Cervical cancer is a malignant tumour that occurs in the cervix and is classified into two histological types, adenocarcinoma and squamous cell carcinoma (SCC); SCC is more common and accounts for 70% of all cases. In 2018 there were ~569,000 new cases of cervical cancer diagnosed worldwide and ~311,000 deaths were attributed to cervical cancer. Of these, between 84 and 90% occurred in low‑ and middle‑income countries (LMICs) such as South Africa, India, China and Brazil. The most common cause of cervical cancer is persistent infection caused by the sexually transmitted human papilloma virus. Other factors that contribute to the incidence of cervical cancer include geography, traditional practices and beliefs, the screening levels, socioeconomic status, healthcare access, public awareness, use of oral contraceptives, smoking and co‑infection with HIV. An estimated 11 million women from LMICs will be diagnosed with cervical cancer in the next 10‑20 years. The aim of this review was to explore various types of genetic and epigenetic factors that influence the development, progression or suppression of cervical cancer.

Artificial intelligence (AI) and machine learning have significantly influenced many facets of the healthcare sector. Advancement in technology has paved the way for analysis of big datasets in a cost- and time-effective manner. Clinical oncology and research are reaping the benefits of AI. The burden of cancer is a global phenomenon. Efforts to reduce mortality rates requires early diagnosis for effective therapeutic interventions. However, metastatic and recurrent cancers evolve and acquire drug resistance. It is imperative to detect novel biomarkers that induce drug resistance and identify therapeutic targets to enhance treatment regimes. The introduction of the next generation sequencing (NGS) platforms address these demands, has revolutionised the future of precision oncology. NGS offers several clinical applications that are important for risk predictor, early detection of disease, diagnosis by sequencing and medical imaging, accurate prognosis, biomarker identification and identification of therapeutic targets for novel drug discovery. NGS generates large datasets that demand specialised bioinformatics resources to analyse the data that is relevant and clinically significant. Through these applications of AI, cancer diagnostics and prognostic prediction are enhanced with NGS and medical imaging that delivers high resolution images. Regardless of the improvements in technology, AI has some challenges and limitations, and the clinical application of NGS remains to be validated. By continuing to enhance the progression of innovation and technology, the future of AI and precision oncology show great promise.

Colon cancer is the third most common cancer globally. The risk of developing colon cancer is influenced by a number of factors that include age and diet, but is primarily a genetic disease, resulting from oncogene over-expression and tumour suppressor gene inactivation. The induction and progression of the disease is briefly outlined, as are the cellular changes that occur in its progression. While colon cancer is uniformly amenable to surgery if detected at the early stages, advanced carcinomas are usually lethal, with metastases to the liver being the most common cause of death. Oncogenes and genetic mutations that occur in colon cancer are featured. The molecules and signals that act to eradicate or initiate the apoptosis cascade in cancer cells, are elucidated, and these include caspases, Fas, Bax, Bid, APC, antisense hTERT, PUMA, 15-LOX-1, ceramide, butyrate, tributyrin and PPARgamma, whereas the molecules which promote colon cancer cell survival are p53 mutants, Bcl-2, Neu3 and COX-2. Cancer therapies aimed at controlling colon cancer are reviewed briefly.

Selenium is a trace and necessary micronutrient for human, animal, and microbial health. Many researchers have recently been interested in selenium nanoparticles (SeNPs) due to their biocompatibility, bioavailability, and low toxicity. As a result of their greater bioactivity, selenium nanoparticles are widely employed in a variety of biological applications. Physical, chemical, and biological approaches can all be used to synthesize selenium nanoparticles. Since it uses non-toxic solvents and operates at a suitable temperature, the biological technique is a preferable option. This review article addresses the processes implemented in the synthesis of SeNPs and highlights their medicinal uses, such as the treatment of fungi, bacteria, cancer, and wounds. Furthermore, we discuss the most recent findings on the potential of several biological materials for selenium nanoparticle production. The precursor, extract, process, time, temperature, and other synthesis criteria will be elaborated in conjunction with the product’s physical properties (size, shape, and stability). The synergies of SeNP synthesis via various methods aid future researchers in precisely synthesizing SeNPs and using them in desired applications.

TSPO is a receptor involved in the regulation of cellular proliferation, apoptosis and mitochondrial functions. Previous studies showed that the expression of TSPO protein correlated positively with tumour malignancy and negatively with patient survival. The aim of this study was to determine the transcription of Tspo mRNA in various types of normal and cancer tissues. In situ hybridization was performed to localise the Tspo mRNA in various human normal and cancer tissues. The relative level of Tspo mRNA was quantified using fluorescent intensity and visual estimation of colorimetric staining. RT-PCR was used to confirm these mRNA levels in normal lung, lung cancer, liver cancer, and cervical cancer cell lines. There was a significant increase in the level of transcription in liver, prostate, kidney, and brain cancers while a significant decrease was observed in cancers of the colon and lung. Quantitative RT-PCR confirmed that the mRNA levels of Tspo are higher in a normal lung cell line than in a lung cancer cell line. An increase in the expression levels of Tspo mRNA is not necessarily a good diagnostic biomarker in most cancers with changes not being large enough to be significantly different when detected by in situ hybridisation.

The kallikrein family of serine proteases has been investigated in many inflammatory disorders as molecular mapping, gene characterisation and cloning of kinin receptor genes have unfolded experimentally. In the molecular events of the inflammatory response the kallikrein cascade plays a significant role, since it is considered to initiate and maintain systemic inflammatory responses and immune-modulated disorders. A primary event is the chemotactic attraction of neutrophils which deliver the kallikrein-kinin cascade to sites of cellular injury and carcinogenic transformation of cells. The present study establishes the casual involvement of the kallikrein cascade in infection, inflammatory joint disease, acute transplant rejection, renal glomerular diseases, angiogenesis and carcinoma. We provide strong evidence for new or enhanced expression of kinin B1 receptors in inflammation, and additionally the induction of kallikrein genes in angiogenesis and carcinoma. The results provide insights into possible roles of kallikrein inhibitors and kinin receptor antagonists.