Identification of lipid metabolism-related genes as prognostic indicators in papillary thyroid cancer

Lipid metabolism associated PLPP4 gene drives oncogenic and adipogenic potential in breast cancer cells

Lipid metabolic reprogramming plays a pivotal role in cancer cell evolution and causing subsequent cancer growth, metastasis and therapy resistance. Cancer associated adipocyte and/or cancer derived adipocyte-like cells often supply fuels and various factors to fulfill the cells bioenergetics to enhance oncogenic potential. This study intends to find out a set of dysregulated genes involved in lipid metabolism in breast cancer studies and uncovers the role of unexplored dysregulated gene in cancer potential. Cancer database analysis determines seven seed signature genes (PLPP2, PLPP4, CDS1, ASAH2, LCLAT1, LPCAT1 and LASS6/CERS6) concluded from relative expression and survival analysis. Furthermore, experimental analysis unveils the gene PLPP4 (Phospholipid Phosphatase 4) as oncogene confirmed by knockdown and overexpression studies in MDA-MB 231 and MCF-7 breast cancer cells. PLPP4 enzyme is involved in regulation of triacyl glycerol metabolism. Lipid accumulation along with other studies documented enhanced lipid droplets, TAG formation and glycerol release with concomitant increased expressions of various adipogenic markers (e.g., PPARγ, perilipin 1 and leptin) in breast cancer cells transfected with PLPP4 gene expressing plasmid whereas downregulation of PLPP4 gene diminished lipid accumulation and adipocyte marker gene expressions. Our findings also revealed that BMP2 induced adipogenic potential in breast cancer cells was mitigated in response to downregulation of PLPP4 gene expression. All these findings together, for first time, demonstrated that BMP2 drives PLPP4 to enhance both oncogenic and adipogenic potential in breast cancer cells. This article uncovers the perturbed lipid metabolism associated PLPP4 acts as oncogene presumably by modulating adipogenic activity in cancer cells.

Emerging Potential of Metabolomics in Thyroid Cancer-A Comprehensive Review

Thyroid cancer is a very common endocrine system malignancy. Nevertheless, a dearth of precise markers makes it challenging to apply precision medicine to thyroid cancer. The limitations of standard diagnosis techniques (fine-needle aspiration biopsy), such as indeterminate cases and inaccuracies in distinguishing between different types of cancers, lead to unnecessary surgeries and thus warrant the development of more discriminatory biomarkers to improve the accuracy of existing diagnostic and prognostic techniques. Moreover, individualized therapies for thyroid cancer are necessary to avoid overtreatment of indolent lesions and undertreatment of high-risk progressive disease. As thyroid cancer metabolic signatures are associated with disease aggressiveness and responsiveness to therapy, metabolomics has been recently used for diagnostic and prognostic biomarker discovery. This strategy has enabled the detection of several metabolites from tissue samples or biofluids to facilitate the classification of disease aggressiveness and to potentially assist in individualized therapies. In this review, we summarize the utilization and potential of metabolomics in thyroid cancer.

iPLA2β regulates the dual effects of arachidonic acid in thyroid cancer

BACKGROUND

Abnormal arachidonic acid metabolism in the tumor microenvironment is closely related to cancer progression; however, thyroid cancer was rarely researched.

METHODS

Through lipidomic analysis, we disclosed that dysregulated arachidonic acid metabolism plays dual effects on thyroid cancer. The promoting role of arachidonic acid in the progression of thyroid cancer cells was evaluated utilizing cell viability (CCK-8 assay) and transwell invasion assays, confirmed by corresponding inhibitors. Lipid peroxidation and the use of various cell death inhibitors confirmed that arachidonic acid confers vulnerability to ferroptosis in thyroid cancer. The roles of arachidonic acid and ferroptosis inducer in thyroid cancer were assessed in a xenograft mouse model.

RESULTS

On one hand, arachidonic acid promotes the progression of thyroid cancer through the cyclooxygenase/prostaglandin pathway; on another hand, arachidonic acid confers vulnerability to ferroptosis through lipoxygenases. Moreover, iPLA2β drives converse roles of arachidonic acid between cancer-progression and ferroptosis vulnerability through releasing free arachidonic acid from the cell membrane. Finally, we confirmed high arachidonic acid diet promotes the development of thyroid cancer in vivo, whereas ferroptosis inducer sulfasalazine dramatically reduced tumor growth of mice with feeding arachidonic acid.

CONCLUSIONS

Our research demonstrated the roles of iPLA2β in conversing dual effects of arachidonic acid in thyroid cancer and provides ferroptosis inducer as a potential therapeutic strategy.

A novel model based on lipid metabolism-related genes associated with immune microenvironment predicts metastasis of breast cancer

BACKGROUND

Breast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC.

METHODS

Clinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis.

RESULTS

This study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC.

CONCLUSION

We developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks

Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.

Integration of scRNA and bulk RNA-sequence to construct the 5-gene molecular prognostic model based on the heterogeneity of thyroid carcinoma endothelial cell

Thyroid cancer (TC) is a kind of cancer with high heterogeneity, which leads to significant difference in prognosis. The prognostic molecular processes are not well understood. Cancer cells and tumor microenvironment (TME) cells jointly determine the heterogeneity. However, quite a little attention was paid to cells in the TME in the past years. In this study, we not only reveal that endothelial cells (ECs) are strongly associated with the progress of papillary thyroid cancer (PTC) using single-cell RNA-seq (scRNA-seq) data downloaded from Gene Expression Omnibus (GEO) and WGCNA, but also screen 5 crucial genes of ECs: CLDN5, ABCG2, NOTCH4, PLAT, and TMEM47. Furthermore, the 5-gene molecular prognostic model is constructed, which can predict how well a patient will do on PD-L1 blockade immunotherapy for TC and evaluate prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrates that PLAT is decreased in TC and the increase of PLAT can restrain the migratory capacity of TC cells. Meanwhile, in TC cells, PLAT suppresses VEGFa/VEGFR2-mediated human umbilical vascular endothelial cell (HUVEC) proliferation and tube formation. Totally, we construct the 5-gene molecular prognostic model from the perspective of EC and provide a new idea for immunotherapy of TC.

The expression of two immunosuppressive SIGLEC family molecules in papillary thyroid cancer and their effect on prognosis

BACKGROUND

The thyroid cancer (THCA) subtype that occurs more frequently is papillary thyroid cancer (PTC). Despite a favorable postoperative outcome, traditional antitumor therapy does not offer ideal results for patients with metastasis, relapse, and radioiodine resistance. Recent studies demonstrated the remarkable effects of immune checkpoint inhibitors on solid tumors, of which the immunoglobulin superfamily member SIGLEC10 and SIGLEC15 act as novel immunotherapy targets for tumors. Nevertheless, their role in PTC prognosis is still indefinite.

METHODS

Immunohistochemistry was utilized to examine the expression of SIGLEC10 and SIGLEC15 in 244 PTC tissue specimens. Then the expression correlation between the two was analyzed in normal tissues (NT), tumor cells (TC), and tumor stroma (TS), respectively. Subsequently, the retrospective data on patients with PTC were collected to examine whether the two immunosuppressive SIGLEC family members could affect their prognosis.

RESULTS

We confirmed that TC expressed higher levels of SIGLEC10 than NT. However, SIGLEC10 was down-regulated in TS and predicted poor outcomes. Meanwhile, down-regulation of SIGLEC15 expression was observed in both TC and TS, indicating a favorable prognosis. PTC patients with both SIGLEC10-SIGLEC15+ expression in TC and TS had a significantly higher recurrence risk. The expression of SIGLEC10 in TS and SIGLEC15 in TC or TS was an independent predictor of PFS, and a positive correlation was shown between SIGLEC10 and SIGLEC15 expression in TS.

CONCLUSIONS

Therefore, our results indicate that SIGLEC10 and SIGLEC15 may be applied as significant prognostic markers for PTC and attractive targets for THCA immunotherapy.

A clinically useful and biologically informative genomic classifier for papillary thyroid cancer

Clinical management of papillary thyroid cancer depends on estimations of prognosis. Standard care, which relies on prognostication based on clinicopathologic features, is inaccurate. We applied a machine learning algorithm (HighLifeR) to 502 cases annotated by The Cancer Genome Atlas Project to derive an accurate molecular prognostic classifier. Unsupervised analysis of the 82 genes that were most closely associated with recurrence after surgery enabled the identification of three unique molecular subtypes. One subtype had a high recurrence rate, an immunosuppressed microenvironment, and enrichment of the EZH2-HOTAIR pathway. Two other unique molecular subtypes with a lower rate of recurrence were identified, including one subtype with a paucity of BRAFV600E mutations and a high rate of RAS mutations. The genomic risk classifier, in addition to tumor size and lymph node status, enabled effective prognostication that outperformed the American Thyroid Association clinical risk stratification. The genomic classifier we derived can potentially be applied preoperatively to direct clinical decision-making. Distinct biological features of molecular subtypes also have implications regarding sensitivity to radioactive iodine, EZH2 inhibitors, and immune checkpoint inhibitors.

Targeting metabolism by B-raf inhibitors and diclofenac restrains the viability of BRAF-mutated thyroid carcinomas with Hif-1α-mediated glycolytic phenotype

BACKGROUND

B-raf inhibitors (BRAFi) are effective for BRAF-mutated papillary (PTC) and anaplastic (ATC) thyroid carcinomas, although acquired resistance impairs tumour cells' sensitivity and/or limits drug efficacy. Targeting metabolic vulnerabilities is emerging as powerful approach in cancer.

METHODS

In silico analyses identified metabolic gene signatures and Hif-1α as glycolysis regulator in PTC. BRAF-mutated PTC, ATC and control thyroid cell lines were exposed to HIF1A siRNAs or chemical/drug treatments (CoCl2, EGF, HGF, BRAFi, MEKi and diclofenac). Genes/proteins expression, glucose uptake, lactate quantification and viability assays were used to investigate the metabolic vulnerability of BRAF-mutated cells.

RESULTS

A specific metabolic gene signature was identified as a hallmark of BRAF-mutated tumours, which display a glycolytic phenotype, characterised by enhanced glucose uptake, lactate efflux and increased expression of Hif-1α-modulated glycolytic genes. Indeed, Hif-1α stabilisation counteracts the inhibitory effects of BRAFi on these genes and on cell viability. Interestingly, targeting metabolic routes with BRAFi and diclofenac combination we could restrain the glycolytic phenotype and synergistically reduce tumour cells' viability.

CONCLUSION

The identification of a metabolic vulnerability of BRAF-mutated carcinomas and the capacity BRAFi and diclofenac combination to target metabolism open new therapeutic perspectives in maximising drug efficacy and reducing the onset of secondary resistance and drug-related toxicity.

Comprehensive analysis of the prognosis and immune infiltration of TMC family members in renal clear cell carcinoma

Renal cancer is a common malignancy of the urinary system, and renal clear cell carcinoma (RCCC) is the most common pathological type. Transmembrane channel-like (TMC) protein is an evolutionarily conserved gene family containing 8 members, however there is still a lack of comprehensive analysis about TMC family members in RCCC. In this study, we analyzed the expression of TMC family members in RCCC from TCGA and investigated the prognosis values and immune infiltration of TMC family members in RCCC. We found that TMC2, TMC3, TMC5, TMC7 and TMC8 were significantly related with overall survival (OS) of RCCC patients. TMC3, TMC6, and TMC8 was positively correlated with the degree of immune infiltration in RCCC. TMC2, TMC6, TMC7, and TMC8 were positively correlated with immune checkpoint genes, whereas TMC4 was negative. According to KEGG and GO analysis, almost all TMCs except TMC4 were involved in the immune response. Thus, we may regard the TMC family members as novel biomarkers to predict potential prognosis and immunotherapeutic response in RCCC patients.

Identification of iron metabolism-related genes as prognostic indicators for papillary thyroid carcinoma: a retrospective study

Background

The thyroid cancer subtype that occurs more frequently is papillary thyroid carcinoma (PTC). Despite a good surgical outcome, treatment with traditional antitumor therapy does not offer ideal results for patients with radioiodine resistance, recurrence, and metastasis. The evidence for the connection between iron metabolism imbalance and cancer development and oncogenesis is growing. Nevertheless, the iron metabolism impact on PTC prognosis is still indefinite.

Methods

Herein, we acquired the medical data and gene expression of individuals with PTC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Typically, three predictive iron metabolism-related genes (IMRGs) were examined and employed to build a risk score (RS) model via the least absolute shrinkage and selection operator (LASSO) regression, univariate Cox, and differential gene expression analyses. Then we analyzed somatic mutation and immune cell infiltration among RS groups. We also validated the prognostic value of two IMRGs (SFXN3 and TFR2) by verifying their biological function through in vitro experiments.

Results

Based on RS, all patients with PTC were stratified into low- and high-risk groups, where Kaplan-Meier analysis indicated that disease-free survival (DFS) in the high-risk group was much lower than in the low-risk group (P < 0.0001). According to ROC analysis, the RS model successfully predicted the 1-, 3-, and 5-year DFS of individuals with PTC. Additionally, in the TCGA cohort, a nomogram model with RS was developed and exhibited a strong capability to anticipate PTC patients' DFS. In the high-risk group, the enriched pathological processes and signaling mechanisms were detected utilizing the gene set enrichment analysis (GSEA). Moreover, the high-risk group had a significantly higher level of BRAF mutation frequency, tumor mutation burden, and immune cell infiltration than the low-risk group. In vitro experiments found that silencing SFXN3 or TFR2 significantly reduced cell viability.

Conclusion

Collectively, our predictive model depended on IMRGs in PTC, which could be potentially utilized to predict the PTC patients' prognosis, schedule follow-up plans, and provide potential targets against PTC.

Untargeted lipidomic analysis and network pharmacology for parthenolide treated papillary thyroid carcinoma cells

BACKGROUND

With fast rising incidence, papillary thyroid carcinoma (PTC) is the most common head and neck cancer. Parthenolide, isolated from traditional Chinese medicine, inhibits various cancer cells, including PTC cells. The aim was to investigate the lipid profile and lipid changes of PTC cells when treated with parthenolide.

METHODS

Comprehensive lipidomic analysis of parthenolide treated PTC cells was conducted using a UHPLC/Q-TOF-MS platform, and the changed lipid profile and specific altered lipid species were explored. Network pharmacology and molecular docking were performed to show the associations among parthenolide, changed lipid species, and potential target genes.

RESULTS

With high stability and reproducibility, a total of 34 lipid classes and 1736 lipid species were identified. Lipid class analysis indicated that parthenolide treated PTC cells contained higher levels of fatty acid (FA), cholesterol ester (ChE), simple glc series 3 (CerG3) and lysophosphatidylglycerol (LPG), lower levels of zymosterol (ZyE) and Monogalactosyldiacylglycerol (MGDG) than controlled ones, but with no significant differences. Several specific lipid species were changed significantly in PTC cells treated by parthenolide, including the increasing of phosphatidylcholine (PC) (12:0e/16:0), PC (18:0/20:4), CerG3 (d18:1/24:1), lysophosphatidylethanolamine (LPE) (18:0), phosphatidylinositol (PI) (19:0/20:4), lysophosphatidylcholine (LPC) (28:0), ChE (22:6), and the decreasing of phosphatidylethanolamine (PE) (16:1/17:0), PC (34:1) and PC (16:0p/18:0). Four key targets (PLA2G4A, LCAT, LRAT, and PLA2G2A) were discovered when combining network pharmacology and lipidomics. Among them, PLA2G2A and PLA2G4A were able to bind with parthenolide confirmed by molecular docking.

CONCLUSIONS

The changed lipid profile and several significantly altered lipid species of parthenolide treated PTC cells were observed. These altered lipid species, such as PC (34:1), and PC (16:0p/18:0), may be involved in the antitumor mechanisms of parthenolide. PLA2G2A and PLA2G4A may play key roles when parthenolide treated PTC cells.

Prognostic subtypes of thyroid cancer was constructed based on single cell and bulk-RNA sequencing data and verified its authenticity

There has been an increase in the mortality rate of thyroid cancer (THCA), which is the most common endocrine malignancy. We identified six distinct cell types in the THAC microenvironment by analyzing single-cell RNA sequencing (Sc-RNAseq) data from 23 THCA tumor samples, indicating high intratumoral heterogeneity. Through re-dimensional clustering of immune subset cells, myeloid cells, cancer-associated fibroblasts, and thyroid cell subsets, we deeply reveal differences in the tumor microenvironment of thyroid cancer. Through an in-depth analysis of thyroid cell subsets, we identified the process of thyroid cell deterioration (normal, intermediate, malignant cells). Through cell-to-cell communication analysis, we found a strong link between thyroid cells and fibroblasts and B cells in the MIF signaling pathway. In addition, we found a strong correlation between thyroid cells and B cells, TampNK cells, and bone marrow cells. Finally, we developed a prognostic model based on differentially expressed genes in thyroid cells from single-cell analysis. Both in the training set and the testing set, it can effectively predict the survival of thyroid patients. In addition, we identified significant differences in the composition of immune cell subsets between high-risk and low-risk patients, which may be responsible for their different prognosis. Through in vitro experiments, we identify that knockdown of NPC2 can significantly promote thyroid cancer cell apoptosis, and NPC2 may be a potential therapeutic target for thyroid cancer. In this study, we developed a well-performing prognostic model based on Sc-RNAseq data, revealing the cellular microenvironment and tumor heterogeneity of thyroid cancer. This will help to provide more accurate personalized treatment for patients in clinical diagnosis.

The specific phagocytosis regulators could predict recurrence and therapeutic effect in thyroid cancer: A study based on bioinformatics analysis

BACKGROUND

Thyroid cancer (TC) is one of the growing cancers and is prone to recurrence. Meanwhile, in immunotherapy, antibody-dependent cellular phagocytosis (ADCP) phagocytosis related regulators (PRs) play an important role. This study aims to investigate the prognostic value of specific PRs in TC.

METHODS

The purpose of this study was to identify specific PRs in TC patients by retrieving RNA-seq and Clustered Regularly Interspaced Short Palindromic Repeats-cas9 data and an algorithm based on LASSO was used to construct the PRs-signature. Subsequently, prognosis value of PRs-signature for recurrence-free survival (RFS) was explored through various statistical analysis, including Cox regression analysis, Kaplan-Meier analysis, and receiver operating characteristic curve. Additionally, an analysis of immune cell content by risk group was conducted using CIBERSORT, single sample gene set enrichment analysis and MCP-counter algorithms, with a particular focus on the correlation between macrophages and specific PRs.

RESULTS

We identified 36 specific PRs, and a PRs-signature was constructed using 5-prognostic PRs (CAPN6, MUC21, PRDM1, SEL1L3, and CPQ). Receiver operating characteristic analysis showed that predictive power of PRs-signature was decent, and the PRs risk score as an independent prognostic factor was found to be correlated with RFS showed by multivariate cox regression analysis. Meanwhile, a lower RFS was observed in the high-risk group than in the low-risk group. The results of the 3 algorithms suggested that our PRs-signature may have certain significance for macrophage content and ADCP. Interestingly, the low-risk group had higher levels of mRNA expression than the high-risk group at PDCD1, CTLA4, and pro-inflammatory factors from macrophage.

CONCLUSION

For the purpose of prognostic management, this study developed a prediction model. And the cross-talk between certain PRs and TC patients was revealed in this study. Besides, the PRs-signature can predict the immunotherapy response, macrophage content, and ADCP status. TC patients will benefit from these developments by gaining insight into novel therapeutic strategies.

Carbohydrate, Lipid, and Apolipoprotein Biomarkers in Blood and Risk of Thyroid Cancer: Findings from the AMORIS Cohort

Background: Previous studies have examined the link between blood metabolic biomarkers and risk of thyroid cancer, with inconclusive results. We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals undergoing health examinations during 1985−1996 with a follow-up of >30 years. Methods: Newly diagnosed cases of thyroid cancer were identified from the Swedish Cancer Register. We assessed the associations of nine blood biomarkers of carbohydrate, lipid, and apolipoprotein metabolism measured at the time of health examinations with the subsequent risk of thyroid cancer and demonstrated the temporal trend of these biomarkers during the 30 years before diagnosis of thyroid cancer. Results: After multivariable adjustment, there was a lower risk of thyroid cancer, per standard deviation increase in total cholesterol (TC; HR 0.91; 95%CI 0.82−0.99) and HDL-C (HR 0.86; 95%CI 0.75−0.99). During the 20 to 30 years before diagnosis, patients with thyroid cancer, as a group, demonstrated constantly lower levels of TC and HDL-C, compared to controls. Further, patients with thyroid cancer demonstrated declining levels of these biomarkers during the ten years before diagnosis, whereas controls demonstrated stable or increasing levels. Conclusions: Taken together, we found blood levels of TC and HDL-C to be associated with the risk of thyroid cancer and that there was a declining level of metabolic biomarkers during the 10 years before diagnosis of thyroid cancer.

A metabolism-related gene signature for predicting the prognosis in thyroid carcinoma

Metabolic reprogramming is one of the cancer hallmarks, important for the survival of malignant cells. We investigated the prognostic value of genes associated with metabolism in thyroid carcinoma (THCA). A prognostic risk model of metabolism-related genes (MRGs) was built and tested based on datasets in The Cancer Genome Atlas (TCGA), with univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. We used Kaplan-Meier (KM) curves, time-dependent receiver operating characteristic curves (ROC), a nomogram, concordance index (C-index) and restricted mean survival (RMS) to assess the performance of the risk model, indicating the splendid predictive performance. We established a three-gene risk model related to metabolism, consisting of PAPSS2, ITPKA, and CYP1A1. The correlation analysis in patients with different risk statuses involved immune infiltration, mutation and therapeutic reaction. We also performed pan-cancer analyses of model genes to predict the mutational value in various cancers. Our metabolism-related risk model had a powerful predictive capability in the prognosis of THCA. This research will provide the fundamental data for further development of prognostic markers and individualized therapy in THCA.

Acetyl-CoA regulates lipid metabolism and histone acetylation modification in cancer

Acetyl-CoA, as an important molecule, not only participates in multiple intracellular metabolic reactions, but also affects the post-translational modification of proteins, playing a key role in the metabolic activity and epigenetic inheritance of cells. Cancer cells require extensive lipid metabolism to fuel for their growth, while also require histone acetylation modifications to increase the expression of cancer-promoting genes. As a raw material for de novo lipid synthesis and histone acetylation, acetyl-CoA has a major impact on lipid metabolism and histone acetylation in cancer. More importantly, in cancer, acetyl-CoA connects lipid metabolism with histone acetylation, forming a more complex regulatory mechanism that influences cancer growth, proliferation, metastasis.

Expression of transcription, growth factors, steroid hormone receptors, LC3B in papillary thyroid cancer tissue, association with prognosis and risk of recurrence

Introduction. Biological characteristics of the tumor play a major role in it’s development and progression. Currently, using the molecular markers aimed at resolving the problems in clinical oncology is becoming more important, including thyroid carcinomas. Heterogeneous contradictory data had been accumulated to date showing the ability of tumors genetic and biological parameters to predict the diseases outcome.Aim. To investigate prognostic value of transcription, growth factors, components of AKT / mTOR signaling pathway and autophagy protein LC3B in patients with papillary thyroid cancer in relation to recurrences and overall survival.Materials and methods. The study included 65 patients with T1–4N0–1M0 papillary thyroid cancer. According to the criteria of the American Thyroid Association (ATA) (2015), patients were divided into groups of patients with high, low and intermediate risk. 30 patients were classified as low risk, 23 as intermediate risk, and 12 as high risk. The BRAFV600 mutation was identified in 18 samples. The expression of transcription factors (p65 and p50 subunits of nuclear factor kappa B (NF-κB p65, NF-κB p50), hypoxia-inducible factor 1 (HIF-1), hypoxia-inducible factor 2 (HIF-2), growth factors (vascular endothelial growth factor (VEGF), receptor VEGF (VEGF-2), carbonic anhydrases of type 9 (CAIX)), AKT, c-RAF, GSK- 3β, p70S6, mammalian target of rapamycin (m-TOR), PDK, PTEN, 4E-BP1 in the tumor was assessed by real-time polymerase chain reaction (PCR). The BRAFV600 mutation was investigated using real-time allele-specific PCR. The content of the LC3B protein was examined using the Western Blot method.Results. As a result of the study, there is an increase in c-RAF expression with an increase in risk from low to high, which was accompanied by a decrease in 4E-BP1 expression. c-RAF mRNA levels were increased 3.0- and 2.8‑fold in the intermediate and high-risk groups, respectively, compared to low risk patients. There is a change in the expression of Brn-3α depending on the relapse risk. The maximum mRNA levels were found in patients with intermediate risk, where the figure was 4.3 and 6.2 times higher than in patients with low and high risk, respectively. An increase in LC3B expression by 56.0 and 28.0 times was shown in the tumor tissue of patients with intermediate risk compared with patients with low and high risk. This fact corresponds with an increasing content of the protein itself, which was higher in patients with intermediate risk. Patients with a negative BRAF gene status had an intermediate and high risk of tumor recurrence. The prognostic significance of the estrogen receptor β (ER-β) and NF-κB p50 expression level had been revealed in relation with relapse-free and overall survival of patients with papillary thyroid cancer.Conclusion. As a result of the study, additional molecular markers were found in order to for predict the tumors recurrence risk. The study showed the significance of ERβ and NF-κB p50 expression levels for predicting disease outcomes.

PDZK1 Interacting Protein 1 Promotes the Progression of Papillary Thyroid Cancer

BACKGROUND

The incidence of papillary thyroid cancer (PTC) has increased rapidly in recent decades, and tumor progression events are common in PTC. The purpose of our study is to identify the differentially expressed genes (DEGs) correlated with PTC progression and investigate the function of PDZK1IP1 (PDZK1 interacting protein 1) in PTC.

METHODS

We first analyzed DEGs associated with PTC progression between paired PTC and normal thyroid tissues in 3 Gene Expression Omnibus data sets (GSE29265, GSE33630, and GSE60542) and The Cancer Genome Atlas (TCGA) database. Data from the TCGA database and our institution were utilized to explore the relationship between PDZK1IP1 expression and clinicopathological characteristics of PTC. The CCK8 cell proliferation assay, clone formation assay, flow cytometry assay, and the xenograft model were used to investigate the function of PDZK1IP1 in PTC.

RESULTS

Thirty-nine DEGs associated with PTC progression were identified, in which only PDZK1IP1 was upregulated in PTC tissue at both messenger RNA and protein levels. In addition, we found that high expression of PDZK1IP1 in the TCGA database was associated with poor progression-free survival, extrathyroidal extension, high stage, tall cell variant, and BRAFV600E mutation of the PTC (P < 0.001). In our collected samples, high expression of PDZK1IP1 was only related to lymph node metastasis (P < 0.05). Overexpression of PDZK1IP1 significantly promoted proliferation and inhibited apoptosis of PTC cells. Knockdown of PDZK1IP1 significantly inhibited proliferation, promoted apoptosis, and prevented xenograft formation of PTC cells.

CONCLUSION

PDZK1IP1 is an oncogene for tumorigenesis and development of PTC and might be a potential therapeutic target.

Function and Clinical Significance of Circular RNAs in Thyroid Cancer

Thyroid cancer (TC) is the leading cause and mortality of endocrine malignancies worldwide. Tumourigenesis involves multiple molecules including circular RNAs (circRNAs). circRNAs with covalently closed single-stranded structures have been identified as a type of regulatory RNA because of their high stability, abundance, and tissue/developmental stage-specific expression. Accumulating evidence has demonstrated that various circRNAs are aberrantly expressed in thyroid tissues, cells, exosomes, and body fluids in patients with TC. CircRNAs have been identified as either oncogenic or tumour suppressor roles in regulating tumourigenesis, tumour metabolism, metastasis, ferroptosis, and chemoradiation resistance in TC. Importantly, circRNAs exert pivotal effects on TC through various mechanisms, including acting as miRNA sponges or decoys, interacting with RNA-binding proteins, and translating functional peptides. Recent studies have suggested that many different circRNAs are associated with certain clinicopathological features, implying that the altered expression of circRNAs may be characteristic of TC. The purpose of this review is to provide an overview of recent advances on the dysregulation, functions, molecular mechanisms and potential clinical applications of circRNAs in TC. This review also aimes to improve our understanding of the functions of circRNAs in the initiation and progression of cancer, and to discuss the future perspectives on strategies targeting circRNAs in TC.