Strategy of targeting the tumor microenvironment via inhibition of fibroblast/fibrosis remodeling new era to cancer chemo-immunotherapy resistance

CRISPR/Cas9-mediated knockout strategies for enhancing immunotherapy in breast cancer

Breast cancer, a prevalent disease with significant mortality rates, often presents treatment challenges due to its complex genetic makeup. This review explores the potential of combining Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene knockout strategies with immunotherapeutic approaches to enhance breast cancer treatment. The CRISPR/Cas9 system, renowned for its precision in inducing genetic alterations, can target and eliminate specific cancer cells, thereby minimizing off-target effects. Concurrently, immunotherapy, which leverages the immune system's power to combat cancer, has shown promise in treating breast cancer. By integrating these two strategies, we can potentially augment the effectiveness of immunotherapies by knocking out genes that enable cancer cells to evade the immune system. However, safety considerations, such as off-target effects and immune responses, necessitate careful evaluation. Current research endeavors aim to optimize these strategies and ascertain the most effective methods to stimulate the immune response. This review provides novel insights into the integration of CRISPR/Cas9-mediated knockout strategies and immunotherapy, a promising avenue that could revolutionize breast cancer treatment as our understanding of the immune system's interplay with cancer deepens.

Pharmacokinetics-Pharmacodynamics Modeling for Evaluating Drug-Drug Interactions in Polypharmacy: Development and Challenges

Polypharmacy is commonly employed in clinical settings. The potential risks of drug-drug interactions (DDIs) can compromise efficacy and pose serious health hazards. Integrating pharmacokinetics (PK) and pharmacodynamics (PD) models into DDIs research provides a reliable method for evaluating and optimizing drug regimens. With advancements in our comprehension of both individual drug mechanisms and DDIs, conventional models have begun to evolve towards more detailed and precise directions, especially in terms of the simulation and analysis of physiological mechanisms. Selecting appropriate models is crucial for an accurate assessment of DDIs. This review details the theoretical frameworks and quantitative benchmarks of PK and PD modeling in DDI evaluation, highlighting the establishment of PK/PD modeling against a backdrop of complex DDIs and physiological conditions, and further showcases the potential of quantitative systems pharmacology (QSP) in this field. Furthermore, it explores the current advancements and challenges in DDI evaluation based on models, emphasizing the role of emerging in vitro detection systems, high-throughput screening technologies, and advanced computational resources in improving prediction accuracy.

Herb pair of Huangqi-Danggui exerts anti-tumor immunity to breast cancer by upregulating PIK3R1

BACKGROUND

According to traditional Chinese medicine (TCM), drugs supplementing the vital energy, Qi, can eliminate tumors by restoring host immunity. The objective of this study is to investigate the underlying immune mechanisms of anti-tumor activity associated with Qi-supplementing herbs, specifically the paired use of Huangqi and Danggui.

METHODS

Analysis of compatibility regularity was conducted to screen the combination of Qi-supplementing TCMs. Using the MTT assay and a transplanted tumor mice model, the anti-tumor effects of combination TCMs were investigated in vitro and in vivo. High content analysis and flow cytometry were then used to evaluate cellular immunity, followed by network pharmacology and molecular docking to dissect the significant active compounds and potential mechanisms. Finally, the anti-tumor activity and the mechanism of the active ingredients were verified by molecular experiments.

RESULTS

There is an optimal combination of Huangqi and Danggui that, administered as an aqueous extract, can activate immunity to suppress tumor and is more effective than each drug on its own in vitro and in vivo. Based on network pharmacology analysis, PIK3R1 is the core target for the anti-tumor immunity activity of combined Huangqi and Danggui. Molecular docking analysis shows 6 components of the combined Danggui and Huangqi extract (quercetin, jaranol, isorhamnetin, kaempferol, calycosin, and suchilactone) that bind to PIK3R1. Jaranol is the most important component against breast cancer. The suchilactone/jaranol combination and, especially, the suchilactone/kaempferol combination are key for immunity enhancement and the anti-tumor effects of the extract.

CONCLUSIONS

The combination of Huangqi and Danggui can activate immunity to suppress breast cancer and is more effective than the individual drugs alone.

Correlation between Angiotensin Inhibitor Administration and Longer Survival in Patients Who Underwent Curative Resection for Pancreatic Cancer

PURPOSE

The microenvironment of pancreatic ductal adenocarcinoma (PDAC) with extensive desmoplastic stroma contributes to aggressive cancer behavior. Angiotensin system inhibitors (ASIs) reduce stromal fibrosis and are a promising therapeutic strategy. The purpose of this study was to examine how ASIs affected the oncological results of patients who had their PDAC removed.

MATERIALS AND METHODS

A retrospective assessment was conducted on the clinicopathological and survival data of patients who received curative resection for PDAC at Severance Hospital between January 2012 and December 2019.

RESULTS

A total of 410 participants (228 male and 182 female), with a median follow-up period of 12.8 months, were included in this study. Patients were divided into three groups, based on ASI use and history of hypertension: group 1, normotensive and never used ASI (n=210, 51.2%); group 2, ASI non-users with hypertension (n=50, 12.2%); and group 3, ASI users with hypertension (n=150, 36.6%). The three groups did not differ significantly in terms of age, sex, kind of operation, T and N stages, or adjuvant and neoadjuvant therapy. Moreover, there was no discernible difference in disease-free survival between those who used ASI and those who did not (p=0.636). The 5-year overall survival (OS) rates in groups 1, 2, and 3 were 52.6%, 32.3%, and 38.0%, respectively. However, the OS rate of ASI users was remarkably higher than that of non-users (p=0.016).

CONCLUSION

In patients with resected PDAC, ASI is linked to longer survival rates. Furthermore, for individuals with hypertension, ASI in conjunction with conventional chemotherapy may be an easy and successful treatment option.

The tumor-associated fibrotic reactions in microenvironment aggravate glioma chemoresistance

Malignant gliomas are one of the most common and lethal brain tumors with poor prognosis. Most patients with glioblastoma (GBM) die within 2 years of diagnosis, even after receiving standard treatments including surgery combined with concomitant radiotherapy and chemotherapy. Temozolomide (TMZ) is the first-line chemotherapeutic agent for gliomas, but the frequent acquisition of chemoresistance generally leads to its treatment failure. Thus, it's urgent to investigate the strategies for overcoming glioma chemoresistance. Currently, many studies have elucidated that cancer chemoresistance is not only associated with the high expression of drug-resistance genes in glioma cells but also can be induced by the alterations of the tumor microenvironment (TME). Numerous studies have explored the use of antifibrosis drugs to sensitize chemotherapy in solid tumors, and surprisingly, these preclinical and clinical attempts have exhibited promising efficacy in treating certain types of cancer. However, it remains unclear how tumor-associated fibrotic alterations in the glioma microenvironment (GME) mediate chemoresistance. Furthermore, the possible mechanisms behind this phenomenon are yet to be determined. In this review, we have summarized the molecular mechanisms by which tumor-associated fibrotic reactions drive glioma transformation from a chemosensitive to a chemoresistant state. Additionally, we have outlined antitumor drugs with antifibrosis functions, suggesting that antifibrosis strategies may be effective in overcoming glioma chemoresistance through TME normalization.

CRISPR/Cas9-mediated silencing of CD44: unveiling the role of hyaluronic acid-mediated interactions in cancer drug resistance

A comprehensive overview of CD44 (CD44 Molecule (Indian Blood Group)), a cell surface glycoprotein, and its interaction with hyaluronic acid (HA) in drug resistance mechanisms across various types of cancer is provided, where CRISPR/Cas9 gene editing was utilized to silence CD44 expression and examine its impact on cancer cell behavior, migration, invasion, proliferation, and drug sensitivity. The significance of the HA-CD44 axis in tumor microenvironment (TME) delivery and its implications in specific cancer types, the influence of CD44 variants and the KHDRBS3 (KH RNA Binding Domain Containing, Signal Transduction Associated 3) gene on cancer progression and drug resistance, and the potential of targeting HA-mediated pathways using CRISPR/Cas9 gene editing technology to overcome drug resistance in cancer were also highlighted.

PD-1/PD-L1 axis induced host immunosuppression via PI3K/Akt/mTOR signalling pathway in piglets infected by Glaesserella Parasuis

Glaesserella parasuis, an important respiratory bacterial pathogen, causes Glässer's disease in piglets, with potential immunosuppression. We established a piglet infection model and explored the immunosuppression mechanism to improve our understanding of the host immune response to G. parasuis. Twenty piglets were randomly divided into two groups (n = 10). The infection group was intraperitoneally challenged with 2 × 108 CFU of G. parasuis in 2 mL TSB. The control group was intraperitoneally injected with equivalent TSB. After 72 h, the piglets were sacrificed, and spleen tissue was collected. PD-1/PD-L1 expression was determined. The splenocytes were isolated to detect CD3+ T, CD3+CD4+ T, CD3+CD8+ T and CD3-CD21+cell differentiation. Via data-independent acquisition (DIA), we compared the proteomics of healthy and infected spleen tissues. Glaesserella parasuis modified CD3+ T, CD3+CD4+ T, CD3+CD8+ T and CD3-CD21+ cell differentiation and PD-1/PD-L1 expression in the spleen. The infection group had 596 proteins with significant differences in expression, of which 301 were significantly upregulated and 295 downregulated. Differentially expressed proteins (DEPs) were mainly related to immune responses. This is the first study on PD-1/PD-L1 expression in the spleen associated with immunosuppression in a piglet model to explore the protein changes related to immune responses via DIA.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

A new era in cancer treatment: harnessing ZIF-8 nanoparticles for PD-1 inhibitor delivery

This review delves into the potential of zeolitic imidazolate framework-8 (ZIF-8) nanoparticles in augmenting the efficacy of cancer immunotherapy, with a special focus on the delivery of programmed cell death receptor 1 (PD-1) inhibitors. The multifunctional nature of ZIF-8 nanoparticles as drug carriers is emphasized, with their ability to encapsulate a range of therapeutic agents, including PD-1 inhibitors, and facilitate their targeted delivery to tumor locations. By manipulating the pore size and surface characteristics of ZIF-8 nanoparticles, controlled drug release can be realized. The strategic use of ZIF-8 nanoparticles to deliver PD-1 inhibitors presents a precise and targeted modality for cancer treatment, reducing off-target impacts and enhancing therapeutic effectiveness. This combined strategy addresses the existing challenges and constraints of current immunotherapy techniques, with the ultimate goal of enhancing patient outcomes in cancer therapy.

Repurposing Therapeutic Drugs Complexed to Vanadium in Cancer

Repurposing drugs by uncovering new indications for approved drugs accelerates the process of establishing new treatments and reduces the high costs of drug discovery and development. Metal complexes with clinically approved drugs allow further opportunities in cancer therapy-many vanadium compounds have previously shown antitumor effects, which makes vanadium a suitable metal to complex with therapeutic drugs, potentially improving their efficacy in cancer treatment. In this review, covering the last 25 years of research in the field, we identified non-oncology-approved drugs suitable as ligands to obtain different vanadium complexes. Metformin-decavanadate, vanadium-bisphosphonates, vanadyl(IV) complexes with non-steroidal anti-inflammatory drugs, and cetirizine and imidazole-based oxidovanadium(IV) complexes, each has a parent drug known to have different medicinal properties and therapeutic indications, and all showed potential as novel anticancer treatments. Nevertheless, the precise mechanisms of action for these vanadium compounds against cancer are still not fully understood.