Interaction of MRPL9 and GGCT Promotes Cell Proliferation and Migration by Activating the MAPK/ERK Pathway in Papillary Thyroid Cancer

Mechanisms underlying the promotion of papillary thyroid carcinoma occurrence and progression by Hashimoto's thyroiditis

Hashimoto's thyroiditis (HT) and papillary thyroid carcinoma (PTC) co-occurrence raises significant questions regarding the immune microenvironment and molecular mechanisms in thyroid tumor development. This review synthesizes recent literature to explore the immune microenvironment and molecular characteristics of PTC patients with HT, and to analyze how these characteristics influence disease onset, progression, and treatment. We focused on the immunological and molecular biological mechanisms underlying the interaction between HT and PTC, particularly the recruitment and activation of immune cells and alterations in key signaling pathways. Studies indicate that PTC with HT exhibits distinctive immune microenvironmental features, such as the role of regulatory T cells (Tregs), activation of the IFN-γ-mediated CXCR3A-CXCL10 signaling axis, and NF-κB pathway activation. Additionally, thyroid-stimulating hormone (TSH) stimulation, RET/PTC gene rearrangements, and changes in STAT6 and DMBT1 gene expression levels also play significant roles in PTC development. Notably, while HT may increase the risk of PTC, patients with concurrent HT tend to have better prognoses. Future research should further elucidate the complex interplay between these two diseases to prevent the transformation of HT into PTC and offer more personalized treatment plans for PTC patients, including considerations for preoperative thyroidectomy and lymph node dissection strategies, as well as postoperative TSH suppression therapy risk assessment. This review underscores the importance of a deeper understanding of HT and PTC interactions and offers new perspectives for future research directions and therapeutic strategies.

GGCT participates in the malignant process of hepatocellular cancer cells by regulating the PTEN/PI3K/AKT pathway through binding to EZH2

BACKGROUND

γ-Glutamylcyclotransferase (GGCT) is implicated in multiple types of cancer diseases. Nevertheless, the roles and relevant mechanisms of GGCT in hepatocellular carcinoma (HCC) remain vague.

METHODS

GGCT expression in HCC and its effect on patient survival curve in HCC were evaluated utilizing the UALCAN database, along with western blot. CCK-8, EdU, and wound healing, together with transwell and western blot assays were adopted to assess the capabilities of cells to proliferate, migrate, invade, and epithelial-mesenchymal transition (EMT). Cell apoptosis was appraised utilizing TUNEL as well as western blot. Glycolysis was measured by western blot and kits. Enhancer of zeste homolog 2 (EZH2) expression in HCC cells was detected by western blot. Co-IP verified the combination of GGCT and EZH2. Moreover, PI3K/AKT pathway-related proteins were assessed employing western blot.

RESULTS

GGCT expression was conspicuously upregulated in HCC samples and HCC cells. GGCT silencing repressed HuH-7 cell proliferative, invasive, and migratory capabilities as well as EMT, whereas facilitated cell apoptosis. In addition, GGCT silencing inhibited PTEN/PI3K/AKT pathway-mediated glycolysis. EZH2 was highly expressed in HCC cells and the interaction of GGCT and EZH2 was verified. Overexpression of EZH2 reversed the effects of GGCT silencing on HuH-7 cell proliferation, migration, invasion, cell apoptosis, and glycolysis. Moreover, the PTEN inhibitor SF1670 reversed the effects of GGCT silencing and EZH2 overexpression on the glycolysis and malignant process in HuH-7 cells.

CONCLUSION

In conclusion, GGCT silencing restrained the proliferation and metastasis, and promoted apoptotic levels of HCC cells via regulating PTEN/PI3K/AKT pathway-mediated glycolysis, which might offer a prospective candidate in treating HCC.

MRPL24 drives breast cancer metastasis and stemness by targeting c-MYC, BRD4, and STAT3

The study aims to investigate the clinicopathological significance of MRPL24 in human cancers, with a particular focus on breast cancer (BC). Comprehensive bioinformatics analyses were conducted using data from The Cancer Genome Atlas (TCGA) and various advanced database, including cBioPortal, UALCAN, TIMER, Prognoscan, TISIDB, KM Plotter, and The Human Protein Atlas, to provide a detailed evaluation of MRPL55's role in cancer. The findings were further validated through experimental studies. Pan-cancer analysis of TCGA/ICGC data revealed significant amplification of MRPL24 across multiple cancer types, with the highest amplification rate of 60% observed in metastatic breast cancer. MRPL24 was found to be overexpressed in primary breast tumors, metastatic, and various molecular subtypes of breast cancer. High MRPL24 expression was associated with poor prognosis and lower survival rates in breast cancer patients. RT-PCR and western blot confirmed MRPL24 depletion in breast cancer cells. Knockdown of MRPL24 was shown to suppress proliferation, and clonogenic potential in breast cancer cells and inhibit cell migration. Additionally, MRPL24 depletion sensitized breast cancer cells to PD0325901 and 5-FU treatment. Mechanistic studies revealed that MRPL24 knock-down downregulates mRNA levels of oncogenic genes, including c-MYC, BRD4, WNT3, and STAT3. Positive correlations were observed between MRPL24 and key genes involved in ferroptosis regulation, such as ERBB2, ERBB3, GRB2, PIK3CA, AKT1, MAPK3, and MAPK1. Finally, through virtual screening and molecular dynamics simulations, we have identified three FDA-approved drugs with strong binding affinities and interactions with MRPL24. These findings underscore MRPL24's oncogenic role in breast cancer and suggest potential therapeutic strategies targeting this protein.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04196-z.

Mitochondrial Ribosomal Proteins and Cancer

Mitochondria play key roles in maintaining cell life and cell function, and their dysfunction can lead to cell damage. Mitochondrial ribosomal proteins (MRPs) are encoded by nuclear genes and are assembled within the mitochondria. MRPs are pivotal components of the mitochondrial ribosomes, which are responsible for translating 13 mitochondrial DNA-encoded proteins essential for the mitochondrial respiratory chain. Recent studies have underscored the importance of MRPs in cancer biology, revealing their altered expression patterns in various types of cancer and their potential as both prognostic biomarkers and therapeutic targets. Herein, we review the current knowledge regarding the multiple functions of MRPs in maintaining the structure of the mitochondrial ribosome and apoptosis, their implications for cancer susceptibility and progression, and the innovative strategies being developed to target MRPs and mitoribosome biogenesis in cancer therapy. This comprehensive overview aims to provide insights into the role of MRPs in cancer biology and highlight promising strategies for future precision oncology.

Gamma-glutamyl cyclotransferase, a molecule identified from the invasive front of follicular thyroid carcinoma, is useful for differential diagnosis of follicular thyroid tumors

We aimed to establish a useful molecular marker for differentiating between follicular thyroid carcinoma (FTC) and follicular adenoma (FA). RNA was extracted from the invasive front and paired tumor center tissues from three FTC cases using laser microdissection for cDNA microarray analysis, revealing high expression of gamma-glutamyl cyclotransferase (GGCT) in the invasive front. Subsequently, immunohistochemical (IHC) staining of GGCT was performed with formalin-fixed paraffin-embedded (FFPE) sections of FTC (n = 32), FA (n = 64), and follicular tumor of uncertain malignant potential (FT-UMP, n = 5). The GGCT expression score (range: 0-300) was calculated by multiplying the intensity score (0-3) and percentage of positive cells. The Ki-67 labeling index was also assessed in 20 FTC and 25 FA cases from the same cohort. The GGCT expression score was higher in FTC than in FA (118.5 ± 51.4 vs. 57.3 ± 34.7, P < 0.0001). With the GGCT expression score, using a cutoff value of 101.1, the differentiation between FTC and FA was possible with a sensitivity of 68.8 % and specificity of 87.5 % (AUC = 0.832). With the Ki-67 labeling index, applying a cutoff value of 4.0 %, the distinction between FTC and FA resulted in a sensitivity of 50.0 % and specificity of 80.0 % (AUC = 0.677). The GGCT expression score was positively related to the Ki-67 labeling index in the FTC cases. (Spearman's ρ = 0.5293, P = 0.0164). Therefore, GGCT is a potential marker for differentiating FTC from FA. The GGCT expression of FTC may be indicative of its invasive and proliferative activity.

The GGCT and REST positive feedback loop promotes tumor growth in Glioma

BACKGROUND

γ-Glutamylcyclotransferase (GGCT), an enzyme crucial in glutathione metabolism, has emerged as a participant in tumorigenesis. The present study is designed to elucidate the biological role and molecular mechanisms underlying GGCT in glioma.

METHODS

Gene Expression Profiling Interactive Analysis (GEPIA), Chinese Glioma Genome Atlas (CGGA), and PrognoScan online databases were utilized to examine the expressions and clinical prognosis of GGCT and REST in glioma. Cell Counting Kit-8 (CCK-8), Transwell, Wound healing, and Flow cytometric assays, and RNA-sequencing analysis were employed to uncover the molecular role of GGCT and REST. Prediction of Differentially expressed microRNA (DE-miRNAs) and miRNAs targeting GGCT 3' Untranslated Region (UTR) was performed using miRanda online datasets. Finally, Real time-quantitative Polymerase Chain Reaction (RT-qPCR), western blot and dual luciferase reporter gene activity analysis were employed to confirm a positive feedback loop involving GGCT/REST/miR-34a-5p in glioma cells.

RESULTS

High expression of GGCT was correlated with poor prognosis in glioma. GGCT silencing demonstrated inhibitory effects on the proliferation, migration, and induction of apoptosis in T98G and U251 cells. Mechanistically, GGCT downregulated REST expression and modulated cancer-associated pathways in glioma cells. High expression of REST was associated with poor prognosis in glioma. In vitro and in vivo experiments showed that REST overexpression restored the repression of proliferation, invasion, migration, and xenograft tumor formation induced by GGCT knockdown. Furthermore, the study uncovered that REST inhibited miR-34a-5p mRNA expression, and miR-34a-5p suppressed GGCT expression by targeting its 3'UTR, forming a positive regulatory loop in glioma. Notably, the inhibitor of miR-34a-5p restored the role of REST silencing in decreasing GGCT expression in glioma cells.

CONCLUSIONS

GGCT/REST/miR-34a-5p axis holds promising potential as a therapeutic target, offering a potential breakthrough in the treatment of glioma.

Machine learning-based cell death marker for predicting prognosis and identifying tumor immune microenvironment in prostate cancer

Background

Prostate cancer (PCa) incidence and mortality rates are rising, necessitating precise prognostic tools to guide personalized treatment. Dysregulation of programmed cell death pathways in tumor suppression and cancer development has garnered increasing attention, providing a new research direction for identifying biomarkers and potential therapeutic targets.

Methods

Integrating multiple database resources, we constructed and optimized a prognostic signature based on the expression of programmed cell death-related genes (PCDRG) using ten machine learning algorithms. Model performance and prognostic effects were further evaluated. We analyzed the relationships between signature and clinicopathological features, somatic mutations, drug sensitivity, and the tumor immune microenvironment, and constructed a nomogram. The expression level of PCDRGs were evaluated and compared.

Results

Of 1560 PCDRGs, 149 were differentially expressed in PCa, with 34 associated with biochemical recurrence. The PCDRG-derived index (PCDI), constructed using the random forest algorithm, exhibited optimal prognostic performance, successfully stratifying PCa patients into two groups with significant prognostic differences. Patients with high PCDI scores exhibited poorer survival and lower immunotherapy benefit. PCDI was closely associated with the infiltration of specific immune cells, particularly positive correlations with macrophages and T helper cells, and negative correlations with neutrophils, suggesting that PCDI may influence the tumor immune microenvironment, thereby affecting patient prognosis and treatment response. PCDI was associated with age, pathological stage, somatic mutations, and drug sensitivity. The PCDI-based nomogram demonstrated excellent performance in predicting biochemical recurrence in PCa patients. Finally, the differential expression of these PCDRGs was verified based on cell lines and PCa patient expression profile data.

Conclusion

This study developed an effective prognostic indicator for prostate cancer, PCDI, using machine learning approaches. PCDI reflects the link between aberrant programmed cell death pathways and disease progression and treatment response.

Identified γ-glutamyl cyclotransferase (GGCT) as a novel regulator in the progression and immunotherapy of pancreatic ductal adenocarcinoma through multi-omics analysis and experiments

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is renowned for its formidable and lethal nature, earning it a notorious reputation among malignant tumors. Due to its challenging early diagnosis, high malignancy, and resistance to chemotherapy drugs, the treatment of pancreatic cancer has long been exceedingly difficult in the realm of oncology. γ-Glutamyl cyclotransferase (GGCT), a vital enzyme in glutathione metabolism, has been implicated in the proliferation and progression of several tumor types, while the biological function of GGCT in pancreatic ductal adenocarcinoma remains unknown.

METHODS

The expression profile of GGCT was validated through western blotting, immunohistochemistry, and RT-qPCR in both pancreatic cancer tissue samples and cell lines. Functional enrichment analyses including GSVA, ssGSEA, GO, and KEGG were conducted to explore the biological role of GGCT. Additionally, CCK8, Edu, colony formation, migration, and invasion assays were employed to evaluate the impact of GGCT on the proliferation and migration abilities of pancreatic cancer cells. Furthermore, the LASSO machine learning algorithm was utilized to develop a prognostic model associated with GGCT.

RESULTS

Our study revealed heightened expression of GGCT in pancreatic cancer tissues and cells, suggesting an association with poorer patient prognosis. Additionally, we explored the immunomodulatory effects of GGCT in both pan-cancer and pancreatic cancer contexts, found that GGCT may be associated with immunosuppressive regulation in various types of tumors. Specifically, in patients with high expression of GGCT in pancreatic cancer, there is a reduction in the infiltration of various immune cells, leading to poorer responsiveness to immunotherapy and worse survival rates. In vivo and in vitro assays indicate that downregulation of GGCT markedly suppresses the proliferation and metastasis of pancreatic cancer cells. Moreover, this inhibitory effect appears to be linked to the regulation of GGCT on c-Myc. A prognostic model was constructed based on genes derived from GGCT, demonstrating robust predictive ability for favorable survival prognosis and response to immunotherapy.

AEBP1 promotes papillary thyroid cancer progression by activating BMP4 signaling

Papillary thyroid cancer (PTC) is the most prevalent endocrine cancer worldwide. Approximately 30 % of PTC patients will progress into the advanced or metastatic stage and have a relatively poor prognosis. It is well known that epithelial-mesenchymal transition (EMT) plays a pivotal role in thyroid cancer metastasis, resistance to therapy, and recurrence. Clarifying the molecular mechanisms of EMT in PTC progression will help develop the targeted therapy of PTC. The aberrant expression of some transcription factors (TFs) participated in many pathological processes of cancers including EMT. In this study, by performing bioinformatics analysis, adipocyte enhancer-binding protein 1 (AEBP1) was screened as a pivotal TF that promoted EMT and tumor progression in PTC. In vitro experiments indicated that knockout of AEBP1 can inhibit the growth and invasion of PTC cells and reduce the expression of EMT markers including N-cadherin, TWIST1, and ZEB2. In the xenograft model, knockout of AEBP1 inhibited the growth and lung metastasis of PTC cells. By performing RNA-sequencing, dual-luciferase reporter assay, and chromatin immunoprecipitation assay, Bone morphogenetic protein 4 (BMP4) was identified as a downstream target of AEBP1. Over-expression of BMP4 can rescue the inhibitory effects of AEBP1 knockout on the growth, invasion, and EMT phenotype of PTC cells. In conclusion, these findings demonstrated that AEBP1 plays a critical role in PTC progression by regulating BMP4 expression and the AEBP1-BMP4 axis may present novel therapeutic targets for PTC treatment.

Development of a thyroid cancer prognostic model based on the mitophagy-associated differentially expressed genes

BACKGROUND

The prevalence of thyroid cancer (ThyC), a frequent malignant tumor of the endocrine system, has been rapidly increasing over time. The mitophagy pathway is reported to play a critical role in ThyC onset and progression in many studies. This research aims to create a mitophagy-related survival prediction model for ThyC patients.

METHODS

Genes connected to mitophagy were found in the GeneCards database. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided information on the expression patterns of ThyC-related genes. To identify differentially expressed genes (DEGs), R software was employed. The prognostic significance of each DEG was assessed using the prognostic K-M curve. The prognostic model was built using LASSO, ROC, univariate, and multivariate Cox regression analyses. Finally, a nomogram model was developed to predict the survival outcome of ThyC patients in the clinical setting.

RESULTS

Through differential analysis, functional enrichment analysis, and protein-protein interaction (PPI) network analysis, we screened 10 key genes related to mitophagy in ThyC. The risk model was eventually developed using LASSO and Cox regression analyses based on the six DEGs related to mitophagy. An altered expression level of a mitophagy-related prognostic gene, GGCT, was found to be the most significant one, according to the KM survival curve analysis. An immunohistochemical (IHC) investigation revealed that ThyC tissues expressed higher levels of GGCT than normal thyroid tissues. The ROC curve verified the satisfactory performance of the model in survival prediction. Multivariate Cox regression analysis showed that the pathological grade, residual tumor volume, and initial tumor lesion type were significantly linked to the prognosis. Finally, we created a nomogram to predict the overall survival rate of ThyC patients at 3-, 5-, and 7- year time points.

CONCLUSION

The nomogram risk prediction model was developed to precisely predict the survival rate of ThyC patients. The model was validated based on the most significant DEG GGCT gene expression in ThyC. This model may serve as a guide for the creation of precise treatment plans for ThyC patients.

Identification of c-Met as a novel target of γ-glutamylcyclotransferase

γ-Glutamylcyclotransferase (GGCT) is highly expressed in multiple types of cancer tissues and its knockdown suppresses the growth of cancer cells in vitro and in vivo. Although GGCT is a promising target for cancer therapy, the mechanisms underlying the antitumor effects remain unclear. The knockdown of GGCT inhibited the MEK-ERK pathway, and activated the tumor suppressor retinoblastoma gene (RB) at the protein level in cancer cell lines. c-Met was down-regulated by the knockdown of GGCT in cancer cells and its overexpression attenuated the dephosphorylation of RB and cell cycle arrest induced by the knockdown of GGCT in lung cancer A549 cells. STAT3 is a transcription factor that induces c-Met expression. STAT3 phosphorylation and its nuclear expression level were decreased in GGCT-depleted A549 and prostate cancer PC3 cells. The simultaneous knockdown of AMPK and GGCT restored the down-regulated expression of c-Met, and attenuated the dephosphorylation of STAT3 and MEK-ERK-RB induced by the knockdown of GGCT in PC3 cells. An intraperitoneal injection of a GGCT inhibitor decreased c-Met protein expression in a mouse xenograft model of PC3 cells. These results suggest that the knockdown of GGCT activates the RB protein by inhibiting the STAT3-c-Met-MEK-ERK pathway via AMPK activation.

A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma

The cell cycle plays a vital role in tumorigenesis and progression. Long non-coding RNAs (lncRNAs) are key regulators of cell cycle processes. Therefore, understanding cell cycle-related lncRNAs (CCR-lncRNAs) is crucial for determining the prognosis of papillary thyroid carcinoma (PTC). RNA-seq and clinical data of PTC were acquired from The Cancer Genome Atlas, and CCR-lncRNAs were selected based on Pearson's correlation coefficients. According to univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses, a five-CCR-lncRNA signature (FOXD2-AS1, LOC100507156, BSG-AS1, EGOT, and TMEM105) was established to predict the progression-free interval (PFI) in PTC. Kaplan-Meier survival, time-dependent receiver operating characteristic curve, and multivariate Cox regression analyses proved that the signature had a reliable prognostic capability. A nomogram consisting of the risk signature and clinical characteristics was constructed that effectively predicted the PFI in PTC. Functional enrichment analyses indicted that the signature was involved in cell cycle- and immune-related pathways. Furthermore, we also analyzed the correlation between the signature and immune cell infiltration. Finally, we verified the differential expression of CCR-lncRNAs in vitro using quantitative real-time polymerase chain reaction. Overall, the newly developed prognostic risk signature based on five CCR-lncRNAs may become a marker for predicting the PFI in PTC.