Single-cell RNA sequencing and bioinformatics as tools to decipher cancer heterogenicity and mechanisms of drug resistance

Applications of single-cell technologies in drug discovery for tumor treatment

Single-cell technologies have been known as advanced and powerful tools to study tumor biological systems at the single-cell resolution and are playing increasingly critical roles in multiple stages of drug discovery and development. Specifically, single-cell technologies can promote the discovery of drug targets, help high-throughput screening at single-cell level, and contribute to pharmacokinetic studies of anti-tumor drugs. Emerging single-cell analysis technologies have been developed to further integrating multidimensional single-cell molecular features, expanding the scale of single-cell data, profiling phenotypic impact of genes in single cell, and providing full-length coverage single-cell sequencing. In this review, we systematically summarized the applications of single-cell technologies in various sections of drug discovery for tumor treatment, including target identification, high-throughput drug screening, and pharmacokinetic evaluation and highlighted emerging single-cell technologies in providing in-depth understanding of tumor biology. Single-cell-technology-based drug discovery is expected to further optimize therapeutic strategies and improve clinical outcomes of tumor patients.

LPCAT2 inhibits colorectal cancer progression via the PRMT1/SLC7A11 axis

Colorectal cancer (CRC) has a high degree of heterogeneity and identifying the genetic information of individual tumor cells could help enhance our understanding of tumor biology and uncover potential therapeutic targets for CRC. In this study, we identified LPCAT2+ tumor cell populations with less malignancy than LPCAT2- tumor cells in human and mouse CRC tissues using scRNA-seq. Combining in vitro and in vivo experiments, we found that LPCAT2 could inhibit the proliferation of CRC cells by inducing ferroptosis. Mechanistically, LPCAT2 arrested PRMT1 in cytoplasm of CRC cells via regulating acetylation of PRMT1 at the K145 site. In turn, PRMT1 enhanced SLC7A11 promoter activity. Thus, LPCAT2 attenuated the positive regulatory effect of PRMT1 on SLC7A11 promoter. Notably, SLC7A11 acts as a ferroptosis regulator. Furthermore, in LPCAT2 knockout mice (LPCAT2-/-) colon cancer model, we found that LPCAT2-/- mice exhibited more severe lesions, while PRMT1 or SLC7A11 inhibitors delayed the progression. Altogether, we elucidated that LPCAT2 suppresses SLC7A11 expression by inhibiting PRMT1 nuclear translocation, thereby inducing ferroptosis in CRC cells. Moreover, inhibitors of the PRMT1/SLC7A11 axis could delay tumor progression in CRC with low LPCAT2 expression, making it a potentially effective treatment for CRC.

A novel long non-coding RNA LINC00524 facilitates invasion and metastasis through interaction with TDP43 in breast cancer

Breast cancer (BC) remains a significant health concern worldwide, with metastasis being a primary contributor to patient mortality. While advances in understanding the disease's progression continue, the underlying mechanisms, particularly the roles of long non-coding RNAs (lncRNAs), are not fully deciphered. In this study, we examined the influence of the lncRNA LINC00524 on BC invasion and metastasis. Through meticulous analyses of TCGA and GEO data sets, we observed a conspicuous elevation of LINC00524 expression in BC tissues. This increased expression correlated strongly with a poorer prognosis for BC patients. A detailed Gene Ontology analysis suggested that LINC00524 likely exerts its effects through RNA-binding proteins (RBPs) mechanisms. Experimentally, LINC00524 was demonstrated to amplify BC cell migration, invasion and proliferation in vitro. Additionally, in vivo tests showed its potent role in promoting BC cell growth and metastasis. A pivotal discovery was LINC00524's interaction with TDP43, which leads to the stabilization of TDP43 protein expression, an element associated with unfavourable BC outcomes. In essence, our comprehensive study illuminates how LINC00524 accelerates BC invasion and metastasis by binding to TDP43, presenting potential avenues for therapeutic interventions.

A novel prognostic model of breast cancer based on cuproptosis-related lncRNAs

OBJECTIVE

Breast cancer (BC) is a deadly form of malignancy responsible for the death of a large number of women every year. Cuproptosis is a newly discovered form of cell death that may have implications for the prognosis of BC. Long non-coding RNAs (lncRNAs) have been shown to be involved in the progression and development of BC. Here within, a novel model capable of predicting the prognosis of patients with BC was established based on cuproptosis-related lncRNAs.

METHODS

Data of breast cancer patients was downloaded, including clinical information from The Cancer Genome Atlas (TCGA) database and lncRNAs related to cuproptosis were isolated. In total, nine lncRNAs related to copper death were obtained by Cox regression model based on Least Absolute Shrinkage and Selector Operation (LASSO) algorithm for model construction. The model was verified by overall survival (OS), progression-free survival (PFS) and receiver operating characteristic (ROC) curve. The differences in immune function, tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) between patients with different risk scores were analyzed.

RESULTS

Based on cuproptosis-related lncRNAs, a prognostic model for predicting BC was constructed. Each patient was assigned a risk score based on our model formula. We found that patients with higher risk scores had significantly lower OS and PFS, increased TMB, and higher sensitivity to immunotherapy.

CONCLUSIONS

The model established in this study based on cuproptosis-related lncRNAs may be capable of improving the OS of patients with BC.

Resistance to PRMT5-targeted therapy in mantle cell lymphoma

ABSTRACT

Mantle cell lymphoma (MCL) is an incurable B-cell non-Hodgkin lymphoma, and patients who relapse on targeted therapies have poor prognosis. Protein arginine methyltransferase 5 (PRMT5), an enzyme essential for B-cell transformation, drives multiple oncogenic pathways and is overexpressed in MCL. Despite the antitumor activity of PRMT5 inhibition (PRT-382/PRT-808), drug resistance was observed in a patient-derived xenograft (PDX) MCL model. Decreased survival of mice engrafted with these PRMT5 inhibitor-resistant cells vs treatment-naive cells was observed (P = .005). MCL cell lines showed variable sensitivity to PRMT5 inhibition. Using PRT-382, cell lines were classified as sensitive (n = 4; 50% inhibitory concentration [IC50], 20-140 nM) or primary resistant (n = 4; 340-1650 nM). Prolonged culture of sensitive MCL lines with drug escalation produced PRMT5 inhibitor-resistant cell lines (n = 4; 200-500 nM). This resistant phenotype persisted after prolonged culture in the absence of drug and was observed with PRT-808. In the resistant PDX and cell line models, symmetric dimethylarginine reduction was achieved at the original PRMT5 inhibitor IC50, suggesting activation of alternative resistance pathways. Bulk RNA sequencing of resistant cell lines and PDX relative to sensitive or short-term-treated cells, respectively, highlighted shared upregulation of multiple pathways including mechanistic target of rapamycin kinase [mTOR] signaling (P < 10-5 and z score > 0.3 or < 0.3). Single-cell RNA sequencing analysis demonstrated a strong shift in global gene expression, with upregulation of mTOR signaling in resistant PDX MCL samples. Targeted blockade of mTORC1 with temsirolimus overcame the PRMT5 inhibitor-resistant phenotype, displayed therapeutic synergy in resistant MCL cell lines, and improved survival of a resistant PDX.

Comprehensive characterization of adipogenesis-related genes in colorectal cancer for clinical significance and immunogenomic landscape analyses

OBJECTIVE

Colorectal cancer (CRC) is a major global health concern, necessitating the identification of biomarkers and molecular subtypes for improved clinical management. This study aims to evaluate the clinical value of adipogenesis-related genes and molecular subtypes in CRC.

METHODS

A comprehensive analysis of adipogenesis-related genes in CRC was performed using publicly available datasets (TCGA and GEO database) and bioinformatics tools. Unsupervised cluster analysis was employed to identify the molecular subtypes of CRC, while LASSO regression analysis was utilized to develop a risk prognostic model. The immunogenomic patterns and immunotherapy analysis were used to predict patient response to immunotherapy. Furthermore, qPCR analysis was conducted to confirm the expression of the identified key genes in vitro.

RESULTS

Through the analysis of RNAseq data from normal and tumor tissues, we identified 50 differentially expressed genes. Unsupervised cluster analysis identified two subtypes (Cluster A and Cluster B) with significantly different survival outcomes. Cluster A and B displayed differential immune cell compositions and enrichment in specific biological pathways, providing insights into potential therapeutic targets. A risk-scoring model was developed using five ARGs, which successfully classified patients into high and low-risk groups, showing distinct survival outcomes. The model was validated and showed robust predictive performance. High-risk patients exhibited altered immune cell proportions and gene expression patterns compared to low-risk patients. In qPCR validation, four out of the five key genes were consistent with the results of bioinformatics analysis.

CONCLUSION

Overall, the findings of our investigation offer valuable understanding regarding the clinical relevance of ARGs and molecular subtypes in CRC, laying the groundwork for improved precision medicine applications and personalized treatment modalities.

Self-Renewal and Pluripotency in Osteosarcoma Stem Cells' Chemoresistance: Notch, Hedgehog, and Wnt/β-Catenin Interplay with Embryonic Markers

Osteosarcoma is a highly malignant bone tumor derived from mesenchymal cells that contains self-renewing cancer stem cells (CSCs), which are responsible for tumor progression and chemotherapy resistance. Understanding the signaling pathways that regulate CSC self-renewal and survival is crucial for developing effective therapies. The Notch, Hedgehog, and Wnt/β-Catenin developmental pathways, which are essential for self-renewal and differentiation of normal stem cells, have been identified as important regulators of osteosarcoma CSCs and also in the resistance to anticancer therapies. Targeting these pathways and their interactions with embryonic markers and the tumor microenvironment may be a promising therapeutic strategy to overcome chemoresistance and improve the prognosis for osteosarcoma patients. This review focuses on the role of Notch, Hedgehog, and Wnt/β-Catenin signaling in regulating CSC self-renewal, pluripotency, and chemoresistance, and their potential as targets for anti-cancer therapies. We also discuss the relevance of embryonic markers, including SOX-2, Oct-4, NANOG, and KLF4, in osteosarcoma CSCs and their association with the aforementioned signaling pathways in overcoming drug resistance.

The non-coding competing endogenous RNAs in acute myeloid leukemia: biological and clinical implications

Acute myeloid leukemia (AML) is a hematologic carcinoma that has seen a considerable improvement in patient prognosis because of genetic diagnostics and molecularly-targeted therapies. Nevertheless, recurrence and drug resistance remain significant obstacles to leukemia treatment. It is critical to investigate the underlying molecular mechanisms and find solutions. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), circular RNAs, long non-coding RNAs, and pseudogenes, have been found to be crucial components in driving cancer. The competing endogenous RNA (ceRNA) mechanism has expanded the complexity of miRNA-mediated gene regulation. A great deal of literature has shown that ncRNAs are essential to the biological functions of the ceRNA network (ceRNET). NcRNAs can compete for the same miRNA response elements to influence miRNA-target RNA interactions. Recent evidence suggests that ceRNA might be a potential biomarker and therapeutic strategy. So far, however, there have been no comprehensive studies on ceRNET about AML. What is not yet clear is the clinical application of ceRNA in AML. This study attempts to summarize the development of research on the related ceRNAs in AML and the roles of ncRNAs in ceRNET. We also briefly describe the mechanisms of ceRNA and ceRNET. What's more significant is that we explore the clinical value of ceRNAs to provide accurate diagnostic and prognostic biomarkers as well as therapeutic targets. Finally, limitations and prospects are considered.

Understanding Breast Cancers through Spatial and High-Resolution Visualization Using Imaging Technologies

Breast cancer is the most common cancer affecting women worldwide. Although many analyses and treatments have traditionally targeted the breast cancer cells themselves, recent studies have focused on investigating entire cancer tissues, including breast cancer cells. To understand the structure of breast cancer tissues, including breast cancer cells, it is necessary to investigate the three-dimensional location of the cells and/or proteins comprising the tissues and to clarify the relationship between the three-dimensional structure and malignant transformation or metastasis of breast cancers. In this review, we aim to summarize the methods for analyzing the three-dimensional structure of breast cancer tissue, paying particular attention to the recent technological advances in the combination of the tissue-clearing method and optical three-dimensional imaging. We also aimed to identify the latest methods for exploring the relationship between the three-dimensional cell arrangement in breast cancer tissues and the gene expression of each cell. Finally, we aimed to describe the three-dimensional imaging features of breast cancer tissues using noninvasive photoacoustic imaging methods.

Applications and Achievements of Single-Cell Sequencing in Gastrointestinal Cancer

Gastrointestinal cancer represents a public health concern that seriously endangers human health. The emerging single-cell sequencing (SCS) technologies are different from the large-scale sequencing technologies which provide inaccurate data. SCS is a powerful tool for deciphering the single-cell resolutions of cellular and molecular landscapes, revealing the features of single-cell genomes, transcriptomes, and epigenomes. Recently, SCS has been applied in the field of gastrointestinal cancer research for clarifying the origin and heterogeneity of gastrointestinal cancer, acquiring micro-environmental information, and improving diagnostic and treatment methods. This review outlines the applications of SCS in gastrointestinal cancer research and summarizes the most recent advances in the field.