Abstract 1132: Quantifying selection intensity of driver genes in primary and metastatic thyroid cancer

Abstract The mutational profiles of primary and metastatic thyroid cancer (THCA) have been identified by comparing genetic alterations between the two stages, using mutation prevalence and P values to identify significant differences. However, these metrics do not quantify the cancer effects of variants. In this study, we quantified somatic selection on variants and genes using exome and targeted sequencing data from 2, 145 primary and 1, 374 metastatic tumors, derived from previous studies as well as GENIE, and TCGA databases, utilizing cancereffectsizeR to measure the cancer effects of new mutations. Comparisons of trinucleotide mutation profile revealed a relatively similar mutational landscape between primary and metastatic THCA, with notable differences such as GTG → GAG, TTG → TCG, and ATG → ACG mutations, which were more prevalent in metastatic tissues. While it is shown that TERT genetic alterations are more frequent in metastatic papillary thyroid carcinomas (PTCs) compared to primary PTCs, our analysis showed that the strength of somatic selection on TERT coding mutations was lower during the span from primary to metastatic THCA than during the span from thyroid organogenesis to primary THCA. Conversely, RET mutations, which is also shown to be more prevalent in metastatic tumors, were highly selected during the progression from primary to metastatic THCA, in comparison from organogenesis to primary THCA, aligning with the broader spectrum of RET mutations observed in metastatic medullary thyroid carcinoma. Furthermore, the selection intensity for mutations in genes such as BRAF, NRAS, TP53, ATM, KMT2D, KMT2C, NF1, NF2, PTEN, and NKX2-1 was higher during the transition from organogenesis to primary THCA compared to the progression from primary to metastatic THCA. In conclusion, our application of cancer effect size analyses revealed that the strengths of selection on mutations vary dynamically across the trajectories from organogenesis to primary THCA and from primary to metastatic THCA. We identified key genes driving THCA initiation and progression, providing a quantitative understanding of the evolutionary trajectory of mutations in this disease. These insights shed light on the determinants of THCA pathogenesis and metastasis and hold potential to inform future precision treatment strategies. Citation Format: Moein Rajaei, Andrew Ju, Jeffrey P. Townsend. Quantifying selection intensity of driver genes in primary and metastatic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1132.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1132
Primary Topic
Nutrition, Genetics, and Disease
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article
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article

Abstract 1132: Quantifying selection intensity of driver genes in primary and metastatic thyroid cancer

Moein Rajaei, Andrew Ju, Jeffrey P. Townsend
Cancer Research
Nutrition, Genetics, and Disease
article

Abstract 1132: Quantifying selection intensity of driver genes in primary and metastatic thyroid cancer

Moein Rajaei, Andrew Ju, Jeffrey P. Townsend
article en

Abstract

Abstract The mutational profiles of primary and metastatic thyroid cancer (THCA) have been identified by comparing genetic alterations between the two stages, using mutation prevalence and P values to identify significant differences. However, these metrics do not quantify the cancer effects of variants. In this study, we quantified somatic selection on variants and genes using exome and targeted sequencing data from 2, 145 primary and 1, 374 metastatic tumors, derived from previous studies as well as GENIE, and TCGA databases, utilizing cancereffectsizeR to measure the cancer effects of new mutations. Comparisons of trinucleotide mutation profile revealed a relatively similar mutational landscape between primary and metastatic THCA, with notable differences such as GTG → GAG, TTG → TCG, and ATG → ACG mutations, which were more prevalent in metastatic tissues. While it is shown that TERT genetic alterations are more frequent in metastatic papillary thyroid carcinomas (PTCs) compared to primary PTCs, our analysis showed that the strength of somatic selection on TERT coding mutations was lower during the span from primary to metastatic THCA than during the span from thyroid organogenesis to primary THCA. Conversely, RET mutations, which is also shown to be more prevalent in metastatic tumors, were highly selected during the progression from primary to metastatic THCA, in comparison from organogenesis to primary THCA, aligning with the broader spectrum of RET mutations observed in metastatic medullary thyroid carcinoma. Furthermore, the selection intensity for mutations in genes such as BRAF, NRAS, TP53, ATM, KMT2D, KMT2C, NF1, NF2, PTEN, and NKX2-1 was higher during the transition from organogenesis to primary THCA compared to the progression from primary to metastatic THCA. In conclusion, our application of cancer effect size analyses revealed that the strengths of selection on mutations vary dynamically across the trajectories from organogenesis to primary THCA and from primary to metastatic THCA. We identified key genes driving THCA initiation and progression, providing a quantitative understanding of the evolutionary trajectory of mutations in this disease. These insights shed light on the determinants of THCA pathogenesis and metastasis and hold potential to inform future precision treatment strategies. Citation Format: Moein Rajaei, Andrew Ju, Jeffrey P. Townsend. Quantifying selection intensity of driver genes in primary and metastatic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1132.

Cancer ResearchVol. 85(8_Supplement_1)
Yale University (US)
Openalex Percentile: Top 90%
Nutrition, Genetics, and Disease
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