Spatial Distance Correlates With Genetic Distance in Diffuse Glioma
Background: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatial...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
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Frontiers Media S.A.
2019-07-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fonc.2019.00676/full |
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| author | Evan D. H. Gates Evan D. H. Gates Jie Yang Jie Yang Kazutaka Fukumura Jonathan S. Lin Jonathan S. Lin Jonathan S. Lin Jeffrey S. Weinberg Sujit S. Prabhu Lihong Long David Fuentes Erik P. Sulman Jason T. Huse Jason T. Huse Dawid Schellingerhout |
| author_facet | Evan D. H. Gates Evan D. H. Gates Jie Yang Jie Yang Kazutaka Fukumura Jonathan S. Lin Jonathan S. Lin Jonathan S. Lin Jeffrey S. Weinberg Sujit S. Prabhu Lihong Long David Fuentes Erik P. Sulman Jason T. Huse Jason T. Huse Dawid Schellingerhout |
| author_sort | Evan D. H. Gates |
| collection | DOAJ |
| description | Background: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatially within the tumor is qualitative, and quantitative data is lacking. We hypothesized that a greater genetic diversity or “genetic distance” would be observed for distinct tumor samples taken with larger physical distances between them.Methods: Stereotactic biopsies were obtained from untreated primary glioma patients as part of a clinical trial between 2011 and 2016, with at least one biopsy pair collected in each case. The physical (Euclidean) distance between biopsy sites was determined using coordinates from imaging studies. The tissue samples underwent whole exome DNA sequencing and epigenetic methylation profiling and genomic distances were defined in three separate ways derived from differences in number of genes, copy number variations (CNV), and methylation profiles.Results: Of the 31 patients recruited to the trial, 23 were included in DNA methylation analysis, for a total of 71 tissue samples (14 female, 9 male patients, age range 21–80). Samples from an 8 patient subset of the 23 evaluated patients were further included in whole exome and copy number variation analysis. Physical and genomic distances were found to be independently and positively correlated for each of the three genomic distance measures. The correlation coefficients were 0.63, 0.65, and 0.35, respectively for (a) gene level mutations, (b) copy number variation, and (c) methylation status. We also derived quantitative linear relationships between physical and genomic distances.Conclusion: Primary brain tumors are genetically heterogeneous, and the physical distance within a given glioma correlates to genomic distance using multiple orthogonal genomic assessments. These data should be helpful in the clinical diagnostic and therapeutic management of glioma, for example by: managing sampling error, and estimating genetic heterogeneity using simple imaging inputs. |
| first_indexed | 2024-12-23T13:34:33Z |
| format | Article |
| id | doaj.art-0e2fdedf54be427fab9129620dff1a0c |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-23T13:34:33Z |
| publishDate | 2019-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-0e2fdedf54be427fab9129620dff1a0c2022-12-21T17:45:03ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2019-07-01910.3389/fonc.2019.00676468863Spatial Distance Correlates With Genetic Distance in Diffuse GliomaEvan D. H. Gates0Evan D. H. Gates1Jie Yang2Jie Yang3Kazutaka Fukumura4Jonathan S. Lin5Jonathan S. Lin6Jonathan S. Lin7Jeffrey S. Weinberg8Sujit S. Prabhu9Lihong Long10David Fuentes11Erik P. Sulman12Jason T. Huse13Jason T. Huse14Dawid Schellingerhout15Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesGraduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, United StatesGraduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth, Houston, TX, United StatesDepartment of Radiation Oncology, NYU Langone School of Medicine, New York, NY, United StatesDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesMedical Scientist Training Program, Baylor College of Medicine, Houston, TX, United StatesDepartment of Bioengineering, Rice University, Houston, TX, United StatesDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Radiation Oncology, NYU Langone School of Medicine, New York, NY, United StatesDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United StatesDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States0Departments of Neuroradiology and Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, United StatesBackground: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatially within the tumor is qualitative, and quantitative data is lacking. We hypothesized that a greater genetic diversity or “genetic distance” would be observed for distinct tumor samples taken with larger physical distances between them.Methods: Stereotactic biopsies were obtained from untreated primary glioma patients as part of a clinical trial between 2011 and 2016, with at least one biopsy pair collected in each case. The physical (Euclidean) distance between biopsy sites was determined using coordinates from imaging studies. The tissue samples underwent whole exome DNA sequencing and epigenetic methylation profiling and genomic distances were defined in three separate ways derived from differences in number of genes, copy number variations (CNV), and methylation profiles.Results: Of the 31 patients recruited to the trial, 23 were included in DNA methylation analysis, for a total of 71 tissue samples (14 female, 9 male patients, age range 21–80). Samples from an 8 patient subset of the 23 evaluated patients were further included in whole exome and copy number variation analysis. Physical and genomic distances were found to be independently and positively correlated for each of the three genomic distance measures. The correlation coefficients were 0.63, 0.65, and 0.35, respectively for (a) gene level mutations, (b) copy number variation, and (c) methylation status. We also derived quantitative linear relationships between physical and genomic distances.Conclusion: Primary brain tumors are genetically heterogeneous, and the physical distance within a given glioma correlates to genomic distance using multiple orthogonal genomic assessments. These data should be helpful in the clinical diagnostic and therapeutic management of glioma, for example by: managing sampling error, and estimating genetic heterogeneity using simple imaging inputs.https://www.frontiersin.org/article/10.3389/fonc.2019.00676/fullgliomagenomicsepigeneticsstereotactic biopsymedical image analysisradiomics |
| spellingShingle | Evan D. H. Gates Evan D. H. Gates Jie Yang Jie Yang Kazutaka Fukumura Jonathan S. Lin Jonathan S. Lin Jonathan S. Lin Jeffrey S. Weinberg Sujit S. Prabhu Lihong Long David Fuentes Erik P. Sulman Jason T. Huse Jason T. Huse Dawid Schellingerhout Spatial Distance Correlates With Genetic Distance in Diffuse Glioma Frontiers in Oncology glioma genomics epigenetics stereotactic biopsy medical image analysis radiomics |
| title | Spatial Distance Correlates With Genetic Distance in Diffuse Glioma |
| title_full | Spatial Distance Correlates With Genetic Distance in Diffuse Glioma |
| title_fullStr | Spatial Distance Correlates With Genetic Distance in Diffuse Glioma |
| title_full_unstemmed | Spatial Distance Correlates With Genetic Distance in Diffuse Glioma |
| title_short | Spatial Distance Correlates With Genetic Distance in Diffuse Glioma |
| title_sort | spatial distance correlates with genetic distance in diffuse glioma |
| topic | glioma genomics epigenetics stereotactic biopsy medical image analysis radiomics |
| url | https://www.frontiersin.org/article/10.3389/fonc.2019.00676/full |
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