Integrative Biology

Diagnostics of ovarian cancer via metabolite analysis and machine learning

AbstractOvarian cancer (OC) is the second most common cancer of the female reproductive system. Due to the asymptomatic nature of early stages of OC and an increasingly poor prognosis in later stages, methods of screening for OC are much desired. Furthermore, screening and diagnosis processes, in order to justify use on asymptomatic patients, must be convenient and non-invasive. Recent developments in machine-learning technologies have made this possible via techniques in the field of metabolomics. The objective of this research was to use existing metabolomics data on OC and various analytic methods to develop a machine-learning model for the classification of potentially OC-related metabolite biomarkers. Pathway analysis and metabolite-set enrichment analysis were performed on gathered metabolite sets. Quantitative molecular descriptors were then used with various machine-learning classifiers for the diagnostics of OC using related metabolites. We elucidated that the metabolites associated with OC used for machine-learning models are involved in five metabolic pathways linked to OC: Nicotinate and Nicotinamide Metabolism, Glycolysis/Gluconeogenesis, Aminoacyl-tRNA Biosynthesis, Valine, Leucine and Isoleucine Biosynthesis, and Alanine, Aspartate and Glutamate Metabolism. Several classification models for the identification of OC using related metabolites were created and their accuracies were confirmed through testing with 10-fold cross-validation. The most accurate model was able to achieve 85.29% accuracy. The elucidation of biological pathways specific to OC using metabolic data and the observation of changes in these pathways in patients have the potential to contribute to the development of screening techniques for OC. Our results demonstrate the possibility of development of the machine-learning models for OC diagnostics using metabolomics data.

Multi-proteomics investigation of the early response to X-rays and carbon ion irradiations of HeLa cells

Abstract Despite the considerable decline of cervical cancer incidence in developed countries, the disease remains a public health problem in low-income and middle-income countries due to the low popularity of human papillomavirus vaccination and cervical cancer screening. Mainly treated with radiotherapy, the number of recurrences linked to radioresistance increases in women suffering from this disease and constitutes major obstacle. Here, we perform a combined proteomic and phosphoproteomic profiling of HeLa cervical cancer cells after in vitro treatment with X-rays and carbon ions. We observed differential and extensive alterations at the proteins and phosphoproteins levels. In total, we observed 96 and 102 differentially expressed proteins (DEPs) after X-rays and C-ions irradiation, respectively. For phosphoproteins, our results revealed 21 and 41 DEPs in response to C-ions and X-rays ionizing radiation respectively. Furthermore, our study revealed several mechanisms significantly activated by cells in response to ionizing radiation, potentially related to cancer radioresistance, including sister chromatid segregation, rRNA processing, ribosomal large subunit biogenesis, positive regulation of phagocytosis, engulfment, peptidase regulatory activity and negative regulation of ERK1/2 cascade. We also identified three proteins IPM3, DUSP3 and COQ7, oppositely expressed across the C-ions and X-rays groups while MX2 phosphorylation was downregulated in both radiation qualities. Finally, our study revealed a specific kinase signature, associated with Hela cells radioresistance: CDK5, MTOR and CDK2 kinases were predicted in the group of X-rays irradiation while CDK1, PLK1 SRC and MAPK1 kinases were predicted in the group of C-ions irradiation. Taken together, these findings could help to define new potential pathways and biomarkers to be targeted in the treatment of cervical cancer. Insight Box Statement of Integration, Innovation and Insight In this study, a robust proteomic and phospho-proteomic strategy was developed in order to display HELA cells responses to radiations. Two time points were selected to highlight the early responses of cells, following irradiation with low and high LET. CDK1, SRC, MAPK1 kinases were predicted to be activated in response to carbon ions irradiation, while CDK5, MTOR, ATM kinases were predicted in response to X-rays. Several accessions, playing pivotal role in cell proliferation and resistance, were upregulated in X-rays irradiated cells and down regulated in carbon ions irradiated cells. This study gives an accurate picture of molecular events linked with HELA cells radioresistance and offer potential drug targets for optimization of cervical cancer radiotherapy.

Role of RGD-binding Integrins in ovarian cancer progression, metastasis and response to therapy

Abstract Integrins are transmembrane receptors that play a crucial role in cell adhesion and signaling by connecting the extracellular environment to the intracellular cytoskeleton. After binding with specific ligands in the extracellular matrix (ECM), integrins undergo conformational changes that transmit signals across the cell membrane. The integrin-mediated bidirectional signaling triggers various cellular responses, such as changes in cell shape, migration and proliferation. Irregular integrin expression and activity are closely linked to tumor initiation, angiogenesis, cell motility, invasion, and metastasis. Thus, understanding the intricate regulatory mechanism is essential for slowing cancer progression and preventing carcinogenesis. Among the four classes of integrins, the arginine-glycine-aspartic acid (RGD)-binding integrins stand out as the most crucial integrin receptor subfamily in cancer and its metastasis. Dysregulation of almost all RGD-binding integrins promotes ECM degradation in ovarian cancer, resulting in ovarian carcinoma progression and resistance to therapy. Preclinical studies have demonstrated that targeting these integrins with therapeutic antibodies and ligands, such as RGD-containing peptides and their derivatives, can enhance the precision of these therapeutic agents in treating ovarian cancer. Therefore, the development of novel therapeutic agents is essential for treating ovarian cancer. This review mainly discusses genes and their importance across different ovarian cancer subtypes, the involvement of RGD motif-containing ECM proteins in integrin-mediated signaling in ovarian carcinoma, ongoing, completed, partially completed, and unsuccessful clinical trials of therapeutic agents, as well as existing limitations and challenges, advancements made so far, potential strategies, and directions for future research in the field. Insight Box Integrin-mediated signaling regulates cell migration, proliferation and differentiation. Dysregulated integrin expression and activity promote tumor growth and dissemination. Thus, a proper understanding of this complex regulatory mechanism is essential to delay cancer progression and prevent carcinogenesis. Notably, integrins binding to RGD motifs play an important role in tumor initiation, evolution, and metastasis. Preclinical studies have demonstrated that therapeutic agents, such as antibodies and small molecules with RGD motifs, target RGD-binding integrins and disrupt their interactions with the ECM, thereby inhibiting ovarian cancer proliferation and migration. Altogether, this review highlights the potential of RGD-binding integrins in providing new insights into the progression and metastasis of ovarian cancer and how these integrins have been utilized to develop effective treatment plans.