Association between dysregulated expression of Ca2+ and ROS-related genes and breast cancer patient survival Sofia Ramos, João Gregório, Ana Sofia Fernandes, Nuno Saraiva Frontiers in Bioinformatics, 2025 The intricate interplay between Ca2+ and reactive oxygen species (ROS) signalling systems influences numerous cellular pathways. Dysregulated expression of genes associated with Ca2+ and ROS homeostasis can significantly impact cancer progression. Despite extensive research, various underlying mechanisms remain elusive, lacking a comprehensive unified perspective. Breast cancer (BC) remains the leading cause of cancer-related deaths among women, highlighting the pressing need to discover novel regulatory mechanisms, therapeutic targets, and potential biomarkers. In this study, we employed a bioinformatic approach based on data from The Cancer Genome Atlas to assess the association between combined dysregulation of specific pairs of genes involved in redox- or Ca2+-related cellular homeostases and patient outcome. These genes were selected by differences in their expression between normal and tumour tissues and in their individual association with patient survival rates. Cumulative proportion survival at the 5-year post-diagnosis was calculated for each quartile of expression within the population exhibiting either high or low expression of a second gene. Additional genes with expression positively or negatively correlated with the set of relevant gene pairs were identified, and a gene enrichment analysis was performed. Our results show that the simultaneous dysregulation of a selected number of gene pairs is substantially associated with BC patient survival. Notably, the expression dysregulation of these gene pairs is associated with altered expression of genes linked to cell cycle regulation, cell adhesion, and cell projection processes. This approach exhibits a significant potential to identify new prognostic biomarkers or drug targets for BC.
Lysyl Oxidases Expression and Breast Cancer Progression: A Bioinformatic Analysis Sofia Ramos, Sandra Ferreira, Ana S. Fernandes, Nuno Saraiva Frontiers in Pharmacology, 2022 LOX (Lysyl oxidase) and LOX like 1–4 (LOXL1–4) are amine oxidases that catalyse the cross-linking of elastin and collagen in the extracellular matrix (ECM). This activity can facilitate cell migration and the formation of metastases. Consequently, inhibition of these enzymes and, in particular of LOXL2, has been suggested as a therapeutic strategy to prevent breast cancer metastasis. Although medicinal chemistry studies have struggled to specifically inhibit LOXL2, the importance of selectivity in this context is not clear. To explore the role of each LOX in breast cancer and consequently their potential as biomarkers or therapeutic targets, a bioinformatic-based approach was followed. The expression profile of LOXs, the putative associations among mRNA expression from each LOX and clinical observations, the correlation between expression of LOX enzymes and other genes, and the association between expression of LOXs and the tumour infiltrates were assessed for breast cancer. Overall, the patient outcome and the characteristics of breast tumours with LOX, LOXL1 and LOXL2 upregulation is distinct from those with high expression of LOXL3 and LOXL4. Additionally, the expression correlation between LOXs and other genes involved in cellular processes relevant for cancer biology, also reveals a similar trend for LOX, LOXL1 and LOX2. This work further supports the relevance of LOXL2 as a breast cancer progression biomarker and therapeutic target. We speculate that while the impact of LOXL3 inhibition may vary with breast cancer subtype, the therapeutical inhibition of LOX, LOXL1 and LOXL2 but not of LOXL4 may be the most beneficial.
Gene expression and survival analysis in cancer research using online open access platforms: A comparative analysis Sofia Ramos, Ana Sofia Fernandes, Nuno Saraiva Biomedical and Biopharmaceutical Research, 2020 The development of genomics and transcriptomics and the potential associated with sharing data related with cancer, led to a growing understanding of cancer biology and to the identification of new biomarkers. Analysis of tumor gene expression and associated patient survival rate enables the dissection of the impact of certain genes in cancer patient ́s survival. For that purpose, it is essential to choose user-friendly platforms, where it is easy to analyze, compare and collect information for a certain set of genes. The goal of this article is to compare the content and utility of five open access online platforms for tumor gene expression and patient survival analysis from TCGA datasets – cBioPortal, USCS Xena, GEPIA, UALCAN and ONCOLNC. We explore these platforms from the point of view of a lay user, assessing their applicability to study differences in gene expression in tumor vs normal tissues, or according to cancer stage, and the impact of such expression patterns on patient survival. Although all five platforms are very intuitive and access to the data is easy, they vary in the information available, results visualization, and statistical tests performed. Therefore, the choice of a platform must take into account the study goals. For some purposes, a combination of platforms may be required.
