Single-Cell Transcriptome Analysis Uncovers Intratumoral Heterogeneity and Underlying Mechanisms for Drug Resistance in Hepatobiliary Tumor Organoids

Decoding β-catenin associated protein-protein interactions: Emerging cancer therapeutic opportunities

The hyperactive Wnt/β-catenin signaling circuit has been proven to be closely related to the progression of various cancers, with β-catenin serving as a central regulator of pro-tumorigenic processes. Preclinical evidences strongly support β-catenin as a promising therapeutic target. However, it has long been considered "undruggable" due to challenges such as the lack of crystal structures for its N- and C-terminal domains, high mutation rates, and limited availability of inhibitors. Notably, the network of β-catenin-associated protein-protein interactions (PPIs) is vital in the progression of multiple diseases. These interactions form a cancer-specific network that participates in all phases of oncogenesis, from cell metastasis to immunosuppressive microenvironment formation. Thus, researches on these PPIs are essential for unraveling the molecular mechanisms behind tumors with aberrant β-catenin activation, as well as for developing new targeted therapies. In this review, we delve into how β-catenin's PPIs orchestrate cancer progression and highlight biological and clinical dilemmas, proposing frontier technologies and potential challenges in targeting β-catenin for cancer therapy.

Targeting MAPK14 by Lobeline Upregulates Slurp1-Mediated Inhibition of Alternative Activation of TAM and Retards Colorectal Cancer Growth

Colorectal cancer (CRC) usually creates an immunosuppressive microenvironment, thereby hindering immunotherapy response. Effective treatment options remain elusive. Using scRNA-seq analysis in a tumor-bearing murine model, it is found that lobeline, an alkaloid from the herbal medicine lobelia, promotes polarization of tumor-associated macrophages (TAMs) toward M1-like TAMs while inhibiting their polarization toward M2-like TAMs. Additionally, lobeline upregulates mRNA expression of secreted Ly-6/UPAR-related protein 1 (Slurp1) in cancer cells. The inhibitory effects of lobeline on tumor load and TAM polarization are almost completely eliminated when Slurp1-deficient MC38 cells are subcutaneously injected into mice, suggesting that lobeline exerts an antitumor effect in a Slurp1-dependent manner. Furthermore, using target-responsive accessibility profiling, MAPK14 is identified as the direct target protein of lobeline. Mechanistically, upon binding to MAPK14 in colon cancer cells, lobeline prevents nuclear translocation of MAPK14, resulting in decreased levels of phosphorylated p53. Consequently, negative transcriptional regulation of SLURP1 by p53 is suppressed, leading to enhanced transcription and secretion of SLURP1. Finally, combination therapy using lobeline and anti-PD1 exhibits stronger antitumor effects. Taken together, these findings suggest that remodeling the immunosuppressive microenvironment using small-molecule lobeline may represent a promising therapeutic strategy for CRC.

State-of-the-Art Liver Cancer Organoids: Modeling Cancer Stem Cell Heterogeneity for Personalized Treatment

Liver cancer poses a global health challenge with limited therapeutic options. Notably, the limited success of current therapies in patients with primary liver cancers (PLCs) may be attributed to the high heterogeneity of both hepatocellular carcinoma (HCCs) and intrahepatic cholangiocarcinoma (iCCAs). This heterogeneity evolves over time as tumor-initiating stem cells, or cancer stem cells (CSCs), undergo (epi)genetic alterations or encounter microenvironmental changes within the tumor microenvironment. These modifications enable CSCs to exhibit plasticity, differentiating into various resistant tumor cell types. Addressing this challenge requires urgent efforts to develop personalized treatments guided by biomarkers, with a specific focus on targeting CSCs. The lack of effective precision treatments for PLCs is partly due to the scarcity of ex vivo preclinical models that accurately capture the complexity of CSC-related tumors and can predict therapeutic responses. Fortunately, recent advancements in the establishment of patient-derived liver cancer cell lines and organoids have opened new avenues for precision medicine research. Notably, patient-derived organoid (PDO) cultures have demonstrated self-assembly and self-renewal capabilities, retaining essential characteristics of their respective in vivo tissues, including both inter- and intratumoral heterogeneities. The emergence of PDOs derived from PLCs serves as patient avatars, enabling preclinical investigations for patient stratification, screening of anticancer drugs, efficacy testing, and thereby advancing the field of precision medicine. This review offers a comprehensive summary of the advancements in constructing PLC-derived PDO models. Emphasis is placed on the role of CSCs, which not only contribute significantly to the establishment of PDO cultures but also faithfully capture tumor heterogeneity and the ensuing development of therapy resistance. The exploration of PDOs' benefits in personalized medicine research is undertaken, including a discussion of their limitations, particularly in terms of culture conditions, reproducibility, and scalability.

Mechanisms and therapeutic prospect of the JAK-STAT signaling pathway in liver cancer

Liver cancer (LC) poses a significant global health challenge due to its high incidence and poor prognosis. Current systemic treatment options, such as surgery, chemotherapy, radiofrequency ablation, and immunotherapy, have shown limited effectiveness for advanced LC patients. Moreover, owing to the heterogeneous nature of LC, it is crucial to uncover more in-depth pathogenic mechanisms and develop effective treatments to address the limitations of the existing therapeutic modalities. Increasing evidence has revealed the crucial role of the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway in the pathogenesis of LC. The specific mechanisms driving the JAK-STAT pathway activation in LC, participate in a variety of malignant biological processes, including cell differentiation, evasion, anti-apoptosis, immune escape, and treatment resistance. Both preclinical and clinical investigations on the JAK-STAT pathway inhibitors have exhibited potential in LC treatment, thereby opening up avenues for the development of more targeted therapeutic strategies for LC. In this study, we provide an overview of the JAK-STAT pathway, delving into the composition, activation, and dynamic interplay within the pathway. Additionally, we focus on the molecular mechanisms driving the aberrant activation of the JAK-STAT pathway in LC. Furthermore, we summarize the latest advancements in targeting the JAK-STAT pathway for LC treatment. The insights presented in this review aim to underscore the necessity of research into the JAK-STAT signaling pathway as a promising avenue for LC therapy.

Standardization and consensus in the development and application of bone organoids

Organoids, self-organized structures derived from stem cells cultured in a specific three-dimensional (3D) in vitro microenvironment, have emerged as innovative platforms that closely mimic in vivo cellular behavior, tissue architecture, and organ function. Bone organoids, a frontier in organoid research, can replicate the complex structures and functional characteristics of bone tissue. Recent advancements have led to the successful development of bone organoids, including models of callus, woven bone, cartilage, trabecular bone, and bone marrow. These organoids are widely utilized in establishing bone-related disease models, bone injury repair, and drug screening. However, significant discrepancies remain between current bone organoids and human skeletal tissues in terms of morphology and functionality, limiting their ability to accurately model human bone physiology and pathology. To address these challenges and promote standardization in the construction, evaluation, and application of bone organoids, we have convened experts and research teams with substantial expertise in the field. By integrating existing research findings, this consortium aims to establish a consensus to guide future research and application of bone organoids.

PIWIL2/PDK1 Axis Promotes the Progression of Cervical Epithelial Lesions via Metabolic Reprogramming to Maintain Tumor-Initiating Cell Stemness

When PIWIL2 expression is restored via heterogeneous integration of human papillomavirus, cellular reprogramming is initiated to form tumor-initiating cells (TICs), which triggers cervical squamous intraepithelial lesions (SIL). TIC stemness is critical for the prognosis of SIL. However, the mechanisms underlying TIC stemness maintenance and tumorigenicity remain unclear. Here, it is revealed that aberrant pyruvate dehydrogenase kinase 1 (PDK1) expression is closely related to aerobic glycolysis in SIL and poor survival in patients with cervical cancer. Mechanistically, that PIWIL2, which induced by stable transfection of either PIWIL2 or HPV16 oncogene E6 in human primary cervical basal epithelial cells and keratinocyte cell line HaCaT, upregulates PDK1 expression via the LIN28/let-7 axis, hence reprogramming metabolism to activate glycolysis and synchronize with TIC formation. It is further demonstrate that PDK1 is critical for TIC stemness maintenance and tumorigenicity via the PI3K/AKT/mTOR pathway both in vitro and in vivo, revealing a previously unclear mechanism for SIL progression, regression or relapse. Therefore, this findings suggest a potential rationale for prognostic predictions and selecting targeted therapy for cervical lesions.

Tumor organoids for primary liver cancers: A systematic review of current applications in diagnostics, disease modeling, and drug screening

Background & Aims

Liver cancer-related deaths are projected to exceed one million annually by 2030. Existing therapies have significant limitations, including severe side effects and inconsistent efficacy. Innovative therapeutic approaches to address primary liver cancer (PLC) have led to the ongoing development of tumor-derived organoids. These are sophisticated three-dimensional structures capable of mimicking native tissue architecture and function in vitro, improving our ability to model in vivo homeostasis and disease.

Methods

This systematic review consolidates known literature on human and mouse liver organoids across all PLC subtypes, emphasizing diagnostic precision, disease modeling, and drug screening capabilities.

Results

Across all 39 included studies, organoids were most frequently patient-derived, closely followed by cancer cell line-derived. The literature concentrated on hepatocellular carcinoma and intrahepatic cholangiocarcinoma, while exploration of other subtypes was limited. These studies demonstrate a valuable role for PLC organoid cultures in biomarker discovery, disease modeling, and therapeutic exploration.

Conclusions

Encouraging advances such as organoid-on-a-chip and co-culturing systems hold promise for advancing treatment regimens for PLC. Standardizing in vitro protocols is crucial to integrate research breakthroughs into practical treatment strategies for PLC.

Impact and implications

This study provides an overview of the current understanding of tumor-derived organoids in primary liver cancers, emphasizing their potential in diagnostics, disease modeling, and drug screening. The scientific foundation rests on the organoids' ability to replicate the tumor microenvironment and genetic landscape, opening new avenues for personalized therapies. These insights are crucial for both researchers and clinicians, as patient-derived organoids can help identify biomarkers and therapeutic targets. Physicians and policymakers can harness these advances to drive progress in precision medicine, while recognizing the challenges involved in standardizing organoid models for clinical implementation.

USP11 promotes lipogenesis and tumorigenesis by regulating SREBF1 stability in hepatocellular carcinoma

BACKGROUND

The relationship between hepatocellular carcinoma (HCC) metastasis and cancer metabolism reprogramming is becoming increasingly evident. Ubiquitin-specific protease 11 (USP11), a member of the deubiquitinating enzyme family, has been linked to various cancer-related processes. While USP11 is known to promote HCC metastasis and proliferation, the precise mechanisms, especially those related to cancer metabolism, remain unclear.

METHODS

Through mass spectrometry, co-immunoprecipitation, immunofluorescence, and ubiquitination assays, we identified USP11 as the key deubiquitinase for SREBF1.Lipogenesis was evaluated using Oil Red O and Nile Red staining, along with the detection of triglycerides and cholesterol. To assess HCC cell proliferation, migration, and invasion in vitro, Transwell assays, EDU, colony formation, and CCK-8 were conducted. Xenograft models in nude mice were developed to verify the role of the USP11/SREBF1 axis in lipogenesis and tumor growth in vivo.

RESULTS

USP11 directly interacts with SREBF1, and its silencing leads to the disruption of SREBF1 stabilization through K48-linked deubiquitination and degradation. Importantly, the truncated mutant USP11 (503-938 aa) interacts with the truncated mutant SREBF1 (569-1147aa), with K1151 playing a crucial role in this interaction. Higher levels of USP11 enhance lipogenesis, proliferation, and metastasis in HCC cells. Importantly, the knockdown of SREBF1 weakened the effects of USP11 in enhancing lipogenesis and tumorigenesis. Futhermore, the elevated expression of USP11 and SREBF1 in HCC tissue serves as an indicator of poor prognosis in HCC patients.

CONCLUSIONS

In summary, our study reveals that USP11 promotes HCC proliferation and metastasis through SREBF1-induced lipogenesis. These findings provide a foundation for novel therapies targeting lipid metabolism in HCC.

Patient-derived organoids in precision cancer medicine

Organoids are three-dimensional (3D) cultures, normally derived from stem cells, that replicate the complex structure and function of human tissues. They offer a physiologically relevant model to address important questions in cancer research. The generation of patient-derived organoids (PDOs) from various human cancers allows for deeper insights into tumor heterogeneity and spatial organization. Additionally, interrogating non-tumor stromal cells increases the relevance in studying the tumor microenvironment, thereby enhancing the relevance of PDOs in personalized medicine. PDOs mark a significant advancement in cancer research and patient care, signifying a shift toward more innovative and patient-centric approaches. This review covers aspects of PDO cultures to address the modeling of the tumor microenvironment, including extracellular matrices, air-liquid interface and microfluidic cultures, and organ-on-chip. Specifically, the role of PDOs as preclinical models in gene editing, molecular profiling, drug testing, and biomarker discovery and their potential for guiding personalized treatment in clinical practice are discussed.

Advancing cancer research through organoid technology

The complexity of tumors and the challenges associated with treatment often stem from the limitations of existing models in accurately replicating authentic tumors. Recently, organoid technology has emerged as an innovative platform for tumor research. This bioengineering approach enables researchers to simulate, in vitro, the interactions between tumors and their microenvironment, thereby enhancing the intricate interplay between tumor cells and their surroundings. Organoids also integrate multidimensional data, providing a novel paradigm for understanding tumor development and progression while facilitating precision therapy. Furthermore, advancements in imaging and genetic editing techniques have significantly augmented the potential of organoids in tumor research. This review explores the application of organoid technology for more precise tumor simulations and its specific contributions to cancer research advancements. Additionally, we discuss the challenges and evolving trends in developing comprehensive tumor models utilizing organoid technology.

Models of fibrolamellar carcinomas, tools for evaluation of a new era of treatments

Fibrolamellar carcinoma (FLC) is a rare but fatal cancer that occurs primarily in young people. There are currently no known effective treatments, although several promising treatments appear to be in development. Genetic studies have confirmed that almost all FLC tumors have a fusion protein marker (DNAJB1-PRKACA) encoded by a fusion gene (DNAJB1-PRKACA); It is currently accepted as a diagnostic criterion for FLCs. Several research teams have established patient-derived xenograft (PDX) FLC models using immunocompromised animals as hosts and patient tissue samples (tumors or ascites) as primary sources for PDX-derived organoids. These FLC organoids are composed of FLC epithelia, endothelial progenitor cells, and stellate cells. CRISPR/Cas9 was used as a gene editing technique to modify mature hepatocytes to obtain ex vivo FLC-like cells expressing the fusion gene and/or other mutated genes associated with FLCs. Although these models simulate some but not all FLC features. Drug screening using these models has not proven effective in identifying clinically useful treatments. Genetic studies comparing FLCs to normal maturing endodermal cell lineages have shown that FLCs share genetic signatures not with hepatocytes, but with subpopulations of biliary tree stem cells (BTSCs), hepato/pancreatic stem/progenitor cells that consistently reside in peribiliary glands (PBGs) located in the biliary tree and are sources of stem cells for the formation and postnatal regeneration of the liver and pancreas. Therefore, it is expected that models of BTSCs, instead of hepatocytes may prove more useful. In this review, we summarize the status of the various FLC models and their features, applications, and limitations. They provide opportunities to understand the cause and characteristics of this deadly disease and are models from which effective treatments can be identified.

Microfluidic Chip-Based Automatic System for Sequencing Patient-Derived Organoids at the Single-Cell Level

Genetically sequencing patient-derived organoids (PDOs) at the single-cell level has emerged as a promising method to infer cell-level heterogeneity of original organs and improve cancer precision medicine. Unfortunately, because of the limited starting quantity and uncontrolled establishing process of PDOs, the existing single-cell sequencing technologies, either manual-operation-based or microfluid-based, are inefficient in processing PDOs originating from clinical tissue samples. To address such issues, this study presents a microfluidic chip-based automatic system for sequencing organoids at the single-cell level, named as MASSO. By performing all required procedures, including PDO establishment/culturing/digesting and single-cell isolation/lysis/whole-genome amplification, in a single microfluidic chip, the possible loss of precious PDO is avoided, and the high quality of on-chip whole-genome amplification of a single PDO cell is ensured. By automating the entire operation process, possible human error is eliminated, and the data repeatability is improved, therefore bridging the technical gap between laboratorial proof-of-concept studies and clinical practices. After characterizing the organoid single-cell whole-genome amplification chip (named as OSA-Chip) and the MASSO, the first successful attempt, to the best of our knowledge, on whole-genome sequencing lung cancer PDO at the single-cell level was performed by MASSO. The results reveal that the MASSO is capable of not only identifying common cancer-related mutations but also discovering specific mutations that affect drug responses, therefore laying the technical foundation for efficiently understanding the cell-level heterogeneities of PDOs and corresponding original organs.

Graph-Based Spatial Proximity of Super-Resolved Protein-Protein Interactions Predicts Cancer Drug Responses in Single Cells

Purpose

Current bulk molecular assays fail to capture spatial signaling activities in cancers, limiting our understanding of drug resistance mechanisms. We developed a graph-based super-resolution protein-protein interaction (GSR-PPI) technique to spatially resolve single-cell signaling networks and evaluate whether higher resolution microscopy enhances the biological study of PPIs using deep learning classification models.

Methods

Single-cell spatial proximity ligation assays (PLA, ≤ 9 PPI pairs) were conducted on EGFR mutant (EGFRm) PC9 and HCC827 cells (>10,000 cells) treated with 100 nM Osimertinib. Multiplexed PPI images were obtained using wide-field and super-resolution microscopy (Zeiss Airyscan, SRRF). Graph-based deep learning models analyzed subcellular protein interactions to classify drug treatment states and test GSR-PPI on clinical tissue samples. GSR-PPI triangulated PPI nodes into 3D relationships, predicting drug treatment labels. Biological discriminative ability (BDA) was evaluated using accuracy, AUC, and F1 scores. The method was also applied to 3D spatial proteomic molecular pixelation (PixelGen) data from T cells.

Results

GSR-PPI outperformed baseline models in predicting drug responses from multiplexed PPI imaging in EGFRm cells. Super-resolution data significantly improved accuracy over localized wide-field imaging. GSR-PPI classified drug treatment states in cancer cells and human lung tissues, with performance improving as imaging resolution increased. It differentiated single and combination drug therapies in HCC827 cells and human tissues. Additionally, GSR-PPI accurately distinguished T-cell stimulation states, identifying key nodes such as CD44, CD45, and CD54.

Conclusion

The GSR-PPI framework provides valuable insights into spatial protein interactions and drug responses, enhancing the study of signaling biology and drug resistance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-024-00822-1.

Bioprinting of Cells, Organoids and Organs-on-a-Chip Together with Hydrogels Improves Structural and Mechanical Cues

The 3D bioprinting technique has made enormous progress in tissue engineering, regenerative medicine and research into diseases such as cancer. Apart from individual cells, a collection of cells, such as organoids, can be printed in combination with various hydrogels. It can be hypothesized that 3D bioprinting will even become a promising tool for mechanobiological analyses of cells, organoids and their matrix environments in highly defined and precisely structured 3D environments, in which the mechanical properties of the cell environment can be individually adjusted. Mechanical obstacles or bead markers can be integrated into bioprinted samples to analyze mechanical deformations and forces within these bioprinted constructs, such as 3D organoids, and to perform biophysical analysis in complex 3D systems, which are still not standard techniques. The review highlights the advances of 3D and 4D printing technologies in integrating mechanobiological cues so that the next step will be a detailed analysis of key future biophysical research directions in organoid generation for the development of disease model systems, tissue regeneration and drug testing from a biophysical perspective. Finally, the review highlights the combination of bioprinted hydrogels, such as pure natural or synthetic hydrogels and mixtures, with organoids, organoid-cell co-cultures, organ-on-a-chip systems and organoid-organ-on-a chip combinations and introduces the use of assembloids to determine the mutual interactions of different cell types and cell-matrix interferences in specific biological and mechanical environments.

Enhanced feature matching in single-cell proteomics characterizes IFN-γ response and co-existence of cell states

Proteome analysis by data-independent acquisition (DIA) has become a powerful approach to obtain deep proteome coverage, and has gained recent traction for label-free analysis of single cells. However, optimal experimental design for DIA-based single-cell proteomics has not been fully explored, and performance metrics of subsequent data analysis tools remain to be evaluated. Therefore, we here formalize and comprehensively evaluate a DIA data analysis strategy that exploits the co-analysis of low-input samples with a so-called matching enhancer (ME) of higher input, to increase sensitivity, proteome coverage, and data completeness. We assess the matching specificity of DIA-ME by a two-proteome model, and demonstrate that false discovery and false transfer are maintained at low levels when using DIA-NN software, while preserving quantification accuracy. We apply DIA-ME to investigate the proteome response of U-2 OS cells to interferon gamma (IFN-γ) in single cells, and recapitulate the time-resolved induction of IFN-γ response proteins as observed in bulk material. Moreover, we uncover co- and anti-correlating patterns of protein expression within the same cell, indicating mutually exclusive protein modules and the co-existence of different cell states. Collectively our data show that DIA-ME is a powerful, scalable, and easy-to-implement strategy for single-cell proteomics.

Targeting ALDOA to modulate tumorigenesis and energy metabolism in retinoblastoma

This study aims to elucidate the pivotal role of aldolase A (ALDOA) in retinoblastoma (RB) and evaluate the potential of the ALDOA inhibitor itaconate in impeding RB progression. Utilizing single-cell RNA sequencing, ALDOA consistently exhibits overexpression across diverse cell types, particularly in cone precursor cells, retinoma-like cells, and retinoblastoma-like cells. This heightened expression is validated in RB tissues and cell lines. ALDOA knockdown significantly diminishes RB cell viability, impedes colony formation, and induces notable metabolic alterations. RNA-seq analysis identifies SUSD2, ARHGAP27, and CLK2 as downstream genes associated with ALDOA. The application of itaconate demonstrates efficacy in inhibiting RB cell proliferation, validated through in vitro and in vivo models. This study emphasizes ALDOA as a promising target for innovative RB therapies, with potential implications for altering tumor energy metabolism.

Development of a prognostic model for NSCLC based on differential genes in tumour stem cells

Non-small cell lung cancer (NSCLC) constitutes a significant portion of lung cancers and cytotoxic drugs (e.g. cisplatin) are currently the first-line treatment. However, NSCLC has developed resistance to this drug, which limits the therapeutic effect and thus affects prognosis. NSCLC sc-RNA-seq data were downloaded from the GEO database and Ku Leuven Laboratory for Functional Epigenetics, and bulk RNA-seq data were obtained from the TCGA database. The "Seurat" package was employed for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were applied for downscaling and cluster identification. Use the FindAllMarkers function to find differential genes (DEGs) for tumor stem cells. Then, we performed univariate regression analyses on the DEGs to identify potential prognostic genes. We created a machine learning framework based on potential prognostic genes, which combines 10 machine learning methods and their 101 combinations to get the optimal prognostic risk model. The model was evaluated in the training set and validation set. A nomogram was developed to provide physicians with a quantitative tool for prognosis prediction. Finally, we evaluated the expression and functionality of SLC2A1. We discovered 22 cell clusters containing 218379 cells by examining single-cell RNA sequencing datasets (GSE148071, KU_lom, GSE131907, GSE136246, GSE127465). Tumour cells were isolated for subpopulation analysis and 162 differential genes from SOX2_cancer were obtained. After univariate Cox analysis, we found 23 genes with prognostic potential prognostic value and utilized them to develop 101‑combination machine learning computational framework. We eventually picked the best performing 'StepCox[both] + RSF', which includes 8 genes. The model has a relatively high prediction accuracy in both TCGA and GEO datasets. In in vitro investigations, targeted suppression of the SLC2A1 gene resulted in significant reductions in proliferation, invasion and migration in A549 cells. In addition, a significant reduction in cisplatin resistance was seen in A549/DDP cells. The outcomes demonstrated the precision and credibility of the prognostic model for NSCLC, highlighting its potential significance in the treatment and prognosis of individuals affected by this disease. SLC2A1 may become a promising prognostic marker and a potential therapeutic target, offering valuable insights to inform clinical treatment decisions.

A distinct subset of urothelial cells with enhanced EMT features promotes chemotherapy resistance and cancer recurrence by increasing COL4A1-ITGB1 mediated angiogenesis

Drug resistance and tumor recurrence remain clinical challenges in the treatment of urothelial carcinoma (UC). However, the underlying mechanism is not fully understood. Here, we performed single-cell RNA sequencing and identified a subset of urothelial cells with epithelial-mesenchymal transition (EMT) features (EMT-UC), which is significantly correlated with chemotherapy resistance and cancer recurrence. To validate the clinical significance of EMT-UC, we constructed EMT-UC like cells by introducing overexpression of two markers, Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Desmin (DES), and examined their histological distribution characteristics and malignant phenotypes. EMT-UC like cells were mainly enriched in UC tissues from patients with adverse prognosis and exhibited significantly elevated EMT, migration and gemcitabine tolerance in vitro. However, EMT-UC was not specifically identified from tumorous tissues, certain proportion of them were also identified in adjacent normal tissues. Tumorous EMT-UC highly expressed genes involved in malignant behaviors and exhibited adverse prognosis. Additionally, tumorous EMT-UC was associated with remodeled tumor microenvironment (TME), which exhibited high angiogenic and immunosuppressive potentials compared with the normal counterparts. Furthermore, a specific interaction of COL4A1 and ITGB1 was identified to be highly enriched in tumorous EMT-UC, and in the endothelial component. Targeting the interaction of COL4A1 and ITGB1 with specific antibodies significantly suppressed tumorous angiogenesis and alleviated gemcitabine resistance of UC. Overall, our findings demonstrated that the driven force of chemotherapy resistance and recurrence of UC was EMT-UC mediated COL4A1-ITGB1 interaction, providing a potential target for future UC treatment.

Organoid as a promising tool for primary liver cancer research: a comprehensive review

Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine.

Applications of single-cell technologies in drug discovery for tumor treatment

Single-cell technologies have been known as advanced and powerful tools to study tumor biological systems at the single-cell resolution and are playing increasingly critical roles in multiple stages of drug discovery and development. Specifically, single-cell technologies can promote the discovery of drug targets, help high-throughput screening at single-cell level, and contribute to pharmacokinetic studies of anti-tumor drugs. Emerging single-cell analysis technologies have been developed to further integrating multidimensional single-cell molecular features, expanding the scale of single-cell data, profiling phenotypic impact of genes in single cell, and providing full-length coverage single-cell sequencing. In this review, we systematically summarized the applications of single-cell technologies in various sections of drug discovery for tumor treatment, including target identification, high-throughput drug screening, and pharmacokinetic evaluation and highlighted emerging single-cell technologies in providing in-depth understanding of tumor biology. Single-cell-technology-based drug discovery is expected to further optimize therapeutic strategies and improve clinical outcomes of tumor patients.

Liver organoids: updates on generation strategies and biomedical applications

The liver is the most important metabolic organ in the body. While mouse models and cell lines have further deepened our understanding of liver biology and related diseases, they are flawed in replicating key aspects of human liver tissue, particularly its complex structure and metabolic functions. The organoid model represents a major breakthrough in cell biology that revolutionized biomedical research. Organoids are in vitro three-dimensional (3D) physiological structures that recapitulate the morphological and functional characteristics of tissues in vivo, and have significant advantages over traditional cell culture methods. In this review, we discuss the generation strategies and current advances in the field focusing on their application in regenerative medicine, drug discovery and modeling diseases.

Preclinical Models of Hepatocellular Carcinoma: Current Utility, Limitations, and Challenges

Hepatocellular carcinoma (HCC), the predominant primary liver tumor, remains one of the most lethal cancers worldwide, despite the advances in therapy in recent years. In addition to the traditional chemically and dietary-induced HCC models, a broad spectrum of novel preclinical tools have been generated following the advent of transgenic, transposon, organoid, and in silico technologies to overcome this gloomy scenario. These models have become rapidly robust preclinical instruments to unravel the molecular pathogenesis of liver cancer and establish new therapeutic approaches against this deadly disease. The present review article aims to summarize and discuss the commonly used preclinical models for HCC, evaluating their strengths and weaknesses.

Crosstalk between tumor and microenvironment: Insights from spatial transcriptomics

Cancer is a dynamic disease, and clonal heterogeneity plays a fundamental role in tumor development, progression, and resistance to therapies. Single-cell and spatial multimodal technologies can provide a high-resolution molecular map of underlying genomic, epigenomic, and transcriptomic alterations involved in inter- and intra-tumor heterogeneity and interactions with the microenvironment. In this review, we provide a perspective on factors driving cancer heterogeneity, tumor evolution, and clonal states. We briefly describe spatial transcriptomic technologies and summarize recent literature that sheds light on the dynamical interactions between tumor states, cell-to-cell communication, and remodeling local microenvironment.

NSUN6-mediated 5-methylcytosine modification of NDRG1 mRNA promotes radioresistance in cervical cancer

BACKGROUND

Radioresistance is the leading cause of death in advanced cervical cancer (CC). Dysregulation of RNA modification has recently emerged as a regulatory mechanism in radiation and drug resistance. We aimed to explore the biological function and clinical significance of 5-methylcytosine (m5C) in cervical cancer radiosensitivity.

METHODS

The abundance of RNA modification in radiotherapy-resistant and sensitive CC specimens was quantified by liquid chromatography-tandem mass spectrometry. The essential RNA modification-related genes involved in CC radiosensitivity were screened via RNA sequencing. The effect of NSUN6 on radiosensitivity was verified in CC cell lines, cell-derived xenograft (CDX), and 3D bioprinted patient-derived organoid (PDO). The mechanisms of NSUN6 in regulating CC radiosensitivity were investigated by integrative m5C sequencing, mRNA sequencing, and RNA immunoprecipitation.

RESULTS

We found a higher abundance of m5C modification in resistant CC samples, and NSUN6 was the essential m5C-regulating gene concerning radiosensitivity. NSUN6 overexpression was clinically correlated with radioresistance and poor prognosis in cervical cancer. Functionally, higher NSUN6 expression was associated with radioresistance in the 3D PDO model of cervical cancer. Moreover, silencing NSUN6 increased CC radiosensitivity in vivo and in vitro. Mechanistically, NDRG1 was one of the downstream target genes of NSUN6 identified by integrated m5C-seq, mRNA-seq, and functional validation. NSUN6 promoted the m5C modification of NDRG1 mRNA, and the m5C reader ALYREF bound explicitly to the m5C-labeled NDRG1 mRNA and enhanced NDRG1 mRNA stability. NDRG1 overexpression promoted homologous recombination-mediated DNA repair, which in turn led to radioresistance in cervical cancer.

CONCLUSIONS

Aberrant m5C hypermethylation and NSUN6 overexpression drive resistance to radiotherapy in cervical cancer. Elevated NSUN6 expression promotes radioresistance in cervical cancer by activating the NSUN6/ALYREF-m5C-NDRG1 pathway. The low expression of NSUN6 in cervical cancer indicates sensitivity to radiotherapy and a better prognosis.

Microbial metabolites affect tumor progression, immunity and therapy prediction by reshaping the tumor microenvironment (Review)

Several studies have indicated that the gut microbiome and tumor microbiota may affect tumors. Emerging metabolomics research illustrates the need to examine the variations in microbial metabolite composition between patients with cancer and healthy individuals. Microbial metabolites can impact the progression of tumors and the immune response by influencing a number of mechanisms, including modulation of the immune system, cancer or immune‑related signaling pathways, epigenetic modification of proteins and DNA damage. Microbial metabolites can also alleviate side effects and drug resistance during chemotherapy and immunotherapy, while effectively activating the immune system to exert tumor immunotherapy. Nevertheless, the impact of microbial metabolites on tumor immunity can be both beneficial and harmful, potentially influenced by the concentration of the metabolites or the specific cancer type. The present review summarizes the roles of various microbial metabolites in different solid tumors, alongside their influence on tumor immunity and treatment. Additionally, clinical trials evaluating the therapeutic effects of microbial metabolites or related microbes on patients with cancer have been listed. In summary, studying microbial metabolites, which play a crucial role in the interaction between the microbiota and tumors, could lead to the identification of new supplementary treatments for cancer. This has the potential to improve the effectiveness of cancer treatment and enhance patient prognosis.

Modulatory effects of cancer stem cell-derived extracellular vesicles on the tumor immune microenvironment

Cancer stem cells (CSCs), accounting for only a minor cell proportion (< 1%) within tumors, have profound implications in tumor initiation, metastasis, recurrence, and treatment resistance due to their inherent ability of self-renewal, multi-lineage differentiation, and tumor-initiating potential. In recent years, accumulating studies indicate that CSCs and tumor immune microenvironment act reciprocally in driving tumor progression and diminishing the efficacy of cancer therapies. Extracellular vesicles (EVs), pivotal mediators of intercellular communications, build indispensable biological connections between CSCs and immune cells. By transferring bioactive molecules, including proteins, nucleic acids, and lipids, EVs can exert mutual influence on both CSCs and immune cells. This interaction plays a significant role in reshaping the tumor immune microenvironment, creating conditions favorable for the sustenance and propagation of CSCs. Deciphering the intricate interplay between CSCs and immune cells would provide valuable insights into the mechanisms of CSCs being more susceptible to immune escape. This review will highlight the EV-mediated communications between CSCs and each immune cell lineage in the tumor microenvironment and explore potential therapeutic opportunities.

Unravelling the role of intratumoral bacteria in digestive system cancers: current insights and future perspectives

Recently, research on the human microbiome, especially concerning the bacteria within the digestive system, has substantially advanced. This exploration has unveiled a complex interplay between microbiota and health, particularly in the context of disease. Evidence suggests that the gut microbiome plays vital roles in digestion, immunity and the synthesis of vitamins and neurotransmitters, highlighting its significance in maintaining overall health. Conversely, disruptions in these microbial communities, termed dysbiosis, have been linked to the pathogenesis of various diseases, including digestive system cancers. These bacteria can influence cancer progression through mechanisms such as DNA damage, modulation of the tumour microenvironment, and effects on the host's immune response. Changes in the composition and function within the tumours can also impact inflammation, immune response and cancer therapy effectiveness. These findings offer promising avenues for the clinical application of intratumoral bacteria for digestive system cancer treatment, including the potential use of microbial markers for early cancer detection, prognostication and the development of microbiome-targeted therapies to enhance treatment outcomes. This review aims to provide a comprehensive overview of the pivotal roles played by gut microbiome bacteria in the development of digestive system cancers. Additionally, we delve into the specific contributions of intratumoral bacteria to digestive system cancer development, elucidating potential mechanisms and clinical implications. Ultimately, this review underscores the intricate interplay between intratumoral bacteria and digestive system cancers, underscoring the pivotal role of microbiome research in transforming diagnostic, prognostic and therapeutic paradigms for digestive system cancers.

Converging bioprinting and organoids to better recapitulate the tumor microenvironment

Bioprinting shows excellent potential for preclinical tumor modeling, with significant advantages over 2D cell cultures in replicating the tumor microenvironment (TME). Recently, the use of tumor organoids in bioprinting models has emerged as a groundbreaking approach to simulate volumetric tumor tissues. This synergetic fabrication method leverages the advantages of the spatial and geometric control of bioprinting to assemble heterogeneous TME components, while tumor organoids maintain collective cell behaviors. In this review, we provide a landscape of the latest progress on the convergence of 3D bioprinting and tumor organoids. Furthermore, we discuss the potential to incorporate organ-on-a-chip with bioprinting tumor organoids to improve the biomimicry and predictability of therapeutic performance. Lastly, we address the challenges to personalized medicine and predictive clinical integration.

Pharmacogenomic profiling of intra-tumor heterogeneity using a large organoid biobank of liver cancer

Inter- and intra-tumor heterogeneity is a major hurdle in primary liver cancer (PLC) precision therapy. Here, we establish a PLC biobank, consisting of 399 tumor organoids derived from 144 patients, which recapitulates histopathology and genomic landscape of parental tumors, and is reliable for drug sensitivity screening, as evidenced by both in vivo models and patient response. Integrative analysis dissects PLC heterogeneity, regarding genomic/transcriptomic characteristics and sensitivity to seven clinically relevant drugs, as well as clinical associations. Pharmacogenomic analysis identifies and validates multi-gene expression signatures predicting drug response for better patient stratification. Furthermore, we reveal c-Jun as a major mediator of lenvatinib resistance through JNK and β-catenin signaling. A compound (PKUF-01) comprising moieties of lenvatinib and veratramine (c-Jun inhibitor) is synthesized and screened, exhibiting a marked synergistic effect. Together, our study characterizes the landscape of PLC heterogeneity, develops predictive biomarker panels, and identifies a lenvatinib-resistant mechanism for combination therapy.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions

Despite considerable efforts to identify human liver cancer genomic alterations that might unveil druggable targets, the systematic translation of multiomics data remains challenging. Here, we report success in long-term culture of 64 patient-derived hepatobiliary tumor organoids (PDHOs) from a Chinese population. A divergent response to 265 metabolism- and epigenetics-related chemicals and 36 anti-cancer drugs is observed. Integration of the whole genome, transcriptome, chromatin accessibility profiles, and drug sensitivity results of 64 clinically relevant drugs defines over 32,000 genome-drug interactions. RUNX1 promoter mutation is associated with an increase in chromatin accessibility and a concomitant gene expression increase, promoting a cluster of drugs preferentially sensitive in hepatobiliary tumors. These results not only provide an annotated PDHO biobank of human liver cancer but also suggest a systematic approach for obtaining a comprehensive understanding of the gene-regulatory network of liver cancer, advancing the applications of potential personalized medicine.

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

DRMref: comprehensive reference map of drug resistance mechanisms in human cancer

Drug resistance poses a significant challenge in cancer treatment. Despite the initial effectiveness of therapies such as chemotherapy, targeted therapy and immunotherapy, many patients eventually develop resistance. To gain deep insights into the underlying mechanisms, single-cell profiling has been performed to interrogate drug resistance at cell level. Herein, we have built the DRMref database (https://ccsm.uth.edu/DRMref/) to provide comprehensive characterization of drug resistance using single-cell data from drug treatment settings. The current version of DRMref includes 42 single-cell datasets from 30 studies, covering 382 samples, 13 major cancer types, 26 cancer subtypes, 35 treatment regimens and 42 drugs. All datasets in DRMref are browsable and searchable, with detailed annotations provided. Meanwhile, DRMref includes analyses of cellular composition, intratumoral heterogeneity, epithelial-mesenchymal transition, cell-cell interaction and differentially expressed genes in resistant cells. Notably, DRMref investigates the drug resistance mechanisms (e.g. Aberration of Drug's Therapeutic Target, Drug Inactivation by Structure Modification, etc.) in resistant cells. Additional enrichment analysis of hallmark/KEGG (Kyoto Encyclopedia of Genes and Genomes)/GO (Gene Ontology) pathways, as well as the identification of microRNA, motif and transcription factors involved in resistant cells, is provided in DRMref for user's exploration. Overall, DRMref serves as a unique single-cell-based resource for studying drug resistance, drug combination therapy and discovering novel drug targets.

Harnessing 3D in vitro systems to model immune responses to solid tumours: a step towards improving and creating personalized immunotherapies

In vitro 3D models are advanced biological tools that have been established to overcome the shortcomings of oversimplified 2D cultures and mouse models. Various in vitro 3D immuno-oncology models have been developed to mimic and recapitulate the cancer-immunity cycle, evaluate immunotherapy regimens, and explore options for optimizing current immunotherapies, including for individual patient tumours. Here, we review recent developments in this field. We focus, first, on the limitations of existing immunotherapies for solid tumours, secondly, on how in vitro 3D immuno-oncology models are established using various technologies - including scaffolds, organoids, microfluidics and 3D bioprinting - and thirdly, on the applications of these 3D models for comprehending the cancer-immunity cycle as well as for assessing and improving immunotherapies for solid tumours.

Revolutionizing digestive system tumor organoids research: Exploring the potential of tumor organoids

Digestive system tumors are the leading cause of cancer-related deaths worldwide. Despite ongoing research, our understanding of their mechanisms and treatment remain inadequate. One promising tool for clinical applications is the use of gastrointestinal tract tumor organoids, which serve as an important in vitro model. Tumor organoids exhibit a genotype similar to the patient's tumor and effectively mimic various biological processes, including tissue renewal, stem cell, and ecological niche functions, and tissue response to drugs, mutations, or injury. As such, they are valuable for drug screening, developing novel drugs, assessing patient outcomes, and supporting immunotherapy. In addition, innovative materials and techniques can be used to optimize tumor organoid culture systems. Several applications of digestive system tumor organoids have been described and have shown promising results in related aspects. In this review, we discuss the current progress, limitations, and prospects of this model for digestive system tumors.

Next-Generation Preclinical Functional Testing Models in Cancer Precision Medicine: CTC-Derived Organoids

Basic and clinical cancer research requires tumor models that consistently recapitulate the characteristics of prima tumors. As ex vivo 3D cultures of patient tumor cells, patient-derived tumor organoids possess the biological properties of primary tumors and are therefore excellent preclinical models for cancer research. Patient-derived organoids can be established using primary tumor tissues, peripheral blood, pleural fluid, ascites, and other samples containing tumor cells. Circulating tumor cells acquired by non-invasive sampling feature dynamic circulation and high heterogeneity. Circulating tumor cell-derived organoids are prospective tools for the dynamic monitoring of tumor mutation evolution profiles because they reflect the heterogeneity of the original tumors to a certain extent. This review discusses the advantages and applications of patient-derived organoids. Meanwhile, this work highlights the biological functions of circulating tumor cells, the latest advancement in research of circulating tumor cell-derived organoids, and potential application and challenges of this technology.

Advancements and application prospects of three-dimensional models for primary liver cancer: a comprehensive review

Primary liver cancer (PLC) is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths. However, traditional liver cancer models fail to replicate tumor heterogeneity and the tumor microenvironment, limiting the study and personalized treatment of liver cancer. To overcome these limitations, scientists have introduced three-dimensional (3D) culture models as an emerging research tool. These 3D models, utilizing biofabrication technologies such as 3D bioprinting and microfluidics, enable more accurate simulation of the in vivo tumor microenvironment, replicating cell morphology, tissue stiffness, and cell-cell interactions. Compared to traditional two-dimensional (2D) models, 3D culture models better mimic tumor heterogeneity, revealing differential sensitivity of tumor cell subpopulations to targeted therapies or immunotherapies. Additionally, these models can be used to assess the efficacy of potential treatments, providing guidance for personalized therapy. 3D liver cancer models hold significant value in tumor biology, understanding the mechanisms of disease progression, and drug screening. Researchers can gain deeper insights into the impact of the tumor microenvironment on tumor cells and their interactions with the surrounding milieu. Furthermore, these models allow for the evaluation of treatment responses, offering more accurate guidance for clinical interventions. In summary, 3D models provide a realistic and reliable tool for advancing PLC research. By simulating tumor heterogeneity and the microenvironment, these models contribute to a better understanding of the disease mechanisms and offer new strategies for personalized treatment. Therefore, 3D models hold promising prospects for future PLC research.

Applications of lung cancer organoids in precision medicine: from bench to bedside

As the leading cause of cancer-related mortality, lung cancer continues to pose a menacing threat to human health worldwide. Lung cancer treatment options primarily rely on chemoradiotherapy, surgery, targeted therapy, or immunotherapy. Despite significant progress in research and treatment, the 5-year survival rate for lung cancer patients is only 10-20%. There is an urgent need to develop more reliable preclinical models and valid therapeutic approaches. Patient-derived organoids with highly reduced tumour heterogeneity have emerged as a promising model for high-throughput drug screening to guide treatment of lung cancer patients. Organoid technology offers a novel platform for disease modelling, biobanking and drug development. The expected benefit of organoids is for cancer patients as the subsequent precision medicine technology. Over the past few years, numerous basic and clinical studies have been conducted on lung cancer organoids, highlighting the significant contributions of this technique. This review comprehensively examines the current state-of-the-art technologies and applications relevant to the formation of lung cancer organoids, as well as the potential of organoids in precision medicine and drug testing. Video Abstract.

Organoid assessment technologies

Despite enormous advances in the generation of organoids, robust and stable protocols of organoids are still a major challenge to researchers. Research for assessing structures of organoids and the evaluations of their functions on in vitro or in vivo is often limited by precision strategies. A growing interest in assessing organoids has arisen, aimed at standardizing the process of obtaining organoids to accurately resemble human-derived tissue. The complex microenvironment of organoids, intricate cellular crosstalk, organ-specific architectures and further complicate functions urgently quest for high-through schemes. By utilizing multi-omics analysis and single-cell analysis, cell-cell interaction mechanisms can be deciphered, and their structures can be investigated in a detailed view by histological analysis. In this review, we will conclude the novel approaches to study the molecular mechanism and cell heterogeneity of organoids and discuss the histological and morphological similarity of organoids in comparison to the human body. Future perspectives on functional analysis will be developed and the organoids will become mature models.

Long Noncoding RNA URB1-Antisense RNA 1 (AS1) Suppresses Sorafenib-Induced Ferroptosis in Hepatocellular Carcinoma by Driving Ferritin Phase Separation

Sorafenib, a first-line molecular-target drug for advanced hepatocellular carcinoma (HCC), has been shown to be a potent ferroptosis inducer in HCC. However, we found that there was a lower level of ferroptosis in sorafenib-resistant HCC samples than in sorafenib-sensitive HCC samples, suggesting that sorafenib resistance in HCC may be a result of ferroptosis suppression. Recent reports have shown that long noncoding RNAs (lncRNAs) are involved in programmed cell death (PCD), including apoptosis and ferroptosis. This study aimed to investigate the roles and underlying molecular mechanisms of lncRNAs in sorafenib-induced ferroptosis in HCC cells. Using lncRNA sequencing, we identified a ferroptosis-related lncRNA, URB1-antisense RNA 1 (AS1), which was highly expressed in sorafenib-resistant HCC samples and predicted poor survival in HCC. Furthermore, URB1-AS1 mitigates sorafenib-induced ferroptosis by inducing ferritin phase separation and reducing the cellular free iron content. Hypoxia inducible factor (HIF)-1α was identified as a key factor promoting URB1-AS1 expression in sorafenib-resistant HCC cells. Notably, we found that specifically inhibiting the expression of URB1-AS1 with N-acetylgalactosamine (GalNAc)-small interfering (si)URB1-AS1 successfully enhanced the sensitivity of HCC cells to sorafenib in an in vivo tumor model. Our study uncovered a critical role for URB1-AS1 in the repression of ferroptosis, suggesting URB1-AS1 targeting may represent a potential approach to overcome sorafenib resistance in HCC.

Targeting carbonic anhydrases for the management of hypoxic metastatic tumors

INTRODUCTION

Several isoforms of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) are connected with tumorigenesis. Hypoxic tumors overexpress CA IX and XII as a consequence of HIF activation cascade, being involved in pH regulation, metabolism, and metastases formation. Other isoforms (CA I, II, III, IV) were also reported to be present in some tumors.

AREAS COVERED

Some CA isoforms are biomarkers for disease progression or response to therapy. Inhibitors, antibodies, and other procedures for targeting these enzymes for the treatment of tumors/metastases are discussed. Sulfonamides and coumarins represent the most investigated classes of inhibitors, but carboxylates, selenium, and tellurium-containing inhibitors were also investigated. Hybrid drugs of CA inhibitors with other antitumor agents for multitargeted therapy were reported.

EXPERT OPINION

Targeting CAs present in solid or hematological tumors with selective, targeted inhibitors is a validated approach, which has been consolidated in the last years. A host of new preclinical data and several clinical trials of antibodies and small-molecule inhibitors are ongoing, which connected with the large number of new chemotypes/procedures discovered to be effective, may lead to a breakthrough in this therapeutic area. The scientific/patent literature has been searched for on PubMed, ScienceDirect, Espacenet, and PatentGuru, from 2018 to 2023.

An Inflammatory Checkpoint Generated by IL1RN Splicing Offers Therapeutic Opportunity for KRAS-Mutant Intrahepatic Cholangiocarcinoma

KRAS mutations are causally linked to protumor inflammation and are identified as driving factors in tumorigenesis. Here, using multiomics data gathered from a large set of patients, we showed that KRAS mutation was associated with a specific landscape of alternative mRNA splicing that connected to myeloid inflammation in intrahepatic cholangiocarcinoma (iCCA). Then, we identified a negative feedback mechanism in which the upregulation of interleukin 1 receptor antagonist (IL1RN)-201/203 due to alternative splicing confers vital anti-inflammatory effects in KRAS-mutant iCCA. In KRAS-mutant iCCA mice, both IL1RN-201/203 upregulation and anakinra treatment ignited a significant antitumor immune response by altering neutrophil recruitment and phenotypes. Furthermore, anakinra treatment synergistically enhanced anti-PD-1 therapy to activate intratumoral GZMB+ CD8+ T cells in KRAS-mutant iCCA mice. Clinically, we found that high IL1RN-201/203 levels in patients with KRAS-mutant iCCA were significantly associated with superior response to anti-PD-1 immunotherapy.

SIGNIFICANCE

This work describes a novel inflammatory checkpoint mediated by IL1RN alternative splicing variants that may serve as a promising basis to develop therapeutic options for KRAS-mutant iCCA and other cancers. This article is featured in Selected Articles from This Issue, p. 2109.

Recent advancements in single-cell metabolic analysis for pharmacological research

Cellular heterogeneity is crucial for understanding tissue biology and disease pathophysiology. Pharmacological research is being advanced by single-cell metabolic analysis, which offers a technique to identify variations in RNA, proteins, metabolites, and drug molecules in cells. In this review, the recent advancement of single-cell metabolic analysis techniques and their applications in drug metabolism and drug response are summarized. High-precision and controlled single-cell isolation and manipulation are provided by microfluidics-based methods, such as droplet microfluidics, microchamber, open microfluidic probe, and digital microfluidics. They are used in tandem with variety of detection techniques, including optical imaging, Raman spectroscopy, electrochemical detection, RNA sequencing, and mass spectrometry, to evaluate single-cell metabolic changes in response to drug administration. The advantages and disadvantages of different techniques are discussed along with the challenges and future directions for single-cell analysis. These techniques are employed in pharmaceutical analysis for studying drug response and resistance pathway, therapeutic targets discovery, and in vitro disease model evaluation.

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Modeling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modeling, such as patient-derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single-cell RNA-sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO-based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, the current use of PDOs in complex 3D in vitro models of the TME is discussed and the emerging directions in the development of these models are highlighted. Next, work that has successfully applied single cell analysis to PDO-based models is examined and important experimental considerations are identified for this approach. Finally, open questions are highlighted that may be amenable to exploration using the integration of PDO-based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor-TME interactions.

Organoid: Bridging the gap between basic research and clinical practice

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy. In addition, we also put forward some practical suggestions on how to construct a new generation of organoid platform, which is destined to vigorously promote the reform of basic-translational medicine.

Organoids: approaches and utility in cancer research

ABSTRACT

Organoids are three-dimensional cellular structures with self-organizing and self-differentiation capacities. They faithfully recapitulate structures and functions of in vivo organs as represented by functionality and microstructural definitions. Heterogeneity in in vitro disease modeling is one of the main reasons for anti-cancer therapy failures. Establishing a powerful model to represent tumor heterogeneity is crucial for elucidating tumor biology and developing effective therapeutic strategies. Tumor organoids can retain the original tumor heterogeneity and are commonly used to mimic the cancer microenvironment when co-cultured with fibroblasts and immune cells; therefore, considerable effort has been made recently to promote the use of this new technology from basic research to clinical studies in tumors. In combination with gene editing technology and microfluidic chip systems, engineered tumor organoids show promising abilities to recapitulate tumorigenesis and metastasis. In many studies, the responses of tumor organoids to various drugs have shown a positive correlation with patient responses. Owing to these consistent responses and personalized characteristics with patient data, tumor organoids show excellent potential for preclinical research. Here, we summarize the properties of different tumor models and review their current state and progress in tumor organoids. We further discuss the substantial challenges and prospects in the rapidly developing tumor organoid field.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Models in Pancreatic Neuroendocrine Neoplasms: Current Perspectives and Future Directions

Pancreatic neuroendocrine neoplasms (pNENs) are a heterogeneous group of tumors derived from multiple neuroendocrine origin cell subtypes. Incidence rates for pNENs have steadily risen over the last decade, and outcomes continue to vary widely due to inability to properly screen. These tumors encompass a wide range of functional and non-functional subtypes, with their rarity and slow growth making therapeutic development difficult as most clinically used therapeutics are derived from retrospective analyses. Improved molecular understanding of these cancers has increased our knowledge of the tumor biology for pNENs. Despite these advances in our understanding of pNENs, there remains a dearth of models for further investigation. In this review, we will cover the current field of pNEN models, which include established cell lines, animal models such as mice and zebrafish, and three-dimensional (3D) cell models, and compare their uses in modeling various disease aspects. While no study model is a complete representation of pNEN biology, each has advantages which allow for new scientific understanding of these rare tumors. Future efforts and advancements in technology will continue to create new options in modeling these cancers.

Mini-organs with big impact: Organoids in liver cancer studies

Hepatocellular carcinoma, the most common primary liver cancer and a leading cause of death, is a difficult disease to treat due to its heterogeneous nature. Traditional models, such as 2D culture and patient-derived xenografts, have not proven effective. However, the development of 3D culture techniques, such as organoids, which can mimic the tumor microenvironment (TME) and preserve heterogeneity and pathophysiological properties of tumor cells, offers new opportunities for treatment and research. Organoids also have the potential for biomarker detection and personalized medication, as well as genome editing using CRISPR/Cas9 to study the behavior of certain genes and therapeutic interventions. This review explores to-the-date development of organoids with a focus on TME modeling in 3D organoid cultures. Further, it discusses gene editing using CRISPR/Cas9 in organoids, the challenges faced, and the prospects in the field of organoids.