chemoradiotherapy versus radiotherapy alone for women with high-risk endometrial cancer (PORTEC-3) an open-label, multicentre, randomised, phase 3 trial. Lancet Oncol. 2016;17:1114–26.

    Article  CAS  PubMed  Google Scholar 

  28. Ytre-Hauge S, Husby J, Magnussen I, Werner H, Salvesen O, et al. Preoperative tumor size at MRI predicts deep myometrial invasion, lymph node metastases, and patient outcome in endometrial carcinomas. Int J Gynecol Cancer. 2015;25:459–66.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Werner H, Troviket J, Marcickiewicz J, Tingulstad S, Staff A, et al. Revision of FIGO surgical staging in 2009 for endometrial cancer validates to improve risk stratification. Gynecologic Oncology, 2012. 125:103–108.

  30. Vallone C, Rigon G, Gulia C, Baffa A, Votino R, et al. Non-Coding RNAs and Endometrial Cancer. Genes (Basel),2018. 9:187.

  31. Liu HY, Wan JH, Chu J. Long non-coding RNAs and endometrial cancer. BIOMED PHARMACOTHER, 2019.119:109396.

  32. Takenaka K, Chen BJ, Modesitt S, Byrne F, Hoehn K, et al. The emerging role of long non-coding RNAs in endometrial cancer. Cancer Genet, 2016. 209: 445-455.

  33. Grillone K, Riillo C, Scionti F, Rocca R, Tradigo G, et al. Non-coding RNAs in cancer: platforms and strategies for investigating the genomic “dark matter”. J Exp Clin Cancer Res,2020.39:1–19.

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Acknowledgements

We thank Obstetrics and Gynecology Hospital of Fudan University, for the support developing our search strategies.

Funding

The work was supported by Natural Science Foundation of Shanghai, China (No. 16ZR1404100), and National Natural Science Foundation of China (No. 82001500).

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Author notes

  1. The two authors Xue Ding, Songping Liu have contributed equally to this work.

Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China

    Xue Ding, Keqin Hua & Weijuan Xin

  2. Department of Obstetrics and Gynecology, Jinshan Hospital of Fudan University, Shanghai, China

    Songping Liu

  3. Department of Pathology, People’s Hospital of Dezhou, Dezhou, China

    Na Liu

Authors
  1. Xue Ding
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  2. Songping Liu
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  3. Na Liu
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  4. Keqin Hua
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  5. Weijuan Xin
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Contributions

Xue Ding, Weijuan Xin, and Keqin Hua designed the study. Xue Ding, Weijuan Xin, Songping Liu, and Na Liu performed the experiments. Xue Ding, Weijuan Xin, Songping Liu, and Keqin Hua analyzed the data and wrote the paper. All authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Keqin Hua or Weijuan Xin.

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Ethics Approval

This study was approved by the ethics review committee of Obstetrics and Gynecology Hospital of Fudan University.

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Informed consent was obtained from all participants in this study.

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All authors consented to publication.

Competing Interests

The authors declare no competing interests.

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Ding, X., Liu, S., Liu, N. et al. LncRNA-LA16c-313D11.11,A Signature to Predict Endometrial Carcinoma Patients with a Better Survival. Reprod. Sci. 30, 883–889 (2023). https://doi.org/10.1007/s43032-022-01052-4

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  • DOI: https://doi.org/10.1007/s43032-022-01052-4

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