Juan Ángel Fresno Vara

Implications of oxidative stress and cell membrane lipid peroxidation in human cancer (Spain)

Reactive Oxygen Species (ROS) result from cell metabolism as well as from extracellular processes. ROS exert some functions necessary for cell homeostasis maintenance. When produced in excess they play a role in the causation of cancer. ROS mediated lipid peroxides are of critical importance because they participate in chain reactions that amplify damage to biomolecules including DNA. DNA attack gives rise to mutations that may involve tumor suppressor genes or oncogenes, and this is an oncogenic mechanism. On the other hand, ROS production is a mechanism shared by many chemotherapeutic drugs due to their implication in apoptosis control. The ROS mediated cell responses depend on the duration and intensity of the cells exposing to the increased ROS environment. Thus the statusredox is of great importance for oncogenetic process activation and it is also implicated in tumor susceptibility to specific chemotherapeutic drugs. Phospholipid Hydroperoxide Glutathione Peroxidase (PH-GPx) is an antioxidant enzyme that is able to directly reduce lipid peroxides even when they are bound to cellular membranes. This article will review the relevance of oxidative stress, particularly of lipid peroxidation, in cell response with special focus in carcinogenesis and cancer therapy that suggests PH-GPx as a potentially important enzyme involved in the control of this processes.

Comparison of gene expression profiling by reverse transcription quantitative PCR between fresh frozen and formalin-fixed, paraffin-embedded breast cancer tissues

Recent reports demonstrate the feasibility of quantifying gene expression by using RNA isolated from blocks of formalin-fixed, paraffin-embedded (FFPE) tumor tissue. The development of molecular tests for clinical use based on archival materials would be of great utility in the search for and validation of important genes or gene expression profiles. In this study, we compared the performance of different normalization strategies in the correlation of quantitative data between fresh frozen (FF) and FFPE samples and analyzed the parameters that characterize such correlation for each gene. Total RNA extracted from FFPE samples presented a shift in raw cycle threshold (Cq) values that can be explained by its extensive degradation. Proper normalization can compensate for the effects of RNA degradation in gene expression measurements. We show that correlation between normalized expression values is better for moderately to highly expressed genes whose expression varies significantly between samples. Nevertheless, some genes had no correlation. These genes should not be included in molecular tests for clinical use based on FFPE samples. Our results could serve as a guide when developing clinical diagnostic tests based on RT-qPCR analyses of FFPE tissues in the coming era of treatment decision-making based on gene expression profiling.

PTRF/Cavin-1 and MIF Proteins Are Identified as Non-Small Cell Lung Cancer Biomarkers by Label-Free Proteomics

With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer.

Aurora kinases as prognostic biomarkers in ovarian carcinoma.

We investigated the expression of Aurora kinases A and B by immunohistochemistry in 68 ovarian carcinomas to analyze their prognostic value. The amplification of AURKA gene by fluorescence in situ hybridization was also assessed. Overall, 58.8% and 85.3% of ovarian carcinomas showed expression of Aurora A and B, respectively. Amplification of AURKA was found in 27.6% of cases examined. Tumors with Aurora A expression showed a lower rate of recurrence than those tumors without Aurora A expression (65% versus 91.7%, P = .019). In the univariate analysis, patients with Aurora A and B expression showed an increased progression-free survival (P = .023 and .06, respectively, log-rank test) and overall survival (P = .03 and .02, respectively, log-rank test). The multivariate analysis adjusted to optimal surgery by Cox proportional hazards regression showed Aurora A expression as an independent prognostic factor for progression-free survival (P = .03) and overall survival (P = .02). In conclusion, Aurora A expression seems to have a prognostic value in ovarian carcinoma.

DICER1, DROSHA and miRNAs in patients with non-small cell lung cancer: implications for outcomes and histologic classification.

The clinical and functional significance of RNA-interference machinery in lung cancer is poorly understood. Besides, microRNAs (miRNA) have the potential to serve both as biomarkers and therapeutic agents, by personalizing diagnosis and therapy. In this study, we investigated whether the expression levels of DICER1 and DROSHA, components of the RNA-interference machinery, can predict survival, and whether the miRNA expression profiles can differentiate histologic subtypes in non-small cell lung cancer (NSCLC). Levels of DICER1, DROSHA and five different miRNAs were measured in NSCLC specimens (N = 115) by qRT-PCR assay and correlated with clinical outcomes. Low expression of DROSHA was associated with an increased median survival (154.2 versus 39.8 months, P = 0.016). Also, high DROSHA expression was associated with decreased median survival in the following subgroups: adenocarcinoma (P = 0.011), grade III tumors (P = 0.038) and low-stage patients (P = 0.014). In multivariate analyses, we found two independent predictors of reduced disease-specific survival: high DROSHA expression [hazards ratio = 2.24; P = 0.04] and advanced tumor stage (hazards ratio = 1.29, P = 0.02). In general, the overall tumor miRNA expression was downregulated in our cohort compared with normal tissues. Expression levels of hsa-let-7a (P = 0.005) and miR-16 (P = 0.003) miRNA were significantly higher in squamous cell carcinoma than in adenocarcinoma samples. This study supports the value of the expression profiling of the components of the miRNA-processing machinery in the prognosis of NSCLC patients, especially DROSHA expression levels. In addition, differential expression of miRNAs, such as hsa-let-7a and miR-16 may be helpful tools in the histologic subclassification of NSCLC.

MALDI profiling of human lung cancer subtypes.

Background Proteomics is expected to play a key role in cancer biomarker discovery. Although it has become feasible to rapidly analyze proteins from crude cell extracts using mass spectrometry, complex sample composition hampers this type of measurement. Therefore, for effective proteome analysis, it becomes critical to enrich samples for the analytes of interest. Despite that one-third of the proteins in eukaryotic cells are thought to be phosphorylated at some point in their life cycle, only a low percentage of intracellular proteins is phosphorylated at a given time. Methodology/Principal Findings In this work, we have applied chromatographic phosphopeptide enrichment techniques to reduce the complexity of human clinical samples. A novel method for high-throughput peptide profiling of human tumor samples, using Parallel IMAC and MALDI-TOF MS, is described. We have applied this methodology to analyze human normal and cancer lung samples in the search for new biomarkers. Using a highly reproducible spectral processing algorithm to produce peptide mass profiles with minimal variability across the samples, lineal discriminant-based and decision tree–based classification models were generated. These models can distinguish normal from tumor samples, as well as differentiate the various non–small cell lung cancer histological subtypes. Conclusions/Significance A novel, optimized sample preparation method and a careful data acquisition strategy is described for high-throughput peptide profiling of small amounts of human normal lung and lung cancer samples. We show that the appropriate combination of peptide expression values is able to discriminate normal lung from non-small cell lung cancer samples and among different histological subtypes. Our study does emphasize the great potential of proteomics in the molecular characterization of cancer.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

BackgroundGene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse.MethodsWe included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models.ResultsAn 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database.ConclusionsThis study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples.

Shotgun proteomics of archival triple‐negative breast cancer samples

Triple‐negative breast cancer (TNBC) accounts for 15–20% of all breast cancers, and has a worse prognosis compared with hormone receptor‐positive disease. Its unfavorable outcome and the lack of hormonal receptors determine the use of adjuvant chemotherapy as part of the standard treatment for these tumors, although several studies have documented that the current standard combination chemotherapy is suboptimal. Therefore, a new functional taxonomy of breast cancer and new targets for therapeutic development are urgently needed.

Implication of miRNA in the diagnosis and treatment of breast cancer

Breast cancer (BC) comprises a group of different diseases characterized by changes in tissue structure and gene expression. Recent advances in molecular biology have shed new light on the participation of genes and their products in the biology of BC. MicroRNAs (miRNAs) are small noncoding endogenous RNA molecules that appear to modulate the expression of more than a third of human genes, and their implications in cancer have grasped the attention of the scientific community. Recently, several studies have described the association between miRNA expression profiles and pathological and clinical BC features. Moreover, these molecules represent a new type of molecular marker that can identify prognosis and guide the management of BC patients. With the increasing understanding of miRNA networks and their impact in the biology of BC, as well as the development of viable strategies to modulate specific miRNAs, we could improve the treatment of this disease.

Comparison of prognostic gene profiles using qRT-PCR in paraffin samples: a retrospective study in patients with early breast cancer.

Introduction Gene profiling may improve prognostic accuracy in patients with early breast cancer, but this technology is not widely available. We used commercial assays for qRT-PCR to assess the performance of the gene profiles included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Ratio. Methods 153 patients with early breast cancer and a minimum follow-up of 5 years were included. All tumours were positive for hormonal receptors and 38% had positive lymph nodes; 64% of patients received adjuvant chemotherapy. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) specimens using a specific kit. qRT-PCR amplifications were performed with TaqMan Gene Expression Assays products. We applied the three gene-expression-based models to our patient cohort to compare the predictions derived from these gene sets. Results After a median follow-up of 91 months, 22% of patients relapsed. The distant metastasis-free survival (DMFS) at 5 years was calculated for each profile. For the 70-Gene Signature, DMFS was 95% -good prognosis- versus 66% -poor prognosis. In the case of the Recurrence Score, DMFS was 98%, 81% and 69% for low, intermediate and high-risk groups, respectively. Finally, for the Two-Gene Ratio, DMFS was 86% versus 70%. The 70-Gene Signature and the Recurrence Score were highly informative in identifying patients with distant metastasis, even in multivariate analysis. Conclusion Commercially available assays for qRT-PCR can be used to assess the prognostic utility of previously published gene expression profiles in FFPE material from patients with early breast cancer. Our results, with the use of a different platform and with different material, confirm the robustness of the 70-Gene Signature and represent an independent test for the Recurrence Score, using different primer/probe sets.