Oncology Research Editorial Office

Oncology Research, Vol.33, No.3, pp. 733-733, 2025, DOI:10.32604/or.2024.056906 - 28 February 2025

Abstract This article has no abstract. More >

DAIEN ZHOU^1,#, HAOYANG YUAN^2,#, YIWEI HU³, CHUXU WANG¹, SA GE¹, KOUFENG SHAO⁴, HONGYING WANG¹, XIAOFENG TIAN^1,*, HAIBO HU^1,*

Oncology Research, Vol.33, No.3, pp. 653-663, 2025, DOI:10.32604/or.2024.050182 - 28 February 2025

Abstract Background: Despite the identification of numerous therapeutic targets in lung cancer, achieving significant efficacy has been challenging. TNFRSF21 plays an important role in various cancers. We investigated the function of TNFRSF21 in lung adenocarcinoma (LUAD). Methods: The prognostic value of TNFRSF21 expression in lung cancer was evaluated by the GEPIA and Kaplan-Meier Plotter databases. Lung cancer cell viability was assessed by the CCK8 assay. TNFRSF21 expression patterns in lung cancer tissues and cells were examined using RT-PCR assay. Tumor sphere growth was evaluated through tumor sphere formation assays. MtROS contents in lung cancer cells were… More >

TAO SUN^1,2, QINGHUA SONG³, HUA LIU^1,*

Oncology Research, Vol.33, No.1, pp. 133-148, 2025, DOI:10.32604/or.2024.054141 - 20 December 2024

Abstract Background: Lung cancer is a life-threatening disease that occurs worldwide, but is especially common in China. The crucial role of the tumour microenvironment (TME) in non-small cell lung cancer (NSCLC) has attracted recent attention. Cancer-associated fibroblasts (CAFs) are the main factors that contribute to the TME function, and CAF exosomes are closely linked to NSCLC. Methods: The expression levels of miR-3124-5p and Toll-interacting protein (TOLLIP) were analysed by bioinformatics prediction combined with RT-qPCR/Western Blot detection. Fibroblasts were isolated and identified from clinical NSCLC tissues. Transmission electron microscopy and Western Blot were used to identify exosomes… More >

ENRICO CALIMAN^1,2, SARA FANCELLI^1,2, FEDERICO SCOLARI³, ADRIANO PASQUI⁴, CLARA MANNESCHI⁴, DANIELE LAVACCHI¹, FRANCESCA MAZZONI⁴, FRANCESCA GENSINI⁵, VALERIA PASINI⁶, CAMILLA EVA COMIN^2,7, LUCA VOLTOLINI^2,8, SERENA PILLOZZI^1,2,*, LORENZO ANTONUZZO^1,2,4

Oncology Research, Vol.33, No.1, pp. 45-55, 2025, DOI:10.32604/or.2024.050161 - 20 December 2024

Abstract Background: Platinum chemotherapy (CT) remains the backbone of systemic therapy for patients with small-cell lung cancer (SCLC). The nucleotide excision repair (NER) pathway plays a central role in the repair of the DNA damage exerted by platinum agents. Alteration in this repair mechanism may affect patients’ survival. Materials and Methods: We conducted a retrospective analysis of data from 38 patients with extensive disease (ED)-SCLC who underwent platinum-CT at the Clinical Oncology Unit, Careggi University Hospital, Florence (Italy), from 2015 to 2020. mRNA expression analysis and single nucleotide polymorphism (SNP) characterization of three NER pathway genes—namely ERCC1, ERCC2,… More >

GENGYUN SUN^1,*, YIPING ZHENG^1,2, JIANFENG CAI², JIE GAO², LIE DONG², XIANGBIN ZHANG², YINGHUI HUANG^2,*

Oncology Research, Vol.33, No.1, pp. 171-184, 2025, DOI:10.32604/or.2024.047626 - 20 December 2024

Abstract Background: Long noncoding RNA, LINC01106 exhibits high expression in lung adenocarcinoma (LUAD) tumor tissues, but its functional role and regulatory mechanism in LUAD cells remain unclear. Methods: LINC01106 expression was analyzed in LUAD tissues and its functional impact on LUAD cells was assessed. LUAD cells were silenced with sh-LINC01106 and injected into nude mice to investigate tumor growth. The downstream transcription factors and molecular mechanism were determined using the Human transcription factor database (TFDB) database and Gene Expression Profiling Interactive Analysis (GEPIA) database. Additionally, the impact of linc01106 on autophagy was analyzed by determining the… More > Graphic Abstract

SHIQIN JIANG^1,#, YICHUN TANG^2,#, FENG MA³, YUCHUN NIU^4,*, LEI SUN^5,*

Oncology Research, Vol.33, No.1, pp. 213-224, 2025, DOI:10.32604/or.2024.046895 - 20 December 2024

Abstract Objective: Small cell lung cancer (SCLC) is commonly recognized as the most fatal lung cancer type. Despite substantial advances in immune checkpoint blockade therapies for treating solid cancers, their benefits are limited to a minority of patients with SCLC. In the present study, novel indicators for predicting the outcomes and molecular targets for SCLC treatment were elucidated. Methods: We conducted bioinformatics analysis to identify the key genes associated with tumor-infiltrating lymphocytes in SCLC. The functional role of the key gene identified in SCLC was determined both in vitro and in vivo. Results: A significant correlation was observed between… More >

Sumaia Mohamed Elhassan¹, Saad Mohamed Darwish^1,*, Saleh Mesbah Elkaffas²

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 835-867, 2025, DOI:10.32604/cmes.2024.058770 - 17 December 2024

Abstract Lung cancer continues to be a leading cause of cancer-related deaths worldwide, emphasizing the critical need for improved diagnostic techniques. Early detection of lung tumors significantly increases the chances of successful treatment and survival. However, current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue. Single-model deep learning technologies for lung cancer detection, while beneficial, cannot capture the full range of features present in medical imaging data, leading to incomplete or inaccurate detection. Furthermore, it may not be robust enough to handle the… More >

Man Liu¹, Zhuoheng Lv^1,#, Hongjing Wang^2,*, Lu Liu^1,*

Psycho-Oncologie, Vol.18, No.4, pp. 305-316, 2024, DOI:10.32604/po.2024.054098 - 04 December 2024

Abstract Objective: Non-small cell lung cancer (NSCLC) patients often experience significant fear of recurrence. To facilitate precise identification and appropriate management of this fear, this study aimed to compare the efficacy and accuracy of a Backpropagation Neural Network (BPNN) against logistic regression in modeling fear of cancer recurrence prediction. Methods: Data from 596 NSCLC patients, collected between September 2023 and December 2023 at the Cancer Hospital of the Chinese Academy of Medical Sciences, were analyzed. Nine clinically and statistically significant variables, identified via univariate logistic regression, were inputted into both BPNN and logistic regression models developed… More >

Lu Liu^#, Zhuoheng Lv^#, Yousheng Mao, Yan Liu^*, Man Liu^*

Psycho-Oncologie, Vol.18, No.4, pp. 317-328, 2024, DOI:10.32604/po.2024.053678 - 04 December 2024

Abstract Background: Lung cancer, one of the most prevalent and deadly malignancies worldwide, not only poses a significant physical burden but also a profound psychological challenge to patients. Among these psychological challenges, the fear of recurrence stands out as a particularly distressing issue. This fear, often rooted in the patients’ past experiences with the disease and its treatment, can significantly impact their quality of life, mental health, and even compliance with follow-up care. Moreover, this fear can be exacerbated by the lack of understanding and support from healthcare professionals and family members, further isolating patients and… More >

Salman Ahmed¹, Fazli Subhan^2,3, Mazliham Mohd Su’ud^3,*, Muhammad Mansoor Alam^3,4, Adil Waheed⁵

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1483-1511, 2024, DOI:10.32604/csse.2024.053997 - 22 November 2024

Abstract In the contemporary era, the death rate is increasing due to lung cancer. However, technology is continuously enhancing the quality of well-being. To improve the survival rate, radiologists rely on Computed Tomography (CT) scans for early detection and diagnosis of lung nodules. This paper presented a detailed, systematic review of several identification and categorization techniques for lung nodules. The analysis of the report explored the challenges, advancements, and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning (DL) algorithm. The findings also highlighted the usefulness of DL… More >