Clinical and Translational Medicine (Jun 2023)

Integrated metabolic and genetic analysis reveals distinct features of human differentiated thyroid cancer

  • Eduardo Cararo Lopes,
  • Akshada Sawant,
  • Dirk Moore,
  • Hua Ke,
  • Fuqian Shi,
  • Saurabh Laddha,
  • Ying Chen,
  • Anchal Sharma,
  • Jake Naumann,
  • Jessie Yanxiang Guo,
  • Maria Gomez,
  • Maria Ibrahim,
  • Tracey L. Smith,
  • Gregory M. Riedlinger,
  • Edmund C. Lattime,
  • Stanley Trooskin,
  • Shridar Ganesan,
  • Xiaoyang Su,
  • Renata Pasqualini,
  • Wadih Arap,
  • Subhajyoti De,
  • Chang S. Chan,
  • Eileen White

DOI
https://doi.org/10.1002/ctm2.1298
Journal volume & issue
Vol. 13, no. 6
pp. n/a – n/a

Abstract

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Abstract Background Differentiated thyroid cancer (DTC) affects thousands of lives worldwide each year. Typically, DTC is a treatable disease with a good prognosis. Yet, some patients are subjected to partial or total thyroidectomy and radioiodine therapy to prevent local disease recurrence and metastasis. Unfortunately, thyroidectomy and/or radioiodine therapy often worsen(s) quality of life and might be unnecessary in indolent DTC cases. On the other hand, the lack of biomarkers indicating a potential metastatic thyroid cancer imposes an additional challenge to managing and treating patients with this disease. Aim The presented clinical setting highlights the unmet need for a precise molecular diagnosis of DTC and potential metastatic disease, which should dictate appropriate therapy. Materials and methods In this article, we present a differential multi‐omics model approach, including metabolomics, genomics, and bioinformatic models, to distinguish normal glands from thyroid tumours. Additionally, we are proposing biomarkers that could indicate potential metastatic diseases in papillary thyroid cancer (PTC), a sub‐class of DTC. Results Normal and tumour thyroid tissue from DTC patients had a distinct yet well‐defined metabolic profile with high levels of anabolic metabolites and/or other metabolites associated with the energy maintenance of tumour cells. The consistency of the DTC metabolic profile allowed us to build a bioinformatic classification model capable of clearly distinguishing normal from tumor thyroid tissues, which might help diagnose thyroid cancer. Moreover, based on PTC patient samples, our data suggest that elevated nuclear and mitochondrial DNA mutational burden, intra‐tumour heterogeneity, shortened telomere length, and altered metabolic profile reflect the potential for metastatic disease. Discussion Altogether, this work indicates that a differential and integrated multi‐omics approach might improve DTC management, perhaps preventing unnecessary thyroid gland removal and/or radioiodine therapy. Conclusions Well‐designed, prospective translational clinical trials will ultimately show the value of this integrated multi‐omics approach and early diagnosis of DTC and potential metastatic PTC.

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