Influence of tumour micro-environment heterogeneity on therapeutic response

Chemokines in the tumor microenvironment: implications for lung cancer and immunotherapy

The tumor microenvironment (TME) is a complex interconnected network of immune cells, fibroblasts, blood vessels, and extracellular matrix surrounding the tumor. Because of its immunosuppressive nature, the TME can pose a challenge for cancer immunotherapies targeting solid tumors. Chemokines have emerged as a crucial element in enhancing the efficacy of cancer immunotherapy, playing a direct role in immune cell signaling within the TME and facilitating immune cell migration towards cancer cells. However, chemokine ligands and their receptors exhibit context-dependent diversity, necessitating evaluation of their tumor-promoting or inhibitory effects based on tumor type and immune cell characteristics. This review explores the role of chemokines in tumor immunity and metastasis in the context of the TME. We also discuss current chemokine-related advances in cancer immunotherapy research, with a particular focus on lung cancer, a common cancer with a low survival rate and limited immunotherapy options.

Nucleic acid cancer vaccines targeting tumor related angiogenesis. Could mRNA vaccines constitute a game changer?

Tumor related angiogenesis is an attractive target in cancer therapeutic research due to its crucial role in tumor growth, invasion, and metastasis. Different agents were developed aiming to inhibit this process; however they had limited success. Cancer vaccines could be a promising tool in anti-cancer/anti-angiogenic therapy. Cancer vaccines aim to initiate an immune response against cancer cells upon presentation of tumor antigens which hopefully will result in the eradication of disease and prevention of its recurrence by inducing an efficient and long-lasting immune response. Different vaccine constructs have been developed to achieve this and they could include either protein-based or nucleic acid-based vaccines. Nucleic acid vaccines are simple and relatively easy to produce, with high efficiency and safety, thus prompting a high interest in the field. Different DNA vaccines have been developed to target crucial regulators of tumor angiogenesis. Most of them were successful in pre-clinical studies, mostly when used in combination with other therapeutics, but had limited success in the clinic. Apparently, different tumor evasion mechanisms and reduced immunogenicity still limit the potential of these vaccines and there is plenty of room for improvement. Nowadays, mRNA cancer vaccines are making remarkable progress due to improvements in the manufacturing technology and represent a powerful potential alternative. Apart from their efficiency, mRNA vaccines are simple and cheap to produce, can encompass multiple targets simultaneously, and can be quickly transferred from bench to bedside. mRNA vaccines have already accomplished amazing results in cancer clinical trials, thus ensuring a bright future in the field, although no anti-angiogenic mRNA vaccines have been described yet. This review aims to describe recent advances in anti-angiogenic DNA vaccine therapy and to provide perspectives for use of revolutionary approaches such are mRNA vaccines for anti-angiogenic treatments.

In vitro throughput screening of anticancer drugs using patient-derived cell lines cultured on vascularized three-dimensional stromal tissues

The development of high-throughput anticancer drug screening methods using patient-derived cancer cell (PDC) lines that maintain their original characteristics in an in vitro three-dimensional (3D) culture system poses a significant challenge to achieving personalized cancer medicine. Because stromal tissue plays a critical role in the composition and maintenance of the cancer microenvironment, in vitro 3D-culture using reconstructed stromal tissues has attracted considerable attention. Here, a simple and unique in vitro 3D-culture method using heparin and collagen together with fibroblasts and endothelial cells to fabricate vascularized 3D-stromal tissues for in vitro culture of PDCs is reported. Whereas co-treatment with bevacizumab, a monoclonal antibody against vascular endothelial growth factor, and 5-fluorouracil significantly reduced the survival rate of 3D-cultured PDCs to 30%, separate addition of each drug did not induce comparable strong cytotoxicity, suggesting the possibility of evaluating the combined effect of anticancer drugs and angiogenesis inhibitors. Surprisingly, drug evaluation using eight PDC lines with the 3D-culture method resulted in a drug efficacy concordance rate of 75% with clinical outcomes. The model is expected to be applicable to in vitro throughput drug screening for the development of personalized cancer medicine. STATEMENT OF SIGNIFICANCE: To replicate the cancer microenvironment, we constructed a cancer-stromal tissue model in which cancer cells are placed above and inside stromal tissue with vascular network structures derived from vascular endothelial cells in fibroblast tissue using CAViTs method. Using this method, we were able to reproduce the invasion and metastasis processes of cancer cells observed in vivo. Using patient-derived cancer cells, we assessed the possibility of evaluating the combined effect with an angiogenesis inhibitor. Further, primary cancer cells also grew on the stromal tissues with the normal medium. These data suggest that the model may be useful for new in vitro drug screening and personalized cancer medicine.

Overcoming Chemoresistance in Cancer: The Promise of Crizotinib

Chemoresistance is a major obstacle in cancer treatment, often leading to disease progression and poor outcomes. It arises through various mechanisms such as genetic mutations, drug efflux pumps, enhanced DNA repair, and changes in the tumor microenvironment. These processes allow cancer cells to survive despite chemotherapy, underscoring the need for new strategies to overcome resistance and improve treatment efficacy. Crizotinib, a first-generation multi-target kinase inhibitor, is approved by the FDA for the treatment of ALK-positive or ROS1-positive non-small cell lung cancer (NSCLC), refractory inflammatory (ALK)-positive myofibroblastic tumors (IMTs) and relapsed/refractory ALK-positive anaplastic large cell lymphoma (ALCL). Crizotinib exists in two enantiomeric forms: (R)-crizotinib and its mirror image, (S)-crizotinib. It is assumed that the R-isomer is responsible for the carrying out various processes reviewed here The S-isomer, on the other hand, shows a strong inhibition of MTH1, an enzyme important for DNA repair mechanisms. Studies have shown that crizotinib is an effective multi-kinase inhibitor targeting various kinases such as c-Met, native/T315I Bcr/Abl, and JAK2. Its mechanism of action involves the competitive inhibition of ATP binding and allosteric inhibition, particularly at Bcr/Abl. Crizotinib showed synergistic effects when combined with the poly ADP ribose polymerase inhibitor (PARP), especially in ovarian cancer harboring BRCA gene mutations. In addition, crizotinib targets a critical vulnerability in many p53-mutated cancers. Unlike its wild-type counterpart, the p53 mutant promotes cancer cell survival. Crizotinib can cause the degradation of the p53 mutant, sensitizing these cancer cells to DNA-damaging substances and triggering apoptosis. Interestingly, other reports demonstrated that crizotinib exhibits anti-bacterial activity, targeting Gram-positive bacteria. Also, it is active against drug-resistant strains. In summary, crizotinib exerts anti-tumor effects through several mechanisms, including the inhibition of kinases and the restoration of drug sensitivity. The potential of crizotinib in combination therapies is emphasized, particularly in cancers with a high prevalence of the p53 mutant, such as triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSOC).

Combinatorial Inhibition of Complement Factor D and BCL2 for Early-Onset Colorectal Cancer

BACKGROUND

The tumor immune microenvironment is distinct between early-onset and late-onset colorectal cancer, which facilitates tumor progression. We previously identified several genes, including complement factor D, as having increased expression in patients with early-onset colorectal cancer.

OBJECTIVE

This study aimed to assess and validate the differential expression of immune genes in early-onset and late-onset colorectal cancer. We also aimed to test known drugs targeting genes increased in early-onset colorectal cancer in preclinical mouse models.

DESIGN

A retrospective cohort study with analysis was performed using tumor RNA from formalin-fixed paraffin-embedded cell culture and immunohistochemistry to validate gene expression and function and in vivo preclinical tumor study to assess drug efficacy.

SETTINGS

The Oregon Colorectal Cancer Registry was queried to identify patients with colorectal cancer.

PATIENTS

The study included 67 patients with early-onset colorectal cancer and 54 patients with late-onset colorectal cancer.

INTERVENTIONS

Preclinical animal models using the HCT-116 colon cancer cell line were treated with the complement factor D inhibitor danicopan and the BCL2 inhibitor venetoclax, or with vehicle controls.

MAIN OUTCOME MEASURES

Elevated RNA signatures using NanoString data were evaluated by the retrospective cohort. When inhibiting these markers in the mouse preclinical model, tumor volume and weight were the main outcome measures.

RESULTS

After updating our sample size from our previously published data, we found that complement factor D and BCL2, genes with known function and small molecule inhibitors, are elevated in patients with early-onset colorectal cancer. When inhibiting these markers with the drugs danicopan and venetoclax in a mouse model, we found that the combination of these drugs decreased tumor burden but also resulted in toxicity.

LIMITATIONS

This study is limited by a small sample size and a subcutaneous tumor model.

CONCLUSIONS

Combinatorial inhibition of early-onset associated genes complement factor D and BCL2 slows the growth of early-onset colorectal cancer in a mouse preclinical model. See Video Abstract .

INHIBICIN COMBINADA DEL FACTOR DCOMPLEMENTARIO Y DEL BCL EN CASOS DE CNCER COLORRECTAL DE APARICIN TEMPRANA

ANTECEDENTES:El microambiente inmunológico del tumor es distinto entre el cáncer colorrectal de aparición temprana y el de aparición tardía, lo que facilita la progresión de dicho tumor. Anteriormente identificamos varios genes, incluidos el factor D-Complementario, con una mayor expresión en pacientes con cáncer colorrectal de aparición temprana.OBJETIVO:El presente estudio tuvo como objetivo el evaluar y validar la expresión diferenciada de genes inmunes en casos de cáncer colorrectal de aparición temprana y tardía. También nos propusimos evaluar los fármacos conocidos dirigidos sobre los genes aumentados en el cáncer colorrectal de aparición temprana en modelos pre-clínicos en ratones.DISEÑO:Estudio de cohortes con análisis retrospectivo utilizando el ARN tumoral procedente de cultivos celulares fijados con formalina e incluidos en parafina, y el analisis por inmunohistoquímica para validar la expresión y la función genética. Se realizó el estudio pre-clínico de los tumores in vivo para evaluar la eficacia de los fármacos.AJUSTES:Se consultó el Registro de Oregon de casos de Cáncer Colorrectal para encontrar los pacientes afectados.SUJETOS:67 pacientes con cáncer colorrectal de aparición temprana y 54 pacientes con cáncer colorrectal de aparición tardía.INTERVENCIONES (SI LAS HUBIESE):Los modelos animales pre-clínicos que utilizaron la línea celular de cáncer de colon HCT-116 se trataron con el inhibidor del factor D-Complementario o Danicopan y con el inhibidor de BCL-2 o Venetoclax, ambos con control del transportador.PRINCIPALES MEDIDAS DE RESULTADO:Se evaluaron las firmas de ARN elevadas utilizando los datos del NanoString a partir de la cohorte retrospectiva. Al inhibir estos marcadores del modelo pre-clínico en los ratones, el volumen y el peso del tumor fueron las principales medidas de resultado.RESULTADOS:Después de actualizar el tamaño de nuestra muestra a partir de datos publicados con anterioridad, encontramos que el factor D-Complementario y BCL-2, genes con función conocida e inhibidores de moléculas pequeñas, se encuentran elevados en aquellos pacientes con cáncer colorrectal de aparición temprana. Al inhibir estos marcadores con los medicamentos Danicopan y Venetoclax en el modelo de ratones vivos, encontramos que la combinación de estos dos farmacos disminuyó la carga tumoral pero también produjo toxicidad.LIMITACIONES:Estudio limitado por un tamaño de muestra pequeño y el modelo de tumor subcutáneo.CONCLUSIONES:La inhibición combinada de genes asociados de aparición temprana, el factor D-Complementario y el BCL-2, enlentecen el crecimiento del cáncer colorrectal de aparición temprana del modelo preclínico en ratones. (Traducción-Dr. Xavier Delgadillo ).

Recent advances in in vitro models simulating the female genital tract toward more effective intravaginal therapeutic delivery

INTRODUCTION

Intravaginal drug delivery has emerged as a promising avenue for treating a spectrum of systemic and local female genital tract (FGT) conditions, using biomaterials as carriers or scaffolds for targeted and efficient administration. Much effort has been made to understand the natural barriers of this route and improve the delivery system to achieve an efficient therapeutic response.

AREAS COVERED

In this review, we conducted a comprehensive literature search using multiple databases (PubMed Scopus Web of Science Google Scholar), to discuss the potential of intravaginal therapeutic delivery, as well as the obstacles unique to this route. The in vitro cell models of the FGT and how they can be applied to probing intravaginal drug delivery are then analyzed. We further explore the limitations of the existing models and the possibilities to make them more promising for delivery studies or biomaterial validation. Complementary information is provided by in vitro acellular techniques that may shed light on mucus-drug interaction.

EXPERT OPINION

Advances in 3D models and cell cultures have enhanced our understanding of the FGT, but they still fail to replicate all variables. Future research should aim to use complementary methods, ensure stability, and develop consistent protocols to improve therapy evaluation and create better predictive in vitro models for women's health.

AEBP1 upregulation contributes to cervical cancer progression by facilitating cell proliferation, migration, and invasion

BACKGROUND

Aberrant expression of adipocyte enhancer-binding protein 1 (AEBP1) has been demonstrated to be involved in the tumorigenesis and progression of numerous cancers. This study was aimed to investigate the mechanism of AEBP1 in the development of cervical cancer.

METHODS

The expression of AEBP1 in cervical cancer was assessed by immunohistochemistry. The function of AEBP1 on cell proliferation, migration, and invasion was determined by methyl thiazolyl tetrazolium assay, colony formation, and transwell assay. The activation of related signaling pathway was determined by western blot. The bioinformatics analysis was performed by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

Higher protein expression of AEBP1 was observed in patients with cervical cancer. Overexpressed AEBP1 promoted cell proliferation, migration, and invasion abilities in cervical cancer cells. Moreover, the research manifested that AEBP1 activated the phosphorylation of STAT3. GO and KEGG analysis showed that genes positively related to AEBP1 were highly enriched in functions like epithelial cell proliferation, muscle cell migration, myoblast migration, smooth muscle tissue development, ECM-receptor interaction, transcriptional misregulation in cancer, and proteoglycans in cancer. While genes negatively related to AEBP1 were associated with immunity, including inflammatory response, external-stimulus response, neutrophil, granulocyte, and macrophage chemotaxis.

CONCLUSIONS

This study suggested that AEBP1 acts as an oncogened and might be a potential therapeutic target for the treatment of cervical cancer.

Enhanced Proteomic Coverage in Tissue Microenvironment by Immune Cell Subtype Library-Assisted DIA-MS

Immune cells that infiltrate the tumor microenvironment (TME) play crucial roles in shaping cancer development and influencing clinical outcomes and therapeutic responses. However, obtaining a comprehensive proteomic snapshot of tumor-infiltrating immunity in clinical specimens is often hindered by small sample amounts and a low proportion of immune infiltrating cells in the TME. To enable in-depth and highly sensitive profiling of microscale tissues, we established an immune cell-enriched library-assisted strategy for data-independent acquisition mass spectrometry (DIA-MS). Firstly, six immune cell subtype-specific spectral libraries were established from sorted cluster of differentiation markers, CD8+, CD4+ T lymphocytes, B lymphocytes, natural killer cells, dendritic cells, and macrophages in murine mesenteric lymph nodes (MLNs), covering 7815 protein groups with surface markers and immune cell-enriched proteins. The feasibility of microscale immune proteomic profiling was demonstrated on 1 μg tissue protein from the tumor of murine colorectal cancer (CRC) models using single-shot DIA; the immune cell-enriched library increased coverage to quantify 7419 proteins compared to directDIA analysis (6978 proteins). The enhancement enabled the mapping of 841 immune function-related proteins and exclusive identification of many low-abundance immune proteins, such as CD1D1, and CD244, demonstrating high sensitivity for immune landscape profiling. This approach was used to characterize the MLNs in CRC models, aiming to elucidate the mechanism underlying their involvement in cancer development within the TME. Even with a low percentage of immune cell infiltration (0.25-3%) in the tumor, our results illuminate downregulation in the adaptive immune signaling pathways (such as C-type lectin receptor signaling, and chemokine signaling), T cell receptor signaling, and Th1/Th2/Th17 cell differentiation, suggesting an immunosuppressive status in MLNs of CRC model. The DIA approach using the immune cell-enriched libraries showcased deep coverage and high sensitivity that can facilitate illumination of the immune proteomic landscape for microscale samples.

Mechanism of the Radioresistant Colorectal Cancer Cell Line SW480RR Established after Fractionated X Irradiation

Radioresistant cancer cells are risk factors for recurrence and are occasionally detected in recurrent tumors after radiotherapy. Intratumor heterogeneity is believed to be a potential cause of treatment resistance. Heterogeneity in DNA content has also been reported in human colorectal cancer; however, little is known about how such heterogeneity changes with radiotherapy or how it affects cancer radioresistance. In the present study, we established radioresistant clone SW480RR cells after fractionated X-ray irradiation of human colorectal cancer-derived SW480.hu cells, which are composed of two cell populations with different chromosome numbers, and examined how cellular radioresistance changed with fractionated radiotherapy. Compared with the parental cell population, which mostly comprised cells with higher ploidy, the radioresistant clones showed lower ploidy and less initial DNA damage. The lower ploidy cells in the parental cell population were identified as having radioresistance prior to irradiation; thus, SW480RR cells were considered intrinsically radioresistant cells selected from the parental population through fractionated irradiation. This study presents a practical example of the emergence of radioresistant cells from a cell population with ploidy heterogeneity after irradiation. The most likely mechanism is the selection of an intrinsically radioresistant population after fractionated X-ray irradiation, with a background in which lower ploidy cells exhibit lower initial DNA damage.

A chitosan-camouflaged nanomedicine triggered by hierarchically stimuli to release drug for multimodal imaging-guided chemotherapy of breast cancer

Breast cancer remains one of the most intractable diseases, especially the malignant form of metastasis, with which the cancer cells are hard to track and eliminate. Herein, the common known carbohydrate polymer chitosan (CS) was innovatively used as a shelter for the potent tumor-killing agent. The designed nanoparticles (NPs) not only enhance the solubility of hydrophobic paclitaxel (PTX), but also provide a "hide" effect for cytotoxic PTX in physiological condition. Moreover, coupled with the photothermal (PTT) properties of MoS2, results in a potent chemo/PTT platform. The MoS2@PTX-CS-K237 NPs have a uniform size (135 ± 17 nm), potent photothermal properties (η = 31.5 %), and environment-responsive (low pH, hypoxia) and near infrared (NIR) laser irradiation-triggered PTX release. Through a series of in vitro and in vivo experiments, the MoS2@PTX-CS-K237 showed high affinity and specificity for breast cancer cells, impressive tumor killing capacity, as well as the effective inhibitory effect of metastasis. Benefit from the unique optical properties of MoS2, this multifunctional nanomedicine also exhibited favorable thermal/PA/CT multimodality imaging effect on tumor-bearing mice. The system developed in this work represents the advanced design concept of hierarchical stimulus responsive drug release, and merits further investigation as a potential nanotheranostic platform for clinical translation.

Histology-Based Radiomics for [18F]FDG PET Identifies Tissue Heterogeneity in Pancreatic Cancer

Radiomics features can reveal hidden patterns in a tumor but usually lack an underlying biologic rationale. In this work, we aimed to investigate whether there is a correlation between radiomics features extracted from [18F]FDG PET images and histologic expression patterns of a glycolytic marker, monocarboxylate transporter-4 (MCT4), in pancreatic cancer. Methods: A cohort of pancreatic ductal adenocarcinoma patients (n = 29) for whom both tumor cross sections and [18F]FDG PET/CT scans were available was used to develop an [18F]FDG PET radiomics signature. By using immunohistochemistry for MCT4, we computed density maps of MCT4 expression and extracted pathomics features. Cluster analysis identified 2 subgroups with distinct MCT4 expression patterns. From corresponding [18F]FDG PET scans, radiomics features that associate with the predefined MCT4 subgroups were identified. Results: Complex heat map visualization showed that the MCT4-high/heterogeneous subgroup was correlating with a higher MCT4 expression level and local variation. This pattern linked to a specific [18F]FDG PET signature, characterized by a higher SUVmean and SUVmax and second-order radiomics features, correlating with local variation. This MCT4-based [18F]FDG PET signature of 7 radiomics features demonstrated prognostic value in an independent cohort of pancreatic cancer patients (n = 71) and identified patients with worse survival. Conclusion: Our cross-modal pipeline allows the development of PET scan signatures based on immunohistochemical analysis of markers of a particular biologic feature, here demonstrated on pancreatic cancer using intratumoral MCT4 expression levels to select [18F]FDG PET radiomics features. This study demonstrated the potential of radiomics scores to noninvasively capture intratumoral marker heterogeneity and identify a subset of pancreatic ductal adenocarcinoma patients with a poor prognosis.

Current trends and research topics regarding organoids: A bibliometric analysis of global research from 2000 to 2023

The use of animal models for biological experiments is no longer sufficient for research related to human life and disease. The development of organ tissues has replaced animal models by mimicking the structure, function, development and homeostasis of natural organs. This provides more opportunities to study human diseases such as cancer, infectious diseases and genetic disorders. In this study, bibliometric methods were used to analyze organoid-related articles published over the last 20+ years to identify emerging trends and frontiers in organoid research. A total of 13,143 articles from 4125 institutions in 86 countries or regions were included in the analysis. The number of papers increased steadily over the 20-year period. The United States was the leading country in terms of number of papers and citations. Harvard Medical School had the highest number of papers published. Keyword analysis revealed research trends and focus areas such as organ tissues, stem cells, 3D culture and tissue engineering. In conclusion, this study used bibliometric and visualization methods to explore the field of organoid research and found that organ tissues are receiving increasing attention in areas such as cancer, drug discovery, personalized medicine, genetic disease modelling and gene repair, making them a current research hotspot and a future research trend.

Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia

The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

The role of LOXL2 in tumor progression, immune response and cellular senescence: a comprehensive analysis

LOXL2, an enzyme belonging to the LOX family, facilitates the cross-linking of extracellular matrix (ECM) elements. However, the roles of the LOXL2 gene in mechanisms of oncogenesis and tumor development have not been clearly defined. In this pan-cancer study, we examined the notable disparity in LOXL2 expression at the mRNA and protein levels among various cancer types and elucidated its interconnected roles in tumor progression, mutational profile, immune response, and cellular senescence. Apart from investigating the hyperexpression of LOXL2 being related to poorer prognosis in different types of tumors, this study also unveiled noteworthy connections between LOXL2 and genetic mutations, infiltration of tumor immune cells, and genes in immune checkpoint pathways. Further analysis revealed the participation of LOXL2 in multiple pathways related to cancer extracellular matrix remodeling and cellular senescence. Moreover, our investigation uncovered that the knockdown and inhibition of LOXL2 significantly attenuated the proliferation and migration of PC-9 and HCC-LM3 cells. The knock-down and inhibition of LOXL2 enhanced cellular senescence in lung and liver cancer cells, as confirmed by SA-β-Gal staining and quantitative RT-PCR analyses. This comprehensive analysis offers valuable insights on the functions of LOXL2 in different types of cancer and its role in regulating the senescence of cancer cells.

Dark force rising: Reawakening and targeting of fetal-like stem cells in colorectal cancer

Stem cells play pivotal roles in maintaining intestinal homeostasis, orchestrating regeneration, and in key steps of colorectal cancer (CRC) initiation and progression. Intriguingly, adult stem cells are reduced during many of these processes. On the contrary, primitive fetal programs, commonly detected in development, emerge during tissue repair, CRC metastasis, and therapy resistance. Recent findings indicate a dynamic continuum between adult and fetal stem cell programs. We discuss critical mechanisms facilitating the plasticity between stem cell states and highlight the heterogeneity observed upon the appearance of fetal-like states. We focus on therapeutic opportunities that arise by targeting fetal-like CRC cells and how those concepts can be translated into the clinic.

Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors

Combination therapy is well established as a key intervention strategy for cancer treatment, with the potential to overcome monotherapy resistance and deliver a more durable efficacy. However, given the scale of unexplored potential target space and the resulting combinatorial explosion, identifying efficacious drug combinations is a critical unmet need that is still evolving. In this paper, we demonstrate a network biology-driven, simulation-based solution, the Simulated Cell™. Integration of omics data with a curated signaling network enables the accurate and interpretable prediction of 66,348 combination-cell line pairs obtained from a large-scale combinatorial drug sensitivity screen of 684 combinations across 97 cancer cell lines (BAC = 0.62, AUC = 0.7). We highlight drug combination pairs that interact with DNA Damage Response pathways and are predicted to be synergistic, and deep network insight to identify biomarkers driving combination synergy. We demonstrate that the cancer cell 'avatars' capture the biological complexity of their in vitro counterparts, enabling the identification of pathway-level mechanisms of combination benefit to guide clinical translatability.

Shaping the immune-suppressive microenvironment on tumor-associated myeloid cells through tumor-derived exosomes

Tumor-associated myeloid cells (TAMCs) play a crucial role in orchestrating the dynamics of the tumor immune microenvironment. This heterogeneous population encompasses myeloid-derived suppressor cells, tumor-associated macrophages and dendritic cells, all of which contribute to the establishment of an immunosuppressive milieu that fosters tumor progression. Tumor-derived exosomes (TEXs), small extracellular vesicles secreted by tumor cells, have emerged as central mediators in intercellular communication within the tumor microenvironment. In this comprehensive review, we explore the intricate mechanisms through which TEXs modulate immune-suppressive effects on TAMCs and their profound implications in cancer progression. We delve into the multifaceted ways in which TEXs influence TAMC functions, subsequently affecting tumor immune evasion. Furthermore, we elucidate various therapeutic strategies aimed at targeting TEX-mediated immune suppression, with the ultimate goal of bolstering antitumor immunity.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

Role and recent progress of P2Y12 receptor in cancer development

P2Y12 receptor (P2Y12R) is an adenosine-activated G protein-coupled receptor (GPCR) that plays a central role in platelet function, hemostasis, and thrombosis. P2Y12R activation can promote platelet aggregation and adhesion to cancer cells, promote tumor angiogenesis, and affect the tumor immune microenvironment (TIME) and tumor drug resistance, which is conducive to the progression of cancers. Meanwhile, P2Y12R inhibitors can inhibit this effect, suggesting that P2Y12R may be a potential therapeutic target for cancer. P2Y12R is involved in cancer development and metastasis, while P2Y12R inhibitors are effective in inhibiting cancer. However, a new study suggests that long-term use of P2Y12R inhibitors may increase the risk of cancer and the mechanism remains to be explored. In this paper, we reviewed the structural and functional characteristics of P2Y12R and its role in cancer. We explored the role of P2Y12R inhibitors in different tumors and the latest advances by summarizing the basic and clinical studies on the effects of P2Y12R inhibitors on tumors.

Risk score constructed with neutrophil extracellular traps-related genes predicts prognosis and immune microenvironment in multiple myeloma

Background

Multiple myeloma (MM) exhibits considerable heterogeneity in treatment responses and survival rates, even when standardized care is administered. Ongoing efforts are focused on developing prognostic models to predict these outcomes more accurately. Recently, neutrophil extracellular traps (NETs) have emerged as a potential factor in MM progression, sparking investigation into their role in prognostication.

Methods

In this study, a multi-gene risk scoring model was constructed using the intersection of NTEs and differentially expressed genes (DEGs), applying the least absolute shrinkage and selection operator (LASSO) Cox regression model. A nomogram was established, and the prognostic model's effectiveness was determined via Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were employed to evaluate the level of immune infiltration. The sensitivity of chemotherapy drugs was assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Ultimately, the presence of the detected genes was confirmed through quantitative real-time polymerase chain reaction (qRT-PCR) analysis in MM cell specimens.

Results

64 NETs-DEGs were yielded, and through univariate Cox regression and LASSO regression analysis, we constructed a risk score composed of six genes: CTSG, HSPE1, LDHA, MPO, PINK1, and VCAM1. MM patients in three independent datasets were classified into high- and low-risk groups according to the risk score. The overall survival (OS) of patients in the high-risk group was significantly reduced compared to the low-risk group. Furthermore, the risk score was an independent predictive factor for OS. In addition, interactions between the risk score, immune score, and immune cell infiltration were investigated. Further analysis indicated that patients in the high-risk group were more sensitive to a variety of chemotherapy and targeted drugs, including bortezomib. Moreover, the six genes provided insights into the progression of plasma cell disorders.

Conclusion

This study offers novel insights into the roles of NETs in prognostic prediction, immune status, and drug sensitivity in MM, serving as a valuable supplement and enhancement to existing grading systems.

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients

BACKGROUND

The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunotherapy response, based on the integration of deep learning and habitat radiomics in patients with advanced non-small cell lung cancer (NSCLC).

METHODS

Independent patient cohorts from three medical centers were enrolled for training (n = 164) and test (n = 82). Habitat imaging radiomics features were derived from sub-regions clustered from individual's tumor by K-means method. The deep learning features were extracted based on 3D ResNet algorithm. Pearson correlation coefficient, T test and least absolute shrinkage and selection operator regression were used to select features. Support vector machine was applied to implement deep learning and habitat radiomics, respectively. Then, a combination model was developed integrating both sources of data.

RESULTS

The combination model obtained a strong well-performance, achieving area under receiver operating characteristics curve of 0.865 (95% CI 0.772-0.931). The model significantly discerned high and low-risk patients, and exhibited a significant benefit in the clinical use.

CONCLUSION

The integration of deep-leaning and habitat radiomics contributed to predicting response to immunotherapy in patients with NSCLC. The developed integration model may be used as potential tool for individual immunotherapy management.

Exploiting cell death and tumor immunity in cancer therapy: challenges and future directions

Cancer remains a significant global challenge, with escalating incidence rates and a substantial burden on healthcare systems worldwide. Herein, we present an in-depth exploration of the intricate interplay between cancer cell death pathways and tumor immunity within the tumor microenvironment (TME). We begin by elucidating the epidemiological landscape of cancer, highlighting its pervasive impact on premature mortality and the pronounced burden in regions such as Asia and Africa. Our analysis centers on the pivotal concept of immunogenic cell death (ICD), whereby cancer cells succumbing to specific stimuli undergo a transformation that elicits robust anti-tumor immune responses. We scrutinize the mechanisms underpinning ICD induction, emphasizing the release of damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs) as key triggers for dendritic cell (DC) activation and subsequent T cell priming. Moreover, we explore the contributions of non-apoptotic RCD pathways, including necroptosis, ferroptosis, and pyroptosis, to tumor immunity within the TME. Emerging evidence suggests that these alternative cell death modalities possess immunogenic properties and can synergize with conventional treatments to bolster anti-tumor immune responses. Furthermore, we discuss the therapeutic implications of targeting the TME for cancer treatment, highlighting strategies to harness immunogenic cell death and manipulate non-apoptotic cell death pathways for therapeutic benefit. By elucidating the intricate crosstalk between cancer cell death and immune modulation within the TME, this review aims to pave the way for the development of novel cancer therapies that exploit the interplay between cell death mechanisms and tumor immunity and overcome Challenges in the Development and implementation of Novel Therapies.

Mouse Models for Head and Neck Squamous Cell Carcinoma

The prognosis and survival rate of head and neck squamous cell carcinoma (HNSCC) have remained unchanged for years, and the pathogenesis of HNSCC is still not fully understood, necessitating further research. An ideal animal model that accurately replicates the complex microenvironment of HNSCC is urgently needed. Among all the animal models for preclinical cancer research, tumor-bearing mouse models are the best known and widely used due to their high similarity to humans. Currently, mouse models for HNSCC can be broadly categorized into chemical-induced models, genetically engineered mouse models (GEMMs), and transplanted mouse models, each with its distinct advantages and limitations. In chemical-induced models, the carcinogen spontaneously initiates tumor formation through a multistep process. The resemblance of this model to human carcinogenesis renders it an ideal preclinical platform for studying HNSCC initiation and progression from precancerous lesions. The major drawback is that these models are time-consuming and, like human cancer, unpredictable in terms of timing, location, and number of lesions. GEMMs involve transgenic and knockout mice with gene modifications, leading to malignant transformation within a tumor microenvironment that recapitulates tumorigenesis in vivo, including their interaction with the immune system. However, most HNSCC GEMMs exhibit low tumor incidence and limited prognostic significance when translated to clinical studies. Transplanted mouse models are the most widely used in cancer research due to their consistency, availability, and efficiency. Based on the donor and recipient species matching, transplanted mouse models can be divided into xenografts and syngeneic models. In the latter, transplanted cells and host are from the same strain, making syngeneic models relevant to study functional immune system. In this review, we provide a comprehensive summary of the characteristics, establishment methods, and potential applications of these different HNSCC mouse models, aiming to assist researchers in choosing suitable animal models for their research.

Developing Engineered Nano-Immunopotentiators for the Stimulation of Dendritic Cells and Inhibition and Prevention of Melanoma

OBJECTIVE

This study aims to utilize PEGylated poly (lactic-co-glycolic acid) (PLGA) nanoparticles as a delivery system for simultaneous administration of the BRAFV600E peptide, a tumor-specific antigen, and imiquimod (IMQ). The objective is to stimulate dendritic cell (DC) maturation, activate macrophages, and facilitate antigen presentation in C57BL6 mice.

METHODS

PEG-PLGA-IMQ-BRAFV600E nanoparticles were synthesized using a PLGA-PEG-PLGA tri-block copolymer, BRAFV600E, and IMQ. Characterization included size measurement and drug release profiling. Efficacy was assessed in inhibiting BPD6 melanoma cell growth and activating immature bone marrow DCs, T cells, macrophages, and splenocyte cells through MTT and ELISA assays. In vivo, therapeutic and immunogenic effects potential was evaluated, comparing it to IMQ + BRAFV600E and PLGA-IMQ-BRAFV600E nanoparticles in inhibiting subcutaneous BPD6 tumor growth.

RESULTS

The results highlight the successful synthesis of PEG-PLGA-IMQ-BRAFV600E nanoparticles (203 ± 11.1 nm), releasing 73.4% and 63.2% of IMQ and BARFV600E, respectively, within the initial 48 h. In vitro, these nanoparticles demonstrated a 1.3-fold increase in potency against BPD6 cells, achieving ~ 2.8-fold enhanced cytotoxicity compared to PLGA-IMQ-BRAFV600E. Moreover, PEG-PLGA-IMQ-BRAFV600E exhibited a 1.3-fold increase in potency for enhancing IMQ cytotoxic effects and a 1.1- to ~ 2.4-fold increase in activating DCs, T cells, macrophages, and splenocyte cells compared to IMQ-BRAFV600E and PLGA-IMQ-BRAFV600E. In vivo, PEG-PLGA-IMQ-BRAFV600E displayed a 1.3- to 7.5-fold increase in potency for inhibiting subcutaneous BPD6 tumor growth compared to the other formulations.

CONCLUSIONS

The findings suggest that PEG-PLGA nanoparticles effectively promote DC maturation, T cell activation, and potentially macrophage activation. The study highlights the promising role of this nanocomposite in vaccine development.

Chaperonin-containing TCP-1 subunit genes are potential prognostic biomarkers and are correlated with Th2 cell infiltration in lung adenocarcinoma: An observational study

A family of molecular chaperone complexes called chaperonin-containing T-complex protein 1 (TCP-1) subunit genes (CCTs) aids in the folding of numerous proteins. With regard to lung adenocarcinoma (LUAD), this study provided a thorough understanding of the diagnostic and prognostic use of CCTs. The expression of CCTs in LUAD was evaluated by using databases including UALCAN and the Gene Expression Omnibus. Immunohistochemistry (IHC) was conducted to validate the expression of CCTs in LUAD. The mutation in the CCTs was identified through the cBioPortal database, while promoter methylation was measured by the UALCAN database. The prognostic value of CCTs was evaluated using the PrognoScan analysis. The GEPIA2.0 database was used to measure the prognostic value of CCTs and associated Hub genes. Correlation analysis between CCTs expression in LUAD was based on the GEPIA2.0 database. The ROC curves, clinical correlation analysis, gene ontology, Kyoto Encyclopedia of Genes and Genome analysis, and immune cell infiltration analysis were downloaded from The Cancer Genome Atlas database and then analyzed and visualized using the R language. The STRING database was used for protein-protein interaction analysis. Upregulation of CCTs expression in patients with LUAD indicated advanced diseases and a poor prognosis. ROC curve analysis revealed that the CCTs may serve as diagnostic indicators. The functional enrichment analysis showed that CCTs were involved in the mitosis-mediated cell cycle process. Additionally, 10 hub genes associated with CCTs that were linked to LUAD prognosis and tumor progression were identified. Immune cell infiltration analysis showed that CCTs expression in tumor tissues tends to be related to T helper type 2 cell infiltration. This study revealed that CCTs may serve as valuable biomarkers for the diagnosis and targeted therapy of LUAD.

Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges

Single-cell RNA sequencing (scRNA-Seq) is a recent technology that allows for the measurement of the expression of all genes in each individual cell contained in a sample. Information at the single-cell level has been shown to be extremely useful in many areas. However, performing single-cell experiments is expensive. Although cellular deconvolution cannot provide the same comprehensive information as single-cell experiments, it can extract cell-type information from bulk RNA data, and therefore it allows researchers to conduct studies at cell-type resolution from existing bulk datasets. For these reasons, a great effort has been made to develop such methods for cellular deconvolution. The large number of methods available, the requirement of coding skills, inadequate documentation, and lack of performance assessment all make it extremely difficult for life scientists to choose a suitable method for their experiment. This paper aims to fill this gap by providing a comprehensive review of 53 deconvolution methods regarding their methodology, applications, performance, and outstanding challenges. More importantly, the article presents a benchmarking of all these 53 methods using 283 cell types from 30 tissues of 63 individuals. We also provide an R package named DeconBenchmark that allows readers to execute and benchmark the reviewed methods (https://github.com/tinnlab/DeconBenchmark).

Cervical extracellular matrix hydrogel optimizes tumor heterogeneity of cervical squamous cell carcinoma organoids

Cervical cancer, primarily squamous cell carcinoma, is the most prevalent gynecologic malignancy. Organoids can mimic tumor development in vitro, but current Matrigel inaccurately replicates the tissue-specific microenvironment. This limitation compromises the accurate representation of tumor heterogeneity. We collected para-cancerous cervical tissues from patients diagnosed with cervical squamous cell carcinoma (CSCC) and prepared uterine cervix extracellular matrix (UCEM) hydrogels. Proteomic analysis of UCEM identified several tissue-specific signaling pathways including human papillomavirus, phosphatidylinositol 3-kinase-AKT, and extracellular matrix receptor. Secreted proteins like FLNA, MYH9, HSPA8, and EEF1A1 were present, indicating UCEM successfully maintained cervical proteins. UCEM provided a tailored microenvironment for CSCC organoids, enabling formation and growth while preserving tumorigenic potential. RNA sequencing showed UCEM-organoids exhibited greater similarity to native CSCC and reflected tumor heterogeneity by exhibiting CSCC-associated signaling pathways including virus protein-cytokine, nuclear factor κB, tumor necrosis factor, and oncogenes EGR1, FPR1, and IFI6. Moreover, UCEM-organoids developed chemotherapy resistance. Our research provides insights into advanced organoid technology through native matrix hydrogels.

Characterization and classification of ductal carcinoma tissue using four channel based stokes-mueller polarimetry and machine learning

Interaction of polarized light with healthy and abnormal regions of tissue reveals structural information associated with its pathological condition. Even a slight variation in structural alignment can induce a change in polarization property, which can play a crucial role in the early detection of abnormal tissue morphology. We propose a transmission-based Stokes-Mueller microscope for quantitative analysis of the microstructural properties of the tissue specimen. The Stokes-Mueller based polarization microscopy provides significant structural information of tissue through various polarization parameters such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP), anisotropy (r) and Mueller decomposition parameters such as diattenuation, retardance and depolarization. Further, by applying a suitable image processing technique such as Machine learning (ML) output images were analysed effectively. The support vector machine image classification model achieved 95.78% validation accuracy and 94.81% testing accuracy with polarization parameter dataset. The study's findings demonstrate the potential of Stokes-Mueller polarimetry in tissue characterization and diagnosis, providing a valuable tool for biomedical applications.

A photo-responsive self-healing hydrogel loaded with immunoadjuvants and MoS2 nanosheets for combating post-resection breast cancer recurrence

Tumor recurrence after surgical resection remains a significant challenge in breast cancer treatment. Immune checkpoint blockade therapy, as a promising alternative therapy, faces limitations in combating tumor recurrence due to the low immune response rate. In this study, we developed an implantable photo-responsive self-healing hydrogel loaded with MoS2 nanosheets and the immunoadjuvant R837 (PVA-MoS2-R837, PMR hydrogel) for in situ generation of tumor-associated antigens at the post-surgical site of the primary tumor, enabling sustained and effective activation of the immune response. This PMR hydrogel exhibited potential for near-infrared (NIR) light response, tissue adhesion, self-healing, and sustained adjuvant release. When implanted at the site after tumor resection, NIR irradiation triggered a photothermal effect, resulting in the ablation of residual cancer cells. The in situ-generated tumor-associated antigens promoted dendritic cell (DC) maturation. In a mouse model, PMR hydrogel-mediated photothermal therapy combined with immune checkpoint blockade effectively inhibited the recurrence of resected tumors, providing new insights for combating post-resection breast cancer recurrence.

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Oxygen-Independent Radiodynamic Therapy: Radiation-Boosted Chemodynamics for Reprogramming the Tumor Immune Environment and Enhancing Antitumor Immune Response

Radiodynamic therapy (RDT) has emerged as a promising modality for cancer treatment, offering notable advantages such as deep tissue penetration and radiocatalytic generation of oxygen free radicals. However, the oxygen-dependent nature of RDT imposes limitations on its efficacy in hypoxic conditions, particularly in modulating and eliminating radioresistant immune suppression cells. A novel approach involving the creation of a "super" tetrahedron polyoxometalate (POM) cluster, Fe12-POM, has been developed for radiation boosted chemodynamic catalysis to enable oxygen-independent RDT in hypoxic conditions. This nanoscale cluster comprises four P2W15 units functioning as energy antennas, while the Fe3 core serves as an electron receptor and catalytic center. Under X-ray radiation, a metal-to-metal charge transfer phenomenon occurs between P2W15 and the Fe3 core, resulting in the valence transition of Fe3+ to Fe2+ and a remarkable 139-fold increase in hydroxyl radical generation compared to Fe12-POM alone. The rapid generation of hydroxyl radicals, in combination with PD-1 therapy, induces a reprogramming of the immune environment within tumors. This reprogramming is characterized by upregulation of CD80/86, downregulation of CD163 and FAP, as well as the release of interferon-γ and tumor necrosis factor-α. Consequently, the occurrence of abscopal effects is facilitated, leading to significant regression of both local and distant tumors in mice. The development of oxygen-independent RDT represents a promising approach to address cancer recurrence and improve treatment outcomes.

Colony-stimulating factor-1 receptor inhibition combined with paclitaxel exerts effective antitumor effects in the treatment of ovarian cancer

Ovarian cancer is the tumor with the highest mortality among gynecological malignancies. Studies have confirmed that paclitaxel chemoresistance is associated with increased infiltration of tumor-associated macrophages (TAMs) in the microenvironment. Colony-stimulating factor 1 (CSF-1) receptor (CSF-1R) plays a key role in regulating the number and differentiation of macrophages in certain solid tumors. There are few reports on the effects of targeted inhibition of CSF-1R in combination with chemotherapy on ovarian cancer and the tumor microenvironment. Here, we explored the antitumor efficacy and possible mechanisms of the CSF - 1R inhibitor pexidartinib (PLX3397) when combined with the first-line chemotherapeutic agent paclitaxel in the treatment of ovarian cancer. We found that CSF-1R is highly expressed in ovarian cancer cells and correlates with poor prognosis. Treatment by PLX3397 in combination with paclitaxel significantly inhibited the growth of ovarian cancer both in vitro and in vivo. Blockade of CSF-1R altered the macrophage phenotype and reprogrammed the immunosuppressive cell population in the tumor microenvironment.

High-multiplex single-cell imaging analysis reveals tumor immune contexture associated with clinical outcomes after CAR T cell therapy

Chimeric antigen receptor (CAR) T cell therapy has made great progress in treating lymphoma, yet patient outcomes still vary greatly. The lymphoma microenvironment may be an important factor in the efficacy of CAR T therapy. In this study, we designed a highly multiplexed imaging mass cytometry (IMC) panel to simultaneously quantify 31 biomarkers from 13 patients with relapsed/refractory diffuse large B cell lymphoma (DLBCL) who received CAR19/22 T cell therapy. A total of 20 sections were sampled before CAR T cell infusion or after infusion when relapse occurred. A total of 35 cell clusters were identified, annotated, and subsequently redefined into 10 metaclusters. The CD4+ T cell fraction was positively associated with remission duration. Significantly higher Ki67, CD57, and TIM3 levels and lower CD69 levels in T cells, especially the CD8+/CD4+ Tem and Te cell subsets, were seen in patients with poor outcomes. Cellular neighborhood containing more immune cells was associated with longer remission. Fibroblasts and vascular endothelial cells resided much closer to tumor cells in patients with poor response and short remission after CAR T therapy. Our work comprehensively and systematically dissects the relationship between cell composition, state, and spatial arrangement in the DLBCL microenvironment and the outcomes of CAR T cell therapy, which is beneficial to predict CAR T therapy efficacy.

Assessing drug uptake and response differences in 2D and 3D cellular environments using stimulated Raman scattering microscopy

The architecture of cell culture-two-dimensional (2D) versus three-dimensional (3D)-significantly impacts various cellular factors, including cell-cell interactions, nutrient and oxygen gradients, metabolic activity, and gene expression profiles. This can result in different cellular responses during cancer drug treatment, with 3D-cultured cells often exhibiting higher resistance to chemotherapeutic drugs. While various genetic and proteomic analyses have been employed to investigate the underlying mechanisms of this increased resistance, complementary techniques that provide experimental evidence of spatial molecular profiling data are limited. Stimulated Raman scattering (SRS) microscopy has demonstrated its capability to measure both intracellular drug uptake and growth inhibition. In this work, we applied three-band SRS imaging to 2D and 3D cell cultures and provided a comparative analysis of drug uptake and response with the goal of understanding whether the difference in drug uptake explains the drug resistance in 3D culture compared to 2D. Our investigations revealed that despite similar intracellular drug levels in 2D and 3D A549 cells during lapatinib treatment, the growth of 3D spheroids is less impacted, supporting an enhanced drug tolerance in the 3D microenvironment. We further elucidated drug penetration patterns and the resulting heterogeneous cellular responses across different spheroid layers. Additionally, we investigated the role of the extracellular matrix in modulating drug delivery and cell response, and we discovered that limited drug penetration in 3D could also contribute to lower drug response. Our study provides valuable insights into the intricate mechanisms of increased drug resistance in 3D tumor models during cancer drug treatments.

Drug repurposing for cancer therapy

Cancer, a complex and multifactorial disease, presents a significant challenge to global health. Despite significant advances in surgical, radiotherapeutic and immunological approaches, which have improved cancer treatment outcomes, drug therapy continues to serve as a key therapeutic strategy. However, the clinical efficacy of drug therapy is often constrained by drug resistance and severe toxic side effects, and thus there remains a critical need to develop novel cancer therapeutics. One promising strategy that has received widespread attention in recent years is drug repurposing: the identification of new applications for existing, clinically approved drugs. Drug repurposing possesses several inherent advantages in the context of cancer treatment since repurposed drugs are typically cost-effective, proven to be safe, and can significantly expedite the drug development process due to their already established safety profiles. In light of this, the present review offers a comprehensive overview of the various methods employed in drug repurposing, specifically focusing on the repurposing of drugs to treat cancer. We describe the antitumor properties of candidate drugs, and discuss in detail how they target both the hallmarks of cancer in tumor cells and the surrounding tumor microenvironment. In addition, we examine the innovative strategy of integrating drug repurposing with nanotechnology to enhance topical drug delivery. We also emphasize the critical role that repurposed drugs can play when used as part of a combination therapy regimen. To conclude, we outline the challenges associated with repurposing drugs and consider the future prospects of these repurposed drugs transitioning into clinical application.

The use of microphysiological systems to model metastatic cancer

Cancer is one of the leading causes of death in the 21st century, with metastasis of cancer attributing to 90% of cancer-related deaths. Therefore, to improve patient outcomes there is a need for better preclinical models to increase the success of translating oncological therapies into the clinic. Current traditional staticin vitromodels lack a perfusable network which is critical to overcome the diffusional mass transfer limit to provide a mechanism for the exchange of essential nutrients and waste removal, and increase their physiological relevance. Furthermore, these models typically lack cellular heterogeneity and key components of the immune system and tumour microenvironment. This review explores rapidly developing strategies utilising perfusable microphysiological systems (MPS) for investigating cancer cell metastasis. In this review we initially outline the mechanisms of cancer metastasis, highlighting key steps and identifying the current gaps in our understanding of the metastatic cascade, exploring MPS focused on investigating the individual steps of the metastatic cascade before detailing the latest MPS which can investigate multiple components of the cascade. This review then focuses on the factors which can affect the performance of an MPS designed for cancer applications with a final discussion summarising the challenges and future directions for the use of MPS for cancer models.

Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma

Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.

Respiratory complex I regulates dendritic cell maturation in explant model of human tumor immune microenvironment

BACKGROUND

Combining cytotoxic chemotherapy or novel anticancer drugs with T-cell modulators holds great promise in treating advanced cancers. However, the response varies depending on the tumor immune microenvironment (TIME). Therefore, there is a clear need for pharmacologically tractable models of the TIME to dissect its influence on mono- and combination treatment response at the individual level.

METHODS

Here we establish a patient-derived explant culture (PDEC) model of breast cancer, which retains the immune contexture of the primary tumor, recapitulating cytokine profiles and CD8+T cell cytotoxic activity.

RESULTS

We explored the immunomodulatory action of a synthetic lethal BCL2 inhibitor venetoclax+metformin drug combination ex vivo, discovering metformin cannot overcome the lymphocyte-depleting action of venetoclax. Instead, metformin promotes dendritic cell maturation through inhibition of mitochondrial complex I, increasing their capacity to co-stimulate CD4+T cells and thus facilitating antitumor immunity.

CONCLUSIONS

Our results establish PDECs as a feasible model to identify immunomodulatory functions of anticancer drugs in the context of patient-specific TIME.

Pathways and molecules for overcoming immunotolerance in metastatic gastrointestinal tumors

Worldwide, gastrointestinal (GI) cancer is recognized as one of the leading malignancies diagnosed in both genders, with mortality largely attributed to metastatic dissemination. It has been identified that in GI cancer, a variety of signaling pathways and key molecules are modified, leading to the emergence of an immunotolerance phenotype. Such modifications are pivotal in the malignancy's evasion of immune detection. Thus, a thorough analysis of the pathways and molecules contributing to GI cancer's immunotolerance is vital for advancing our comprehension and propelling the creation of efficacious pharmacological treatments. In response to this necessity, our review illuminates a selection of groundbreaking cellular signaling pathways associated with immunotolerance in GI cancer, including the Phosphoinositide 3-kinases/Akt, Janus kinase/Signal Transducer and Activator of Transcription 3, Nuclear Factor kappa-light-chain-enhancer of activated B cells, Transforming Growth Factor-beta/Smad, Notch, Programmed Death-1/Programmed Death-Ligand 1, and Wingless and INT-1/beta-catenin-Interleukin 10. Additionally, we examine an array of pertinent molecules like Indoleamine-pyrrole 2,3-dioxygenase, Human Leukocyte Antigen G/E, Glycoprotein A Repetitions Predominant, Clever-1, Interferon regulatory factor 8/Osteopontin, T-cell immunoglobulin and mucin-domain containing-3, Carcinoembryonic antigen-related cell adhesion molecule 1, Cell division control protein 42 homolog, and caspases-1 and -12.

GTADC: A Graph-Based Method for Inferring Cell Spatial Distribution in Cancer Tissues

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.

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.

JAML inhibits colorectal carcinogenesis by modulating the tumor immune microenvironment

It is necessary to explore new targets for the treatment of colon adenocarcinoma (COAD) according to the tumor microenvironment. The expression levels of JAML and CXADR were analyzed by bioinformatics analysis and validation of clinical samples. JAML over-expression CD8+ T cell line was constructed, and the proliferation activity was detected by MTT. The production of inflammatory factors was detected by ELISA. The expression of immune checkpoint PD-1 and TIM-3 was detected by Western blot. The apoptosis level was detected by flow cytometry and apoptosis markers. The AOM/DSS mouse model of colorectal cancer was constructed. The expression levels of JAML, CXADR and PD-1 were detected by PCR and Western blot, and the proportion of CD8+ T cells and exhausted T cells were detected by flow cytometry. The expression levels of JAML and CXADR were significantly decreased in colon cancer tissues. Overexpression of JAML can promote the proliferation of T cells, secrete a variety of inflammatory factors. Overexpression of CXADR can reduce the proliferation of colorectal cancer cells, promote apoptosis, and down-regulate the migration and invasion ability of tumor cells. Both JAML agonists and PD-L1 inhibitors can effectively treat colorectal cancer, and the combined use of JAML agonists and PD-L1 inhibitors can enhance the effect. JAML can promote the proliferation and toxicity of CD8+ T cells and down-regulate the expression of immune checkpoints in colon cancer. CXADR can inhibit the proliferation of cancer cells and promote the apoptosis. JAML agonist can effectively treat colorectal cancer by regulating CD8+ T cells.

Distinctly altered lipid components in hepatocellular carcinoma relate to impaired T cell-dependent antitumor immunity

BACKGROUND AND AIMS

T cells are master effectors of anti-tumor immunity in cancer. Recent studies suggest that altered lipid metabolism imposed by the tumor microenvironment constrains anti-tumor immunity. However, the tumor-associated lipid species changes that dampen T cell ability to control tumor progression are not fully understood. Here, we plan to clarify the influences of distinctly altered lipid components in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) on T-cell function, aiming to seek lipid metabolic targets for improving T cell anti-tumor effects.

METHODS

Tumor tissues and non-tumor liver from HCC patients were collected for RNA-sequencing, lipid profiling and T cell characterizing, followed by correlation analysis. Additionally, the effects of significantly changed lipid components on anti-tumor potential of T cells were tested by in vitro cell experiments and/or in vivo tumor inoculated model.

RESULTS

Altered lipid metabolism coincides with impaired T cell response in HBV-related HCC. Characteristic lipid composition, significantly marked by accumulation of long-chain acylcarnitines (LCACs) and reduction of lysophosphatidylcholines (LPCs), are found in the tumor tissue. Notably, LCACs accumulated are associated with T cells exhaustion and deficient functionality, while LPCs correlate to anti-tumor effects of T cells. In particular, supplement of LPCs, including LPC (20:0) and LPC (22:0), directly promote the activation and IFN-γ secretion of T cells in vitro, and suppress tumor growth in vivo.

CONCLUSIONS

Our study highlights the distinctly changed lipid components closely related to T cell dysregulation in HCC, and suggests a promising strategy by decreasing LCACs and increasing LPCs for anti-tumor immunotherapy.

USP7 inhibitors suppress tumour neoangiogenesis and promote synergy with immune checkpoint inhibitors by downregulating fibroblast VEGF

BACKGROUND

Understanding how to modulate the microenvironment of tumors that are resistant to immune checkpoint inhibitors represents a major challenge in oncology.Here we investigate the ability of USP7 inhibitors to reprogram the tumor microenvironment (TME) by inhibiting secretion of vascular endothelial growth factor (VEGF) from fibroblasts.

METHODS

To understand the role played by USP7 in the TME, we systematically evaluated the effects of potent, selective USP7 inhibitors on co-cultures comprising components of the TME, using human primary cells. We also evaluated the effects of USP7 inhibition on tumor growth inhibition in syngeneic models when dosed in combination with immune checkpoint inhibitors (ICIs).

RESULTS

Abrogation of VEGF secretion from fibroblasts in response to USP7 inhibition resulted in inhibition of tumor neoangiogenesis and increased tumor recruitment of CD8-positive T-lymphocytes, leading to significantly improved sensitivity to immune checkpoint inhibitors. In syngeneic models, treatment with USP7 inhibitors led to striking tumor responses resulting in significantly improved survival.

CONCLUSIONS

USP7-mediated reprograming of the TME is not linked to its previously characterized role in modulating MDM2 but does require p53 and UHRF1 in addition to the well-characterized VEGF transcription factor, HIF-1α. This represents a function of USP7 that is unique to fibroblasts, and which is not observed in cancer cells or other components of the TME. Given the potential for USP7 inhibitors to transform "immune desert" tumors into "immune responsive" tumors, this paves the way for a novel therapeutic strategy combining USP7 inhibitors with immune checkpoint inhibitors (ICIs).

Single cell analysis unveils the commonality and heterogeneity between nasopharyngeal and oropharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) and oropharyngeal carcinoma (OPC) are subtypes of head and neck cancer with different treatment effects due to the heterogeneity of tumor microenvironments. This study was to investigate the distinctive tumor microenvironments of NPC and OPC. Analyzing single-cell data from 10 cases of each subtype, we reveal significant differences in cellular composition, with NPC microenvironment dominated by T/NK and B cells, and OPC characterized by prevalent epithelial cells and fibroblasts. Dynamic transitions of CD8 T cells are observed in both tumor types, involving shifts from naivety to cytotoxicity, proliferation, and eventual exhaustion/exhausted states. Additionally, Tregs exhibit heightened proliferative abilities in later developmental stages, concomitant with exhaustion. These highly proliferative T cells and Tregs manifest elevated glycolysis and lactate metabolism activities. Furthermore, we explore intercellular communication between glycolytic malignant epithelial cells and these proliferative T cells. These findings offer comprehensive insights into the heterogeneity of tumor microenvironments and provide a solid foundation for future therapeutic strategies and targeted interventions.

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

Mimicking angiogenic microenvironment of alveolar soft-part sarcoma in a microfluidic coculture vasculature chip

Alveolar soft-part sarcoma (ASPS) is a slow-growing soft tissue sarcoma with high mortality rates that affects adolescents and young adults. ASPS resists conventional chemotherapy; thus, decades of research have elucidated pathogenic mechanisms driving the disease, particularly its angiogenic capacities. Integrated blood vessels that are rich in pericytes (PCs) and metastatic potential are distinctive of ASPS. To mimic ASPS angiogenic microenvironment, a microfluidic coculture vasculature chip has been developed as a three-dimensional (3D) spheroid composed of mouse ASPS, a layer of PCs, and endothelial cells (ECs). This ASPS-on-a-chip provided functional and morphological similarity as the in vivo mouse model to elucidate the cellular crosstalk within the tumor vasculature before metastasis. We successfully reproduce ASPS spheroid and leaky vessels representing the unique tumor vasculature to assess effective drug delivery into the core of a solid tumor. Furthermore, this ASPS angiogenesis model enabled us to investigate the role of proteins in the intracellular trafficking of bioactive signals from ASPS to PCs and ECs during angiogenesis, including Rab27a and Sytl2. The results can help to develop drugs targeting the crosstalk between ASPS and the adjacent cells in the tumoral microenvironment.

Tumor Microenvironment-Activatable Nanosystem Capable of Overcoming Multiple Therapeutic Obstacles for Augmenting Immuno/Metal-Ion Therapy

Abnormal tumor microenvironment (TME) imposes barriers to nanomedicine penetration into tumors and evolves tumor-supportive nature to provide tumor cell protection, seriously weakening the action of antitumor nanomedicines and posing significant challenges to their development. Here, we engineer a TME-activatable size-switchable core-satellite nanosystem (Mn-TI-Ag@HA) capable of increasing the effective dose of therapeutic agents in deep-seated tumors while reversing tumor-supportive microenvironment for augmenting immuno/metal-ion therapy. When activated by TME, the nanosystem disintegrates, allowing ultrasmall-sized Ag nanoparticles to become unbound and penetrate deep into solid tumors. Simultaneously, the nanosystem produces O2 and releases TGF-β inhibitors in situ to drive macrophage M2-to-M1 polarization, increasing intratumoral H2O2 concentration, and ultimately augmenting metal-ion therapy by accelerating hypertoxic Ag+ production. The nanosystem can overcome multiple obstacles that aid in tumor resistance to nanomedicine, demonstrating effective tumor penetration, TME regulation, and tumor inhibition effects. It can provoke long-term immunological memory effects against tumor rechallenge when combined with immune checkpoint inhibitor anti-PD-1. This work provides a paradigm for designing efficient antitumor nanomedicines.