S100A16 is a potential target for reshaping the tumor microenvironment in the hypoxic context of liver cancer.

BACKGROUND: The research on the S100 family has garnered significant attention; however, there remains a dearth of understanding regarding the precise role of S100A16 in the tumor microenvironment of liver cancer. METHOD: Comprehensive analysis was conducted on the expression of S100A16 in tumor tissues and its correlation with hypoxia genes. Furthermore, an investigation was carried out to examine the association between S100A16 and infiltration of immune cells in tumors as well as immunotherapy. Relevant findings were derived from the analysis of single cell sequencing data, focusing on the involvement of S100A16 in both cellular differentiation and intercellular communication. Finally, we validated the expression of S100A16 in liver cancer by Wuhan cohort and multiplexed immunofluorescence to investigate the correlation between S100A16 and hypoxia. RESULT: Tumor tissues displayed a notable increase in the expression of S100A16. A significant correlation was observed between S100A16 and genes associated with hypoxic genes. Examination of immune cell infiltration revealed an inverse association between T cell infiltration and the level of S100A16 expression. The high expression group of S100A16 exhibited a decrease in the expression of genes related to immune cell function. Single-cell sequencing data analysis revealed that non-immune cells predominantly expressed S100A16, and its expression levels increased along with the trajectory of cell differentiation. Additionally, there were significant variations observed in hypoxia genes as cells underwent differentiation. Cellular communication identified non-immune cells interacting with immune cells through multiple signaling pathways. The Wuhan cohort verified that S100A16 expression was increased in liver cancer. The expression of S100A16 and HIF was simultaneously elevated in endothelial cells. CONCLUSION: The strong association between S100A16 and immune cell infiltration is observed in the context of hypoxia, indicating its regulatory role in shaping the hypoxic tumor microenvironment in liver cancer.

B-Myb deficiency boosts bortezomib-induced immunogenic cell death in colorectal cancer.

B-Myb has received considerable attention for its critical tumorigenic function of supporting DNA repair. However, its modulatory effects on chemotherapy and immunotherapy have rarely been reported in colorectal cancer. Bortezomib (BTZ) is a novel compound with chemotherapeutic and immunotherapeutic effects, but it fails to work in colorectal cancer with high B-Myb expression. The present study was designed to investigate whether B-Myb deletion in colorectal cancer could potentiate the immune efficacy of BTZ against colorectal cancer and to clarify the underlying mechanism. Stable B-Myb knockdown was induced in colorectal cancer cells, which increased apoptosis of the cancer cells relative to the control group in vitro and in vivo. We found that BTZ exhibited more favourable efficacy in B-Myb-defective colorectal cancer cells and tumor-bearing mice. BTZ treatment led to differential expression of genes enriched in the p53 signaling pathway promoted more powerful downstream DNA damage, and arrested cell cycle in B-Myb-defective colorectal cancer. In contrast, recovery of B-Myb in B-Myb-defective colorectal cancer cells abated BTZ-related DNA damage, cell cycle arrest, and anticancer efficacy. Moreover, BTZ promoted DNA damage-associated enhancement of immunogenicity, as indicated by potentiated expression of HMGB1 and HSP90 in B-Myb-defective cells, thereby driving M1 polarization of macrophages. Collectively, B-Myb deletion in colorectal cancer facilitates the immunogenic death of cancer cells, thereby further promoting the immune efficacy of BTZ by amplifying DNA damage. The present work provides an effective molecular target for colorectal cancer immunotherapy with BTZ.

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq data reveals dynamic changes in tumor-associated neutrophils in the tumor microenvironment of hepatocellular carcinoma and leads to the establishment of a neutrophil-related prognostic model.

BACKGROUND: Analysis of hepatocellular carcinoma (HCC) single-cell sequencing data was conducted to explore the role of tumor-associated neutrophils in the tumor microenvironment. METHODS: Analysis of single-cell sequencing data from 12 HCC tumor cores and five HCC paracancerous tissues identified cellular subpopulations and cellular marker genes. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to establish and validate prognostic models. xCELL, TIMER, QUANTISEQ, CIBERSORT, and CIBERSORT-abs analyses were performed to explore immune cell infiltration. Finally, the pattern of tumor-associated neutrophil roles in tumor microenvironmental components was explored. RESULTS: A total of 271 marker genes for tumor-associated neutrophils were identified based on single-cell sequencing data. Prognostic models incorporating eight genes were established based on TCGA data. Immune cell infiltration differed between the high- and low-risk groups. The low-risk group benefited more from immunotherapy. Single-cell analysis indicated that tumor-associated neutrophils were able to influence macrophage, NK cell, and T-cell functions through the IL16, IFN-II, and SPP1 signaling pathways. CONCLUSION: Tumor-associated neutrophils regulate immune functions by influencing macrophages and NK cells. Models incorporating tumor-associated neutrophil-related genes can be used to predict patient prognosis and immunotherapy responses.

High intramuscular adipose tissue content associated with prognosis and postoperative complications of cancers.

Sarcopenia has been considered an adverse prognostic factor in cancer patients. Intramuscular adipose tissue content, as a new marker of sarcopenia, can effectively reflect skeletal muscle quality. The aim of this study was performed to evaluate the association between high intramuscular adipose tissue content (IMAC) and survival outcomes and postoperative complications in cancer patients. Specific databases, including the Web of Science, Embase and Web of Science, were systematically searched to identify relevant articles evaluating the prognostic value of IMAC in cancer patients. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were utilized for comprehensive analysis. All data analyses were performed using STATA 12.0 software. A total of 25 studies from 24 articles including 5663 patients were enrolled in the study. Meta-analysis showed that high IMAC was associated with unfavourable overall survival (OS) (HR: 2.21, 95% CI: 1.70-2.86, P < 0.001), relapse-free survival (RFS) (HR: 1.51, 95% CI: 1.30-1.75, P < 0.001) and disease-specific survival (DSS) (HR: 1.64, 95% CI: 1.19-2.28, P = 0.003). Subgroup analysis revealed that high IMAC remained an adverse prognostic factor when stratified by different country, treatment methods, cancer type or analysis type. High IMAC had better predictive value for gallbladder carcinoma (GBC) (HR: 3.50, 95% CI: 1.98-6.17, P < 0.001), hepatocellular carcinoma (HCC) (HR: 1.84, 95% CI: 1.45-2.33, P < 0.001), pancreatic cancer (PC) (HR: 2.11, 95% CI: 1.67-2.66, P < 0.001) and colorectal cancer (CRC) (HR: 2.54, 95% CI: 1.27-5.10, P = 0.009). High IMAC was also identified as a significant risk factor for postoperative complications (OR: 2.05, 95% CI: 1.22-3.46, P = 0.007). High IMAC was associated with an adverse prognosis and an increased risk of postoperative complications in cancer patients. IMAC may be a good indicator of sarcopenia.

Tumor-associated endothelial cell prognostic risk model and tumor immune environment modulation in liver cancer based on single-cell and bulk RNA sequencing: Experimental verification.

BACKGROUND: To build a prognostic and immunotherapeutic response prediction model for liver cancer based on marker genes of tumor-associated endothelial cell (TEC). METHOD: Single cell sequencing data from Gene Expression Omnibus (GEO) liver cancer patients were utilized to identify TEC subpopulations. Models were built from transcriptomic and clinical data of TCGA liver cancer patients. The GSE76427 and ICGC databases were used as independent validation sets. Time-dependent receiver operating characteristic (ROC) curves and Kaplan-Meier curves were used to verify the ability of the model to predict survival. XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA were applied to evaluate tumor immune cell infiltration. The TIDE score was used to predict the effect of immunotherapy. Immune blockade checkpoint gene, tumor mutational load and GSVA enrichment analyses were further explored. The expression levels of candidate genes were measured and validated by real-time PCR between liver cancer tissues and adjacent nontumor liver tissues. RESULTS: Eighty-seven genes were identified as marker genes for TECs. IGFBP3, RHOC, S100A16, FSCN1, and CLEC3B were included in the constructed prognostic model. Time-dependent ROC curve values were higher than 0.700 in both the model and validation groups. The low risk group exhibited high immune cell infiltration and function than the higher risk group. The TIDE score indicated that the low-risk group benefited more from immunotherapy than the high-risk group. The risk score and multiple immune blockade checkpoint genes and immune-related pathways were strongly correlated. CONCLUSION: Novel signatures of TEC marker genes showed a powerful ability to predict prognosis and immunotherapy response in patients with liver cancer.

MLF2 Negatively Regulates P53 and Promotes Colorectal Carcinogenesis.

Inactivation of the p53 pathway is linked to a variety of human cancers. As a critical component of the p53 pathway, ubiquitin-specific protease 7 (USP7) acts as a deubiquitinase for both p53 and its ubiquitin E3 ligase mouse double minute 2 homolog. Here, myeloid leukemia factor 2 (MLF2) is reported as a new negative regulator of p53. MLF2 interacts with both p53 and USP7. Via these interactions, MLF2 inhibits the binding of USP7 to p53 and antagonizes USP7-mediated deubiquitination of p53, thereby leading to p53 destabilization. Functionally, MLF2 plays an oncogenic role in colorectal cancer, at least partially, via the negative regulation of p53. Clinically, MLF2 is elevated in colorectal cancer and its high expression is associated with poor prognosis in patients with colorectal cancer. In wild-type-p53-containing colorectal cancer, MLF2 and p53 expressions are inversely correlated. These findings establish MLF2 as an important suppressor of p53 function. The study also reveals a critical role for the MLF2-p53 axis in promoting colorectal carcinogenesis.

Analysis of M2 macrophage-associated risk score signature in pancreatic cancer TME landscape and immunotherapy.

Background: M2 macrophages perform an influential role in the progression of pancreatic cancer. This study is dedicated to explore the value of M2 macrophage-related genes in the treatment and prognosis of pancreatic cancer. Methods: RNA-Seq and clinical information were downloaded from TCGA, GEO and ICGC databases. The pancreatic cancer tumour microenvironment was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to detect M2 macrophage-associated gene modules. Univariate Cox regression, Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression were applied to develop the prognostic model. The modelling and validation cohorts were divided into high-risk and low-risk groups according to the median risk score. The nomogram predicting survival was constructed based on risk scores. Correlations between risk scores and tumour mutational load, clinical variables, immune checkpoint blockade, and immune cells were further explored. Finally, potential associations between different risk models and chemotherapeutic agent efficacy were predicted. Results: The intersection of the WGCNA results from the TCGA and GEO data screened for 317 M2 macrophage-associated genes. Nine genes were identified by multivariate COX regression analysis and applied to the construction of risk models. The results of GSEA analysis revealed that most of these genes were related to signaling, cytokine receptor interaction and immunodeficiency pathways. The high and low risk groups were closely associated with tumour mutational burden, immune checkpoint blockade related genes, and immune cells. The maximum inhibitory concentrations of metformin, paclitaxel, and rufatinib lapatinib were significantly differences on the two risk groups. Conclusion: WGCNA-based analysis of M2 macrophage-associated genes can help predict the prognosis of pancreatic cancer patients and may provide new options for immunotherapy of pancreatic cancer.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on NK cell marker genes to predict prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Prognostic modeling of NK cell marker genes in patients with hepatocellular carcinoma based on single cell sequencing and transcriptome data analysis. METHODS: Marker genes of NK cells were analyzed according to single cell sequencing data of hepatocellular carcinoma. Univariate Cox regression, lasso regression analysis, and multivariate Cox regression were performed to estimate the prognostic value of NK cell marker genes. TCGA, GEO and ICGC transcriptomic data were applied to build and validate the model. Patients were divided into high and low risk groups based on the median risk score. XCELL, timer, quantitative sequences, MCP counter, EPIC, CIBERSORT and CIBERSORT-abs were performed to explore the relationship between risk score and tumor microenvironment in hepatocellular carcinoma. Finally the sensitivity of the model to chemotherapeutic agents was predicted. RESULTS: Single-cell sequencing identified 207 marker genes for NK cells in hepatocellular carcinoma. Enrichment analysis suggested that NK cell marker genes were mainly involved in cellular immune function. Eight genes were selected for prognostic modeling after multifactorial COX regression analysis. The model was validated in GEO and ICGC data. Immune cell infiltration and function were higher in the low-risk group than in the high-risk group. The low-risk group was more suitable for ICI and PD-1 therapy. Half-maximal inhibitory concentrations of Sorafenib, Lapatinib, Dabrafenib, and Axitinib were significantly different on the two risk groups. CONCLUSION: A new signature of hepatocyte NK cell marker genes possesses a powerful ability to predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma.

Construction and validation of a nomogram for patients with multiple hepatocellular carcinoma: A SEER-based study.

BACKGROUND: American Joint Committee on Cancer (AJCC)-TNM system doesn't accurately predict prognosis. Our study was designed to identify prognostic factors in patients with multiple hepatocellular carcinoma (MHCC), establish and validate a nomogram model to predict the risk and overall survival (OS) of MHCC patients. METHODS: We selected eligible HCC patients from the Surveillance, Epidemiology, and End Results (SEER) database, used univariate and multivariate COX regression to determine prognostic factors in MHCC patients, and used these factors to build a nomogram. The accuracy of the prediction was evaluated using the C-index, receiver operating characteristic (ROC) and calibration curve. Decision curve analysis (DCA), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to compare the nomogram with AJCC-TNM staging system. Finally, the prognosis of different risks was analyzed using Kaplan-Meier (K-M) method. RESULTS: 4950 eligible patients with MHCC were enrolled in our study and randomly assigned to the training cohort and test cohort in a 7:3 ratio. After COX regression analysis, age, sex, histological grade, AJCC-TNM stage, tumor size, alpha-fetoprotein (AFP), surgery, radiotherapy and chemotherapy in total 9 factors could be used to independently determine OS of patients. the above factors were used to construct a nomogram, and the consistency C-index was 0.775. C-index, DCA, NRI and IDI showed that our nomogram was superior to the AJCC-TNM staging system. K-M plots for OS were performed using the log-rank test, the P-value of which was <0.001. CONCLUSIONS: The practical nomogram can provide more accurate prognostic prediction for multiple hepatocellular carcinoma patients.

Matrine alleviates oxidative stress and ferroptosis in severe acute pancreatitis-induced acute lung injury by activating the UCP2/SIRT3/PGC1α pathway.

Acute lung injury (ALI) is one of the most serious complications of severe acute pancreatitis (SAP). Matrine is well known for its powerful antioxidant and antiapoptotic properties, although its specific mechanism of action in SAP-ALI is unknown. In this study, we examined the effects of matrine on SAP-associated ALIand the specific signaling pathways implicated in SAP-induced ALI, such as oxidative stress, the UCP2-SIRT3-PGC1α pathway, and ferroptosis. The administration of caerulein and lipopolysaccharide (LPS) to UCP2-knockout (UCP2-/-) and wild-type (WT) mice that were pretreated with matrine resulted in pancreatic and lung injury. Changes in reactive oxygen species (ROS) levels, inflammation, and ferroptosis in BEAS-2B and MLE-12 cells were measured following knockdown or overexpression and LPS treatment. Matrine inhibited excessive ferroptosis and ROS production by activating the UCP2/SIRT3/PGC1α pathway while reducing histological damage, edema, myeloperoxidase activity and proinflammatory cytokine expression in the lung. UCP2 knockout decreased the anti-inflammatory properties of matrine and reduced the therapeutic effects of matrine on ROS accumulation and ferroptosis hyperactivation. LPS-induced ROS production and ferroptosis activation in BEAS-2B cells and MLE-12 cells were further enhanced by knockdown of UCP2, but this effect was rescued by UCP2 overexpression. This study demonstrated that matrine reduced inflammation, oxidative stress, and excessive ferroptosis in lung tissue during SAP by activating the UCP2/SIRT3/PGC1α pathway, demonstrating its therapeutic potential in SAP-ALI.

Up-regulation of ABCG2 by MYBL2 deletion drives Chlorin e6-mediated photodynamic therapy resistance in colorectal cancer.

OBJECTIVE: Photodynamic therapy (PDT) may be an effective therapeutic strategy for colorectal cancer at an early stage. However, malignant cells' resistance to photodynamic agents can lead to treatment failure. MYBL2 (B-Myb) is an oncogene in colorectal carcinogenesis and development, for which little research has focused on its effect on drug resistance. MATERIALS AND METHODS: In the present work, a colorectal cancer cell line with a stable knockdown of MYBL2 (ShB-Myb) was constructed first. Chlorin e6 (Ce6) was utilized to induced PDT. The anti-cancer efficacy was measured by CCK-8, PI staining, and Western blots. The drug uptake of Ce6 was assayed by flow cytometry and confocal microscopy. The ROS generation was detected by the CellROX probe. DDSB and DNA damage were assayed through comet experiment and Western blots. The over-expression of MYBL2 was conducted by MYBL2 plasmid. RESULTS: The findings indicated that the viability of ShB-Myb treated with Ce6-PDT was not decreased compared to control SW480 cells (ShNC), which were resistant to PDT. Further investigation revealed reduced photosensitizer enrichment and mitigated oxidative DNA damage in colorectal cancer cells with depressed MYBL2. It turned out that SW480 cells knocking down MYBL2 showed phosphorylation of NF-κB and led to up-regulation of ABCG2 expression thereupon. When MYBL2 was replenished back in MYBL2-deficient colorectal cancer cells, phosphorylation of NF-κB was blocked and ABCG2 expression up-regulation was suppressed. Additionally, replenishment of MYBL2 also increased the enrichment of Ce6 and the efficacy of PDT. CONCLUSION: In summary, MYBL2 absence in colorectal cancer contributes to drug resistance by activating NF-κB to up-regulate ABCG2 and thereby leading to photosensitizer Ce6 efflux. This study provides a novel theoretical basis and strategy for how to effectively improve the anti-tumor efficacy of PDT.

Prognostic value of nectin-4 in human cancers: A meta-analysis.

Background: Many reports have described that abnormal nectin-4 expression may be used as a prognostic marker in many tumors. However, these studies failed to reach a consensus. Here, we performed a meta-analysis to comprehensively evaluate the prognostic value of nectin-4 in cancers. Methods: Relevant studies were identified through a comprehensive search of PubMed, EMBASE and Web of science until August 31, 2022. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to evaluate the relationship between nectin-4 expression and overall survival (OS) and disease-free survival/progression-free survival/relapse-free survival (DFS/PFS/RFS). Odds ratios (ORs) with 95% CIs were applied to assess the relationship between nectin-4 expression and clinicopathologic features. Subgroup analysis was performed to explore the sources of heterogeneity. Sensitivity analysis and funnel plot were used to test the reliability of the results. All data analyses were performed using STATA version 12.0 software. Results: Fifteen articles involving 2245 patients were included in the meta-analysis. The pooled analysis showed that high nectin-4 expression was significantly associated with poor OS (HR: 1.75, 95% CI: 1.35-2.28). There was no relationship between high nectin-4 expression and DFS/PFS/RFS (HR: 178, 95% CI: 0.78-4.08).Subgroup analyses revealed that that high nectin-4 expression mainly presented adverse OS in esophageal cancer (EC) (HR: 1.78, 95% CI: 1.30-2.44) and gastric cancer (GC) (HR: 1.92, 95% CI: 1.43-2.58). We also found that high nectin-4 expression was associated with tumor diameter (big vs small) (OR: 1.96, 95% CI: 1.02-3.75), tumor stage (III-IV vs I-II) (OR: 2.04, 95% CI: 1.01-4.12) and invasion depth (T3+T4 vs T2+T1) (OR: 3.95, 95% CI: 2.06-7.57). Conclusions: Nectin-4 can be used as an effective prognostic indicator for specific cancers.

Insight into the Crosstalk between Photodynamic Therapy and Immunotherapy in Breast Cancer.

Breast cancer (BC) is the world's second most frequent malignancy and the leading cause of mortality among women. All in situ or invasive breast cancer derives from terminal tubulobular units; when the tumor is present only in the ducts or lobules in situ, it is called ductal carcinoma in situ (DCIS)/lobular carcinoma in situ (LCIS). The biggest risk factors are age, mutations in breast cancer genes 1 or 2 (BRCA1 or BRCA2), and dense breast tissue. Current treatments are associated with various side effects, recurrence, and poor quality of life. The critical role of the immune system in breast cancer progression/regression should always be considered. Several immunotherapy techniques for BC have been studied, including tumor-targeted antibodies (bispecific antibodies), adoptive T cell therapy, vaccinations, and immune checkpoint inhibition with anti-PD-1 antibodies. In the last decade, significant breakthroughs have been made in breast cancer immunotherapy. This advancement was principally prompted by cancer cells' escape of immune regulation and the tumor's subsequent resistance to traditional therapy. Photodynamic therapy (PDT) has shown potential as a cancer treatment. It is less intrusive, more focused, and less damaging to normal cells and tissues. It entails the employment of a photosensitizer (PS) and a specific wavelength of light to create reactive oxygen species. Recently, an increasing number of studies have shown that PDT combined with immunotherapy improves the effect of tumor drugs and reduces tumor immune escape, improving the prognosis of breast cancer patients. Therefore, we objectively evaluate strategies for their limitations and benefits, which are critical to improving outcomes for breast cancer patients. In conclusion, we offer many avenues for further study on tailored immunotherapy, such as oxygen-enhanced PDT and nanoparticles.

Blood biomarkers predict outcomes in patients with hepatocellular carcinoma treated with immune checkpoint Inhibitors: A pooled analysis of 44 retrospective sudies.

OBJECTIVE: We conducted the first meta-analysis to identify the predictive significance of baseline blood biomarkers (such as neutrophil to lymphocyte ratio (NLR), early alpha-fetoprotein (AFP) response, albumin-bilirubin (ALBI), AFP, platelet to lymphocyte ratio (PLR), C-reactive protein (CRP), protein induced by vitamin K absence II (PIVKA-II), and lymphocyte to monocyte ratio (LMR)) in hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitors (ICIs). METHODS: Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by November 24, 2022. Clinical outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and hyperprogressive disease (HPD). RESULTS: A total of 44 articles with 5322 patients were included in this meta-analysis. The pooled results demonstrated that patients with high NLR levels had significantly poorer OS (HR: 1.951, P < 0.001) and PFS (HR: 1.632, P < 0.001), lower ORR (OR: 0.484, P < 0.001) and DCR (OR: 0.494, P = 0.027), and higher HPD (OR: 8.190, P < 0.001). The patients with high AFP levels had shorter OS (HR: 1.689, P < 0.001) and PFS (HR: 1.380, P < 0.001), and lower DCR (OR: 0.440, P < 0.001) than those with low AFP levels, however, there was no difference in ORR (OR: 0.963, P = 0.933). We also found that early AFP response was correlated with better OS (HR: 0.422, P < 0.001) and PFS (HR: 0.385, P < 0.001), higher ORR (OR: 7.297, P < 0.001) and DCR (OR: 13.360, P < 0.001) compared to non-responders. Besides, a high ALBI grade was significantly related to shorter OS (HR: 2.440, P = 0.009) and PFS (HR: 1.373, P = 0.022), lower ORR (OR: 0.618, P = 0.032) and DCR (OR: 0.672, P = 0.049) than those with an ALBI grade 1. CONCLUSION: The NLR, early AFP response, and ALBI were useful predictors of outcomes in HCC patients treated with ICIs.

The RNA binding protein RALY suppresses p53 activity and promotes lung tumorigenesis.

The tumor suppressor p53 plays a pivotal role in tumor prevention. The activity of p53 is mainly restrained by the ubiquitin E3 ligase Mdm2. However, it is not well understood how the Mdm2-p53 pathway is intricately regulated. Here we report that the RNA binding protein RALY functions as an oncogenic factor in lung cancer. RALY simultaneously binds to Mdm2 and the deubiquitinating enzyme USP7. Via these interactions, RALY not only stabilizes Mdm2 by stimulating the deubiquitinating activity of USP7 toward Mdm2 but also increases the trans-E3 ligase activity of Mdm2 toward p53. Consequently, RALY enhances Mdm2-mediated ubiquitination and degradation of p53. Functionally, RALY promotes lung tumorigenesis, at least partially, via negative regulation of p53. These findings suggest that RALY destabilizes p53 by modulating the function of Mdm2 at multiple levels. Our study also indicates a critical role for RALY in promoting lung tumorigenesis via p53 inhibition.

Clinical Features and Prognostic Models in Patients with Intrahepatic Cholangiocarcinoma: a Population-Based Analysis.

BACKGROUND: This study aims to construct a risk classification system and a nomogram in intrahepatic cholangiocarcinomafor patients (ICC). METHODS: Three thousand seven hundred thirty-seven patients diagnosed with ICC between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results. The consistency index, time-dependent receiver operating characteristic curve, and the calibration plots were adopted to evaluate the effective performance of nomogram. Decision curve analysis (DCA), net reclassification index (NRI), and comprehensive discrimination improvement (IDI) were used to compare the advantages and disadvantages of two models. Kaplan-Meier curve showed the difference in prognosis among different groups. RESULTS: Ten variables were selected to establish the nomogram for ICCA. The C-index (training cohort: 0.765, P < 0.05; validation cohort: 0.776, P < 0.05) and the time-dependent AUCs (the training cohort: the values of 1, 3, 5 years were 0.836, 0.873, and 0.888; the validation cohort: the values of 1, 3, 5 years were 0.833, 0.838, and 0.881) showed satisfactory discrimination. The calibration curves also revealed that the nomogram was consistent with the actual observations. The NRI (training cohort: 1-, 3-, 5-year CSS: 0.879, 0.94, 0.771; validation cohort: 1-, 3-, 5-year CSS: 0.905, 0.945, 0.717) and IDI (training cohort: 1-, 3-, 5-year CSS: 0.24, 0.23, 0.22; validation cohort: 1-, 3-, 5-year CSS: 0.24, 0.46, 0.27) (P < 0.05) (compared with AJCC staging). DCA showed that the new model was more practical and had better recognition than AJCC staging. CONCLUSIONS: A new risk stratification system for ICC patients has been developed, which can be a practical tool for patient management.

The prognostic value of the advanced lung cancer inflammation index in patients with gastrointestinal malignancy.

BACKGROUND: Systemic inflammation is crucial for the development and progression of cancers. The advanced lung cancer inflammation index (ALI) is considered to be a better indicator of systemic inflammation than current biomarkers. However, the prognostic value of the ALI in gastrointestinal neoplasms remains unclear. We performed the first meta-analysis to explore the association between ALI and gastrointestinal oncologic outcomes to help physicians better evaluate the prognosis of those patients. METHODS: Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by December 29, 2022. Clinical outcomes were overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and cancer-specific survival (CSS). RESULTS: A total of 18 articles with 6898 patients were included in this meta-analysis. The pooled results demonstrated that a low ALI was correlated with poor OS (HR = 1.914, 95% CI: 1.514-2.419, P < 0.001), DFS (HR = 1.631, 95% CI: 1.197-2.224, P = 0.002), and PFS (HR = 1.679, 95% CI: 1.073-2.628, P = 0.023) of patients with gastrointestinal cancers. Subgroup analysis revealed that a low ALI was associated with shorter OS (HR = 2.279, 95% CI: 1.769-2.935, P < 0.001) and DFS (HR = 1.631, 95% CI: 1.197-2.224, P = 0.002), and PFS (HR = 1.911, 95% CI: 1.517-2.408, P = 0.002) of patients with colorectal cancer. However, the ALI was not related to CSS in the patients with gastrointestinal malignancy (HR = 1.121, 95% CI: 0.694-1.812, P = 0.640). Sensitivity analysis supported the stability and dependability of the above results. CONCLUSION: The pre-treatment ALI was a useful predictor of prognosis in patients with gastrointestinal cancers.

Effects of agricultural activities on hydrochemistry in the Shiyang River Basin, China.

Agricultural water accounts for more than 80% of the available water in arid areas. Agricultural activities have a great impact on surface water and groundwater. If the impact of agricultural activities on hydrochemistry is not prevented, the risk of water quality change in arid areas may be greatly intensified. Based on the hydrochemical data of the whole Shiyang River Basin from April 2014 to October 2019, this paper analyzes the impact of agricultural activities on hydrochemistry in the basin. The results show that (i) in the middle and lower reaches of farmland with high intensity of agricultural activities, the ion concentration of groundwater in summer and autumn is significantly higher than that in winter and spring due to the influence of irrigation; (ii) the runoff ion concentration in the backflow of the river reaches recharged by irrigation water is significantly higher than that of other reaches; (iii) due to strong evaporation, different types of reservoirs will lead to an overall increase in ion concentration, which is more obvious in plain reservoirs and river tail lakes. In addition, the reservoirs have a certain removal effect on nitrates.

Low-grade hepatocellular carcinoma characteristics, a practical nomogram and risk stratification system: a SEER population-based study.

BACKGROUND: The purpose of this study is to establish a nomogram and risk stratification system to predict OS in patients with low-grade HCC. RESEARCH DESIGN AND METHODS: Data were extracted from the SEER database. C-index, time-dependent AUCs, and calibration plots were used to evaluate the effective performance of the nomogram. NRI, IDI, and DCA curves were adopted to compare the clinical utility of nomogram with AJCC. RESULTS: 3415 patients with low-grade HCC were available. The C-indices for the training and validation cohorts were 0.773 and 0.772. The time-dependent AUCs in the training cohort were 0.821, 0.817, and 0.846 at 1, 3 and 5 years. Calibration plots for 1-, 3- and 5-year OS showed good consistency between actual observations and that predicted by the nomogram. The values of NRI at 1, 3, and 5 years were 0.37, 0.66, and 0.64. The IDI values at 1, 3, and 5 years were 0.11, 0.16, and 0.23 (P< 0.001). DCA curves demonstrated that the nomogram showed better ability of predicting 1-, 3-, and 5-year OS probabilities than AJCC. CONCLUSIONS: A nomogram and risk stratification system for predicting OS in patients with low-grade HCC were established and validated.

A Practical Nomogram and Risk Stratification System Predicting the Cancer-Specific Survival for Patients With Advanced Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) has the highest cancer-related mortality rate. This study aims to create a nomogram to predict the cancer-specific survival (CSS) in patients with advanced hepatocellular carcinoma. Methods: Patients diagnosed with advanced HCC (AJCC stage III and IV) during 1975 to 2018 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Qualified patents were randomized into training cohort and validation cohort at a ratio of 7:3. The results of univariate and multivariate Cox regression analyses were used to construct the nomogram. Consistency index (C-index), area under the time-dependent receiver operating characteristic (ROC) curve [time-dependent area under the curve (AUC)], and calibration plots were used to identify and calibrate the nomogram. The net reclassification index (NRI), integrated discrimination improvement (IDI), and C-index, and decision curve analysis DCA were adopted to compare the nomogram's clinical utility with the AJCC criteria. Results: The 3,103 patients with advanced hepatocellular carcinoma were selected (the training cohort: 2,175 patients and the validation cohort: 928 patients). The C-index in both training cohort and validation cohort were greater than 0.7. The AUC for ROC in the training cohort was 0.781, 0.771, and 0.791 at 1, 2, and 3 years CSS, respectively. Calibration plots showed good consistency between actual observations and the 1-, 2-, and 3-year CSS predicted by the nomogram. The 1-, 2-, and 3-year NRI were 0.77, 0.46, and 0.48, respectively. The 1-, 2-, and 3-year IDI values were 0.16, 0.15, and 0.12 (P < 0.001), respectively. DCA curves in both the training and validation cohorts demonstrated that the nomogram showed better predicted 1-, 2-, and 3-year CSS probabilities than AJCC criteria. Conclusions: This study established a practical nomogram for predicting CSS in patients with advanced HCC and a risk stratification system that provided an applicable tool for clinical management.