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Comprehensive omics analyses profile genesets related with tumor heterogeneity of multifocal glioblastomas and reveal LIF/CCL2 as biomarkers for mesenchymal subtype.

ABSTRACT: Rationale: Around 10%-20% patients with glioblastoma (GBM) are diagnosed with more than one tumor lesions or multifocal GBM (mGBM). However, the understanding on genetic, DNA methylomic, and transcriptomic characteristics of mGBM is still limited. Methods: In this study, we collected nine tumor foci from three mGBM patients followed by whole genome sequencing, whole genome bisulfite sequencing, RNA sequencing, and immunohistochemistry. The data were further examined using public GBM databases and GBM cell line. Results: Analysis on genetic data confirmed common features of GBM, including gain of chr.7 and loss of chr.10, loss of critical tumor suppressors, high frequency of PDGFA and EGFR amplification. Through profiling DNA methylome of individual tumor foci, we found that promoter methylation status of genes involved in detection of chemical stimulus, immune response, and Hippo/YAP1 pathway was significantly changed in mGBM. Although both CNV and promoter methylation alteration were involved in heterogeneity of different tumor foci from same patients, more CNV events than promoter hypomethylation events were shared by different tumor foci, implying CNV were relatively earlier than promoter methylation alteration during evolution of different tumor foci from same mGBM. Moreover, different tumor foci from same mGBM assumed different molecular subtypes and mesenchymal subtype was prevalent in mGBM, which might explain the worse prognosis of mGBM than single GBM. Interestingly, we noticed that LIF and CCL2 was tightly correlated with mesenchymal subtype tumor focus in mGBM and predicted poor survival of GBM patients. Treatment with LIF and CCL2 produced mesenchymal-like transcriptome in GBM cells. Conclusions: Together, our work herein comprehensively profiled multi-omics features of mGBM and emphasized that components of extracellular microenvironment, such as LIF and CCL2, contributed to the evolution and prognosis of tumor foci in mGBM patients.

SUBMITTER: Lv SQ

PROVIDER: S-EPMC8690928 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND AND PURPOSE:Multifocal glioblastomas (ie, glioblastomas with multiple foci, unconnected in postcontrast pretreatment T1-weighted images) represent a challenge in clinical practice due to their poor prognosis. We wished to obtain imaging biomarkers with prognostic value that have not been found previously. MATERIALS AND METHODS:A retrospective review of 1155 patients with glioblastomas from 10 local institutions during 2006-2017 provided 97 patients satisfying the inclusion criteria of the study and classified as having multifocal glioblastomas. Tumors were segmented and morphologic features were computed using different methodologies: 1) measured on the largest focus, 2) aggregating the different foci as a whole, and 3) recording the extreme value obtained for each focus. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell concordance indices (c-indices) were used for the statistical analysis. RESULTS:Age (P < .001, hazard ratio = 2.11, c-index = 0.705), surgery (P < .001, hazard ratio = 2.04, c-index = 0.712), contrast-enhancing rim width (P < .001, hazard ratio = 2.15, c-index = 0.704), and surface regularity (P = .021, hazard ratio = 1.66, c-index = 0.639) measured on the largest focus were significant independent predictors of survival. Maximum contrast-enhancing rim width (P = .002, hazard ratio = 2.05, c-index = 0.668) and minimal surface regularity (P = .036, hazard ratio = 1.64, c-index = 0.600) were also significant. A multivariate model using age, surgery, and contrast-enhancing rim width measured on the largest foci classified multifocal glioblastomas into groups with different outcomes (P < .001, hazard ratio = 3.00, c-index = 0.853, median survival difference = 10.55 months). Moreover, quartiles with the highest and lowest individual prognostic scores based on the focus with the largest volume and surgery were identified as extreme groups in terms of survival (P < .001, hazard ratio = 18.67, c-index = 0.967). CONCLUSIONS:A prognostic model incorporating imaging findings on pretreatment postcontrast T1-weighted MRI classified patients with glioblastoma into different prognostic groups.

Project description:BackgroundCommercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality.MethodsWe designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared.ResultsDerived expression scores were positively correlated with tumor grade (rS = 0.53-0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ?GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (?GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05).ConclusionsMultifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease.FundingProstate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

Project description:BackgroundOmicron variant impacts populations with its rapid contagiousness, and part of patients suffered from persistent symptoms termed as long COVID. The molecular and immune mechanisms of this currently dominant global variant leading to long COVID remain unclear, due to long COVID heterogeneity across populations.MethodsWe recruited 66 participants in total, 22 out of 66 were healthy control without COVID-19 infection history, and 22 complaining about long COVID symptoms 6 months after first infection of Omicron, referred as long COVID (LC) Group. The left ones were defined as non-long COVID (NLC) Group. We profiled them via plasma neutralizing antibody titer, SARS-CoV-2 viral load, transcriptomic and proteomics screening, and machine learning.ResultsNo serum residual SARS-CoV-2 was observed in the participants 6 months post COVID-19 infection. No significant difference in neutralizing antibody titers was found between the long COVID (LC) Group and the non-long COVID (NLC) Group. Transcriptomic and proteomic profiling allow the stratification of long COVID into neutrophil function upregulated (NU-LC) and downregulated types (ND-LC). The NU-LC, identifiable through a refined set of 5 blood gene markers (ABCA13, CEACAM6, CRISP3, CTSG and BPI), displays evidence of relatively higher neutrophil counts and function of degranulation than the ND-LC at 6 months after infection, while recovered at 12 months post COVID-19.ConclusionThe transcriptomic and proteomic profiling revealed heterogeneity among long COVID patients. We discovered a subgroup of long COVID population characterized by neutrophil activation, which might associate with the development of psychiatric symptoms and indicate a higher inflammatory state. Meanwhile, a cluster of 5 genes was manually curated as the most potent discriminators of NU-LC from long COVID population. This study can serve as a foundational exploration of the heterogeneity in the pathogenesis of long COVID and assist in therapeutic targeting and detailed epidemiological investigation of long COVID.

Project description:BackgroundHepatocellular carcinoma (HCC) often presents with multiple nodules within the liver, with limited effective interventions. The high genetic heterogeneity of HCC might be the major cause of treatment failure. We aimed to characterize genomic heterogeneity, infer clonal evolution, investigate RNA expression pattern and explore tumour immune microenvironment profile of multifocal HCC.Patients and methodsWhole-exome sequencing and RNA sequencing were carried out in 34 tumours and 6 adjacent normal liver tissue samples from 6 multifocal HCC patients. Protein expression of Ki67, AFP, P53, Survivin and CD8 was detected by immunohistochemistry. Fluorescence in situ hybridization was carried out to validate the amplification status of sorafenib-targeted genes.ResultsWe deciphered genomic and transcriptional heterogeneity among tumours in each multifocal HCC patient including mutational profiles, copy number alterations, tumour evolutionary trajectory and tumour immune microenvironment profiles. Of note, sorafenib-targeted alterations were identified in the trunk of phylogenetic tree in only one out of the six patients, which may explain the relative low treatment response rate to sorafenib in clinical practice. Moreover, we demonstrated RNA expression patterns and tumour immune microenvironment profiles of all nodules. We found that RNA expression pattern was associated with Edmondson-Steiner grading. Based on the differential expression of 66 reported immune markers, unsupervised hierarchical clustering analysis of 34 nodules identified immune subsets: one low expression cluster with seven nodules and one high expression cluster with 11 nodules. CD8+ T cells were more enriched in nodules of the high expression cluster.ConclusionsOur study provided a detailed view of genomic and transcriptional heterogeneity, clonal evolution and immune infiltration of multifocal HCC. The heterogeneity of druggable targets and immune landscape might help interpret the clinical responsiveness to targeted drugs and immunotherapy for multifocal HCC patients.

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Comprehensive omics analyses profile genesets related with tumor heterogeneity of multifocal glioblastomas and reveal LIF/CCL2 as biomarkers for mesenchymal subtype.

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