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Cancers
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Genetic and Molecular Approaches to Cancer Epidemiology: Opportunities and Challenges...
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Genetic and Molecular Approaches to Cancer Epidemiology: Opportunities and Challenges in the Precision Medicine Era

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Epidemiology and Prevention".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 3966

Special Issue Editors

Prof. Dr. Lifang Hou

E-Mail Website
Guest Editor
Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, FL, USA
Interests: cardiovascular diseases; digestive cancer; environmental health; epidemiology; prostate cancer
Dr. Brian Joyce

E-Mail Website
Guest Editor
Department of Preventive Medicine, Division of Cancer Epidemiology and Prevention, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
Interests: epidemiology epigenetics aging

Special Issue Information

Dear Colleagues, 

As we enter a new era of precision medicine, our knowledge of the relationships between genomic, epigenomic, transcriptomic, and molecular factors and cancer development grows larger every year. Individual genes and SNPs have been associated with cancer risk, as well as prognostic factors like survival and response to treatment, and have been used to construct genetic risk scores for cancer. Similarly epigenome-wide hypomethylation, hypermethylation of tumor suppressor genes, and age-related changes in DNA methylation and other epigenetic factors are all being identified as hallmarks of cancer. And yet challenges remain, such as integrating data on gene expression and other molecular markers to fully characterize the interactions of these ‘omics’ systems in relation to cancer development, prevention, diagnosis, and treatment. This Special Issue will focus on the role of (associations with) ‘omics’ and molecular factors in cancer, with an emphasis on the potential for new approaches in cancer precision medicine as well as barriers to the studying interconnected ‘omics’ systems in cancer epidemiology. This includes studies of methodology development, studies of lifestyle factors and gene-environment interactions, and other omics-related studies including metabolomics and the microbiome. Original research or secondary analyses of genetic and epigenetic factors in cancer are also welcome. 

Prof. Dr. Lifang Hou
Dr. Brian Joyce
Guest Editors

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. Cancers is an international peer-reviewed open access semimonthly 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 2900 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

  • genomics
  • epigenomics
  • molecular epidemiology
  • transcriptomics
  • gene-environment interaction
  • biomarkers
  • cancer risk factors
  • bioinformatics
  • metabolomics

Published Papers (2 papers)

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Research

21 pages, 10214 KiB  
Article
Identification of Ubiquitin-Related Gene-Pair Signatures for Predicting Tumor Microenvironment Infiltration and Drug Sensitivity of Lung Adenocarcinoma
by Yumei Li, Lanfen An, Zhe Jia, Jingxia Li, E Zhou, Feng Wu, Zhengrong Yin, Wei Geng, Tingting Liao, Wenjing Xiao, Jingjing Deng, Wenjuan Chen, Minglei Li and Yang Jin
Cancers 2022, 14(14), 3478; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14143478 - 18 Jul 2022
Cited by 2 | Viewed by 1887
Abstract
Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer worldwide, and new biomarkers are urgently required to guide more effective individualized therapy for patients. Ubiquitin-related genes (UbRGs) partially participate in the initiation and progression of lung cancer. In this study, we [...] Read more.
Lung adenocarcinoma (LUAD) is a common pathological type of lung cancer worldwide, and new biomarkers are urgently required to guide more effective individualized therapy for patients. Ubiquitin-related genes (UbRGs) partially participate in the initiation and progression of lung cancer. In this study, we used ubiquitin-related gene pairs (UbRGPs) in tumor tissues to access the function of UbRGs in overall survival, immunocyte infiltration, and tumor mutation burden (TMB) of patients with LUAD from The Cancer Genome Atlas (TCGA) database. In addition, we constructed a prognostic signature based on six UbRGPs and evaluated its performance in an internal (TCGA testing set) and an external validation set (GSE13213). The prognostic signature revealed that risk scores were negatively correlated with the overall survival, immunocyte infiltration, and expression of immune checkpoint inhibitor-related genes and positively correlated with the TMB. Patients in the high-risk group showed higher sensitivity to partially targeted and chemotherapeutic drugs than those in the low-risk group. This study contributes to the understanding of the characteristics of UbRGPs in LUAD and provides guidance for effective immuno-, chemo-, and targeted therapy. Full article
(This article belongs to the Special Issue Genetic and Molecular Approaches to Cancer Epidemiology: Opportunities and Challenges in the Precision Medicine Era)
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11 pages, 1088 KiB  
Article
Detecting Early-Stage Oral Cancer from Clinically Diagnosed Oral Potentially Malignant Disorders by DNA Methylation Profile
by Kazuki Mori, Tomofumi Hamada, Mahiro Beppu, Hiroki Tsuchihashi, Yuichi Goto, Kenichi Kume, Hiroshi Hijioka, Keitaro Nishi, Yumiko Mishima and Tsuyoshi Sugiura
Cancers 2022, 14(11), 2646; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14112646 - 26 May 2022
Cited by 4 | Viewed by 1607
Abstract
Clinically, early-stage oral cancers are difficult to distinguish from oral potentially malignant disorders (OPMDs), and invasive tissue biopsy should be performed to determine a treatment strategy. Previously, we focused on gargle fluid as a noninvasive testing method and reported aberrant methylation in gargle [...] Read more.
Clinically, early-stage oral cancers are difficult to distinguish from oral potentially malignant disorders (OPMDs), and invasive tissue biopsy should be performed to determine a treatment strategy. Previously, we focused on gargle fluid as a noninvasive testing method and reported aberrant methylation in gargle fluid in patients with oral cancer. This study aimed to distinguish early-stage oral cancer from clinically diagnosed OPMDs using gargle fluid samples. We collected gargle fluid samples from 40 patients who were clinically diagnosed with OPMDs in the training set; among them, 9 patients were pathologically diagnosed with oral cancer. Methylation levels of 25 tumor suppressor genes were analyzed using the methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) method. We found that a combination of six genes (TP73, CASP8, RARB, KLLN, GSTP1, and CHFR) could distinguish oral cancer from clinically diagnosed OPMDs with high diagnostic performance (area under the curve [AUC], 0.885; sensitivity, 77.8%; and specificity, 87.1%). Additionally, the panel comprised of the six methylated genes was validated in the test set. Furthermore, when compared with cytology testing, the panel could accurately detect oral cancer. The present methylated gene panel may serve as a novel biomarker for oral cancer. Full article
(This article belongs to the Special Issue Genetic and Molecular Approaches to Cancer Epidemiology: Opportunities and Challenges in the Precision Medicine Era)
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