Establishing a metastasis-related diagnosis and prognosis model for lung adenocarcinoma through CRISPR library and TCGA database

Abstract

Purpose: Existing biomarkers for diagnosing and predicting the metastasis of lung adenocarcinoma (LUAD) may not meet the demands of clinical practice. Risk prediction models based on multiple markers may provide better prognostic factors for accurate diagnosis and prediction of metastatic LUAD.Methods: An animal model of LUAD metastasis was constructed using CRISPR library technology, and genes related to LUAD metastasis were screened by mRNA sequencing of normal and metastatic tissues.The immune characteristics of different subtypes were analyzed, and the differential genes were subjected to survival and Cox regression analysis to identify the speci c genes for metastasis. The biological function of RFLNA was rst veri ed by analyzing cck-8, migration, invasion and apoptosis in LUAD cell lines.Results: We identi ed 108 differential genes related to metastasis, and classi ed LUAD samples into two subtypes according to their expression levels. Subsequently, a prediction model composed of 8 metastasis-related genes (RHOBTB2, KIAA1524, CENPW, DEPDC1, RFLNA, COL7A1, MMP12 and HOXB9) was constructed. The AUC values of the logistic regression and neural network were 0.946 and 0.856, respectively. Moreover, the model can effectively classify patients into low-and high-risk groups. We found a better prognosis in the low-risk group both in the training cohort and test cohort, indicating that the prediction model has good diagnosis and predictive power. Up-regulation of RFLNA expression successfully promoted cell proliferation, migration, invasion, and attenuated apoptosis, suggesting that RFLNA plays a role in promoting LUAD development and metastasis. Conclusion:The model has important diagnostic and prognostic value for metastatic LUAD, and may serve as a novel biomarker for LUAD patients in clinic.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters

“…(2) Exclusion criteria: Patients with pneumonia, advanced liver disease, and severely abnormal liver function before treatment; patients with severe blood and immune system diseases before treatment and patients with other tumor diseases. Tumor metastasis: non-metastatic (0), metastasis to one organ (1), metastasis to two organs (2), and metastasis to three or more organs (3).…”

“… 2 Many clinical studies have found that LC patients must achieve “three early”, that is, early detection, early diagnosis, and early treatment, in order to achieve good therapeutic results. 3 , 4 However, the prognosis for most LC patients is still very poor. This is mainly because the early symptoms of LC are not obvious and have been overlooked by patients, while when patients enter the hospital, about 75% of patients are already in the late stage of LC, and the prognosis of the late stage is relatively poor.…”