Advanced Malignant Melanoma: Immunologic and Multimodal Therapeutic Strategies

Immunologic treatment strategies are established in malignant melanoma treatment, mainly focusing on Interleukin-2 in advanced disease and interferon alpha in the adjuvant situation. In advanced disease, therapies with IL-2, interferon and different chemotherapeutic agents were not associated with better patient survival in the vast majority of patients. Therefore, an overview of novel immunological agents and combined therapeutic approaches is presented in this review, covering allogenic and autologous vaccine strategies, dendritic cell vaccination, strategies for adoptive immunotherapy and T cell receptor gene transfer, treatment with cytokines and monoclonal antibodies against the CTLA-4 antigen. As emerging treatment strategies are based on individual molecular and immunological characterization of individual tumors/patients, tailored targeted drug therapies move into the focus of treatment strategies. Multimodal combination therapies with considerable potential in altering the immune response in malignant melanoma patients are currently emerging. As oncology moves forward into the field of personalized therapies, a careful molecular and immunological characterization of patients is crucial to select patients for individual targeted treatment

Estimation of Immune Cell Densities in Immune Cell Conglomerates: An Approach for High-Throughput Quantification

Determining the correct number of positive immune cells in immunohistological sections of colorectal cancer and other tumor entities is emerging as an important clinical predictor and therapy selector for an individual patient. This task is usually obstructed by cell conglomerates of various sizes. We here show that at least in colorectal cancer the inclusion of immune cell conglomerates is indispensable for estimating reliable patient cell counts. Integrating virtual microscopy and image processing principally allows the high-throughput evaluation of complete tissue slides.For such large-scale systems we demonstrate a robust quantitative image processing algorithm for the reproducible quantification of cell conglomerates on CD3 positive T cells in colorectal cancer. While isolated cells (28 to 80 microm(2)) are counted directly, the number of cells contained in a conglomerate is estimated by dividing the area of the conglomerate in thin tissues sections (< or =6 microm) by the median area covered by an isolated T cell which we determined as 58 microm(2). We applied our algorithm to large numbers of CD3 positive T cell conglomerates and compared the results to cell counts obtained manually by two independent observers. While especially for high cell counts, the manual counting showed a deviation of up to 400 cells/mm(2) (41% variation), algorithm-determined T cell numbers generally lay in between the manually observed cell numbers but with perfect reproducibility.In summary, we recommend our approach as an objective and robust strategy for quantifying immune cell densities in immunohistological sections which can be directly implemented into automated full slide image processing systems

Exemplary workflow for the described algorithm.

<p>Stained immune cells are either counted individually (where possible) or the number of cells is estimated by the conglomerate surface. Both results are added.</p

Impact of cell counts from conglomerates on total cell counts in 10 individual 1 mm² fields from sections of 10 different patients.

<p>Omitting conglomerates in the quantification would substantially distort the total cell counts.</p

Cell counts of T cells (CD3+) in thirty different fields of 1 mm² size.

<p>Fields with maximum differences between manual cell counts are highlighted.</p><p>Abs. Diff. Man. = Absolute Difference between Manual1 and Manual2, % Diff. Man. = Percentage Difference between Manual1 and Manual2.</p

Repeated quantification (six times) of a large conglomerate by one observer.

<p>Triangles show single values for each repetition and thin vertical lines indicate range, thick horizontal line indicates average value.</p