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Concentrating on molecular biomarkers in cancer research, Cancer Biomarkers publishes original research findings (and reviews solicited by the editor) on the subject of the identification of markers associated with the disease processes whether or not they are an integral part of the pathological lesion.
The disease markers may include, but are not limited to, genomic, epigenomic, proteomics, cellular and morphologic, and genetic factors predisposing to the disease or indicating the occurrence of the disease. Manuscripts on these factors or biomarkers, either in altered forms, abnormal concentrations or with abnormal tissue distribution leading to disease causation will be accepted.
Authors: Zhang, Zhixiang | Guo, Jipeng | Gong, Chongwen | Wu, Sai | Sun, Yanlei
Article Type: Research Article
Abstract: BACKGROUND: N6-methyladenosine (m6 A) modification has been associated with non-small cell lung cancer (NSCLC) tumorigenesis. OBJECTIVES: This study aimed to determine the functions of Vir-like m6 A methyltransferase-associated (KIAA1429) and relaxin family peptide receptor 1 (RXFP1) in NSCLC. METHODS: A quantitative real-time polymerase chain reaction was used to analyze the mRNA levels of KIAA1429 and RXFP1 in NSCLC. After silencing KIAA1429 or RXFP1 in NSCLC cells, changes in the malignant phenotypes of NSCLC cells were assessed using cell counting kit-8, colony formation, and transwell assays. Finally, the m6 A modification of RXFP1 mediated …by KIAA1429 was confirmed using luciferase, methylated RNA immunoprecipitation, and western blot assays. RESULTS: KIAA1429 and RXFP1 were upregulated and downregulated in NSCLC, respectively. Silencing of KIAA1429 attenuated the viability, migration, and invasion of NSCLC cells, whereas silencing of RXFP1 showed the opposite function in NSCLC cells. Moreover, RXFP1 expression was inhibited by KIAA1429 via m6 A-modification. Therefore, silencing RXFP1 reversed the inhibitory effect of KIAA1429 knockdown in NSCLC cells. CONCLUSION: Our findings confirmed that the KIAA1429/RXFP1 axis promotes NSCLC tumorigenesis. This is the first study to reveal the inhibitory function of RXFP1 in NSCLC via KIAA1429-mediated m6 A-modification. These findings may help identify new biomarkers for targeted NSCLC therapy. Show more
Keywords: N6-methyladenosine, KIAA1429, RXFP1, non-small cell lung cancer
DOI: 10.3233/CBM-230188
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-12, 2024
Authors: Kim, Roger Y.
Article Type: Research Article
Abstract: Pulmonary nodules are ubiquitously found on computed tomography (CT) imaging either incidentally or via lung cancer screening and require careful diagnostic evaluation and management to both diagnose malignancy when present and avoid unnecessary biopsy of benign lesions. To engage in this complex decision-making, clinicians must first risk stratify pulmonary nodules to determine what the best course of action should be. Recent developments in imaging technology, computer processing power, and artificial intelligence algorithms have yielded radiomics-based computer-aided diagnosis tools that use CT imaging data including features invisible to the naked human eye to predict pulmonary nodule malignancy risk and are designed …to be used as a supplement to routine clinical risk assessment. These tools vary widely in their algorithm construction, internal and external validation populations, intended-use populations, and commercial availability. While several clinical validation studies have been published, robust clinical utility and clinical effectiveness data are not yet currently available. However, there is reason for optimism as ongoing and future studies aim to target this knowledge gap, in the hopes of improving the diagnostic process for patients with pulmonary nodules. Show more
Keywords: Radiomics, artificial intelligence, lung cancer, risk stratification, pulmonary nodule
DOI: 10.3233/CBM-230360
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-11, 2024
Authors: Pei, Wenceng | Jiang, Minren | Liu, Haiyan | Song, Jiahong | Hu, Jian
Article Type: Research Article
Abstract: BACKGROUND: Liver hepatocellular cancer (LIHC) and stomach adenocarcinoma (STAD) are common malignancies with high lethal ratios worldwide. Great progress has been achieved by using diverse therapeutic strategies; however, these diseases still have an unfavourable prognosis. Ferroptosis inducer drugs, unlike apoptosis-related drugs, can overcome the resistance to cancer therapy caused by traditional chemicals. However, the relationship between overall survival (OS) and ferroptosis-related genes, as well as the mechanisms involved, are largely unclear. METHODS: The expression levels of AIFM2, GPX4, ACSL4, FTH1, NOS1, and PTGS2 in LIHC and STAD were obtained from UALCAN. The correlations of OS with …these gene expression levels were obtained using the Kaplan-Meier Plotter database. The OS associated with genetic mutations of those genes compared to that of unchanged genes was analysed using the TIMER website. GO and KEGG enrichment analyses of ferroptosis-related genes and their coexpressed genes in LIHC and STAD were conducted using the STRING and DAVID databases. The relationship of PTGS2 and ACSL4 to immune cell infiltration was analysed using the TIMER website. The viability and GPX5 expression levels in LIHC cells treated with RSL3 and As 2 O 3 were detected by MTT methods and western blotting, respectively. RESULTS: Our results showed that GPX4, FTH1 and AIFM2 were overexpressed in LIHC and STAD. High levels of GPX4, FTH1 and AIFM2 were prominently correlated with better prognosis in LIHC. However, GPX and FTH1 in STAD did not show significant correlations with OS. AIFM2 in STAD had the opposite trend with OS compared with that in LIHC. Moreover, a high mutation rate of these genes (35.74%) was also observed in LIHC patients, and genetic mutation of these genes was correlated with shorter OS. In contrast, the genetic mutation of these genes did not change OS in STAD. Enrichment analysis showed that the respiratory electron transport chain, cell chemotaxis and T-cell migration were related to ferroptosis. ASCL4 and PTGS2 coexpressed with cytokines associated with immune cell infiltration. Compared to RSL3 or As 2 O 3 alone, As2O3 plus RSL3 significantly inhibited the growth of Huh7 cells. GPX4 was downregulated to an undetectable level when in combination with RSL3. CONCLUSIONS: Our results indicated that ferroptosis-related genes might play an important role in LIHC and STAD and might be risk factors for overall survival in LIHC and STAD. Show more
Keywords: Liver hepatocellular cancer, stomach adenocarcinoma, ferroptosis, prognosis, enrichment analysis
DOI: 10.3233/CBM-230114
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-13, 2023
Authors: Li, Wuping | Yao, Ruizhe | Yu, Nasha | Zhang, Weiming
Article Type: Research Article
Abstract: BACKGROUND: Therapies for diffuse large B-cell lymphoma (DLBCL) are limited due to the diverse gene expression profiles and complicated immune microenvironments, making it an aggressive lymphoma. Beyond this, researches have shown that ferroptosis contributes to tumorigenesis, progression, and metastasis. We thus are interested to dissect the connection between ferroptosis and disease status of DLBCL. We aim at generating a valuable prognosis gene signature for predicting the status of patients of DLBCL, with focus on ferroptosis-related genes (FRGs). OBJECTIVE: To examine the connection between ferroptosis-related genes (FRGs) and clinical outcomes in DLBCL patients based on public datasets. …METHODS: An expression profile dataset for DLBCL was downloaded from GSE32918 (https://www.ncbi.nlm.nih.gov/geo/ query/acc.cgi?acc=gse32918 ), and a ferroptosis-related gene cluster was obtained from the FerrDb database (http://www. zhounan.org/ferrdb/ ). A prognostic signature was developed from this gene cluster by applying a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to GSE32918, followed by external validation. Its effectiveness as a biomarker and the prognostic value was determined by a receiver operator characteristic curve mono factor analysis. Finally, functional enrichment was evaluated by the package Cluster Profiler of R. RESULTS: Five ferroptosis-related genes (FRGs) (GOP1 , GPX2 , SLC7A5 , ATF4 , and CXCL2 ) associated with DLBCL were obtained by a multivariate analysis. The prognostic power of these five FRGs was verified by TCGA (https://xenabrowser.net/datapages/?dataset=TCGA.DLBC.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A44 ) and GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse 32918 ) datasets, with ROC analyses. KEGG and GO analyses revealed that upregulated genes in the high-risk group based on the gene signature were enriched in receptor interactions and other cancer-related pathways, including pathways related to abnormal metabolism and cell differentiation. CONCLUSION: The newly developed signature involving GOP1 , GPX2 , SLC7A5 , ATF4 , and CXCL2 has the potential to serve as a prognostic biomarker. Furthermore, our results provide additional support for the contribution of ferroptosis to DLBCL. Show more
Keywords: GOP1, GPX2, SLC7A5, ATF4, CXCL2, ferroptosis-related genes, DLBCL
DOI: 10.3233/CBM-230325
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-15, 2024
Authors: Wang, Tianxiang | Qian, Luxi | Zhang, Pingchuan | Du, Mingyu | Wu, Jing | Peng, Fanyu | Yao, Chengyun | Yin, Rong | Yin, Li | He, Xia
Article Type: Research Article
Abstract: INTRODUCTION: GINS2 exerts a carcinogenic effect in multiple human malignancies, while it is still unclear that the potential roles and underlying mechanisms of GINS2 in HNSCC. METHODS: TCGA database was used to screen out genes with significant differences in expression in HNSCC. Immunohistochemistry and qRT-PCR were used to measure the expression of GINS2 in HNSCC tissues and cells. GINS2 was detected by qRT-PCR or western blot after knockdown or overexpression. Celigo cell counting, MTT, colony formation, and flow cytometric assay were used to check the ability of proliferation and apoptosis. Bioinformatics and microarray were used to …screen out the downstream genes of GINS2. RESULTS: GINS2 in HNSCC tissues and cells was up-regulated, which was correlated with poor prognosis. GINS2 gene expression was successfully inhibited and overexpressed in HNSCC cells. Knockdown of GINS2 could inhibit proliferation and increase apoptosis of cells. Meanwhile, overexpression of GINS2 could enhance cell proliferation and colony formation. Knockdown of RRM2 may inhibit HNSCC cell proliferation, while overexpression of RRM2 rescued the effect of reducing GINS2 expression. CONCLUSION: Our study reported the role of GINS2 in HNSCC for the first time. The results demonstrated that in HNSCC cells, GINS2 promoted proliferation and inhibited apoptosis via altering RRM2 expression. Therefore, GINS2 might play a carcinogen in HNSCC, and become a specific promising therapeutic target. Show more
Keywords: HNSCC, GINS2, RRM2, proliferation, apoptosis
DOI: 10.3233/CBM-230337
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-14, 2024
Authors: Priya C V, Lakshmi | V G, Biju | B R, Vinod | Ramachandran, Sivakumar
Article Type: Research Article
Abstract: BACKGROUND: Breast cancer is one of the leading causes of death in women worldwide. Histopathology analysis of breast tissue is an essential tool for diagnosing and staging breast cancer. In recent years, there has been a significant increase in research exploring the use of deep-learning approaches for breast cancer detection from histopathology images. OBJECTIVE: To provide an overview of the current state-of-the-art technologies in automated breast cancer detection in histopathology images using deep learning techniques. METHODS: This review focuses on the use of deep learning algorithms for the detection and classification of breast …cancer from histopathology images. We provide an overview of publicly available histopathology image datasets for breast cancer detection. We also highlight the strengths and weaknesses of these architectures and their performance on different histopathology image datasets. Finally, we discuss the challenges associated with using deep learning techniques for breast cancer detection, including the need for large and diverse datasets and the interpretability of deep learning models. RESULTS: Deep learning techniques have shown great promise in accurately detecting and classifying breast cancer from histopathology images. Although the accuracy levels vary depending on the specific data set, image pre-processing techniques, and deep learning architecture used, these results highlight the potential of deep learning algorithms in improving the accuracy and efficiency of breast cancer detection from histopathology images. CONCLUSION: This review has presented a thorough account of the current state-of-the-art techniques for detecting breast cancer using histopathology images. The integration of machine learning and deep learning algorithms has demonstrated promising results in accurately identifying breast cancer from histopathology images. The insights gathered from this review can act as a valuable reference for researchers in this field who are developing diagnostic strategies using histopathology images. Overall, the objective of this review is to spark interest among scholars in this complex field and acquaint them with cutting-edge technologies in breast cancer detection using histopathology images. Show more
Keywords: Computer-aided detection, breast cancer, histopathology images, deep learning, Convolutional Neural Network (CNN)
DOI: 10.3233/CBM-230251
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-25, 2024
Authors: Zhang, Yuke | Liu, Kai | Wang, Jianzhong
Article Type: Research Article
Abstract: BACKGROUND: Osteosarcoma (OS) is a relatively rare malignant bone tumor in teenagers; however, its molecular mechanisms are not yet understood comprehensively. OBJECTIVE: The study aimed to use necroptosis-related genes (NRGs) and their relationships with immune-related genes to construct a prognostic signature for OS. METHODS: TARGET-OS was used as the training dataset, and GSE 16091 and GSE 21257 were used as the validation datasets. Univariate regression, survival analysis, and Kaplan-Meier curves were used to screen for hub genes. The immune-related targets were screened using immune infiltration assays and immune checkpoints. The results were validated …using nomogram and decision curve analyses (DCA). RESULTS: Using univariate Cox regression analysis, TNFRSF1A was screened from 14 NRGs as an OS prognostic signature. Functional enrichment was analyzed based on the median expression of TNFRSF1A. The prognosis of the TNFRSF1A low-expression group in the Kaplan-Meier curve was notably worse. Immunohistochemistry analysis showed that the number of activated T cells and tumor purity increased considerably. Furthermore, the immune checkpoint lymphocyte activation gene 3 (LAG-3) is a possible target for intervention. The nomogram accurately predicted 1-, 3-, and 5-year survival rates. DCA validated the model (C = 0.669). Conclusion: TNFRSF1A can be used to elucidate the potential relationship between the immune microenvironment and NRGs in OS pathogenesis. Show more
Keywords: Osteosarcoma, necroptosis, tumor immune microenvironment, TNFRSF1A, prognosis
DOI: 10.3233/CBM-230086
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-14, 2023
Authors: Zhu, Liucun | Yuan, Fa | Wang, Xue | Zhu, Rui | Guo, Wenna
Article Type: Research Article
Abstract: Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating …characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients. Show more
Keywords: Lower-grade glioma, cuproptosis, DNA-methylation, tumor microenvironment, immune checkpoint inhibitors
DOI: 10.3233/CBM-230341
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-14, 2024
Authors: Wen, Yixin | Xu, Feng | Zhang, Hui
Article Type: Research Article
Abstract: BACKGROUND: Circular RNAs (circRNAs) perform key regulatory functions in osteosarcoma (OS) tumorigenesis. In this study, we aimed to explore the detailed action mechanisms of circ_0049271 in OS progression. METHODS: Cell colony formation, cell counting kit-8, and transwell assays were performed to assess the proliferation and invasion of OS cells. Quantitative reverse transcription-polymerase chain reaction and western blotting were used to determine the expression levels of polymerase 1 and transcript release factor (PTRF), microRNA (miR)-1197, and circ_0049271 in OS cells. Furthermore, RNA immunoprecipitation and dual luciferase assays were conducted to explore the targeted relationships among PTRF …, miR-1197 , and circ_0049271 . Finally, a tumor formation assay was conducted to determine the effects of circ_0049271 on in vivo tumor growth in mice. RESULTS: High expression levels of miR-1197 and low levels of circ_0049271 and PTRF were observed in OS cells. circ _0049271 targeted miR-1197 to mediate PTRF expression. Moreover, the proliferation and invasion of OS cells were repressed by circ_0049271 or PTRF overexpression and increased by miR-1197 upregulation. Enforced circ_0049271 also impeded tumor growth in vivo . Upregulation of miR-1197 reversed the antitumor effects of circ_0049271 on OS progression in vitro ; however, PTRF overexpression attenuated the cancer-promoting effects of miR-1197 on OS in vitro . CONCLUSIONS: Our findings revealed that circ_0049271 targeted the miR-1197/PTRF axis to attenuate the malignancy of OS, suggesting a potential target for its clinical treatment. Show more
Keywords: Osteosarcoma, circRNA, circ_0049271, miR-1197, PTRF
DOI: 10.3233/CBM-230191
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
Authors: Horackova, Klara | Vocka, Michal | Lopatova, Sarka | Zemankova, Petra | Kleibl, Zdenek | Soukupova, Jana
Article Type: Research Article
Abstract: BACKGROUND: Ovarian cancer (OC) is mostly diagnosed in advanced stages with high incidence-to-mortality rate. Nevertheless, some patients achieve long-term disease-free survival. However, the prognostic markers have not been well established. OBJECTIVE: The primary objective of this study was to analyse the association of the suggested prognostic marker rs2185379 in PRDM1 with long-term survival in a large independent cohort of advanced OC patients. METHODS: We genotyped 545 well-characterized advanced OC patients. All patients were tested for OC predisposition. The effect of PRDM1 rs2185379 and other monitored clinicopathological and genetic variables on survival …were analysed. RESULTS: The univariate analysis revealed no significant effect of PRDM1 rs2185379 on survival whereas significantly worse prognosis was observed in postmenopausal patients (HR = 2.49; 95%CI 1.90–3.26; p = 4.14 × 10 - 11 ) with mortality linearly increasing with age (HR = 1.05 per year; 95%CI 1.04–1.07; p = 2 × 10 - 6 ), in patients diagnosed with non-high-grade serous OC (HR = 0.44; 95%CI 0.32–0.60; p = 1.95 × 10 - 7 ) and in patients carrying a gBRCA1 pathogenic variant (HR = 0.65; 95%CI 0.48–0.87; p = 4.53 × 10 - 3 ). The multivariate analysis interrogating the effect of PRDM1 rs2185379 with other significant prognostic factors revealed marginal association of PRDM1 rs2185379 with worse survival in postmenopausal women (HR = 1.54; 95%CI 1.01–2.38; p = 0.046). CONCLUSIONS: Unlike age at diagnosis, OC histology or gBRCA1 status, rs2185379 in PRDM1 is unlikely a marker of long-term survival in patients with advance OC. Show more
Keywords: Ovarian cancer, long-term survival, PRDM1, BRCA1, biomarker
DOI: 10.3233/CBM-230358
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-5, 2024
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