Clinical response after intradermal immature dendritic cell vaccination in metastatic melanoma is associated with immune response to particulate antigen

Metastatic melanoma is poorly responsive to treatment, and immunotherapeutic approaches are potentially beneficial. Predictors of clinical response are needed to identify suitable patients. We sought factors associated with melanoma-specific clinical response following intradermal vaccination with autologous melanoma peptide and particulate hepatitis B antigen (HBsAg)-exposed immature monocyte-derived dendritic cells (MDDC). Nineteen patients with metastatic melanoma received a maximum of 8, 2-weekly vaccinations of DC, exposed to HBsAg in addition to autologous melanoma peptides. A further 3 patients received an otherwise identical vaccine that did not include HBsAg. Patients were assessed 1-2 monthly for safety, disease volume, and cellular responses to HBsAg and melanoma peptide. There was no significant toxicity. Of 19 patients receiving HBsAg-exposed DC, 9 primed or boosted a cellular response to HBsAg, and 10 showed no HBsAg response. HBsAg-specific responses were associated with in vitro T cell responses to melanoma peptides and to phytohemagglutinin (PHA). Zero out of 10 non-HBsAg-responding and 4/9 HBsAg-responding patients achieved objective melanoma-specific clinical responses or disease stabilization- 1 complete and 2 partial responses and I case of stable disease (P=0.018). Development of melanoma-specific cellular immunity and T cell responsiveness to mitogen were greater in the group of patients responding to HBsAg. Therefore stimulation of an immune response to nominal particulate antigen was necessary when presented by melanoma peptide-exposed immature DC, to achieve clinical responses in metastatic melanoma. Since general immune competence may be a determinant of treatment response, it should be assessed in future trials on DC immunotherapy.

Durable complete clinical responses in a phase I/II trial using an autologous melanoma cell/dendritic cell vaccine

Advanced metastatic melanoma is incurable by standard treatments, but occasionally responds to immunotherapy. Recent trials using dendritic cells (DC) as a cellular adjuvant have concentrated on defined peptides as the source of antigens, and rely on foreign proteins as a source of help to generate a cell-mediated immune response. This approach limits patient accrual, because currently defined, non-mutated epitopes are restricted by a small number of human leucocyte antigens. It also fails to take advantage of mutated epitopes peculiar to the patient's own tumour, and of CD4(+) T lymphocytes as potential effectors of anti-tumour immunity. We therefore sought to determine whether a fully autologous DC vaccine is feasible, and of therapeutic benefit. Patients with American Joint Cancer Committee stage IV melanoma were treated with a fully autologous immunotherapy consisting of monocyte-derived DC, matured after culture with irradiated tumour cells. Of 19 patients enrolled into the trial, sufficient tumour was available to make treatments for 17. Of these, 12 received a complete priming phase of six cycles of either 0.9X10(6) or 5X10(6) DC/intradermal injection, at 2-weekly intervals. Where possible, treatment continued with the lower dose at 6-weekly intervals. The remaining five patients could not complete priming, due to progressive disease. Three of the 12 patients who completed priming have durable complete responses (average duration 3 5 months +), three had partial responses, and the remaining six had progressive disease (WHO criteria). Disease regression was not correlated with dose or with the development of delayed type hypersensitivity responses to intradermal challenge with irradiated, autologous tumour. However, plasma S-100B levels prior to the commencement of treatment correlated with objective clinical response (P = 0.05) and survival (log rank P < 0.001). The treatment had minimal side-effects and was well tolerated by all patients. Mature, monocyte-derived DC preparations exposed to appropriate tumour antigen sources can be reliably produced for patients with advanced metastatic melanoma, and in a subset of those patients with lower volume disease their repeated administration results in durable complete responses.

Follicular dendritic cell sarcoma associated with Castelmans disease presenting in the oral cavity

Follicular dendritic cell sarcoma (FDCS) is a rare intermediate grade malignant neoplasm of reticular dendritic origin. Castleman’s disease (CD) represents a non-neoplastic lymphoproliferative disorder with various clinical and morphological features. FDCS has been reported to be associated with CD. In this article, we describe the first case of follicular dendritic cell sarcoma associated with Castleman’s disease presenting in the oral cavity. Copyright © 2005 Elsevier Ltd All rights reserved.

The key role of CD40 ligand in overcoming tumor-induced dendritic cell dysfunction

Overcoming dendritic cell (DC) dysfunction is a prerequisite for successful active immunotherapy against breast cancer. CD40 ligand (CD40L), a key molecule in the interface between T-lymphocytes and DCs, seems to be instrumental in achieving that goal. Commenting on our data that CD40L protects circulating DCs from apoptosis induced by breast tumor products, Lenahan and Avigan highlighted the potential of CD40L for immunotherapy. We expand on that argument by pointing to additional findings that CD40L not only rescues genuine DCs but also functionally improves populations of immature antigen-presenting cells that fill the DC compartment in patients with breast cancer.

A key role for PTP1B in dendritic cell maturation, migration and T cell activation

Acknowledgements We thank the Iain Fraser Flow Cytometry Centre and the Medical Research Facility of the University of Aberdeen. We are grateful to Drs West, Zaru, and Davidson (University of Dundee) for the scientific discussion and technical assistance. Wethank Derek Mitchell (University of Dundee) for aiding with the quantification of focal contacts. Funding This work was supported by Saving Sight in Grampian and the Development Trust of the UoA (both to J.V.F.). Work on this project was partly funded by project grants from British Heart Foundation and European Foundation for the Study of Diabetes/Lilly diabetes programme grant (to M.D.).

A key role for PTP1B in dendritic cell maturation, migration and T cell activation

Acknowledgements We thank the Iain Fraser Flow Cytometry Centre and the Medical Research Facility of the University of Aberdeen. We are grateful to Drs West, Zaru, and Davidson (University of Dundee) for the scientific discussion and technical assistance. Wethank Derek Mitchell (University of Dundee) for aiding with the quantification of focal contacts. Funding This work was supported by Saving Sight in Grampian and the Development Trust of the UoA (both to J.V.F.). Work on this project was partly funded by project grants from British Heart Foundation and European Foundation for the Study of Diabetes/Lilly diabetes programme grant (to M.D.).

FdDCA : A Novel Fuzzy Deterministic Dendritic Cell Algorithm

Postprint

Demonstration of changes in plasma cell subsets in multiple myeloma.

Increases in free light chain (FLC) production are associated with disease progression in multiple myeloma (MM). Using a double immunofluorescence staining method to produce a differential count of plasma cells in bone marrow, single populations were demonstrated, containing intact monoclonal immunoglobulins (M-Igs) in 74% and FLCs only in 8% of cases. However, 18% contained a mixture of both cell populations. Progression from cells making intact M-Ig to cells restricted to FLC only production occurred in individual cases during the course of their disease. The presence of FLC only cells was associated with shortened survival.

Classification and clinical behavior of blastic plasmacytoid dendritic cell neoplasms according to their maturation-associated immunophenotypic profile

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare subtype of leukemia/lymphoma, whose diagnosis can be difficult to achieve due to its clinical and biological heterogeneity, as well as its overlapping features with other hematologic malignancies. In this study we investigated whether the association between the maturational stage of tumor cells and the clinico-biological and prognostic features of the disease, based on the analysis of 46 BPDCN cases classified into three maturation-associated subgroups on immunophenotypic grounds. Our results show that blasts from cases with an immature plasmacytoid dendritic cell (pDC) phenotype exhibit an uncommon CD56- phenotype, coexisting with CD34+ non-pDC tumor cells, typically in the absence of extramedullary (e.g. skin) disease at presentation. Conversely, patients with a more mature blast cell phenotype more frequently displayed skin/extramedullary involvement and spread into secondary lymphoid tissues. Despite the dismal outcome, acute lymphoblastic leukemia-type therapy (with central nervous system prophylaxis) and/or allogeneic stem cell transplantation appeared to be the only effective therapies. Overall, our findings indicate that the maturational profile of pDC blasts in BPDCN is highly heterogeneous and translates into a wide clinical spectrum -from acute leukemia to mature lymphoma-like behavior-, which may also lead to variable diagnosis and treatment.

Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is successful at detecting port scans.

The deterministic Dendritic Cell Algorithm

The Dendritic Cell Algorithm is an immune-inspired algorithm originally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to analyse due to the number of random-based elements. In this paper a deterministic version of the algorithm is proposed, implemented and tested using a port scan dataset to provide a controllable system. This version consists of a controllable amount of parameters, which are experimented with in this paper. In addition the effects are examined of the use of time windows and variation on the number of cells, both which are shown to influence the algorithm. Finally a novel metric for the assessment of the algorithms output is introduced and proves to be a more sensitive metric than the metric used with the original Dendritic Cell Algorithm.

Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.