The Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Sub-Classification of Leukemia: Final Report on 3252 Cases from the International MILE Study Group

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 753-753 ◽  
Author(s):  
Torsten Haferlach ◽  
Alexander Kohlmann ◽  
Giuseppe Basso ◽  
Marie-Christine Béné ◽  
Sabina Chiaretti ◽  
...  

Abstract During the years of 2005 to 2008, the MILE (Microarray Innovations in LEukemia) study research program was performed in 11 laboratories across three continents: 7 from the European Leukemia Network (ELN, WP13), 3 from the US and 1 in Singapore. The first stage was designed as biomarker discovery phase to generate whole-genome gene expression profiles (GEP) from recognized categories of clinically relevant leukemias and myelodysplastic syndromes (MDS). These were C1: mature B-ALL with t(8;14), C2: pro-B-ALL with t(11q23)/MLL, C3: c-ALL/pre-B-ALL with t(9;22), C4: T-ALL, C5: ALL with t(12;21), C6: ALL with t(1;19), C7: ALL with hyperdiploid karyotype, C8: c-ALL/pre-B-ALL without specific genetic abnormalities, C9: AML with t(8;21), C10: AML with t(15;17), C11: AML with inv(16)/t(16;16), C12: AML with t(11q23)/MLL, C13: AML with normal karyotype or other abnormalities, C14: AML with complex aberrant karyotype, C15: CLL, C16: CML, C17: MDS, and C18: non-leukemic and healthy bone marrow samples as controls and were compared to conventional diagnostic assays (“Gold Standard”). Data from the completed MILE Stage I included 2143 retrospectively collected adult and pediatric samples tested with HG-U133 Plus 2.0 microarrays (Affymetrix). In total only 47 analyses (2.1%) failed technical quality criteria. Cross-validation accuracy (average of three 30-fold cross-validations) of the final 2096 MILE Stage I samples was 92.1% concordant with the center-specific “Gold Standard” diagnosis (average call rate 99.4%). In nine classes the sensitivity was ≥94.3%: C2, C3, C4, C5, C9, C10, C11, C15, and C16. Lower sensitivities were observed for C7, C8, C14, and C17; which can largely be explained by the biological heterogeneity and non-standardized “Gold Standard” definitions for these entities. Yet, it is notable that all these classes showed specificities above 98.1%. In order to assess the clinical utility of microarray-based diagnostics a prospective Stage II was subsequently performed using a customized microarray representing 1480 probe sets. Overall, 1156 high quality GEP have been generated in MILE Stage II and represent an independent and blinded test set for the algorithms developed. A focused classification scheme aimed at accurately addressing only acute leukemias resulted in a 95.5% median sensitivity and a 99.5% median specificity for the 14 classes included in the classifier (C1 – C14, n=696). Lower accuracies were observed for the interface of C7–C8 in ALL, as well as C12 and C14 in AML. Interestingly, during the process of discrepant results analyses, it was observed that for 7.5% (n=52) of acute leukemias microarray results were correctly diagnosing samples as compared to the initial “Gold Standard” diagnoses entered into the study database, either because of erroneous entries into case report forms (24%) or subsequent re-testing of left-over material following the suggested diagnosis from the microarray (76%). In addition, predicted accuracies for CLL, CML and MDS in Stage II were 99.2%, 95.2%, and 81.5%, respectively. In conclusion, the MILE research study confirms in a final cohort of 3252 patients that microarrays accurately classify acute and chronic leukemia samples into known diagnostic and prognostic sub-categories. This final report underlines that the standardized method of gene expression profiling with low technical failure rate and simplified standard operating procedures may improve current “Gold Standards” as an adjunct to conventional diagnostic algorithms and potentially offers a reliable diagnostic/prognostic tool for many patients who don’t have access to a state-of-the-art “Gold Standard” workup. Our gene expression database, intended to be submitted to the public domain, will further contribute to research that aims to elucidate the molecular understanding of leukemias.

2010 ◽  
Vol 28 (15) ◽  
pp. 2529-2537 ◽  
Author(s):  
Torsten Haferlach ◽  
Alexander Kohlmann ◽  
Lothar Wieczorek ◽  
Giuseppe Basso ◽  
Geertruy Te Kronnie ◽  
...  

Purpose The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. Methods The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling–based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. Results On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. Conclusion Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias.


Lung Cancer ◽  
2020 ◽  
Vol 147 ◽  
pp. 56-63
Author(s):  
Yoshiteru Kidokoro ◽  
Tomohiko Sakabe ◽  
Tomohiro Haruki ◽  
Taichi Kadonaga ◽  
Kanae Nosaka ◽  
...  

Oncogene ◽  
2006 ◽  
Vol 26 (18) ◽  
pp. 2642-2648 ◽  
Author(s):  
A Barrier ◽  
F Roser ◽  
P-Y Boëlle ◽  
B Franc ◽  
C Tse ◽  
...  

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 10-10
Author(s):  
Yvonne Bombard ◽  
Linda Rozmovits ◽  
Maureen E. Trudeau ◽  
Natasha B. Leighl ◽  
Ken Deal ◽  
...  

10 Background: Genomic information is increasingly used to personalize health care. One example is gene-expression profiling (GEP) tests that estimate recurrence risk to inform chemotherapy decisions in breast cancer treatment. Recently, GEP tests were publicly funded in Ontario. We assessed the clinical utility of GEP tests, exploring the factors facilitating their use and value in treatment decision-making. Methods: As part of a mixed-methods clinical utility study, we conducted interviews with oncologists (n=14), and focus groups and interviews with breast cancer patients (n=28) who underwent GEP, recruited through oncology clinics in Ontario. Data were analyzed using content analysis and constant comparison. Results: Various factors governing access to GEP have given rise to challenges for patients and oncologists. Oncologists are positioned as gatekeepers of GEP, providing access in medically appropriate cases. However, varying perceptions of appropriateness led to perceived inequities in access and negative impacts on the doctor-patient relationship. Media attention facilitated patient awareness of GEP but complicated gatekeeping. Additional administration burden and long waits for results led to increased patient anxiety and delayed treatment. Collectively, these factors inadvertently heightened GEP’s perceived value for patients relative to other prognostic indicators because of barriers to access. Conclusions: This study delineates the factors facilitating and restricting access to GEP, and highlights the roles of the media and organization of services in GEP’s perceived value and utilization. Results identify a need for administrative changes and practice guidelines to support streamlined and standardized utilization of the test.


2011 ◽  
Vol 8 (6) ◽  
pp. 615-622 ◽  
Author(s):  
Marianne Laouri ◽  
Meredith Halks-Miller ◽  
W David Henner ◽  
J Scott Nystrom

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 7657-7657
Author(s):  
J. Jassem ◽  
M. Jarzab ◽  
J. Niklinski ◽  
W. Rzyman ◽  
M. Kowalska ◽  
...  

7657 Background: Our aim was to determine the genes predictive for relapse-free and overall survival in stage I-II NSCLC. Methods: We analyzed the gene expression profiles in lung cancer specimens collected from 70 NSCLC patients (pts) who underwent curative pulmonary resection between 1999 and 2004 in two Polish centers (Gdansk, Bialystok). There were 54 men and 16 women aged 37–77 yrs (median 62.5 yrs), 45 with squamous cell ca, 22 with adenoca and 3 with large cell ca. Eight pts were staged pT1, 59 pT2 and 3 pT3; there were 49 and 21 pN0 and pN1 pts, respectively. 30 pts had a relapse and 32 pts died (median follow-up 36 months). Samples of tumor tissue were collected intraoperatively and snap-frozen, total RNA was isolated and gene expression profiling was carried out by Affymetrix HG-U133 2.0 Plus oligonucleotide microarray. Samples were pre-processed with RMA algorithm, gene selection was carried out by Support Vector Machines and Bayesian Compound Covariate Classifier, using own procedures and BRB-Array software developed by Simon and Peng Lam. Survival time prediction was carried out by method developed by Bair and Tibshirani (PLoS Biology 2004). Results: Based on the microarray gene expression profiling, the relapse could be predicted with 75.0% specificity and 53.3% sensitivity (positive predictive value [PPV] 61.5%, negative predictive value [NPV] 68.2%). The classifier, obtained by cross-validation of 70-sample dataset, consisted of 170 transcripts. Further gene selection was based on the prediction of the relapse-free survival: 1,919 genes, selected by fitting Cox proportional hazard model (p<0.05) and further used to predict survival by 4 principal components, distinguished between pts with high and low risk of relapse (p<0.05, log-rank test). The prediction of death was possible with 66.7% specificity and 57.1% sensitivity (PPV 53.3%, NPV 70%), but the distinction between high- and low-risk pts was significantly weaker than based on lymph node involvement (N0 vs. N1). Thus, for the final selection of genes this clinical variable was incorporated into the model as a covariate. Conclusions: Prediction of the risk of relapse in stage I-II NSCLC based on the gene expression profile is feasible, with NPV of 68.2%. No significant financial relationships to disclose.


Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 3375-3375
Author(s):  
Peter Hokland ◽  
Charlotte Guldborg Nyvold ◽  
Caroline Juhl Christensen ◽  
Anita Rethmeier ◽  
Torben Ørntoft ◽  
...  

Abstract Acute leukemias are remarkably heterogeneous as evidenced by the increasing number of recurring genetic and epigenetic abnormalities, especially the presence or absence of balanced translocations, which have been shown to be of independent prognostic significance. Thus, In a recent single center study we analyzed 250 AML patients for a series a genetic alteration and found that balanced translocations (identified by a multiplex PCR reaction; Pallisgaard et al, BLOOD, 1998 and Olesen et al, Brit. J. Hem. in press) were present in 17% of the patients, FLT3 internal tandem duplication in 24%, and MLL partial tandem duplication in 4%. In addition, we delineated the presence of promoter hypermethylation for the p15 (71%), MDR1 (4%), E-cadherin (CDH1) (64%), and Estrogen receptor (ER) (40%) genes by bisulfite DGGE (Aggerholm, Cancer Res. 1999) as well as the abnormal expression by RQ-PCR of genes related to increased chemotherapy resistance (MDR1 and MRP1) as well as resistance to undergo apoptosis (FAS, Bcl2, BAX and CASPASE3). Here we have performed gene expression profiling focusing on patients negative for all these molecular lesions. Out of the 250 patients, 8 were determined to be molecularly negative. Global gene expression analysis (Affymetrix human genome chip (U133A)) was performed on the 6 samples, from which high-quality RNA could be harvested. Figure Figure As will be seen from the Figure, all samples could be easily distinguished from TEL/AML pre-B ALL samples, and also in 4/6 cases clustered differently from AML/ETO+ and CBF/MYH11+ AML groups. Interestingly, as seen from the dendrogram, the 6 samples separated in three clusters, one also containing a CBF/MYH11+ patient (4 cases), one consisting of one single patient, while the last patient clustered together with the AML/ETO cases. While these data suggest that the gene expression in the molecularly negative patients can be different from that in CBF leukemias, it gives no clues for the leukemogenetic events in these patients. To that end, we analyzed the gene expression data and found 24 genes to be more than 5-fold overexpressed and 26 genes to be underexpressed compared to CBF AMLs. Of special notice was the increased usage of the prostaglandin/leukotriene metabolism pathway in two patients with strikingly similar global gene expression (arrows 3 and 4 from right on Fig.) including the prostaglandin I2 (prostacyclin) synthase, and the prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase) genes, which were more than 10-fold increased. Also noteworthy was the upregulation of LR8 protein IQ motif containing GTPase activating protein 1 in the remaining 4 cases. Applied together with novel global cytogenetic techniques, these data will form a platform for the identification of leukemogenesis in AML patients with no demonstrable genetic aberrations.ßßß


Sign in / Sign up

Export Citation Format

Share Document