Overexpression of HOMER2 predicts better outcome in low-grade endometrioid endometrial adenocarcinoma

HOMER3 promotes liver hepatocellular carcinoma cancer progression by -upregulating EZH2 and mediating miR-361/GPNMB axis

Liver hepatocellular carcinoma (LIHC) is among the most lethal human cancers. Studies have shown that Homer scaffold protein 3 (HOMER3) plays important roles in various diseases and cancers, but its biological function and molecular mechanism in LIHC have never been investigated. Our study discovered the aberrantly high expression of HOMER3 and its promising diagnostic and prognostic significance in LIHC. Functionally, HOMER3 knockdown inhibited the proliferative and migrative abilities of LIHC cells and tumor growth in vivo. Mechanically, HOMER3 mediated the aggressiveness of LIHC cells via GPNMB. Meanwhile, miR-361 directly targeted GPNMB and attenuated LIHC progression by suppressing GPNMB expression. The regulatory effect of HOMER3 during LIHC progression was exerted through the miR-361/GPNMB axis. Furthermore, EZH2 supplementation or miR-361 depletion effectively abated the tumor-suppressive effect of HOMER3 knockdown on LIHC progression. In conclusion, HOMER3 mediated LIHC progression through the EZH2/miR-361/GPNMB axis.

Identification of biomarkers associated with the invasion of nonfunctional pituitary neuroendocrine tumors based on the immune microenvironment

Introduction

The invasive behavior of nonfunctioning pituitary neuroendocrine tumors (NF-PitNEts) affects complete resection and indicates a poor prognosis. Cancer immunotherapy has been experimentally used for the treatment of many tumors, including pituitary tumors. The current study aimed to screen the key immune-related genes in NF-PitNEts with invasion.

Methods

We used two cohorts to explore novel biomarkers in NF-PitNEts. The immune infiltration-associated differentially expressed genes (DEGs) were obtained based on high/low immune scores, which were calculated through the ESTIMATE algorithm. The abundance of immune cells was predicted using the ImmuCellAI database. WGCNA was used to construct a coexpression network of immune cell-related genes. Random forest analysis was used to select the candidate genes associated with invasion. The expression of key genes was verified in external validation set using quantitative real-time polymerase chain reaction (qRT‒PCR).

Results

The immune and invasion related DEGs was obtained based on the first dataset of NF-PitNEts (n=112). The immune cell-associated modules in NF-PitNEts were calculate by WGCNA. Random forest analysis was performed on 81 common genes intersected by immune-related genes, invasion-related genes, and module genes. Then, 20 of these genes with the highest RF score were selected to construct the invasion and immune-associated classification model. We found that this model had high prediction accuracy for tumor invasion, which had the largest area under the receiver operating characteristic curve (AUC) value in the training dataset from the first dataset (n=78), the self-test dataset from the first dataset (n=34), and the independent test dataset (n=73) (AUC=0.732/0.653/0.619). Functional enrichment analysis revealed that 8 out of the 20 genes were enriched in multiple signaling pathways. Subsequently, the 8-gene (BMP6, CIB2, FABP5, HOMER2, MAML3, NIN, PRKG2 and SIDT2) classification model was constructed and showed good efficiency in the first dataset (AUC=0.671). In addition, the expression levels of these 8 genes were verified by qRT‒PCR.

Conclusion

We identified eight key genes associated with invasion and immunity in NF-PitNEts that may play a fundamental role in invasive progression and may provide novel potential immunotherapy targets for NF-PitNEts.

Identification of Novel Biomarkers for Abdominal Aortic Aneurysm Promoted by Obstructive Sleep Apnea

BACKGROUND

We sought to find new biomarkers for abdominal aortic aneurysms (AAA) caused by chronic intermittent hypoxia (CIH).

METHODS

The AAA mice model was created using Ang II. The mice were divided into normoxic and CIH groups. The structure of AAA was observed using abdominal ultrasonography, Elastica van Gieson (EVG), and hematoxylin and eosin (HE) staining. The expression of ɑ-SMA was investigated using immunohistochemistry. The novel biomarkers were screened using bioinformatics analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to verify the expression of novel genes in both normal oxygen and CIH.

RESULTS

CIH appears to cause greater aortic dilation, higher AAA incidence, lower survival rate, thicker vessel wall, and more brittle elastic lamellae when compared to controls. The immunohistochemistry results showed that the expression of ɑ-SMA in the CIH group was reduced significantly. Four novel genes, including Homer2, Robo2, Ehf, and Asic1, were found to be differentially expressed between normal oxygen and CIH using qRT-PCR, indicating the same trend as bioinformatics analysis.

CONCLUSIONS

We discovered that CIH could hasten the occurrence and progression of AAA. Four genes (Homer2, Robo2, Ehf, and Asic1) may be novel biomarkers for AAA, which could aid in the search for new therapies for patients with AAA caused by CIH.

Homer2 and Homer3 Act as Novel Biomarkers in Diagnosis of hepatitis B virus-induced Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common causes of cancer‐related mortality worldwide. Early detection of HCC can significantly improve patients' outcomes. An increasing number of studies have validated that Homer is dysregulated in cancers and may serve as diagnostic markers. In the present study, we investigated the expression profile and diagnostic significance of Homer2 and Homer3 in hepatitis B virus-induced HCC (HBV-HCC).

Methods: Quantitative real-time PCR (QRT-PCR), western blot analysis and immunohistochemistry analysis.

Results: Homer2 and Homer3 were downregulated in HCC. The expression of Homer2 was associated with tumor differentiation grade (P= 0.012) and total protein (TP) level (P= 0.032). Homer3 was related to tumor size (P= 0.010), tumor nodes (P= 0.026) and γ-glutamyl transferase (GGT) level (P= 0.001). The receiver operating characteristic curve analyses indicated that the combination of Homer2, Homer3 and AFP possessed a high accuracy (AUC=0.900) to diagnose HCC cases from healthy controls.

Conclusion: Our data indicated that Homer2 and Homer3 were downregulated in HCC and might be potential diagnostic marker for HCC.