A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

Ara-C suppresses H3 K27-altered spinal cord diffuse midline glioma growth and enhances immune checkpoint blockade sensitivity

H3 K27-altered spinal cord diffuse midline glioma (H3-SCDMG) poses therapeutic challenges. Analysis of 73 clinical samples revealed heightened proliferation in H3-SCDMG versus wild-type tumors, suggesting therapeutic vulnerabilities. Drug screening identified cytarabine (Ara-C) as highly effective in inhibiting proliferation in H3 K27M cell models, recently established patient-derived cells, and patient-derived xenograft models. Mechanistically, Ara-C can suppress tumor growth through DNA damage, cell-cycle arrest, and apoptosis. An investigator-initiated clinical trial involving four patients showed benefits in three cases. In addition, a subset of cells exhibited senescence and senescence-associated secretory phenotype post-Ara-C treatment, accompanied by several immune checkpoint ligands' up-regulation and more immune cell infiltration. Combining Ara-C with dual Programmed cell death protein 1 (PD-1) and TIGIT blockade emerged as a promising strategy to disrupt immune evasion by senescent cells, enhancing antitumor responses. These findings highlight Ara-C's potential as a monotherapy and in synergy with immunotherapy for H3-SCDMG, offering potential strategies for clinical management.

Clinical potential and experimental validation of prognostic genes in hepatocellular carcinoma revealed by risk modeling utilizing single cell and transcriptome constructs

Background

Hepatocellular carcinoma (HCC) is the leading cause of tumor-related mortality worldwide. There is an urgent need for predictive biomarkers to guide treatment decisions. This study aimed to identify robust prognostic genes for HCC and to establish a theoretical foundation for clinical interventions.

Methods

The HCC datasets were obtained from public databases and then differential expression analysis were used to obtain significant gene expression profiles. Subsequently, univariate Cox regression analysis and PH assumption test were performed, and a risk model was developed using an optimal algorithm from 101 combinations on the TCGA-LIHC dataset to pinpoint prognostic genes. Immune infiltration and drug sensitivity analyses were conducted to assess the impact of these genes and to explore potential chemotherapeutic agents for HCC. Additionally, single-cell analysis was employed to identify key cellular players and their interactions within the tumor microenvironment. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was utilized to validate the roles of these prognostic genes in HCC.

Results

A total of eight prognostic genes were identified (MCM10, CEP55, KIF18A, ORC6, KIF23, CDC45, CDT1, and PLK4). The risk model, constructed based on these genes, was effective in predicting survival outcomes for HCC patients. CEP55 exhibited the strongest positive correlation with activated CD4 T cells. The top 10 drugs showed increased sensitivity in the low-risk group. B cells were identified as key cellular components with the highest interaction numbers and strengths with macrophages in both HCC and control groups. Prognostic genes were more highly expressed in the initial state of B cell differentiation. RT-qPCR confirmed significant upregulation of MCM10, KIF18A, CDC45, and PLK4 in HCC tissues (p< 0.05).

Conclusion

This study successfully identified eight prognostic genes (MCM10, CEP55, KIF18A, ORC6, KIF23, CDC45, CDT1, and PLK4), which provided new directions for exploring the potential pathogenesis and clinical treatment research of HCC.

Rationally Designed Cell Membrane Biomimetic Biosensing Platform for the Binding Analysis of Drugs with Intracellular Kinase Domain of Epidermal Growth Factor Receptor

Biosensing technologies have demonstrated significant potential in exploring the binding of drugs to receptor tyrosine kinases (RTKs). As a typical transmembrane receptor, there are still several shortcomings in the utilization of the intracellular kinase domain of RTKs, the primary action site of small-molecule inhibitors, resulting in insufficient binding and unclear action sites, which impair the efficiency and accuracy of biosensing. Herein, using epidermal growth factor receptor (EGFR) as an example, we reported a biosensing platform based on cell membrane camouflage technology for evaluating drugs binding to the intracellular kinase domain of EGFR. The azide-functionalized cell membranes modified through glucose metabolism were reverse-coated onto alkyne-functionalized magnetic nanoparticles via bioorthogonal reaction (CMRMNPs), therefore effectively exposing the intracellular kinase domain of EGFR without damage. To construct the biosensing platform, a small-molecule fluorescent probe derived from the gefitinib pharmacophore (GN probe) was further synthesized and incubated with CMRMNPs. This strategy facilitated the efficient localization of the GN probe within the intracellular kinase domain of EGFR. Ultimately, this approach was successfully implemented to evaluate the binding of three inhibitors with EGFR. This study provides a viable strategy for constructing biomimetic biosensors with a defined cell membrane orientation and offers novel insights and methodologies for the study of drug binding with the intracellular kinase regions of RTKs.

Organoids and spheroids: advanced in vitro models for liver cancer research

Liver cancer is a leading cause of cancer-related deaths worldwide, highlighting the need for innovative approaches to understand its complex biology and develop effective treatments. While traditional in vivo animal models have played a vital role in liver cancer research, ethical concerns and the demand for more human-relevant systems have driven the development of advanced in vitro models. Spheroids and organoids have emerged as powerful tools due to their ability to replicate tumor microenvironment and facilitate preclinical drug development. Spheroids are simpler 3D culture models that partially recreate tumor structure and cell interactions. They can be used for drug penetration studies and high-throughput screening. Organoids derived from stem cells or patient tissues that accurately emulate the complexity and functionality of liver tissue. They can be generated from pluripotent and adult stem cells, as well as from liver tumor specimens, providing personalized models for studying tumor behavior and drug responses. Liver organoids retain the genetic variability of the original tumor and offer a robust platform for high-throughput drug screening and personalized treatment strategies. However, both organoids and spheroids have limitations, such as the absence of functional vasculature and immune components, which are essential for tumor growth and therapeutic responses. The field of preclinical modeling is evolving, with ongoing efforts to develop more predictive and personalized models that reflect the complexities of human liver cancer. By integrating these advanced in vitro tools, researchers can gain deeper insights into liver cancer biology and accelerate the development of novel treatments.

Trends and challenges in organoid modeling and expansion with pluripotent stem cells and somatic tissue

The increasing demand for disease modeling, preclinical drug testing, and long waiting lists for alternative organ substitutes has posed significant challenges to current limitations in organoid technology. Consequently, organoid technology has emerged as a cutting-edge tool capable of accurately recapitulating the complexity of actual organs in physiology and functionality. To bridge the gaps between basic research and pharmaceutical as well as clinical applications, efforts have been made to develop organoids from tissue-derived stem cells or pluripotent stem cells. These developments include optimizing starting cells, refining culture systems, and introducing genetic modifications. With the rapid development of organoid technology, organoid composition has evolved from single-cell to multi-cell types, enhancing their level of biomimicry. Tissue structure has become more refined, and core challenges like vascularization are being addressed actively. These improvements are expected to pave the way for the construction of organoid atlases, automated large-scale cultivation, and universally compatible organoid biobanks. However, major obstacles remain to be overcome before urgently proof-of-concept organoids can be readily converted to practical applications. These obstacles include achieving structural and functional summarily to native tissue, remodeling the microenvironment, and scaling up production. This review aims to summarize the status of organoid development and applications, highlight recent progress, acknowledge existing limitations and challenges, and provide insights into future advancements. It is expected that this will contribute to the establishment of a reliable, scalable, and practical platform for organoid production and translation, further promoting their use in the pharmaceutical industry and regenerative medicine.

Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine

Organoids are miniature, highly accurate representations of organs that capture the structure and unique functions of specific organs. Although the field of organoids has experienced exponential growth, driven by advances in artificial intelligence, gene editing, and bioinstrumentation, a comprehensive and accurate overview of organoid applications remains necessary. This review offers a detailed exploration of the historical origins and characteristics of various organoid types, their applications-including disease modeling, drug toxicity and efficacy assessments, precision medicine, and regenerative medicine-as well as the current challenges and future directions of organoid research. Organoids have proven instrumental in elucidating genetic cell fate in hereditary diseases, infectious diseases, metabolic disorders, and malignancies, as well as in the study of processes such as embryonic development, molecular mechanisms, and host-microbe interactions. Furthermore, the integration of organoid technology with artificial intelligence and microfluidics has significantly advanced large-scale, rapid, and cost-effective drug toxicity and efficacy assessments, thereby propelling progress in precision medicine. Finally, with the advent of high-performance materials, three-dimensional printing technology, and gene editing, organoids are also gaining prominence in the field of regenerative medicine. Our insights and predictions aim to provide valuable guidance to current researchers and to support the continued advancement of this rapidly developing field.

Hyaluronic acid-conjugated methotrexate and 5-fluorouracil for targeted drug delivery

The delivery of chemotherapeutical drugs via nanomaterials has become a focus of pharmaceutical research over several decades due to improved drug delivery to cancer cells, decreased side effects on normal tissues, and increased therapeutic efficacy. Herein, a novel hyaluronic acid-conjugated methotrexate and 5-fluorouracil nanodrug system has been developed to address the critical limitations associated with the high toxicity and side effects of methotrexate and 5-fluorouracil. Furthermore, this nanodrug system enhances the targeting capacity of drug molecules and facilitates the potential integration of multimodal drug therapies. Concomitantly, the synergistic effects of MTX with 5-fluorouracil have been shown to improve the therapeutic index of MTX while attenuating the associated toxicities of MTX. The structure and micromorphology of the novel nanodrug can be confirmed by 1HNMR, FT-IR, UV-Vis, DLS, TEM, and AFM. Due to the ability of HA to bind to CD44 receptors activated on the surface of cancer cells and its enhanced permeability and retention (EPR) effect, the novel nanodrug we designed and synthesized can effectively target cancer cells. Cell counting Kit-8 (CCK8), flow cytometry, and live-dead staining assays in vitro showed that this nanodrug system had high targeting and antitumor activity against CD44 receptors. By using drugs to act on patient-derived colorectal, liver, and breast cancer organoids, the anticancer effect of the nanodrug was identified and verified. These results showed that the nanodrug system developed in this study may have great potential as a targeted therapy for cancer.

Emerging therapeutic drug monitoring technologies: considerations and opportunities in precision medicine

In recent years, the development of sensor and wearable technologies have led to their increased adoption in clinical and health monitoring settings. One area that is in early, but promising, stages of development is the use of biosensors for therapeutic drug monitoring (TDM). Traditionally, TDM could only be performed in certified laboratories and was used in specific scenarios to optimize drug dosage based on measurement of plasma/blood drug concentrations. Although TDM has been typically pursued in settings involving medications that are challenging to manage, the basic approach is useful for characterizing drug activity. TDM is based on the idea that there is likely a clear relationship between plasma/blood drug concentration (or concentration in other matrices) and clinical efficacy. However, these relationships may vary across individuals and may be affected by genetic factors, comorbidities, lifestyle, and diet. TDM technologies will be valuable for enabling precision medicine strategies to determine the clinical efficacy of drugs in individuals, as well as optimizing personalized dosing, especially since therapeutic windows may vary inter-individually. In this mini-review, we discuss emerging TDM technologies and their applications, and factors that influence TDM including drug interactions, polypharmacy, and supplement use. We also discuss how using TDM within single subject (N-of-1) and aggregated N-of-1 clinical trial designs provides opportunities to better capture drug response and activity at the individual level. Individualized TDM solutions have the potential to help optimize treatment selection and dosing regimens so that the right drug and right dose may be matched to the right person and in the right context.

Galectin-7 Induction by EHMT2 Inhibition Enhances Immunity in Microsatellite Stability Colorectal Cancer

BACKGROUND & AIMS

Although immunotherapy shows substantial advancement in colorectal cancer (CRC) with microsatellite instability high, it has limited efficacy for CRC with microsatellite stability (MSS). Identifying combinations that reverse immune suppression and prime MSS tumors for current immunotherapy approaches remains an urgent need.

METHODS

An in vitro CRISPR screen was performed using coculture models of primary tumor cells and autologous immune cells from MSS CRC patients to identify epigenetic targets that could enhance immunotherapy efficacy in MSS tumors.

RESULTS

We revealed EHMT2, a histone methyltransferase, as a potential target for MSS CRC. EHMT2 inhibition transformed the immunosuppressive microenvironment of MSS tumors into an immunomodulatory one by altering cytokine expression, leading to T-cell-mediated cytotoxicity activation and improved responsiveness to anti-PD1 treatment. We observed galectin-7 up-regulation upon EHMT2 inhibition, which converted a "cold" MSS tumor environment into a T-cell-inflamed one. Mechanistically, CHD4 repressed galectin-7 expression by recruiting EHMT2 to form a cotranscriptional silencing complex. Galectin-7 administration enhanced anti-PD1 efficacy in MSS CRC, serving as a potent adjunct cytokine therapy.

CONCLUSIONS

Our findings suggest that targeting the EHMT2/galectin-7 axis could provide a novel combination strategy for immunotherapy in MSS CRC.