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BACKGROUND: Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear. METHODS: We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated. RESULTS: We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated. CONCLUSION: Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.
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Neoplasias Colorretais , Microambiente Tumoral , Neoplasias Colorretais/patologia , Humanos , Ligantes , Linfócitos do Interstício Tumoral/metabolismo , Prognóstico , Microambiente Tumoral/genéticaRESUMO
Droplet manipulation with high efficiency, high flexibility, and programmability, is essential for various applications in biomedical sciences and engineering. Bioinspired liquid-infused slippery surfaces (LIS), with exceptional interfacial properties, have led to expanding research for droplet manipulation. In this review, an overview of actuation principles is presented to illustrate how materials or systems can be designed for droplet manipulation on LIS. Recent progress on new manipulation methods on LIS is also summarized and their prospective applications in anti-biofouling and pathogen control, biosensing, and the development of digital microfluidics are presented. Finally, an outlook is made on the key challenges and opportunities for droplet manipulation on LIS.
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Adsorption is an important technology to deal with volatile organic compounds (VOCs), and biochar has attracted much attention as a new type of adsorbent for VOCs. In this study, rice husk, corn stover and pine wood sawdust biochars from different pyrolysis temperatures (300 °C, 500 °C and 700 °C) were synthesized and treated by ball milling. The pristine and ball-milled biochars were used as adsorbents for acetone and toluene removal. Results showed that wood biochar had higher adsorption capacity for VOCs. After ball milling, the BET specific surface area and the oxygen functional group content of biochars increased. With these changes, all the ball-milled biochars showed higher adsorption rate than the pristine biochars. The ball-milled biochars under pyrolysis temperature of 300 °C showed the best adsorption performance for acetone (304 mg g-1), which was 1.7-fold greater than that of pristine biochar. Increasing the surface area by ball milling is conducive to the diffusion of hydrophobic VOCs molecules such as toluene to the adsorption sites in the biochar. However, for hydrophilic VOCs such as acetone, higher oxygen functional groups were the main reason for the enhanced adsorption by ball milling. Therefore, ball-milled biochar can be used as a potential adsorbent material in VOCs treatment.
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Compostos Orgânicos Voláteis , Adsorção , Carvão Vegetal , PiróliseRESUMO
BACKGROUND: Pyroptosis has been confirmed as a type of inflammatory programmed cell death in recent years. However, the prognostic role of pyroptosis in colon cancer (CC) remains unclear. METHODS: Dataset TCGA-COAD which came from the TCGA portal was taken as the training cohort. GSE17538 from the GEO database was treated as validation cohorts. Differential expression genes (DEGs) between normal and tumor tissues were confirmed. Patients were classified into two subgroups according to the expression characteristics of pyroptosis-related DEGs. The LASSO regression analysis was used to build the best prognostic signature, and its reliability was validated using Kaplan-Meier, ROC, PCA, and t-SNE analyses. And a nomogram based on the multivariate Cox analysis was developed. The enrichment analysis was performed in the GO and KEGG to investigate the potential mechanism. In addition, we explored the difference in the abundance of infiltrating immune cells and immune microenvironment between high- and low-risk groups. And we also predicted the association of common immune checkpoints with risk scores. Finally, we verified the expression of the pyroptosis-related hub gene at the protein level by immunohistochemistry. RESULTS: A total of 23 pyroptosis-related DEGs were identified in the TCGA cohort. Patients were classified into two molecular clusters (MC) based on DEGs. Kaplan-Meier survival analysis indicated that patients with MC1 represented significantly poorer OS than patients with MC2. 13 overall survival- (OS-) related DEGs in MCs were used to construct the prognostic signature. Patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. Combined with the clinical features, the risk score was found to be an independent prognostic factor of CC patients. The above results are verified in the external dataset GSE17538. A nomogram was established and showed excellent performance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the varied prognostic performance between high- and low-risk groups may be related to the immune response mediated by local inflammation. Further analysis showed that the high-risk group has stronger immune cell infiltration and lower tumor purity than the low-risk group. Through the correlation between risk score and immune checkpoint expression, T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) was predicted as a potential therapeutic target for the high-risk group. CONCLUSION: The 13-gene signature was associated with OS, immune cells, tumor purity, and immune checkpoints in CC patients, and it could provide the basis for immunotherapy and predicting prognosis and help clinicians make decisions for individualized treatment.
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PURPOSE: To evaluate the impact of the log odds of positive lymph nodes (LODDS) on cancer-specific survival (CSS) in colon mucinous adenocarcinoma (MAC) patients, compared with pN stage and the lymph nodes ratio (LNR). METHODS: A total of 10,182 colon MAC patients from the Surveillance, Epidemiology, and End Results database were divided into the training group. The external validation group included 153 patients from Fujian Medical University Union Hospital. The Cox regression method was used to identify prognostic risk factors. Nomograms were evaluated by Harrell's concordance index (C-index) and calibration curves. Recursive partitioning analysis (RPA) was used to develop a novel staging system. RESULTS: Time-dependent receiver operating characteristic curves (ROC) to predict CSS showed the areas under the ROC curve of LODDS were always higher than pN stage and LNR. LNR and LODDS classifications can well distinguish the prognosis of patients with the same pN stage. Cox analyses indicated that age, tumor size, pT stage, pN stage, LNR, and LODDS were independent predictors of CSS (p < 0.05). Based on three lymph nodes classifications, we constructed three prognostic nomograms models for CSS. The C-index of the pN, LNR, and LODDS classification nomograms were 0.746 (95% confidence interval [95% CI]: 0.736-0.756), 0.750 (95% CI: 0.740-0.760), and 0.758 (95% CI: 0.748-0.768), respectively. In external validation, we observed the C-index of LODDS classification nomograms was 0.787 (95% CI: 0.648-0.926). RPA stage, including four stages, was constructed successfully based on pT stage and LNR or LODDS, respectively. The 3-, 5-, and 8-year areas under the ROC curve of LNR-RPA stage and LODDS-RPA stage were superior to tumor-node-metastasis stage. CONCLUSION: LODDS to be a better prognostic factor of CSS for colon MAC patients than pN stage and LNR. A nomogram and RPA stage base on LODDS can provide accurate information for personalized cancer treatment.
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Adenocarcinoma Mucinoso/patologia , Neoplasias do Colo/patologia , Metástase Linfática/patologia , Idoso , China , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Prognóstico , Fatores de RiscoRESUMO
Ferroptosis is a form of iron-dependent programmed cell death. Regulation of ferroptosis in tumor cells is a novel treatment modality. The present study aimed to investigate ferroptosis-related long non-coding RNAs (lncRNAs) and construct a prognostic model for colon adenocarcinoma (COAD). RNA- sequencing data and ferroptosis-related genes were obtained from The Cancer Genome Atlas database and FerrDb database. COAD patients were randomly assigned to training- and validation groups. The Least Absolute Shrinkage and Selection Operator regression and Cox regression model were used to determine and develop a predictive model. The model was corroborated using the validation group and the entire group. In total, 259 ferroptosis-related genes and 905 ferroptosis-related LncRNAs were obtained. Cox model revealed and constructed seven ferroptosis-related LncRNAs signature (LINC01503, AC004687.1, AC010973.2, AP001189.3, ARRDC1-AS1, OIP5-AS1, and NCK1-DT). Patients were assigned into two groups according to the median risk score. Kaplan-Meier survival curves showed that overall survival between high- and low-risk groups was statistically significant (P<0.01). Cox multivariate analysis seven ferroptosis-related LncRNAs signature was an independent risk factor for COAD outcomes (P<0.05). The relationship between seven ferroptosis-related LncRNAs and clinicopathological features was also examined. The principal component analysis showed a difference between high- and low-risk groups intuitively. With the aid of gene set enrichment analysis, the underlying mechanisms of seven ferroptosis-related LncRNAs were uncovered, including the MAPK signaling pathway, mTOR signaling pathway, and glutathione metabolism pathway. Finally, we established and validated seven ferroptosis-related lncRNAs signature for COAD patients to predict survival. These results may provide meaningful targets for future study.