Cancer-derived exosomal lncRNA SNHG3 promotes the metastasis of colorectal cancer through hnRNPC-mediating RNA stability of ß-catenin.

Metastasis is the leading cause of death in colorectal cancer (CRC) patients. By mediating intercellular communication, exosomes exhibit considerable value in regulating tumor metastasis. Long non-coding RNAs (lncRNAs) are abundant in exosomes and participate in regulating tumor progression. However, it is poorly understood how the cancer-secreted exosomal lncRNAs affect CRC proliferation and metastasis. Here, by analyzing the public databases we identified a lncRNA SNHG3 and demonstrated that SNHG3 was delivered through CRC cells-derived exosomes to promote metastasis in CRC. Mechanistically, exosomal SNHG3 was internalized by CRC cells and afterward upregulated the expression of ß-catenin by facilitating the intranuclear transport of hnRNPC. Consequently, the RNA stability of ß-catenin was enhanced which led to the activation of EMT and metastasis of CRC cells. Our findings expand the oncogenic mechanisms of exosomal SNHG3 and identify it as a diagnostic marker for CRC.

GC-CDSS: Personalized gastric cancer treatment recommendations system based on knowledge graph.

BACKGROUND: Gastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and screening is increasing rapidly. OBJECTIVE: The purpose of this study is to (1) summarize the treatment decision process for GC according to the treatment guidelines in China, and then create a knowledge graph (KG) for GC, (2) based on aforementioned KG, built a CDSS and conducted an initial feasibility evaluation for the current system. METHODS: Firstly, we summarized the decision-making process for treatment of GC. Then, we extracted relevant decision nodes and relationships and utilized Neo4j to create the KG. After obtaining the initial node features for building the graph embedding model, graph embedding algorithm, such as Node2Vec and GraphSAGE, were used to construct the GC-CDSS. At last, a retrospective cohort study was used to compare the consistency between GC-CDSS and MDT in treatment decision making. RESULTS: In current study, we introduce a GC-CDSS, which is constructed based on Chinese GC treatment guidelines knowledge graph (KG). In the KG, we define four types of nodes and four types of relationships, and it comprise a total of 207 nodes and 300 relationships. Regarding GC-CDSS, the system is capable of providing dynamic and personalized diagnostic and treatment recommendations based on the patient's condition. Furthermore, a retrospective cohort study is conducted to compare GC-CDSS recommendations with those of the MDT group, the overall consistency rate of treatment recommendations between the auxiliary decision system and MDT team is 92.96%. CONCLUSIONS: We construct a GC treatment support system, GC-CDSS, based on KG. The GC-CDSS may help oncologists make treatment decisions more efficient and promote standardization in primary healthcare settings.

Revolutionizing sphincter preservation in ultra-low rectal cancer: exploring the potential of transanal endoscopic intersphincteric resection (taE-ISR): a propensity score-matched cohort study.

BACKGROUND: With the optimization of neoadjuvant treatment regimens, the indications for intersphincteric resection (ISR) have expanded. However, limitations such as unclear surgical field, impaired anal function, and failure of anal preservation still exist. Transanal total mesorectal excision can complement the drawbacks of ISR. Therefore, this study combined these two techniques and proposed transanal endoscopic intersphincteric resection (taE-ISR), aiming to explore the value of this novel technique in anal preservation for ultra-low rectal cancer. MATERIAL AND METHODS: Four high-volume centres were involved. After 1:1 propensity score-matching, patients with ultra-low rectal cancer underwent taE-ISR ( n =90) or ISR ( n =90) were included. Baseline characteristics, perioperative outcomes, pathological results, and follow-up were compared between the two groups. A nomogram model was established to assess the potential risks of anal preservation. RESULTS: The incidence of adjacent organ injury (0.0% vs. 5.6%, P =0.059), positive distal resection margin (1.1% vs. 8.9%, P =0.034), and incomplete specimen (2.2% vs. 13.3%, P =0.012) were lower in taE-ISR group. Moreover, the anal preservation rate was significantly higher in taE-ISR group (97.8% vs. 82.2%, P =0.001). Patients in the taE-ISR group showed a better disease-free survival ( P =0.044) and lower cumulative recurrence ( P =0.022) compared to the ISR group. Surgery procedure, tumour distance, and adjacent organ injury were factors influencing anal preservation in patients with ultra-low rectal cancer. CONCLUSION: taE-ISR technique was safe, feasible, and improved surgical quality, anal preservation rate and survival outcomes in ultra-low rectal cancer patients. It held significant clinical value and showed promising application prospects for anal preservation.

Exploring the relationship between lactate metabolism and immunological function in colorectal cancer through genes identification and analysis.

Introduction: Metabolic dysregulation is a widely acknowledged contributor for the development and tumorigenesis of colorectal cancer (CRC), highlighting the need for reliable prognostic biomarkers in this malignancy. Methods: Herein, we identified key genes relevant to CRC metabolism through a comprehensive analysis of lactate metabolism-related genes from GSEA MsigDB, employing univariate Cox regression analysis and random forest algorithms. Clinical prognostic analysis was performed following identification of three key genes, and consistent clustering enabled the classification of public datasets into three patterns with significant prognostic differences. The molecular pathways and tumor microenvironment (TME) of these patterns were then investigated through correlation analyses. Quantitative PCR was employed to quantify the mRNA expression levels of the three pivotal genes in CRC tissue. Single-cell RNA sequencing data and fluorescent multiplex immunohistochemistry were utilized to analyze relevant T cells and validate the correlation between key genes and CD4+ T cells. Results: Our analysis revealed that MPC1, COQ2, and ADAMTS13 significantly stratify the cohort into three patterns with distinct prognoses. Additionally, the immune infiltration and molecular pathways were significantly different for each pattern. Among the key genes, MPC1 and COQ2 were positively associated with good prognosis, whereas ADAMTS13 was negatively associated with good prognosis. Single-cell RNA sequencing (scRNA-seq) data illustrated that the relationship between three key genes and T cells, which was further confirmed by the results of fluorescent multiplex immunohistochemistry demonstrating a positive correlation between MPC1 and COQ2 with CD4+ T cells and a negative correlation between ADAMTS13 and CD4+ T cells. Discussion: These findings suggest that the three key lactate metabolism genes, MPC1, COQ2, and ADAMTS13, may serve as effective prognostic biomarkers and support the link between lactate metabolism and the immune microenvironment in CRC.

Exploring the role of pyroptosis in shaping the tumor microenvironment of colorectal cancer by bulk and single-cell RNA sequencing.

BACKGROUND: Emerging studies have shown that pyroptosis plays a non-negligible role in the development and treatment of tumors. However, the mechanism of pyroptosis in colorectal cancer (CRC) remains still unclear. Therefore, this study investigated the role of pyroptosis in CRC. METHODS: A pyroptosis-related risk model was developed using univariate Cox regression and LASSO Cox regression analyses. Based on this model, pyroptosis-related risk scores (PRS) of CRC samples with OS time > 0 from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database were calculated. The abundance of immune cells in CRC tumor microenvironment (TME) was predicted by single-sample gene-set enrichment analysis (ssGSEA). Then, the responses to chemotherapy and immunotherapy were predicted by pRRophetic algorithm, the tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms, respectively. Moreover, the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing dataset (PRISM) were used to explore novel drug treatment strategies of CRC. Finally, we investigated pyroptosis-related genes in the level of single-cell and validated the expression levels of these genes between normal and CRC cell lines by RT-qPCR. RESULTS: Survival analysis showed that CRC samples with low PRS had better overall survival (OS) and progression-free survival (PFS). CRC samples with low PRS had higher immune-related gene expression and immune cell infiltration than those with high PRS. Besides, CRC samples with low PRS were more likely to benefit from 5-fluorouracil based chemotherapy and anti-PD-1 immunotherapy. In novel drug prediction, some compounds such as C6-ceramide and noretynodrel, were inferred as potential drugs for CRC with different PRS. Single-cell analysis revealed pyroptosis-related genes were highly expressed in tumor cells. RT-qPCR also demonstrated different expression levels of these genes between normal and CRC cell lines. CONCLUSIONS: Taken together, this study provides a comprehensive investigation of the role of pyroptosis in CRC at the bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) levels, advances our understanding of CRC characteristics, and guides more effective treatment regimens.

Polyamine metabolism patterns characterized tumor microenvironment, prognosis, and response to immunotherapy in colorectal cancer.

BACKGROUND: Changes in Polyamine metabolism (PAM) have been shown to establish a suppressive tumor microenvironment (TME) and substantially influence the progression of cancer in the recent studies. However, newly emerging data have still been unable to fully illuminate the specific effects of PAM in human cancers. Here, we analyzed the expression profiles and clinical relevance of PAM genes in colorectal cancer (CRC). METHODS: Based on unsupervised consensus clustering and principal component analysis (PCA) algorithm, we designed a scoring model to evaluate the prognosis of CRC patients and characterize the TME immune profiles, with related independent immunohistochemical validation cohort. Through comparative profiling of cell communities defined by single cell sequencing data, we identified the distinct characteristics of polyamine metabolism in the TME of CRC. RESULTS: Three PAM patterns with distinct prognosis and TME features were recognized from 1224 CRC samples. Moreover, CRC patients could be divided into high- and low-PAMscore subgroups by PCA-based scoring system. High PAMscore subgroup were associated to more advanced stage, higher infiltration level of immunosuppressive cells, and unfavorable prognosis. These results were also validated in CRC samples from other public CRC datasets and our own cohort, which suggested PAM genes were ideal biomarkers for predicting CRC prognosis. Notably, PAMscore also corelated with microsatellite instability-high (MSI-H) status, higher tumor mutational burden (TMB), and increased immune checkpoint gene expression, implying a potential role of PAM genes in regulating response to immunotherapy. To further confirm above results, we demonstrated a high-resolution landscape of TME and cell-cell communication network in different PAM patterns using single cell sequencing data and found that polyamine metabolism affected the communication between cancer cells and several immune cells such as T cells, B cells and myeloid cells. CONCLUSION: In total, our findings highlighted the significance of polyamine metabolism in shaping the TME and predicting the prognosis of CRC patients, providing novel strategies for immunotherapy and the targeting polyamine metabolites.

Integrative analysis revealed that distinct cuprotosis patterns reshaped tumor microenvironment and responses to immunotherapy of colorectal cancer.

Background: Cuprotosis is a novel form of programmed cell death that involves direct targeting of key enzymes in the tricarboxylic acid (TCA) cycle by excess copper and may result in mitochondrial metabolic dysfunction. However, whether cuprotosis may mediate the tumor microenvironment (TME) and immune regulation in colorectal cancer (CRC) remains unclear. Methods: Ten cuprotosis-related genes were selected and unsupervised consensus clustering was performed to identify the cuprotosis patterns and the correlated TME characteristics. Using principal component analysis, a COPsig score was established to quantify cuprotosis patterns in individual patients. The top 9 most important cuprotosis signature genes were analyzed using single-cell transcriptome data. Results: Three distinct cuprotosis patterns were identified. The TME cell infiltration characteristics of three patterns were associated with immune-excluded, immune-desert, and immune-inflamed phenotype, respectively. Based on individual cuprotosis patterns, patients were assigned into high and low COPsig score groups. Patients with a higher COPsig score were characterized by longer overall survival time, lower immune cell as well as stromal infiltration, and greater tumor mutational burden. Moreover, further analysis demonstrated that CRC patients with a higher COPsig score were more likely to respond to immune checkpoint inhibitors and 5-fluorouracil chemotherapy. Single-cell transcriptome analysis indicated that cuprotosis signature genes recruited tumor-associated macrophages to TME through the regulation of TCA and the metabolism of glutamine and fatty acid, thus influencing the prognosis of CRC patients. Conclusion: This study indicated that distinct cuprotosis patterns laid a solid foundation to the explanation of heterogeneity and complexity of individual TME, thus guiding more effective immunotherapy as well as adjuvant chemotherapy strategies.

Roles and mechanisms of tumour-infiltrating B cells in human cancer: a new force in immunotherapy.

Immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 have emerged as a revolutionary treatment strategy for human cancer patients. However, as the response rate to ICI therapy varies widely among different types of tumours, we are beginning to gain insight into the mechanisms as well as biomarkers of therapeutic response and resistance. Numerous studies have highlighted the dominant role of cytotoxic T cells in determining the treatment response to ICIs. Empowered by recent technical advances, such as single-cell sequencing, tumour-infiltrating B cells have been identified as a key regulator in several solid tumours by affecting tumour progression and the response to ICIs. In the current review, we summarized recent advances regarding the role and underlying mechanisms of B cells in human cancer and therapy. Some studies have shown that B-cell abundance in cancer is positively associated with favourable clinical outcomes, while others have indicated that they are tumour-promoting, implying that the biological function of B cells is a complex landscape. The molecular mechanisms involved multiple aspects of the functions of B cells, including the activation of CD8+ T cells, the secretion of antibodies and cytokines, and the facilitation of the antigen presentation process. In addition, other crucial mechanisms, such as the functions of regulatory B cells (Bregs) and plasma cells, are discussed. Here, by summarizing the advances and dilemmas of recent studies, we depicted the current landscape of B cells in cancers and paved the way for future research in this field.

PKCδ promotes the invasion and migration of colorectal cancer through c-myc/NDRG1 pathway.

Objective: Colorectal cancer (CRC) is the third cause of expected cancer deaths both in men and women in the U.S. and the third most commonly diagnosed cancer in China Targeted therapy has been proven to improve overall survival for unresectable metastatic CRC. But the location of the primary tumor or the presence of various core driver gene mutations that confer resistance may limit the utility of targeted therapy. Therefore, it is of great significance to further elucidate novel mechanisms of invasion and metastasis of CRC and find potential novel therapeutic targets. Protein Kinase C Delta (PKCδ) plays an important role in various diseases, including tumors. In CRC, the function of PKCδ on proliferation and differentiation is mostly studied but various research results were reported. Therefore, the role of PKCδ in CRC needs to be further studied, especially in tumor invasion and metastasis in CRC which few studies have looked into. Methods: The expression of PRKCD was analyzed by the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases and Immunohistochemical (IHC). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) enrichment analysis were used to explore the biological functions and pathways related to PRKCD. Lentivirus transfection was used to construct CRC cell lines with overexpression and knock-down of PKCδ or N-myc Downstream Regulated Gene 1 (NDRG1). Cell invasion and migration assay, wound healing assay were used to detect the function of PKCδ and NDRG1 in the invasion and migration of cells. Flow cytometry analysis was used to detect the influence of PKCδ on the CRC cell cycles .Immunofluorescence histochemistry ,Immunoprecipitation Assay and qPCR were used to detect the relationship of PKCδ and NDRG1. Xenograft model was used to verify the role of PKCδ in vivo. Results: PKCδ is overexpressed in CRC and could promote Epithelial-Mesenchymal Transition (EMT) and the invasion and migration of CRC in vitro. We confirmed that PKCδ and the tumor suppressor factor NDRG1 had a co-localization relationship in CRC. PKCδ inhibited NDRG1 transcription and protein expression. Overexpressing NDRG1 could inhibit the function of PKCδ in promoting tumor invasion and migration. PKCδ could regulate c-Myc, one transcription factor of NDRG1, to down-regulate NDRG1. In vivo, overexpressing PKCδ could promote xenograft growth and volume. Thus, our results showed that PKCδ reduced the expression of NDRG1 through c-Myc, promoting the invasion and migration of CRC through promoting EMT. Conclusion: The increased expression of PKCδ in CRC tumor tissue could promote the invasion and migration of tumor cells, and one of the mechanisms may be regulating c-Myc to inhibit the expression of NDRG1 and promote EMT.

An intravenous anesthetic drug-propofol, influences the biological characteristics of malignant tumors and reshapes the tumor microenvironment: A narrative literature review.

Malignant tumors are the second leading cause of death worldwide. This is a public health concern that negatively impacts human health and poses a threat to the safety of life. Although there are several treatment approaches for malignant tumors, surgical resection remains the primary and direct treatment for malignant solid tumors. Anesthesia is an integral part of the operation process. Different anesthesia techniques and drugs have different effects on the operation and the postoperative prognosis. Propofol is an intravenous anesthetic that is commonly used in surgery. A substantial number of studies have shown that propofol participates in the pathophysiological process related to malignant tumors and affects the occurrence and development of malignant tumors, including anti-tumor effect, pro-tumor effect, and regulation of drug resistance. Propofol can also reshape the tumor microenvironment, including anti-angiogenesis, regulation of immunity, reduction of inflammation and remodeling of the extracellular matrix. Furthermore, most clinical studies have also indicated that propofol may contribute to a better postoperative outcome in some malignant tumor surgeries. Therefore, the author reviewed the chemical properties, pharmacokinetics, clinical application and limitations, mechanism of influencing the biological characteristics of malignant tumors and reshaping the tumor microenvironment, studies of propofol in animal tumor models and its relationship with postoperative prognosis of propofol in combination with the relevant literature in recent years, to lay a foundation for further study on the correlation between propofol and malignant tumor and provide theoretical guidance for the selection of anesthetics in malignant tumor surgery.

Exploration of the Associations of lncRNA Expression Patterns with Tumor Mutation Burden and Prognosis in Colon Cancer.

BACKGROUND: Tumor mutation burden (TMB) is emerging as a new biomarker to monitor the response of cancer patients to immunotherapy. Long non-coding RNAs (lncRNAs) are critical in regulating gene expression and play a significant role in cancer-associated immune responses. However, the association between lncRNA expression patterns and TMB levels and survival outcomes remains unknown in colon cancer. METHODS: In colon cancer patients from The Cancer Genome Atlas Program (TCGA), a multi-lncRNAs based classifier for predicting TMB levels was established using the least absolute shrinkage and selection operator (LASSO) method. The association between classifier index and immune-related characteristics of patients was also investigated. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of these lncRNAs in normal and CRC cell lines. RESULTS: The multi-lncRNAs based classifier had ability to predict TMB level of patients with accuracy (AUC= 0.70), and the general applicability of this classifier was proved in the validation set (AUC= 0.71) and the pooled set (AUC= 0.70). The classifier index was related to three immune checkpoints (PD1, PD-L1, and CTLA-4), the infiltration level of immune cells, and immune response-related score (IFN-γ score, gene expression profiles (GEP) score, cytolytic activity (CYT) score and MHC score). A nomogram, which integrates classifier and some common clinical information, was able to predict the overall survival of colon cancer patients accurately. CONCLUSION: LncRNA expression patterns are associated with TMB, which may serve as a classifier to predict the TMB in colon cancer patients. The nomogram could potentially evaluate survival outcomes and provide a reference to better manage colon cancer patients.

Characterization of the fatty acid metabolism in colorectal cancer to guide clinical therapy.

Colorectal cancer (CRC) is one of the most common malignant tumors, with the second-highest mortality of all 36 cancers worldwide. The roles of fatty acid metabolism in CRC were investigated to explore potential therapeutic strategies. The data files were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a prognostic risk score model with fatty acid metabolism-related genes for predicting prognosis in CRC. Patients with a high-risk score had a poorer prognosis in TCGA cohort than those with a low-risk score and were confirmed in the GEO cohort. Further analysis using the "pRRophetic" R package revealed that low-risk patients were more sensitive to 5-fluorouracil. A comprehensive evaluation of the association between prognostic risk score model and tumor microenvironment (TME) characteristics showed that high-risk patients were suitable for activating a type I/II interferon (IFN) response and inflammation-promoting function. Tumor Immune Dysfunction and Exclusion (TIDE) and SubMap algorithm results also demonstrated that high-risk patients are more suitable for anti-CTLA4 immunotherapy. Therefore, the evaluation of the fatty acid metabolism pattern promotes our comprehension of TME infiltration characteristics, thus guiding effective immunotherapy regimens.