Science in Focus: Genomic Instability and its Implications for Clinical Cancer Care

Ahmad, Saif; Ahmed, Karim; Venkitaraman, Ashok R.

doi:10.1016/j.clon.2018.09.001

Cited by 9 publications

(6 citation statements)

References 30 publications

(30 reference statements)

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“…Because a) regulatory elements, NBD and DNA repeats have been thoroughly documented to impede transcription and replication in both a transcription-associated (Gaillard et Aguilera 2016) and replication-associated (Gaillard, García-Muse, et Aguilera 2015) manner and to cause GI, and b) GI is predictive of poor prognosis (Ahmad, Ahmed, et Venkitaraman 2018), we hypothesized that there is a link between transcription- and replication-associated DNA-breakage mechanisms and metastatic clinical outcome in LMS. To test this hypothesis, we sought to quantify the overall transcription-associated and replication-associated GI.…”

Section: Resultsmentioning

confidence: 99%

“…GI has long been thought to be predictive of poor prognosis, although an accurate method for measuring it remains to be discovered (Ahmad, Ahmed, et Venkitaraman 2018). Furthermore, the current lack of a measure that captures the dynamic nature of GI limits our ability to leverage it for prognostic and therapeutic purposes (Sansregret, Vanhaesebroeck, et Swanton 2018) in a clinical setting.…”

Section: Introductionmentioning

confidence: 99%

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Metastatic risk stratification of leiomyosarcoma patients using transcription- and replication-associated chromosomal instability mechanisms

Benhaddou

Gaston

Pérot

et al. 2021

Preprint

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Leiomyosarcoma (LMS) is an aggressive smooth muscle cancer with few therapeutic options. LMSs show a high level of genomic instability (GI) and the mechanisms underlying their oncogenic processes are poorly understood. While the level of GI influences treatment efficacy and resistance, an accurate measure of it is lacking. Current measures of GI are based on counts of specific structural variation (SV) and mutational signatures. Here, we present a holistic approach to measuring GI based on the quantification of the steady-state equilibrium between DNA damage and repair as assessed by the residual breakpoints (BP) remaining after repair, irrespective of SV type. We use the notion of Hscore, a BP “hotspotness” magnitude scale, to measure the propensity of genomic structural or functional DNA elements to break more than expected by chance. We then derived new measures of transcription- and replication-associated GI that we call iTRAC (Transcription-Associated Chromosomal instability index (iTRAC) and iRACIN (Replication-Associated Chromosomal INstability index). We show that iTRAC and iRACIN are predictive of metastatic relapse in LMS and that they may be combined to form a new classifier called MAGIC (Mixed transcription-and replication-Associated Genomic Instability Classifier). MAGIC outperforms the gold standards FNCLCC and CINSARC in stratifying metastatic risk in LMS. Furthermore, iTRAC stratifies chemotherapeutic response in LMS. We finally show that this approach is applicable to other cancers.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Metastatic risk stratification of leiomyosarcoma patients using transcription- and replication-associated chromosomal instability mechanisms

Benhaddou

Gaston

Pérot

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Because (a) regulatory elements, NBD and DNA repeats have been thoroughly documented to impede transcription and replication in both a transcription-associated 18 and replication-associated 3 manner and to cause GI, and (b) GI is predictive of poor prognosis 45 , we hypothesized that there is a link between transcription- and replication-associated DNA-breakage mechanisms and metastatic clinical outcome in LMS. To test this hypothesis, we sought to quantify the overall transcription-associated and replication-associated GI.…”

Section: Resultsmentioning

confidence: 99%

Medium levels of transcription and replication related chromosomal instability are associated with poor clinical outcome

Benhaddou

Gaston

Pérot

et al. 2021

Sci Rep

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Genomic instability (GI) influences treatment efficacy and resistance, and an accurate measure of it is lacking. Current measures of GI are based on counts of specific structural variation (SV) and mutational signatures. Here, we present a holistic approach to measuring GI based on the quantification of the steady-state equilibrium between DNA damage and repair as assessed by the residual breakpoints (BP) remaining after repair, irrespective of SV type. We use the notion of Hscore, a BP “hotspotness” magnitude scale, to measure the propensity of genomic structural or functional DNA elements to break more than expected by chance. We then derived new measures of transcription- and replication-associated GI that we call iTRAC (transcription-associated chromosomal instability index) and iRACIN (replication-associated chromosomal instability index). We show that iTRAC and iRACIN are predictive of metastatic relapse in Leiomyosarcoma (LMS) and that they may be combined to form a new classifier called MAGIC (mixed transcription- and replication-associated genomic instability classifier). MAGIC outperforms the gold standards FNCLCC and CINSARC in stratifying metastatic risk in LMS. Furthermore, iTRAC stratifies chemotherapeutic response in LMS. We finally show that this approach is applicable to other cancers.

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“…Genomic instability (GI) is defined as a process in which genomic changes are prone to increase and can influence the phenotype [7,8], and has been recognized as an evolving hallmark or characteristic of most types of cancer [9]. GI promotes inter-and intra-tumor heterogeneity and is a major driving force for cancer cells to survive, proliferate, and disseminate [10].…”

Section: Introductionmentioning

confidence: 99%

Genomic instability-derived plasma extracellular vesicle-microRNA signature as a minimally invasive predictor of risk and unfavorable prognosis in breast cancer

Bao

Liu

et al. 2021

J Nanobiotechnol

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Background Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer-associated deaths in women. Recent studies have indicated that microRNA (miRNA) regulation in genomic instability (GI) is associated with disease risk and clinical outcome. Herein, we aimed to identify the GI-derived miRNA signature in extracellular vesicles (EVs) as a minimally invasive biomarker for early diagnosis and prognostic risk stratification. Experimental design Integrative analysis of miRNA expression and somatic mutation profiles was performed to identify GI-associated miRNAs. Then, we constructed a discovery and validation study with multicenter prospective cohorts. The GI-derived miRNA signature (miGISig) was developed in the TCGA discovery cohort (n = 261), and was subsequently independently validated in internal TCGA validation (n = 261) and GSE22220 (n = 210) cohorts for prognosis prediction, and in GSE73002 (n = 3966), GSE41922 (n = 54), and in-house clinical exosome (n = 30) cohorts for diagnostic performance. Results We identified a GI-derived three miRNA signature (MIR421, MIR128-1 and MIR128-2) in the serum extracellular vesicles of BC patients, which was significantly associated with poor prognosis in all the cohorts tested and remained as an independent prognostic factor using multivariate analyses. When integrated with the clinical characteristics, the composite miRNA-clinical prognostic indicator showed improved prognostic performance. The miGISig also showed high accuracy in differentiating BC from healthy controls with the area under the receiver operating characteristics curve (ROC) with 0.915, 0.794 and 0.772 in GSE73002, GSE41922 and TCGA cohorts, respectively. Furthermore, circulating EVs from BC patients in the in-house cohort harbored elevated levels of miGISig, with effective diagnostic accuracy. Conclusions We report a novel GI-derived three miRNA signature in EVs, as an excellent minimally invasive biomarker for the early diagnosis and unfavorable prognosis in BC.

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Science in Focus: Genomic Instability and its Implications for Clinical Cancer Care

Abstract: Clinical Oncology j o ur n a l h o m e p a ge : w w w. c l i n i c a l on c o l o gy o n l i ne. n e t

Cited by 9 publications

References 30 publications

Metastatic risk stratification of leiomyosarcoma patients using transcription- and replication-associated chromosomal instability mechanisms

Metastatic risk stratification of leiomyosarcoma patients using transcription- and replication-associated chromosomal instability mechanisms

Medium levels of transcription and replication related chromosomal instability are associated with poor clinical outcome

Genomic instability-derived plasma extracellular vesicle-microRNA signature as a minimally invasive predictor of risk and unfavorable prognosis in breast cancer

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