Research Interest

Our major research interest is to better understand the biology underlying cancer using quantitative approaches. Especially, we have more passion in projects that bridge basic biological studies and clinical research.

Integrative Analysis

We have rich experience in integrative analysis of multilevel (epi)genomic data and clinical outcomes for dissecting cancer heterogeneity.


Identifying and characterizing molecularly distinct cancer subtypes that are in relation to clinical responses.


Identifying prognostic and predictive cancer biomarkers that are more accessible in the clinic.

Therapeutic targets

Identifying potential therapeutic targets using network-based approaches.


Developing bioconductor packages and web tools for analyzing next-generation sequencing data (SPP2), high-throughput screens (HTSanalyzeR), etc.


We always welcome outsanding bioinformatics students to join our lab. Please see Contact for details.

Recent Publications

Integrative network biology analysis identifies miR-508-3p as the determinant for the mesenchymal identity and a strong prognostic biomarker of ovarian cancer.

on May 2631, 26118

Authors Zhao L†, Wang W†, Xu L, Yi T, Zhao X, Wei Y, Vermeulen L, Goel A, Zhou S* and Wang X* Oncogene 2018, doi: Abstract Ovarian cancer is a heterogeneous malignancy that poses tremendous clinical challenge. Based on unsupervised classification of whole-genome gene expression profiles, four molecular subtypes of ovarian cancer were recently identified. However, single-driver molecular events specific to these subtypes have not been clearly elucidated. We aim to characterize the regulatory mechanisms underlying the poor prognosis mesenchymal subtype of ovarian cancer using a systems biology approach, involving a variety of molecular modalities including gene and microRNA expression profiles.

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High-throughput Brain Activity Mapping and Machine Learning as a Foundation for Systems Neuropharmacology.

on May 331, 3118

Authors Lin X†, Duan X†, Jacobs C, Ullmann J, Chan CY, Chen S, Cheng SH, Zhao WN, Poduri A, Wang X*, Haggarty SJ*, Shi P* Nature Communications 2018, doi: Abstract Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherapeutics for neurological and psychiatric disorders.

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mTORC1 Promotes Metabolic Reprogramming by the Suppression of GSK3-Dependent Foxk1 Phosphorylation.

on May 731, 7068

Authors He L, Gomes AP†, Wang X†, Yoon SO, Lee G, Nagiec M, Cho S, Chavez A, Islam T, Yu Y, Asara JM, Kim BY, Blenis J. Molecular Cell 2018, doi: Abstract Highlights mTORC1 suppresses GSK3-dependent Foxk1 phosphorylation Foxk1 phosphorylation promotes 14-3-3 binding and nuclear exclusion Foxk1 transcriptionally regulates Hif1α expression Foxk1 and Hif1α contribute to mTORC1-regulated metabolic reprogramming Summary The mammalian Target of Rapamycin Complex 1 (mTORC1)-signaling system plays a critical role in the maintenance of cellular homeostasis by sensing and integrating multiple extracellular and intracellular cues.

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Molecular subtyping of colorectal cancer: recent progress, new challenges and emerging opportunities.

on May 1731, 17058

Authors Wang W†, Kandimalla R†, Huang H†, Zhu L, Li Y, Gao F, Goel A*,Wang X* Seminars in Cancer Biology 2018, doi:10.1016/j.semcancer.2018.05.002 Abstract Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Similar to many other malignancies, CRC is a heterogeneous disease, making it a clinical challenge for optimization of treatment modalities in reducing the morbidity and mortality associated with this disease. A more precise understanding of the biological properties that distinguish patients with colorectal tumors, especially in terms of their clinical features, is a key requirement towards a more robust, targeted-drug design, and implementation of individualized therapies.

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Our Collaborations