Prognosis Of Colon Cancer Patients Research Articles

Tumor necrosis serves as an important pathological characteristic of stage I-II colon cancer.

The long-term prognosis of colon cancer patients remains little changed with relatively high mortality and morbidity. Since the most widely used prognostic parameter TNM staging system is less satisfactory in predicting prognosis in early-stage cancers, numerous clinicopathological factors, including tumor necrosis, have been proposed for prognosis stratification, but substantial evidences are still lacking for early-stage colon cancer. In the retrospective study, a total of eligible 173 stage I-II colon cancer patients, who received tumor radical resection and lymphadenectomy in the local hospital between January 1, 2010, and December 31, 2018, were enrolled for analyzing the prognostic role of tumor necrosis. The primary endpoints included 5-year overall survival (OS) and progression-free survival (PFS). The median follow-up of enrolled early-stage colon cancer patients was 58.3 months. The 2-year and 5-year OS rates were 88.3% and 68.2%, respectively, and the 2-year and 5-year PFS rates were 85.6% and 62.7%, respectively. Seventy-eight patients (45.1%) were diagnosed with tumor necrosis by pathological examination. Demographic analysis revealed a significant association of tumor necrosis with larger tumor size and a marginal association with vascular invasion. Kaplan-Meier survival curves demonstrated that tumor necrosis was associated with worse OS (log-rank P = 0.003) and PFS (log-rank P = 0.002). The independent unfavorable prognostic effect of tumor necrosis was further validated in univariate and multivariate Cox regression analysis (hazard ratio = 1.91 (1.52-2.40), P = 0.004). The current study confirmed the independent prognostic role of tumor necrosis from pathological review in early-stage colon cancer patients. This pathological criterion promises to help in identifying high-risk subgroup from early-stage colon cancer patients, who may benefit from strict follow-up and adjuvant therapy.

Expression of Anoikis-Related Genes and Potential Biomarkers in Colon Cancer Based on RNA-seq and scRNA-seq.

Colon cancer (CC) is a malignant tumor in the colon. Despite some progress in the early detection and treatment of CC in recent years, some patients still experience recurrence and metastasis. Therefore, it is urgent to better predict the prognosis of CC patients and identify new biomarkers. Recent studies have shown that anoikis-related genes (ARGs) play a significant role in the progression of many tumors. Hence, it is essential to confirm the role of ARGs in the development and treatment of CC by integrating scRNA-seq and transcriptome data. This study integrated transcriptome and single-cell sequencing (scRNA-seq) data from CC samples to evaluate patient stratification, prognosis, and ARG expression in different cell types. Specifically, differential expression of ARGs was identified through consensus clustering to classify CC subtypes. Subsequently, a CC risk model composed of CDKN2A, NOX4, INHBB, CRYAB, TWIST1, CD36, SERPINE1, and MMP3 was constructed using prognosis-related ARGs. Finally, using scRNA-seq data of CC, the expression landscape of prognostic genes in different cell types and the relationship between important immune cells and other cells were explored. Through the above analysis, two CC subtypes were identified, showing significant differences in prognosis and clinical factors. Subsequently, a risk model comprising aforementioned genes successfully categorized all CC samples into two risk groups, which also exhibited significant differences in prognosis, clinical factors, involved pathways, immune landscape, and drug sensitivity. Multiple pathways (cell adhesion molecules (CAMs), and extracellular matrix (ECM) receptor interaction) and immune cells/immune functions (B cell naive, dendritic cell activate, plasma cells, and T cells CD4 memory activated) related to CC were identified. Furthermore, it was found that prognostic genes were highly expressed in various immune cells, and B cells exhibited more and stronger interaction pathways with other cells. The results of this study may provide references for personalized treatment and potential biomarker identification in CC.

Emergency resection for stage II colon cancer: patterns of recurrence and prognostic factors

Background: The prognosis in colon cancer patients who undergo emergency curative resection remains uncertain. This study aimed to analyze the oncological outcomes in stage II colon cancer patients who underwent emergency or elective colon resection and identify the prognostic factors for recurrence following emergency resection. Methods: Patients in this study underwent curative resection for stage II colon cancer between March 2008 and December 2020. Based on surgical condition, patients were divided into two groups: emergency and elective. The two groups were compared regarding clinicopathological features and postoperative recurrence. Prognostic factors for recurrence were analyzed in the emergency resection group. Results: Among 161 patients, 60 and 101 patients were emergency group and elective group, respectively. The emergency group had significantly lower adequately harvested lymph nodes than the elective group (p=0.02). The emergency group had significantly poorer disease-free survival compared to the elective group (p=0.019). The most common recurrence site was local recurrence. No statistically significant difference was observed between the two groups in recurrence site. The presence of lymphovascular invasion and clinical perforation were prognostic factors for recurrence in the emergency resection group. Conclusion: Emergency resection for stage II colon cancer is associated with poor disease-free survival compared to elective resection. The prognosis may improve by performing appropriate radical surgery including extensive lymph node dissection. Adjuvant chemotherapy should be performed following emergency surgery for stage II colon cancer, especially when lymphovascular invasion or colonic perforation is identified.

Extracellular matrix stiffness modulates the mechanophenotypes and focal adhesions of colon cancer cells leading to their invasions via YAP1

Distal metastasis is the main cause of clinical treatment failure in patients with colon cancer. It is now known that the invasion and metastasis of cancer cells is precisely regulated by chemical and physical factors in vivo. However, the role of extracellular matrix (ECM) stiffness in colon cancer cell (CCCs) invasion and metastasis remains unclear. Here, bioinformatical analysis suggested that a high expression level of yes associated protein 1 (YAP1) was significantly associated with metastasis and poor prognosis in colon cancer patients. We further investigated the effects of polyacrylamide hydrogels with different stiffnesses (3, 20, and 38 ​kPa), which were simulated as ECM, on the mechanophenotype (F-actin cytoskeleton organization, electrophoretic rate, membrane fluidity, and Young's modulus) of CCCs. The results showed that a stiffer ECM could induce the maturation of focal adhesions and formation of stress fibers in CCCs, regulate their mechanophenotypes, and promote cell motility. We also demonstrated that the expression levels of YAP1 and paxillin were positively correlated in patients with colon cancer. YAP1 knockdown reduces paxillin clustering and cell motility and alters the cellular mechanophenotypes of CCCs. This is of great significance for an in-depth understanding of the invasion and metastatic mechanisms of colon cancer and for the optimization of clinical therapy from the perspective of mechanobiology.

Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.

Prognostic and immunological role of adaptor related protein complex 3 subunit mu2 in colon cancer

The expression levels and prognostic role of AP3M2 in colorectal adenocarcinoma (CRAC) have yet to be fully unveiled. Our study comprehensively investigated the clinical significance of AP3M2 in colorectal cancer through an extensive bioinformatics data mining process (TCGA, GEO, GEPIA, Timer, Ualcan, ROCPLOT, and David), followed by experimental validation. We found AP3M2 is a cancer gene, which can be used to distinguish between colorectal cancer and colorectal adenomas, liver metastasis, lung metastasis, colorectal polyp. Higher AP3M2 expression levels were associated with longer overall survival in colon adenocarcinoma. AP3M2 might be the primary biomarker for oxaliplatin in colon cancer and an acquired resistance biomarker for oxaliplatin and 5-fu. AP3M2 was positively associated with CD274, CTLA4. AP3M2 might be associated with T-cell, NF-kappaB transcription factor activity, and response to hypoxia. AP3M2 could predict chemotherapy effectiveness and prognosis for colon cancer patients. AP3M2 might inhibit tumor growth via influencing tumor-infiltrating immune cells in the context of Tumor microenvironment. AP3M2 plays as an oncogene in CRAC and is suggested as a new potential biotarget for therapy.

The Ferroptosis Induced by Palmitic Acid via CD36 Activating ER Stress to Break Calcium-Iron Balance in Colon Cancer Cells

There have been numerous studies to date on the treatment of tumors by saturated fatty acids. But the role that ferroptosis plays in this is not clear. Palmitic acid (PA) is a common saturated fatty acid with huge application prospects for inducing tumor cell ferroptosis. In vivo and in vitro experiments were performed to verify changes in cell proliferation, apoptosis and ferroptosis after PA treatment of colon cancer cells. Changes in ROS, lipid peroxidation, ferric ions, calcium ions, endoplasmic reticulum (ER) stress, endocytosis recycling trafficking of transferrin after PA treatment of colon cancer cells were detected. Further using necrosis inhibitor (Necrostatin-1), apoptosis inhibitor (Z-VAD-FMK), autophagy inhibitor (CQ), iron death inhibitor (Fer-1), calcium / ferric ion chelator (BAPTA-AM / DFP), iron supplement (FAC), calcium ion agonist (thapsigargin) for positive and negative verification. The association of CD36 expression and patient prognosis in colon cancer patients was subsequently evaluated by bioinformatics analysis. Detect the difference of CD36 expression in different colon cancer cells induced by PA, and further knock down or over express CD36 to explore the change of sensitivity to PA induced ferroptosis. PA inhibited colon cancer cell viability in vitro and in vivo, in conjunction with an accumulation of ROS and lipid peroxidation. The ferroptosis inhibitor Ferrostatin-1 but not Z-VAD-FMK, Necrostatin-1, or CQ rescued the cell death induced by PA. Subsequently, we verified that PA-induced ferroptosis through excess iron as cell death was inhibited by iron chelator deferiprone (DFP) but exacerbated by a supplement of ferric ammonium citrate (FAC). Mechanistically, PA leads to endoplasmic reticulum calcium release by inducing ER stress, and the increase of cytosolic calcium level positively regulates the endocytosis recycling transport of transferrin to promote the increase of intracellular iron content. Furthermore, we observed that cells with high expression of CD36 were more vulnerable to PA-induced ferroptosis. Knocking down the expression of CD36 can inhibit the sensitivity of colon cancer cells to PA induced ferroptosis, and vice versa. In general, we report for the first time that PA can selectively induce ferroptosis in colon cancer cells with high expression of CD36 by activating ER stress/ER calcium release/transferrin-dependent ferroptosis. This provides a new strategy and basis for the precise treatment of tumors.

Validation of quercetin in the treatment of colon cancer with diabetes via network pharmacology, molecular dynamics simulations, and in vitro experiments.

This study built a prognostic model for CRC-diabetes and analyzed whether quercetin could be used for CRC-diabetes treatment through a network of pharmacology, molecular dynamics simulation, bioinformatics, and in vitro experiments. First, multivariate Cox proportional hazards regression was used to construct the prognosis modelof CRC-diabetes. Then, the intersection of quercetin target genes with CRC-diabetes genes was used to find the potential target for quercetin in the treatment of CRC-diabetes. Molecular docking and molecular dynamics simulations were used to screen the potential targets for quercetin in the treatment of CRC-diabetes. Finally, we verified the target and pathway of quercetin in the treatment of CRC-diabetes through in vitro experiments. Through molecular docking, seven proteins (HMOX1, ACE, MYC, MMP9, PLAU, MMP3, and MMP1) were selected as potential targets of quercetin. We conducted molecular dynamics simulations of quercetin and the above proteins, respectively, and found that the binding structure of quercetin with MMP9 and PLAU was relatively stable. Finally, according to the results of Western blot results, it was confirmed that quercetin could interact with MMP9. The experimental results show that quercetin may affect the JNK pathway, glycolysis, and epithelial-mesenchymal transition (EMT) to treat CRC-diabetes. Based on the TCGA, TTD, DrugBank, and other databases, a prediction model that can effectively predict the prognosis of colon cancer patients with diabetes was constructed. According to experiment results, quercetin can regulate the expression of MMP9. By acting on the JNK pathway, glycolysis, and EMT, it can treat colon cancer patients with diabetes.

Transcription activation of SPINK4 by ELF-1 augments progression of colon cancer by regulating biological behaviors

BackgroundSPINK4 was highly expressed in colorectal cancer and resulted in worse prognosis of colorectal cancer patients. However, the expression and function of SPINK4 in colon cancer have not been revealed. MethodsAnalysis from GEPIA website showed the expression and function of SPINK4 in colon cancer samples. Colon cancer cell lines were applied to detect the biological function of SPINK4. Functionally, the transcriptional factor of SPINK4 has been predicted and verified. Finally, the associations between transcriptional factor and SPINK4 have been confirmed. ResultsSPINK4 expression was obviously increased in colon cancer samples. HCT-116 and DXH-1 cells in si-SPINK4–1 or si-SPINK4–2 group displayed an obvious reduction in its proliferation, cell cycle, invasion and migration compared to those in the si-control group. Moreover, transcriptional factor ELF-1 bound to the promoter of SPINK4 and affected its expression in colon cancer cells. High ELF-1 expression was presented in colon cancer samples and resulted in worse prognosis of colon cancer patients. Additionally, si-SPINK4 antagonized the function of ELF-1 overexpression in modulating colon cancer cell proliferation, cell cycle and mobility. ConclusionsOur findings afforded a theoretical basis for further research on the treatment of colon cancer based on the control of ELF-1/SPINK4 expression.

Prognostic value and chemotherapy response prediction of a proliferation essential gene signature in colon cancer.

Colon cancer is a common malignant tumor in the digestive tract. Exploring new treatment targets is of great significance for improving the survival rate of colon cancer patients. The present study mainly analyzes the impact of proliferation essential genes (PLEGs) on the prognosis and chemotherapy response of colon cancer patients, as well as identifying the expression and cellular functions of important PLEG. The DepMap database was utilized for identification of PLEG in colon cancer cells. Through DEGs screening, WGCNA, univariate cox regression survival analysis, and LASSO, a PLEG signature (PLEGs) model was constructed. The impact of PLEGs on the prognosis of colon cancer patients and their response to chemotherapy was further analyzed. Finally, we conducted a random forest analysis and implemented functional experiments to investigate the prominent PLEG that is linked to the development of colon cancer. Based on the expression and prognosis of PLEG, we constructed a PLEGs prognosis model which can effectively predict the prognosis of colon cancer patients and their response to chemotherapy treatment. Random forest analysis showed that UBA1 is a key PLEG in the progression of colon cancer. Immunohistochemistry results revealed that UBA1 protein is significantly upregulated in colon cancer tissues. Cell functional experiments demonstrated that knocking down UBA1 can inhibit the proliferation, invasion, and migration abilities of colon cancer cells. PLEGs have the potential to serve as predictive biomarkers for prognosis and chemotherapy response in colon cancer patients. Among the PLEG, UBA1 plays a prominent role in promoting the malignant progression of colon cancer cells.

Prognosis of colon cancer patients based on enhancer RNAs-related genes.

Colon cancer (CC) is a cancer of the large intestine with high prevalence and poor prognosis. enhancer RNAs. Therefore, valuable tools or biomarkers for predicting patient status, directing clinical practice, and reducing overtreatment are needed. Enhancer RNAs (eRNAs), a class of noncoding RNAs transcribed from enhancers, have been shown to function as regulators of oncogene or tumor suppressor gene expression. The aim of our study was to explore the potential roles of eRNAs and their target enhancer-related genes (ERGs) in the prognosis of CC. Selected CC cases (stage I-III) from The Cancer Genome Atlas database were used as a training set, and cases from the Gene Expression Omnibus were used as the validation set. ERGs associated with prognosis were screened through three steps: potential, candidate, and prognosis ERGs. Multivariate Cox proportional hazards analysis was used to identify independent prognostic factors, and a nomogram was created. Calibration curves were drawn by comparing predicted and observed survival probability. For validation, the calibration curves and ROC analysis were also applied to two external validation sets. The biological significance and clinical application of the genes obtained were investigated. Based on the multiple tiers of strict screening, 11 prognostic ERGs were obtained, which were combined to obtain a prognosis signature. A compound nomogram integrating age, TNM classification, and the prognostic signature was constructed. The model was reliable in distinguishing the risk of patients with stage I-III CC, with AUCs of 0.78 and 0.70 at 5 and 7years, respectively. There was good reproducibility in calibration curves. The prognostic model also yielded good prediction capability in the validation sets. In this study, the usefulness and specificity of the ERGs in prognosis were described, which should be considered a key feature in the clinical guidance of CC patients with early stage. We concluded that the major implications of the eRNAs and ERGs should be valued, which would be an emerging hallmark in the prognosis of cancer.

Clinical characteristics and prognosis analysis of postoperative patients with stage I-III colon cancer based on SEER database.

To identify the relevant factors affecting the prognosis and survival time of colon cancer and construct a survival prediction model. Data on postoperative stage I-III colon cancer patients were obtained from the Surveillance, Epidemiology, and End Results database. We used R project to analyze the data. Univariate and multivariate Cox regression analyses were performed for independent factors correlated with overall survival from colon cancer. The C-index was used to screen the factors that had the greatest influence in overall survival after surgery in colon cancer patients. Receiver operating characteristic (ROC) curve was made according to the Risk score and calculated to validate the predictive accuracy of the model. In addition, we used decision curve analysis (DCA) to evaluate the clinical benefits and utility of the nomogram. We created a model survival curve to determine the difference in prognosis between patients in the low-risk group and those in the high-risk group. Univariate and multifactor COX analyses showed that the race, Grade, tumor size, N-stage and T-stage were independent risk factors affecting survival time of patients. The analysis of ROC and DCA showed the nomogram prediction model constructed based on the above indicators has good predictive effects. Overall, the nomogram constructed in this study has good predictive effects. It can provide a reference for future clinicians to evaluate the prognosis of colon cancer patients.

Constructing a novel signature and predicting the immune landscape of colon cancer using N6-methylandenosine-related lncRNAs.

Background: Colon cancer (CC) is a prevalent malignant tumor that affects people all around the world. In this study, N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) in 473 colon cancers and 41 adjacent tissues of CC patients from The Cancer Genome Atlas (TCGA) were investigated. Method: The Pearson correlation analysis was conducted to examine the m6A-related lncRNAs, and the univariate Cox regression analysis was performed to screen 38 prognostic m6A-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) regression analysis were carried out on 38 prognostic lncRNAs to develop a 14 m6A-related lncRNAs prognostic signature (m6A-LPS) in CC. The availability of the m6A-LPS was evaluated using the Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. Results: Three m6A modification patterns with significantly different N stages, survival time, and immune landscapes were identified. It has been discovered that the m6A-LPS, which is based on 14 m6A-related lncRNAs (TNFRSF10A-AS1, AC245041.1, AL513550.1, UTAT33, SNHG26, AC092944.1, ITGB1-DT, AL138921.1, AC099850.3, NCBP2-AS1, AL137782.1, AC073896.3, AP006621.2, AC147651.1), may represent a new, promising biomarker with great potential. It was re-evaluated in terms of survival rate, clinical features, tumor infiltration immune cells, biomarkers related to Immune Checkpoint Inhibitors (ICIs), and chemotherapeutic drug efficacy. The m6A-LPS has been revealed to be a novel potential and promising predictor for evaluating the prognosis of CC patients. Conclusion: This study revealed that the risk signature is a promising predictive indicator that may provide more accurate clinical applications in CC therapeutics and enable effective therapy strategies for clinicians.

Identification of Hypoxia-Associated Signature in Colon Cancer to Assess Tumor Immune Microenvironment and Predict Prognosis Based on 14 Hypoxia-Associated Genes.

Colon cancer is the main malignant tumor of the digestive tract. Hypoxia is highly related to the occurrence, progression and tumor immune microenvironment (TIME) of cancer. The aim of this study was to identify a hypoxia-associated signature with high accuracy for predicting the prognosis and TIME of colon cancer. Download colon cancer data from the GEO and TCGA databases. A novel hypoxia risk model was identified to predict the prognosis of colon cancer patients. Subsequently, GSEA, TIME and mutation analysis were performed in the hypoxia high and low risk score groups. Finally, the signature gene ANKZF1 was selected for functional verification at the cellular level. A novel hypoxia risk model was identified. The risk score was significantly associated with poorer overall survival in colon cancer, and could be used as an independent prognostic factor for colon cancer. GSEA analysis found that the processes related to stimulate tumor proliferation and anti-apoptosis were significantly enriched in the hypoxia high risk score group. The expression of immunosuppressive cells and most immune checkpoints in the high risk score group was significantly higher than that in the low risk score group. In vitro cell experiments showed that knockdown the expression of ANKZF1 could inhibit the proliferation, migration and invasion of colon cancer cells. Hypoxia plays an important role in evaluating the TIME and predicting the prognosis of colon cancer.

Construction and validation of a chemokine family-based signature for the prediction of prognosis and therapeutic response in colon cancer

The role of chemokines in predicting the prognosis of colon cancer has not been mentioned. Chemokines have been shown to be associated with immune cell chemotaxis and activation, so the expression of chemokine genes in tumor tissue may be related to prognosis. We used a least absolute shrinkage and selection operator (LASSO) model based on chemokine gene families to construct a model that can predict the prognosis of colon cancer patients. We divided patients into high-risk groups and low-risk groups to study the prognosis. Then, we evaluated the relationship between the different risk groups in infiltration of immune cells. It was found that there was less immune cell infiltration in the high-risk group. We conducted a functional enrichment analysis based on model stratification, and explored the biological signal pathways enriched in the high and low-risk groups, which provided ideas for studying the mechanism behind its impact on prognosis. In addition, the chemokine-related gene signature could predict the response of patients to immunotherapy and chemotherapy.

The Expression and Role of NADPH Oxidase 2 in Colon Cancer.

Recent studies have reported that nicotinamide adenine dinucleotide phosphate oxidases (NOXs) are expressed in various cancers and play important roles in tumor progression. However, no studies have examined the expression and role of NOX2 in colon cancer. The aim of this study is to investigate the pathophysiological roles of NOX2 in colon cancer patients and cell lines. One-hundred and sixteen primary colon cancer samples of patients who underwent radical resection for locally advanced colon cancer were used for immunohistochemistry of NOX2 protein. The relationship between NOX2 expression and clinicopathological factors was assessed and the prognostic significance of NOX2 expression was evaluated in colon cancer patients. NOX2 siRNA transfection experiments were performed using two colon cancer cell lines (HCT116 and RKO) to analyze the impact of NOX2 expression on cellular physiological functions. The expression of NOX2 protein in noncancerous tissue was scarcely observed, and 45 samples (38.8%) showed positively stained NOX2 expression in cancer tissue. There were no clinicopathological factors significantly associated with NOX2 expression. The 5-year recurrence-free survival rate of the NOX2 positive group was significantly lower than that of the NOX2 negative group (61.1% vs. 79.3%, p=0.029). NOX2 depletion significantly inhibited cell proliferation with G1 arrest, and motility in the two cell lines. NOX2 expression level has a close association with the prognosis of colon cancer patients and physiological functions of colon cancer cells. NOX2 may be a useful prognostic biomarker for colon cancer patients.

TMEM211 Promotes Tumor Progression and Metastasis in Colon Cancer.

Colon cancer is the third most important cancer type, leading to a remarkable number of deaths, indicating the necessity of new biomarkers and therapeutic targets for colon cancer patients. Several transmembrane proteins (TMEMs) are associated with tumor progression and cancer malignancy. However, the clinical significance and biological roles of TMEM211 in cancer, especially in colon cancer, are still unknown. In this study, we found that TMEM211 was highly expressed in tumor tissues and the increased TMEM211 was associated with poor prognosis in colon cancer patients from The Cancer Genome Atlas (TCGA) database. We also showed that abilities regarding migration and invasion were reduced in TMEM211-silenced colon cancer cells (HCT116 and DLD-1). Moreover, TMEM211-silenced colon cancer cells showed decreased levels of Twist1, N-cadherin, Snail and Slug but increased levels of E-cadherin. Levels of phosphorylated ERK, AKT and RelA (NF-κB p65) were also decreased in TMEM211-silenced colon cancer cells. Our findings indicate that TMEM211 regulates epithelial-mesenchymal transition for metastasis through coactivating the ERK, AKT and NF-κB signaling pathways, which might provide a potential prognostic biomarker or therapeutic target for colon cancer patients in the future.

Proteomic profiling and functional characterization of serum-derived extracellular vesicles in the mucinous and non-mucinous colon adenocarcinoma.

Mucinous adenocarcinoma (MC) is a distinct pathological subtype of colon adenocarcinoma, which is associated with a worse prognosis compared with non-mucinous adenocarcinoma (AC). However, clear distinctions between MC and AC remain unknown. Extracellular vesicles (EVs) are a class of enclosed vesicles containing proteins, lipids, and nucleic acids that are secreted by cells into surrounding tissues or into serum. The EVs could facilitate tumorigenesis by regulating tumor cell proliferation, invasiveness, metastasis, angiogenesis, and evasion of immune surveillance. Quantitative proteomics analysis was performed to determine the characterization and biological differences of serum-derived EVs in two subtypes of colon adenocarcinoma (MC and AC). Serum-derived EVs from patients with MC, AC, and healthy volunteers were included in this study. The role of PLA2G2A in cell migration and invasion were evaluate with transwell assay, and its prognostic predictive value was further assessed based on TCGA database. Quantitative proteomics analysis revealed 846 differentially expressed proteins (DEPs) in EVs from MC patients compared with those from AC patients. Bioinformatics analysis revealed that the most prominent protein cluster included those involved in cell migration and the tumor microenvironment. Overexpression of PLA2G2A, one of the key EV proteins upregulated in patients with MC, in colon cancer cell line SW480 promoted the cell invasion and migration ability. In addition, the high level of PLA2G2A is associated with poor prognosis of colon cancer patients harboring BRAF mutations. Further, after EV stimulation, proteomic analysis of recipient SW480 cells showed that MC-derived EVs activated multiple cancer-related pathways, including the Wnt/β-Catenin signaling pathway, and might promote the malignancy of mucinous adenocarcinoma through these pathways. The identification of differential protein profiles between MC and AC helps to elucidate the underlying molecular mechanisms of MC pathogenesis. The PLA2G2A in EVs is a potential prognostic predictive marker for those patients harboring with BRAF mutations.

Construction of a Risk Model for Colon Cancer Prognosis Based on Ubiquitin-Related Genes.

Colon cancer is a frequently developed malignancy from the digestive system that leads to poor prognosis of patients due to its high recurrence and high metastasis. Dysregulation of ubiquitin-mediated signaling can result in tumor formation and metastasis. We aimed to develop prognostic markers related to ubiquitination in colon cancer and a risk assessment model based on these markers to improve the prognosis of colon cancer patients. We constructed a prognosis-related model by performing differential expression analysis on ubiquitin-related genes in colon cancer patients based on public data and then undertaking Cox analysis, which selected 7 ubiquitin-related prognostic genes (TRIM58, ZBTB7C, TINCR, NEBL, WDR72, KCTD9, and KLHL35). The samples were divided into high and low RiskScore groups according to the risk assessment model, and as Kaplan-Meier suggested, the overall survival of patients with high RiskScore was prominently lower than that of patients with low RiskScore. The accuracy of RiskScore was assessed by receiver operating characteristic curves. Accordingly, the area under the curve values of 1-, 3-, and 5-year were 0.76, 0.74, and 0.77 in the training set and 0.67, 0.66, and 0.74 in the validation set, respectively. These data confirmed the preferable performance of this prognostic model in predicting colon cancer patients' prognoses. The relationship between this RiskScore and clinicopathological factors of colon cancer patients was analyzed via stratification. Univariate and multivariate Cox regression analyses were performed to determine whether this RiskScore could be applied as an independent prognostic factor. Finally, in order to better apply the prognostic model in clinical practice, we constructed an overall survival nomogram for colon cancer patients' prognoses based on clinical factors and RiskScores, which has preferable prediction accuracy and is better than the traditional tumor, node, and metastasis (TNM) staging system. The overall survival nomogram for prognosis can assist clinical oncologists to make a more accurate evaluation of patients' prognosis, as well as the implementation of individualized diagnosis and treatment for colon cancer patients.

NXNL2 Promotes Colon Cancer Proliferation and Metastasis by Regulating AKT Pathway.

This study aimed to explore the role of nucleoredoxin-like 2 (NXNL2) in colon cancer (CC). The GEPIA and UALCAN databases were analyzed to explore genes involved in the prognosis of CC patients. DLD1 cells were treated with the DNA methylation inhibitor 5-azacitidine to validate the above findings. The methyltransferase DNMT (DNA methylation) was further knocked down by shRNA, then the expression of NXNL2 was assessed by qPCR. The role of NXNL2 on cell proliferation and metastasis was examined using corresponding assays. NXNL2 was found to exhibit the greatest impact on the prognosis of CC patients. High NXNL2 correlated with poor survival outcomes of CC. The expression of NXNL2 was regulated by DNA methylation. NXNL2 promoted CC cell proliferation and metastasis. Also, NXNL2 promoted the AKT pathway activity. In conclusion, NXNL2 could affect the cancer cell proliferation and metastasis, and has a poor survival prognosis in CC.