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This study aims to evaluate the predictive value of proteome profiling for brain metastasis in limited-stage small-cell lung cancer
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Small-cell lung cancer (SCLC) constitutes approximately 15% of all lung cancer cases and is characterized by a highly aggressive disease course and poor prognosis. The brain is the most common metastatic site of SCLC, and it is also an important cause of high mortality. More than 20% of SCLC patients have developed brain metastasis (BM) at the first diagnosis. Prophylactic cranial irradiation (PCI), as an essential part of the treatment of limited-stage small-cell lung cancer (LS-SCLC), inevitably leads to neurotoxicity. Therefore, there is an urgent need for a convenient and effective prediction model to realize the early prediction of SCLC brain metastasis. Patients at high risk of brain metastases were treated with individualized PCI.
In the current study, the investigators have analyzed the proteome profiling using Data-independent Acquisition mass spectrometry (DIA-MS) method in formalin-fixed paraffin-embedded (FFPE) tissues from patients with limited-stage small-cell lung cancer. The prognostic biomarkers were developed based on machine learning in the non-PCI group. Patients in the non-PCI group were classified into modeling cohort and external validation cohort . Furthermore, the prognostic value of the candidate biomarkers be evaluated in a prospective cohort . Based on the brain metastasis model, patients were divided into high- and low-risk groups. The benefit value of PCI was analyzed in high-risk and low-risk groups.
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228 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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