We recently showed that sentinel lymph node (SLN) disaggregation followed by immunocytology enables precise quantification of disseminated cancer cells (DCC). We demonstrated that this approach has a 20-fold higher sensitivity to detect melanoma DCCs than routine histopathology and that the DCC density (DCCD, defined as the number of DCCs per million lymph node cells) together with ulceration state and tumor thickness enables individual risk prediction superior to current AJCC guidelines (Ulmer et al., PLoS Medicine, 2014). Here, we present the adaptation of this method to a semi-automated workflow, including automated single cell detection and isolation by DEPArrayTM technology for subsequent molecular analysis of DCCs from SLN of melanoma patients.

The developed workflow includes a mechanical disaggregation of lymph node tissue and collection of the mononuclear cells after Percoll density centrifugation. Several tumor cell enrichment methods were tested (CellSearch® and size-based enrichment technologies), however, failed to process cell suspensions generated from lymph nodes due to clumping of cells during the enrichment procedure. Tumor cell enrichment using MACS depletion of CD45+ cells delivered approx. 50% of spiked-in cell line cells with a mean depletion rate of lymphocytes and erythrocytes > 98%. To prevent limitations in DCC detection caused by phenotypic heterogeneity of tumor cells, we established a double staining against two melanoma-associated markers gp100 and MCSP. Individual melanoma cells are then detected and isolated by DEPArrayTM technology enabling single cell whole genome amplification (Ampli1TM) for subsequent molecular analysis as assessment of copy number alterations (e.g. by arrayCGH) or sequence analysis for melanoma specific point mutations (e.g. BRAF or NRAS). We successfully applied the workflow to first SLN samples from melanoma patients.

The established workflow enables a standardized detection of single DCCs from lymph nodes of melanoma patients applicable in clinical diagnostic labs. Automated single cell isolation and subsequent molecular analysis of DCCs is feasible within short time after SLN biopsy. In the future, this approach could help to select individualized therapies for melanoma patients.

Citation Format: Sebastian Scheitler, Kathrin Weidele, Barbara Alberter, Christian Werno, Christoph A. Klein, Bernhard Polzer. A digital sorting-based detection and isolation assay for single disseminated cancer cells from lymph nodes of melanoma patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 472.