High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders. / Mkrtchyan, Garik V.; Veviorskiy, Alexander; Izumchenko, Evgeny; Shneyderman, Anastasia; Pun, Frank W.; Ozerov, Ivan V.; Aliper, Alex; Zhavoronkov, Alex; Scheibye-Knudsen, Morten.

In: Cell Death and Disease, Vol. 13, No. 11, 999, 2022.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Mkrtchyan, GV, Veviorskiy, A, Izumchenko, E, Shneyderman, A, Pun, FW, Ozerov, IV, Aliper, A, Zhavoronkov, A & Scheibye-Knudsen, M 2022, 'High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders', Cell Death and Disease, vol. 13, no. 11, 999. https://doi.org/10.1038/s41419-022-05437-w

APA

Mkrtchyan, G. V., Veviorskiy, A., Izumchenko, E., Shneyderman, A., Pun, F. W., Ozerov, I. V., Aliper, A., Zhavoronkov, A., & Scheibye-Knudsen, M. (2022). High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders. Cell Death and Disease, 13(11), [999]. https://doi.org/10.1038/s41419-022-05437-w

Vancouver

Mkrtchyan GV, Veviorskiy A, Izumchenko E, Shneyderman A, Pun FW, Ozerov IV et al. High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders. Cell Death and Disease. 2022;13(11). 999. https://doi.org/10.1038/s41419-022-05437-w

Author

Mkrtchyan, Garik V. ; Veviorskiy, Alexander ; Izumchenko, Evgeny ; Shneyderman, Anastasia ; Pun, Frank W. ; Ozerov, Ivan V. ; Aliper, Alex ; Zhavoronkov, Alex ; Scheibye-Knudsen, Morten. / High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders. In: Cell Death and Disease. 2022 ; Vol. 13, No. 11.

Bibtex

@article{5e72f6685ad246ecad2873659b75a4f7,
title = "High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders",
abstract = "Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform (https://pandaomics.com/) to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets. Our analysis revealed that CEP135, a scaffolding protein associated with early centriole biogenesis, is commonly downregulated in DNA repair diseases with high cancer predisposition. Further screening of survival data in 33 cancers available at TCGA database identified sarcoma as a cancer type where lower survival was significantly associated with high CEP135 expression. Stratification of cancer patients based on CEP135 expression enabled us to examine therapeutic targets that could be used for the improvement of existing therapies against sarcoma. The latter was based on application of the PandaOmics target-ID algorithm coupled with in vitro studies that revealed polo-like kinase 1 (PLK1) as a potential therapeutic candidate in sarcoma patients with high CEP135 levels and poor survival. While further target validation is required, this study demonstrated the potential of in silico-based studies for a rapid biomarker discovery and target characterization.",
author = "Mkrtchyan, {Garik V.} and Alexander Veviorskiy and Evgeny Izumchenko and Anastasia Shneyderman and Pun, {Frank W.} and Ozerov, {Ivan V.} and Alex Aliper and Alex Zhavoronkov and Morten Scheibye-Knudsen",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
doi = "10.1038/s41419-022-05437-w",
language = "English",
volume = "13",
journal = "Cell Death & Disease",
issn = "2041-4889",
publisher = "nature publishing group",
number = "11",

}

RIS

TY - JOUR

T1 - High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders

AU - Mkrtchyan, Garik V.

AU - Veviorskiy, Alexander

AU - Izumchenko, Evgeny

AU - Shneyderman, Anastasia

AU - Pun, Frank W.

AU - Ozerov, Ivan V.

AU - Aliper, Alex

AU - Zhavoronkov, Alex

AU - Scheibye-Knudsen, Morten

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022

Y1 - 2022

N2 - Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform (https://pandaomics.com/) to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets. Our analysis revealed that CEP135, a scaffolding protein associated with early centriole biogenesis, is commonly downregulated in DNA repair diseases with high cancer predisposition. Further screening of survival data in 33 cancers available at TCGA database identified sarcoma as a cancer type where lower survival was significantly associated with high CEP135 expression. Stratification of cancer patients based on CEP135 expression enabled us to examine therapeutic targets that could be used for the improvement of existing therapies against sarcoma. The latter was based on application of the PandaOmics target-ID algorithm coupled with in vitro studies that revealed polo-like kinase 1 (PLK1) as a potential therapeutic candidate in sarcoma patients with high CEP135 levels and poor survival. While further target validation is required, this study demonstrated the potential of in silico-based studies for a rapid biomarker discovery and target characterization.

AB - Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform (https://pandaomics.com/) to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets. Our analysis revealed that CEP135, a scaffolding protein associated with early centriole biogenesis, is commonly downregulated in DNA repair diseases with high cancer predisposition. Further screening of survival data in 33 cancers available at TCGA database identified sarcoma as a cancer type where lower survival was significantly associated with high CEP135 expression. Stratification of cancer patients based on CEP135 expression enabled us to examine therapeutic targets that could be used for the improvement of existing therapies against sarcoma. The latter was based on application of the PandaOmics target-ID algorithm coupled with in vitro studies that revealed polo-like kinase 1 (PLK1) as a potential therapeutic candidate in sarcoma patients with high CEP135 levels and poor survival. While further target validation is required, this study demonstrated the potential of in silico-based studies for a rapid biomarker discovery and target characterization.

U2 - 10.1038/s41419-022-05437-w

DO - 10.1038/s41419-022-05437-w

M3 - Journal article

C2 - 36435816

AN - SCOPUS:85142632342

VL - 13

JO - Cell Death & Disease

JF - Cell Death & Disease

SN - 2041-4889

IS - 11

M1 - 999

ER -

ID: 332601350