Background:Renal angiomyolipoma (AML) is a common benign tumor of the kidney. The main complication of AML is retroperitoneal hemorrhage caused by AML rupture, which can be severe and life threatening. The risk of AML rupture used to be determined by tumor size. However, these criteria have been challenged by series of clinical studies and case reports, suggesting prediction AML rupture based on tumor size is not always reliable.Methods:The authors searched PubMed using “angiomyolipoma,” “AML,” and “rupture” and reviewed relevant studies. The authors investigated the risk factors of AML rupture using the retrieved literature. The authors also summarized current modalities to evaluate and manage AML.Results:It is established that risk of AML rupture is associated with lesion size. However, genetic abnormality, aneurysm formation, and pregnancy are also risk factors for tumor rupture. Thus, the prediction of AML rupture should be based on a more comprehensive risk assessment system. The management of renal AML and tumor rupture was also discussed in the present paper.Conclusion:The risk of AML rupture is associated with but not exclusive to lesion size. Any decision to intervene AML must be based on multiple factors including risk, symptoms, and auxiliary findings.

A20 (TNFAIP3), known to inhibit NF-κB function by deubiquitinating-specific NF-κB signaling molecules, has been found in many cell types of the immune system. Recent findings suggest that A20 is essential for the development and functional performance of dendritic cell, B cell, T cell and macrophage. A number of studies further demonstrate that these cells are crucial in the pathogenesis of autoimmune diseases, such as type 1 diabetes, systemic lupus erythematosus, inflammatory bowel disease, ankylosing arthritis, Sjögren's syndrome and rheumatoid arthritis. In this article, we focus on the recent advances on the roles of A20 in autoimmune diseases and discuss the therapeutic significance of these new findings.

At present, immunotherapy is widely used for different mismatch repair (dMMR) or highly microsatellite instability (MSI-H) colorectal cancer patients, and tumor mutation burden (TMB) is a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in colon cancer remains unclear. In the present study, we analyzed somatic mutation data of colon cancer from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets, and found that 17 frequently mutated genes were occurred in both cohorts, including APC, TP53, TNN, KRAS, MUC16, MUC4 (mucin 4), SYNE1, FLG, FAT4, OBSCN, FAT3, RYR2, PIK3CA, FBXW7, DNAH11, MUC5B and ZFHX4. Interestingly, only MUC4 mutation was associated with higher TMB and patient clinical prognosis among the 17 mutated genes. Moreover, according to gene set enrichment analysis (GSEA) and the CIBERSORT algorithm, we revealed that MUC4 mutation activated signaling pathways involved in the immune system and enhanced the antitumor immune response. In conclusion, MUC4 may have important clinical implications for immune therapy of colon cancer.

Background. Currently, immunotherapy is widely used for breast cancer (BC) patients, and tumor mutation burden (TMB) is regarded as a valuable independent predictor of response to immunotherapy. However, specific gene mutations and their relationship with TMB and tumor-infiltrating immune cells in BC are not fully understood. Methods. Comprehensive bioinformatic analyses were performed using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. Survival curves were analyzed via Kaplan-Meier analysis. Univariate and multivariate Cox regression analyses were used for prognosis analysis. Gene set enrichment analysis (GSEA) was performed to explore regulatory mechanisms and functions. The CIBERSORT algorithm was used to calculate the tumor-infiltrating immune cell fractions. Results. We analyzed somatic mutation data of BC from TCGA and ICGC datasets and found that 19 frequently mutated genes were reported in both cohorts, namely, SPTA1, TTN, MUC17, MAP3K1, CDH1, FAT3, SYNE1, FLG, HMCN1, RYR2 (ryanodine receptor 2), GATA3, MUC4, PIK3CA, KMT2C, TP53, PTEN, ZFHX4, MUC16, and USH2A. Among them, we observed that RYR2 mutation was significantly associated with higher TMB and better clinical prognosis. Moreover, GSEA revealed that RYR2 mutation-enriched signaling pathways were related to immune-associated pathways. Furthermore, based on the CIBERSORT algorithm, we found that RYR2 mutation enhanced the antitumor immune response by enriching CD8+ T cells, activated memory CD4+ T cells, and M1 macrophages. Conclusion. RYR2 is frequently mutated in BC, and its mutation is related to increased TMB and promotes antitumor immunity; thus, RYR2 may serve as a valuable biomarker to predict the immune response.

Background Fatty acid-binding protein 4 (FABP4) has been reported to be associated with tumor progress and poor prognosis in various cancers. However, the relationship between FABP4 expression and tumor immunity in colon adenocarcinoma (COAD) is still poorly understood. Methods FABP4 mRNA expression was analyzed using The Cancer Genome Atlas (TCGA)-COAD data. FABP4 protein staining was performed by immunohistochemistry (IHC) staining in our 10 paired COAD samples and corresponding adjacent noncancerous tissues. The association between FABP4 and immune cell infiltration was evaluated by Tumor Immune Estimation Resource (TIMER) database. FABP4 coexpressed genes were identified based on Cancer Cell Line Encyclopedia (CCLE) database, which were employed for further enrichment analysis. FABP4 related immunomodulators was identified by Tumor and Immune System Interaction Database (TISIDB) database, and a prognostic risk signature was constructed based on FABP4-related immunomodulators using stepwise Cox regression analysis. A nomogram consists of FABP4 related immunomodulators signature and clinical parameters was developed to predict the overall survival (OS). Results In TCGA data, we found that the decreased FABP4 mRNA expression in COAD samples compared with normal samples, and low FABP4 mRNA expression was associated with B cells, CD4+ T cells, CD8+ T cells, myeloid dendritic cells, macrophages, and neutrophils. In our 10 paired samples, the protein levels of COAD were lower in all COAD tissues than in their adjacent noncancerous tissues. Functional enrichment analysis revealed that FABP4 coexpressed genes were mostly enriched in immune-related pathways. Based on 54 FABP4-related immunomodulators, a 2-gene FABP4-related prognostic risk signature was developed, and the signature stratified the patients into the high-risk and low-risk groups with statistically different survival outcomes. The Nomogram consists of the prognostic signature and clinical parameters had a certain predictability for prognosis of COAD patients. Conclusion These findings suggest that FABP4 is associated with 2-gene immune signature which also correlate with the prognosis of COAD patients.

BackgroundLow-fat diet reduces the risk of chronic metabolic diseases such as obesity and diabetes, which exhibit overlapping mechanisms with liver cancer. However, the association between low-fat diet and liver cancer risk remains unclear.AimTo investigate whether adherence to low-fat diet is associated with a reduced risk of liver cancer in a prospective study.Materials and methodsData of participants in this study were collected from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A low-fat diet score was calculated to reflect adherence to low-fat dietary pattern, with higher scores indicating greater adherence. Cox regression was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for liver cancer incidence with adjustment for potential covariates. Restricted cubic spline model was used to characterize liver cancer risk across the full range of the low-fat diet score. Prespecified subgroup analyses were used to identify potential impact modifiers. Sensitivity analyses were performed to test the robustness of this association.ResultsA total of 98,455 participants were included in the present analysis. The mean (standard deviation) age, low-fat diet score, and follow-up time were 65.52 (5.73) years, 14.99 (6.27) points, and 8.86 (1.90) years, respectively. During 872639.5 person-years of follow-up, 91 liver cancers occurred, with an overall incidence rate of 0.01 cases per 100 person-years. In the fully adjusted Cox model, the highest versus the lowest quartile of low-fat diet score was found to be associated with a reduced risk of liver cancer (HRQ4 vs. Q1: 0.458; 95% CI: 0.218, 0.964; P = 0.035 for trend), which remained associated through a series of sensitivity analyses. The restricted cubic spline model showed a linear dose–response association between low-fat diet score and liver cancer incidence (p = 0.482 for non-linear). Subgroup analyses did not show significant interaction between low-fat diet score and potential impact modifiers in the incidence of liver cancer.ConclusionIn this study, low-fat diet score is associated with reduced liver cancer risk in the US population, indicating that adherence to low-fat diet may be helpful for liver cancer prevention. Future studies should validate our findings in other populations.

ObjectiveLocal invasion is the first step of metastasis, the main cause of colorectal cancer (CRC)-related death. Recent studies have revealed extensive intertumoral and intratumoral heterogeneity. Here, we focused on revealing local invasion-related genes in CRC. MethodsWe used spatial transcriptomic techniques to study the process of local invasion in four CRC tissues. First, we compared the pre-cancerous, cancer center, and invasive margin in one section (S115) and used pseudo-time analysis to reveal the differentiation trajectories from cancer center to invasive margin. Next, we performed immunohistochemical staining for RPL5, STC1, AKR1B1, CD47, and HLA-A on CRC samples. Moreover, we knocked down AKR1B1 in CRC cell lines and performed CCK-8, wound healing, and transwell assays to assess cell proliferation, migration, and invasion.ResultsWe demonstrated that 13 genes were overexpressed in invasive clusters, among which the expression of CSTB and TM4SF1 was correlated with poor PFS in CRC patients. The ribosome pathway was increased, while the antigen processing and presentation pathway was decreased along CRC progression. RPL5 was upregulated, while HLA-A was downregulated along cancer invasion in CRC samples. Pseudo-time analysis revealed that STC1, AKR1B1, SIRPA, C4orf3, EDNRA, CES1, PRRX1, EMP1, PPIB, PLTP, SULF2, and EGFL6 were unpregulated along the trajectories. Immunohistochemic3al staining showed the expression of STC1, AKR1B1, and CD47 was increased along cancer invasion in CRC samples. Knockdown of AKR1B1 inhibited CRC cells’ proliferation, migration, and invasion.ConclusionsWe revealed the spatial heterogeneity within CRC tissues and uncovered some novel genes that were associated with CRC invasion.

<p>Supplementary Figure S2. Cluster analysis of multiple cohorts combined CRC set. A-C. Principal components analysis performed on all CRC patients using the top 500 mRNAs showing the highest standard deviation across all patients. The first four principal components which explain the most of the data variation are shown. Patients are labeled with different color according to the cohort which they belong. (A) The first two principal components; (B) The third and fourth principal components; (C) Explained variances of each principal components. D. Hierarchical clustering of CRC patients using the Ward method to compute the distance between patients.</p>