IGSF10 (Immunoglobulin Superfamily Member 10)

Mechanistically, high expression of IGSF10 can inhibit the epithelial-mesenchymal transition of LUAD cells via p53-triggering ferroptosis and impede G1/S cell cycle transition of LUAD cells via the p53-p21 axis, leading to suppression of LUAD cell migration, growth and tumorigenic capacity. Our findings clarified the specific role of IGSF10 in LUAD, and theoretically suggested new avenues for the presumable IGSF10-targeting therapy of lung cancer in the future.

We show that the IGSF10-RET-GAS1-cdc42 pathway regulates migration of GnRH neurons and that IGSF10 mutants linked to delayed puberty are defective in RET-cdc42 regulation. These results reveal a critical role of IGSF10 as a RET antagonist in Ewing sarcoma and GnRH neurons.

In this study, four key biomarkers closely related to mesenchymal stem cell proliferation/differentiation (MSCPD) were identified in lung adenocarcinoma (LUAD), namely MS4A2, IGSF10, NTRK3, and MFAP3L. Through multi-omics integrated analysis and independent cohort validation, it was confirmed that these markers not only affect disease progression by regulating mesenchymal - epithelial transition (MET) and tumor microenvironment remodeling but can also effectively predict patient prognosis and response to immunotherapy.

This indicated that the model was reliable in separating BC patients from healthy individuals. The model may assist in early diagnosis of BC with implications for improving the prognosis of BC patients.

It was proven in a mechanistic sense that IGSF10 inhibits the capacity of LUAD cells to metastasize through the Spi-B/Integrin-β1 signaling pathway. These findings gave credence to the premise that IGSF10 performed a crucial function in LUAD.

Six of the signature genes, BSG/CD147, GNB2L1/RACK1, TXNDC5, FNPB1, B3GAT1, and IGSF10, play a role in cell differentiation. Our findings strongly suggest that the identified gene signature is a potential prognostic biomarker and therapeutic target for neuroblastoma patients and that it is associated with neuroblastoma cell differentiation through the activation of the NTRK1-PTPN6-TP53 module.

These subclasses of OPMDs have the potential to be used to stratify patient prognoses and therapeutic options for tongue OPMDs. Lastly, we identified a gene set (ELF5; RPTN; IGSF10; CRMP1; HTR3A) whose transcript changes have the power to classify OPMDs and SCCs and developed a Firth logistic regression model using the changes in these transcripts relative to paired normal tissue to validate pathological diagnosis and potentially predict the likelihood of an OPMD developing into SCC, as data sets become available.