Histone deacetylases (HDACs) are a class of zinc (Zn)-dependent metalloenzymes that are responsible for epigenetic modifications. HDACs are largely associated with histone proteins that regulate gene expression at the DNA level. This tight regulation is controlled by acetylation [via histone acetyl transferases (HATs)] and deacetylation (via HDACs) of histone and non-histone proteins that alter the coiling state of DNA, thus impacting gene expression as a downstream effect. For the last two decades, HDACs have been studied extensively and indicated in a range of diseases where HDAC dysregulation has been strongly correlated with disease emergence and progression—most prominently, cancer, neurodegenerative diseases, HIV, and inflammatory diseases. The involvement of HDACs as regulators in these biochemical pathways established them as an attractive therapeutic target. This review summarizes the drug development efforts exerted to create HDAC inhibitors (HDACis), specifically class I HDACs, with a focus on the medicinal chemistry, structural design, and pharmacology aspects of these inhibitors.

Cancer stem-like cells (CSCs) identified by self-renewal ability and tumor-initiating potential are responsible for tumor recurrence and metastasis in many cancers. Conventional chemotherapy fails to eradicate CSCs that hold a state of dormancy and possess multi-drug resistance. Spurred by the progress of nanotechnology for drug delivery and biomedical applications, nanomedicine has been increasingly developed to tackle stemness-associated chemotherapeutic resistance for cancer therapy. This review focuses on advances in nanomedicine-mediated therapeutic strategies to overcome chemoresistance by specifically targeting CSCs, the combination of chemotherapeutics with chemopotentiators, and programmable controlled drug release. Perspectives from materials and formulations at the nano-scales are specifically surveyed. Future opportunities and challenges are also discussed.

Precision oncology is a rapidly evolving field that uses advanced technologies to deliver personalized cancer care based on a patient’s unique genetic and clinical profile. The use of artificial intelligence (AI) in precision oncology has shown great potential to improve diagnosis, treatment planning, and treatment outcomes. However, the integration of AI in precision oncology also raises important ethical considerations related to patient privacy, autonomy, and protection from bias. In this opinion paper, an overview is provided of previous studies that have explored the use of AI in precision oncology and the ethical considerations associated with this technology. The conclusions of these studies are compared, and the importance of approaching the use of AI in precision oncology with caution is emphasized. It is stressed that patient privacy, autonomy, and protection from bias should be made central to the development and use of AI in precision oncology. Clear guidelines and regulations must be established to ensure that AI is used ethically and for the benefit of patients. The use of AI in precision oncology has the potential to revolutionize cancer care, but it should be ensured that it striked a balance between advancements in technology and ethical considerations. In conclusion, the use of AI in precision oncology is a promising development that has the potential to improve cancer outcomes. However, ethical considerations related to patient privacy, autonomy, and protection from bias must be central to the development and use of AI in precision oncology.

One of the major causes of death on the globe is cancer. The fourth most frequent malignancy in women worldwide is cervical cancer. Several cancer patients are remaining incurable due to the emergence of medication resistance, despite notable advances in cancer research over the previous few decades. The importance of natural sources as possible therapeutic candidates may be significant. Anthraquinones are one of the many chemical families of natural products, and they stand out for their wide range of structural variations, notable biological activity, and low toxicity. A natural substance called emodin, an anthraquinone derivative, is present in the roots and rhizomes of several plants. This substance has demonstrated antineoplastic, anti-inflammatory, antiangiogenic, and antiproliferative properties. It is also capable of preventing cancer spread and can reverse cancer cells’ multidrug resistance. Emodin, a broad-spectrum inhibitor of cancer cells, have anticancer properties in many different types of biological pathways. These molecular mechanisms in cancer cells include the suppression of cell growth and proliferation, deterioration of the cell cycle arrest, the start of apoptosis, antimetastasis, and antiangiogenic impact. Therefore, the aim of the present review summarised the antiproliferative and anticarcinogenic qualities of cervical cancer of emodin.

Interferon (IFN)-stimulated gene 15 (ISG15) is a member of the ubiquitin-like (UBL) protein family that can modify specific proteins via a catalytic process called ISGylation. This posttranslational modification can modulate the stability of the ISGylated proteins and protein-protein interactions. Some proteins modified by ISG15 have been identified in malignant neoplasms, suggesting the functional relevance of ISGylation in cancer. This review discusses the ISGylated proteins reported in malignant neoplasms that suggest the potential of ISG15 as a biomarker and therapeutic target in cancer.

Epidermal growth factor receptor (EGFR) is one of the most well-studied oncogenes with roles in proliferation, growth, metastasis, and therapeutic resistance. This intense study has led to the development of a range of targeted therapeutics including small-molecule tyrosine kinase inhibitors (TKIs), monoclonal antibodies, and nanobodies. These drugs are excellent at blocking the activation and kinase function of wild-type EGFR (wtEGFR) and several common EGFR mutants. These drugs have significantly improved outcomes for patients with cancers including head and neck, glioblastoma, colorectal, and non-small cell lung cancer (NSCLC). However, therapeutic resistance is often seen, resulting from acquired mutations or activation of compensatory signaling pathways. Additionally, these therapies are ineffective in tumors where EGFR is found predominantly in the nucleus, as can be found in triple negative breast cancer (TNBC). In TNBC, EGFR is subjected to alternative trafficking which drives the nuclear localization of the receptor. In the nucleus, EGFR interacts with several proteins to activate transcription, DNA repair, migration, and chemoresistance. Nuclear EGFR (nEGFR) correlates with metastatic disease and worse patient prognosis yet targeting its nuclear localization has proved difficult. This review provides an overview of current EGFR-targeted therapies and novel peptide-based therapies that block nEGFR, as well as their clinical applications and potential for use in oncology.

Aspirin is a well-known nonsteroidal anti-inflammatory drug (NSAID) that has a recognized role in cancer prevention as well as evidence to support its use as an adjuvant for cancer treatment. Importantly there has been an increasing number of studies contributing to the mechanistic understanding of aspirins’ anti-tumour effects and these studies continue to inform the potential clinical use of aspirin for both the prevention and treatment of cancer. This review focuses on the emerging role of aspirin as a regulator of metabolic reprogramming, an essential “hallmark of cancer” required to support the increased demand for biosynthetic intermediates needed for sustained proliferation. Cancer cells frequently undergo metabolic rewiring driven by oncogenic pathways such as hypoxia-inducible factor (HIF), wingless-related integration site (Wnt), mammalian target of rapamycin (mTOR), and nuclear factor kappa light chain enhancer of activated B cells (NF-κB), which supports the increased proliferative rate as tumours develop and progress. Reviewed here, cellular metabolic reprogramming has been identified as a key mechanism of action of aspirin and include the regulation of key metabolic drivers, the regulation of enzymes involved in glycolysis and glutaminolysis, and altered nutrient utilisation upon aspirin exposure. Importantly, as aspirin treatment exposes metabolic vulnerabilities in tumour cells, there is an opportunity for the use of aspirin in combination with specific metabolic inhibitors in particular, glutaminase (GLS) inhibitors currently in clinical trials such as telaglenastat (CB-839) and IACS-6274 for the treatment of colorectal and potentially other cancers. The increasing evidence that aspirin impacts metabolism in cancer cells suggests that aspirin could provide a simple, relatively safe, and cost-effective way to target this important hallmark of cancer. Excitingly, this review highlights a potential new role for aspirin in improving the efficacy of a new generation of metabolic inhibitors currently undergoing clinical investigation.

Hepatocellular carcinoma (HCC) constitutes an extremely malignant form of primary liver cancer. Intricate connections linking to the immune system might be associated with the pathogenesis of HCC. Meanwhile, immunotherapy with immune checkpoint inhibitors has been established to be a favorable therapeutic possibility for advanced HCC. Although curative opportunities for advanced HCC are restricted, the immune checkpoint immunotherapy has developed as the main choice for treating HCC. However, patients with metabolic-associated fatty liver disease (MAFLD)-linked HCC might be less likely to benefit from the immunotherapy alone. The limitation of the effect of the immunotherapy might be owing to the impaired T cell activation in MAFLD patients, which could be well explained by a dysfunctional gut-liver axis. Gut microbiota and their metabolites including several bile acids could contribute to modulating the responses of the immune checkpoint immunotherapy. Roles of gut microbiota in the development of cancers have expected great interest in the latest studies. Here, an interplay between the gut and liver has been presented, which might suggest to affect the efficacy of immune checkpoint immunotherapy against HCC.

Cancer is a fatal disease and the second most cause of death worldwide. Treatment of cancer is a complex process and requires a multi-modality-based approach. Cancer detection and treatment starts with screening/diagnosis and continues till the patient is alive. Screening/diagnosis of the disease is the beginning of cancer management and continued with the staging of the disease, planning and delivery of treatment, treatment monitoring, and ongoing monitoring and follow-up. Imaging plays an important role in all stages of cancer management. Conventional oncology practice considers that all patients are similar in a disease type, whereas biomarkers subgroup the patients in a disease type which leads to the development of precision oncology. The utilization of the radiomic process has facilitated the advancement of diverse imaging biomarkers that find application in precision oncology. The role of imaging biomarkers and artificial intelligence (AI) in oncology has been investigated by many researchers in the past. The existing literature is suggestive of the increasing role of imaging biomarkers and AI in oncology. However, the stability of radiomic features has also been questioned. The radiomic community has recognized that the instability of radiomic features poses a danger to the global generalization of radiomic-based prediction models. In order to establish radiomic-based imaging biomarkers in oncology, the robustness of radiomic features needs to be established on a priority basis. This is because radiomic models developed in one institution frequently perform poorly in other institutions, most likely due to radiomic feature instability. To generalize radiomic-based prediction models in oncology, a number of initiatives, including Quantitative Imaging Network (QIN), Quantitative Imaging Biomarkers Alliance (QIBA), and Image Biomarker Standardisation Initiative (IBSI), have been launched to stabilize the radiomic features.

Targeting the B-cell lymphoma 2 (Bcl-2) family proteins has been the backbone for hematological malignancies with overall survival improvements. The Bcl-2 family is a major player in apoptosis regulation and, has captured the researcher’s interest in the treatment of solid tumors. Sarcomas are a heterogeneous group of diseases, comprising several entities, with high morbidity and mortality and with few specific therapies available. The treatment for sarcomas is based on platinum regimens, with variable results and poor outcomes, especially in advanced lesions. The high number of different sarcoma entities makes treatment standardization as well as the performance of clinical trials difficult. The use of Bcl-2 family members modifiers has revealed promising results in in vitro and in vivo models and may be a valid option, especially when used in combination with chemotherapy. In this article, a revision of these results and possibilities for the use of Bcl-2 family members inhibitors in sarcomas was performed.

In the past few years, artificial intelligence (AI) has been increasingly used to create tools that can enhance workflow in medicine. In particular, neuro-oncology has benefited from the use of AI and especially machine learning (ML) and radiogenomics, which are subfields of AI. ML can be used to develop algorithms that dynamically learn from available medical data in order to automatically do specific tasks. On the other hand, radiogenomics can identify relationships between tumor genetics and imaging features, thus possibly giving new insights into the pathophysiology of tumors. Therefore, ML and radiogenomics could help treatment tailoring, which is crucial in personalized neuro-oncology. The aim of this review is to illustrate current and possible future applications of ML and radiomics in neuro-oncology.