The prevalence of Anaplastic Lymphoma Kinase gene () fusion is about 5% among patients with lung adenocarcinoma, underscoring the importance of pinpointing distinct fusion variants for optimizing treatment approaches. This is the first reported case of a 74-year-old female with stage IV lung adenocarcinoma, featuring a novel Kinesin Family Member 13A () fusion, identified via next-generation sequencing (NGS) and confirmed with fluorescence hybridization (FISH). Initially undergoing chemotherapy and then crizotinib, she achieved a partial response (PR) before progressing with multiple bone metastases. However, subsequent treatment with alectinib as a third-line option yielded positive results. A stable disease state persisted for an impressive 31 months of progression-free survival (PFS), accompanied by minimal toxicity symptoms. Up until now, a remarkable near 4-year span of overall survival (OS) has been consistently observed and monitored. This report of a fusion case benefit significantly from alectinib with extensive follow-up. The case diversifies the array of fusion partners and holds clinical relevance in refining therapeutic choices for fusion-associated lung cancer.
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http://dx.doi.org/10.3389/fgene.2023.1289346 | DOI Listing |
Anticancer Drugs
January 2025
Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning.
Uncommon atypical mutations account for 10-15% of all epidermal growth factor receptor (EGFR) activating mutations in nonsmall-cell lung cancer (NSCLC). Tumors harboring rare EGFR mutations show highly heterogeneous responses to EGFR tyrosine kinase inhibitors (TKIs). There is insufficient clinical evidence for uncommon types of EGFR mutations, especially those with compound EGFR mutations.
View Article and Find Full Text PDFProceedings (IEEE Int Conf Bioinformatics Biomed)
December 2024
Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, USA.
Lung cancer remains a predominant cause of cancer-related deaths, with notable disparities in incidence and outcomes across racial and gender groups. This study addresses these disparities by developing a computational framework leveraging explainable artificial intelligence (XAI) to identify both patient- and cohort-specific biomarker genes in lung cancer. Specifically, we focus on two lung cancer subtypes, Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC), examining distinct racial and sex-specific cohorts: African American males (AAMs) and European American males (EAMs).
View Article and Find Full Text PDFFront Public Health
January 2025
School of Public Health, Gansu University of Chinese Medicine, Lanzhou, China.
Objective: To investigate the role of PCBP1 in the inhibition of lung adenocarcinoma proliferation by carbon irradiation.
Methods: A549 cells were irradiated with different doses of carbon ions to observe clonal survival and detect changes in cell proliferation. Whole transcriptome sequencing and the Illumina platform were used to analyze the differentially expressed genes in A549 cells after carbon ion irradiation.
Front Oncol
January 2025
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Objective: To develop and validate a deep learning signature for noninvasive prediction of spread through air spaces (STAS) in clinical stage I lung adenocarcinoma and compare its predictive performance with conventional clinical-semantic model.
Methods: A total of 513 patients with pathologically-confirmed stage I lung adenocarcinoma were retrospectively enrolled and were divided into training cohort (n = 386) and independent validation cohort (n = 127) according to different center. Clinicopathological data were collected and CT semantic features were evaluated.
Front Oncol
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Purpose: To develop and validate a radiomics nomogram model for predicting the micropapillary pattern (MPP) in lung adenocarcinoma (LUAD) tumors of ≤2 cm in size.
Methods: In this study, 300 LUAD patients from our institution were randomly divided into the training cohort (n = 210) and an internal validation cohort (n = 90) at a ratio of 7:3, besides, we selected 65 patients from another hospital as the external validation cohort. The region of interest of the tumor was delineated on the computed tomography (CT) images, and radiomics features were extracted.
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