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.
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.
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. Graphical Abstract
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.
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. Graphical Abstract
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.
Background Changes of 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 were still 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 CRC. Methods Based on unsupervised consistent clustering and 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 characteristic 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 higher levels of immune checkpoint gene expression, implying a potential role of PAM genes in regulating response to immunotherapy. To further verify above results, we demonstrated a high-resolution landscape of TME and cell-cell communication network in different PAM patterns with 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 formation of TME and predicting the prognosis of CRC patients, providing novel strategies for immunotherapy and the targeting therapy of polyamine metabolites.
BackgroundCuprotosis 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.MethodsTen 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.ResultsThree 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.ConclusionThis 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.
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