TY - JOUR
T1 - Spatial Distance Correlates With Genetic Distance in Diffuse Glioma
AU - Gates, Evan D.H.
AU - Yang, Jie
AU - Fukumura, Kazutaka
AU - Lin, Jonathan S.
AU - Weinberg, Jeffrey S.
AU - Prabhu, Sujit S.
AU - Long, Lihong
AU - Fuentes, David
AU - Sulman, Erik P.
AU - Huse, Jason T.
AU - Schellingerhout, Dawid
N1 - Funding Information:
Funding. UT MD Anderson Institutional Research Grant (DS). UT MD Anderson Clinical Research Trial Support (DS). UT MD Anderson Diagnostic Imaging Clinical Research Committee Imaging costs support (DS). UT MD Anderson Sequencing and Microarray Facility Core grant CA016672(SMF) provided support for exome sequencing. EG is supported by a fellowship from the Gulf Coast Consortia on the NLM Training Program in Biomedical Science and Data Science T15LM007093.
Publisher Copyright:
© Copyright © 2019 Gates, Yang, Fukumura, Lin, Weinberg, Prabhu, Long, Fuentes, Sulman, Huse and Schellingerhout.
PY - 2019/7/30
Y1 - 2019/7/30
N2 - 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.
AB - 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.
KW - epigenetics
KW - genomics
KW - glioma
KW - imaging genomics
KW - medical image analysis
KW - radiologic-pathologic correlation
KW - radiomics
KW - stereotactic biopsy
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U2 - 10.3389/fonc.2019.00676
DO - 10.3389/fonc.2019.00676
M3 - Article
C2 - 31417865
AN - SCOPUS:85072731215
SN - 2234-943X
VL - 9
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 676
ER -