Capturing tumour heterogeneity in pre- and post-chemotherapy colorectal cancer ascites-derived cells using single-cell RNA-sequencing

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Metastasis-associated fibroblasts in peritoneal surface malignancies

Over decades, peritoneal surface malignancies (PSMs) have been associated with limited treatment options and poor prognosis. However, advancements in perioperative systemic chemotherapy, cytoreductive surgery (CRS), and hyperthermic intraperitoneal chemotherapy (HIPEC) have significantly improved clinical outcomes. PSMs predominantly result from the spread of intra-abdominal neoplasia, which then form secondary peritoneal metastases. Colorectal, ovarian, and gastric cancers are the most common contributors. Despite diverse primary origins, the uniqueness of the peritoneum microenvironment shapes the common features of PSMs. Peritoneal metastization involves complex interactions between tumour cells and the peritoneal microenvironment. Fibroblasts play a crucial role, contributing to tumour development, progression, and therapy resistance. Peritoneal metastasis-associated fibroblasts (MAFs) in PSMs exhibit high heterogeneity. Single-cell RNA sequencing technology has revealed that immune-regulatory cancer-associated fibroblasts (iCAFs) seem to be the most prevalent subtype in PSMs. In addition, other major subtypes as myofibroblastic CAFs (myCAFs) and matrix CAFs (mCAFs) were frequently observed across PSMs studies. Peritoneal MAFs are suggested to originate from mesothelial cells, submesothelial fibroblasts, pericytes, endothelial cells, and omental-resident cells. This plasticity and heterogeneity of CAFs contribute to the complex microenvironment in PSMs, impacting treatment responses. Understanding these interactions is crucial for developing targeted and local therapies to improve PSMs patient outcomes.

scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network

Cells respond divergently to drugs due to the heterogeneity among cell populations. Thus, it is crucial to identify drug-responsive cell populations in order to accurately elucidate the mechanism of drug action, which is still a great challenge. Here, we address this problem with scRank, which employs a target-perturbed gene regulatory network to rank drug-responsive cell populations via in silico drug perturbations using untreated single-cell transcriptomic data. We benchmark scRank on simulated and real datasets, which shows the superior performance of scRank over existing methods. When applied to medulloblastoma and major depressive disorder datasets, scRank identifies drug-responsive cell types that are consistent with the literature. Moreover, scRank accurately uncovers the macrophage subpopulation responsive to tanshinone IIA and its potential targets in myocardial infarction, with experimental validation. In conclusion, scRank enables the inference of drug-responsive cell types using untreated single-cell data, thus providing insights into the cellular-level impacts of therapeutic interventions.

Drug repurposing for cancer therapy

Cancer, a complex and multifactorial disease, presents a significant challenge to global health. Despite significant advances in surgical, radiotherapeutic and immunological approaches, which have improved cancer treatment outcomes, drug therapy continues to serve as a key therapeutic strategy. However, the clinical efficacy of drug therapy is often constrained by drug resistance and severe toxic side effects, and thus there remains a critical need to develop novel cancer therapeutics. One promising strategy that has received widespread attention in recent years is drug repurposing: the identification of new applications for existing, clinically approved drugs. Drug repurposing possesses several inherent advantages in the context of cancer treatment since repurposed drugs are typically cost-effective, proven to be safe, and can significantly expedite the drug development process due to their already established safety profiles. In light of this, the present review offers a comprehensive overview of the various methods employed in drug repurposing, specifically focusing on the repurposing of drugs to treat cancer. We describe the antitumor properties of candidate drugs, and discuss in detail how they target both the hallmarks of cancer in tumor cells and the surrounding tumor microenvironment. In addition, we examine the innovative strategy of integrating drug repurposing with nanotechnology to enhance topical drug delivery. We also emphasize the critical role that repurposed drugs can play when used as part of a combination therapy regimen. To conclude, we outline the challenges associated with repurposing drugs and consider the future prospects of these repurposed drugs transitioning into clinical application.

Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data

BACKGROUND

Investigations elucidating the complex immunological mechanisms involved in colorectal cancer (CRC) and accurately predicting patient outcomes via bulk RNA-Seq analysis have been notably limited. This study aimed to identify the immune status of CRC patients, construct a prognostic model, and identify prognostic signatures via bulk RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq).

METHODS

The scRNA-seq data of CRC were downloaded from Gene Expression Omnibus (GEO). The UCSC Xena database was used to obtain bulk RNA-seq data. Differentially expressed gene (DEG), functional enrichment, and random forest analyses were conducted in order to identify core genes associated with colorectal cancer (CRC) that were relevant to prognosis. A molecular immune prediction model was developed using logistic regression after screening features using the least absolute shrinkage and selection operator (LASSO). The differences in immune cell infiltration, mutation, chemotherapeutic drug sensitivity, cellular senescence, and communication between patients who were at high and low risk of CRC according to the predictive model were investigated. The prognostic genes that were closely associated with CRC were identified by random survival forest (RSF) analysis. The expression levels and clinical significance of the hub genes were analyzed in vitro. The LoVo cell line was employed to ascertain the biological role of thyroid hormone receptor-interacting protein 6 (TRIP6).

RESULTS

A total of seven main cell subtypes were identified by scRNA-seq analysis. A molecular immune predictive model was constructed based on the risk scores. The risk score was significantly associated with OS, stage, mutation burden, immune cell infiltration, response to immunotherapy, key pathways, and cell-cell communication. The functions of the six hub genes were determined and further utilized to establish a regulatory network. Our findings unequivocally confirmed that TRIP6 upregulation was verified in the CRC samples. After knocking down TRIP6, cell proliferation, migration, and invasion of LoVo cells were inhibited, and apoptosis was promoted.

CONCLUSIONS

The molecular predictive model reliably distinguished the immune status of CRC patients. We further revealed that TRIP6 may act as an oncogene in CRC, making it a promising candidate for targeted therapy and as a prognostic marker for CRC.

Integrated single-cell and bulk RNA sequencing analysis identifies a prognostic signature related to ferroptosis dependence in colorectal cancer

Ferroptosis is an iron-dependent form of cell death induced by lipid oxidation with an essential role in diseases, including cancer. Since prognostic value of ferroptosis-dependent related genes (FDRGs) in colorectal cancer (CRC) remains unclear, we explored the significance of FDRGs in CRC through comprehensive single-cell analysis. We downloaded the GSE161277 dataset for single-cell analyses and calculated the ferroptosis-dependent gene score (FerrScore) for each cell type. According to each cell type-specific median FerrScore, we categorized the cells into low- and high-ferroptosis groups. By analyzing differentially-expressed genes across the two groups, we identified FDRGs. We further screened these prognosis-related genes used to develop a prognostic signature and calculated its correlation with immune infiltration. We also compared immune checkpoint gene efficacy among different risk groups, and qRT-PCR was performed in colorectal normal and cancer cell lines to explore whether the signature genes could be used as clinical prognostic indicators. In total, 523 FDRGs were identified. A prognostic signature including five signature genes was constructed, and patients were divided into two risk groups. The high-risk group had poor survival rates and displayed high levels of immune infiltration. Our newly developed ferroptosis-based prognostic signature possessed a high predictive ability for CRC.

Repurposing of Chronically Used Drugs in Cancer Therapy: A Chance to Grasp

Despite the advancement in drug discovery for cancer therapy, drug repurposing remains an exceptional opportunistic strategy. This approach offers many advantages (faster, safer, and cheaper drugs) typically needed to overcome increased challenges, i.e., side effects, resistance, and costs associated with cancer therapy. However, not all drug classes suit a patient's condition or long-time use. For that, repurposing chronically used medications is more appealing. This review highlights the importance of repurposing anti-diabetic and anti-hypertensive drugs in the global fight against human malignancies. Extensive searches of all available evidence (up to 30 March 2023) on the anti-cancer activities of anti-diabetic and anti-hypertensive agents are obtained from multiple resources (PubMed, Google Scholar, ClinicalTrials.gov, Drug Bank database, ReDo database, and the National Institutes of Health). Interestingly, more than 92 clinical trials are evaluating the anti-cancer activity of 14 anti-diabetic and anti-hypertensive drugs against more than 15 cancer types. Moreover, some of these agents have reached Phase IV evaluations, suggesting promising official release as anti-cancer medications. This comprehensive review provides current updates on different anti-diabetic and anti-hypertensive classes possessing anti-cancer activities with the available evidence about their mechanism(s) and stage of development and evaluation. Hence, it serves researchers and clinicians interested in anti-cancer drug discovery and cancer management.

Malignant ascites in pancreatic cancer: Pathophysiology, diagnosis, molecular characterization, and therapeutic strategies

Malignant ascites is the accumulation of fluid in the peritoneum as a result of advanced cancer and often signifies the terminal phase of the disease. Management of malignant ascites remains a clinical challenge as symptom palliation is the current standard of cure. Previously, studies examining malignant ascites largely focused on ovarian and gastric cancer. In recent years, there has been a significant increase in research on malignant ascites in pancreatic cancer. Malignant ascites is usually diagnosed based on positive cytology, but cytology is not always diagnostic, indicating the need for novel diagnostic tools and biomarkers. This review aims to summarize the current understanding of malignant ascites in pancreatic cancer and the recent advances in the molecular characterization of malignant ascites fluid from patients with pancreatic cancer including analysis of soluble molecules and extracellular vesicles. Current standard of care treatment options such as paracenteses and diuretics are outlined along with new emerging treatment strategies such as immunotherapy and small-molecule based therapies. New potential investigative directions resulting from these studies are also highlighted.

Patient-derived spheroids and patient-derived organoids simulate evolutions of lung cancer

Cancer cells harbor many genetic mutations and gene expression profiles different from normal cells. Patient-derived cancer cells (PDCC) are preferred materials in cancer study. We established patient-derived spheroids (PDSs) and patient-derived organoids (PDOs) from PDCCs isolated from the malignant pleural effusion in 8 patients. The morphologies suggested that PDSs may be a model of local cancer extensions, while PDOs may be a model of distant cancer metastases. The gene expression profiles differed between PDSs and PDOs: Gene sets related to inflammatory responses and EMT were antithetically regulated in PDSs or in PDOs. PDSs demonstrated an attenuation of the pathways that contribute to the enhancement of transforming growth factor beta (TGF-β) induced epithelial mesenchymal transition (EMT), while PDOs demonstrated an attenuation of it. Taken together, PDSs and PDOs have differences in both the interaction to the immune systems and to the stroma. PDSs and PDOs will provide a model system that enable intimate investigation of the behavior of cancer cells in the body.

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.