A Novel Hypoxic-Angiogenesis-Immune-Related Gene Model for Prognostic and Therapeutic Effect Prediction in Hepatocellular Carcinoma Patients

Background. Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant tumors that have been discovered so far, which makes the prognostic prediction difficult. The hypoxia, angiogenesis, and immunity-related genes (HAIRGs) are closely related to the development of liver cancer. However, the prognostic and treatment effect of hypoxia, angiogenesis, and immunity-related genes in HCC continues to be further clarified. Methods. The gene expression quantification data and clinical information in patients with liver cancer were downloaded from the TCGA database, and HAIRG signature was built by using the least absolute shrinkage and selection operator (LASSO) technique. Patient from the ICGC database validated the model. Then, tumor immune dysfunction and exclusion (TIDE) algorithm was applied to estimate the clinical response to immunotherapy and the sensitivity of drugs was evaluated by the half-maximal inhibitory concentration (IC50). Result. The HAIRGs were identified between the HCC patients and normal patients in the TCGA database. In univariate Cox regression analysis, seventeen differentially expressed genes (DEGs) were associated with overall survival (OS). An eight HAIRG signature model was constructed and was used to divide the patients into two groups according to the median value of the risk score base on the TCGA dataset. Patients in the high-risk group had a significant reduction in OS compared to those in the low-risk group ( P < 0.001 in the TCGA, P < 0.001 in the ICGC). For TCGA and ICGC databases of univariate Cox regression analyses, the risk score was used as an independent predictor of OS ( HR > 1 , P < 0.001 ). Functional analysis showed that the relevant immune pathways and immune responses were enriched, cellular component analysis showed that the immunoglobulin complex and other related substances were enriched, and immune status existed a difference in the high- and low-risk groups. Then, the tumor immune dysfunction and exclusion (TIDE) algorithm presented differences in immune response in the high- and low-risk groups ( P < 0.05 ), and based on drug sensitivity prediction, patients in the high-risk group were more sensitive to cisplatin compared to those in the low-risk group in both the TCGA and ICGC cohorts ( P < 0.05 ). Conclusions. HAIRG signature can be utilized for prognostic prediction in HCC, while it can be considered a prediction model for clinical evaluation of immunotherapy response and chemotherapy sensitivity in HCC.

Immune dysfunction in chronic kidney disease

Chronic kidney disease is characterized by immune dysfunction that increases predisposition to infections, virus-associated cancers and impaired response to vaccination. The altered immune response is caused by impairment of both innate and adaptive immune systems, as well as other factors that are hallmarks of renal disease, such as uremia, malnutrition, chronic inflammation, mineral bone disease and anemia. The aim of this article is to review the causes and mechanisms that lead to immune dysfunction in patients with chronic kidney disease.

Remodeling Articular Immune Homeostasis with an Efferocytosis-inspired Nanoimitator Mitigates Rheumatoid Arthritis

Massive intra-articular infiltration of the pro-inflammatory macrophages is a prominent feature of rheumatoid arthritis (RA) lesions, which are thought to underlie articular immune dysfunction, severe synovitis and ultimate joint erosion. Here we report an efferocytosis-inspired nanoimitator (EINI) for in situ targeted reprogramming of the synovial inflammatory macrophages (SIMs) and thus thwarting their autoimmune attack and reinstating articular immune homeostasis, which mitigates RA. The EINI consisted of a drug-based core with an oxidative stress-responsive phosphatidylserine (PtdSer) corona and a shell of P-selectin-blocking motif, low molecular weight heparin (LMWH). When systemically administrated, the LMWH on the EINI first bound to P-selectin overexpressed on endothelium in subsynovial capillaries, which functioned as an antagonist disrupting neutrophils synovial trafficking. Due to the high dysregulation of the synovial microvasculature, the EINI subsequently enriched in joint synovium where the shell was exfoliated upon the reactive oxygen species stimulation, and PtdSer corona was then exposed. In an efferocytosis-like manner, the PtdSer-coroneted core was in turn phagocytosed by SIMs, which synergistically terminated the SIMs-initiated pathological cascades and serially reconstructed the intra-articular immune homeostasis, conferring a chondroprotection effect. These findings demonstrate that SIMs can be precisely remodeled via the efferocytosis-mimetic strategy, which holds great potential for RA treatment.

Pretreatment with 6-Gingerol Ameliorates Sepsis-Induced Immune Dysfunction by Regulating the Cytokine Balance and Reducing Lymphocyte Apoptosis

Sepsis is characterized by an initial net hyperinflammatory response, followed by a period of immunosuppression, termed immunoparalysis. During this immunosuppressive phase, patients may have difficulty eradicating invading pathogens and are susceptible to life-threatening secondary hospital-acquired infections. Due to progress in antimicrobial treatment and supportive care, most patients survive early sepsis. Mortality is more frequently attributed to subsequent secondary nosocomial infections and multiorgan system failure. 6-Gingerol is the major pharmacologically active component of ginger. Although it is known to exhibit a variety of biological activities, including anti-inflammation and antioxidation, the role of 6-gingerol in sepsis-induced immune dysfunction remains elusive. Thus, we investigated whether 6-gingerol improves septic host response to infections during sepsis. 6-Gingerol-treated mice showed significantly lower mortality in polymicrobial sepsis induced by cecal ligation and puncture LPS via enhanced bacterial clearance in the peritoneum, blood, and organs (liver, spleen, and kidney) and inhibited the production of TNF-α and IL-6 in TLR2 and/or TLR4-stimulated macrophages. In addition, we demonstrated that survival improvement of secondary infection following septic insult was associated with an initial response of enhanced neutrophil numbers and function at the infection site, reduced apoptosis of immune cells, and a shift from a T helper cell type 2 (Th2) to a T helper cell type 1 (Th1) cytokine balance in the hypoinflammation phase. Our overall findings suggest that 6-gingerol potentially restores sepsis-induced immune dysfunction by shifting the balance of Th1/Th2 and by regulating apoptosis of immune cells.

Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma

Background. Acidosis in the tumor microenvironment (TME) is involved in tumor immune dysfunction and tumor progression. We attempted to develop an acidosis-related index (ARI) signature to improve the prognostic prediction of pancreatic carcinoma (PC). Methods. Differential gene expression analyses of two public datasets (GSE152345 and GSE62452) from the Gene Expression Omnibus database were performed to identify the acidosis-related genes. The Cancer Genome Atlas–pancreatic carcinoma (TCGA-PAAD) cohort in the TCGA database was set as the discovery dataset. Univariate Cox regression and the Kaplan–Meier method were applied to screen for prognostic genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish the optimal model. The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm. Results. We identified 133 acidosis-related genes, of which 37 were identified as prognostic genes by univariate Cox analysis in combination with the Kaplan–Meier method ( p values of both methods < 0.05). An acidosis-related signature involving seven genes (ARNTL2, DKK1, CEP55, CTSV, MYEOV, DSG2, and GBP2) was developed in TCGA-PAAD and further validated in GSE62452. Patients in the acidosis-related high-risk group consistently showed poorer survival outcomes than those in the low-risk group. The 5-year AUCs (areas under the curve) for survival prediction were 0.738 for TCGA-PAAD and 0.889 for GSE62452, suggesting excellent performance. The low-risk group in TCGA-PAAD showed a higher abundance of CD8+ T cells and activated natural killer cells and was predicted to possess an elevated proportion of immunotherapeutic responders compared with the high-risk counterpart. Conclusions. We developed a reliable acidosis-related signature that showed excellent performance in prognostic prediction and correlated with tumor immune infiltration, providing a new direction for prognostic evaluation and immunotherapy management in PC.

Development of Biomarker Signatures Associated with Anoikis to Predict Prognosis in Endometrial Carcinoma Patients

Purpose. To generate a signature based on anoikis-related genes (ARGs) for endometrial carcinoma (EC) patients and elucidate the molecular mechanisms in EC. Methods. On the basis of TCGA-UCEC dataset, we identified specific anoikis-related genes (ARGs) in EC. Cox-relative regression methods were used to generate an anoikis-related signature (ARS). The possible biological pathways of ARS-related genes were analyzed by GSEA. The clinical potency and immune status of ARS were analyzed by CIBERSORT method, ssGSEA algorithm, Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Moreover, the expression patterns of ARS genes were verified by HPA database. Results. Seven anoikis genes (CDKN2A, E2F1, ENDOG, EZH2, HMGA1, PLK1, and SLC2A1) were determined to develop a prognostic ARS. Both genes of ARS were closely bound up with the prognosis of EC patients. The ARS could accurately classify EC cases with different clinical outcome and mirror the specific immune status of EC. We observed that ARS-high patients could not benefit from immunotherapy. Finally, all the hub genes of ARS were proved to be upregulated in EC tissues by immunohistology. Conclusion. ARS can be used to stratify the risk and forecast the survival outcome of EC patients and provide prominent reference for individualized treatment in EC.