CCR6, the Sole Receptor for the Chemokine CCL20, Promotes Spontaneous Intestinal Tumorigenesis

Interactions between the inflammatory chemokine CCL20 and its receptor CCR6 have been associated with colorectal cancer growth and metastasis, however, a causal role for CCL20 signaling through CCR6 in promoting intestinal carcinogenesis has not been demonstrated in vivo. In this study, we aimed to determine the role of CCL20-CCR6 interactions in spontaneous intestinal tumorigenesis. CCR6-deficient mice were crossed with mice heterozygous for a mutation in the adenomatous polyposis coli (APC) gene (APCMIN/+ mice) to generate APCMIN/+ mice with CCR6 knocked out (CCR6KO-APCMIN/+ mice). CCR6KO-APCMIN/+ mice had diminished spontaneous intestinal tumorigenesis. CCR6KO-APCMIN/+ also had normal sized spleens as compared to the enlarged spleens found in APCMIN/+ mice. Decreased macrophage infiltration into intestinal adenomas and non-tumor epithelium was observed in CCR6KO-APCMIN/+ as compared to APCMIN/+ mice. CCL20 signaling through CCR6 caused increased production of CCL20 by colorectal cancer cell lines. Furthermore, CCL20 had a direct mitogenic effect on colorectal cancer cells. Thus, interactions between CCL20 and CCR6 promote intestinal carcinogenesis. Our results suggest that the intestinal tumorigenesis driven by CCL20-CCR6 interactions may be driven by macrophage recruitment into the intestine as well as proliferation of neoplastic epithelial cells. This interaction could be targeted for the treatment or prevention of malignancy

Identification of novel myeloma-specific XBP1 peptides able to generate cytotoxic T lymphocytes: A potential therapeutic application in multiple myeloma

The purpose of these studies was to identify HLA-A2+ immunogenic peptides derived from XBP1 antigens to induce a multiple myeloma (MM)-specific immune response. Six native peptides from non-spliced XBP1 antigen and three native peptides from spliced XBP1 antigen were selected and evaluated for their HLA-A2 specificity. Among them,$XBP1_{184–192}$, XBP1 $SP_{196–204}$ and XBP1 $SP_{367–375}$ peptides showed the highest level of binding affinity, but not stability to HLA-A2 molecules. Novel heteroclitic XBP1 peptides, YISPWILAV or YLFPQLISV, demonstrated a significant improvement in HLA-A2 stability from their native $XBP1_{184–192}$ or XBP1 $SP_{367–375}$ peptide, respectively. Cytotoxic T lymphocytes generated by repeated stimulation of CD3+ T cells with each HLA-A2-specific heteroclitic peptide showed an increased percentage of CD8+ (cytotoxic) and CD69+/CD45RO+ (activated memory) T cells and a lower percentage of CD4+ (helper) and CD45RA+/CCR7+ (naïve) T cells, which were distinct from the control T cells. Functionally, the CTLs demonstrated MM-specific and HLA-A2-restricted proliferation, IFN-γ secretion and cytotoxic acivity in response to MM cell lines and importantly, cytotoxicty against primary MM cells. These data demonstrate the distinct immunogenic characteristics of unique heteroclitic XBP1 peptides which induce MM-specific CTLs and highlights their potential application for immunotherapy to treat the patients with MM or its pre-malignant condition

canEvolve: A Web Portal for Integrative Oncogenomics

Background & objective: Genome-wide profiles of tumors obtained using functional genomics platforms are being deposited to the public repositories at an astronomical scale, as a result of focused efforts by individual laboratories and large projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium. Consequently, there is an urgent need for reliable tools that integrate and interpret these data in light of current knowledge and disseminate results to biomedical researchers in a user-friendly manner. We have built the canEvolve web portal to meet this need. Results: canEvolve query functionalities are designed to fulfill most frequent analysis needs of cancer researchers with a view to generate novel hypotheses. canEvolve stores gene, microRNA (miRNA) and protein expression profiles, copy number alterations for multiple cancer types, and protein-protein interaction information. canEvolve allows querying of results of primary analysis, integrative analysis and network analysis of oncogenomics data. The querying for primary analysis includes differential gene and miRNA expression as well as changes in gene copy number measured with SNP microarrays. canEvolve provides results of integrative analysis of gene expression profiles with copy number alterations and with miRNA profiles as well as generalized integrative analysis using gene set enrichment analysis. The network analysis capability includes storage and visualization of gene co-expression, inferred gene regulatory networks and protein-protein interaction information. Finally, canEvolve provides correlations between gene expression and clinical outcomes in terms of univariate survival analysis. Conclusion: At present canEvolve provides different types of information extracted from 90 cancer genomics studies comprising of more than 10,000 patients. The presence of multiple data types, novel integrative analysis for identifying regulators of oncogenesis, network analysis and ability to query gene lists/pathways are distinctive features of canEvolve. canEvolve will facilitate integrative and meta-analysis of oncogenomics datasets

Telomerase inhibition by siRNA causes senescence and apoptosis in Barrett's adenocarcinoma cells: mechanism and therapeutic potential

BACKGROUND: In cancer cells, telomerase induction helps maintain telomere length and thereby bypasses senescence and provides enhanced replicative potential. Chemical inhibitors of telomerase have been shown to reactivate telomere shortening and cause replicative senescence and apoptotic cell death of tumor cells while having little or no effect on normal diploid cells. RESULTS: We designed siRNAs against two different regions of telomerase gene and evaluated their effect on telomere length, proliferative potential, and gene expression in Barrett's adenocarcinoma SEG-1 cells. The mixture of siRNAs in nanomolar concentrations caused a loss of telomerase activity that appeared as early as day 1 and was essentially complete at day 3. Inhibition of telomerase activity was associated with marked reduction in median telomere length and complete loss of detectable telomeres in more than 50% of the treated cells. Telomere loss caused senescence in 40% and apoptosis in 86% of the treated cells. These responses appeared to be associated with activation of DNA sensor HR23B and subsequent activation of p53 homolog p73 and p63 and E2F1. Changes in these gene regulators were probably the source of observed up-regulation of cell cycle inhibitors, p16 and GADD45. Elevated transcript levels of FasL, Fas and caspase 8 that activate death receptors and CARD 9 that interacts with Bcl10 and NFKB to enhance mitochondrial translocation and activation of caspase 9 were also observed. CONCLUSION: These studies show that telomerase siRNAs can cause effective suppression of telomerase and telomere shortening leading to both cell cycle arrest and apoptosis via mechanisms that include up-regulation of several genes involved in cell cycle arrest and apoptosis. Telomerase siRNAs may therefore be strong candidates for highly selective therapy for chemoprevention and treatment of Barrett's adenocarcinoma

The shaping and functional consequences of the dosage effect landscape in multiple myeloma

Background: Multiple myeloma (MM) is a malignant proliferation of plasma B cells. Based on recurrent aneuploidy such as copy number alterations (CNAs), myeloma is divided into two subtypes with different CNA patterns and patient survival outcomes. How aneuploidy events arise, and whether they contribute to cancer cell evolution are actively studied. The large amount of transcriptomic changes resultant of CNAs (dosage effect) pose big challenges for identifying functional consequences of CNAs in myeloma in terms of specific driver genes and pathways. In this study, we hypothesize that gene-wise dosage effect varies as a result from complex regulatory networks that translate the impact of CNAs to gene expression, and studying this variation can provide insights into functional effects of CNAs. Results: We propose gene-wise dosage effect score and genome-wide karyotype plot as tools to measure and visualize concordant copy number and expression changes across cancer samples. We find that dosage effect in myeloma is widespread yet variable, and it is correlated with gene expression level and CNA frequencies in different chromosomes. Our analysis suggests that despite the enrichment of differentially expressed genes between hyperdiploid MM and non-hyperdiploid MM in the trisomy chromosomes, the chromosomal proportion of dosage sensitive genes is higher in the non-trisomy chromosomes. Dosage-sensitive genes are enriched by genes with protein translation and localization functions, and dosage resistant genes are enriched by apoptosis genes. These results point to future studies on differential dosage sensitivity and resistance of pro- and anti-proliferation pathways and their variation across patients as therapeutic targets and prognosis markers. Conclusions: Our findings support the hypothesis that recurrent CNAs in myeloma are selected by their functional consequences. The novel dosage effect score defined in this work will facilitate integration of copy number and expression data for identifying driver genes in cancer genomics studies. The accompanying R code is available at http://www.canevolve.org/dosageEffect/

The dChip survival analysis module for microarray data

International audienceBACKGROUND: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters. RESULTS: We have developed the survival analysis module in the dChip software that performs survival analysis across the genome for gene expression and copy number microarray data. Built on the current dChip software's microarray analysis functions such as chromosome display and clustering, the new survival functions include interactive exploring of Kaplan-Meier (K-M) plots using expression or copy number data, computing survival p-values from the log-rank test and Cox models, and using permutation to identify significant chromosome regions associated with survival. CONCLUSIONS: The dChip survival module provides user-friendly way to perform survival analysis and visualize the results in the context of genes and cytobands. It requires no coding expertise and only minimal learning curve for thousands of existing dChip users. The implementation in Visual C++ also enables fast computation. The software and demonstration data are freely available at http://dchip-surv.chenglilab.org

Transcription factor-pathway co-expression analysis reveals cooperation between SP1 and ESR1 on dysregulating cell cycle arrest in non-hyperdiploid multiple myeloma

Multiple myeloma is a hematological cancer of plasma B-cells and remains incurable. Two major subtypes of myeloma, hyperdiploid (HMM) and non-hyperdiploid myeloma (NHMM), have distinct chromosomal alterations and different survival outcomes. Transcription factors (TrFs) have been implicated in myeloma oncogenesis but their dysregulation in myeloma subtypes are less studied. Here we develop a TrF-pathway co-expression analysis to identify altered co-expression between two sample types. We apply the method to the two myeloma subtypes and the cell cycle arrest pathway, which is significantly differentially expressed between the two subtypes. We find that TrFs MYC, NF-κB and HOXA9 have significantly lower co-expression with cell cycle arrest in HMM, co-occurring with their over-activation in HMM. In contrast, TrFs ESR1, SP1 and E2F1 have significantly lower co-expression with cell cycle arrest in NHMM. SP1 ChIP targets are enriched by cell cycle arrest genes. These results motivate a cooperation model of ESR1 and SP1 in regulating cell cycle arrest, and a hypothesis that their over-activation in NHMM disrupts proper regulation of cell cycle arrest. Co-targeting ESR1 and SP1 shows a synergistic effect on inhibiting myeloma proliferation in NHMM cell lines. Therefore, studying TrF-pathway co-expression dysregulation in human cancers facilitates forming novel hypotheses towards clinical utility

Classify Hyperdiploidy Status of Multiple Myeloma Patients Using Gene Expression Profiles

Multiple myeloma (MM) is a cancer of antibody-making plasma cells. It frequently harbors alterations in DNA and chromosome copy numbers, and can be divided into two major subtypes, hyperdiploid (HMM) and non-hyperdiploid multiple myeloma (NHMM). The two subtypes have different survival prognosis, possibly due to different but converging paths to oncogenesis. Existing methods for identifying the two subtypes are fluorescence in situ hybridization (FISH) and copy number microarrays, with increased cost and sample requirements. We hypothesize that chromosome alterations have their imprint in gene expression through dosage effect. Using five MM expression datasets that have HMM status measured by FISH and copy number microarrays, we have developed and validated a K-nearest-neighbor method to classify MM into HMM and NHMM based on gene expression profiles. Classification accuracy for test datasets ranges from 0.83 to 0.88. This classification will enable researchers to study differences and commonalities of the two MM subtypes in disease biology and prognosis using expression datasets without need for additional subtype measurements. Our study also supports the advantages of using cancer specific characteristics in feature design and pooling multiple rounds of classification results to improve accuracy. We provide R source code and processed datasets at www.ChengLiLab.org/software

The monoclonal antibody nBT062 conjugated to maytansinoids has potent and selective cytotoxicity against CD138 positive multiple myeloma cells _in vitro_ and _in vivo_

CD138 (Syndecan1) is highly expressed on multiple myeloma (MM) cells. In this study, we examined the anti-MM effect of murine/human chimeric CD138-specific monoclonal antibody (mAb) nBT062 conjugated with highly cytotoxic maytansinoid derivatives _in vitro_ and _in vivo_. These agents significantly inhibited growth of CD138-positive MM cell lines and primary tumor cells from MM patients, without cytotoxicity against peripheral blood mononuclear cells from healthy volunteers. In MM cells, they induced G2/M cell cycle arrest followed by apoptosis associated with cleavage of PARP and caspase-3, -8 and -9. Non-conjugated nBT062 completely blocked cytotoxicity induced by nBT062-maytansinoid conjugate, confirming that binding is required for inducing cytotoxicity. Moreover, nBT062-maytansinoid conjugates blocked adhesion of MM cells to bone marrow stromal cells (BMSCs). Co-culture of MM cells with BMSCs, which protects against dexamethasone-induced death, had no impact on the cytotoxicity of the immunoconjugates. Importantly, nBT062-SPDB-DM4 and nBT062-SPP-DM1 significantly inhibited MM tumor growth _in vivo_ in both human multiple myeloma xenograft mouse models and in SCID-human bone grafts (SCID-hu mouse model). These studies provide the preclinical framework supporting evaluation of nBT062-maytansinoid derivatives in clinical trials to improve patient outcome in MM

The Medical Research Council Myeloma IX trial: the impact on treatment paradigms*

Osteolytic bone disease is a hallmark of symptomatic multiple myeloma. Bisphosphonates have been the mainstay of treatment to preserve skeletal integrity and prevent skeletal-related events in patients with myeloma-related bone disease. Recently, the MRC Myeloma IX trial demonstrated for the first time improved survival and delayed disease progression with the use of an intravenous amino-bisphosphonate, zoledronic acid, vs. an oral agent, clodronate, with intensive and non-intensive anti-myeloma treatment regimens in patients with newly diagnosed multiple myeloma. These results validate a large body of preclinical, translational and other clinical data suggesting anti-myeloma effects of amino-bisphosphonates. In addition, this trial also provided the first head-to-head evidence for superiority of one bisphosphonate over another (zoledronic acid vs. clodronate) for reducing skeletal morbidity in patients with multiple myeloma, as well as a prospective comparison of toxicities. Despite the use of non-bortezomib containing anti-myeloma treatment regimens in the MRC Myeloma IX trial, these results are encouraging and provide an impetus to continue to evaluate current treatment guidelines for myeloma-associated bone disease