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Massachusetts Institute of Technology

Mapping the therapy resistance landscapes of acute leukemias using in vivo functional genomics

Abstract

dc:description.abstract

The recurrence of therapy resistant disease remains an intractable problem in oncology clinical care. To address this issue, investigators have traditionally focused on elucidating cell-intrinsic mechanisms that render tumors refractory to both classical chemotherapeutics and targeted agents. However, cancers resident in organs throughout the body do not develop in isolation. Instead, tumors arise in the context of the non-malignant components of a tissue, defined as the tumor microenvironement (TME). While the importance of cell-extrinsic factors in cancer biology is well established, our understanding of the TME's influence on therapeutic outcome is in its infancy. Pooled in vivo screens offer an unbiased strategy for identifying novel resistance mediators in the context of a normal immune system and microenvironment.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Biology
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ramos, Azucena.
Advisor dc:contributor.advisor
  • Michael T. Hemann.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/129040
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/129040

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Ramos, Azucena.. Mapping the therapy resistance landscapes of acute leukemias using in vivo functional genomics. Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129040