As medical science and technology progress towards the era of “big data”, a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC’s diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

Non‐melanoma skin cancer frequently results from chronic exposure to ultraviolet (UV) irradiation. UV‐induced DNA damage activates cell cycle arrest checkpoints through degradation of the cyclin‐dependent kinase activators, the cell division cycle 25 (CDC25) phosphatases. We previously reported increased CDC25A in nonmelanoma skin cancer, but CDC25B and CDC25C had not been previously examined. Consequently, we hypothesized that increased expression of CDC25B and CDC25C increases tumor cell proliferation and skin tumor growth. We found that CDC25B and CDC25C were increased in mouse and human skin cancers. CDC25B was primarily cytoplasmic in skin and skin tumors and was significantly increased in the squamous cell carcinoma (SCC), while CDC25C was mostly nuclear in the skin, with an increased cytoplasmic signal in the premalignant and malignant tumors. Surprisingly, forced expression of CDC25B or CDC25C in cultured SCC cells did not affect proliferation, but instead suppressed apoptosis, while CDC25C silencing increased apoptosis without impacting proliferation. Targeting CDC25C to the nucleus via mutation of its nuclear export sequence, however, increased proliferation in SCC cells. Overexpression of CDC25C in the nuclear compartment did not hinder the ability of CDC25C to suppress apoptosis, neither did mutation of sites necessary for its interaction with 14‐3‐3 proteins. Analysis of apoptotic signaling pathways revealed that CDC25C increased activating phosphorylation of Akt on Ser⁴⁷³, increased inhibitory phosphorylation of proapoptotic BAD on Ser¹³⁶, and increased the survival protein Survivin. Silencing of CDC25C significantly reduced Survivin levels. Taken together, these data suggest that increased expression of CDC25B or CDC25C are mechanisms by which skin cancers evade apoptotic cell death.

Conventional anticancer treatments, such as radiotherapy and chemotherapy, have significantly improved cancer therapy. Nevertheless, the existing traditional anticancer treatments have been reported to cause serious side effects and resistance to cancer and even to severely affect the quality of life of cancer survivors, which indicates the utmost urgency to develop effective and safe anticancer treatments. As the primary focus of cancer nanotheranostics, nanomaterials with unique surface chemistry and shape have been investigated for integrating cancer diagnostics with treatment techniques, including guiding a prompt diagnosis, precise imaging, treatment with an effective dose, and real-time supervision of therapeutic efficacy. Several theranostic nanosystems have been explored for cancer diagnosis and treatment in the past decade. However, metal-based nanotheranostics continue to be the most common types of nonentities. Consequently, the present review covers the physical characteristics of effective metallic, functionalized, and hybrid nanotheranostic systems. The scope of coverage also includes the clinical advantages and limitations of cancer nanotheranostics. In light of these viewpoints, future research directions exploring the robustness and clinical viability of cancer nanotheranostics through various strategies to enhance the biocompatibility of theranostic nanoparticles are summarised.

Amplification of specific cancer genes leads to their over-expression contributing to tumor growth, spread, and drug resistance. Little is known about the ability of these amplified oncogenes to augment the expression of cancer genes through post-transcriptional control. The AU-rich elements (ARE)-mediated mRNA decay is compromised for many key cancer genes leading to their increased abundance and effects. Here, we performed a post-transcriptional screen for frequently amplified cancer genes demonstrating that ERBB2/Her2 overexpression was able to augment the post-transcriptional effects. The ERBB1/2 inhibitor, lapatinib, led to the reversal of the aberrant ARE-mediated process in ERBB2-amplified breast cancer cells. The intersection of overexpressed genes associated with ERBB2 amplification in TCGA datasets with ARE database (ARED) identified ERBB2-associated gene cluster. Many of these genes were over-expressed in the ERBB2-positive SKBR3 cells compared to MCF10A normal-like cells, and were under-expressed due to ERBB2 siRNA treatment. Lapatinib accelerated the ARE-mRNA decay for several ERBB2-regulated genes. The ERBB2 inhibitor decreased both the abundance and stability of the phosphorylated inactive form of the mRNA decay-promoting protein, tristetraprolin (ZFP36/TTP). The ERBB2 siRNA was also able to reduce the phosphorylated ZFP36/TTP form. In contrast, ectopic expression of ERBB2 in MCF10A or HEK293 cells led to increased abundance of the phosphorylated ZFP36/TTP. The effect of ERBB2 on TTP phosphorylation appeared to be mediated via the MAPK-MK2 pathway. Screening for the impact of other amplified cancer genes in HEK293 cells also demonstrated that EGFR, AKT2, CCND1, CCNE1, SKP2, and FGFR3 caused both increased abundance of phosphorylated ZFP36/TTP and ARE-post-transcriptional reporter activity. Thus, specific amplified oncogenes dysregulate post-transcriptional ARE-mediated effects, and targeting the ARE-mediated pathway itself may provide alternative therapeutic approaches.

The novel coronavirus-19 (SARS-CoV-2), has infected numerous individuals worldwide, resulting in millions of fatalities. The pandemic spread with high mortality rates in multiple waves, leaving others with moderate to severe symptoms. Co-morbidity variables, including hypertension, diabetes, and immunosuppression, have exacerbated the severity of COVID-19. In addition, numerous efforts have been made to comprehend the pathogenic and host variables that contribute to COVID-19 susceptibility and pathogenesis. One of these endeavours is understanding the host genetic factors predisposing an individual to COVID-19. Genome-Wide Association Studies (GWAS) have demonstrated the host predisposition factors in different populations. These factors are involved in the appropriate immune response, their imbalance influences susceptibility or resistance to viral infection. This review investigated the host genetic components implicated at the various stages of viral pathogenesis, including viral entry, pathophysiological alterations, and immunological responses. In addition, the recent and most updated genetic variations associated with multiple host factors affecting COVID-19 pathogenesis are described in the study.