scholarly journals Predicting Prognosis and IDH Mutation Status for Patients with Lower-Grade Gliomas Using Whole Slide Images

2021 ◽  
Author(s):  
Shuai Jiang ◽  
George J. Zanazzi ◽  
Saeed Hassanpour
Keyword(s):  
Performance Metrics ◽  
Small Sample Size ◽  
Small Sample ◽  
The Cancer Genome Atlas ◽  
World Health ◽  
Lower Grade ◽  
Who Grade ◽  
Mutation Status ◽  
Idh Mutations ◽  
Whole Slide Images

ABSTRACTWe developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the grade 3 gliomas TCGA dataset, which was not used for training, our models were able to predict survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas.

scholarly journals Predicting prognosis and IDH mutation status for patients with lower-grade gliomas using whole slide images

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shuai Jiang ◽  
George J. Zanazzi ◽  
Saeed Hassanpour
Keyword(s):  
Performance Metrics ◽  
Small Sample Size ◽  
Small Sample ◽  
The Cancer Genome Atlas ◽  
World Health ◽  
Lower Grade ◽  
Who Grade ◽  
Mutation Status ◽  
Idh Mutations ◽  
Whole Slide Images

AbstractWe developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the WHO grade 3 gliomas from the TCGA dataset, which were not used for training, our models predicted survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas.

scholarly journals BICD Cargo Adaptor 1 (BICD1) Downregulation Correlates with a Decreased Level of PD-L1 and Predicts a Favorable Prognosis in Patients with IDH1-Mutant Lower-Grade Gliomas

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 701
Author(s):  
Shang-Pen Huang ◽  
Chien-Hsiu Li ◽  
Wei-Min Chang ◽  
Yuan-Feng Lin
Keyword(s):  
The Cancer Genome Atlas ◽  
World Health ◽  
Egfr Mutations ◽  
Lower Grade ◽  
Karnofsky Performance Score ◽  
Wild Type ◽  
Who Grade ◽  
Favorable Prognosis ◽  
Potential Biomarker ◽  
Genome Atlas

Although several biomarkers have been identified to predict the prognosis of lower-grade (Grade II/III) gliomas (LGGs), we still need to identify new markers to facilitate those well-known markers to obtain more accurate prognosis prediction in LGGs. Bioinformatics data from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and the Cancer Cell Line Encyclopedia (CCLE) datasets were used as the research materials. In total, 34 genes associated with the HIF1A pathway were analyzed using the hierarchical method to search for the most compatible gene. The BICD cargo adaptor 1 (BICD1) gene (BICD1) was shown to be significantly correlated with The hypoxic inducible factor 1A (HIF1A) expression, the World Health Organization (WHO) grade, and IDH1 mutation status. In addition, BICD1 downregulation was significantly correlated with a higher Karnofsky performance score (KPS), IDH1/TP53/ATRX mutations, wild-type EGFR, and younger patient age in the enrolled LGG cohort. Moreover, BICD1 expression was significantly upregulated in wild-type IDH1 LGGs with EGFR mutations. Kaplan–Meier survival analysis revealed that BICD1 downregulation predicts a favorable overall survival (OS) in LGG patients, especially in those with IDH1 mutations. Intriguingly, we found a significant correlation between BICD1 downregulation and a decreased level of CD274, GSK3B, HGF, or STAT3 in LGGs. Our findings suggest that BICD1 downregulation could be a potential biomarker for a favorable prognosis of LGGs.

scholarly journals A COMPARATIVE CLINICAL STUDY ON JARA WITH RESPECT TO AGEING PROCESS WITH ASHWAGANDHA RASAYANA AND MATRA BASTI

2016 ◽  
Author(s):  
Singh Binod Kumar ◽  
Bharkher D.L
Keyword(s):  
Life Expectancy ◽  
Small Sample Size ◽  
Small Sample ◽  
The Body ◽  
World Health ◽  
Ageing Process ◽  
Health Security ◽  
Chief Complaints ◽  
Comparative Clinical Study ◽  
Later Phase

The problem of ageing is experienced by all the countries. According to World Health statistics the life expectancy of Nepalese people has risen from 58.91 years to 67.86 years (1996 to 2015). Ageing is emerging issue in Nepal as well as global. Its tempo is expected to be unexpectedly fast as mortality continues to decline and life expectancy continues to increase. Ayurveda the science of life has observed ageing as a Jara avastha, which is a later phase of life, it is natural, inevitable phenomenon, in which maximum decline of bodily elements that may become as major cause of disability and functional dependency requiring services that affect many sectors of economy, health, security, income, housing, transportation etc. Jara chikitsa has been mentioned as one independent Anga in Ashtanga Ayurveda where Rasayana therapy is capable to impede the ageing process and to delay the degenerative process in the body. In this study we measured the effectiveness of Ashwagandha rasayana and Matra basti and compared with the Ashwagandha Rasayan only in Jara avastha. A total of thirty elderly patients were selected and divided in two groups A and B, given them either Ashwagandha Rasayana with Matra basti or Ashwagandha rasayana in prescribed doses for 45 days. Changes in the subjective complaints, objective parameters of the patients and appearance of adverse events were also evaluated. Both the groups provided better results on the chief complaints But, comparison in between both the groups is insignificant, that may be due to small sample size.

scholarly journals Mitotic Index Thresholds Do Not Predict Clinical Outcome for IDH-Mutant Astrocytoma

2019 ◽  
Vol 78 (11) ◽  
pp. 1002-1010 ◽  
Author(s):  
Rebecca A Yoda ◽  
Troy Marxen ◽  
Lauren Longo ◽  
Chibawanye Ene ◽  
Hans-Georg Wirsching ◽  
...  
Keyword(s):  
Mitotic Activity ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Homozygous Deletion ◽  
World Health ◽  
Mitotic Figure ◽  
Lower Grade ◽  
Histological Grading ◽  
Who Grade ◽  
Diagnostic Uncertainty

Abstract Current histological grading recommendations for isocitrate dehydrogenase (IDH)-mutant astrocytoma are imprecise and not reliably predictive of patient outcome, while somatic copy number alterations are emerging as important prognostic biomarkers. One explanation for this relative underperformance of histological grading is that current criteria to distinguish World Health Organization (WHO) grade III anaplastic astrocytomas from lower-grade diffuse astrocytomas (WHO grade II) are vague (“increased mitotic activity”). This qualitative approach ensures diagnostic uncertainty and a broad “gray zone” where both diffuse and anaplastic designations can reasonably be assigned. Thus, we hypothesized that interobserver variability and lack of defined mitotic thresholds for IDH-mutant astrocytomas underlies poor predictive accuracy of current histologic grading approaches. To test this hypothesis, we quantified total mitotic figures and maximum mitotic activity per 10 high-powered fields in an institutional cohort of IDH-mutant astrocytomas. In our cohort, there was no mitotic activity threshold that was reflective of progression-free or overall survival (OS). Furthermore, in a multivariate Cox regression model consisting of mitotic activity, molecular markers, and clinical characteristics, only CDKN2A homozygous deletion was identified as a relevant variant for poor OS. We conclude that lack of defined mitotic figure thresholds may not contribute to underperformance of histological grading for IDH-mutant astrocytomas.

scholarly journals IDH mutation status is associated with distinct vascular gene expression signatures in lower-grade gliomas

2018 ◽  
Vol 20 (11) ◽  
pp. 1505-1516 ◽  
Author(s):  
Lei Zhang ◽  
Liqun He ◽  
Roberta Lugano ◽  
Kenney Roodakker ◽  
Michael Bergqvist ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endothelial Cells ◽  
Lower Grade ◽  
Idh Mutation ◽  
Wild Type ◽  
Who Grade ◽  
Mutation Status ◽  
Grade Ii ◽  
Grade Ii Glioma

Abstract Background Vascular gene expression patterns in lower-grade gliomas (LGGs; diffuse World Health Organization [WHO] grades II–III gliomas) have not been thoroughly investigated. The aim of this study was to molecularly characterize LGG vessels and determine if tumor isocitrate dehydrogenase (IDH) mutation status affects vascular phenotype. Methods Gene expression was analyzed using an in-house dataset derived from microdissected vessels and total tumor samples from human glioma in combination with expression data from 289 LGG samples available in the database of The Cancer Genome Atlas. Vascular protein expression was examined by immunohistochemistry in human brain tumor tissue microarrays (TMAs) representing WHO grades II–IV gliomas and nonmalignant brain samples. Regulation of gene expression was examined in primary endothelial cells in vitro. Results Gene expression analysis of WHO grade II glioma indicated an intermediate stage of vascular abnormality, less severe than that of glioblastoma vessels but distinct from normal vessels. Enhanced expression of laminin subunit alpha 4 (LAMA4) and angiopoietin 2 (ANGPT2) in WHO grade II glioma was confirmed by staining of human TMAs. IDH wild-type LGGs displayed a specific angiogenic gene expression signature, including upregulation of ANGPT2 and serpin family H (SERPINH1), connected to enhanced endothelial cell migration and matrix remodeling. Transcription factor analysis indicated increased transforming growth factor beta (TGFβ) and hypoxia signaling in IDH wild-type LGGs. A subset of genes specifically induced in IDH wild-type LGG vessels was upregulated by stimulation of endothelial cells with TGFβ2, vascular endothelial growth factor, or cobalt chloride in vitro. Conclusion IDH wild-type LGG vessels are molecularly distinct from the vasculature of IDH-mutated LGGs. TGFβ and hypoxia-related signaling pathways may be potential targets for anti-angiogenic therapy of IDH wild-type LGG.

scholarly journals MLW-gcForest: A Multi-Weighted gcForest Model for Cancer Subtype Classification by Methylation Data

2019 ◽  
Vol 9 (17) ◽  
pp. 3589 ◽  
Author(s):  
Yunyun Dong ◽  
Wenkai Yang ◽  
Jiawen Wang ◽  
Juanjuan Zhao ◽  
Yan Qiang
Keyword(s):  
Machine Learning ◽  
Small Sample Size ◽  
Small Sample ◽  
The Cancer Genome Atlas ◽  
High Dimensionality ◽  
Methylation Data ◽  
Learning Methods ◽  
Cancer Subtypes ◽  
Machine Learning Methods

Effective cancer treatment requires a clear subtype. Due to the small sample size, high dimensionality, and class imbalances of cancer gene data, classifying cancer subtypes by traditional machine learning methods remains challenging. The gcForest algorithm is a combination of machine learning methods and a deep neural network and has been indicated to achieve better classification of small samples of data. However, the gcForest algorithm still faces many challenges when this method is applied to the classification of cancer subtypes. In this paper, we propose an improved gcForest algorithm (MLW-gcForest) to study the applicability of this method to the small sample sizes, high dimensionality, and class imbalances of genetic data. The main contributions of this algorithm are as follows: (1) Different weights are assigned to different random forests according to the classification ability of the forests. (2) We propose a sorting optimization algorithm that assigns different weights to the feature vectors generated under different sliding windows. The MLW-gcForest model is trained on the methylation data of five data sets from the cancer genome atlas (TCGA). The experimental results show that the MLW-gcForest algorithm achieves high accuracy and area under curve (AUC) values for the classification of cancer subtypes compared with those of traditional machine learning methods and state of the art methods. The results also show that methylation data can be effectively used to diagnose cancer.

scholarly journals Transcriptomic Analysis of Glioma Based on IDH Status Identifies ACAA2 as a Prognostic Factor in Lower Grade Glioma

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chenxing Wu ◽  
Hongwang Song ◽  
Xiaojun Fu ◽  
Shouwei Li ◽  
Tao Jiang
Keyword(s):  
Prognostic Factor ◽  
Network Analysis ◽  
Targeted Therapies ◽  
Correlation Network ◽  
Lower Grade ◽  
Gene Expressions ◽  
Who Grade ◽  
Lower Grade Glioma ◽  
Idh Mutations ◽  
Weighted Correlation

Background. Glioma is the most common and lethal tumor in the central nervous system (CNS). More than 70% of WHO grade II/III gliomas were found to harbor isocitrate dehydrogenase (IDH) mutations which generated targetable metabolic vulnerabilities. Focusing on the metabolic vulnerabilities, some targeted therapies, such as NAMPT, have shown significant effects in preclinical and clinical trials. Methods. We explored the TCGA as well as CGGA database and analyzed the RNA-seq data of lower grade gliomas (LGG) with the method of weighted correlation network analysis (WGCNA). Differential expressed genes were screened, and coexpression relationships were grouped together by performing average linkage hierarchical clustering on the topological overlap. Clinical data were used to conduct Kaplan–Meier analysis. Results. In this study, we identified ACAA2 as a prognostic factor in IDH mutation lower grade glioma with the method of weighted correlation network analysis (WGCNA). The difference of ACAA2 gene expressions between the IDH wild-type (IDH-WT) group and the IDH mutant (IDH-MUT) group suggested that there may be different potential targeted therapies based on the fatty acid metabolic vulnerabilities, which promoted the personalized treatment for LGG patients.

scholarly journals The Summary of an Urdu Version of Diabetes Self-Care Activities Measure: Psychometric Evaluation and Validation

2020 ◽  
Vol 11 ◽  
pp. 215013272093529
Author(s):  
Rashid M. Ansari ◽  
Mark F. Harris ◽  
Hassan Hosseinzadeh ◽  
Nicholas Zwar
Keyword(s):  
Small Sample Size ◽  
Self Care ◽  
Reliability And Validity ◽  
Psychometric Evaluation ◽  
Small Sample ◽  
World Health ◽  
Self Management ◽  
English Version ◽  
Health Organization ◽  
Test Retest Reliability

Objective: The English version of the Summary of Diabetes Self-Care Activities (SDSCA) measure is the most frequently used self-reporting instrument assessing diabetes self-management. This study is aimed at translating English SDSCA into the Urdu version and validating and evaluating its psychometric properties. Methods: The Urdu version of SDSCA was developed based on the guidelines provided by the World Health Organization for translation and adaptation of instruments. The panel of experts examined the content validity, reliability, and internal consistency of the instrument. The translation process from the English version to the Urdu version revealed excellent results at all the stages. Results: The instrument showed promising and acceptable results. Of particular mention are the results related to split-half reliability coefficient 0.90, test-retest reliability ( r = 0.918, P < .001), intraclass coefficient (0.912), and Cronbach’s alpha (.79). The factor analysis (exploratory and confirmatory) was not performed in this study due to the small sample size (n = 30) as the objective was to validate the Urdu version of the SDSCA instrument. Conclusions: This study provided evidence for the reliability and validity of the Urdu Summary of Diabetes Self-Care Activities (U-SDSCA) instrument, which may be used in the future for the patients of diabetes in order to assess type 2 diabetes self-management activities in the rural area of Pakistan and other Urdu-speaking countries.

scholarly journals Significance of tumor protein p53 mutation in cellular process and drug selection in brain lower grade (WHO grades II and III) glioma

2020 ◽  
Vol 14 (12) ◽  
pp. 1139-1150
Author(s):  
Chang-feng Guo ◽  
Yugang Zhuang ◽  
Yuanzhuo Chen ◽  
Sheng Chen ◽  
Hu Peng ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Tp53 Mutation ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
World Health ◽  
Outcome Analysis ◽  
Lower Grade ◽  
Protein P53 ◽  
Tumor Protein P53

Aim: Tumor protein p53 ( TP53) mutant is one of the most frequently mutated genes in glioma. Results: The Cancer Genome Atlas data has shown that TP53 mutation is present in 49% of lower grade (World Health Organization [WHO] grades II and III) glioma patients. Data from The Genomics of Drug Sensitivity in Cancer database showed that three drugs: (5Z)-7-oxozeaenol, dabrafenib and nutlin-3a (−), have shown more resistance in patients with TP53 mutation. We identified 1100 differentially expressed genes. Functional enrichment analysis showed that the differentially expressed genes are mainly concentrated in the transport of ionic and cancer-related pathways. The top ten hub genes were identified and an outcome analysis revealed the most critical genes related to prognosis. Conclusion: Our results identified the key genes and pathways that might provide the basic proof to improve individualized treatment in patients with glioma.

scholarly journals MPC-2 Clinical course and prognosis of lower-grade glioma, IDH wildtype and pTERT mutant

2021 ◽  
Vol 3 (Supplement_6) ◽  
pp. vi16-vi16
Author(s):  
Yoshinobu Takahashi ◽  
Hayato Takeuchi ◽  
Seisuke Tanigawa ◽  
Takanari Okamoto ◽  
Naoya Hashimoto
Keyword(s):  
Median Survival ◽  
Lower Grade ◽  
Diffuse Astrocytoma ◽  
Who Grade ◽  
Female Ratio ◽  
Astrocytic Glioma ◽  
Tert Promoter ◽  
Lower Grade Glioma ◽  
Idh Mutations ◽  
Astrocytic Gliomas

Abstract Background and Purpose: In the cIMPACT-Now update 3, it was proposed that grade 2 astrocytic gliomas without IDH-mutations and grade 3 astrocytic gliomas with TERT promoter mutations should be designated as diffuse IDH wildtype astrocytic glioma with molecular features of WHO grade IV glioblastoma. Therefore, we investigated whether this group of tumors actually corresponds to grade IV prognostically in cases that we encountered ourselves. Cases and Methods: Among the 65 patients having primary astrocytic glioma who were operated in our hospital from January 2016 to March 2021, the prognostic values of seven patients with lower-grade glioma, IDH wildtype, and pTERT mutant were investigated. Results: Among the seven patients, the median age was 59 years (50–66 years). Four of them had anaplastic astrocytoma, two had diffuse astrocytoma, and no tumor lesion could be identified upon histological examination for one patient. The male-to-female ratio was 1:6. MGMT methylation was observed in two patients (29%). The median survival was 20 months, with a significantly worse prognosis when compared with lower-grade glioma without the TERT promoter mutation (13 patients: median survival 40 months), but a better prognosis when compared with glioblastoma (45 patients: median survival 13 months) (Log-rank p = 0.0051). Conclusion: Although EGFR amplification, combined whole chromosome 7 gain, and whole chromosome 10 loss were not examined, the prognostic value of lower-grade glioma, IDH wildtype, and pTERT mutant was not as poor as that of glioblastoma. Further investigation is required to confirm whether these groups of tumors should be treated in the same way as grade IV glioblastoma.

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