GHR knockdown enhances the sensitivity of HCC cells to sorafenib

Reproducible generation of human liver organoids (HLOs) on a pillar plate platform via microarray 3D bioprinting

Human liver organoids (HLOs) hold significant potential for recapitulating the architecture and function of liver tissues in vivo. However, conventional culture methods of HLOs, forming Matrigel domes in 6-/24-well plates, have technical limitations such as high cost and low throughput in organoid-based assays for predictive assessment of compounds in clinical and pharmacological lab settings. To address these issues, we have developed a unique microarray 3D bioprinting protocol of progenitor cells in biomimetic hydrogels on a pillar plate with sidewalls and slits, coupled with a clear bottom, 384-deep well plate for scale-up production of HLOs. Microarray 3D bioprinting, a droplet-based printing technology, was used to generate a large number of small organoids on the pillar plate for predictive hepatotoxicity assays. Foregut cells, differentiated from human iPSCs, were mixed with Matrigel and then printed on the pillar plate rapidly and uniformly, resulting in coefficient of variation (CV) values in the range of 15-18%, without any detrimental effect on cell viability. Despite utilizing 10-50-fold smaller cell culture volume compared to their counterparts in Matrigel domes in 6-/24-well plates, HLOs differentiated on the pillar plate exhibited similar morphology and superior function, potentially due to rapid diffusion of nutrients and oxygen at the small scale. Day 25 HLOs were robust and functional on the pillar plate in terms of their viability, albumin secretion, CYP3A4 activity, and drug toxicity testing, all with low CV values. From three independent trials of in situ assessment, the IC50 values calculated for sorafenib and tamoxifen were 6.2 ± 1.6 μM and 25.4 ± 8.3 μM, respectively. Therefore, our unique 3D bioprinting and miniature organoid culture on the pillar plate could be used for scale-up, reproducible generation of HLOs with minimal manual intervention for high-throughput assessment of compound hepatotoxicity.

Approach to the Patient: Case Studies in Pediatric Growth Hormone Deficiency and Their Management

CONTEXT

Pathologies attributed to perturbations of the GH/IGF-I axis are among the most common referrals received by pediatric endocrinologists.

AIM

In this article, distinctive cased-based presentations are used to provide a practical and pragmatic approach to the management of pediatric growth hormone deficiency (GHD).

CASES

We present 4 case vignettes based on actual patients that illustrate (1) congenital GHD, (2) childhood GHD presenting as failure to thrive, (3) childhood GHD presenting in adolescence as growth deceleration, and (4) childhood-onset GHD manifesting as metabolic complications in adolescence. We review patient presentation and a management approach that aims to highlight diagnostic considerations for treatment based on current clinical guidelines, with mention of new therapeutic and diagnostic modalities being used in the field.

CONCLUSION

Pediatric GHD is diverse in etiology and clinical presentation. Timely management has the potential not only to improve growth but can also ameliorate or even mitigate adverse metabolic outcomes, which can be directly attributed to a GH deficient state.

Genome-wide DNA methylation profiling of HPV-negative leukoplakia and gingivobuccal complex cancers

BACKGROUND

Gingivobuccal complex oral squamous cell carcinoma (GBC-OSCC) is an aggressive malignancy with high mortality often preceded by premalignant lesions, including leukoplakia. Previous studies have reported genomic drivers in OSCC, but much remains to be elucidated about DNA methylation patterns across different stages of oral carcinogenesis.

RESULTS

There is a serious lack of biomarkers and clinical application of biomarkers for early detection and prognosis of gingivobuccal complex cancers. Hence, in search of novel biomarkers, we measured genome-wide DNA methylation in 22 normal oral tissues, 22 leukoplakia, and 74 GBC-OSCC tissue samples. Both leukoplakia and GBC-OSCC had distinct methylation profiles as compared to normal oral tissue samples. Aberrant DNA methylation increases during the different stages of oral carcinogenesis, from premalignant lesions to carcinoma. We identified 846 and 5111 differentially methylated promoters in leukoplakia and GBC-OSCC, respectively, with a sizable fraction shared between the two sets. Further, we identified potential biomarkers from integrative analysis in gingivobuccal complex cancers and validated them in an independent cohort. Integration of genome, epigenome, and transcriptome data revealed candidate genes with gene expression synergistically regulated by copy number and DNA methylation changes. Regularised Cox regression identified 32 genes associated with patient survival. In an independent set of samples, we validated eight genes (FAT1, GLDC, HOXB13, CST7, CYB5A, MLLT11, GHR, LY75) from the integrative analysis and 30 genes from previously published reports. Bisulfite pyrosequencing validated GLDC (P = 0.036), HOXB13 (P < 0.0001) promoter hypermethylation, and FAT1 (P < 0.0001) hypomethylation in GBC-OSCC compared to normal controls.

CONCLUSIONS

Our findings identified methylation signatures associated with leukoplakia and gingivobuccal complex cancers. The integrative analysis in GBC-OSCC identified putative biomarkers that enhance existing knowledge of oral carcinogenesis and may potentially help in risk stratification and prognosis of GBC-OSCC.

Growth hormone after CNS tumor diagnosis: the fundamentals, fears, facts, and future directions

Growth hormone deficiency (GHD) may occur in pediatric patients with central nervous system (CNS) tumors at initial tumor presentation or later as treatment-related sequelae. While it is well recognized that growth hormone (GH) has beneficial effects on growth and endocrinopathies, there's often hesitancy by clinicians to initiate GH therapy for GHD after CNS tumor diagnosis due to the perceived increased risk of tumor recurrence. The available data is described here and based on this review, there is no evidence of increased risk of tumor recurrence or secondary malignancy in patients treated with GH after CNS tumor diagnosis. Further understanding of tumor biology and presence of downstream GH targets including insulin-like growth factor-1 (IGF-1) and insulin receptor activity is still needed.

Integrated analysis of RNA-seq in hepatocellular carcinoma reveals competing endogenous RNA network composed of circRNA, lncRNA, and mRNA

BACKGROUND

Circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) have been hypothesized to have important roles in the etiology of hepatocellular carcinoma (HCC). However, the synergistic effect of circRNA and lncRNA in the pathogenesis of HCC has rarely been studied.

METHODS

In this study, the Gene Expression Omnibus database was used to get the expression profiles of circRNAs, micro RNAs (miRNAs), lncRNAs, and messenger RNAs (mRNAs) in HCC tissues and normal tissues. The accession numbers for this database are GSE101728, GSE155949, and GSE108724. We found 291 differentially overexpressed lncRNAs and 541 differentially overexpressed mRNA in GSE101728, 30 differentially overexpressed circRNA in GSE155949, and 48 significantly downregulated miRNA in GSE198724. Meanwhile, based on Pearson correlation test, we established lncRNA-mRNA networks. We constructed lncRNA/circRNA-miRNA pairs through Starbase database prediction and identified the common miRNAs. The intersection of co-predicted miRNAs and the 48 significantly low expression miRNAs in GSE198724 were included in the following study. miRDB, Targetscan, miRwalk, and lncRNA-related mRNA jointly determined the miRNA-mRNA portion of the circRNA/lncRNA-miRNA-mRNA co-expression network. And, among 55 differentially expressed mRNA in circRNA/lncRNA-miRNA-mRNA network, CPEB3, EFNB3, FATA4, growth hormone receptor, GSTZ1, KLF8, MFAP4, PAIP2B, PHACTR3, PITPNM3, RPS6KA6, RSPO3, SLITRK6, SMOC1, STEAP4, SYT1, TMEM132E, TSPAN11, and ZFPM2 were intimately related to the prognosis of HCC patients in Kaplan-Meier plotter analysis (P < .05).

CONCLUSION

We have discovered that the prognosis-related lncRNAs/circRNAs-miRNA-mRNA network plays a significant role in the pathogenesis of HCC. These findings may offer fresh perspectives for further research into the pathogenesis of HCC and the search for novel treatments for HCC.

Integrated bioinformatical analysis, machine learning and in vitro experiment-identified m6A subtype, and predictive drug target signatures for diagnosing renal fibrosis

Renal biopsy is the gold standard for defining renal fibrosis which causes calcium deposits in the kidneys. Persistent calcium deposition leads to kidney inflammation, cell necrosis, and is related to serious kidney diseases. However, it is invasive and involves the risk of complications such as bleeding, especially in patients with end-stage renal diseases. Therefore, it is necessary to identify specific diagnostic biomarkers for renal fibrosis. This study aimed to develop a predictive drug target signature to diagnose renal fibrosis based on m6A subtypes. We then performed an unsupervised consensus clustering analysis to identify three different m6A subtypes of renal fibrosis based on the expressions of 21 m6A regulators. We evaluated the immune infiltration characteristics and expression of canonical immune checkpoints and immune-related genes with distinct m6A modification patterns. Subsequently, we performed the WGCNA analysis using the expression data of 1,611 drug targets to identify 474 genes associated with the m6A modification. 92 overlapping drug targets between WGCNA and DEGs (renal fibrosis vs. normal samples) were defined as key drug targets. A five target gene predictive model was developed through the combination of LASSO regression and stepwise logistic regression (LASSO-SLR) to diagnose renal fibrosis. We further performed drug sensitivity analysis and extracellular matrix analysis on model genes. The ROC curve showed that the risk score (AUC = 0.863) performed well in diagnosing renal fibrosis in the training dataset. In addition, the external validation dataset further confirmed the outstanding predictive performance of the risk score (AUC = 0.755). These results indicate that the risk model has an excellent predictive performance for diagnosing the disease. Furthermore, our results show that this 5-target gene model is significantly associated with many drugs and extracellular matrix activities. Finally, the expression levels of both predictive signature genes EGR1 and PLA2G4A were validated in renal fibrosis and adjacent normal tissues by using qRT-PCR and Western blot method.

Development and Verification of a Combined Immune- and Metabolism-Related Prognostic Signature for Hepatocellular Carcinoma

Immune escape and metabolic reprogramming are becoming important characteristics of tumor biology, which play critical roles in tumor initiation and progression. However, the integrative analysis of immune and metabolic characteristics for the tumor microenvironment in hepatocellular carcinoma (HCC) remains unclear. Herein, by univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, a prognostic signature associated with tumor microenvironment was established based on five immune- and metabolism-related genes (IMRGs), which was fully verified and evaluated in both internal and external cohorts. The C-index was superior to previously published HCC signatures, indicating the robustness and reliability of IMRGs prognostic signature. A nomogram was built based on IMRGs prognostic signature and various clinical parameters, such as age and T stage. The AUCs of nomogram at 1-, 3-, and 5-year (AUC = 0.829, 0.749, 0.749) were slightly better than that of IMRGs signature (AUC = 0.809, 0.734, 0.711). The relationship of risk score (RS) with immune checkpoint expressions, immunophenoscore (IPS), as well as microsatellite instability (MSI) together accurately predicted the treatment efficacy. Collectively, the IMRGs signature might have the potential to better predict prognostic risk, evaluate immunotherapy efficacy, and help personalize immunotherapy for HCC patients.

Identification of Feature Genes of a Novel Neural Network Model for Bladder Cancer

Background: The combination of deep learning methods and oncogenomics can provide an effective diagnostic method for malignant tumors; thus, we attempted to construct a reliable artificial neural network model as a novel diagnostic tool for Bladder cancer (BLCA). Methods: Three expression profiling datasets (GSE61615, GSE65635, and GSE100926) were downloaded from the Gene Expression Omnibus (GEO) database. GSE61615 and GSE65635 were taken as the train group, while GSE100926 was set as the test group. Differentially expressed genes (DEGs) were filtered out based on the logFC and FDR values. We also performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to explore the biological functions of the DEGs. Consequently, we utilized a random forest algorithm to identify feature genes and further constructed a neural network model. The test group was given the same procedures to validate the reliability of the model. We also explored immune cells' infiltration degree and correlation coefficients through the CiberSort algorithm and corrplot R package. The qRT-PCR assay was implemented to examine the expression level of the feature genes in vitro. Results: A total of 265 DEGs were filtered out and significantly enriched in muscle system processes, collagen-containing and focal adhesion signaling pathways. Based on the random forest algorithm, we selected 14 feature genes to construct the neural network model. The area under the curve (AUC) of the training group was 0.950 (95% CI: 0.850-1.000), and the AUC of the test group was 0.667 (95% CI: 0.333-1.000). Besides, we observed significant differences in the content of immune infiltrating cells and the expression levels of the feature genes. Conclusion: After repeated verification, our neural network model had clinical feasibility to identify bladder cancer patients and provided a potential target to improve the management of BLCA.

Systemic Deficiency of GHR in Pigs leads to Hepatic Steatosis via Negative Regulation of AHR Signaling

Laron syndrome (LS) is an autosomal recessive genetic disease mainly caused by mutations in the human growth hormone receptor (GHR) gene. Previous studies have focused on Ghr mutant mice, but compared with LS patients, Ghr knockout (KO) mice exhibit differential lipid metabolism. To elucidate the relationship between GHR mutation and lipid metabolism, the role of GHR in lipid metabolism was examined in GHR KO pigs and hepatocytes transfected with siGHR. We observed high levels of free fatty acids and hepatic steatosis in GHR KO pigs, which recapitulates the abnormal lipid metabolism in LS patients. RNAseq analysis revealed that genes related to the fatty acid oxidation pathway were significantly altered in GHR KO pigs. AHR, a transcription factor related to lipid metabolism, was significantly downregulated in GHR KO pigs and siGHR-treated human hepatocytes. We found that AHR directly regulated fatty acid oxidation by directly binding to the promoters of ACOX1 and CPT1A and activating their expression. These data indicate that loss of GHR disturbs the ERK-AHR-ACOX1/CPT1A pathway and consequently leads to hepatic steatosis. Our results established AHR as a modulator of hepatic steatosis, thereby providing a therapeutic target for lipid metabolism disorder.

Dual Characters of GH-IGF1 Signaling Pathways in Radiotherapy and Post-radiotherapy Repair of Cancers

Radiotherapy remains one of the most important cancer treatment modalities. In the course of radiotherapy for tumor treatment, the incidental irradiation of adjacent tissues could not be completely avoided. DNA damage is one of the main factors of cell death caused by ionizing radiation, including single-strand (SSBs) and double-strand breaks (DSBs). The growth hormone-Insulin-like growth factor 1 (GH-IGF1) axis plays numerous roles in various systems by promoting cell proliferation and inhibiting apoptosis, supporting its effects in inducing the development of multiple cancers. Meanwhile, the GH-IGF1 signaling involved in DNA damage response (DDR) and DNA damage repair determines the radio-resistance of cancer cells subjected to radiotherapy and repair of adjacent tissues damaged by radiotherapy. In the present review, we firstly summarized the studies on GH-IGF1 signaling in the development of cancers. Then we discussed the adverse effect of GH-IGF1 signaling in radiotherapy to cancer cells and the favorable impact of GH-IGF1 signaling on radiation damage repair to adjacent tissues after irradiation. This review further summarized recent advances on research into the molecular mechanism of GH-IGF1 signaling pathway in these effects, expecting to specify the dual characters of GH-IGF1 signaling pathways in radiotherapy and post-radiotherapy repair of cancers, subsequently providing theoretical basis of their roles in increasing radiation sensitivity during cancer radiotherapy and repairing damage after radiotherapy.