Jian-Hua Mao

Dr. Jian-Hua Mao

Biological Systems & Engineering Division, Lawrence Berkeley Laboratory, Berkeley, CA 94720, USA
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Research Focus & Metrics

Academic Career Length

34Years (1993-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 September 2008 in Science
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Jian-Hua MaoJian-Hua Mao
Jian-Hua Mao
IKIl-Jin Kim
Il-Jin Kim
DWDi Wu
Di Wu
Joan ClimentJoan Climent
Joan Climent
HKHio Chung Kang
Hio Chung Kang
ABAllan Balmain
Allan Balmain
The enzyme mTOR (mammalian target of rapamycin) is a major target for therapeutic intervention to treat many human diseases, including cancer, but very little is known about the processes that control levels of mTOR protein. Here, we show that mTOR is targeted for ubiquitination and consequent degradation by binding to the tumor suppressor protein FBXW7. Human breast cancer cell lines and primary tumors showed a reciprocal relation between loss of FBXW7 and deletion or mutation of PTEN (phosphatase and tensin homolog), which also activates mTOR. Tumor cell lines harboring deletions or mutations in FBXW7 are particularly sensitive to rapamycin treatment, which suggests that loss of FBXW7 may be a biomarker for human cancers susceptible to treatment with inhibitors of the mTOR pathway.

1 October 2007 in Clinical Cancer Research
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YGYinghui Guan
Yinghui Guan
WKWen-Lin Kuo
Wen-Lin Kuo
JSJackie L. Stilwell
Jackie L. Stilwell
HTHirokuni Takano
Hirokuni Takano
ALAnna V. Lapuk
Anna V. Lapuk
JGJoe W. Gray
Joe W. Gray
Purpose: This study was designed to elucidate the role of amplification at 8q24 in the pathophysiology of ovarian and breast cancer because increased copy number at this locus is one of the most frequent genomic abnormalities in these cancers. Experimental Design: To accomplish this, we assessed the association of amplification at 8q24 with outcome in ovarian cancers using fluorescence in situ hybridization to tissue microarrays and measured responses of ovarian and breast cancer cell lines to specific small interfering RNAs against the oncogene MYC and a putative noncoding RNA, PVT1, both of which map to 8q24. Results: Amplification of 8q24 was associated with significantly reduced survival duration. In addition, small interfering RNA–mediated reduction in either PVT1 or MYC expression inhibited proliferation in breast and ovarian cancer cell lines in which they were both amplified and overexpressed but not in lines in which they were not amplified/overexpressed. Inhibition of PVT1 expression also induced a strong apoptotic response in cell lines in which it was overexpressed but not in lines in which it was not amplified/overexpressed. Inhibition of MYC, on the other hand, did not induce an apoptotic response in cell lines in which MYC was amplified and overexpressed. Conclusions: These results suggest that MYC and PVT1 contribute independently to ovarian and breast pathogenesis when overexpressed because of genomic abnormalities. They also suggest that PVT1-mediated inhibition of apoptosis may explain why amplification of 8q24 is associated with reduced survival duration in patients treated with agents that act through apoptotic mechanisms.

9 December 2004 in Nature
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Jian-Hua MaoJian-Hua Mao
Jian-Hua Mao
JPJesus Perez-Losada
Jesus Perez-Losada
DWDi Wu
Di Wu
RDReyno DelRosario
Reyno DelRosario
RTRyosuke Tsunematsu
Ryosuke Tsunematsu
ABAllan Balmain
Allan Balmain

14 March 2013 in Clinical Cancer Research
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HTHao Tang
Hao Tang
GXGuanghua Xiao
Guanghua Xiao
CBCarmen Behrens
Carmen Behrens
JSJoan Schiller
Joan Schiller
JAJeffrey Allen
Jeffrey Allen
YXYang Xie
Yang Xie
Purpose: Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for non–small cell lung cancer (NSCLC) patients. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefits of ACT in NSCLC. Experimental Design: An 18-hub-gene prognosis signature was developed through a systems biology approach, and its prognostic value was evaluated in six independent cohorts. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefits in NSCLC. Results: Using a cohort of 442 stage I to III NSCLC patients who underwent surgical resection, we identified an 18-hub-gene set that robustly predicted the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The hub genes, identified through a purely data-driven approach, have significant biological implications in tumor pathogenesis, including NKX2-1, Aurora Kinase A, PRC1, CDKN3, MBIP, and RRM2. The 12-gene predictive signature was successfully validated in two independent datasets (n = 90 and 176). The predicted benefit group showed significant improvement in survival after ACT (UT Lung SPORE data: HR = 0.34, P = 0.017; JBR.10 clinical trial data: HR = 0.36, P = 0.038), whereas the predicted nonbenefit group showed no survival benefit for 2 datasets (HR = 0.80, P = 0.70; HR = 0.91, P = 0.82). Conclusions: This is the first study to integrate genetic aberration, genome-wide RNAi data, and mRNA expression data to identify a functional gene set that predicts which resectable patients with non–small cell lung cancer will have a survival benefit with ACT. Clin Cancer Res; 19(6); 1577–86. ©2013 AACR.

27 July 2003 in Nature Genetics
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ATAmanda Toland
Amanda Toland
PBParaskevi Briassouli
Paraskevi Briassouli
JKJohn P de Koning
John P de Koning
Jian-Hua MaoJian-Hua Mao
Jian-Hua Mao
JYJinwei Yuan
Jinwei Yuan
ABAllan Balmain
Allan Balmain

30 November 2016 in Chemical Research in Toxicology
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PJPeyton Jacob
Peyton Jacob
NBNeal L. Benowitz
Neal L. Benowitz
HDHugo Destaillats
Hugo Destaillats
LGLara Gundel
Lara Gundel
BHBo Hang
Bo Hang
TWTodd P. Whitehead
Todd P. Whitehead