A two-gene signature, SKI and SLAMF1, predicts time-to-treatment in previously untreated patients with chronic lymphocytic leukemia

Super-Enhancer–Associated nine-gene prognostic score model for prediction of survival in chronic lymphocytic leukemia patients

Chronic lymphocytic leukemia (CLL) is a type of highly heterogeneous mature B-cell malignancy with various disease courses. Although a multitude of prognostic markers in CLL have been reported, insights into the role of super-enhancer (SE)–related risk indicators in the occurrence and development of CLL are still lacking. A super-enhancer (SE) is a cluster of enhancers involved in cell differentiation and tumorigenesis, and is one of the promising therapeutic targets for cancer therapy in recent years. In our study, the CLL-related super-enhancers in the training database were processed by LASSO-penalized Cox regression analysis to screen a nine-gene prognostic model including TCF7, VEGFA, MNT, GMIP, SLAMF1, TNFRSF25, GRWD1, SLC6AC, and LAG3. The SE-related risk score was further constructed and it was found that the predictive performance with overall survival and time-to-treatment (TTT) was satisfactory. Moreover, a high correlation was found between the risk score and already known prognostic markers of CLL. In the meantime, we noticed that the expressions of TCF7, GMIP, SLAMF1, TNFRSF25, and LAG3 in CLL were different from those of healthy donors (p < 0.01). Moreover, the risk score and LAG3 level of matched pairs before and after treatment samples varied significantly. Finally, an interactive nomogram consisting of the nine-gene risk group and four clinical traits was established. The inhibitors of mTOR and cyclin-dependent kinases (CDKs) were considered effective in patients in the high-risk group according to the pRRophetic algorithm. Collectively, the SE-associated nine-gene prognostic model developed here may be used to predict the prognosis and assist in the risk stratification and treatment of CLL patients in the future.

Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort

Background

The incidence and mortality rates of colon adenocarcinoma (COAD), which is the fourth most diagnosed cancer worldwide, are high. A subset of patients with COAD has shown promising responses to immunotherapy. However, the percentage of patients with COAD benefiting from immunotherapy is unclear. Therefore, gaining a better understanding of the immune milieu of colon cancer could aid in the development of immunotherapy and suitable combination strategies.

Methods

In this study, gene expression profiles and clinical follow-up data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and molecular subtypes were identified using the ConsensusClusterPlus package in R. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic value of immune subtypes. The graph structure learning method was used to reduce the dimension to reveal the internal structure of the immune system. Weighted correlation network analysis (WGCNA) was performed to identify immune-related gene modules. Finally, western blotting was performed to verify the gene expression patterns in COAD samples.

Results

The results showed that 424 COAD samples could be divided into three subtypes based on 1921 immune cell-related genes, with significant differences in prognosis between subtypes. Furthermore, immune-related genes could be divided into five functional modules, each with a different distribution pattern of immune subtypes. Immune subtypes and gene modules were highly reproducible across many data sets. There were significant differences in the distribution of immune checkpoints, molecular markers, and immune characteristics among immune subtypes. Four core genes, namely, CD2, FGL2, LAT2, and SLAMF1, with prognostic significance were identified by WGCNA and univariate Cox analysis.

Conclusion

Overall, this study provides a conceptual framework for understanding the tumor immune microenvironment of colon cancer.

MicroRNA‑195‑5p inhibits the progression of hemangioma via targeting SKI

Hemangioma (HA), which is characterized by aberrant endothelial cell proliferation in blood vessels, is a common tumor during infancy. MicroRNAs (miRNAs/miRs) collectively participate in the development of HA; however, the potential roles of miR-195-5p in HA are not completely understood. The aim of the present study was to investigate the roles of miR-195-5p in HA. In the present study, miR-195-5p was found to be downregulated in HA cells, such as the XPTS-1 human infantile hemangioma-derived endothelial cell line and the EOMA hemangioendothelioma cell line. Overexpression of miR-195-5p was shown to suppress HA cell viability, colony formation and proliferation, and induced HA cell apoptosis. Furthermore, miR-195-5p downregulated Bcl-2 expression and upregulated Bax and Bcl-2 expression levels. V-ski sarcoma viral oncogene homolog (SKI) was identified as a target of miR-195-5p. Co-transfection of miR-195-5p mimics and SKI 3'-untranslated region wild-type decreased HA cell luciferase activity. SKI overexpression alleviated the miR-195-5p-induced decrease in HA cell proliferation and increased HA cell apoptosis. In addition, the regulatory role of miR-195-5p on the expression of Bcl-2, Bax and poly(ADP-ribose) polymerase was reversed by SKI. Collectively, the results of the present study demonstrated that miR-195-5p suppressed HA progression and its effects were mediated via SKI. Therefore, the miR-195-5p/SKI axis may represent a novel therapeutic target for HA.

Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis

Background

Previous studies have found that the microenvironment of cervical cancer (CESC) affects the progression and treatment of this disease. Thus, we constructed a multigene model to assess the survival of patients with cervical cancer.

Methods

We scored 307 CESC samples from The Cancer Genome Atlas (TCGA) and divided them into high and low matrix and immune scores using the ESTIMATE algorithm for differential gene analysis. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The multigene signature prognostic model was constructed by Cox analyses. Multivariate Cox analysis was applied to evaluate the significance of the multigene signature for cervical cancer prognosis. Prognosis was assessed by Kaplan–Meier curves comparing the different groups, and the accuracy of the prognostic model was analyzed by receiver operating characteristic-area under the curve (ROC-AUC) analysis and calibration curve. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the relationship between the multigene signature and immune cell infiltration.

Results

We obtained 420 differentially expressed genes in the tumor microenvironment from 307 patients with cervical cancer. A three-gene signature (SLAMF1, CD27, SELL) model related to the tumor microenvironment was constructed to assess patient survival. Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis. The ROC-AUC value indicated that the model was an accurate predictor of cervical cancer prognosis. Multivariate cox analysis showed the three-gene signature to be an independent risk factor for the prognosis of cervical cancer. A nomogram combining the three-gene signature and clinical features was constructed, and calibration plots showed that the nomogram resulted in an accurate prognosis for patients. The three-gene signature was associated with T stage, M stage and degree of immune infiltration in patients with cervical cancer.

Conclusions

This research suggests that the developed three-gene signature may be applied as a biomarker to predict the prognosis of and personalized therapy for CESC.

SLAMF receptors negatively regulate B cell receptor signaling in chronic lymphocytic leukemia via recruitment of prohibitin-2

We identified a subset of Chronic Lymphocytic Leukemia (CLL) patients with high Signaling Lymphocytic Activation Molecule Family (SLAMF) receptor-related signaling that showed an indolent clinical course. Since SLAMF receptors play a role in NK cell biology, we reasoned that these receptors may impact NK cell-mediated CLL immunity. Indeed, our experiments showed significantly decreased degranulation capacity of primary NK cells from CLL patients expressing low levels of SLAMF1 and SLAMF7. Since the SLAMF^low signature was strongly associated with an unmutated CLL immunoglobulin heavy chain (IGHV) status in large datasets, we investigated the impact of SLAMF1 and SLAMF7 on the B cell receptor (BCR) signaling axis. Overexpression of SLAMF1 or SLAMF7 in IGHV mutated CLL cell models resulted in reduced proliferation and impaired responses to BCR ligation, whereas the knockout of both receptors showed opposing effects and increased sensitivity toward inhibition of components of the BCR pathway. Detailed molecular analyzes showed that SLAMF1 and SLAMF7 receptors mediate their BCR pathway antagonistic effects via recruitment of prohibitin-2 (PHB2) thereby impairing its role in signal transduction downstream the IGHV-mutant IgM-BCR. Together, our data indicate that SLAMF receptors are important modulators of the BCR signaling axis and may improve immune control in CLL by interference with NK cells.

Prognostic models for newly-diagnosed chronic lymphocytic leukaemia in adults: a systematic review and meta-analysis

BACKGROUND

Chronic lymphocytic leukaemia (CLL) is the most common cancer of the lymphatic system in Western countries. Several clinical and biological factors for CLL have been identified. However, it remains unclear which of the available prognostic models combining those factors can be used in clinical practice to predict long-term outcome in people newly-diagnosed with CLL.

OBJECTIVES

To identify, describe and appraise all prognostic models developed to predict overall survival (OS), progression-free survival (PFS) or treatment-free survival (TFS) in newly-diagnosed (previously untreated) adults with CLL, and meta-analyse their predictive performances.

SEARCH METHODS

We searched MEDLINE (from January 1950 to June 2019 via Ovid), Embase (from 1974 to June 2019) and registries of ongoing trials (to 5 March 2020) for development and validation studies of prognostic models for untreated adults with CLL. In addition, we screened the reference lists and citation indices of included studies.

SELECTION CRITERIA

We included all prognostic models developed for CLL which predict OS, PFS, or TFS, provided they combined prognostic factors known before treatment initiation, and any studies that tested the performance of these models in individuals other than the ones included in model development (i.e. 'external model validation studies'). We included studies of adults with confirmed B-cell CLL who had not received treatment prior to the start of the study. We did not restrict the search based on study design.

DATA COLLECTION AND ANALYSIS

We developed a data extraction form to collect information based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS). Independent pairs of review authors screened references, extracted data and assessed risk of bias according to the Prediction model Risk Of Bias ASsessment Tool (PROBAST). For models that were externally validated at least three times, we aimed to perform a quantitative meta-analysis of their predictive performance, notably their calibration (proportion of people predicted to experience the outcome who do so) and discrimination (ability to differentiate between people with and without the event) using a random-effects model. When a model categorised individuals into risk categories, we pooled outcome frequencies per risk group (low, intermediate, high and very high). We did not apply GRADE as guidance is not yet available for reviews of prognostic models.

MAIN RESULTS

From 52 eligible studies, we identified 12 externally validated models: six were developed for OS, one for PFS and five for TFS. In general, reporting of the studies was poor, especially predictive performance measures for calibration and discrimination; but also basic information, such as eligibility criteria and the recruitment period of participants was often missing. We rated almost all studies at high or unclear risk of bias according to PROBAST. Overall, the applicability of the models and their validation studies was low or unclear; the most common reasons were inappropriate handling of missing data and serious reporting deficiencies concerning eligibility criteria, recruitment period, observation time and prediction performance measures. We report the results for three models predicting OS, which had available data from more than three external validation studies: CLL International Prognostic Index (CLL-IPI) This score includes five prognostic factors: age, clinical stage, IgHV mutational status, B2-microglobulin and TP53 status. Calibration: for the low-, intermediate- and high-risk groups, the pooled five-year survival per risk group from validation studies corresponded to the frequencies observed in the model development study. In the very high-risk group, predicted survival from CLL-IPI was lower than observed from external validation studies. Discrimination: the pooled c-statistic of seven external validation studies (3307 participants, 917 events) was 0.72 (95% confidence interval (CI) 0.67 to 0.77). The 95% prediction interval (PI) of this model for the c-statistic, which describes the expected interval for the model's discriminative ability in a new external validation study, ranged from 0.59 to 0.83. Barcelona-Brno score Aimed at simplifying the CLL-IPI, this score includes three prognostic factors: IgHV mutational status, del(17p) and del(11q). Calibration: for the low- and intermediate-risk group, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of four external validation studies (1755 participants, 416 events) was 0.64 (95% CI 0.60 to 0.67); 95% PI 0.59 to 0.68. MDACC 2007 index score The authors presented two versions of this model including six prognostic factors to predict OS: age, B2-microglobulin, absolute lymphocyte count, gender, clinical stage and number of nodal groups. Only one validation study was available for the more comprehensive version of the model, a formula with a nomogram, while seven studies (5127 participants, 994 events) validated the simplified version of the model, the index score. Calibration: for the low- and intermediate-risk groups, the pooled survival per risk group corresponded to the frequencies observed in the model development study, although the score seems to overestimate survival for the high-risk group. Discrimination: the pooled c-statistic of the seven external validation studies for the index score was 0.65 (95% CI 0.60 to 0.70); 95% PI 0.51 to 0.77.

AUTHORS' CONCLUSIONS

Despite the large number of published studies of prognostic models for OS, PFS or TFS for newly-diagnosed, untreated adults with CLL, only a minority of these (N = 12) have been externally validated for their respective primary outcome. Three models have undergone sufficient external validation to enable meta-analysis of the model's ability to predict survival outcomes. Lack of reporting prevented us from summarising calibration as recommended. Of the three models, the CLL-IPI shows the best discrimination, despite overestimation. However, performance of the models may change for individuals with CLL who receive improved treatment options, as the models included in this review were tested mostly on retrospective cohorts receiving a traditional treatment regimen. In conclusion, this review shows a clear need to improve the conducting and reporting of both prognostic model development and external validation studies. For prognostic models to be used as tools in clinical practice, the development of the models (and their subsequent validation studies) should adapt to include the latest therapy options to accurately predict performance. Adaptations should be timely.

In chronic lymphocytic leukaemia, SLAMF1 deregulation is associated with genomic complexity and independently predicts a worse outcome

In a series of 349 patients with chronic lymphocytic leukaemia (CLL), we found lower levels of signalling lymphocytic activation molecule family member 1 (SLAMF1) expression in cases with highly complex karyotypes, as defined by the presence of five or more chromosomal abnormalities (CK5; P < 0·001) and with major chromosomal structural abnormalities (P < 0·001). SLAMF1 downregulation was significantly associated with advanced Binet Stage (P = 0·001), CD38 positivity (P < 0·001), high β₂ -microglobulin levels (P < 0·001), immunoglobulin heavy chain variable region gene (IGHV) unmutated status (P < 0·001), 11q deletion (P < 0·001), tumour protein p53 (TP53) disruption (P = 0·011) and higher risk CLL International Prognostic Index categories (P < 0·001). Multivariate analysis showed that downregulated SLAMF1 levels had independent negative prognostic impact on time-to-first treatment (P < 0·001) and overall survival (P < 0·001).

SLAMF receptors on normal and malignant B cells

The Signaling Lymphocyte Activation Molecule family (SLAMF) is a collection of nine surface receptors expressed mainly on hematopoietic cells, and was found to modulate the behavior of immune cells. SLAMF receptors are expressed on B cells in health and disease. Each SLAM receptor has a unique differential expression pattern during the development and activation of B cells. Furthermore, recent findings have revealed a principal role for this family of receptors in B cell malignancies, emphasizing their importance in the control of malignant cell survival, cell to cell communication within the tumor microenvironment, retention in the supporting niches and regulation of T cell anti-tumor response. This review summarizes the latest studies regarding SLAMF expression and behavior in B cells and in B cell pathologies, and discusses the therapeutic potential of these receptors.

SLAMF1/CD150 in hematologic malignancies: Silent marker or active player?

SLAMF1/CD150 receptor is a founder of signaling lymphocyte activation molecule (SLAM) family of cell-surface receptors. It is widely expressed on cells within hematopoietic system. In hematologic malignancies CD150 cell surface expression is restricted to cutaneous T-cell lymphomas, few types of B-cell non-Hodgkin's lymphoma, near half of cases of chronic lymphocytic leukemia, Hodgkin's lymphoma, and multiple myeloma. Differential expression among various types of hematological malignancies allows considering CD150 as diagnostical and potential prognostic marker. Moreover, CD150 may be a target for antibody-based or measles virus oncolytic therapy. Due to CD150 signaling properties it is involved in regulation of malignant cell fate decision and tumor microenvironment in Hodgkin's lymphoma and chronic lymphocytic leukemia. This review summarizes evidence for the important role of CD150 in pathogenesis of hematologic malignancies.

Transcriptional cofactors Ski and SnoN are major regulators of the TGF-β/Smad signaling pathway in health and disease

The transforming growth factor-β (TGF-β) family plays major pleiotropic roles by regulating many physiological processes in development and tissue homeostasis. The TGF-β signaling pathway outcome relies on the control of the spatial and temporal expression of >500 genes, which depend on the functions of the Smad protein along with those of diverse modulators of this signaling pathway, such as transcriptional factors and cofactors. Ski (Sloan-Kettering Institute) and SnoN (Ski novel) are Smad-interacting proteins that negatively regulate the TGF-β signaling pathway by disrupting the formation of R-Smad/Smad4 complexes, as well as by inhibiting Smad association with the p300/CBP coactivators. The Ski and SnoN transcriptional cofactors recruit diverse corepressors and histone deacetylases to repress gene transcription. The TGF-β/Smad pathway and coregulators Ski and SnoN clearly regulate each other through several positive and negative feedback mechanisms. Thus, these cross-regulatory processes finely modify the TGF-β signaling outcome as they control the magnitude and duration of the TGF-β signals. As a result, any alteration in these regulatory mechanisms may lead to disease development. Therefore, the design of targeted therapies to exert tight control of the levels of negative modulators of the TGF-β pathway, such as Ski and SnoN, is critical to restore cell homeostasis under the specific pathological conditions in which these cofactors are deregulated, such as fibrosis and cancer.

Proteins that repress molecular signaling through the transforming growth factor-beta (TGF-β) pathway offer promising targets for treating cancer and fibrosis. Marina Macías-Silva and colleagues from the National Autonomous University of Mexico in Mexico City review the ways in which a pair of proteins, called Ski and SnoN, interact with downstream mediators of TGF-β to inhibit the effects of this master growth factor. Aberrant levels of Ski and SnoN have been linked to diverse range of diseases involving cell proliferation run amok, and therapies that regulate the expression of these proteins could help normalize TGF-β signaling to healthier physiological levels. For decades, drug companies have tried to target the TGF-β pathway, with limited success. Altering the activity of these repressors instead could provide a roundabout way of remedying pathogenic TGF-β activity in fibrosis and oncology.

Signaling lymphocytic activation molecules Slam and cancers: friends or foes?

Signaling Lymphocytic Activation Molecules (SLAM) family receptors are initially described in immune cells. These receptors recruit both activating and inhibitory SH2 domain containing proteins through their Immunoreceptor Tyrosine based Switch Motifs (ITSMs). Accumulating evidence suggest that the members of this family are intimately involved in different physiological and pathophysiological events such as regulation of immune responses and entry pathways of certain viruses. Recently, other functions of SLAM, principally in the pathophysiology of neoplastic transformations have also been deciphered. These new findings may prompt SLAM to be considered as new tumor markers, diagnostic tools or potential therapeutic targets for controlling the tumor progression. In this review, we summarize the major observations describing the implications and features of SLAM in oncology and discuss the therapeutic potential attributed to these molecules.

A combination of an anti-SLAMF6 antibody and ibrutinib efficiently abrogates expansion of chronic lymphocytic leukemia cells

The signaling lymphocyte activation molecule family [SLAMF] of cell surface receptors partakes in both the development of several immunocyte lineages and innate and adaptive immune responses in humans and mice. For instance, the homophilic molecule SLAMF6 (CD352) is in part involved in natural killer T cell development, but also modulates T follicular helper cell and germinal B cell interactions. Here we report that upon transplantation of a well-defined aggressive murine B220⁺CD5⁺ Chronic Lymphocytic Leukemia (CLL) cell clone, TCL1-192, into SCID mice one injection of a monoclonal antibody directed against SLAMF6 (αSlamf6) abrogates tumor progression in the spleen, bone marrow and blood. Similarly, progression of a murine B cell lymphoma, LMP2A/λMyc, was also eliminated by αSlamf6. But, surprisingly, αSLAMF6 neither eliminated TCL1-192 nor LMP2A/λMyc cells, which resided in the peritoneal cavity or omentum. This appeared to be dependent upon the tumor environment, which affected the frequency of sub-populations of the TCL1-192 clone or the inability of peritoneal macrophages to induce Antibody Dependent Cellular Cytotoxicity (ADCC). However, co-administering αSlamf6 with the Bruton tyrosine kinase (Btk) inhibitor, ibrutinib, synergized to efficiently eliminate the tumor cells in the spleen, bone marrow, liver and the peritoneal cavity. Because an anti-human SLAMF6 mAb efficiently killed human CLL cells in vitro and in vivo, we propose that a combination of αSlamf6 with ibrutinib should be considered as a novel therapeutic approach for CLL and other B cell tumors.

The interplay of CD150 and CD180 receptor pathways contribute to the pathobiology of chronic lymphocytic leukemia B cells by selective inhibition of Akt and MAPK signaling

Cell surface expression of CD150 and CD180 receptors in chronic lymphocytic leukemia (CLL) associates with mutational IGHV status and favourable prognosis. Here we show a direct correlation between cell surface expression and colocalization of these receptors on CLL B cells. In the absence of CD150 and CD180 on the cell surface both receptors were expressed in the cytoplasm. The CD150 receptor was colocalized with markers of the endoplasmic reticulum, the Golgi apparatus and early endosomes. In contrast, CD180 was detected preferentially in early endosomes. Analysis of CD150 isoforms differential expression revealed that regardless of CD150 cell surface expression the mCD150 isoform with two ITSM signaling motifs was a predominant CD150 isoform in CLL B cells. The majority of CLL cases had significantly elevated expression level of the soluble sCD150, moreover CLL B cells secrete this isoform. CD150 or CD180 crosslinking on CLL B cells alone led to activation of Akt, mTORC1, ERK1/2, p38MAPK and JNK1/2 networks. Both CD150 and CD180 target the translation machinery through mTOR independent as well as mTOR dependent pathways. Moreover, both these receptors transmit pro-survival signals via Akt-mediated inhibition of GSK3β and FOXO1/FOXO3a. Unexpectedly, coligation CD150 and CD180 receptors on CLL B cells led to mutual inhibition of the Akt and MAPK pathways. While CD150 and CD180 coligation resulted in reduced phosphorylation of Akt, ERK1/2, c-Jun, RSK, p70S6K, S6RP, and 4E-BP; it led to complete blocking of mTOR and p38MAPK phosphorylation. At the same time coligation of CD150 and CD40 receptors did not result in Akt and MAPK inhibition. This suggests that combination of signals via CD150 and CD180 leads to blocking of pro-survival pathways that may be a restraining factor for neoplastic CLL B cells propagation in more than 50% of CLL cases where these receptors are coexpressed.

Early B-cell factor 1 (EBF1) is critical for transcriptional control of SLAMF1 gene in human B cells

Signaling lymphocytic activation molecule family member 1 (SLAMF1)/CD150 is a co-stimulatory receptor expressed on a variety of hematopoietic cells, in particular on mature lymphocytes activated by specific antigen, costimulation and cytokines. Changes in CD150 expression level have been reported in association with autoimmunity and with B-cell chronic lymphocytic leukemia. We characterized the core promoter for SLAMF1 gene in human B-cell lines and explored binding sites for a number of transcription factors involved in B cell differentiation and activation. Mutations of SP1, STAT6, IRF4, NF-kB, ELF1, TCF3, and SPI1/PU.1 sites resulted in significantly decreased promoter activity of varying magnitude, depending on the cell line tested. The most profound effect on the promoter strength was observed upon mutation of the binding site for Early B-cell factor 1 (EBF1). This mutation produced a 10-20 fold drop in promoter activity and pinpointed EBF1 as the master regulator of human SLAMF1 gene in B cells. We also identified three potent transcriptional enhancers in human SLAMF1 locus, each containing functional EBF1 binding sites. Thus, EBF1 interacts with specific binding sites located both in the promoter and in the enhancer regions of the SLAMF1 gene and is critical for its expression in human B cells.

SLAMF1 regulation of chemotaxis and autophagy determines CLL patient response

Chronic lymphocytic leukemia (CLL) is a variable disease; therefore, markers to identify aggressive forms are essential for patient management. Here, we have shown that expression of the costimulatory molecule and microbial sensor SLAMF1 (also known as CD150) is lost in a subset of patients with an aggressive CLL that associates with a shorter time to first treatment and reduced overall survival. SLAMF1 silencing in CLL-like Mec-1 cells, which constitutively express SLAMF1, modulated pathways related to cell migration, cytoskeletal organization, and intracellular vesicle formation and recirculation. SLAMF1 deficiency associated with increased expression of CXCR4, CD38, and CD44, thereby positively affecting chemotactic responses to CXCL12. SLAMF1 ligation with an agonistic monoclonal antibody increased ROS accumulation and induced phosphorylation of p38, JNK1/2, and BCL2, thereby promoting the autophagic flux. Beclin1 dissociated from BCL2 in response to SLAMF1 ligation, resulting in formation of the autophagy macrocomplex, which contains SLAMF1, beclin1, and the enzyme VPS34. Accordingly, SLAMF1-silenced cells or SLAMF1(lo) primary CLL cells were resistant to autophagy-activating therapeutic agents, such as fludarabine and the BCL2 homology domain 3 mimetic ABT-737. Together, these results indicate that loss of SLAMF1 expression in CLL modulates genetic pathways that regulate chemotaxis and autophagy and that potentially affect drug responses, and suggest that these effects underlie unfavorable clinical outcome experienced by SLAMF1(lo) patients.

Developing Molecular Signatures for Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is a clonal malignancy of mature B cells that displays a great clinical heterogeneity, with many patients having an indolent disease that will not require intervention for many years, while others present an aggressive and symptomatic leukemia requiring immediate treatment. Although there is no cure for CLL, the disease is treatable and current standard chemotherapy regimens have been shown to prolong survival. Recent advances in our understanding of the biology of CLL have led to the identification of numerous cellular and molecular markers with potential diagnostic, prognostic and therapeutic significance. We have used the recently developed digital multiplexed gene-expression technique (DMGE) to analyze a cohort of 30 CLL patients for the presence of specific genes with known diagnostic and prognostic potential. Starting from a set of 290 genes we were able to develop a molecular signature, based on the analysis of 13 genes, which allows distinguishing CLL from normal peripheral blood and from normal B cells, and a second signature based on 24 genes, which distinguishes mutated from unmutated cases (LymphCLL Mut). A third classifier (LymphCLL Diag), based on a 44-gene signature, distinguished CLL cases from a series of other B-cell chronic lymphoproliferative disorders (n = 51). While the methodology presented here has the potential to provide a "ready to use" classification tool in routine diagnostics and clinical trials, application to larger sample numbers are still needed and should provide further insights about its robustness and utility in clinical practice.

Gene expression profiling for targeted cancer treatment

INTRODUCTION

There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations.

AREAS COVERED

The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples.

EXPERT OPINION

The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

Personalized medicine in CLL: current status and future perspectives

Chronic lymphocytic leukemia (CLL) is the most common hematologic malignancy in the Western Hemisphere. Despite advances in research and the development of effective treatment regimens, CLL is still largely an incurable disease. Although several prognostic factors have been identified in recent years, most of the new prognostic factors are not utilized, and treatment decisions are still based on clinical staging and limited use of cytogenetic analysis. Patients with advanced disease are treated at diagnosis, whereas others, regardless of their prognostic indicators, are offered treatment only at disease progression. Furthermore, treatment guidelines for elderly or "unfit" patients are unavailable because most CLL trials have included mostly younger, healthier patients. Given theheterogeneity of the clinical manifestations and prognosis of CLL, patients are likely to benefit from a personalized therapeutic approach. Recent advances in CLL pathobiology research, the use of high-throughput technologies, and most importantly, the introduction of novel targeted therapies with high efficacy and low toxicity are currently transforming the treatment of CLL. A personalized approach that includes early intervention in selected patients with CLL is likely to bring physicians closer to the goal of attaining cures in most patients with CLL.