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A quantitative characterization of the spatial distribution of brain metastases from breast cancer and respective molecular subtypes

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Abstract

Purpose

Brain metastases (BM) remain a significant cause of morbidity and mortality in breast cancer (BC) patients. Specific factors promoting the process of BM and predilection for selected neuro-anatomical regions remain unknown, yet may have major implications for prevention or treatment. Anatomical spatial distributions of BM from BC suggest a predominance of metastases in the hindbrain and cerebellum. Systematic approaches to quantifying BM location or location-based analyses based on molecular subtypes, however, remain largely unavailable.

Methods

We analyzed stereotactic Cartesian coordinates derived from 134 patients undergoing gamma- knife radiosurgery (GKRS) for treatment of 407 breast cancer BMs to quantitatively study BM spatial distribution along principal component axes and by intrinsic molecular subtype (ER, PR, Herceptin). We used kernel density estimators (KDE) to highlight clustering and distribution regions in the brain, and we used the metric of mutual information (MI) to tease out subtle differences in the BM distributions associated with different molecular subtypes of BC. BM location maps according to vascular and anatomical distributions using Cartesian coordinates to aid in systematic classification of tumor locations were additionally developed.

Results

We corroborated that BC BMs show a consistent propensity to arise posteriorly and caudally, and that Her2+ tumors are relatively more likely to arise medially rather than laterally. To compare the distributions among varying BC molecular subtypes, the mutual information metric reveal that the ER−PR−Her2+ and ER−PR−Her2− subtypes show the smallest amount of mutual information and are most molecularly distinct. The kernel density contour plots show a propensity for triple negative BC to arise in more superiorly or cranially situated BMs.

Conclusions

We present a novel and shareable workflow for characterizing and comparing spatial distributions of BM which may aid in identifying therapeutic or diagnostic targets and interactions with the tumor microenvironment. Further characterization of these patterns with larger multi-institutional data-sets may have major impacts on treatment or management of cancer patients.

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Acknowledgements

Partial funding through the USC Norris Comprehensive Cancer Center’s Multi-Level Cancer Risk Prediction Models pilot Project Award, ’Molecular, Clinical and Neuro-imaging Determinants of Spatiotemporal Pathogenesis of Cancer-Specific Brain Metastases: Data Analysis and Longitudinal Modeling’ (12/01/2020-11/30/2021) is gratefully acknowledged.

Funding

Funding was provided by National Institutes of Health (Grant no. USC Norris Comprehensive Cancer Center Pilot Award).

Author information

Authors and Affiliations

  1. Department of Neurosurgery, Keck School of Medicine of University of Southern California, 1300 N. State Street, Suite 3300, Los Angeles, CA, 90033, USA

    Dhiraj J. Pangal, Tyler Cardinal, Josh Neman & Gabriel Zada

  2. Department of Aerospace and Mechanical Engineering, Mathematics and The Ellison Institute for Transformative Medicine of University of Southern California, Viterbi School of Engineering of University of Southern California, 854 Downey Way, Los Angeles, CA, 90089, USA

    Paul K. Newton

  3. Department of Physics, Astronomy of University of Southern California, Los Angeles, CA, 90089, USA

    Saeedeh Mahmoodifar

  4. Department of Translational Genomics, Keck School of Medicine of University of Southern California, 1450 Biggy Street, Los Angeles, CA, 90033, USA

    David Craig, Thomas Simon, Ben Yi Tew & Bodour Salhia

  5. Convergent Science Institute in Cancer, Michelson Center for Convergent Bioscience of University of Southern California, Los Angeles, CA, 90089, USA

    Jeremy Mason

  6. Catherine Joseph Aresty Department of Urology, Institute of Urology, Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA

    Jeremy Mason

  7. Keck School of Medicine of University of Southern California, Los Angeles, CA, 90033, USA

    Wensha Yang, Eric Chang, Min Yu & Arthur Toga

Authors
  1. Saeedeh Mahmoodifar
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  2. Dhiraj J. Pangal
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  3. Tyler Cardinal
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  4. David Craig
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  6. Ben Yi Tew
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  7. Wensha Yang
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  8. Eric Chang
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  9. Min Yu
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  10. Josh Neman
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  11. Jeremy Mason
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  13. Bodour Salhia
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  14. Gabriel Zada
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  15. Paul K. Newton
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Correspondence to Paul K. Newton.

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Mahmoodifar, S., Pangal, D.J., Cardinal, T. et al. A quantitative characterization of the spatial distribution of brain metastases from breast cancer and respective molecular subtypes. J Neurooncol 160, 241–251 (2022). https://doi.org/10.1007/s11060-022-04147-9

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  • DOI: https://doi.org/10.1007/s11060-022-04147-9

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