Dynamics and Statistics of Cancer Evolution : Applying Mathematics to Experimental and Clinical Data / Evolution tumorale, dynamique et statistiques: mathématiques pour données cliniques & expérimentales

Collection Dynamics and Statistics of Cancer Evolution : Applying Mathematics to Experimental and Clinical Data / Evolution tumorale, dynamique et statistiques: mathématiques pour données cliniques & expérimentales

Organizer(s) Curtius, Kathleen ; Huang, Weini ; Martinez, Pierre ; Werner, Benjamin ; Williams, Marc

Date(s) 06/06/2022 - 10/06/2022

linked URL https://conferences.cirm-math.fr/2409.html

00:00:00 / 00:00:00

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Every patient deserves their own equation: Sex, drugs and radiomics of brain Cancer

By Kristin Swanson

mathematical oncology

Glioblastoma are notoriously aggressive, malignant primary brain tumors that have variable response to treatment. This presentation will focus on the integrative role of 1) biological sex-differences, 2) heterogeneity in drug-delivery and 3) intra-tumoral molecular diversity (revealed by radiomics) in capturing and predicting this variable response to treatment. Specifically, I will highlight burgeoning insights into sex differences in tumor incidence, outcomes, propensity and response to therapy. I will further, quantify the degree to which heterogeneity in drug delivery, even for drugs that are able to bypass the blood-brain barrier, contributes to differences in treatment response. Lastly, I will propose an integrative role for spatially resolved MRI-based radiomics models to reveal the intra-tumoral biological heterogeneity that can be used to guide treatment targeting and management.

Information about the video

Date of recording 07/06/2022
Date of publication 01/07/2022
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers, Graduate Students
Director(s) Guillaume Hennenfent
Format MP4

Citation data

DOI 10.24350/CIRM.V.19931803
Cite this video Swanson, Kristin (07/06/2022). Every patient deserves their own equation: Sex, drugs and radiomics of brain Cancer. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19931803
URL https://dx.doi.org/10.24350/CIRM.V.19931803

Domain(s)

Quantitative Biology

Bibliography

HU, Leland S., WANG, Lujia, HAWKINS-DAARUD, Andrea, et al. Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma. Scientific reports, 2021, vol. 11, no 1, p. 1-14. - https://doi.org/10.1038/s41598-021-83141-z
MASSEY, Susan Christine, WHITMIRE, Paula, DOYLE, Tatum E., et al. Sex differences in health and disease: A review of biological sex differences relevant to cancer with a spotlight on glioma. Cancer letters, 2021, vol. 498, p. 178-187. - https://doi.org/10.1016/j.canlet.2020.07.030
URCUYO, Javier C., MASSEY, Susan Christine, HAWKINS-DAARUD, Andrea, et al. Complementary role of mathematical modeling in preclinical glioblastoma: differentiating poor drug delivery from drug insensitivity. bioRxiv, 2021. - https://doi.org/10.1101/2021.12.07.471540
WHITMIRE, Paula, RICKERTSEN, Cassandra R., HAWKINS-DAARUD, Andrea, et al. Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients. BMC cancer, 2020, vol. 20, no 1, p. 1-10. - https://doi.org/10.1186/s12885-020-06816-2
MORRIS, Bethan, CURTIN, Lee, HAWKINS-DAARUD, Andrea, et al. Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations. Mathematical biosciences and engineering: MBE, 2020, vol. 17, no 5, p. 4905. - https://doi.org/10.3934/mbe.2020267
SINGLETON, Kyle W., PORTER, Alyx B., HU, Leland S., et al. Days gained response discriminates treatment response in patients with recurrent glioblastoma receiving bevacizumab-based therapies. Neuro-oncology advances, 2020, vol. 2, no 1, p. vdaa085. - https://doi.org/10.1093/noajnl/vdaa085
GAW, Nathan, HAWKINS-DAARUD, Andrea, HU, Leland S., et al. Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI. Scientific reports, 2019, vol. 9, no 1, p. 1-9. - https://doi.org/10.1038/s41598-019-46296-4
HAWKINS-DAARUD, Andrea, JOHNSTON, Sandra K., et SWANSON, Kristin R. Quantifying uncertainty and robustness in a biomathematical model–based patient-specific response metric for glioblastoma. JCO clinical cancer informatics, 2019, vol. 3, p. 1-8. - http://dx.doi.org/10.1200/CCI.18.00066
YANG, Wei, WARRINGTON, Nicole M., TAYLOR, Sara J., et al. Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data. Science translational medicine, 2019, vol. 11, no 473, p. eaao5253. - https://doi.org/10.1126/scitranslmed.aao5253

MSC codes

92C50 Medical applications

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