LU ZHANG^*, JINGUO CHU^*, YUSHAN YU

Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988

Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups… More >

ELHAM AMJAD¹, RAFFAELE PEZZANI^2,3,*, BABAK SOKOUTI^1,*

Oncology Research, Vol.32, No.3, pp. 439-461, 2024, DOI:10.32604/or.2023.044473

Abstract Noncoding RNAs instruct the Cas9 nuclease to site-specifically cleave DNA in the CRISPR/Cas9 system. Despite the high incidence of hepatocellular carcinoma (HCC), the patient’s outcome is poor. As a result of the emergence of therapeutic resistance in HCC patients, clinicians have faced difficulties in treating such tumor. In addition, CRISPR/Cas9 screens were used to identify genes that improve the clinical response of HCC patients. It is the objective of this article to summarize the current understanding of the use of the CRISPR/Cas9 system for the treatment of cancer, with a particular emphasis on HCC as part of the current state… More >

YANG ZHANG^1,2,#, NANNAN QIN^5,#, XIJUN WANG^6,#, RUI LIANG⁷, QUAN LIU⁴, RUOYI GENG⁸, TIANXIAO JIANG⁸, YUNFEI LIU^8,*, JINWEI LI^3,4,*

Oncology Research, Vol.32, No.3, pp. 563-576, 2024, DOI:10.32604/or.2023.029697

Abstract Glycogen metabolism plays a key role in the development of hepatocellular carcinoma (HCC), but the function of glycogen metabolism genes in the tumor microenvironment (TME) is still to be elucidated. Single-cell RNA-seq data were obtained from ten HCC tumor samples totaling 64,545 cells, and 65 glycogen metabolism genes were analyzed by a nonnegative matrix factorization (NMF). The prognosis and immune response of new glycogen TME cell clusters were predicted by using HCC and immunotherapy cohorts from public databases. HCC single-cell analysis was divided into fibroblasts, NT T cells, macrophages, endothelial cells, and B cells, which were separately divided into new… More >

DONGYE YANG^1,#,*, DONGDONG GUO^2,3,#, YUNMEI PENG², DONGMENG LIU¹, YANQIU FU¹, FEN SUN², LISHI ZHOU¹, JIAQI GUO¹, LAIQING HUANG^2,3,*

BIOCELL, Vol.47, No.9, pp. 2037-2049, 2023, DOI:10.32604/biocell.2023.028863

Abstract Introduction: Sulfatase 2 (SULF2), an endogenous extracellular sulfatase, can remove 6-O-sulfate groups of glucosamine residues from heparan sulfate (HS) chains to modulate the Wnt/β-catenin signaling pathway, which plays an important role in both liver carcinogenesis and embryogenesis. Side population (SP) cells are widely identified as stem-like cancer cells and are closely related to carcinoma metastasis, recurrence, and poor patient prognosis. However, the roles of SULF2 in SP cells of hepatomas are unclear, and the underlying mechanism is undefined. Objectives: This study aimed to compare the heterogeneity between SP cells and non-side population (NSP) cells derived from three different liver cancer… More > Graphic Abstract

TONG WANG^1,4,#, JINHUAN HONG^1,5,#, JIAJIE XIE^1,5, QIAN LIU⁴, JINRUI YUE^1,5, XUTING HE^1,5, SHIYU GE⁴, TAO LI⁴, GUOXIN LIU⁴, BENZHI CAI^1,3,5, LINQIANG LI^2,*, YE YUAN^1,3,5,*

BIOCELL, Vol.47, No.8, pp. 1811-1820, 2023, DOI:10.32604/biocell.2023.029120

Abstract Background: Phototherapies based on sunlight, infrared, ultraviolet, visible, and laser-based treatments present advantages like high curative effects, small invasion, and negligible adverse reactions in cancer treatment. We aimed to explore the potential therapeutic effects of blue light emitting diode (LED) in human hepatoma cells and decipher the underlying cellular and molecular mechanisms. Methods: Wound healing and transwell assays were employed to probe the inhibition of the invasion and migration of hepatocellular carcinoma cells in the presence of blue LED. The sphere-forming test was used to evaluate the effect of LED blue light irradiation on cancer stem cell properties. Immunofluorescence and… More > Graphic Abstract

MUHAMMAD BABAR KHAWAR^1,2,3,#, YAJUN WANG^4,#, ANEEQA MAJEED³, ALI AFZAL⁵, KABEER HANEEF⁶, HAIBO SUN^1,2,*

Oncology Research, Vol.31, No.5, pp. 677-688, 2023, DOI:10.32604/or.2023.029718

Abstract Hepatocellular carcinoma, the most common primary liver cancer and a leading cause of death, is a difficult disease to treat due to its heterogeneous nature. Traditional models, such as 2D culture and patient-derived xenografts, have not proven effective. However, the development of 3D culture techniques, such as organoids, which can mimic the tumor microenvironment (TME) and preserve heterogeneity and pathophysiological properties of tumor cells, offers new opportunities for treatment and research. Organoids also have the potential for biomarker detection and personalized medication, as well as genome editing using CRISPR/Cas9 to study the behavior of certain genes and therapeutic interventions. This… More > Graphic Abstract

P. Sabitha^*, G. Meeragandhi

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1983-2000, 2023, DOI:10.32604/iasc.2023.034402

Abstract Developing an automatic and credible diagnostic system to analyze the type, stage, and level of the liver cancer from Hematoxylin and Eosin (H&E) images is a very challenging and time-consuming endeavor, even for experienced pathologists, due to the non-uniform illumination and artifacts. Albeit several Machine Learning (ML) and Deep Learning (DL) approaches are employed to increase the performance of automatic liver cancer diagnostic systems, the classification accuracy of these systems still needs significant improvement to satisfy the real-time requirement of the diagnostic situations. In this work, we present a new Ensemble Classifier (hereafter called ECNet) to classify the H&E stained… More >

Murtada K. Elbashir¹, Alshimaa Mahmoud², Ayman Mohamed Mostafa^1,*, Eslam Hamouda¹, Meshrif Alruily¹, Sadeem M. Alotaibi¹, Hosameldeen Shabana^3,4, Mohamed Ezz^1,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5105-5121, 2023, DOI:10.32604/cmc.2023.037728

Abstract The convolutional neural network (CNN) is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions; Hemangioma and hepatocellular carcinoma (HCC). Ultrasound images, which are commonly available and have low cost and low risk compared to computerized tomography (CT) scan images, will be used as input for the model. A total of 350 ultrasound images belonging to 59 patients are used. The number of images with HCC is 202 and 148, respectively. These images were collected from ultrasound cases.info (28 Hemangiomas patients and 11 HCC patients), the department of radiology,… 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

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 >

Shengjin Yu, Huiming Lv, Jinhui Zhang, He Zhang, Weiwei Ju, Yu Jiang^*, Lijuan Lin^*

Oncologie, Vol.24, No.3, pp. 539-551, 2022, DOI:10.32604/oncologie.2022.024882

Abstract Background: Although heparanase/syndecan-1 axis is involved in malignant progression of many cancers, its significance in liver cancer is not well understood. In this study, we explored the value of heparanase/syndecan-1 axis expression in liver cancer and the intervention mechanisms that target this axis by inhibiting the proliferation of hepatocellular carcinoma cells. Materials and Methods: We conducted tissue microarray analysis that included 90 primary liver cancer and their corresponding adjacent samples to evaluate the expression of heparanase and syndecan-1 and their correlation with clinicopathologic characteristics. RNA interference and western blot assays were performed to analyze the effect of heparanase on syndecan-1… More >