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23 results on '"Cintolo-Gonzalez, Jessica"'

2. Impact of Social Determinants of Health on Melanoma Nodal Surveillance in a Multi-institutional Cohort

Author

Montgomery, Kelsey B., McLeod, M. Chandler, DePalo, Danielle K., Dugan, Michelle M., Zager, Jonathan S., Elleson, Kelly M., Sabel, Michael S., Hieken, Tina J., Kottschade, Lisa A., Ollila, David W., Pham, Veronica, Archer, Dion, Berman, Russell S., Lee, Ann Y., Cintolo-Gonzalez, Jessica A., McDonald, Hannah G., Winchester, Sydney, Burke, Erin E., Rhodin, Kristen E., Beasley, Georgia M., and Broman, Kristy K.

Published
2024
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3. ASO Visual Abstract: Impact of Social Determinants of Health on Melanoma Nodal Surveillance in a Multi-Institutional Cohort

Author

Montgomery, Kelsey B., Chandler McLeod, M., DePalo, Danielle K., Dugan, Michelle M., Zager, Jonathan S., Elleson, Kelly M., Sabel, Michael S., Hieken, Tina J., Kottschade, Lisa A., Ollila, David W., Pham, Veronica, Archer, Dion, Berman, Russell S., Lee, Ann Y., Cintolo-Gonzalez, Jessica A., McDonald, Hannah G., Winchester, Sydney, Burke, Erin E., Rhodin, Kristen E., Beasley, Georgia M., and Broman, Kristy K.

Published
2024
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13. Genetic Risk Prediction in Breast Cancer

Author

Nguyen, Anvy, primary, Plichta, Jennifer K., additional, Cintolo-Gonzalez, Jessica, additional, Kartal, Kinyas, additional, Griffin, Molly Elizabeth, additional, and Hughes, Kevin, additional

Published
2017
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15. Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Author

Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Shi, Alvin, Kasumova, Gyulnara G, Michaud, William A, Cintolo-Gonzalez, Jessica, Díaz-Martínez, Marta, Ohmura, Jacqueline, Mehta, Arnav, Chien, Isabel, Frederick, Dennie T, Cohen, Sonia, Plana, Deborah, Johnson, Douglas, Flaherty, Keith T, Sullivan, Ryan J, Kellis, Manolis, Boland, Genevieve M, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Shi, Alvin, Kasumova, Gyulnara G, Michaud, William A, Cintolo-Gonzalez, Jessica, Díaz-Martínez, Marta, Ohmura, Jacqueline, Mehta, Arnav, Chien, Isabel, Frederick, Dennie T, Cohen, Sonia, Plana, Deborah, Johnson, Douglas, Flaherty, Keith T, Sullivan, Ryan J, Kellis, Manolis, and Boland, Genevieve M

Abstract

Immune checkpoint inhibitors (ICIs) show promise, but most patients do not respond. We identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response. We undertook transcriptomic profiling of plasma-derived EVs and tumors from 50 patients with metastatic melanoma receiving ICI, and validated with an independent EV-only cohort of 30 patients. Plasma-derived EV and tumor transcriptomes correlate. EV profiles reveal drivers of ICI resistance and melanoma progression, exhibit differentially expressed genes/pathways, and correlate with clinical response to ICI. We created a Bayesian probabilistic deconvolution model to estimate contributions from tumor and non-tumor sources, enabling interpretation of differentially expressed genes/pathways. EV RNA-seq mutations also segregated ICI response. EVs serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, function as predictive markers of ICI responsiveness, and monitor tumor persistence and immune activation.

Published
2022

16. Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Author

Shi, Alvin, Kasumova, Gyulnara G, Michaud, William A, Cintolo-Gonzalez, Jessica, Díaz-Martínez, Marta, Ohmura, Jacqueline, Mehta, Arnav, Chien, Isabel, Frederick, Dennie T, Cohen, Sonia, Plana, Deborah, Johnson, Douglas, Flaherty, Keith T, Sullivan, Ryan J, Kellis, Manolis, Boland, Genevieve M, Shi, Alvin, Kasumova, Gyulnara G, Michaud, William A, Cintolo-Gonzalez, Jessica, Díaz-Martínez, Marta, Ohmura, Jacqueline, Mehta, Arnav, Chien, Isabel, Frederick, Dennie T, Cohen, Sonia, Plana, Deborah, Johnson, Douglas, Flaherty, Keith T, Sullivan, Ryan J, Kellis, Manolis, and Boland, Genevieve M

Abstract

Immune checkpoint inhibitors (ICIs) show promise, but most patients do not respond. We identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response. We undertook transcriptomic profiling of plasma-derived EVs and tumors from 50 patients with metastatic melanoma receiving ICI, and validated with an independent EV-only cohort of 30 patients. Plasma-derived EV and tumor transcriptomes correlate. EV profiles reveal drivers of ICI resistance and melanoma progression, exhibit differentially expressed genes/pathways, and correlate with clinical response to ICI. We created a Bayesian probabilistic deconvolution model to estimate contributions from tumor and non-tumor sources, enabling interpretation of differentially expressed genes/pathways. EV RNA-seq mutations also segregated ICI response. EVs serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, function as predictive markers of ICI responsiveness, and monitor tumor persistence and immune activation.

Published
2021

18. Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Author

Shi, Alvin, primary, Kasumova, Gyulnara G., additional, Michaud, William A., additional, Cintolo-Gonzalez, Jessica, additional, Díaz-Martínez, Marta, additional, Ohmura, Jacqueline, additional, Mehta, Arnav, additional, Chien, Isabel, additional, Frederick, Dennie T., additional, Cohen, Sonia, additional, Plana, Deborah, additional, Johnson, Douglas, additional, Flaherty, Keith T., additional, Sullivan, Ryan J., additional, Kellis, Manolis, additional, and Boland, Genevieve M., additional

Published
2020
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19. Abstract A35: BRAF inhibition increases exosomal PD-L1 protein expression in melanoma

Author

Kasumova, Gyulnara G., primary, Shi, Alvin, additional, Cintolo-Gonzalez, Jessica A., additional, Chein, Isabel, additional, Frederick, Dennie T., additional, Alpatov, Roman, additional, Michaud, William A., additional, Plana, Deborah, additional, Panka, David J., additional, Corcoran, Ryan B., additional, Flaherty, Keith T., additional, Sullivan, Ryan J., additional, Kellis, Manolis, additional, and Boland, Genevieve M., additional

Published
2018
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20. Abstract B25: Exosomal transcriptomic signatures tracks and predicts response to checkpoint blockade immunotherapy

Author

Shi, Alvin, primary, Cintolo-Gonzalez, Jessica A., additional, Chien, Isabel, additional, Frederick, Dennis T., additional, Alpatov, Roman, additional, Michaud, William, additional, Plana, Deborah, additional, Panka, David, additional, Corcoran, Ryan, additional, Flaherty, Keith, additional, Sullivan, Ryan, additional, Kellis, Manolis, additional, and Boland, Genevieve, additional

Published
2018
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21. Abstract 4282: Deconvolution of plasma-derived exosomes for tracking and prediction of immunotherapy across multiple tissues

Author

Shi, Alvin, primary, Kasumova, Gyulnara, additional, Chien, Isabel, additional, Cintolo-Gonzalez, Jessica, additional, Frederick, Dennie T., additional, Alpatov, Roman, additional, Michaud, William A., additional, Plana, Deborah, additional, Corcoran, Ryan, additional, Flaherty, Keith, additional, Sullivan, Ryan, additional, Kellis, Manolis, additional, and Boland, Genevieve, additional

Published
2018
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