Gene expression profiling of microdissected Hodgkin Reed-Sternberg cells correlates with treatment outcome in classical Hodgkin lymphoma.

In classical Hodgkin lymphoma (CHL), 20%-30% of patients experience relapse or progressive disease after initial treatment. The pathogenesis and biology of treatment failure are still poorly understood, in part because the molecular phenotype of the rare malignant Hodgkin Reed-Sternberg (HRS) cells is difficult to study. Here we examined microdissected HRS cells from 29 CHL patients and 5 CHL-derived cell lines by gene expression profiling. We found significant overlap of HL-specific gene expression in primary HRS cells and HL cell lines, but also differences, including surface receptor signaling pathways. Using integrative analysis tools, we identified target genes with expression levels that significantly correlated with genomic copy-number changes in primary HRS cells. Furthermore, we found a macrophage-like signature in HRS cells that significantly correlated with treatment failure. CSF1R is a representative of this signature, and its expression was significantly associated with progression-free and overall survival in an independent set of 132 patients assessed by mRNA in situ hybridization. A combined score of CSF1R in situ hybridization and CD68 immunohistochemistry was an independent predictor for progression-free survival in multivariate analysis. In summary, our data reveal novel insights into the pathobiology of treatment failure and suggest CSF1R as a drug target of at-risk CHL.

Genome-wide copy number analysis of Hodgkin Reed-Sternberg cells identifies recurrent imbalances with correlations to treatment outcome.

In classical Hodgkin lymphoma (cHL) the mechanisms underlying primary refractory disease and relapse remain unknown. To gain further insight into cHL pathogenesis and genomic changes linked to treatment response, we studied 53 cHL patients by array comparative genomic hybridization, including 23 patients whose primary treatment failed, using DNA from microdissected HRS cells. Copy number alterations found in more than 20% of cases included gains of 2p, 9p, 16p, 17q, 19q, 20q, and losses of 6q, 11q, and 13q. We identified at high resolution recurrent changes defining minimally gained and lost regions harboring genes involved in nuclear factor kappaB signaling, such as REL, IKBKB, CD40, and MAP3K14. Gains of chromosome 16p11.2-13.3 were significantly more frequent in pretreatment and relapse biopsies of unresponsive patients and were associated with shortened disease-specific survival (P = .028). In the therapy-resistant HL cell line KMH2, we found genomic gains and overexpression of the multidrug resistance gene ABCC1 mapping to cytoband 16p13.11. We show that doxorubicin exposure to KMH2 induces ABCC1 expression and that siRNA silencing of ABCC1 sensitizes KMH2 cells to doxorubicin toxicity in vitro, suggesting that overexpression of ABCC1 contributes to the drug resistance phenotype found in KMH2.

Sequence variant discovery in DNA repair genes from radiosensitive and radiotolerant prostate brachytherapy patients.

PURPOSE: The presence of intrinsic radiosensitivity within prostate cancer patients may be an important factor contributing to development of radiation toxicity. We investigated whether variants in genes responsible for detecting and repairing DNA damage independently contribute to toxicity following prostate brachytherapy. EXPERIMENTAL DESIGN: Genomic DNA was extracted from blood samples of 41 prostate brachytherapy patients, 21 with high and 20 with low late toxicity scores. For each patient, 242 PCR amplicons were generated containing 173 exons of eight candidate genes: ATM, BRCA1, ERCC2, H2AFX, LIG4, MDC1, MRE11A, and RAD50. These amplicons were sequenced and all sequence variants were subjected to statistical analysis to identify those associated with late radiation toxicity. RESULTS: Across 41 patients, 239 sites differed from the human genome reference sequence; 170 of these corresponded to known polymorphisms. Sixty variants, 14 of them novel, affected protein coding regions and 43 of these were missense mutations. In our patient population, the high toxicity group was enriched for individuals with at least one LIG4 coding variant (P = 0.028). One synonymous variant in MDC1, rs28986317, was associated with increased radiosensitivity (P = 0.048). A missense variant in ATM, rs1800057, associated with increased prostate cancer risk, was found exclusively in two high toxicity patients but did not reach statistical significance for association with radiosensitivity (P = 0.488). CONCLUSIONS: Our data revealed new germ-line sequence variants, indicating that existing sequence databases do not fully represent the full extent of sequence variation. Variants in three DNA repair genes were linked to increased radiosensitivity but require validation in larger populations.

Epithelial-mesenchymal transition (EMT) is not sufficient for spontaneous murine breast cancer metastasis.

Epithelial-mesenchymal transition (EMT) has been linked to metastatic propensity. The 4T1 tumor is a clinically relevant model of spontaneous breast cancer metastasis. Here we characterize 4T1-derived cell lines for EMT, in vitro invasiveness and in vivo metastatic ability. Contrary to expectations, 67NR cells, which form primary tumors but fail to metastasize, express vimentin and N-cadherin, but not E-cadherin. 4T1 cells express E-cadherin and ZO-1, but are migratory, invasive, and metastasize to multiple sites. 66cl4 cells form lung metastases and display a mixed phenotype, but are not as migratory or invasive as 67NR cells. These findings demonstrate that the metastatic ability of breast cancer cells does not strictly correlate with genotypic and phenotypic properties of EMT per se, and suggest that other processes may govern metastatic capability. Gene expression analysis of primary tumors did not identify differences in EMT markers, but did reveal candidate genes that may influence metastatic ability.

Correlations of EGFR mutations and increases in EGFR and HER2 copy number to gefitinib response in a retrospective analysis of lung cancer patients.

BACKGROUND: Gefitinib, a small molecule tyrosine kinase inhibitor of the Epidermal Growth Factor Receptor (EGFR), has shown limited efficacy in the treatment of lung cancer. Recognized clinical predictors of response to this drug, specifically female, non-smoker, Asian descent, and adenocarcinoma, together suggest a genetic basis for drug response. Recent studies have addressed the relationship between response and either sequence mutations or increased copy number of specific receptor tyrosine kinases. We set out to examine the relationship between response and the molecular status of two such kinases, EGFR and HER2, in 39 patients treated with gefitinib at the BC Cancer Agency. METHODS: Archival patient material was reviewed by a pathologist and malignant cells were selectively isolated by laser microdissection or manual recovery of cells from microscope slides. Genomic DNA was extracted from 37 such patient samples and exons 18-24, coding for the tyrosine kinase domain of EGFR, were amplified by PCR and sequenced. EGFR and HER2 copy number status were also assessed using FISH in 26 samples. Correlations between molecular features and drug response were assessed using the two-sided Fisher's exact test. RESULTS: Mutations previously correlated with response were detected in five tumours, four with exon 19 deletions and one with an exon 21 missense L858R point mutation. Increased gene copy number was observed in thirteen tumours, seven with EGFR amplification, three with HER2 amplification, and three with amplification of both genes. In our study cohort, a correlation was not observed between response and EGFR mutations (exon 19 deletion p = 0.0889, we observed a single exon 21 mutation in a non-responder) or increases in EGFR or HER2 copy number (p = 0.552 and 0.437, respectively). CONCLUSION: Neither mutation of EGFR nor increased copy number of EGFR or HER2 was diagnostic of response to gefitinib in this cohort. However, validation of these features in a larger sample set is appropriate. Identification of additional predictive biomarkers beyond EGFR status may be necessary to accurately predict treatment outcome.