Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 135.00Impact Factor 2023: 3.1
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: Li, Thomas Z. | Xu, Kaiwen | Chada, Neil C. | Chen, Heidi | Knight, Michael | Antic, Sanja | Sandler, Kim L. | Maldonado, Fabien | Landman, Bennett A. | Lasko, Thomas A.
Article Type: Research Article
Abstract: BACKGROUND: Large community cohorts are useful for lung cancer research, allowing for the analysis of risk factors and development of predictive models. OBJECTIVE: A robust methodology for (1) identifying lung cancer and pulmonary nodules diagnoses as well as (2) associating multimodal longitudinal data with these events from electronic health record (EHRs) is needed to optimally curate cohorts at scale. METHODS: In this study, we leveraged (1) SNOMED concepts to develop ICD-based decision rules for building a cohort that captured lung cancer and pulmonary nodules and (2) clinical knowledge to define time windows for …collecting longitudinal imaging and clinical concepts. We curated three cohorts with clinical data and repeated imaging for subjects with pulmonary nodules from our Vanderbilt University Medical Center. RESULTS: Our approach achieved an estimated sensitivity 0.930 (95% CI: [0.879, 0.969]), specificity of 0.996 (95% CI: [0.989, 1.00]), positive predictive value of 0.979 (95% CI: [0.959, 1.000]), and negative predictive value of 0.987 (95% CI: [0.976, 0.994]) for distinguishing lung cancer from subjects with SPNs. CONCLUSION: This work represents a general strategy for high-throughput curation of multi-modal longitudinal cohorts at risk for lung cancer from routinely collected EHRs. Show more
Keywords: Pulmonary nodules, lung cancer, EHR mining, multimodal longitudinal cohorts
DOI: 10.3233/CBM-230340
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-9, 2024
Authors: Xie, Kai | Wang, Bin | Pang, Pei | Li, Guangbin | Yang, Qianqian | Fang, Chen | Jiang, Wei | Feng, Yu | Ma, Haitao
Article Type: Research Article
Abstract: BACKGROUND: Lung adenocarcinoma (LUAD) is a prevalent form of malignancy globally. Disulfidptosis is novel programmed cell death pathway based on disulfide proteins, may have a positive impact on the development of LUAD treatment strategies. OBJECTIVE: To investigate the impact of disulfidptosis-related genes (DRGs) on the prognosis of LUAD, developed a risk model to facilitate the diagnosis and prognostication of patients. We also explored ACTN4 (DRGs) as a new therapeutic biomarker for LUAD. METHODS: We investigated the expression patterns of DRGs in both LUAD and noncancerous tissues. To assess the prognostic value of …the DRGs, we developed risk models through univariate Cox analysis and lasso regression. The expression and function of ACTN4 was evaluated by qRT-PCR, immunohistochemistry and in vitro experiments. The TIMER examined the association between ACTN4 expression and immune infiltration in LUAD. RESULTS: Ten differentially expressed DRGs were identified. And ACTN4 was identified as potential risk factors through univariate Cox regression analysis (P < 0.05). ACTN4 expression and riskscore were used to construct a risk model to predict overall survival in LUAD, and high-risk demonstrated a significantly higher mortality rate compared to the low-risk cohort. qRT-PCR and immunohistochemistry assays indicated ACTN4 was upregulated in LUAD, and the upregulation was associated with clinicopathologic features. In vitro experiments showed the knockdown of ACTN4 expression inhibited the proliferation in LUAD cells. The TIMER analysis demonstrated a correlation between the expression of ACTN4 and the infiltration of diverse immune cells. Elevated ACTN4 expression was associated with a reduction in memory B cell count. Additionally, the ACTN4 expression was associated with m6A modification genes. CONCLUSIONS: Our study introduced a prognostic model based on DRGs, which could forecast the prognosis of patients with LUAD. The biomarker ACTN4 exhibits promise for the diagnosis and management of LUAD, given its correlation with tumor immune infiltration and m6A modification. Show more
Keywords: Disulfidptosis, lung adenocarcinoma, ACTN4, immune infiltration, therapeutic target
DOI: 10.3233/CBM-230276
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-14, 2024
Authors: Liu, Yang | Pang, Zhongqi | Wang, Jianshe | Wang, Jinfeng | Ji, Bo | Xu, Yidan | He, Jiaxin | Zhang, Lu | Han, Yansong | Shen, Linkun | Xu, Wanhai | Ren, Minghua
Article Type: Research Article
Abstract: BACKGROUND: N6-methyladenosine (m6A) is the most frequent RNA modification in mammals, and its role in bladder cancer (BC) remains rarely revealed. OBJECTIVE: To predict the value of m6A-related genes in prognosis and immunity in BC. METHODS: We performed multiple omics analysis of 618 TCGA and GEO patients and used principal component analysis (PCA) to calculate the m6A score for BC patients. RESULTS: We described the multiple omics status of 23 m6A methylation-related genes (MRGs), and four m6A clusters were identified, which showed significant differences in immune infiltration and biological pathways. …Next, we intersected the differential genes among m6A clusters, and 11 survival-related genes were identified, which were used to calculate the m6A score for the patients. We found that the high-score (HS) group showed lower tumor mutation burden (TMB) and TP53 mutations and better prognosis than the low-score (LS) group. Lower immune infiltration, higher expression of PD-L1, PD-1, and CTLA4, and higher immune dysfunction and immune exclusion scores were identified in the LS group, suggesting a higher possibility of immune escape. Finally, the experimental verification shows that the m6A related genes, such as IGFBP1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS: These findings revealed the important roles of m6A MRGs in predicting prognosis, TMB status, TP53 mutation, immune functions and immunotherapeutic response in BC. Show more
Keywords: N6-methyladenosine, bladder cancer, prognosis, immunotherapy, m6A score
DOI: 10.3233/CBM-230286
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
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
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]