A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell�lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis
Alexandra Butzmann
1
,
Kaushik Sridhar
1
,
Diwash Jangam
1
,
Jyoti Kumar
1
,
Malaya K. Sahoo
1
,
Nahid Shahmarvand
1
,
ROGER WARNKE
1
,
Elumalai Rangasamy
2
,
Benjamin A. Pinsky
1
,
Robert S. Ohgami
1
2
Agilent Technologies, Santa Clara, CA 95051, USA
|
Publication type: Journal Article
Publication date: 2020-07-28
scimago Q1
wos Q1
SJR: 1.381
CiteScore: 13.2
Impact factor: 5.8
ISSN: 11073756, 1791244X
PubMed ID:
32945366
General Medicine
Genetics
Abstract
Angioimmunoblastic T‑cell lymphoma (AITL) is a uniquely aggressive mature T‑cell neoplasm. In recent years, recurrent genetic mutations in ras homolog family member A (RHOA), tet methylcytosine dioxygenase 2 (TET2), DNA methyltransferase 3 alpha (DNMT3A) and isocitrate dehydrogenase [NADP(+)] 2 (IDH2) have been identified as associated with AITL. However, a deep molecular study assessing both DNA mutations and RNA expression profile combined with digital image analysis is lacking. The present study aimed to evaluate the significance of molecular and morphologic features by high resolution digital image analysis in several cases of AITL. To do so, a total of 18 separate tissues from 10 patients with AITL were collected and analyzed. The results identified recurrent mutations in RHOA, TET2, DNMT3A, and IDH2, and demonstrated increased DNA mutations in coding, promoter and CCCTC binding factor (CTCF) binding sites in RHOA mutated AITLs vs. RHOA non‑mutated cases, as well as increased overall survival in RHOA mutated patients. In addition, single cell computational digital image analysis morphologically characterized RHOA mutated AITL cells as distinct from cells from RHOA mutation negative patients. Computational analysis of single cell morphological parameters revealed that RHOA mutated cells have decreased eccentricity (more circular) compared with RHOA non‑mutated AITL cells. In conclusion, the results from the present study expand our understanding of AITL and demonstrate that there are specific cell biological and morphological manifestations of RHOA mutations in cases of AITL.
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Butzmann A. et al. A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell�lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis // International Journal of Molecular Medicine. 2020. Vol. 46. No. 4.
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Butzmann A., Sridhar K., Jangam D., Kumar J., Sahoo M. K., Shahmarvand N., WARNKE R., Rangasamy E., Pinsky B. A., Ohgami R. S. A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell�lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis // International Journal of Molecular Medicine. 2020. Vol. 46. No. 4.
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TY - JOUR
DO - 10.3892/ijmm.2020.4686
UR - https://doi.org/10.3892/ijmm.2020.4686
TI - A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell�lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis
T2 - International Journal of Molecular Medicine
AU - Butzmann, Alexandra
AU - Sridhar, Kaushik
AU - Jangam, Diwash
AU - Kumar, Jyoti
AU - Sahoo, Malaya K.
AU - Shahmarvand, Nahid
AU - WARNKE, ROGER
AU - Rangasamy, Elumalai
AU - Pinsky, Benjamin A.
AU - Ohgami, Robert S.
PY - 2020
DA - 2020/07/28
PB - Spandidos Publications
IS - 4
VL - 46
PMID - 32945366
SN - 1107-3756
SN - 1791-244X
ER -
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BibTex (up to 50 authors)
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@article{2020_Butzmann,
author = {Alexandra Butzmann and Kaushik Sridhar and Diwash Jangam and Jyoti Kumar and Malaya K. Sahoo and Nahid Shahmarvand and ROGER WARNKE and Elumalai Rangasamy and Benjamin A. Pinsky and Robert S. Ohgami},
title = {A comprehensive analysis of RHOA mutation positive and negative angioimmunoblastic T-cell�lymphomas by targeted deep sequencing, expression profiling and single cell digital image analysis},
journal = {International Journal of Molecular Medicine},
year = {2020},
volume = {46},
publisher = {Spandidos Publications},
month = {jul},
url = {https://doi.org/10.3892/ijmm.2020.4686},
number = {4},
doi = {10.3892/ijmm.2020.4686}
}