Molecular Markers of Pediatric Solid Tumors—Diagnosis, Optimizing Treatments, and Determining Susceptibility: Current State and Future Directions

Targeting pediatric solid tumors in the new era of RNA therapeutics

Despite substantial progress in pediatric cancer treatment, poor prognosis remained for patients with recurrent or metastatic disease, given the limitations of approved targeted treatments and immunotherapies. RNA therapeutics offer significant potential for addressing a broad spectrum of diseases, including cancer. Advances in manufacturing and delivery systems are paving the way for the rapid development of therapeutic RNAs for clinical applications. This review summarizes therapeutic RNA classifications and the mechanisms of action, highlighting their potential in manipulating major cancer-related pathways and biological effects. We also focus on the pre-clinical investigation of RNA molecules with efficient delivery systems for their therapeutic potential targeting pediatric solid tumors.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

Detection of Naturally occurring abortive transcripts by Base-Stacking Hybridization Assisted Ligation and PCR amplification

Abortive transcripts (ATs) refer to nascent 2-10 nucleotides (nt) RNAs released by RNA polymerases before synthesizing productive RNAs. The quantitative detection of ATs is important for studying transcription initiation and the biological function of ATs; however, no method is available for the qualitative and quantitative assessment of such ultra-short oligonucleotides (typically shorter than 11 nt) in vivo at present, even with the LNA probes, the detection limit can only reach 11 nt. Here, we demonstrated the base stacking hybridization assisted ligation (BSHAL) technique, combined with TaqMan-MGB qPCR, can detect 4-10 nt ATs with a specificity of nucleotide resolution and a sensitivity of approximately 10 pM. By this technique, we detected endogenous ATs in cell lines, mice plasmas, and mice liver tissues, respectively, and proved that naturally occurring ATs do exist. We found that the 8 nt ATs of HMSB and Gapdh could be used as reference ATs for data normalization in Homo and mouse respectively, and 8 nt ATs of Afp and Gpc3 were suitable for use as plasma biomarkers of Hepatocellular carcinoma in mouse, indicate ATs are promising biomarkers. This study offers opportunities to study ATs and other ultra-short oligonucleotides in biological samples.

Targeting B7-H3-A Novel Strategy for the Design of Anticancer Agents for Extracranial Pediatric Solid Tumors Treatment

Recent scientific data recognize the B7-H3 checkpoint molecule as a potential target for immunotherapy of pediatric solid tumors (PSTs). B7-H3 is highly expressed in extracranial PSTs such as neuroblastoma, rhabdomyosarcoma, nephroblastoma, osteosarcoma, and Ewing sarcoma, whereas its expression is absent or very low in normal tissues and organs. The influence of B7-H3 on the biological behavior of malignant solid neoplasms of childhood is expressed through different molecular mechanisms, including stimulation of immune evasion and tumor invasion, and cell-cycle disruption. It has been shown that B7-H3 knockdown decreased tumor cell proliferation and migration, suppressed tumor growth, and enhanced anti-tumor immune response in some pediatric solid cancers. Antibody-drug conjugates targeting B7-H3 exhibited profound anti-tumor effects against preclinical models of pediatric solid malignancies. Moreover, B7-H3-targeting chimeric antigen receptor (CAR)-T cells demonstrated significant in vivo activity against different xenograft models of neuroblastoma, Ewing sarcoma, and osteosarcoma. Finally, clinical studies demonstrated the potent anti-tumor activity of B7-H3-targeting antibody-radioimmunoconjugates in metastatic neuroblastoma. This review summarizes the established data from various PST-related studies, including in vitro, in vivo, and clinical research, and explains all the benefits and potential obstacles of targeting B7-H3 by novel immunotherapeutic agents designed to treat malignant extracranial solid tumors of childhood.

Artificial intelligence assists precision medicine in cancer treatment

Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the same drugs or surgical methods in patients with the same tumor may have different curative effects, leading to the need for more accurate treatment methods for tumors and personalized treatments for patients. The precise treatment of tumors is essential, which renders obtaining an in-depth understanding of the changes that tumors undergo urgent, including changes in their genes, proteins and cancer cell phenotypes, in order to develop targeted treatment strategies for patients. Artificial intelligence (AI) based on big data can extract the hidden patterns, important information, and corresponding knowledge behind the enormous amount of data. For example, the ML and deep learning of subsets of AI can be used to mine the deep-level information in genomics, transcriptomics, proteomics, radiomics, digital pathological images, and other data, which can make clinicians synthetically and comprehensively understand tumors. In addition, AI can find new biomarkers from data to assist tumor screening, detection, diagnosis, treatment and prognosis prediction, so as to providing the best treatment for individual patients and improving their clinical outcomes.

Splicing-Disrupting Mutations in Inherited Predisposition to Solid Pediatric Cancer

The prevalence of hereditary cancer in children was estimated to be very low until recent studies suggested that at least 10% of pediatric cancer patients carry a germline mutation in a cancer predisposition gene. A significant proportion of pathogenic variants associated with an increased risk of hereditary cancer are variants affecting splicing. RNA splicing is an essential process involved in different cellular processes such as proliferation, survival, and differentiation, and alterations in this pathway have been implicated in many human cancers. Hereditary cancer genes are highly susceptible to splicing mutations, and among them there are several genes that may contribute to pediatric solid tumors when mutated in the germline. In this review, we have focused on the analysis of germline splicing-disrupting mutations found in pediatric solid tumors, as the discovery of pathogenic splice variants in pediatric cancer is a growing field for the development of personalized therapies. Therapies developed to correct aberrant splicing in cancer are also discussed as well as the options to improve the diagnostic yield based on the increase in the knowledge in splicing.