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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes.

ABSTRACT: Medulloblastoma, a common pediatric malignant tumor, has been recognized to have four molecular subgroups [wingless (WNT), sonic hedgehog (SHH), group 3, group 4], which are defined by the characteristic gene transcriptomic and DNA methylomic profiles, and has distinct clinical features within each subgroup. The tumor immune microenvironment is integral in tumor initiation and progression and might be associated with therapeutic responses. However, to date, the immune infiltrative landscape of medulloblastoma has not yet been elucidated. Thus, we proposed MethylCIBERSORT to estimate the degree of immune cell infiltration and weighted correlation network analysis (WGCNA) to find modules of highly correlated genes. Synthesizing the hub genes in the protein-protein interaction (PPI) network and modules of the co-expression network, we identify three candidate biomarkers [GRB2-associated-binding protein 1 (GAB1), Abelson 1 (ABL1), and CXC motif chemokine receptor type 4 (CXCR4)] via the molecular profiles of medulloblastoma. Given this, we investigated the correlation between these three immune hub genes and immune checkpoint blockade response and the potential of drug prediction further. In addition, this study demonstrated a higher presence of endothelial cells and infiltrating immune cells in Group 3 tumor bulk. The above results will be conducive to better comprehending the immune-related pathogenesis and treatment of medulloblastoma.

SUBMITTER: Chen J

PROVIDER: S-EPMC9367478 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes.

Chen Jinyi J Kang Zhuang Z Li Shenglan S Wang Can C Zheng Xiaohong X Cai Zehao Z Pan Lexin L Chen Feng F Li Wenbin W

Frontiers in immunology 20220728

Medulloblastoma, a common pediatric malignant tumor, has been recognized to have four molecular subgroups [wingless (WNT), sonic hedgehog (SHH), group 3, group 4], which are defined by the characteristic gene transcriptomic and DNA methylomic profiles, and has distinct clinical features within each subgroup. The tumor immune microenvironment is integral in tumor initiation and progression and might be associated with therapeutic responses. However, to date, the immune infiltrative landscape of m ...[more]

PMID: 35967388

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Project description:BackgroundFerroptosis is associated with the development of many cancers; the molecular features of colorectal carcinoma (CRC) based on ferroptosis-related genes (FRGs) remain unknown. Herein, we aimed to identify ferroptosis-associated molecular subtypes of CRC based on the expression profiles of FRGs.MethodsTo explore ferroptosis-associated subtypes of CRC, the gene expression data and clinical information of 682 patients were extracted from The Cancer Genome Atlas and Gene Expression Omnibus databases. We performed consensus clustering to identify robust clusters of patients. Then the distribution of the subtypes in terms of prognosis significance, transcriptome features, immune microenvironment, drug sensitivity, gene mutations, and copy number alternations (CNAs) were evaluated respectively. In addition, we analyzed the correlation of these ferroptosis-associated molecular subtypes with the distribution of conventional clinical indicators in CRC.ResultsFour subtypes of CRC (C1, C2, C3, and C4) were identified in which the prognosis, immune cell infiltration, immune score, stromal score, and tumor purity were significantly different between the four subtypes. The C3 subtype had a higher infiltration of B cells, M2 macrophages, resting mast cells, monocytes, natural killer cells, plasma cells, and CD8 T cells. The C3 subtype had the highest immune and stromal scores and the lowest tumor purity. In contrast, the C4 subtype demonstrated the lowest immune and stromal scores and the highest tumor purity. Programmed cell death ligand 1 (PD-L1), an immune checkpoint protein, was differentially expressed in the four subtypes (P < 2e-16) and was significantly correlated with the expression of several FRGs in all subtypes. Significant differences in stem cell indices (P < 0.01) and drug sensitivity (P < 0.01) were observed in the four subtypes. Additionally, gene mutations analysis showed that FRGs such as TP53 had a high frequency of mutation in the four subtypes (49%, 62%, 61%, and 71%, respectively), and the CNAs showed significant difference among all subtypes (P < 0.001).ConclusionIn summary, the ferroptosis-associated subtypes could serve as an independent biomarker for estimating oncological outcomes in patients with CRC. Our results demonstrated that the high level of heterogeneity in the expression of FRGs might be useful for the stratification of patients with CRC and the implementation of individualized therapeutic strategies.

Project description:BackgroundPorcine seminal plasma (SP) is endowed with a heterogeneous population of extracellular vesicles (sEVs). This study evaluated the immunophenotypic profile by high-sensitivity flow cytometry of eight sEV subpopulations isolated according to their size (small [S-sEVs] and large [L-sEVs]) from four different SP sources, namely three ejaculate fractions (the first 10 mL of the sperm rich fraction [SRF-P1], the remaining SRF [SRF-P2], and the post-SRF [PSRF]) and entire ejaculate (EE).MethodsSeminal EVs were isolated using a size exclusion chromatography-based protocol from six SP pools (five ejaculates/pool) of each SP source and characterized using complementary approaches including total protein (BCA™assay), particle size distribution (dynamic light scattering), morphology (transmission electron microscopy), and purity (albumin by Western blot). Expression of CD9, CD63, CD81, CD44 and HSP90β was analyzed in all sEV subpopulations by high-sensitivity flow cytometry according to MIFlowCyt-EV guidelines, including an accurate calibration, controls, and discrimination by CFSE-labelling.ResultsEach sEV subpopulation exhibited a specific immunophenotypic profile. The percentage of sEVs positive for CD9, CD63, CD81 and HSP90β differed between S- and L-sEVs (P < 0.0001). Specifically, the percentage of sEVs positive for CD9 and CD63 was higher and that for CD81 was lower in S- than L-sEVs in the four SP sources. However, the percentage of HSP90β-positive sEVs was lower in S-sEVs than L-sEVs in the SRF-P1 and EE samples. The percentage of sEVs positive for CD9, CD63, and CD44 also differed among the four SP sources (P < 0.0001), being highest in PSRF samples. Notably, virtually all sEV subpopulations expressed CD44 (range: 88.04-98.50%).ConclusionsThis study demonstrated the utility of high-sensitivity flow cytometry for sEV immunophenotyping, allowing the identification of distinct sEV subpopulations that may have different cellular origin, cargo, functions, and target cells.

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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes.

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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes.

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