Influence of tumour micro-environment heterogeneity on therapeutic response

Marine-Derived Leads as Anticancer Candidates by Disrupting Hypoxic Signaling through Hypoxia-Inducible Factors Inhibition

The inadequate vascularization seen in fast-growing solid tumors gives rise to hypoxic areas, fostering specific changes in gene expression that bolster tumor cell survival and metastasis, ultimately leading to unfavorable clinical prognoses across different cancer types. Hypoxia-inducible factors (HIF-1 and HIF-2) emerge as druggable pivotal players orchestrating tumor metastasis and angiogenesis, thus positioning them as prime targets for cancer treatment. A range of HIF inhibitors, notably natural compounds originating from marine organisms, exhibit encouraging anticancer properties, underscoring their significance as promising therapeutic options. Bioprospection of the marine environment is now a well-settled approach to the discovery and development of anticancer agents that might have their medicinal chemistry developed into clinical candidates. However, despite the massive increase in the number of marine natural products classified as 'anticancer leads,' most of which correspond to general cytotoxic agents, and only a few have been characterized regarding their molecular targets and mechanisms of action. The current review presents a critical analysis of inhibitors of HIF-1 and HIF-2 and hypoxia-selective compounds that have been sourced from marine organisms and that might act as new chemotherapeutic candidates or serve as templates for the development of structurally similar derivatives with improved anticancer efficacy.

Iterative nanoparticle bioengineering enabled by x-ray fluorescence imaging

Nanoparticles (NPs) are currently developed for drug delivery and molecular imaging. However, they often get intercepted before reaching their target, leading to low targeting efficacy and signal-to-noise ratio. They tend to accumulate in organs like lungs, liver, kidneys, and spleen. The remedy is to iteratively engineer NP surface properties and administration strategies, presently a time-consuming process that includes organ dissection at different time points. To improve this, we propose a rapid iterative approach using whole-animal x-ray fluorescence (XRF) imaging to systematically evaluate NP distribution in vivo. We applied this method to molybdenum-based NPs and clodronate liposomes for tumor targeting with transient macrophage depletion, leading to reduced accumulations in lungs and liver and eventual tumor detection. XRF computed tomography (XFCT) provided 3D insight into NP distribution within the tumor. We validated the results using a multiscale imaging approach with dye-doped NPs and gene expression analysis for nanotoxicological profiling. XRF imaging holds potential for advancing therapeutics and diagnostics in preclinical pharmacokinetic studies.

Engineering a Dual-Receptor Targeted Multivalent Probe for Enhanced Magnetic Resonance Imaging of Metastatic Cancer

Noninvasive monitoring of cancer metastasis is essential to improving clinical outcomes. Molecular MRI (mMRI) is a special implementation of noninvasive molecular imaging that promises to offer a powerful means for early detection and analysis of pathological states of cancer by tracking molecular markers. However, this is often hindered by the challenging issue of obtaining transformable mMRI contrast agents with high sensitivity, specificity, and broad applicability, given the high tumor heterogeneity and complex metastatic features. Herein, we present a dual-receptor targeted, multivalent recognition strategy and report a new class of mMRI probes for enhanced imaging of metastatic cancer. This probe is designed by covalently conjugating Gd-chelate with phenylboronic acid and an aptamer via an affordable polymerization chemistry to concurrently target two different cell-membrane receptors that are commonly overexpressed and highly implicated in both tumorigenesis and metastasis. Moreover, the polymerization chemistry allows the probe to contain a bunch of targeting ligands and signal reporters in a single chain, which not only leads to more than 2-fold enhancement in T1 relaxivity at 1.5 T compared to the commercial contrast agent but also enables it to actively target tumor cells in a multivalent recognition manner, contributing to a much higher imaging contrast than single-receptor targeted probes and the commercial agent in mouse models with lung metastases, yet without inducing systemic side effects. We expect this study to offer a useful molecular tool to promote transformable applications of mMRI and a better understanding of molecular mechanisms involved in cancer development.

Host-functionalization of macrin nanoparticles to enable drug loading and control tumor-associated macrophage phenotype

Macrophages are critical regulators of the tumor microenvironment and often present an immuno-suppressive phenotype, supporting tumor growth and immune evasion. Promoting a robust pro-inflammatory macrophage phenotype has emerged as a therapeutic modality that supports tumor clearance, including through synergy with immune checkpoint therapies. Polyglucose nanoparticles (macrins), which possess high macrophage affinity, are useful vehicles for delivering drugs to macrophages, potentially altering their phenotype. Here, we examine the potential of functionalized macrins, synthesized by crosslinking carboxymethyl dextran with L-lysine, as effective carriers of immuno-stimulatory drugs to tumor-associated macrophages (TAMs). Azide groups incorporated during particle synthesis provided a handle for click-coupling of propargyl-modified β-cyclodextrin to macrins under mild conditions. Fluorescence-based competitive binding assays revealed the ability of β-cyclodextrin to non-covalently bind to hydrophobic immuno-stimulatory drug candidates (Keq ~ 103 M-1), enabling drug loading within nanoparticles. Furthermore, transcriptional profiles of macrophages indicated robust pro-inflammatory reprogramming (elevated Nos2 and Il12; suppressed Arg1 and Mrc1 expression levels) for a subset of these immuno-stimulatory agents (UNC2025 and R848). Loading of R848 into the modified macrins improved the drug's effect on primary murine macrophages by three-fold in vitro. Intravital microscopy in IL-12-eYFP reporter mice (24 h post-injection) revealed a two-fold enhancement in mean YFP fluorescence intensity in macrophages targeted with R848-loaded macrins, relative to vehicle controls, validating the desired pro-inflammatory reprogramming of TAMs in vivo by cell-targeted drug delivery. Finally, in an intradermal MC38 tumor model, cyclodextrin-modified macrin NPs loaded with immunostimulatory drugs significantly reduced tumor growth. Therefore, efficient and effective repolarization of tumor-associated macrophages to an M1-like phenotype-via drug-loaded macrins-inhibits tumor growth and may be useful as an adjuvant to existing immune checkpoint therapies.

Diversity of Intercellular Communication Modes: A Cancer Biology Perspective

From the moment a cell is on the path to malignant transformation, its interaction with other cells from the microenvironment becomes altered. The flow of molecular information is at the heart of the cellular and systemic fate in tumors, and various processes participate in conveying key molecular information from or to certain cancer cells. For instance, the loss of tight junction molecules is part of the signal sent to cancer cells so that they are no longer bound to the primary tumors and are thus free to travel and metastasize. Upon the targeting of a single cell by a therapeutic drug, gap junctions are able to communicate death information to by-standing cells. The discovery of the importance of novel modes of cell-cell communication such as different types of extracellular vesicles or tunneling nanotubes is changing the way scientists look at these processes. However, are they all actively involved in different contexts at the same time or are they recruited to fulfill specific tasks? What does the multiplicity of modes mean for the overall progression of the disease? Here, we extend an open invitation to think about the overall significance of these questions, rather than engage in an elusive attempt at a systematic repertory of the mechanisms at play.

Collagen modifications predictive of lymph node metastasis in dogs with carcinoma in mixed tumours

Introduction

Mixed tumours in the canine mammary gland are the most common histological type in routine diagnosis. In general, these neoplasms have a favourable prognosis that does not evolve into metastatic disease. However, some cases develop into lymph node metastases and are associated with worse patient survival rates.

Methods

Here is a retrospective study of 46 samples of primary mixed tumours of the canine mammary gland: 15 cases of benign mixed tumours (BMT), 16 cases of carcinoma in mixed tumours without lymph node metastasis (CMT), and 15 cases of carcinomas in mixed tumours with lymph node metastasis (CMTM). In addition, we selected 23 cases of normal mammary glands (NMT) for comparison. The samples were collected from biopsies performed during nodulectomy, simple mastectomy, regional mastectomy, or unilateral/bilateral radical mastectomy. We used multiphoton microscopy, second harmonic generation, and two-photon excited fluorescence, to evaluate the characteristics of collagen fibres and cellular components in biopsies stained with haematoxylin and eosin. We performed Ki67, ER, PR, and HER-2 immunostaining to define the immunophenotype and COX-2. We showed that carcinomas that evolved into metastatic disease (CMTM) present shorter and wavier collagen fibres as compared to CMT.

Results and discussion

When compared to NMT and BMT the carcinomas present a smaller area of fibre coverage, a larger area of cellular coverage, and a larger number of individual fibres. Furthermore, we observed a correlation between the strong expression of COX-2 and a high rate of cell proliferation in carcinomas with a smaller area covered by cell fibres and a larger number of individual fibres. These findings highlight the fundamental role of collagen during tumour progression, especially in invasion and metastatic dissemination.

RSK4 promotes the macrophage recruitment and M2 polarization in esophageal squamous cell carcinoma

High infiltration of tumor-associated macrophages (TAMs) participates in host immunity and tumor progression in patients with esophageal squamous cell carcinoma (ESCC). Ribosomal s6 kinase 4 (RSK4) has been shown to be aberrantly overexpressed in ESCC. The role of RSK4 in cytokine secretion and its impact on macrophage recruitment and M2 polarization remains unclear. Therefore, a thorough understanding of RSK4 is needed to expand our knowledge of its therapeutic potential. Herein, RSK4 expression in human ESCC tissues and a xenograft mouse model was positively correlated with high infiltration of M0 and M2 macrophages which is positively associated with unfavorable overall survival outcomes and treatment resistance in patients with ESCC. In vitro experiments revealed that RSK4 derived from ESCC cells promoted macrophage recruitment and M2 polarization by enhancingsoluble intercellular adhesion molecule-1 (sICAM-1) secretion via direct and indirect STAT3 phosphorylation. Furthermore, RSK4-induced macrophages enhanced tumor proliferation, migration, and invasion by secreting C-C motif chemokine ligand 22 (CCL22). We further showed that patients with elevated CD68 and CD206 expression had unfavorable overall survival. Collectively, these results demonstrate that RSK4 promotes the macrophage recruitment and M2 polarization by regulating the STAT3/ICAM-1 axis in ESCC, influencing tumor progression primarily in a CCL22-dependent manner. These data also offer valuable insights for developing novel agents for the treatment of ESCC.

Metabolic challengers selecting tumor-persistent cells

Resistance to anticancer therapy still represents one of the main obstacles to cancer treatment. Numerous components of the tumor microenvironment (TME) contribute significantly to the acquisition of drug resistance. Microenvironmental pressures arising during cancer evolution foster tumor heterogeneity (TH) and facilitate the emergence of drug-resistant clones. In particular, metabolic pressures arising in the TME may favor epigenetic adaptations supporting the acquisition of persistence features in tumor cells. Tumor-persistent cells (TPCs) are characterized by high phenotypic and metabolic plasticity, representing a noticeable advantage in chemo- and radio-resistance. Understanding the crosslink between the evolution of metabolic pressures in the TME, epigenetics, and TPC evolution is significant for developing novel therapeutic strategies specifically targeting TPC vulnerabilities to overcome drug resistance.

Tumor Microenvironment Modulating CaCO3 -Based Colloidosomal Microreactors Can Generally Reinforce Cancer Immunotherapy

Tumor hypoxia and acidity, two general features of solid tumors, are known to have negative effect on cancer immunotherapy by directly causing dysfunction of effector immune cells and promoting suppressive immune cells inside tumors. Herein, a multifunctional colloidosomal microreactor is constructed by encapsulating catalase within calcium carbonate (CaCO3 ) nanoparticle-assembled colloidosomes (abbreviated as CaP CSs) via the classic double emulsion method. The yielded CCaP CSs exhibit well-retained proton-scavenging and hydrogen peroxide decomposition performances and can thus neutralize tumor acidity, attenuate tumor hypoxia, and suppress lactate production upon intratumoral administration. Consequently, CCaP CSs treatment can activate potent antitumor immunity and thus significantly enhance the therapeutic potency of coloaded anti-programmed death-1 (anti-PD-1) antibodies in both murine subcutaneous CT26 and orthotopic 4T1 tumor xenografts. In addition, such CCaP CSs treatment also markedly reinforces the therapeutic potency of epidermal growth factor receptor expressing chimeric antigen receptor T (EGFR-CAR-T) cells toward a human triple-negative breast cancer xenograft by promoting their tumor infiltration and effector cytokine secretion. Therefore, this study highlights that chemical modulation of tumor acidity and hypoxia can collectively reverse tumor immunosuppression and thus significantly potentiate both immune checkpoint blockade and CAR-T cell immunotherapies toward solid tumors.

Adjuvant Novel Nanocarrier-Based Targeted Therapy for Lung Cancer

Lung cancer has the lowest survival rate due to its late-stage diagnosis, poor prognosis, and intra-tumoral heterogeneity. These factors decrease the effectiveness of treatment. They release chemokines and cytokines from the tumor microenvironment (TME). To improve the effectiveness of treatment, researchers emphasize personalized adjuvant therapies along with conventional ones. Targeted chemotherapeutic drug delivery systems and specific pathway-blocking agents using nanocarriers are a few of them. This study explored the nanocarrier roles and strategies to improve the treatment profile's effectiveness by striving for TME. A biofunctionalized nanocarrier stimulates biosystem interaction, cellular uptake, immune system escape, and vascular changes for penetration into the TME. Inorganic metal compounds scavenge reactive oxygen species (ROS) through their photothermal effect. Stroma, hypoxia, pH, and immunity-modulating agents conjugated or modified nanocarriers co-administered with pathway-blocking or condition-modulating agents can regulate extracellular matrix (ECM), Cancer-associated fibroblasts (CAF),Tyro3, Axl, and Mertk receptors (TAM) regulation, regulatory T-cell (Treg) inhibition, and myeloid-derived suppressor cells (MDSC) inhibition. Again, biomimetic conjugation or the surface modification of nanocarriers using ligands can enhance active targeting efficacy by bypassing the TME. A carrier system with biofunctionalized inorganic metal compounds and organic compound complex-loaded drugs is convenient for NSCLC-targeted therapy.

In vivo C6 glioma models: an update and a guide toward a more effective preclinical evaluation of potential anti-glioblastoma drugs

Glioblastoma multiform (GBM) is the most common primary brain tumor with a poor prognosis and few therapeutic choices. In vivo, tumor models are useful for enhancing knowledge of underlying GBM pathology and developing more effective therapies/agents at the preclinical level, as they recapitulate human brain tumors. The C6 glioma cell line has been one of the most widely used cell lines in neuro-oncology research as they produce tumors that share the most similarities with human GBM regarding genetic, invasion, and expansion profiles and characteristics. This review provides an overview of the distinctive features and the different animal models produced by the C6 cell line. We also highlight specific applications of various C6 in vivo models according to the purpose of the study and offer some technical notes for more convenient/repeatable modeling. This work also includes novel findings discovered in our laboratory, which would further enhance the feasibility of the model in preclinical GBM investigations.

Disulfidptosis characterizes the tumor microenvironment and predicts immunotherapy sensitivity and prognosis in bladder cancer

BACKGROUND

Bladder cancer (BLCA) is prone to metastasis and has poor prognosis with unsatisfactory treatment responsiveness. Disulfidptosis is a recently discovered, novel mode of cell death that is closely associated with human cancers. However, a comprehensive analysis of the relationship between disulfidptosis and BLCA is lacking. Therefore, this study aimed to explore the potential effect of disulfidptosis on BLCA and identify a biomarker for evaluating the prognosis and immunotherapy of patients with BLCA.

MATERIAL AND METHODS

We acquired BLCA RNA sequencing data from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) cohort (containing 19 normal samples and 409 tumor samples) and the GES39281 cohort (containing 94 tumor samples) which were used for external validation of the signature. Initially, we performed unsupervised consensus clustering to explore disulfidptosis-related subgroups. We then conducted functional enrichment analysis on these subgroups to gain insights into their biological significance and evaluate their immunotherapy response and chemotherapy sensitivity. Next, we conducted Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression to construct a prognostic signature in the TCGA training set for prognosis-related differentially expressed genes (DEGs) in the disulfidptosis-related subgroups. Subsequently, we used a receiver operating characteristic (ROC) curve and independent prognostic analysis to validate the predictive performance of the signature in the TCGA testing and the GES39281 cohorts. Finally, we explored the therapeutic value of this signature in patients with BLCA, in terms of immunotherapy and chemotherapy.

RESULT

In this study, we obtained two subgroups: DRG-high (238 samples) and DRG-low (160 samples). The DRG-high group exhibited a poor survival rate compared to the DRG-low group and had a significant association with tumor grade, stage, and metastasis. Additionally, several pathways related to cancer and the immune system were enriched in the high-DRG group. Moreover, the DRG-high group exhibited higher expression of PD1 and CTLA4 and had a better response to immunotherapy in patients with both PD1 and CTLA4 positivity. Conversely, the DRG-high group was more sensitive to common chemotherapeutic agents. A prognostic signature was created, consisting of COL5A1, DIRAS3, NKG7, and POLR3G and validated as having a robust predictive capability. Patients in the low-risk-score group had more immune cells associated with tumor suppression and better immunotherapy outcomes.

CONCLUSION

This study contributes to our understanding of the characteristics of disulfidptosis-related subgroups in BLCA. Disulfidptosis-related signatures can be used to assess the prognosis and immunotherapy of patients with BLCA.

The progressive trend of modeling and drug screening systems of breast cancer bone metastasis

Bone metastasis is considered as a considerable challenge for breast cancer patients. Various in vitro and in vivo models have been developed to examine this occurrence. In vitro models are employed to simulate the intricate tumor microenvironment, investigate the interplay between cells and their adjacent microenvironment, and evaluate the effectiveness of therapeutic interventions for tumors. The endeavor to replicate the latency period of bone metastasis in animal models has presented a challenge, primarily due to the necessity of primary tumor removal and the presence of multiple potential metastatic sites.The utilization of novel bone metastasis models, including three-dimensional (3D) models, has been proposed as a promising approach to overcome the constraints associated with conventional 2D and animal models. However, existing 3D models are limited by various factors, such as irregular cellular proliferation, autofluorescence, and changes in genetic and epigenetic expression. The imperative for the advancement of future applications of 3D models lies in their standardization and automation. The utilization of artificial intelligence exhibits the capability to predict cellular behavior through the examination of substrate materials' chemical composition, geometry, and mechanical performance. The implementation of these algorithms possesses the capability to predict the progression and proliferation of cancer. This paper reviewed the mechanisms of bone metastasis following primary breast cancer. Current models of breast cancer bone metastasis, along with their challenges, as well as the future perspectives of using these models for translational drug development, were discussed.

The 'Other' subfamily of HECT E3 ubiquitin ligases evaluate the tumour immune microenvironment and prognosis in patients with hepatocellular carcinoma

Primary liver cancer is the sixth most common cancer and the third leading cause of cancer-related death worldwide. The role of the 'Other' subfamily of HECT E3 ligases (E3s) in hepatocellular carcinoma (HCC) remains unknown. The expression of the 'Other' HECT E3s was performed using The Cancer Genome Atlas (TCGA) data, and the authors found that the 'Other' HECT E3s were differentially expressed in HCC. Prognostic values were assessed using the Kaplan-Meier method and indicated that the high expressions of HECTD2, HECTD3, and HACE1 were associated with a worse clinical prognosis of HCC patients. The expression of HECTD2 was significantly correlated with the infiltration of CD4+ T cells and neutrophils. The levels of HECTD3 and HACE1 were notably related to the dendritic cells and memory B cells infiltrated in HCC. In addition, the three previously mentioned genes have shown to be associated with immune checkpoint genes, such as FOXP3, CCR8, STAT5B, TGFB1 and TIM-3. Moreover, HECTD2 could promote the proliferative activity, cell migration and invasive ability of HCC cells. Collectively, the authors' study demonstrated that HECTD2 was a novel immune-related prognostic biomarker for HCC, providing new insight into the treatment and prognosis of HCC.

A comprehensive review of 3D cancer models for drug screening and translational research

The 3D cancer models fill the discovery gap of 2D cancer models and play an important role in cancer research. In addition to cancer cells, a range of other factors include the stroma, density and composition of extracellular matrix, cancer-associated immune cells (e.g., cancer-associated fibroblasts cancer cell-stroma interactions and subsequent interactions, and a number of other factors (e.g., tumor vasculature and tumor-like microenvironment in vivo) has been widely ignored in the 2D concept of culture. Despite this knowledge, the continued use of monolayer cell culture methods has led to the failure of a series of clinical trials. This review discusses the immense importance of tumor microenvironment (TME) recapitulation in cancer research, prioritizing the individual roles of TME elements in cancer histopathology. The TME provided by the 3D model fulfills the requirements of in vivo spatiotemporal arrangement, components, and is helpful in analyzing various different aspects of drug sensitivity in preclinical and clinical trials, some of which are discussed here. Furthermore, it discusses models for the co-assembly of different TME elements in vitro and focuses on their synergistic function and responsiveness as tumors. Furthermore, this review broadly describes of a handful of recently developed 3D models whose main focus is limited to drug development and their screening and/or the impact of this approach in preclinical and translational research.

Tumor heterogeneity: how could we use it to achieve better clinical outcomes?

Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.

Tumor microenvironment and CAR-T cell immunotherapy in B-cell lymphoma

Chimeric receptor antigen T cell (CAR-T cell) therapy has demonstrated effectiveness and therapeutic potential in the immunotherapy of hematological malignancies, representing a promising breakthrough in cancer treatment. Despite the efficacy of CAR-T cell therapy in B-cell lymphoma, response variability, resistance, and side effects remain persistent challenges. The tumor microenvironment (TME) plays an intricate role in CAR-T cell therapy of B-cell lymphoma. The TME is a complex and dynamic environment that includes various cell types, cytokines, and extracellular matrix components, all of which can influence CAR-T cell function and behavior. This review discusses the design principles of CAR-T cells, TME in B-cell lymphoma, and the mechanisms by which TME influences CAR-T cell function. We discuss emerging strategies aimed at modulating the TME, targeting immunosuppressive cells, overcoming inhibitory signaling, and improving CAR-T cell infiltration and persistence. Therefore, these processes enhance the efficacy of CAR-T cell therapy and improve patient outcomes in B-cell lymphoma. Further research will be needed to investigate the molecular and cellular events that occur post-infusion, including changes in TME composition, immune cell interactions, cytokine signaling, and potential resistance mechanisms. Understanding these processes will contribute to the development of more effective CAR-T cell therapies and strategies to mitigate treatment-related toxicities.

Identification and characterization of CLEC11A and its derived immune signature in gastric cancer

Introduction

C-type lectin domain family 11 member A (CLEC11A) was characterized as a growth factor that mainly regulates hematopoietic function and differentiation of bone cells. However, the involvement of CLEC11A in gastric cancer (GC) is not well understood.

Methods

Transcriptomic data and clinical information pertaining to GC were obtained and analyzed from publicly available databases. The relationships between CLEC11A and prognoses, genetic alterations, tumor microenvironment (TME), and therapeutic responses in GC patients were analyzed by bioinformatics methods. A CLEC11A-derived immune signature was developed and validated, and its mutational landscapes, immunological characteristics as well as drug sensitivities were explored. A nomogram was established by combining CLEC11A-derived immune signature and clinical factors. The expression and carcinogenic effects of CLEC11A in GC were verified by qRT-PCR, cell migration, invasion, cell cycle analysis, and in vivo model analysis. Myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), M2 macrophages, and T cells in tumor samples extracted from mice were analyzed utilizing flow cytometry analysis.

Results

CLEC11A was over-expressed in GC, and the elevated CLEC11A expression indicated an unfavorable prognosis in GC patients. CLEC11A was involved in genomic alterations and associated with the TME in GC. Moreover, elevated CLEC11A was found to reduce the benefit of immunotherapy according to immunophenoscore (IPS) and the tumor immune dysfunction, exclusion (TIDE). After validation, the CLEC11A-derived immune signature demonstrated a consistent ability to predict the survival outcomes in GC patients. A nomogram that quantifies survival probability was constructed to improve the accuracy of prognosis prediction in GC patients. Using shRNA to suppress the expression of CLEC11A led to significant inhibitions of cell cycle progression, migration, and invasion, as well as a marked reduction of in vivo tumor growth. Moreover, the flow cytometry assay showed that the knock-down of CLEC11A increased the infiltration of cytotoxic CD8+ T cells and helper CD4+ T into tumors while decreasing the percentage of M2 macrophages, MDSCs, and Tregs.

Conclusion

Collectively, our findings revealed that CLEC11A could be a prognostic and immunological biomarker in GC, and CLEC11A-derived immune signature might serve as a new option for clinicians to predict outcomes and formulate personalized treatment plans for GC patients.

Multiplex miRNA reporting platform for real-time profiling of living cells

Accurately characterizing cell types within complex cell structures provides invaluable information for comprehending the cellular status during biological processes. In this study, we have developed an miRNA-switch cocktail platform capable of reporting and tracking the activities of multiple miRNAs (microRNAs) at the single-cell level, while minimizing disruption to the cell culture. Drawing on the principles of traditional miRNA-sensing mRNA switches, our platform incorporates subcellular tags and employs intelligent engineering to segment three subcellular regions using two fluorescent proteins. These designs enable the quantification of multiple miRNAs within the same cell. Through our experiments, we have demonstrated the platform's ability to track marker miRNA levels during cell differentiation and provide spatial information of heterogeneity on outlier cells exhibiting extreme miRNA levels. Importantly, this platform offers real-time and in situ miRNA reporting, allowing for multidimensional evaluation of cell profile and paving the way for a comprehensive understanding of cellular events during biological processes.

Protein cargo in extracellular vesicles as the key mediator in the progression of cancer

Exosomes are small vesicles of endosomal origin that are released by almost all cell types, even those that are pathologically altered. Exosomes widely participate in cell-to-cell communication via transferring cargo, including nucleic acids, proteins, and other metabolites, into recipient cells. Tumour-derived exosomes (TDEs) participate in many important molecular pathways and affect various hallmarks of cancer, including fibroblasts activation, modification of the tumour microenvironment (TME), modulation of immune responses, angiogenesis promotion, setting the pre-metastatic niche, enhancing metastatic potential, and affecting therapy sensitivity and resistance. The unique exosome biogenesis, composition, nontoxicity, and ability to target specific tumour cells bring up their use as promising drug carriers and cancer biomarkers. In this review, we focus on the role of exosomes, with an emphasis on their protein cargo, in the key mechanisms promoting cancer progression. We also briefly summarise the mechanism of exosome biogenesis, its structure, protein composition, and potential as a signalling hub in both normal and pathological conditions. Video Abstract.

Deep Learning Image Recognition-Assisted Atomic Force Microscopy for Single-Cell Efficient Mechanics in Co-culture Environments

Atomic force microscopy (AFM)-based force spectroscopy assay has become an important method for characterizing the mechanical properties of single living cells under aqueous conditions, but a disadvantage is its reliance on manual operation and experience as well as the resulting low throughput. Particularly, providing a capacity to accurately identify the type of the cell grown in co-culture environments without the need of fluorescent labeling will further facilitate the applications of AFM in life sciences. Here, we present a study of deep learning image recognition-assisted AFM, which not only enables fluorescence-independent recognition of the identity of single co-cultured cells but also allows efficient downstream AFM force measurements of the identified cells. With the use of the deep learning-based image recognition model, the viability and type of individual cells grown in co-culture environments were identified directly from the optical bright-field images, which were confirmed by the following cell growth and fluorescent labeling results. Based on the image recognition results, the positional relationship between the AFM probe and the targeted cell was automatically determined, allowing the precise movement of the AFM probe to the target cell to perform force measurements. The experimental results show that the presented method was applicable not only to the conventional (microsphere-modified) AFM probe used in AFM indentation assay for measuring the Young's modulus of single co-cultured cells but also to the single-cell probe used in AFM-based single-cell force spectroscopy (SCFS) assay for measuring the adhesion forces of single co-cultured cells. The study illustrates deep learning imaging recognition-assisted AFM as a promising approach for label-free and high-throughput detection of single-cell mechanics under co-culture conditions, which will facilitate unraveling the mechanical cues involved in cell-cell interactions in their native states at the single-cell level and will benefit the field of mechanobiology.

Destabilizing the genome as a therapeutic strategy to enhance response to immune checkpoint blockade: a systematic review of clinical trials evidence from solid and hematological tumors

Background: Genomic instability is increased alterations in the genome during cell division and is common among most cancer cells. Genome instability enhances the risk of initial carcinogenic transformation, generating new clones of tumor cells, and increases tumor heterogeneity. Although genome instability contributes to malignancy, it is also an "Achilles' heel" that constitutes a therapeutically-exploitable weakness-when sufficiently advanced, it can intrinsically reduce tumor cell survival by creating DNA damage and mutation events that overwhelm the capacity of cancer cells to repair those lesions. Furthermore, it can contribute to extrinsic survival-reducing events by generating mutations that encode new immunogenic antigens capable of being recognized by the immune system, particularly when anti-tumor immunity is boosted by immunotherapy drugs. Here, we describe how genome-destabilization can induce immune activation in cancer patients and systematically review the induction of genome instability exploited clinically, in combination with immune checkpoint blockade. Methods: We performed a systematic review of clinical trials that exploited the combination approach to successfully treat cancers patients. We systematically searched PubMed, Cochrane Central Register of Controlled Trials, Clinicaltrials.gov, and publication from the reference list of related articles. The most relevant inclusion criteria were peer-reviewed clinical trials published in English. Results: We identified 1,490 studies, among those 164 were clinical trials. A total of 37 clinical trials satisfied the inclusion criteria and were included in the study. The main outcome measurements were overall survival and progression-free survival. The majority of the clinical trials (30 out of 37) showed a significant improvement in patient outcome. Conclusion: The majority of the included clinical trials reported the efficacy of the concept of targeting DNA repair pathway, in combination with immune checkpoint inhibitors, to create a "ring of synergy" to treat cancer with rational combinations.

The importance of cancer-associated fibroblasts in targeted therapies and drug resistance in breast cancer

Cancer-associated fibroblasts (CAFs) play a substantial role in the tumor microenvironment, exhibiting a strong association with the advancement of various types of cancer, including breast, pancreatic, and prostate cancer. CAFs represent the most abundant mesenchymal cell population in breast cancer. Through diverse mechanisms, including the release of cytokines and exosomes, CAFs contribute to the progression of breast cancer by influencing tumor energy metabolism, promoting angiogenesis, impairing immune cell function, and remodeling the extracellular matrix. Moreover, CAFs considerably impact the response to treatment in breast cancer. Consequently, the development of interventions targeting CAFs has emerged as a promising therapeutic approach in the management of breast cancer. This article provides an analysis of the role of CAFs in breast cancer, specifically in relation to diagnosis, treatment, drug resistance, and prognosis. The paper succinctly outlines the diverse mechanisms through which CAFs contribute to the malignant behavior of breast cancer cells, including proliferation, invasion, metastasis, and drug resistance. Furthermore, the article emphasizes the potential of CAFs as valuable tools for early diagnosis, targeted therapy, treatment resistance, and prognosis assessment in breast cancer, thereby offering novel approaches for targeted therapy and overcoming treatment resistance in this disease.

Ultrasound-activated prodrug-loaded liposome for efficient cancer targeting therapy without chemotherapy-induced side effects

BACKGROUND

Off-targeted distribution of chemotherapeutic drugs causes severe side effects, further leading to poor prognosis and patient compliance. Ligand/receptor-mediated targeted drug delivery can improve drug accumulation in the tumor but it always attenuated by protein corona barriers.

RESULTS

To address these problems, a radically different strategy is proposed that can leave the off-targeted drugs inactive but activate the tumor-distributed drugs for cancer-targeting therapy in a tumor microenvironment-independent manner. The feasibility and effectiveness of this strategy is demonstrated by developing an ultrasound (US)-activated prodrug-loaded liposome (CPBSN38L) comprising the sonosensitizer chlorin e6 (Ce6)-modified lipids and the prodrug of pinacol boronic ester-conjugated SN38 (PBSN38). Once CPBSN38L is accumulated in the tumor and internalized into the cancer cells, under US irradiation, the sonosensitizer Ce6 rapidly induces extensive production of intracellular reactive oxygen species (ROS), thereby initiating a cascade amplified ROS-responsive activation of PBSN38 to release the active SN38 for inducing cell apoptosis. If some of the injected CPBSN38L is distributed into normal tissues, the inactive PBSN38 exerts no pharmacological activity on normal cells. CPBSN38L exhibited strong anticancer activity in multiple murine tumor models of colon adenocarcinoma and hepatocellular carcinoma with no chemotherapy-induced side effects, compared with the standard first-line anticancer drugs irinotecan and topotecan.

CONCLUSIONS

This study established a side-effect-evitable, universal, and feasible strategy for cancer-targeting therapy.

A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images1

BACKGROUND

By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse PET and PET/CT images, is commonly used to evaluate lesions.

OBJECTIVE

This study aims to build an image processing technique with the purpose of automatically detecting and isolating lesions in PET/CT images, as well as measuring and assessing the SUVmed.

METHODS

The pictures are separated into their respective lesions using mathematical morphology and the crescent region, which are both part of the image processing method. In this research, a total of 18 different pictures of lesions were evaluated.

RESULTS

The findings of the study reveal that the threshold is satisfied by both the SUVmax and the SUVmed for most of the lesion types. However, in six instances, the SUVmax and SUVmed values are found to be in different courts.

CONCLUSION

The new information revealed by this study needs to be further investigated to determine if it has any practical value in diagnosing and monitoring lesions. However, results of this study suggest that SUVmed should receive more attention in the evaluation of lesions in PET and CT images.

Drug target therapy and emerging clinical relevance of exosomes in meningeal tumors

Meningioma is the most common central nervous system (CNS) tumor. In recent decades, several efforts have been made to eradicate this disease. Surgery and radiotherapy remain the standard treatment options for these tumors. Drug therapy comes to play its role when both surgery and radiotherapy fail to treat the tumor. This mostly happens when the tumors are close to vital brain structures and are nonbenign. Although a wide variety of chemotherapeutic drugs and molecular targeted drugs such as tyrosine kinase inhibitors, alkylating agents, endocrine drugs, interferon, and targeted molecular pathway inhibitors have been studied, the roles of numerous drugs remain unexplored. Recent interest is growing toward studying and engineering exosomes for the treatment of different types of cancer including meningioma. The latest studies have shown the involvement of exosomes in the theragnostic of various cancers such as the lung and pancreas in the form of biomarkers, drug delivery vehicles, and vaccines. Proper attention to this new emerging technology can be a boon in finding the consistent treatment of meningioma.

Prognostic value and immunological role of cathepsin S gene in pan‑cancer

The cathepsin S (CTSS) gene encodes a lysine cysteine protease and serves an important role in the development of autoimmune diseases, inflammation and nervous system diseases. Furthermore, CTSS is implicated in tumor invasion and metastasis by the induction of tumor angiogenesis and the degradation of the tumor extracellular matrix. Nevertheless, the precise impact of CTSS on predicting pan-cancer prognosis and its influence on the tumor microenvironment and immune infiltration in human cancers remains unknown. This present study employed a comprehensive array of bioinformatic methods to evaluate the expression of CTSS and its associations with prognosis, clinicopathological characteristics, tumor microenvironment, tumor immune infiltration, tumor mutational burden and microsatellite instability across numerous cancer types. The current study demonstrated abnormal expression and distinct genomic alteration profiles of CTSS in many of the cancers tested. Furthermore, CTSS expression exhibited close associations with the prognosis of numerous cancers. High CTSS expression was significantly associated with better overall survival and disease-specific survival in bladder urothelial carcinoma (BLCA) and skin cutaneous melanoma (SKCM) but worse outcomes in brain lower grade glioma (LGG) and uveal melanoma (UVM). Moreover, CTSS demonstrated significant correlations with tumor mutational burden and microsatellite instability in 8 and 12 cancer types respectively, as well as different responses in immunotherapy sub-cohorts, especially in melanoma and bladder cancers. CTSS expression showed a positive correlation with stromal and immune cell scores in the four aforementioned cancers. Moreover, CTSS expression was correlated with the number of infiltrating CD8+ T cells, CD4+ T cells and macrophages. Conversely, CTSS was negatively associated with resting Mast cells, resting NK cells and resting memory CD4+ T cell infiltration in BLCA, SKCM and kidney renal clear cell carcinoma (KIRC). Furthermore, CTSS expression was correlated with immune-related gene expression, notably PDCD1, LAG3, PDCD1 and TIGIT in BLCA, KIRC, SKCM, LGG and UVM. Functional enrichment analysis suggested that CTSS could drive a dynamic adjustment of biological functions and pathways in BLCA, SKCM, LGG and UVM, including immune response regulating signaling pathways, regulation of lymphocyte activation and T cell receptor singling pathways. The current study suggested that CTSS could be an essential biomarker for prognosis and immune infiltration features in multiple cancers.

Glucosylated Hybrid TiO2 /Polymer Nanomaterials for Actively Targeted Sonodynamic Therapy of Cancer

Sonodynamic therapy (SDT) is an anti-cancer therapeutic strategy based on the generation of reactive oxygen species (ROS) upon local ultrasound (US) irradiation of sono-responsive molecules or nanomaterials that accumulate in the tumor. In this work, the sonodynamic efficiency of sono-responsive hybrid nanomaterials composed of amorphous titanium dioxide and an amphiphilic poly(ethylene oxide)-b-poly(propylene oxide) block copolymer is synthesized, fully characterized, and investigated both in vitro and in vivo. The modular and versatile synthetic pathway enables the control of the nanoparticle size between 30 and 300 nm (dynamic light scattering) and glucosylation of the surface for active targeting of tumors overexpressing glucose transporters. Studies on 2D and 3D rhabdomyosarcoma cell cultures reveal a statistically significant increase in the sonodynamic efficiency of glucosylated hybrid nanoparticles with respect to unmodified ones. Using a xenograft rhabdomyosarcoma murine model, it is demonstrated that by tuning the nanoparticle size and surface features, the tumor accumulation is increased by ten times compared to main off-target clearance organs such as the liver. Finally, the SDT of rhabdomyosarcoma-bearing mice is investigated with 50-nm glucosylated nanoparticles. Findings evidence a dramatic prolongation of the animal survival and tumor volumes 100 times smaller than those treated only with ultrasound or nanoparticles.

Cellular signaling in the hypoxic cancer microenvironment: Implications for drug resistance and therapeutic targeting

The rewiring of cellular metabolism is a defining characteristic of cancer, as tumor cells adapt to acquire essential nutrients from a nutrient-poor environment to sustain their viability and biomass. While hypoxia has been identified as a major factor depriving cancer cells of nutrients, recent studies have revealed that cancer cells distant from supporting blood vessels also face nutrient limitations. To overcome this challenge, hypoxic cancer cells, which heavily rely on glucose as an energy source, employ alternative pathways such as glycogen metabolism and reductive carboxylation of glutamine to meet their energy requirements for survival. Our preliminary studies, alongside others in the field, have shown that under glucose-deficient conditions, hypoxic cells can utilize mannose and maltose as alternative energy sources. This review aims to comprehensively examine the hypoxic cancer microenvironment, its association with drug resistance, and potential therapeutic strategies for targeting this unique niche. Furthermore, we will critically evaluate the current literature on hypoxic cancer microenvironments and explore state-of-the-art techniques used to analyze alternate carbohydrates, specifically mannose and maltose, in complex biological fluids. We will also propose the most effective analytical methods for quantifying mannose and maltose in such biological samples. By gaining a deeper understanding of the hypoxic cancer cell microenvironment and its role in drug resistance, novel therapeutic approaches can be developed to exploit this knowledge.

Voxel-wise mapping of DCE-MRI time-intensity-curve profiles enables visualizing and quantifying hemodynamic heterogeneity in breast lesions

OBJECTIVES

To propose a novel model-free data-driven approach based on the voxel-wise mapping of DCE-MRI time-intensity-curve (TIC) profiles for quantifying and visualizing hemodynamic heterogeneity and to validate its potential clinical applications.

MATERIALS AND METHODS

From December 2018 to July 2022, 259 patients with 325 pathologically confirmed breast lesions who underwent breast DCE-MRI were retrospectively enrolled. Based on the manually segmented breast lesions, the TIC of each voxel within the 3D whole lesion was classified into 19 subtypes based on wash-in rate (nonenhanced, slow, medium, and fast), wash-out enhancement (persistent, plateau, and decline), and wash-out stability (steady and unsteady), and the composition ratio of these 19 subtypes for each lesion was calculated as a new feature set (type-19). The three-type TIC classification, semiquantitative parameters, and type-19 features were used to build machine learning models for identifying lesion malignancy and classifying histologic grades, proliferation status, and molecular subtypes.

RESULTS

The type-19 feature-based model significantly outperformed models based on the three-type TIC method and semiquantitative parameters both in distinguishing lesion malignancy (respectively; AUC = 0.875 vs. 0.831, p = 0.01 and 0.875vs. 0.804, p = 0.03), predicting tumor proliferation status (AUC = 0.890 vs. 0.548, p = 0.006 and 0.890 vs. 0.596, p = 0.020), but not in predicting histologic grades (p = 0.820 and 0.970).

CONCLUSION

In addition to conventional methods, the proposed computational approach provides a novel, model-free, data-driven approach to quantify and visualize hemodynamic heterogeneity.

CLINICAL RELEVANCE STATEMENT

Voxel-wise intra-lesion mapping of TIC profiles allows for visualization of hemodynamic heterogeneity and its composition ratio for differentiation of malignant and benign breast lesions.

KEY POINTS

• Voxel-wise TIC profiles were mapped, and their composition ratio was compared between various breast lesions. • The model based on the composition ratio of voxel-wise TIC profiles significantly outperformed the three-type TIC classification model and the semiquantitative parameters model in lesion malignancy differentiation and tumor proliferation status prediction in breast lesions. • This novel, data-driven approach allows the intuitive visualization and quantification of the hemodynamic heterogeneity of breast lesions.

Revealing the inhibitory effect of VASH1 on ovarian cancer from multiple perspectives

The function of Vasohibin-1 (VASH1) in human cancer has not been thoroughly or comprehensively examined. Here, we identified the tumor suppressor part of VASH1 across cancers, including epithelial ovarian tumors. Our study carefully contrasted the expression of VASH1 in pancancer and nontumorous tissues in a public database to explore its regulatory role in clinical prognosis, diagnosis, tumor purity, and immune cell infiltration. Next, we explored the antitumor mechanism of VASH1 through drug sensitivity, functional enrichment, and phenotypic experiments in ovarian cancer. Research suggests that the expression of VASH1 in neoplastic tissues is lower than that in normal tissues. VASH1 affects the OS and RFS of several tumor types. In addition, VASH1 expression resulted in a high OS and RFS in the diagnosis of tumor and nontumor tissues and negatively regulated tumor purity. Moreover, VASH1 controls the tumor microenvironment by regulating immunocyte infiltration. In ovarian cancer, VASH1 can serve as a biomarker to estimate the efficacy of chemotherapy. Functional enrichment analysis suggests that VASH1 plays a tumor suppressor role by regulating the extracellular matrix receptor pathway. VASH1 inhibition of the malignant phenotype of ovarian cancer cells was further confirmed by in vivo experiments. These results indicate that VASH1 acts as a cancer-inhibiting factor and potential therapeutic target in ovarian cancer.

Mapping the transcriptome: Realizing the full potential of spatial data analysis

RNA sequencing in situ allows for whole-transcriptome characterization at high resolution, while retaining spatial information. These data present an analytical challenge for bioinformatics-how to leverage spatial information effectively? Properties of data with a spatial dimension require special handling, which necessitate a different set of statistical and inferential considerations when compared to non-spatial data. The geographical sciences primarily use spatial data and have developed methods to analye them. Here we discuss the challenges associated with spatial analysis and examine how we can take advantage of practice from the geographical sciences to realize the full potential of spatial information in transcriptomic datasets.

Evolving CAR-T-Cell Therapy for Cancer Treatment: From Scientific Discovery to Cures

In recent years, chimeric antigen receptor (CAR)-T-cell therapy has emerged as the most promising immunotherapy for cancer that typically uses patients' T cells and genetically engineered them to target cancer cells. Although recent improvements in CAR-T-cell therapy have shown remarkable success for treating hematological malignancies, the heterogeneity in tumor antigens and the immunosuppressive nature of the tumor microenvironment (TME) limits its efficacy in solid tumors. Despite the enormous efforts that have been made to make CAR-T-cell therapy more effective and have minimal side effects for treating hematological malignancies, more research needs to be conducted regarding its use in the clinic for treating various other types of cancer. The main concern for CAR-T-cell therapy is severe toxicities due to the cytokine release syndrome, whereas the other challenges are associated with complexity and immune-suppressing TME, tumor antigen heterogeneity, the difficulty of cell trafficking, CAR-T-cell exhaustion, and reduced cytotoxicity in the tumor site. This review discussed the latest discoveries in CAR-T-cell therapy strategies and combination therapies, as well as their effectiveness in different cancers. It also encompasses ongoing clinical trials; current challenges regarding the therapeutic use of CAR-T-cell therapy, especially for solid tumors; and evolving treatment strategies to improve the therapeutic application of CAR-T-cell therapy.

Downregulation of osteoprotegerin in colorectal cancer cells promotes liver metastasis via activating tumor-associated macrophage

Osteoprotegerin (OPG) is a secreted cytokine that functions as a decoy receptor for receptor activator of nuclear factor kappa-B (RANK) ligand (RANKL). Anti-RANKL treatment for bone metastasis has been widely accepted for solid tumors. However, the mechanism of OPG-RANKL-RANK signaling in systemic colorectal cancer (CRC) metastasis remains unclear. In this study, we investigated the relevance and function of OPG expression in CRC liver metastasis. First, we performed in silico analysis using The Cancer Genome Atlas public database and found that lower OPG expression in CRC was associated with poor overall survival. Immunohistochemistry analyses using resected specimen from patients with CRC in our institute confirmed the result. Patient-matched primary CRC and liver metastases showed a significant downregulation of OPG expression in metastatic lesions. In CRC cell lines, OPG expression did not suppress cell proliferation and migration. However, OPG expression inhibited macrophage migration by suppressing the RANKL-RANK pathway. Moreover, in vivo mouse liver metastasis models showed that OPG expression in CRC cells suppressed liver metastases. In addition, treatment with an anti-RANKL neutralizing antibody also suppressed liver metastases. These results showed that downregulation of OPG expression in CRC cells promotes liver metastasis by activating tumor-associated macrophage, which can become a candidate for targeted therapy with anti-RANKL neutralizing antibody for CRC liver metastasis.

Promising preclinical patient-derived organoid (PDO) and xenograft (PDX) models in upper gastrointestinal cancers: progress and challenges

Gastrointestinal (GI) cancers (gastric cancer, oesophageal cancer, liver cancer, colorectal cancer, etc.) are the most common cancers with the highest morbidity and mortality in the world. The therapy for most GI cancers is difficult and is associated with a poor prognosis. In China, upper GI cancers, mainly gastric cancer (GC) and oesophageal cancer (EC), are very common due to Chinese people's characteristics, and more than half of patients are diagnosed with distant metastatic or locally advanced disease. Compared to other solid cancers, such as lung cancer and breast cancer, personalized therapies, especially targeted therapy and immunotherapy, in GC and EC are relatively lacking, leading to poor prognosis. For a long time, most studies were carried out by using in vitro cancer cell lines or in vivo cell line-derived xenograft models, which are unable to reproduce the characteristics of tumours derived from patients, leading to the possible misguidance of subsequent clinical validation. The patient-derived models represented by patient-derived organoid (PDO) and xenograft (PDX) models, known for their high preservation of patient tumour features, have emerged as a very popular platform that has been widely used in numerous studies, especially in the research and development of antitumour drugs and personalized medicine. Herein, based on some of the available published literature, we review the research and application status of PDO and PDX models in GC and EC, as well as detail their future challenges and prospects, to promote their use in basic and translational studies or personalized therapy.

Comprehensive analysis of mitophagy-related subtypes of breast cancer and the association with immune related characteristics

Breast cancer (BRCA) is a common neoplasm characterized by high levels of molecular heterogeneity. Previous studies have noted the importance of mitophagy for the progression and prognosis of BRCA. However, little was found in the similarity and difference of mitophagy-related gene expression patterns of BRCA. This study intended to investigate the differences in functional activation, somatic mutation, and immune-related characteristics among different subtypes of BRCA associated with mitophagy. Based on bioinformatics analysis, we systematically examined the heterogeneity of breast cancer concerning mitophagy and observed two distinct subtypes with different tumor microenvironments and prognoses. BRCA samples from TCGA database were divided into two subtypes based on the expression of 29 mitophagy-related genes by ConsensusClusterPlus algorithm. Two mitophagy-related subtypes with marked prognostic discrepancies were significantly correlated with race, intrinsic subtype grouped based on PAM50 subtype purity and BRCA Pathology. The results of GSVA and immune microenvironment analysis showed significant differences in cancer-related and immune-related features between the two subtypes. METABRIC datasets were extracted to validate the immune characteristics scoring and the expression of immune checkpoints between different subtypes based on the medium value of TCGA-Mitophagy score. It is noteworthy that the present study is the first to demonstrate a new classification based on the mitophagy of breast cancer, which comes up with a new perspective for the assessment and prognoses of BRCA.

Cancer nanomedicine: emergence, expansion, and expectations

The introduction of cancer nanomedicine has substantially enhanced the effectiveness of cancer treatments. Nano-formulations are becoming more prevalent among other treatment methods due to their improved therapeutic efficacy and low systemic toxicity. The discovery of the enhanced permeability and retention (EPR) effect has led to the development of numerous nanodrugs that passively target tumours. Then researchers identified certain cancer cells overexpress certain receptors, targeting these over-expressing receptors using targeting moiety on the surface of the nanoparticles becomes promising and surface functionalization of nanoparticles has become an important area of cancer nanomedicine. This leads to the physiochemical modification of nanoparticles for strengthening the EPR effect and active targeting. This review comprehensively outlines the origins of cancer nanomedicine, the role of the EPR effect, the tools of nanotechnology and their specifications, and the nature of passive and active targeting, which gives important direction for the progress of cancer therapy using nanomedicine. The review briefly enlists the available nano formulations for different cancers and attempts were made to account for the barriers to clinical translation. The review also briefly describes the transition of research from nanomedicine to nano-immunotherapy.

Bifunctional bone substitute materials for bone defect treatment after bone tumor resection

Aggressive benign, malignant and metastatic bone tumors can greatly decrease the quality of patients' lives and even lead to substantial mortality. Several clinical therapeutic strategies have been developed to treat bone tumors, including preoperative chemotherapy, surgical resection of the tumor tissue, and subsequent systemic chemo- or radiotherapy. However, those strategies are associated with inevitable drawbacks, such as severe side effects, substantial local tumor recurrence, and difficult-to-treat bone defects after tumor resection. To overcome these shortcomings and achieve satisfactory clinical outcomes, advanced bifunctional biomaterials which simultaneously promote bone regeneration and combat bone tumor growth are increasingly advocated. These bifunctional bone substitute materials fill bone defects following bone tumor resection and subsequently exert local anticancer effects. Here we describe various types of the most prevalent bone tumors and provide an overview of common treatment options. Subsequently, we review current progress regarding the development of bifunctional bone substitute materials combining osteogenic and anticancer efficacy. To this end, we categorize these biomaterials based on their anticancer mechanism deriving from i) intrinsic biomaterial properties, ii) local drug release of anticancer agents, and iii) oxidative stress-inducing and iv) hyperthermia-inducing biomaterials. Consequently, this review offers researchers, surgeons and oncologists an up-to-date overview of our current knowledge on bone tumors, their treatment options, and design of advanced bifunctional biomaterials with strong potential for clinical application in oncological orthopedics.

Clonal dynamics limits detection of selection in tumour xenograft CRISPR/Cas9 screens

Transplantable in vivo CRISPR/Cas9 knockout screens, in which cells are edited in vitro and inoculated into mice to form tumours, allow evaluation of gene function in a cancer model that incorporates the multicellular interactions of the tumour microenvironment. To improve our understanding of the key parameters for success with this method, we investigated the choice of cell line, mouse host, tumour harvesting timepoint and guide RNA (gRNA) library size. We found that high gRNA (80-95%) representation was maintained in a HCT116 subline transduced with the GeCKOv2 whole-genome gRNA library and transplanted into NSG mice when tumours were harvested at early (14 d) but not late time points (38-43 d). The decreased representation in older tumours was accompanied by large increases in variance in gRNA read counts, with notable expansion of a small number of random clones in each sample. The variable clonal dynamics resulted in a high level of 'noise' that limited the detection of gRNA-based selection. Using simulated datasets derived from our experimental data, we show that considerable reductions in count variance would be achieved with smaller library sizes. Based on our findings, we suggest a pathway to rationally design adequately powered in vivo CRISPR screens for successful evaluation of gene function.

Integrative landscape analysis of prognostic model biomarkers and immunogenomics of disulfidptosis-related genes in breast cancer based on LASSO and WGCNA analyses

BACKGROUND

Disulfidptosis is a novel type of programmed cell death. However, the value of disulfidptosis-related genes (DRGs) in the prediction of breast cancer prognosis is unclear.

METHODS

RNA-seq data of 1231 patients, together with information on patient clinical characteristics and prognosis, were downloaded from TCGA. DRGs were identified between cancerous and non-cancerous tissues. The LASSO algorithm was used to assign half of the samples to the training set. Risk scores were used for construction of a prognostic model for risk stratification and prognosis prediction, and the clinical applicability was examined using a line diagram. The relationships between risk scores, immune cell infiltration, molecular subtypes, and responses to immunotherapy and chemotherapy were examined.

RESULTS

We identified and obtained four DRG-related prognostic lncRNAs (AC009097.2, AC133552.5, YTHDF3-AS1, and AC084824.5), which were used for establishing the risk model. Longer survival was associated with low risk. The DRG-associated lncRNAs were found to independently predict patient prognosis. The AUCs under the ROCs for one-, three-, and 5-year survival in the training cohort were 0.720, 0.687, and 0.692, respectively. The model showed that the high-risk patients had reduced overall survival as well as high tumor mutation burdens. Furthermore, high-risk patients showed increased sensitivity to therapeutic drugs, including docetaxel, paclitaxel, and oxaliplatin.

CONCLUSION

The risk score model was effective for predicting both prognosis and sensitivity to therapeutic drugs, suggesting its possible usefulness for the management of patients with breast cancer.

Regulatory mechanism and promising clinical application of exosomal circular RNA in gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide and the leading cause of cancer-related deaths. Exosomes are nanoscale extracellular vesicles secreted by a variety of cells and play an important role in cellular communication and epigenetics by transporting bioactive substances in the tumor microenvironment (TME). Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a specific structure, which is widely enriched in exosomes and is involved in various pathophysiological processes mediated by exosomes. Exosomal circRNAs play a critical role in the development of GC by regulating epithelial-mesenchymal transition (EMT), angiogenesis, proliferation, invasion, migration, and metastasis of GC. Given the biological characteristics of exosomal circRNAs, they have more significant diagnostic sensitivity and specificity in the clinic and may become biomarkers for GC diagnosis and prognosis. In this review, we briefly describe the biogenesis of exosomes and circRNAs and their biological functions, comprehensively summarize the mechanisms of exosomal circRNAs in the development of GC and chemotherapy resistance, and finally, we discuss the potential clinical application value and challenges of exosomal circRNAs in GC.

Current state of radiomics in hepatobiliary and pancreatic malignancies

Rising in incidence, hepatobiliary and pancreatic (HPB) cancers continue to exhibit dismal long-term survival. The overall poor prognosis of HPB cancers is reflective of the advanced stage at which most patients are diagnosed. Late diagnosis is driven by the often-asymptomatic nature of these diseases, as well as a dearth of screening modalities. Additionally, standard imaging modalities fall short of providing accurate and detailed information regarding specific tumor characteristics, which can better inform surgical planning and sequencing of systemic therapy. Therefore, precise therapeutic planning must be delayed until histopathological examination is performed at the time of resection. Given the current shortcomings in the management of HPB cancers, investigations of numerous noninvasive biomarkers, including circulating tumor cells and DNA, proteomics, immunolomics, and radiomics, are underway. Radiomics encompasses the extraction and analysis of quantitative imaging features. Along with summarizing the general framework of radiomics, this review synthesizes the state of radiomics in HPB cancers, outlining its role in various aspects of management, present limitations, and future applications for clinical integration. Current literature underscores the utility of radiomics in early detection, tumor characterization, therapeutic selection, and prognostication for HPB cancers. Seeing as single-center, small studies constitute the majority of radiomics literature, there is considerable heterogeneity with respect to steps of the radiomics workflow such as segmentation, or delineation of the region of interest on a scan. Nonetheless, the introduction of the radiomics quality score (RQS) demonstrates a step towards greater standardization and reproducibility in the young field of radiomics. Altogether, in the setting of continually improving artificial intelligence algorithms, radiomics represents a promising biomarker avenue for promoting enhanced and tailored management of HPB cancers, with the potential to improve long-term outcomes for patients.

Multifunctional mesoporous silica nanoparticles for biomedical applications

Mesoporous silica nanoparticles (MSNs) are recognized as a prime example of nanotechnology applied in the biomedical field, due to their easily tunable structure and composition, diverse surface functionalization properties, and excellent biocompatibility. Over the past two decades, researchers have developed a wide variety of MSNs-based nanoplatforms through careful design and controlled preparation techniques, demonstrating their adaptability to various biomedical application scenarios. With the continuous breakthroughs of MSNs in the fields of biosensing, disease diagnosis and treatment, tissue engineering, etc., MSNs are gradually moving from basic research to clinical trials. In this review, we provide a detailed summary of MSNs in the biomedical field, beginning with a comprehensive overview of their development history. We then discuss the types of MSNs-based nanostructured architectures, as well as the classification of MSNs-based nanocomposites according to the elements existed in various inorganic functional components. Subsequently, we summarize the primary purposes of surface-functionalized modifications of MSNs. In the following, we discuss the biomedical applications of MSNs, and highlight the MSNs-based targeted therapeutic modalities currently developed. Given the importance of clinical translation, we also summarize the progress of MSNs in clinical trials. Finally, we take a perspective on the future direction and remaining challenges of MSNs in the biomedical field.

Radiological artificial intelligence - predicting personalized immunotherapy outcomes in lung cancer

Personalized medicine has revolutionized approaches to treatment in the field of lung cancer by enabling therapies to be specific to each patient. However, physicians encounter an immense number of challenges in providing the optimal treatment regimen for the individual given the sheer complexity of clinical aspects such as tumor molecular profile, tumor microenvironment, expected adverse events, acquired or inherent resistance mechanisms, the development of brain metastases, the limited availability of biomarkers and the choice of combination therapy. The integration of innovative next-generation technologies such as deep learning-a subset of machine learning-and radiomics has the potential to transform the field by supporting clinical decision making in cancer treatment and the delivery of precision therapies while integrating numerous clinical considerations. In this review, we present a brief explanation of the available technologies, the benefits of using these technologies in predicting immunotherapy response in lung cancer, and the expected future challenges in the context of precision medicine.

Research trends and hotspots in the immune microenvironment related to osteosarcoma and tumor cell aging: a bibliometric and visualization study

Background

It is well known that cancers have a common feature that even if the environment is extremely poor in nutrients, they can still make good use of them to maintain viability as well as to produce new biomass, which is one of the reasons why tumor cells are powerfully less susceptible to senescence and death. The microenvironment has a profound impact on the senescence as well as the growth and development of tumor cells, and it is also the focus of scientists' research because it may even affect the discovery of the treatment and pathogenesis of cancer. And so the study of the microenvironment in the tumor cells is of great significance to the analysis of the tumor cells as well as to the impact of their senescence. Similarly, the microenvironment of osteosarcoma is also crucial for its impact, but to our knowledge, there is no bibliometric study that systematically analyzes and describes the trends and future hotspots in this field of research as we do, and we are going to fill this gap in this study.

Methods

We searched the Web Science Core Collection 2010-2023 in WOS on August 1, 2023. Based on the criteria needed for the search, we retained articles that matched the topic, excluded studies other than articles and reviews, and selected only studies whose language was English. We performed an intuitive visualization and bibliometric approach to analyze the research content in this field and a systematic visualization of global trends and hotspots in the research of osteosarcoma and the microenvironment, for which we used multiple specialized For this purpose, we used several specialized software packages, such as VOSviewer and the Bibliometrix package for R software. Because research in this area of osteosarcoma and the microenvironment has begun to gain popularity in the last 10 years or so, and is a very novel piece of research, there were almost no studies in this area prior to 2010 and they were not very informative, and in the end, we chose to look at studies from after 2010.

Results

Based on the criteria needed for the search, resulting in a final selection of 821 articles. In the research area related to osteosarcoma and microenvironment, we found that China in Asia and the United States in North America and Italy in Europe were the three countries or regions with the highest number of published articles. In addition, the institution that published the most research in this area was Shanghai Jiao Tong University. In terms of publications in the field of osteosarcoma and microenvironmental research, Baldini, Heymann, and Avnet are among the top 3 authors. The terms "cancer", "cells" and "expression" are found to be more commonly employed.

Conclusion

Using a variety of highly specialized software, we have undertaken a visual and bibliometric study of the current state of research and potential future hotspots in the field of osteosarcoma and microenvironment research. The microenvironment has a profound impact on the senescence and growth and development of cells in tumors, including osteosarcoma, and may even influence the discovery of cancer treatment and pathogenesis, and is also a hotspot and focus that scientists have begun to gradually study in recent years. This analysis and visualization will help guide future research in the field.

Phytochemical-Based Nanomedicine for Targeting Tumor Microenvironment and Inhibiting Cancer Chemoresistance: Recent Advances and Pharmacological Insights

Cancer remains the leading cause of death and rapidly evolving disease worldwide. The understanding of disease pathophysiology has improved through advanced research investigation, and several therapeutic strategies are being used for better cancer treatment. However, the increase in cancer relapse and metastatic-related deaths indicate that available therapies and clinically approved chemotherapy drugs are not sufficient to combat cancer. Further, the constant crosstalk between tumor cells and the tumor microenvironment (TME) is crucial for the development, progression, metastasis, and therapeutic response to tumors. In this regard, phytochemicals with multimodal targeting abilities can be used as an alternative to current cancer therapy by inhibiting cancer survival pathways or modulating TME. However, due to their poor pharmacokinetics and low bioavailability, the success of phytochemicals in clinical trials is limited. Therefore, developing phytochemical-based nanomedicine or phytonanomedicine can improve the pharmacokinetic profile of these phytochemicals. Herein, the molecular characteristics and pharmacological insights of the proposed phytonanomedicine in cancer therapy targeting tumor tissue and altering the characteristics of cancer stem cells, chemoresistance, TME, and cancer immunity are well discussed. Further, we have highlighted the clinical perspective and challenges of phytonanomedicine in filling the gap in potential cancer therapeutics using various nanoplatforms. Overall, we have discussed how clinical success and pharmacological insights could make it more beneficial to boost the concept of nanomedicine in the academic and pharmaceutical fields to counter cancer metastases and drug resistance.

An Activated Dendritic-Cell-Related Gene Signature Indicative of Disease Prognosis and Chemotherapy and Immunotherapy Response in Colon Cancer Patients

Accumulating evidence has underscored the prognostic value of tumor-infiltrating immune cells in the tumor microenvironment of colon cancer (CC). In this retrospective study, based on publicly available transcriptome profiles and clinical data from the Gene Expression Omnibus and The Cancer Genome Atlas databases, we derived and verified an activated dendritic cell (aDC)-related gene signature (aDCRS) for predicting the survival outcomes and chemotherapy and immunotherapy response of CC patients. We quantified the infiltration abundance of 22 immune cell subtypes via the "CIBERSORT" R script. Univariate Cox proportional hazards (PHs) regression was used to identify aDC as the most robust protective cell type for CC prognosis. After selecting differentially expressed genes (DEGs) significantly correlated with aDC infiltration, we performed univariate Cox-PH regression, LASSO regression, and stepwise multivariate Cox-PH regression successively to screen out prognosis-related genes from selected DEGs for constructing the aDCRS. Receiver operating characteristic (ROC) curves and Kaplan-Meier (KM) analysis were employed to assess the discriminatory ability and risk-stratification capacity. The "oncoPredict" package, Cancer Treatment Response gene signature DataBase, and Tumor Immune Dysfunction and Exclusion algorithm were utilized to estimate the practicability of the aDCRS in predicting response to chemotherapy and immune checkpoint blockade. Gene set enrichment analysis and single-cell RNA sequencing analysis were also implemented. Furthermore, an aDCRS-based nomogram was constructed and validated via ROC curves, calibration plots and decision curve analysis. In conclusion, aDCRS and an aDCRS-based nomogram will facilitate precise prognosis prediction and individualized therapeutic interventions, thus improving the survival outcomes of CC patients in the future.

Prognostic significance of the rho GTPase RHOV and its role in tumor immune cell infiltration: a comprehensive pan-cancer analysis

Ras homolog gene family member V (RHOV) is an atypical Rho GTPase that participates in various important cellular processes. Although RHOV has been identified to play an oncogenic role in lung cancer and triple-negative breast cancer, its role in other types of tumors remains unknown. In this study, we investigated the expression of RHOV in pan-cancer analysis using The Cancer Genome Atlas (TCGA) and Gene-Tissue Expression datasets. RHOV mRNA levels were dysregulated in several types of tumors. RHOV expression was identified as an independent prognostic factor in 7 of 33 types of tumors; however, the relationship varied according to tumor type. Higher RHOV expression was associated with a favorable prognosis in kidney renal cell carcinoma and prostate adenocarcinoma, for which RHOV expression was downregulated, whereas RHOV expression was associated with a poor prognosis for patients with adenoid cystic carcinoma, lung adenocarcinoma, pancreatic ductal adenocarcinoma, skin cutaneous melanoma, and uveal melanoma with upregulated RHOV expression. Furthermore, RHOV expression was associated with various clinicopathological parameters in these tumors. RHOV expression showed varied associations with different types of tumor-infiltrating immune cells and demonstrated a potential impact on the response to immunotherapy depending on the cancer type. Additionally, functional enrichment analysis of RHOV-related genes demonstrated a role in a wide range of developmental and immune-related processes. This study provides valuable insights into the role of RHOV in pan-cancer development, indicating its role as a tumor suppressor or oncogene according to the cancer type and tumor microenvironment.

Toward the clinical development of synthetic immunity to cancer

Synthetic biology (synbio) tools, such as chimeric antigen receptors (CARs), have been designed to target, activate, and improve immune cell responses to tumors. These therapies have demonstrated an ability to cure patients with blood cancers. However, there are significant challenges to designing, testing, and efficiently translating these complex cell therapies for patients who do not respond or have immune refractory solid tumors. The rapid progress of synbio tools for cell therapy, particularly for cancer immunotherapy, is encouraging but our development process should be tailored to increase translational success. Particularly, next-generation cell therapies should be rooted in basic immunology, tested in more predictive preclinical models, engineered for potency with the right balance of safety, educated by clinical findings, and multi-faceted to combat a range of suppressive mechanisms. Here, we lay out five principles for engineering future cell therapies to increase the probability of clinical impact, and in the context of these principles, we provide an overview of the current state of synbio cell therapy design for cancer. Although these principles are anchored in engineering immune cells for cancer therapy, we posit that they can help guide translational synbio research for broad impact in other disease indications with high unmet need.

Neo-Antigen-Reactive T Cells Immunotherapy for Colorectal Cancer: A More Personalized Cancer Therapy Approach

Colorectal cancer (CRC) is the second most common malignancy in women and the third most frequent cancer in men. Evidence has revealed that the survival of patients with metastatic CRC is very low, between one and three years. Neoantigens are known proteins encoded by mutations in tumor cells. It is theorized that recognizing neoantigens by T cells leads to T cell activation and further antitumor responses. Neoantigen-reactive T cells (NRTs) are designed against the mentioned neoantigens expressed by tumor cells. NRTs selectively kill tumor cells without damage to non-cancerous cells. Identifying patient-specific and high immunogen neoantigens is important in NRT immunotherapy of patients with CRC. However, the main challenges are the side effects and preparation of NRTs, as well as the effectiveness of these cells in vivo. This review summarized the properties of neoantigens as well as the preparation and therapeutic outcomes of NRTs for the treatment of CRC.