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 >

HONGYUAN LIANG^1,#, YANQIU LI^2,#, YONGGANG QU³, LINGYUN ZHANG^4,*

Oncology Research, Vol.32, No.2, pp. 393-407, 2024, DOI:10.32604/or.2023.031134

Abstract Advanced LUAD shows limited response to treatment including immune therapy. With the development of sequencing omics, it is urgent to combine high-throughput multi-omics data to identify new immune checkpoint therapeutic response markers. Using GSE72094 (n = 386) and GSE31210 (n = 226) gene expression profile data in the GEO database, we identified genes associated with lung adenocarcinoma (LUAD) death using tools such as “edgeR” and “maftools” and visualized the characteristics of these genes using the “circlize” R package. We constructed a prognostic model based on death-related genes and optimized the model using LASSO-Cox regression methods. By calculating the cell death… More >

Hassen Louati^1,2, Ali Louati^3,*, Elham Kariri³, Slim Bechikh²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2519-2547, 2024, DOI:10.32604/cmes.2023.030806

Abstract Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression of a convolutional neural network… More >

ZHONGXIANG TANG^1,2, LILI WANG^1,2, GUOJUN WU^1,2, LING QIN^1,2,*, YURONG TAN^1,2,*

BIOCELL, Vol.47, No.11, pp. 2503-2516, 2023, DOI:10.32604/biocell.2023.031565

Abstract Background: Non-small cell lung cancer (NSCLC) has a poor prognosis with a low 5-year survival rate. Lung adenocarcinoma (LUAD) accounts for 50%. Facio-genital dysplasia-5 (FGD5), a member of a subfamily of Rho GTP-GDP exchange factors, may be a good molecular biomarker for diagnosis and prognosis. Objective: To explore the clinical application of FGD5, the study was designed to investigate the prognosis value of FGD5 expression and its correlation with immune infiltrates in LUAD patients. Methods: Through the Wilcoxon signed-rank test and logistic regression, the correlation between clinical characteristics and FGD5 expression was analyzed. Kaplan–Meier plotter analysis, Cox regression, and a… More > Graphic Abstract

HAOSHENG ZHENG^1,#, RUIJUN LIN^2,#, WEIJIE CAI¹, YUZHEN ZHENG¹, XINGPING YANG¹, ZUI LIU¹, FEI QIN¹, YONGJIE CAI³, XIANYU QIN^1,*, HONGYING LIAO^1,*

BIOCELL, Vol.47, No.11, pp. 2453-2469, 2023, DOI:10.32604/biocell.2023.030032

Abstract Introduction: The difficulty in treating lung adenocarcinoma (LUAD) is caused by a shortage of knowledge about the biological mechanisms and a lack of treatment choices. Objectives: The aim of this study was to identify a valuable molecular target for the treatment of LUAD. Methods: Using multiple databases, we screened for hub genes in LUAD using Cytoscape and explored the expression and prognosis of DLG associated protein 5 (DLGAP5) in LUAD. We investigated the genetic variation, functional enrichment, and epigenetic activity of DLGAP5. Furthermore, we evaluated the relationship between the tumor microenvironment (TME) and DLGAP5. Results: Our study identified 10 hub… More > Graphic Abstract

HEE JU SONG, TAEHEE KIM, HAN NA CHOI, SOO JIN KIM, SANG DO LEE^*

Oncology Research, Vol.32, No.1, pp. 151-161, 2024, DOI:10.32604/or.2023.030690

Abstract Lung cancer has the highest mortality rate among all cancers, in part because it readily metastasizes. The tumor microenvironment, comprising blood vessels, fibroblasts, immune cells, and macrophages [including tumor-associated macrophages (TAMs)], is closely related to cancer cell growth, migration, and invasion. TAMs secrete several cytokines, including interleukin (IL)-1β, which participate in cancer migration and invasion. p21-activated kinase 1 (PAK1), an important signaling molecule, induces cell migration and invasion in several carcinomas. Tonicity-responsive enhancer-binding protein (TonEBP) is also known to participate in cancer cell growth, migration, and invasion. However, the mechanisms by which it increases lung cancer migration remain unclear. Therefore,… More > Graphic Abstract

HENG LI^1,#, YOUMING LEI^3,#, GAOFENG LI¹, YUNCHAO HUANG^2,*

Oncology Research, Vol.32, No.1, pp. 187-197, 2024, DOI:10.32604/or.2023.030656

Abstract Lung cancer is a prevalent malignancy, and fatalities of the disease exceed 400,000 cases worldwide. Lung squamous cell carcinoma (LUSC) has been recognized as the most common pathological form of lung cancer. The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management. In this study, we aim to identify a panel of signature genes closely associated with LUSC, which can provide novel insights into the progression of LUSC. Gene expression profiles were retrieved from public resources including gene expression omnibus (GEO) and the cancer genome atlas (TCGA) database. Differentially expressed… More >

QIUQIANG CHEN^1,*, XIAOLEI ZHAO², WENXUE MA^3,*

Oncology Research, Vol.32, No.1, pp. 95-98, 2024, DOI:10.32604/or.2023.046174

Abstract Greenblatt and his team have unveiled vertebral skeletal stem cells (vSSCs) as a critical player in the landscape of bone metastasis. This commentary delves into the transformative discoveries surrounding vSSCs, emphasizing their distinct role in bone metastasis compared to other stem cell lineages. We illuminate the unique properties and functions of vSSCs, which may account for the elevated susceptibility of vertebral bones to metastatic invasion. Furthermore, we explore the exciting therapeutic horizons opened by this newfound understanding. These include potential interventions targeting vSSCs, modulation of associated signaling pathways, and broader implications for the treatment and management of bone metastasis. By… More > Graphic Abstract

Shazia Shamas¹, Surya Narayan Panda^1,*, Ishu Sharma^1,*, Kalpna Guleria¹, Aman Singh^2,3,4, Ahmad Ali AlZubi⁵, Mallak Ahmad AlZubi⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

CHUNYANG XU^1,#, CAIYUN YANG^1,#, JINSONG ZHANG², XIAOHUA PAN³, JUN WANG⁴, LEI JIANG², HONGWEI YE^1,*, BO CHEN^1,*

BIOCELL, Vol.47, No.9, pp. 2027-2035, 2023, DOI:10.32604/biocell.2023.029277

Abstract Background: The lung is one of the primary target organs of hydrogen sulfide (H₂S), as exposure to H₂S can cause acute lung injury (ALI) and pulmonary edema. Dexamethasone (Dex) exerts a protective effect on ALI caused by exposure to toxic gases and is commonly used in the clinic; however, the underlying mechanisms remain elusive, and the dose is unclear. Methods: In vivo experiments: divided C57BL6 mice into 6 groups at random, 12 in each group. The mice were exposed to H₂S for 3 h and 5 or 50 mg/kg Dex pretreated before exposure, sacrificed 12 h later. The morphological changes… More >