Human XCR1+ dendritic cells derived in vitro from CD34+ progenitors closely resemble blood dendritic cells, including their adjuvant responsiveness, contrary to monocyte-derived dendritic cells.

Human monocyte-derived dendritic cell (MoDC) have been used in the clinic with moderately encouraging results. Mouse XCR1(+) DC excel at cross-presentation, can be targeted in vivo to induce protective immunity, and share characteristics with XCR1(+) human DC. Assessment of the immunoactivation potential of XCR1(+) human DC is hindered by their paucity in vivo and by their lack of a well-defined in vitro counterpart. We report in this study a protocol generating both XCR1(+) and XCR1(-) human DC in CD34(+) progenitor cultures (CD34-DC). Gene expression profiling, phenotypic characterization, and functional studies demonstrated that XCR1(-) CD34-DC are similar to canonical MoDC, whereas XCR1(+) CD34-DC resemble XCR1(+) blood DC (bDC). XCR1(+) DC were strongly activated by polyinosinic-polycytidylic acid but not LPS, and conversely for MoDC. XCR1(+) DC and MoDC expressed strikingly different patterns of molecules involved in inflammation and in cross-talk with NK or T cells. XCR1(+) CD34-DC but not MoDC efficiently cross-presented a cell-associated Ag upon stimulation by polyinosinic-polycytidylic acid or R848, likewise to what was reported for XCR1(+) bDC. Hence, it is feasible to generate high numbers of bona fide XCR1(+) human DC in vitro as a model to decipher the functions of XCR1(+) bDC and as a potential source of XCR1(+) DC for clinical use.

RNA extracted from blood samples with a rapid automated procedure is fit for molecular diagnosis or minimal residual disease monitoring in patients with a variety of malignant blood disorders.

Scientific studies in oncology, cancer diagnosis, and monitoring tumor response to therapeutics currently rely on a growing number of clinico-pathological information. These often include molecular analyses. The quality of these analyses depends on both pre-analytical and analytical information and often includes the extraction of DNA and/or RNA from human tissues and cells. The quality and quantity of obtained nucleic acids are of utmost importance. The use of automated techniques presents several advantages over manual techniques, such as reducing technical time and thus cost, and facilitating standardization. The purpose of this study was to validate an automated technique for RNA extraction from cells of patients treated for various malignant blood diseases. A well-established manual technique was compared to an automated technique, in order to extract RNA from blood samples drawn for the molecular diagnosis of a variety of leukemic diseases or monitoring of minimal residual disease. The quality of the RNA was evaluated by real-time quantitative RT-PCR (RQ-PCR) analyses of the Abelson gene transcript. The results show that both techniques produce RNA with comparable quality and quantity, thus suggesting that an automated technique can be substituted for the reference and manual technique used in the daily routine of a molecular pathology laboratory involved in minimal residual disease monitoring. Increased costs of reagents and disposables used for automated techniques can be compensated by a decrease in human resource.

Loss of heterozygosity at microsatellite markers from region p11-21 of chromosome 8 in microdissected breast tumor but not in peritumoral cells.

Alterations of chromosomal region 8p11-21 are very frequent in human cancers, and especially in breast cancer; yet, most of the genes involved have not been identified. We performed laser capture microdissection in a series of 52 consecutive breast tumor samples to obtain pure tumor cells without surrounding normal breast. To determine genomic subregions in which some of the cancer genes may be located, we conducted a search for loss of heterozygosity (LOH) at 13 microsatellite markers from this region. Two-thirds of the tumors showed LOH at least at one marker. Microdissection of pure tumor samples was helpful to precisely define four LOH subregions. No LOH was observed in the corresponding peritumoral tissues. We studied by immunohistochemistry (IHC) on tissue-microarrays the expression in the same tumors, of the protein product of three potential tumor genes lying close to or within the subregions of LOH. In most samples, the TACC1 gene product was downregulated in tumor cells as compared to normal cells. Our results show that the centromeric portion of chromosome arm 8p is frequently altered in breast tumor cells.

Distinct and complementary information provided by use of tissue and DNA microarrays in the study of breast tumor markers.

Emerging high-throughput screening technologies are rapidly providing opportunities to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. Currently, cDNA arrays allow the quantitative measurement of thousands of mRNA expression levels simultaneously. Validation of this tool in hospital settings can be done on large series of archival paraffin-embedded tumor samples using the new technique of tissue microarray. On a series of 55 clinically and pathologically homogeneous breast tumors, we compared for 15 molecules with a proven or suspected role in breast cancer, the mRNA expression levels measured by cDNA array analysis with protein expression levels obtained using tumor tissue microarrays. The validity of cDNA array and tissue microarray data were first verified by comparison with quantitative reverse transcriptase-polymerase chain reaction measurements and immunohistochemistry on full tissue sections, respectively. We found a good correlation between cDNA and tissue array analyses in one-third of the 15 molecules, and no correlation in the remaining two-thirds. Furthermore, protein but not RNA levels may have prognostic value; this was the case for MUC1 protein, which was studied further using a tissue microarray containing approximately 600 tumor samples. For THBS1 the opposite was observed because only RNA levels had prognostic value. Thus, differences extended to clinical prognostic information obtained by the two methods underlining their complementarity and the need for a global molecular analysis of tumors at both the RNA and protein levels.