WEI ZHAI^1,2, XIANG ZHENG², MENGYUAN LIU², QIURONG ZHAO², YUSHU ZHANG², YUQING LUO³, SHANSHAN FENG³, JINJING WANG³, XUEYING LI^2,*, MINGSONG WU^1,*

BIOCELL, Vol.47, No.8, pp. 1821-1833, 2023, DOI:10.32604/biocell.2023.027175 - 28 August 2023

Abstract Objective: Endoplasmic reticulum-Golgi intermediate compartment 3 (ERGIC3) promotes cell proliferation and metastasis in lung cancer, but its molecular mechanism is unclear. Methods: The GLC-82 cells were randomly divided into the ERGIC3i group and the negative control group. The cells were transfected with ERGIC3 siRNA or control siRNA in the groups, respectively. The ERGIC3-interacting proteins expressed in cells or extracellularly were isolated by the immunoprecipitation method and detected by isobaric tags for relative and absolute quantitation and liquid chromatography-tandem mass spectrometry. The differentially expressed proteins were determined by bioinformatic methods. Results: After ERGIC3 knockdown, 88 extracellular differentially… More >

Sindhuja Manickavasagam^*, Poonkuzhali Sugumaran

Computer Systems Science and Engineering, Vol.47, No.1, pp. 135-151, 2023, DOI:10.32604/csse.2023.030344 - 26 May 2023

Abstract Cancer disease is a deadliest disease cause more dangerous one. By identifying the disease through Artificial intelligence to getting the mage features directly from patients. This paper presents the lung knob division and disease characterization by proposing an enhancement calculation. Most of the machine learning techniques failed to observe the feature dimensions leads inaccuracy in feature selection and classification. This cause inaccuracy in sensitivity and specificity rate to reduce the identification accuracy. To resolve this problem, to propose a Chicken Sine Cosine Algorithm based Deep Belief Network to identify the disease factor. The general technique… More >

LU LIU^1,2, BIN XIE^1,2, WEI ZHU^1,2, QIUYAN HE^1,2, JIANHUA ZHOU^1,2, SHUANG LIU³, YONGGUANG TAO⁴, DESHENG XIAO^1,2,*

Oncology Research, Vol.31, No.3, pp. 275-286, 2023, DOI:10.32604/or.2023.028227 - 22 May 2023

Abstract Background: Lung cancer is one of the most lethal cancers worldwide, but studies have shown that the higher the expression of programmed cell death protein 1 ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC), the more likely it will benefit from anti-PD-L1 immunotherapy. The purpose of our study was to collect and analyze abundant clinical samples in order to provide evidence for clinicians and patients who might consider anti-PD-L1 immunotherapy while jointly formulating treatment plans. Methods: On the one hand, we obtained cases from The Cancer Genome Atlas (TCGA) database, including 498 lung squamous… More >

YANGYI HE^1,2, DAVID SANCHEZ-LORENTE^3,4,5, MELISSA ACOSTA-PLASENCIA¹, MARC BOADA^3,4,5, ANGELA GUIRAO^3,4,5, RAMON M. MARRADES^4,5,6,7, LAUREANO MOLINS^3,4,5, ALFONS NAVARRO^1,4,5,*

BIOCELL, Vol.47, No.5, pp. 951-957, 2023, DOI:10.32604/biocell.2023.027718 - 10 April 2023

Abstract Tumor-secreted extracellular vesicles (EVs) participate in the metastasis process through different mechanisms, including the preparation of the pre-metastatic niche to grant circulating tumor cells (CTCs) implantation and growth. The study of the metastasis process through the analysis of CTCs and tumor-derived EVs is difficult because of the dilution grade of these elements in peripheral blood. In early-stage lung cancer patients, the tumor-secreted products are even more diluted. An attractive strategy in surgical lung cancer patients is to purify them from a pulmonary tumor-draining vein where they are enriched. The information obtained from the analysis of More >

SANDRA STICKLER¹, BARBARA RATH¹, MAXIMILIAN HOCHMAIR², CLEMENS LANG³, LUKAS WEIGL⁴, GERHARD HAMILTON^1,*

Oncology Research, Vol.31, No.1, pp. 13-22, 2023, DOI:10.32604/or.2022.027281 - 01 March 2023

Abstract Small cell lung cancer (SCLC) is frequently disseminated and has a dismal prognosis with survival times of approximately two years. This cancer responds well to initial chemotherapy but recurs within a short time as a globally chemoresistant tumor. Circulating tumor cells (CTCs) are held responsible for metastasis, the extremely high numbers of these cells in advanced SCLC allowed us to establish several permanent CTC cell lines. These CTCs are distinguished by the spontaneous formation of large spheroids, termed tumorospheres, in regular tissue culture. These contain quiescent and hypoxic cells in their interior and are associated… More >

Debnath Bhattacharyya¹, Eali. Stephen Neal Joshua², N. Thirupathi Rao², Yung-cheol Byun^3,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1447-1465, 2023, DOI:10.32604/cmc.2023.031878 - 06 February 2023

Abstract Lung cancer is the leading cause of mortality in the world affecting both men and women equally. When a radiologist just focuses on the patient’s body, it increases the amount of strain on the radiologist and the likelihood of missing pathological information such as abnormalities are increased. One of the primary objectives of this research work is to develop computer-assisted diagnosis and detection of lung cancer. It also intends to make it easier for radiologists to identify and diagnose lung cancer accurately. The proposed strategy which was based on a unique image feature, took into… More >

Ahmed A. Alsheikhy^1,*, Yahia F. Said¹, Tawfeeq Shawly²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 799-817, 2023, DOI:10.32604/csse.2023.035269 - 20 January 2023

Abstract Lung cancer is the leading cause of cancer-related death around the globe. The treatment and survival rates among lung cancer patients are significantly impacted by early diagnosis. Most diagnostic techniques can identify and classify only one type of lung cancer. It is crucial to close this gap with a system that detects all lung cancer types. This paper proposes an intelligent decision support system for this purpose. This system aims to support the quick and early detection and classification of all lung cancer types and subtypes to improve treatment and save lives. Its algorithm uses… More >

P. S. Ramapraba^1,*, P. Epsiba², K. Umapathy³, E. Sivanantham⁴

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2177-2189, 2023, DOI:10.32604/iasc.2023.032040 - 05 January 2023

Abstract The classification of lung nodules is a challenging problem as the visual analysis of the nodules and non-nodules revealed homogenous textural patterns. In this work, an Auxiliary Classifier (AC)-Generative Adversarial Network (GAN) based Lung Cancer Classification (LCC) system is developed. The proposed AC-GAN-LCC system consists of three modules; preprocessing, Lungs Region Detection (LRD), and AC-GAN classification. A Wiener filter is employed in the preprocessing module to remove the Gaussian noise. In the LRD module, only the lung regions (left and right lungs) are detected using iterative thresholding and morphological operations. In order to extract the… More >

YUANYUAN HUANG^#, HONGMEI WU^#, RUYUAN LIU, SONG JIN, WEILAI XIANG, CHANG YANG, LI XU, XIAONIAN ZHU^*

BIOCELL, Vol.47, No.3, pp. 445-454, 2023, DOI:10.32604/biocell.2023.025880 - 03 January 2023

Abstract The tripartite motif (TRIMs) protein family has E3 ubiquitin ligase activity among most of its members. They participate in multiple cellular processes and signaling pathways in living organisms, including cell cycle, growth, and metabolism, and mediate chromatin modification, transcriptional regulation, post-translational modification, and cellular autophagy. Previous studies have confirmed that the TRIMs protein family is involved in the development of various cancers and correlated with the prognosis of tumor patients. Here we summarize the biological roles of the TRIMs protein family in cancers. More >

K. Jagadeesh^1,*, A. Rajendran²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2017-2032, 2023, DOI:10.32604/csse.2023.029169 - 03 November 2022

Abstract Lung Cancer is one of the hazardous diseases that have to be detected in earlier stages for providing better treatment and clinical support to patients. For lung cancer diagnosis, the computed tomography (CT) scan images are to be processed with image processing techniques and effective classification process is required for appropriate cancer diagnosis. In present scenario of medical data processing, the cancer detection process is very time consuming and exactitude. For that, this paper develops an improved model for lung cancer segmentation and classification using genetic algorithm. In the model, the input CT images are More >