A Personalized Genomics Approach of the Prostate Cancer

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Papillary Thyroid Cancer Remodels the Genetic Information Processing Pathways

The genetic causes of the differentiated, highly treatable, and mostly non-fatal papillary thyroid cancer (PTC) are not yet fully understood. The mostly accepted PTC etiology blames the altered sequence or/and expression level of certain biomarker genes. However, tumor heterogeneity and the patient's unique set of favoring factors question the fit-for-all gene biomarkers. Publicly accessible gene expression profiles of the cancer nodule and the surrounding normal tissue from a surgically removed PTC tumor were re-analyzed to determine the cancer-induced alterations of the genomic fabrics responsible for major functional pathways. Tumor data were compared with those of standard papillary and anaplastic thyroid cancer cell lines. We found that PTC regulated numerous genes associated with DNA replication, repair, and transcription. Results further indicated that changes of the gene networking in functional pathways and the homeostatic control of transcript abundances also had major contributions to the PTC phenotype occurrence. The purpose to proliferate and invade the entire gland may explain the substantial transcriptomic differences we detected between the cells of the cancer nodule and those spread in homo-cellular cultures (where they need only to survive). In conclusion, the PTC etiology should include the complex molecular mechanisms involved in the remodeling of the genetic information processing pathways.

Low-Salt Diet Regulates the Metabolic and Signal Transduction Genomic Fabrics, and Remodels the Cardiac Normal and Chronic Pathological Pathways

Low-salt diet (LSD) is a constant recommendation to hypertensive patients, but the genomic mechanisms through which it improves cardiac pathophysiology are still not fully understood. Our publicly accessible transcriptomic dataset of the left ventricle myocardium of adult male mice subjected to prolonged LSD or normal diet was analyzed from the perspective of the Genomic Fabric Paradigm. We found that LSD shifted the metabolic priorities by increasing the transcription control for fatty acids biosynthesis while decreasing it for steroid hormone biosynthesis. Moreover, LSD remodeled pathways responsible for cardiac muscle contraction (CMC), chronic Chagas (CHA), diabetic (DIA), dilated (DIL), and hypertrophic (HCM) cardiomyopathies, and their interplays with the glycolysis/glucogenesis (GLY), oxidative phosphorylation (OXP), and adrenergic signaling in cardiomyocytes (ASC). For instance, the statistically (p < 0.05) significant coupling between GLY and ASC was reduced by LSD from 13.82% to 2.91% (i.e., -4.75×), and that of ASC with HCM from 10.50% to 2.83% (-3.71×). The substantial up-regulation of the CMC, ASC, and OXP genes, and the significant weakening of the synchronization of the expression of the HCM, CHA, DIA, and DIL genes within their respective fabrics justify the benefits of the LSD recommendation.

Advanced Molecular Solutions for Cancer Therapy-The Good, the Bad, and the Ugly of the Biomarker Paradigm

Identifying the most effective actionable molecules whose "smart" manipulation might selectively kill/slow down/stop the proliferation of cancer cells, with few side effects on the normal cells of the tissue, was for decades the single major objective of countless investigators [...].

Genomic Fabrics of the Excretory System's Functional Pathways Remodeled in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most frequent form of kidney cancer. Metastatic stages of ccRCC reduce the five-year survival rate to 15%. In this report, we analyze the ccRCC-induced remodeling of the five KEGG-constructed excretory functional pathways in a surgically removed right kidney and its metastasis in the chest wall from the perspective of the Genomic Fabric Paradigm (GFP). The GFP characterizes every single gene in each region by these independent variables: the average expression level (AVE), relative expression variability (REV), and expression correlation (COR) with each other gene. While the traditional approach is limited to only AVE analysis, the novel REV analysis identifies the genes whose correct expression level is critical for cell survival and proliferation. The COR analysis determines the real gene networks responsible for functional pathways. The analyses covered the pathways for aldosterone-regulated sodium reabsorption, collecting duct acid secretion, endocrine and other factor-regulated sodium reabsorption, proximal tubule bicarbonate reclamation, and vasopressin-regulated water reabsorption. The present study confirms the conclusion of our previously published articles on prostate and kidney cancers that even equally graded cancer nodules from the same tumor have different transcriptomic topologies. Therefore, the personalization of anti-cancer therapy should go beyond the individual, to his/her major cancer nodules.

Metabolic Deregulation in Pulmonary Hypertension

The high morbidity and mortality rate of pulmonary arterial hypertension (PAH) is partially explained by metabolic deregulation. The present study complements our previous publication in "Genes" by identifying significant increases of the glucose transporter solute carrier family 2 (Slc2a1), beta nerve growth factor (Ngf), and nuclear factor erythroid-derived 2-like 2 (Nfe2l2) in three standard PAH rat models. PAH was induced by subjecting the animals to hypoxia (HO), or by injecting with monocrotaline in either normal (CM) or hypoxic (HM) atmospheric conditions. The Western blot and double immunofluorescent experiments were complemented with novel analyses of previously published transcriptomic datasets of the animal lungs from the perspective of the Genomic Fabric Paradigm. We found substantial remodeling of the citrate cycle, pyruvate metabolism, glycolysis/gluconeogenesis, and fructose and mannose pathways. According to the transcriptomic distance, glycolysis/gluconeogenesis was the most affected functional pathway in all three PAH models. PAH decoupled the coordinated expression of many metabolic genes, and replaced phosphomannomutase 2 (Pmm2) with phosphomannomutase 1 (Pmm1) in the center of the fructose and mannose metabolism. We also found significant regulation of key genes involved in PAH channelopathies. In conclusion, our data show that metabolic dysregulation is a major PAH pathogenic factor.

TOR1B: a predictor of bone metastasis in breast cancer patients

Recent therapeutic advances in breast cancer (BC) have improved survival outcomes; however, the prognosis for patients with bone metastasis (BM) remains poor. Hence, novel clinical biomarkers are needed to accurately predict BC BM as well as to promote personalized medicine. Here, we discovered a novel biomarker, TOR1B, for BM in BC patients via analysis of BC gene expression data and clinical information downloaded from open public databases. In cancer cells, we found high expression levels of TOR1B in the nucleus and endoplasmic reticulum. Regarding gene expression, the level of TOR1B was significantly upregulated in BC patients with BM (p < 0.05), and the result was externally validated. In addition, gene expression clearly demonstrated two distinct types of prognoses in ER- and PR-positive patients. In multivariate regression, the gene could be an independent predictor of BM in BC patients, i.e., a low expression level of TOR1B was associated with delayed metastasis to bone in BC patients (HR, 0.28; 95% CI 0.094-0.84). Conclusively, TOR1B might be a useful biomarker for predicting BM; specifically, patients with ER- and PR-positive subtypes would benefit from the clinical use of this promising prognostic biomarker.

Theory and Applications of the (Cardio) Genomic Fabric Approach to Post-Ischemic and Hypoxia-Induced Heart Failure

The genomic fabric paradigm (GFP) characterizes the transcriptome topology by the transcripts’ abundances, the variability of the expression profile, and the inter-coordination of gene expressions in each pathophysiological condition. The expression variability analysis provides an indirect estimate of the cell capability to limit the stochastic fluctuations of the expression levels of key genes, while the expression coordination analysis determines the gene networks in functional pathways. This report illustrates the theoretical bases and the mathematical framework of the GFP with applications to our microarray data from mouse models of post ischemic, and constant and intermittent hypoxia-induced heart failures. GFP analyses revealed the myocardium priorities in keeping the expression of key genes within narrow intervals, determined the statistically significant gene interlinkages, and identified the gene master regulators in the mouse heart left ventricle under normal and ischemic conditions. We quantified the expression regulation, alteration of the expression control, and remodeling of the gene networks caused by the oxygen deprivation and determined the efficacy of the bone marrow mono-nuclear stem cell injections to restore the normal transcriptome. Through the comprehensive assessment of the transcriptome, GFP would pave the way towards the development of personalized gene therapy of cardiac diseases.

Personalized 3-Gene Panel for Prostate Cancer Target Therapy

Many years and billions spent for research did not yet produce an effective answer to prostate cancer (PCa). Not only each human, but even each cancer nodule in the same tumor, has unique transcriptome topology. The differences go beyond the expression level to the expression control and networking of individual genes. The unrepeatable heterogeneous transcriptomic organization among men makes the quest for universal biomarkers and “fit-for-all” treatments unrealistic. We present a bioinformatics procedure to identify each patient’s unique triplet of PCa Gene Master Regulators (GMRs) and predict consequences of their experimental manipulation. The procedure is based on the Genomic Fabric Paradigm (GFP), which characterizes each individual gene by the independent expression level, expression variability and expression coordination with each other gene. GFP can identify the GMRs whose controlled alteration would selectively kill the cancer cells with little consequence on the normal tissue. The method was applied to microarray data on surgically removed prostates from two men with metastatic PCas (each with three distinct cancer nodules), and DU145 and LNCaP PCa cell lines. The applications verified that each PCa case is unique and predicted the consequences of the GMRs’ manipulation. The predictions are theoretical and need further experimental validation.

Role of adaptin protein complexes in intracellular trafficking and their impact on diseases

Adaptin proteins (APs) play a crucial role in intracellular cell trafficking. The 'classical' role of APs is carried out by AP1‒3, which bind to clathrin, cargo, and accessory proteins. Accordingly, AP1-3 are crucial for both vesicle formation and sorting. All APs consist of four subunits that are indispensable for their functions. In fact, based on studies using cells, model organism knockdown/knock-out, and human variants, each subunit plays crucial roles and contributes to the specificity of each AP. These studies also revealed that the sorting and intracellular trafficking function of AP can exert varying effects on pathology by controlling features such as cell development, signal transduction related to the apoptosis and proliferation pathways in cancer cells, organelle integrity, receptor presentation, and viral infection. Although the roles and functions of AP1‒3 are relatively well studied, the functions of the less abundant and more recently identified APs, AP4 and AP5, are still to be investigated. Further studies on these APs may enable a better understanding and targeting of specific diseases.APs known or suggested locations and functions.