Erythroleukemia: Classification.

Acute erythroid leukemia (AEL) is a rare (2%-5%) form of acute myeloid leukemia (AML). Molecular alterations found in AEL resemble those of other AMLs. We report a classification of AELs in three major classes, with different prognosis and some specific features such as a tendency to mutual exclusion of mutations in epigenetic regulators and signaling genes.

Gene mutations differently impact the prognosis of the myelodysplastic and myeloproliferative classes of chronic myelomonocytic leukemia.

Initially classified in the myelodysplastic syndromes (MDSs), chronic myelomonocytic leukemia (CMML) is currently considered as a MDS/myeloproliferative neoplasm. Two classes-myelodysplastic and myeloproliferative-have been distinguished upon the level of the white blood cell count (threshold 13 G/L). We analyzed mutations in 19 genes reported in CMML to determine if and how these mutations impacted the respective prognosis of the two classes. We defined four major mutated pathways (DNA methylation, ASXL1, splicing, and signaling) and determined their prognostic impact. The number of mutated pathways impacted overall survival in the myelodysplastic class but not in the myeloproliferative class. The myeloproliferative class had a worse prognosis than the myelodysplastic class and was impacted by RUNX1 mutations only. Our results argue for a reclassification of CMML based on the myelodysplastic/myeloproliferative status.

Molecular similarity between myelodysplastic form of chronic myelomonocytic leukemia and refractory anemia with ring sideroblasts.

Chronic myelomonocytic leukemia is similar to but a separate entity from both myeloproliferative neoplasms and myelodysplastic syndromes, and shows either myeloproliferative or myelodysplastic features. We ask whether this distinction may have a molecular basis. We established the gene expression profiles of 39 samples of chronic myelomonocytic leukemia (including 12 CD34-positive) and 32 CD34-positive samples of myelodysplastic syndromes by using Affymetrix microarrays, and studied the status of 18 genes by Sanger sequencing and array-comparative genomic hybridization in 53 samples. Analysis of 12 mRNAS from chronic myelomonocytic leukemia established a gene expression signature of 122 probe sets differentially expressed between proliferative and dysplastic cases of chronic myelomonocytic leukemia. As compared to proliferative cases, dysplastic cases over-expressed genes involved in red blood cell biology. When applied to 32 myelodysplastic syndromes, this gene expression signature was able to discriminate refractory anemias with ring sideroblasts from refractory anemias with excess of blasts. By comparing mRNAS from these two forms of myelodysplastic syndromes we derived a second gene expression signature. This signature separated the myelodysplastic and myeloproliferative forms of chronic myelomonocytic leukemias. These results were validated using two independent gene expression data sets. We found that myelodysplastic chronic myelomonocytic leukemias are characterized by mutations in transcription/epigenetic regulators (ASXL1, RUNX1, TET2) and splicing genes (SRSF2) and the absence of mutations in signaling genes. Myelodysplastic chronic myelomonocytic leukemias and refractory anemias with ring sideroblasts share a common expression program suggesting they are part of a continuum, which is not totally explained by their similar but not, however, identical mutation spectrum.

Mevalonate metabolism regulates Basal breast cancer stem cells and is a potential therapeutic target.

There is increasing evidence that breast tumors are organized in a hierarchy, with a subpopulation of tumorigenic cancer cells, the cancer stem cells (CSCs), which sustain tumor growth. The characterization of protein networks that govern CSC behavior is paramount to design new therapeutic strategies targeting this subpopulation of cells. We have sought to identify specific molecular pathways of CSCs isolated from 13 different breast cancer cell lines of luminal or basal/mesenchymal subtypes. We compared the gene expression profiling of cancer cells grown in adherent conditions to those of matched tumorsphere cultures. No specific pathway was identified to be commonly regulated in luminal tumorspheres, resulting from a minor CSC enrichment in tumorsphere passages from luminal cell lines. However, in basal/mesenchymal tumorspheres, the enzymes of the mevalonate metabolic pathway were overexpressed compared to those in cognate adherent cells. Inhibition of this pathway with hydroxy-3-methylglutaryl CoA reductase blockers resulted in a reduction of breast CSC independent of inhibition of cholesterol biosynthesis and of protein farnesylation. Further modulation of this metabolic pathway demonstrated that protein geranylgeranylation (GG) is critical to breast CSC maintenance. A small molecule inhibitor of the geranylgeranyl transferase I (GGTI) enzyme reduced the breast CSC subpopulation both in vitro and in primary breast cancer xenografts. We found that the GGTI effect on the CSC subpopulation is mediated by inactivation of Ras homolog family member A (RHOA) and increased accumulation of P27(kip1) in the nucleus. The identification of protein GG as a major contributor to CSC maintenance opens promising perspectives for CSC targeted therapy in basal breast cancer.

Mutation analysis of ASXL1, CBL, DNMT3A, IDH1, IDH2, JAK2, MPL, NF1, SF3B1, SUZ12, and TET2 in myeloproliferative neoplasms.

Since the discovery of the JAK2V617F tyrosine kinase-activating mutation several genes have been found mutated in nonchronic myeloid leukemia (CML) myeloproliferative neoplasms (MPNs), which mainly comprise three subtypes of "classic" MPNs; polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF). We searched for mutations in ASXL1, CBL, DNMT3A, IDH1, IDH2, JAK2, MPL, NF1, SF3B1, SUZ12, and TET2 genes in 149 non-CML MPNs, including 127 "classic" MPNs cases. JAK2 was mutated in 100% PV, 66% ET and 68% MF. We found a high incidence of ASXL1 mutation in MF patients (20%) and a low incidence in PV (7%) and ET (4%) patients. Mutations in the other genes were rare (CBL, DNMT3A, IDH2, MPL, SF3B1, SUZ12, NF1) or absent (IDH1).

Gene expression profiling and its utility in prediction of local relapse after breast-conserving therapy in early breast cancer.

BACKGROUND: Local relapse (LR) after breast-conserving therapy (BCT) is not accurately predicted by histological/clinical factors. Gene expression profiling was used here to discover LR-associated transcriptional alterations. MATERIALS AND METHODS: Gene expression profiling was carried out of 81 early breast carcinomas obtained from 30 patients who developed a LR (LR(+)) after BCT and 51 who did not (LR(-)). LR(+) and LR(-) samples were matched for known LR risk features. RESULTS: LR was not associated with a given molecular subtype. Supervised analysis identified a 212-gene signature, which was not validated in independent tumors. No gene set or biological pathway was differentially expressed between LR(+) and LR(-) groups. Twelve published prognostic expression signatures failed to distinguish these groups of carcinomas. The gene expression profiles of 9 cases of LR and the corresponding primary tumors were very similar despite the delivery of radiotherapy. CONCLUSION: In this series, the onset of LR was not predicted by gene expression alterations.

Kinome expression profiling and prognosis of basal breast cancers.

BACKGROUND: Basal breast cancers (BCs) represent ~15% of BCs. Although overall poor, prognosis is heterogeneous. Identification of good- versus poor-prognosis patients is difficult or impossible using the standard histoclinical features and the recently defined prognostic gene expression signatures (GES). Kinases are often activated or overexpressed in cancers, and constitute targets for successful therapies. We sought to define a prognostic model of basal BCs based on kinome expression profiling. METHODS: DNA microarray-based gene expression and histoclinical data of 2515 early BCs from thirteen datasets were collected. We searched for a kinome-based GES associated with disease-free survival (DFS) in basal BCs of the learning set using a metagene-based approach. The signature was then tested in basal tumors of the independent validation set. RESULTS: A total of 591 samples were basal. We identified a 28-kinase metagene associated with DFS in the learning set (N = 73). This metagene was associated with immune response and particularly cytotoxic T-cell response. On multivariate analysis, a metagene-based predictor outperformed the classical prognostic factors, both in the learning and the validation (N = 518) sets, independently of the lymphocyte infiltrate. In the validation set, patients whose tumors overexpressed the metagene had a 78% 5-year DFS versus 54% for other patients (p = 1.62E-4, log-rank test). CONCLUSIONS: Based on kinome expression, we identified a predictor that separated basal BCs into two subgroups of different prognosis. Tumors associated with higher activation of cytotoxic tumor-infiltrative lymphocytes harbored a better prognosis. Such classification should help tailor the treatment and develop new therapies based on immune response manipulation.

A gene expression signature identifies two prognostic subgroups of basal breast cancer.

Prognosis of basal breast cancers is poor but heterogeneous. Medullary breast cancers (MBC) display a basal profile, but a favorable prognosis. We hypothesized that a previously published 368-gene expression signature associated with MBC might serve to define a prognostic classifier in basal cancers. We collected public gene expression and histoclinical data of 2145 invasive early breast adenocarcinomas. We developed a Support Vector Machine (SVM) classifier based on this 368-gene list in a learning set, and tested its predictive performances in an independent validation set. Then, we assessed its prognostic value and that of six prognostic signatures for disease-free survival (DFS) in the remaining 2034 samples. The SVM model accurately classified all MBC samples in the learning and validation sets. A total of 466 cases were basal across other sets. The SVM classifier separated them into two subgroups, subgroup 1 (resembling MBC) and subgroup 2 (not resembling MBC). Subgroup 1 exhibited 71% 5-year DFS, whereas subgroup 2 exhibited 50% (P = 9.93E-05). The classifier outperformed the classical prognostic variables in multivariate analysis, conferring lesser risk for relapse in subgroup 1 (HR = 0.52, P = 3.9E-04). This prognostic value was specific to the basal subtype, in which none of the other prognostic signatures was informative. Ontology analysis revealed effective immune response (IR), enhanced tumor cell apoptosis, elevated levels of metastasis-inhibiting factors and low levels of metastasis-promoting factors in the good-prognosis subgroup, and a more developed cell migration system in the poor-prognosis subgroup. In conclusion, based on this 368-gene SVM model derived from an MBC signature, basal breast cancers were classified in two prognostic subgroups, suggesting that MBC and basal breast cancers share similar molecular alterations associated with aggressiveness. This signature could help define the prognosis, adapt the systemic treatment, and identify new therapeutic targets.

Loss, mutation and deregulation of L3MBTL4 in breast cancers.

BACKGROUND: Many alterations are involved in mammary oncogenesis, including amplifications of oncogenes and losses of tumor suppressor genes (TSG). Losses may affect almost all chromosome arms and many TSGs remain to be identified. RESULTS: We studied 307 primary breast tumors and 47 breast cancer cell lines by high resolution array comparative genomic hybridization (aCGH). We identified a region on 18p11.31 lost in about 20% of the tumors and 40% of the cell lines. The minimal common region of loss (Chr18:6,366,938-6,375,929 bp) targeted the L3MBTL4 gene. This gene was also targeted by breakage in one tumor and in two cell lines. We studied the exon sequence of L3MBTL4 in 180 primary tumor samples and 47 cell lines and found six missense and one nonsense heterozygous mutations. Compared with normal breast tissue, L3MBTL4 mRNA expression was downregulated in 73% of the tumors notably in luminal, ERBB2 and normal-like subtypes. Losses of the 18p11 region were associated with low L3MBTL4 expression level. Integrated analysis combining genome and gene expression profiles of the same tumors pointed to 14 other potential 18p TSG candidates. Downregulated expression of ZFP161, PPP4R1 and YES1 was correlated with luminal B molecular subtype. Low ZFP161 gene expression was associated with adverse clinical outcome. CONCLUSION: We have identified L3MBTL4 as a potential TSG of chromosome arm 18p. The gene is targeted by deletion, breakage and mutations and its mRNA is downregulated in breast tumors. Additional 18p TSG candidates might explain the aggressive phenotype associated with the loss of 18p in breast tumors.

Retinoid signaling regulates breast cancer stem cell differentiation.

The cancer stem cell (CSC) hypothesis implicates the development of new therapeutic approaches to target the CSC population. Characterization of the pathways that regulate CSCs activity will facilitate the development of targeted therapies. We recently reported that the enzymatic activity of ALDH1, as measured by the ALDELFUOR assay, can be utilized to isolate normal and malignant breast stem cells in both primary tumors and cell lines. In this study, utilizing a tumorsphere assay, we have demonstrated the role of retinoid signaling in the regulation of breast CSCs self-renewal and differentiation. Utilizing the gene set enrichment analysis (GSEA) algorithm we identified gene sets and pathways associated with retinoid signaling. These pathways regulate breast CSCs biology and their inhibition may provide novel therapeutic approaches to target breast CSCs.

Mutations of polycomb-associated gene ASXL1 in myelodysplastic syndromes and chronic myelomonocytic leukaemia.

The myelodysplastic syndromes (MDSs) are a heterogeneous group of clonal haematological diseases characterized by ineffective haematopoiesis and predisposition to acute myeloid leukaemia (AML). The pathophysiology of MDSs remains unclear. A definition of the molecular biology of MDSs may lead to a better classification, new prognosis indicators and new treatments. We studied a series of 40 MDS/AML samples by high-density array-comparative genome hybridization (aCGH). The genome of MDSs displayed a few alterations that can point to candidate genes, which potentially regulate histone modifications and WNT pathways (e.g. ASXL1, ASXL2, UTX, CXXC4, CXXC5, TET2, TET3). To validate some of these candidates we studied the sequence of ASXL1. We found mutations in the ASXL1 gene in four out of 35 MDS patients (11%). To extend these results we searched for mutations of ASXL1 in a series of chronic myelomonocytic leukaemias, a disease classified as MDS/Myeloproliferative disorder, and found mutations in 17 out of 39 patients (43%). These results show that ASXL1 might play the role of a tumour suppressor in myeloid malignancies.

Gene expression profiling and prediction of clinical outcome in ovarian cancer.

Epithelial ovarian cancer is the most lethal gynaecological cancer. Despite debulking surgery and platinum/taxane-based chemotherapy, the prognosis remains poor with approximately 25% 5-year survival. Current histo-clinical prognostic factors are insufficient to capture the complex cascade of events that drive the heterogeneous clinical behaviour of the disease. There is a crucial need to identify new prognostic subclasses of disease as well as new therapeutic targets. Today, DNA microarrays allow the simultaneous and quantitative analysis of the mRNA expression levels of thousands of genes in a tumour sample. They have been applied to ovarian cancer research for predicting initial surgical resectability, survival and response to first-line chemotherapy. The first results are promising. In this review, we describe recent applications of DNA microarrays in ovarian cancer research and discuss some issues to address in the near future to allow the technology to reach its full potential in clinical practice.

Breast cancer cell lines contain functional cancer stem cells with metastatic capacity and a distinct molecular signature.

Tumors may be initiated and maintained by a cellular subcomponent that displays stem cell properties. We have used the expression of aldehyde dehydrogenase as assessed by the ALDEFLUOR assay to isolate and characterize cancer stem cell (CSC) populations in 33 cell lines derived from normal and malignant mammary tissue. Twenty-three of the 33 cell lines contained an ALDEFLUOR-positive population that displayed stem cell properties in vitro and in NOD/SCID xenografts. Gene expression profiling identified a 413-gene CSC profile that included genes known to play a role in stem cell function, as well as genes such as CXCR1/IL-8RA not previously known to play such a role. Recombinant interleukin-8 (IL-8) increased mammosphere formation and the ALDEFLUOR-positive population in breast cancer cell lines. Finally, we show that ALDEFLUOR-positive cells are responsible for mediating metastasis. These studies confirm the hierarchical organization of immortalized cell lines, establish techniques that can facilitate the characterization of regulatory pathways of CSCs, and identify potential stem cell markers and therapeutic targets.

How different are luminal A and basal breast cancers?

Heterogeneity of breast cancer makes its evolution difficult to predict, and its treatment far from being optimal. At least 5 main molecular subtypes exist. Two major subtypes are luminal A and basal subtypes, which have opposite features, notably survival. To characterize these 2 subtypes better, with the hope of better understanding their different biology and clinical outcome, we have profiled a series of 138 tumours (80 luminal A and 58 basal) using Affymetrix whole-genome DNA microarrays. We have identified 5,621 probe sets as differentially expressed between the 2 subtypes in our series. These differences were validated in 6 independent public series (more than 600 tumours) profiled using different DNA microarrays platforms. Analysis of functions and pathways related to these probe sets, and the extent of the observed differences, confirmed that the 2 subtypes represent very distinct entities. Genes associated with proliferation, cell cycle, cell motility, angiogenesis, and NFkB signalling were overexpressed in basal tumours. Genes involved in fatty acid metabolism, TGFB signalling, and oestrogen receptor (ER) signalling were overexpressed in luminal A samples. Half of the genes overexpressed in luminal tumours contained ER-binding sites. The number of differentially expressed genes was as high as the set of genes discriminating 2 cancers of different anatomical origin (breast and colon) or discriminating acute myeloid and lymphoid leukaemia. We provide a comprehensive list of genes/pathways that define potential diagnostic, prognostic and therapeutic targets for these 2 subtypes, which should be treated differently given the profound differences observed at the molecular level.

[Prognostic classification of breast cancer and gene expression profiling]. / Classification pronostiquedu cancer du sein et profils d'expression génique sur puces à ADN.

Clinical and pathological heterogeneity of breast cancer, partly responsible of therapeutic failures, reflects complex and combinatory molecular alterations until now poorly documented by classical investigation tools. Thorough molecular typing is crucial. The advent of DNA microarray-based gene expression profiling allowed consistent progresses in this direction. A novel molecular taxonomy of breast cancer has been defined, signatures that predict clinical outcome or therapeutic response have been identified, some of them being tested in ongoing prospective clinical trials. In this review, we present the main results and their potential clinical applications. We also discuss their current limits and future hopes in the therapeutic management of patients.

How basal are triple-negative breast cancers?

The basal molecular subtype of breast cancer (BC) is defined by the mRNA expression pattern of an intrinsic approximately 500-gene set. It is the most homogeneous subtype in transcriptional terms, and one of the most aggressive in prognostic terms. Clinical trials testing new systemic therapeutic strategies have been launched in basal BCs. Although no proof of evidence has yet been reported, basal tumors are currently assimilated to and selected as triple-negative (TN) BCs in these trials because of their frequent immunohistochemical (IHC) negativity for hormone and ERBB2 receptors. Here, we have assessed the degrees of correlation and of homogeneity of the TN phenotype (IHC-based definition) and the basal subtype (gene expression-based definition). We analyzed 172 TN BCs defined by gene expression profile as basal (123 cases) and nonbasal (49 cases). Conversely, 160 tumors were defined as basal by their gene expression profile and included 123 TN and 37 non-TN samples. Uni- and multivariate analyses revealed that TN BCs represent a more heterogeneous group than basal BCs, including basal and nonbasal tumors very different both at the histoclinical and molecular level, notably for mRNA expression of molecules targeted by specific therapies under evaluation in clinical trials. These results call for caution in the interpretation of ongoing trials and selection of patients in future trials. They also warrant the identification of molecular markers for basal BCs more clinically applicable than gene expression profiles.