Prostate cancer has a long disease history and a wide variety and uncertainty in individual patients’ clinical progress. In recent years, we have seen a revolutionary advance in both prostate cancer patient care and in the research field. The power of deep sequencing has provided cistromic and transcriptomic knowledge of prostate cancer that has not discovered before. Our understanding of prostate cancer biology, from bedside and molecular imaging techniques, has also been greatly advanced. It is important that our current theragnostic schemes, including our diagnostic modalities, therapeutic responses, and the drugs available to target non-AR signaling should be improved. This review article discusses the current progress in the understanding of prostate cancer biology and the recent advances in diagnostic and therapeutic strategies.

Despite the knowledge that mutation, multiplication, and anomalous function of α-synuclein cause progressive transformation of α-synuclein monomers into toxic amyloid fibrils in neurodegenerative diseases, the understanding of canonical signaling, interaction network molecules, biological functions, and role of α-synuclein remains ambiguous. The evolution of artificial intelligence and Bioinformatics tools have enabled us to analyze a vast pool of data to draw meaningful conclusions about the events occurring in complex biological systems. We have taken the advantage of such a Bioinformatics tool, ingenuity pathway analysis (IPA) to decipher the signaling pathways, interactome, biological functions, and role of α-synuclein. IPA of the α-synuclein NCBI gene dataset revealed neuroinflammation, Huntington’s disease, TREM1, phagosome maturation, and sirtuin signaling as the key canonical signaling pathways. IPA further revealed Parkinson’s disease (PD), sumoylation, and SNARE signaling pathways specific to the toxicity of α-synuclein. A frequency distribution analysis of α-synuclein-associated genes from the NCBI dataset that appeared in the predicted canonical pathways revealed that NFKB1 was the most populated gene across the predicted pathways followed by FOS, PRKCD, TNF, GSK3B, CDC42, IL6, MTOR, PLCB1, and IL1B. Overlapping of the predicted top-five canonical signaling pathways and the α-synuclein NCBI gene dataset divulged that neuroinflammation signaling was the most overlapped pathway, while NFKB1, TNF, and CASP1 were the most shared molecules among the pathways. The major diseases associated with α-synuclein were predicted to be neurological diseases, organismal injury and abnormalities, skeletal and muscular disorders, psychological disorders, and hereditary disorders. The molecule activity predictor (MAP) analysis of the principal interaction network of α-synuclein gene SNCA revealed that SNCA directly interacts with APP, CLU, and NEDD4, whereas it indirectly communicates with CALCA and SOD1. Besides, IPA also predicted amyloid plaque forming APP, cytokines/inflammatory mediators IL1B, TNF, MIF, PTGS2, TP53, and CCL2, and kinases of MAPK family Mek, ERK, and P38 MAPK as the top upstream regulators of α-synuclein signaling cascades. Taken together, the first IPA analysis of α-synuclein predicted PD as the key toxicity pathway, neurodegeneration as the major pathological outcome, and inflammatory mediators as the critical interacting partners of α-synuclein.

Mutations in superoxide dismutase 1 (SOD1) result in misfolding and aggregation of the protein, causing neurodegenerative amyotrophic lateral sclerosis (ALS). In recent years, several new SOD1 variants that trigger ALS have been identified, making it increasingly crucial to understand the SOD1 toxicity pathway in ALS. Here we used an integrated bioinformatics approach, including the Ingenuity Pathway Analysis (IPA) tool to analyze signaling pathways, regulators, functions, and network molecules of SOD1 with an emphasis on ALS. IPA toxicity analysis of SOD1 identified superoxide radicals’ degradation, apelin adipocyte, ALS, NRF2-mediated oxidative stress response, and sirtuin signaling as the key signaling pathways, while the toxicity of SOD1 is exerted via mitochondrial swelling and oxidative stress. IPA listed CNR1, APLN, BTG2, MAPK, DRAP1, NFE2L2, SNCA, and CG as the upstream regulators of SOD1. IPA further revealed that mutation in SOD1 results in hereditary disorders, including ALS. The exploration of the relationship between SOD1 and ALS using IPA unveiled SOD1-ALS pathway molecules. The gene ontology (GO) analysis of SOD1-ALS pathway molecules with ShinyGO reaffirmed that SOD1 toxicity results in ALS and neurodegeneration. The GO analysis further identified enriched biological processes, molecular functions, and cellular components for SOD1-ALS pathway molecules. The construction of a protein–protein interaction network of SOD1-ALS pathway molecules using STRING and further analysis of that network with Cytoscape identified ACTB followed by TP53, IL6, CASP3, SOD1, IL1B, APP, APOE, and VEGFA as the major network hubs. Taken together, our study provides insight into the molecular underpinning of SOD1’s toxicity in ALS.