Browsing by Author "Lima, Ana Rita"
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- Advances and perspectives in prostate cancer biomarker discovery in the last 5 years through tissue and urine metabolomicsPublication . Lima, Ana Rita; Pinto, Joana; Amaro, Filipa; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, PaulaProstate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.
- Analysis of extracellular metabolome by HS-SPME/GC–MS: optimization and application in a pilot study to evaluate galactosamine-induced hepatotoxicityPublication . Araújo, Ana Margarida; Moreira, Nathalie; Lima, Ana Rita; Bastos, Maria de Lourdes; Carvalho, Félix; Carvalho, Márcia; Guedes de Pinho, PaulaTwo methods based on headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-mass spectrometry (GC-MS) were developed to study in vitro the volatile exometabolome, which were then further tested in a pilot study to evaluate galactosamine-induced hepatotoxicity. The analysis of volatile organic compounds (VOCs) was carried out directly in the headspace of the cell culture medium, while some other volatile organic compounds such as volatile carbonyl compounds (VCCs) (aldehydes and ketones) were determined in the headspace of the cell culture medium after a previous derivatization step with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA). Fiber selection was performed using a univariate mode, whereas a central composite design (CCD) was used in the optimization of several other parameters that affect the extraction conditions. VOCs showed optimal extraction results using a DVB/CAR/PDMS fiber, by adding 0.43 g of NaCl to a sample volume of 2 mL and allowing the sample to equilibrate for 10 min at 45 °C with a subsequent extraction for 39 min at the same temperature. For VCCs, the best extraction response was achieved after in-solution (2 mL) derivatization with 0.94 g L-1 of PFBHA (final concentration), followed by an incubation period of 6 min and an extraction time of 37 min at 53 °C, using a PDMS/DVB fiber. The applicability of both optimized methods was then tested, through a untargeted study, on cell culture medium samples obtained from primary mouse hepatocytes (PMH) exposed to three low concentrations (LC01, LC10 and LC30) of the well-known hepatotoxic agent galactosamine (GalN). The results obtained by both methods showed that volatile compounds from GalN exposed cells are separated from controls in a concentration-dependent manner. Several volatile compounds, namely aldehydes, ketones and alcohols, suffered significant alterations, suggesting that GalN induces marked metabolic alterations in cells even at low, non-toxic concentrations. Although preliminary, this metabolomics approach proved its potential to be used in future studies to evaluate toxicity of different xenobiotics.
- Aplicação do volatiloma urinário no diagnóstico não invasivo do carcinoma de células renaisPublication . Pinto, Joana; Amaro, Filipa; Lima, Ana Rita; Carvalho-Maia, Carina; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, PaulaO carcinoma de células renais do subtipo células claras (ccCCR) representa o tipo mais comum (~70%) de cancro renal. Investigações recentes sugerem que o desenvolvimento deste tipo de cancro está relacionado com alterações metabólicas induzidas por mutações que ocorrem em genes que controlam o metabolismo celular (p.ex., von Hippel–Lindau e fumarato hidratase). Deste modo, o estudo de potenciais biomarcadores de ccCCR, através de uma abordagem metabolómica, torna-se bastante pertinente e atual. Em particular, a fração volátil do metaboloma urinário tem revelado resultados muito promissores na identificação de painéis de biomarcadores com elevada sensibilidade para a deteção de cancros urológicos. Devido aos avanços consideráveis na área dos sensores bioelectrónicos, espera-se que num futuro próximo este tipo de cancro possa ser diagnosticado de uma forma simples, rápida e não invasiva em contexto clínico. Objetivos: Este trabalho teve como objetivo principal a identificação de um painel de biomarcadores para deteção não invasiva de ccCCR através da análise do perfil volátil da urina de doentes com ccCCR (n=75) e de indivíduos controlo (sem cancro, n=75). Material e Métodos: Os compostos orgânicos voláteis (COVs), e mais especificamente os compostos carbonílicos voláteis (CCVs), presentes na urina foram analisados por microextração em fase sólida por headspace e cromatografia gasosa acoplada à espectrometria de massa (HS-SPME-GC-MS). Os dados obtidos foram pré-processados e analisados com recurso a ferramentas bioinformáticas. Resultados: Os modelos de classificação obtidos para as análises de COVs e CCVs mostraram uma boa separação entre as urinas de doentes com ccCCR e controlos, com áreas sob a curva (AUC) de 0,846 e 0,818, respetivamente. No total, 22 compostos revelaram alterações estatisticamente significativas entre os dois grupos, incluindo vários aldeídos, cetonas, hidrocarbonetos aromáticos e terpenos. Foi ainda encontrado um conjunto de seis potenciais biomarcadores de ccCCR que revelou uma AUC de 0.869, sensibilidade de 80%, especificidade de 82% e exatidão de 81%. Deste painel fazem parte o octanal, 3-metilbutanal, benzaldeído, 2-furaldeído, 4-heptanona e p-cresol. As desregulações observadas nos níveis destes compostos sugerem alterações no metabolismo energético e uma maior expressão das enzimas ligadas a processos de carcinogénese. Conclusões: Estes resultados confirmam o potencial da assinatura volátil da urina para a deteção não invasiva de ccCCR e revelam um conjunto de biomarcadores moleculares que podem ser utilizados no desenvolvimento de novos materiais que permitam o seu reconhecimento por sensores bioelectrónicos, comummente chamados de “E-noses”.
- Biomarker discovery in human prostate cancer: an update in metabolomics studiesPublication . Lima, Ana Rita; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, PaulaProstate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.
- Caracterização da assinatura metabólica do cancro da próstata em urinaPublication . Lima, Ana Rita; Pinto, Joana; Barros‑Silva, Daniela; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula
- Discrimination between the human prostate normal and cancer cell exometabolome by GC-MSPublication . Lima, Ana Rita; Araújo, Ana Margarida; Pinto, Joana; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, PaulaSerum prostate-specific antigen (PSA) is currently the most used biomarker in clinical practice for prostate cancer (PCa) detection. However, this biomarker has several drawbacks. In this work, an untargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling of PCa cells was performed to prove the concept that metabolic alterations might differentiate PCa cell lines from normal prostate cell line. For that, we assessed the differences in volatile organic compounds (VOCs) profile in the extracellular medium (exometabolome) of four PCa cell lines and one normal prostate cell line at two pH values (pH 2 and 7) by GC-MS. Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal prostate cells. The most altered metabolites included ketones, aldehydes and organic acids. Among these, we highlight pentadecane-2-one and decanoic acid, which were significantly increased in PCa compared to normal cells, and cyclohexanone, 4-methylheptan-2-one, 2-methylpentane-1,3-diol, 4-methylbenzaldehyde, 1-(3,5-dimethylfuran-2-yl)ethanone, methyl benzoate and nonanoic acid, which were significantly decreased in PCa cells. The PCa volatilome was markedly influenced by the VOCs extraction pH, though the discriminant capability was similar. Overall, our data suggest that VOCs monitoring has the potential to be used as a PCa screening methodology.
- Effect of subtoxic and toxic concentrations of galactosamine in the metabolome of primary mouse hepatocytesPublication . Araújo, Ana Margarida; Lima, Ana Rita; de Lourdes Bastos, Maria; Carvalho, Félix; Carvalho, Márcia; de Pinho, Paula Guedes
- Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urinePublication . Lima, Ana Rita; Pinto, Joana; Azevedo, Ana Isabel; Barros-Silva, Daniela; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Guedes de Pinho, Paula; Carvalho, MárciaBackground: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.
- Integration of metabolomics and lipidomics for prostate cancer tissue fingerprintingPublication . Lima, Ana Rita; Carvalho-Maia, Carina; Jerónimo, Carmen; Henrique, Rui; Aveiro, S. S.; Melo, Tânia; Domingues, Rosário; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula; Pinto, Joana
- Investigation of urinary volatile metabolites as potential prostate cancer biomarkers by headspace solid-phase microextraction in combination with gas chromatography-mass spectrometryPublication . Lima, Ana Rita; Azevedo, Ana Isabel; Pinto, Joana; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula