Metabolic signature of lung cancer: a metabolomic study of human tissues and biofluids

This thesis reports the application of metabolomics to human tissues and biofluids (blood plasma and urine) to unveil the metabolic signature of primary lung cancer. In Chapter 1, a brief introduction on lung cancer epidemiology and pathogenesis, together with a review of the main metabolic dysregulations known to be associated with cancer, is presented. The metabolomics approach is also described, addressing the analytical and statistical methods employed, as well as the current state of the art on its application to clinical lung cancer studies. Chapter 2 provides the experimental details of this work, in regard to the subjects enrolled, sample collection and analysis, and data processing. In Chapter 3, the metabolic characterization of intact lung tissues (from 56 patients) by proton High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is described. After careful assessment of acquisition conditions and thorough spectral assignment (over 50 metabolites identified), the metabolic profiles of tumour and adjacent control tissues were compared through multivariate analysis. The two tissue classes could be discriminated with 97% accuracy, with 13 metabolites significantly accounting for this discrimination: glucose and acetate (depleted in tumours), together with lactate, alanine, glutamate, GSH, taurine, creatine, phosphocholine, glycerophosphocholine, phosphoethanolamine, uracil nucleotides and peptides (increased in tumours). Some of these variations corroborated typical features of cancer metabolism (e.g., upregulated glycolysis and glutaminolysis), while others suggested less known pathways (e.g., antioxidant protection, protein degradation) to play important roles. Another major and novel finding described in this chapter was the dependence of this metabolic signature on tumour histological subtype. While main alterations in adenocarcinomas (AdC) related to phospholipid and protein metabolisms, squamous cell carcinomas (SqCC) were found to have stronger glycolytic and glutaminolytic profiles, making it possible to build a valid classification model to discriminate these two subtypes. Chapter 4 reports the NMR metabolomic study of blood plasma from over 100 patients and near 100 healthy controls, the multivariate model built having afforded a classification rate of 87%. The two groups were found to differ significantly in the levels of lactate, pyruvate, acetoacetate, LDL+VLDL lipoproteins and glycoproteins (increased in patients), together with glutamine, histidine, valine, methanol, HDL lipoproteins and two unassigned compounds (decreased in patients). Interestingly, these variations were detected from initial disease stages and the magnitude of some of them depended on the histological type, although not allowing AdC vs. SqCC discrimination. Moreover, it is shown in this chapter that age mismatch between control and cancer groups could not be ruled out as a possible confounding factor, and exploratory external validation afforded a classification rate of 85%. The NMR profiling of urine from lung cancer patients and healthy controls is presented in Chapter 5. Compared to plasma, the classification model built with urinary profiles resulted in a superior classification rate (97%). After careful assessment of possible bias from gender, age and smoking habits, a set of 19 metabolites was proposed to be cancer-related (out of which 3 were unknowns and 6 were partially identified as N-acetylated metabolites). As for plasma, these variations were detected regardless of disease stage and showed some dependency on histological subtype, the AdC vs. SqCC model built showing modest predictive power. In addition, preliminary external validation of the urine-based classification model afforded 100% sensitivity and 90% specificity, which are exciting results in terms of potential for future clinical application. Chapter 6 describes the analysis of urine from a subset of patients by a different profiling technique, namely, Ultra-Performance Liquid Chromatography coupled to Mass Spectrometry (UPLC-MS). Although the identification of discriminant metabolites was very limited, multivariate models showed high classification rate and predictive power, thus reinforcing the value of urine in the context of lung cancer diagnosis. Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the potential of integrated metabolomics of tissues and biofluids to improve current understanding of lung cancer altered metabolism and to reveal new marker profiles with diagnostic value.

Antioxidant and detoxify genes polymorphisms in colorectal cancer predisposition

Colorectal cancer (CRC) results from histologic and gene alterations can lead to a massive cellular proliferation. Most of the authors assume multifactorial causes to CRC genesis. Low physical activity, a fat diet poor in fibers and smoking habits seems to have an important role in CRC. However, there are also genetic causes associated with CRC risk. It has been described that oxidative stress levels could influence CRC development. Thus, cellular balance reactive species and defense enzymes involved in oxidative stress are crucial to maintain a good tissue function and avoid neoplasic process. Therefore, genome variations on these defense enzymes, such as MNSOD, SOD3, GSTP1, GSTT1 and GSTM1, could be important biomarkers to colorectal adenocarcinomas. We intend to determine frequencies distribution of most common polymorphisms involved on oxidative stress regulation (MNSOD, SOD3, GSTP1, GSTT1 and GSTM1) in patients with sporadic colorectal adenocarcinoma (SCA) and in healthy controls, evaluation their possible correlation with SCA risk. Samples common polymorphisms of antioxidant and detoxify genes (MNSOD T175C, SOD3 R213G, GSTP1 A105G, GSTP1 C114T, GSTT1del and GSTM1del) analysis was done by PCR-SSP techniques. In this study we found a higher prevalence of MNSOD 175CC (55% vs 2%; p<0.0001; OR: 58.5; CI 13.3 to 256.7), SOD3 213GG (31% vs 2%; p<0.0001; OR: 21.89; CI 4.93 to 97.29), GSTP1 105GG (46% vs 12%; p<0.0001; OR: 6.14; CI 2.85 to 13.26), GSTP1 114TT (38% vs 0%; p<0.0001; OR: Infinity) and GSTT1 null (75% vs 28%; p<0.0001; OR: 7.71; CI 3.83 to 15.56) mutated genotypes among SCA patients, while the normal genotypes were associated with SCA absence. Furthermore, we found GSTP1 114TT mutated genotype (52% vs 27%; p=0.003; OR: 2.88; CI: 1.41 to 5.89) and GSTT1 null genotype (87% vs 65%; p=0.003; OR: 3.66; CI 1.51 to 8.84) associated with colon samples. These findings suggest a positive association between most of common polymorphisms involved on oxidative stress regulation and SCA prevalence. Dysregulation of MNSOD, SOD3, GSTP1, GSTT1 and GSTM1 genes could be associated with an increase of ROS in colon and rectum tissue and p53 pathway deregulation, induced by oxidative stress on colonic and rectal cells. The present study also provides preliminary evidence that MNSOD 175C, SOD3 213G, GSTP1 105G, GSTP1 114T and GSTT1 null polymorphisms, may be involved in SCA risk and could be useful to clarify this multifactorial disorder.