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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: Zhao, Zhi Yi | Cao, Yin | Wang, Hong Liang | Liu, Ling Yun
Article Type: Research Article
Abstract: OBJECTIVES: We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC. METHODS: We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram …for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507. RESULTS: Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1–penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group’s OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P = 5.678e-07) was poorer than that of low-risk groups’ (HR, 1.675; 95% CI, 1.037 to 2.713; P = 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p = 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score. CONCLUSIONS: The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC. Show more
Keywords: Competing endogenous RNA, prognosis, nomogram, bladder cancer
DOI: 10.3233/CBM-230216
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-11, 2023
Authors: Abd ELhafeez, Ahmed Saeed | Ghanem, Hala Mostafa | Swellam, Menha | Taha, AlShaimaa Mohamed
Article Type: Research Article
Abstract: BACKGROUND: FAM170B-AS1 is usually expressed low in all organs except for testicular tissues. No study was performed to explore its role in breast cancer (BC). Contradictory results were reported about hsa-miR-1202 and hsa-miR-146a-5p in BC. OBJECTIVE: The present study aimed to explore the involvement of FAM170B-AS1 in BC using bioinformatics predictive tools, followed by a practical validation besides exploring the impact of hsa-miR-1202 and hsa-miR-146a-5p in BC. METHODS: This study enrolled 96 female patients with BC, 30 patients with benign breast diseases (BBD), and 25 control subjects. The …expressions of circulating FAM170B-AS1, hsa-miR-1202, and hsa-miR-146a-5p were quantified using qRT-PCR. These ncRNAs’ associations, predictive, and diagnostic roles in BC were statistically tested. The underlying miRNA/mRNA targets of FAM170B-AS1 in BC were bioinformatically predicted followed by confirmation based on the GEPIA and TCGA databases. RESULTS: The expression of FAM170B-AS1 was upregulated in sera of BC patients and hsa-miR-1202 was upregulated in sera of BBD and BC patients while that of hsa-miR-146a-5p was downregulated in BC. These FAM170B-AS1 was significantly associated with BC when compared to BBD. FAM170B-AS1 and hsa-miR-1202 were statistically associated with the BC’s stage, grade, and LN metastasis. FAM170B-AS1 and hsa-miR-146a-5p gave the highest specificity and sensitivity for BC. KRAS and EGFR were predicted to be targeted by FAM170B-AS1 through interaction with hsa-miR-143-3p and hsa-miR-7-5p , respectively. Based on the TCGA database, cancer patients having mutations in FAM170B show good overall survival. CONCLUSIONS: The present study reported that for the first time, FAM170B-AS1 may be a potential risk factor, predictive, and diagnostic marker for BC. In addition, FAM170B-AS1 might be involved in BC by interacting with hsa-miR-143-3p/KRAS and hsa-miR-7-5p/EGFR through enhancement or repression that may present a new therapeutic option for BC. Show more
Keywords: Bioinformatics, diagnostic, EGFR, KRAS, risk factor
DOI: 10.3233/CBM-230396
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-21, 2023
Authors: Singh, Varsha | Katiyar, Amit | Malik, Prabhat | Kumar, Sunil | Mohan, Anant | Singh, Harpreet | Jain, Deepali
Article Type: Research Article
Abstract: OBJECTIVES: Significant progress has been made in the treatment of patients with pulmonary adenocarcinoma (ADCA) based on molecular profiling. However, no such molecular target exists for squamous cell carcinoma (SQCC). An exome sequence may provide new markers for personalized medicine for lung cancer patients of all subtypes. The current study aims to discover new genetic markers that can be used as universal biomarkers for non-small cell lung cancer (NSCLC). METHODS: WES of 19 advanced NSCLC patients (10 ADCA and 9 SQCC) was performed using Illumina HiSeq 2000. Variant calling was performed using GATK HaplotypeCaller and then …the impacts of variants on protein structure or function were predicted using SnpEff and ANNOVAR. The clinical impact of somatic variants in cancer was assessed using cancer archives. Somatic variants were further prioritized using a knowledge-driven variant interpretation approach. Sanger sequencing was used to validate functionally important variants. RESULTS: We identified 24 rare single-nucleotide variants (SNVs) including 17 non-synonymous SNVs, and 7 INDELs in 18 genes possibly linked to lung carcinoma. Variants were classified as known somatic (n = 10), deleterious (n = 8), and variant of uncertain significance (n = 6). We found TBP and MPRIP genes exclusively associated with ADCA subtypes, FBOX6 with SQCC subtypes and GPRIN2, KCNJ18 and TEKT4 genes mutated in all the patients. The Sanger sequencing of 10 high-confidence somatic SNVs showed 100% concordance in 7 genes, and 80% concordance in the remaining 3 genes. CONCLUSIONS: Our bioinformatics analysis identified KCNJ18, GPRIN2, TEKT4, HRNR, FOLR3, ESSRA, CTBP2, MPRIP, TBP, and FBXO6 may contribute to progression in NSCLC and could be used as new biomarkers for the treatment. The mechanism by which GPRIN2, KCNJ12, and TEKT4 contribute to tumorigenesis is unclear, but our results suggest they may play an important role in NSCLC and it is worth investigating in future. Show more
Keywords: Non-small cell lung cancer, adenocarcinoma, squamous cell carcinoma, biomarker, whole-exome sequencing
DOI: 10.3233/CBM-220211
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-18, 2023
Authors: Zhu, Ziwen | Jiang, Weizhen | Zhou, Danhong | Zhu, Weidong | Chen, Cheng
Article Type: Research Article
Abstract: BACKGROUND: In clinical practice, preoperative identification of mixed ground-glass opacity (mGGO) nodules with micropapillary component (MPC) to facilitate the implementation of individualized therapeutic strategies and avoid unnecessary surgery is increasingly important OBJECTIVE: This study aimed to build a predictive model based on clinical and radiological variables for the early identification of MPC in lung adenocarcinoma presenting as mGGO nodules. METHODS: The enrolled 741 lung adenocarcinoma patients were randomly divided into a training cohort and a validation cohort (3:1 ratio). The pathological specimens and preoperative images of malignant mGGO nodules from the study subjects …were retrospectively reviewed. Furthermore, in the training cohort, selected clinical and radiological variables were utilized to construct a predictive model for MPC prediction. RESULTS: The MPC was found in 228 (43.3%) patients in the training cohort and 72 (41.1%) patients in the validation cohort. Based on the predictive nomogram, the air bronchogram was defined as the most dominant independent risk factor for MPC of mGGO nodules, followed by the maximum computed tomography (CT) value (> 200), adjacent to pleura, gender (male), and vacuolar sign. The nomogram demonstrated good discriminative ability with a C-index of 0.783 (95%[CI] 0.744–0.822) in the training cohort and a C-index of 0.799 (95%[CI] 0.732–0.866) in the validation cohort Additionally, by using the bootstrapping method, this predictive model calculated a corrected AUC of 0.774 (95% CI: 0.770–0.779) in the training cohort. CONCLUSIONS: This study proposed a predictive model for preoperative identification of MPC in known lung adenocarcinomas presenting as mGGO nodules to facilitate individualized therapy. This nomogram model needs to be further externally validated by subsequent multicenter studies. Show more
Keywords: Mixed ground-glass opacity (mGGO), micropapillary component (MPC), lung adenocarcinoma, predictive model, nomogram
DOI: 10.3233/CBM-230104
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-11, 2023
Authors: Chen, Cheng | Wang, Caiming | Liu, Wei | Chen, Jiacheng | Chen, Liang | Luo, Xiangxiang | Wu, Jincai
Article Type: Research Article
Abstract: BACKGROUND: Cms1 ribosomal small subunit homolog (CMSS1) is an RNA-binding protein that may play an important role in tumorigenesis and development. OBJECTIVE: RNA-seq data from the GEPIA database and the UALCAN database were used to analyze the expression of CMSS1 in liver hepatocellular carcinoma (LIHC) and its relationship with the clinicopathological features of the patients. METHODS: LinkedOmics was used to identify genes associated with CMSS1 expression and to identify miRNAs and transcription factors significantly associated with CMSS1 by GSEA. RESULTS: The expression level of CMSS1 in hepatocellular carcinoma tissues was …significantly higher than that in normal tissues. In addition, the expression level of CMSS1 in advanced tumors was significantly higher than that in early tumors. The expression level of CMSS1 was higher in TP53-mutated tumors than in non-TP53-mutated tumors. CMSS1 expression levels were strongly correlated with disease-free survival (DFS) and overall survival (OS) in patients with LIHC, and high CMSS1 expression predicted poorer OS (P < 0.01) and DFS (P < 0.01). Meanwhile, our results suggested that CMSS1 is associated with the composition of the immune microenvironment of LIHC. CONCLUSIONS: The present study suggests that CMSS1 is a potential molecular marker for the diagnosis and prognostic of LIHC. Show more
Keywords: CMSS1, hepatocellular carcinoma, . bioinformatics, diagnosis, prognosis
DOI: 10.3233/CBM-230209
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-10, 2023
Authors: Heredia, David | Bolaño-Guerra, Laura | Valencia-Velarde, Angel | Santoyo, Edgar Varela | Lara-Mejía, Luis | Cárdenas-Fernández, Daniela | Orozco, Mario | Cruz-Rico, Graciela | Arrieta, Oscar
Article Type: Research Article
Abstract: BACKGROUND: Liquid biopsy (LB) is used to detect epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) and has been demonstrated to have prognostic and predictive value. OBJECTIVE: To associate the rates of EGFR and T790M mutations detected by LB during disease progression after first- or second-generation EGFR-TKIs with clinical characteristics and survival outcomes. METHODS: From January 2018 to December 2021, 295 patients with advanced EGFR mutant (EGFRm) NSCLC treated with first- or second-generation EGFR-TKIs were retrospectively analyzed. LB was collected at the time of progression. The frequency of …EGFR T790M mutations, overall survival (OS), and the clinical characteristics associated with LB positivity were determined. RESULTS: The prevalence of EGFR T790M mutation detected using LB was 44%. In patients with negative vs. positive LB, the median OS was 45.0 months vs. 25.0 months (p = 0.0001), respectively. Patients with a T790M mutation receiving osimertinib had a median OS of 44 months (95% CI [33.05–54.99]). Clinical characteristics associated with positive LB at progression extra-thoracic involvement, > 3 metastatic sites, and bone metastases. CONCLUSIONS: Our findings showed that LB positivity was associated with worse survival outcomes and specific clinical characteristics. This study also confirmed the feasibility and detection rate of T790M mutation in a Latin American population. Show more
Keywords: EGFRm NSCLC, liquid biopsy, T790M mutation, osimertinib, ctDNA
DOI: 10.3233/CBM-230124
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-11, 2023
Authors: Karamti, Hanen | Alharthi, Raed | Umer, Muhammad | Shaiba, Hadil | Ishaq, Abid | Abuzinadah, Nihal | Alsubai, Shtwai | Ashraf, Imran
Article Type: Research Article
Abstract: Breast cancer is a major cause of female deaths, especially in underdeveloped countries. It can be treated if diagnosed early and chances of survival are high if treated appropriately and timely. For timely and accurate automated diagnosis, machine learning approaches tend to show better results than traditional methods, however, accuracy lacks the desired level. This study proposes the use of an ensemble model to provide accurate detection of breast cancer. The proposed model uses the random forest and support vector classifier along with automatic feature extraction using an optimized convolutional neural network (CNN). Extensive experiments are performed using the original, …as well as, CNN-based features to analyze the performance of the deployed models. Experimental results involving the use of the Wisconsin dataset reveal that CNN-based features provide better results than the original features. It is observed that the proposed model achieves an accuracy of 99.99% for breast cancer detection. Performance comparison with existing state-of-the-art models is also carried out showing the superior performance of the proposed model. Show more
Keywords: Breast cancer detection, image processing, healthcare, machine learning, ensemble learning, deep convoluted features
DOI: 10.3233/CBM-230294
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-16, 2023
Authors: Yao, Ningning | Hou, Qing | Liang, Yu | Cao, Xin | Sun, Bochen | Wei, Lijuan | Sun, Ruifang | Cao, Jianzhong
Article Type: Research Article
Abstract: BACKGROUND: Aspartate aminotransferase (AST), an indicator of liver cell damage, was related to the prognosis of certain malignant tumors. OBJECTIVE: This study examined the predictive value of AST in patients with extranodal natural killer/T cell lymphoma (ENKTL). METHODS: We reviewed 183 cases diagnosed with ENKTL and selected 26 U/L as the optimum cut-off value of AST. We used the univariate and multivariate Cox regression to compare the different AST groups’ overall survival (OS) and progression-free survival (PFS). RESULTS: Prior to propensity score matching (PSM), Kaplan-Meier analysis showed that patients in …the low AST subgroup had better OS and PFS than the high AST subgroup. Multivariate analysis revealed that AST was an independent indicator for prognosis. After PSM, the low AST subgroup maintained a significantly better OS and PFS than the high AST subgroup. CONCLUSION: AST might represent a significant prognostic marker for ENKTL patients. Show more
Keywords: Serum aspartate aminotransferase, extranodal natural killer/T cell lymphoma, nasal type, survival, prognosis
DOI: 10.3233/CBM-230068
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-11, 2023
Authors: Li, Shan | Li, Ting | Shi, Yan-Qing | Xu, Bin-Jie | Deng, Yu-Yong | Sun, Xu-Guang
Article Type: Research Article
Abstract: BACKGROUND: Our study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis. METHODS: The data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency …of Hub gene mutations, and the effects of mutation on the patients’ prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes. RESULTS: We identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle. CONCLUSION: Overexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells. Show more
Keywords: Colorectal cancer, bioinformatics analysis, Hub genes, prognosis
DOI: 10.3233/CBM-230113
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-19, 2024
Authors: S, Vinoth | Balasubramanian, Satheeswaran | Perumal, Ekambaram | Santhakumar, Kirankumar
Article Type: Research Article
Abstract: BACKGROUND: Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent types of kidney cancer. Unravelling the genes responsible for driving cellular changes and the transformation of cells in ccRCC pathogenesis is a complex process. OBJECTIVE: In this study, twelve microarray ccRCC datasets were chosen from the gene expression omnibus (GEO) database and subjected to integrated analysis. METHODS: Through GEO2R analysis, 179 common differentially expressed genes (DEGs) were identified among the datasets. The common DEGs were subjected to functional enrichment analysis using ToppFun followed by construction of protein-protein interaction network (PPIN) …using Cytoscape. Clusters within the DEGs PPIN were identified using the Molecular Complex Detection (MCODE) Cytoscape plugin. To identify the hub genes, the centrality parameters degree, betweenness, and closeness scores were calculated for each DEGs in the PPIN. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to validate the relative expression levels of hub genes in the normal and ccRCC tissues. RESULTS: The common DEGs were highly enriched in Hypoxia-inducible factor (HIF) signalling and metabolic reprogramming pathways. VEGFA , CAV1 , LOX , CCND1 , PLG , EGF , SLC2A1 , and ENO2 were identified as hub genes. CONCLUSION: Among 8 hub genes, only the expression levels of VEGFA , LOX , CCND1 , and EGF showed a unique expression pattern exclusively in ccRCC on compared to other type of cancers. Show more
Keywords: Kidney cancer, hypoxia, metabolic reprogramming, hub genes, cancer biomarker
DOI: 10.3233/CBM-230271
Citation: Cancer Biomarkers, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
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