Publicação
MitoProfiles: cancer mitochondrial profiles in high metabolic rate organs
| Resumo: | Metabolic reprogramming is recognized as a critical hallmark of cancer, influencing cancer initiation and progression. Emerging evidence suggests that the metabolism of non-cancer cells within the tumor microenvironment plays a pivotal role in modulating tumor development, underscoring the importance of metabolic variables for better understanding cancer. The main goal of this study is to identify genes exhibiting differential expression in cancer, with a specific emphasis on distinguishing between organs with high metabolic rates (brain, liver, and kidneys) and organs with low metabolic rates (bladder, colon, and skin), particularly focusing on genes encoding mitochondrial proteins. For this, we used two databases containing RNA-seq samples from normal and cancer tissues, obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) projects, respectively. General Linear Models (GLMs) were applied for differential expression analysis, and hierarchical clustering e soft fuzzy clustering to identify distinct gene expression profiles. Our research showed that many of the differentially expressed mitochondrial genes, such as ACSM1 and ACSM5, and PRODH, represent potential adaptations of cancer cells to metabolic and micro environmental stress. Additionally, FDX2, a crucial player in iron-sulfur protein biogenesis, and ACSM2B, responsible for catalyzing the activation of free fatty acids (FFAs) to CoA, showed substantial expression differences, highlighting the importance of these two pathways for the oncogenic process. The most sub stantial genetic expression differences were observed between normal and cancer tissues, rather than between high and low metabolic rate organs, suggesting that the signal from the metabolic rate could be masked by the pronounced changes that cancer induces in cells. Despite the unequal sample sizes and the usage of two different data sources, our findings provide valuable insights into the complex interplay between metabolism and gene expression in cancer. |
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| Autores principais: | Ferreira, Catarina Gomes |
| Assunto: | Cancer Metabolic rate Mitochondrial proteins Differential gene expression Clustering Cancro Taxa metabólica Proteínas mitocondriais Expressão genética diferencial |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Metabolic reprogramming is recognized as a critical hallmark of cancer, influencing cancer initiation and progression. Emerging evidence suggests that the metabolism of non-cancer cells within the tumor microenvironment plays a pivotal role in modulating tumor development, underscoring the importance of metabolic variables for better understanding cancer. The main goal of this study is to identify genes exhibiting differential expression in cancer, with a specific emphasis on distinguishing between organs with high metabolic rates (brain, liver, and kidneys) and organs with low metabolic rates (bladder, colon, and skin), particularly focusing on genes encoding mitochondrial proteins. For this, we used two databases containing RNA-seq samples from normal and cancer tissues, obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) projects, respectively. General Linear Models (GLMs) were applied for differential expression analysis, and hierarchical clustering e soft fuzzy clustering to identify distinct gene expression profiles. Our research showed that many of the differentially expressed mitochondrial genes, such as ACSM1 and ACSM5, and PRODH, represent potential adaptations of cancer cells to metabolic and micro environmental stress. Additionally, FDX2, a crucial player in iron-sulfur protein biogenesis, and ACSM2B, responsible for catalyzing the activation of free fatty acids (FFAs) to CoA, showed substantial expression differences, highlighting the importance of these two pathways for the oncogenic process. The most sub stantial genetic expression differences were observed between normal and cancer tissues, rather than between high and low metabolic rate organs, suggesting that the signal from the metabolic rate could be masked by the pronounced changes that cancer induces in cells. Despite the unequal sample sizes and the usage of two different data sources, our findings provide valuable insights into the complex interplay between metabolism and gene expression in cancer. |
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