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Multi-modal molecular programs regulate melanoma cell state

delete2022-07-09
delete11
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OA
AI
M
Miles C. Andrews
J
Junna Oba
C
Chang‐Jiun Wu
H
Haifeng Zhu
T
Tatiana V. Karpinets
C
Caitlin Creasy
M
Marie‐Andrée Forget
X
Xiaoxing Yu
X
Xingzhi Song
X
Xizeng Mao
A
A. Gordon Robertson
G
Gabriele Romano
P
Peng Li
E
Elizabeth M. Burton
Y
Yiling Lu
R
Robert Szczepaniak‐Sloane
K
Khalida Wani
K
Kunal Rai
A
Alexander J. Lazar
L
Lauren E. Haydu
M
Matías A. Bustos
J
Jianjun Shen
Y
Yueping Chen
M
Margaret Morgan
J
Jennifer A. Wargo
L
Lawrence N. Kwong
C
Cara Haymaker
E
Elizabeth A. Grimm
P
Patrick Hwu
D
Dave S.�B. Hoon
张建华 cover
张建华 (Jianhua Zhang)
J
Jeffrey E. Gershenwald
M
Michael A. Davies
P
P. Andrew Futreal
C
Chantale Bernatchez
S
Scott E. Woodman *
DOI:10.1038/s41467-022-31510-1delete
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Abstract

Abstract

En 中文
The regulation of the distinct intrinsic phenotypic states in melanoma remain poorly characterised. Here, multi-omics analysis for a panel of 68 early passage melanoma cell lines reveals that cancer cell intrinsic transcriptomic programs are associated with distinct immune features. Melanoma cells display distinct intrinsic phenotypic states. Here, we seek to characterize the molecular regulation of these states using multi-omic analyses of whole exome, transcriptome, microRNA, long non-coding RNA and DNA methylation data together with reverse-phase protein array data on a panel of 68 highly annotated early passage melanoma cell lines. We demonstrate that clearly defined cancer cell intrinsic transcriptomic programs are maintained in melanoma cells ex vivo and remain highly conserved within melanoma tumors, are associated with distinct immune features within tumors, and differentially correlate with checkpoint inhibitor and adoptive T cell therapy efficacy. Through integrative analyses we demonstrate highly complex multi-omic regulation of melanoma cell intrinsic programs that provide key insights into the molecular maintenance of phenotypic states. These findings have implications for cancer biology and the identification of new therapeutic strategies. Further, these deeply characterized cell lines will serve as an invaluable resource for future research in the field.
Keywords:
MICRORNA TARGET PREDICTION
INTEGRATIVE ANALYSIS
CTLA-4 BLOCKADE
COPY-NUMBER
GENE
EXPRESSION
IMMUNOTHERAPY
MITF
QUANTIFICATION
CLASSIFICATION
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Journal

Nature Communications cover
Nature Communications
IF:
15.7
Papers:
9.2W
Citations:
91.2W

Organization

M
Monash University
Scholars:
5.4W
Papers: 5.4W
Citations: 79
K
Keio University
Scholars:
2.2W
Papers: 1.6W
Citations: 13
U
utmd anderson cancer center
Scholars:
3.0W
Papers: 2.4W
Citations: 27
J
john wayne cancer institute
Scholars:
751
Papers: 500
Citations: 0
U
university of texas system
Scholars:
18.5W
Papers: 15.6W
Citations: 210
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