Tan Boon Toh

Hepatocellular carcinoma is a devastating malignancy with numerous therapeutic targets to guide treatment strategies against the disease. However, given the limited efficacy of current frontline targeted therapies in prolonging the survival for HCC patients both as single agents and in combination, evaluating the potential of epigenome remodelling as a therapeutic target opens unexplored avenues for the clinical management of HCC. In this study, we identified epigenetic vulnerabilities to expand the repertoire of therapeutic strategies for HCC patients. To identify epigenetic regulators essential in HCC, we integrated the functional responses of six HCC cell lines to genetic perturbation of epigenetic regulators using esiRNA with existing data from publicly available databases. Correlation between phenotypic responses of HCC cells to large-scale genetic knockdown of epigenetic regulators and publicly available datasets narrowed down the pool of epigenetic vulnerabilities in HCC to two prospective epigenetic oncogenes (SUPT7L and SMARCC1) and one prospective epigenetic tumour suppressor (PHF2). Subsequently, PHF2 loss-of-function studies in HCC cells were performed through functional, molecular and proteomic analyses. Deeper investigations into PHF2 further established its functional role in mitigating cancer cell growth in vitro. Molecular and proteomic analyses in PHF2-deficient cells further suggested that PHF2 functionally suppresses cancer growth in part through the regulation of the cytoprotective protein, SRXN1. Further characterisation of PHF2-deficient cells were suggestive of independence from the Keap1-Nrf2 pathway. Collectively, our study suggests that PHF2 acts as a candidate epigenetic tumour suppressor in HCC patients through the downregulation of SRXN1, potentially independent of Nrf2.

Precision oncology has emerged as a promising strategy for treating high-grade gliomas, yet its clinical impact has been disappointing, with over 300 clinical trials on targeted therapies failing to yield substantial improvements in patient outcomes. Current approaches primarily focus on static, marker-driven tumor features, which capture only a small portion of the complex biology that governs therapeutic responses. Functional precision oncology (FPO) offers a complementary approach, enhancing treatment selection in a personalized manner by dynamically testing patient-derived tumor cells against a range of available therapeutic agents. Here this review examines both historical and contemporary treatment strategies for high-grade gliomas and explores underlying reasons for the limited success of multiple precision oncology initiatives. We demonstrate how the incorporation of FPO in the armamentarium of glioma therapies may address these challenges and outline its proposed role as well as the practical considerations in utilizing FPO for clinical decision-making in patients with glioma.

Artificial intelligence is transforming breast cancer management through various machine learning applications. Artificial intelligence supports precision medicine by enhancing detection, diagnosis, prognosis, and treatment response prediction. It achieves this by analysing data from medical imaging, histopathology, genomics and multi-omics sources to improve patient recovery. This review summarises AI-driven advancements across the entire continuum of breast cancer management, spanning detection, diagnosis, prognosis, treatment and recovery. It evaluates their efficacy and limitations, explores their impact on healthcare costs and clinical practice, and addresses key challenges including generalisability, reproducibility and regulatory barriers. Evidence from recent studies highlights AI’s role in improving breast cancer detection, molecular subtyping and prognostic accuracy. It also facilitates more patient-tailored therapeutic strategies and supports quality of life interventions. Nonetheless, the translation of these benefits into clinical practice requires rigorous validation, transparent model development, and equitable implementation.

Soft tissue sarcomas (STS) are rare, heterogeneous tumors with poor survival outcomes, primarily due to reliance on cytotoxic chemotherapy and lack of targeted therapies. Given the uniquely individualized nature of STS, we hypothesized that the ex vivo drug sensitivity platform, quadratic phenotypic optimization platform (QPOP), can predict treatment response and enhance combination therapy design for STS. Using QPOP, we screened 45 primary STS patient samples, and showed improved or concordant patient outcomes that are attributable to QPOP predictions. From a panel of approved and investigational agents, QPOP identified AZD5153 (BET inhibitor) and pazopanib (multi-kinase blocker) as the most effective combination with superior efficacy compared to standard regimens. Validation in a panel of established patient lines and in vivo models supported its synergistic interaction, accompanied by repressed oncogenic MYC and related pathways. These findings provide preliminary clinical evidence for QPOP to predict STS treatment outcomes and guide the development of novel therapeutic strategies for STS patients.

Introduction: High grade astrocytic glioma (HGG) is a lethal solid malignancy with high recurrence rates and limited survival. While several cytotoxic agents have demonstrated efficacy against HGG, drug sensitivity testing platforms to aid in therapy selection are lacking. Patient-derived organoids (PDOs) have been shown to faithfully preserve the biological characteristics of several cancer types including HGG, and coupled with the experimental-analytical hybrid platform Quadratic Phenotypic Optimization Platform (QPOP) which evaluates therapeutic sensitivity at a patient-specific level, may aid as a tool for personalized medical decisions to improve treatment outcomes for HGG patients. Methods: This is an interventional, non-randomized, open-label study, which aims to enroll 10 patients who will receive QPOP-guided chemotherapy at the time of first HGG recurrence following progression on standard first-line therapy. At the initial presentation of HGG, tumor will be harvested for primary PDO generation during the first biopsy/surgery. At the point of tumor recurrence, patients will be enrolled onto the main study to receive systemic therapy as second-line treatment. Subjects who undergo surgery at the time of recurrence will have a second harvest of tissue for PDO generation. Established PDOs will be subject to QPOP analyses to determine their therapeutic sensitivities to specific panels of drugs. A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. The primary endpoint of the study is six-month progression-free survival. The secondary endpoints include twelve-month overall survival, RANO criteria and toxicities. In our radiological biomarker sub-study, we plan to evaluate novel radiopharmaceutical-based neuroimaging in determining blood-brain barrier permeability and to assess in vivo drug effects on tumor vasculature over time. Trial registration: This trial was registered on 8^th September 2022 with ClinicalTrials.gov Identifier: NCT05532397.

Epitranscriptomic RNA modifications are crucial for the maintenance of glioma stem cells (GSCs), the most malignant cells in glioblastoma (GBM). 3-methylcytosine (m³C) is a new epitranscriptomic mark on RNAs and METTL8 represents an m³C writer that is dysregulated in cancer. Although METTL8 has an established function in mitochondrial tRNA (mt-tRNA) m³C modification, alternative splicing of METTL8 can also generate isoforms that localize to the nucleolus where they may regulate R-loop formation. The molecular basis for METTL8 dysregulation in GBM, and which METTL8 isoform(s) may influence GBM cell fate and malignancy remain elusive. Here, we investigated the role of METTL8 in regulating GBM stemness and tumorigenicity. In GSC, METTL8 is exclusively localized to the mitochondrial matrix where it installs m³C on mt-tRNA^Thr/Ser(UCN) for mitochondrial translation and respiration. High expression of METTL8 in GBM is attributed to histone variant H2AZ-mediated chromatin accessibility of HIF1α and portends inferior glioma patient outcome. METTL8 depletion impairs the ability of GSC to self-renew and differentiate, thus retarding tumor growth in an intracranial GBM xenograft model. Interestingly, METTL8 depletion decreases protein levels of HIF1α, which serves as a transcription factor for several receptor tyrosine kinase (RTK) genes, in GSC. Accordingly, METTL8 loss inactivates the RTK/Akt axis leading to heightened sensitivity to Akt inhibitor treatment. These mechanistic findings, along with the intimate link between METTL8 levels and the HIF1α/RTK/Akt axis in glioma patients, guided us to propose a HIF1α/Akt inhibitor combination which potently compromises GSC proliferation/self-renewal in vitro. Thus, METTL8 represents a new GBM dependency that is therapeutically targetable.

Glioblastoma (GBM) is a fatal brain tumour that is traditionally diagnosed based on histological features. Recent molecular profiling studies have reshaped the World Health Organization approach in the classification of central nervous system tumours to include more pathogenetic hallmarks. These studies have revealed that multiple oncogenic pathways are dysregulated, which contributes to the aggressiveness and resistance of GBM. Such findings have shed light on the molecular vulnerability of GBM and have shifted the disease management paradigm from chemotherapy to targeted therapies. Targeted drugs have been developed to inhibit oncogenic targets in GBM, including receptors involved in the angiogenic axis, the signal transducer and activator of transcription 3 (STAT3), the PI3K/AKT/mTOR signalling pathway, the ubiquitination-proteasome pathway, as well as IDH1/2 pathway. While certain targeted drugs showed promising results in vivo, the translatability of such preclinical achievements in GBM remains a barrier. We also discuss the recent developments and clinical assessments of targeted drugs, as well as the prospects of cell-based therapies and combinatorial therapy as novel ways to target GBM. Targeted treatments have demonstrated preclinical efficacy over chemotherapy as an alternative or adjuvant to the current standard of care for GBM, but their clinical efficacy remains hindered by challenges such as blood-brain barrier penetrance of the drugs. The development of combinatorial targeted therapies is expected to improve therapeutic efficacy and overcome drug resistance.

Precise control of cellular signaling events during programmed cell death is crucial yet challenging for cancer therapy. The modulation of signal transduction in cancer cells holds promise but is limited by the lack of efficient, biocompatible, and spatiotemporally controllable approaches. Here we report a photodynamic strategy that modulates both apoptotic and pyroptotic cell death by altering caspase-3 protein activity and the associated signaling crosstalk. This strategy employs a mitochondria-targeting, near-infrared activatable probe (termed M-TOP) that functions via a type-I photochemical mechanism. M-TOP is less dependent on oxygen and more effective in treating drug-resistant cancer cells, even under hypoxic conditions. Our study shows that higher doses of M-TOP induce pyroptotic cell death via the caspase-3/gasdermin-E pathway, whereas lower doses lead to apoptosis. This photodynamic method is effective across diverse gasdermin-E-expressing cancer cells. Moreover, the M-TOP mediated shift from apoptotic to pyroptotic modulation can evoke a controlled inflammatory response, leading to a robust yet balanced immune reaction. This effectively inhibits both distal tumor growth and postsurgical tumor recurrence. This work demonstrates the feasibility of modulating intracellular signaling through the rational design of photodynamic anticancer drugs.

Globally, colorectal cancer (CRC) is the third most frequently occurring cancer. Progression on to an advanced metastatic malignancy (metCRC) is often indicative of poor prognosis, as the 5-year survival rates of patients decline rapidly. Despite the availability of many systemic therapies for the management of metCRC, the long-term efficacies of these regimens are often hindered by the emergence of treatment resistance due to intratumoral and intertumoral heterogeneity. Furthermore, not all systemic therapies have associated biomarkers that can accurately predict patient responses. Hence, a functional personalised oncology (FPO) approach can enable the identification of patient-specific combinatorial vulnerabilities and synergistic combinations as effective treatment strategies. To this end, we established a panel of CRC patient-derived organoids (PDOs) as clinically relevant biological systems, of which three pairs of matched metCRC PDOs were derived from the primary sites (ptCRC) and metastatic lesions (mCRC). Histological and genomic characterisation of these PDOs demonstrated the preservation of histopathological and genetic features found in the parental tumours. Subsequent application of the phenotypic-analytical drug combination interrogation platform, Quadratic Phenotypic Optimisation Platform, in these pairs of PDOs identified patient-specific drug sensitivity profiles to epigenetic-based combination therapies. Most notably, matched PDOs from one patient exhibited differential sensitivity patterns to the rationally designed drug combinations despite being genetically similar. These findings collectively highlight the limitations of current genomic-driven precision medicine in guiding treatment strategies for metCRC patients. Instead, it suggests that epigenomic profiling and application of FPO could complement the identification of novel combinatorial vulnerabilities to target synchronous ptCRC and mCRC.