Shaik Mohammad Naushad1, Patchava Dorababu2, Yedluri Rupasree3, Addepalli Pavani3, Digumarti Raghunadharao4, Tajamul Hussain5,6, Salman A Alrokayan6,7, Vijay Kumar Kutala8. 1. Head-Biochemical Genetics and Pharmacogenomics, Sandor Speciality Diagnostics Pvt Ltd, Banjara Hills, Road No 3, Hyderabad, 500034, India. naushadsm@gmail.com. 2. Department of Pharmacology, Apollo Institute of Medical Sciences and Research, Hyderabad, India. 3. Head-Biochemical Genetics and Pharmacogenomics, Sandor Speciality Diagnostics Pvt Ltd, Banjara Hills, Road No 3, Hyderabad, 500034, India. 4. Homibhabha Cancer Hospital and Research Centre, Aganampudi, Visakhapatnam, India. 5. Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia. 6. Research Chair for Biomedical Applications of Nanomaterials, Department of Biochemistry, College of Science, King Saud University, Riyadh, Saudi Arabia. 7. Biochemistry Department, College of Science, King Saud University, Riyadh, Saudi Arabia. 8. Department of Clinical Pharmacology and Therapeutics, Nizam's Institute of Medical Sciences, Hyderabad, India.
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.
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. TPMTint3, 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.
Authors: Haixiao Wu; Shu Li; Yile Lin; Jun Wang; Vladimir P Chekhonin; Karl Peltzer; Vladimir P Baklaushev; Kirellos Said Abbas; Jin Zhang; Huiyang Li; Chao Zhang Journal: Front Nutr Date: 2022-07-28