Possibility of multivariate function composed of plasma amino acid profiles as a novel screening index for non-small cell lung cancer: a case control study

<p>Abstract</p> <p>Background</p> <p>The amino-acid balance in cancer patients often differs from that in healthy individuals, because of metabolic changes. This study investigated the use of plasma amino-acid profiles as a novel marker for screening non-small-cell lung cancer (NSCLC) patients.</p> <p>Methods</p> <p>The amino-acid concentrations in venous blood samples from pre-treatment NSCLC patients (<it>n </it>= 141), and age-matched, gender-matched, and smoking status-matched controls (<it>n </it>= 423), were measured using liquid chromatography and mass spectrometry. The resultant study data set was subjected to multiple logistic regression analysis to identify amino acids related with NSCLC and construct the criteria for discriminating NSCLC patients from controls. A test data set derived from 162 patients and 3,917 controls was used to validate the stability of the constructed criteria.</p> <p>Results</p> <p>The plasma amino-acid profiles significantly differed between the NSCLC patients and the controls. The obtained model (including alanine, valine, isoleucine, histidine, tryptophan and ornithine concentrations) performed well, with an area under the curve of the receiver-operator characteristic curve (ROC_AUC) of >0.8, and allowed NSCLC patients and controls to be discriminated regardless of disease stage or histological type.</p> <p>Conclusions</p> <p>This study shows that plasma amino acid profiling will be a potential screening tool for NSCLC.</p

Plasma Free Amino Acid Profiling of Five Types of Cancer Patients and Its Application for Early Detection

BACKGROUND: Recently, rapid advances have been made in metabolomics-based, easy-to-use early cancer detection methods using blood samples. Among metabolites, profiling of plasma free amino acids (PFAAs) is a promising approach because PFAAs link all organ systems and have important roles in metabolism. Furthermore, PFAA profiles are known to be influenced by specific diseases, including cancers. Therefore, the purpose of the present study was to determine the characteristics of the PFAA profiles in cancer patients and the possibility of using this information for early detection. METHODS AND FINDINGS: Plasma samples were collected from approximately 200 patients from multiple institutes, each diagnosed with one of the following five types of cancer: lung, gastric, colorectal, breast, or prostate cancer. Patients were compared to gender- and age- matched controls also used in this study. The PFAA levels were measured using high-performance liquid chromatography (HPLC)-electrospray ionization (ESI)-mass spectrometry (MS). Univariate analysis revealed significant differences in the PFAA profiles between the controls and the patients with any of the five types of cancer listed above, even those with asymptomatic early-stage disease. Furthermore, multivariate analysis clearly discriminated the cancer patients from the controls in terms of the area under the receiver-operator characteristics curve (AUC of ROC >0.75 for each cancer), regardless of cancer stage. Because this study was designed as case-control study, further investigations, including model construction and validation using cohorts with larger sample sizes, are necessary to determine the usefulness of PFAA profiling. CONCLUSIONS: These findings suggest that PFAA profiling has great potential for improving cancer screening and diagnosis and understanding disease pathogenesis. PFAA profiles can also be used to determine various disease diagnoses from a single blood sample, which involves a relatively simple plasma assay and imposes a lower physical burden on subjects when compared to existing screening methods

INTEGRATIVE SYSTEM BIOLOGY STUDIES ON HIGH THROUGHPUT GENOMICS AND PROTEOMICS DATASET

Indiana University-Purdue University Indianapolis (IUPUI)The post genomic era has propelled us to the view that the biological systems are complex network of interacting genes, proteins and small molecules that give rise to biological form and function. The past decade has seen the advent of number of new technologies designed to study the biological systems on a genome wide scale. These new technologies offers an insight in to the activity of thousands of genes and proteins in cell thereby changed the conventional reductionist view of the systems. However the deluge of data surpasses the analytical and critical abilities of the researches and thereby demands the development of new computational methods. The challenge no longer lies in the acquisition of expression profiles, but rather in the interpretation for the results to gain insights into biological mechanisms. In three different case studies, we applied various system biology techniques on publicly available and in-house genomics and proteomics data set to identify sub-network signatures. In First study, we integrated prior knowledge from gene signatures, GSEA and gene/protein network modeling to identify pathways involved in colorectal cancer, while in second, we identified plasma based network signatures for Alzheimer's disease by combining various feature selection and classification approach. In final study, we did an integrated miRNA-mRNA analysis to identify the role of Myeloid Derived Stem Cells (MDSCs) in T-Cell suppression

Non-invasive, innovative and promising strategy for breast cancer diagnosis based on metabolomic profile of urine, cancer cell lines and tissue

The work presented in this thesis aimed to establish the metabolomic profile of urine and breast cancer (BC) tissue from BC patients (samples cordially provided by Funchal Hospital), in addition to BC cell lines (MCF-7, MDA-MB-231, T-47D) as a powerful strategy to identify metabolites as potential BC biomarkers, helping on the development of non-invasive approaches for BC diagnosis and management. To achieve the main goal and obtain a deeper and comprehensive knowledge on BC metabolome, different analytical platforms, namely headspace solid-phase microextraction (HSSPME) combined with gas chromatography-quadrupole mass spectrometry (GC-qMS) and nuclear magnetic ressonance (1H NMR) spectroscopy were used. The application of multivariate statistical methods - principal component analysis (PCA) and orthogonal partial least square – discriminant analysis (OPLS-DA), to data matrix obtained from the different target samples allowed to find a set of highly sensitive and specific metabolites metabolites, namely, 4-heptanone, acetic acid and glutamine, able to be used as potential biomarkers in BC diagnosis. Significant group separation was observed in OPLS-DA score plot between BC and CTL indicating intrinsic metabolic alterations in each group. To attest the robustness of the model, a random permutation test with 1000 permutations was performed with OPLS-DA. The permutation test yielded R2 (represents goodness of fit) and Q2 values (represents predictive ability) with values higher than 0.717 and 0.691, respectively. Several metabolic pathways were dysregulated in BC considering the analytical approaches used. The main pathways included pyruvate, glutamine and sulfur metabolisms, indicating that there might be an association between the metabolites arising from the type of biological sample of the same donor used to perform the investigation. The integration of data obtained from different analytical platforms (GC-qMS and 1H NMR) for urinary and tissue samples revealed that five metabolites (e.g., acetone, 3-hexanone, 4-heptanone, 2methyl-5-(methylthio)-furan and acetate), were found significant using a dual analytical approach.O trabalho apresentado nesta tese teve como objetivo estabelecer o perfil metabolómico da urina e do tecido da mama de doentes com cancro de mama (BC) (amostras cordialmente fornecidas pelo Hospital do Funchal), além das linhas celulares de BC (MCF-7, MDA-MB-231, T -47D) como uma poderosa estratégia para identificar metabolitos como potenciais biomarcadores de BC, auxiliando no desenvolvimento de abordagens não invasivas para o diagnóstico e a gestão da patologia. Para obter um conhecimento mais profundo e abrangente do metaboloma de BC, diferentes plataformas analíticas, nomeadamente a microextração em fase sólida em modo headspace (HS-SPME) combinada com a cromatografia em fase gasosa acoplada à espectrometria de massa (GC-qMS) e espectroscopia de ressonância magnética nuclear (1H RMN), foram usadas para atingir o objetivo principal. A aplicação de métodos estatísticos multivariados - análise de componentes principais (PCA) e análise discriminante de mínimos quadrados parciais ortogonais (OPLS-DA) à matriz de dados obtida a partir das diferentes amostras alvo, permitiu estabelecer um grupo de metabolitos sensíveis e específicos, nomeadamente a 4-heptanona, o ácido acético e a glutamina, possíveis de serem utilizados como potenciais biomarcadores no diagnóstico de BC. Uma separação significativa entre os grupos BC e CTL foi observada pelo OPLS-DA, indicando alterações metabólicas em cada grupo. Para verificar a robustez do modelo, foi realizado um teste de permutação aleatória com 1000 permutações com o sistema OPLS-DA. Valores de R2 (representa o ajuste) e Q2 (representa a capacidade preditiva) superiores a 0,717 e 0,691, foram obtidos utilizando o teste da permutação. Diversas vias metabólicas estavam desreguladas no BC considerando as abordagens analíticas utilizadas. As principais vias incluíram os metabolismos do piruvato e glutamina, indicando que poderá haver uma associação entre os metabolitos derivados do tipo de amostra biológica do mesmo doador utilizado para realizar a investigação. A integração de dados obtidos pelas diferentes plataformas analíticas (GC-qMS e 1H RMN) para amostras urinárias e de tecido revelou cinco metabolitos significativos usando a dupla abordagem analítica. (i.e., acetona, 3-hexanona, 4-heptanona, 2-metil-5- (metiltio) - furano e acetato)

Metabolic impacts of weight loss intervention on morbid obesity

Morbid obesity can result in life-altering health issues, such as type 2 diabetes. Roux-en-Y gastric bypass (RYGB) surgery has been demonstrated to be one of the most effective treatments for morbid obesity and its co-morbidities in long-term. This aim of this thesis is to investigate the metabolic impact of weight loss intervention (RYGB, caloric restriction, and gut hormone treatment) on urine, plasma, and faecal profiles from morbidly obese patients, and to answer two hypotheses: 1) RYGB-induced metabolic changes are partially attributed to caloric restriction and increased gut hormones; 2) RYGB alters metabolic profile of faecal bacterial pellets separated using a newly developed method. Samples at pre-intervention time point were compared with post-intervention time point, and multivariate and univariate analysis were applied based on different types of datasets using different software to avoid missing potential biomarkers. Samples at post-intervention time point were compared across the intervention groups using the same strategy as above. At 1-month-post-intervention, RYGB-induced metabolic changes could be attributed by caloric restriction via increased metabolisms of ketone bodies, lactic acid, and tricarboxylic acid, and decreased concentrations of total apolipoprotein A1, high-density lipoprotein (HDL) subfraction 3&4, and very-low-density-lipoprotein (VLDL) subfraction 5. RYGB-induced distinct metabolic changes included metabolisms of amino acids, short chain fatty acids, creatine, increased concentration of low-density lipoprotein fraction of triglycerides, and decreased concentration of HDL subfraction 2 of phospholipids. Gut hormone treatment exerted limited metabolic effects on urine and plasma samples. A separation method was developed for faecal bacterial pellets profiling and applied on RYGB and caloric restriction cohorts. Propionate and butyrate productions via dicarboxylic acid pathway were increased significantly 2-5 years after RYGB and 3 months after caloric restriction, respectively. My study showed RYGB-induced metabolic changes could not be fully explained by caloric restriction nor increased gut hormone levels; Gut hormone treatment induced limited metabolic changes and could be an alternate therapy for morbid obesity followed by clinical trial with increased sample size and follow-up study in long term.Open Acces