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Discovery and validation of tissue-specific DNA methylation as noninvasive diagnostic markers for colorectal cancer. Clin Epigenetics 2022; 14:102. [PMID: 35974349 PMCID: PMC9382793 DOI: 10.1186/s13148-022-01312-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 07/12/2022] [Indexed: 11/20/2022] Open
Abstract
Background Noninvasive diagnostic markers that are capable of distinguishing patients with colorectal cancer (CRC) from healthy individuals or patients with other cancer types are lacking. We report the discovery and validation of a panel of methylation-based markers that specifically detect CRC. Methods This was a large-scale discovery study based on publicly available datasets coupled with a validation study where multiple types of specimens from six cohorts with CRC, other cancer types, and healthy individuals were used to identify and validate the tissue-specific methylation patterns of CRC and assess their diagnostic performance. Results In the discovery and validation cohort (N = 9307), ten hypermethylated CpG sites located in three genes, C20orf194, LIFR, and ZNF304, were identified as CRC-specific markers. Different analyses have suggested that these CpG sites are CRC-specific hypermethylated and play a role in transcriptional silencing of corresponding genes. A random forest model based on ten markers achieved high accuracy rates between 85.7 and 94.3% and AUCs between 0.941 and 0.970 in predicting CRC in three independent datasets and a low misclassification rate in ten other cancer types. In the in-house validation cohort (N = 354), these markers achieved consistent discriminative capabilities. In the cfDNA pilot cohort (N = 14), hypermethylation of these markers was observed in cfDNA samples from CRC patients. In the cfDNA validation cohort (N = 155), the two-gene panel yielded a sensitivity of 69.5%, specificity of 91.7%, and AUC of 0.806. Conclusions Hypermethylation of the ten CpG sites is a CRC-specific alteration in tissue and has the potential use as a noninvasive cfDNA marker to diagnose CRC. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01312-9.
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Halder S, Parte S, Kshirsagar P, Muniyan S, Nair HB, Batra SK, Seshacharyulu P. The Pleiotropic role, functions and targeted therapies of LIF/LIFR axis in cancer: Old spectacles with new insights. Biochim Biophys Acta Rev Cancer 2022; 1877:188737. [PMID: 35680099 PMCID: PMC9793423 DOI: 10.1016/j.bbcan.2022.188737] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/09/2022] [Accepted: 05/28/2022] [Indexed: 12/30/2022]
Abstract
The dysregulation of leukemia inhibitory factor (LIF) and its cognate receptor (LIFR) has been associated with multiple cancer initiation, progression, and metastasis. LIF plays a significant tumor-promoting role in cancer, while LIFR functions as a tumor promoter and suppressor. Epithelial and stromal cells secrete LIF via autocrine and paracrine signaling mechanism(s) that bind with LIFR and subsequently with co-receptor glycoprotein 130 (gp130) to activate JAK/STAT1/3, PI3K/AKT, mTORC1/p70s6K, Hippo/YAP, and MAPK signaling pathways. Clinically, activating the LIF/LIFR axis is associated with poor survival and anti-cancer therapy resistance. This review article provides an overview of the structure and ligands of LIFR, LIF/LIFR signaling in developmental biology, stem cells, cancer stem cells, genetics and epigenetics of LIFR, LIFR regulation by long non-coding RNAs and miRNAs, and LIF/LIFR signaling in cancers. Finally, neutralizing antibodies and small molecule inhibitors preferentially blocking LIF interaction with LIFR and antagonists against LIFR under pre-clinical and early-phase pre-clinical trials were discussed.
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Affiliation(s)
- Sushanta Halder
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA
| | - Seema Parte
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA
| | - Prakash Kshirsagar
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA
| | - Sakthivel Muniyan
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA
| | | | - Surinder K. Batra
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA,Eppley Institute for Research in Cancer and Allied Diseases, USA,Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA,Corresponding authors at: Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA. (S.K. Batra), (P. Seshacharyulu)
| | - Parthasarathy Seshacharyulu
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA,Eppley Institute for Research in Cancer and Allied Diseases, USA,Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA,Corresponding authors at: Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE 68198-5870, USA. (S.K. Batra), (P. Seshacharyulu)
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Roberts ML, Kotchen TA, Pan X, Li Y, Yang C, Liu P, Wang T, Laud PW, Chelius TH, Munyura Y, Mattson DL, Liu Y, Cowley AW, Kidambi S, Liang M. Unique Associations of DNA Methylation Regions With 24-Hour Blood Pressure Phenotypes in Blacks. Hypertension 2022; 79:761-772. [PMID: 34994206 PMCID: PMC8917053 DOI: 10.1161/hypertensionaha.121.18584] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Epigenetic marks (eg, DNA methylation) may capture the effect of gene-environment interactions. DNA methylation is involved in blood pressure (BP) regulation and hypertension development; however, no studies have evaluated its relationship with 24-hour BP phenotypes (daytime, nighttime, and 24-hour average BPs). METHODS We examined the association of whole blood DNA methylation with 24-hour BP phenotypes and clinic BPs in a discovery cohort of 281 Blacks using reduced representation bisulfite sequencing. We developed a deep and region-specific methylation sequencing method, Bisulfite ULtrapLEx Targeted Sequencing and utilized it to validate our findings in a separate validation cohort (n=117). RESULTS Analysis of 38 215 DNA methylation regions (MRs), derived from 1 549 368 CpG sites across the genome, identified up to 72 regions that were significantly associated with 24-hour BP phenotypes. No MR was significantly associated with clinic BP. Two to 3 MRs were significantly associated with various 24-hour BP phenotypes after adjustment for age, sex, and body mass index. Together, these MRs explained up to 16.5% of the variance of 24-hour average BP, while age, sex, and BMI explained up to 11.0% of the variance. Analysis of one of the MRs in an independent cohort using Bisulfite ULtrapLEx Targeted Sequencing confirmed its association with 24-hour average BP phenotype. CONCLUSIONS We identified several MRs that explain a substantial portion of variances in 24-hour BP phenotypes, which might be excellent markers of cumulative effect of factors influencing 24-hour BP levels. The Bisulfite ULtrapLEx Targeted Sequencing workflow has potential to be suitable for clinical testing and population screenings on a large scale.
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Affiliation(s)
- Michelle L Roberts
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Theodore A Kotchen
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - Xiaoqing Pan
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,Department of Mathematics, Shanghai Normal University, China (X.P.)
| | - Yingchuan Li
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,Department of Critical Care Medicine, Shanghai JiaoTong University affiliated the Sixth People's Hospital, China (Y.L.)
| | - Chun Yang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Pengyuan Liu
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.).,The Sir Run Run Shaw Hospital, Institute of Translational Medicine, Zhejiang University, China (P.L.)
| | | | - Purushottam W Laud
- Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee. (P.W.L.)
| | - Thomas H Chelius
- Division of Epidemiology, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee. (T.H.C.)
| | - Yannick Munyura
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - David L Mattson
- Department of Physiology, Medical College of Georgia, Augusta (D.L.M.)
| | | | - Allen W Cowley
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
| | - Srividya Kidambi
- Department of Medicine, Medical College of Wisconsin, Milwaukee. (T.A.K., Y.M., S.K.)
| | - Mingyu Liang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee. (M.L.R., X.P., Y.L., C.Y., P.L., F.L.M., A.W.C., M.L.)
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Zhang W, Chen X, Wong KC. Noninvasive early diagnosis of intestinal diseases based on artificial intelligence in genomics and microbiome. J Gastroenterol Hepatol 2021; 36:823-831. [PMID: 33880763 DOI: 10.1111/jgh.15500] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 03/15/2021] [Accepted: 03/17/2021] [Indexed: 12/15/2022]
Abstract
The maturing development in artificial intelligence (AI) and genomics has propelled the advances in intestinal diseases including intestinal cancer, inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS). On the other hand, colorectal cancer is the second most deadly and the third most common type of cancer in the world according to GLOBOCAN 2020 data. The mechanisms behind IBD and IBS are still speculative. The conventional methods to identify colorectal cancer, IBD, and IBS are based on endoscopy or colonoscopy to identify lesions. However, it is invasive, demanding, and time-consuming for early-stage intestinal diseases. To address those problems, new strategies based on blood and/or human microbiome in gut, colon, or even feces were developed; those methods took advantage of high-throughput sequencing and machine learning approaches. In this review, we summarize the recent research and methods to diagnose intestinal diseases with machine learning technologies based on cell-free DNA and microbiome data generated by amplicon sequencing or whole-genome sequencing. Those methods play an important role in not only intestinal disease diagnosis but also therapy development in the near future.
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Affiliation(s)
- Weitong Zhang
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
| | - Xingjian Chen
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
| | - Ka-Chun Wong
- Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR.,Hong Kong Institute for Data Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
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Min B, Jeon K, Park JS, Kang Y. Demethylation and derepression of genomic retroelements in the skeletal muscles of aged mice. Aging Cell 2019; 18:e13042. [PMID: 31560164 PMCID: PMC6826136 DOI: 10.1111/acel.13042] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 08/07/2019] [Accepted: 08/30/2019] [Indexed: 12/13/2022] Open
Abstract
Changes in DNA methylation influence the aging process and contribute to aging phenotypes, but few studies have been conducted on DNA methylation changes in conjunction with skeletal muscle aging. We explored the DNA methylation changes in a variety of retroelement families throughout aging (at 2, 20, and 28 months of age) in murine skeletal muscles by methyl‐binding domain sequencing (MBD‐seq). The two following contrasting patterns were observed among the members of each repeat family in superaged mice: (a) hypermethylation in weakly methylated retroelement copies and (b) hypomethylation in copies with relatively stronger methylation levels, representing a pattern of “regression toward the mean” within a single retroelement family. Interestingly, these patterns depended on the sizes of the copies. While the majority of the elements showed a slight increase in methylation, the larger copies (>5 kb) displayed evident demethylation. All these changes were not observed in T cells. RNA sequencing revealed a global derepression of retroelements during the late phase of aging (between 20 and 28 months of age), which temporally coincided with retroelement demethylation. Following this methylation drift trend of “regression toward the mean,” aging tended to progressively lose the preexisting methylation differences and local patterns in the genomic regions that had been elaborately established during the early period of development.
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Affiliation(s)
- Byungkuk Min
- Development and Differentiation Research Center Korea Research Institute of Bioscience Biotechnology (KRIBB) Daejeon Korea
| | - Kyuheum Jeon
- Development and Differentiation Research Center Korea Research Institute of Bioscience Biotechnology (KRIBB) Daejeon Korea
- Department of Functional Genomics University of Science and Technology (UST) Daejeon Korea
| | - Jung Sun Park
- Development and Differentiation Research Center Korea Research Institute of Bioscience Biotechnology (KRIBB) Daejeon Korea
| | - Yong‐Kook Kang
- Development and Differentiation Research Center Korea Research Institute of Bioscience Biotechnology (KRIBB) Daejeon Korea
- Department of Functional Genomics University of Science and Technology (UST) Daejeon Korea
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