Molecular profiling reveals the malignant potential in solid pseudopapillary neoplasms of the pancreas.

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Tác giả: Menghua Dai, Junchao Guo, Xianlin Han, Yuze Hua, Jorg Kleeff, Jiayi Li, Zhiyong Liang, Quan Liao, Qiaofei Liu, Junliang Lu, Boju Pan, Weibin Wang, Huanwen Wu, Qiang Xu, Taiping Zhang, Xiang Zhang, Huaijin Zheng, Liangrui Zhou

Ngôn ngữ: eng

Ký hiệu phân loại: 949.59012 *Greece

Thông tin xuất bản: Ireland : Cancer letters , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 746280

Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare tumor primarily affecting middle-aged women, typically characterized by indolent behavior but occasionally demonstrating malignant potential through invasive growth and metastasis. To elucidate the molecular mechanisms driving this heterogeneity, a multi-omics approach was applied to analyze paired metastatic lesions, primary tumors, and normal pancreatic tissues. Methylation profiling via the Illumina Infinium Methylation EPIC BeadChip identified 2425 differentially methylated positions (DMPs) in metastatic versus primary lesions, with 798 DMPs conserved across both lesion types. Tyrosine kinases and cGMP-PKG signaling pathway were the most significantly enriched KEGG pathways involved in the DMPs. Transcriptomic analysis of invasive and non-invasive SPNs using NanoString revealed 99 differentially expressed genes (DEGs). Immunohistochemical validation confirmed elevated protein expression of LY96, IFI16, and GLUD1 in invasive cases. Circulating free DNA (cfDNA) sequencing did not detect genetic mutation in non-metastatic SPN, in contrast, 42.9 % positivity of genetic mutations were detected in metastatic SPNs. Tumor microenvironment analysis by using the GEO database, 850 K methylation sequencing, NanoString transcriptome, highlighted enriched immune-suppressive stromal components in aggressive tumors. These findings establish a molecular signature linking methylation dysregulation, transcriptomic alterations, liquid biopsy, and immune evasion to SPN progression, offering potential biomarkers for risk stratification and therapeutic targeting.
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