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Classification and regression tree-based prediction of 6-mercaptopurine-induced leucopenia grades in children with acute lymphoblastic leukemia

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Abstract

Purpose

The rationale of the current study was to develop 6-mercaptopurine (6-MP)-mediated hematological toxicity prediction model for acute lymphoblastic leukemia (ALL) therapeutic management.

Methods

A total of 96 children with ALL undergoing therapy with MCP-841 protocol were screened for all the ten exons of TPMT, exon 2, exon 3 and intron 2 of ITPA using bidirectional sequencing. This dataset was used to construct prediction models of leucopenia grade by constructing classification and regression trees (CART) followed by smart pruning.

Results

The developed CART model indicated TPMT*12 and TPMT*3C as the key determinants of toxicity. TPMT int3, int4 and int7 polymorphisms exert toxicity when co-segregated with one mutated allele of TPMT*12 or TPMT*3C or ITPA exon 3. The developed CART model exhibited 93.6% accuracy in predicting the toxicity. The area under the receiver operating characteristic curve was 0.9649.

Conclusions

TPMT *3C and TPMT*12 are the key determinants of 6-MP-mediated hematological toxicity while other variants of TPMT (int3, int4 and int7) and ITPA ex2 interact synergistically with TPMT*3C or TPMT*12 variant alleles to enhance the toxicity. TPMT and ITPA variants cumulatively are excellent predictors of 6-MP-mediated toxicity.

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Data availability

The datasets during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We acknowledge the team of Department of Medical Oncology, Nizam’s Institute of Medical Sciences, Hyderabad for their cooperation for this study.

Funding

No funding was received for this work.

Author information

Author notes

  1. Shaik Mohammad Naushad and Patchava Dorababu equal first authorship.

Authors and Affiliations

  1. Head-Biochemical Genetics and Pharmacogenomics, Sandor Speciality Diagnostics Pvt Ltd, Banjara Hills, Road No 3, Hyderabad, 500034, India

    Shaik Mohammad Naushad, Yedluri Rupasree & Addepalli Pavani

  2. Department of Pharmacology, Apollo Institute of Medical Sciences and Research, Hyderabad, India

    Patchava Dorababu

  3. Homibhabha Cancer Hospital and Research Centre, Aganampudi, Visakhapatnam, India

    Digumarti Raghunadharao

  4. Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia

    Tajamul Hussain

  5. Research Chair for Biomedical Applications of Nanomaterials, Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia

    Tajamul Hussain & Salman A. Alrokayan

  6. Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia

    Salman A. Alrokayan

  7. Department of Clinical Pharmacology and Therapeutics, Nizam’s Institute of Medical Sciences, Hyderabad, India

    Vijay Kumar Kutala

Authors
  1. Shaik Mohammad Naushad
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  2. Patchava Dorababu
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  3. Yedluri Rupasree
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  4. Addepalli Pavani
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  5. Digumarti Raghunadharao
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  6. Tajamul Hussain
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  7. Salman A. Alrokayan
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  8. Vijay Kumar Kutala
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Contributions

The study was conceived and designed by DR and VKK. The research and analytical work was carried out by SMN, PD, SAA and TH. The statistical models were developed and manuscript was drafted by SMN and VKK.

Corresponding author

Correspondence to Shaik Mohammad Naushad.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in the study 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.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Cite this article

Naushad, S.M., Dorababu, P., Rupasree, Y. et al. Classification and regression tree-based prediction of 6-mercaptopurine-induced leucopenia grades in children with acute lymphoblastic leukemia. Cancer Chemother Pharmacol 83, 875–880 (2019). https://doi.org/10.1007/s00280-019-03803-8

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  • DOI: https://doi.org/10.1007/s00280-019-03803-8

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