CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms

AbstractUnderstanding the levels of metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Using transcriptomic data from 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we developed a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. This pathway dysregulation was confirmed in separate patient populations, further demonstrating the robustness of this approach. A bootstrapping simulation was then applied to assess whether these alterations were biologically meaningful, rather than expected by chance. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest in both common and rare disease sites. Utilizing a pathway mapping approach to understand patterns of metabolic flux, differential drug sensitivity, can accurately be predicted. Further, the identification of Master Metabolic Transcriptional Regulators, whose expression was highly correlated with pathway gene expression, explains why metabolic differences exist in different disease sites. We demonstrate these also have the ability to segregate patient populations and predict responders to different metabolism-targeted therapeutics.

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The role of miR-92b in cholangiocarcinoma patients

The International Journal of Biological Markers ◽

10.1177/1724600817751524 ◽

2018 ◽

Vol 33 (3) ◽

pp. 293-300 ◽

Cited By ~ 3

Author(s):

Min-hang Zhou ◽

Hong-wei Zhou ◽

Mo Liu ◽

Jun-zhong Sun

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Gene Expression Omnibus ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Positive Regulation ◽

Cancer Genome Atlas ◽

High Level ◽

Genome Atlas

Purpose: The role of microRNA (miRNA) in cholangiocarcinoma was not clear. The aim of this study was to find the potential diagnostic and prognostic miRNA in cholangiocarcinoma patients. Methods: The miRNA expression profiles in cholangiocarcinoma patients from The Cancer Genome Atlas and Gene Expression Omnibus (GSE53870) were analyzed. The comparison of overall survival was performed using the Kaplan–Meier method. The targeted genes of prognostic miRNA were identified in miRanda, PicTar, or TargetScan, and their cell signaling pathways were analyzed by the Database for Annotation, Visualization and Integrated Discovery. Results: In The Cancer Genome Atlas and the Gene Expression Omnibus miRNA dataset, miR-92b and miR-99a were found with concordant directionality, up-regulated and down-regulated, respectively. In The Cancer Genome Atlas survival data, patients with the high level of miR-99b had obviously shorter overall survival time ( P=0.038). However, the level of miR-99a was not found to be significant. The 17 shared target genes of miR-92b were identified, such as DAB21IP, BCL21L11, SPHK2, PER2, and TSC1. The related pathways included positive regulation of transcription, positive regulation of cellular biosynthetic process, regulation of programmed cell death, etc. Conclusion: miR-92b was up-regulated in cholangiocarcinoma compared with normal controls. The high level of miR-92b was associated with adverse outcomes in cholangiocarcinoma patients, which might be partly explained by the targeted genes of miR-92b and their signaling pathways.

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Biological Validation of RNA Sequencing Data From Formalin-Fixed Paraffin-Embedded Primary Melanomas

JCO Precision Oncology ◽

10.1200/po.17.00259 ◽

2018 ◽

pp. 1-19 ◽

Cited By ~ 6

Author(s):

Lawrence N. Kwong ◽

Mariana Petaccia De Macedo ◽

Lauren Haydu ◽

Aron Y. Joon ◽

Michael T. Tetzlaff ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Formalin Fixed Paraffin ◽

Ffpe Samples ◽

Formalin Fixed Paraffin Embedded ◽

Cancer Genome Atlas ◽

Formalin Fixed ◽

Genome Atlas

Purpose Initiatives such as The Cancer Genome Atlas and International Cancer Genome Consortium have generated high-quality, multiplatform molecular data from thousands of frozen tumor samples. Although these initiatives have provided invaluable insight into cancer biology, a tremendous potential resource remains largely untapped in formalin-fixed, paraffin-embedded (FFPE) samples that are more readily available but which can present technical challenges because of crosslinking of fragile molecules such as RNA. Materials and Methods We extracted RNA from FFPE primary melanomas and assessed two gene expression platforms—genome-wide RNA sequencing and targeted NanoString—for their ability to generate coherent biologic signals. To do so, we generated an improved approach to quantifying gene expression pathways. We refined pathway scores through correlation-guided gene subsetting. We also make comparisons to The Cancer Genome Atlas and other publicly available melanoma datasets. Results The comparison of the gene expression patterns to each other, to established biologic modules, and to clinical and immunohistochemical data confirmed the fidelity of biologic signals from both platforms using FFPE samples to known biology. Moreover, correlations with patient outcome data were consistent with previous frozen-tissue–based studies. Conclusion FFPE samples from previously difficult-to-access cancer types, such as small primary melanomas, represent a valuable and previously unexploited source of analyte for RNA sequencing and NanoString platforms. This work provides an important step toward the use of such platforms to unlock novel molecular underpinnings and inform future biologically driven clinical decisions.

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Using machine learning method to identify MYLK as a novel marker to predict biochemical recurrence in prostate cancer

Biomarkers in Medicine ◽

10.2217/bmm-2020-0495 ◽

2021 ◽

Vol 15 (1) ◽

pp. 29-41

Author(s):

Peng Qiao ◽

Di Zhang ◽

Song Zeng ◽

Yicun Wang ◽

Biao Wang ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Biochemical Recurrence ◽

Surgical Margin ◽

Gene Expression Omnibus ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Support Vector ◽

Cancer Genome Atlas ◽

Genome Atlas

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion: MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

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