High resolution array comparative genomic hybridization identifies copy number alterations in diffuse large B-cell lymphoma that predict response to immuno-chemotherapy

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Disease risk prediction based on genomic sequence and transcriptional profile can improve disease screening and prevention. Despite identifying many disease-associated DNA variants, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. In this study, we designed in vitro experiments to uncover the significance of occupancy and competitive binding between P53 and cMYC on common target genes. Analyzing publicly available ChIP-seq data for P53 and cMYC in embryonic stem cells showed that ~344-366 regions are co-occupied, and on average, two cis-overlapping motifs (CisOMs) per region were identified, suggesting that co-occupancy is evolutionarily conserved. Using U2OS and Raji cells untreated and treated with doxorubicin to increase P53 protein level while potentially reducing cMYC level, ChIP-seq analysis illustrated that around 16 to 922 genomic regions were co-occupied by P53 and cMYC, and substitutions of cMYC signals by P53 were detected post doxorubicin treatment. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data analysis. We utilized a computational motif-matching approach to illustrate that changes in predicted P53 binding affinity in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data, and expression of target genes from GTEx portal. We found significant correlation between change in cMYC-motif binding affinity in CisOMs and altered expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with common diseases.

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Background and methods

Disease risk prediction based on DNA sequence and transcriptional profile can improve disease screening, prevention, and potential therapeutic approaches by revealing contributing genetic factors and altered regulatory networks. Despite identifying many disease-associated DNA variants through genome-wide association studies, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. We previously reported that non-coding variations disrupting cis-overlapping motifs (CisOMs) of opposing transcription factors significantly affect enhancer activity. We designed in vitro experiments to uncover the significance of the co-occupancy and competitive binding and inhibition between P53 and cMYC on common target gene expression.

Results

Analyzing publicly available ChIP-seq data for P53 and cMYC in human embryonic stem cells and mouse embryonic cells showed that ~ 344-366 genomic regions are co-occupied by P53 and cMYC. We identified, on average, two CisOMs per region, suggesting that co-occupancy is evolutionarily conserved in vertebrates. Our data showed that treating U2OS cells with doxorubicin increased P53 protein level while reducing cMYC level. In contrast, no change in protein levels was observed in Raji cells. ChIP-seq analysis illustrated that 16-922 genomic regions were co-occupied by P53 and cMYC before and after treatment, and substitutions of cMYC signals by P53 were detected after doxorubicin treatment in U2OS. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data. We utilized a computational motif-matching approach to determine that changes in predicted P53 binding affinity by DNA variations in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data in U2OS and Raji, and expression of target genes from the GTEx portal.

Conclusions

We found a significant correlation between change in motif-predicted cMYC binding affinity by SNPs in CisOMs and altered gene expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with P53 and cMYC-dependent diseases.

Advances in Lymphoma Molecular Diagnostics

Lymphomas encompass a diverse group of malignant lymphoid neoplasms. Over recent years much scientific effort has been undertaken to identify and understand molecular changes in lymphomas, resulting in a wide range of genetic alterations that have been reported across all types of lymphomas. As many of these changes are now incorporated into the World Health Organization’s defined criteria for the diagnostic evaluation of patients with lymphoid neoplasms, their accurate identification is crucial. Even if many alterations are not routinely evaluated in daily clinical practice, they may still have implications in risk stratification, treatment, prognosis or disease monitoring. Moreover, some alterations can be used for targeted treatment. Therefore, these advances in lymphoma molecular diagnostics in some cases have led to changes in treatment algorithms. Here, we give an overview of and discuss advances in molecular techniques in current clinical practice, as well as highlight some of them in a clinical context.

Revised International Prognostic Index and genetic alterations are associated with early failure to R-CHOP in patients with diffuse large B-cell lymphoma

Relapsed or refractory diffuse large B-cell lymphoma (DLBCL) cases have a poor outcome. Here we analysed clinico-biological features in 373 DLBCL patients homogeneously treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisolone (R-CHOP), in order to identify variables associated with early failure to treatment (EF), defined as primary refractoriness or relapse within 12 months from diagnosis. In addition to clinical features, mutational status of 106 genes was studied by targeted next-generation sequencing in 111 cases, copy number alterations in 87, and gene expression profile (GEP) in 39. Ninety-seven cases (26%) were identified as EF and showed significantly shorter overall survival (OS). Patients with B symptoms, advanced stage, high levels of serum lactate dehydrogenase (LDH) or β2-microglobulin, low lymphocyte/monocyte ratio and higher Revised International Prognostic Index (R-IPI) scores, as well as those with BCL2 rearrangements more frequently showed EF, with R-IPI being the most important in logistic regression. Mutations in NOTCH2, gains in 5p15·33 (TERT), 12q13 (CDK2), 12q14·1 (CDK4) and 12q15 (MDM2) showed predictive importance for EF independently from R-IPI. GEP studies showed that EF cases were significantly enriched in sets related to cell cycle regulation and inflammatory response, while cases in response showed over-representation of gene sets related to extra-cellular matrix and tumour microenvironment.

Hematopoietic neoplasms in Prkar2a-deficient mice

Background

Protein kinase A (PKA) is a holoenzyme that consists of a dimer of regulatory subunits and two inactive catalytic subunits that bind to the regulatory subunit dimer. Four regulatory subunits (RIα, RIβ, RIIα, RIIβ) and four catalytic subunits (Cα, Cβ, Cγ, Prkx) have been described in the human and mouse genomes. Previous studies showed that complete inactivation of the Prkar1a subunit (coding for RIα) in the germline leads to embryonic lethality, while Prkar1a–deficient mice are viable and develop schwannomas, thyroid, and bone neoplasms, and rarely lymphomas and sarcomas. Mice with inactivation of the Prkar2a and Prkar2b genes (coding for RIIα and RIIβ, respectively) are also viable but have not been studied for their susceptibility to any tumors.

Methods

Cohorts of Prkar1a^+/−, Prkar2a^+/−, Prkar2a^−/−, Prkar2b^+/− and wild type (WT) mice have been observed between 5 and 25 months of age for the development of hematologic malignancies. Tissues were studied by immunohistochemistry; tumor-specific markers were also used as indicated. Cell sorting and protein studies were also performed.

Results

Both Prkar2a^−/− and Prkar2a^+/− mice frequently developed hematopoietic neoplasms dominated by histiocytic sarcomas (HS) with rare diffuse large B cell lymphomas (DLBCL). Southern blot analysis confirmed that the tumors diagnosed histologically as DLBCL were clonal B cell neoplasms. Mice with other genotypes did not develop a significant number of similar neoplasms.

Conclusions

Prkar2a deficiency predisposes to hematopoietic malignancies in vivo. RIIα’s likely association with HS and DLBCL was hitherto unrecognized and may lead to better understanding of these rare neoplasms.

High-resolution copy number analysis of paired normal-tumor samples from diffuse large B cell lymphoma

Copy number analysis can be useful for assessing prognosis in diffuse large B cell lymphoma (DLBCL). We analyzed copy number data from tumor samples of 60 patients diagnosed with DLBCL de novo and their matched normal samples. We detected 63 recurrent copy number alterations (CNAs), including 33 gains, 30 losses, and nine recurrent acquired copy number neutral loss of heterozygosity (CNN-LOH). Interestingly, 20 % of cases acquired CNN-LOH of 6p21 locus, which involves the HLA region. In normal cells, there were no CNAs but we observed CNN-LOH involving some key lymphoma regions such as 6p21 and 9p24.1 (5 %) and 17p13.1 (2.5 %) in DLBCL patients. Furthermore, a model with some specific CNA was able to predict the subtype of DLBCL, 1p36.32 and 10q23.31 losses being restricted to germinal center B cell-like (GCB) DLBCL. In contrast, 8p23.3 losses and 11q24.3 gains were strongly associated with the non-GCB subtype. A poor prognosis was associated with biallelic inactivation of TP53 or 18p11.32 losses, while prognosis was better in cases carrying 11q24.3 gains. In summary, CNA abnormalities identify specific DLBCL groups, and we describe CNN-LOH in germline cells from DLBCL patients that are associated with genes that probably play a key role in DLBCL development.

Multiparameter analysis of homogeneously R-CHOP-treated diffuse large B cell lymphomas identifies CD5 and FOXP1 as relevant prognostic biomarkers: report of the prospective SAKK 38/07 study

BACKGROUND

The prognostic role of tumor-related parameters in diffuse large B cell lymphoma (DLBCL) is a matter of controversy.

METHODS

We investigated the prognostic value of phenotypic and genotypic profiles in DLBCL in clinical trial (NCT00544219) patients homogenously treated with six cycles of rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine, prednisone (R-CHOP), followed by two cycles of R (R-CHOP-14). The primary endpoint was event-free survival at 2 years (EFS). Secondary endpoints were progression-free (PFS) and overall survival (OS). Immunohistochemical (bcl2, bcl6, CD5, CD10, CD20, CD95, CD168, cyclin E, FOXP1, GCET, Ki-67, LMO2, MUM1p, pSTAT3) and in situ hybridization analyses (BCL2 break apart probe, C-MYC break apart probe and C-MYC/IGH double-fusion probe, and Epstein-Barr virus probe) were performed and correlated with the endpoints.

RESULTS

One hundred twenty-three patients (median age 58 years) were evaluable. Immunohistochemical assessment succeeded in all cases. Fluorescence in situ hybridization was successful in 82 instances. According to the Tally algorithm, 81 cases (66%) were classified as non-germinal center (GC) DLBCL, while 42 cases (34%) were GC DLBCL. BCL2 gene breaks were observed in 7/82 cases (9%) and C-MYC breaks in 6/82 cases (8%). "Double-hit" cases with BCL2 and C-MYC rearrangements were not observed. Within the median follow-up of 53 months, there were 51 events, including 16 lethal events and 12 relapses. Factors able to predict worse EFS in univariable models were failure to achieve response according to international criteria, failure to achieve positron emission tomography response (p < 0.005), expression of CD5 (p = 0.02), and higher stage (p = 0.021). Factors predicting inferior PFS were failure to achieve response according to international criteria (p < 0.005), higher stage (p = 0.005), higher International Prognostic Index (IPI; p = 0.006), and presence of either C-MYC or BCL2 gene rearrangements (p = 0.033). Factors predicting inferior OS were failure to achieve response according to international criteria and expression of FOXP1 (p < 0.005), cyclin E, CD5, bcl2, CD95, and pSTAT3 (p = 0.005, 0.007, 0.016, and 0.025, respectively). Multivariable analyses revealed that expression of CD5 (p = 0.044) and FOXP1 (p = 0.004) are independent prognostic factors for EFS and OS, respectively.

CONCLUSION

Phenotypic studies with carefully selected biomarkers like CD5 and FOXP1 are able to prognosticate DLBCL course at diagnosis, independent of stage and IPI and independent of response to R-CHOP.

Advances in subunits of PI3K class I in cancer

Phosphatidylinositol 3-kinases (PI3Ks) include members of a unique and conserved family of intracellular lipid kinases that phosphorylate the 3-hydroxyl group of phosphatidylinositols and phosphoinositides. The resultant activation of many intracellular signalling pathways regulates various biological functions such as cell metabolism, survival, growth, proliferation, polarity, and apoptosis. PI3Ks are classified into three types: class I, II, and III. Of them, class I PI3K is most widely studied and plays an important role in the development and progression of tumours. In this review, we describe PI3K family members and their functions, especially the subunits of class I PI3K, their alterations in cancers, as well as PI3K inhibitors and their clinical trial status in cancer-targeted therapy.

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

INTRODUCTION

Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach.

METHODS

Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n=84), gene expression profiling (n=47), matched pre- and post-AI aCGH (n=19 pairs) and Ki67-based AI-response analysis (n=39).

RESULTS

Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1).

CONCLUSIONS

These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response.

An RCOR1 loss–associated gene expression signature identifies a prognostically significant DLBCL subgroup

Integration of genome-wide copy number and whole transcriptome data identifies key mutational events in the pathogenesis of DLBCL. Genomic deletions in RCOR1 are associated with a specific gene expression signature and with unfavorable clinical outcomes in DLBCL patients.

Array-based comparative genomic hybridization analysis reveals chromosomal copy number aberrations associated with clinical outcome in canine diffuse large B-cell lymphoma

Canine Diffuse Large B-cell Lymphoma (cDLBCL) is an aggressive cancer with variable clinical response. Despite recent attempts by gene expression profiling to identify the dog as a potential animal model for human DLBCL, this tumor remains biologically heterogeneous with no prognostic biomarkers to predict prognosis. The aim of this work was to identify copy number aberrations (CNAs) by high-resolution array comparative genomic hybridization (aCGH) in 12 dogs with newly diagnosed DLBCL. In a subset of these dogs, the genetic profiles at the end of therapy and at relapse were also assessed. In primary DLBCLs, 90 different genomic imbalances were counted, consisting of 46 gains and 44 losses. Two gains in chr13 were significantly correlated with clinical stage. In addition, specific regions of gains and losses were significantly associated to duration of remission. In primary DLBCLs, individual variability was found, however 14 recurrent CNAs (>30%) were identified. Losses involving IGK, IGL and IGH were always found, and gains along the length of chr13 and chr31 were often observed (>41%). In these segments, MYC, LDHB, HSF1, KIT and PDGFRα are annotated. At the end of therapy, dogs in remission showed four new CNAs, whereas three new CNAs were observed in dogs at relapse compared with the previous profiles. One ex novo CNA, involving TCR, was present in dogs in remission after therapy, possibly induced by the autologous vaccine. Overall, aCGH identified small CNAs associated with outcome, which, along with future expression studies, may reveal target genes relevant to cDLBCL.

Deregulation of COMMD1 is associated with poor prognosis in diffuse large B-cell lymphoma

Background

Despite improved survival for the patients with diffuse large B-cell lymphoma (DLBCL), the prognosis after relapse is poor. The aim was to identify molecular events that contribute to relapse and treatment resistance in DLBCL.

Methods

We analysed 51 prospectively collected pretreatment tumour samples from clinically high risk patients treated in a Nordic phase II study with dose-dense chemoimmunotherapy and central nervous system prophylaxis with high resolution array comparative genomic hybridization (aCGH) and gene expression microarrays. Major finding was validated at the protein level immunohistochemically in a trial specific tissue microarray series of 70, and in an independent validation series of 146 patients.

Results

We identified 31 genes whose expression changes were strongly associated with copy number aberrations. In addition, gains of chromosomes 2p15 and 18q12.2 were associated with unfavourable survival. The 2p15 aberration harboured COMMD1 gene, whose expression had a significant adverse prognostic impact on survival. Immunohistochemical analysis of COMMD1 expression in two series confirmed the association of COMMD1 expression with poor prognosis.

Conclusion

COMMD1 is a potential novel prognostic factor in DLBCLs. The results highlight the value of integrated comprehensive analysis to identify prognostic markers and genetic driver events not previously implicated in DLBCL.

Trial Registration

ClinicalTrials.gov NCT01502982

Inactivation of the CDKN2A tumor-suppressor gene by deletion or methylation is common at diagnosis in follicular lymphoma and associated with poor clinical outcome

PURPOSE

Follicular lymphoma, the most common indolent lymphoma, is clinically heterogeneous. CDKN2A encodes the tumor suppressors p16(INK4a) and p14(ARF) and frequently suffers deleterious alterations in cancer. We investigated the hypothesis that deletion or hypermethylation of CDKN2A might identify follicular lymphoma cases with distinct clinical or pathologic features potentially amenable to tailored clinical management.

EXPERIMENTAL DESIGN

Deletion of CDKN2A was detected in pretreatment biopsy specimens using a single nucleotide polymorphism-based approach or endpoint PCR, and methylation of CpG elements in CDKN2A was quantified by methylation-specific PCR. Correlations between CDKN2A status and pathologic or clinical characteristics, including overall survival (OS), were investigated in 106 cases using standard statistical methods.

RESULTS

Deletion of CDKN2A was detected in 9 of 111 samples (8%) and methylation was detectable in 22 of 113 (19%). CDKN2A was either deleted or methylated in 29 of 106 cases (27%) and this status was associated with inferior OS especially among patients treated with rituximab (P = 0.004). CDKN2A deletion or methylation was associated with more advanced age (P = 0.012) and normal hemoglobin (P = 0.05) but not with sex, FLIPI score, ECOG stage, LDH, performance status, number of involved nodal sites, B symptoms, histologic grade, the presence of a component of diffuse large B-cell lymphoma, proliferation index, or other pathologic factors.

CONCLUSIONS

Our results show that deletion or methylation of CDKN2A is relatively common in pretreatment follicular lymphoma biopsy specimens and defines a group of cases associated with reduced survival in the rituximab era presumably on the basis of more aggressive disease biology.

Frequent copy number variations of PI3K/AKT pathway and aberrant protein expressions of PI3K subunits are associated with inferior survival in diffuse large B cell lymphoma

BACKGROUND

It has been reported that the PI3K/AKT signaling pathway is activated in diffuse large B-cell lymphoma (DLBCL), PI3K constitutive activation plays a crucial role in PI3K/AKT pathway. However, the copy number variations (CNVs) of PI3K subunits on gene level remain unknown in DLBCL. Therefore, the aim of the study is to investigate the CNV of PI3K subunits and their relationship with clinicopathological features exploring the possible mechanism underlying of PI3K activation in DLBCL.

METHODS

CNV of 12 genes in the PI3K/AKT pathway was detected by NanoString nCounter in 60 de novo DLBCLs and 10 reactive hyperplasia specimens as controls. Meanwhile, immunohistochemistry (IHC) was performed to examine the expression of p110α, p110β, p110γ, p110δ, and pAKT on DLBCL tissue microarrays.

RESULTS

All PI3K and AKT subunits, except for PIK3R1, had various CNVs in the form of copy number amplifications and copy number losses. Their rates were in the range of 8.3-20.0%. Of them PIK3CA and PIK3CB gene CNVs were significantly associated with decreased overall survival (P = 0.029 and P = 0.019, respectively). IHC showed that the frequency of strong positive expression of p110α, p110β, p110γ, and p110δ were 26.7%, 25.0%, 18.3%, and 25.0% respectively, and they were found to be associated with decreased survival (P = 0.022, P = 0.015, P = 0.015, and P = 0.008, respectively). Expression of p110α was not only significantly associated with CNVs of PIK3CA (P = 0.002) but also positively correlated with strong positive expression of pAKT (P = 0.026).

CONCLUSIONS

CNV of PIK3CA is highly associated with aberrant p110α protein expression and subsequent activation of PI3K/AKT pathway. CNVs of PIK3CA and PIK3CB, and aberrant protein expression of p110 isoforms are of great important value for predicting inferior prognosis in DLBCL. Frequent CNVs of PI3K/AKT subunits may play an important role in the tumorigenesis of DLBCL.

MicroRNAs and Recent Insights into Pediatric Ovarian Cancers

Ovarian cancer is the most common pediatric gynecologic malignancy. When diagnosed in children, ovarian cancers present unique challenges that differ dramatically from those faced by adults. Here, we review the spectrum of ovarian cancers found in young women and girls and discuss the biology of these diseases. A number of advances have recently shed significant new understanding on the potential causes of ovarian cancer in this unique population. Particular emphasis is placed on understanding how altered expression of non-coding RNA transcripts known as microRNAs play a key role in the etiology of ovarian germ cell and sex cord-stromal tumors. Emerging transgenic models for these diseases are also reviewed. Lastly, future challenges and opportunities for understanding pediatric ovarian cancers, delineating clinically useful biomarkers, and developing targeted therapies are discussed.

Fine map of the Gct1 spontaneous ovarian granulosa cell tumor locus

The spontaneous development of juvenile-onset, ovarian granulosa cell (GC) tumors in the SWR/Bm (SWR) inbred mouse strain is a model for juvenile-type GC tumors that appear in infants and young girls. GC tumor susceptibility is supported by multiple Granulosa cell tumor (Gct) loci, but the Gct1 locus on Chr 4 derived from SWR strain background is fundamental for GC tumor development and uniquely responsive to the androgenic precursor dehydroepiandrosterone (DHEA). To resolve the location of Gct1 independently from other susceptibility loci, Gct1 was isolated in a congenic strain that replaces the distal segment of Chr 4 in SWR mice with a 47 × 10(6)-bp genomic segment from the Castaneus/Ei (CAST) strain. SWR females homozygous for the CAST donor segment were confirmed to be resistant to DHEA- and testosterone-induced GC tumorigenesis, indicating successful exchange of CAST alleles (Gct1 ( CA )) for SWR alleles (Gct1 ( SW )) at this tumor susceptibility locus. A series of nested, overlapping, congenic sublines was created to fine-map Gct1 based on GC tumor susceptibility under the influence of pubertal DHEA treatment. Twelve informative lines have resolved the Gct1 locus to a 1.31 × 10(6)-bp interval on mouse Chr 4, a region orthologous to human Chr 1p36.22.

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large B-cell lymphoma: a review of the literature

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes.

Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL.