CRISPR/Cas9 as precision and high-throughput genetic engineering tools in gastrointestinal cancer research and therapy

CRISPR technology in human diseases

Gene editing is a growing gene engineering technique that allows accurate editing of a broad spectrum of gene-regulated diseases to achieve curative treatment and also has the potential to be used as an adjunct to the conventional treatment of diseases. Gene editing technology, mainly based on clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated protein systems, which is capable of generating genetic modifications in somatic cells, provides a promising new strategy for gene therapy for a wide range of human diseases. Currently, gene editing technology shows great application prospects in a variety of human diseases, not only in therapeutic potential but also in the construction of animal models of human diseases. This paper describes the application of gene editing technology in hematological diseases, solid tumors, immune disorders, ophthalmological diseases, and metabolic diseases; focuses on the therapeutic strategies of gene editing technology in sickle cell disease; provides an overview of the role of gene editing technology in the construction of animal models of human diseases; and discusses the limitations of gene editing technology in the treatment of diseases, which is intended to provide an important reference for the applications of gene editing technology in the human disease.

A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection

Background

Pancreatic cancer is characterized by an extremely poor prognosis, even following potentially curative resection. Classical prognostic markers such as histopathological or clinical parameters have limited predictive power. The present study aimed to establish a prognostic model combining mRNA expression data with histopathological and clinical data to better predict survival and stratify pancreatic cancer patients following resection. We pioneered three models in one study and systematically evaluated the clinical benefits of all three models.

Methods

To identify differentially expressed genes in pancreatic cancer, mRNA data from normal (GTEx database) and pancreatic cancer (TCGA database) tissues were used. Survival analysis was carried out to identify prognosis-relevant genes from the identified differentially expressed genes and LASSO regression was used to filter out hub genes. The risk score of several hub genes was calculated according to gene expression and coefficients. Validation was carried out using an independent set of GEO microarray data. Multivariate COX regression was used for identifying independent clinical and pathological risk factors related to patient's survival in the TCGA database and a prognostic model combining mRNA expression data with histopathological and clinical data was established. Another prognostic model using clinicopathological factors from the SEER database was conceived based on multivariate COX regression. NRI (net reclassification improvement) and IDI (integrated discrimination index) were used to compare the predictive capabilities of the different models.

Results

We identified 1589 differentially expressed genes (DEGs) through the comparison of normal and pancreatic cancer tissues, of whom 317 were associated with prognosis(p < 0.05). LASSO regression identified five hub genes, MYEOV, ANXA2P2, MET, CEP55, and KRT7, that were used for the five-mRNA-classifier prognostic model. The classifier could stratify patients into a short and long survival group: 5-year overall survival in the training set (TCGA, 6 % vs 52 %, p < 0.001), test set (TCGA, 18 % vs 55 %,p < 0.01) and external validation set (GEO, 0 % vs 25 %, p < 0.05). Sensitivity analysis showed that the mRNA model (model 1) was better than the clinicopathological no-mRNA model (model 2) in predicting 5-year survival in the TCGA database (AUC: 0.877 vs 0.718, z = 3.165, p < 0.01) and better than the multi-factor prognostic model (model 3) from the SEER database (AUC: 0.754, z = 2.637, p < 0.01). On predictive performance, model 1 improved model 2 (NRI = 0.084, z = 1.288, p = 0.198; IDI = 0.055, z = 1.041,p = 0.298) and model 3 (NRI = 0.167,z = 1.961,p = 0.05; IDI = 0.086, z = 1.427, p = 0.154).

Conclusion

The five-mRNA-classifier is a reliable and feasible instrument to predict the prognosis of pancreatic cancer patients following resection. It might help in patiens counseling and assist clinicians in providing individualized treatment for patients in different risk groups.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Intelligent berberine-loaded erythrocytes attenuated inflammatory cytokine productions in macrophages

Erythrocytes are impressive tools for drug delivery, especially to macrophages. Therefore, berberine was loaded into erythrocytes using both hypotonic pre-swelling and endocytosis methods to target macrophages. Physicochemical and kinetic parameters of the resulting carrier cells, such as drug loading/release kinetics, osmotic fragility, and hematological indices, were determined. Drug loading was optimized for the study using Taguchi experimental design and lab experiments. Loaded erythrocytes were targeted to macrophages using ZnCl2 and bis-sulfosuccinimidyl-suberate, and targeting was evaluated using flow cytometry and Wright-Giemsa staining. Differentiated macrophages were stimulated with lipopolysaccharide, and the inflammatory profiles of macrophages were evaluated using ELISA, western blotting, and real-time PCR. Findings indicated that the endocytosis method is preferred due to its low impact on the erythrocyte's structural integrity. Maximum loading achieved (1386.68 ± 22.43 μg/ml) at 1500 μg/ml berberine treatment at 37 °C for 2 h. Berberine successfully inhibited NF-κB translation in macrophages, and inflammatory response markers such as IL-1β, IL-8, IL-23, and TNF-α were decreased by approximately ninefold, sixfold, twofold, eightfold, and twofold, respectively, compared to the LPS-treated macrophages. It was concluded that berberine-loaded erythrocytes can effectively target macrophages and modulate the inflammatory response.

Epigenetic disruption of histone deacetylase-2 accelerated apoptotic signaling and retarded malignancy in gastric cells

Background: The objective of this research was to determine whether HDAC2 function is associated with gastric cancer progression. Methods: HDAC2 was knocked out in EPG85.257 cells using CRISPR/Cas9 and tumorigenesis pathways were evaluated. Results: Cell proliferation, colony formation, wound healing and transwell invasion were inhibited in ΔHDAC2:EPG85.257 cells. Quantitative analyses revealed a significant downregulation of MMP1, p53, Bax, MAPK1, MAPK3, pro-Caspase3, ERK1/2, p-ERK1/2, AKT1/2/3, p-AKT1/2/3, p-NF-κB (p65), Twist, Snail and p-FAK transcripts/proteins, while SIRT1, PTEN, p21 and Caspase3 were upregulated in ΔHDAC2:EPG85.257 cells. Conclusion: These results indicated that HDAC2 enhanced migration, colony formation and transmigration ability. HDAC2 inhibition may improve gastric cancer chemotherapy pathways.

Essential genes analysis reveals small ribosomal subunit protein eS28 may be a prognostic factor and potential vulnerability in osteosarcoma

Background

Osteosarcoma, the most common primary malignant bone tumor, is currently treated with surgery combined with chemotherapy, but the limited availability of targeted drugs contributes to a poor prognosis. Identifying effective therapeutic targets is crucial for improving the prognosis of osteosarcoma patients.

Methods

We screened the DepMap database to identify essential genes as potential therapeutic targets for osteosarcoma. Gene Set Enrichment Analysis (GSEA) was employed to elucidate the biological roles of these essential genes. Promising candidates were filtered through univariate and multivariate Cox analyses, as well as Kaplan-Meier survival analyses using the GSE21257-OSA and TARGET-OSA datasets. The functional role of the target gene was assessed through cell experiments. Additionally, an in situ nude mice model was established to observe the gene's function, and RNA sequencing was utilized to explore the underlying molecular mechanism.

Results

A total of 934 essential genes were identified based on their effects (Chronos) using the DepMap database. These genes were primarily enriched in the ribosome pathway according to GSEA analysis. Among them, 195 genes were associated with the ribosome pathway. Rps28, Rps7, and Rps25 were validated as promising candidates following univariate and multivariate Cox analyses of the TARGET-OSA and GSE21257-OSA datasets. Kaplan-Meier survival analyses indicated Rps28 represented an especially promising target, with high expression correlating with poor prognosis. Knockdown of small ribosomal subunit protein eS28, the protein of Rps28, inhibited proliferation, migration, and invasion in both in vitro and in vivo experiments. Silencing RPS28 affected the MAPK signaling pathway in osteosarcoma.

Conclusion

In summary, Rps28 has been identified as an essential gene for osteosarcoma cell survival and eS28 may serve as a potential vulnerability in osteosarcoma.

Prime editing: Its systematic optimization and current applications in disease treatment and agricultural breeding

CRISPR/Cas-mediated genome-editing technology has accelerated the development of the life sciences. Prime editing has raised genome editing to a new level because it allows for all 12 types of base substitutions, targeted insertions and deletions, large DNA fragment integration, and even combinations of these edits without generating DNA double-strand breaks. This versatile and game-changing technology has successfully been applied to human cells and plants, and it currently plays important roles in basic research, gene therapy, and crop breeding. Although prime editing has substantially expanded the range of possibilities for genome editing, its efficiency requires improvement. In this review, we briefly introduce prime editing and highlight recent optimizations that have improved the efficiency of prime editors. We also describe how the dual-pegRNA strategy has expanded current editing capabilities, and we summarize the potential of prime editing in treating mammalian diseases and improving crop breeding. Finally, we discuss the limitations of current prime editors and future prospects for optimizing these editors.

New Advances in Gastroenterology: The Crucial Role of Molecular Medicine

The significant progress we have recently observed in the field of gastroenterology, both in the understanding of pathophysiological mechanisms and in the diagnosis and treatment of diseases, is closely related to the improvement and discovery of new biomolecular techniques [...].

Organoid: Bridging the gap between basic research and clinical practice

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy. In addition, we also put forward some practical suggestions on how to construct a new generation of organoid platform, which is destined to vigorously promote the reform of basic-translational medicine.

Unlocking the potential of non-coding RNAs in cancer research and therapy

Non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression, with growing evidence implicating their involvement in cancer development and progression. The potential of ncRNAs as diagnostic and prognostic biomarkers for cancer is promising, with emphasis on their use in liquid biopsy and tissue-based diagnostics. In a nutshell, the review comprehensively summarizes the diverse classes of ncRNAs implicated in cancer, including microRNAs, long non-coding RNAs, and circular RNAs, and their functions and mechanisms of action. Furthermore, we describe the potential therapeutic applications of ncRNAs, including anti-miRNA oligonucleotides, siRNAs, and other RNA-based therapeutics in cancer treatment. However, significant challenges remain in developing effective ncRNA-based diagnostics and therapeutics, including the lack of specificity, limited understanding of mechanisms, and delivery challenges. This review also covers the current state-of-the-art non-coding RNA research technologies and bioinformatic analysis tools. Lastly, we outline future research directions in non-coding RNA research in cancer, including developing novel biomarkers, therapeutic targets, and modalities. In summary, this review provides a comprehensive understanding of non-coding RNAs in cancer and their potential clinical applications, highlighting both the opportunities and challenges in this rapidly evolving field.

Efficient CRISPR/Cas9-mediated gene editing in mammalian cells by the novel selectable traffic light reporters

CRISPR/Cas9 is a powerful tool for gene editing in various cell types and organisms. However, it is still challenging to screen genetically modified cells from an excess of unmodified cells. Our previous studies demonstrated that surrogate reporters can be used for efficient screening of genetically modified cells. Here, we developed two novel traffic light screening reporters, puromycin-mCherry-EGFP (PMG) based on single-strand annealing (SSA) and homology-directed repair (HDR), respectively, to measure the nuclease cleavage activity within transfected cells and to select genetically modified cells. We found that the two reporters could be self-repaired coupling the genome editing events driven by different CRISPR/Cas nucleases, resulting in a functional puromycin-resistance and EGFP selection cassette that can be afforded to screen genetically modified cells by puromycin selection or FACS enrichment. We further compared the novel reporters with different traditional reporters at several endogenous loci in different cell lines, for the enrichment efficiencies of genetically modified cells. The results indicated that the SSA-PMG reporter exhibited improvements in enriching gene knockout cells, while the HDR-PMG system was very useful in enriching knock-in cells. These results provide robust and efficient surrogate reporters for the enrichment of CRISPR/Cas9-mediated editing in mammalian cells, thereby advancing basic and applied research.