<P><B>Summary</B></P> <P>Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the deg...
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https://www.riss.kr/link?id=A107455651
Malta, Tathiane M. ; Sokolov, Artem ; Gentles, Andrew J. ; Burzykowski, Tomasz ; Poisson, Laila ; Weinstein, John N. ; Kamiń ; ska, Boż ; ena ; Huelsken, Joerg ; Omberg, Larsson ; Gevaert, Olivier ; Colaprico, Antonio ; Czerwiń ; ska, Patrycja ; Mazurek, Sylwia ; Mishra, Lopa ; Heyn, Holger ; Krasnitz, Alex ; Godwin, Andrew K. ; Lazar, Alexander J. ; Caesar-Johnson, Samantha J. ; Demchok, John A. ; Felau, Ina ; Kasapi, Melpomeni ; Ferguson, Martin L. ; Hutter, Carolyn M. ; Sofia, Heidi J. ; Tarnuzzer, Roy ; Wang, Zhining ; Yang, Liming ; Zenklusen, Jean C. ; Zhang, Jiashan (Julia) ; Chudamani, Sudha ; Liu, Jia ; Lolla, Laxmi ; Naresh, Rashi ; Pihl, Todd ; Sun, Qiang ; Wan, Yunhu ; Wu, Ye ; Cho, Juok ; DeFreitas, Timothy ; Frazer, Scott ; Gehlenborg, Nils ; Getz, Gad ; Heiman, David I. ; Kim, Jaegil ; Lawrence, Michael S. ; Lin, Pei ; Meier, Sam ; Noble, Michael S. ; Saksena, Gordon ; Voet, Doug ; Zhang, Hailei ; Bernard, Brady ; Chambwe, Nyasha ; Dhankani, Varsha ; Knijnenburg
2018
-
SCI,SCIE,SCOPUS
학술저널
338-35415(35078쪽)
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
<P><B>Summary</B></P> <P>Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the deg...
<P><B>Summary</B></P> <P>Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.</P> <P><B>Video Abstract</B></P> <P>Display Omitted</P> <P><B>Highlights</B></P> <P> <UL> <LI> Epigenetic and expression-based stemness indices measure oncogenic dedifferentiation </LI> <LI> Immune microenvironment content and PD-L1 levels associate with stemness indices </LI> <LI> Stemness index is increased in metastatic tumors and reveals intratumor heterogeneity </LI> <LI> Applying stemness indices reveals potential drug targets for anti-cancer therapies </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>
Pathogenic Germline Variants in 10,389 Adult Cancers
Oncogenic Signaling Pathways in The Cancer Genome Atlas
Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics