Browsing by Author "Pinto, Joana"
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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.
- 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”.
- 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
- Caracterização do exometaboloma volátil de linhas celulares de cancro renal com diferentes potenciais metastáticos e subtipos histológicosPublication . Amaro, Filipa; Pinto, Joana; Rocha, Sílvia; Araújo, Ana Margarida; Miranda-Gonçalves, Vera; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, PaulaO Carcinoma de Células Renais (CCR) representa o terceiro cancro urológico mais frequente e letal em Portugal. Este tipo de cancro inclui vários subtipos histológicos com diferentes potenciais metastáticos, sendo o carcinoma de células claras (ccCCR) e o papilar (pCCR) os mais comuns. É atualmente reconhecida a importância da descoberta de biomarcadores moleculares específicos para o diagnóstico e estadiamento do CCR de forma a superar as limitações dos métodos existentes (ecografia, tomografia computorizada e nefrectomia). O uso da metabolómica constitui uma das abordagens mais promissoras para a identificação de biomarcadores, uma vez que o metabolismo das células tumorais é muito diferente do das células normais. Desta forma, estudos recentes têm mostrado o potencial dos compostos orgânicos voláteis (COVs) e compostos carbonílicos voláteis (CCVs), não só na identificação de novos biomarcadores, mas também na compreensão de vias metabólicas envolvidas na carcinogénese. Objetivos: Este trabalho incluiu o estudo do exometaboloma volátil de linhas celulares dos dois subtipos histológicos mais comuns de CCR (ccCCR e pCCR) com diferentes potenciais metastáticos. Assim, o objetivo principal deste trabalho é identificar os COVs e CCVs, presentes no meio extracelular (exometaboloma), com potencial para serem utilizados como biomarcadores no processo de estadiamento de CCR e consequentemente ajudar na escolha da terapêutica mais dirigida. Material e Métodos: De modo a avaliar as diferenças na composição volátil do exometaboloma de três linhas celulares de ccCCR (não metastáticas: 769-P, 786-O; metastáticas: Caki-1) e duas de pCCR (não metastática: Caki-2; metastática: ACHN), os COVs e CCVs foram extraídos no headspace do meio de cultura por microextração em fase sólida (HS-SPME) e analisados por cromatografia gasosa acoplada à espectrometria de massa (GC-MS). Os dados foram posteriormente tratados através de métodos de análise estatística multivariada e univariada. Resultados: Os resultados obtidos demonstraram que o exometaboloma volátil é mais robusto a discriminar células com diferentes potenciais metastáticos do que a discriminar entre os dois subtipos histológicos. No entanto, foram encontradas diferenças significativas nos níveis de quinze compostos entre ccCCR e pCCR, tais como o 2,4-dimetil-1-hepteno, 3-careno e 4-metilbenzaldeído. Na comparação entre as linhas celulares metastáticas e não metastáticas de ccCCR, foram detetadas alterações nos níveis de diversos alcanos, alcenos e derivados de benzeno, enquanto que nas linhas celulares pCCR, as principais alterações encontradas foram em compostos pertencentes à classe dos aldeídos e cetonas, como o acetaldeído e a 2-pentadecanona. Conclusões: Os resultados obtidos revelaram o potencial do exometaboloma volátil na identificação de biomarcadores promissores para o diagnóstico e estadiamento de CCR.
- 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.
- GC-MS metabolomics reveals distinct profiles of low- and high-grade bladder cancer cultured cellsPublication . Rodrigues, Daniela; Pinto, Joana; Araújo, Ana; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria; Guedes de Pinho, Paula; Carvalho, MárciaPrevious studies have shown that metabolomics can be a useful tool to better understand the mechanisms of carcinogenesis; however, alterations in biochemical pathways that lead to bladder cancer (BC) development have hitherto not been fully investigated. In this study, gas chromatography-mass spectrometry (GC-MS)-based metabolomics was applied to unveil the metabolic alterations between low-grade and high-grade BC cultured cell lines. Multivariable analysis revealed a panel of metabolites responsible for the separation between the two tumorigenic cell lines. Significantly lower levels of fatty acids, including myristic, palmitic, and palmitoleic acids, were found in high-grade versus low-grade BC cells. Furthermore, significantly altered levels of some amino acids were observed between low- and high-grade BC, namely glycine, leucine, methionine, valine, and aspartic acid. This study successfully demonstrated the potential of metabolomic analysis to discriminate BC cells according to tumor aggressiveness. Moreover, these findings suggest that bladder tumorigenic cell lines of different grades disclose distinct metabolic profiles, mainly affecting fatty acid biosynthesis and amino acid metabolism to compensate for higher energetic needs.
- GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patientsPublication . Monteiro, Márcia; Moreira, Nathalie; Pinto, Joana; Pires-Luís, Ana S.; Henrique, Rui; Jerónimo, Carmen; Bastos, Maria de Lourdes; Gil, Ana M.; Carvalho, Márcia; Guedes de Pinho, PaulaThe analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers.
- GC-MS-based endometabolome analysis differentiates prostate cancer from normal prostate cellsPublication . Lima, Ana; Araújo, Ana; Pinto, Joana; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria; Carvalho, Márcia; Guedes de Pinho, PaulaProstate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography-mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine.
- 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.
- Impacto no metabolismo de células de carcinoma de células renais ao tratamento com sunitinib por espectroscopia de ressonância magnética nuclearPublication . Amaro, Filipa; Pisoeiro, Carolina; Miranda-Gonçalves, Vera; Jerónimo, Carmen; Henrique, Rui; Bastos, Maria de Lourdes; Guedes de Pinho, Paula; Carvalho, Márcia; Pinto, Joana
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