Ninety Percent Sustained Complete Response (CR) Rate Projected 4 Years after Onset of CR in Gene Expression Profiling (GEP)-Defined Low-Risk Multiple Myeloma (MM) Treated with Total Therapy 3 (TT3): Basis for GEP-Risk-Adapted TT4 and TT5

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 162-162 ◽  
Author(s):  
Bart Barlogie ◽  
Elias J. Anaissie ◽  
John D. Shaughnessy ◽  
Frits van Rhee ◽  
Mauricio Pineda-Roman ◽  
...  

Abstract We have previously reported on the remarkable activity of the TT3 program that incorporated both bortezomib (V) and thalidomide (T) into the up-front management of 303 patients. TT3 consisted of 2 cycles each of induction prior to and of dose-reduced consolidation therapy with VTD-PACE (cisplatin, doxorubicin, cyclophosphamide, etoposide) after melphalan 200mg/m2 (M200)-based tandem transplants, followed by maintenance therapy for 3 years with VTD and, in later stages, VRD (substituting T for lenalidomide, R). Characteristics included a median age of 59yr (range, 33–75yr), B2M >=4mg/L in 37%, albumin <3.5g/dL in 26%, ISS stages II and III in 33% and 21%, cytogenetic abnormalities (CA) in 33% and gene expression profiling (GEP)-defined high-risk MM in 15% of the 275 patients with such data. With a median follow-up of 39 months, 4-yr overall survival (OS) and event-free survival (EFS) estimates were 78% and 71%, respectively, including 84% and 77% among the 85% with GEP-defined low-risk MM contrasting with 43% and 33% in the remainder with high-risk MM (both p<0.0001). Near-CR and CR, attained in 86% and 63%, were sustained at 4 years from response onset in 78% and 87%, which pertained to 83% and 90% with low-risk MM but to only 44% and 57% with high-risk MM (all p <0.0001). These results were corroborated in a TT3 extension trial (TT3E) that enrolled 175 additional patients, comprising higher proportions of CA (42%) and GEP-defined high-risk MM (21%). Two-year estimates of OS and EFS are 85% and 85%, with 94% and 92% in low-risk patients versus 61% and 62% in high-risk MM (p=0.0001, p=0.0003); the 2-yr estimate of remaining in CR is 93% including 100% in low-risk and 77% in high-risk MM (p=0.01). Multivariate analysis of features linked to OS in TT3 included GEP-defined high-risk, CA, B2M and LDH elevation, collectively accounting for 41% of outcome variability by R2 statistics; the corresponding R2 values for EFS and n-CR duration were 38% and 39%. Compared to the predecessor trial, TT2, that evaluated the role of T in a randomized trial design in 668 patients, TT3 data were superior for OS (p=0.08), EFS (<0.0001), n-CR duration (p<0.0001) and CR duration (p=0.0002). In the low-risk subgroup, EFS (p=0.0001), n-CR duration (p<0.0001) and CR duration (Figure 1a; p=0.0002) all were superior in TT3 versus TT2; whereas, in the high-risk MM group, outcomes remained poor also with TT3 despite superior EFS (Figure 1b; p=0.03). Based on these data, we have now started a GEP-risk-based algorithm of assigning separate therapies to good-risk (TT4) and poor-risk MM (TT5). As the TT3 results for low-risk are difficult to improve upon, TT4 randomizes patients between standard TT3 and TT3-LITE that employs only 1 cycle each of induction and consolidation (with anticipated further improvement in compliance) and 4-day-fractionated M50×4 to enable the addition of VTD and thus exploit synergistic drug interactions to occur. In order to sustain tolerable effective therapies for at least 3 years and prevent recurrence from previous drug-free or insufficiently effective phases in TT3, TT5 for high-risk MM employs less dose-intense and more dose-dense highly synergistic combination therapy, utilizing M10-VTD-PACE for induction, M80 (in 4 daily fractions of M20) plus VRD-PACE tandem transplants, separated by 2 cycles of M20 (in 4 daily fractions of M5) plus VTD-PACE, and followed by 2 years of monthly alternating R-VD and M-VD. Figure 1a: Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1a:. Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1b: Superior event-free survival with TT3 v TT2 in GEP-high-risk MM: Figure 1b:. Superior event-free survival with TT3 v TT2 in GEP-high-risk MM:

Blood ◽  
2010 ◽  
Vol 115 (21) ◽  
pp. 4168-4173 ◽  
Author(s):  
Bijay Nair ◽  
Frits van Rhee ◽  
John D. Shaughnessy ◽  
Elias Anaissie ◽  
Jackie Szymonifka ◽  
...  

The Total Therapy 3 trial 2003-33 enrolled 303 newly diagnosed multiple myeloma patients and was noted to provide superior clinical outcomes compared with predecessor trial Total Therapy 2, especially in gene expression profiling (GEP)–defined low-risk disease. We report here on the results of successor trial 2006-66 with 177 patients, using bortezomib, lenalidomide, and dexamethasone maintenance for 3 years versus bortezomib, thalidomide, and dexamethasone in year 1 and thalidomide/dexamethasone in years 2 and 3 in the 2003-33 protocol. Overall survival (OS) and event-free survival (EFS) plots were super-imposable for the 2 trials, as were onset of complete response and complete response duration (CRD), regardless of GEP risk. GEP-defined high-risk designation, pertinent to 17% of patients, imparted inferior OS, EFS, and CRD in both protocols and, on multivariate analysis, was the sole adverse feature affecting OS, EFS, and CRD. Mathematical modeling of CRD in low-risk myeloma predicted a 55% cure fraction (P < .001). Despite more rapid onset and higher rate of CR than in other molecular subgroups, CRD was inferior in CCND1 without CD20 myeloma, resembling outcomes in MAF/MAFB and proliferation entities. The robustness of the GEP risk model should be exploited in clinical trials aimed at improving the notoriously poor outcome in high-risk disease.


2016 ◽  
Vol 6 (9) ◽  
pp. e471-e471 ◽  
Author(s):  
Y Jethava ◽  
A Mitchell ◽  
M Zangari ◽  
S Waheed ◽  
C Schinke ◽  
...  

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 73-73 ◽  
Author(s):  
Dirk Hose ◽  
Jean-Francois Rossi ◽  
Carina Ittrich ◽  
John deVos ◽  
Axel Benner ◽  
...  

Abstract AIM was to establish a new molecular classification of Multiple Myeloma (MM) based on changes in global gene expression attributable to cytogenetic aberrations detected by interphase FISH (iFISH) in order to (i) predict event free survival (EFS) and (ii) investigate differentially expressed genes as basis for a group specific and risk adapted therapy. PATIENTS AND METHODS. Bone marrow aspirates of 105 newly diagnosed MM-patients (65 trial (TG) / 40 independent validation group (VG)) and 7 normal donors (ND) were CD138-purified by magnetic activated cell sorting. RNA was in-vitro transcribed and hybridised to Affymetrix HG U133 A+B GeneChip (TG) and HG U133 2.0 plus arrays (VG). CCND1 and CCND2 expression was verified by real time RT-PCR. iFISH was performed on purified MM-cells using probes for chromosomes 11q23, 11q13, 13q14, 17p13 and the IgH-translocations t(4;14) and t(11;14). Expression data were normalised (Bioconductor package gcrma) and nearest shrunken centroids (NSC) applied to calculate and cross validate a predictor on 40 patients of the TG with a comprehensive iFISH panel available combined with CCND overexpression. Differentially expressed genes were identified using empirical Bayes statistics for pairwise comparison. RESULTS. Overexpression of a D-type cyclin (D1 or D2) was found in 61/65 patients with MM compared to ND. CCND3 overexpression only appeared concomitantly with CCND2 overexpression. Four groups could be distinguished: (1.1) CCND1 (11q13) overexpression and trisomy 11q13, (1.2) CCND1 overexpression and translocations involving 11q13 i.e. t(11;14), (2.1) CCND2 overexpression without 11q13+, t(11;14), t(4;14), (2.2) CCND2 overexpression with t(4;14) and FGFR3 upregulation. A predictor of 6 to 566 genes correctly classifies all 40 patients of the TG (estimated cross validated error rate 0%). An independent VG of 40 patients was used. Genes with highest scores in NSC are: (1.1) CCND1, ribosomal proteins (e.g. RPL 28, 29), GPX1, CCRL2, (1.2) CCND1, TGIF, and NCAM (non-overexpression), (2.1) CCND2, (2.2) FGFR3, WHSC1, CCND2, IRTA2, SELL, and MAGED4. Distribution of clinical parameters (i.e. β2M, Durie Salmon stages, ISS) was not significantly different between the groups. The distribution of del(13)(q14q14) was (1.1) 31.5%, (1.2) 37.5%, (2.1) 37.5% and (2.2) 100%. (p<0.01). I.e. HGF, DKK1, VCAM, CD163 are differentially expressed between all 4 groups and ND (adjusted p<0.001). The groups defined by the predictor show a significantly different EFS after autologous stem cell transplantation according to the GMMG-HD3 protocol (median: (1.1) 18 / (1.2) not reached (no event) / (2.1) 22 / (2.2) 6 months; log-rank-test: p=0.004). CONCLUSION. CCND1 or CCND2 overexpression is nearly ubiquitous in MM and attributable to defined cytogenetic aberrations. Gene expression and iFISH allow a molecular classification of MM which can be predicted by gene expression profiling alone. Groups in the classification show a distinctive pattern in gene expression as well as a different EFS interpretable as risk stratification and indicator of therapeutic targets.


Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3401-3401
Author(s):  
Maud Condomines ◽  
Dirk Hose ◽  
Thierry Reme ◽  
Michael Hundemer ◽  
John De Vos ◽  
...  

Abstract Cancer-testis (CT) antigens are expressed in testis and malignant tumors, but rarely in non-gametogenic tissues. Due to this pattern, they represent attractive targets for cancer vaccination approaches. The aims of the present study were (1) to assess for the first time the expression of CT genes on a pangenomic basis in multiple myeloma (MM), (2) to provide selection strategies of CT antigens for clinical vaccination trials and (3) to assess the impact of CT gene expression on event-free survival. We report here the expression pattern of CT genes in purified MM cells (MMC) of 64 patients with newly-diagnosed MM, 12 patients with monoclonal gammopathy of unknown significance (MGUS), in normal plasma cell and B cell samples and in 20 MMC lines, using gene expression profiling (GEP). Out of 46 CT genes interrogated by the Affymetrix HG U133 Set arrays, 35 were expressed in MMC of at least one patient, according to the Affymetrix “present” call (frequency range: 2% – 66%). Of these, 24 CT genes were expressed in more than 5% of the MMC samples and 25 are located on chromosome X. MMC of 98% of the patients expressed at least one CT gene, 86% at least two, and 70% at least three CT genes. By using a set of 10 CT genes including KM-HN-1, MAGE-C1, MAGE-A3/6/12, MAGE-A5, MORC, DDX43, SPACA3, SSX-4, GAGE-1–8 and MAGE-C2, a combination of at least three CT genes - desirable to circumvent tumor escape mechanisms and immune tolerance - could be obtained in MMC of 67% of the patients. Thus, gene expression profiling can be used to select CT antigens as vaccination targets in individual patients. In a series of MMC from 111 patients treated with the same high-dose chemotherapy and autologous peripheral blood stem cell transplantation protocol and having a median two-year follow-up, we found that the expression of six CT genes, i.e. CTAG-1B, CTAG-2, MAGE-A1, MAGE-A2, MAGE-A3 and MAGE-A6 was associated with a shorter event-free survival (EFS). Furthermore, considering only the 25 CT genes encoded by chromosome X, a CT-Xhigh cluster comprising MMC of one third of the patients (35 of 111) could be defined using a binary hierarchical clustering based on Affymetrix call. Patients in the CT-Xhigh cluster had a shorter EFS (median 13 months) compared to patients in the CT-Xlow cluster (median 18 months, P = .003). The CT-Xhigh clsuter included more patients with a stage III disease (P = .004). These results confirm data from previous studies indicating that patients expressing some CT genes located on chromosome X have a poor outcome.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3517-3517
Author(s):  
Allison C. Rosenthal ◽  
Colleen Ramsower ◽  
Raphael Mwangi ◽  
Matthew J. Maurer ◽  
Diego Villa ◽  
...  

Abstract BACKGROUND: Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin lymphoma with variable clinical outcomes. Commonly used risk stratification tools (Ki67 IHC, MIPI) in newly diagnosed MCL are not frequently used when selecting therapy, resulting in treatment choice being dictated by age and co-morbidities rather than disease biology. The MCL35 risk score was developed as a more reliable measure of proliferation and has been shown to be prognostic and can risk stratify younger transplant eligible MCL patients into three groups with significantly different overall survival (OS; Scott et al. 2017; Holte et al. 2018) but has not been evaluated in older transplant ineligible patients. We report results evaluating the prognostic value of the MCL35 assay in older MCL patients (≥65) treated with frontline bendamustine/rituximab (BR). METHODS: Archived tissue samples from 119 patients age ≥65 years treated with BR from collaborating Lymphoma/Leukemia Molecular Profiling Project (LLMPP) sites and the LEO/MER cohort were collected and analyzed using the MCL35 assay and stratified into three distinct risk groups (low, standard, and high risk). Association between MCL35 proliferation scores and OS were estimated by the Kaplan-Meier method and hazard ratios were calculated. Associations between Ki67, s-MIPI, p53 IHC status, morphology and OS were also evaluated. RESULTS: The MCL35 assay was run on tissue samples from 119 patients. Median patient age was 74 (range 65-93) and 69.5% were male. Ki67 was &lt;30% in 29 patients (24%) and ≥30% in 90 patients (76%). Simplified MIPI (s-MIPI) score was 0-3 in 21 patients (24%), 4-5 in 42 patients (48%) and ≥6 in 25 patients (28%). Thirty-one did not have sufficient data to calculate a s-MIPI score. MCL35 was low risk in 51 patients (43%), standard risk in 39 patients (33%) and high risk in 29 patients (24%). Eleven patients had blastic morphology, 7 had pleomorphic morphology and the remainder were classic morphology (n=56). Of 57 samples with p53 IHC staining 7 (12.3%) were positive. At a median follow up of 33.4 months, 82 patients were alive and 35 had died. Patients with high risk MCL35 score had inferior OS compared to low risk (HR 2.27, 95% CI: 1.03-5.00; p=0.042) while standard risk was not statistically significant compared to low risk (HR 0.87, 95% CI: 0.37-2.0; p=0.740)(Figure 1). Ki67 IHC using a cutoff of ≥ 30% and 10%-29% was not significantly associated with OS compared to Ki67 &lt;10% ( Ki67 ≥ 30% vs. Ki67 &lt; 10%, HR 0.87, 95% CI: 0.12-6.41; p=0.892, Ki67 ≥ 10%-29% vs. Ki67 &lt; 10%, HR 0.32, 95% CI: 0.04-2.83; p=0.303), however high s-MIPI score (≥6) (s-MIPI ≥6 vs. s-MIPI 0-3, HR 3.86, 95% CI 1.20-12.5; p=0.024) and positive p53 IHC (HR: 9.51, 3.26-27.7; p &lt;0.001) were both associated with poor OS. Eighteen cases were blastic/pleomorphic by morphology, 12 of which were in the high-risk group by MCL35, and this subset also had worse survival than classic MCL (p=0.0052). CONCLUSIONS: These results suggest high risk MCL35 score is a prognostic biomarker of poor OS in patients &gt;65 with MCL treated with BR. Conversely, Ki67 was not significantly associated with OS in these patients. Additional clinical validation using a larger sample size from the E1411 study is planned. If similar results are found, the MCL35 assay in combination with s-MIPI and p53 status may have utility in stratifying patients into risk adapted treatment arms in future prospective clinical trial designs. Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Cohen: Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo, BeiGene, Adaptive: Consultancy; Genentech, BMS/Celgene, LAM, BioINvent, LOXO, Astra Zeneca, Novartis, M2Gen, Takeda: Research Funding. Hill: Celgene (BMS): Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Gentenech: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; Incyte/Morphysis: Consultancy, Honoraria, Research Funding. Raess: Scopio Labs: Research Funding. Scott: Celgene: Consultancy; NanoString Technologies: Patents & Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents & Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; Rich/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Incyte: Consultancy; Abbvie: Consultancy; AstraZeneca: Consultancy. Rimsza: NanoString Technologies: Other: Fee-for-service contract.


Blood ◽  
2010 ◽  
Vol 116 (23) ◽  
pp. 4874-4884 ◽  
Author(s):  
Richard C. Harvey ◽  
Charles G. Mullighan ◽  
Xuefei Wang ◽  
Kevin K. Dobbin ◽  
George S. Davidson ◽  
...  

Abstract To resolve the genetic heterogeneity within pediatric high-risk B-precursor acute lymphoblastic leukemia (ALL), a clinically defined poor-risk group with few known recurring cytogenetic abnormalities, we performed gene expression profiling in a cohort of 207 uniformly treated children with high-risk ALL. Expression profiles were correlated with genome-wide DNA copy number abnormalities and clinical and outcome features. Unsupervised clustering of gene expression profiling data revealed 8 unique cluster groups within these high-risk ALL patients, 2 of which were associated with known chromosomal translocations (t(1;19)(TCF3-PBX1) or MLL), and 6 of which lacked any previously known cytogenetic lesion. One unique cluster was characterized by high expression of distinct outlier genes AGAP1, CCNJ, CHST2/7, CLEC12A/B, and PTPRM; ERG DNA deletions; and 4-year relapse-free survival of 94.7% ± 5.1%, compared with 63.5% ± 3.7% for the cohort (P = .01). A second cluster, characterized by high expression of BMPR1B, CRLF2, GPR110, and MUC4; frequent deletion of EBF1, IKZF1, RAG1-2, and IL3RA-CSF2RA; JAK mutations and CRLF2 rearrangements (P < .0001); and Hispanic ethnicity (P < .001) had a very poor 4-year relapse-free survival (21.0% ± 9.5%; P < .001). These studies reveal striking clinical and genetic heterogeneity in high-risk ALL and point to novel genes that may serve as new targets for diagnosis, risk classification, and therapy.


2007 ◽  
Vol 13 (23) ◽  
pp. 7073-7079 ◽  
Author(s):  
Jeffrey Haessler ◽  
John D. Shaughnessy ◽  
Fenghuang Zhan ◽  
John Crowley ◽  
Joshua Epstein ◽  
...  

2020 ◽  
Vol 4 (3) ◽  
pp. 221
Author(s):  
Graham H Litchman ◽  
Giselle Prado ◽  
Rebeca W Teplitz ◽  
Darrell Rigel

To decrease morbidity and mortality from melanoma, it is imperative to identify patients who are at high risk for developing widespread disease. Gene expression profiling (GEP) technology may impact melanoma management as physicians are better equipped to measure prognosis. Many different GEP signatures have been investigated. We searched Pubmed, Cochrane CENTRAL, and Embase for studies on GEP in primary melanoma prognosis and assessed GEP signatures for prognostic and analytic validity and clinical impact. The relationship between GEP and survival was measured using hazard ratios (HR) and odds ratios (OR). We found twenty-nine articles comprising 9 gene signatures meeting inclusion criteria and conducted a meta-analysis on 6 studies on a 31-gene signature. High-risk GEP status was associated with poorer recurrence-free survival (HR=7.22; 95% CI, 4.75-10.98), distant metastasis-free survival (HR=6.62; 95% CI, 4.91-8.91), and overall survival (HR=7.06; 95% CI, 4.44-11.22); as well as sentinel lymph node biopsy positivity (OR=2.99; 95% CI, 2.15-4.15). With recent improvements in treating advanced melanoma, accurately assessing prognosis is important. This study has clinical implications for melanoma patients who may benefit from prognostic testing. These results may be useful to clinicians when ordering GEP testing and help them make better management decisions.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 412-412
Author(s):  
Huining Kang ◽  
Carla S. Wilson ◽  
Richard C. Harvey ◽  
I-Ming Chen ◽  
Maurice H. Murphy ◽  
...  

Abstract Abstract 412 ALL arising in infants is a highly refractory disease. Overall event-free survival (EFS) remains poor and infants with MLL rearrangements (MLL-R) or those <90 days of age are known to have particularly poor outcomes. To identify genes predictive of event-free survival (EFS) that might serve as new diagnostic and therapeutic targets, we completed gene expression profiling (Affymetrix HG_U133Plus2) in 97 infant ALL cases registered to COG Clinical Trial P9407. Of these 97 infants, 78 were most recently uniformly treated on P9407 cohort 3. In the 97 cases, median age at diagnosis was 166 days (range 1–365) and increased age at diagnosis was significantly associated with improved EFS (P = 0.001). 89/97 infants had MLL-R, of which 49 had an AF4 partner gene (MLL-AF4 (AFF1)). Infants <90 days of age (P=.0001) and those with MLL-R (MLL-AF4, MLL-ENL (MLLT1), MLL-Other) had a significantly decreased EFS, while infants with MLL-AF9 (MLLT3) or cases lacking MLL-R had a significantly better EFS (P=0.014). From modeling expression profiles and multivariate analyses, a number of genes were identified that had a significant effect on EFS and were independent of patient age or MLL-R status, including: TACC2 and IRX2 (from modeling the entire cohort of 97 cases); RORA, IGJ, ZEB1, YES1 (cohort 3 modeled alone); and IRX1, IRX2, ST3GAL6, HLA-DQB1, STAB1, NEGR1, IRX5 (MLL-AF4 cases modeled alone). The significant effect of MEIS1 and KCNK12 expression on EFS was lost after consideration of MLL-R status, while the significance of many genes (particularly in the HOXA family) was not independent of patient age in multivariate analyses. Assessment of the expression levels of two genes alone at diagnosis: TACC2 and IRX2 in the entire cohort of 97 cases (P<0.0001; Fig. A), or, NEGRI and IRX2 in the MLL-AF4 cases (P<0.0001; Fig. B), were highly predictive of outcome on current treatment regimens. Distinctive and strikingly different gene expression profiles were also seen in infant ALL cases <90 days of age vs. >90 days of age (in the overall cohort and in the MLL-AF4 cases). Specifically evaluating the impact of patient age treated as a continuous variable revealed a striking transition in expression profiles at 90 days with a differential expression pattern involving many genes encoding histone-related, heat shock family, or immune response regulators (including HLA-DRB4, IL1R2, HSPA1A///1B). These distinctive profiles may reflect different transformed stem/precursor cells or susceptibilities to leukemic transformation at different patient ages, altered marrow microenvironments, or altered immune status; high expression of the heat shock proteins in particular among the youngest infants may reflect a more limited immune surveillance capacity. Given the rarity of infant ALL, this study represents one of the largest uniformly treated groups of infant leukemia to undergo gene expression profiling. In these studies we have identified genes that are highly predictive of outcome at diagnosis, in all infant ALL and in MLL-AF4 cases. Further analysis of these expression profiles, coupled with validation studies in other infant ALL cohorts, may allow for the identification of novel therapeutic targets among the genes discovered herein and ultimately for the development of more effective therapies. Disclosures: Felix: None: Patent not licensed.


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