Molecular Signatures of Cancer Stemness Characterize the Correlations with Prognosis and Immune Landscape and Predict Risk Stratification in Pheochromocytomas and Paragangliomas.

in Bioengineering (Basel, Switzerland) by Lei Li, Shuangyu Liu, Zeqi Guo, Yueming Tang, Yue Zhang, Ling Qiu, Yue Li

TLDR

  • The study found that tumor stemness is related to metastasis and progression in PPGLs and established a reliable prognostic model for predicting patient outcomes.

Abstract

Pheochromocytoma and paragangliomas (PPGLs) caused refractory hypertension in clinics. The sustained risk of local or metastatic recurrences or new tumor development prompted more research on diagnosis, prognosis prediction, and immunotherapy. The tumor stemness is closely related to the heterogeneous growth of tumor, metastasis, and drug-resistance, and mRNA expression-based stemness indices (mRNAsi) could reflect tumor stemness. This was calculated based on OCLR machine learning algorithm and PPGLs patients' TCGA RNAseq data. The relationship between clinical, molecular, and tumor microenvironment (TME) features and tumor stemness was analyzed through the hub genes that best captured the stem cell characteristics of PPGLs using weighted gene co-expression network analysis (WGCNA), Cox, and LASSO regression analysis. Our study found that metastatic PPGLs had higher mRNAsi scores, suggesting the degree of tumor stemness could affect metastasis and progression.,,,, and-mutant subtypes displayed significant difference in stemness expression. Patients were divided into stemness high-score and low-score subtypes. High-score PPGLs displayed the more unfavorable prognosis compared with low-score, associated with their immune-suppressive features, manifested as low macrophages M1 infiltration and downregulated expression of immune checkpoints. Furthermore, from the viewpoint of stemness features, we established a reliable prognostic for PPGLs, which has the highest AUC value (0.908) in the field so far. And this could stratify PPGLs patients into high-risk and low-risk subtypes, showing the significant differences in prognosis, underlying mechanisms correlated with specific molecular alterations, biological processes activation, and TME. Notably, high immune infiltration and tumor neoantigen in low-risk patients and further resulted in more responsive to immunotherapy. We indicated that tumor stemness could act as the potential biomarker for metastasis or prognosis of PPGLs, and integrated multi-data sources, analyzed valuable stemness-related genes, developed and verified a novel stemness scoring system to predict prognosis and guide the choice of treatment strategies.

Overview

  • The study aimed to investigate the role of tumor stemness in predicting the metastasis and prognosis of pheochromocytoma and paragangliomas (PPGLs).
  • The researchers used machine learning algorithms and RNAseq data to develop an mRNA expression-based stemness index (mRNAsi) to quantify tumor stemness.
  • The study analyzed the relationship between clinical, molecular, and tumor microenvironment (TME) features and tumor stemness using weighted gene co-expression network analysis (WGCNA), Cox, and LASSO regression analysis.

Comparative Analysis & Findings

  • The study found that metastatic PPGLs had higher mRNAsi scores, which suggests that tumor stemness affects metastasis and progression.
  • The researchers identified hub genes that best captured the stem cell characteristics of PPGLs and found that patients with high stemness scores had unfavorable prognosis compared to those with low stemness scores.
  • The study established a reliable prognostic model with the highest AUC value (0.908) and could stratify PPGLs patients into high-risk and low-risk subtypes based on stemness features.

Implications and Future Directions

  • Tumor stemness could be used as a potential biomarker for metastasis or prognosis of PPGLs, and integrated multi-data sources could be used to develop personalized treatment strategies.
  • Future studies could explore the relationship between tumor stemness and the immune system to develop novel immunotherapies for PPGLs.
  • The development of new biomarkers and therapeutics for PPGLs would require further investigation and validation.
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