Primary extramedullary plasmacytomas are infrequent, typically solitary, plasma cell neoplasms that generally pursue an indolent clinical course but may, rarely, convert to multiple myeloma. Phenotypic differences between these two entities are not well defined. Twenty-eight cases of primary extramedullary plasmacytoma and 26 cases of both medullary (n = 17) and extramedullary (n = 9) multiple myeloma were analysed for the expression of proteins known to play a role in the biology of multiple myeloma. Immunohistochemistry was performed on paraffin wax sections using antibodies against cyclin D1, Bcl-2, Bcl-xL, p27, p21, p53, MIB1, CD20, and CD56. Twenty-three extramedullary plasmacytomas were localized in the upper aerodigestive tract, four in the lymph nodes, and one in the testis. There was a strong male predominance (M : F = 6 : 1). None of the patients died from the disease or progressed to multiple myeloma (mean follow-up 50 months). Nine patients developed local relapse and one patient's tumour evolved into a B-cell non-Hodgkin's lymphoma. In contrast to both intra- and extra-medullary multiple myeloma, extramedullary plasmacytoma showed absence of cyclin D1 (p < 0.001) and infrequent expression of CD56 (p < 0.001). Furthermore, extramedullary plasmacytomas were characterized by weaker staining for Bcl-2 protein and rare overexpression of p21 and p53. In comparison to extramedullary multiple myeloma, extramedullary plasmacytoma showed a more mature morphology and lower proliferation indices (p = 0.008). There was no association between the phenotypic parameters investigated and clinical outcome in extramedullary plasmacytoma. In summary, extramedullary plasmacytoma and multiple myeloma show significant immunophenotypic differences, some of which may be of both diagnostic utility and biological relevance.

Discordant bone marrow (BM) involvement in patients with a diagnosis of large-cell non-Hodgkin's lymphoma (NHL) is characterized by marrow infiltrates predominantly composed of small lymphoid cell, cytologically compatible with low-grade NHL. Although this phenomenon is well described morphologically, molecular data concerning the relationship of the two lesions are lacking. The aim of the study was to investigate the clonal relationship of discordant lymphoma manifestations by using immunoglobulin heavy chain gene (IgH), as well as bcl-2 rearrangements, as molecular markers. IgH rearrangements were amplified by PCR with consensus primers directed against framework regions 3 or 2 (FR3 and FR2), followed by automated fragment length analysis and sequencing in selected cases. Rearrangements of the bcl-2 gene were identified with primers against the major breakpoint region. Small BM infiltrates were isolated by laser capture microdissection. In addition, immunohistochemistry was performed on paraffin sections using antibodies against CD3, CD10, CD20, bcl-2, bcl-6, p53, and the Ki67 antigen. Paraffin-embedded tissues of 21 cases diagnosed as diffuse large B-cell lymphoma (DLBCL) with discordant BM involvement and no previous history of low-grade B-cell NHL were analyzed. After review of immunohistochemical stains, 5 cases were excluded either as concordant BM infiltrates by large-cell lymphoma with abundant reactive T-cells (2 cases) or as benign, reactive lymphoid infiltrates (3 cases), as confirmed by a polyclonal pattern in the IgH analysis. Of the remaining 16 cases, a common clonal origin was confirmed in 8 cases by the presence of an identical clonal IgH rearrangement or bcl-2 rearrangement. In 4 cases, identification of distinct IgH or bcl-2 rearrangements gave evidence for the presence of two clonally unrelated neoplasms. The remaining 4 cases were not evaluable for technical reasons. Morphological, phenotypical, and molecular findings were compatible with a lymphoma of germinal center origin in the majority of cases. However, in 4 cases, flow cytometric analysis of the BM infiltrates revealed a B-cell chronic lymphocytic leukemia phenotype. Two of these cases were clonally related to the DLBCL and thus represented Richter's transformation. In summary, discordant BM infiltrates in DLBCL represent a heterogeneous group of disorders, encompassing cases with a clonally related, clinically occult small-cell component, as well as cases with two clonally distinct, unrelated B-cell neoplasms presenting synchronously at different locations.

To advance preclinical testing of novel targeted drugs in colorectal cancer (CRC) we established a panel of 133 mouse xenograft models from fresh tumor specimens of 239 patients with CRC of all four UICC stages. A subgroup of 67 xenograft models was treated with cetuximab, bevacizumab and oxaliplatin as single agents. Mutation status of KRAS (G12, G13, A146T), BRAF (V600E) and PIK3CA (E542K, E545K, H1047R) was assessed in all xenografts by allelespecific real-time PCR. KRAS codon 61 was assessed by conventional sequencing. AREG and EREG expression levels were analyzed by real-time PCR expression assays. In the treatment experiment we observed response rates of 27% (18/67) for cetuximab, 3% (2/67) for bevacizumab, and 6% (4/67) for oxaliplatin. Classification based on KRAS, BRAF and PIK3CA mutation status identified 15 of the responders (sensitivity 83%, confidence interval at p = 0.05 (CI): 59% -96%), and 38 nonresponders (specificity 78%, CI: 63% -88%). If any mutation except in KRAS codon 13 were considered, the classifier reached sensitivity of 94% and specificity of 69%. We improved specificity of the classifiers to 90% and 86% respectively by adding AREG and EREG RNA expression thresholds retrospectively. In patient-derived xenograft models, we found a predictive classifier for response to cetuximab that is more accurate than established biomarkers. We confirmed its potential performance in primary human tumors. For patients, the classifier's sensitivity promises increased response rates and its specificity limits unnecessary toxicity. Given the scope of our xenograft models across all UICC stages, this applies not only to mCRC but also to the adjuvant setting of earlier stages. The xenograft collection allows to mimic randomized phase II trials and to test novel drugs effectively as single agents or in combinations. It also enables the development of highly accurate companion diagnostics as demonstrated by us for cetuximab.

Pancreatic ductal adenocarcinoma (PDAC) is a tumor with an extremely poor prognosis, predominantly as a result of chemotherapy resistance and numerous somatic mutations. Consequently, PDAC is a prime candidate for the use of sequencing to identify causative mutations, facilitating subsequent administration of targeted therapy. In a feasibility study, we retrospectively assessed the therapeutic recommendations of a novel, evidence‐based software that analyzes next‐generation sequencing (NGS) data using a large panel of pharmacogenomic biomarkers for efficacy and toxicity. Tissue from 14 patients with PDAC was sequenced using NGS with a 620 gene panel. FASTQ files were fed into treatmentmap. The results were compared with chemotherapy in the patients, including all side effects. No changes in therapy were made. Known driver mutations for PDAC were confirmed (e.g. KRAS,TP53). Software analysis revealed positive biomarkers for predicted effective and ineffective treatments in all patients. At least one biomarker associated with increased toxicity could be detected in all patients. Patients had been receiving one of the currently approved chemotherapy agents. In two patients, toxicity could have been correctly predicted by the software analysis. The results suggest that NGS, in combination with an evidence‐based software, could be conducted within a 2‐week period, thus being feasible for clinical routine. Therapy recommendations were principally off‐label use. Based on the predominant KRAS mutations, other drugs were predicted to be ineffective. The pharmacogenomic biomarkers indicative of increased toxicity could be retrospectively linked to reported negative side effects in the respective patients. Finally, the occurrence of somatic and germline mutations in cancer syndrome‐associated genes is noteworthy, despite a high frequency of these particular variants in the background population. These results suggest software‐analysis of NGS data provides evidence‐based information on effective, ineffective and toxic drugs, potentially forming the basis for precision cancer medicine in PDAC.

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