The treatment of central nervous system (CNS) tumors is complicated by high rates of recurrence and treatment resistance that contribute to high morbidity and mortality (Nat Rev Neurol. 2022;18:221–36. doi: 10.1038/s41582-022-00621-0). One of the challenges of treating these tumors is the limited permeability of the blood brain barrier (BBB). Early pharmacologic treatments worked to overcome the BBB by targeting vulnerabilities in the tumor cell replication process directly through alkylating agents like temozolomide. However, as advancements have been made options have expanded to include immunologic targets through the use of monoclonal antibodies. In the future, treatment will likely continue to focus on the use of immunotherapies, as well as emerging technology like the use of low-intensity focused ultrasound (LIFU). Ultimately, this paper serves as an introductory overview of current therapeutic options for post-resection primary brain tumors, as well as a look towards future work and emerging treatment options.

Hepatocellular carcinoma (HCC) is a complex process that plays an important role in its progression. Abnormal glucose metabolism in HCC cells can meet the nutrients required for the occurrence and development of liver cancer, better adapt to changes in the surrounding microenvironment, and escape the attack of the immune system on the tumor. There is a close relationship between reprogramming of glucose metabolism and immune escape. This article reviews the current status and progress of glucose metabolism reprogramming in promoting immune escape in liver cancer, aiming to provide new strategies for clinical immunotherapy of liver cancer.

Transmission of a malignancy from a donor’s organ to the recipient of the graft is a rare event, though it is a severe complication that can result in a poor outcome. Usually, immunosuppressive therapy is discontinued and the allograft is removed. However, treatment of patients with the disseminated cancers implies that after the graft removal and cessation of the immunosuppression, radiotherapy, chemotherapy, or immunotherapy with alpha-interferon (INF-α) or interleukin-2 (IL-2) are required. The case report presents a clinical case of a transmitted kidney graft with multiple metastases (MTS) in a 31-year-old woman with the spontaneous regression of the metastatic cancer after transplantectomy and cancellation of the immunosuppressive therapy. Obviously, the determining factor is the recognition of the tumor by the effectors of the antitumor immunity due to the human leukocyte antigen (HLA) mismatch between the donor and the recipient. Therefore, cancellation of the immunosuppressive therapy in cases of transferal of a malignancy with a transplanted organ allows the effectors of the immune system to distinguish the tumor as a foreign tissue and effectively eliminate this neoplasm.

Soft tissue sarcomas (STSs) are rare, heterogeneous, and very often asymptomatic diseases. Their diagnosis is fundamental, as is the identification of the degree of malignancy, which may be high, medium, or low. The Italian Medical Oncology Association and European Society of Medical Oncology (ESMO) guidelines recommend magnetic resonance imaging (MRI) because the clinical examination is typically ineffective. The diagnosis of these rare diseases with artificial intelligence (AI) techniques presents reduced datasets and therefore less robust methods. However, the combination of AI techniques with radiomics may be a new angle in diagnosing rare diseases such as STSs. Results obtained are promising within the literature, not only for the performance but also for the explicability of the data. In fact, one can make tumor classification, site localization, and prediction of the risk of developing metastasis. Thanks to the synergy between computer scientists and radiologists, linking numerical features to radiological evidence with excellent performance could be a new step forward for the diagnosis of rare diseases.

Cancer remains the second leading cause of death worldwide despite modern breakthroughs in medicine, and novel treatments are urgently needed. The revolutionary success of immune checkpoint inhibitors in the past decade serves as proof of concept that the immune system can be effectively harnessed to treat cancer. Cytokines are small signalling proteins with critical roles in orchestrating the immune response and have become an attractive target for immunotherapy. Type 1 immune cytokines, including interferon γ (IFNγ), interleukin-12 (IL-12), and tumour necrosis factor α (TNFα), have been shown to have largely tumour suppressive roles in part through orchestrating anti-tumour immune responses mediated by natural killer (NK) cells, CD8⁺ T cells and T helper 1 (Th1) cells. Conversely, type 2 immunity involving group 2 innate lymphoid cells (ILC2s) and Th2 cells are involved in tissue regeneration and wound repair and are traditionally thought to have pro-tumoural effects. However, it is found that the classical type 2 immune cytokines IL-4, IL-5, IL-9, and IL-13 may have conflicting roles in cancer. Similarly, type 2 immunity-related cytokines IL-25 and IL-33 with recently characterised roles in cancer may either promote or suppress tumorigenesis in a context-dependent manner. Furthermore, type 1 cytokines IFNγ and TNFα have also been found to have pro-tumoural effects under certain circumstances, further complicating the overall picture. Therefore, the dichotomy of type 1 and type 2 cytokines inhibiting and promoting tumours respectively is not concrete, and attempts of utilising these for cancer immunotherapy must take into account all available evidence. This review provides an overview summarising the current understanding of type 1 and type 2 cytokines in tumour immunity and discusses the prospects of harnessing these for immunotherapy in light of previous and ongoing clinical trials.

Immunotherapy strategies targeting immune checkpoint molecules such as programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) are revolutionizing oncology. However, its effectiveness is limited in part due to the loss of effector cytotoxic T lymphocytes. Interestingly, supplementation of vitamin D could abolish the repressive effect of programmed cell death-ligand 1 (PD-L1) on CD8⁺ T cells, which might prevent the lymphocytopenia. In addition, vitamin D signaling could contribute to the differentiation of T-regulatory (Treg) cells associated with the expression of Treg markers such as forkhead box P3 (FOXP3) and CTLA-4. Furthermore, vitamin D may be associated with the stimulation of innate immunity. Peroxisome proliferator-activated receptor (PPAR) and estrogen receptor (ESR) signaling, and even the signaling from phosphoinositide-3 kinase (PI3K)/AKT pathway could have inhibitory roles in carcinogenesis possibly via the modulation of immune checkpoint molecules. In some cases, certain small molecules including vitamin D could be a novel therapeutic modality with a promising potential for the better performance of immune checkpoint blockade cancer therapies.

Rectal cancer (RC) is one of the most common tumours worldwide in both males and females, with significant morbidity and mortality rates, and it accounts for approximately one-third of colorectal cancers (CRCs). Magnetic resonance imaging (MRI) has been demonstrated to be accurate in evaluating the tumour location and stage, mucin content, invasion depth, lymph node (LN) metastasis, extramural vascular invasion (EMVI), and involvement of the mesorectal fascia (MRF). However, these features alone remain insufficient to precisely guide treatment decisions. Therefore, new imaging biomarkers are necessary to define tumour characteristics for staging and restaging patients with RC. During the last decades, RC evaluation via MRI-based radiomics and artificial intelligence (AI) tools has been a research hotspot. The aim of this review was to summarise the achievement of MRI-based radiomics and AI for the evaluation of staging, response to therapy, genotyping, prediction of high-risk factors, and prognosis in the field of RC. Moreover, future challenges and limitations of these tools that need to be solved to favour the transition from academic research to the clinical setting will be discussed.