Pan-cancer analysis identifies RNA helicase DDX1 as a prognostic marker

Gao, Baocai; Li, Xiangnan; Li, Shujie; Wang, Sen; Wu, Jiaxue; Li, Jixi

doi:10.1007/s43657-021-00034-x

Cited by 12 publications

(10 citation statements)

References 57 publications

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“…The stability of RNA reference materials at storage of -80 °C was monitored for up to 20 months. RIN values were assessed at the 0, 1, 2, 3,4,5,6,7,8,9,11,12,13,15,16,17, and 20 months. Three replicates per sample group were assessed each timepoint.…”

Section: Methodsmentioning

confidence: 99%

“…RNA sequencing (RNAseq) is an indispensable tool for transcriptome-wide analysis of differential gene expression and is widely used in biomedical research to discover biomarkers for clinical diagnosis, prognosis, and therapeutic action [1][2][3][4][5][6][7][8] . As RNAseqbased biomarker discovery continues to advance, RNAseq-based routine clinical utility is expected to become a reality 4,9 .…”

mentioning

confidence: 99%

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Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Hou

Wang

et al. 2022

Preprint

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As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Hou

Wang

et al. 2022

Preprint

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“…Though FAM98B has been shown to play an important role in the development of multiple cancers, it has not previously been identified as a biomarker for any cancer. FAM98B is an arginine methyltransferase, is utilized in tumorigenesis, and works in tandem with DDX1, a pan-cancer marker, in RNA metabolism/processing (70,71). Like YES1 and FERMT2, FAM98B has not been previously identified as a biomarker for BCNHL.…”

Section: Machine Learning Predicts Novel Biomarkers Of Bcnhlmentioning

confidence: 99%

Transcriptomic meta-analysis of non-Hodgkin’s B-cell lymphomas reveals reliance on pathways associated with the extracellular matrix

Rapier-Sharman

Clancy

Pickett

2022

Preprint

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Approximately 450,000 cases of Non-Hodgkin’s lymphoma are diagnosed annually worldwide, resulting in ∼240,000 deaths. An augmented understanding of the common mechanisms of pathology among relatively large numbers of B-cell Non-Hodgkin’s Lymphoma (BCNHL) patients is sorely needed. We consequently performed a large transcriptomic meta-analysis of available BCNHL RNA-sequencing data from GEO, consisting of 322 relevant samples across ten distinct public studies, to find common underlying mechanisms across BCNHL subtypes. The study was limited to GEO’s publicly available human B-cell RNA-sequencing datasets that met our criteria, and limitations may include lack of diversity in ethnicities and age groups. We found ∼10,400 significant differentially expressed genes (FDR-adjusted p-value < 0.05) and 33 significantly modulated pathways (Bonferroni-adjusted p-value < 0.05) when comparing lymphoma samples to non-diseased samples. Our findings include a significant class of proteoglycans not previously associated with lymphomas as well as significant modulation of extracellular matrix-associated proteins. Our drug prediction results yielded new candidates including ocriplasmin and collagenase. We also used a machine learning approach to identify the BCNHL biomarkers YES1, FERMT2, and FAM98B, novel biomarkers of high predictive fidelity. This meta-analysis validates existing knowledge while providing novel insights into the inner workings and mechanisms of B-cell lymphomas that could give rise to improved diagnostics and/or therapeutics. No external funding was used for this study.

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“…RNA sequencing (RNAseq) is an indispensable tool for transcriptome-wide analysis of differential gene expression and is widely used in biomedical research to discover biomarkers for clinical diagnosis, prognosis, and therapeutic action [1][2][3][4][5][6][7][8] . As transcriptome-based biomarker discovery continues to advance, RNAseq-based routine clinical utility is expected to become a reality 4,9 .…”

Section: Introductionmentioning

confidence: 99%

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Hou

Wang

et al. 2022

Preprint

View full text Add to dashboard Cite

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications such as companion diagnostics and prognostics. However, there is a lack of certified RNA reference materials and the corresponding reference datasets of differential expression for assessing the reliability of RNAseq for its intended use in detecting intrinsically small biological differences in clinical settings such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multiomics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two reference samples, providing "ground truth" for cross-platform and cross-lab proficiency test. Moreover, Quartet-sample-based quality metrics were developed for assessing the reliability of RNAseq technology in terms of intra-batch measurement and cross-batch data integration. The small intrinsic biological differences among the Quartet samples enabled sensitive assessment of performance of transcriptomic measurements and their cross-batch integration at the ratio level. The Quartet RNA reference materials combined with the ratio-based reference datasets can serve as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

show abstract

Pan-cancer analysis identifies RNA helicase DDX1 as a prognostic marker

Cited by 12 publications

References 57 publications

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

Transcriptomic meta-analysis of non-Hodgkin’s B-cell lymphomas reveals reliance on pathways associated with the extracellular matrix

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

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