scholarly journals Gene Expression Profiling forIn SilicoMicrodissection of Hodgkin's Lymphoma Microenvironment and Identification of Prognostic Features

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
François Bertucci ◽  
Bruno Chetaille ◽  
Luc Xerri
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Tissue Sample ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Tissue ◽  
Tissue Samples ◽  
Prognostic Features

Gene expression profiling studies based on DNA microarrays have demonstrated their ability to define the interaction pathways between neoplastic and nonmalignant stromal cells in cancer tissues. During the past ten years, a number of approaches including microdissection have tried to resolve the variability in DNA microarray measurements stemming from cancer tissue sample heterogeneity. Another approach, designated as virtual orin silicomicrodissection, avoids the laborious and time-consuming step of anatomic microdissection. It consists of confronting the gene expression profiles of complex tissue samples to those of cell lines representative of different cell lineages, different differentiation stages, or different signaling pathways. This strategy has been used in recent studies aiming to analyze microenvironment alterations using gene expression profiling of nonmicrodissected classical Hodgkin lymphoma tissues in order to generate new prognostic factors. These recent contributions are detailed and discussed in the present paper.

scholarly journals Biological Threat Detection via Host Gene Expression Profiling

2003 ◽  
Vol 49 (7) ◽  
pp. 1045-1049 ◽  
Author(s):  
Baochuan Lin ◽  
Maryanne T Vahey ◽  
Dzung Thach ◽  
David A Stenger ◽  
Joseph J Pancrazio
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Host Gene ◽  
Threat Detection ◽  
Host Gene Expression ◽  
Detection Techniques

Abstract With the increased threat posed by biological weapons, detection techniques for biothreat pathogens are critically needed to monitor and assess the severity of the illness once exposure has occurred. Current approaches for detecting biological threats are either time-consuming or highly specific but provide little information regarding pathogenicity. Genotyping of pathogens by PCR provides a fast and definitive means for identifying pathogens, but reliance on pathogen genotypic endpoints has several limitations. Current progress in DNA microarrays technology provides an alternative way to address the issues faced by traditional detection systems through host gene expression profiles of peripheral blood cells. We discuss the advantages and critical issues facing the use of host gene expression profiling for biological threat detection.

scholarly journals Effectiveness of Gene Expression Profiling for Response Prediction of Rectal Adenocarcinomas to Preoperative Chemoradiotherapy

2005 ◽  
Vol 23 (9) ◽  
pp. 1826-1838 ◽  
Author(s):  
B. Michael Ghadimi ◽  
Marian Grade ◽  
Michael J. Difilippantonio ◽  
Sudhir Varma ◽  
Richard Simon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response Prediction ◽  
Preoperative Chemoradiotherapy ◽  
Response To Therapy ◽  
Phase Iii ◽  
Correct Prediction

Purpose There is a wide spectrum of tumor responsiveness of rectal adenocarcinomas to preoperative chemoradiotherapy ranging from complete response to complete resistance. This study aimed to investigate whether parallel gene expression profiling of the primary tumor can contribute to stratification of patients into groups of responders or nonresponders. Patients and Methods Pretherapeutic biopsies from 30 locally advanced rectal carcinomas were analyzed for gene expression signatures using microarrays. All patients were participants of a phase III clinical trial (CAO/ARO/AIO-94, German Rectal Cancer Trial) and were randomized to receive a preoperative combined-modality therapy including fluorouracil and radiation. Class comparison was used to identify a set of genes that were differentially expressed between responders and nonresponders as measured by T level downsizing and histopathologic tumor regression grading. Results In an initial set of 23 patients, responders and nonresponders showed significantly different expression levels for 54 genes (P < .001). The ability to predict response to therapy using gene expression profiles was rigorously evaluated using leave-one-out cross-validation. Tumor behavior was correctly predicted in 83% of patients (P = .02). Sensitivity (correct prediction of response) was 78%, and specificity (correct prediction of nonresponse) was 86%, with a positive and negative predictive value of 78% and 86%, respectively. Conclusion Our results suggest that pretherapeutic gene expression profiling may assist in response prediction of rectal adenocarcinomas to preoperative chemoradiotherapy. The implementation of gene expression profiles for treatment stratification and clinical management of cancer patients requires validation in large, independent studies, which are now warranted.

Gene Expression Profiling Reveals Fundamental Differences between Leukemic Stem Cells (Lin-CD34+CD38−) and Mature Blasts (Lin−CD34+CD38+) of Acute Myeloid Leukaemia (AML) Patients.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1377-1377
Author(s):  
Kazem Zibara ◽  
Daniel Pearce ◽  
David Taussig ◽  
Spyros Skoulakis ◽  
Simon Tomlinson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Populations ◽  
Leukemic Stem Cells ◽  
Significant Differential Expression ◽  
New Genes

Abstract The identification of LSC has important implications for future research as well as for the development of novel therapies. The phenotypic description of LSC now enables their purification and should facilitate the identification of genes that are preferentially expressed in these cells compared to normal HSC. However, gene-expression profiling is usually conducted on mononuclear cells of AML patients from either peripheral blood and/or bone marrow. These samples contain a mixture of blasts cells, normal hematopoietic cells and limited number of leukemic stem cells. Thus, this results in a composite profile that obscure differences between LSC and blasts cells with low proliferative potential. The aim of this study was to compare the gene expression profile of highly purified LSC versus leukemic blasts in order to identify genes that might have important roles in driving the leukemia. For this purpose, we analyzed the gene expression profiles of highly purified LSCs (Lin−CD34+CD38−) and more mature blast cells (Lin−CD34+CD38+) isolated from 7 adult AML patients. All samples were previously tested for the ability of the Lin−CD34+CD38− cells but not the Lin−CD34+CD38+ fraction to engraft using the non-obese diabetic/severe combined immuno-deficiency (NOD-SCID) repopulation assay. Affymetrix microarrays (U133A chip), containing 22,283 genes, were used for the analysis. Comparison of Lin-CD34+CD38- cell population to the Lin−CD34+CD38+ cell fraction showed 5421 genes to be expressed in both fractions. Comparative analysis of gene-expression profiles showed statistically significant differential expression of 133 genes between the 2 cell populations. Most of the genes were downregulated in the LSC-enriched fraction, compared to the more differentiated fraction. Gene ontology was used to determine the categories of the up-regulated transcripts. These transcripts, which are selectively expressed, include a number of known genes (e.g., receptors, signalling genes, proliferation and cell cycle genes and transcription factors). These genes play important roles in differentiation, self-renewal, migration and adhesion of HSCs. Among the genes showing the highest differences in expression levels were the following: ribonucleotide reductase M2 polypeptide, thymidylate synthetase, ZW10 interactor, cathepsin G, azurocidin 1, topoisomerase II, CDC20, nucleolar and spindle associated protein 1, Rac GTPase activating protein 1, leukocyte immunoglobulin-like receptor, proliferating cell nuclear antigen, myeloperoxidase, cyclin A1 (RRM2, TYMS, ZWINT, CTSG, AZU1, TOP2A, CDC20, NUSAP1, RACGAP1, LILRB2, PCNA, MPO, CCNA1). Some transcripts detected have not been implicated in HSC functions, and others have unknown function so far. This work identifies new genes that might play a role in leukemogenesis and cancer stem cells. It also leads to a better description and understanding of the molecular phenotypes of these 2 cell populations. Hence, in addition to being a more efficient way to further understand the biology of LSC, this should also provide a more efficient way of identifying new therapeutics and diagnostic targets.

scholarly journals Gene expression profiling of the Notch-AhR-IL22 axis at homeostasis and in response to tissue injury

2017 ◽  
Vol 37 (6) ◽  
Author(s):  
Marc Weidenbusch ◽  
Severin Rodler ◽  
Shangqing Song ◽  
Simone Romoli ◽  
Julian A. Marschner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Tissue Injury ◽  
Expression Profiles ◽  
Notch Pathway ◽  
Gene Expression Profiles ◽  
Sterile Inflammation ◽  
Specific Gene ◽  
Specific Gene Expression

Notch and interleukin-22 (IL-22) signaling are known to regulate tissue homeostasis and respond to injury in humans and mice, and the induction of endogenous aryl hydrocarbon receptor (Ahr) ligands through Notch links the two pathways in a hierarchical fashion. However in adults, the species-, organ- and injury-specific gene expression of the Notch-AhR-IL22 axis components is unknown. We therefore performed gene expression profiling of DLL1, DLL3, DLL4, DLK1, DLK2, JAG1, JAG2, Notch1, Notch2, Notch3, Notch4, ADAM17/TNF-α ADAM metalloprotease converting enzyme (TACE), PSEN1, basigin (BSG)/CD147, RBP-J, HES1, HES5, HEY1, HEYL, AHR, ARNT, ARNT2, CYP1A1, CYP24A1, IL-22, IL22RA1, IL22RA2, IL10RB, and STAT3 under homeostatic conditions in ten mature murine and human organs. Additionally, the expression of these genes was assessed in murine models of acute sterile inflammation and progressive fibrosis. We show that there are organ-specific gene expression profiles of the Notch-AhR-IL22 axis in humans and mice. Although there is an overall interspecies congruency, specific differences between human and murine expression signatures do exist. In murine tissues with AHR/ARNT expression CYP1A1 and IL-22 were correlated with HES5 and HEYL expression, while in human tissues no such correlation was found. Notch and AhR signaling are involved in renal inflammation and fibrosis with specific gene expression changes in each model. Despite the presence of all Notch pathway molecules in the kidney and a model-specific induction of Notch ligands, IL-22 was only up-regulated in acute inflammation, but rapidly down-regulated during regeneration. This implies that for targeting injury responses, e.g. via IL-22, species-specific differences, injury type and time points have to be considered.

scholarly journals Prediction of cytogenetic abnormalities with gene expression profiles

Blood ◽  
2012 ◽  
Vol 119 (21) ◽  
pp. e148-e150 ◽  
Author(s):  
Yiming Zhou ◽  
Qing Zhang ◽  
Owen Stephens ◽  
Christoph J. Heuck ◽  
Erming Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Parameters ◽  
Proof Of Concept ◽  
Accuracy Rate ◽  
Cytogenetic Abnormalities

Abstract Cytogenetic abnormalities are important clinical parameters in various types of cancer, including multiple myeloma. We developed a model to predict cytogenetic abnormalities in patients with multiple myeloma using gene expression profiling and validated it by different cytogenetic techniques. The model has an accuracy rate up to 0.89. These results provide proof of concept for the hypothesis that gene expression profiling is a superior genomic method for clinical molecular diagnosis and/or prognosis.

Infant Acute Lymphoblastic Leukemias Are Pan-Sensitive to Obatoclax Across molecular/Cytogenetic Subtypes, Especially MLL-ENL, and gene Expression Profiles Determine Obatoclax IC50: A Report on the Children's Oncology Group (COG) P9407 Trial

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2757-2757 ◽  
Author(s):  
Karen A. Urtishak ◽  
Li-San Wang ◽  
Richard Harvey ◽  
Susan R Atlas ◽  
I-Ming L. Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Single Agent ◽  
Gene Expression Profiles ◽  
Poor Survival ◽  
Molecular Cytogenetic ◽  
Ic50 Values ◽  
Mtt Assays

Abstract Abstract 2757 Introduction: The outcome of infants with acute lymphoblastic leukemia (ALL) remains poor because of the association of frequently occurring MLL translocations with drug resistance and vulnerability of the very young to treatment complications. The two most common MLL partner genes in infant ALL, AF4 (AFF1) and ENL (MLLT1), are associated with particularly poor survival. Better therapies are urgent. One candidate is obatoclax (GeminX Biotechnologies, Inc.), which targets interactions of pan-anti-apoptotic BCL-2 family proteins with BH3 proteins and is now in a Phase I trial for relapsed/refractory pediatric cancers (COG ADVL0816). Previously we showed potent single agent in vitro activity of obatoclax against MLL-rearranged infant ALL (Zhang ASH 2008). Here we evaluate correlations of obatoclax activity with MLL translocation status and gene expression profiles in a large number of cases of infant ALL to define molecular determinants of sensitivity. Methods: Bone marrow, peripheral blood or apheresis samples from the time of diagnosis in 54 infants (age 1–365 d, median 168 d; WBC count 15–1230×103/μL, median 445×103/μL) with ALL (n=52) or bilineal acute leukemia (n=2) were examined, 48 of which were from the COG P9407 trial. By molecular/cytogenetic classification, the cases were MLL-AF4+ (n= 28), MLL-ENL+ (n= 11), other MLL rearrangement positive (other MLL+) (n= 8) or MLL germline (MLL-) (n= 7). Single agent IC50 values from MTT assays after 72 h obatoclax exposures were determined in all cases (including 13 previously tested; Zhang ASH 2008) by plotting the surviving fractions. IC50s in the MLL-AF4+ group were compared to those in each of the other 3 molecular/cytogenetic groups by Wilcoxon's test. Gene expression profiling was performed on Affymetrix HG_U133 Plus2.0 arrays in 47 of the 48 COG P9407 cases. Spearman test was used to identify correlation between log2 expression levels for each probeset and IC50 values across subjects. A heatmap of significant probesets (p≤0.001) was generated by transforming expression levels to z-scores and ordering rows and columns by complete linkage hierarchical clustering. Ingenuity pathway analysis was applied to all probesets with p≤0.01 to identify pathways significantly correlated with IC50. Additional MTT assays were initiated to test sensitivity to agents targeting these pathways. Results: Even though most cases in all 4 groups were sensitive to obatoclax as indicated by IC50s within a clinically achievable range, MLL translocation status still had a significant effect on IC50. MLL-AF4+ cases were least sensitive and MLL-ENL+ cases were most sensitive to obatoclax. Respective IC50 ranges across all 54 cases were: MLL-AF4+, 26–918 nM; MLL-ENL+, 13–294 nM; other MLL+ 10–356 nM; MLL−, 31–488. Compared to MLL-AF4+, the IC50s in MLL-ENL+ cases were significantly lower (p=0.047), IC50s in other MLL+ cases were lower but the difference did not achieve significance (p=0.10), and IC50s in MLL- cases were not significantly different (p=0.64). In the 47 COG P9407 cases studied by MTT assay and gene expression profiling, 450 probesets defined a cluster of 16 cases with higher IC50s, which were predominantly MLL-AF4+ (68.7%). Ingenuity analysis identified significant correlations of the following canonical pathways with the IC50 in the same 47 cases: glycolysis/gluconeogenesis, mTOR signaling, regulation of eIF4 and p70S6K signaling, EIF2 signaling, and fructose and mannose metabolism. In preliminary analyses, cell lines with t(4;11) exhibited time and dose-dependant sensitivity to the eIF4e inhibitor ribavirin. Conclusions: In infant ALL, obatoclax has broad-spectrum activity and there is pan-sensitivity across MLL translocation subtypes and MLL− cases. Still specific MLL partner genes have a strong effect on obatoclax IC50 and there is exquisite sensitivity in MLL-ENL+ cases. This result is important because MLL-ENL is associated with particularly poor survival when conventional therapies are used. The association of differentially expressed genes in canonical cell signaling and metabolism pathways with differences in obatoclax sensitivity forms the basis to combine obatoclax with targeted agents directed at restoring these pathways to enhance responsiveness even further. Disclosures: Felix: None: Patent not licensed.

scholarly journals Arrays of Arrays for High-Throughput Gene Expression Profiling

2001 ◽  
Vol 11 (7) ◽  
pp. 1256-1261
Author(s):  
Patrick P. Zarrinkar ◽  
James K. Mainquist ◽  
Matthew Zamora ◽  
David Stern ◽  
John B. Welsh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Ovarian Tissue ◽  
Disease Diagnosis ◽  
Full Potential ◽  
Ovarian Carcinomas ◽  
Single Experiment ◽  
Tissue Samples

Gene expression profiling using DNA arrays is rapidly becoming an essential tool for research and drug discovery and may soon play a central role in disease diagnosis. Although it is possible to make significant discoveries on the basis of a relatively small number of expression profiles, the full potential of this technology is best realized through more extensive collections of expression measurements. The generation of large numbers of expression profiles can be a time-consuming and labor-intensive process with current one-at-a-time technology. We have developed the ability to obtain expression profiles in a highly parallel yet straightforward format using glass wafers that contain 49 individual high-density oligonucleotide arrays. This arrays of arrays concept is generalizable and can be adapted readily to other types of arrays, including spotted cDNA microarrays. It is also scalable for use with hundreds and even thousands of smaller arrays on a single piece of glass. Using the arrays of arrays approach and parallel preparation of hybridization samples in 96-well plates, we were able to determine the patterns of gene expression in 27 ovarian carcinomas and 4 normal ovarian tissue samples, along with a number of control samples, in a single experiment. This new approach significantly increases the ease, efficiency, and throughput of microarray-based experiments and makes possible new applications of expression profiling that are currently impractical.

Identification of Target Genes for the Tumor Suppressor RIZ1 Using Gene Expression Profiling.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4351-4351
Author(s):  
Wei-Feng Dong ◽  
Naoto Takahashi ◽  
Matthew N. Bainbridge ◽  
Andrea R. Hull ◽  
Stuart A. Scott ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Suppressor ◽  
Gene Expression Profiling ◽  
Cell Line ◽  
Expression Profiling ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Gene Expression Profiles ◽  
Cmv Promoter

Abstract RIZ1 (PRDM2) is a tumor suppressor gene on 1p36 that frequently undergoes deletion, rearrangements, and loss of heterozygosity in a broad spectrum of tumors. RIZ1 is a member of the nuclear protein methyltransferase superfamily involved in chromatin remodeling. RIZ1 contains a ~130 amino acid conserved domain (PR or SET) that is important in chromatin-mediated regulation of gene expression and in the development of cancer. RIZ1 methylates Histone H3 on K9 and this activity may play a role in transcription repression as H3-K9 methylation is known to be associated with repression. Aberrant activities or mistargeting of chromatin modifying activities are proving to have unexpected links to cancer. We and others have shown that RIZ1 expression is down regulated in human leukemias and in the human erythroleukemia cell line K562. Expression of RIZ1 in K562 reduced proliferation, increased apoptosis, and promoted erythroid differentiation. To understand how RIZ1’s DNA binding, methyltransferase, and transcription repressor functions are related to its tumor suppressor activity it is necessary to characterize RIZ1 target genes. We used DNA microarrays to globally monitor how RIZ1 affects gene expression profiles. We constructed a K562 cell line with RIZ1 stably integrated under the control of a CMV promoter and analyzed the gene expression profiles of K652 and K562 + RIZ1 using a 42K Stanford human gene microarray. By comparing the gene expression profiles of these cell lines, we identified potential RIZ1 gene targets that are up and down regulated in the presence of RIZ1. In total, we identified 5 upregulated genes and 20 down regulated genes using significance analysis of microarrays (SAM) and standard deviation filter analysis of the gene expression data. RIZ1-mediated changes in gene expression profiling indicate that RIZ1 is potentially involved in the regulation and connection of the IGF-1 (IGF-1, IGFBP2) and integrin (LMS1) pathways, and in the activation of the TGF-β (SPARC) pathway. The genes perturbed by RIZ1 expression suggest that the tumor suppressor properties of RIZ1 arise from its control of proliferation, apoptosis and differentiation using these pathways. Finally, we observed an overrepresentation of the SP-1 transcription factor binding sites in genes that are upregulated in the absence of RIZ1. This correlates with the ability of RIZ1 to recognize SP1 sequences.

Characterization of Distinct Molecular Signatures in Myeloproliferative Diseases with the JAK2V617F Mutation and Wild Type JAK2.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 119-119
Author(s):  
Benjamin L. Ebert ◽  
Ross L. Levine ◽  
Martha Wadleigh ◽  
Jean-Philippe Brunet ◽  
Jennifer L. Pretz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Polycythemia Vera ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Jak2v617f Mutation ◽  
Wild Type ◽  
Jak2 Mutation ◽  
Myeloproliferative Diseases

Abstract The recently discovered JAK2V617F mutation provides a critical insight into the molecular pathogenesis of polycythemia vera and other myeloproliferative diseases (MPD). However, the mutations present in patients with wild type JAK2 have not been discovered, and the precise molecular consequences of JAK2 mutation have not been elucidated. We employed gene expression profiling to characterize the molecular phenotype of cells with the JAK2V617F mutation, to identify a distinct signature in cells without JAK2 mutations, and to refine a molecular taxonomy of MPDs. Using purified neutrophils from 70 patients with myeloproliferative diseases and 11 unaffected individuals, we performed gene expression profiling using oligonucleotide microarrays, sequencing of the JAK2 gene, quantitative genotyping by mass spectrometry and allele-specific quantitative PCR, and X-inactivation clonality assays. To reduce the confounding influence of normal neutrophils that are admixed with cells bearing disease-causing mutations, we examined the gene expression profiles of samples in which greater than 80% of JAK2 alleles bear the V617F mutation. PRV1, a previously identified marker of polycythemia vera, was powerfully overexpressed in neutrophils with a homozygous JAK2 mutation. In addition, cells with the JAK2 mutation had increased expression of a set of kinases, including JAK2, and decreased expression of a set of phosphatases. Cells that rely on JAK2 activation for clonal dominance may therefore derive a selective advantage from increased expression of the JAK2 gene. We next examined samples that have high clonality, and therefore relatively few normal neutrophils, but do not have a mutation in the JAK2 gene. These samples have a markedly different gene expression profile and overexpress a distinct set of kinases. The kinases overexpressed in cells with wild type JAK2 are candidates for further mutational analysis and are potential therapeutic targets. Utilizing these signatures and unsupervised analytical algorithms, the samples cluster according to their mutational status and the percentage of normal neutrophils in the sample. Our data demonstrate that the gene expression profiles of MPD samples are not uniform regardless of JAK2 genotype, implying that samples with and without JAK2 mutations have not activated the same pathway via alternative mechanisms. Moreover, we have identified a common signature in samples without JAK2 mutations that meets significance, indicating that one or a small number of mutations may play a critical role in these cells. Genotype and gene expression analyses are defining a molecular classification of myeloproliferative diseases with subtypes that have distinct therapeutic targets.

Prospective analysis of mRNA expression signatures as predictive tests in primary breast cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 2531-2531
Author(s):  
J. Hannemann ◽  
H. Halfwerk ◽  
A. Velds ◽  
C. Loo ◽  
E. J. Rutgers ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Complete Remission ◽  
Gene Expression Profiling ◽  
Preoperative Chemotherapy ◽  
Expression Profiling ◽  
Primary Breast Cancer ◽  
Molecular Subtypes ◽  
Expression Profiles ◽  
Gene Expression Profiles

2531 Background: Preoperative chemotherapy is increasingly employed to treat primary breast cancer, allowing an ‘in vivo chemosensitivity test’. Markers which predict a pathological complete response are urgently needed to refine this strategy. This study was conducted to evaluate the use of gene expression profiling to predict response to neoadjuvant anthracycline- or taxane-based chemotherapy. Methods: Patients with operable or locally advanced HER2-negative breast cancer received preoperative chemotherapy: either dose- dense doxorubicin and cyclophosphamide (ddAC) or capecitabine and docetaxel (CD). Core needle biopsies were taken before treatment and gene expression profiling was performed using 35k oligo microarrays. Results: Gene expression profiles were obtained from pretreatment biopsies of 63 tumors. 27% of the patients achieved a (near) pathologic complete remission (pCR), 40% of the patients had a partial remission and 33% of the patients did not respond to chemotherapy. Based on the gene expression profiles, tumors were assigned to the previously identified “molecular subtypes” luminal, basal-like or ERBB2-like (Sorlie et al., PNAS 98: 10869, 2001). 13 out of 25 patients with a basal-like tumor (52%) achieved a complete remission, whereas for the luminal tumors a pCR was only obtained in 2 out of 29 patients. Using four published gene expression classifiers of response to chemotherapy, a reasonable separation between responders and non-responders could be observed for two of these. We also performed exploratory supervised classification analyses on our dataset to identify a novel classifier. This resulted in a classifier for response to therapy irrespective of the chemotherapy regimen used and a second classifier specifically associated with response to ddAC chemotherapy. We will perform validation of these classifiers in samples from patients that are currently being enrolled in the study. Conclusions: Basal-like tumors have a better response to neoadjuvant chemotherapy as compared to other tumor types. The identification of robust gene expression signatures for better response prediction may require larger patient groups and should probably be established separately for each of the molecular subtypes of breast cancer. No significant financial relationships to disclose.

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