Colon Cancer Microenvironment Research Articles

CACNA2D1 regulates the progression and influences the microenvironment of colon cancer.

Calcium voltage-gated channel auxiliary subunit alpha 2/delta 1 (CACNA2D1), a gene encoding a voltage-gated calcium channel, has been reported as an oncogene in several cancers. However, its role in colon cancer (CC) remains unclear. This study aimed to investigate the function of CACNA2D1 and its effect on the microenvironment in CC. Immunohistochemistry (IHC) analysis was performed on samples collected from 200 patients with CC who underwent curative colectomy. Knockdown experiments were performed using CACNA2D1 siRNA in the human CC cell lines HCT116 and RKO, and cell proliferation, cycle, apoptosis, and migration were then analyzed. The fibroblast cell line CCD-18Co was co-cultured with CC cell lines to determine the effect of CACNA2D1 on fibroblasts and the relationship between CACNA2D1 and the cancer microenvironment. Gene expression profiles of cells were analyzed using microarray analysis. IHC revealed that high CACNA2D1 expression was an independent poor prognostic factor in patients with CC and that CACNA2D1 expression and the stroma are correlated. CACNA2D1 depletion decreased cell proliferation and migration; CACNA2D1 knockdown increased the number of cells in the sub-G1 phase and induced apoptosis. CCD-18Co and HCT116 or RKO cell co-culture revealed that CACNA2D1 affects the cancer microenvironment via fibroblast regulation. Furthermore, microarray analysis showed that the p53 signaling pathway and epithelial-mesenchymal transition-associated pathways were enhanced in CACNA2D1-depleted HCT116 cells. CACNA2D1 plays an important role in the progression and the microenvironment of CC by regulating fibroblasts and may act as a biomarker for disease progression and a therapeutic target for CC.

Abstract 4914: Mapping the cancer immune landscape in colorectal adenocarcinoma using multiplexed imaging and AI based analysis

Abstract Colorectal cancer is a high burden cancer in the United States, leading to the second highest cause of cancer deaths. Despite chemotherapeutic intervention and surgical resection, recurrent disease may occur in some patients and typically, has a poorer prognosis. Thus, there is a demand for advanced therapies such as immunotherapies for improved clinical outcomes. An in-depth understanding of the colon cancer microenvironment is necessary to improve outcome in this subset of patients. Spatial biology approaches are well positioned to comprehensively uncover the molecular and biological mechanisms of cancer cell aggression in colorectal cancer. Here, we visualized nearly 30 biomarkers in colon adenocarcinoma (CAC) tissue using the Cell DIVE multiplexed imaging workflow and validated antibodies from Cell Signaling Technology (CST®). Using this approach, we were able to probe multiple pathways of interest in cancer progression, such as vascularization of tumor tissue, immune cell responses, and cell proliferation. Together, these data allow the creation of a spatial map of tumor cell aggression and offer predictive value for the progression of the disease. Deep molecular and architectural insights on this level are possible only with a spatial biology approach and offer multiple downstream hypotheses to further understand cancer progression and interrogate the heterogeneity within the tumor microenvironment. Citation Format: Vasundhara Agrawal, Lisa Arvidson, Michael J. Smith, Katie O. White, Richard A. Heil-Chapdelaine, Samuel Jensen, Arindam Bose. Mapping the cancer immune landscape in colorectal adenocarcinoma using multiplexed imaging and AI based analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4914.

Prognostic value of fatty acid metabolism-related genes in colorectal cancer and their potential implications for immunotherapy.

Colorectal cancer is one of the most common gastrointestinal cancers and the second leading cause of cancer-related death. Although colonoscopy screening has greatly improved the early diagnosis of colorectal cancer, its recurrence and metastasis are still significant problems. Tumour cells usually have the hallmark of metabolic reprogramming, while fatty acids play important roles in energy storage, cell membrane synthesis, and signal transduction. Many pathways of fatty acid metabolism (FAM) are involved in the occurrence and development of colon cancer, and the complex molecular interaction network contains a variety of genes encoding key enzymes and related products. Clinical information and RNA sequencing data were collected from TCGA and GEO databases. The prognosis model of colon cancer was constructed by LASSO-Cox regression analysis among the selected fatty acid metabolism genes with differential expression. Nomogram for the prognosis model was also constructed in order to analyze its value in evaluating the survival and clinical stage of the colon cancer patients. The differential expression of the selected genes was verified by qPCR and immunohistochemistry. GSEA and GSVA were used to analyze the enrichment pathways for high- and low-risk groups. CIBERSORT was used to analyze the immune microenvironment of colon cancer and to compare the infiltration of immune cells in the high- and low-risk groups. The "circlize" package was used to explore the correlation between the risk score signature and immunotherapy for colon cancer. We analysed the differential expression of 704 FAM-related genes between colon tumour and normal tissue and screened 10 genes with prognostic value. Subsequently, we constructed a prognostic model for colon cancer based on eight optimal FAM genes through LASSO Cox regression analysis in the TCGA-COAD dataset, and its practicality was validated in the GSE39582 dataset. Moreover, the risk score calculated based on the prognostic model was validated as an independent prognostic factor for colon cancer patients. We further constructed a nomogram composed of the risk score signature, age and American Joint Committee on Cancer (AJCC) stage for clinical application. The colon cancer cohort was divided into high- and low-risk groups according to the optimal cut-off value, and different enrichment pathways and immune microenvironments were depicted in the groups. Since the risk score signature was significantly correlated with the expression of immune checkpoint molecules, the prognostic model might be able to predict the immunotherapy response of colon cancer patients. In summary, our findings expand the prognostic value of FAM-related genes in colon cancer and provide evidence for their application in guiding immunotherapy.

Spatial profiling of cancer-associated fibroblasts of sporadic early onset colon cancer microenvironment

The incidence of sporadic early-onset colon cancer (EOCC) has increased worldwide. The molecular mechanisms in the tumor and the tumor microenvironment (TME) in EOCC are not fully understood. The aim of this study is to unravel unique spatial transcriptomic and proteomic profiles in tumor epithelial cells and cancer-associated fibroblasts (CAFs). Here, we divide the sporadic colon cancer tissue samples with transcriptomic data into patients diagnosed with EOCC (<50 yrs) and late-onset colon cancer (LOCC, ≥50 yrs) and then, analyze the data using CIBERSORTx deconvolution software. EOCC tumors are more enriched in CAFs with fibroblast associated protein positive expression (FAP(+)) than LOCC tumors. EOCC patients with higher FAP mRNA levels in CAFs have shorter OS (Log-rank test, p < 0.029). Spatial transcriptomic analysis of 112 areas of interest, using NanoString GeoMx digital spatial profiling, demonstrate that FAP(+) CAFs at the EOCC tumor invasive margin show a significant upregulation of WNT signaling and higher mRNA/protein levels of fibroblast growth factor 20 (FGF20). Tumor epithelial cells at tumor invasive margin of EOCC tumors neighboring FAP(+) CAFs show significantly higher mRNA/protein levels of fibroblast growth factor receptor (FGFR2) and PI3K/Akt signaling activation. NichNET analysis show a potential interaction between FGF20 and FGFFR2. The role of FGF20 in activating FGFR2/pFGFR2 and AKT/pAKT was validated in-vitro. In conclusion, we identify a unique FAP(+) CAF population that showed WNT signaling upregulation and increased FGF20 levels; while neighbor tumor cells show the upregulation/activation of FGFR2-PI3K/Akt signaling at the tumor invasive margin of EOCC tumors.

An Activated Dendritic-Cell-Related Gene Signature Indicative of Disease Prognosis and Chemotherapy and Immunotherapy Response in Colon Cancer Patients

Accumulating evidence has underscored the prognostic value of tumor-infiltrating immune cells in the tumor microenvironment of colon cancer (CC). In this retrospective study, based on publicly available transcriptome profiles and clinical data from the Gene Expression Omnibus and The Cancer Genome Atlas databases, we derived and verified an activated dendritic cell (aDC)-related gene signature (aDCRS) for predicting the survival outcomes and chemotherapy and immunotherapy response of CC patients. We quantified the infiltration abundance of 22 immune cell subtypes via the “CIBERSORT” R script. Univariate Cox proportional hazards (PHs) regression was used to identify aDC as the most robust protective cell type for CC prognosis. After selecting differentially expressed genes (DEGs) significantly correlated with aDC infiltration, we performed univariate Cox-PH regression, LASSO regression, and stepwise multivariate Cox-PH regression successively to screen out prognosis-related genes from selected DEGs for constructing the aDCRS. Receiver operating characteristic (ROC) curves and Kaplan–Meier (KM) analysis were employed to assess the discriminatory ability and risk-stratification capacity. The “oncoPredict” package, Cancer Treatment Response gene signature DataBase, and Tumor Immune Dysfunction and Exclusion algorithm were utilized to estimate the practicability of the aDCRS in predicting response to chemotherapy and immune checkpoint blockade. Gene set enrichment analysis and single-cell RNA sequencing analysis were also implemented. Furthermore, an aDCRS-based nomogram was constructed and validated via ROC curves, calibration plots and decision curve analysis. In conclusion, aDCRS and an aDCRS-based nomogram will facilitate precise prognosis prediction and individualized therapeutic interventions, thus improving the survival outcomes of CC patients in the future.

Promoting effect and immunologic role of secretogranin II on bladder cancer progression via regulating MAPK and NF-κB pathways.

Bladder cancer (BLCA) is ranked among the top ten most prevalent cancers worldwide and is the second most common malignant tumor within the field of urology. The limited effectiveness of immune targeted therapy in treating BLCA, due to its high metastasis and recurrence rates, necessitates the identification of new therapeutic targets. Secretogranin II (SCG2), a member of the chromaffin granin/secreted granin family, plays a crucial role in the regulated release of peptides and hormones. The role of SCG2 in the tumor microenvironment (TME) of lung adenocarcinoma and colon cancer has been established, but its functional significance in BLCA remains uncertain. This study aimed to investigate SCG2 expression in 15 bladder cancer tissue samples and their corresponding adjacent control tissues. The potential involvement of SCG2 in BLCA progression was assessed using various techniques, including analysis of public databases, immunohistochemistry, Western Blotting, immunofluorescence, wound-healing assay, Transwell assay, and xenograft tumor formation experiments in nude mice. This study provided novel evidence indicating that SCG2 plays a pivotal role in facilitating the proliferation, migration, and invasion of BLCA by activating the MEK/Erk and MEK/IKK/NF-κB signaling pathways, as well as by promoting M2 macrophage polarization. These findings propose the potential of SCG2 as a molecular target for immunotherapy in human BLCA.

Identification of Colon Immune Cell Marker Genes Using Machine Learning Methods.

Immune cell infiltration that occurs at the site of colon tumors influences the course of cancer. Different immune cell compositions in the microenvironment lead to different immune responses and different therapeutic effects. This study analyzed single-cell RNA sequencing data in a normal colon with the aim of screening genetic markers of 25 candidate immune cell types and revealing quantitative differences between them. The dataset contains 25 classes of immune cells, 41,650 cells in total, and each cell is expressed by 22,164 genes at the expression level. They were fed into a machine learning-based stream. The five feature ranking algorithms (last absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, minimum redundancy maximum relevance, and random forest) were first used to analyze the importance of gene features, yielding five feature lists. Then, incremental feature selection and two classification algorithms (decision tree and random forest) were combined to filter the most important genetic markers from each list. For different immune cell subtypes, their marker genes, such as KLRB1 in CD4 T cells, RPL30 in B cell IGA plasma cells, and JCHAIN in IgG producing B cells, were identified. They were confirmed to be differentially expressed in different immune cells and involved in immune processes. In addition, quantitative rules were summarized by using the decision tree algorithm to distinguish candidate immune cell types. These results provide a reference for exploring the cell composition of the colon cancer microenvironment and for clinical immunotherapy.

Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon cancer

BackgroundThe most common cause of death for colon cancer patients is liver metastasis.MethodsAll the data enrolled in this study were downloaded from two public databases, The Cancer Genome Atlas Program, the TCGA-COAD project and Gene Expression Omnibus, GSE41258 project. All the analysis was performed in R software.ResultsIn our study, we systematically explored the molecules involved in the liver metastasis process of colon cancer. The biological role of these molecules was identified through the GO and KEGG analysis. Moreover, we identified that the molecules SERPINA3, SERPINA1, MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective factor against colon cancer independent of other clinical parameters like age, gender, clinical stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14 is predominantly involved in the activating of the WNT/β/catenin pathway, pancreas beta cells, peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, we found that the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and sunitinib.ConclusionsOur result could improve the understanding of the liver metastasis process in colon cancer. Also, CXCL14 was identified as an underlying therapeutic target for colon cancer.

Clinical plasma cells-related genes to aid therapy in colon cancer

The tumor immune microenvironment (TIME) of colon cancer (CC) has been associated with extensive immune cell infiltration (IMI). Increasing evidence demonstrated that plasma cells (PC) have an extremely important role in advance of antitumor immunity. Nonetheless, there is a lack of comprehensive analyses of PC infiltration in clinical prognosis and immunotherapy in CC. This study systematically addressed the gene expression model and clinical information of CC patients. Clinical samples were obtained from the TCGA (The Cancer Genome Atlas) databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), GSVA, and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were employed to research the potential mechanism and pathways. Immunophenoscore (IPS) was obtained to evaluate the immunotherapeutic significance of risk score. Half maximal inhibitory concentration (IC50) of chemotherapeutic medicine was predicted by employing the pRRophetic algorithm. A total of 513 CC samples (including 472 tumor samples and 41 normal samples) were collected from the TCGA-GDC database. Significant black modules and 313 candidate genes were considered PC-related genes by accessing WGCNA. Five pivotal genes were established through multiple analyses, which revealed excellent prognostic. The underlying correlation between risk score with tumor mutation burden (TMB) was further explored. In addition, the risk score was obviously correlated with various tumor immune microenvironment (TIME). Also, risk CC samples showed various signaling pathways activity and different pivotal sensitivities to administering chemotherapy. Finally, the biological roles of the CD177 gene were uncovered in CC.

H2S‐Activated Ion‐Interference Therapy: A Novel Tumor Targeted Therapy Based on Copper‐Overload‐Mediated Cuproptosis and Pyroptosis

AbstractCopper overload is a novel way to achieve copper‐ion‐interference therapy by disrupting copper homeostasis and treating diseases through multiple cell death pathways. However, it is difficult to reach copper overload since excess intracellular copper ions will be pumped out. Herein, copper overload is achieved by both raising cellular uptake and reducing the efflux of copper ions using hydrogen sulfide (H2S)‐responsive copper hydroxyphosphate nanoparticles (Cu2(PO4)(OH) NPs). After immersion in an H2S‐enriched colon cancer microenvironment, Cu2(PO4)(OH) NPs can transform into copper sulfide NPs with reduced size for higher cell entering, resulting in improved Fenton activity as well as copper ion dissociation. Reactive oxygen species generated by the Fenton reaction not only activate inflammasomes and Caspase‐1 proteins, cause the cleavage of gasdermin D to induce pyroptosis, but also affect mitochondrial function and down‐regulate copper exporter ATP7A to further reduce the copper excretion. The combination of higher endocytosis and lower exportation leads to maximized copper overload. Together with the efficient copper ions release, mitochondrial tricarboxylic acid cycle can be disrupted and iron‐sulfur cluster proteins are downregulated, ultimately triggering cuproptosis. As both pyroptosis and cuproptosis are efficient ways to induce cell death, this study provides a novel way to realize effective tumor‐targeted therapy based on H2S‐activated copper overload with simple Cu2(PO4)(OH) NPs.

Effects of SMC1A on immune microenvironment and cancer stem cells in colon adenocarcinoma.

Our previous study suggested that SMC1 has significant functions in colorectal cancer (CRC). However, few reports have shown the effects of structural maintenance of chromosomes 1 (SMC1A) on the immune microenvironment and tumor stem cells. The Cancer Genome Atlas (TCGA) database, CPTAC database, Human Protein Atlas (HPA) database, the Cancer Cell Line Encyclopedia (CCLE) and Tumor Immune Single-cell Hub were used. Flow cytometry and immunohistochemical analysis were checked for immune infiltration on MC38 mice model. Human CRC tissues were tested with RT-qPCR. The mRNA and protein levels of SMC1A were increased in colon adenocarcinoma (COAD) samples.SMC1A was associated with DNA activity. Interestingly, SMC1A was highly expressed in many types of immune cells at single-cell levels. Moreover, the high expression of SMC1A was positively correlated with immune infiltration, and immunohistochemical analysis showed that SMC1A was positively associated with CD45 expression in MC38 mice model. Also, the percentage of IL4+ CD4+ T cells (Th2) and FoxP3+ CD4+ T cells (Tregs) was significantly higher in the SMC1A overexpression group than in control by flow cytometry assay in vivo. SMC1A expression could affect the proliferation of T cells in the mice model. The mutation and somatic cell copy number variation (SCNV) of SMC1A were also associated with immune cell infiltration. In addition to SMC1A in the "hot" T-cell inflammatory microenvironment of colon cancer, SMC1A also positively correlates with the immune checkpoint genes CD274, CTLA4, and PDCD1 in colon adenocarcinoma (COAD) samples. Furthermore, we also found that SMC1A plays a positive correlation with the induction of cancer stem cells (CSCs). Our results also showed that miR-23b-3p binds SMC1A. SMC1A may be a bidirectional target switch that simultaneously regulates the immune microenvironment and tumor stem cells. Moreover, SMC1A may be a biomarker for the prediction of immune checkpoint inhibitor (ICI) therapy.

Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer

Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease. To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients. The main purpose was to assess whether reasonable induction of these biomarkers reduces mortality among patients with colon cancers. Data obtained from The Cancer Genome Atlas and Gene Expression Omnibus and the Genotype-Tissue Expression were used in differential analysis to explore differential expression genes associated with cuproptosis and immune activation. The least absolute shrinkage and selection operator and Cox regression algorithm was applied to build a cuproptosis- and immune-related combination model, and the model was utilized for principal component analysis and survival analysis to observe the survival and prognosis of the patients. A series of statistically meaningful transcriptional analysis results demonstrated an intrinsic relationship between cuproptosis and the micro-environment of colon cancer. Once prognostic characteristics were obtained, the CDKN2A and DLAT genes related to cuproptosis were strongly linked to colon cancer: The first was a risk factor, whereas the second was a protective factor. The finding of the validation analysis showed that the comprehensive model associated with cuproptosis and immunity was statistically significant. Within the component expressions, the expressions of HSPA1A, CDKN2A, and UCN3 differed markedly. Transcription analysis primarily reflects the differential activation of related immune cells and pathways. Furthermore, genes linked to immune checkpoint inhibitors were expressed differently between the subgroups, which may reveal the mechanism of worse prognosis and the different sensitivities of chemotherapy. The prognosis of the high-risk group evaluated in the combined model was poorer, and cuproptosis was highly correlated with the prognosis of colon cancer. It is possible that we may be able to improve patients' prognosis by regulating the gene expression to intervene the risk score.

Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer

BackgroundColon cancer is a common and highly malignant tumor. Its incidence is increasing rapidly with poor prognosis. At present, immunotherapy is a rapidly developing treatment for colon cancer. The aim of this study was to construct a prognostic risk model based on immune genes for early diagnosis and accurate prognostic prediction of colon cancer.MethodsTranscriptome data and clinical data were downloaded from the cancer Genome Atlas database. Immunity genes were obtained from ImmPort database. The differentially expressed transcription factors (TFs) were obtained from Cistrome database. Differentially expressed (DE) immune genes were identified in 473 cases of colon cancer and 41 cases of normal adjacent tissues. An immune-related prognostic model of colon cancer was established and its clinical applicability was verified. Among 318 tumor-related transcription factors, differentially expressed transcription factors were finally obtained, and a regulatory network was constructed according to the up-down regulatory relationship.ResultsA total of 477 DE immune genes (180 up-regulated and 297 down-regulated) were detected. We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. The model was proved to be an independent prognostic variable with good prognostic ability. A total of 68 DE TFs (40 up-regulated and 23 down-regulated) were obtained. The regulation network between TF and immune genes was plotted by using TF as source node and immune genes as target node. In addition, Macrophage, Myeloid Dendritic cell and CD4+ T cell increased with the increase of risk score.ConclusionWe developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. This model can be used as a tool variable to predict the prognosis of colon cancer.

Raptinal ameliorates 1,2-dimethylhydrazine-induced colon cancer through p53/Bcl2/Bax/caspase-3-mediated apoptotic events in vitro and in vivo.

Colon carcinoma stands as the most familiar malignancy throughout across the globe. Raptinal induce apoptosis through the alteration of cellular events. Thus, in the present investigation, the anticancer activity of raptinal counter to 1,2-dimethylhydrazine (DMH) persuaded colon carcinoma has been evaluated through both in vivo and in vitro systems. The pharmacophore analysis demonstrated the binding efficacy of raptinal with the apoptotic proteins. The chemotherapeutic activity of raptinal was examined through HT-29 human colorectal cancer (CRC) cell line as well as DMH persuaded CRC in the rat model. The cytotoxicity analysis, flow cytometry, and DAPI analysis have been carried out on HT-29 cell line through in vitro assessment. The colon carcinoma has been induced through DMH administration and subsequently Dextran sulfate sodium treatment in male Wistar rats. After 18 weeks of raptinal treatment, the colon tissues have been investigated for aberrant crypt foci (ACF) count, antioxidant status, histology, immunohistochemical assessment, and apoptotic analysis. The raptinal therapy on HT-29 cells demonstrated a substantial % of early apoptosis followed by G0 and G1 phase arrest, which subsequently led to apoptosis. Furthermore, it inhibits ACF development with improved colonic abrasions and structural integrity of colonic mucosa with increased levels of antioxidants, proapoptotic biomarkers including p53, caspase-3, Bax and downstream effects of Bcl-2, tumor necrosis factor (TNF)-α, and interleukin (IL)-6 mutation. These findings indicate the raptinal effectively reduces colon cancer by inducing apoptosis through p53/Bcl2/Bax/caspase-3 pathway and suppressing IL-6, TNF-mediated chronic inflammation in the colon cancer microenvironment.

Extracellular matrix-based gene signature for predicting prognosis in colon cancer and immune microenvironment.

The extracellular matrix (ECM) plays a vital role in progression, expansion, and prognosis of malignancies. In this study, we aimed to explore a novel ECM-based prognostic model for patients with colon cancer (CC). ECM-related genes were obtained from Molecular Signatures database. Differential expression analysis was performed using the CC dataset from The Cancer Genome Atlas (TCGA) database. Four ECM-related genes related to overall survival were identified using the Cox regression and LASSO analysis. Then an ECM-related signature was developed and verified in three independent CC cohorts (GSE33882, GSE39582 and GSE29621) from the Gene Expression Omnibus (GEO). A prognostic nomogram was developed incorporating the ECM-related gene signature with clinical risk factors. CIBERSORT was used to explore the immune cell infiltration level. Human Protein Atlas (HPA) database was utilized to validate the expression levels of identified prognostic ECM genes. Four ECM-related genes (CXCL13, CXCL14, SFRP5 and THBS4) were identified to develop an ECM-based gene signature and demarcated CC patients into the high- and low-risk groups. In training and validation datasets, patients in the low-risk group had better overall survival outcomes than those in the high-risk group (log-rank P<0.001). In addition, ECM-related signature was significantly associated with consensus molecular subtype 4 (CMS4) as well as other known clinical risk factors such as a higher Tumor, Nodal Involvement, Metastasis (TNM) stage. Moreover, the risk score derived from the ECM-based gene signature could be utilized as an independent prognostic factor for CC patients. A nomogram including the ECM-related gene signature, age and stage was developed to serve clinical practice. CIBERSORT analysis showed immune cell infiltration was different between high- and low-risk groups. The immunohistochemical results derived from HPA indicated differential expression of prognosis-related ECM genes in CC and normal tissues. In the present study, a novel risk model based on ECM-signature could effectively reflect individual risk classification and provide potential therapeutic targets for CC patients. Moreover, the prognostic nomogram may help predict individualized survival.

Colon tumor CD31 expression is associated with higher disease-free survival in patients with metabolic syndrome.

Metabolic syndrome (MS) is recognized as a risk factor for colon cancer (CC). However, how does the interplay between metabolic dysfunction caused by MS and its individual components affect CC microenvironment and prognosis remains unexplored. Angiogenesis and lymphangiogenesis are fundamental processes for tumor progression and dissemination, ensuring oxygen and nutrient delivery and supporting one of the most important pathways of tumor dissemination, contributing to metastasis. Thus, our aim was to evaluate whether the expression of molecular biomarkers involved in angiogenic and lymphangiogenic processes influenced CC clinicopathological features and prognosis in patients with MS. Clinical and pathological data of 300 patients submitted to CC surgical resection at a single tertiary hospital were retrospectively retrieved from hospital records. Tumor tissue microarrays of archived paraffin-embedded blocks were used to assess CD31, VEGF-A and D2-40 tissue expression by immunohistochemistry. The percentage of stained area was quantified by computerized morphometric analysis. No association between tissue expression of angiogenesis and lymphangiogenesis biomarkers and tumor clinical and pathological characteristics was found. However, in subgroup analysis of patients with MS, dysglycemia was associated with lower D2-40 expression (p=0.007) and high waist-circumference was associated with higher D2-40 (p=0.0029) and VEGF-A expression (p=0.026). In an adjusted Cox proportional hazard model CD31 expression was significantly associated with greater disease-free survival (HR=0.62; 95% CI: 0.41-0.95, p=0.028). No association was found between D2-40 and VEGF-A expression and CC prognosis. Our data reinforces previous reports that suggest the potential use of CD31 as a CC prognostic biomarker. Additionally, our data further supports the evidence for an interplay between metabolic dysfunction, tumor microenvironment, and vascularization pathways.

Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer

BackgroundEnergy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients.MethodsThe transcriptome profile and clinical data of patients with colon cancer were retrieved from The Cancer Genome Atlas database. Using consensus clustering, cases were divided into two clusters and Kaplan–Meier analysis was executed to analyze differences in their prognoses. The gene set enrichment analysis (GSEA) was used to discover biological processes and signaling pathways. A lipid metabolism-related lncRNA prognostic model (lipid metabolism-LncRM) was created utilizing the least absolute shrinkage and selection operator (LASSO) regression. The tumor microenvironment was evaluated on the basis of the composition of immune and stromal cells.ResultsThe patients in Cluster 2 were found to have a better prognosis and higher expression of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) relative to Cluster 1. The results of GSEA showed the enrichment of energy metabolism pathways in Cluster 2. LASSO regression was used to identify the five LncRNAs that were shown to be most substantially linked to patient prognosis. These were NSMCE1-DT, LINC02084, MYOSLID, LINC02428, and MRPS9-AS1. Receiver operating characteristic (ROC) curves and survival analysis illustrated that the lipid metabolism-LncRM had a significant prognostic value. Further analysis showed that high- and low-risk groups were significantly different in terms of clinical characteristics and immune cells infiltration.ConclusionsLipid metabolism-related lncRNAs could predict the prognoses and tumor microenvironment of colon cancer and might be important biomarkers relevant to immunotherapy.

PD-1 blockage combined with vaccine therapy can facilitate immune infiltration in tumor microenvironment of Lynch syndrome colon cancer.

Background: Lynch syndrome is a genetic disease resulting from mismatch repair gene mutation. Vaccine therapy can enhance the immunogenicity of Lynch syndrome and improve the therapeutic efficacy of immunotherapy. However, there is no approved Lynch syndrome vaccine coming onto the market. Methods: Herein, we used gene knockdown method to construct Lynch syndrome cell model, paving way for us to develop Lynch syndrome tumor lysate vaccine. Then the isograft technique was employed for constructing the tumor-bearing mouse model of Lynch syndrome. And this isograft model was treated with PD-1 monoclonal antibody and tumor vaccine, respectively. Flow cytometry was used for detecting the proportion of immune cells and immunosuppressive cells, and ELISA was used for detecting the contents of chemokines and cytokines in the blood circulation system and tumor tissues of mice. Finally, IHC was used to detect the effects of tumor vaccines as well as PD-1 antibody on tumor tissue proliferation and angiogenesis. Results: The results demonstrated that tumor vaccine could prolong the overall survival of mice, and improve the disease-free survival rate of mice. The vaccine could increase the proportion of inflammatory cells and decrease the proportion of anti-inflammatory cells in the blood circulation system of mice. In addition, tumor vaccine could also improve inflammatory infiltration in the tumor microenvironment and reduce the proportion of immunosuppressive cells. The results of IHC showed that tumor vaccine could inhibit angiogenesis and tumor cell proliferation in mouse tumor tissues. Conclusion: In colon cancer associated with Lynch syndrome, tumor vaccine can hinder the growth of tumor cells, and assist immunotherapy whose therapeutic effect on this kind of cancer is thus enhanced.

Significance of ZEB2 in the immune microenvironment of colon cancer.

Background: ZEB2 is a protein-coding gene that is differentially expressed in tumors and can regulate the growth of tumor cells. This study investigated the specific regulatory mechanism of ZEB2 in COAD, a common cancer with high rates of morbidity and mortality. Methods: Multi-omics panoramic display of expression and function of ZEB2 in colon cancer. R software was used to study the expression of ZEB2 in 33 types of cancer. Furthermore, RT-PCR was used to detect the expression of ZEB2 in colon cancers and para-cancer tissues, as well as in colon cancer cells and normal cells. The ssGSEA was then used to explore the relationship between ZEB2 and immune cells, with UALCAN, EWAS and MEXPRESS applied to explore the methylation of ZEB2. The relationship between immunomodulators and chemokines (or receptors) based on expression data, copy number data, methylation data, and mutation data of ZEB2 was investigated using TISIDB. Finally, a protein interaction network of ZEB2 was constructed, and GO and KEGG analyses were performed on the differentially expressed genes. Results: ZEB2 is downregulated in most cancers, including COAD. The infiltration of the immune cells NK CD56 and Th17 cells was negatively correlated with ZEB2 expression, while the other 22 cells were positively correlated with ZEB2 expression. The DNA methylation of ZEB2 and the methylation of the ZEB2 protein on the EWAS website increased significantly. Analysis of the methylation levels and ZEB2 expression revealed that only the DNA methylation level and the expression of ZEB2 were significantly negatively correlated. The tumor-infiltrating lymphocytes positively correlated with the expression of ZEB2 but negatively correlated with the methylation of ZEB2. The same trend was observed for immunomodulators, chemokines, and receptors. The network showed that the protein performed certain biological functions, thereby affecting disease symptoms. Conclusion: These findings provide evidence that ZEB2-based therapy may represent a powerful treatment strategy for COAD.

Modulating the Siah2-PHD3-HIF1α axis and/or autophagy potentially retard colon cancer proliferation possibly, due to the damping of colon cancer stem cells

BackgroundHypoxic microenvironment of colon cancer is associated with HIF-1α upregulation. HIF-1α response elements are responsible for autophagy induction that promotes tumor proliferation. Moreover, HIF-1α induces tumor cell proliferation via maintaining cancer stem cells (CSCs) survival. Siah2 is E3 ubiquitin ligase that indirectly stabilizes HIF-1α. We hypothesized that dual inhibition of Siah2 as well as autophagy could be a promising approach that may inhibit CSCs growth. Aim of the workThis study investigated the possible effect of vitamin K3 as a Siah2 inhibitor and hydroxychloroquine as an autophagy inhibitor in colon cancer management. The effect (if any) of these agents on CSCs growth will be also manipulated. MethodsColon cancer was induced by dimethylhydrazine. MDA and GSH were selected as oxidative stress markers, Expression of HIF-1α, Caspase-3, VEGF, MMP-9, EpCAM, SCF, and CA19.9 were assayed using immunoassay. The Western blot technique was used to assess LC3Ⅰ, CD44, and CD133 whereas RT-PCR was used to investigate PHD3 and CD44 in colon tissues. Additionally, Ki-67 and Siah2 were detected immunohistochemically. Resultsvitamin K3 and hydroxychloroquine either alone or in combination downregulated the expression of Siah2 and HIF-1α through upregulating PHD3 in colon tissues. This combination significantly downregulated MDA, Ki-67, VEGF, and MMP-9 expression and upregulated the expression of GSH and caspase-3. LC3Ⅰ was also upregulated. Interestingly, these therapeutic options were correlated with down-regulation of the cancer stem cell marker such as CD44 and EpCAM. ConclusionOur results suggested that suppression of both Siah2-PHD3-HIF-1α axis and autophagy retard colon cancer proliferation and dampened CSCs