Comparison of P-53, Ki-67 and Cd-10 Expression Between Fibroadenoma, Benign Phyllodes Tumor and Malignant Phyllodes Tumor

Background: Fibroepithelial tumors of the breast are a heterogeneous group of biphasic lesions comprising of an epithelial component and a quantitatively predominant mesenchymal component. These are classified into two major categories: Fibroadenoma and phyllodes tumor (PT). Phyllodes tumors are classified into benign, borderline and malignant grade categories based on histological parameters. Methods: An analytical-cross sectional study was conducted in the Department of Pathology, Hindu Rao Hospital, Delhi-110007 from November 2016 to December 2018. Total 50 cases were included in the study comprising of 30 cases of fibroadenoma, 15 cases of benign phyllodes tumor and 5 cases of malignant phyllodes tumor. All specimens were fixed in 10% buffered formalin. Tissue were processed and embedded in paraffin. The sections were stained with hematoxylin and eosin (H&E) to study the histopathological section. Immunostaining using CD-10, Ki-67 and p53 antibodies was done in all cases. Result: Among fibroadenoma cases only 3.33% showed positive CD-10 expression and 96.66% were negative. CD-10 expression was positive in 26.67% cases of benign phyllodes while 73.33 showed negative expression. 40% malignant phyllodes cases showed positive CD-10 expression and 60% showed negative CD-10 expression. CD-10 expression was significantly higher in benign phyllodes (p value = 0.019) and malignant phyllodes (p value 0.007) group as compared to fibroadenoma. P-53 expression in epithelium was seen in 56% of fibroadenoma and 26% of benign phyllodes cases, while all cases of malignant phyllodes tumor show negative P-53 expression. The stromal expression of P-53 was significantly higher in malignant phyllodes as compared to fibroadenoma and benign phyllodes tumor. Stromal expression of Ki-67 was significantly higher in malignant phyllodes as compared to benign phyllodes and fibroadenoma. Epithelial expression of Ki-67 was negative in all malignant phyllodes cases while positive epithelial Ki-67 expression was seen in 56% of fibroadenoma and 33% of benign phyllodes tumor. Conclusion: Both Ki-67 and P-53 showed a significantly increasing expression from fibroadenoma to benign phyllodes to malignant phyllodes tumor. The difference in expression of CD-10 was insignificant among fibroadenoma, benign phyllodes and malignant phyllodes tumor.

Adeno‐associated virus (AAV)-based gene therapy for glioblastoma

Glioblastoma (GBM) is the most common and malignant Grade IV primary craniocerebral tumor caused by glial cell carcinogenesis with an extremely poor median survival of 12–18 months. The current standard treatments for GBM, including surgical resection followed by chemotherapy and radiotherapy, fail to substantially prolong survival outcomes. Adeno-associated virus (AAV)-mediated gene therapy has recently attracted considerable interest because of its relatively low cytotoxicity, poor immunogenicity, broad tissue tropism, and long-term stable transgene expression. Furthermore, a range of gene therapy trials using AAV as vehicles are being investigated to thwart deadly GBM in mice models. At present, AAV is delivered to the brain by local injection, intracerebroventricular (ICV) injection, or systematic injection to treat experimental GBM mice model. In this review, we summarized the experimental trials of AAV-based gene therapy as GBM treatment and compared the advantages and disadvantages of different AAV injection approaches. We systematically introduced the prospect of the systematic injection of AAV as an approach for AAV-based gene therapy for GBM.

Prediction of Pathological and Radiological Nature of Glioma by Mass Spectrometry Combined With Machine Learning

ABSTRACT BACKGROUND We have previously developed a medical diagnostic pipeline that employs mass spectrometry and machine learning. It does not annotate molecular markers that are specific to cancer but uses entire mass spectra for predicting the properties of glioma. OBJECTIVE To validate the power of our diagnostic method in predicting the pathological and radiological properties of glioma with a simple sample preparation procedure. METHODS A total of 10 patients with glioma and 4 nonglioma patients who went through surgical resection were enrolled in our hospital. A total of 1020 mass spectra were acquired from 88 specimens. In order to examine the prediction power of the diagnostic pipeline that we have developed, we performed 10-fold cross-validation for pathological and radiological findings and calculated agreement rates with the conventional methods such as pathological diagnosis (World Health Organization [WHO] grading, MIB-1 labeling index [LI], mutations in the isocitrate dehydrogenase [IDH]-1 gene, and positive 5-aminolevulinic acid [5-ALA] fluorescence) and radiological information (gadolinium [Gd]-enhanced area and high-intensity area on fluid-attenuated inversion recovery [FLAIR] imaging). RESULTS Prediction accuracy for WHO malignant grade was 91.37%. Those for MIB-1 LI ≥ 10% and IDH-1 mutation-positive were 82.84% and 87.75%, respectively. Our method achieved an accurate prediction of 95.00% for the 5-ALA-positive lesion. The present method displayed an accuracy of 82.36% in predicting the area of FLAIR hyperintensity and 81.27% for the Gd-enhanced area. CONCLUSION Our methodology achieved a higher rate of prediction of glioma in terms of pathology and radiology. Research is ongoing to develop a validation cohort to verify the biological profiles of glioma specimens.

Hemisphere-Specific Functional Remodeling and Its Relevance to Tumor Malignancy of Cerebral Glioma Based on Resting-State Functional Network Analysis

Background: Functional remodeling may vary with tumor aggressiveness of glioma. Investigation of the functional remodeling is expected to provide scientific relevance of tumor characterization and disease management of glioma. In this study, we aimed to investigate the functional remodeling of the contralesional hemisphere and its utility in predicting the malignant grade of glioma at the individual level with multivariate logistic regression (MLR) analysis. Subjects and Methods: One hundred and twenty-six right-handed subjects with histologically confirmed cerebral glioma were included with 80 tumors located in the left hemisphere (LH) and 46 tumors located in the right hemisphere (RH). Resting-state functional networks of the contralesional hemisphere were constructed using the human brainnetome atlas based on resting-state fMRI data. Functional connectivity and topological features of functional networks were quantified. The performance of functional features in predicting the glioma grade was evaluated using area under (AUC) the receiver operating characteristic curve (ROC). The dataset was divided into training and validation datasets. Features with high AUC values in malignancy classification in the training dataset were determined as predictive features. An MLR model was constructed based on predictive features and its classification performance was evaluated on the training and validation datasets with 10-fold cross validation. Results: Predictive functional features showed apparent hemispheric specifications. MLR classification models constructed with age and predictive functional connectivity features (AUC of 0.853 ± 0.079 and 1.000 ± 0.000 for LH and RH group, respectively) and topological features (AUC of 0.788 ± 0.150 and 0.897 ± 0.165 for LH and RH group, respectively) achieved efficient performance in predicting the malignant grade of gliomas. Conclusion: Functional remodeling of the contralesional hemisphere was hemisphere-specific and highly predictive of the malignant grade of glioma. Network approach provides a novel pathway that may innovate glioma characterization and management at the individual level.

Recurrence prediction for breast phyllodes tumours: validation of the Singapore nomogram in Korean women

AimThe Singapore nomogram was developed to predict recurrence risk of phyllodes tumours (PTs) of the breast based on histological features of stromal atypia, stromal mitoses, stromal overgrowth and surgical margin status. We aimed to validate the utility of the Singapore nomogram in a Korean PT cohort.MethodsOne hundred and twenty-four patients with Korean PT who underwent surgical resection between 1996 and 2015 were included in this study. Pathology reports and slides were reviewed to obtain histopathologic features and acquire Singapore nomogram scores. The probability of concordance between predicted and observed survivals by means of the Singapore nomogram was evaluated using a concordance index (C-index).ResultsOf the 124 cases, 57 (46%) were diagnosed as benign, 50 (40.3%) as borderline and 17 (13.7%) as malignant. Recurrences occurred in 25 (20.2%) patients. Univariate analysis showed PTs with higher stromal mitotic counts, marked stromal cellularity, stromal overgrowth, positive surgical margin, marked stromal atypia or a malignant grade presented higher risks of recurrence. Multivariate analysis showed stromal mitoses and surgical margin status independently predicted recurrence-free survival. Patients with high nomogram scores were at greater risk of recurrence (HR=1.05, 95% CI: 1.02 to 1.07, p<0.001) with a C-index of 0.762.ConclusionThe Singapore nomogram provided a useful means of predicting PT outcomes in a Korean PT cohort.

NI-01 Usefulness of preoperative evaluation of glioma elasticity by the magnetic resonance elastography

Introduction: The elasticity of intracranial tumors is difficult to assess non-invasively because the lesion is surrounded by the skull. Therefore, intracranial tumors have not been verified before surgery in terms of elastic modulus. Magnetic resonance elastography (MRE) is an epoch-making method capable of non-invasively imaging the elasticity of internal organs. We have examined the elasticity of meningiomas and pituitary adenomas and reported their usefulness. This time, we measured the glioma elasticity and verified usefulness of MRE. Method: Twenty-four gliomas (mean age 51.8±15.7 years, male: female = 17: 7) who underwent tumor resection after MRE imaging from July 2017 to May 2020 were targeted. The average elasticity was measured as an evaluation of tumor elastic modulus by MRE. Gliomas were divided into a low-grade glioma group (LGG: Grade 1, 2) and a high-grade glioma group (HGG: Grade 3, 4). Then, a comparative statistical study was conducted. Results: The average values of the average elasticity of LGG group (9 cases) and HGG group (15 cases) were 1.8±0.8 kPa and 2.5±0.8 kPa, respectively. The average elasticity was significantly higher in the HGG group (p=0.023). In the ROC analysis, the cutoff value was 2.1 kPa (sensitivity 70%, specificity 70%). Therefore, it was suggested that the tumor is likely to be HGG when the average elasticity is 2.1 kPa or more. Discussion: The glioma elasticity by preoperative MRE was significantly higher in the HGG group. Based on actual surgical experience, the tumor seems to be hard in the HGG group, and it was judged to be consistent with this our MRE research. The preoperative evaluation of glioma elasticity by MRE was considered useful, and it might help in planning a surgical strategy considering malignant grade.

CO-01 Prediction of pathological and radiological nature of glioma by mass spectrometry combined with machine learning

BACKGROUND: We have previously developed a medical diagnostic pipeline that employs mass spectrometry and machine learning. It does not annotate molecular markers that are specific to cancer but uses entire mass spectra for predicting the properties of glioma. OBJECT: To validate the power of our diagnostic method in predicting the pathological and radiological properties of glioma with a simple sample preparation procedure. METHODS: Ten patients with glioma and 4 non-glioma patients who went through surgical resection were enrolled in our hospital. A total of 1020 mass spectra were acquired from 88 specimens. In order to examine the prediction power of the diagnostic pipeline that we have developed, we performed ten-fold cross-validation for pathological and radiological findings and calculated agreement rates with the conventional methods such as pathological diagnosis (WHO grading, MIB-1 labeling index (LI), mutations in the isocitrate dehydrogenase (IDH)-1 gene and positive 5-ALA fluorescence) and radiological information (gadolinium (Gd)-enhanced area, high-intensity area on fluid-attenuated inversion recovery (FLAIR) imaging,). RESULTS: Prediction accuracy for WHO malignant grade was 91.37%. Those for MIB-1 LI more than 10% and IDH-1 mutation-positive were 82.84% and 87.75%, respectively. Our method achieved an accurate prediction of 95.00% for the 5-ALA-positive lesion. The present method displayed an accuracy of 82.36% in predicting the area of FLAIR hyperintensity and 81.27% for the Gd enhanced area. CONCLUSION: Our methodology achieved a higher rate of prediction of glioma in terms of pathology and radiology. Research is ongoing to develop a validation cohort to verify the biological profiles of glioma specimens.

Prognosis and risk factors for malignant peripheral nerve sheath tumor: a systematic review and meta-analysis

Background No available meta-analysis was printed to systematically introduce the MPNST clinic outcome and risk factors based on largely pooled data. This systematic review and meta-analysis aimed to investigate 5-year OS rate, 5-year EFS rate, and LR rate for MPNST, and to assess potential risk factors for prognosis. Methods Electronic articles published between January 1, 1966 and February 29, 2020 were searched and critically evaluated. The authors independently reviewed the abstracts and extracted data for 5-year OS rate, 5-year EFS rate, LR rate, and potential risk factors for prognosis. Results Twenty-eight literatures were finally included for meta-analysis. The pooled 5-year OS rate, 5-year EFS rate, and LR rate were 49%, 37%, and 38%, respectively. The significant prognostic factors for survival were NF1 status, tumor size, depth, location, malignant grade, margin status, chemotherapy, and radiotherapy. Age and sex were not associated with survival. Conclusion Survival and local recurrence of MPNST are poor. Worse prognosis is mainly associated with NF 1, large size, deep to fascia, high grade, metastases, and location (trunk and head and neck). Complete resection with adequate surgical margins is the mainstay protective factor of MPNST patients, following necessary adjuvant therapies.