Influence of tumour micro-environment heterogeneity on therapeutic response

IGF2BP3 overexpression predicts poor prognosis and correlates with immune infiltration in bladder cancer

BACKGROUND

IGF2BP3 expression is associated with poor prognosis in cancers of multiple tissue origins. However, the precise mechanism of its co-carcinogenic action in bladder cancer is unknown.

METHODS

We aimed to demonstrate the relationship between IGF2BP3 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. We next validated IGF2BP3 expression in the Gene Expression Omnibus (GEO) database (GSE3167). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic values of IGF2BP3. Cox and logistic regression were used to explore the factors affecting the prognosis. Protein-protein interactions (PPIs) network was constructed by STRING. Enrichment analyses were performed to infer involved pathways and functional categories of IGF2BP3 using the cluster Profiler package. We applied single-sample gene set enrichment analysis (ssGSEA) algorithm and TIMER database to evaluate the expression level of immune genes.

RESULTS

Pan-cancer analyses reveal that IGF2BP3 was higher in most cancer types, including bladder cancer, and the same results were found in GSE3167. The area under the ROC curve of IGF2BP3 was 0.736, which indicated that IGF2BP3 may be a potential diagnostic biomarker. High IGF2BP3 expression was associated with poorer overall survival (OS) (P = 0.015). For validation, we collected 95 bladder cancer samples and found that IGF2BP3 expression was higher in bladder cancer tissues than that in non-tumor bladder tissues by immunohistochemistry staining. We found a positive correlation between the expression level of IGF2BP3 and the clinical stage of bladder cancer. Immunocyte infiltration analysis showed that high IGF2BP3 expression was correlated with regulating the infiltration level of immune cell, including neutrophil cells and macrophages. IGF2BP3 promotes migration and invasion of bladder cancer cells, while IGF2BP3 inhibition had the opposite effects. Higher IGF2BP3 expression was closely associated with advanced TNM stage.

CONCLUSION

IGF2BP3 overexpression was related to disease progression and poor prognosis, as well as infiltration of immune cells in bladder cancer. IGF2BP3 can be a promising independent prognostic biomarker and potential treatment target for bladder cancer.

Heterogeneity of cGMP signalling in tumour cells and the tumour microenvironment: Challenges and chances for cancer pharmacology and therapeutics

The second messenger cyclic guanosine monophosphate (cGMP) is an important regulator of human (patho-)physiology and has emerged as an attractive drug target. Currently, cGMP-elevating drugs are mainly used to treat cardiovascular diseases, but there is also increasing interest in exploring their potential for cancer prevention and therapy. In this review article, we summarise recent findings in cancer-related cGMP research, with a focus on melanoma, breast cancer, colorectal cancer, prostate cancer, glioma, and ovarian cancer. These studies indicate tremendous heterogeneity of cGMP signalling in tumour tissue. It appears that different tumour and stroma cells, and perhaps different sexes, express different cGMP generators, effectors, and degraders. Therefore, the same cGMP-elevating drug can lead to different outcomes in different tumour settings, ranging from inhibition to promotion of tumourigenesis or therapy resistance. These findings, together with recent evidence that increased cGMP signalling is associated with worse prognosis in several human cancers, challenge the traditional view that cGMP elevation generally has an anti-cancer effect. As cGMP pathways appear to be more stable in the stroma than in tumour cells, we suggest that cGMP-modulating drugs should preferentially target the tumour microenvironment. Indeed, there is evidence that phosphodiesterase 5 inhibitors like sildenafil enhance anti-tumour immunity by acting on immune cells. Moreover, many in vivo results obtained with cGMP-modulating drugs could be explained by effects on the tumour vasculature rather than on the tumour cells themselves. We therefore propose a model that incorporates the NO/cGMP signalling pathway in tumour vessels as a key target for cancer therapy. Deciphering the multifaceted roles of cGMP in cancer is not only a challenge for basic research, but also provides a chance to predict potential adverse effects of cGMP-modulating drugs in cancer patients and to develop novel anti-tumour therapies by precision targeting of the relevant cells and molecular pathways.

Rational Design of a Triple Tumor Microenvironment-Responsive Nanoplatform for Enhanced Tumor Theranostics

The development of responsive nanoplatforms based on the tumor microenvironment (TME) is critical for tumor diagnosis and treatment. Concentrating on a single TME-responsive nanoplatform, however, may result in insufficient diagnostic accuracy and treatment efficacy. Herein, layered double-hydroxides (LDHs) and rare earth nanomaterials (Er@Lu) were combined to create a triple TME-responsive nanoplatform that was then modified with cypate (a fluorescent dye with strong absorbance) by a peptide chain and loaded with epigallocatechin gallate (EGCG), a chemotherapeutic drug. Multiple responses to TME occurred when Er@Lu/LDH-EGCG reached the colorectal tumor region. Based on an acidic TME, the nanoplatform cracked and released Ni²⁺ and EGCG. NiS, which was produced by the reaction of Ni²⁺ with abundant H₂ S in tumor cells, was used for photothermal therapy and the released EGCG was used for chemotherapy. The MMP-7 enzyme specifically expressed in tumor cells recognized and cut the peptide chain, resulting in cypate release. The fluorescence of the Er@Lu was then restored along with the release of cypate because of the absorption competition disappearance. Compared to a single TME response, Er@Lu/LDH-EGCG with a triple TME response led to a better synergistic therapeutic effect in vitro and in vivo. This work has provided new approaches for developing multiple TME-responsive therapeutic nanoplatforms for synergistic therapy with improved diagnosis and therapeutic efficiency.

Expression of the prognostic marker IL-8 correlates with the immune signature and epithelial-mesenchymal transition in breast cancer

BACKGROUND

IL-8 has been implicated in the malignant progression of various types of cancers; however, the precise molecular mechanisms associated with IL-8 in breast cancer (BRCA) are unclear.

METHODS

We analyzed the clinical signature and immune characteristics of BRCA patients and its correlation with IL-8 expression using The Cancer Genome Atlas (TCGA) datasets. The role of IL-8 in epithelial-mesenchymal transition (EMT) was verified through Western blotting, Cell Counting Kit-8 assay, and wound healing assays, as well as cell invasion experiments.

RESULTS

Through a comprehensive bioinformatics study, we determined that high IL-8 expression was associated with poor prognosis. Enrichment analysis revealed that high IL-8 expression was enriched in immune-related processes and cancer-related signaling pathways. In addition, IL-8 was associated with most of the immune-infiltrating cells, and high IL-8 expression indicated poor response to immunotherapy. Importantly, we found that IL-8 induced EMT in vitro.

CONCLUSIONS

Taken together, our data indicate that IL-8 may be a potential and valuable prognostic marker in BRCA, which may induce adverse outcomes by modulating the immune response and promoting EMT in BRCA patients.

Tuned activation of MSLN-CAR T cells induces superior antitumor responses in ovarian cancer models

BACKGROUND

Limited persistence of functional CAR T cells in the immunosuppressive solid tumor microenvironment remains a major hurdle in the successful translation of CAR T cell therapy to treat solid tumors. Fine-tuning of CAR T cell activation by mutating CD3ζ chain immunoreceptor tyrosine-based activation motifs (ITAMs) in CD19-CAR T cells (containing the CD28 costimulatory domain) has proven to extend functional CAR T cell persistence in preclinical models of B cell malignancies.

METHODS

In this study, two conventional second-generation MSLN-CAR T cell constructs encoding for either a CD28 co-stimulatory (M28z) or 4-1BB costimulatory (MBBz) domain and a novel mesothelin (MSLN)-directed CAR T cell construct encoding for the CD28 costimulatory domain and CD3ζ chain containing a single ITAM (M1xx) were evaluated using in vitro and in vivo preclinical models of ovarian cancer. Two ovarian cancer cell lines and two orthotopic models of ovarian cancer in NSG mice were used: SKOV-3 cells inoculated through microsurgery in the ovary and to mimic a disseminated model of advanced ovarian cancer, OVCAR-4 cells injected intraperitoneally. MSLN-CAR T cell treatment efficacy was evaluated by survival analysis and the characterization and quantification of the different MSLN-CAR T cells were performed by flow cytometry, quantitative PCR and gene expression analysis.

RESULTS

M1xx CAR T cells elicited superior antitumor potency and persistence, as compared with the conventional second generation M28z and MBBz CAR T cells. Ex vivo M28z and MBBz CAR T cells displayed a more exhausted phenotype than M1xx CAR T cells as determined by co-expression of PD-1, LAG-3 and TIM-3. Furthermore, M1xx CAR T cells showed superior ex vivo IFNy, TNF and GzB production and were characterized by a self-renewal gene signature.

CONCLUSIONS

Altogether, our study demonstrates the enhanced therapeutic potential of MSLN-CAR T cells expressing a mutated CD3ζ chain containing a single ITAM for the treatment of ovarian cancer. CAR T cells armored with calibrated activation potential may improve the clinical responses in solid tumors.

3D bioprinting and its innovative approach for biomedical applications

3D bioprinting or additive manufacturing is an emerging innovative technology revolutionizing the field of biomedical applications by combining engineering, manufacturing, art, education, and medicine. This process involved incorporating the cells with biocompatible materials to design the required tissue or organ model in situ for various in vivo applications. Conventional 3D printing is involved in constructing the model without incorporating any living components, thereby limiting its use in several recent biological applications. However, this uses additional biological complexities, including material choice, cell types, and their growth and differentiation factors. This state-of-the-art technology consciously summarizes different methods used in bioprinting and their importance and setbacks. It also elaborates on the concept of bioinks and their utility. Biomedical applications such as cancer therapy, tissue engineering, bone regeneration, and wound healing involving 3D printing have gained much attention in recent years. This article aims to provide a comprehensive review of all the aspects associated with 3D bioprinting, from material selection, technology, and fabrication to applications in the biomedical fields. Attempts have been made to highlight each element in detail, along with the associated available reports from recent literature. This review focuses on providing a single platform for cancer and tissue engineering applications associated with 3D bioprinting in the biomedical field.

Using CT radiomic features based on machine learning models to subtype adrenal adenoma

BACKGROUND

Functioning and non-functioning adrenocortical adenoma are two subtypes of benign adrenal adenoma, and their differential diagnosis is crucial. Current diagnostic procedures use an invasive method, adrenal venous sampling, for endocrinologic assessment.

METHODS

This study proposes establishing an accurate differential model for subtyping adrenal adenoma using computed tomography (CT) radiomic features and machine learning (ML) methods. Dataset 1 (289 patients with adrenal adenoma) was collected to develop the models, and Dataset 2 (54 patients) was utilized for external validation. Cuboids containing the lesion were cropped from the non-contrast, arterial, and venous phase CT images, and 1,967 features were extracted from each cuboid. Ten discriminative features were selected from each phase or the combined phases. Random forest, support vector machine, logistic regression (LR), Gradient Boosting Machine, and eXtreme Gradient Boosting were used to establish prediction models.

RESULTS

The highest accuracies were 72.7%, 72.7%, and 76.1% in the arterial, venous, and non-contrast phases, respectively, when using radiomic features alone with the ML classifier of LR. When features from the three CT phases were combined, the accuracy of LR reached 83.0%. After adding clinical information, the area under the receiver operating characteristic curve increased for all the machine learning methods except for LR. In Dataset 2, the accuracy of LR was the highest, reaching 77.8%.

CONCLUSION

The radiomic features of the lesion in three-phase CT images can potentially suggest the functioning or non-functioning nature of adrenal adenoma. The resulting radiomic models can be a non-invasive, low-cost, and rapid method of minimizing unnecessary testing in asymptomatic patients with incidentally discovered adrenal adenoma.

CAR-cell therapy in the era of solid tumor treatment: current challenges and emerging therapeutic advances

In the last decade, Chimeric Antigen Receptor (CAR)-T cell therapy has emerged as a promising immunotherapeutic approach to fight cancers. This approach consists of genetically engineered immune cells expressing a surface receptor, called CAR, that specifically targets antigens expressed on the surface of tumor cells. In hematological malignancies like leukemias, myeloma, and non-Hodgkin B-cell lymphomas, adoptive CAR-T cell therapy has shown efficacy in treating chemotherapy refractory patients. However, the value of this therapy remains inconclusive in the context of solid tumors and is restrained by several obstacles including limited tumor trafficking and infiltration, the presence of an immunosuppressive tumor microenvironment, as well as adverse events associated with such therapy. Recently, CAR-Natural Killer (CAR-NK) and CAR-macrophages (CAR-M) were introduced as a complement/alternative to CAR-T cell therapy for solid tumors. CAR-NK cells could be a favorable substitute for CAR-T cells since they do not require HLA compatibility and have limited toxicity. Additionally, CAR-NK cells might be generated in large scale from several sources which would suggest them as promising off-the-shelf product. CAR-M immunotherapy with its capabilities of phagocytosis, tumor-antigen presentation, and broad tumor infiltration, is currently being investigated. Here, we discuss the emerging role of CAR-T, CAR-NK, and CAR-M cells in solid tumors. We also highlight the advantages and drawbacks of CAR-NK and CAR-M cells compared to CAR-T cells. Finally, we suggest prospective solutions such as potential combination therapies to enhance the efficacy of CAR-cells immunotherapy.

The application of patient-derived organoid in the research of lung cancer

Lung cancer is the most common cancer and the leading cause of cancer-related death worldwide. However, mechanisms of its progression remained unclear and new treatments against this disease are rapidly emerging. As a novel preclinical model, patient-derived organoid (PDO) can also be established from the patient's tumor tissue and cultured in the laboratory, which preserves the key biological characteristics of the original tumor. Compared to the patient-derived xenograft (PDX) model of lung cancer, the culture success rate is improved, and the time and cost of model establishment are largely reduced. PDO is also expected to provide a more individual model to predict the efficacy of anti-cancer treatment in vitro. This paper summarizes the current application of PDO in the translational research of lung cancer.

Intratumoral heterogeneity affects tumor regression and Ki67 proliferation index in perioperatively treated gastric carcinoma

BACKGROUND

Intratumoral heterogeneity (ITH) is a major problem in gastric cancer (GC). We tested Ki67 and tumor regression for ITH after neoadjuvant/perioperative chemotherapy.

METHODS

429 paraffin blocks were obtained from 106 neoadjuvantly/perioperatively treated GCs (one to five blocks per case). Serial sections were stained with Masson's trichrome, antibodies directed against cytokeratin and Ki67, and finally digitalized. Tumor regression and three different Ki67 proliferation indices (PI), i.e., maximum PI (KiH), minimum PI (KiL), and the difference between KiH/KiL (KiD) were obtained per block. Statistics were performed in a block-wise (all blocks irrespective of their case-origin) and case-wise manner.

RESULTS

Ki67 and tumor regression showed extensive ITH in our series (maximum ITH within a case: 31% to 85% for KiH; 4.5% to 95.6% for tumor regression). In addition, Ki67 was significantly associated with tumor regression (p < 0.001). Responders (<10% residual tumor, p = 0.016) exhibited prolonged survival. However, there was no significant survival benefit after cut-off values were increased ≥20% residual tumor mass. Ki67 remained without prognostic value.

CONCLUSIONS

Digital image analysis in tumor regression evaluation might help overcome inter- and intraobserver variability and validate classification systems. Ki67 may serve as a sensitivity predictor for chemotherapy and an indicator of ITH.

Mitochondrial Metabolism in X-Irradiated Cells Undergoing Irreversible Cell-Cycle Arrest

Irreversible cell-cycle-arrested cells not undergoing cell divisions have been thought to be metabolically less active because of the unnecessary consumption of energy for cell division. On the other hand, they might be actively involved in the tissue microenvironment through an inflammatory response. In this study, we examined the mitochondria-dependent metabolism in human cells irreversibly arrested in response to ionizing radiation to confirm this possibility. Human primary WI-38 fibroblast cells and the BJ-5ta fibroblast-like cell line were exposed to 20 Gy X-rays and cultured for up to 9 days after irradiation. The mitochondrial morphology and membrane potential were evaluated in the cells using the mitochondrial-specific fluorescent reagents MitoTracker Green (MTG) and 5,5',6,6'-tetraethyl-benzimidazolylcarbocyanine iodide (JC-1), respectively. The ratio of the mean MTG-stained total mitochondrial area per unit cell area decreased for up to 9 days after X-irradiation. The fraction of the high mitochondrial membrane potential area visualized by JC-1 staining reached its minimum 2 days after irradiation and then increased (particularly, WI-38 cells increased 1.8-fold the value of the control). Their chronological changes indicate that the mitochondrial volume in the irreversible cell-cycle-arrested cells showed significant increase concurrently with cellular volume expansion, indicating that the mitochondria-dependent energy metabolism was still active. These results indicate that the energy metabolism in X-ray-induced senescent-like cells is active compared to nonirradiated normal cells, even though they do not undergo cell divisions.

The predictive value of neutrophil-to-lymphocyte ratio for overall survival and pathological complete response in breast cancer patients receiving neoadjuvant chemotherapy

Purpose

Previous studies have reported that neutrophil-to-lymphocyte ratio (NLR) at pre-treatment was predictive for overall survival (OS) and pathologic complete response (pCR) in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC). This study aims to explore the predictive role of both pre- and post-NLR for OS as well as longitudinal NLR kinetics towards pCR in BC patients undergoing NAC.

Methods

We retrospectively included 501 BC patients who received NAC from 2009 to 2018. NLR at pre-, mid (every two cycles of NAC)-, and post-treatment were collected. Overall, 421 patients were included in the survival analysis. These patients were randomly divided into a training cohort (n = 224) and a validation cohort (n = 197). A multivariable Cox model was built using all significant factors in the multivariable analysis from the training cohort. The performance of the model was verified in the validation cohort by the concordance index (C-index). Longitudinal analysis for pCR prediction of NLR was performed using a mixed-effects regression model among 176 patients who finished eight cycles of NAC.

Results

The median follow-up time was 43.2 months for 421 patients. In the training cohort, multivariable analysis revealed that ER status, clinical node stage, pCR, pre-NLR, and post-NLR (all p < 0.05) were independent predictors of OS. The OS nomogram was established based on these parameters. The C-indexes of the nomogram were 0.764 and 0.605 in the training and validation cohorts, respectively. In the longitudinal analysis, patients who failed to achieve pCR experienced an augment of NLR during NAC while NLR remained stable among patients with pCR. Pre-NLR tended to be significantly associated with OS in patients of HER2 overexpressing and TNBC subtypes (all p < 0.05), but not in Luminal A and Luminal B subtypes.

Conclusions

This study demonstrated the prognostic value of both pre-NLR and post-NLR on clinical outcomes in BC patients receiving NAC. A novel nomogram was established to predict OS. Non-pCR patients developed increased NLRs during NAC. Routine assessment of NLR may be a simple and affordable tool to predict prognosis for BC patients receiving NAC.

Traditional Chinese medicine for transformation of gastric precancerous lesions to gastric cancer: A critical review

Gastric cancer (GC) is a common gastrointestinal tumor. Gastric precancerous lesions (GPL) are the last pathological stage before normal gastric mucosa transforms into GC. However, preventing the transformation from GPL to GC remains a challenge. Traditional Chinese medicine (TCM) has been used to treat gastric disease for millennia. A series of TCM formulas and active compounds have shown therapeutic effects in both GC and GPL. This article reviews recent progress on the herbal drugs and pharmacological mechanisms of TCM in preventing the transformation from GPL to GC, especially focusing on anti-inflammatory, anti-angiogenesis, proliferation, and apoptosis. This review may provide a meaningful reference for the prevention of the transformation from GPL to GC using TCM.

Distinct but interchangeable subpopulations of colorectal cancer cells with different growth fates and drug sensitivity

Dynamic changes in cell properties lead to intratumor heterogeneity; however, the mechanisms of nongenetic cellular plasticity remain elusive. When the fate of each cell from colorectal cancer organoids was tracked through a clonogenic growth assay, the cells showed a wide range of growth ability even within the clonal organoids, consisting of distinct subpopulations; the cells generating large spheroids and the cells generating small spheroids. The cells from the small spheroids generated only small spheroids (S-pattern), while the cells from the large spheroids generated both small and large spheroids (D-pattern), both of which were tumorigenic. Transition from the S-pattern to the D-pattern occurred by various extrinsic triggers, in which Notch signaling and Musashi-1 played a key role. The S-pattern spheroids were resistant to chemotherapy and transited to the D-pattern upon drug treatment through Notch signaling. As the transition is linked to the drug resistance, it can be a therapeutic target.

Application of individualized multimodal radiotherapy combined with immunotherapy in metastatic tumors

Radiotherapy is one of the mainstays of cancer treatment. More than half of cancer patients receive radiation therapy. In addition to the well-known direct tumoricidal effect, radiotherapy has immunomodulatory properties. When combined with immunotherapy, radiotherapy, especially high-dose radiotherapy (HDRT), exert superior systemic effects on distal and unirradiated tumors, which is called abscopal effect. However, these effects are not always effective for cancer patients. Therefore, many studies have focused on exploring the optimized radiotherapy regimens to further enhance the antitumor immunity of HDRT and reduce its immunosuppressive effect. Several studies have shown that low-dose radiotherapy (LDRT) can effectively reprogram the tumor microenvironment, thereby potentially overcoming the immunosuppressive stroma induced by HDRT. However, bridging the gap between preclinical commitment and effective clinical delivery is challenging. In this review, we summarized the existing studies supporting the combined use of HDRT and LDRT to synergistically enhance antitumor immunity, and provided ideas for the individualized clinical application of multimodal radiotherapy (HDRT+LDRT) combined with immunotherapy.

Selective advantage of epigenetically disrupted cancer cells via phenotypic inertia

The evolution of established cancers is driven by selection of cells with enhanced fitness. Subclonal mutations in numerous epigenetic regulator genes are common across cancer types, yet their functional impact has been unclear. Here, we show that disruption of the epigenetic regulatory network increases the tolerance of cancer cells to unfavorable environments experienced within growing tumors by promoting the emergence of stress-resistant subpopulations. Disruption of epigenetic control does not promote selection of genetically defined subclones or favor a phenotypic switch in response to environmental changes. Instead, it prevents cells from mounting an efficient stress response via modulation of global transcriptional activity. This "transcriptional numbness" lowers the probability of cell death at early stages, increasing the chance of long-term adaptation at the population level. Our findings provide a mechanistic explanation for the widespread selection of subclonal epigenetic-related mutations in cancer and uncover phenotypic inertia as a cellular trait that drives subclone expansion.

Opportunities and challenges of hepatocellular carcinoma organoids for targeted drugs sensitivity screening

Hepatocellular carcinoma is one of the malignancies worldwide with a high mortality rate and an increasing incidence. Molecular Targeted agents are its common first-line treatment. Organoid technology, as a cutting-edge technology, is gradually being applied in the development of therapeutic oncology. Organoid models can be used to perform sensitivity screening of targeted drugs to facilitate the development of innovative therapeutic agents for the treatment of hepatocellular carcinoma. The purpose of this review is to provide an overview of the opportunities and challenges of hepatocellular carcinoma organoids in targeted drug sensitivity testing as well as a future outlook.

Knowledge atlas of antibody-drug conjugates on CiteSpace and clinical trial visualization analysis

Objective

Antibody-drugs conjugates (ADCs) are novel drugs with highly targeted and tumor-killing abilities and developing rapidly. This study aimed to evaluate drug discovery and clinical trials of and explore the hotspots and frontiers from 2012 to 2022 using bibliometric methods.

Methods

Publications on ADCs were retrieved between 2012 and 2022 from Web of Science (WoS) and analyzed with CiteSpace 6.1.R2 software for the time, region, journals, institutions, etc. Clinical trials were downloaded from clinical trial.org and visualized with Excel software.

Results

A total of 696 publications were obtained and 187 drug trials were retrieved. Since 2012, research on ADCs has increased year by year. Since 2020, ADC-related research has increased dramatically, with the number of relevant annual publications exceeding 100 for the first time. The United States is the most authoritative and superior country and region in the field of ADCs. The University of Texas MD Anderson Cancer Center is the most authoritative institution in this field. Research on ADCs includes two clinical trials and one review, which are the most influential references. Clinical trials of ADCs are currently focused on phase I and phase II. Comprehensive statistics and analysis of the published literature and clinical trials in the field of ADCs, have shown that the most studied drug is brentuximab vedotin (BV), the most popular target is human epidermal growth factor receptor 2 (HER2), and breast cancer may become the main trend and hotspot for ADCs indications in recent years.

Conclusion

Antibody-drug conjugates have become the focus of targeted therapies in the field of oncology. The innovation of technology and combination application strategy will become the main trend and hotspots in the future.

Signaling pathways in cancer-associated fibroblasts: recent advances and future perspectives

As a critical component of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) play important roles in cancer initiation and progression. Well-known signaling pathways, including the transforming growth factor-β (TGF-β), Hedgehog (Hh), Notch, Wnt, Hippo, nuclear factor kappa-B (NF-κB), Janus kinase (JAK)/signal transducer and activator of transcription (STAT), mitogen-activated protein kinase (MAPK), and phosphoinositide 3-kinase (PI3K)/AKT pathways, as well as transcription factors, including hypoxia-inducible factor (HIF), heat shock transcription factor 1 (HSF1), P53, Snail, and Twist, constitute complex regulatory networks in the TME to modulate the formation, activation, heterogeneity, metabolic characteristics and malignant phenotype of CAFs. Activated CAFs remodel the TME and influence the malignant biological processes of cancer cells by altering the transcriptional and secretory characteristics, and this modulation partially depends on the regulation of signaling cascades. The results of preclinical and clinical trials indicated that therapies targeting signaling pathways in CAFs demonstrated promising efficacy but were also accompanied by some failures (e.g., NCT01130142 and NCT01064622). Hence, a comprehensive understanding of the signaling cascades in CAFs might help us better understand the roles of CAFs and the TME in cancer progression and may facilitate the development of more efficient and safer stroma-targeted cancer therapies. Here, we review recent advances in studies of signaling pathways in CAFs and briefly discuss some future perspectives on CAF research.

Insights into the Oncogenic, Prognostic, and Immunological Role of BRIP1 in Pan-Cancer: A Comprehensive Data-Mining-Based Study

Background

BRCA1 interacting helicase 1 (BRIP1), an ATP-dependent DNA helicase which belongs to an Iron-Sulfur (Fe-S) helicase cluster family with a DEAH domain, plays a key role in DNA damage and repair, Fanconi anemia, and development of several cancers including breast and ovarian cancer. However, its role in pan-cancer remains largely unknown.

Methods

BRIP1 expression data of tumor and normal tissues were downloaded from the Cancer Genome Atlas, Genotype-Tissue Expression, and Human Protein Atlas databases. Correlation between BRIP1 and prognosis, genomic alterations, and copy number variation (CNV) as well as methylation in pan-cancer were further analyzed. Protein-protein interaction (PPI) and gene set enrichment and variation analysis (GSEA and GSVA) were performed to identify the potential pathways and functions of BRIP1. Besides, BRIP1 correlations with tumor microenvironment (TME), immune infiltration, immune-related genes, tumor mutation burden (TMB), microsatellite instability (MSI), and immunotherapy as well as antitumor drugs were explored in pan-cancer.

Results

Differential analyses showed an increased expression of BRIP1 in 28 cancer types and its aberrant expression could be an indicator for prognosis in most cancers. Among the various mutation types of BRIP1 in pan-cancer, amplification was the most common type. BRIP1 expression had a significant correlation with CNV and DNA methylation in 23 tumor types and 16 tumor types, respectively. PPI, GSEA, and GSVA results validated the association between BRIP1 and DNA damage and repair, cell cycle, and metabolism. In addition, the expression of BRIP1 and its correlation with TME, immune-infiltrating cells, immune-related genes, TMB, and MSI as well as a variety of antitumor drugs and immunotherapy were confirmed.

Conclusions

Our study indicates that BRIP1 plays an imperative role in the tumorigenesis and immunity of various tumors. It may not only serve as a diagnostic and prognostic biomarker but also can be a predictor for drug sensitivity and immunoreaction during antitumor treatment in pan-cancer.

Validation of an orthotopic non-small cell lung cancer mouse model, with left or right tumor growths, to use in conformal radiotherapy studies

Orthotopic non-small cell lung cancer (NSCLC) mice models are important for establishing translatability of in vitro results. However, most orthotopic lung models do not produce localized tumors treatable by conformal radiotherapy (RT). Here we report on the performance of an orthotopic mice model featuring conformal RT treatable tumors following either left or right lung tumor cell implantation. Athymic Nude mice were surgically implanted with H1299 NSCLC cell line in either the left or right lung. Tumor development was tracked bi-weekly using computed tomography (CT) imaging. When lesions reached an appropriate size for treatment, animals were separated into non-treatment (control group) and RT treated groups. Both RT treated left and right lung tumors which were given a single dose of 20 Gy of 225 kV X-rays. Left lung tumors were treated with a two-field parallel opposed plan while right lung tumors were treated with a more conformal four-field plan to assess tumor control. Mice were monitored for 30 days after RT or after tumor reached treatment size for non-treatment animals. Treatment images from the left and right lung tumor were also used to assess the dose distribution for four distinct treatment plans: 1) Two sets of perpendicularly staggered parallel opposed fields, 2) two fields positioned in the anterior-posterior and posterior-anterior configuration, 3) an 180° arc field from 0° to 180° and 4) two parallel opposed fields which cross through the contralateral lung. Tumor volumes and changes throughout the follow-up period were tracked by three different types of quantitative tumor size approximation and tumor volumes derived from contours. Ultimately, our model generated delineable and conformal RT treatable tumor following both left and right lung implantation. Similarly consistent tumor development was noted between left and right models. We were also able to demonstrate that a single 20 Gy dose of 225 kV X-rays applied to either the right or left lung tumor models had similar levels of tumor control resulting in similar adverse outcomes and survival. And finally, three-dimensional tumor approximation featuring volume computed from the measured length across three perpendicular axes gave the best approximation of tumor volume, most closely resembled tumor volumes obtained with contours.

Comprehensive Analysis of NABP2 as a Prognostic Biomarker and Its Correlation with Immune Infiltration in Hepatocellular Carcinoma

Background

The DNA binding protein NABP2 (nucleic acid binding protein 2) is a member of the SSB (single-stranded DNA-binding) protein family, which is involved in DNA damage repair. Its prognostic significance and relationship with immune infiltration in hepatocellular carcinoma (HCC), however, remain unknown.

Methods

The purpose of this study was to estimate the prognostic value of NABP2 and to investigate its possible immune function in HCC. By applying multiple bioinformatics methods, we gathered and analysed data from The Cancer Genome Atlas (TCGA), Cancer Cell Lineage Encyclopedia (CCLE), and Gene Expression Omnibus (GEO) to investigate the potential oncogenic and cancer-promoting role of NABP2, including the differential expression, prognostic value, immune cell infiltration association, and drug sensitivity of NABP2 in HCC. Immunohistochemistry and Western blotting were used to validate the expression of NABP2 in HCC. The knockdown of NABP2 expression by siRNA was further used to validate its role in hepatocellular carcinoma.

Results

Our findings indicated that NABP2 was overexpressed in HCC samples and was related to poor survival, clinical stage, and tumour grade in HCC patients. Analysis of functional enrichment indicated that NABP2 was potentially involved in the cell cycle, DNA replication, G2M checkpoint, E2F targets, apoptosis, P53 signalling, TGFA signalling via NF-κB, and so on. NABP2 was shown to be significantly linked to immune cell infiltration and immunological checkpoints in HCC. Analyses of drug sensitivity predict a number of drugs that could potentially be used to target NABP2. Moreover, in vitro experiments verified the promoting effect of NABP2 on the migration and proliferation of hepatocellular carcinoma cells.

Conclusion

Based on these findings, NABP2 appears to be a candidate biomarker for HCC prognosis and immunotherapy.

Evolution of precision oncology-guided treatment paradigms

Cancer treatment is gradually evolving from the classical use of nonspecific cytotoxic drugs targeting generic mechanisms of cell growth and proliferation. Instead, new "patient-specific treatment paradigms" that are based on an individual patient's tumor-specific molecular features are emerging, and these include "druggable" genomic alterations such as oncogenic driver mutations, downstream activities of cancer-signaling pathways, and the expression of specific genes involved in tumorigenesis and cancer progression. This evolving landscape of making evidence-based treatment decisions forms the foundation of precision oncology, which aims to deliver "the right drug, to the right patient and at the right time". The long-term vision for this approach is to maximize the treatment efficacy while minimizing exposure to ineffective therapy and reducing co-morbidity-related side effects. Successful clinical translation and implementation of this vision have the potential to revolutionize treatment paradigms from predominantly reactive, to more evidence-based, proactive and predictive care. In this article, we review the past and current approaches in precision oncology, and describe their remarkable power and limitations. We also speculate on the evolution of newly emerging methodologies of the future that can be used to address some of the key challenges associated with the existing paradigms. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics Cancer > Molecular and Cellular Physiology Cancer > Computational Models.

Challenges and emerging strategies for next generation liposomal based drug delivery: An account of the breast cancer conundrum

The global cancer burden is witnessing an upsurge with breast cancer surpassing other cancers worldwide. Furthermore, an escalation in the breast cancer caseload is also expected in the coming years. The conventional therapeutic regimens practiced routinely are associated with many drawbacks to which nanotechnological interventions offer a great advantage. But how eminent could liposomes and their advantages be in superseding these existing therapeutic modalities? A solution is reflected in this review that draws attention to a decade-long journey embarked upon by researchers in this wake. This text is a comprehensive discussion of liposomes, the front runners of the drug delivery systems, and their active and passive targeting approaches for breast cancer management. Active targeting has been studied over the decade by many receptors overexpressed on the breast cancer cells and passive targeting with many drug combinations. The results converge on the fact that the actively targeted formulations exhibit a superior efficacy over their non-targeted counterparts and the all liposomal formulations are efficacious over the free drugs. This undoubtedly underlines the dominion of liposomal formulations over conventional chemotherapy. These investigations have led to the development of different liposomal formulations with active and passive targeting capacities that could be explored in depth. Acknowledging and getting a deeper insight into the liposomal evolution through time also unveiled many imperfections and unchartered territories that can be explored to deliver dexterous liposomal formulations against breast cancer and more in the clinical trial pipeline.

Towards a consensus definition of immune exclusion in cancer

Background

The immune cell topography of solid tumors has been increasingly recognized as an important predictive factor for progression of disease and response to immunotherapy. The distribution pattern of immune cells in solid tumors is commonly classified into three categories - namely, "Immune inflamed", "Immune desert" and "Immune excluded" - which, to some degree, connect immune cell presence and positioning within the tumor microenvironment to anti-tumor activity.

Materials and methods

In this review, we look at the ways immune exclusion has been defined in published literature and identify opportunities to develop consistent, quantifiable definitions, which in turn, will allow better determination of the underlying mechanisms that span cancer types and, ultimately, aid in the development of treatments to target these mechanisms.

Results

The definitions of tumor immune phenotypes, especially immune exclusion, have largely been conceptual. The existing literature lacks in consistency when it comes to practically defining immune exclusion, and there is no consensus on a definition. Majority of the definitions use somewhat arbitrary cut-offs in an attempt to place each tumor into a distinct phenotypic category. Tumor heterogeneity is often not accounted for, which limits the practical application of a definition.

Conclusions

We have identified two key issues in existing definitions of immune exclusion, establishing clinically relevant cut-offs within the spectrum of immune cell infiltration as well as tumor heterogeneity. We propose an approach to overcome these limitations, by reporting the degree of immune cell infiltration, tying cut-offs to clinically meaningful outcome measures, maximizing the number of regions of a tumor that are analyzed and reporting the degree of heterogeneity. This will allow for a consensus practical definition for operationalizing this categorization into clinical trial and signal-seeking endpoints.

A simple self-assembly nanomicelle based on brain tumor-targeting peptide-mediated siRNA delivery for glioma immunotherapy via intranasal administration

The blood-brain barrier (BBB) has a key role in preventing drugs from entering the brain. Non-invasive intranasal drug delivery routes that bypass the BBB are increasing in popularity because of their ability to shorten the journey and reduce the loss of genetic drugs such as siRNA in transit. However, the complex synthesis and quality control process of most nose-to-brain delivery carriers and the limited mass production are the main obstacles to their clinical application. Here, we constructed a siRNA delivery system with simple synthesis and quality control methods using cholesterol-modified T7 (T7-C), in which T7 can bind to the transferrin receptor (TfR) expressed on glioma cells to target gliomas. In our results, T7-C had dual functions as a glioma-targeting carrier and immune adjuvant. As a targeted delivery carrier, T7-C intranasally delivered siRNA into the mouse brain through the olfactory bulb pathway and was taken up by glioma cells by the caveolin- and transferrin-dependent pathway. As an immune adjuvant, T7-C could promote DC maturation and combined with slit2 siRNA could promote polarization of M2 subtype macrophages to M1 subtype macrophages and then increase the proportion of effector T cells to remodel the tumor environment. In conclusion, T7-C with glioma targeting as a delivery system of slit2 siRNA showed a good therapeutic effect in the treatment of glioma after intranasal administration and had potential application prospects. STATEMENT OF SIGNIFICANCE: In contrast to the existing literature that uses complex materials to deliver drugs across the blood-brain barrier (BBB) in an invasive manner for glioma treatment, we developed a simple, self-assembling siRNA delivery system (T7-C) based on brain tumor-targeted T7 peptide to treat glioma by intranasal administration. T7-C/siRNA could reach the tumor site through the olfactory bulb route and adjust the "cold" tumor microenvironment to the "hot" tumor microenvironment and non-invasive intranasal delivery route could shorten the journey and reduce the loss of genetic drugs. Therefore, our design has good application prospects and is expected to serve as a general strategy for intranasal drug delivery in the treatment of brain tumors.

MRI-based radiomics for pretreatment prediction of response to concurrent chemoradiotherapy in locally advanced cervical squamous cell cancer

PURPOSE

To investigate the value of magnetic resonance imaging (MRI)-based radiomics in predicting the treatment response to concurrent chemoradiotherapy (CCRT) in patients with locally advanced cervical squamous cell cancer (LACSC).

METHODS

In total, 198 patients (training: n = 138; testing: n = 60) with LACSC treated with CCRT between January 2014 and December 2019 were retrospectively enrolled in this study. Responses were evaluated by MRI and clinical data performed at one month after completion of CCRT according to RECIST standards, and patients were divided into the residual group and nonresidual group. Overall, 200 radiomics features were extracted from T2-weighted imaging and apparent diffusion coefficient maps. The radiomics score (Rad-score) was constructed with a feature selection strategy. Logistic regression analysis was used for multivariate analysis of radiomics features and clinical variables. The performance of all models was assessed using receiver operating characteristic curves.

RESULTS

Among the clinical variables, tumor grade and FIGO stage were independent risk factors, and the areas under the curve (AUCs) of the clinical model were 0.741 and 0.749 in the training and testing groups. The Rad-score, consisting of 4 radiomics features selected from 200 radiomics features, showed good predictive performance with an AUC of 0.819 in the training group and 0.776 in the testing group, which were higher than the clinical model, but the difference was not statistically significant. The combined model constructed with tumor grade, FIGO stage, and Rad-score achieved the best performance, with an AUC of 0.857 in the training group and 0.842 in the testing group, which were significantly higher than the clinical model.

CONCLUSION

MRI-based radiomics features could be used as a noninvasive biomarker to improve the ability to predict the treatment response to CCRT in patients with LACSC.

Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine

BACKGROUND

Stomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear.

METHOD

743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram.

RESULTS

We identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples.

CONCLUSION

The OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD.

Multiplex immunofluorescence and single-cell transcriptomic profiling reveal the spatial cell interaction networks in the non-small cell lung cancer microenvironment

BACKGROUND

Conventional immunohistochemistry technologies were limited by the inability to simultaneously detect multiple markers and the lack of identifying spatial relationships among cells, hindering understanding of the biological processes in cancer immunology.

METHODS

Tissue slices of primary tumours from 553 IA∼IIIB non-small cell lung cancer (NSCLC) cases were stained by multiplex immunofluorescence (mIF) assay for 10 markers, including CD4, CD38, CD20, FOXP3, CD66b, CD8, CD68, PD-L1, CD133 and CD163, evaluating the amounts of 26 phenotypes of cells in tumour nest and tumour stroma. StarDist depth learning model was utilised to determine the spatial location of cells based on mIF graphs. Single-cell RNA sequencing (scRNA-seq) on four primary NSCLC cases was conducted to investigate the putative cell interaction networks.

RESULTS

Spatial proximity among CD20+ B cells, CD4+ T cells and CD38+ T cells (r2  = 0.41) was observed, whereas the distribution of regulatory T cells was associated with decreased infiltration levels of CD20+ B cells and CD38+ T cells (r2  = -0.45). Univariate Cox analyses identified closer proximity between CD8+ T cells predicted longer disease-free survival (DFS). In contrast, closer proximity between CD133+ cancer stem cells (CSCs), longer distances between CD4+ T cells and CD20+ B cells, CD4+ T cells and neutrophils, and CD20+ B cells and neutrophils were correlated with dismal DFS. Data from scRNA-seq further showed that spatially adjacent N1-like neutrophils could boost the proliferation and activation of T and B lymphocytes, whereas spatially neighbouring M2-like macrophages showed negative effects. An immune-related risk score (IRRS) system aggregating robust quantitative and spatial prognosticators showed that high-IRRS patients had significantly worse DFS than low-IRRS ones (HR 2.72, 95% CI 1.87-3.94, p < .001).

CONCLUSIONS

We developed a framework to analyse the cell interaction networks in tumour microenvironment, revealing the spatial architecture and intricate interplays between immune and tumour cells.

Lysophosphatidic acid-induced amphiregulin secretion by cancer-associated fibroblasts augments cancer cell invasion

Cancer-associated fibroblasts (CAFs) are key structural components of the tumor microenvironment and are closely associated with tumor invasion and metastasis. Lysophosphatidic acid (LPA) is a biolipid produced extracellularly and involved in tumorigenesis and metastasis. LPA has recently been implicated in the education and transdifferentiation of normal fibroblasts (NFs) into CAFs. However, little is known about the effects of LPA on CAFs and their participation in cancer cell invasion. In the present study, we identified a critical role of LPA-induced amphiregulin (AREG) secreted from CAFs in cancer invasiveness. CAFs secrete higher amounts of AREG than NFs, and LPA induces AREG expression in CAFs to augment their invasiveness. Strikingly, knocking out the AREG gene in CAFs attenuates cancer invasiveness and metastasis. Mechanistically, LPA induces Yes-associated protein (YAP) activation and Zinc finger E-box binding homeobox 1 (Zeb1) expression through the LPAR1 and LPAR3/Gi/Rho signaling axes, leading to AREG expression. Furthermore, we provide evidence that metformin, a biguanide derivative, significantly inhibits LPA-induced AREG expression in CAFs to attenuate cancer cell invasiveness. Collectively, the present data show that LPA induces AREG expression through YAP and Zeb1 in CAFs to promote cancer cell invasiveness, with the process being inhibited by metformin, providing potential biomarkers and therapeutic avenues to interdict cancer cell invasion.

A Novel Molecular Signature of Cancer-Associated Fibroblasts Predicts Prognosis and Immunotherapy Response in Pancreatic Cancer

Cancer-associated fibroblasts (CAFs), a prominent population of stromal cells, play a crucial role in tumor progression, prognosis, and treatment response. However, the relationship among CAF-based molecular signatures, clinical outcomes, and tumor microenvironment infiltration remains largely elusive in pancreatic cancer (PC). Here, we collected multicenter PC data and performed integrated analysis to investigate the role of CAF-related genes (CRGs) in PC. Firstly, we demonstrated that α-SMA⁺ CAFs were the most prominent stromal components and correlated with the poor survival rates of PC patients in our tissue microarrays. Then, we discriminated two diverse molecular subtypes (CAF clusters A and B) and revealed the significant differences in the tumor immune microenvironment (TME), four reported CAF subpopulations, clinical characteristics, and prognosis in PC samples. Furthermore, we analyzed their association with the immunotherapy response of PC patients. Lastly, a CRG score was constructed to predict prognosis, immunotherapy responses, and chemosensitivity in pancreatic cancer patients. In summary, these findings provide insights into further research targeting CAFs and their TME, and they pave a new road for the prognosis evaluation and individualized treatment of PC patients.

Capturing the spatial and temporal dynamics of tumor stroma for on-chip optimization of microenvironmental targeting nanomedicine

Malignant cells grow in a complex microenvironment that plays a key role in cancer progression. The "dynamic reciprocity" existing between cancer cells and their microenvironment is involved in cancer differentiation, proliferation, invasion, metastasis, and drug response. Therefore, understanding the molecular mechanisms underlying the crosstalk between cancer cells and their surrounding tissue (i.e., tumor stroma) and how this interplay affects the disease progression is fundamental to design and validate novel nanotherapeutic approaches. As an important regulator of tumor progression, metastasis and therapy resistance, the extracellular matrix of tumors, the acellular component of the tumor microenvironment, has been identified as very promising target of anticancer treatment, revolutionizing the traditional therapeutic paradigm that sees the neoplastic cells as the preferential objective to fight cancer. To design and to validate such a target therapy, advanced 3D preclinical models are necessary to correctly mimic the complex, dynamic and heterogeneous tumor microenvironment. In addition, the recent advancement in microfluidic technology allows fine-tuning and controlling microenvironmental parameters in tissue-on-chip devices in order to emulate the in vivo conditions. In this review, after a brief description of the origin of tumor microenvironment heterogeneity, some examples of nanomedicine approaches targeting the tumor microenvironment have been reported. Further, how advanced 3D bioengineered tumor models coupled with a microfluidic device can improve the design and testing of anti-cancer nanomedicine targeting the tumor microenvironment has been discussed. We highlight that the presence of a dynamic extracellular matrix, able to capture the spatiotemporal heterogeneity of tumor stroma, is an indispensable requisite for tumor-on-chip model and nanomedicine testing.

3D imaging analysis on an organoid-based platform guides personalized treatment in pancreatic ductal adenocarcinoma

BACKGROUNDPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with unpredictable responses to chemotherapy. Approaches to assay patient tumors before treatment and identify effective treatment regimens based on tumor sensitivities are lacking. We developed an organoid-based platform (OBP) to visually quantify patient-derived organoid (PDO) responses to drug treatments and associated tumor-stroma modulation for personalized PDAC therapy.METHODSWe retrospectively quantified apoptotic responses and tumor-stroma cell proportions in PDOs via 3D immunofluorescence imaging through annexin A5, α-smooth muscle actin (α-SMA), and cytokeratin 19 (CK-19) levels. Simultaneously, an ex vivo organoid drug sensitivity assay (ODSA) was used to measure responses to standard-of-care regimens. Differences between ODSA results and patient tumor responses were assessed by exact McNemar's test.RESULTSImmunofluorescence signals, organoid growth curves, and Ki-67 levels were measured and authenticated through the OBP for up to 14 days. ODSA drug responses were not different from patient tumor responses, as reflected by CA19-9 reductions following neoadjuvant chemotherapy (P = 0.99). PDOs demonstrated unique apoptotic and tumor-stroma modulation profiles (P < 0.0001). α-SMA/CK-19 ratio levels of more than 1.0 were associated with improved outcomes (P = 0.0179) and longer parental patient survival by Kaplan-Meier analysis (P = 0.0046).CONCLUSIONHeterogenous apoptotic drug responses and tumor-stroma modulation are present in PDOs after standard-of-care chemotherapy. Ratios of α-SMA and CK-19 levels in PDOs are associated with patient survival, and the OBP could aid in the selection of personalized therapies to improve the efficacy of systemic therapy in patients with PDAC.FUNDINGNIH/National Cancer Institute grants (K08CA218690, P01 CA117969, R50 CA243707-01A1, U54CA224065), the Skip Viragh Foundation, the Bettie Willerson Driver Cancer Research Fund, and a Cancer Center Support Grant for the Flow Cytometry and Cellular Imaging Core Facility (P30CA16672).

Engineering chimeric antigen receptor T cells for solid tumour therapy

Cell-based immunotherapy, for example, chimeric antigen receptor T (CAR-T) cell immunotherapy, has revolutionized cancer treatment, particularly for blood cancers. However, factors such as insufficient T cell tracking, tumour heterogeneity, inhibitory tumour microenvironment (TME) and T cell exhaustion limit the broad application of CAR-based immunotherapy for solid tumours. In particular, the TME is a complex and evolving entity, which is composed of cells of different types (e.g., cancer cells, immune cells and stromal cells), vasculature, soluble factors and extracellular matrix (ECM), with each component playing a critical role in CAR-T immunotherapy. Thus, developing approaches to mitigate the inhibitory TME factors is critical for future success in applying CAR-T cells for solid tumour treatment. Accordingly, understanding the bilateral interaction of CAR-T cells with the TME is in pressing need to pave the way for more efficient therapeutics. In the following review, we will discuss TME-associated aspects with an emphasis on T cell trafficking, ECM barriers, abnormal vasculature, solid tumour heterogenicity and immune suppressive microenvironment. We will then summarize current engineering strategies to overcome the challenges posed by the TME-associated factors. Lastly, the future directions for engineering efficient CAR-T cells for solid tumour therapy will be discussed.

The Senescence-Related Signature Predicts Prognosis and Characterization of Tumor Microenvironment Infiltration in Pancreatic Cancer

Background. Senescence is thought to be an imperative effect on the development of cancer. However, few studies pay an attention to the senescence-associated genes in pancreatic cancer (PC). The prognostic value of senescence-related genes (SRGs) and their involvement in tumor microenvironment (TME) in the PC remain obscure. The aim of this research was to investigate the prognostic role of senescence-associated genes and their affection in TME in PC. Methods. The transcriptome and clinical information of PC patients were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Two SRG-mediated molecular clusters were comprehensively identified. In total, data from the 285 PC patients were randomly used to develop a senescence-associated gene signature in the training set and verified in the validation set. Immune microenvironment analysis pertained to senescence-related genes was performed. Results. A SRG_score including five senescence-associated genes was established to separate PC patients into two risk groups. High-risk patients had worse overall survival than low-risk patients. The result of the multivariate Cox regression analysis identified the risk score and stage as independent prognostic factors for PC patients. Receiver operating characteristic curve (ROC) analysis confirmed the credible predictive ability of the nomogram. The area under time-dependent ROC curve (AUC) reached 0.746 at 1 year, 0.781 at 3 years, and 0.868 at 5 years in the training set and 0.653 at 1 year, 0.755 at 3 years, and 0.785 at 5 years in the validation set. Moreover, the SRG_score was associated with TME, tumor mutation burden (TMB), and chemotherapeutic drug sensitivity. Conclusions. This study found that the novel SRG_score could be an independent prognostic target for PC patients. Senescence-associated genes had a vital impact on the immune microenvironment and the treatment of PC patients.

Development and validation of a computed tomography-based immune ecosystem diversity index as an imaging biomarker in non-small cell lung cancer

OBJECTIVES

To date, there are no data on the noninvasive surrogate of intratumoural immune status that could be prognostic of survival outcomes in non-small cell lung cancer (NSCLC). We aimed to develop and validate the immune ecosystem diversity index (iEDI), an imaging biomarker, to indicate the intratumoural immune status in NSCLC. We further investigated the clinical relevance of the biomarker for survival prediction.

METHODS

In this retrospective study, two independent NSCLC cohorts (Resec1, n = 149; Resec2, n = 97) were included to develop and validate the iEDI to classify the intratumoural immune status. Paraffin-embedded resected specimens in Resec1 and Resec2 were stained by immunohistochemistry, and the density percentiles of CD3+, CD4+, and CD8+ T cells to all cells were quantified to estimate intratumoural immune status. Then, EDI features were extracted using preoperative computed tomography to develop an imaging biomarker, called iEDI, to determine the immune status. The prognostic value of iEDI was investigated on NSCLC patients receiving surgical resection (Resec1; Resec2; internal cohort Resec3, n = 419; external cohort Resec4, n = 96; and TCIA cohort Resec5, n = 55).

RESULTS

iEDI successfully classified immune status in Resec1 (AUC 0.771, 95% confidence interval [CI] 0.759-0.783; and 0.770 through internal validation) and Resec2 (0.669, 0.647-0.691). Patients with higher iEDI-score had longer overall survival (OS) in Resec3 (unadjusted hazard ratio 0.335, 95%CI 0.206-0.546, p < 0.001), Resec4 (0.199, 0.040-1.000, p < 0.001), and TCIA (0.303, 0.098-0.944, p = 0.001).

CONCLUSIONS

iEDI is a non-invasive surrogate of intratumoural immune status and prognostic of OS for NSCLC patients receiving surgical resection.

KEY POINTS

• Decoding tumour immune microenvironment enables advanced biomarkers identification. • Immune ecosystem diversity index characterises intratumoural immune status noninvasively. • Immune ecosystem diversity index is prognostic for NSCLC patients.

Proteomic characterisation of prostate cancer intercellular communication reveals cell type-selective signalling and TMSB4X-dependent fibroblast reprogramming

BACKGROUND

In prostate cancer, the tumour microenvironment (TME) represents an important regulator of disease progression and response to treatment. In the TME, cancer-associated fibroblasts (CAFs) play a key role in tumour progression, however the mechanisms underpinning fibroblast-cancer cell interactions are incompletely resolved. Here, we address this by applying cell type-specific labelling with amino acid precursors (CTAP) and mass spectrometry (MS)-based (phospho)proteomics to prostate cancer for the first time.

METHODS

Reciprocal interactions between PC3 prostate cancer cells co-cultured with WPMY-1 prostatic fibroblasts were characterised using CTAP-MS. Signalling network changes were determined using Metascape and Enrichr and visualised using Cytoscape. Thymosin β4 (TMSB4X) overexpression was achieved via retroviral transduction and assayed by ELISA. Cell motility was determined using Transwell and random cell migration assays and expression of CAF markers by indirect immunofluorescence.

RESULTS

WPMY-1 cells co-cultured with PC3s demonstrated a CAF-like phenotype, characterised by enhanced PDGFRB expression and alterations in signalling pathways regulating epithelial-mesenchymal transition, cytoskeletal organisation and cell polarisation. In contrast, co-cultured PC3 cells exhibited more modest network changes, with alterations in mTORC1 signalling and regulation of the actin cytoskeleton. The expression of the actin binding protein TMSB4X was significantly decreased in co-cultured WPMY-1 fibroblasts, and overexpression of TMSB4X in fibroblasts decreased migration of co-cultured PC3 cells, reduced fibroblast motility, and protected the fibroblasts from being educated to a CAF-like phenotype by prostate cancer cells.

CONCLUSIONS

This study highlights the potential of CTAP-MS to characterise intercellular communication within the prostate TME and identify regulators of cellular crosstalk such as TMSB4X.

Nanomedicine-Enabled/Augmented Cell Pyroptosis for Efficient Tumor Nanotherapy

The terrible morbidity and mortality of malignant tumors urgently require innovative therapeutics, especially for apoptosis-resistant tumors. Pyroptosis, a pro-inflammatory form of programmed cell death (PCD), is featured with pore formation in plasma membrane, cell swelling with giant bubbles, and leakage of cytoplasmic pro-inflammatory cytokines, which can remodel the tumor immune microenvironment by stimulating a "cold" tumor microenvironment to be an immunogenic "hot" tumor microenvironment, and consequently augment the therapeutic efficiency of malignant tumors. Benefiting from current advances in nanotechnology, nanomedicine is extensively applied to potentiate, enable, and augment pyroptosis for enhancing cancer-therapeutic efficacy and specificity. This review provides a concentrated summary and discussion of the most recent progress achieved in this emerging field, highlighting the nanomedicine-enabled/augmented specific pyroptosis strategy for favoring the construction of next-generation nanomedicines to efficiently induce PCD. It is highly expected that the further clinical translation of nanomedicine can be accelerated by inducing pyroptotic cell death based on bioactive nanomedicines.

Intratumor graph neural network recovers hidden prognostic value of multi-biomarker spatial heterogeneity

Biomarkers are indispensable for precision medicine. However, focused single-biomarker development using human tissue has been complicated by sample spatial heterogeneity. To address this challenge, we tested a representation of primary tumor that synergistically integrated multiple in situ biomarkers of extracellular matrix from multiple sampling regions into an intratumor graph neural network. Surprisingly, the differential prognostic value of this computational model over its conventional non-graph counterpart approximated that of combined routine prognostic biomarkers (tumor size, nodal status, histologic grade, molecular subtype, etc.) for 995 breast cancer patients under a retrospective study. This large prognostic value, originated from implicit but interpretable regional interactions among the graphically integrated in situ biomarkers, would otherwise be lost if they were separately developed into single conventional (spatially homogenized) biomarkers. Our study demonstrates an alternative route to cancer prognosis by taping the regional interactions among existing biomarkers rather than developing novel biomarkers.

Cell-Derived Vesicles for Nanoparticles' Coating: Biomimetic Approaches for Enhanced Blood Circulation and Cancer Therapy

Cancer nanomedicines are designed to encapsulate different therapeutic agents, prevent their premature release, and deliver them specifically to cancer cells, due to their ability to preferentially accumulate in tumor tissue. However, after intravenous administration, nanoparticles immediately interact with biological components that facilitate their recognition by the immune system, being rapidly removed from circulation. Reports show that less than 1% of the administered nanoparticles effectively reach the tumor site. This suboptimal pharmacokinetic profile is pointed out as one of the main factors for the nanoparticles' suboptimal therapeutic effectiveness and poor translation to the clinic. Therefore, an extended blood circulation time may be crucial to increase the nanoparticles' chances of being accumulated in the tumor and promote a site-specific delivery of therapeutic agents. For that purpose, the understanding of the forces that govern the nanoparticles' interaction with biological components and the impact of the physicochemical properties on the in vivo fate will allow the development of novel and more effective nanomedicines. Therefore, in this review, the nano-bio interactions are summarized. Moreover, the application of cell-derived vesicles for extending the blood circulation time and tumor accumulation is reviewed, focusing on the advantages and shortcomings of each cell source.

Colorectal cancer organoid models uncover oxaliplatin-resistant mechanisms at single cell resolution

PURPOSE

Oxaliplatin-based chemotherapy is a standard treatment for advanced colorectal cancer (CRC) patients. However, chemoresistance-induced resistance is an essential cause for mortality. Therefore, it is necessary to study the mechanism of drug resistance in CRC.

METHODS

Here, we established two strains of patient-derived organoids (PDOs) selected from oxaliplatin-resistant and treatment-naïve CRC patients. To dissect the drug-resistant mechanisms, these CRC-PDOs were subjected to single-cell RNA sequencing (scRNA-Seq).

RESULTS

We found that the drug sensitivity test outcome from these organoids subjected to oxaliplatin and 5-FU exposure was consistent with the clinic readout. CRC-PDOs well recapitulated the morphology and histology of their parental biopsies based on HE and IHC staining of pathological biomarkers. The scRNA-Seq data filtered drug-resistant cell populations and related signaling pathways (e.g. oxidative phosphorylation and ATP metabolic process). The data also revealed several putative drug resistant-driven genes (STMN1, VEGFA and NDRG1) and transcription factors (E2F1, BRCA1, MYBL2, CDX2 and CDX1).

CONCLUSION

We generated an oxaliplatin-resistant CRC organoid model that was employed to provide potential therapeutic targets for treating CRC patients exhibiting oxaliplatin-resistance.

Next generation patient derived tumor organoids

Patient-derived tumor organoids (PDTOs) have emerged as exceptional pre-clinical models as they preserved, in most of the cases, the mutational landscape and tumor-clonal heterogeneity of the primary tumors. Despite being extensively used in disease modelling as well as in precision medicine for drug testing and discovery, they still have some limitations. The main limitation is that during their establishment they lose all components of the tumor microenvironment (TME) which are known modulators of tumor response to therapeutic treatment as well as disease progression. In this review we address the effects of different players of the TME such as immune cells, fibroblasts, endothelial cells and the extracellular matrix composition on tumor behavior and response to treatment as well as the different culture and co-culture strategies that could improve PDTOs value as pre-clinical models leading to the development of next generation PDTOs.

Fibronectin 1 derived from tumor-associated macrophages and fibroblasts promotes metastasis through the JUN pathway in hepatocellular carcinoma

OBJECTIVE

Intercellular communication in the tumor microenvironment is a potential regulator of metastasis. To explore the specific mechanism, we performed a multi-omics analysis of hepatocellular carcinoma.

MATERIALS AND METHODS

Multiple omics data including scRNA-seq, ATAC-seq, RNA-seq, and methylation data were obtained from GEO and TCGA databases. SCENIC was used to identify key transcription factors and their Regulatory networks. ScMLnet was used to explore the mechanism of intercellular communication in the microenvironment. Multiple omics studies based on RNA-seq, ATAC-seq, and methylation data were used to explore downstream mechanisms of key transcription factors. Based on the analysis of cell differentiation trajectory and transcription subtypes, the regulation of cell communication on tumor subtypes was studied, and possible therapeutic compounds were explored. The universality of this mechanism was investigated by post-Pan-cancer analysis.

RESULTS

JUN and its regulatory network play a key role in HCC, which was mainly positively correlated with tumor-associated macrophages and fibroblasts. Intercellular communication analysis showed that macrophage and fibroblast-derived FN1 could increase JUN by TNFRSF11B/SMAD3. Multiomics analysis showed that KIF13A was a key downstream gene of JUN, which was involved in the activation of the hippo pathway. Analysis of cell differentiation trajectory, transcriptome subtypes, and neural network modeling showed that intercellular communication in the microenvironment can regulate the transcriptome characterization of HCC. Pan-cancer analysis indicates that this mechanism may be universal.

CONCLUSION

FN1 derived from tumor-associated macrophages and fibroblasts promotes metastasis and alters transcriptome subtypes through the JUN-Hippo signaling pathway in HCC, which may be universal in cancers.

Radiotherapy induced immunogenic cell death by remodeling tumor immune microenvironment

Emerging evidence indicates that the induction of radiotherapy(RT) on the immunogenic cell death (ICD) is not only dependent on its direct cytotoxic effect, changes in the tumor immune microenvironment also play an important role in it. Tumor immune microenvironment (TIME) refers to the immune microenvironment that tumor cells exist, including tumor cells, inflammatory cells, immune cells, various signaling molecules and extracellular matrix. TIME has a barrier effect on the anti-tumor function of immune cells, which can inhibit all stages of anti-tumor immune response. The remodeling of TIME caused by RT may affect the degree of immunogenicity, and make it change from immunosuppressive phenotype to immunostimulatory phenotype. It is of great significance to reveal the causes of immune escape of tumor cells, especially for the treatment of drug-resistant tumor. In this review, we focus on the effect of RT on the TIME, the mechanism of RT in reversing the TIME to suppress intrinsic immunity, and the sensitization effect of the remodeling of TIME caused by RT on the effectiveness of immunotherapy.

A Lanthanide Upconversion Nanothermometer for Precise Temperature Mapping on Immune Cell Membrane

Cell temperature monitoring is of great importance to uncover temperature-dependent intracellular events and regulate cellular functions. However, it remains a great challenge to precisely probe the localized temperature status in living cells. Herein, we report a strategy for in situ temperature mapping on an immune cell membrane for the first time, which was achieved by using the lanthanide-doped upconversion nanoparticles. The nanothermometer was designed to label the cell membrane by combining metabolic labeling and click chemistry and can leverage ratiometric upconversion luminescence signals to in situ sensitively monitor temperature variation (1.4% K^-1). Moreover, a purpose-built upconversion hyperspectral microscope was utilized to synchronously map temperature changes on T cell membrane and visualize intracellular Ca²⁺ influx. This strategy was able to identify a suitable temperature status for facilitating thermally stimulated calcium influx in T cells, thus enabling high-efficiency activation of immune cells. Such findings might advance understandings on thermally dependent biological processes and their regulation methodology.

Prognostic value and immunological role of FOXM1 in human solid tumors

FOXM1 acts as an oncogenic transcription factor and is involved in multiple hallmarks of human malignancies. Recent studies have demonstrated that FOXM1 is upregulated and correlated with poor prognosis in a majority of cancers. However, there are few pan-cancer analyses of FOXM1. This study aimed to investigate the expression profiles and clinical significance of FOXM1 in 31 types of solid tumors. We explored the expression profiles and the prognostic value of FOXM1 in pan-cancer across The Cancer Genome Atlas (TCGA). We further used lung adenocarcinoma (LUAD) tissues combined with quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) for experimental validation of FOXM1 expression. Besides, we verified the function of FOXM1 in a lung cancer cell line. Gene set enrichment analysis (GSEA) was conducted to explore signaling pathways related to FOXM1 expression. We observed that up-regulated FOXM1 was significantly related to poor survival in most tumors. Furthermore, there are significant correlations between FOXM1 expression and the infiltrating levels of different types of immune cells, TMB, MSI and immune checkpoint genes in a variety of cancers. Additional analysis based on IMvigor 210 cohort confirmed that patients with high level of FOXM1 exhibited a superior response to anti-PD-L1 therapy, and had a prolonged OS. In conclusion, this study indicated that FOXM1 could serve as a prognostic biomarker for most types of cancers and played a crucial role in the tumor immune microenvironment.

Recent Advances of Organ-on-a-Chip in Cancer Modeling Research

Although many studies have focused on oncology and therapeutics in cancer, cancer remains one of the leading causes of death worldwide. Due to the unclear molecular mechanism and complex in vivo microenvironment of tumors, it is challenging to reveal the nature of cancer and develop effective therapeutics. Therefore, the development of new methods to explore the role of heterogeneous TME in individual patients' cancer drug response is urgently needed and critical for the effective therapeutic management of cancer. The organ-on-chip (OoC) platform, which integrates the technology of 3D cell culture, tissue engineering, and microfluidics, is emerging as a new method to simulate the critical structures of the in vivo tumor microenvironment and functional characteristics. It overcomes the failure of traditional 2D/3D cell culture models and preclinical animal models to completely replicate the complex TME of human tumors. As a brand-new technology, OoC is of great significance for the realization of personalized treatment and the development of new drugs. This review discusses the recent advances of OoC in cancer biology studies. It focuses on the design principles of OoC devices and associated applications in cancer modeling. The challenges for the future development of this field are also summarized in this review. This review displays the broad applications of OoC technique and has reference value for oncology development.

Ovarian Cancer-Cell Pericellular Hyaluronan Deposition Negatively Impacts Prognosis of Ovarian Cancer Patients

BACKGROUND

Hyaluronan (HA), a component of the extracellular matrix, is frequently increased under pathological conditions including cancer. Not only stroma cells but also cancer cells themselves synthesize HA, and the interaction of HA with its cognate receptors promotes malignant progression and metastasis.

METHODS

In the present study, HA deposition in tissue sections was analyzed by hyaluronan-binding protein (HABP) ligand histochemistry in 17 borderline tumors and 102 primary and 20 recurrent ovarian cancer samples. The intensity and, particularly, localization of the HA deposition were recorded: for the localization, the pericellular deposition around the ovarian cancer cells was distinguished from the deposition within the stromal compartment. These histochemical data were correlated with clinical and pathological parameters. Additionally, within a reduced subgroup of ovarian cancer samples (n = 70), the RNA levels of several HA-associated genes were correlated with the HA localization and intensity.

RESULTS

Both stroma-localized and pericellular tumor-cell-associated HA deposition were observed. Cancer-cell pericellular HA deposition, irrespective of its staining intensity, was significantly associated with malignancy, and in the primary ovarian cancer cohort, it represents an independent unfavorable prognostic marker for overall survival. Furthermore, a significant association between high CD44, HAS2 and HAS3 mRNA levels and a cancer-cell pericellular HA-deposition pattern was noted. In contrast, stromal hyaluronan deposition had no impact on ovarian cancer prognosis.

CONCLUSIONS

In conclusion, the site of HA deposition is of prognostic value, but the amount deposited is not. The significant association of only peritumoral cancer-cell HA deposition with high CD44 mRNA expression levels suggests a pivotal role of the CD44-HA signaling axis for malignant progression in ovarian cancer.