Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women.

BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Characterization of bone marrow-derived mesenchymal stromal cells (MSC) based on gene expression profiling of functionally defined MSC subsets.

BACKGROUND AIMS: Human mesenchymal stromal cells (MSC) are promising candidates for cell therapy because of their intriguing properties (high proliferation and differentiation capacity, microenvironmental function and immune modulation). However, MSC are heterogeneous and a better understanding of the heterogeneity of the cells that form the MSC cultures is critical. METHODS: Human MSC were generated in standard cultures and stained with carboxyfluorescein succinimidyl ester (CFSE) for cell division tracking. Gene expression profiling of MSC that were sorted based on functional parameters (i.e. proliferation characteristics) was utilized to characterize potential MSC subpopulations (progenitor content and differentiation capacity) and identify potential MSC subpopulation markers. RESULTS: The majority of MSC had undergone more than two cell divisions (79.7+/-2.0%) after 10 days of culture, whereas 3.5+/-0.9% of MSC had not divided. MSC were then sorted into rapidly dividing cells (RDC) and slowly/non-dividing cells (SDC/NDC). Colony-forming unit-fibroblast (CFU-F) frequencies were lowest in NDC and highest in RDC with low forward-/side-scatter properties (RDC(lolo)). Comparative microarray analysis of NDC versus RDC identified 102 differentially expressed genes. Two of these genes (FMOD and VCAM1) corresponded to cell-surface molecules that enabled the prospective identification of a VCAM1(+)/FMOD(+) MSC subpopulation, which increased with passage and showed very low progenitor activity and limited differentiation potential. CONCLUSIONS: These data clearly demonstrate functional differences within MSC cultures. Furthermore, this study shows that cell sorting based on proliferation characteristics and gene expression profiling can be utilized to identify surface markers for the characterization of MSC subpopulations.

Genes associated with the tumour microenvironment are differentially expressed in cured versus primary chemotherapy-refractory diffuse large B-cell lymphoma.

In order to identify genes associated with primary chemotherapy-resistance, gene expression profiles (GEP) in tumour tissue from 37 patients with de novo diffuse large B-cell lymphoma (DLBCL), stage II-IV, either in continuous complete remission (n = 24) or with progressive disease during primary treatment (n = 13), were examined using spotted 55K oligonucleotide arrays. Immunohistochemistry was used for confirmation at the protein level. The top 86 genes that best discriminated between the two cohorts were chosen for further analysis. Only seven of 86 genes were overexpressed in the refractory cohort, e.g. RABGGTB and POLE, both potential targets for drug intervention. Seventy-nine of 86 genes were overexpressed in the cured cohort and mainly coded for proteins expressed in the tumour microenvironment, many of them involved in proteolytic activity and remodelling of extra cellular matrix. Furthermore, major histocompatibility complex class I molecules, CD3D and ICAM1 were overexpressed, indicating an enhanced immunological reaction. Immunohistochemistry confirmed the GEP results. The frequency of tumour infiltrating lymphocytes, macrophages, and reactive cells expressing ICAM-1, lysozyme, cathepsin D, urokinase plasminogen activator receptor, signal transducer and activator of transcription 1, and galectin-3 was higher in the cured cohort. These findings indicate that a reactive microenvironment has an impact on the outcome of chemotherapy in DLBCL.