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The liver is the most common organ for the formation of colorectal cancer metastasis. Non-invasive prognostication of colorectal cancer liver metastasis (CRLM) may better inform clinicians for decision-making. Contrast-enhanced computed tomography images of 180 CRLM cases were included in the final analyses. Radiomics features, including shape, first-order, wavelet, and texture, were extracted with Pyradiomics, followed by feature engineering by penalized Cox regression. Radiomics signatures were constructed for disease-free survival (DFS) by both elastic net (EN) and random survival forest (RSF) algorithms. The prognostic potential of the radiomics signatures was demonstrated by Kaplan-Meier curves and multivariate Cox regression. 11 radiomics features were selected for prognostic modelling for the EN algorithm, with 835 features for the RSF algorithm. Survival heatmap indicates a negative correlation between EN or RSF risk scores and DFS. Radiomics signature by EN algorithm successfully separates DFS of high-risk and low-risk cases in the training dataset (log-rank test: p < 0.01, hazard ratio: 1.45 (1.07–1.96), p < 0.01) and test dataset (hazard ratio: 1.89 (1.17–3.04), p < 0.05). RSF algorithm shows a better prognostic implication potential for DFS in the training dataset (log-rank test: p < 0.001, hazard ratio: 2.54 (1.80–3.61), p < 0.0001) and test dataset (log-rank test: p < 0.05, hazard ratio: 1.84 (1.15–2.96), p < 0.05). Radiomics features have the potential for the prediction of DFS in CRLM cases.

BackgroundPlatycodin D (PD) has been reported to treat metabolic diseases, including non-alcoholic fatty liver disease. In addition, platycodin D has been reported to activate intestinal 5'AMP-activated protein kinase (AMPK) phosphorylation levels, thereby reducing lipid absorption. Therefore, the aim of this study is to explore whether PD activation of intestinal AMPK and reduced lipid absorption can improve non-alcoholic fatty liver disease.MethodsClean-grade male C57/BL mice were fed a high-fat diet (HFD) (containing 60% calories) for 16 weeks, and oral PD (10 mg/kg/day) was administered at the same time. The liver and intestines were the collected, and the intestines were tested. The expressions of lipid absorption genes (CD36, NPC1L1, and ApoB), the serum total triglyceride (TG) and total cholesterol (TC) levels in the intestines and livers, the fecal free fatty acid (FFA) levels, and the expression of AMPK phosphorylated proteins in the intestines were examined using Western blot analyses. The lipid distribution in the livers, intestines, and fat was detected using Oil Red O and hematoxylin and eosin (H&E) staining. A colon cancer cell line (Caco2) was used to confirm the effect of PD on the cellular lipid uptake in vitro. In addition, serum inflammatory factors and liver enzymes were measured to clarify the impact of PD on the circulation of metabolic syndrome. Leptin-deficient mice (OB) were then used to further explore the improvement of PD on body weight and blood lipids.ResultsPD had a very significant therapeutic or preventive effect on metabolic syndrome and fatty liver induced by a high-fat diet. PD improved body weight, insulin sensitivity, and glucose tolerance in mice fed a high-fat diet and also prevented non-alcoholic fatty liver disease, reduced blood lipid levels, and increased fecal lipid excretion. In addition, PD reduced lipid absorption by activating the intestinal AMPK protein, which may have involved the inhibition of the gene expression levels of intestinal lipid absorption genes (CD36, NPC1L1, and ApoB). The combined effect of these factors improved hepatic lipid accumulation and lipid accumulation in adipose tissue. It was further found that PD also improved the body weights and blood lipid levels of leptin-deficient mice (OB) mice.ConclusionPD had a very strong therapeutic effect on mice under a high-fat diet. PD reduced high-fat diet-induced obesity and non-alcoholic fatty liver disease by inhibiting intestinal fat absorption.

Cell death is ubiquitous during development and throughout life and is a genetically determined active and ordered process that plays a crucial role in regulating homeostasis. Cell death includes regulated cell death and non-programmed cell death, and the common types of regulatory cell death are necrosis, apoptosis, necroptosis, autophagy, ferroptosis, and pyroptosis. Apoptosis, Necrosis and necroptosis are more common than autophagy, ferroptosis and pyroptosis among cell death. Non-coding RNAs are regulatory RNA molecules that do not encode proteins and include mainly microRNAs, long non-coding RNAs, and circular RNAs. Non-coding RNAs can act as oncogenes and tumor suppressor genes, with significant effects on tumor occurrence and development, and they can also regulate tumor cell autophagy, ferroptosis, and pyroptosis at the transcriptional or post-transcriptional level. This paper reviews the recent research progress on the effects of the non-coding RNAs involved in autophagy, ferroptosis, and pyroptosis on tumorigenesis, tumor development, and treatment, and looks forward to the future direction of this field, which will help to elucidate the molecular mechanisms of tumorigenesis and tumor development, as well as provide a new vision for the treatment of tumors.

Objectives To identify the most significantly differentially expressed circular RNAs (circRNAs) in colorectal cancer (CRC) tissues in terms of their expression levels and circularity, and to analyze the relationship between their expression levels and the clinical characteristics of patients. Methods circRNA RNA-seq technology was used to screen differentially expressed circRNAs in CRC. Sanger sequencing was used to identify circRNA back-splice junction sites. The relative expression levels of hsa_circ_0003761 (circMSH3) in CRC tissues and cell lines were detected by quantitative real-time fluorescence PCR technology. An RNA-protein pull-down assay was used to detect protein binding to circRNAs. Dual-luciferase reporter gene vectors were constructed to verify that circRNAs bind to microRNAs. Results Four hundred twenty circRNAs were found to be upregulated, and 616 circRNAs were downregulated. circMSH3 was derived from the MutS homolog 3 (MSH3) gene and was formed by a loop of exons 9, 10, 11, and 12. In 110 pairs of CRC and adjacent tissues, circMSH3 expression was 4.487-fold higher in CRC tissues. circMSH3 was also highly expressed in the HT-29 and LOVO CRC cell lines. The expression level of circMSH3 was associated with distant metastasis in CRC patients (P = 0.043); the area under the curve (AUC) of circMSH3 for CRC diagnosis was 0.75, with a sensitivity and specificity of 70.9% and 66.4%, respectively. circMSH3 could bind to a variety of proteins, mainly those involved in RNA transcription, splicing, cell cycle, and cell junctions. Furthermore, circMSH3 could bind to miR-1276, miR-942-5p, and miR-409-3p. Conclusion circMSH3 is a potential biomarker for the diagnosis of CRC and affects the distant metastasis of CRC. Multiple RNA-binding protein binds to circMSH3, and circMSH3 binds to miR-1276, miR-942-5p, and miR-409-3p, thereby affecting the expression of circMSH3.

Abstract Background Colon cancer (CRC) is the second leading cause of cancer-related death, and its 5-year survival rate is very low. Homologous recombination repair (HRR) is deficient in most colon cancer. Some long non-coding RNAs (lncRNAs) participate in tumorigenesis of colon cancer through the HRR pathway. We aim to establish a prognostic model based on the HRR-related lncRNAs, expecting to provide a new strategy for precision treatment development in colon cancer. Methods Pearson’s correlation was used to identify the HRR-related prognostic lncRNAs in the TCGA-COAD cohort. The TCGA-COAD cohort was randomized into the training set and the testing set. LASSO Cox regression was used to establish the model which was analyzed in the training set and validated in the testing set and the entire TCGA-COAD cohort. Finally, we explored the potential biological function of our model. Results A prognostic model was established based on nineteen HRR-related lncRNAs in the training set. COAD patients were scored by the uniform formula and divided into high-risk and low-risk groups based on the median risk score. Patients with high-risk scores indicated poor prognosis in the training set, and the result was confirmed in the testing set and the entire TCGA-COAD cohort (all p < 0.01). Multivariable analysis suggested that our model was an independent factor for overall survival in COAD. The area under the curve (AUC) and C-index indicated that our model had better predictive efficiency than other indicators in the TCGA-COAD cohort. Functional enrichment analysis suggested that our model was associated with the MAPK pathway in COAD. Besides, our model was positively correlated with the HRD scores. Conclusion A new prognostic model was established based on nineteen HRR-related lncRNAs which had excellent predictive efficiency on the prognosis of COAD. This prognostic model may provide a new strategy for prognostic prediction of COAD patients.

Colorectal carcinoma (CRC) is the second most frequent cancer worldwide. MiR-491-3p, a tumor-suppressive microRNA (miRNA, miR), has been revealed to be abnormally expressed in CRC tissues. Meanwhile, up-regulated ubiquitous mitochondrial creatine kinase (uMtCK) contributes to CRC cell proliferation. Here we aim to explore whether aberrant miR-491-3p expression promotes CRC progression through regulating uMtCK. To this end, miR-491-3p and uMtCK levels were assessed in CRC tissues using quantitative real-time PCR (qRT-PCR). The biological roles of miR-491-3p and uMtCK in regulating CRC growth were evaluated using colony formation assay and mouse Xenograft tumour model. We found that miR-491-3p expression was decreased in CRC tissues compared with matched para-cancerous tissues, whereas uMtCK expression was increased. Functionally, miR-491-3p overexpression repressed SW480 cell growth, whereas miR-491-3p depletion accelerated SW620 cell proliferation and growth. Inversely, uMtCK positively regulated CRC cell proliferation. Mechanistically, miR-491-3p post-transcriptionally downregulated uMtCK expression by binding to 3’-UTR of uMtCK. Consequently, restoring uMtCK expression markedly eliminated the role of miR-491-3p in suppressing CRC growth. Collectively, miR-491-3p functions as a tumour suppressor gene by repressing uMtCK, and may be a potential target for CRC treatment.

The current study aimed to construct a prognostic predictive model based on tumor microenvironment. CIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration (ICI) landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. ICI scores of each patient were determined by principal component analysis. Patients were divided into high and low ICI score groups. Survival, gene expression, and somatic mutation of the two groups were compared. We found that patients with no lymph node invasion, no metastasis, T1–2 disease, and stage I–II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and Wnt signaling pathway were enriched in the high ICI score group. Immune-checkpoint and immune-activity associated genes were decreased in high ICI score patients. Patients in the high ICI score group had better survival. Prognostic value of ICI score was independent of tumor mutational burden (TMB). The ICI score model constructed in the current study may serve as an independent prognostic biomarker in colon cancer.

Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information. It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results. Spatial omics technologies include spatial transcriptomics, spatial proteomics, spatial metabolomics, and other technologies, the most widely used of which are spatial transcriptomics and spatial proteomics. The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist, including the surrounding blood vessels, immune cells, fibroblasts, bone marrow-derived inflammatory cells, various signaling molecules, and extracellular matrix. A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment, which can reveal problems that conventional research techniques cannot, potentially leading to the development of novel therapeutic agents for cancer. This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment. [ABSTRACT FROM AUTHOR]