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Endocrine Abstracts (2024) 99 EP45 | DOI: 10.1530/endoabs.99.EP45

ECE2024 Eposter Presentations Endocrine-Related Cancer (90 abstracts)

"Deciphering the genomic complexity of thyroid cancers: an in-depth exploration through pan-exomic analysis using whole exome next-generation sequencing"

Ramesh Bangaraiahgari 1 , Rajesh Bangaraiahgari 1 , Ramakanth Bhargav Panchangam 2 , Udaya Kumar 3 , Banala Rajkiran Reddy Banala 4 & Chakrapani Bangaraiahgari 5


1TRR Institute of Medical Sciences, Hyderabad, India; 2Bhargav Endocare Hospital, Endocrine and Metabolic Surgery, Andhra pradesh, India; 3Arundathi Institute of Medical Sciences, Pediatrics, Hyderabad, India; 4Sunshine Hospital, CRL, Hyderabad, India; 5Chakri Neuro Hospital, Neurology, Nizamabad, India


Background: Thyroid cancers represent a diverse group of malignancies characterized by intricate genomic landscapes, necessitating advanced molecular investigations for a comprehensive understanding of their underlying genetic alterations. This study harnesses the power of Whole Exome Next-Generation Sequencing (WES) to unravel pan-exomic mutations in thyroid cancer samples. The primary objectives include correlating genomic changes with clinicopathologic features and unravelling the intricate mechanisms steering disease onset and progression.

Methods: Raw sequencing data derived from both normal and cancerous thyroid tissues underwent a meticulous analytical pipeline. Leveraging tools such as the NGS QC Toolkit, Burrows-Wheeler Aligner, and GATK, the study commenced with a thorough assessment of read quality. Subsequent steps involved alignment of sequences to the human reference genome (hg19), recalibration of base quality, and calculation of coverage metrics. Somatic variations were identified using MuTect for single nucleotide variations (SNVs) and VarScan for small insertions and deletions (indels). ANNOVAR facilitated comprehensive annotation of the identified variants. Stringent filtering criteria excluded common single nucleotide polymorphisms (SNPs), noncoding variants, and those residing within repetitive genomic regions. Manual validation using the Integrated Genomics Viewer ensured the accuracy of the identified mutations.

Results: The study unveiled significant mutations predominantly in BRAF, CDKN2A, HRAS, NRAS, PI3KCA, RET, RAS, and TP53 genes. Noteworthy common mutations included RET (M918T), NRAS (Q61R), BRAF (V600E), HRAS (Q61R), and a missense mutation in TP53 (c.217 – c.1178). Additionally, a mutation in the KMT2D gene was identified in one patient sample, introducing an intriguing aspect to the genomic landscape.

Conclusion: This research significantly contributes to the evolving field of thyroid cancer genomics. By identifying prevalent mutations and indicating the need for ongoing efforts to detect rare mutations, our findings underscore the complexity of these cancers. The discerned genomic landscape not only advances scientific understanding but also lays the groundwork for the potential integration of precision medicine into thyroid cancer diagnosis and treatment strategies. The structured approach offers a comprehensive overview of the research methodology, key findings, and their broader implications.

Keywords: Thyroid cancers, Whole Exome Sequencing, Pan-exomic mutations, Somatic variations, Precision medicine.

Disclosure of interest: None declared

Volume 99

26th European Congress of Endocrinology

Stockholm, Sweden
11 May 2024 - 14 May 2024

European Society of Endocrinology 

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