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CC BY 4.0 · Indian J Med Paediatr Oncol
DOI: 10.1055/s-0045-1804890
Original Article

Analysis of TCGA (The Cancer Genome Atlas) Data for Prognosis, Risk Categorization, and Survival of AML Patients Using Bioinformatics

Bhavika Rishi    *
1   ICMR - National Institute of Child Health & Development Research (Formerly - ICMR - National Institute of Pathology), Department of Health Research, Safdarjung Hospital Campus, New Delhi, India
,
Shamsuz Zaman   *
2   ICMR - National Institute Cancer Prevention and Research, Noida, Department of Health Research, Uttar Pradesh, India
,
Fouzia Siraj
1   ICMR - National Institute of Child Health & Development Research (Formerly - ICMR - National Institute of Pathology), Department of Health Research, Safdarjung Hospital Campus, New Delhi, India
,
Sree Vishmaya
3   Department of Health Research, Indian Council of Medical Research–Advanced molecular diagnostic facility, ICMR-NICHDR New Delhi, India
,
Himanshu Dhanda
3   Department of Health Research, Indian Council of Medical Research–Advanced molecular diagnostic facility, ICMR-NICHDR New Delhi, India
,
Manpreet Kaur
3   Department of Health Research, Indian Council of Medical Research–Advanced molecular diagnostic facility, ICMR-NICHDR New Delhi, India
,
Sandeep Swain
3   Department of Health Research, Indian Council of Medical Research–Advanced molecular diagnostic facility, ICMR-NICHDR New Delhi, India
,
Baseer Noor
3   Department of Health Research, Indian Council of Medical Research–Advanced molecular diagnostic facility, ICMR-NICHDR New Delhi, India
,
Sumita Chaudhry
4   Department of Haematology, Vardhman Mahavir Medical College and Safdarjung Hospital New Delhi, India
,
Ankur Jain 
4   Department of Haematology, Vardhman Mahavir Medical College and Safdarjung Hospital New Delhi, India
,
Prashant Prabhakar
5   Department of Pediatrics, Vardhman Mahavir Medical College and Safdarjung Hospital New Delhi, India
,
Amitabh Singh    #
5   Department of Pediatrics, Vardhman Mahavir Medical College and Safdarjung Hospital New Delhi, India
,
Aroonima Misra    #
1   ICMR - National Institute of Child Health & Development Research (Formerly - ICMR - National Institute of Pathology), Department of Health Research, Safdarjung Hospital Campus, New Delhi, India
› Author Affiliations Funding None.
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Abstract

Introduction Acute myeloid leukemia (AML) is a leading cause of mortality among Indian children and adults, driven by diverse genetic and epigenetic abnormalities. Limited access to genomic sequencing in India due to resource constraints has hindered a comprehensive understanding of prognostic factors specific to this population.

Objectives This study aims to analyze publicly available genomic data using statistical and bioinformatics tools to identify key prognostic markers relevant to Indian AML patients.

Materials and Methods The study utilized tumor/normal pair data from 200 adult de novo AML patients, obtained from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression database, analyzed using cBioPortal. Statistical and bioinformatics tools were employed to assess the impact of existing prognostic targets on disease response and to identify variables with clinical relevance and practical testing feasibility.

Results Analysis of the TCGA-AML data set identified high-frequency gene mutations (≥ 10%) and well-defined cytogenetic subtypes, including t(8;21)(q22;q22), NPM1 mutations, and CEBPA mutations as key factors for future prognostic evaluation. These findings will contribute to the development of a prognostic scoring system using R programming in future.

Conclusion This study offers insights into the cytogenetic and mutational landscape of AML in the Indian population, identifying critical genetic and cytogenetic markers with the potential to enhance prognostication, guide treatment strategies, and inform transplant decisions. Using R tools like limma and edgeR, differential expression analysis identified five key genes—NPM1, FLT3, IDH2, RUNX1, and STAG2—as significantly upregulated in AML. Notably, STAG2 emerges as a novel marker with potential prognostic significance, warranting validation in larger Indian cohorts. These findings may help uncover novel therapeutic targets not currently recognized in Western populations, paving the way for a more tailored and personalized approach to treatment in India. By leveraging global genomic databases, this research addresses regional gaps in knowledge. Future work should focus on validating these findings through large-scale studies in Indian cohorts to ensure their broader applicability and impact.

Keywords

bioinformatics - TCGA data - AML genetics - prognosis in AML - risk categorization

Note

The manuscript has been read and approved by all the authors and that each author believes that the manuscript represents honest work.


* Joint First authors.


# Joint corresponding authors.




Publication History

Article published online:
24 February 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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