Targeting carcinoma-associated mesothelial cells with antibody-drug conjugates in ovarian carcinomatosis.

Ovarian carcinomatosis is characterized by the accumulation of carcinoma-associated mesothelial cells (CAMs) in the peritoneal stroma and mainly originates through a mesothelial-to-mesenchymal transition (MMT) process. MMT has been proposed as a therapeutic target for peritoneal metastasis. Most ovarian cancer (OC) patients present at diagnosis with peritoneal seeding, which makes tumor progression control difficult by MMT modulation. An alternative approach is to use antibody-drug conjugates (ADCs) targeted directly to attack CAMs. This strategy could represent the cornerstone of precision-based medicine for peritoneal carcinomatosis. Here, we performed complete transcriptome analyses of ascitic fluid-isolated CAMs in advanced OC patients with primary-, high-, and low-grade, serous subtypes and following neoadjuvant chemotherapy. Our findings suggest that both cancer biological aggressiveness and chemotherapy-induced tumor mass reduction reflect the MMT-associated changes that take place in the tumor surrounding microenvironment. Accordingly, MMT-related genes, including fibroblast activation protein (FAP), mannose receptor C type 2 (MRC2), interleukin-11 receptor alpha (IL11RA), myristoylated alanine-rich C-kinase substrate (MARCKS), and sulfatase-1 (SULF1), were identified as specific actionable targets in CAMs of OC patients, which is a crucial step in the de novo design of ADCs. These cell surface target receptors were also validated in peritoneal CAMs of colorectal cancer peritoneal implants, indicating that ADC-based treatment could extend to other abdominal tumors that show peritoneal colonization. As proof of concept, a FAP-targeted ADC reduced tumor growth in an OC xenograft mouse model with peritoneal metastasis-associated fibroblasts. In summary, we propose MMT as a potential source of ADC-based therapeutic targets for peritoneal carcinomatosis. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms.

INTRODUCTION: Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables. RESEARCH DESIGN AND METHODS: Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort. RESULTS: Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively. CONCLUSIONS: We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

Expression of Epithelial and Mesenchymal Markers in Plasmatic Extracellular Vesicles as a Diagnostic Tool for Neoplastic Processes.

Tumor-derived extracellular vesicles (TD-EVs) have active roles as cancer hallmark enablers. EVs RNA of epithelial and stromal cells carry information that facilitates the communication processes that contribute to oncological progression, so the objective of this work was to validate by RT-PCR the presence of epithelial (KRT19; CEA) and stromal (COL1A2; COL11A1) markers in RNA of plasmatic EVs in healthy and diverse-malignancy patients for the development of a non-invasive cancer diagnosis system using liquid biopsy. Ten asymptomatic controls and 20 cancer patients were included in the study, and results showed that the isolated plasmatic EVs by scanning transmission electron microscopy (STEM) andBiomedical Research Institute A Coruña nanoparticle tracking analysis (NTA) contained most exosome structures with also a considerable percentage of microvesicles. No differences were found in concentration and size distribution between the two cohorts of patients, but significant gene expression in epithelial and mesenchymal markers between healthy donors and patients with active oncological disease was shown. Results of quantitative RT-PCR are solid and reliable for KRT19, COL1A2, and COL11A1, so the analysis of RNA extracted from TD-EVs could be a correct approach to develop a diagnostic tool in oncological processes.

Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet.

Hypothesis: Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet. Methods: 2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5. Results: Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM. Conclusions: We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.

Genetic Variants in Folate and Cobalamin Metabolism-Related Genes in Pregnant Women of a Homogeneous Spanish Population: The Need for Revisiting the Current Vitamin Supplementation Strategies.

Polymorphisms of genes involved in the metabolism and transport of folate and cobalamin could play relevant roles in pregnancy outcomes. This study assessed the prevalence of genetic polymorphisms of folate and cobalamin metabolism-related genes such as MTHFR, MTR, CUBN, and SLC19A1 in pregnant women of a homogeneous Spanish population according to conception, pregnancy, delivery, and newborns complications. This study was conducted on 149 nulliparous women with singleton pregnancies. Sociodemographic and obstetrics variables were recorded, and all patients were genotyped in the MTHFR, MTR, CUBN, and SLC10A1 polymorphisms. The distribution of genotypes detected in this cohort was similar to the population distribution reported in Europe, highlighting that more than 50% of women were carriers of risk alleles of the studied genes. In women with the MTHFR risk allele, there was a statistically significant higher frequency of assisted fertilisation and a higher frequency of preeclampsia and preterm birth. Moreover, CUBN (rs1801222) polymorphism carriers showed a statistically significantly lower frequency of complications during delivery. In conclusion, the prevalence of genetic variants related to folic acid and vitamin B12 metabolic genes in pregnant women is related to mother and neonatal outcomes. Knowing the prevalence of these polymorphisms may lead to a personalised prescription of vitamin intake.

Interaction between rs10830962 polymorphism in MTNR1B and lifestyle intervention on maternal and neonatal outcomes: secondary analyses of the DALI lifestyle randomized controlled trial.

BACKGROUND: Interactions between polymorphisms of the melatonin receptor 1B (MTNR1B) gene and lifestyle intervention for gestational diabetes have been described. Whether these are specific for physical activity or the healthy eating intervention is unknown. OBJECTIVES: The aim was to assess the interaction between MTNR1B rs10830962 and rs10830963 polymorphisms and lifestyle interventions during pregnancy. METHODS: Women with a BMI (in kg/m2) of ≥29 (n = 436) received counseling on healthy eating (HE), physical activity (PA), or both. The control group received usual care. This secondary analysis had a factorial design with comparison of HE compared with no HE and PA compared with no PA. Maternal outcomes at 24-28 wk were gestational weight gain (GWG), maternal fasting glucose, insulin, insulin resistance (HOMA-IR), disposition index, and development of GDM. Neonatal outcomes were cord blood leptin and C-peptide and estimated neonatal fat percentage. The interaction between receiving either the HE or PA intervention and genotypes of both rs10830962 and rs10830963 was assessed using multilevel regression analysis. RESULTS: GDM risk was increased in women homozygous for the G allele of rs10830962 (OR: 2.60; 95% CI: 1.34, 5.06) or rs10830963 (OR: 2.83; 95% CI: 1.24, 6.47). Significant interactions between rs10830962 and interventions were found: in women homozygous for the G allele but not in the other genotypes, the PA intervention reduced maternal fasting insulin (ß: -0.16; 95% CI: -0.33, 0.02; P = 0.08) and HOMA-IR (ß: -0.17; 95% CI: -0.35, 0.01; P = 0.06), and reduced cord blood leptin (ß: -0.84; 95% CI: -1.42, -0.25; P = 0.01) and C-peptide (ß: -0.62; 95% CI: -1.07, -0.17; P = 0.01). In heterozygous women, the HE intervention had no effect, whereas in women homozygous for the C allele, HE intervention reduced GWG (ß: -1.6 kg; 95% CI: -2.4, -0.8 kg). No interactions were found. CONCLUSIONS: In women homozygous for the risk allele of MTNR1B rs10830962, GDM risk was increased and PA intervention might be more beneficial than HE intervention for reducing maternal insulin resistance, cord blood C-peptide, and cord blood leptin.

OMTX705, a Novel FAP-Targeting ADC Demonstrates Activity in Chemotherapy and Pembrolizumab-Resistant Solid Tumor Models.

PURPOSE: The tumor microenvironment plays a key role in cancer development and progression and is involved in resistance to chemo- and immunotherapy. Cancer-associated fibroblast expressing fibroblast-activating protein α (FAPα) is one of the predominant stroma cell types and is involved in resistance to immunotherapy. EXPERIMENTAL DESIGN: We generated OMTX705, a novel antibody-drug conjugate from a humanized anti-FAP antibody linked to a new cytolysin. Here, we studied its antineoplastic activity in vitro and in preclinical mouse models alone and in combination with chemotherapy as well as immunotherapy in PD-1-resistant tumors. RESULTS: In Avatar models, OMTX705 showed a 100% tumor growth inhibition and prolonged tumor regressions as single agent and in combination with chemotherapy. Treatment rechallenge following treatment discontinuation induced additional tumor regression, suggesting lack of treatment resistance. In a mouse model with a humanized immune system resistant to PD-1 inhibition, OMTX705 increased tumor infiltration by CD8+ T cells, induced complete regressions, and delayed tumor recurrence. CONCLUSIONS: These data suggest that FAP targeting with OMTX705 represents a novel and potent strategy for cancer treatment, including tumors resistant to immunotherapy, and support its clinical development.

Influence of obesity, parental history of diabetes, and genes in type 2 diabetes: A case-control study.

Obesity, parental history (PH) of type 2 diabetes (T2D), and genes play an important role in T2D development. However, the influence of each factor on T2D variability is unclear. This study aimed to investigate the influence of obesity (body mass index [BMI], waist/hip ratio), PH, and 16 single-nucleotide polymorphisms (SNPs) associated with T2D on T2D variability in Mexico, comparing 1234 non-diabetic controls and 1219 diabetic patients. To replicate the data, a case-control (n = 2904) and a cross-sectional (n = 1901) study were also included. In a multivariate logistic regression model, all factors accounted for only 27.3% of T2D variability: SNPs (8.4%); PH (11.8%) and obesity (7.1%). These factors contributed more in men (33.2%) than in women (25%), specifically when the disease was diagnosed before the age of 46 (46.7% vs. 30%). Genes played a substantially more important role in men than in women (14.9% vs. 5.5%), while obesity and PH played a similar role in both genders. Genes and PH appeared to play a greater role than obesity in T2D. However, obesity contribution was calculated at the time of recruitment and may be underestimated in patients because the BMI decreased linearly with the number of years with the disease. The data suggest that sexual hormones may play important roles in genes that are associated with T2D.

Preclinical Efficacy of Endoglin-Targeting Antibody-Drug Conjugates for the Treatment of Ewing Sarcoma.

PURPOSE: Endoglin (ENG; CD105) is a coreceptor of the TGFß family that is highly expressed in proliferating endothelial cells. Often coopted by cancer cells, ENG can lead to neo-angiogenesis and vasculogenic mimicry in aggressive malignancies. It exists both as a transmembrane cell surface protein, where it primarily interacts with TGFß, and as a soluble matricellular protein (sENG) when cleaved by matrix metalloproteinase 14 (MMP14). High ENG expression has been associated with poor prognosis in Ewing sarcoma, an aggressive bone cancer that primarily occurs in adolescents and young adults. However, the therapeutic value of ENG targeting has not been fully explored in this disease. EXPERIMENTAL DESIGN: We characterized the expression pattern of transmembrane ENG, sENG, and MMP14 in preclinical and clinical samples. Subsequently, the antineoplastic potential of two novel ENG-targeting monoclonal antibody-drug conjugates (ADC), OMTX503 and OMTX703, which differed only by their drug payload (nigrin-b A chain and cytolysin, respectively), was assessed in cell lines and preclinical animal models of Ewing sarcoma. RESULTS: Both ADCs suppressed cell proliferation in proportion to the endogenous levels of ENG observed in vitro. Moreover, the ADCs significantly delayed tumor growth in Ewing sarcoma cell line-derived xenografts and patient-derived xenografts in a dose-dependent manner. CONCLUSIONS: Taken together, these studies demonstrate potent preclinical activity of first-in-class anti-ENG ADCs as a nascent strategy to eradicate Ewing sarcoma.

Collagen, type XI, alpha 1: an accurate marker for differential diagnosis of breast carcinoma invasiveness in core needle biopsies.

Accurate diagnosis of invasive breast lesions, when analyzed by Core Needle Biopsy, may suppose a major challenge for the pathologist. Various markers of invasiveness such as laminin, S-100 protein, P63 or calponin have been described; however, none of them is completely reliable. The use of a specific marker of the infiltrating tumor microenvironment seems vital to support the diagnosis of invasive against in situ lesions. At this point, Collagen, type XI, alpha 1 (COL11A1), might be helpful since it has been described to be associated to cancer associated fibroblasts in other tumors such as lung, pancreas or colorectal. This paper aims to analyze the role of COL11A1 as a marker of invasiveness in breast tumor lesions. Two hundred and one breast Core Needle Biopsy samples were analyzed by immunohistochemistry against pro-COL11A1. The results show a significant difference (p < 0.0001) when comparing the expression in infiltrative tumors (93%) versus immunostaining of non-invasive lesions (4%). Forty cases of underestimated DCIS were also stained for COL11A1, presenting a sensitivity of 90% when compared with p63 and calponin which not tagged invasion. In conclusion, pro-COL11A1 expression is a promising marker of invasive breast lesions, and may be included in immunohistochemical panels aiming at identifying infiltration in problematic breast lesions.

Genetic predisposition to early recurrence in clinically localized prostate cancer.

UNLABELLED: WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Currently available nomograms to predict preoperative risk of early biochemical recurrence (EBCR) after radical prostatectomy are solely based on classic clinicopathological variables. Despite providing useful predictions, these models are not perfect. Indeed, most researchers agree that nomograms can be improved by incorporating novel biomarkers. In the last few years, several single nucleotide polymorphisms (SNPs) have been associated with prostate cancer, but little is known about their impact on disease recurrence. We have identified four SNPs associated with EBCR. The addition of SNPs to classic nomograms resulted in a significant improvement in terms of discrimination and calibration. The new nomogram, which combines clinicopathological and genetic variables, will help to improve prediction of prostate cancer recurrence. OBJECTIVES: To evaluate genetic susceptibility to early biochemical recurrence (EBCR) after radical prostatectomy (RP), as a prognostic factor for early systemic dissemination. To build a preoperative nomogram to predict EBCR combining genetic and clinicopathological factors. PATIENTS AND METHODS: We evaluated 670 patients from six University Hospitals who underwent RP for clinically localized prostate cancer (PCa), and were followed-up for at least 5 years or until biochemical recurrence. EBCR was defined as a level prostate-specific antigen >0.4 ng/mL within 1 year of RP; preoperative variables studied were: age, prostate-specific antigen, clinical stage, biopsy Gleason score, and the genotype of 83 PCa-related single nucleotide polymorphisms (SNPs). Univariate allele association tests and multivariate logistic regression were used to generate predictive models for EBCR, with clinicopathological factors and adding SNPs. We internally validated the models by bootstrapping and compared their accuracy using the area under the curve (AUC), net reclassification improvement, integrated discrimination improvement, calibration plots and Vickers' decision curves. RESULTS: Four common SNPs at KLK3, KLK2, SULT1A1 and BGLAP genes were independently associated with EBCR. A significant increase in AUC was observed when SNPs were added to the model: AUC (95% confidence interval) 0.728 (0.674-0.784) vs 0.763 (0.708-0.817). Net reclassification improvement showed a significant increase in probability for events of 60.7% and a decrease for non-events of 63.5%. Integrated discrimination improvement and decision curves confirmed the superiority of the new model. CONCLUSIONS: Four SNPs associated with EBCR significantly improved the accuracy of clinicopathological factors. We present a nomogram for preoperative prediction of EBCR after RP.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PURPOSE: Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. MATERIALS AND METHODS: We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. RESULTS: The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. CONCLUSIONS: Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information.

Prediction of functional impairment and remission in rheumatoid arthritis patients by biochemical variables and genetic polymorphisms.

OBJECTIVE: To develop a model to predict RA outcome based on biochemical variables and single nucleotide polymorphisms (SNPs). METHODS: We collected baseline data from RA patients. SNP genotyping was performed using an oligonucleotide microarray. Remission and severe disability were investigated as outcomes of the study. Logistic regression models and receiver operating characteristic (ROC) curves were used to determine sensitivity (S), specificity (Sp) and likelihood ratio (LR). RESULTS: Six hundred and thirty-two patients (375 in the study and 257 in the validation) were included. Twenty-two out of 152, and 19 out of 208 patients had an HAQ > 2. The model obtained to predict disability included levels of the anti-cyclic citrullinated peptide (anti-CCP) antibodies, ESR and SNP rs2070874 in the IL-4 gene. Homozygous and heterozygous carriers of the IL-4 33T allele had a decreased risk of severe disability. The discriminative power had an area under the curve (AUC) of 0.792 (95% CI 0.694, 0.889), with S 41%, Sp 95% and LR +7.6. Twenty-one out of 268 and 17 out of 211 patients were in remission in the study and validation cohorts, respectively. The model included absence of anti-CCP antibodies and the SNP rs2476601 on the PTPN22 gene. Homozygous and heterozygous carriers of the PTPN22 1858T allele had a decreased probability of remission. The discriminative power had an AUC of 0.842 (95% CI 0.756, 0.928), with S 76%, Sp 86% and LR + 5.4. Predictive ability was confirmed on the validation cohort. CONCLUSIONS: We have developed two models based on laboratory variables that are associated with relevant outcomes for RA patients at disease onset.

Comprehensive proteomic analysis of human endometrial fluid aspirate.

The endometrial fluid is a noninvasive sample which contains numerous secreted proteins representative of endometrial function and reflects the state of the endometrium. In this study, we describe, for the first time, a comprehensive catalogue of proteins of the endometrial fluid during the secretory phase of the menstrual cycle. To achieve this objective, three different but complementary strategies were used: First, in-solution digestion followed by reverse phase high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS); second, protein separation by denaturing one-dimensional electrophoresis (SDS-PAGE) followed by HPLC-MS/MS analysis. Finally, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) followed by MALDI-TOF/TOF analysis. The combination of the three strategies led to the successful identification of 803 different proteins in the International Protein Index (IPI) human database (v3.48). An extensive description of the endometrial fluid proteome will help provide the basis for a better understanding of a number of diseases and processes, including endometriosis, endometrial cancer and embryo implantation. We believe that the thorough catalogue of proteins presented here can serve as a valuable reference for the study of embryo implantation and for future biomarker discovery involved in pathologic alterations of endometrial function.

The use of gene array technology and proteomics in the search of new targets of diseases for therapeutics.

The advent of functional genomics has been greatly broadening our view and accelerating our way in numerous medical research fields. The complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study complex diseases, has allowed rapid evolution of genomic and proteomic technologies, speeding the rate and number of discoveries in new biomarkers. By jointly using genomics, proteomics and bioinformatics there is a great potential to make considerable contribution to biomarker identification and to revolutionize both the development of new therapies and drug development process.

Plexin B1 is downregulated in renal cell carcinomas and modulates cell growth.

Plexins are a family of transmembrane receptors that interact with the repulsive axon guidance molecules (Semaphorins) in neural tissues. In extraneural tissues, plexins are involved in other cellular functions often altered in neoplastic cells, such as adhesion, migration, and apoptosis. Plexin B1 has been implicated in the regulation of Akt, which is an activated pathway in renal cell neoplasms, and only 1 report has emphasized its role as an oncogenic factor. Furthermore, plexin B1 is located in 3p21, which is a chromosomal region deleted frequently in renal cell carcinomas. In accordance with a hypothetical oncogenic role for plexin B1, we have shown by reverse transcription-polymerase chain reaction that plexin B1 is expressed in nonneoplastic renal tissue, and it is severely downregulated in clear cell renal carcinomas. We have also demonstrated by immunohistochemistry on tissue microarrays that plexin B1 protein is absent in more than 80% of renal cell carcinomas (169 in 209 carcinomas examined). Otherwise, all kinds of renal tubules showed strong membrane reactivity. Moreover, when we have induced plexin B1 expression with an expression vector in the renal adenocarcinoma cell line ACHN, a marked reduction in proliferation rate was produced. Altogether, this evidence suggests a possible role for plexin B1 in renal oncogenesis.

Transcriptional profiling of hematologic malignancies with a low-density DNA microarray.

BACKGROUND: High-density microarrays are powerful tools for expression analysis of thousands of genes simultaneously; however, experience with low-density microarrays in gene expression studies has been limited. METHODS: We developed an optimized procedure for gene expression analysis based on a microarray containing 538 oligonucleotides and used this procedure to analyze neoplastic cell lines and whole-blood samples from healthy individuals and patients with different hematologic neoplasias. Hierarchical clustering and the Welch t-test with adjusted P values were used for data analysis. RESULTS: This procedure detects 0.2 fmol of mRNA and generates a linear response of 2 orders of magnitude, with CV values of <20% for hybridization and label replicates. We found statistically significant differences between Jurkat and U937 cell lines, between blood samples from 15 healthy donors and 59 chronic lymphocytic leukemia (CLL) samples, and between 6 acute myeloid leukemia patients and 4 myelodysplastic syndrome patients. A classification system constructed from the expression data predicted healthy or CLL status from a whole-blood sample with a 97% success rate. CONCLUSION: Transcriptional profiling of whole-blood samples was carried out without any cellular or sample manipulation before RNA extraction. This gene expression analysis procedure uncovered statistically significant differences associated with different hematologic neoplasias and made possible the construction of a classification system that predicts the healthy or CLL status from a whole-blood sample.

Identification of chitotriosidase isoforms in plasma of Gaucher disease patients by two dimensional gel electrophoresis.

Chitotriosidase protein (ChT) is the most important biochemical marker described for Gaucher disease (GD). ChT activity is increased several hundred-fold in plasma of GD patients and shows a strong positive correlation with the severity of the disease. However, a recessively inherited enzyme deficiency, with an incidence of about 6% in the Caucasian population, means that not all patients with GD can be monitored by measuring ChT activity. Applying two-dimensional gel electrophoresis (2-DE) technology this study describes the localization and identification of five ChT isoforms in 2-DE images obtained from plasma of GD patients. All these isoforms were unequivocally identified using MALDI-TOF mass spectrometry (MS) and validated by western blot analysis. The features of each ChT isoform separated by 2-DE in plasma from GD patients homozygous for the wild-type ChT allele, carriers of one defective allele and patients homozygous for the mutant allele are presented. We also show the correlation between each ChT isoform and the plasma ChT enzymatic activity of the GD patients sampled in this study.

Reliable low-density DNA array based on allele-specific probes for detection of 118 mutations causing familial hypercholesterolemia.

BACKGROUND: Patients with familial hypercholesterolemia (FH) have a high risk of premature cardiovascular disease (PCVD). Mutations in the LDL receptor (LDLR) gene and the R3500Q mutation in the apolipoprotein B (APOB) gene are known to cause FH, but lack of high-throughput methods makes routine genetic diagnosis difficult. The objective of this work was to develop a DNA array for large-scale identification of mutant LDLR alleles. METHODS: We developed a low-density oligonucleotide microarray to identify 118 DNA sequence variations (117 for the LDLR gene and 1 for the APOB gene). We verified specificity and sensitivity by analyzing 1180 previously sequenced DNA samples, and conducted a blind study screening 407 Spanish patients with a clinical diagnosis of FH. RESULTS: The DNA array confirmed the previous genotyping results in almost all cases. In the blind study, the microarray detected at least 1 mutation in 51% of the patients for whom clinical diagnosis was classified as certain according to Dutch FH-MEDPED criteria; it also identified mutations in 37% of those with a diagnosis of probable/possible FH, thus giving a definite diagnosis. Patients harboring null mutations had shorter PCVD-free survival times and higher relative risk of PCVD than patients with a missense mutation. CONCLUSIONS: The proposed DNA array allows large-scale population screening and provides molecular information regarding mutation type and its correlation with clinical severity of FH, which can be used to develop therapeutic strategies.