A Potential Four-Gene Signature and Nomogram for Predicting the Overall Survival of Papillary Thyroid Cancer

Abstract

Background. Although the prognosis of papillary thyroid cancer (PTC) is relatively good, some patients experience recurrence or distant metastasis after thyroidectomy and progress to radioactive iodine refractory stage. Therefore, accurate prediction of clinical outlook can aid to screen out the minority of patients with poorer prognosis and avoid excessive treatment in low-risk patients. Methods. The RNA-seq and clinical data of PTC patients was downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Multivariate and Lasso Cox regression analyses were used to construct a prognostic nomogram to predict overall survival (OS). Thereafter, quantitative RT-PCR and Human Protein Atlas (HPA) database were employed to verify the expression of key genes. Results. A four-gene risk score comprising ABI3BP, DPT, MRO, and TENM1 was exhibited strong prognostic value. Moreover, an integrated nomogram was established based on the risk score, age, AJCC (American Joint Commission on Cancer) stage, tumor size, extrathyroidal extension, and history of neoadjuvant treatment, which exhibited significantly better predictive performance than TNM stage system ( P < 0.05 ). GSEA (Gene Set Enrichment Analysis) and GSVA (Gene Set Variation Analysis) revealed that the different tumor-associated hallmarks, biological processes, and pathways were substantially enriched in the poor-prognosis group. In addition, a ceRNA network was constructed by including the four genes (ABI3BP, DPT, MRO, and TENM1), 54 lncRNAs, and 10 miRNAs. Finally, both the relative mRNA and protein expression of ABI3BP, DPT, MRO, and TENM1 were validated. Conclusion. The present study identified a four-gene risk signature and developed a novel nomogram, which could be regarded as a reliable prognostic model for PTC patients. The findings also revealed preliminary potential mechanisms that may influence the prognosis outcome. These results can be conducive to design personalized treatment and prognosis management in affected patients.

The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature

“…ABI family member 3 binding protein (ABI3BP) is an ECM protein expressed in multiple organs, including the heart, kidney, lung, pancreas, and placenta, with low or variable expression in the spleen, liver, brain, bone, and skeletal muscle ( 98 ). ABI3BP expression has been associated with many physiological and pathological processes ( 99 ), and it is well known for its role in multiple cancer types, acting as a tumor suppressor by inhibiting cancer cell proliferation and migration and promoting cellular senescence ( 100 – 104 ). The role of ABI3BP in lung cancer has been investigated only recently and it has been indicated that this molecule is downregulated in the lesions compared to normal lung tissue and it gradually decreases as lung cancer progresses ( 28 ).…”

Construction of a nomogram for predicting HNSCC distant metastasis and identification of EIF5A as a hub gene

“…While numerous studies have developed lncRNA-related nomogram models to predict tumor development and progression, the majority have focused on predicting early-stage micrometastasis 21 , 22 . Our research, however, is primarily focused on the distant metastasis of HNSCC.…”

Construction and validation of a PANoptosis-related lncRNA signature for predicting prognosis and targeted drug response in thyroid cancer

“…A calibration curve was used to test the agreement between the actual results and model predictions according to the Hosmer–Lemeshow test. To compare the accuracy, we calculated the consistency index (c-index) and restricted mean survival (RMS) of the published models ( Guo et al, 2022 ; Qin et al, 2022 ; Ding et al, 2022 ; Liu et al, 2022 ; Shan et al, 2022 ) and the model we developed.…”