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Oncologist
Oncologist
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The Oncologist
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10.1093/oncolo/oyae075
oyae075
Endocrinology
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Metabolomics reveals the implication of acetoacetate and ketogenic diet therapy in radioiodine-refractory differentiated thyroid carcinoma
Wang Jiaqi Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China
Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, People’s Republic of China

Xu Qianqian Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China
Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, People’s Republic of China

Xuan Ziyang Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China
Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, People’s Republic of China

Mao Yuting Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China
Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, People’s Republic of China

Tang Xi Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China

Yang Ke Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China

Song Fahuan Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, People’s Republic of China

https://orcid.org/0000-0001-5337-4661
Zhu Xin Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China
Postgraduate training base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, People’s Republic of China

Corresponding author: Xin Zhu, Key Laboratory of Head and Neck Cancer Translation Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, People’s Republic of China (zhuxin@zjcc.org.cn)
Corresponding author: Fahuan Song, Cancer Center, Department of Nuclear Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, People’s Republic of China (seefarworld@163.com).
Jiaqi Wang and Qianqian Xu Contributed equally.

9 2024
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Abstract

Objective

Patients with radioiodine-refractory (RAIR) differentiated thyroid carcinoma (DTC; RAIR-DTC) have a poor prognosis. The aim of this study was to provide new insights and possibilities for the diagnosis and treatment of RAIR-DTC.

Methods

The metabolomics of 24 RAIR-DTC and 18 non-radioiodine-refractory (NonRAIR) DTC patients samples were analyzed by liquid chromatograph-mass spectrometry. Cellular radioiodine uptake was detected with γ counter. Sodium iodide symporter (NIS) expression and thyroid stimulating hormone receptor (TSHR) were measured by Western blot analysis. CCK8 and colony formation assays were used to measure cellular proliferation. Scratch and transwell assays were performed to assess cell migration and invasion. Annexin V/PI staining was used to detect cell apoptosis. Cell growth in vivo was evaluated by a tumor xenograft model. The acetoacetate (AcAc) level was measured by ELISA. Pathological changes, Ki67, NIS, and TSHR expression were investigated by immunohistochemistry.

Results

The metabolite profiles of RAIR could be distinguished from those of NonRAIR, with AcAc significantly lower in RAIR. The significantly different metabolic pathway was ketone body metabolism. AcAc increased NIS and TSHR expression and improved radioiodine uptake. AcAc inhibited cell proliferation, migration, and invasion, and as well promoted cell apoptosis. Ketogenic diet (KD) elevated AcAc levels and significantly suppressed tumor growth, as well as improved NIS and TSHR expression.

Conclusion

Significant metabolic differences were observed between RAIR and NonRAIR, and ketone body metabolism might play an important role in RAIR-DTC. AcAc improved cellular iodine uptake and had antitumor effects for thyroid carcinoma. KD might be a new therapeutic strategy for RAIR-DTC.

Patients with radioiodine-refractory differentiated thyroid carcinoma (RAIR-DTC) have a poor prognosis. The aim of this study was to provide new insights and possibilities for the diagnosis and treatment of RAIR-DTC.

radioiodine-refractory differentiated thyroid carcinoma
metabolomics
acetoacetate
ketogenic diet
National Natural Science Foundation of China 10.13039/501100001809 82072950 China Postdoctoral Science Foundation 10.13039/501100002858 2021M702908 Zhejiang Province Postdoctoral Research Excellence Funding Project ZJ2021039 Zhejiang Provincial Health Commission 2024037191
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pmcImplications for Practice

This article describes the metabolic characteristics and potential contributions of a ketogenic diet as complementary nutritional treatment for radioiodine-refractory differentiated thyroid carcinoma.

Introduction

Thyroid carcinoma is the most common malignancy of the endocrine system and the ninth most common cancer.1 Differentiated thyroid carcinoma (DTC), including papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC), are identified based on histopathological criteria and account for approximately 90% of thyroid malignancies.2 Patients with DTC have a favorable prognosis after surgery, postoperative radioiodine therapy, and thyroid stimulating hormone (TSH) inhibition therapy.3 However, 7%-23% of patients with DTC develop distant metastases.4 Among these patients, two-thirds become RAIR-DTC,5-7 with an average survival of 3-5 years and a 10-year survival rate of less than 10%.8-10 Clinical early diagnosis of these patients is difficult and current treatment is limited.11 Hence, new approaches to both diagnosis and treatment of RAIR-DTC are urgently needed.

During the development of tumors, metabolites, as downstream products of gene and protein expression, undergo alterations.12 In cancer cells, metabolism is altered and dysregulated in order to provide the energy necessary for uncontrolled cell growth.13,14 Thyroid carcinoma is associated with metabolic abnormalities,15 with obvious metabolic differences among PTC,16 benign thyroid nodule (BTN),17 and normal thyroid tissue.18 Compared to normal cells, different types of thyroid carcinoma exhibit significant differences in the metabolism of sugars, lipids, amino acids, nucleosides, and other substances.19

Metabolomics is the global analysis of small-molecule metabolites.20 Such analysis can be used to compare the metabolite characteristics (variety and quantity) of normal metabolic processes to the environmental changes associated with abnormal processes.21 By metabolomics, biomarkers can be identified that are associated with disease progression and with microbiome alterations. As such, metabolomics can provide useful information regarding individual genetic differences, environmental influence factors, and disease states, which can be used as biomarkers for prediction of health, well-being, and disease.22

In this study, liquid chromatograph-mass spectrometry (LC-MS) was used to assess RAIR and NonRAIR patient tissue samples for metabolite differences in; acetoacetate (AcAc), butanal, 2-hydroxybutyric acid, l-phenylalanine, d-synephrine, l-leucine, glycylleucine, l-isoleucine, and l-methionine. Among the above metabolites, the most significant metabolic pathway difference was in ketone body metabolism. Furthermore, AcAc was found to improve radioiodine uptake by PTC cells, with antitumor effects. This study provided evidence for a new therapeutic strategy, ketogenic diet (KD), for the treatment of RAIR-DTC.

Materials and methods

Clinical samples

A total of 42 primary patients with DTC were enrolled in this study from the Department of Head and Neck Surgery at Zhejiang Cancer Hospital from May 2012 to December 2019. Tissue specimens were acquired from the tissue bank of Zhejiang Cancer Hospital and reconfirmed by 2 expert pathologists. The clinico-pathology, CT examination, and radioiodine whole-body scan (131I WBS) of these patients were obtained from clinical records. Classification of RAIR-DTC was as described in the 2015 American Thyroid Association (ATA) Guidelines23 and included: (1) lack of radioiodine uptake in malignant/metastatic tumor tissue; (2) tumor tissue lost the ability to concentrate radioiodine after previous evidence of radioiodine uptake; (3) radioiodine is concentrated in some metastatic tumor tissue, but not in others; and (4) metastatic disease progresses despite significant concentrations of radioiodine and relevant clinical experience. Forty-two patients were divided into 2 groups: 24 RAIR patients and 18 NonRAIR patients. The clinico-pathology characteristics of these patients were analyzed retrospectively and included sex, age, tumor size, extrathyroidal extension, lymph node metastasis, and TNM stage. The TNM staging of patients with DTC was determined using the AJCC Version 8 Cancer Staging System. The Ethics Committee of Zhejiang Cancer Hospital approved the study, and all patients signed informed consent before inclusion in the study.

Untargeted LC-MS-based metabolomics methods

The sample preparation methods

A total of 42 patients’ tissue specimens were collected, including 24 RAIR and 18 NonRAIR. Extract 30 mg of each sample into 1.5 mL centrifuge tubes, add 400 µL of methanol (precooled at −20 °C) to each tube and 2 small steel beads, after precooled for 2 minutes in −20 °C, put into the grinder (60 Hz, 2 minutes). Then ultrasound extraction 10 minutes and stand for 30 minutes in −20 °C. After vortex for 60 seconds, centrifuge at 4 °C for 10 minutes at 12 000 rpm, and then transfer all supernatant from each sample into another 1.5 mL centrifuge tube. Samples were concentrated to dry in vacuum. Dissolve samples with 150 μL 2-chlorobenzalanine (4 ppm) 80% methanol solution, and the supernatant was filtered through 0.22-µm membrane to obtain the prepared samples for LC-MS. Take 20 µL from each sample to the quality control (QC) samples (these QC samples were used to monitor deviations of the analytical results from these pool mixtures and compare them to the errors caused by the analytical instrument itself). Use the rest of the samples for LC-MS detection.

Liquid phase and mass spectrometry conditions

Chromatographic separation was accomplished in a Thermo Vanquish system equipped with an ACQUITY UPLC HSS T3 (150 × 2.1 mm, 1.8 µm, Waters) column maintained at 40°C. The temperature of the autosampler was 8 °C. Gradient elution of analytes was carried out with 0.1% formic acid in water (A2) and 0.1% formic acid in acetonitrile (B2) or 5 mM ammonium formate in water (A1) and acetonitrile (B2) at a flow rate of 0.25 mL/minutes. Injection of 2 μL of each sample was done after equilibration. An increasing linear gradient of solvent A (v/v) was used as follows: 0~1 minute, 2% B1/B2; 1~9 minutes, 2%~50% B1/B2; 9~12 minutes, 50%~98% B1/B2; 12~13.5 minutes, 98% B1/B2; 13.5~14 minutes, 98%~2% B1/B2; 14~20 minutes, 2% B2-positive model (14~17 minutes, 2% B1-negative model).

The ESI-MSn experiments were executed on the Thermo Q Exactive Focus mass spectrometer with the spray voltage of 3.8 kV and −2.5 kV in positive and negative modes, respectively. Sheath gas and auxiliary gas were set at 30 and 10 arbitrary units, respectively. The capillary temperature was 325 °C. The analyzer scanned over a mass range of m/z 81-1 000 for full scan at a mass resolution of 70 000. Data-dependent acquisition (DDA) MS/MS experiments were performed with HCD scan. The normalized collision energy was 30 eV. Dynamic exclusion was implemented to remove some unnecessary information in MS/MS spectra.

LC-MS data analysis methods

First, partial least squares-discrimination analysis (PLS-DA) was performed for classification. Subsequently, orthogonal partial least squares-discrimination analysis (OPLS-DA) was conducted to maximize the separation between the comparison groups. Furthermore, a permutation test was used to test model reliability. R2 and Q2 were obtained through a permutation test and were used to verify whether the model was overfitting. Variable importance in projection (VIP) is the variable weight value of the OPLS-DA model variables, which can be used to measure the influence intensity and interpretation ability of metabolite accumulation differences in the classification and discrimination of each group of samples. The data array was uploaded to MetaboAnalyst (https://www.metaboanalyst.ca/). The preprocessed data were normalized: normalization to a constant sum; data scaling: Autoscaling. MetaboAnalyst provided fold change analysis and t-tests for 2-group data. Box plots and heat maps were drawn according to the analysis results. Moreover, receiver operating characteristic curve (ROC) analysis was performed using the survival analysis module to evaluate the area under the curve (AUC) and compare the diagnostic ability of significant metabolites between the tested groups. The differential metabolites between RAIR and NonRAIR were then identified by the criteria of variable importance in projection VIP score > 1 and P value < .05. Finally, meaningful metabolic pathways were analyzed using MetaboAnalyst 5.0. This study referred to the GenomeNet database (KEGG, https://www.genome.jp/kegg) to elucidate any changes or interference patterns observed in the metabolic pathways of the study participants.

Materials and reagents

AcAc was purchased from Macklin (Shanghai, China), dissolved in ddH2O, and then diluted with culture medium to working concentrations. Cell Counting Kit 8s (CCK8) were purchased from BestBio (Shanghai, China). The following primary antibodies were prepared: Rabbit anti‐NIS (Proteintech, Wuhan, China), Mouse anti‐β-actin (Proteintech), Mouse anti‐TSHR (abcam, Shanghai, China), and Rabbit anti-Ki67 (Cell Signaling Technology, Shanghai, China). Secondary antibody was Horseradish peroxidase (HRP)‐conjugated goat anti‐rabbit/mouse IgG (Beyotime, Shanghai, China).

Cell culture

BCPAP and TPC-1 cell lines were purchased from the Cell Resource Center, Shanghai Institutes for Biological Sciences of the Chinese Academy of Sciences. The cell lines were incubated in RPMI-1640 (Thermo Fisher Scientific Inc., MA, USA) supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific Inc.) and cultured in an incubator, with a humidified atmosphere of 5% CO2 at 37 °C.

Radioiodine uptake

A total of 1 × 106 cells were cultured in 6-well plates and treated with AcAc for 48 hours after adherence. The cells were washed 3 times with phosphate-buffered saline (PBS; Servicebio, Wuhan, China) and 2 mL of medium containing 1 µCi Na131I was added. The cells were incubated at 37 °C for 2 hours. Cells were washed 3 times with PBS, digested with trypsin, collected, and counted. Radioactive counts per minute (CPM) were measured using an automatic gamma counter (PerkinElmer Instruments, 2470 Wizard2). CPM/105 cells were used as cellular radioactive iodine uptake units to evaluate the effect of AcAc on radioactive iodine uptake.

Western blot analysis

Cells were lysed with RIPA buffer containing phosphatase and protease inhibitors (Beyotime). Equal amounts of protein were separated by electrophoresis on 10% SDS-PAGE gels and transferred onto methanol-activated polyvinylidene fluoride (PVDF) membranes for 1.5 hours at 90 V. The PVDF membranes were blocked with 5% nonfat milk for 2 hours at 25 °C. Membranes were incubated overnight at 4 °C with primary antibodies reactive with NIS, TSHR, and β-actin. The membranes were incubated with horseradish peroxidase-conjugated anti-rabbit/mouse IgG secondary antibodies for 1 hour at 25 °C. The protein bands were detected by enhanced chemiluminescence. ImageJ software (National Institutes of Health, Bethesda, MD, USA) was used to scan and analyze the protein bands.

CCK8 assay

Cell viability was quantified with CCK8, according to the manufacturer’s instructions. The cells were plated at a density of 3 × 103 cells per well in 96-well plates. After 24 hours, 3 groups of cells were prepared as follows: a control group, a 5-mM AcAc group, and a 10-mM AcAc group. Fresh culture medium was added to each well. After 24 and 48 hours, 10 µL of CCK8 was added to each well and incubated at 37 °C for 2 hours and absorbance at 450 nm was measured with a microplate reader.

Colony formation assay

The cells were plated at a density of 1 × 103 cells per well in 6-well plates. The following groups were prepared: a control group, a 5-mM AcAc group, and a 10-mM AcAc group. After 5-7 days of culture, the colonies were stained with 0.5% Crystal Violet (Biotec, Beijing, China) to assess colony formation.

Wound healing assay

Cells were plated at a density of 5 × 105 cells per well in 6-well plates. The following groups were prepared: a control group, a 5-mM AcAc group, and a 10-mM AcAc group. After overnight cell adherence and scratch injury, same position photographs were obtained at 0, 24, and 48 hours to compare the healing of scratches and to investigate the effect of AcAc on cell migration.

Transwell assay

Transwell inserts (pore size: 8 µm) coated with Matrigel (Corning, NY, USA) were used to evaluate the invasive capacity of BCPAP and TPC-1 cells. For invasion assays, inserts were coated with 12.5% matrigel in serum-free RPMI-1640 medium. 4 × 104 cells were added in 200 µL of serum-free medium to the upper chambers and 700 µL of RPMI-1640 medium to the lower chambers. The cells were incubated for 24 hours and the following groups were prepared: a control group, a 5-mM AcAc group, and a 10-mM AcAc group. After 24 hours of culture, cells were fixed with paraformaldehyde and stained with crystal violet for 15 minutes. Numbers of invasive cells were assessed in 3 microscopic fields.

Flow cytometric analysis of apoptosis

Cells were plated at a density of 1 × 105 cells per well in 6-well plates. After overnight adherence, the cells were treated with AcAc for 48 hours, collected, washed twice with precooled PBS, stained with Annexin V/PI (Multi Sciences, Hangzhou, China), and the percentage of apoptotic cells was determined by flow cytometry.

Tumor xenograft Model

BCPAP cells were harvested and resuspended in PBS at a density of 1 × 108 cells/mL. Four-week-old male BALB/c athymic nude mice were subcutaneously injected with 0.1 mL of the suspension. Based on the literature,24 KD was customized (Supplementary Table S1). Athymic nude mice were randomly divided into 2 groups, a standard diet (SD) group and a KD group. The weight and tumor size of the athymic nude mice were dynamically observed and recorded. Tumor volumes were recorded every week and were calculated with the formula: V = length × (width) 2/2. After 4 weeks, animals were euthanized and tumor xenografts were weighed. The Ethics Committee of Zhejiang Cancer Hospital approved all test steps.

Enzyme-linked immunosorbent assay

Serum was obtained by centrifugation of whole blood and levels of AcAc were determined with a mouse AcAc enzyme-linked immunosorbent assay kit (Solarbio, Beijing, China) according to the manufacturer’s instructions.

Tissue microarray analysis constructs and immunohistochemistry

Two representative areas (1 mm in diameter) per tumor were selected for tissue microarray analysis (TMA) and stained with hematoxylin/eosin. Immunohistochemistry was performed with TMA 4-µm sections using Ki67, NIS, and TSHR reactive monoclonal antibodies. H-scores were used to quantify Ki67, NIS, and TSHR reactivities. H-score=Σpi(i + 1), where pi represents the number of positive cells as a percentage of all cells in the section and i represents the color intensity.25

Statistical analysis

All experimental data were analyzed by GraphPad Prism 8.0 with results expressed as means ± SD. The chi-square test was used for categorical variables. Differences between 2 groups were compared by the t-test. Differences among multiple groups were compared by one-way ANOVA. P < .05 was considered statistically significant.

Results

It is difficult to distinguish RAIR and NonRAIR based on clinical characteristics

The clinical characteristics of 24 RAIR patients and 18 NonRAIR patients were similar in sex, tumor size, extrathyroidal extension, lymph node metastasis, and TNM stage (Supplementary Table S2). There was no significant difference between the clinical characteristics of RAIR and NonRAIR patients. Images of 2 patients are shown in Figure 1. One image is of a 25-year-old male with no 131I uptake, who was judged as an RAIR patient (Figure 1A-1C). Enhanced neck CT scans showed enlarged lymph nodes in the left neck region (level IIb), indicating metastatic lesions. The other image is of a 34-year-old female with obvious radioactive iodine uptake in the right neck, who was judged as a NonRAIR patient (Figure 1D-1F). Enhanced neck CT scans showed enlarged lymph nodes in the right neck region (level VIb), indicating metastatic lesions.

Figure 1. Images of 2 patients. (A-C) Images of a 25-year-old male with thyroidectomy 10 months previous. (A) 131I WBS. (B) Neck plane CT image. (C) Neck enhanced CT image. (D-F) Images of a 34-year-old female with thyroidectomy 7 months previous. (D) 131I WBS. (E) Neck plane CT image. (F) Neck enhanced CT image.

Metabolomics analysis.

To identify significantly different metabolites, 42 tissue samples were analyzed by LC-MS in both positive and negative ion modes. Results showed differences between RAIR and NonRAIR patients. PLS-DA and OPLS-DA dispersion plots of these differences are presented in Supplementary Figure S1. Permutation analysis demonstrated that the model was not overfitted (Supplementary Figure S1C, S1F). Metabolites were analyzed based on differential metabolite screening conditions and results identified 9 different metabolites; AcAc, butanal, 2-hydroxybutyric acid, l-phenylalanine, d-synephrine, l-leucine, glycylleucine, l-isoleucine, and l-methionine (Figure 2A-2I). The detailed information is shown in Table 1. Differential metabolic pathways were analyzed with the KEGG database and results identified a significant difference in the ketone body metabolism pathway (Figure 2K).

Table 1. List of identified differential metabolites between the RAIR patients and NonRAIR patients.

No.	Name	Formula	mz	rt	VIP	P value	ppm	Fold change	
1	Acetoacetate	C4H6O3	85.03	94.83	2.43	.01	0.09	0.69	
2	Butanal	C4H8O	72.08	70.80	1.85	.02	0.05	1.21	
3	2-Hydroxybutyric acid	C4H8O3	104.05	71.68	1.90	.03	0.95	1.54	
4	l-Phenylalanine	C9H11NO2	166.14	239.59	1.79	.01	2.24	1.37	
5	d-Synephrine	C9H13NO2	168.09	239.40	1.78	.02	0.21	1.36	
6	l-Leucine	C6H13NO2	130.09	196.94	1.92	.04	3.29	1.40	
7	Glycylleucine	C8H16N2O3	187.11	258.78	2.06	.03	2.25	2.02	
8	l-Isoleucine	C6H13NO2	132.14	146.14	2.33	.01	2.32	1.63	
9	l-Methionine	C5H11NO2S	150.06	95.08	1.95	.02	1.70	1.78	
P values were calculated by an independent t-test.

Figure 2. Analysis of differential metabolites and metabolic pathways. (A-I) Box plots and ROC curves analysis of differential metabolites. (J) Differential metabolite heat map. (K) Differential metabolic pathways analyzed with the KEGG database. *P < .05; **P < .01.

In thyroid carcinoma, AcAc improves iodine uptake by cells and produces antitumor effects

After 48 hours of in vitro treatment with AcAc, 131I uptake by BCPAP and TPC-1 cells was significantly increased (Figure 3A) as were the levels of NIS and TSHR protein (Figure 3B, 3C). The viability of BCPAP and TPC-1 cells was significantly decreased by high concentrations of AcAc (Figure 4B, 4C). Furthermore, after 48 hours of treatment, AcAc significantly inhibited colony formation by TPC-1 cells (Figure 4A, 4E) and increased significantly the apoptosis of BCPAP and TPC-1 cells (Figure 4D, 4F). Wound healing assays demonstrated the migration of TPC-1 cells to be significantly inhibited by AcAc (Figure 5A, 5B, 5E, 5F). Furthermore, AcAc significantly inhibited the invasion of BCPAP and TPC-1 by transwell assay (Figure 5C, 5D, 5G, 5H).

Figure 3. AcAc affects iodine uptake by BCPAP and TPC-1 cells. (A) Changes in 131I uptake by BCPAP and TPC-1 cells at differing concentrations of AcAc. (B, C) NIS and TSHR levels in BCPAP and TPC-1 cells treated with differing concentrations of AcAc. *P < .05; ***P < .001.

Figure 4. AcAc affects the proliferation and apoptosis of BCPAP and TPC-1 cells. (A, E) Colony formation by BCPAP and TPC-1 cells with differing concentrations of AcAc. (B, C) Effect on the viability of differing concentrations of AcAc on BCPAP and TPC-1 cells. (D-F) Effect of differing concentrations of AcAc on apoptosis of BCPAP and TPC-1 cells. ns, not significant; *P < .05; **P < .01; ***P < .001.

Figure 5. Effect of AcAc on BCPAP and TPC-1 cell migration and invasion. (A, B) The effect of AcAc on the migration of BCPAP cells. (C, D) Effect of AcAc on invasion by BCPAP cells. (E, F) Effect of AcAc on migration of TPC-1 cells. (G, H) Effect of AcAc on invasion of TPC-1 cells. ns, not significant; *P < .05; ***P < .001.

KD significantly suppresses the growth of thyroid carcinoma in vivo

BCPAP cells were used to construct a transplanted tumor model in nude mice. Mice were randomly divided into SD group and KD group. Weight change and tumor size were dynamically observed and recorded. KD significantly inhibited tumor growth (Figure 6A, 6B, 6F) but had no effect on body weight (Figure 6C). AcAc serum levels for mice fed KD were significantly increased (Figure 6G). For animals fed KD, Ki67 levels in tumor tissues were significantly decreased and NIS and TSHR levels were significantly increased compared to animals fed a SD (Figure 6D, 6E, 6H).

Figure 6. Effects of KD in vivo. (A) Transplanted tumor model and tumor size of nude mice. (B) Tumor volume. (C) Body weight. (D) HE staining, Ki67, NIS, and TSHR levels in tumor tissue of animals fed SD. (E) HE staining, Ki67, NIS, and TSHR levels in tumor tissue of animals fed KD. (F) Tumor weight. (G) AcAc concentration in serum. (H) H-score for Ki67, NIS, and TSHR in tumor tissue. SD: standard diet group; KD: ketogenic diet group; ns, not significant; *P < .05; **P < .01; ***P < .001.

Discussion

Patients with RAIR-DTC have a poor prognosis with an average survival time of 3-5 years and a 10-year survival rate of less than 10%.26-28 Early diagnosis and treatment of these patients are important clinical issues. Therefore, we retrospectively analyzed 24 RAIR patients and 18 NonRAIR patients for their clinical characteristics including; sex, age, tumor size, extrathyroidal extension, lymph node metastasis, and TNM stage. There was no significant difference in the clinical characteristics of RAIR and NonRAIR patients. Currently, there is no reliable biomarker to differentiate RAIR from NonRAIR DTC patients. For other tumors, metabolic abnormalities can serve as important biomarkers that provide the means by which to accurately diagnose, phenotype, predict, and treat patients with cancer.29-32 This study compared RAIR and NonRAIR clinical tissue samples by LC-MS analysis. We identified the metabolomic signatures associated with RAIR and NonRAIR patients and found the metabolic profiles of the 2 groups of patients to be significantly different. We found 9 differential metabolites: AcAc, butanal, 2-hydroxybutyric acid, l-phenylalanine, d-synephrine, l-leucine, glycylleucine, l-isoleucine, and l-methionine. Furthermore, we found ketone body metabolism to be the most significantly different pathway. These findings demonstrate that ketone body metabolism played an important role in RAIR-DTC. Based on the results of the metabolomics, the differential ketone body metabolite, AcAc, was investigated.

AcAc is the main ketone body present in the body and is mainly derived by fatty acid oxidation within the liver. AcAc is an alternative cellular fuel during starvation or carbohydrate restriction,33 and in this study, was found to be significantly upregulated in NonRAIR as compared to RAIR patients. Interestingly, we found that AcAc enhances 131I uptake and upregulates NIS and TSHR levels in thyroid carcinoma. The unique radioiodine uptake capacity of thyroid carcinoma cells makes 131I the main mode of patient treatment and is crucial to prognosis. Decreased expression or abnormal localization of NIS are the main mechanisms of RAIR-DTC.34 TSHR is a key factor in regulating NIS expression in thyroid follicular cells.26 This study demonstrated the important role of AcAc in iodine uptake by thyroid carcinoma cells. As such, this observation may provide a new means by which to reverse the radioiodine uptake capacity of RAIR-DTC and allow 131I to be used again for RAIR-DTC therapy.

Therefore, AcAc may be a new treatment for RAIR-DTC. It has been reported that AcAc influences the occurrence and development of various types of tumors. Yang35 found that AcAc inhibited the growth of hepatocellular carcinoma by reducing the recruitment of tumor-associated macrophages (TAMs). Eugene J. Fine36 found that AcAc inhibited proliferation and ATP production by 7 aggressive human colon and breast cancer cell lines. The basic characteristics of cancer cells are indefinite proliferative capacity, evasion of apoptosis, activation of invasion, and metastasis. Herein, cell viability and cell colony assays demonstrated AcAc to reduce the proliferation of BCPAP and TPC-1 cells. Transwell and wound healing assays showed that AcAc inhibited the invasion and migration of BCPAP and TPC-1 cells. Furthermore, AcAc increased apoptosis. These results demonstrated AcAc to have thyroid carcinoma antitumor effects. This observation may open a new direction for the treatment of RAIR-DTC.

KD is a means by which to supplement AcAc and it is a high fat ratio, low carbohydrate ratio, protein and other nutrients suitable to diet structure.37,38 To apply our findings to future clinical applications, we developed a tumor xenotransplantation model to simulate the effect of AcAc in vivo through KD. The data not only demonstrated KD to increase AcAc in the serum, but also that KD significantly inhibited tumor growth, downregulated Ki67, and upregulated NIS and TSHR in tumor tissues. There was no significant effect on the body weight of the mice. Ki67 is a means by which to assess proliferative capacity of tumor cells.39 KD simulates the human hunger state, reduces glucose supply, and selectively cuts off tumor cell energy sources. KD can influence immune regulation, and produce anti-inflammatory, as well as antitumor effects.40-42 Therefore, our study provided the first direct evidence that KD inhibited thyroid carcinoma growth in vivo without obvious side effects. Furthermore, KD may be used as a supplemental nutritional therapy for RAIR-DTC.

In summary, ketone body metabolism played an important role in RAIR-DTC. AcAc improved iodine uptake capacity and had antitumor effects for thyroid carcinoma cells. As such, this study provided new approaches by which to treat RAIR-DTC.

Conclusion

In conclusion, this study demonstrated AcAc to improve iodine uptake and exert antitumor effects for thyroid carcinoma. Furthermore, the therapeutic effects of KD for thyroid carcinoma in vivo were demonstrated. As such, KD may be a new therapeutic strategy for the treatment of patients with RAIR-DTC.

Supplementary material

Supplementary material is available at The Oncologist online.

oyae075_suppl_Supplementary_Table_1

oyae075_suppl_Supplementary_Table_2

oyae075_suppl_Supplementary_Figure_1

Author contributions

Jiaqi Wang and Qianqian Xu: Conception/Design and manuscript writing. Ziyang Xuan and Yuting Mao: Provision of study material or patients. Xi Tang: Collection of data. Ke Yang: Data analysis and interpretation. Xin Zhu and Fahuan Song: Final approval of the manuscript.

Funding

This research was supported by National Natural Science Foundation of China (No. 82072950), China Postdoctoral Science Foundation (No. 2021M702908), Zhejiang Province Postdoctoral Research Excellence Funding Project (No. ZJ2021039), and Traditional Chinese Medicine Science and Technology Project of Zhejiang Provincial Health Commission (No. 2024037191).

Conflicts of interest

The authors indicated no financial relationships.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.
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References

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