Spatial resolution of cellular senescence dynamics in human colorectal liver metastasis

Immune therapeutic strategies for the senescent tumor microenvironment

Senescent cells can either to promote immunosuppressive tumor microenvironment or facilitate immune surveillance. Despite the revolutionary impact of cancer immunotherapy, durable responses in solid tumors, particularly in advanced stages, remain limited. Recent studies have shed light on the influence of senescent status within the tumor microenvironment (TME) on therapy resistance and major efforts are needed to overcome these challenges. This review summarizes recent advancements in targeting cellular senescence, with a particular focus on immunomodulatory approaches on the hallmarks of cellular senescence.

Senescence-related genes as prognostic indicators in breast cancer survival

Breast cancer is a leading cause of cancer-related mortality among women worldwide, particularly affecting those in their later years. As the incidence of breast cancer increases with age, understanding the biological mechanisms that link aging and cancer becomes crucial. Cellular senescence, a hallmark of aging, plays a dual role in cancer by inhibiting tumorigenesis while also contributing to tumor progression through the senescence-associated secretory phenotype (SASP). This study aims to investigate the prognostic significance of senescence-related genes in breast cancer. We utilized the SenMayo gene list, a comprehensive set of senescence-related genes, to analyze gene expression data from a large cohort of breast cancer samples. The data was sourced from the Kaplan-Meier plotter, an integrated database that compiles gene expression information from multiple independent cohorts. Cox proportional hazards regression and false discovery rate (FDR) corrections were employed to evaluate the correlation between gene expression and survival outcomes, aiming to establish a prognostic signature. Our findings demonstrate that higher expression levels of senescence-related genes are significantly associated with improved survival, while lower expression levels correlate with shorter survival outcomes. These results suggest that senescence-related pathways play a protective role in breast cancer, potentially serving as valuable prognostic indicators. The identification of a prognostic signature based on senescence-related genes underscores the importance of cellular senescence in breast cancer progression and survival. Our study highlights the potential of senescence-related biomarkers in enhancing patient stratification and informing treatment strategies, contributing to the growing body of literature on the intersection of aging and cancer.

Prognostic significance of a signature based on senescence-related genes in colorectal cancer

Colorectal cancer, recognized as a quintessential age-related disease, underscores the intricate interplay between aging mechanisms and disease pathogenesis. Cellular senescence, a DNA damage-induced cellular stress response, is characterized by cell cycle arrest, the expression of an inflammatory senescence-associated secretory phenotype, and alterations in extracellular matrix metabolism. It is widely recognized as a fundamental and evolutionarily conserved mechanism of aging. Guided by geroscience principles, which assert that the pathogenesis of age-related diseases involves cellular mechanisms of aging, this study delves into the role of senescence-related genes in colon cancer progression. Leveraging a gene set reflective of senescence-associated pathways, we employed uni- and multivariate Cox proportional hazards survival analysis combined with the determination of the false discovery rate to analyze correlations between gene expression and survival. The integrated database of 1130 colon cancer specimens with available relapse-free survival time and relapse event data from ten independent cohorts provided a robust platform for survival analyses. We identified senescence-related genes associated with differential expression levels linked to shorter survival. Our findings unveil a prognostic signature utilizing cellular senescence-related genes (hazard ratio: 2.73, 95% CI 2.12-3.52, p = 6.4E - 16), offering valuable insights into survival prediction in colon cancer. Multivariate analysis underscored the independence of the senescence-related signature from available epidemiological and pathological variables. This study highlights the potential of senescence-related genes as prognostic biomarkers. Overall, our results underscore the pivotal role of cellular senescence, a fundamental mechanism of aging, in colon cancer progression.

Deciphering the spatiotemporal transcriptional landscape of intestinal diseases (Review)

The intestines are the largest barrier organ in the human body. The intestinal barrier plays a crucial role in maintaining the balance of the intestinal environment and protecting the intestines from harmful bacterial invasion. Single‑cell RNA sequencing technology allows the detection of the different cell types in the intestine in two dimensions and the exploration of cell types that have not been fully characterized. The intestinal mucosa is highly complex in structure, and its proper functioning is linked to multiple structures in the proximal‑distal intestinal and luminal‑mucosal axes. Spatial localization is at the core of the efforts to explore the interactions between the complex structures. Spatial transcriptomics (ST) is a method that allows for comprehensive tissue analysis and the acquisition of spatially separated genetic information from individual cells, while preserving their spatial location and interactions. This approach also prevents the loss of fragile cells during tissue disaggregation. The emergence of ST technology allows us to spatially dissect enzymatic processes and interactions between multiple cells, genes, proteins and signals in the intestine. This includes the exchange of oxygen and nutrients in the intestine, different gradients of microbial populations and the role of extracellular matrix proteins. This regionally precise approach to tissue studies is gaining more acceptance and is increasingly applied in the investigation of disease mechanisms related to the gastrointestinal tract. Therefore, this review summarized the application of ST in gastrointestinal diseases.

Guidelines for minimal information on cellular senescence experimentation in vivo

Cellular senescence is a cell fate triggered in response to stress and is characterized by stable cell-cycle arrest and a hypersecretory state. It has diverse biological roles, ranging from tissue repair to chronic disease. The development of new tools to study senescence in vivo has paved the way for uncovering its physiological and pathological roles and testing senescent cells as a therapeutic target. However, the lack of specific and broadly applicable markers makes it difficult to identify and characterize senescent cells in tissues and living organisms. To address this, we provide practical guidelines called "minimum information for cellular senescence experimentation in vivo" (MICSE). It presents an overview of senescence markers in rodent tissues, transgenic models, non-mammalian systems, human tissues, and tumors and their use in the identification and specification of senescent cells. These guidelines provide a uniform, state-of-the-art, and accessible toolset to improve our understanding of cellular senescence in vivo.

GJA4 expressed on cancer associated fibroblasts (CAFs)-A 'promoter' of the mesenchymal phenotype

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Connexin is a transmembrane protein involved in gap junctions (GJs) formation. Our previous study found that connexin 37 (Cx37), encoded by gap junction protein alpha 4 (GJA4), expressed on fibroblasts acts as a promoter of CRC and is closely related to epithelial-mesenchymal transition (EMT) and tumor immune microenvironment. However, to date, the mechanism concerning the malignancy of GJA4 in tumor stroma has not been studied.

METHODS

Hematoxylin-eosin (HE) and immunohistochemical (IHC) staining were used to validate the expression and localization of GJA4. Using single-cell analysis, enrichment analysis, spatial transcriptomics, immunofluorescence staining (IF), Sirius red staining, wound healing and transwell assays, western blotting (WB), Cell Counting Kit-8 (CCK8) assay and in vivo experiments, we investigated the possible mechanisms of GJA4 in promoting CRC.

RESULTS

We discovered that in CRC, GJA4 on fibroblasts is involved in promoting fibroblast activation and promoting EMT through a fibroblast-dependent pathway. Furthermore, GJA4 may act synergistically with M2 macrophages to limit T cell infiltration by stimulating the formation of an immune-excluded desmoplasic barrier. Finally, we found a significantly correlation between GJA4 and pathological staging (P < 0.0001) or D2 dimer (R = 0.03, P < 0.05).

CONCLUSION

We have identified GJA4 expressed on fibroblasts is actually a promoter of the tumor mesenchymal phenotype. Our findings suggest that the interaction between GJA4+ fibroblasts and M2 macrophages may be an effective target for enhancing tumor immunotherapy.

Senescence-related signatures predict prognosis and response to immunotherapy in colon cancer

Background

Colorectal cancer (CRC) is one of the most common cancers. Cellular senescence plays a vital role in carcinogenesis by activating many pathways. In this study, we aimed to identify biomarkers for predicting the survival and recurrence of CRC through cellular senescence-related genes.

Methods

Utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, RNA-sequencing data and clinical information for CRC were collected. A risk model for predicting overall survival was established based on five differentially expressed genes using least absolute shrinkage and selection operator-Cox regression (LASSO-Cox regression), receiver operating characteristic (ROC), and Kaplan-Meier analyses. The study also delved into both the tumor microenvironment and the response to immunotherapy. Moreover, we gathered clinical sample data from our center in order to confirm the findings of public database analysis.

Results

Through ROC and Kaplan-Meier analyses, a risk model was developed using five cellular senescence-related genes [i.e., CDKN2A, SERPINE1, SNAI1, CXCL1, and ETS2] to categorize patients into high- and low-risk groups. In the TCGA-colon adenocarcinoma (COAD) and GEO-COAD cohorts, the high-risk group was associated with a bleaker forecast (P<0.05), immune cell inactivation, and insensitivity to immunotherapy in IMvigor210 database (http://research-pub.gene.com/IMvigor210CoreBiologies/). Clinical samples were then used to confirm that ETS2 and CDKN2A could serve as independent prognostic biomarkers in CRC.

Conclusions

Gene signatures related to cellular senescence, specifically involving CDKN2A and ETS2, are emerging as promising biomarkers for predicting CRC prognosis and guiding immunotherapy.

STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics

Recent advances in multi-modal algorithms have driven and been driven by the increasing availability of large image-text datasets, leading to significant strides in various fields, including computational pathology. However, in most existing medical image-text datasets, the text typically provides high-level summaries that may not sufficiently describe sub-tile regions within a large pathology image. For example, an image might cover an extensive tissue area containing cancerous and healthy regions, but the accompanying text might only specify that this image is a cancer slide, lacking the nuanced details needed for in-depth analysis. In this study, we introduce STimage-1K4M, a novel dataset designed to bridge this gap by providing genomic features for sub-tile images. STimage-1K4M contains 1,149 images derived from spatial transcriptomics data, which captures gene expression information at the level of individual spatial spots within a pathology image. Specifically, each image in the dataset is broken down into smaller sub-image tiles, with each tile paired with 15,000 - 30,000 dimensional gene expressions. With 4,293,195 pairs of sub-tile images and gene expressions, STimage-1K4M offers unprecedented granularity, paving the way for a wide range of advanced research in multi-modal data analysis an innovative applications in computational pathology, and beyond.

Spatial transcriptomics in cancer research and potential clinical impact: a narrative review

Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?

Spatiotemporal heterogeneity of LMOD1 expression summarizes two modes of cell communication in colorectal cancer

Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknown. Here, we investigated the spatiotemporal heterogeneity of CC molecular expression during malignant transformation. It was found that although both tight junctions (TJs) and gap junctions (GJs) were involved in maintaining the tumor microenvironment (TME), they exhibited opposite characteristics. Mechanistically, for epithelial cells (parenchymal component), the expression of TJ molecules consistently decreased during normal-cancer transformation and is a potential oncogenic factor. For fibroblasts (mesenchymal component), the expression of GJs consistently increased during normal-cancer transformation and is a potential oncogenic factor. In addition, the molecular profiles of TJs and GJs were used to stratify colorectal cancer (CRC) patients, where subtypes characterized by high GJ levels and low TJ levels exhibited enhanced mesenchymal signals. Importantly, we propose that leiomodin 1 (LMOD1) is biphasic, with features of both TJs and GJs. LMOD1 not only promotes the activation of cancer-associated fibroblasts (CAFs) but also inhibits the Epithelial-mesenchymal transition (EMT) program in cancer cells. In conclusion, these findings demonstrate the molecular heterogeneity of CC and provide new insights into further understanding of TME heterogeneity.

Emerging Roles of Spatial Transcriptomics in Liver Research

Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.

Cellular Senescence in Liver Cancer: How Dying Cells Become "Zombie" Enemies

Liver cancer represents the fourth leading cause of cancer-associated death worldwide. The heterogeneity of its tumor microenvironment (TME) is a major contributing factor of metastasis, relapse, and drug resistance. Regrettably, late diagnosis makes most liver cancer patients ineligible for surgery, and the frequent failure of non-surgical therapeutic options orientates clinical research to the investigation of new drugs. In this context, cellular senescence has been recently shown to play a pivotal role in the progression of chronic inflammatory liver diseases, ultimately leading to cancer. Moreover, the stem-like state triggered by senescence has been associated with the emergence of drug-resistant, aggressive tumor clones. In recent years, an increasing number of studies have emerged to investigate senescence-associated hepatocarcinogenesis and its derived therapies, leading to promising results. In this review, we intend to provide an overview of the recent evidence that unveils the role of cellular senescence in the most frequent forms of primary and metastatic liver cancer, focusing on the involvement of this mechanism in therapy resistance.

The multistep path to replicative senescence onset: zooming on triggering and inhibitory events at telomeric DNA

Replicative senescence is an essential cellular process playing important physiological functions, but it is better known for its implications in aging, cancer, and other pathologies. One of the main triggers of replicative senescence is telomere shortening and/or its dysfunction and, therefore, a deep understanding of the molecular determinants is crucial. However, replicative senescence is a heterogeneous and hard to study process, especially in mammalian cells, and some important questions still need an answer. These questions concern i) the exact molecular causes triggering replicative senescence, ii) the role of DNA repair mechanisms and iii) the importance of R-loops at telomeres in regulating senescence onset, and iv) the mechanisms underlying the bypass of replicative senescence. In this review, we will report and discuss recent findings about these mechanisms both in mammalian cells and in the model organism Saccharomyces cerevisiae.