| Literature DB >> 35454025 |
Liang Lu1, Xueyan Wan1, Yu Xu1, Juan Chen1, Kai Shu1, Ting Lei1.
Abstract
Pituitary adenomas (PAs) are benign lesions; nonetheless, some PAs exhibit aggressive behaviors, which lead to recurrence. The impact of pituitary dysfunction, invasion-related risks, and other complications considerably affect the quality of life of patients with recurrent PAs. Reliable prognostic factors are needed for recurrent PAs but require confirmation. This review summarizes research progress on two aspects-namely, the clinical and biological factors (biomarkers) for recurrent PAs. Postoperative residue, age, immunohistological subtypes, invasion, tumor size, hormone levels, and postoperative radiotherapy can predict the risk of recurrence in patients with PAs. Additionally, biomarkers such as Ki-67, p53, cadherin, pituitary tumor transforming gene, matrix metalloproteinase-9, epidermal growth factor receptor, fascin actin-bundling protein 1, cyclooxygenase-2, and some miRNAs and lncRNAs may be utilized as valuable tools for predicting PA recurrence. As no single marker can independently predict PA recurrence, we introduce an array of comprehensive models and grading methods, including multiple prognostic factors, to predict the prognosis of PAs, which have shown good effectiveness and would be beneficial for predicting PA recurrence.Entities:
Keywords: biomarkers; clinical factors; model; pituitary adenoma; prognostic factors; recurrence
Year: 2022 PMID: 35454025 PMCID: PMC9024548 DOI: 10.3390/diagnostics12040977
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Figure 1Summary of clinical prognostic factors for PA recurrence. Postoperative residue, invasion, aggressive subtypes, and higher preoperative serum hormone levels could promote the recurrence of PAs. Whereas postoperative radiotherapy, older age, smaller tumor size, and lower postoperative serum hormone levels could inhibit the recurrence of PAs.
Figure 2Summary of biological factors (biomarkers) for PA recurrence. Prognostic biomarkers (highlighted in red) from various sources could be used as valuable tools for predicting the recurrence of PAs (see text for details). Pituitary tumor transforming gene (PTTG), matrix metalloproteinase (MMP), cyclooxygenase-2 (COX-2), epidermal growth factor receptor (EGFR), fascin actin-bundling protein 1 (FSCN1), epithelial mesenchymal transformation (EMT), extracellular signal-regulated kinase (ERK), mitogen-activated protein kinase (MAPK).
Summary of recent studies on comprehensive model for predicting the recurrence of pituitary adenomas.
| References | Content of the Models | Form | Sample Size | Prediction Performance |
|---|---|---|---|---|
| Pappy A. L. et al., 2019 [ | Model 1 (CSI, diameter ≥ 2.9 cm and ki-67 > 3%) | Prognostic model | Training (n = 501) | 98.7% specificity (OR 8.6; CI 3.0–24.7) |
| Model 2 (ki-67 > 3% and CSI) | 93.1% specificity (OR 3.3; CI 1.8–6.0) | |||
| Model 3 (ki-67 > 3%, mitoses and p53, former “atypical” adenoma) | 96.0% specificity (OR 2.3; CI 1.0–5.0) | |||
| Wang X. et al., 2019 [ | SPRY3, ZNF343, GZF1, C15orf61, SLC24A4, HOXB5, SLC9A3R2 | Prognostic model | Training (n = 57) Validation (n = 50) |
Training (AUC 0.857) Validation (AUC 0.936) All (AUC 0.848) |
| Trouillas J. et al., 2013 [ |
Grade 1a: non-invasive tumour Grade 1b: non-invasive and proliferative tumour Grade 2a: invasive tumour Grade 2b: invasive and proliferative tumour Grade 3: metastatic tumour (cerebrospinal or systemic metastases) | Grading classification | Training (n = 410) | Invasion + proliferation (AUC = 81.4%); |
| Invasion + Ki-67 ≥ 3% (AUC = 81.4%) | ||||
| Proliferation without invasion (AUC = 0.713); | ||||
| Ki-67 ≥ 3% without invasion (AUC = 0.711) | ||||
| Wen L. et al., 2021 [ |
Age (HR = 0.50), Tumor size (HR = 11.06), CSI (HR = 7.53), SSI (HR = 13.14), GTR (HR = 0.12) | Nomogram | Training (n = 145) | AUC = 0.953 |
| A well-fitted calibration curve | ||||
| Chen Y. et al., 2021 [ |
Smoking history (HR = 3.10), BMI ≥ 25 kg/m2 (HR = 2.00), Knosp grade 4 (HR = 4.09), partial resection (HR = 3.72), Ki-67 ≥ 3% (HR = 4.64) | Nomogram | Training (n = 172) | AUC for 1-, 2-, and 3-year survival (0.889, 0.885 and 0.832, respectively) |
| Well-fitted calibration curves |
CSI: cavernous sinus invasion; HR: hazard ratio; OR: odds ratio; CI: confidence interval; AUC: area under the curve; PAs: pituitary adenomas; SSI: sphenoid sinus invasion; GTR: gross-total resection; BMI: body mass index.