F11R RNA trinucleotide over-edited by ADAR in gastric and colorectal cancers: Cross-cohort validation, gene expression regulation, and diagnostic significance.

The F11 receptor (F11R) gene encoding junctional adhesion molecule A has been associated with gastric cancer (GC) and colorectal cancer (CRC), in which its role and regulation remain to be further elucidated. Recently F11R was also identified as a potential target of adenosine-to-inosine (A-to-I) mediated by the adenosine deaminases acting on RNA (ADARs). Herein, using RNA-Seq and experimental validation, our current study revealed an F11R RNA trinucleotide over-edited by ADAR, with its regulation of gene expression and clinical significance in four GC and three CRC cohorts. Our results found an over-edited AAA trinucleotide in an AluSg located in the F11R 3'-untranslated region (3'-UTR), which showed editing levels correlated with elevated ADAR expression across all GC and CRC cohorts in our study. Overexpression and knockdown of ADAR in GC and CRC cells, followed by RNA-Seq and Sanger sequencing, confirmed the ADAR-mediated F11R 3'-UTR trinucleotide editing, which potentially disrupted an RBM45 binding site identified by crosslinking immunoprecipitation sequencing (CLIP-seq) and regulated F11R expression in luciferase reporter assays. Moreover, the F11R trinucleotide editing showed promising predictive performance for diagnosing GC and CRC across GC and CRC cohorts. Our findings thus highlight both the potential biological and clinical significance of an ADAR-edited F11R trinucleotide in GC and CRC, providing new insights into its application as a novel diagnostic biomarker for both cancers.

ADAR-mediated RNA editing regulates PVR immune checkpoint in colorectal cancer.

Recent studies have revealed that tumor immunotherapy resistance is influenced by ADAR-mediated RNA editing, but its targets remain unelucidated. Our current study identified the poliovirus receptor (PVR) oncogene, which encodes an immune checkpoint in colorectal cancer (CRC), as a potential target for RNA editing. We performed transcriptome sequencing analysis and experimental validation in two Chinese CRC cohorts. PVR and ADAR expressions significantly increased in CRC tumors and showed positive correlations in both cohorts, coupled with upregulated PVR RNA editing in CRC tumors. Manipulation of ADAR expression by over-expression or knockdown substantially changed PVR expression and RNA editing in HTC116 CRC cells. Luciferase reporter and actinomycin D assays further revealed that RNA editing in PVR 3'-UTR could upregulate PVR RNA expression, probably by increasing the RNA stability. By increasing PVR expression, ADAR-mediate RNA editing might contribute to tumor- and immune-related gene functions and pathways in CRC. Moreover, a signature combining PVR RNA editing and expression showed promising predictive performance in CRC diagnosis in both Chinese CRC cohorts. Our findings thus highlight the importance of ADAR-mediated RNA editing in PVR up-regulation in CRC tumors and provide new insight into the application of PVR RNA editing as a novel diagnostic biomarker for CRC.

Can texture analysis of T2-weighted MRI be used to predict extrathyroidal extension in papillary thyroid carcinoma?

Determining the presence of extrathyroidal extension (ETE) is important for established of different surgical protocol and postoperative patient management in patients with papillary thyroid carcinoma (PTC). The correlation relationship between texture features from T2-weighted imaging (T2WI) and ETE has not been explored extensively. This study aimed to explore the value of T2-weighted magnetic resonance imaging - based whole tumor texture analysis in predict extrathyroidal extension with PTC. In this retrospectively study, 76 patients with pathologically proven PTC were recruited, who received surgical resection and underwent preoperative thyroid magnetic resonance imaging. Based on histo-pathologically findings, patients were classified into ETE and no ETE groups. ETE group was further divided into 2 subgroups (minimal ETE and extensive ETE). Whole-tumor texture analysis was independently performed by 2 radiologists on axial T2WI images. Nine histogram and gray-level co-occurrence matrix (GLCM) texture features were automatically extracted. Univariate and multivariate analysis were performed to determine risk factors associated with ETE. Predictive performance was evaluated by receiver operating characteristic (ROC) analysis. Interobserver agreement, confirmed by intraclass correlation coefficients (ICCs) ranging from 0.78 to 0.89, was excellent for texture analysis between 2 radiologists. T2WI image derived entropy, standard deviation, energy and correlation have significant difference between PTC with and without ETE (all P < .05). Among these, entropy showed the best diagnostic efficiency with the area under ROC curve of 0.837, diagnostic threshold of 5.86, diagnostic sensitivity and specificity of 81.5% and 75.6%, respectively. Additionally, the multivariate analysis revealed that high entropy was an independent risk factor of ETE (odds ratio, OR = 19.348; 95%CI, 4.578-81.760; P = .001). The findings indicate a significant association between texture features of the primary tumor based on T2WI and the presence of ETE in PTC. These results have the potential to help predict ETE preoperatively in patients with PTC, offering valuable insights for clinical decision-making.

Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients.

Purpose: We aim to investigate the clinical significance of dynamic changes in the lymphocyte-to-monocyte ratio (LMR) and neutrophil-lymphocyte ratio (NLR) in peripheral blood at different time points combined with CEA in the prediction of postoperative-recurrence-in-patients with colorectal cancer (CRC). Patients and Methods: This study collected 357 patients with stage I-III CRC between 2016 and April 2018. The dynamic changes from preoperative to postoperative LMR (p-LMR-p) and NLR (p-NLR-p) were analyzed using COX regression for multivariate analysis. Logistic regression was used to investigate whether the dynamic changes from post-treatment to pre-end of follow-up LMR (p-LMR-f) and NLR (p-NLR-f) were independent risk factors for CRC recurrence and to construct a predictive model. Internal validation using bootstrapping was performed to validate the discrimination ability of the model. The models' discriminative effect, calibration degree, and clinical utility were assessed. Results: In both the total cohort and the adjuvant therapy group, the dynamic changes of p-LMR-p (High-High vs Low-Low: p=0.006; HR:2.210, 95% CI: 1.256-3.890) were found to be independent prognostic factors for recurrence-free survival (RFS) in CRC patients. Additionally, logistic regression analysis revealed that N stage, CEA, LMR of pre-end of follow-up (f-LMR), and p-LMR-f were independent risk factors for CRC recurrence. In the total cohort, the p-LMR-f had an area under the curve (AUC) of 0.704, with a sensitivity of 64% and a specificity of 75.3%. By combining p-LMR-f with CEA, a predictive model was constructed, which showed an AUC of 0.913 (0.986-0.913) in the total cohort and an AUC of 0.924 (0.902-0.924) in the adjuvant therapy group during internal validation using bootstrapping. Conclusion: Dynamic changes in LMR can be used to predict the prognosis of CRC and serve as a biomarker for predicting CRC recurrence. Combined with CEA, it can improve the predictive performance for detecting CRC recurrence.

Gastric juice microbiota in pediatric chronic gastritis that clinically tested positive and negative for Helicobacter pylori.

Purpose: Helicobacter pylori (HP) infection is an identified risk factor for pediatric chronic gastritis (PCG), but its impact on gastric juice microbiota (GJM) remains to be further elucidated in PCG. This study aimed to analyze and compare the microbial communities and microbial interactive networks of GJM in PCG that clinically tested positive and negative for HP (HP+ and HP-, respectively). Methods: A total of 45 PCG patients aged from 6 to 16 years were recruited, including 20 HP+ and 25 HP- patients tested by culture and rapid urease test. Gastric juice samples were collected from these PCG patients and subjected to high-throughput amplicon sequencing and subsequent analysis of 16S rRNA genes. Results: While no significant change in alpha diversity, significant differences in beta diversity were observed between HP+ and HP- PCG. At the genus level, Streptococcus, Helicobacter, and Granulicatella were significantly enriched in HP+ PCG, whereas Campylobacter and Absconditabacteriales (SR1) were significantly enriched in HP- PCG. Network analysis showed that Streptococcus was the only genus positively correlated with Helicobacter (r = 0.497) in the GJM network of overall PCG. Moreover, compared to HP- PCG, HP+ PCG showed a reduction in microbial network connectivity in GJM. Netshift analysis identified driver microbes including Streptococcus and other four genera, which substantially contributed to the GJM network transition from HP- PCG to HP+ PCG. Furthermore, Predicted GJM function analysis indicated up-regulated pathways related to the metabolism of nucleotides, carbohydrates, and L-Lysine, the urea cycle, as well as endotoxin peptidoglycan biosynthesis and maturation in HP+ PCG. Conclusion: GJM in HP+ PCG exhibited dramatically altered beta diversity, taxonomic structure, and function, with reduced microbial network connectivity, which could be involved in the disease etiology.

L-Fucose increases the fucosylation of colorectal cancer cells via promoting the accumulation of serine.

Fucosylation, a kind of posttranslational modification, has been identified as a key regulator of health, with alterations in this process serving as an indicator of diseases such as colorectal cancer. L-Fucose, an essential substrate of fucosylation, was reported to possess anticancer potential and increase fucosylation. However, the association between its tumour-inhibitory effect and its ability to regulate fucosylation was not fully understood. Herein, we demonstrate that the simultaneous inhibitory effect of L-fucose on cancer cell growth and enhanced fucosylation occurred only in certain colorectal cancer cells (HCT-116 cells) but not in normal cells (HCoEpic cells), which may be related to the induction of pro-apoptotic fucosylated proteins by L-fucose in HCT-116 cells. RNA-seq analysis showed that upregulation of the transcription levels of serine biosynthesis genes (e.g. PSAT1) and decreased levels of genes involved in serine consumption with supplemental L-fucose were also unique to HCT-116 cells. Increased serine concentrations only in HCT-116 cells and increased α1,3/6-fucosylation in CRC cells induced by exogenous serine also verified that L-fucose enhanced fucosylation via promoting intracellular serine accumulation. Additionally, the knockdown of PSAT1 and serine-deficiency impaired fucosylation. Notably, PSAT1 knockdown weakened the inhibitory effect of L-fucose on cell proliferation and migration. Interestingly, simultaneous increased levels of α1,3/6-fucosylation and PSAT1 transcription were also identified in colorectal tumor tissues of CRC patients. Together, these results uncover a novel role of serine synthesis and PSAT1 in the regulation of fucosylation and provide insights into the potential application of L-fucose in CRC therapy.

Cytotoxic T-Cell Trafficking Chemokine Profiles Correlate With Defined Mucosal Microbial Communities in Colorectal Cancer.

The involvement of gut microbiota in T-cell trafficking into tumor tissue of colorectal cancer (CRC) remains to be further elucidated. The current study aimed to evaluate the expression of major cytotoxic T-cell trafficking chemokines (CTTCs) and chemokine-associated microbiota profiles in both tumor and adjacent normal tissues during CRC progression. We analyzed the expression of chemokine C-X-C motif ligands 9, 10, and 11 (CXCL9, CXCL10, and CXCL11), and C-C motif ligand 5 (CCL5), characterized gut mucosa-associated microbiota (MAM), and investigated their correlations in CRC patients. Our results showed that the expression of CXCL9, CXCL10, and CXCL11 was significantly higher in tumor than in adjacent normal tissues in 136 CRC patients. Notably, the high expression of CXCL9 in tumor tissues was associated with enhanced CD8+ T-cell infiltration and improved survival. Moreover, the MAM in tumor tissues showed reduction of microbial diversity and increase of oral bacteria. Microbial network analysis identified differences in microbial composition and structure between tumor and adjacent normal tissues. In addition, stronger associations between oral bacteria and other gut microbes were observed. Furthermore, the correlation analysis between the defined MAM and individual CTTCs showed that the CTTCs' correlated operational taxonomic units (OTUs) in tumor and adjacent normal tissues rarely overlap with each other. Notably, all the enriched OTUs were positively correlated with the CTTCs in either tumor or adjacent normal tissues. Our findings demonstrated stronger interactions between oral bacteria and gut microbes, and a shifted correlation pattern between MAM and major CTTCs in tumor tissues, underlining possible mechanisms of gut microbiota-host interaction in CRC.

A 21­gene Support Vector Machine classifier and a 10­gene risk score system constructed for patients with gastric cancer.

Gastric cancer (GC) ranks fifth in terms of incidence and third in terms of tumor mortality worldwide. The present study was designed to construct a Support Vector Machine (SVM) classifier and risk score system for GC. The GSE62254 (training set) and GSE26253 (validation set 2) datasets were downloaded from the Gene Expression Omnibus database. Furthermore, the gene expression profile of GC (validation set 1) was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) between recurrent and non­recurrent samples were determined using the limma package. The feature genes were selected using the Caret package, and an SVM classifier was built using the e1071 package. Using the penalized package, the optimal predictive genes for constructing a risk score system were screened. Finally, stratification analysis of clinical factors and pathway enrichment analysis were performed using Gene Set Enrichment Analysis. A total of 239 DEGs were identified in GSE62254, among which 114 DEGs were significantly associated with both recurrence­free survival and overall survival. Subsequently, 21 feature genes were screened from the 114 DEGs, and an SVM classifier was built. A risk score system for survival prediction was constructed, following the selection of 10 optimal genes, including A­kinase anchoring protein 12, angiopoietin­like protein 1, cysteine­rich sequence 1, myeloid/lymphoid or mixed­lineage leukemia, translocated to chromosome 11, neuron navigator 3, neurobeachin, nephroblastoma overexpressed, pleiotrophin, tumor suppressor candidate 3 and zinc finger and SCAN domain containing 18. The stratification analysis revealed that pathological stage was an independent prognostic clinical factor in the high­risk group. Additionally, eight significant pathways were associated with the 10­gene signature. The SVM classifier and risk score system may be applied for classifying and predicting the prognosis of patients with GC, respectively.

Loss of c-Cbl expression correlates with de-differentiation status and lymphatic metastasis in gastric cancer.

CONTEXT: C-Cbl is an important negative regulator of the cell signaling that acts as an adaptor protein and E3 ubiquitin ligase. The role of c-Cbl in development and regulation of human cancer has aroused intensive attention. AIMS: In this study, we aimed to assess the correlation between the expression of c-Cbl and clinicopathological parameters and explored the role of c-Cbl in the development and progression of GC. SETTINGS AND DESIGN: This is a Pilot study. METHODS AND MATERIALS: In total, 84 tissue samples including 44 gastric cancers (GC) and 40 matched adjacent normal tissues were collected after surgery. Then tissue microarray (TMA) and immunohistochemistry (IHC) technology were combined to detect the protein expression of c-Cbl. STATISTICAL ANALYSIS USED: Statistical analysis was performed using SPSS 22.0 (IBM Corporation, Armonk, NY, USA). RESULTS: We have studied the correlation between c-Cbl expression and clinicopathological parameters. Our study showed that c-Cbl has a low expression in 61.4% (27/44) of GC tissues, and the incidence of cases was significantly higher than that in adjacent normal tissues (P < 0.0001). In addition, the correlation between c-Cbl expression and gastric carcinoma subtype (P = 0.027), histological type (P = 0.033), Borrmann classification (P = 0.009), histological differentiation (P = 0.0005), lymph node metastasis (P = 0.007), and intravascular tumor thrombus (P = 0.036) has also been revealed. CONCLUSIONS: Our results show that c-Cbl is down-regulated in GC tissues compared with normal gastric tissue, which may play an important role in the development and progression of GC.

Biomarkers in Tumor Microenvironment? Upregulation of Fibroblast Activation Protein-α Correlates with Gastric Cancer Progression and Poor Prognosis.

Gastric cancer is the third leading cause of cancer-related mortality worldwide. Recent evidence points to importance of cross talk between cancer cells and the surrounding stroma on gastric cancer progression. Tumor microenvironment biomarkers thus represent a new opportunity for diagnostics innovation. Reactive stromal fibroblasts selectively express the fibroblast activation protein alpha (FAP-α), a homodimeric integral membrane gelatinase that belongs to the serine protease family. We report here that FAP-α expression is significantly elevated in gastric cancer samples by more than fivefold (p < 0.05), using transcriptome data from The Cancer Genome Atlas. Notably, the greatest FAP-α upregulation was observed in the poorly differentiated group (p < 0.001). Moreover, elevated FAP-α expression levels correlated with adverse clinical-pathological characteristics, such as diffuse histological subtype (p < 0.001), advanced pathological stage (p < 0.01) and poor survival. Functional annotation analysis demonstrated that FAP-α upregulation was associated with activation of biological processes implicated in tumor progression, including cell migration and angiogenesis pathways. These observations underscore the possible prognostic significance of FAP-α in gastric cancer and its potential as a novel biomarker for personalized medicine. We caution, however, that further multiomics, biochemical, and animal studies are necessary to ascertain the role of FAP-α as a causative and mechanistic biomarker. Based on pathway analyses, we hypothesize that gastric cancer patients exhibiting FAP-α upregulation might presumably benefit from antiangiogenic drugs in addition to standard therapeutic regimens. We call for future research focusing on the tumor microenvironment biomarkers in clinical oncology.

A subset of metastatic pancreatic ductal adenocarcinomas depends quantitatively on oncogenic Kras/Mek/Erk-induced hyperactive mTOR signalling.

OBJECTIVE: Oncogenic Kras-activated robust Mek/Erk signals phosphorylate to the tuberous sclerosis complex (Tsc) and deactivates mammalian target of rapamycin (mTOR) suppression in pancreatic ductal adenocarcinoma (PDAC); however, Mek and mTOR inhibitors alone have demonstrated minimal clinical antitumor activity. DESIGN: We generated transgenic mouse models in which mTOR was hyperactivated either through the Kras/Mek/Erk cascade, by loss of Pten or through Tsc1 haploinsufficiency. Primary cancer cells were isolated from mouse tumours. Oncogenic signalling was assessed in vitro and in vivo, with and without single or multiple targeted molecule inhibition. Transcriptional profiling was used to identify biomarkers predictive of the underlying pathway alterations and of therapeutic response. Results from the preclinical models were confirmed on human material. RESULTS: Reduction of Tsc1 function facilitated activation of Kras/Mek/Erk-mediated mTOR signalling, which promoted the development of metastatic PDACs. Single inhibition of mTOR or Mek elicited strong feedback activation of Erk or Akt, respectively. Only dual inhibition of Mek and PI3K reduced mTOR activity and effectively induced cancer cell apoptosis. Analysis of downstream targets demonstrated that oncogenic activity of the Mek/Erk/Tsc/mTOR axis relied on Aldh1a3 function. Moreover, in clinical PDAC samples, ALDH1A3 specifically labelled an aggressive subtype. CONCLUSIONS: These results advance our understanding of Mek/Erk-driven mTOR activation and its downstream targets in PDAC, and provide a mechanistic rationale for effective therapeutic matching for Aldh1a3-positive PDACs.

Pancreas-specific activation of mTOR and loss of p53 induce tumors reminiscent of acinar cell carcinoma.

BACKGROUND: Pancreatic acinar cell carcinoma (ACC) is a rare tumor entity with an unfavorable prognosis. Recent whole-exome sequencing identified p53 mutations in a subset of human ACC. Activation of the mammalian target of rapamycin (mTOR) pathway is associated with various pancreatic neoplasms. We thus aimed at analyzing whether activation of mTOR with a concomitant loss of p53 may initiate ACC. METHODS: We generated transgenic mouse models in which mTOR was hyperactivated through pancreas-specific, homozygous tuberous sclerosis 1 (Tsc1) deficiency, with or without deletion of p53 (Tsc1 (-/-) and Tsc1 (-/-) ; p53 (-/-) ). Activity of mTOR signaling was investigated using mouse tissues and isolated murine cell lines. Human ACC specimens were used to corroborate the findings from the transgenic mouse models. RESULTS: Hyperactive mTOR signaling in Tsc1 (-/-) mice was not oncogenic but rather induced a near-complete loss of the pancreatic acinar compartment. Acinar cells were lost as a result of apoptosis which was associated with p53 activation. Concomitantly, ductal cells were enriched. Ablation of p53 in Tsc1-deficient mice prevented acinar cell death but promoted formation of acinar cells with severe nuclear abnormalities. One out of seven Tsc1 (-/-) ; p53 (-/-) animals developed pancreatic tumors showing a distinctive tumor morphology, reminiscent of human ACC. Hyperactive mTOR signaling was also detected in a subset of human ACC. CONCLUSION: Hyperactive mTOR signaling combined with loss of p53 in mice induces tumors similar to human ACC.