Publications
19 results found
Cacciatore S, Tenori L, Luchinat C, et al., 2017, KODAMA: an R package for knowledge discovery and data mining, Bioinformatics, Vol: 33, Pages: 621-623, ISSN: 1367-4803
Summary: KODAMA, a novel learning algorithm for unsuper-vised feature extraction, is specifically designed for analysing noisy and high-dimensional data sets. Here we present an R package of the algorithm with additional functions that allow improved interpretation of high-dimensional data. The pack-age requires no additional software and runs on all major plat-forms.Availability and Implementation: KODAMA is freely available from the R archive CRAN (http://cran.r-project.org). The soft-ware is distributed under the GNU General Public License (ver-sion 3 or later).
Kindinger LM, Kyrgiou M, MacIntyre DA, et al., 2016, Preterm Birth Prevention Post-Conization: A Model of Cervical Length Screening with Targeted Cerclage, PLOS One, Vol: 11, ISSN: 1932-6203
Women with a history of excisional treatment (conization) for cervical intra-epithelial neoplasia (CIN) are at increased risk of preterm birth, perinatal morbidity and mortality in subsequent pregnancy. We aimed to develop a screening model to effectively differentiate pregnancies post-conization into low- and high-risk for preterm birth, and to evaluate the impact of suture material on the efficacy of ultrasound indicated cervical cerclage. We analysed longitudinal cervical length (CL) data from 725 pregnant women post-conization attending preterm surveillance clinics at three London university Hospitals over a ten year period (2004–2014). Rates of preterm birth <37 weeks after targeted cerclage for CL<25mm were compared with local and national background rates and expected rates for this cohort. Rates for cerclage using monofilament or braided suture material were also compared. Of 725 women post-conization 13.5% (98/725) received an ultrasound indicated cerclage and 9.7% (70/725) delivered prematurely, <37weeks; 24.5% (24/98) of these despite insertion of cerclage. The preterm birth rate was lower for those that had monofilament (9/60, 15%) versus braided (15/38, 40%) cerclage (RR 0.7, 95% CI 0.54 to 0.94, P = 0.008). Accuracy parameters of interval reduction in CL between longitudinal second trimester screenings were calculated to identify women at low risk of preterm birth, who could safely discontinue surveillance. A reduction of CL <10% between screening timepoints predicts term birth, >37weeks. Our triage model enables timely discharge of low risk women, eliminating 36% of unnecessary follow-up CL scans. We demonstrate that preterm birth in women post-conization may be reduced by targeted cervical cerclage. Cerclage efficacy is however suture material-dependant: monofilament is preferable to braided suture. The introduction of triage prediction models has the potential to reduce the number of unnecessary CL scan for women at low risk of
Kindinger LM, MacIntyre DA, Lee YS, et al., 2016, Relationship between vaginal microbial dysbiosis, inflammation and pregnancy outcomes in cervical cerclage, Science Translational Medicine, Vol: 8, ISSN: 1946-6242
Preterm birth, the leading cause of death in children under five, may be caused by inflammation triggered by ascending vaginal infection. About two million cervical cerclages are performed annually to prevent preterm birth. The procedure is thought to provide structural support and maintain the endocervical mucus plug as a barrier to ascending infection. Two types of suture material are used for cerclage: monofilament or multifilament braided. Braided sutures are most frequently used, though no evidence exists to favor them over monofilament sutures. In this study we assessed birth outcomes in a retrospective cohort of 678 women receiving cervical cerclage in 5 UK university hospitals and showed that braided cerclage was associated with increased intrauterine death (15% v 5%, P = 0.0001) and preterm birth (28% v 17%, P = 0.0006) compared to monofilament suture. To understand the potential underlying mechanism, we performed a prospective, longitudinal study of the vaginal microbiome in women at risk of preterm birth because of short cervical length (≤25 mm) who received braided (n=25) or monofilament (n=24) cerclage under otherwise comparable circumstances. Braided suture induced a persistent shift towards vaginal microbiome dysbiosis characterized by reduced Lactobacillus spp. and enrichment of pathobionts. Vaginal dysbiosis was associated with inflammatory cytokine and interstitial collagenase excretion into cervicovaginal fluid and premature cervical remodeling. Monofilament suture had comparatively minimal impact upon the vaginal microbiome and its interactions with the host. These data provide in vivo evidence that a dynamic shift of the human vaginal microbiome toward dysbiosis correlates with preterm birth.
Migale R, MacIntyre DA, Cacciatore S, et al., 2016, Modeling hormonal and inflammatory contributions to preterm and term labor using uterine temporal transcriptomics, BMC Medicine, Vol: 14, ISSN: 1741-7015
BACKGROUND: Preterm birth is now recognized as the primary cause of infant mortality worldwide. Interplay between hormonal and inflammatory signaling in the uterus modulates the onset of contractions; however, the relative contribution of each remains unclear. In this study we aimed to characterize temporal transcriptome changes in the uterus preceding term labor and preterm labor (PTL) induced by progesterone withdrawal or inflammation in the mouse and compare these findings with human data. METHODS: Myometrium was collected at multiple time points during gestation and labor from three murine models of parturition: (1) term gestation; (2) PTL induced by RU486; and (3) PTL induced by lipopolysaccharide (LPS). RNA was extracted and cDNA libraries were prepared and sequenced using the Illumina HiSeq 2000 system. Resulting RNA-Seq data were analyzed using multivariate modeling approaches as well as pathway and causal network analyses and compared against human myometrial transcriptome data. RESULTS: We identified a core set of temporal myometrial gene changes associated with term labor and PTL in the mouse induced by either inflammation or progesterone withdrawal. Progesterone withdrawal initiated labor without inflammatory gene activation, yet LPS activation of uterine inflammation was sufficient to override the repressive effects of progesterone and induce a laboring phenotype. Comparison of human and mouse uterine transcriptomic datasets revealed that human labor more closely resembles inflammation-induced PTL in the mouse. CONCLUSIONS: Labor in the mouse can be achieved through inflammatory gene activation yet these changes are not a requisite for labor itself. Human labor more closely resembles LPS-induced PTL in the mouse, supporting an essential role for inflammatory mediators in human "functional progesterone withdrawal." This improved understanding of inflammatory and progesterone influence on the uterine transcriptome has important implications for
Al-Memar M, Cacciatore S, Bobdiwala S, et al., 2016, Urine metabolomic changes by gestational age in early pregnancy and differences in the metabolome in viable pregnancies that miscarry compared to those that remain viable, Publisher: Wiley, Pages: 76-76, ISSN: 1470-0328
Cacciatore S, Georgakopoulou N, Jimenez B, et al., 2016, Urine Metabolic Phenotype Diversity in Pregnancy and Its Association with Preterm Delivery and Cervical Length, 63rd Annual Scientific Meeting of the Society for Reproductive Investigation, Publisher: SAGE Publications, Pages: 191A-191A, ISSN: 1933-7205
Migale R, MacIntyre DA, Cacciatore S, et al., 2016, Relative Contribution of Hormonal and Inflammatory Pathways to Uterine Transcriptome Dynamics in Term and Preterm Labor, 63rd Annual Scientific Meeting of the Society-for-Reproductive-Investigation, Publisher: SAGE PUBLICATIONS INC, Pages: 125A-125A, ISSN: 1933-7191
Georgakopoulou N, MacIntyre DA, Cacciatore S, et al., 2016, Early Second Trimester Plasma Metabolome Signatures of Cervical Shortening and Preterm Delivery., 63rd Annual Scientific Meeting of the Society-for-Reproductive-Investigation, Publisher: SAGE PUBLICATIONS INC, Pages: 208A-208A, ISSN: 1933-7191
Labbe DP, Zadra G, Ebot EM, et al., 2016, High-fat diet enhances MYC-driven prostate cancer through epigenomic and metabolomic rewiring, American-Association-for-Cancer-Research (AACR) Special Conference on Chromatin and Epigenetics in Cancer, Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472
Diet is hypothesized to be a critical environmental risk factor for prostate cancer (PCa) development, and progression; however, the mechanisms underlying these associations remain elusive. In a MYC-driven PCa mouse model we find that a high fat diet significantly alters the transcription of genes implicated in chromatin function and remodeling in prostatic tumor tissues but not in the normal prostate. Importantly, this chromatin associated gene expression signature was observed well before the appearance of a high fat diet-driven phenotype that was characterized by greater cell proliferation and increased tumor burden. Consistent with this finding, high-throughput targeted quantitative histone mass spectrometry revealed a robust MYC-driven signature affecting more than half of the 68 histone marks profiled. Surprisingly, high fat diet further enhanced the MYC-induced epigenetic signature while it was unable to affect the normal murine prostate. Epigenetic remodeling relies on substrates and cofactors that are obtained from the diet. Untargeted metabolomic analyses revealed that MYC overexpression, as expected, impacted glutamine uptake. In addition, high fat diet leads to additional carbohydrates, amino acids, lipids and nucleotides necessary to sustain an increased cellular proliferation in MYC-driven cancers while it had little influence on the normal prostate. Moreover, the pool of metabolites altered by high fat diet in the context of MYC overexpression is highly suggestive of a global methylation defect. Finally, using the genome-wide mRNA profiles of tumor (N=402) and adjacent normal (N=200) prostate tissues from the Health Professionals Follow-up Study and the Physicians' Health Study cohorts, we have discovered an enrichment in genes implicated in chromatin function and remodeling in tumor tissues from overweight/obese men, but not in normal adjacent tissues, consistent with the high fat diet signature observed in mice. Strikingly, men whose tumors had high
Paglia G, Stocchero M, Cacciatore S, et al., 2015, Unbiased Metabolomic Investigation of Alzheimer’s Disease Brain Points to Dysregulation of Mitochondrial Aspartate Metabolism, Journal of Proteome Research, Vol: 15, Pages: 608-618, ISSN: 1535-3907
Alzheimer’s disease (AD) is the most common cause of adult dementia. Yet the complete set of molecular changes accompanying this inexorable, neurodegenerative disease remains elusive. Here we adopted an unbiased lipidomics and metabolomics approach to surveying frozen frontal cortex samples from clinically characterized AD patients (n = 21) and age-matched controls (n = 19), revealing marked molecular differences between them. Then, by means of metabolomic pathway analysis, we incorporated the novel molecular information into the known biochemical pathways and compared it with the results of a metabolomics meta-analysis of previously published AD research. We found six metabolic pathways of the central metabolism as well as glycerophospholipid metabolism predominantly altered in AD brains. Using targeted metabolomics approaches and MS imaging, we confirmed a marked dysregulation of mitochondrial aspartate metabolism. The altered metabolic pathways were further integrated with clinical data, showing various degrees of correlation with parameters of dementia and AD pathology. Our study highlights specific, altered biochemical pathways in the brains of individuals with AD compared with those of control subjects, emphasizing dysregulation of mitochondrial aspartate metabolism and supporting future venues of investigation.
Kindinger LM, Poon LC, Cacciatore S, et al., 2015, The effect of gestational age and cervical length measurements in the prediction of spontaneous preterm birth in twin pregnancies: an individual patient level meta-analysis, Bjog-An International Journal of Obstetrics and Gynaecology, Vol: 123, Pages: 877-884, ISSN: 1471-0528
ObjectiveTo assess the effect of gestational age (GA) and cervical length (CL) measurements at transvaginal ultrasound (TVUS) in the prediction of preterm birth in twin pregnancy.DesignIndividual patient data (IPD) meta-analysis.SettingInternational multicentre study.PopulationAsymptomatic twin pregnancy.MethodsMEDLINE and EMBASE searches were performed and IPD obtained from authors of relevant studies. Multinomial logistic regression analysis determined probabilities for birth at ≤28+0, 28+1 to 32+0, 32+1 to 36+0, and ≥36+1 weeks as a function of GA at screening and CL measurements.Main outcome measuresPredicted probabilities for preterm birth at ≤28+0, 28+1 to 32+0, and 32+1 to 36+0.ResultsA total of 6188 CL measurements were performed on 4409 twin pregnancies in 12 studies. Both GA at screening and CL had a significant and non-linear effect on GA at birth. The best prediction of birth at ≤28+0 weeks was provided by screening at ≤18+0 weeks (P < 0.001), whereas the best prediction of birth between 28+1 and 36+0 weeks was provided by screening at ≥24+0 weeks (P < 0.001). Negative prediction value of 100% for birth at ≤28+0 weeks is achieved at CL 65 mm and 43 mm at ultrasound GA at ≤18+0 weeks and at 22+1 to 24+0 weeks, respectively.ConclusionIn twin pregnancies, prediction of preterm birth depends on both CL and the GA at screening. When CL is <30 mm, screening at ≤18+0 weeks is most predictive for birth at ≤28+0 weeks. Later screening at >22+0 weeks is most predictive of delivery at 28+1 to 36+0 weeks. In twins, we recommend CL screening in twins to commence from ≤18+0 weeks.
Cacciatore S, Loda M, 2015, Innovation in metabolomics to improve personalized healthcare, Annals of the New York Academy of Sciences, Vol: 1346, Pages: 57-62, ISSN: 0077-8923
Metabolomics is the systemic study of all small molecules (metabolites) and their concentration as affected by pathological and physiological alterations or environmental or other factors. Metabolic alterations represent a “window” on the complex interactions between genetic expression, enzyme activity, and metabolic reactions. Techniques, including nuclear magnetic resonance spectroscopy, mass spectrometry, Fourier-transform infrared, and Raman spectroscopy, have led to significant advances in metabolomics. The field is shifting from feasibility studies to biological and clinical applications. Fields of application range from cancer biology to stem cell research and assessment of xenobiotics and drugs in tissues and single cells. Cross-validation across high-throughput platforms has allowed findings from expression profiling to be confirmed with metabolomics. Specific genetic alterations appear to drive unique metabolic programs. These, in turn, can be used as biomarkers of genetic subtypes of prostate cancer or as discovery tools for therapeutic targeting of metabolic enzymes. Thus, metabolites in blood may serve as biomarkers of tumor state, including inferring driving oncogenes. Novel applications such as these suggest that metabolic profiling may be utilized in refining personalized medicine.
Cacciatore S, Saccenti E, Piccioli M, 2015, Hypothesis: The Sound of the Individual Metabolic Phenotype? Acoustic Detection of NMR Experiments, OMICS: A Journal of Integrative Biology, Vol: 19, Pages: 147-156, ISSN: 1536-2310
Priolo C, Pyne S, Rose J, et al., 2014, AKT1 and MYC Induce Distinctive Metabolic Fingerprints in Human Prostate Cancer, Cancer Research, Vol: 74, Pages: 7198-7204, ISSN: 0008-5472
<jats:title>Abstract</jats:title> <jats:p>Cancer cells may overcome growth factor dependence by deregulating oncogenic and/or tumor-suppressor pathways that affect their metabolism, or by activating metabolic pathways de novo with targeted mutations in critical metabolic enzymes. It is unknown whether human prostate tumors develop a similar metabolic response to different oncogenic drivers or a particular oncogenic event results in its own metabolic reprogramming. Akt and Myc are arguably the most prevalent driving oncogenes in prostate cancer. Mass spectrometry–based metabolite profiling was performed on immortalized human prostate epithelial cells transformed by AKT1 or MYC, transgenic mice driven by the same oncogenes under the control of a prostate-specific promoter, and human prostate specimens characterized for the expression and activation of these oncoproteins. Integrative analysis of these metabolomic datasets revealed that AKT1 activation was associated with accumulation of aerobic glycolysis metabolites, whereas MYC overexpression was associated with dysregulated lipid metabolism. Selected metabolites that differentially accumulated in the MYC-high versus AKT1-high tumors, or in normal versus tumor prostate tissue by untargeted metabolomics, were validated using absolute quantitation assays. Importantly, the AKT1/MYC status was independent of Gleason grade and pathologic staging. Our findings show how prostate tumors undergo a metabolic reprogramming that reflects their molecular phenotypes, with implications for the development of metabolic diagnostics and targeted therapeutics. Cancer Res; 74(24); 7198–204. ©2014 AACR.</jats:p>
Cacciatore S, Luchinat C, Tenori L, 2014, Knowledge discovery by accuracy maximization, Proceedings of the National Academy of Sciences, Vol: 111, Pages: 5117-5122, ISSN: 0027-8424
<jats:title>Significance</jats:title> <jats:p>We propose an innovative method to extract new knowledge from noisy and high-dimensional data. Our approach differs from previous methods in that it has an integrated procedure of validation of the results through maximization of cross-validated accuracy. In many cases, this method performs better than existing feature extraction methods and offers a general framework for analyzing any kind of complex data in a broad range of sciences. Examples ranging from genomics and metabolomics to astronomy and linguistics show the versatility of the method.</jats:p>
Cacciatore S, Hu X, Viertler C, et al., 2013, Effects of Intra- and Post-Operative Ischemia on the Metabolic Profile of Clinical Liver Tissue Specimens Monitored by NMR, Journal of Proteome Research, Vol: 12, Pages: 5723-5729, ISSN: 1535-3893
Cacciatore S, Tenori L, 2013, Brain cholesterol homeostasis in Wilson disease, Medical Hypotheses, Vol: 81, Pages: 1127-1129, ISSN: 0306-9877
Maccaferri S, Klinder A, Cacciatore S, et al., 2012, In vitro fermentation of potential prebiotic flours from natural sources: Impact on the human colonic microbiota and metabolome, Molecular Nutrition & Food Research, Vol: 56, Pages: 1342-1352, ISSN: 1613-4125
<jats:sec><jats:title>Scope</jats:title><jats:p>Fibers and prebiotics represent a useful dietary approach for modulating the human gut microbiome. Therefore, aim of the present study was to investigate the impact of four flours (wholegrain rye, wholegrain wheat, chickpeas and lentils 50:50, and barley milled grains), characterized by a naturally high content in dietary fibers, on the intestinal microbiota composition and metabolomic output.</jats:p></jats:sec><jats:sec><jats:title>Methods and results</jats:title><jats:p>A validated three‐stage continuous fermentative system simulating the human colon was used to resemble the complexity and diversity of the intestinal microbiota. Fluorescence in situ hybridization was used to evaluate the impact of the flours on the composition of the microbiota, while small‐molecule metabolome was assessed by <jats:styled-content style="fixed-case">NMR</jats:styled-content> analysis followed by multivariate pattern recognition techniques. <jats:styled-content style="fixed-case">HT</jats:styled-content>29 cell‐growth curve assay was used to evaluate the modulatory properties of the bacterial metabolites on the growth of intestinal epithelial cells. All the four flours showed positive modulations of the microbiota composition and metabolic activity. Furthermore, none of the flours influenced the growth‐modulatory potential of the metabolites toward <jats:styled-content style="fixed-case">HT</jats:styled-content>29 cells.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Our findings support the utilization of the tested ingredients in the development of a variety of potentially prebiotic food products aimed at improving gastrointestinal health.</jats:p></jats:sec>
Bertini I, Cacciatore S, Jensen BV, et al., 2012, Metabolomic NMR Fingerprinting to Identify and Predict Survival of Patients with Metastatic Colorectal Cancer, Cancer Research, Vol: 72, Pages: 356-364, ISSN: 0008-5472
<jats:title>Abstract</jats:title> <jats:p>Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance (1H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist that is strong enough to predict overall survival (OS). In 153 patients with mCRC and 139 healthy subjects from three Danish hospitals, we profiled two independent sets of serum samples in a prospective phase II study. In the training set, 1H-NMR metabolomic profiling could discriminate patients with mCRC from healthy subjects with a cross-validated accuracy of 100%. In the validation set, 96.7% of subjects were correctly classified. Patients from the training set with maximally divergent OS were chosen to construct an OS predictor. After validation, patients predicted to have short OS had significantly reduced survival (HR, 3.4; 95% confidence interval, 2.06–5.50; P = 1.33 × 10−6). A number of metabolites concurred with the 1H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that 1H-NMR profiling of patient serum can provide a strong metabolomic signature of mCRC and that analysis of this signature may offer an independent tool to predict OS. Cancer Res; 72(1); 356–64. ©2011 AACR.</jats:p>
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