Gut microbial subtypes and clinicopathological value for colorectal cancer.

BACKGROUND: Gut bacteria are related to colorectal cancer (CRC) and its clinicopathologic characteristics. OBJECTIVE: To develop gut bacterial subtypes and explore potential microbial targets for CRC. METHODS: Stool samples from 914 volunteers (376 CRCs, 363 advanced adenomas, and 175 normal controls) were included for 16S rRNA sequencing. Unsupervised learning was used to generate gut microbial subtypes. Gut bacterial community composition and clustering effects were plotted. Differences of gut bacterial abundance were analyzed. Then, the association of CRC-associated bacteria with subtypes and the association of gut bacteria with clinical information were assessed. The CatBoost models based on gut differential bacteria were constructed to identify the diseases including CRC and advanced adenoma (AA). RESULTS: Four gut microbial subtypes (A, B, C, D) were finally obtained via unsupervised learning. The characteristic bacteria of each subtype were Escherichia-Shigella in subtype A, Streptococcus in subtype B, Blautia in subtype C, and Bacteroides in subtype D. Clinical information (e.g., free fatty acids and total cholesterol) and CRC pathological information (e.g., tumor depth) varied among gut microbial subtypes. Bacilli, Lactobacillales, etc., were positively correlated with subtype B. Positive correlation of Blautia, Lachnospiraceae, etc., with subtype C and negative correlation of Coriobacteriia, Coriobacteriales, etc., with subtype D were found. Finally, the predictive ability of CatBoost models for CRC identification was improved based on gut microbial subtypes. CONCLUSION: Gut microbial subtypes provide characteristic gut bacteria and are expected to contribute to the diagnosis of CRC.

Oral Microto-Nano Genome-Editing System Enabling Targeted Delivery and Conditional Activation of CRISPR-Cas9 for Gene Therapy of Inflammatory Bowel Disease.

The potent CRISPR-Cas9 technology can correct genes in human mutated cells to achieve the treatment of multiple diseases, but it lacks safe and effective delivery systems. Herein, we proposed an oral microto-nano genome-editing system aiming at the enteric excessive level of TNF-α for specific gene therapy of inflammatory bowel disease (IBD). This editing system facilitated the assembly of Cas9/sgRNA ribonucleoprotein (RNP) into nanoclusters (NCs) through the bridging of disulfide bonds. RNP-NCs were subsequently encapsulated within inflammatory cell-targeted lipopolysaccharide-deleted outer membrane vesicles (dOMVs) sourced from Escherichia coli Nissle 1917, which were further shielded by an outer layer of calcium alginate microspheres (CAMs). By leveraging the protection effect of CAMs, the oral administration system withstood gastric acid degradation upon entry into the stomach, achieving targeted delivery to the intestines with high efficiency. As the pH gradually rose, the microscale CAMs swelled and disintegrated, releasing nanoscale RNP-NCs encapsulated in dOMVs into the intestines. These RNP-NCs@dOMVs could traverse the mucosal barrier and target inflammatory macrophages where conditionally activated Cas9/sgRNA RNPs effectively perform genomic editing of TNF-α within the nucleus. Such oral microto-nano genome-editing systems represent a promising translational platform for the treatment of IBD.

Analysis of clinical characteristics of mismatch repair status in colorectal cancer: a multicenter retrospective study.

BACKGROUND: Microsatellite instability (MSI) caused by DNA mismatch repair (MMR) deficiency is of great significance in the occurrence, diagnosis and treatment of colorectal cancer (CRC). AIM: This study aimed to analyze the relationship between mismatch repair status and clinical characteristics of CRC. METHODS: The histopathological results and clinical characteristics of 2029 patients who suffered from CRC and underwent surgery at two centers from 2018 to 2020 were determined. After screening the importance of clinical characteristics through machine learning algorithms, the patients were divided into deficient mismatch repair (dMMR) and proficient mismatch repair (pMMR) groups based on the immunohistochemistry results and the clinical feature data between the two groups were observed by statistical methods. RESULTS: The dMMR and pMMR groups had significant differences in histologic type, TNM stage, maximum tumor diameter, lymph node metastasis, differentiation grade, gross appearance, and vascular invasion. There were significant differences between the MLH1 groups in age, histologic type, TNM stage, lymph node metastasis, tumor location, and depth of invasion. The MSH2 groups were significantly different in age. The MSH6 groups had significant differences in age, histologic type, and TNM stage. There were significant differences between the PMS2 groups in lymph node metastasis and tumor location. CRC was dominated by MLH1 and PMS2 combined expression loss (41.77%). There was a positive correlation between MLH1 and MSH2 and between MSH6 and PMS2 as well. CONCLUSIONS: The proportion of mucinous adenocarcinoma, protruding type, and poor differentiation is relatively high in dMMR CRCs, but lymph node metastasis is rare. It is worth noting that the expression of MMR protein has different prognostic significance in different stages of CRC disease.

Highly efficient prevention of radiation dermatitis using a PEGylated superoxide dismutase dissolving microneedle patch.

PEGylated superoxide dismutase (PEG-SOD) is commonly used as a cytoprotective agent in radiotherapy. However, its effectiveness in preventing radiation dermatitis is limited owing to its poor skin permeability. To address this issue, a PEG-SOD-loaded dissolving microneedle (PSMN) patch was developed to effectively prevent radiation dermatitis. Initially, PSMN patches were fabricated using a template mold method with polyvinylpyrrolidone K90 as the matrix material. PSMNs exhibited a conical shape with adequate mechanical strength to penetrate the stratum corneum. More than 90 % of PEG-SOD was released from the PSMN patches within 30 min. Notably, the PSMN patches showed a significantly higher drug skin permeation than the PEG-SOD solutions, with a 500-fold increase. In silico simulations and experiments on skin pharmacokinetics confirmed that PSMN patches enhanced drug permeation and skin absorption, in contrast to PEG-SOD solutions. More importantly, PSMN patches efficiently mitigated ionizing radiation-induced skin damage, accelerated the healing process of radiation-affected skin tissues, and exhibited highly effective radioprotective activity for DNA in the skin tissue. Therefore, PSMN patches are promising topical remedy for the prevention of radiation dermatitis.

Bacterial imaging in tumour diagnosis.

Some bacteria, such as Escherichia coli (E. coli) and Salmonella typhimurium (S. typhimurium), have an inherent ability to locate solid tumours, making them a versatile platform that can be combined with other tools to improve the tumour diagnosis and treatment. In anti-cancer therapy, bacteria function by carrying drugs directly or expressing exogenous therapeutic genes. The application of bacterial imaging in tumour diagnosis, a novel and promising research area, can indeed provide dynamic and real-time monitoring in both pre-treatment assessment and post-treatment detection. Different imaging techniques, including optical technology, acoustic imaging, magnetic resonance imaging (MRI) and nuclear medicine imaging, allow us to observe and track tumour-associated bacteria. Optical imaging, including bioluminescence and fluorescence, provides high-sensitivity and high-resolution imaging. Acoustic imaging is a real-time and non-invasive imaging technique with good penetration depth and spatial resolution. MRI provides high spatial resolution and radiation-free imaging. Nuclear medicine imaging, including positron emission tomography (PET) and single photon emission computed tomography (SPECT) can provide information on the distribution and dynamics of bacterial population. Moreover, strategies of synthetic biology modification and nanomaterial engineering modification can improve the viability and localization ability of bacteria while maintaining their autonomy and vitality, thus aiding the visualization of gut bacteria. However, there are some challenges, such as the relatively low bacterial abundance and heterogeneously distribution within the tumour, the high dimensionality of spatial datasets and the limitations of imaging labeling tools. In summary, with the continuous development of imaging technology and nanotechnology, it is expected to further make in-depth study on tumour-associated bacteria and develop new bacterial imaging methods for tumour diagnosis.

Third-generation PacBio sequencing to explore gut bacteria and gender in colorectal cancer.

BACKGROUND: Gut bacteria have an important influence on colorectal cancer (CRC). The differences of gut bacteria between genders have been the hot spots. OBJECTIVE: To analyze the relationship between gut bacteria and gender differences in patients with CRC. METHODS: A total of 212 patients with CRC and 212 healthy volunteers were recruited. The subjects' fecal samples were obtained, and the fecal microorganisms were analyzed by the third-generation sequencing PacBio. The composition of gut bacteria was analyzed. Linear discriminant analysis Effect Size (LEfSe) was used to analyze the differences in gut bacteria. Pearson coefficient was used to calculate the correlation between differential bacteria. CRC risk prediction models were used to rank the importance of effective differential bacteria. RESULTS: Escherichia flexneri and Phocaeicola vulgatus were the most frequent bacteria in both male and female CRC patients. Bacteroides, Verrucomicrobia and Akkermansiaceae were highly enriched in male CRC group, while Bacteroidetes, Phocaeicola and Tissierellales were highly enriched in female CRC group. Peptostreptococcus anaerobius and Phocaeicola vulgatus were important CRC related bacteria in males and females, respectively. Peptostreptococcus anaerobius was the most important characteristic bacterium of males (AUC = 0.951), and the sensitivity and specificity of the discovery set were 78.74 % and 93.98 %, respectively. Blautia stercoris was the most important characteristic bacterium of females (AUC = 0.966), and the sensitivity and specificity of the discovery set were 90.63 % and 90.63 %, respectively. CONCLUSION: Gut bacteria varied in different genders. Therefore, gender should be considered when gut bacteria are applied in the diagnose and prevention of CRC.

Tislelizumab combined with GT chemotherapy for intimal sarcoma of inferior vena cava: A case report.

RATIONALE: Intimal sarcoma of inferior vena cava (IVC) is a rare soft tissue sarcoma with no typical symptoms and specific imaging features in the early stage, and there is a lack of standardized treatment and methods. PATIENT CONCERNS: A 54-year-old female patient presented to Fenghua District People's Hospital with a post-active cough and hemoptysis and was subsequently referred to our hospital. DIAGNOSES: The patient was pathologically diagnosed as intimal sarcoma of IVC complicating multiple intrapulmonary metastases. Chest CT revealed left lung malignant tumor with multiple intrapulmonary metastases; while enhanced upper abdominal CT showed cancer embolus of IVC with extension to right atrium and bilateral renal veins. Besides, hematoxylin and eosin staining suggested intimal sarcoma of veins. Immunohistochemical staining showed positivity for PD-L1, Ki-67, CD31, Desmin and ERG. INTERVENTIONS: The patient initially received GT chemotherapy (gemcitabine injection + docetaxel). Then, immunotherapy (tislelizumab) was added based on the results of genetic testing (TP53 gene mutation). OUTCOMES: The disease was stabilized after receiving the treatment. LESSONS: Given the lack of characteristic clinical manifestations in patients with intimal sarcoma of IVC, imaging examination combined with immunohistochemical index were helpful for diagnosis of intimal sarcoma of IVC. Furthermore, the combination of tislelizumab and GT chemotherapy was feasible in such patients with positive PD-L1 expression and TP53 mutation.

Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule.

BACKGROUND: Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC). OBJECTIVE: To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples. METHODS: One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation. RESULTS: ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS. CONCLUSION: ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

Classification of Colorectal Cancer Subtypes Based on Endoplasmic Reticulum Stress.

INTRODUCTION: Endoplasmic reticulum stress (ERS) is associated with the occurrence and development of colorectal cancer (CRC). METHODS: One thousand nine CRC samples and 3 ERS gene sets from GEO database were used to screen and validate genes related to stage and prognosis of CRC. Twenty thousand five hundred thirty samples from the TCGA database validated the ERS genes related to prognosis. PPI network construction and coexpression analysis were used to investigate the correlation of genes. ConsensusClusterPlus analysis was used to classify CRC subtypes. Cox regression and the LASSO algorithm were used to screen ERS genes related to prognosis. HE staining, immunohistochemical staining, and RT-qPCR of 50 owner-central samples were used to verify the genes. The ERscore model was constructed based on the ERS genes related to prognosis. The nomogram model was used to verify that different subtypes of CRC patients have different prognosis. RESULTS: Fifty ERS differentially expressed genes related to CRC stage and 8 ERS model genes related to prognosis were screened. Three subtypes of CRC were classified based on the former 50 genes. The clinical characteristics were significantly different among the subtypes. The ERscore model was constructed based on the latter 8 genes, and its accuracy was verified by clinical samples. Finally, the nomogram was constructed based on ERscore, age, and CRC stage, and the accuracy of the nomogram prediction was verified. CONCLUSION: ERS-related genes can be used as classification criteria for CRC, and the related clinical characteristics of different CRC subtypes are different.

Advances in immunotyping of colorectal cancer.

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies.

Aging characteristics of colorectal cancer based on gut microbiota.

BACKGROUND: Aging is one of the factors leading to cancer. Gut microbiota is related to aging and colorectal cancer (CRC). METHODS: A total of 11 metagenomic data sets related to CRC were collected from the R package curated Metagenomic Data. After batch effect correction, healthy individuals and CRC samples were divided into three age groups. Ggplot2 and Microbiota Process packages were used for visual description of species composition and PCA in healthy individuals and CRC samples. LEfSe analysis was performed for species relative abundance data in healthy/CRC groups according to age. Spearman correlation coefficient of age-differentiated bacteria in healthy individuals and CRC samples was calculated separately. Finally, the age prediction model and CRC risk prediction model were constructed based on the age-differentiated bacteria. RESULTS: The structure and composition of the gut microbiota were significantly different among the three groups. For example, the abundance of Bacteroides vulgatus in the old group was lower than that in the other two groups, the abundance of Bacteroides fragilis increased with aging. In addition, seven species of bacteria whose abundance increases with aging were screened out. Furthermore, the abundance of pathogenic bacteria (Escherichia_coli, Butyricimonas_virosa, Ruminococcus_bicirculans, Bacteroides_fragilis and Streptococcus_vestibularis) increased with aging in CRCs. The abundance of probiotics (Eubacterium_eligens) decreased with aging in CRCs. The age prediction model for healthy individuals based on the 80 age-related differential bacteria and model of CRC patients based on the 58 age-related differential bacteria performed well, with AUC of 0.79 and 0.71, respectively. The AUC of CRC risk prediction model based on 45 disease differential bacteria was 0.83. After removing the intersection between the disease-differentiated bacteria and the age-differentiated bacteria from the healthy samples, the AUC of CRC risk prediction model based on remaining 31 bacteria was 0.8. CRC risk prediction models for each of the three age groups showed no significant difference in accuracy (young: AUC=0.82, middle: AUC=0.83, old: AUC=0.85). CONCLUSION: Age as a factor affecting microbial composition should be considered in the application of gut microbiota to predict the risk of CRC.

Single-cell transcriptome analysis reveals T population heterogeneity and functions in tumor microenvironment of colorectal cancer metastases.

Cell mediated immune escape, a microenvironment factor, induces tumorigenesis and metastasis. The purpose of this study was to display the characteristics of T cell populations in immune microenvironments for colorectal cancer (CRC) metastasis. Unsupervised cluster analysis was conducted to identify functionally distinct T cell clusters from 3,003 cells in peripheral blood and 4,656 cells in tissues. Subsequently, a total of 8 and 4 distinct T cell population clusters were identified from tumor tissue and peripheral blood, respectively. High levels of CD8+TEX, CD4+TRM, TH1-like T cells, CD8+TEM, tumor-Treg from tissues, and CD4+TN from peripheral blood are essential components of immune microenvironment for the prediction of CRC metastasis. Moreover, exhausted T cells are characterized by higher expression of multiple inhibitory receptors, including PDCD1 and LAG3. Some genes such as PFKFB3, GNLY, circDCUN1D4, TXNIP and NR4A2 in T cells of cluster were statistically different between CRC metastasis and non-metastasis. The ligand-receptor interactions identified between different cluster cells and metastases-related DEGs identified from each cluster revealed that the communications of cells, alterations of functions, and numbers of T subsets may contribute to the metastasis of CRC. The mutation frequency of KiAA1551, ATP8B4 and LNPEP in T cells from tissues and SOR1 from peripheral blood were higher in metastatic CRC than that in non-metastatic CRC. In conclusion, the discovery of differential genes in T cells may provide potential targets for immunotherapy of CRC metastasis and relevant insights into the clinical prediction and prognosis of CRC metastasis.

Pancreatic follicular dendritic cell sarcoma: a rare case report and systematic literature review of 7 cases.

INTRODUCTION: Pancreatic follicular dendritic cell sarcoma (FDCS) is an exceptionally rare and low-to-moderate malignancy, with only seven reported cases to date. Clinical diagnosis of FDCS is challenging due to the lack of distinct biological and radiographic features. CASE PRESENTATION: A 67-year-old woman presented to the hospital with a 4-day history of severe abdominal pain. Imaging studies (CT and MRI) revealed a large cystic mass located at the tail of the pancreas, which was suspected to be myeloid sarcoma (MS) based on EUS and CT-guided pancreatic puncture. Postoperative pathology and immunohistochemistry confirmed the diagnosis of pancreatic FDCS. After the diagnosis was confirmed, the patient received postoperative chemotherapy with the CHOP regimen. At 11 months of follow-up, there was no evidence of recurrence. Seven published cases have been reviewed to comprehensively summarize the clinical characteristics, diagnosis, and treatment options of FDCS. CONCLUSION: While imaging can be useful in detecting pancreatic FDCS, it should be interpreted with caution as it can be challenging to differentiate from other pancreatic tumors. Pathology and immunohistochemistry are considered the gold standard for diagnosis, with CD21, CD23, and CD35 being specific tumor cell markers. However, preoperative diagnosis of pancreatic FDCS remains difficult, and the pancreatic puncture may further increase the risk of misdiagnosis. The disease is highly prone to recurrence and metastasis, and surgery is the preferred method for both diagnosis and treatment of localized disease.

Mitochondria-associated endoplasmic reticulum membrane: Overview and inextricable link with cancer.

The mitochondrial-associated membrane (MAM) is a physical platform that facilitates communication between the endoplasmic reticulum (ER) and mitochondria. It is enriched with many proteins and enzymes and plays an important role in the regulation of several fundamental physiological processes, such as calcium (Ca2+ ) transfer, lipid synthesis, cellular autophagy and ER stress. Accumulating evidence suggests that oncogenes and suppressor genes are present at the ER-mitochondrial contact site, and their alterations can affect Ca2+ flux, lipid homeostasis, and the dysregulation of mitochondrial dynamics, thereby influencing the fate of cancer cells. Understanding the fundamental role of MAM-resident proteins in tumorigenesis could support the search for novel therapeutic targets in cancer. In this review, we summarize the basic structure of MAM and the core functions of MAM-resident proteins in tumorigenesis. In addition, we discuss the mechanisms by which natural compounds promote cancer cell apoptosis from the perspective of ER stress.

Analysis of bacterial diversity and community structure in gastric juice of patients with advanced gastric cancer.

BACKGROUND: The occurrence and development of gastric cancer are related to microorganisms, which can be used as potential biomarkers of gastric cancer. OBJECTIVE: To screen the microbiological markers of gastric cancer from the microorganisms of gastric juice. METHODS: Gastric juice samples were collected from 61 healthy people and 78 patients with gastric cancer (48 cases of early gastric cancer and 30 cases of advanced gastric cancer). The bacterial 16 S rRNA V1-V4 region of gastric juice samples was sequenced. The Shannon index, Simpson index, Ace index and Chao index were used to analyze the diversity of gastric juice samples. The RDP classifier Bayesian algorithm was used to analyze the community structure of 97% OTU representative sequences with similar levels. Linear discriminant analysis and ST-test were used to analyze the differences. Six machine learning algorithms, including the logistic regression algorithm, random forest algorithm, neural network algorithm, support vector machine algorithm, Catboost algorithm and gradient lifting tree algorithm, were used to construct risk prediction models for gastric cancer and advanced gastric cancer. RESULTS: The microbiota diversity and the abundance of bacteria was different in the healthy group, early gastric cancer and advanced gastric cancer (P < 0.05). The top five abundant bacteria among the three groups were Streptococcus, Rhodococcus, Prevotella, Pseudomonas and Helicobacter. Bacterial flora such as Streptococcus, Rhodococcus and Ochrobactrum were significantly different between the healthy group and the gastric cancer group. The accuracy of the random forest prediction model is the highest (82.73% correct). The bacteria with the highest predictive value included Streptococcus, Lactobacillus and Ochrobactrum. The abundance of bacteria such as Fusobacterium, Capnocytophaga, Atopobium, Corynebacterium was high in the advanced gastric cancer group. CONCLUSION: Gastric juice bacteria can be used as potential biomarkers to predict the occurrence and development of gastric cancer.

The different prognostic factors between metastatic and nonmetastatic disease of esophageal neuroendocrine carcinoma.

PURPOSE: The specific risk factors of metastatic and nonmetastatic esophageal neuroendocrine carcinoma (NEC) are still uncertain. Whether primary site surgery is necessary for all patients with esophageal NEC is unknown. METHODS: Patients with esophageal NEC in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2014 were selected. STATA 12 was used to analyze the clinical and pathological features of esophageal NEC. RESULTS: In total, 241 patients with esophageal NEC were included. Metastatic patients had shorter overall survival than nonmetastatic patients (6.03 versus 11.90 months, respectively). Prognostic factors varied between metastatic and nonmetastatic esophageal NEC. The location of the primary tumor is a key point for the prognosis of esophageal NEC. For nonmetastatic esophageal NEC, patients with tumors in the upper third of the esophagus had the worst survival, and patients with metastatic esophageal NEC with a primary tumor in the lower part of the esophagus tended to have an increased risk of death. Moreover, age ≥68 years (hazard ratio [HR] = 2.05; 95% confidence interval [CI]: 1.28-3.31; P < 0.01) and large cell carcinoma (HR = 2.79; 95% CI: 1.30-6.00; P < 0.01) were independent risk factors in patients with metastatic esophageal NEC. Primary site resection benefited patients with nonmetastatic esophageal NEC (HR = 0.20; 95% CI: 0.07-0.56; P < 0.01) rather than patients with metastatic esophageal NEC (HR = 0.91; 95% CI: 0.29-2.83; P > 0.05). CONCLUSIONS: Our study presented that primary tumor location is an important risk factor for nonmetastatic esophageal NEC patients. Age and pathological type are important risk factors for patients with metastatic esophageal NEC. Nonmetastatic esophageal NEC will benefit from primary tumor resection. Systematic treatment is recommended for metastatic esophageal NEC.

Different Characteristics in Gut Microbiome between Advanced Adenoma Patients and Colorectal Cancer Patients by Metagenomic Analysis.

The occurrence and development of colorectal cancer (CRC) and advanced adenoma (AA) are closely related to the gut microbiome, and AA has a high cancerization progression rate to CRC. Current studies have revealed that bacteriological analysis cannot identify CRC from AA. The objective was to explore microbial targets that could identify CRC and AA from a microecological perspective and to figure out the best way to identify CRC based on fecal microbes. The metagenomic sequencing data were used to describe the gut microbiome profile and analyze the differences between microbial abundance and microbial single nucleotide polymorphism (SNP) characteristics in AA and CRC patients. It was found that there were no significant differences in the diversity between the two groups. The abundance of bacteria (e.g., Firmicutes, Clostridia, and Blautia), fungi (Hypocreales), archaea (Methanosarcina, Methanoculleus, and Methanolacinia), and viruses (Alphacoronavirus, Sinsheimervirus, and Gammaretrovirus) differed between AA and CRC patients. Multiple machine-learning algorithms were used to establish prediction models, aiming to identify CRC and AA. The accuracy of the random forest (RF) model based on the gut microbiome was 86.54%. Nevertheless, the accuracy of SNP was 92.31% in identifying CRC from AA. In conclusion, using microbial SNP was the best method to identify CRC, it was superior to using the gut microbiome, and it could provide new targets for CRC screening. IMPORTANCE There are differences in characteristic microorganisms between AA and CRC. However, current studies have indicated that bacteriological analysis cannot identify CC from AA, and thus, we wondered if there were some other targets that could be used to identify CRC from AA in the gut microbiome. The differences of SNPs in the gut microbiota of intraindividuals were significantly smaller than those of interindividuals. In addition, compared with intestinal microbes, SNP was less affected by time with certain stability. It was discovered that microbial SNP was better than the gut microbiome for identifying CRC from AA. Therefore, screening characteristic microbial SNP could provide a new research direction for identifying CRC from AA.

Key Markers Involved in the Anticolon Cancer Response of CD8+ T Cells through the Regulation of Cholesterol Metabolism.

BACKGROUND: T cell-mediated antitumor immune response is the basis of colorectal cancer (CRC) immunotherapy. Cholesterol plays an important role in T cell signal transduction and function. Apolipoprotein E (APOE) plays a major role in cholesterol metabolism. OBJECTIVE: To screen and analyze key markers involved in the anticolon cancer response of CD8+ T cells through the regulation of cholesterol metabolism. METHODS: Based on the median cutoff of the expression value of APOE according to the data downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database, patients were grouped into low and high expression groups. Differences in clinical factors were assessed, and survival analysis was performed. Differentially expressed genes (DEGs) in the high and low expression groups were screened, followed by the analysis of differences in tumor-infiltrating immune cells and weighted gene coexpression network analysis results. The closely related genes to APOE were identified, followed by enrichment analysis, protein-protein interaction (PPI) network analysis, and differential expression analysis. Immunohistochemical staining (IHC) was used to detect the expression of CD8 in CRC tissues. RESULTS: There were significant differences in prognosis and pathologic_N between the APOE low and high expression groups. A total of 2,349 DEGs between the high and low expression groups were selected. A total of 967 genes were obtained from the blue and brown modules. The probability of distribution of CD8+ T cells differed significantly between the two groups, and 320 closely related DEGs of APOE were screened. Genes including the HLA gene family, B2M, IRF4, and STAT5A had a higher degree in the PPI network. GEO datasets verified the prognosis and the related DEGs of APOE. IHC staining verified the relationship between the distribution of CD8+ T cells and APOE expression. CONCLUSION: Genes including the HLA gene family, B2M, IRF4, and STAT5A might be the key genes involved in the anticolon cancer response of CD8+ T cells through the regulation of cholesterol metabolism.

ELK1 Enhances Pancreatic Cancer Progression Via LGMN and Correlates with Poor Prognosis.

Pancreatic cancer is one of the most lethal cancers and its prognosis is extremely poor. Clarification of molecular mechanisms and identification of prognostic biomarkers are urgently needed. Though we previously found that LGMN was involved in pancreatic carcinoma progression, the upstream regulation of LGMN remains unknown. We used reliable software to search for the potential transcription factors that may be related with LGMN transcription, we found that ELK1 could be a new regulator of LGMN transcription that binded directly to the LGMN promoter. Moreover, knocking down of ELK1 reduced pancreatic cancer cells proliferation, invasion and survival, while LGMN restored the malignancy of pancreatic cancer in vitro and in vivo. Overexpression of ELK1 further increased cancer cells proliferation, invasion and survival. Clinically, ELK1 and LGMN were positively correlated with clinical stage, degree of differentiation and Lymph node infiltration. ELK1 and LGMN were identified as independent prognostic factors for overall survival. The patients with low expression of ELK1/LGMN survived an average of 29.65 months, whereas those with high expression of ELK1/LGMN survived an average of 16.67 months. In conclusive, our results revealed a new mechanism by which ELK1 promoted the progression of pancreatic cancer via LGMN and conferred poor prognosis.

Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients.

Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients. Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses. Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis. Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients.