KEGANG JIA^1,#, YAWEI WANG^2,#, QI CAO^3,*, YOUYU WANG^1,*

Oncology Research, Vol.32, No.2, pp. 409-419, 2024, DOI:10.32604/or.2023.042863

Abstract Background: Lung cancer is the most prevalent cancer diagnosis and the leading cause of cancer death worldwide. Therapeutic failure in lung cancer (LUAD) is heavily influenced by drug resistance. This challenge stems from the diverse cell populations within the tumor, each having unique genetic, epigenetic, and phenotypic profiles. Such variations lead to varied therapeutic responses, thereby contributing to tumor relapse and disease progression. Methods: The Genomics of Drug Sensitivity in Cancer (GDSC) database was used in this investigation to obtain the mRNA expression dataset, genomic mutation profile, and drug sensitivity information of NSCLS. Machine Learning (ML) methods, including Random Forest… More >

LIHUA CHEN^1,2,#, HONGTIAN ZHANG^1,2,#, YONG XIA^1,2, KAI SUN¹, WENJIN CHEN¹, RUXIANG XU^1,2,*

BIOCELL, Vol.47, No.5, pp. 1065-1073, 2023, DOI:10.32604/biocell.2023.025924

Abstract Purpose: The present study summarized cases of children (n = 32) with medulloblastoma (MB) who were treated using stratified therapy based on risk grading and also discussed the factors affecting prognosis. Methods: According to the risk stratification criteria, the cases were divided into the following four risk groups: low, standard, high, and very high. The 5-year overall survival (OS) and progression-free survival (PFS) rates were summarized. Further, the effects on the prognosis of tumor size, tumor stage, degree of resection, treatment mode, metastatic recurrence, molecular typing, and risk stratification were analyzed. Results: In the present study, following surgery, 3 cases… More >