Shugosin 2 is a biomarker for pathological grading and survival prediction in patients with gliomas.
Ontology highlight
ABSTRACT:
SUBMITTER: Kao Y
PROVIDER: S-EPMC8448842 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Primary high-grade gliomas possess invasive growth and lead to unfavorable survival outcome. The investigation of biomarkers for prediction of survival outcome in patients with gliomas is important for clinical assessment. The DEAD (Asp-Glu-Ala-Asp) box helicase 3, X-linked (DDX3X) controls tumor migration, proliferation, and progression. However, the role of DDX3X in defining the pathological grading and survival outcome in patients with human gliomas is not yet clarified. We analyzed the DDX3X gene expression, WHO pathological grading, and overall survival from de-linked data. Further validation was done using quantitative RT-PCR of cDNA from normal brain and glioma, and immunohistochemical (IHC) staining of tissue microarray. Statistical analysis of GEO datasets showed that DDX3X mRNA expression demonstrated statistically higher in WHO grade IV (n = 81) than in non-tumor controls (n = 23, p = 1.13 × 10(-10)). Moreover, DDX3X level was also higher in WHO grade III (n = 19) than in non-tumor controls (p = 2.43 × 10(-5)). Kaplan-Meier survival analysis showed poor survival in patients with high DDX3X mRNA levels (n = 24) than in those with low DDX3X expression (n = 53) (median survival, 115 vs. 58 weeks, p = 0.0009, by log-rank test, hazard ratio: 0.3507, 95% CI: 0.1893-0.6496). Furthermore, DDX3X mRNA expression and protein production significantly increased in glioma cells compared with normal brain tissue examined by quantitative RT-PCR, and Western blot. IHC staining showed highly staining of high-grade glioma in comparison with normal brain tissue. Taken together, DDX3X expression level positively correlates with WHO pathologic grading and poor survival outcome, indicating that DDX3X is a valuable biomarker in human gliomas.
| S-EPMC4519914 | biostudies-literature
Project description:MotivationOnline assessment of tumor characteristics during surgery is important and has the potential to establish an intra-operative surgeon feedback mechanism. With the availability of such feedback, surgeons could decide to be more liberal or conservative regarding the resection of the tumor. While there are methods to perform metabolomics-based tumor pathology prediction, their model complexity predictive performance is limited by the small dataset sizes. Furthermore, the information conveyed by the feedback provided on the tumor tissue could be improved both in terms of content and accuracy.ResultsIn this study, we propose a metabolic pathway-informed deep learning model (PiDeeL) to perform survival analysis and pathology assessment based on metabolite concentrations. We show that incorporating pathway information into the model architecture substantially reduces parameter complexity and achieves better survival analysis and pathological classification performance. With these design decisions, we show that PiDeeL improves tumor pathology prediction performance of the state-of-the-art in terms of the Area Under the ROC Curve by 3.38% and the Area Under the Precision-Recall Curve by 4.06%. Similarly, with respect to the time-dependent concordance index (c-index), PiDeeL achieves better survival analysis performance (improvement of 4.3%) when compared to the state-of-the-art. Moreover, we show that importance analyses performed on input metabolite features as well as pathway-specific neurons of PiDeeL provide insights into tumor metabolism. We foresee that the use of this model in the surgery room will help surgeons adjust the surgery plan on the fly and will result in better prognosis estimates tailored to surgical procedures.Availability and implementationThe code is released at https://github.com/ciceklab/PiDeeL. The data used in this study are released at https://zenodo.org/record/7228791.
| S-EPMC10663986 | biostudies-literature
Project description:Pediatric high-grade gliomas (HGG) are rare aggressive tumors that present a prognostic and therapeutic challenge. Diffuse midline glioma, H3K27M-mutant is a new entity introduced to HGG in the latest WHO classification. In this study we evaluated the presence of H3K27M mutation in 105 tumor samples histologically classified into low-grade gliomas (LGG) (n?=?45), and HGG (n?=?60). Samples were screened for the mutation in histone H3.3 and H3.1 variants to examine its prevalence, prognostic impact, and assess its potential clinical value in limited resource settings. H3K27M mutation was detected in 28 of 105 (26.7%) samples, and its distribution was significantly associated with midline locations (p-value?<?0.0001) and HGG (p-value?=?0.003). Overall and event- free survival (OS and EFS, respectively) of patients with mutant tumors did not differ significantly, neither according to histologic grade (OS p-value?=?0.736, EFS p-value?=?0.75) nor across anatomical sites (OS p-value?=?0.068, EFS p-value?=?0.153). Detection of H3K27M mutation in pediatric gliomas provides more precise risk stratification compared to traditional histopathological techniques. Hence, mutation detection should be pursued in all pediatric gliomas. Meanwhile, focusing on midline LGG can be an alternative in lower-middle-income countries to maximally optimize patients' treatment options.
| S-EPMC7239884 | biostudies-literature
Project description:There is no consensus agreement regarding optimal management of locally excised ductal carcinoma in situ (DCIS) or features of greatest assistance in predicting disease behaviour. Cases in the UKCCCR/ANZ DCIS trial have been histologically reviewed to determine the features of prognostic importance.A total of 72% of 1694 cases entered into the UKCCCR/ANZ DCIS trial had full pathological review. A large number of histological features were assessed, blinded to outcome and compared regarding ability to predict ipsilateral recurrence, as either DCIS or progression to invasive carcinoma.Pathological features associated with ipsilateral recurrence in univariate analysis included high cytonuclear grade, larger lesion size, growth pattern, presence of necrosis or chronic inflammation, incompleteness (or uncertainty of completeness) of excision and smaller margin width. Receipt of post-operative radiotherapy was also a strong prognostic factor.We report a novel sub-division of the large group of high-grade lesions, which enables identification of a very poor prognosis sub-group; namely, DCIS that is of high cytonuclear grade, predominantly (>50%) solid architecture, bearing extensive comedo-type necrosis (>50% of ducts). In addition, we found little difference in ipsilateral recurrence rates between low- and intermediate-grade groups. Hazard ratios for low, intermediate, high and the new, very high, grade were 0.42, 0.33, 0.62 and 1.00, respectively, for ipsilateral in situ or invasive recurrence.We present a novel pathological classification for DCIS with substantially better prognostic discrimination for ipsilateral recurrence than the classical categorisation based on cytonuclear grade alone.
| S-EPMC2905282 | biostudies-other
Project description:The 2021 WHO Classification of Central Nervous System Tumors recommended evaluation of cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletion in addition to codeletion of 1p/19q to characterize IDH-mutant gliomas. Here, we demonstrated the use of a nanopore-based copy-number variation sequencing (nCNV-seq) approach to simultaneously identify deletions of CDKN2A/B and 1p/19q. The nCNV-seq approach was initially evaluated on three distinct glioma cell lines and then applied to 19 IDH-mutant gliomas (8 astrocytomas and 11 oligodendrogliomas) from patients. The whole-arm 1p/19q codeletion was detected in all oligodendrogliomas with high concordance among nCNV-seq, FISH, DNA methylation profiling, and whole-genome sequencing. For the CDKN2A/B deletion, nCNV-seq detected the loss in both astrocytoma and oligodendroglioma, with strong correlation with the CNV profiles derived from whole-genome sequencing (Pearson correlation (r) = 0.95, P < 2.2 × 10-16 to r = 0.99, P < 2.2 × 10-16 ) and methylome profiling. Furthermore, nCNV-seq can differentiate between homozygous and hemizygous deletions of CDKN2A/B. Taken together, nCNV-seq holds promise as a new, alternative approach for a rapid and simultaneous detection of the molecular signatures of IDH-mutant gliomas without capital expenditure for a sequencer.
| S-EPMC10711254 | biostudies-literature
Project description:PurposeTo develop a predictive grading model based on diffusion kurtosis imaging (DKI) metrics in children affected by gliomas, and to investigate the clinical impact of the predictive model by correlating with overall survival and progression-free survival.Materials and methods59 patients with a histological diagnosis of glioma were retrospectively studied (33 M, 26 F, median age 7.2 years). Patients were studied on a 3T scanner with a standardized MR protocol, including conventional and DKI sequences. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) maps were obtained. Whole tumour volumes (VOIs) were segmented semi-automatically. Mean DKI values were calculated for each metric. The quantitative values from DKI-derived metrics were used to develop a predictive grading model to develop a probability prediction of a high-grade glioma (pHGG). Three models were tested: DTI-based, DKI-based, and combined (DTI and DKI). The grading accuracy of the resulting probabilities was tested with a receiver operating characteristics (ROC) analysis for each model. In order to account for dataset imbalances between pLGG and pHGG, we applied a random synthetic minority oversampling technique (SMOTE) analysis. Lastly, the most accurate model predictions were correlated with progression-free survival (PFS) and overall survival (OS) using the Kaplan-Meier method.ResultsThe cohort included 46 patients with pLGG and 13 patients with pHGG. The developed model predictions yielded an AUC of 0.859 (95%CI: 0.752-0.966) for the DTI model, of 0.939 (95%CI: 0.879-1) for the DKI model, and of 0.946 (95%CI: 0.890-1) for the combined model, including input from both DTI and DKI metrics, which resulted in the most accurate model. Sample estimation with the random SMOTE analysis yielded an AUC of 0.98 on the testing set. Model predictions from the combined model were significantly correlated with PFS (25.2 months for pHGG vs. 40.0 months for pLGG, p < 0.001) and OS (28.9 months for pHGG vs. 44.9 months for pLGG, p < 0.001).Conclusionsa DKI-based predictive model was highly accurate for pediatric glioma grading. The combined model, derived from both DTI and DKI metrics, proved that DKI-based model predictions of tumour grade were significantly correlated with progression-free survival and overall survival.
| S-EPMC9563289 | biostudies-literature
Project description:BackgroundPerineural invasion has been found in several types of human tumors, and is associated with poor prognosis; however, few studies have examined perineural invasion in lung cancer. We evaluated the relationship between autonomic nervous densities, pathological risk grading, and prognosis in patients with lung adenocarcinoma (LADC).MethodsNeural fiber expression was examined by immunofluorescence in resected lung specimens in control patients (n = 30), and low-risk (n = 22), and high-risk LADC patients (n = 43). The nerve densities of normal lung tissue and abnormal lung tissues in the tumor and surrounding tissues were evaluated by a semi-quantitative score method.ResultsIncreased sympathetic fibers mainly infiltrated the paratumoral area, while increased parasympathetic fibers were largely restricted to the tumor (paratumor vs. tumor, P = 0.000 in high, P = 0.034 in low; each). In addition, high-risk patients presented the highest density of neural fibers, followed by low-risk and control patients ( P = 0.000; each). In Kaplan-Meier survival analysis, the densities of sympathetic fibers in paratumoral tissue and parasympathetic fibers in the tumor, respectively, correlated with poor recurrence-free survival in patients who were not treated with adjuvant therapy ( P < 0.001; each). Further multivariate analysis showed that these two factors were associated with poor prognosis in all LADC patients ( P = 0.024 sympathetic fibers; P = 0.037 parasympathetic fibers).ConclusionThese findings reveal a positive correlation between nervous infiltration and risk of poor prognosis in patients with LADC.
| S-EPMC5193011 | biostudies-literature
Project description:BackgroundDiffuse gliomas, grades II and III, hereafter called lower-grade gliomas (LGG), have variable, difficult to predict clinical courses, resulting in multiple studies to identify prognostic biomarkers. The purpose of this study was to assess expression or methylation of the homeobox family gene SHOX2 as independent markers for LGG survival.MethodsWe downloaded publically available glioma datasets for gene expression and methylation. The Cancer Genome Atlas (TCGA) (LGG, n=516) was used as a training set, and three other expression datasets (n=308) and three other methylation datasets (n=320), were used for validation. We performed Kaplan-Meier survival curves and univariate and multivariate Cox regression model analyses.FindingsSHOX2 expression and gene body methylation varied among LGG patients and highly significantly predicted poor overall survival. While they were tightly correlated, SHOX2 expression appeared more potent as a prognostic marker and was used for most further studies. The SHOX2 prognostic roles were maintained after analyses by histology subtypes or tumor grade. We found that the combination of SHOX2 expression and IDH genotype status identified a subset of LGG patients with IDH wild-type (IDHwt) and low SHOX2 expression with considerably favorable survival. We further investigated the combination of SHOX2 with other known clinically relevant markers of LGG (TERT expression, 1p/19q chromosome co-deletion, MGMT methylation, ATRX mutation and NES expression). When combined with SHOX2 expression, we identified subsets of LGG patients with significantly favorable survival outcomes, especially in the subgroup with worse prognosis for each individual marker. Finally, multivariate analysis demonstrated that SHOX2 was a potent independent survival marker.InterpretationWe have identified that SHOX2 expression or methylation are potent independent prognostic indicators for predicting LGG patient survival, and have potential to identify an important subset of LGG patients with IDHwt status with significantly better overall survival. The combination of IDH or other relevant markers with SHOX2 identified LGG subsets with significantly different survival outcomes, and further understanding of these subsets may benefit therapeutic target identification and therapy selections for glioma patients.
| S-EPMC5264450 | biostudies-literature
Project description:Introduction: Consistent association between elevated baseline serum values and C-reactive protein (CRP), cross-linked fibrin degradation products (D-dimer), lactate dehydrogenase (LDH), decreased baseline serum albumin, absolute lymphocyte count to absolute monocyte count ratio (LMR), elevated absolute neutrophil count to absolute lymphocyte count ratio (NLR), elevated platelet count to absolute lymphocyte count ratio (PLR), and between some combinations of these biomarkers and the short overall survival of patients with malignant diseases has already been reported. These biomarkers are independent prognostic factors for cancer. Here, the most significant biomarker combination of these values was searched and studied in real-life advanced cancer patients of a single center. Methods: The authors retrospectively analyzed the association of the aforementioned biomarkers and their combination and OS of 75 consecutive cancer patients with locally advanced, recurrent, or metastatic diseases. Validated cut-off determination was used. Results: CRP, albumin, and PLR showed marked association with OS. Cut-off values for significant shorter OS were 30.65 mg/L (p < 0.001), 44.35 g/L (p < 0.001), and 168.20 (p < 0.001), respectively. Based on assessed biomarker cut-offs, four patient groups were created to determine whether biomarker values were out of range (ORV) compared to cut-off: 1) No ORV biomarkers (n = 24; OS = 26.07 months); 2) one ORV biomarker (n = 21; OS = 13.50 months); 3) two ORV biomarkers (n = 20; OS = 7.97 months), and 4) three ORV biomarkers (n = 10; OS = 3.91 months). Significant differences in OS were detected between the groups: For 1. vs. 2. hazard ratio (HR) = 3.0 (95% CI: 1.5-6.2), p = 0.003; for 1. vs. 3. HR = 4.1 (95% CI: 2.0-8.3), p < 0.001; and for 1. vs. 4. HR = 10.2 (95% CI: 4.2-24.6), p < 0.001. Conclusion: Based on our analysis, we can confirm that the complex monitoring of CRP, albumin, and PLR would provide a good estimation of OS. Large scale prospective studies are warranted to explore this and other useful combinations of prognostic biomarkers and their relationship to the well-established prognostic systems in real-life.
| S-EPMC8842665 | biostudies-literature
Project description:BackgroundThe diffusion tensor image analysis along the perivascular space (DTI-ALPS) may have the potential to reflect glymphatic dysfunction in patients with glioma. The study aimed to determine the correlation of DTI-ALPS with glioma grade and isocitrate dehydrogenase 1 (IDH1) genotype and to then compare the ALPS index with other diffusion metrics.MethodsIn this study, 81 patients with glioma and 31 healthy controls underwent magnetic resonance imaging (MRI) examination. The ALPS-index, fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) were calculated. Comparisons were made between the left and right hemispheres and between patients and controls. IDH1 status was compared after age adjustment. The diagnostic performance of each metric was assessed via receiver operating characteristic (ROC) analysis.ResultsIn patients with glioma, the ALPS-index of the hemisphere ipsilateral to glioma was significantly lower than that of the hemisphere contralateral to glioma (1.417±0.177 vs. 1.478±0.165; P=0.002), and the bilateral ALPS-index values in patients were significantly decreased compared with those in healthy controls. The ALPS-index was significantly higher in lower-grade gliomas (LrGGs) than that in glioblastomas (GBMs) (1.495±0.151 vs. 1.320±0.159; P<0.001) and was significantly lower in IDH1-wild-type LrGGs than in IDH1-mutant LrGGs (1.400±0.185 vs. 1.530±0.123; P=0.036). FA, MD, and MK also showed significant differences between LrGGs and GBMs and between IDH1-mutant and IDH1-wild-type LrGGs (P<0.05). Furthermore, the combination of the ALPS-index with FA, MD, or MK, exhibited superior discrimination ability compared to each metric used alone. The ALPS-index combined with MD had the highest area under the curve (AUC) of 0.854 as compared to that of 0.614-0.807 for a single metric in glioma grading, while for IDH1 mutation prediction, this combination had the highest AUC of 0.861 as compared to that of 0.707-0.778 for a single metric.ConclusionsThe reduced ALPS-index may reflect tumor-induced glymphatic system impairment, and the ALPS-index may be able to complement conventional diffusion metrics in glioma grading and IDH1 genotyping.
| S-EPMC10721998 | biostudies-literature