Prediction of key milk biomarkers in dairy cows through milk mid-infrared spectra and international collaborations.

At the individual cow level, suboptimum fertility, mastitis, negative energy balance, and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were (1) to assess the potential of milk mid-infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6 phosphate [glucose-6P], free glucose), ketosis (ß-hydroxybutyrate [BHB] and acetone), mastitis (N-acetyl-ß-d-glucosaminidase activity [NAGase] and lactate dehydrogenase), and fertility (progesterone); (2) to test alternative methodologies to partial least squares (PLS) regression to better account for the specific asymmetric distribution of the biomarkers; and (3) to create robust models by merging large datasets from 5 international or national projects. Benefiting from this international collaboration, the dataset comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents, whereas the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. Partial least squares regression was used as the reference basis, and compared with a random modification of distribution associated with PLS (random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS), and support vector machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low versus high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation dataset. The remaining 80% of herds were used as the calibration dataset. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose, and lactate dehydrogenase (coefficient of determination in external herd validation [R2v] = 0.48, 0.58, 0.28, and 0.24, respectively). For other molecules, PLS-random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase, and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15, respectively). Hence, PLS and SVM based on the entire dataset provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis, and mastitis in dairy cows, which in turn have major influences on their fertility and survival.

MiRNome variations in milk fractions during feed restrictions of different intensities in dairy cows.

BACKGROUND: In dairy cows, diet is one factor that can affect their milk production and composition. However, the effect of feed restriction on milk miRNome has not yet been described. Indeed, milk is the body fluid with the highest RNA concentration, which includes numerous microRNA. Its presence in the four different milk fractions, whole milk, fat globules, mammary epithelial cells and extracellular vesicles, is still poorly documented. This study aimed to describe the effects of different feed restrictions on the miRNome composition of different milk fractions. RESULTS: Two feed restrictions were applied to lactating dairy cows, one of high intensity and one of moderate intensity. 2,896 mature microRNA were identified in the different milk fractions studied, including 1,493 that were already known in the bovine species. Among the 1,096 microRNA that were sufficiently abundant to be informative, the abundance of 1,027 of them varied between fractions: 36 of those were exclusive to one milk fraction. Feed restriction affected the abundance of 155 microRNA, with whole milk and milk extracellular vesicles being the most affected, whereas milk fat globules and exfoliated mammary epithelial cells were little or not affected at all. The high intensity feed restriction led to more microRNA variations in milk than moderate restriction. The target prediction of known microRNA that varied under feed restriction suggested the modification of some key pathways for lactation related to milk fat and protein metabolisms, cell cycle, and stress responses. CONCLUSIONS: This study highlighted that the miRNome of each milk fraction is specific, with mostly the same microRNA composition but with variations in abundance between fractions. These specific miRNomes were affected differently by feed restrictions, the intensity of which appeared to be a major factor modulating milk miRNomes. These findings offer opportunities for future research on the use of milk miRNA as biomarkers of energy status in dairy cows, which is affected by feed restrictions.

Regression trees to identify combinations of farming practices that achieve the best overall intrinsic quality of milk.

Many studies over the last 30 years have shown the effects of farming practices on milk compounds. Combinations of practices may have antagonistic or synergistic effects on milk compounds, but these combination effects remain underinvestigated. Research needs to focus on overall intrinsic milk quality (including sensory, technological, health, and nutritional dimensions) and identify the combinations that can optimize it. The aim of this study was to identify which combinations of farming practices achieved the best scores for sensory, technological, health, and nutritional dimensions and for overall intrinsic milk quality. Ninety-nine private farms were visited once each to sample their bulk tank milk and survey their farming practices. The surveyed practices concerned herd characteristics, feeding management, housing conditions, and milking and milk storage conditions on the day of test. Analyses of bulk tank milk were designed to evaluate the overall intrinsic quality of the milk for 2 target products: raw milk cheese and semi-skimmed UHT milk. Regression trees were then used to identify the combinations of farming practices that achieved the best scores on each dimension and on overall intrinsic quality of the milk. Breed and diet (type of forage) were the most influential factors for sensory and health dimensions and for technological and nutritional dimension scores, respectively, in the cheese assessment. Overall cheese quality was highly positively correlated with these 4 dimension scores. Therefore, breed and diet emerged as the most influential practices in the regression tree for overall cheese quality. However, the combinations of practices that resulted in the best quality scores differed according to dimension studied and product targeted. This suggests that advice on farming practices to improve intrinsic milk quality needs to be adapted according to the end-purpose of the collected milk. This innovative approach combining on-farm data and regression trees provides farm managers with a valuable and practical tool to prioritize practices in terms of their role in shaping milk quality, and to identify the combinations of practices that promote good milk quality and practice thresholds or modalities needed to achieve it.

Milk proteins as a feed restriction signature indicating the metabolic adaptation of dairy cows.

Milk production in dairy cows is affected by numerous factors, including diet. Feed restriction is known to have little impact on milk total protein content but its effect on the fine protein composition is still poorly documented. The objective of this study was to describe the effects of two feed restriction trials of different intensities on the milk protein composition of Holstein cows. One restriction trial was of high intensity (H: 8 mid-lactation Holstein cows) and the second of moderate intensity (M: 19 peak lactation Holstein cows). Feed restriction decreased the milk protein yield for caseins under the M trial and of all six major milk proteins under the H trial. These decreased yields lead to lower concentrations of αs1-, αs2- and ß-caseins during the H trial. The milk proteome, analyzed on 32 milk samples, was affected as a function of restriction intensity. Among the 345 proteins identified eight varied under the M trial and 160 under the H trial. Ontology analyses revealed their implication in carbohydrate, lipid and protein metabolisms as well as in the immune system. These proteins reflected adaptations of the animal and mammary gland physiology to feed restriction and constituted a signature of this change.

Characterization of the nongenetic causes of variation in the calcium content of bovine milk on French farms.

Milk is an important source of Ca in Western diets. Milk Ca is important for the cheesemaking process and could be a useful biomarker of Ca regulation in cows. The objective of this study was to identify and quantify nongenetic factors affecting the variation of Ca content in bovine milk. During the PhénoFinLait program, a survey was performed in 3 major areas of milk production in France. This survey consisted of collecting milk samples, together with information about herd management and cow nutrition, from 924 commercial farms. More than 200,000 individual milk samples were collected, and Ca content was measured by mid-infrared spectroscopy. Each farm was surveyed several times during the year, and 3 to 6 milk samples were collected from each cow. An equation to predict milk Ca content from mid-infrared spectra was developed based on the Ca contents of 292 milk samples, and the milk Ca contents of the 200,000 samples were then predicted. Milk Ca content was lowest in Holstein cows, intermediate in Montbéliarde cows, and highest in Normande cows. For all 3 breeds, milk Ca decreased during the first month of lactation and increased after the fourth month of lactation, with the range between minimum and maximum values largest in Holsteins, intermediate in Montbéliardes, and smallest in Normandes. Milk Ca content also decreased with parity in all 3 breeds. By using multiple factorial analysis, 6 major feeding strategies employed on French dairy farms were characterized based on the data from the survey. Calendar month and cow feeding strategy affected milk Ca content, which dropped in the spring during grazing turnout and was lower when cows were fed fresh and conserved grass rather than corn silage. In conclusion, environmental factors induce variations in milk Ca content in addition to the genetics of the cows, which to date have been identified as a main factor of variation of milk Ca content in dairy cows. In several of the tested conditions, increases in milk production and in the amount of Ca daily secreted in milk were associated with a decrease in milk Ca content as though the mammary gland operated to limit the exportation of Ca when milk production rapidly increased. This result would suggest that milk Ca content could be a biomarker of Ca regulation in dairy cows.

Short communication: Genetic parameters for milk protein composition predicted using mid-infrared spectroscopy in the French Montbéliarde, Normande, and Holstein dairy cattle breeds.

Genetic parameters for the major milk proteins were estimated in the 3 main French dairy cattle breeds (i.e. Montbéliarde, Normande, and Holstein) as part of the PhénoFinlait program. The 6 major milk protein contents as well as the total protein content (PC) were estimated from mid-infrared spectrometry on 133,592 test-day milk samples from 20,434 cows in first lactation. Lactation means, expressed as a percentage of milk (protein contents) or of protein (protein fractions), were analyzed with an animal mixed model including fixed environmental effects (herd, year × month of calving, and spectrometer) and a random genetic effect. Genetic parameter estimates were very consistent across breeds. Heritability estimates (h2) were generally higher for protein fractions than for protein contents. They were moderate to high for αS1-casein, αS2-casein, ß-casein, κ-casein, and α-lactalbumin (0.25 < h2 < 0.72). In each breed, ß-lactoglobulin was the most heritable trait (0.61 < h2 < 0.86). Genetic correlations (rg) varied depending on how the percentage was expressed. The PC was strongly positively correlated with protein contents but almost genetically independent from protein fractions. Protein fractions were generally in opposition, except between κ-casein and α-lactalbumin (0.39 < rg < 0.46) and κ-casein and αS2-casein (0.36 < rg < 0.49). Between protein contents, rg estimates were positive, with highest values found between caseins (0.83 < rg < 0.98). In the 3 breeds, ß-lactoglobulin was negatively correlated with caseins (-0.75 < rg < -0.08), in particular with κ-casein (-0.75 < rg < -0.55). These results, obtained from a large panel of cows of the 3 main French dairy cattle breeds, show that routinely collected mid-infrared spectra could be used to modify milk protein composition by selection.

Whole-genome scan to detect quantitative trait loci associated with milk protein composition in 3 French dairy cattle breeds.

In the context of the PhénoFinLait project, a genome-wide analysis was performed to detect quantitative trait loci (QTL) that affect milk protein composition estimated using mid-infrared spectrometry in the Montbéliarde (MO), Normande (NO), and Holstein (HO) French dairy cattle breeds. The 6 main milk proteins (α-lactalbumin, ß-lactoglobulin, and αS1-, αS2-, ß-, and κ-caseins) expressed as grams per 100g of milk (% of milk) or as grams per 100g of protein (% of protein) were estimated in 848,068 test-day milk samples from 156,660 cows. Genotyping was performed for 2,773 MO, 2,673 NO, and 2,208 HO cows using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Individual test-day records were adjusted for environmental effects and then averaged per cow to define the phenotypes analyzed. Quantitative trait loci detection was performed within each breed using a linkage disequilibrium and linkage analysis approach. A total of 39 genomic regions distributed on 20 of the 29 Bos taurus autosomes (BTA) were significantly associated with milk protein composition at a genome-wide level of significance in at least 1 of the 3 breeds. The 9 most significant QTL were located on BTA2 (133 Mbp), BTA6 (38, 47, and 87 Mbp), BTA11 (103 Mbp), BTA14 (1.8 Mbp), BTA20 (32 and 58 Mbp), and BTA29 (8 Mbp). The BTA6 (87 Mbp), BTA11, and BTA20 (58 Mbp) QTL were found in all 3 breeds, and they had highly significant effects on κ-casein, ß-lactoglobulin, and α-lactalbumin, expressed as a percentage of protein, respectively. Each of these QTL explained between 13% (BTA14) and 51% (BTA11) of the genetic variance of the trait. Many other QTL regions were also identified in at least one breed. They were located on 14 additional chromosomes (1, 3, 4, 5, 7, 15, 17, 19, 21, 22, 24, 25, 26, and 27), and they explained 2 to 8% of the genetic variance of 1 or more protein composition traits. Concordance analyses, performed between QTL status and sequence-derived polymorphisms from 13 bulls, revealed previously known causal polymorphisms in LGB (BTA11) and GHR (BTA20 at 32 Mbp) and excluded some other previously described mutations. These results constitute a first step in identifying causal mutations and using routinely collected mid-infrared predictions in future genomic selection programs to improve bovine milk protein composition.

The many faces of interleukin-17 in inflammatory skin diseases.

Interleukin (IL)-17 is an emerging target for inflammatory skin disorders. Given the remarkable success of its therapeutic inhibition in psoriasis, the pathogenic role of this cytokine is being explored in other immune-mediated diseases. Interestingly, IL-17 is linked to particular skin conditions where its activation coincides with disease flares. The leading hypothesis for its contribution to proinflammatory signalling cascades is driving inflammasome activation. However, IL-17 stimulation also releases a range of noninflammasome-related cytokines from human skin. Furthermore, a role in cytotoxic responses and an important interplay with the microbiome is hypothesized. While treatment failure would be surprising in neutrophilic dermatoses, the picture might be more complex in lymphocyte-mediated conditions. Nonetheless, increasing insights into the pathogenesis suggest that beneficial responses are also probable in the latter conditions. Study of this pathway in the skin reveals some intriguing aspects of the IL-17-related immunological network.

Development of Fourier transform mid-infrared calibrations to predict acetone, ß-hydroxybutyrate, and citrate contents in bovine milk through a European dairy network.

To manage negative energy balance and ketosis in dairy farms, rapid and cost-effective detection is needed. Among the milk biomarkers that could be useful for this purpose, acetone and ß-hydroxybutyrate (BHB) have been proved as molecules of interest regarding ketosis and citrate was recently identified as an early indicator of negative energy balance. Because Fourier transform mid-infrared spectrometry can provide rapid and cost-effective predictions of milk composition, the objective of this study was to evaluate the ability of this technology to predict these biomarkers in milk. Milk samples were collected in commercial and experimental farms in Luxembourg, France, and Germany. Acetone, BHB, and citrate contents were determined by flow injection analysis. Milk mid-infrared spectra were recorded and standardized for all samples. After edits, a total of 548 samples were used in the calibration and validation data sets for acetone, 558 for BHB, and 506 for citrate. Acetone content ranged from 0.020 to 3.355mmol/L with an average of 0.103mmol/L; BHB content ranged from 0.045 to 1.596mmol/L with an average of 0.215mmol/L; and citrate content ranged from 3.88 to 16.12mmol/L with an average of 9.04mmol/L. Acetone and BHB contents were log-transformed and a part of the samples with low values was randomly excluded to approach a normal distribution. The 3 edited data sets were then randomly divided into a calibration data set (3/4 of the samples) and a validation data set (1/4 of the samples). Prediction equations were developed using partial least square regression. The coefficient of determination (R(2)) of cross-validation was 0.73 for acetone, 0.71 for BHB, and 0.90 for citrate with root mean square error of 0.248, 0.109, and 0.70mmol/L, respectively. Finally, the external validation was performed and R(2) obtained were 0.67 for acetone, 0.63 for BHB, and 0.86 for citrate, with respective root mean square error of validation of 0.196, 0.083, and 0.76mmol/L. Although the practical usefulness of the equations developed should be further verified with other field data, results from this study demonstrated the potential of Fourier transform mid-infrared spectrometry to predict citrate content with good accuracy and to supply indicative contents of BHB and acetone in milk, thereby providing rapid and cost-effective tools to manage ketosis and negative energy balance in dairy farms.

Characterization of the in vivo immune network of IDO, tryptophan metabolism, PD-L1, and CTLA-4 in circulating immune cells in melanoma.

In melanoma, both the induction of immunosuppression by tumor cells and the inflammatory antitumor response can induce an upregulation of counter-regulatory mechanisms such as indoleamine 2,3-dioxygenase (IDO), programmed death-ligand 1 (PD-L1) and CTLA-4+ regulatory T-cells (Tregs) in the tumor microenvironment. Even though these immunosuppressive mediators are targets for immunotherapy, research investigating their expression in the peripheral blood is lacking. We therefore, performed flow cytometry on PBMCs of stage I-IV melanoma patients. IDO expression was detected in plasmacytoid dendritic cells (pDC) and monocytic myeloid-derived suppressor cells (mMDSC), and increased in advanced disease stage (p = 0.027). Tryptophan breakdown confirmed the functional activity of IDO and was linked with increased PD-L1+ cytotoxic T-cells (p = 0.009), relative lymphopenia (p = 0.036), and a higher mDC/pDC ratio (p = 0.002). High levels of circulating PD-L1+ cytotoxic T-cells were associated with increased CTLA-4 expression by Tregs (p = 0.005) and MDSC levels (p = 0.033). This illustrates that counter-regulatory immune mechanisms in melanoma should be considered as one interrelated signaling network. Moreover, both increased PD-L1+ T-cells and CTLA-4 expression in Tregs conferred a negative prognosis, indicating their in vivo relevance. Remarkably, circulating CTLA-4, IDO, and pDC levels were altered according to prior invasion of the sentinel lymph node and IDO expression in the sentinel was associated with more IDO+ PBMCs. We conclude that the expression of IDO, PD-L1, and CTLA-4 in the peripheral blood of melanoma patients is strongly interconnected, associated with advanced disease and negative outcome, independent of disease stage. Combination treatments targeting several of these markers are therefore likely to exert a synergistic response.

Peritumoral indoleamine 2,3-dioxygenase expression in melanoma: an early marker of resistance to immune control?

BACKGROUND: Indoleamine 2,3-dioxygenase (IDO) is an emerging immunomodulating factor in cancer. IDO expression in tumour-negative sentinel lymph nodes (SLNs) of patients with melanoma has a negative prognostic value. OBJECTIVES: To analyse the expression pattern of IDO and associated immunological changes in corresponding primary melanomas (PMs), SLNs and metastases. METHODS: In 120 patients with melanoma, PMs with corresponding SLNs (n = 85) and metastases (n = 18) were analysed by immunohistochemical staining for IDO and FoxP3. Tumour-infiltrating lymphocytes (TILs) were scored. IDO expression in stimulated peripheral blood mononuclear cells (PBMCs) was analysed in 27 patients. RESULTS: IDO expression in the sentinel node strongly correlated with endothelial IDO expression in the peritumoral stroma of the corresponding primary (P < 0·001) and metastatic melanoma (P < 0·05). Sentinel IDO positivity was inversely correlated with CD8+ lymphocytes (P = 0·01) and TILs (P = 0·05) in PM. Both IDO expression in the sentinel (P < 0·01) and the PM (P = 0·04) had a negative prognostic effect on overall survival, independent of Breslow thickness, sex, age, ulceration and sentinel invasion. IDO expression by PBMCs after stimulation with cytotoxic T-lymphocyte antigen 4 was not correlated with sentinel IDO expression but tended to correlate with disease stage (P = 0·04). CONCLUSIONS: Endothelial IDO expression is highly consistent in primary, sentinel and metastatic tissues of patients with melanoma, indicating that immune suppression in melanoma is determined very early in the disease course. This supports that IDO expression in melanoma is a marker of antitumour immune response with an independent prognostic value.

Identification of a ZEB2-MITF-ZEB1 transcriptional network that controls melanogenesis and melanoma progression.

Deregulation of signaling pathways that control differentiation, expansion and migration of neural crest-derived melanoblasts during normal development contributes also to melanoma progression and metastasis. Although several epithelial-to-mesenchymal (EMT) transcription factors, such as zinc finger E-box binding protein 1 (ZEB1) and ZEB2, have been implicated in neural crest cell biology, little is known about their role in melanocyte homeostasis and melanoma. Here we show that mice lacking Zeb2 in the melanocyte lineage exhibit a melanoblast migration defect and, unexpectedly, a severe melanocyte differentiation defect. Loss of Zeb2 in the melanocyte lineage results in a downregulation of the Microphthalmia-associated transcription factor (Mitf) and melanocyte differentiation markers concomitant with an upregulation of Zeb1. We identify a transcriptional signaling network in which the EMT transcription factor ZEB2 regulates MITF levels to control melanocyte differentiation. Moreover, our data are also relevant for human melanomagenesis as loss of ZEB2 expression is associated with reduced patient survival.

Prediction of fatty acid profiles in cow, ewe, and goat milk by mid-infrared spectrometry.

Mid-infrared (MIR) spectrometry was used to estimate the fatty acid (FA) composition in cow, ewe, and goat milk. The objectives were to compare different statistical approaches with wavelength selection to predict the milk FA composition from MIR spectra, and to develop equations for FA in cow, goat, and ewe milk. In total, a set of 349 cow milk samples, 200 ewe milk samples, and 332 goat milk samples were both analyzed by MIR and by gas chromatography, the reference method. A broad FA variability was ensured by using milk from different breeds and feeding systems. The methods studied were partial least squares regression (PLS), first-derivative pretreatment + PLS, genetic algorithm + PLS, wavelets + PLS, least absolute shrinkage and selection operator method (LASSO), and elastic net. The best results were obtained with PLS, genetic algorithm + PLS and first derivative + PLS. The residual standard deviation and the coefficient of determination in external validation were used to characterize the equations and to retain the best for each FA in each species. In all cases, the predictions were of better quality for FA found at medium to high concentrations (i.e., for saturated FA and some monounsaturated FA with a coefficient of determination in external validation >0.90). The conversion of the FA expressed in grams per 100mL of milk to grams per 100g of FA was possible with a small loss of accuracy for some FA.

Identifying targets for topical RNAi therapeutics in psoriasis: assessment of a new in vitro psoriasis model.

Diseases of the skin are amenable to RNAi-based therapies and targeting key components in the pathophysiology of psoriasis using RNAi may represent a successful new therapeutic strategy. We aimed to develop a straightforward and highly reproducible in vitro psoriasis model useful to study the effects of gene knockdown by RNAi and to identify new targets for topical RNAi therapeutics. We evaluated the use of keratinocytes derived from psoriatic plaques and normal human keratinocytes (NHKs). To induce a psoriatic phenotype in NHKs, combinations of pro-inflammatory cytokines (IL-1α, IL-17A, IL-6 and TNF-α) were tested. The model based on NHK met our needs of a reliable and predictive preclinical model, and this model was further selected for gene expression analyses, comprising a panel of 55 psoriasis-associated genes and five micro-RNAs (miRNAs). Gene silencing studies were conducted by using small interfering RNAs (siRNAs) and miRNA inhibitors directed against potential target genes such as CAMP and DEFB4 and miRNAs such as miR-203. We describe a robust and highly reproducible in vitro psoriasis model that recapitulates expression of a large panel of genes and miRNAs relevant to the pathogenesis of psoriasis. Furthermore, we show that our model is a powerful first step model system for testing and screening RNAi-based therapeutics.

Immune reactions in benign and malignant melanocytic lesions: lessons for immunotherapy.

Spontaneous regression of benign and malignant melanocytic lesions can be a visible sign of immunosurveillance. In this review, we discuss different immune reactions against melanocytic lesions: halo nevus, Meyerson's nevus, regression in melanoma and melanoma-associated depigmentation. These entities present with particular clinical aspects, histology and evolution. In all entities, a melanocyte-specific T-cell reaction has been assumed but a different degree of melanocyte destruction is present. A focus on the immune responses in melanocytic lesions reveals several aspects of an adequate skin immunity and may help to identify the key points in the immune destruction of melanocytes. These insights can add to the knowledge of how to optimize immunotherapeutic strategies in melanoma.

Cutaneous short-interfering RNA therapy.

Since the 1990s, RNA interference (RNAi) has become a major subject of interest, not only as a tool for biological research, but also, more importantly, as a therapeutic approach for gene-related diseases. The use of short-interfering RNAs (siRNAs) for the sequence-specific knockdown of disease-causing genes has led to numerous preclinical and even a few clinical studies. Applications for cutaneous delivery of therapeutic siRNA are now emerging owing to a strong demand for effective treatments of various cutaneous disorders. Although successful studies have been performed using several different delivery techniques, most of these techniques encounter limitations for translation to the clinic with regards to patient compliance. This review describes the principal findings and applications in cutaneous RNAi therapy and focuses on the promises and pitfalls of the delivery systems.

Ultradeformable cationic liposomes for delivery of small interfering RNA (siRNA) into human primary melanocytes.

The aim of this work was to develop a system that can deliver siRNA into cells present in the human epidermis. More specifically, we wanted to block the expression of a specific Myosin Va exon F containing isoform that is physiologically involved in melanosome transport in human melanocytes. Therefore, we prepared and investigated the capacity of ultradeformable cationic liposomes (UCLs) to deliver siRNA in hard-to-transfect human primary melanocytes. UCLs were formulated from different w:w ratios (6:1, 8:1 and 10:1) of the cationic lipid 1,2-dioleoyl-3-trimethylammonium propane (DOTAP) and the edge activator sodium cholate. Subsequently, UCL/siRNA complexes were prepared and their particle size, surface charge, deformability, cytotoxicity, transfection efficiency and long-term stability were tested. The best results were obtained with UCLs composed of a DOTAP/NaChol ratio of 6:1 (w:w) which are promising for future in vivo experiments.

Combined M-FISH and CGH analysis allows comprehensive description of genetic alterations in neuroblastoma cell lines.

Cancer cell lines are essential gene discovery tools and have often served as models in genetic and functional studies of particular tumor types. One of the future challenges is comparison and interpretation of gene expression data with the available knowledge on the genomic abnormalities in these cell lines. In this context, accurate description of these genomic abnormalities is required. Here, we show that a combination of M-FISH with banding analysis, standard FISH, and CGH allowed a detailed description of the genetic alterations in 16 neuroblastoma cell lines. In total, 14 cryptic chromosome rearrangements were detected, including a balanced t(2;4)(p24.3;q34.3) translocation in cell line NBL-S, with the 2p24 breakpoint located at about 40 kb from MYCN. The chromosomal origin of 22 marker chromosomes and 41 cytogenetically undefined translocated segments was determined. Chromosome arm 2 short arm translocations were observed in six cell lines (38%) with and five (31%) without MYCN amplification, leading to partial chromosome arm 2p gain in all but one cell line and loss of material in the various partner chromosomes, including 1p and 11q. These 2p gains were often masked in the GGH profiles due to MYCN amplification. The commonly overrepresented region was chromosome segment 2pter-2p22, which contains the MYCN gene, and five out of eleven 2p breakpoints clustered to the interface of chromosome bands 2p16 and 2p21. In neuroblastoma cell line SJNB-12, with double minutes (dmins) but no MYCN amplification, the dmins were shown to be derived from 16q22-q23 sequences. The ATBF1 gene, an AT-binding transcription factor involved in normal neurogenesis and located at 16q22.2, was shown to be present in the amplicon. This is the first report describing the possible implication of ATBF1 in neuroblastoma cells. We conclude that a combined approach of M-FISH, cytogenetics, and CGH allowed a more complete and accurate description of the genetic alterations occurring in the investigated cell lines.

Tumor formation and inactivation of RIZ1, an Rb-binding member of a nuclear protein-methyltransferase superfamily.

The retinoblastoma protein-interacting zinc finger gene RIZ (PRDM2) is a member, by sequence homology, of a nuclear protein-methyltransferase (MTase) superfamily involved in chromatin-mediated gene expression. The gene produces two protein products, RIZ1 that contains a conserved MTase domain and RIZ2 that lacks the domain. RIZ1 gene expression is frequently silenced in human cancers, and the gene is also a common target of frameshift mutation in microsatellite-unstable cancers. We now report studies of mice with a targeted mutation in the RIZ1 locus. The mutation inactivates RIZ1 but not RIZ2. These RIZ1 mutant mice were viable and fertile but showed a high incidence of diffuse large B-cell lymphomas (DLBL) and a broad spectrum of unusual tumors. RIZ1 deficiency also accelerated tumorigenesis in p53 heterozygous mutant mice. Finally, several missense mutations of RIZ1 were found in human tumor tissues and cell lines; one of these was particularly common in human DLBL tumors. These missense mutations, as well as the previously described frameshift mutation, all mapped to the MTase functional domains. All abolished the capacity of RIZ1 to enhance estrogen receptor activation of transcription. These data suggest a direct link between tumor formation and the MTase domain of RIZ1 and describe for the first time a tumor susceptibility gene among methyltransferases.