Screening and Identification of Key Microenvironment-Related Genes in Non-functioning Pituitary Adenoma

Identification of cholesterol metabolism-related subtypes in nonfunctioning pituitary neuroendocrine tumors and analysis of immune infiltration

OBJECTIVE

This study aimed to investigate the role of cholesterol metabolism-related genes in nonfunctioning pituitary neuroendocrine tumors (NF-PitNETs) invading the cavernous sinus and analyze the differences in immune cell infiltration between invasive and noninvasive NF-PitNETs.

METHODS

First, a retrospective analysis of single-center clinical data was performed. Second, the immune cell infiltration between invasive and noninvasive NF-PitNETs in the GSE169498 dataset was further analyzed, and statistically different cholesterol metabolism-related gene expression matrices were obtained from the dataset. The hub cholesterol metabolism-related genes in NF-PitNETs were screened by constructing machine learning models. In accordance with the hub gene, 73 cases of NF-PitNETs were clustered into two subtypes, and the functional differences and immune cell infiltration between the two subtypes were further analyzed.

RESULTS

The clinical data of 146 NF-PitNETs were evaluated, and the results showed that the cholesterol (P = 0.034) between invasive and noninvasive NF-PitNETs significantly differed. After binary logistic analysis, cholesterol was found to be an independent risk factor for cavernous sinus invasion (CSI) in NF-PitNETs. Bioinformatics analysis found three immune cells between invasive and noninvasive NF-PitNETs were statistically significant in the GSE169498 dataset, and 34 cholesterol metabolism-related genes with differences between the two groups were obtained 12 hub genes were selected by crossing the two machine learning algorithm results. Subsequently, cholesterol metabolism-related subgroups, A and B, were obtained by unsupervised hierarchical clustering analysis. The results showed that 12 immune cells infiltrated differentially between the two subgroups. The chi-square test revealed that the two subgroups had statistically significance in the invasive and noninvasive samples (P = 0.001). KEGG enrichment analysis showed that the differentially expressed genes were mainly enriched in the neural ligand-receptor pathway. GSVA analysis showed that the mTORC signaling pathway was upregulated and played an important role in the two-cluster comparison.

CONCLUSION

By clinical data and bioinformatics analysis, cholesterol metabolism-related genes may promote the infiltration abundance of immune cells in NF-PitNETs and the invasion of cavernous sinuses by NF-PitNETs through the mTOR signaling pathway. This study provides a new perspective to explore the pathogenesis of cavernous sinus invasion by NF-PitNETs and determine potential therapeutic targets for this disease.

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.

Tumour microenvironment and pituitary tumour behaviour

The pituitary tumour microenvironment encompasses a spectrum of non-tumoural cells, such as immune, stromal or endothelial cells, as well as enzymes and signalling peptides like cytokines, chemokines and growth factors, which surround the tumour cells and may influence pituitary tumour behaviour and tumourigenic mechanisms. Recently, there has been intensive research activity in this field describing various pituitary tumour-infiltrating immune and stromal cell subpopulations, and immune- and microenvironment-related pathways. Key changes in oncological therapeutic avenues resulted in the recognition of pituitary as a target of adverse events for patients treated with immune checkpoint regulators. However, these phenomena can be turned into therapeutic advantage in severe cases of pituitary tumours. Therefore, unravelling the pituitary tumour microenvironment will allow a better understanding of the biology and behaviour of pituitary tumours and may provide further developments in terms of diagnosis and management of patients with aggressively growing or recurrent pituitary tumours.

The immune microenviroment in somatotropinomas: from biology to personalized and target therapy

Pituitary tumors are rare neoplasms, with a heterogeneous biological and clinical behavior, due to their clinical course, local invasive growth, resistance to conventional therapies and the risk of disease progression. Recent studies on tumor microenvironment (TME) provided new knowledge on the biology of these neoplasia, that may explain the different phenotypes of these tumors and suggest new biomarkers able to predict the prognosis and the treatment outcome. The identification of molecular markers that act as targets for biological therapies may open new perspectives in the medical treatments of aggressive pituitary tumors.In this paper, we will review data of TME and target therapies in somatotropinomas.

The microenvironment of pituitary adenomas: biological, clinical and therapeutical implications

The microenvironment of pituitary adenomas (PAs) includes a range of non-tumoral cells, such as immune and stromal cells, as well as cell signaling molecules such as cytokines, chemokines and growth factors, which surround pituitary tumor cells and may modulate tumor initiation, progression, invasion, angiogenesis and other tumorigenic processes. The microenvironment of PAs has been actively investigated over the last years, with several immune and stromal cell populations, as well as different cytokines, chemokines and growth factors being recently characterized in PAs. Moreover, key microenvironment-related genes as well as immune-related molecules and pathways have been investigated, with immune check point regulators emerging as promising targets for immunotherapy. Understanding the microenvironment of PAs will contribute to a deeper knowledge of the complex biology of PAs, as well as will provide developments in terms of diagnosis, clinical management and ultimately treatment of patients with aggressive and/or refractory PAs.