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Biao Luo

Bio: Biao Luo is an academic researcher from Broad Institute. The author has contributed to research in topics: RNA interference & Gene knockdown. The author has an hindex of 8, co-authored 10 publications receiving 3002 citations. Previous affiliations of Biao Luo include Massachusetts Institute of Technology.

Papers
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Journal ArticleDOI
24 Mar 2006-Cell
TL;DR: A screen based on high-content imaging was developed to identify genes required for mitotic progression in human cancer cells and applied to an arrayed set of 5,000 unique shRNA-expressing lentiviruses that target 1,028 human genes, providing a widely applicable resource for loss-of-function screens.

1,760 citations

Journal ArticleDOI
TL;DR: An efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines is reported.
Abstract: More complete knowledge of the molecular mechanisms underlying cancer will improve prevention, diagnosis and treatment. Efforts such as The Cancer Genome Atlas are systematically characterizing the structural basis of cancer, by identifying the genomic mutations associated with each cancer type. A powerful complementary approach is to systematically characterize the functional basis of cancer, by identifying the genes essential for growth and related phenotypes in different cancer cells. Such information would be particularly valuable for identifying potential drug targets. Here, we report the development of an efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines. By integrating these functional data with comprehensive genetic analyses of primary human tumors, we identified known and putative oncogenes such as EGFR, KRAS, MYC, BCR-ABL, MYB, CRKL, and CDK4 that are essential for cancer cell proliferation and also altered in human cancers. We further used this approach to identify genes involved in the response of cancer cells to tumoricidal agents and found 4 genes required for the response of CML cells to imatinib treatment: PTPN1, NF1, SMARCB1, and SMARCE1, and 5 regulators of the response to FAS activation, FAS, FADD, CASP8, ARID1A and CBX1. Broad application of this highly parallel genetic screening strategy will not only facilitate the rapid identification of genes that drive the malignant state and its response to therapeutics but will also enable the discovery of genes that participate in any biological process.

587 citations

Journal ArticleDOI
TL;DR: Assessment of the essentiality of 11,194 genes in 102 human cancer cell lines shows that the integration of genome-scale functional and structural studies provides an efficient path to identify dependencies of specific cancer types on particular genes and pathways.
Abstract: A comprehensive understanding of the molecular vulnerabilities of every type of cancer will provide a powerful roadmap to guide therapeutic approaches. Efforts such as The Cancer Genome Atlas Project will identify genes with aberrant copy number, sequence, or expression in various cancer types, providing a survey of the genes that may have a causal role in cancer. A complementary approach is to perform systematic loss-of-function studies to identify essential genes in particular cancer cell types. We have begun a systematic effort, termed Project Achilles, aimed at identifying genetic vulnerabilities across large numbers of cancer cell lines. Here, we report the assessment of the essentiality of 11,194 genes in 102 human cancer cell lines. We show that the integration of these functional data with information derived from surveying cancer genomes pinpoints known and previously undescribed lineage-specific dependencies across a wide spectrum of cancers. In particular, we found 54 genes that are specifically essential for the proliferation and viability of ovarian cancer cells and also amplified in primary tumors or differentially overexpressed in ovarian cancer cell lines. One such gene, PAX8, is focally amplified in 16% of high-grade serous ovarian cancers and expressed at higher levels in ovarian tumors. Suppression of PAX8 selectively induces apoptotic cell death of ovarian cancer cells. These results identify PAX8 as an ovarian lineage-specific dependency. More generally, these observations demonstrate that the integration of genome-scale functional and structural studies provides an efficient path to identify dependencies of specific cancer types on particular genes and pathways.

422 citations

Journal ArticleDOI
TL;DR: It is found that EglN2 inactivation decreases Cyclin D1 levels and suppresses mammary gland proliferation in vivo and support the exploration of Egln2 inhibitors as therapeutics for estrogen-dependent breast cancer and other malignancies.

126 citations

Journal ArticleDOI
TL;DR: It is shown that CRKL, encoding for an adaptor protein, is amplified and overexpressed in non-small cell lung cancer (NSCLC) cells that harbor 22q11.21 amplifications, andCRKL is credentialed as an oncogene in a subset of NSCLC and implicate CRKl as an additional mechanism of resistance to EGFR-directed therapy.
Abstract: We previously identified a region of recurrent amplification on chromosome 22q11.21 in a subset of primary lung adenocarcinomas. Here we show that CRKL , encoding for an adaptor protein, is amplified and overexpressed in non–small cell lung cancer (NSCLC) cells that harbor 22q11.21 amplifications. Overexpression of CRKL in immortalized human airway epithelial cells promoted anchorage-independent growth and tumorigenicity. Oncogenic CRKL activates the SOS1-RAS-RAF-ERK and SRC-C3G-RAP1 pathways. Suppression of CRKL in NSCLC cells that harbor CRKL amplifications induced cell death. Overexpression of CRKL in epidermal growth factor receptor ( EGFR )-mutant cells induces resistance to gefitinib by activating extracellular signal–regulated kinase and AKT signaling. We identified CRKL amplification in an EGFR inhibitor–treated lung adenocarcinoma that was not present before treatment. These observations demonstrate that CRKL overexpression induces cell transformation, credential CRKL as a therapeutic target for a subset of NSCLC that harbor CRKL amplifications, and implicate CRKL as an additional mechanism of resistance to EGFR-directed therapy. Significance: These studies credential CRKL as an oncogene in a subset of NSCLC. Overexpression of CRKL induces cell transformation and resistance to epidermal growth factor receptor inhibitor treatment and suggest that therapeutic interventions targeting CRKL may confer a clinical benefit in a defined subset of NSCLCs. Cancer Discovery; 1(7) ; 608–25. ©2011 AACR . Read the Commentary on this article by Ladanyi, [p. 560][1] This article is highlighted in the In This Issue feature, [p. 539][2] [1]: /lookup/volpage/1/560?iss=7 [2]: /lookup/volpage/1/539?iss=7

124 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
25 May 2012-Cell
TL;DR: This paper identified the small molecule ferrostatin-1 as a potent inhibitor of ferroptosis in cancer cells and glutamate-induced cell death in organotypic rat brain slices, suggesting similarities between these two processes.

7,192 citations

Journal ArticleDOI
TL;DR: The first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler is described, which can address a variety of biological questions quantitatively.
Abstract: Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).

4,578 citations

Journal ArticleDOI
03 Jan 2014-Science
TL;DR: This work shows that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells, and observes a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation.
Abstract: The simplicity of programming the CRISPR (clustered regularly interspaced short palindromic repeats)–associated nuclease Cas9 to modify specific genomic loci suggests a new way to interrogate gene function on a genome-wide scale. We show that lentiviral delivery of a genome-scale CRISPR-Cas9 knockout (GeCKO) library targeting 18,080 genes with 64,751 unique guide sequences enables both negative and positive selection screening in human cells. First, we used the GeCKO library to identify genes essential for cell viability in cancer and pluripotent stem cells. Next, in a melanoma model, we screened for genes whose loss is involved in resistance to vemurafenib, a therapeutic RAF inhibitor. Our highest-ranking candidates include previously validated genes NF1 and MED12 , as well as novel hits NF2 , CUL3 , TADA2B , and TADA1. We observe a high level of consistency between independent guide RNAs targeting the same gene and a high rate of hit confirmation, demonstrating the promise of genome-scale screening with Cas9.

4,147 citations

Journal ArticleDOI
TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
Abstract: Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.

4,119 citations