Identification of prognostic and bone metastasis​-related alternative splicing signatures in mesothelioma

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Mesothelioma (MESO) has a poor prognosis despite advances in understanding tumor progression.
• Alternative splicing events (ASEs) play roles in oncogenesis, metastasis, and drug resistance in various cancers.
• The prognostic and therapeutic significance of ASEs in MESO remains largely unstudied.

Purpose of the Study:

• To construct a prognostic model for mesothelioma using alternative splicing events.
• To identify key splicing factors and their associated splicing events in mesothelioma.
• To explore the role of specific splicing events in mesothelioma metastasis, particularly bone metastasis.

Main Methods:

• Utilized RNA sequencing and alternative splicing data from TCGA and TCGASpliceSeq databases for mesothelioma patients.
• Applied Cox and lasso regression analyses to identify survival-associated ASEs and build a prognostic model.
• Performed co-expression analysis and Gene Set Variation Analysis (GSVA) to investigate signaling pathways and splicing factor interactions.

Main Results:

• A total of 3,993 ASEs were initially identified as associated with overall survival (OS).
• An eight-ASE prognostic model was developed, demonstrating independent predictive power for patient prognosis.
• Splicing factor HSPA1A was significantly associated with specific OS-ASEs, including SNX5-58744-AT and SNX5-58745-AT, which were linked to bone metastasis.

Conclusions:

• The developed prognostic model effectively predicts mesothelioma patient survival based on ASEs.
• Splicing factor HSPA1A may regulate mesothelioma tumorigenesis and bone metastasis through specific ASEs and the Class I MHC signaling pathway.
• This research highlights the potential of targeting ASEs for mesothelioma treatment and understanding metastasis.