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The presence of CBFA2T3-GLIS2 fusion gene has been identified in childhood Acute Myeloid Leukemia (AML). In view of the genomic studies indicating a distinct gene expression profile, we evaluated the role of immunophenotyping in characterizing a rare subtype of AML-CBFA2T3-GLIS2 rearranged. Immunophenotypic data were obtained by studying a cohort of 20 pediatric CBFA2T3-GLIS2-AML and 77 AML patients not carrying the fusion transcript. Enrolled cases were included in the Associazione Italiana di Ematologia Oncologia Pediatrica (AIEOP) AML trials and immunophenotypes were compared using different statistical approaches. By multiple computational procedures, we identified two main core antigens responsible for the identification of the CBFA2T3-GLIS2-AML. CD56 showed the highest performance in single marker evaluation (AUC = 0.89) and granted the most accurate prediction when used in combination with HLA-DR (AUC = 0.97) displaying a 93% sensitivity and 99% specificity. We also observed a weak-to-negative CD45 expression, being exceptional in AML. We here provide evidence that the combination of HLA-DR negativity and intense bright CD56 expression detects a rare and aggressive pediatric AML genetic lesion improving the diagnosis performance.

CD19-directed treatment in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) frequently leads to the downmodulation of targeted antigens. As multicolour flow cytometry (MFC) application for minimal/measurable residual disease (MRD) assessment in BCP-ALL is based on B-cell compartment study, CD19 loss could hamper MFC-MRD monitoring after blinatumomab or chimeric antigen receptor T-cell (CAR-T) therapy. The use of other antigens (CD22, CD10, CD79a, etc.) as B-lineage gating markers allows the identification of CD19-negative leukaemia, but it could also lead to misidentification of normal very-early CD19-negative BCPs as tumour blasts. In the current study, we summarized the results of the investigation of CD19-negative normal BCPs in 106 children with BCP-ALL who underwent CD19 targeting (blinatumomab, n = 64; CAR-T, n = 25; or both, n = 17). It was found that normal CD19-negative BCPs could be found in bone marrow after CD19-directed treatment more frequently than in healthy donors and children with BCP-ALL during chemotherapy or after stem cell transplantation. Analysis of the antigen expression profile revealed that normal CD19-negative BCPs could be mixed up with residual leukaemic blasts, even in bioinformatic analyses of MFC data. The results of our study should help to investigate MFC-MRD more accurately in patients who have undergone CD19-targeted therapy, even in cases with normal CD19-negative BCP expansion.

Current treatments have reduced to less than 10% the incidence of central nervous system (CNS) relapses of pediatric acute lymphoblastic leukemia (ALL). Nevertheless, CNS relapses still account for...

Purpose Juvenile myelomonocytic leukemia (JMML) is a rare early childhood myelodysplastic/myeloproliferative disorder characterized by an aggressive clinical course. Age and hemoglobin F percentage at diagnosis have been reported to predict both survival and outcome after hematopoietic stem cell transplantation (HSCT). However, no genetic markers with prognostic relevance have been identified so far. We applied gene expression–based classification to JMML samples in order to identify prognostic categories related to clinical outcome. Patients and Methods Samples of 44 patients with JMML were available for microarray gene expression analysis. A diagnostic classification (DC) model developed for leukemia and myelodysplastic syndrome classification was used to classify the specimens and identify prognostically relevant categories. Statistical analysis was performed to determine the prognostic value of the classification and the genes identifying prognostic categories were further analyzed through R software. Results The samples could be divided into two major groups: 20 specimens were classified as acute myeloid leukemia (AML) –like and 20 samples as nonAML-like. Four patients could not be assigned to a unique class. The 10-year probability of survival after diagnosis of AML-like and nonAML-like patients was significantly different (7% v 74%; P = .0005). Similarly, the 10-year event-free survival after HSCT was 6% for AML-like and 63% for nonAML-like patients (P = .0010). Conclusion Gene expression–based classification identifies two groups of patients with JMML with distinct prognosis outperforming all known clinical parameters in terms of prognostic relevance. Gene expression–based classification could thus be prospectively used to guide clinical/therapeutic decisions.

Detection of Philadelphia chromosome t(9;22) (Ph) in children with precursor-B-ALL (pB-ALL) is an adverse prognostic factor, thus leading to a high-risk protocol for treatment. RT-PCR is the gold-standard for the detection of this abnormality. Specific gene and protein expression signatures have recently been identified for genetic subclasses in childhood and adult ALL using gene profiling and flow cytometric analyses, respectively. Our aim is the characterization of Ph+ pB-ALL for a fast and cheap screening approach in routine immunophenotyping applied at diagnosis. Forty-one children with Ph+ and 99 Ph- newly diagnosed pB-ALL (AIEOP cohort) were analyzed. The expression level of 16 marker proteins was monitored by five color flow cytometry (FC) and quantified in terms of Geometric Mean Fluorescence (GMF). Computational analyses were applied to the patient cohort: we identified a Cluster A, including the majority of Ph+ patients (35/41), associated with upregulation of CD52, TdT, CD45, CD34, HLA-DR, CD33, and downregulation of CD38, CD24, CD58, CD22, CD19; a Cluster B+C gathers most of the Ph- patients (86/99) showing the opposite tendency for listed markers. The immunophenotypic method identifies Ph+ cases with a comprehensive accuracy of 86% providing a rapid and effectual screening method for the identification of Ph+ pB-ALL.

Pediatric acute lymphoblastic leukemia (ALL) comprises genetically distinct subtypes. However, 25% of cases still lack defined genetic hallmarks. To identify genomic aberrancies in childhood ALL patients nonclassifiable by conventional methods, we performed a single nucleotide polymorphisms (SNP) array-based genomic analysis of leukemic cells from 29 cases. The vast majority of cases analyzed (19/24, 79%) showed genomic abnormalities; at least one of them affected either genes involved in cell cycle regulation or in B-cell development. The most relevant abnormalities were CDKN2A/9p21 deletions (7/24, 29%), ETV6 (TEL)/12p13 deletions (3/24, 12%), and intrachromosomal amplifications of chromosome 21 (iAMP21) (3/24, 12%). To identify variation in expression of genes directly or indirectly affected by recurrent genomic alterations, we integrated genomic and gene expression data generated by microarray analyses of the same samples. SMAD1 emerged as a down-regulated gene in CDKN2A homozygous deleted cases compared with nondeleted. The JAG1 gene, encoding the Jagged 1 ligand of the Notch receptor, was among a list of differentially expressed (up-regulated) genes in ETV6-deleted cases. Our findings demonstrate that integration of genomic analysis and gene expression profiling can identify genetic lesions undetected by routine methods and potential novel pathways involved in B-progenitor ALL pathogenesis. © 2008 Wiley-Liss, Inc.

// Marco Agostini 1, 2, 3 , Klaus-Peter Janssen 4 , ll-Jin Kim 5 , Edoardo D’Angelo 1, 2 , Silvia Pizzini 6 , Andrea Zangrando 2, 7 , Carlo Zanon 8 , Chiara Pastrello 9 , Isacco Maretto 1 , Maura Digito 1 , Chiara Bedin 1, 3 , Igor Jurisica 9 , Flavio Rizzolio 10, 11 , Antonio Giordano 11 , Stefania Bortoluzzi 12 , Donato Nitti 1, * , Salvatore Pucciarelli 1, * 1 Department of Surgical, Oncological and Gastroenterological Sciences, Section of Surgery, University of Padova, Padua, Italy 2 Istituto di Ricerca Pediatrica-Citta della Speranza, Padua, Italy 3 The Methodist Hospital Research Institute, Houston, USA 4 Department of Surgery, UCSF, San Francisco, CA, USA 5 Department of Surgery, UCSF, San Francisco, CA 94143, California, CA 6 Department of Biology, University of Padua, Padua, Italy 7 Department of Woman and Child Health, University of Padua, Padua, Italy 8 Neuroblastoma Laboratory, Istituto di Ricerca Pediatrica-Citta della Speranza, Padua, Italy 9 Ontario Cancer Institute, the Campbell Family Institute for Cancer Research, and Techna Institute, University Health Network, Toronto, ON, Canada 10 Department of Translational Research, National Cancer Institute – CRO-IRCSS, Aviano, Italy 11 Sbarro Institute for Cancer Research and Molecular Medicine, Center for Biotechnology, College of Science and Technology, Temple University, Philadelphia, PA, USA 12 Department of Molecular Medicine, University of Padua, Padua, Italy * These authors have contributed equally to this work Correspondence to: Marco Agostini, e-mail: m.agostini@unipd.it Keywords: rectal cancer, integrated approach, biological network, prognostic, predictive Received: April 28, 2015 Accepted: August 20, 2015 Published: September 02, 2015 ABSTRACT Introduction: Colorectal cancer is the third most common cancer in the world, a small fraction of which is represented by locally advanced rectal cancer (LARC). If not medically contraindicated, preoperative chemoradiotherapy, represent the standard of care for LARC patients. Unfortunately, patients shows a wide range of response rates in which approximately 20% has a complete pathological response, whereas in 20 to 40% the response is poor or absent. Results: The following specific gene signature, able to discriminate responders’ patients from non-responders, were founded: AKR1C3, CXCL11, CXCL10, IDO1, CXCL9, MMP12 and HLA-DRA. These genes are mainly involved in immune system pathways and interact with drugs traditionally used in the adjuvant treatment of rectal cancer. Discussion: The present study suggests that new ideas for therapy could be found not only limited to studying genes differentially expressed between the two groups of patients but deepening the mechanisms, associated to response, in which they are involved. Methods: Gene expression studies performed by: Agostini et al ., Rimkus et al . and Kim et al . have been merged through a meta-analysis of the raw data. Gene expression data-sets have been processed using A-MADMAN. Common differentially expressed gene (DEG) were identified through SAM analysis. To further characterize the identified DEG we deeply investigated its biological role using an integrative computational biology approach.

Preoperative chemoradiotherapy is widely used to improve local control of disease, sphincter preservation and to improve survival in patients with locally advanced rectal cancer. Patients enrolled in the present study underwent preoperative chemoradiotherapy, followed by surgical excision. Response to chemoradiotherapy was evaluated according to Mandard’s Tumor Regression Grade (TRG). TRG 3, 4 and 5 were considered as partial or no response while TRG 1 and 2 as complete response. From pretherapeutic biopsies of 84 locally advanced rectal carcinomas available for the analysis, only 42 of them showed 70% cancer cellularity at least. By determining gene expression profiles, responders and non-responders showed significantly different expression levels for 19 genes (P < 0.001). We fitted a logistic model selected with a stepwise procedure optimizing the Akaike Information Criterion (AIC) and then validated by means of leave one out cross validation (LOOCV, accuracy D 95%). Four genes were retained in the achieved model: ZNF160, XRCC3, HFM1 and ASXL2. Real time PCR confirmed that XRCC3 is overexpressed in responders group and HFM1 and ASXL2 showed a positive trend. In vitro test on colon cancer resistant/susceptible to chemoradioterapy cells, finally prove that XRCC3 deregulation is extensively involved in the chemoresistance mechanisms. Protein-protein interactions (PPI) analysis involving the predictive classifier revealed a network of 45 interacting nodes (proteins) with TRAF6 gene playing a keystone role in the network. The present study confirmed the possibility that gene expression profiling combined with integrative computational biology is useful to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cancer.

SummaryWe investigated the engraftment properties and impact on patient outcome of 50 pediatric acute lymphoblastic leukemia (ALL) samples transplanted into NOD/SCID mice. Time to leukemia (TTL) was determined for each patient sample engrafted as weeks from transplant to overt leukemia. Short TTL was strongly associated with high risk for early relapse, identifying an independent prognostic factor. This high-risk phenotype is reflected by a gene signature that upon validation in an independent patient cohort (n = 197) identified a high-risk cluster of patients with early relapse. Furthermore, the signature points to independent pathways, including mTOR, involved in cell growth and apoptosis. The pathways identified can directly be targeted, thereby offering additional treatment approaches for these high-risk patients.

MLL partner genes drive distinct gene expression profiles and genomic alterations in pediatric acute myeloid leukemia: an AIEOP study

Background The presence of MLL rearrangements in acute leukemia results in a complex number of biological modifications that still remain largely unexplained. Armstrong et al. proposed MLL rearrangement positive ALL as a distinct subgroup, separated from acute lymphoblastic (ALL) and myeloblastic leukemia (AML), with a specific gene expression profile. Here we show that MLL, from both ALL and AML origin, share a signature identified by a small set of genes suggesting a common genetic disregulation that could be at the basis of mixed lineage leukemia in both phenotypes. Methods Using Affymetrix® HG-U133 Plus 2.0 platform, gene expression data from 140 (training set) + 78 (test set) ALL and AML patients with (24+13) and without (116+65) MLL rearrangements have been investigated performing class comparison (SAM) and class prediction (PAM) analyses. Results We identified a MLL translocation-specific (379 probes) signature and a phenotype-specific (622 probes) signature which have been tested using unsupervised methods. A final subset of 14 genes grants the characterization of acute leukemia patients with and without MLL rearrangements. Conclusion Our study demonstrated that a small subset of genes identifies MLL-specific rearrangements and clearly separates acute leukemia samples according to lineage origin. The subset included well-known genes and newly discovered markers that identified ALL and AML subgroups, with and without MLL rearrangements.

Validation of NG2 antigen in identifying BP-ALL patients with MLL rearrangements using qualitative and quantitative flow cytometry: a prospective study

Acute myeloid leukemia (AML) is a heterogeneous disease group morphologically classified, based on the French–American–British (FAB) classification, into eight main subgroups defined as subtypes M0–M7. Besides morphologic differences, genetic abnormalities have been recognized; cytogenetics and molecular analyses are currently used to identify subgroups of AML with different clinical prognosis. However, in spite of available prognostic factors, accurate prediction of risk for treatment failure or relapse is not completely satisfactory. In order to improve risk assignment and develop new therapeutic strategies, gene expression profiling and proteomic analysis seem to offer important improvements in leukemia classification.

10042 Background: Acute lymphoblastic leukemia (ALL) is the most frequent malignant disease in childhood. Although advances in therapy have led to improved long term survival, relapse remains a major challenge. In a recent study we transplanted pediatric leukemia samples from newly diagnosed BCP-ALL patients into NOD/SCID mice. Time to leukemia (TTL) was analyzed for each patient sample as time from transplant to overt leukemia in the recipients. Patients whose leukemia cells engrafted rapidly showed a clearly inferior relapse free survival in contrast to patient samples with prolonged in vivo growth. Multivariate analysis showed an almost 45- fold increased risk for relapse in patients with short TTL. Methods: Gene expression profiles of ALL samples (N = 14) with short versus long TTL in the xenograft model were analyzed using a human whole genome array (Affymetrix U133 Plus 2.0) correlating gene expression values (relative expression) to the time from transplant to manifestation of leukemia in the NOD/SCID mice (TTL, in weeks) by quantitative traits analysis (QTA). Results: Among 5 genes significantly correlated (Spearman correlation, P < .0001) XIAP-associated factor 1 (XAF1) was found to be up-regulated in patients with long TTL. XAF1 abrogates the inhibitory effect of XIAP on caspase-3 thereby sensitizing for apoptosis. In accordance to this caspase-3 activation was also found to be up-regulated in patients with long TTL. Patient samples exhibiting a short time to overt leukemia in the xenotransplant model associated with poor relapse free survival showed down-regulated XAF1 and impaired caspase-3 activation leading to decreased apoptosis of the leukemia cells. Conclusions: Taken together, we used a novel approach directly correlating gene expression values to time from transplant to overt leukemia (TTL) identifying the apoptosis regulator XAF1 to be associated with poor outcome of patients. Small XIAP-inhibiting molecules can be used to substitute the lacking inhibitory effect of down-regulated XAF1 in these poor responding pediatric ALL patients. No significant financial relationships to disclose.

A number of clinical and biological prognostic factors are currently used for B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) patient risk stratification into (standard risk) SR, (medium risk) MR and (high risk) HR treatment protocols. In spite of careful stratification patients stratified in the same risk class may respond differently to therapy suggestive of a need for additional prognostic markers in BCP-ALL. Here we analyzed gene expression profiles (GEP) of BCP-ALL patients at diagnosis in search for correlations with the diverse responses to therapy among these patients. We specifically searched for expression signatures that predict relapse or the absence of relapse in BCP-ALL. Among BCP-ALL 50% of patients are characterized by recurrent genomic aberrations that are strong indicators for risk stratification of which BCR/ABL and MLL rearrangements have a HR to relapse; TEL/AML1 and hyperdiploid have a standard risk to relapse. BCPALL patients without these aberrations form a heterogeneous risk group in which new prognostic markers will be very important to help stratify these patients. A GEP data set of 86 BCP-ALL patients (47 males; 39 females) without known aberrations was obtained using Affymetrix HG-U133Plus2.0 arrays that were analyzed using Partek and R software packages. Patients were treated according to AIEOP ALL 2000 protocols. Nine out of 86 patients relapsed of which 6 within 24 months; the minimum follow-up time was 24 months. For each probe set the variance among patients was computed and 10 % of the probe sets with the major variance were selected for further analysis. Unsupervised hierarchical cluster analysis separated patients in two groups: one group of 19 patients that were all in complete remission (CR) and a second group of 67 patients in which all patients that eventually relapsed (14%) and CR patients (86%) cluster together. The median follow-up time in the first group of patients was 40 months and the median patient age at diagnosis was 7 years. In the second group median follow-up was 29 months and median patient age at diagnosis was 5.5 years. The separation of patients into two groups was not related to risk group (SR, MR or HR), gender, age or response to induction therapy. A t-test (multiplicity corrections were adopted to control for false positives) was used to find probe sets that were differentially expressed between the two groups. Functional evaluation of the top 200 probe sets of this analysis established 3 major biological categories according to the GO database and revealed differential expression of genes involved in cell adhesion, signal transduction and immune response. We identified a subtype of patients with a gene expression signature that is correlated with excellent prognosis using GEP analysis on BCP-ALL patients that present no recurrent known genomic aberrancies. The signature of excellent prognosis involves about 20% of BCP-ALL patients without common genotypic aberrations and 8% of all BCP-ALL patients and is independent of currently applied prognostic risk factors.

Acute lymphoblastic leukemia (ALL) is the most frequent malignant disease in childhood. Advances in therapy, in particular stratification of patients to appropriate treatment according to risk factors improved long term survival attaining cure rates of up to 80 %. Despite the efforts achieved by the stratification strategies the majority of relapse patients are recruited from the low risk groups emphasizing the need for additional independent risk factors. In a recent study we transplanted primary leukemia samples obtained from pediatric patients with newly diagnosed B cell precursor ALL (BCP-ALL) into NOD/SCID mice. Time to leukemia (TTL) was analyzed for each patient sample transplanted from date of transplant to date of leukemia manifestation in the recipients. We demonstrated that patients whose leukemia cells engrafted rapidly leading to manifestation of the disease within 10 weeks (TTLshort) showed a clearly inferior relapse free survival in contrast to patient samples with prolonged in vivo growth (TTLlong). Interestingly, the same distinct difference in relapse free survival was observed in the low risk groups only. Multivariate analysis showed an almost 45- fold increased risk for relapse in TTLshort patients. In order to further characterize the biological properties of the leukemia cells in the two groups, gene expression profiles of samples with short versus long TTL in the xenograft model were analyzed using a human whole genome array (Affymetrix U133 Plus 2.0). Here, we used quantitative traits analysis (QTA) correlating gene expression values (relative expression) to the time from transplant to manifestation of leukemia in the NOD/SCID mice (TTL, in weeks). 14 different xenograft samples (TTLshort n= 7, mean TTL 8.14 weeks; TTLlong n= 7, mean TTL 19.71 weeks; T-test P = .03) isolated from leukemia bearing mice were investigated. All 14 patients included were stratified in low (standard or intermediate) risk groups. All patients were negative for TEL/AML1- fusion, BCR/ABL- fusion or MLL rearrangement. By QTA we identified 5 genes that were significantly correlated (Spearman correlation, for all 5 genes P < .0001) to time from transplant to leukemia manifestation in the recipient mice (TTL). Analysis of the 14 xenograft samples using the 5 genes identified showed clustering of all but one sample in one group. The 5 genes were than explored for their power to predict relapse in an independent cohort of pediatric ALL patients. For these patients expression profiles were analyzed in leukemia samples obtained at diagnosis. All patients in this cohort were also stratified in low risk groups and negative for the presence of TEL/AML1-, BCR/ABL- or MLL- fusion transcripts. 8 of the 38 patients encountered relapse, 5 at early and 3 at late time points (< or > 24 months after diagnosis). Clustering according to the 5 genes identified by QTA lead to separation of the patients into two groups. Interestingly, all relapsed patients except one clustered in the group associated with the signature characteristic for TTLshort. Most importantly, all 5 patients with early relapse gathered in this cluster. Taken together, we used a novel approach directly correlating gene expression values to the continuous variable time to leukemia (TTL) which might be reflected more accurately by this strategy than comparing two groups. We applied this gene signature characteristic for TTLshort, thereby identifying poor overall survival in a set of independent pediatric ALL patients and found clustering of all early relapse patients in one group. This new independent risk factor might identify patients with high risk for early relapse avoiding xenografting in the mouse model.