To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases

CRISPR-Cas-based biosensors for the detection of cancer biomarkers

Along with discovering cancer biomarkers, non-invasive detection methods have played a critical role in early cancer diagnosis and prognostic improvement. Some traditional detection methods have been used for detecting cancer biomarkers, but they are time-consuming and involve materials and human costs. With great flexibility, sensitivity and specificity, the clustered regularly interspaced short palindromic repeats (CRISPR)-associated system provides a wide range of application prospects in this field. Herein, we introduce the background of the CRISPR-Cas (CRISPR-associated) system and comprehensively summarize the diagnosis strategies of cancer mediated by the CRISPR-Cas system, including four kinds of biochemical-based markers: nucleic acid, enzyme, tumor-specific protein and exosome. Furthermore, we discuss the challenges in implementing the CRISPR-Cas system in clinical applications.

Recent advances in CRISPR-Cas systems for colorectal cancer research and therapeutics

INTRODUCTION

Colon cancer, ranked as the fourth leading global cause of cancer death, exhibits a complex progression marked by genetic variations. Over the past decade, the utilization of diverse CRISPR systems has propelled accelerated research into colorectal cancer (CRC) treatment.

AREAS COVERED

CRISPR/Cas9, a key player in this research, identifies new oncogenes, tumor suppressor genes (TSGs), and drug-resistance genes. Additionally, it facilitates the construction of experimental models, conducts genome-wide library screening, and develops new therapeutic targets, especially for targeted knockout in vivo or molecular targeted drug delivery, contributing to personalized treatments and significantly enhancing the care of colon cancer patients. In this review, we provide insights into the mechanism of the CRISPR/Cas9 system, offering a comprehensive exploration of its applications in CRC, spanning screening, modeling, gene functions, diagnosis, and gene therapy. While acknowledging its transformative potential, the article  highlights the challenges and limitations of CRISPR systems.

EXPERT OPINION

The application of CRISPR/Cas9 in CRC research provides a promising avenue for personalized treatments. Its potential for identifying key genes and enabling experimental models and genome-wide screening enhances patient care. This review underscores the significance of CRISPR-Cas9 gene editing technology across basic research, diagnosis, and the treatment landscape of colon cancer.

Challenges for gene therapy in the financial sustainability of health systems: a scoping review

AIM

To review the available evidence about the strategies implemented or proposed for coverage or reimbursement for currently approved gene therapies.

METHODS

A scoping review was conducted to analyze the evidence published during the years 2016 to 2023. The main search criteria were coverage or reimbursement of gene therapy by healthcare systems. The eligible articles were those that described or proposed a financing model used to provide coverage in the various systems around the world.

RESULTS

The study identified 279 publications, and after removing duplicates and screening for eligibility, 10 were included in the study. The results show that various financing models have been proposed, including subscription-based payment models, outcome-based payment models, and amortization strategies. However, several barriers to implementing these models were identified, such as deficiencies in informatics systems for data collection, changes in laws or regulations, the lack of accessible clinical endpoints and administrative costs.

CONCLUSION

This scoping review provides an overview of financing strategies for gene therapies. Gene therapies can cure rare or previously intractable diseases, but their high cost can make access difficult. Publishing experiences with these models can help evaluate their use and gather more evidence for their effectiveness.

The upregulation and transcriptional regulatory mechanisms of Extra spindle pole bodies like 1 in bladder cancer: An immunohistochemistry and high-throughput screening Evaluation

Background

This study aimed to explore the expression level and transcriptional regulation mechanism of Extra Spindle Pole Bodies Like 1 (ESPL1) in bladder cancer (BC).

Methods

A multicentre database of samples (n = 1391) was assayed for ESPL1 mRNA expression in BC and validated at the protein level by immunohistochemical (IHC) staining of in-house samples (n = 202). Single-cell sequencing (scRNA-seq) analysis and enrichment analysis explored ESPL1 distribution and their accompanying molecular mechanisms. ATAC-seq, ChIP-seq and Hi-C data from multiple platforms were used to investigate ESPL1 upstream transcription factors (TFs) and potential epigenetic regulatory mechanisms. Immune-related analysis, drug sensitivity and molecular docking of ESPL1 were also calculated. Furthermore, upstream microRNAs and the binding sites of ESPL1 were predicted. The expression level and early screening efficacy of miR-299-5p in blood (n = 6625) and tissues (n = 537) were examined.

Results

ESPL1 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 0.75; 95 % CI = 0.09, 1.40), and IHC staining of in-house samples verified this finding (p < 0.0001). ESPL1 was predominantly distributed in BC epithelial cells. Coexpressed genes of ESPL1 were enriched in cell cycle-related signalling pathways, and ESPL1 might be involved in the communication between epithelial and residual cells in the Hippo, ErbB, PI3K-Akt and Ras signalling pathways. Three TFs (H2AZ, IRF5 and HIF1A) were detected upstream of ESPL1 and presence of promoter-super enhancer and promoter-typical enhancer loops. ESPL1 expression was correlated with various immune cell infiltration levels. ESPL1 expression might promote BC growth and affect the sensitivity and therapeutic efficacy of paclitaxel and gemcitabine in BC patients. As an upstream regulator of ESPL1, miR-299-5p expression was downregulated in both the blood and tissues, possessing great potential for early screening.

Conclusions

ESPL1 expression was upregulated in BC and was mainly distributed in epithelial cells. Elevated ESPL1 expression was associated with TFs at the upstream transcription start site (TSS) and distant chromatin loops of regulatory elements. ESPL1 might be an immune-related predictive and diagnostic marker for BC, and the overexpression of ESPL1 played a cancer-promoting role and affected BC patients' sensitivity to drug therapy. miR-299-5p was downregulated in BC blood and tissues and was also expected to be a novel marker for early screening.

Radiogenomic landscape: Assessment of specific phagocytosis regulators in lower-grade gliomas

Genome-wide CRISPR-Cas9 knockout screens have emerged as a powerful method for identifying key genes driving tumor growth. The aim of this study was to explore the phagocytosis regulators (PRs) specifically associated with lower-grade glioma (LGG) using the CRISPR-Cas9 screening database. Identifying these core PRs could lead to novel therapeutic targets and pave the way for a non-invasive radiogenomics approach to assess LGG patients' prognosis and treatment response. We selected 24 PRs that were overexpressed and lethal in LGG for analysis. The identified PR subtypes (PRsClusters, geneClusters, and PRs-score models) effectively predicted clinical outcomes in LGG patients. Immune response markers, such as CTLA4, were found to be significantly associated with PR-score. Nine radiogenomics models using various machine learning classifiers were constructed to uncover survival risk. The area under the curve (AUC) values for these models in the test and training datasets were 0.686 and 0.868, respectively. The CRISPR-Cas9 screen identified novel prognostic radiogenomics biomarkers that correlated well with the expression status of specific PR-related genes in LGG patients. These biomarkers successfully stratified patient survival outcomes and treatment response using The Cancer Genome Atlas (TCGA) database. This study has important implications for the development of precise clinical treatment strategies and holds promise for more accurate therapeutic approaches for LGG patients in the future.

Systems Medicine for Precise Targeting of Glioblastoma

Glioblastoma (GBM) is a malignant cancer that is fatal even after standard therapy and the effects of current available therapeutics are not promising due its complex and evolving epigenetic and genetic profile. The mysteries that lead to GBM intratumoral heterogeneity and subtype transitions are not entirely clear. Systems medicine is an approach to view the patient in a whole picture integrating systems biology and synthetic biology along with computational techniques. Since the GBM oncogenesis involves genetic mutations, various therapies including gene therapeutics based on CRISPR-Cas technique, MicroRNAs, and implanted synthetic cells endowed with synthetic circuits against GBM with neural stem cells and mesenchymal stem cells acting as potential vehicles carrying therapeutics via the intranasal route, avoiding the risks of invasive methods in order to reach the GBM cells in the brain are discussed and proposed in this review. Systems medicine approach is a rather novel strategy, and since the GBM of a patient is complex and unique, thus to devise an individualized treatment strategy to tailor personalized multimodal treatments for the individual patient taking into account the phenotype of the GBM, the unique body health profile of the patient and individual responses according to the systems medicine concept might show potential to achieve optimum effects.

Network Biology-Inspired Machine Learning Features Predict Cancer Gene Targets and Reveal Target Coordinating Mechanisms

Anticipating and understanding cancers' need for specific gene activities is key for novel therapeutic development. Here we utilized DepMap, a cancer gene dependency screen, to demonstrate that machine learning combined with network biology can produce robust algorithms that both predict what genes a cancer is dependent on and what network features coordinate such gene dependencies. Using network topology and biological annotations, we constructed four groups of novel engineered machine learning features that produced high accuracies when predicting binary gene dependencies. We found that in all examined cancer types, F1 scores were greater than 0.90, and model accuracy remained robust under multiple hyperparameter tests. We then deconstructed these models to identify tumor type-specific coordinators of gene dependency and identified that in certain cancers, such as thyroid and kidney, tumors' dependencies are highly predicted by gene connectivity. In contrast, other histologies relied on pathway-based features such as lung, where gene dependencies were highly predictive by associations with cell death pathway genes. In sum, we show that biologically informed network features can be a valuable and robust addition to predictive pharmacology models while simultaneously providing mechanistic insights.

Identification of the Factor That Leads Human Mesenchymal Stem Cell Lines into Decellularized Bone

Hematopoiesis is maintained by the interaction of hematopoietic stem cells (HSCs) and bone marrow mesenchymal stem cells (MSCs) in bone marrow microenvironments, called niches. Certain genetic mutations in MSCs, not HSCs, provoke some hematopoietic neoplasms, such as myelodysplastic syndrome. An in vivo bone marrow niche model using human MSC cell lines with specific genetic mutations and bone scaffolds is necessary to elucidate these interactions and the disease onset. We focused on decellularized bone (DCB) as a useful bone scaffold and attempted to induce human MSCs (UE7T-9 cells) into the DCB. Using the CRISPR activation library, we identified SHC4 upregulation as a candidate factor, with the SHC4 overexpression in UE7T-9 cells activating their migratory ability and upregulating genes to promote hematopoietic cell migration. This is the first study to apply the CRISPR library to engraft cells into decellularized biomaterials. SHC4 overexpression is essential for engrafting UE7T-9 cells into DCB, and it might be the first step toward creating an in vivo human–mouse hybrid bone marrow niche model.

High-Throughput CRISPR Screening in Hematological Neoplasms

CRISPR is becoming an indispensable tool in biological research, revolutionizing diverse fields of medical research and biotechnology. In the last few years, several CRISPR-based genome-targeting tools have been translated for the study of hematological neoplasms. However, there is a lack of reviews focused on the wide uses of this technology in hematology. Therefore, in this review, we summarize the main CRISPR-based approaches of high throughput screenings applied to this field. Here we explain several libraries and algorithms for analysis of CRISPR screens used in hematology, accompanied by the most relevant databases. Moreover, we focus on (1) the identification of novel modulator genes of drug resistance and efficacy, which could anticipate relapses in patients and (2) new therapeutic targets and synthetic lethal interactions. We also discuss the approaches to uncover novel biomarkers of malignant transformations and immune evasion mechanisms. We explain the current literature in the most common lymphoid and myeloid neoplasms using this tool. Then, we conclude with future directions, highlighting the importance of further gene candidate validation and the integration and harmonization of the data from CRISPR screening approaches.

Synthetic Vulnerabilities in the KRAS Pathway

Mutations in Kristen Rat Sarcoma viral oncogene (KRAS) are among the most frequent gain-of-function genetic alterations in human cancer. Most KRAS-driven cancers depend on its sustained expression and signaling. Despite spectacular recent success in the development of inhibitors targeting specific KRAS alleles, the discovery and utilization of effective directed therapies for KRAS-mutant cancers remains a major unmet need. One potential approach is the identification of KRAS-specific synthetic lethal vulnerabilities. For example, while KRAS-driven oncogenesis requires the activation of a number of signaling pathways, it also triggers stress response pathways in cancer cells that could potentially be targeted for therapeutic benefit. This review will discuss how the latest advances in functional genomics and the development of more refined models have demonstrated the existence of molecular pathways that can be exploited to uncover synthetic lethal interactions with a promising future as potential clinical treatments in KRAS-mutant cancers.