A signature of seven hypoxia-related lncRNAs is a potential biomarker for predicting the prognosis of melanoma.

Melanoma is the most aggressive type of skin cancer and has a high mortality rate once metastasis occurs. Hypoxia is a universal characteristic of the microenvironment of cancer and a driver of melanoma progression. In recent years, long noncoding RNAs (lncRNAs) have attracted widespread attention in oncology research. In this study, screening was performed and revealed seven hypoxia-related lncRNAs AC008687.3, AC009495.1, AC245128.3, AL512363.1, LINC00518, LINC02416 and MCCC1-AS1 as predictive biomarkers. A predictive risk model was constructed via univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Patients were grouped according to the model risk score, and Kaplan-Meier analysis was performed to compare survival between groups. Functional and pathway enrichment analyses were performed to compare gene set enrichment between groups. Moreover, a nomogram was constructed with the risk score as a variable. In both the training and validation sets, patients in the low-risk group had better overall survival than did those in the high-risk group (P<0.001). The 3-, 5- and 10-year area under the curve (AUC) values for the nomogram model were 0.821, 0.795 and 0.820, respectively. Analyses of immune checkpoints, immunotherapy response, drug sensitivity, and mutation landscape were also performed. The results suggested that the low-risk group had a better response to immunotherapeutic. In addition, the nomogram can effectively predict the prognosis and immunotherapy response of melanoma patients. The signature of seven hypoxia-related lncRNAs showed great potential value as an immunotherapy response biomarker, and these lncRNAs might be treatment targets for melanoma patients.

Systematic Pan-Cancer Analysis Reveals X-C Motif Chemokine Receptor 1 as a Prognostic and Immunological Biomarker.

Chemokines and their receptors play an important role in immune monitoring and immune defense during tumor growth and metastasis. However, their prognostic roles in pan-cancer have not been elucidated. In this work, we screened all chemokine receptors in pan-cancer and discovered X-C Motif Chemokine Receptor 1 (XCR1) as a reliable immunological and prognostic biomarker in pan-cancer using bioinformation. The TCGA database served as the foundation for the primary research database analysis in this work. XCR1 was downregulated in tumors. Patients with reduced XCR1 showed worse prognoses and a concomitant decrease in immune cell infiltration (DCs and CD8+ T cells). According to a gene enrichment study, XCR1 enhanced immune system performance by promoting T-cell infiltration through the C-X-C Motif Chemokine Ligand 9 (CXCL9)- C-X-C Motif Chemokine Receptor 3 (CXCR3) axis. In addition, XCR1 is mainly expressed in infiltrated DCs and some malignant cells in tumor tissues. Our data revealed the important role of XCR1 in remodeling the tumor microenvironment and predicting the survival prognosis, which could also be used as a sensitive biomarker for tumor immunotherapy.

Developing a novel necroptosis-related signature to evaluate the prognostic and therapeutic characteristics of esophageal cancer.

BACKGROUND: The prognostic assessment and therapeutic interventions of esophageal cancer (ESCA) require novel molecular targets. The prognostic value of necroptosis, a specific mode of programmed cell death strongly linked to cancer progression, remains largely unexplored in ESCA. The primary goal of this research is to develop a necroptosis-based prognostic signature, which will represent the microenvironmental characteristics and prognosis of individuals diagnosed with ESCA. METHODS: Transcriptome data of ESCA samples from The Cancer Genome Atlas were utilized to screen for necroptosis-related long non-coding RNAs (NR-lncRNAs) and genes (NRGs). The research employed the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression analysis to identify prognostic candidates. Based on these analyses, a signature was developed in the training set and subsequently verified in the testing and entire sets. A clinicopathologic relevance assessment was carried out, after which a nomogram was established. The features of the immune microenvironment, functional pathways, mutational burden, checkpoint expression, and stemness of tumors were analyzed. Moreover, the sensitivity of individuals to immunotherapy and chemotherapy was compared for therapeutic guidance. RESULTS: A necroptosis-associated signature comprising two genes and eleven lncRNAs was constructed. High-risk patients showed worse prognosis and clinicopathologic features, with more tumor-infiltrating naïve B cells, CD4+ memory resting T cells, and regulatory T cells. Furthermore, stromal and ESTIMATE scores were decreased along with increased stemness scores and tumor mutational burden in high-risk individuals. For the quantitative prediction of the outcomes of individuals, a nomogram was established. High-risk individuals showed greater sensitivity to immunotherapy while low-risk individuals benefited more from conventional chemotherapeutic or targeted therapy. CONCLUSION: A necroptosis-related prognostic signature was developed to study the tumor microenvironment, mutational burden, clinical features, and the treatment response of ESCA patients. This may contribute to precision medicine for ESCA.

Risk stratification based on DNA damage-repair-related signature reflects the microenvironmental feature, metabolic status and therapeutic response of breast cancer.

DNA damage-repair machinery participates in maintaining genomic integrity and affects tumorigenesis. Molecular signatures based on DNA damage-repair-related genes (DRGs) capable of comprehensively indicating the prognosis, tumor immunometabolic profile and therapeutic responsiveness of breast cancer (BRCA) patients are still lacking. Integrating public datasets and bioinformatics algorithms, we developed a robust prognostic signature based on 27 DRGs. Multiple patient cohorts identified significant differences in various types of survival between high- and low-risk patients stratified by the signature. The signature correlated well with clinicopathological factors and could serve as an independent prognostic indicator for BRCA patients. Furthermore, low-risk tumors were characterized by more infiltrated CD8+ T cells, follicular helper T cells, M1 macrophages, activated NK cells and resting dendritic cells, and fewer M0 and M2 macrophages. The favorable immune infiltration patterns of low-risk tumors were also accompanied by specific metabolic profiles, decreased DNA replication, and enhanced antitumor immunity. Low-risk patients may respond better to immunotherapy, and experience improved outcomes with conventional chemotherapy or targeted medicine. Real-world immunotherapy and chemotherapy cohorts verified the predictive results. Additionally, four small molecule compounds promising to target high-risk tumors were predicted. In vitro experiments confirmed the high expression of GNPNAT1 and MORF4L2 in BRCA tissues and their association with immune cells, and the knockdown of these two DRGs suppressed the proliferation of human BRCA cells. In summary, this DNA damage-repair-related signature performed well in predicting patient prognosis, immunometabolic profiles and therapeutic sensitivity, hopefully contributing to precision medicine and new target discovery of BRCA.

Integrating single-cell and bulk transcriptomic analyses to develop a cancer-associated fibroblast-derived biomarker for predicting prognosis and therapeutic response in breast cancer.

Background: Cancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA. Methods: CAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA. Results: Integrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA. Conclusions: A novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.

Endocapillary hypercellularity levels are associated with early complete remission in children with class IV lupus nephritis as the initial presentation of SLE.

BACKGROUND: Endocapillary hypercellularity (ECHC) is commonly seen in class IV lupus nephritis (LN), the most common and severe LN in children. Factors influencing early complete remission (CR) in pediatric class IV LN have been poorly described. We investigated the relationship between ECHC levels and early CR in pediatric class IV LN. METHODS: Patients with newly, simultaneously diagnosed systemic lupus erythematosus (SLE) and class IV LN by renal biopsy from 2012 to 2021 were studied. In this retrospective study, two pathologists who were blind to clinical information reviewed all pathological data retrospectively and classified glomerular lesions according to the revised criteria of the International Society of Nephrology and the Renal Pathology Society (ISN/RPS). The demographics, baseline clinical characteristics, laboratory parameters, renal histopathological findings, treatment regimen and CR at 6 months after immunosuppressive therapy were analyzed. ECHC was categorized as: > 50% (group A), 25-50% (group B) and < 25% (group C). CR was defined as absence of clinical symptoms, 24-hour urinary protein < 0.15 g, and normal levels of serum creatinine and albumin. RESULTS: Sixty-four patients were identified: 23, 15 and 26 in groups A, B and C, respectively. Group A had significantly higher levels of D-dimer, urine protein, and SLE disease activity index (SLEDAI) than groups B and C. Group C had a markedly higher estimated glomerular filtration rate (eGFR) than groups A and B. A substantially greater proportion of patients in group A had glomerular microthrombi and basement membrane thickening than in groups B and C. At 6 months post treatment, CR was achieved in 19 (82.6%), 5 (33.3%) and 11 (42.3%) in groups A, B and C, respectively (p < 0.05, group A vs groups B and C). Multiple logistic regression analysis revealed that ECHC and urine protein levels were significantly associated with CR. CONCLUSION: ECHC and urine protein levels may be valuable biomarkers for predicting early CR in pediatric class IV LN.

Development of a metabolism-related signature for predicting prognosis, immune infiltration and immunotherapy response in breast cancer.

Breast cancer (BRCA) is the most commonly diagnosed cancer and among the top causes of cancer deaths globally. The abnormality of the metabolic process is an important characteristic that distinguishes cancer cells from normal cells. Currently, there are few metabolic molecular models to evaluate the prognosis and treatment response of BRCA patients. By analyzing RNA-seq data of BRCA samples from public databases via bioinformatic approaches, we developed a prognostic signature based on seven metabolic genes (PLA2G2D, GNPNAT1, QPRT, SHMT2, PAICS, NT5E and PLPP2). Low-risk patients showed better overall survival in all five cohorts (TCGA cohort, two external validation cohorts and two internal validation cohorts). There was a higher proportion of tumor-infiltrating CD8+ T cells, CD4+ memory resting T cells, gamma delta T cells and resting dendritic cells and a lower proportion of M0 and M2 macrophages in the low-risk group. Low-risk patients also showed higher ESTIMATE scores, higher immune function scores, higher Immunophenoscores (IPS) and checkpoint expression, lower stemness scores, lower TIDE (Tumor Immune Dysfunction and Exclusion) scores and IC50 values for several chemotherapeutic agents, suggesting that low-risk patients could respond more favorably to immunotherapy and chemotherapy. Two real-world patient cohorts receiving anti-PD-1 therapy were applied for validating the predictive results. Molecular subtypes identified based on these seven genes also showed different immune characteristics. Immunohistochemical data obtained from the human protein atlas database demonstrated the protein expression of signature genes. This research may contribute to the identification of metabolic targets for BRCA and the optimization of risk stratification and personalized treatment for BRCA patients.

Identification of an Immune-Related Gene Signature Associated with Prognosis and Tumor Microenvironment in Esophageal Cancer.

Background: Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC. Methods: Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses. Results: A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4+ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified. Conclusion: Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.

Neutropenia in 6 cases of childhood onset type 1 diabetes and its possible mechanisms.

OBJECTIVE: Type 1 diabetes (T1D) is a chronic inflammatory disease caused by a selective destruction of the pancreatic ß-cells. There are few reports on peripheral neutropenia in T1D for different reasons. We reported 6 cases of childhood onset T1D combined with neutropenia and explored its possible mechanisms. METHODS: The clinical diagnosis and treatment course of 6 cases of childhood onset T1D combined with neutropenia, who were hospitalized in our hospital from January 2013 to December 2016, were studied retrospectively. RESULTS: We have diagnosed and treated 38 cases of childhood onset T1D during this period, while only 6 cases (15.79%) had neutropenia. The diagnostic ages of the 6 cases ranged from 5 to 12 years. Diabetic ketoacidosis (DKA) was complicated in 5 cases. Neutropenia happened within 14 to 21 days of the onset of disease and 3 to 11 days after using insulin, respectively, and returned spontaneously to normal range within 5 to 9 days. The serum levels of granulocyte colony-stimulating factor (G-CSF) and granulocyte macrophage colony-stimulating factor (GM-CSF) increased slightly before the usage of insulin in all 6 cases, and decreased to normal range after the usage of insulin. CONCLUSION: Neutropenia can be seen in childhood onset T1D, and can return spontaneously to normal range without special treatments. The possible mechanisms might be the regulation effects of insulin on G-CSF and GM-CSF.