Intratumoral heterogeneity in cancer progression and response to immunotherapy

Metabolic crosstalk: Extracellular ATP and the tumor microenvironment in cancer progression and therapy

Adenosine 5'-triphosphate (ATP) is a vital element in energy information. It plays a critical role in transmitting signals inside the body, which is necessary for controlling the life activities of all cells, including tumor cells [1]. Its significance extends from intracellular signaling pathways to tumor regression. Purinergic signaling, a form of extracellular paracrine signaling, relies on purine nucleotides. Extracellular ectonucleotidases convert these purine nucleotides to their respective di and mono-phosphate nucleoside forms, contributing significantly to immune biology, cancer biology, and inflammation studies. ATP functions as a mighty damage-linked molecular pattern when released outside the cell, accumulating in inflammatory areas. In the tumor microenvironment (TME), purinergic receptors such as ATP-gated ion channels P2X1-5 and G protein-coupled receptors (GPCR) (P2Y) interact with ATP and other nucleotides, influencing diverse immune cell activities. CD39 and CD73-mediated extracellular ATP degradation contributes to immunosuppression by diminishing ATP-dependent activation and generating adenosine (ADO), potentially hindering antitumor immunity and promoting tumor development. Unraveling the complexities of extracellular ATP (e-ATP) and ADO effects on the TME poses challenges in identifying optimal treatment targets, yet ongoing investigations aim to devise strategies combating e-ATP/ADO-induced immunosuppression, ultimately enhancing anti-tumor immunity. This review explores e-ATP metabolism, its purinergic signaling, and therapeutic strategies targeting associated receptors and enzymes.

SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma

Melanoma, arising from the malignant transformation of melanocytes, stands as the most lethal type of skin cancer. While significant strides have been made in targeted therapy and immunotherapy, substantially enhancing therapeutic efficacy, the prognosis for melanoma patients remains unoptimistic. SIRT7, a nuclear-localized deacetylase, plays a pivotal role in maintaining cellular homeostasis and adapting to external stressors in melanoma, with its activity closely tied to intracellular nicotinamide adenine dinucleotide (NAD+). However, its involvement in adaptive resistance to targeted therapy remains unclear. Herein, we unveil that up-regulated SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma. Initially, we observed a significant increase of SIRT7 expression in publicly available datasets following targeted therapy within a short duration. In consistent, we found elevated SIRT7 expression in melanoma cells subjected to BRAF or MEK inhibitors in vitro. The up-regulation of SIRT7 expression was also confirmed in xenograft tumors in mice after targeted therapy in vivo. Furthermore, we proved that SIRT7 deficiency led to decreased cell viability upon prolonged exposure to BRAF or MEK inhibitors, accompanied by an increase in cell apoptosis. Mechanistically, SIRT7 deficiency restrained the upregulation of genes associated with mitochondrial biogenesis and intracellular ATP levels in response to targeted therapy treatment in melanoma cells. Ultimately, we proved that SIRT7 deficieny could sensitize BRAF-mutant melanoma cells to MAPK inhibition targeted therapy in vivo. In conclusion, our findings underscore the role of SIRT7 in fostering adaptive resistance to targeted therapy through the facilitation of mitochondrial biogenesis. Targeting SIRT7 emerges as a promising strategy to overcome MAPK inhibitor adaptive resistance in melanoma.

Single-cell transcriptome profiles the heterogeneity of tumor cells and microenvironments for different pathological endometrial cancer and identifies specific sensitive drugs

Endometrial cancer (EC) is a highly heterogeneous malignancy characterized by varied pathology and prognoses, and the heterogeneity of its cancer cells and the tumor microenvironment (TME) remains poorly understood. We conducted single-cell RNA sequencing (scRNA-seq) on 18 EC samples, encompassing various pathological types to delineate their specific unique transcriptional landscapes. Cancer cells from diverse pathological sources displayed distinct hallmarks labeled as immune-modulating, proliferation-modulating, and metabolism-modulating cancer cells in uterine clear cell carcinomas (UCCC), well-differentiated endometrioid endometrial carcinomas (EEC-I), and uterine serous carcinomas (USC), respectively. Cancer cells from the UCCC exhibited the greatest heterogeneity. We also identified potential effective drugs and confirmed their effectiveness using patient-derived EC organoids for each pathological group. Regarding the TME, we observed that prognostically favorable CD8+ Tcyto and NK cells were prominent in normal endometrium, whereas CD4+ Treg, CD4+ Tex, and CD8+ Tex cells dominated the tumors. CXCL3+ macrophages associated with M2 signature and angiogenesis were exclusively found in tumors. Prognostically relevant epithelium-specific cancer-associated fibroblasts (eCAFs) and SOD2+ inflammatory CAFs (iCAFs) predominated in EEC-I and UCCC groups, respectively. We also validated the oncogenic effects of SOD2+ iCAFs in vitro. Our comprehensive study has yielded deeper insights into the pathogenesis of EC, potentially facilitating personalized treatments for its varied pathological types.

Mechanism insights and therapeutic intervention of tumor metastasis: latest developments and perspectives

Metastasis remains a pivotal characteristic of cancer and is the primary contributor to cancer-associated mortality. Despite its significance, the mechanisms governing metastasis are not fully elucidated. Contemporary findings in the domain of cancer biology have shed light on the molecular aspects of this intricate process. Tumor cells undergoing invasion engage with other cellular entities and proteins en route to their destination. Insights into these engagements have enhanced our comprehension of the principles directing the movement and adaptability of metastatic cells. The tumor microenvironment plays a pivotal role in facilitating the invasion and proliferation of cancer cells by enabling tumor cells to navigate through stromal barriers. Such attributes are influenced by genetic and epigenetic changes occurring in the tumor cells and their surrounding milieu. A profound understanding of the metastatic process's biological mechanisms is indispensable for devising efficacious therapeutic strategies. This review delves into recent developments concerning metastasis-associated genes, important signaling pathways, tumor microenvironment, metabolic processes, peripheral immunity, and mechanical forces and cancer metastasis. In addition, we combine recent advances with a particular emphasis on the prospect of developing effective interventions including the most popular cancer immunotherapies and nanotechnology to combat metastasis. We have also identified the limitations of current research on tumor metastasis, encompassing drug resistance, restricted animal models, inadequate biomarkers and early detection methods, as well as heterogeneity among others. It is anticipated that this comprehensive review will significantly contribute to the advancement of cancer metastasis research.

Impacts of tumor microenvironment during neoadjuvant chemotherapy in patients with esophageal squamous cell carcinoma

With the advent of immune checkpoint inhibitors (ICIs), a better understanding of tumor microenvironment (TME) is becoming crucial in managing esophageal squamous cell carcinoma (ESCC) patients. We investigated the survival impact of TME status and changes in patients with ESCC who underwent neoadjuvant chemotherapy (NAC) followed by surgery (n = 264). We examined immunohistochemical status (CD4+, CD8+, CD20+, Foxp3+, HLA class-1+, CD204+, and programmed death ligand-1 [PD-L1+]) on 264 pre-NAC and 204 paired post-NAC specimens. Patients were classified by their pre- and post-NAC immune cell status and their changes following NAC. Our findings showed that pre-NAC TME status was not significantly associated with survival outcomes. In contrast, post-NAC TME status, such as low level of T cells, CD4+ T cells, and high PD-L1 combined positive score (CPS), were significantly associated with poor overall survival (OS). Notably, TME changes through NAC exerted significant survival impacts; patients with consistently low levels of T cells, low levels of CD4+ T cells, or high levels of PD-L1 (CPS) had very poor OS (3-year OS: 35.5%, 40.2%, and 33.3%, respectively). Tumor microenvironment changes of consistently low T cells, low CD4+ T cells, and high PD-L1 were independent predictors of poor OS in multivariate Cox hazards analyses, while factors indicating post-NAC status (T cells, CD4+, and PD-L1 [CPS]) alone were not. Therefore, we suggest that the consistently low T/high PD-L1 group could benefit from additional therapies, such as ICIs, and the importance of stratification by the TME, which has recently been recognized.

Towards targeting the breast cancer immune microenvironment

The tumour immune microenvironment is shaped by the crosstalk between cancer cells, immune cells, fibroblasts, endothelial cells and other stromal components. Although the immune tumour microenvironment (TME) serves as a source of therapeutic targets, it is also considered a friend or foe to tumour-directed therapies. This is readily illustrated by the importance of T cells in triple-negative breast cancer (TNBC), culminating in the advent of immune checkpoint therapy in combination with cytotoxic chemotherapy as standard of care for both early and advanced-stage TNBC, as well as recent promising signs of efficacy in a subset of hormone receptor-positive disease. In this Review, we discuss the various components of the immune TME in breast cancer and therapies that target or impact the immune TME, as well as the complexity of host physiology.

Metabolic heterogeneity in tumor microenvironment - A novel landmark for immunotherapy

The surrounding non-cancer cells and tumor cells that make up the tumor microenvironment (TME) have various metabolic rhythms. TME metabolic heterogeneity is influenced by the intricate network of metabolic control within and between cells. DNA, protein, transport, and microbial levels are important regulators of TME metabolic homeostasis. The effectiveness of immunotherapy is also closely correlated with alterations in TME metabolism. The response of a tumor patient to immunotherapy is influenced by a variety of variables, including intracellular metabolic reprogramming, metabolic interaction between cells, ecological changes within and between tumors, and general dietary preferences. Although immunotherapy and targeted therapy have made great strides, their use in the accurate identification and treatment of tumors still has several limitations. The function of TME metabolic heterogeneity in tumor immunotherapy is summarized in this article. It focuses on how metabolic heterogeneity develops and is regulated as a tumor progresses, the precise molecular mechanisms and potential clinical significance of imbalances in intracellular metabolic homeostasis and intercellular metabolic coupling and interaction, as well as the benefits and drawbacks of targeted metabolism used in conjunction with immunotherapy. This offers insightful knowledge and important implications for individualized tumor patient diagnosis and treatment plans in the future.

BNIP3-mediated mitophagy boosts the competitive growth of Lenvatinib-resistant cells via energy metabolism reprogramming in HCC

An increasing evidence supports that cell competition, a vital selection and quality control mechanism in multicellular organisms, is involved in tumorigenesis and development; however, the mechanistic contributions to the association between cell competition and tumor drug resistance remain ill-defined. In our study, based on a contructed lenvitinib-resistant hepatocellular carcinoma (HCC) cells display obvious competitive growth dominance over sensitive cells through reprogramming energy metabolism. Mechanistically, the hyperactivation of BCL2 interacting protein3 (BNIP3) -mediated mitophagy in lenvatinib-resistant HCC cells promotes glycolytic flux via shifting energy production from mitochondrial oxidative phosphorylation to glycolysis, by regulating AMP-activated protein kinase (AMPK) -enolase 2 (ENO2) signaling, which perpetually maintaining lenvatinib-resistant HCC cells' competitive advantage over sensitive HCC cells. Of note, BNIP3 inhibition significantly sensitized the anti-tumor efficacy of lenvatinib in HCC. Our findings emphasize a vital role for BNIP3-AMPK-ENO2 signaling in maintaining the competitive outcome of lenvitinib-resistant HCC cells via regulating energy metabolism reprogramming; meanwhile, this work recognizes BNIP3 as a promising target to overcome HCC drug resistance.

Deconstructing Intratumoral Heterogeneity through Multiomic and Multiscale Analysis of Serial Sections

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that are consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

Revisiting the advances and challenges in the clinical applications of extracellular vesicles in cancer

Extracellular vesicles (EVs) have been the subject of an exponentially growing number of studies covering their biogenesis mechanisms, isolation and analysis techniques, physiological and pathological roles, and clinical applications, such as biomarker and therapeutic uses. Nevertheless, the heterogeneity of EVs both challenges our understanding of them and presents new opportunities for their potential application. Recently, the EV field experienced a wide range of advances. However, the challenges also remain huge. This review focuses on the recent progress and difficulties encountered in the practical use of EVs in clinical settings. In addition, we also explored the concept of EV heterogeneity to acquire a more thorough understanding of EVs and their involvement in cancer, specifically focusing on the fundamental nature of EVs.

CT-derived Radiomics Predicts the Efficacy of Tyrosine Kinase Inhibitors in Osteosarcoma Patients with Pulmonary Metastasis

BACKGROUND

To construct and validate the CT-based radiomics model for predicting the tyrosine kinase inhibitors (TKIs) effects in osteosarcoma (OS) patients with pulmonary metastasis.

METHODS

OS patients with pulmonary metastasis treated with TKIs were randomly separated into training and testing cohorts (2:1 ratio). Radiomic features were extracted from the baseline unenhanced chest CT images. The random survival forest (RSF) and Kaplan-Meier survival analyses were performed to construct and evaluate radiomics signatures (R-model-derived). The univariant and multivariant Cox regression analyses were conducted to establish clinical (C-model) and combined models (RC-model). The discrimination abilities, goodness of fit and clinical benefits of the three models were assessed and validated in both training and testing cohorts.

RESULTS

A total of 90 patients, 57 men and 33 women, with a mean age of 18 years and median progression-free survival (PFS) of 7.2 months, were enrolled. The R-model was developed with nine radiomic features and demonstrated significant predictive and prognostic values. In both training and testing cohorts, the time-dependent area under the receiver operating characteristic curves (AUC) of the R-model and RC-model exhibited obvious superiority over C-model. The calibration and decision curve analysis (DCA) curves indicated that the accuracy of the R-model was comparable to RC-model, which exhibited significantly better performance than C-model.

CONCLUSIONS

The R-model showed promising potential as a predictor for TKI responses in OS patients with pulmonary metastasis. It can potentially identify pulmonary metastatic OS patients most likely to benefit from TKIs treatment and help guide optimized clinical decisions.

Single cell RNA-sequencing in uveal melanoma: advances in heterogeneity, tumor microenvironment and immunotherapy

Uveal melanoma (UM) is a highly aggressive and fatal tumor in the eye, and due the special biology of UM, immunotherapy showed little effect in UM patients. To improve the efficacy of immunotherapy for UM patients is of great clinical importance. Single-cell RNA sequencing(scRNA-seq) provides a critical perspective for deciphering the complexity of intratumor heterogeneity and tumor microenvironment(TME). Combing the bioinformatics analysis, scRNA-seq could help to find prognosis-related molecular indicators, develop new therapeutic targets especially for immunotherapy, and finally to guide the clinical treatment options.

Metabolic Insight into Glioma Heterogeneity: Mapping Whole Exome Sequencing to In Vivo Imaging with Stereotactic Localization and Deep Learning

Intratumoral heterogeneity (ITH) complicates the diagnosis and treatment of glioma, partly due to the diverse metabolic profiles driven by underlying genomic alterations. While multiparametric imaging enhances the characterization of ITH by capturing both spatial and functional variations, it falls short in directly assessing the metabolic activities that underpin these phenotypic differences. This gap stems from the challenge of integrating easily accessible, colocated pathology and detailed genomic data with metabolic insights. This study presents a multifaceted approach combining stereotactic biopsy with standard clinical open-craniotomy for sample collection, voxel-wise analysis of MR images, regression-based GAM, and whole-exome sequencing. This work aims to demonstrate the potential of machine learning algorithms to predict variations in cellular and molecular tumor characteristics. This retrospective study enrolled ten treatment-naïve patients with radiologically confirmed glioma. Each patient underwent a multiparametric MR scan (T1W, T1W-CE, T2W, T2W-FLAIR, DWI) prior to surgery. During standard craniotomy, at least 1 stereotactic biopsy was collected from each patient, with screenshots of the sample locations saved for spatial registration to pre-surgical MR data. Whole-exome sequencing was performed on flash-frozen tumor samples, prioritizing the signatures of five glioma-related genes: IDH1, TP53, EGFR, PIK3CA, and NF1. Regression was implemented with a GAM using a univariate shape function for each predictor. Standard receiver operating characteristic (ROC) analyses were used to evaluate detection, with AUC (area under curve) calculated for each gene target and MR contrast combination. Mean AUC for five gene targets and 31 MR contrast combinations was 0.75 ± 0.11; individual AUCs were as high as 0.96 for both IDH1 and TP53 with T2W-FLAIR and ADC, and 0.99 for EGFR with T2W and ADC. These results suggest the possibility of predicting exome-wide mutation events from noninvasive, in vivo imaging by combining stereotactic localization of glioma samples and a semi-parametric deep learning method. The genomic alterations identified, particularly in IDH1, TP53, EGFR, PIK3CA, and NF1, are known to play pivotal roles in metabolic pathways driving glioma heterogeneity. Our methodology, therefore, indirectly sheds light on the metabolic landscape of glioma through the lens of these critical genomic markers, suggesting a complex interplay between tumor genomics and metabolism. This approach holds potential for refining targeted therapy by better addressing the genomic heterogeneity of glioma tumors.

Recent advances in chemical biology tools for protein and RNA profiling of extracellular vesicles

Extracellular vesicles (EVs) are nano-sized vesicles secreted by cells that contain various cellular components such as proteins, nucleic acids, and lipids from the parent cell. EVs are abundant in body fluids and can serve as circulating biomarkers for a variety of diseases or as a regulator of various biological processes. Considering these characteristics of EVs, analysis of the EV cargo has been spotlighted for disease diagnosis or to understand biological processes in biomedical research. Over the past decade, technologies for rapid and sensitive analysis of EVs in biofluids have evolved, but detection and isolation of targeted EVs in complex body fluids is still challenging due to the unique physical and biological properties of EVs. Recent advances in chemical biology provide new opportunities for efficient profiling of the molecular contents of EVs. A myriad of chemical biology tools have been harnessed to enhance the analytical performance of conventional assays for better understanding of EV biology. In this review, we will discuss the improvements that have been achieved using chemical biology tools.

Nanodrugs based on co-delivery strategies to combat cisplatin resistance

Cisplatin (CDDP), as a broad-spectrum anticancer drug, is able to bind to DNA and inhibit cell division. Despite the widespread use of cisplatin since its discovery, cisplatin resistance developed during prolonged chemotherapy, similar to other small molecule chemotherapeutic agents, severely limits its clinical application. Cisplatin resistance in cancer cells is mainly caused by three reasons: DNA repair, decreased cisplatin uptake/increased efflux, and cisplatin inactivation. In earlier combination therapies, the emergence of multidrug resistance (MDR) in cancer cells prevented the achievement of the desired therapeutic effect even with the accurate combination of two chemotherapeutic drugs. Therefore, combination therapy using nanocarriers for co-delivery of drugs is considered to be ideal for alleviating cisplatin resistance and reducing cisplatin-related toxicity in cancer cells. This article provides an overview of the design of cisplatin nano-drugs used to combat cancer cell resistance, elucidates the mechanisms of action of cisplatin and the pathways through which cancer cells develop resistance, and finally discusses the design of drugs and related carriers that can synergistically reduce cancer resistance when combined with cisplatin.

Exploring the mechanism of contact-dependent cell-cell communication on chemosensitivity based on single-cell high-throughput drug screening platform

High-throughput drug screening (HTDS) has significantly reduced the time and cost of new drug development. Nonetheless, contact-dependent cell-cell communication (CDCCC) may impact the chemosensitivity of tumour cells. There is a pressing need for low-cost single-cell HTDS platforms, alongside a deep comprehension of the mechanisms by which CDCCC affects drug efficacy, to fully unveil the efficacy of anticancer drugs. In this study, we develop a microfluidic chip for single-cell HTDS and evaluate the molecular mechanisms impacted by CDCCC using quantitative mass spectrometry-based proteomics. The chip achieves high-quality drug mixing and single-cell capture, with single-cell drug screening results on the chip showing consistency with those on the 96-well plates under varying concentration gradients. Through quantitative proteomic analysis, we deduce that the absence of CDCCC in single tumour cells can enhance their chemoresistance potential, but simultaneously subject them to stronger proliferation inhibition. Additionally, pathway enrichment analysis suggests that CDCCC could impact several signalling pathways in tumour single cells that regulate vital biological processes such as tumour proliferation, adhesion, and invasion. These results offer valuable insights into the potential connection between CDCCC and the chemosensitivity of tumour cells. This research paves the way for the development of single-cell HTDC platforms and holds the promise of advancing tumour personalized treatment strategies.

Targeting immunogenic cell stress and death for cancer therapy

Immunogenic cell death (ICD), which results from insufficient cellular adaptation to specific stressors, occupies a central position in the development of novel anticancer treatments. Several therapeutic strategies to elicit ICD - either as standalone approaches or as means to convert immunologically cold tumours that are insensitive to immunotherapy into hot and immunotherapy-sensitive lesions - are being actively pursued. However, the development of ICD-inducing treatments is hindered by various obstacles. Some of these relate to the intrinsic complexity of cancer cell biology, whereas others arise from the use of conventional therapeutic strategies that were developed according to immune-agnostic principles. Moreover, current discovery platforms for the development of novel ICD inducers suffer from limitations that must be addressed to improve bench-to-bedside translational efforts. An improved appreciation of the conceptual difference between key factors that discriminate distinct forms of cell death will assist the design of clinically viable ICD inducers.

Mn-phenolic networks as synergistic carrier for STING agonists in tumor immunotherapy

The cGAS-STING pathway holds tremendous potential as a regulator of immune responses, offering a means to reshape the tumor microenvironment and enhance tumor immunotherapy. Despite the emergence of STING agonists, their clinical viability is hampered by stability and delivery challenges, as well as variations in STING expression within tumors. In this study, we present Mn-phenolic networks as a novel carrier for ADU-S100, a hydrophilic STING agonist, aimed at bolstering immunotherapy. These nanoparticles, termed TMA NMs, are synthesized through the coordination of tannic acid and manganese ions, with surface modification involving bovine serum albumin to enhance their colloidal stability. TMA NMs exhibit pH/GSH-responsive disintegration properties, enabling precise drug release. This effectively addresses drug stability issues and facilitates efficient intracellular drug delivery. Importantly, TMA NMs synergistically enhance the effects of ADU-S100 through the concurrent release of Mn2+, which serves as a sensitizer of the STING pathway, resulting in significant STING pathway activation. Upon systemic administration, these nanoparticles efficiently accumulate within tumors. The activation of STING pathways not only induces immunogenic cell death (ICD) in tumor cells but also orchestrates systemic remodeling of the immunosuppressive microenvironment. This includes the promotion of cytokine release, dendritic cell maturation, and T cell infiltration, leading to pronounced suppression of tumor growth. Combining with the excellent biocompatibility and biodegradability, this Mn-based nanocarrier represents a promising strategy for enhancing tumor immunotherapy through the cGAS-STING pathway.

Extracellular vesicles-powered immunotherapy: Unleashing the potential for safer and more effective cancer treatment

Cancer treatment has seen significant advancements with the introduction of Onco-immunotherapies (OIMTs). Although some of these therapies have received approval for use, others are either undergoing testing or are still in the early stages of development. Challenges persist in making immunotherapy widely applicable to cancer treatment. To maximize the benefits of immunotherapy and minimize potential side effects, it's essential to improve response rates across different immunotherapy methods. A promising development in this area is the use of extracellular vesicles (EVs) as novel delivery systems. These small vesicles can effectively deliver immunotherapies, enhancing their effectiveness and reducing harmful side effects. This article discusses the importance of integrating nanomedicines into OIMTs, highlighting the challenges with current anti-OIMT methods. It also explores key considerations for designing nanomedicines tailored for OIMTs, aiming to improve upon existing immunotherapy techniques. Additionally, the article looks into innovative approaches like biomimicry and the use of natural biomaterial-based nanocarriers (NCs). These advancements have the potential to transform the delivery of immunotherapy. Lastly, the article addresses the challenges of moving OIMTs from theory to clinical practice, providing insights into the future of using advanced nanotechnology in cancer treatment.

Time-dependent proteomics and drug response in expanding cancer cells

Cancer cell line is commonly used for discovery and development of anti-cancer drugs. It is generally considered that drug response remains constant for a certain cell line due to the identity of genetics thus protein patterns. Here, we demonstrated that cancer cells continued dividing even after reaching confluence, in that the proteomics was changed continuously and dramatically with strong relevance to cell division, cell adhesion and cell metabolism, indicating time-dependent intrinsically reprogramming of cells during expansion. Of note, the inhibition effect of most anti-cancer drugs was strikingly attenuated in culture cells along with cell expansion, with the strongest change at the third day when cells were still expanding. Profiling of an FDA-approved drug library revealed that attenuation of response with cell expansion is common for most drugs, an exception was TAK165 that was a selective inhibitor of mitochondrial respiratory chain complex I. Finally, we screened a panel of natural products and identified four pentacyclic triterpenes as selective inhibitors of cancer cells under prolonged growth. Taken together, our findings underscore that caution should be taken in evaluation of anti-cancer drugs using culture cells, and provide agents selectively targeting overgrowth cancer cells.

Stable Isotope Tracing Analysis in Cancer Research: Advancements and Challenges in Identifying Dysregulated Cancer Metabolism and Treatment Strategies

Metabolic reprogramming is a hallmark of cancer, driving the development of therapies targeting cancer metabolism. Stable isotope tracing has emerged as a widely adopted tool for monitoring cancer metabolism both in vitro and in vivo. Advances in instrumentation and the development of new tracers, metabolite databases, and data analysis tools have expanded the scope of cancer metabolism studies across these scales. In this review, we explore the latest advancements in metabolic analysis, spanning from experimental design in stable isotope-labeling metabolomics to sophisticated data analysis techniques. We highlight successful applications in cancer research, particularly focusing on ongoing clinical trials utilizing stable isotope tracing to characterize disease progression, treatment responses, and potential mechanisms of resistance to anticancer therapies. Furthermore, we outline key challenges and discuss potential strategies to address them, aiming to enhance our understanding of the biochemical basis of cancer metabolism.

Integrated pan-cancer analysis reveals the immunological and prognostic potential of RBFOX2 in human tumors

Background

The role of RNA-binding fox one homolog 2 (RBFOX2) in the progression of multiple tumors is increasingly supported by evidence. However, the unclearness pertaining to the expression of RBFOX2, its prognostic potential, and its correlation with the tumor microenvironment (TME) in pan-cancer persists. This study aims to comprehensively investigate the immunological prognostic value of RBFOX2.

Methods

The Cancer Genome Atlas Gene Expression Omnibus Genotype-Tissue Expression (GTEx), TIMER2.0, Kaplan-Meier (K-M) Plotter, University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), cbioportal, and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) were utilized for a systematic analysis of RBFOX2. This analysis included studying its expression, prognostic value, DNA methylation, enrichment analysis, immune infiltration cells, and immune-related genes. Additionally, qRT-PCR, CCK-8, colony formation, transwell assays, and immunohistochemistry were employed to analyze the expression and biological function of RBFOX2 in liver cancer.

Results

Variations in RBFOX2 expression have been observed across diverse tumors and have been identified as indicators of unfavorable prognosis. It is closely linked to immune infiltration cells, immune checkpoints, chemokines, and chemokine receptors in the TME. Higher levels of RBFOX2 have been significantly associated with low response and poor prognosis in patients with non-small cell lung cancer (NSCLC) and melanoma who receive immunotherapy. Furthermore, the DNA methylation of RBFOX2 varies across different types of cancer and has shown better prognosis in patients with BLCA, BRCA, CESC, COAD, DLBC, HNSC, LAML, LGG, LUAD, PAAD, SKCM and THYM. Interestingly, RBFOX2 expression was found to be lower in hepatocellular carcinoma (HCC) patients' tumor tissues compared to their paired adjacent tissues. In vitro studies have shown that knockdown of RBFOX2 significantly promotes the growth and metastasis of liver cancer cells.

Conclusion

This study investigates the correlation between DNA methylation, prognostic value, and immune cell infiltration with the expression of RBFOX2 in pan-cancer and indicates its potential role to inhibit metastasis of liver cancer.

In silico study of heterogeneous tumour-derived organoid response to CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapy for treating cancers. This method consists in modifying the patients' T-cells to directly target antigen-presenting cancer cells. One of the barriers to the development of this type of therapies, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency. In this work we introduce an agent-based model (ABM), built upon a previous ABM, to rationalise the outcomes of different CAR T-cells therapies strategies over heterogeneous tumour-derived organoids. We found that one dose of CAR T-cell therapy should be expected to reduce the tumour size as well as its growth rate, however it may not be enough to completely eliminate it. Moreover, the amount of free CAR T-cells (i.e. CAR T-cells that did not kill any cancer cell) increases as we increase the dosage, and so does the risk of side effects. We tested different strategies to enhance smaller dosages, such as enhancing the CAR T-cells long-term persistence and multiple dosing. For both approaches an appropriate dosimetry strategy is necessary to produce "effective yet safe" therapeutic results. Moreover, an interesting emergent phenomenon results from the simulations, namely the formation of a shield-like structure of cells with low antigen expression. This shield turns out to protect cells with high antigen expression. Finally we tested a multi-antigen recognition therapy to overcome antigen escape and heterogeneity. Our studies suggest that larger dosages can completely eliminate the organoid, however the multi-antigen recognition increases the risk of side effects. Therefore, an appropriate small dosages dosimetry strategy is necessary to improve the outcomes. Based on our results, it is clear that a proper therapeutic strategy could enhance the therapies outcomes. In that direction, our computational approach provides a framework to model treatment combinations in different scenarios and to explore the characteristics of successful and unsuccessful treatments.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Classification of multiple primary lung cancer in patients with multifocal lung cancer: assessment of a machine learning approach using multidimensional genomic data

Background

Multiple primary lung cancer (MPLC) is an increasingly well-known clinical phenomenon. However, its molecular characterizations are poorly understood, and still lacks of effective method to distinguish it from intrapulmonary metastasis (IM). Herein, we propose an identification model based on molecular multidimensional analysis in order to accurately optimize treatment.

Methods

A total of 112 Chinese lung cancers harboring at least two tumors (n = 270) were enrolled. We retrospectively selected 74 patients with 121 tumor pairs and randomly divided the tumor pairs into a training cohort and a test cohort in a 7:3 ratio. A novel model was established in training cohort, optimized for MPLC identification using comprehensive genomic profiling analyzed by a broad panel with 808 cancer-related genes, and evaluated in the test cohort and a prospective validation cohort of 38 patients with 112 tumors.

Results

We found differences in molecular characterizations between the two diseases and rigorously selected the characterizations to build an identification model. We evaluated the performance of the classifier using the test cohort data and observed an 89.5% percent agreement (PA) for MPLC and a 100.0% percent agreement for IM. The model showed an excellent area under the curve (AUC) of 0.947 and a 91.3% overall accuracy. Similarly, the assay achieved a considerable performance in the independent validation set with an AUC of 0.938 and an MPLC predictive value of 100%. More importantly, the MPLC predictive value of the classification achieved 100% in both the test set and validation cohort. Compared to our previous mutation-based method, the classifier showed better κ consistencies with clinical classification among all 112 patients (0.84 vs. 0.65, p <.01).

Conclusion

These data provide novel evidence of MPLC-specific genomic characteristics and demonstrate that our one-step molecular classifier can accurately classify multifocal lung tumors as MPLC or IM, which suggested that broad panel NGS may be a useful tool for assisting with differential diagnoses.

Immune-tumor interaction dictates spatially directed evolution of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a poor-prognostic cancer type with extensive intra- and inter-patient heterogeneity in both genomic variations and tumor microenvironment (TME). However, the patterns and drivers of spatial genomic and microenvironmental heterogeneity of ESCC remain largely unknown. Here, we generated a spatial multi-omic atlas by whole-exome, transcriptome, and methylome sequencing of 507 tumor samples from 103 patients. We identified a novel tumor suppressor PREX2, accounting for 22% of ESCCs with frequent somatic mutations or hyper-methylation, which promoted migration and invasion of ESCC cells in vitro. Analysis of the TME and quantification of subclonal expansion indicated that ESCCs undergo spatially directed evolution, where subclones mostly originated from the tumor center but had a biased clonal expansion to the upper direction of the esophagus. Interestingly, we found upper regions of ESCCs often underwent stronger immunoediting with increased selective fitness, suggesting more stringent immune selection. In addition, distinct TMEs were associated with variable genomic and clinical outcomes. Among them, hot TME was associated with high immune evasion and subclonal heterogeneity. We also found that immunoediting, instead of CD8+ T cell abundance, acts as an independent prognostic factor of ESCCs. Importantly, we found significant heterogeneity in previously considered potential therapeutic targets, as well as BRCAness characteristics in a subset of patients, emphasizing the importance of focusing on heterogeneity in ESCC targeted therapy. Collectively, these findings provide novel insights into the mechanisms of the spatial evolution of ESCC and inform precision therapeutic strategies.

Multifactorial drug carrier system bringing both chemical and physical therapeutics to the treatment of tumor heterogeneity

Tumor heterogeneity and drug resistance have been invincible features of cancer for its complete cure. Despite the advent of immunotherapy, the expansion and diversification of cancer cells evolved even in the absence or presence of drug treatment discourage additional therapeutic interventions. For the eradication of cancer cells, therefore, an 'all-at-once' strategy is required, which exploits both target-selective chemotherapy and non-selective physicotherapy. Multifactorial microcapsules comprising gold nanoparticles (AuNPs) and a self-assembly protein of α-synuclein (αS) were fabricated, in which hydrophobic and hydrophilic drugs could be separately encapsulated by employing lipid-based inverted micelles (IMs). Their combined physico-chemical therapeutic effects were examined since they also contained both membrane-disrupting IMs and heat-generating AuNPs upon irradiation as physicotherapeutic agents. For the optimal enclosure of IMs containing hydrophilic drugs, a porous inner skeleton made of poly(lactic-co-glycolic acid) was introduced, which would play the roles of not only compartmentalizing the internal space but also enhancing proteolytic disintegration of the microcapsules to discharge and stabilize IMs to the outside. In fact, hydrophobic paclitaxel and hydrophilic doxorubicin showed markedly enhanced drug efficacy when delivered in the IM-containing microcapsules exhibiting the 'quantal' release of both drugs into the cells whose integrity could be also affected by the IMs. In addition, the remnants of αS-AuNP microcapsules produced via proteolysis also caused cell death through photothermal effect. The multifactorial microcapsules are therefore considered as a promising anti-cancer drug carrier capable of performing combinatorial selective and non-selective chemical and physical therapies to overcome tumor heterogeneity and drug resistance.

Sensing, Imaging, and Therapeutic Strategies Endowing by Conjugate Polymers for Precision Medicine

Conjugated polymers (CPs) have promising applications in biomedical fields, such as disease monitoring, real-time imaging diagnosis, and disease treatment. As a promising luminescent material with tunable emission, high brightness and excellent stability, CPs are widely used as fluorescent probes in biological detection and imaging. Rational molecular design and structural optimization have broadened absorption/emission range of CPs, which are more conductive for disease diagnosis and precision therapy. This review provides a comprehensive overview of recent advances in the application of CPs, aiming to elucidate their structural and functional relationships. The fluorescence properties of CPs and the mechanism of detection signal amplification are first discussed, followed by an elucidation of their emerging applications in biological detection. Subsequently, CPs-based imaging systems and therapeutic strategies are illustrated systematically. Finally, recent advancements in utilizing CPs as electroactive materials for bioelectronic devices are also investigated. Moreover, the challenges and outlooks of CPs for precision medicine are discussed. Through this systematic review, it is hoped to highlight the frontier progress of CPs and promote new breakthroughs in fundamental research and clinical transformation.

Cell Electrokinetic Fingerprint: A Novel Approach Based on Optically Induced Dielectrophoresis (ODEP) for In-Flow Identification of Single Cells

A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a "ping-pong" match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.

LARP4B promotes hepatocellular carcinoma progression and impairs sorafenib efficacy by activating SPINK1-mediated EGFR pathway

La-related proteins (LARPs) regulate gene expression by binding to RNAs and exhibit critical effects on disease progression, including tumors. However, the role of LARP4B and its underlying mechanisms in the progression of hepatocellular carcinoma (HCC) remain largely unclear. In this study, we found that LARP4B expression is upregulated and correlates with poor prognosis in patients with HCC. Gain- and loss-of-function assays showed that LARP4B promotes stemness, proliferation, metastasis, and angiogenesis in vitro and in vivo. Furthermore, LARP4B inhibition enhances the antitumor effects of sorafenib and blocks the metastasis-enhancing effects of low sorafenib concentrations in HCC. Mechanistically, LARP4B expression is upregulated by METTL3-mediated N6-methyladenosine (m6A)-IGF2BP3-dependent modification in HCC. RNA- and RNA immunoprecipitation (RIP)- sequencing uncovered that LARP4B upregulates SPINK1 by binding to SPINK1 mRNA via the La motif and maintaining mRNA stability. LARP4B activates the SPINK1-mediated EGFR signaling pathway, which supports stemness, progression and sorafenib resistance in HCC. Additionally, a positive feedback loop with the LARP4B/SPINK1/p-AKT/C/EBP-β axis is responsible for the sorafenib-therapeutic benefit of LARP4B depletion. Overall, this study demonstrated that LARP4B facilitates HCC progression, and LARP4B inhibition provides benefits to sorafenib treatment in HCC, suggesting that LARP4B might be a potential therapeutic target for HCC.

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Cancer cell metabolism and antitumour immunity

Accumulating evidence suggests that metabolic rewiring in malignant cells supports tumour progression not only by providing cancer cells with increased proliferative potential and an improved ability to adapt to adverse microenvironmental conditions but also by favouring the evasion of natural and therapy-driven antitumour immune responses. Here, we review cancer cell-intrinsic and cancer cell-extrinsic mechanisms through which alterations of metabolism in malignant cells interfere with innate and adaptive immune functions in support of accelerated disease progression. Further, we discuss the potential of targeting such alterations to enhance anticancer immunity for therapeutic purposes.

A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments

Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by using droplet microfluidic technology based on a microinjection strategy. This method enables precise manipulation of clinical microsamples and rapid generation of LCAs with good intra-batch consistency in size and cell composition by evenly encapsulating patient tumor-derived TME cells and lung cancer organoids inside microgels. LCAs recapitulate the inter- and intratumoral heterogeneity, TME cellular diversity, and genomic and transcriptomic landscape of their parental tumors. LCA model could reconstruct the functional heterogeneity of cancer-associated fibroblasts and reflect the influence of TME on drug responses compared to cancer organoids. Notably, LCAs accurately replicate the clinical outcomes of patients, suggesting the potential of the LCA model to predict personalized treatments. Collectively, our studies provide a valuable method for precisely fabricating cancer assembloids and a promising LCA model for cancer research and personalized medicine.

Noncovalently particle-anchored cytokines with prolonged tumor retention safely elicit potent antitumor immunity

Preclinical studies have shown that immunostimulatory cytokines elicit antitumor immune responses but their clinical use is limited by severe immune-related adverse events upon systemic administration. Here, we report a facile and versatile strategy for noncovalently anchoring potent Fc-fused cytokine molecules to the surface of size-discrete particles decorated with Fc-binding peptide for local administration. Following intratumoral injection, particle-anchored Fc cytokines exhibit size-dependent intratumoral retention. The 1-micrometer particle prolongs intratumoral retention of Fc cytokine for over a week and has minimal systemic exposure, thereby eliciting antitumor immunity while eliminating systemic toxicity caused by circulating cytokines. In addition, the combination of these particle-anchored cytokines with immune checkpoint blockade antibodies safely promotes tumor regression in various syngeneic tumor models and genetically engineered murine tumor models and elicits systemic antitumor immunity against tumor rechallenge. Our formulation strategy renders a safe and tumor-agnostic approach that uncouples cytokines' immunostimulatory properties from their systemic toxicities for potential clinical application.

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.

miRNome targeting NF-κB signaling orchestrates macrophage-triggered cancer metastasis and recurrence

Whether and how tumor intrinsic signature determines macrophage-elicited metastasis remain elusive. Here, we show, in detailed studies of data regarding 7,477 patients of 20 types of human cancers, that only 13.8% ± 2.6%/27.9% ± 3.03% of patients with high macrophage infiltration index exhibit early recurrence/vascular invasion. In parallel, although macrophages enhance the motility of various hepatoma cells, their enhancement intensity is significantly heterogeneous. We identify that the expression of malignant Dicer, a ribonuclease that cleaves miRNA precursors into mature miRNAs, determines macrophage-elicited metastasis. Mechanistically, the downregulation of Dicer in cancer cells leads to defects in miRNome targeting NF-κB signaling, which in turn enhances the ability of cancer cells to respond to macrophage-related inflammatory signals and ultimately promotes metastasis. Importantly, transporting miR-26b-5p, the most potential miRNA targeting NF-κB signaling in hepatocellular carcinoma, can effectively reverse macrophage-elicited metastasis of hepatoma in vivo. Our results provide insights into the crosstalk between Dicer-elicited miRNome and cancer immune microenvironments and suggest that strategies to remodel malignant cell miRNome may overcome pro-tumorigenic activities of inflammatory cells.

Single-cell RNA-seq reveals T cell exhaustion and immune response landscape in osteosarcoma

Background

T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear.

Methods

In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups.

Results

The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group.

Conclusion

In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients.

XTX301, a Tumor-Activated Interleukin-12 Has the Potential to Widen the Therapeutic Index of IL12 Treatment for Solid Tumors as Evidenced by Preclinical Studies

IL12 is a proinflammatory cytokine, that has shown promising antitumor activity in humans by promoting the recruitment and activation of immune cells in tumors. However, the systemic administration of IL12 has been accompanied by considerable toxicity, prompting interest in researching alternatives to drive preferential IL12 bioactivity in the tumor. Here, we have generated XTX301, a tumor-activated IL12 linked to the human Fc protein via a protease cleavable linker that is pharmacologically inactivated by an IL12 receptor subunit beta 2 masking domain. In vitro characterization demonstrates multiple matrix metalloproteases, as well as human primary tumors cultured as cell suspensions, can effectively activate XTX301. Intravenous administration of a mouse surrogate mXTX301 demonstrated significant tumor growth inhibition (TGI) in inflamed and non-inflamed mouse models without causing systemic toxicities. The superiority of mXTX301 in mediating TGI compared with non-activatable control molecules and the greater percentage of active mXTX301 in tumors versus other organs further confirms activation by the tumor microenvironment-associated proteases in vivo. Pharmacodynamic characterization shows tumor selective increases in inflammation and upregulation of immune-related genes involved in IFNγ cell signaling, antigen processing, presentation, and adaptive immune response. XTX301 was tolerated following four repeat doses up to 2.0 mg/kg in a nonhuman primate study; XTX301 exposures were substantially higher than those at the minimally efficacious dose in mice. Thus, XTX301 has the potential to achieve potent antitumor activity while widening the therapeutic index of IL12 treatment and is currently being evaluated in a phase I clinical trial.

Harnessing atomic force microscopy-based single-cell analysis to advance physical oncology

Single-cell analysis is an emerging and promising frontier in the field of life sciences, which is expected to facilitate the exploration of fundamental laws of physiological and pathological processes. Single-cell analysis allows experimental access to cell-to-cell heterogeneity to reveal the distinctive behaviors of individual cells, offering novel opportunities to dissect the complexity of severe human diseases such as cancers. Among the single-cell analysis tools, atomic force microscopy (AFM) is a powerful and versatile one which is able to nondestructively image the fine topographies and quantitatively measure multiple mechanical properties of single living cancer cells in their native states under aqueous conditions with unprecedented spatiotemporal resolution. Over the past few decades, AFM has been widely utilized to detect the structural and mechanical behaviors of individual cancer cells during the process of tumor formation, invasion, and metastasis, yielding numerous unique insights into tumor pathogenesis from the biomechanical perspective and contributing much to the field of cancer mechanobiology. Here, the achievements of AFM-based analysis of single cancer cells to advance physical oncology are comprehensively summarized, and challenges and future perspectives are also discussed. RESEARCH HIGHLIGHTS: Achievements of AFM in characterizing the structural and mechanical behaviors of single cancer cells are summarized, and future directions are discussed. AFM is not only capable of visualizing cellular fine structures, but can also measure multiple cellular mechanical properties as well as cell-generated mechanical forces. There is still plenty of room for harnessing AFM-based single-cell analysis to advance physical oncology.

Bimetallic nanoparticles as cascade sensitizing amplifiers for low-dose and robust cancer radio-immunotherapy

Radiotherapy (RT) is one of the most feasible and routinely used therapeutic modalities for treating malignant tumors. In particular, immune responses triggered by RT, known as radio-immunotherapy, can partially inhibit the growth of distantly spreading tumors and recurrent tumors. However, the safety and efficacy of radio-immunotherapy is impeded by the radio-resistance and poor immunogenicity of tumor. Herein, we report oxaliplatin (IV)-iron bimetallic nanoparticles (OXA/Fe NPs) as cascade sensitizing amplifiers for low-dose and robust radio-immunotherapy. The OXA/Fe NPs exhibit tumor-specific accumulation and activation of OXA (II) and Fe2+ in response to the reductive and acidic microenvironment within tumor cells. The cascade reactions of the released metallic drugs can sensitize RT by inducing DNA damage, increasing ROS and O2 levels, and amplifying the immunogenic cell death (ICD) effect after RT to facilitate potent immune activation. As a result, OXA/Fe NPs-based low-dose RT triggered a robust immune response and inhibited the distant and metastatic tumors effectively by a strong abscopal effect. Moreover, a long-term immunological memory effect to protect mice from tumor rechallenging is observed. Overall, the bimetallic NPs-based cascade sensitizing amplifier system offers an efficient radio-immunotherapy regimen that addresses the key challenges.

FAP is a prognostic marker, but not a viable therapeutic target for clinical translation in HNSCC

PURPOSE

PD-1 targeted immunotherapy has imparted a survival benefit to advanced head and neck squamous cell carcinoma (HNSCC), but less than 20% patients produce a durable response to this therapy. Here we aimed to investigate the potential biomarkers for predicting the clinical outcome and resistance to PD-1 targeted immunotherapy in HNSCC patients, and to examine the involvement of FAP+ cancer-associated fibroblasts (CAFs).

METHODS

Bioinformatics methods were applied to analyze multiple datasets and explore the role of PD-1 and FAP in HNSCC. Immunohistochemistry was used to detect the expression of FAP protein. Fap gene knockout mice (Fap-/-) and L929 cells with different levels of Fap overexpression (L929-Fap-Low/High) were established to demonstrate the role of FAP+ CAFs in tumor development and immune checkpoint blockade (ICB) resistance.

RESULTS

The expression level of PD-1 gene was positively correlated with better overall survival and therapeutic response to PD-1 blockade in HNSCC, but not all tumors with high expression of both PD-1 and PD-L1 were responsive. Moreover, FAP gene was overexpressed in pan-cancer tissues, and could serve as a prognostic biomarker for several cancers, including HNSCC. However, FAP protein was undetectable in mouse MTCQ1 tumors and barely expressed in human HNSCC tumors. Furthermore, FAP+ CAFs did not promote tumor growth or enhance the resistance to PD-1 inhibitor treatment.

CONCLUSION

Although FAP+ CAFs have attracted increasing attention for their role in cancer, the feasibility and efficacy of FAP-targeting therapies for HNSCC remain doubtful.

Regulation of immunomodulatory networks by Nrf2-activation in immune cells: Redox control and therapeutic potential in inflammatory diseases

Inflammatory diseases present a serious health challenge due to their widespread prevalence and the severe impact on patients' lives. In the quest to alleviate the burden of these diseases, nuclear factor erythroid 2-related factor 2 (Nrf2) has emerged as a pivotal player. As a transcription factor intimately involved in cellular defense against metabolic and oxidative stress, Nrf2's role in modulating the inflammatory responses of immune cells has garnered significant attention. Recent findings suggest that Nrf2's ability to alter the redox status of cells underlies its regulatory effects on immune responses. Our review delves into preclinical and clinical evidence that underscores the complex influence of Nrf2 activators on immune cell phenotypes, particularly in the inflammatory milieu. By offering a detailed analysis of Nrf2's role in different immune cell populations, we cast light on the potential of Nrf2 activators in shaping the immune response towards a more regulated state, mitigating the adverse effects of inflammation through modeling redox status of immune cells. Furthermore, we explore the innovative use of nanoencapsulation techniques that enhance the delivery and efficacy of Nrf2 activators, potentially advancing the treatment strategies for inflammatory ailments. We hope this review will stimulate the development and expansion of Nrf2-targeted treatments that could substantially improve outcomes for patients suffering from a broad range of inflammatory diseases.

Crosstalk Between NK Cell Receptors and Tumor Membrane Hsp70-Derived Peptide: A Combined Computational and Experimental Study

Natural killer (NK) cells are central components of the innate immunity system against cancers. Since tumor cells have evolved a series of mechanisms to escape from NK cells, developing methods for increasing the NK cell antitumor activity is of utmost importance. It is previously shown that an ex vivo stimulation of patient-derived NK cells with interleukin (IL)-2 and Hsp70-derived peptide TKD (TKDNNLLGRFELSG, aa450-461) results in a significant upregulation of activating receptors including CD94 and CD69 which triggers exhausted NK cells to target and kill malignant solid tumors expressing membrane Hsp70 (mHsp70). Considering that TKD binding to an activating receptor is the initial step in the cytolytic signaling cascade of NK cells, herein this interaction is studied by molecular docking and molecular dynamics simulation computational modeling. The in silico results showed a crucial role of the heterodimeric receptor CD94/NKG2A and CD94/NKG2C in the TKD interaction with NK cells. Antibody blocking and CRISPR/Cas9-mediated knockout studies verified the key function of CD94 in the TKD stimulation and activation of NK cells which is characterized by an increased cytotoxic capacity against mHsp70 positive tumor cells via enhanced production and release of lytic granules and pro-inflammatory cytokines.

Extracellular Matrix-Trapped Bioinspired Lipoprotein Prolongs Tumor Retention to Potentiate Antitumor Immunity

The immunomodulatory effects of many therapeutic agents are significantly challenged by their insufficient delivery efficiency and short retention time in tumors. Regarding the distinctively upregulated fibronectin (FN1) and tenascin C (TNC) in tumor stroma, herein a protease-activated FN1 and/or TNC binding peptide (FTF) is designed and an extracellular matrix (ECM)-trapped bioinspired lipoprotein (BL) (FTF-BL-CP) is proposed that can be preferentially captured by the TNC and/or FN1 for tumor retention, and then be responsively dissociated from the matrix to potentiate the antitumor immunity. The FTF-BL-CP treatment produces a 6.96-, 9.24-, 6.72-, 7.32-, and 6.73-fold increase of CD3+CD8+ T cells and their interferon-γ-, granzyme B-, perforin-, and Ki67-expressing subtypes versus the negative control, thereby profoundly eliciting the antitumor immunity. In orthotopic and lung metastatic breast cancer models, FTF-BL-CP produces notable therapeutic benefits of retarding tumor growth, extending survivals, and inhibiting lung metastasis. Therefore, this ECM-trapping strategy provides an encouraging possibility of prolonging tumor retention to potentiate the antitumor immunity for anticancer immunotherapy.

Recent advances in patient-derived tumor organoids for reconstructing TME of head and neck cancer

BACKGROUND

The differences between existing preclinical models and the tumor microenvironment in vivo are one of the significant challenges hindering cancer therapy development. Patient-derived tumor organoids (PDTO) can highly retain tumor heterogeneity. Thus, it provides a more reliable platform for research in tumor biology, new drug screening, and precision medicine.

METHODS

We conducted a systematic review to summarise the characteristics of the existing preclinical models, the advantages of patient-derived tumor organoids in reconstructing the tumor microenvironment, and the latest research progress. Moreover, this study deciphers organoid culture technology in the clinical precision treatment of head and neck cancer to achieve better transformation. Studies were identified through a comprehensive search of Ovid MEDLINE (Wolters Kluwer), PubMed (National Library of Medicine), web of Science (Thomson Reuters) and, Scopus (Elsevier) databases, without publication date or language restrictions.

RESULTS

In tumor development, the interaction between cellular and non-cellular components in the tumor microenvironment (TME) has a crucial role. Co-culture, Air-liquid interface culture, microfluidics, and decellularized matrix have depicted great potential in reconstructing the tumor microenvironment and simulating tumor genesis, development, and metastasis.

CONCLUSION

An accurate determination of stromal cells, immune cells, and extracellular matrix can be achieved by reconstructing the head and neck cancer tumor microenvironment using the PDTO model. Moreover, the interaction between head and neck cancer cells can also play an essential role in implementing the individualized precision treatment of head and neck cancer.

Using Drosophila to uncover the role of organismal physiology and the tumor microenvironment in cancer

Cancer metastasis causes over 90% of cancer patient fatalities. Poor prognosis is determined by tumor type, the tumor microenvironment (TME), organ-specific biology, and animal physiology. While model organisms do not fully mimic the complexity of humans, many processes can be studied efficiently owing to the ease of genetic, developmental, and cell biology studies. For decades, Drosophila has been instrumental in identifying basic mechanisms controlling tumor growth and metastasis. The ability to generate clonal populations of distinct genotypes in otherwise wild-type animals makes Drosophila a powerful system to study tumor-host interactions at the local and global scales. This review discusses advancements in tumor biology, highlighting the strength of Drosophila for modeling TMEs and systemic responses in driving tumor progression and metastasis.

The regulatory relationship between NAMPT and PD-L1 in cancer and identification of a dual-targeting inhibitor

Cancer is a heterogeneous disease. Although both tumor metabolism and tumor immune microenvironment are recognized as driving factors in tumorigenesis, the relationship between them is still not well-known, and potential combined targeting approaches remain to be identified. Here, we demonstrated a negative correlation between the expression of NAMPT, an NAD+ metabolism enzyme, and PD-L1 expression in various cancer cell lines. A clinical study showed that a NAMPTHigh PD-L1Low expression pattern predicts poor prognosis in patients with various cancers. In addition, pharmacological inhibition of NAMPT results in the transcription upregulation of PD-L1 by SIRT-mediated acetylation change of NF-κB p65, and blocking PD-L1 would induce NAMPT expression through a HIF-1-dependent glycolysis pathway. Based on these findings, we designed and synthesized a dual NAMPT/PD-L1 targeting compound, LZFPN-90, which inhibits cell growth in a NAMPT-dependent manner and blocks the cell cycle, subsequently inducing apoptosis. Under co-culture conditions, LZFPN-90 treatment contributes to the proliferation and activation of T cells and blocks the growth of cancer cells. Using mice bearing genetically manipulated tumors, we confirmed that LZFPN-90 exerted target-dependent antitumor activities, affecting metabolic processes and the immune system. In conclusion, our results demonstrate the relevance of NAD+-related metabolic processes in antitumor immunity and suggest that co-targeting NAD+ metabolism and PD-L1 represents a promising therapeutic approach.

GraphPath: a graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network

MOTIVATION

Studying the molecular heterogeneity of cancer is essential for achieving personalized therapy. At the same time, understanding the biological processes that drive cancer development can lead to the identification of valuable therapeutic targets. Therefore, achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels.

RESULTS

Here, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling. Experiment results show that our method outperforms P-NET and other baseline methods. Besides, two external cohorts are used to validate that the model can be generalized to unseen samples with adequate predictive performance. We reduce the dimensionality of latent pathway embeddings and visualize corresponding classes to further demonstrate the optimal performance of the model. Additionally, since GraphPath's predictions are interpretable, we identify target cancer-associated pathways that significantly contribute to the model's predictions. Such a robust and interpretable model has the potential to greatly enhance our understanding of cancer's biological mechanisms and accelerate the development of targeted therapies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/amazingma/GraphPath.

The two sides of chromosomal instability: drivers and brakes in cancer

Chromosomal instability (CIN) is a hallmark of cancer and is associated with tumor cell malignancy. CIN triggers a chain reaction in cells leading to chromosomal abnormalities, including deviations from the normal chromosome number or structural changes in chromosomes. CIN arises from errors in DNA replication and chromosome segregation during cell division, leading to the formation of cells with abnormal number and/or structure of chromosomes. Errors in DNA replication result from abnormal replication licensing as well as replication stress, such as double-strand breaks and stalled replication forks; meanwhile, errors in chromosome segregation stem from defects in chromosome segregation machinery, including centrosome amplification, erroneous microtubule-kinetochore attachments, spindle assembly checkpoint, or defective sister chromatids cohesion. In normal cells, CIN is deleterious and is associated with DNA damage, proteotoxic stress, metabolic alteration, cell cycle arrest, and senescence. Paradoxically, despite these negative consequences, CIN is one of the hallmarks of cancer found in over 90% of solid tumors and in blood cancers. Furthermore, CIN could endow tumors with enhanced adaptation capabilities due to increased intratumor heterogeneity, thereby facilitating adaptive resistance to therapies; however, excessive CIN could induce tumor cells death, leading to the "just-right" model for CIN in tumors. Elucidating the complex nature of CIN is crucial for understanding the dynamics of tumorigenesis and for developing effective anti-tumor treatments. This review provides an overview of causes and consequences of CIN, as well as the paradox of CIN, a phenomenon that continues to perplex researchers. Finally, this review explores the potential of CIN-based anti-tumor therapy.

Starfysh integrates spatial transcriptomic and histologic data to reveal heterogeneous tumor-immune hubs

Spatially resolved gene expression profiling provides insight into tissue organization and cell-cell crosstalk; however, sequencing-based spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for rigorous interpretation of cell states, mostly do not use associated histology images and are not capable of inferring shared neighborhoods across multiple tissues. Here we present Starfysh, a computational toolbox using a deep generative model that incorporates archetypal analysis and any known cell type markers to characterize known or new tissue-specific cell states without a single-cell reference. Starfysh improves the characterization of spatial dynamics in complex tissues using histology images and enables the comparison of niches as spatial hubs across tissues. Integrative analysis of primary estrogen receptor (ER)-positive breast cancer, triple-negative breast cancer (TNBC) and metaplastic breast cancer (MBC) tissues led to the identification of spatial hubs with patient- and disease-specific cell type compositions and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC.