Glioblastoma multiforme (GBM) is known as the most aggressive and prevalent brain tumor with a high mortality rate. It is reported in people who are as young as 10 years old to as old as over 70 years old, exhibiting inter and intra tumor heterogeneity. There are several genomic and proteomic investigations that have been performed to find the unexplored potential targets of the drug against GBM. Therefore, certain effective targets have been taken to further validate the studies embarking on the robustness in the field of medicinal chemistry followed by testing in clinical trials. Also, The Cancer Genome Atlas (TCGA) project has identified certain overexpressed targets involved in the pathogenesis of GBM in three major pathways, i.e., tumor protein 53 (p53), retinoblastoma (RB), and receptor tyrosine kinase (RTK)/rat sarcoma virus (Ras)/phosphoinositide 3-kinase (PI3K) pathways. This review focuses on the compilation of recent developments in the fight against GBM thus, directing future research into the elucidation of pathogenesis and potential cure for GBM. Also, it highlights the potential biomarkers that have undergone extensive research and have promising prognostic and predictive values. Additionally, this manuscript analyses the advent of gene therapy and immunotherapy, unlocking the way to consider treatment approaches other than, or in addition to, conventional chemo-radiation therapies. This review study encompasses all the relevant research studies associated with the pathophysiology, occurrence, diagnostic tools, and therapeutic intervention for GBM. It highlights the evolution of various therapeutic perspectives against GBM from the most conventional form of radiotherapy to the recent advancement of gene/cell/immune therapy. Further, the review focuses on various targeted therapies for GBM including chemotherapy sensitization, radiotherapy, nanoparticles based, immunotherapy, cell therapy, and gene therapy which would offer a comprehensive account for exploring several facets related to GBM prognostics.

The onset and development of breast cancer in postmenopausal women are associated with closely related individual-dependent factors, including weight gain and high levels of circulating androgens. Adipose tissue is the most peripheral site of aromatase enzyme synthesis; therefore, the excessive accumulation of visceral fat results in increased androgens aromatization and estradiol production that provides the microenvironment favorable to tumorigenesis in mammary epithelial cells expressing estrogen receptors (ERs). Moreover, to meet the increased requirement of cholesterol for cell membrane assembly and the production of steroid hormones to sustain their proliferation, ER-positive cells activate de novo cholesterol biosynthesis and subsequent steroidogenesis. Several approaches have been followed to neutralize the de novo cholesterol synthesis, including specific enzyme inhibitors, statins, and, more recently, metformin. Cumulating evidence indicated that inhibiting cholesterol biosynthesis by statins and metformin may be a promising therapeutic strategy to block breast cancer progression. Unlike antiestrogens and aromatase inhibitors (AIs) which compete for binding to ER and inhibit androgens aromatization, respectively, statins block the production of mevalonic acid by inhibiting the activity of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, and metformin hampers the activation of the sterol regulatory element-binding protein 2 (SREBP2) transcription factor, thus inhibiting the synthesis of several enzymes involved in cholesterol biosynthesis. Noteworthy, statins and metformin not only improve the prognosis of overweight patients with ER-positive cancer but also improve the prognosis of patients with triple-negative breast cancer, the aggressive tumor subtype that lacks, at present, specific therapy.

Among the malignant tumors in the central nervous system (CNS), glioma is the most challenging tumor to the public society, which accounts for the majority of intracranial malignant tumors with impaired brain function. In general, conventional therapies are still unable to provide an effective cure. However, novel immunotherapies have changed the treatment scene giving patients a greater potential to attain long term survival, improved quality of life. Having shown favorable results in solid tumors, those therapies are now at a cancer research hotspot, which could even shrink the growth of glioma cells without causing severe complications. However, it is important to recognize that the therapy may be occasionally associated with noteworthy adverse action called immune-related adverse events (IRAEs) which have emerged as a potential limitation of the therapy. Multiple classes of mediators have been developed to enhance the ability of immune system to target malignant tumors including glioma but may also be associated with the IRAEs. In addition, it is probable that it would take long time after the therapy to exhibit severe immune-related disorders. Gut microbiota could play an integral role in optimal immune development and/or appropriate function for the cancer therapy, which is a vital component of the multidirectional communication between immune system, brain, and gut, also known as gut-brain-immune axis. Here, we show the potential effects of the gut-brain-immune axis based on an “engram theory” for the innovative treatment of IRAEs.

The advent of artificial intelligence (AI) represents a real game changer in today’s landscape of breast cancer imaging. Several innovative AI-based tools have been developed and validated in recent years that promise to accelerate the goal of real patient-tailored management. Numerous studies confirm that proper integration of AI into existing clinical workflows could bring significant benefits to women, radiologists, and healthcare systems. The AI-based approach has proved particularly useful for developing new risk prediction models that integrate multi-data streams for planning individualized screening protocols. Furthermore, AI models could help radiologists in the pre-screening and lesion detection phase, increasing diagnostic accuracy, while reducing workload and complications related to overdiagnosis. Radiomics and radiogenomics approaches could extrapolate the so-called imaging signature of the tumor to plan a targeted treatment. The main challenges to the development of AI tools are the huge amounts of high-quality data required to train and validate these models and the need for a multidisciplinary team with solid machine-learning skills. The purpose of this article is to present a summary of the most important AI applications in breast cancer imaging, analyzing possible challenges and new perspectives related to the widespread adoption of these new tools.

Antibody-drug conjugates (ADCs) are a recent, revolutionary approach for malignancies treatment, designed to provide superior efficacy and specific targeting of tumor cells, compared to systemic cytotoxic chemotherapy. Their structure combines highly potent anti-cancer drugs (payloads or warheads) and monoclonal antibodies (Abs), specific for a tumor-associated antigen, via a chemical linker. Because the sensitive targeting capabilities of monoclonal Abs allow the direct delivery of cytotoxic payloads to tumor cells, these agents leave healthy cells unharmed, reducing toxicity. Different ADCs have been approved by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for the treatment of a wide range of malignant conditions, both as monotherapy and in combination with chemotherapy, including for lymphoma patients. Over 100 ADCs are under preclinical and clinical investigation worldwide. This paper it provides an overview of approved and promising ADCs in clinical development for the treatment of lymphoma. Each component of the ADC design, their mechanism of action, and the highlights of their clinical development progress are discussed.

Major advances in cancer treatment have emerged with the introduction of immunotherapies using blocking antibodies that target T-cell inhibitory receptors, such as programmed death-1 (PD-1) and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), known as immune checkpoints. However, most cancer patients do not respond to immune checkpoint blockade (ICB) therapies, suggesting the development of resistance mechanisms associated with either an insufficient number of preexisting tumor-specific T-cell precursors and/or inappropriate T-cell reactivation. To broaden clinical benefit, anti-PD-1/PD-1 ligand (PD-L1) neutralizing antibodies have been combined with therapeutic cancer vaccines based on non-mutant and/or mutant tumor antigens, to stimulate and expand tumor-specific T lymphocytes. Although these combination treatments achieve the expected goal in some patients, relapse linked to alterations in antigen presentation machinery (APM) of cancer cells often occurs leading to tumor escape from CD8 T-cell immunity. Remarkably, an alternative antigenic peptide repertoire, referred to as T-cell epitopes associated with impaired peptide processing (TEIPP), arises on these malignant cells with altered APM. TEIPP are derived from ubiquitous non-mutant self-proteins and represent a unique resource to target immune-edited tumors that have acquired resistance to cytotoxic T lymphocytes (CTLs) related to defects in transporter associated with antigen processing (TAP) and possibly also to ICB. The present review discusses tumor-associated antigens (TAAs) and mutant neoantigens and their use as targets in peptide- and RNA-based therapeutic cancer vaccines. Finally, this paper highlights TEIPP as a promising immunogenic non-mutant neoantigen candidates for active cancer immunotherapy and combination with TAA and mutant neoantigens. Combining these polyepitope cancer vaccines with ICB would broaden T-cell specificity and reinvigorate exhausted antitumor CTL, resulting in the eradication of all types of neoplastic cells, including immune-escaped subtypes.