Tissue osmolarity varies among different organs and can be considerably increased under pathologic conditions. Hyperosmolarity has been associated with altered stimulatory properties of immune cells, ...especially macrophages and dendritic cells. We have recently reported that dendritic cells upon exposure to hypertonic stimuli shift their profile towards a macrophage-M2-like phenotype, resulting in attenuated local alloreactivity during acute kidney graft rejection. Here, we examined how hyperosmotic microenvironment affects the cross-priming capacity of dendritic cells. Using ovalbumin as model antigen, we showed that exposure of dendritic cells to hyperosmolarity strongly inhibits activation of antigen-specific T cells despite enhancement of antigen uptake, processing and presentation. We identified TRIF as key mediator of this phenomenon. Moreover, we detected a hyperosmolarity-triggered, TRIF-dependent clustering of MHCI loaded with the ovalbumin-derived epitope, but not of overall MHCI molecules, providing a possible explanation for a reduced T cell activation. Our findings identify dendritic cells as important players in hyperosmolarity-mediated immune imbalance and provide evidence for a novel pathway of inhibition of antigen specific CD8
T cell response in a hypertonic micromilieu.
Melanoma is the deadliest form of skin cancer showing rising incidence over the past years. New insights into the mechanisms of melanoma progression contributed to the development of novel treatment ...options, such as immunotherapies. However, acquiring resistance to treatment poses a big problem to therapy success. Therefore, understanding the mechanisms underlying resistance could improve therapy efficacy. Correlating expression levels in tissue samples of primary melanoma and metastases revealed that secretogranin 2 (SCG2) is highly expressed in advanced melanoma patients with poor overall survival (OS) rates. By conducting transcriptional analysis between SCG2-overexpressing (OE) and control melanoma cells, we detected a downregulation of components of the antigen presenting machinery (APM), which is important for the assembly of the MHC class I complex. Flow cytometry analysis revealed a downregulation of surface MHC class I expression on melanoma cells that showed resistance towards the cytotoxic activity of melanoma-specific T cells. IFNγ treatment partially reversed these effects. Based on our findings, we suggest that SCG2 might stimulate mechanisms of immune evasion and therefore be associated with resistance to checkpoint blockade and adoptive immunotherapy.
Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity ...can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification.
The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore).
The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively.
GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities.
Transcription factor Growth Factor Independence 1 (GFI1) regulates the expression of genes important for survival, proliferation and differentiation of hematopoietic cells. A single nucleotide ...polymorphism (SNP) variant of GFI1 (GFI1-36N: serine replaced by asparagine at position 36), has a prevalence of 5-7% among healthy Caucasians and 10-15% in patients with myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML) predisposing GFI-36N carriers to these diseases. Since GFI1 is implicated in B cell maturation and plasma cell (PC) development, we examined its prevalence in patients with multiple myeloma (MM), a haematological malignancy characterized by expansion of clonal PCs. Strikingly, as in MDS and AML, we found that the GFI1-36N had a higher prevalence among MM patients compared to the controls. In subgroup analyses, GFI1-36N correlates to a shorter overall survival of MM patients characterized by the presence of t(4;14) translocation and gain of 1q21 (≤3 copies). MM patients carrying gain of 1q21 (≥3 copies) demonstrated poor progression free survival. Furthermore, gene expression analysis implicated a role for GFI1-36N in epigenetic regulation and metabolism, potentially promoting the initiation and progression of MM.
In cancer, normal epigenetic patterns are disturbed and contribute to gene expression changes, disease onset, and progression. The cancer epigenome is composed of the epigenetic patterns present in ...the tumor-initiating cell at the time of transformation, and the tumor-specific epigenetic alterations that are acquired during tumor initiation and progression. The precise dissection of these two components of the tumor epigenome will facilitate a better understanding of the biological mechanisms underlying malignant transformation. Chronic lymphocytic leukemia (CLL) originates from differentiating B cells, which undergo extensive epigenetic programming. This poses the challenge to precisely determine the epigenomic ground state of the cell-of-origin in order to identify CLL-specific epigenetic aberrations.
We developed a linear regression model, methylome-based cell-of-origin modeling (Methyl-COOM), to map the cell-of-origin for individual CLL patients based on the continuum of epigenomic changes during normal B cell differentiation.
Methyl-COOM accurately maps the cell-of-origin of CLL and identifies CLL-specific aberrant DNA methylation events that are not confounded by physiologic epigenetic B cell programming. Furthermore, Methyl-COOM unmasks abnormal action of transcription factors, altered super-enhancer activities, and aberrant transcript expression in CLL. Among the aberrantly regulated transcripts were many genes that have previously been implicated in T cell biology. Flow cytometry analysis of these markers confirmed their aberrant expression on malignant B cells at the protein level.
Methyl-COOM analysis of CLL identified disease-specific aberrant gene regulation. The aberrantly expressed genes identified in this study might play a role in immune-evasion in CLL and might serve as novel targets for immunotherapy approaches. In summary, we propose a novel framework for in silico modeling of reference DNA methylomes and for the identification of cancer-specific epigenetic changes, a concept that can be broadly applied to other human malignancies.
The purpose of this study was to analyze size and growth dynamics of focal lesions (FL) as well as to quantify diffuse infiltration (DI) in untreated smoldering multiple myeloma (SMM) patients and ...correlate those MRI features with timepoint and cause of progression. We investigated 199 whole-body magnetic resonance imaging (wb-MRI) scans originating from longitudinal imaging of 60 SMM patients and 39 computed tomography (CT) scans for corresponding osteolytic lesions (OL) in 17 patients. All FLs >5 mm were manually segmented to quantify volume and growth dynamics, and DI was scored, rating four compartments separately in T1- and fat-saturated T2-weighted images. The majority of patients with at least two FLs showed substantial spatial heterogeneity in growth dynamics. The volume of the largest FL (
= 0.001, c-index 0.72), the speed of growth of the fastest growing FL (
= 0.003, c-index 0.75), the DI score (DIS,
= 0.014, c-index 0.67), and its dynamic over time (DIS dynamic,
< 0.001, c-index 0.67) all significantly correlated with the time to progression. Size and growth dynamics of FLs correlated significantly with presence/appearance of OL in CT within 2 years after the respective MRI assessment (
= 0.016 and
= 0.022). DIS correlated with decrease of hemoglobin (
< 0.001). In conclusion, size and growth dynamics of FLs correlate with prognosis and local bone destruction. Connections between MRI findings and progression patterns (fast growing FL-OL; DIS-hemoglobin decrease) might enable more precise diagnostic and therapeutic approaches for SMM patients in the future.
Abstract
Glioblastoma is a highly aggressive brain tumor for which there is no cure. The metabolic enzyme 6-Phosphofructo-2-Kinase/Fructose-2,6-Biphosphatase 4 (PFKFB4) is essential for glioblastoma ...stem-like cell (GSC) survival but its mode of action is unclear. Understanding the role of PFKFB4 in tumor cell survival could allow it to be leveraged in a cancer therapy. Here, we show the importance of PFKFB4 for glioblastoma growth in vivo in an orthotopic patient derived mouse model. In an evaluation of patient tumor samples of different cancer entities, PFKFB4 protein was found to be overexpressed in prostate, lung, colon, mammary and squamous cell carcinoma, with expression level correlating with tumor grade. Gene expression profiling in
PFKFB4
-silenced GSCs revealed a downregulation of hypoxia related genes and Western blot analysis confirmed a dramatic reduction of HIF (hypoxia inducible factor) protein levels. Through mass spectrometric analysis of immunoprecipitated PFKFB4, we identified the ubiquitin E3 ligase, F-box only protein 28 (FBXO28), as a new interaction partner of PFKFB4. We show that PFKFB4 regulates the ubiquitylation and subsequent proteasomal degradation of HIF-1α, which is mediated by the ubiquitin ligase activity of FBXO28. This newly discovered function of PFKFB4, coupled with its cancer specificity, provides a new strategy for inhibiting HIF-1α in cancer cells.
Melanoma is an aggressive form of skin cancer that is often characterized by activating mutations in the Mitogen-Activated Protein (MAP) kinase pathway, causing hyperproliferation of the cancer ...cells. Thus, inhibitors targeting this pathway were developed. These inhibitors are initially very effective, but the occurrence of resistance eventually leads to a failure of the therapy and is the major obstacle for clinical success. Therefore, investigating the mechanisms causing resistance and discovering ways to overcome them is essential for the success of therapy. Here, we observed that treatment of melanoma cells with the B-Raf Proto-Oncogene, Serine/Threonine Kinase (BRAF) inhibitor vemurafenib caused an increased cell surface expression and activation of human epidermal growth factor receptor 3 (HER3) by shed ligands. HER3 promoted the activation of signal transducer and activator of transcription 3 (STAT3) resulting in upregulation of the STAT3 target gene SRY-Box Transcription Factor 2 (
) and survival of the cancer cells. Pharmacological blocking of HER led to a diminished STAT3 activation and increased sensitivity toward vemurafenib. Moreover, HER blocking sensitized vemurafenib-resistant cells to drug treatment. We conclude that the inhibition of the STAT3 upstream regulator HER might help to overcome melanoma therapy resistance toward targeted therapies.
The Cox proportional hazards regression model is the most popular approach to model covariate information for survival times. In this context, the development of high‐dimensional models where the ...number of covariates is much larger than the number of observations ( $p \,{\gg }\, n$ ) is an ongoing challenge. A practicable approach is to use ridge penalized Cox regression in such situations. Beside focussing on finding the best prediction rule, one is often interested in determining a subset of covariates that are the most important ones for prognosis. This could be a gene set in the biostatistical analysis of microarray data. Covariate selection can then, for example, be done by L1‐penalized Cox regression using the lasso (Tibshirani (1997). Statistics in Medicine 16, 385–395). Several approaches beyond the lasso, that incorporate covariate selection, have been developed in recent years. This includes modifications of the lasso as well as nonconvex variants such as smoothly clipped absolute deviation (SCAD) (Fan and Li (2001). Journal of the American Statistical Association 96, 1348–1360; Fan and Li (2002). The Annals of Statistics 30, 74–99). The purpose of this article is to implement them practically into the model building process when analyzing high‐dimensional data with the Cox proportional hazards model. To evaluate penalized regression models beyond the lasso, we included SCAD variants and the adaptive lasso (Zou (2006). Journal of the American Statistical Association 101, 1418–1429). We compare them with “standard” applications such as ridge regression, the lasso, and the elastic net. Predictive accuracy, features of variable selection, and estimation bias will be studied to assess the practical use of these methods. We observed that the performance of SCAD and adaptive lasso is highly dependent on nontrivial preselection procedures. A practical solution to this problem does not yet exist. Since there is high risk of missing relevant covariates when using SCAD or adaptive lasso applied after an inappropriate initial selection step, we recommend to stay with lasso or the elastic net in actual data applications. But with respect to the promising results for truly sparse models, we see some advantage of SCAD and adaptive lasso, if better preselection procedures would be available. This requires further methodological research.
To investigate cytogenetic evolution after upfront autologous stem cell transplantation for newly diagnosed myeloma we retrospectively analyzed fluorescence
hybridization results of 128 patients with ...paired bone marrow samples from the time of primary diagnosis and at relapse. High-risk cytogenetic abnormalities (deletion 17p and/or gain 1q21) occurred more frequently after relapse (odds ratio: 6.33; 95% confidence interval: 1.86-33.42;
<0.001). No significant changes were observed for defined
translocations t(4;14); t(11;14); t(14;16) or hyperdiploid karyotypes between primary diagnosis and relapse.
translocations with unknown partners occurred more frequently at relapse. New deletion 17p and/or gain 1q21 were associated with cytogenetic heterogeneity, since some
lesions with different copy numbers were present only in subclones. No distinct baseline characteristics were associated with the occurrence of new high-risk cytogenetic abnormalities after progression. Patients who relapsed after novel agent-based induction therapy had an increased risk of developing high-risk aberrations (odds ratio 10.82; 95% confidence interval: 1.65-127.66;
=0.03) compared to those who were treated with conventional chemotherapy. Survival analysis revealed dismal outcomes regardless of whether high-risk aberrations were present at baseline (hazard ratio, 3.53; 95% confidence interval: 1.53-8.14;
=0.003) or developed at relapse only (hazard ratio, 3.06; 95% confidence interval: 1.09-8.59;
=0.03). Our results demonstrate cytogenetic evolution towards high-risk disease after autologous transplantation and underline the importance of repeated genetic testing in relapsed myeloma (EudraCT number of the HD4 trial: 2004-000944-26).
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