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Biomolecules
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Biomarkers for Cancer
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Biomarkers for Cancer

A special issue of Biomolecules (ISSN 2218-273X).

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 19954

Special Issue Editor

Assoc. Prof. Chamindie K. Punyadeera

E-Mail Website
Guest Editor
The School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia
Interests: biomarkers; salivary diagnostics; heart diseases; head and neck cancer; proteomics; mass spectrometry; lung cancer, glioblastoma; human papilloma virus
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the emergence of precision medicine, advancements in next-generation genomic profiling technologies, and selective molecular targeted therapies, biomarkers have started to play an important role in the clinical management of cancer patients. By definition, a biomarker is a molecule or gene which can characterize a particular pathological or physiological process or disease. Biomarkers can be categorised broadly into diagnostic, prognostic, predictive, recurrence, and pharmacodynamic. Cancer biomarkers can be DNA, DNA methylation, mRNA, miRNA/LnCRNA, proteins, metabolites, or processes such as apoptosis, angiogenesis, or proliferation. In cancer research and management, the concept of precision medicine, i.e., the prevention and treatment strategies that take into consideration an individual’s genetic variability, relies on the development of valid biomarkers that can interrogate key aberrant cellular pathways potentially targetable with molecular targeted or immunologic therapies.The objective of this Special Issue is to discuss biomarker types (liquid biopsies) for cancer management, the standardization of biomarker development, traditional biomarkers versus non-invasive biomarkers, pitfalls and challenges in translating biomarkers into clinical practice, and strategies to accelerate biomarker uptake. 

Prof. Dr. Chamindie Punyadeera

Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • liquid biopsy
  • non-invasive body fluids
  • personalized medicine
  • sensitivity
  • specificity
  • standardization of biomarker development
  • epigenetics

Published Papers (3 papers)

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Research

28 pages, 9897 KiB  
Article
Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis
by Ali Mohamed Alshabi, Basavaraj Vastrad, Ibrahim Ahmed Shaikh and Chanabasayya Vastrad
Biomolecules 2019, 9(5), 201; https://doi.org/10.3390/biom9050201 - 24 May 2019
Cited by 30 | Viewed by 6395
Abstract
The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of [...] Read more.
The present study aimed to investigate the molecular mechanisms underlying glioblastoma multiform (GBM) and its biomarkers. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppGene (ToppFun) was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and TF-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs was carried out. A total of 590 DEGs, including 243 up regulated and 347 down regulated genes, were diagnosed between scrambled shRNA expression and Lin7A knock down. The up-regulated genes were enriched in ribosome, mitochondrial translation termination, translation, and peptide biosynthetic process. The down-regulated genes were enriched in focal adhesion, VEGFR3 signaling in lymphatic endothelium, extracellular matrix organization, and extracellular matrix. The current study screened the genes in the PPI network, extracted modules, miRNA-target genes regulatory network, and TF-target genes regulatory network with higher degrees as hub genes, which included NPM1, CUL4A, YIPF1, SHC1, AKT1, VLDLR, RPL14, P3H2, DTNA, FAM126B, RPL34, and MYL5. Survival analysis indicated that the high expression of RPL36A and MRPL35 were predicting longer survival of GBM, while high expression of AP1S1 and AKAP12 were predicting shorter survival of GBM. High expression of RPL36A and AP1S1 were associated with pathogenesis of GBM, while low expression of ALPL was associated with pathogenesis of GBM. In conclusion, the current study diagnosed DEGs between scrambled shRNA expression and Lin7A knock down samples, which could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new diagnostic markers might be used as therapeutic targets for GBM. Full article
(This article belongs to the Special Issue Biomarkers for Cancer)
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19 pages, 1253 KiB  
Article
Promoter Hypermethylation of Tumor-Suppressor Genes p16INK4a, RASSF1A, TIMP3, and PCQAP/MED15 in Salivary DNA as a Quadruple Biomarker Panel for Early Detection of Oral and Oropharyngeal Cancers
by Chamikara Liyanage, Asanga Wathupola, Sanjayan Muraleetharan, Kanthi Perera, Chamindie Punyadeera and Preethi Udagama
Biomolecules 2019, 9(4), 148; https://doi.org/10.3390/biom9040148 - 12 Apr 2019
Cited by 49 | Viewed by 8235
Abstract
Silencing of tumor-suppressor genes (TSGs) by DNA promoter hypermethylation is an early event in carcinogenesis; hence, TSGs may serve as early tumor biomarkers. We determined the promoter methylation levels of p16INK4a, RASSF1A, TIMP3, and PCQAP/MED15 TSGs in salivary DNA [...] Read more.
Silencing of tumor-suppressor genes (TSGs) by DNA promoter hypermethylation is an early event in carcinogenesis; hence, TSGs may serve as early tumor biomarkers. We determined the promoter methylation levels of p16INK4a, RASSF1A, TIMP3, and PCQAP/MED15 TSGs in salivary DNA from oral cancer (OC) and oropharyngeal cancer (OPC) patients, using methylation-specific PCR coupled with densitometry analysis. We assessed the association between DNA methylation of individual TSGs with OC and OPC risk factors. The performance and the clinical validity of this quadruple-methylation marker panel were evaluated in discriminating OC and OPC patients from healthy controls using the CombiROC web tool. Our study reports that RASSF1A, TIMP3, and PCQAP/MED15 TSGs were significantly hypermethylated in OC and OPC cases compared to healthy controls. DNA methylation levels of TSGs were significantly augmented by smoking, alcohol use, and betel quid chewing, indicating the fact that frequent exposure to risk factors may drive oral and oropharyngeal carcinogenesis through TSG promoter hypermethylation. Also, this quadruple-methylation marker panel of p16INK4a, RASSF1A, TIMP3, and PCQAP/MED15 TSGs demonstrated excellent diagnostic accuracy in the early detection of OC at 91.7% sensitivity and 92.3% specificity and of OPC at 99.8% sensitivity and 92.1% specificity from healthy controls. Full article
(This article belongs to the Special Issue Biomarkers for Cancer)
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13 pages, 863 KiB  
Article
Association of MMP9-1562C/T and MMP13-77A/G Polymorphisms with Non-Small Cell Lung Cancer in Southern Chinese Population
by Wen Li, Ming Xi Jia, Jian Hui Wang, Jie Li Lu, Jing Deng, Jian Xin Tang and Cun Liu
Biomolecules 2019, 9(3), 107; https://doi.org/10.3390/biom9030107 - 18 Mar 2019
Cited by 125 | Viewed by 4596
Abstract
Background: Matrix metalloproteinases (MMPs) are capable of degrading and modifying most components of the extracellular matrix (ECM) and the basal membrane (BM), and play crucial roles in cancer invasion and metastasis. MMP gene expressions were regulated primarily at the transcriptional level, which was [...] Read more.
Background: Matrix metalloproteinases (MMPs) are capable of degrading and modifying most components of the extracellular matrix (ECM) and the basal membrane (BM), and play crucial roles in cancer invasion and metastasis. MMP gene expressions were regulated primarily at the transcriptional level, which was associated with tumor spread and patient prognosis. Polymorphisms in MMPs have been reported to be associated with non-small cell lung cancer (NSCLC). The objective of this study aim to evaluate the serum levels and polymorphisms of MMP-9 and MMP-13 in non-small cell lung cancer patients compared to normal subjects and their correlation to non-small cell lung cancer histopathology findings in Southern Chinese people. Methods: This case–control study included 245 patients with NSCLC and 258 healthy controls. Genomic DNA was extracted by using DNA extraction kit, genotyping was confirmed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct DNA sequencing, and serum levels of MMP-9 and MMP-13 were measured by using a specific ELISA, Human Matrix Metalloproteinase Enzyme Immunoassay Kits. Statistical analysis was carried out using the SPSS 23.0 software package. Results: The subjects carrying the TT genotype had a decreased risk of lung cancer in MMP9-1562C/T comparing with the CC genotype (p = 0.00, OR = 0.45, 95% CI = 0.29–0.68), and the MMP13-77 AA genotype was associated with a decreased risk of NSCLC by comparing with the GG genotype (p = 0.03, OR = 0.56, 95% CI = 0.33–0.94). Moreover, the C allele of MMP9-1562C/T could increase serum level of NSCLC in compared with the A allele (OR = 1.19, 95% CI = 0.75–1.89). Similarly, the AA genotype of MMP13 might be a marker of decreased serum level of lung cancer (OR = 0.76, 95% CI = 0.51–1.14). Conclusions: The results of these analyses underline the support of the notion that the CC genotype of MMP9-1562C/T and GG genotypes of MMP13-77G/A were associated with the increased risk NSCLC, and the serum levels of MMP9 and MMP13 were consistent with the results of the SNP analysis. MMP13 and MMP9 might be function as a key oncogene in NSCLC with a Southern Chinese population. Combined detection of SNP and enzyme activity between MMP9 and MMP13 are expected to be a potential diagnostic method of non-small cell lung cancer. Full article
(This article belongs to the Special Issue Biomarkers for Cancer)
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