Browsing by Author "Fu, Denggang"

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    Characterization of tumor immune microenvironment and cancer therapy for head and neck squamous cell carcinoma through identification of a genomic instability-related lncRNA prognostic signature
    (Frontiers Media, 2022-08-29) Jing, Lijun; Du, Yabing; Fu, Denggang; Medicine, School of Medicine
    Head and neck squamous cell carcinoma (HNSCC) represents one of the most prevalent and malignant tumors of epithelial origins with unfavorable outcomes. Increasing evidence has shown that dysregulated long non-coding RNAs (lncRNAs) correlate with tumorigenesis and genomic instability (GI), while the roles of GI-related lncRNAs in the tumor immune microenvironment (TIME) and predicting cancer therapy are still yet to be clarified. In this study, transcriptome and somatic mutation profiles with clinical parameters were obtained from the TCGA database. Patients were classified into GI-like and genomic stable (GS)-like groups according to the top 25% and bottom 25% cumulative counts of somatic mutations. Differentially expressed lncRNAs (DElncRNAs) between GI- and GS-like groups were identified as GI-related lncRNAs. These lncRNA-related coding genes were enriched in cancer-related KEGG pathways. Patients totaling 499 with clinical information were randomly divided into the training and validation sets. A total of 18 DElncRNAs screened by univariate Cox regression analysis were associated with overall survival (OS) in the training set. A GI-related lncRNA signature that comprised 10 DElncRNAs was generated through least absolute shrinkage and selection operator (Lasso)-Cox regression analysis. Patients in the high-risk group have significantly decreased OS vs. patients in the low-risk group, which was verified in internal validation and entire HNSCC sets. Integrated HNSCC sets from GEO confirmed the notable survival stratification of the signature. The time-dependent receiver operating characteristic curve demonstrated that the signature was reliable. In addition, the signature retained a strong performance of OS prediction for patients with various clinicopathological features. Cell composition analysis showed high anti-tumor immunity in the low-risk group which was evidenced by increased infiltrating CD8+ T cells and natural killer cells and reduced cancer-associated fibroblasts, which was convinced by immune signatures analysis via ssGSEA algorithm. T helper/IFNγ signaling, co-stimulatory, and co-inhibitory signatures showed increased expression in the low-risk group. Low-risk patients were predicted to be beneficial to immunotherapy, which was confirmed by patients with progressive disease who had high risk scores vs. complete remission patients. Furthermore, the drugs that might be sensitive to HNSCC were identified. In summary, the novel prognostic GILncRNA signature provided a promising approach for characterizing the TIME and predicting therapeutic strategies for HNSCC patients.
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    Immunogenomic classification of lung squamous cell carcinoma characterizes tumor immune microenvironment and predicts cancer therapy
    (Elsevier, 2023-03-28) Fu, Denggang; Zhang, Biyu; Zhang, Yinghua; Feng, Jueping; Jiang, Hua; Medicine, School of Medicine
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    Molecular subtyping of acute myeloid leukemia through ferroptosis signatures predicts prognosis and deciphers the immune microenvironment
    (Frontiers Media, 2023-08-24) Fu, Denggang; Zhang, Biyu; Wu, Shiyong; Feng, Jueping; Jiang, Hua; Pediatrics, School of Medicine
    Acute myeloid leukemia (AML) is one of the most aggressive hematological malignancies with a low 5-year survival rate and high rate of relapse. Developing more efficient therapies is an urgent need for AML treatment. Accumulating evidence showed that ferroptosis, an iron-dependent form of programmed cell death, is closely correlated with cancer initiation and clinical outcome through reshaping the tumor microenvironment. However, understanding of AML heterogeneity based on extensive profiling of ferroptosis signatures remains to be investigated yet. Herein, five independent AML transcriptomic datasets (TCGA-AML, GSE37642, GSE12417, GSE10358, and GSE106291) were obtained from the GEO and TCGA databases. Then, we identified two ferroptosis-related molecular subtypes (C1 and C2) with distinct prognosis and tumor immune microenvironment (TIME) by consensus clustering. Patients in the C1 subtype were associated with favorable clinical outcomes and increased cytotoxic immune cell infiltration, including CD8+/central memory T cells, natural killer (NK) cells, and non-regulatory CD4+ T cells while showing decreased suppressive immune subsets such as M2 macrophages, neutrophils, and monocytes. Functional enrichment analysis of differentially expressed genes (DEGs) implied that cell activation involved in immune response, leukocyte cell–cell adhesion and migration, and cytokine production were the main biological processes. Phagosome, antigen processing and presentation, cytokine–cytokine receptor interaction, B-cell receptor, and chemokine were identified as the major pathways. To seize the distinct landscape in C1 vs. C2 subtypes, a 5-gene prognostic signature (LSP1, IL1R2, MPO, CRIP1, and SLC24A3) was developed using LASSO Cox stepwise regression analysis and further validated in independent AML cohorts. Patients were divided into high- and low-risk groups, and decreased survival rates were observed in high- vs. low-risk groups. The TIME between high- and low-risk groups has a similar scenery in C1 vs. C2 subtypes. Single-cell-level analysis verified that LSP1 and CRIP1 were upregulated in AML and exhausted CD8+ T cells. Dual targeting of these two markers might present a promising immunotherapeutic for AML. In addition, potential effective chemical drugs for AML were predicted. Thus, we concluded that molecular subtyping using ferroptosis signatures could characterize the TIME and provide implications for monitoring clinical outcomes and predicting novel therapies.
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    Prognosis and Characterization of Immune Microenvironment in Acute Myeloid Leukemia Through Identification of an Autophagy-Related Signature
    (Frontiers, 2021) Fu, Denggang; Zhang, Biyu; Wu, Shiyong; Zhang, Yinghua; Xie, Jingwu; Ning, Wangbin; Jiang, Hua; Pediatrics, School of Medicine
    Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.
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    Validated graft-specific biomarkers identify patients at risk for chronic graft-versus-host disease and death
    (The American Society for Clinical Investigation, 2023-08-01) Logan, Brent R.; Fu, Denggang; Howard, Alan; Fei, Mingwei; Kou, Jianqun; Little, Morgan R.; Adom, Djamilatou; Mohamed, Fathima A.; Blazar, Bruce R.; Gafken, Philip R.; Paczesny, Sophie; Pediatrics, School of Medicine
    BACKGROUND: Chronic graft-versus-host disease (cGVHD) is a serious complication of allogeneic hematopoietic cell transplantation (HCT). More accurate information regarding the risk of developing cGVHD is required. Bone marrow (BM) grafts contribute to lower cGVHD, which creates a dispute over whether risk biomarker scores should be used for peripheral blood (PB) and BM. METHODS: Day 90 plasma proteomics from PB and BM recipients developing cGVHD revealed 5 risk markers that were added to 8 previous cGVHD markers to screen 982 HCT samples of 2 multicenter Blood and Marrow Transplant Clinical Trials Network (BMTCTN) cohorts. Each marker was tested for its association with cause-specific hazard ratios (HRs) of cGVHD using Cox-proportional-hazards models. We paired these clinical studies with biomarker measurements in a mouse model of cGVHD. RESULTS: Spearman correlations between DKK3 and MMP3 were significant in both cohorts. In BMTCTN 0201 multivariate analyses, PB recipients with 1-log increase in CXCL9 and DKK3 were 1.3 times (95% CI: 1.1–1.4, P = 0.001) and 1.9 times (95%CI: 1.1–3.2, P = 0.019) and BM recipients with 1-log increase in CXCL10 and MMP3 were 1.3 times (95%CI: 1.0–1.6, P = 0.018 and P = 0.023) more likely to develop cGVHD. In BMTCTN 1202, PB patients with high CXCL9 and MMP3 were 1.1 times (95%CI: 1.0–1.2, P = 0.037) and 1.2 times (95%CI: 1.0–1.3, P = 0.009) more likely to develop cGVHD. PB patients with high biomarkers had increased likelihood to develop cGVHD in both cohorts (22%–32% versus 8%–12%, P = 0.002 and P < 0.001, respectively). Mice showed elevated circulating biomarkers before the signs of cGVHD. CONCLUSION: Biomarker levels at 3 months after HCT identify patients at risk for cGVHD occurrence.