Laureano Simón

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 C677T polymorphism in the MTHFR gene is associated with the toxicity of methotrexate in a Spanish rheumatoid arthritis population.

Objective: Methotrexate (MTX) is the first-choice drug for the treatment of rheumatoid arthritis (RA) patients. However, 30% of RA patients discontinue therapy within 1 year, usually because of adverse effects. Previous studies have reported conflicting results on the association of polymorphisms in the MTHFR gene with the toxicity of MTX in RA. The aim of this study was to assess the involvement of the C677T and A1298C polymorphisms in the MTHFR gene in the toxicity of MTX in a Spanish RA population. Methods: The study included retrospectively 468 Spanish RA patients treated with MTX. Single nucleotide polymorphism (SNP) genotyping was performed using the oligonucleotide microarray technique. Allele and genotype association analyses with regard to MTX toxicity and a haplotype association test were also performed. Results: Eighty-four out of the 468 patients (18%) had to discontinue therapy due to adverse effects or MTX toxicity. The C677T polymorphism (rs1801133) was associated with increased MTX toxicity [odds ratio (OR) 1.42, 95% confidence interval (CI) 1.01–1.98, p = 0.0428], and the strongest association was shown in the recessive model (OR 1.95, 95% CI 1.08–3.53, p = 0.0246). The A1298C polymorphism (rs1801131) was not associated with increased MTX toxicity (OR 0.94, 95% CI 0.65–1.38, p = 0.761). A borderline significant risk haplotype was found: 677T-1298A (OR 1.40, 95% CI 1.00–1.96, p = 0.0518). Conclusion: These results demonstrate that the C677T polymorphism in the MTHFR gene is associated with MTX toxicity in a Spanish RA population.

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.

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.

Genetic predisposition to early recurrence in clinically localized prostate cancer.

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.

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.

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.