Wenliang Liu^*, Peng Xiao^†, Han Wu^*, Li Wang^*, Demiao Kong^*, Fenglei Yu^*

Oncology Research, Vol.28, No.7-8, pp. 829-829, 2020, DOI:10.3727/096504021X16207253542097

Abstract This article has no abstract. More >

Xiangbin Tan^*1, Zefei Liao^†1, Shuangyou Zou^*, Liangyun Ma^†, Aimin Wang^*

Oncology Research, Vol.28, No.1, pp. 3-11, 2020, DOI:10.3727/096504019X15509383469698

Abstract Vasohibin2 (VASH2), a proangiogenic factor, has been demonstrated to play an oncogenic role in some common human cancers. However, the detailed function of VASH2 in non-small cell lung cancer (NSCLC) has not previously been studied. In this study, we found that VASH2 was significantly upregulated in NSCLC tissues and cell lines, and its increased expression was associated with NSCLC progression and poor prognosis of patients. Knockdown of VASH2 markedly inhibited cell proliferation and P-glycoprotein expression in NSCLC cells. Overexpression of VASH2 enhanced cell proliferation, P-glycoprotein expression, as well as doxorubicin resistance in NSCLC cells. Moreover, the expression levels of VASH2… More >

Yudie Yang^*1, Xia Zhang^†1, Yajie Gao^*, Yan Dong^*, Di Wang^*, Yanping Huang^*, Tianhao Qu^*, Buqun Fan^*, Qizheng Li^*, Chunxia Zhang^*, Xiaonan Cui^*, Bin Zhang^*

Oncology Research, Vol.29, No.1, pp. 63-74, 2021, DOI:10.3727/096504022X16462176651719

Abstract Lung cancer is a malignant tumor with high incidence and mortality across the world. The use of immune checkpoint inhibitors for lung cancer has improved the prognosis of some lung cancer patients to a greater extent and provided a new direction for the clinical treatment of lung cancer. Immunotherapy still has limitations in terms of its appropriate population and adverse reactions. Particularly for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation, there has been no major breakthrough in current immunotherapy. Whether immunotherapy can bring new benefits after drug resistance is induced by tyrosine kinase inhibitor-targeted… More >

A. Alice Blessie^1,*, P. Ramesh²

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1467-1484, 2023, DOI:10.32604/csse.2023.025399

Abstract The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medical field. In that case, the image processing is performed to improve the image data, wherein it inhibits unintended distortion of image features or it enhances further processing in various applications and fields. This helps to show better results especially for diagnosing diseases. Of late the early prediction of cancer is necessary to prevent disease-causing problems. This work is proposed to identify lung cancer using lung computed tomography (CT) scan images. It helps to identify cancer cells’ affected areas. In the… More >

Yicheng Xie^1,*, Jinyue Xia²

Journal of Intelligent Medicine and Healthcare, Vol.1, No.1, pp. 43-54, 2022, DOI:10.32604/jimh.2022.032405

Abstract Lung cancer is now the most common type of cancer worldwide, with high levels of morbidity and mortality. The cost of treatment and emotional stress put a high burden on families and society. This paper aims to collect relevant information and provide predictive analysis for the prognosis of patients with lung cancer. Using the public data of SEER database and the method of machine learning, a model is constructed to predict the five-year survival of patients with lung cancer. The re-coding method is used for data processing, the eigenvalues are re-coded to adapt to the construction of the model, and… More >

Mahmoud Ragab^1,2,3,*, Hesham A. Abdushkour⁴, Alaa F. Nahhas⁵, Wajdi H. Aljedaibi⁶

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 533-546, 2022, DOI:10.32604/cmc.2022.028856

Abstract Lung cancer is the main cause of cancer related death owing to its destructive nature and postponed detection at advanced stages. Early recognition of lung cancer is essential to increase the survival rate of persons and it remains a crucial problem in the healthcare sector. Computer aided diagnosis (CAD) models can be designed to effectually identify and classify the existence of lung cancer using medical images. The recently developed deep learning (DL) models find a way for accurate lung nodule classification process. Therefore, this article presents a deer hunting optimization with deep convolutional neural network for lung cancer detection and… More >

Mohammad Alamgeer¹, Hanan Abdullah Mengash², Radwa Marzouk², Mohamed K Nour³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Abu Sarwar Zamani⁴, Mohammed Rizwanullah⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1437-1448, 2022, DOI:10.32604/cmc.2022.027896

Abstract Early detection of lung cancer can help for improving the survival rate of the patients. Biomedical imaging tools such as computed tomography (CT) image was utilized to the proper identification and positioning of lung cancer. The recently developed deep learning (DL) models can be employed for the effectual identification and classification of diseases. This article introduces novel deep learning enabled CAD technique for lung cancer using biomedical CT image, named DLCADLC-BCT technique. The proposed DLCADLC-BCT technique intends for detecting and classifying lung cancer using CT images. The proposed DLCADLC-BCT technique initially uses gray level co-occurrence matrix (GLCM) model for feature… More >

R. Vidhya^1,*, T. T. Mirnalinee²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 911-925, 2022, DOI:10.32604/iasc.2022.025060

Abstract Computer tomography (CT) scan images can provide more helpful diagnosis information regarding the lung cancers. Many machine learning and deep learning algorithms are formulated using CT input scan images for the improvisation in diagnosis and treatment process. But, designing an accurate and intelligent system still remains in darker side of the research side. This paper proposes the novel classification model which works on the principle of fused features and optimized learning network. The proposed framework incorporates the principle of saliency maps as a first tier segmentation, which is then fused with deep convolutional neural networks to improve the classification maps… More >

Hangxing Wang^1,#, Jingyun Fang^1,#, Yujiao Wang^2,#, Shuo Li², Zirui Wang², Wei He², Nan Wang¹, Shuang Luo¹, Huimei Zou^3,*, Fan Zhang^4,5,*

Oncologie, Vol.24, No.1, pp. 65-83, 2022, DOI:10.32604/oncologie.2022.021863

Abstract Lung cancer is the most common malignant tumor with the highest morbidity and mortality in the world, and non-small cell lung cancer (NSCLC) accounts for the vast majority of cases. At present, its main treatment methods are still traditional surgery, radiotherapy and chemotherapy, with disadvantages such as a high recurrence rate and limited effectiveness. Therefore, a new, better treatment method is urgently needed. Gene editing technology, as a new genetic engineering approach, has shown great potential in gene research, gene therapy and genetic improvement. It has also emerged as a promising treatment for lung cancer. This paper reviews the current… More >

YANYAN LI¹, SHAHANAVAJ KHAN^2,3,4, ANIS AHMAD CHAUDHARY⁵, HASSAN AHMED RUDAYNI⁵, ABDUL MALIK², ASHWAG SHAMI⁶

BIOCELL, Vol.46, No.1, pp. 87-95, 2022, DOI:10.32604/biocell.2022.016509

Abstract Available reports have confirmed a link between bacterial infection and the progression of different types of cancers, including colon, lungs, and prostate cancer. Here we report the Chlamydia pneumonia proteins targeting in endoplasmic reticulum (ER) using in-silico approaches and their possible role in lung cancer etiology. We predicted 48 proteins that target human ER, which may be associated with protein folding and protein-protein interactions during infection. The results showed C. pneumoniae proteins targeting human ER and their implications in lung cancer growth. These targeted proteins may be involved in competitive interactions between host and bacterial proteins, which may change the… More >