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Kenneth N. Ross

Bio: Kenneth N. Ross is an academic researcher from Harvard University. The author has contributed to research in topics: Gene expression profiling & Cellular differentiation. The author has an hindex of 45, co-authored 79 publications receiving 19177 citations. Previous affiliations of Kenneth N. Ross include Boston University & Massachusetts Institute of Technology.


Papers
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Journal ArticleDOI
29 Sep 2006-Science
TL;DR: The first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules is created, and it is demonstrated that this “Connectivity Map” resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs.
Abstract: To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.

4,429 citations

Journal ArticleDOI
TL;DR: The results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.

2,574 citations

Journal ArticleDOI
TL;DR: It is found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome, suggesting that the metastatic potential of human tumors is encoded in the bulk of aPrimary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.
Abstract: Metastasis is the principal event leading to death in individuals with cancer, yet its molecular basis is poorly understood. To explore the molecular differences between human primary tumors and metastases, we compared the gene-expression profiles of adenocarcinoma metastases of multiple tumor types to unmatched primary adenocarcinomas. We found a gene-expression signature that distinguished primary from metastatic adenocarcinomas. More notably, we found that a subset of primary tumors resembled metastatic tumors with respect to this gene-expression signature. We confirmed this finding by applying the expression signature to data on 279 primary solid tumors of diverse types. We found that solid tumors carrying the gene-expression signature were most likely to be associated with metastasis and poor clinical outcome (P < 0.03). These results suggest that the metastatic potential of human tumors is encoded in the bulk of a primary tumor, thus challenging the notion that metastases arise from rare cells within a primary tumor that have the ability to metastasize.

2,434 citations

Journal ArticleDOI
TL;DR: Genes implicated in DLBCL outcome included some that regulate responses to B-cell–receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis, and identify rational targets for intervention.
Abstract: Diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy in adults, is curable in less than 50% of patients. Prognostic models based on pre-treatment characteristics, such as the International Prognostic Index (IPI), are currently used to predict outcome in DLBCL. However, clinical outcome models identify neither the molecular basis of clinical heterogeneity, nor specific therapeutic targets. We analyzed the expression of 6,817 genes in diagnostic tumor specimens from DLBCL patients who received cyclophosphamide, adriamycin, vincristine and prednisone (CHOP)-based chemotherapy, and applied a supervised learning prediction method to identify cured versus fatal or refractory disease. The algorithm classified two categories of pa- tients with very different five-year overall survival rates (70% versus 12%). The model also ef- fectively delineated patients within specific IPI risk categories who were likely to be cured or to die of their disease. Genes implicated in DLBCL outcome included some that regulate responses to B-cell-receptor signaling, critical serine/threonine phosphorylation pathways and apoptosis. Our data indicate that supervised learning classification techniques can predict outcome in DLBCL and identify rational targets for intervention. © 2002 Nature Publishing Group http://medicine.nature.com

2,381 citations

Journal ArticleDOI
TL;DR: Enhanced intracellular conversion of adrenal androgens to testosterone and dihydrotestosterone is a mechanism by which prostate cancer cells adapt to androgen deprivation and suggest new therapeutic targets.
Abstract: Androgen receptor (AR) plays a central role in prostate cancer, and most patients respond to androgen deprivation therapies, but they invariably relapse with a more aggressive prostate cancer that has been termed hormone refractory or androgen independent. To identify proteins that mediate this tumor progression, gene expression in 33 androgen-independent prostate cancer bone marrow metastases versus 22 laser capture-microdissected primary prostate cancers was compared using Affymetrix oligonucleotide microarrays. Multiple genes associated with aggressive behavior were increased in the androgen-independent metastatic tumors (MMP9, CKS2, LRRC15, WNT5A, EZH2, E2F3, SDC1, SKP2, and BIRC5), whereas a candidate tumor suppressor gene (KLF6) was decreased. Consistent with castrate androgen levels, androgen-regulated genes were reduced 2- to 3-fold in the androgen-independent tumors. Nonetheless, they were still major transcripts in these tumors, indicating that there was partial reactivation of AR transcriptional activity. This was associated with increased expression of AR (5.8-fold) and multiple genes mediating androgen metabolism (HSD3B2, AKR1C3, SRD5A1, AKR1C2, AKR1C1, and UGT2B15). The increase in aldo-keto reductase family 1, member C3 (AKR1C3), the prostatic enzyme that reduces adrenal androstenedione to testosterone, was confirmed by real-time reverse transcription-PCR and immunohistochemistry. These results indicate that enhanced intracellular conversion of adrenal androgens to testosterone and dihydrotestosterone is a mechanism by which prostate cancer cells adapt to androgen deprivation and suggest new therapeutic targets.

1,071 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
31 Jan 2002-Nature
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
Abstract: Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

9,664 citations

Journal ArticleDOI
09 Jun 2005-Nature
TL;DR: A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
Abstract: Recent work has revealed the existence of a class of small non-coding RNA species, known as microRNAs (miRNAs), which have critical functions across various biological processes. Here we use a new, bead-based flow cytometric miRNA expression profiling method to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers. The miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. We observe a general downregulation of miRNAs in tumours compared with normal tissues. Furthermore, we were able to successfully classify poorly differentiated tumours using miRNA expression profiles, whereas messenger RNA profiles were highly inaccurate when applied to the same samples. These findings highlight the potential of miRNA profiling in cancer diagnosis.

9,470 citations

Journal ArticleDOI
TL;DR: An overview of the endocrine functions of adipose tissue can be found in this paper, where the authors highlight the adverse metabolic consequences of both adipose excess and deficiency, and propose a more rational therapy for these increasingly prevalent disorders.
Abstract: Adipose tissue is a complex, essential, and highly active metabolic and endocrine organ. Besides adipocytes, adipose tissue contains connective tissue matrix, nerve tissue, stromovascular cells, and immune cells. Together these components function as an integrated unit. Adipose tissue not only responds to afferent signals from traditional hormone systems and the central nervous system but also expresses and secretes factors with important endocrine functions. These factors include leptin, other cytokines, adiponectin, complement components, plasminogen activator inhibitor-1, proteins of the renin-angiotensin system, and resistin. Adipose tissue is also a major site for metabolism of sex steroids and glucocorticoids. The important endocrine function of adipose tissue is emphasized by the adverse metabolic consequences of both adipose tissue excess and deficiency. A better understanding of the endocrine function of adipose tissue will likely lead to more rational therapy for these increasingly prevalent disorders. This review presents an overview of the endocrine functions of adipose tissue.

5,484 citations

Journal ArticleDOI
TL;DR: The results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.
Abstract: Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

5,281 citations