Publications by Year: 2021

Background: BRAFV600E acts as an ATP-dependent cytosolic kinase. BRAFV600E inhibitors are widely available, but resistance to them is widely reported in the clinic. Lipid metabolism (fatty acids) is fundamental for energy and to control cell stress. Whether and how BRAFV600E impacts lipid metabolism regulation in papillary thyroid carcinoma (PTC) is still unknown. Acetyl-CoA carboxylase (ACC) is a rate-limiting enzyme for de novo lipid synthesis and inhibition of fatty acid oxidation (FAO). ACC1 and ACC2 genes encode distinct isoforms of ACC. The aim of our study was to determine the relationship between BRAFV600E and ACC in PTC. Methods: We performed RNA-seq and DNA copy number analyses in PTC and normal thyroid (NT) in The Cancer Genome Atlas samples. Validations were performed by using assays on PTC-derived cell lines of differing BRAF status and a xenograft mouse model derived from a heterozygous BRAFWT/V600E PTC-derived cell line with knockdown (sh) of ACC1 or ACC2. Results:ACC2 mRNA expression was significantly downregulated in BRAFV600E-PTC vs. BRAFWT-PTC or NT clinical samples. ACC2 protein levels were downregulated in BRAFV600E-PTC cell lines vs. the BRAFWT/WT PTC cell line. Vemurafenib increased ACC2 (and to a lesser extent ACC1) mRNA levels in PTC-derived cell lines in a BRAFV600E allelic dose-dependent manner. BRAFV600E inhibition increased de novo lipid synthesis rates, and decreased FAO due to oxygen consumption rate (OCR), and extracellular acidification rate (ECAR), after addition of palmitate. Only shACC2 significantly increased OCR rates due to FAO, while it decreased ECAR in BRAFV600E PTC-derived cells vs. controls. BRAFV600E inhibition synergized with shACC2 to increase intracellular reactive oxygen species production, leading to increased cell proliferation and, ultimately, vemurafenib resistance. Mice implanted with a BRAFWT/V600E PTC-derived cell line with shACC2 showed significantly increased tumor growth after vemurafenib treatment, while vehicle-treated controls, or shGFP control cells treated with vemurafenib showed stable tumor growth. Conclusions: These findings suggest a potential link between BRAFV600E and lipid metabolism regulation in PTC. BRAFV600E downregulates ACC2 levels, which deregulates de novo lipid synthesis, FAO due to OCR, and ECAR rates. ShACC2 may contribute to vemurafenib resistance and increased tumor growth. ACC2 rescue may represent a novel molecular strategy for overcoming resistance to BRAFV600E inhibitors in refractory PTC.

CONTEXT: Pericyte populations abundantly express tyrosine kinases (eg, platelet-derived growth factor receptor-β [PDGFR-β]) and impact therapeutic response. Lenvatinib is a clinically available tyrosine kinase inhibitor that also targets PDGFR-β. Duration of therapeutic response was shorter in patients with greater disease burden and metastasis. Patients may develop drug resistance and tumor progression.

OBJECTIVES: Develop a gene signature of pericyte abundance to assess with tumor aggressiveness and determine both the response of thyroid-derived pericytes to lenvatinib and their synergies with thyroid carcinoma-derived cells.

DESIGN: Using a new gene signature, we estimated the relative abundance of pericytes in papillary thyroid carcinoma (PTC) and normal thyroid (NT) TCGA samples. We also cocultured CD90+;PAX8- thyroid-derived pericytes and BRAFWT/V600E-PTC-derived cells to determine effects of coculture on paracrine communications and lenvatinib response.

RESULTS: Pericyte abundance is significantly higher in BRAFV600E-PTC with hTERT mutations and copy number alterations compared with NT or BRAFWT-PTC samples, even when data are corrected for clinical-pathologic confounders. We have identified upregulated pathways important for tumor survival, immunomodulation, RNA transcription, cell-cycle regulation, and cholesterol metabolism. Pericyte growth is significantly increased by platelet-derived growth factor-BB, which activates phospho(p)-PDGFR-β, pERK1/2, and pAKT. Lenvatinib strongly inhibits pericyte viability by down-regulating MAPK, pAKT, and p-p70S6-kinase downstream PDGFR-β. Critically, lenvatinib significantly induces higher BRAFWT/V600E-PTC cell death when cocultured with pericytes, as a result of pericyte targeting via PDGFR-β.

CONCLUSIONS: This is the first thyroid-specific model of lenvatinib therapeutic efficacy against pericyte viability, which disadvantages BRAFWT/V600E-PTC growth. Assessing pericyte abundance in patients with PTC could be essential to selection rationales for appropriate targeted therapy with lenvatinib.

Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, whereas anaplastic thyroid carcinoma (ATC) is a lethal form of cancer. Different genetic and epigenetic alterations have been identified in aggressive forms of TC such as ATC. Non-coding RNAs (ncRNAs) represent functional regulatory molecules that control chromatin reprogramming, including transcriptional and post-transcriptional mechanisms. Intriguingly, they also play an important role as coordinators of complex gene regulatory networks (GRNs) in cancer. GRN analysis can model molecular regulation in different species. Neural networks are robust computing systems for learning and modeling the dynamics or dependencies between genes, and are used for the reconstruction of large data sets. Canonical network motifs are coordinated by ncRNAs through gene production from each transcript as well as through the generation of a single transcript that gives rise to multiple functional products by post-transcriptional modifications. In non-canonical network motifs, ncRNAs interact through binding to proteins and/or protein complexes and regulate their functions. This article overviews the potential role of ncRNAs GRNs in TC. It also suggests prospective applications of deep neural network analysis to predict ncRNA molecular language for early detection and to determine the prognosis of TC. Validation of these analyses may help in the design of more effective and precise targeted therapies against aggressive TC.

Thyroid cancer is the most common endocrine malignancy, and aggressive radioactive iodine refractory thyroid carcinomas still lack an effective treatment. A deeper understanding of tumor heterogeneity and microenvironment will be critical to establishing new therapeutic approaches. One of the important influencing factors of tumor heterogeneity is the diversity of cells in the tumor microenvironment. Among these are pericytes, which play an important role in blood vessel stability and angiogenesis, as well as tumor growth and metastasis. Pericytes also have stem cell-like properties and are a heterogeneous cell population, and their lineage, which has been challenging to define, may impact tumor resistance at different tumor stages. Pericytes are also important stroma cell types in the angiogenic microenvironment which express tyrosine-kinase (TK) pathways (e.g., PDGFR-β). Although TK inhibitors (TKI) and BRAFV600E inhibitors are currently used in the clinic for thyroid cancer, their efficacy is not durable and drug resistance often develops. Characterizing the range of distinct pericyte populations and distinguishing them from other perivascular cell types may enable the identification of their specific functions in the thyroid carcinoma vasculature. This remains an essential step in developing new therapeutic strategies. Also, assessing whether thyroid tumors hold immature and/or mature vasculature with pericyte populations coverage may be key to predicting tumor response to either targeted or anti-angiogenesis therapies. It is also critical to apply different markers in order to identify pericyte populations and characterize their cell lineage. This chapter provides an overview of pericyte ontogenesis and the lineages of diverse cell populations. We also discuss the role(s) and targeting of pericytes in thyroid carcinoma, as well as their potential impact on precision targeted therapies and drug resistance.