Long-term clinical outcomes of combined modality therapy for advanced-stage Hodgkin lymphoma in the PET era: A retrospective study.

BACKGROUND OBJECTIVES: The role of consolidation radiation therapy (CRT) after complete metabolic response to chemotherapy in advanced-stage (stage III and IV) Hodgkin lymphoma (HL) is controversial. This study was undertaken to assess the clinical outcomes in terms of event free survival, local failure free survival and overall survival in individuals with advanced HL treated with chemotherapy and CRT. METHODS: A retrospective review was conducted to study the long-term clinical outcomes in individuals diagnosed with HL and treated with chemotherapy and CRT from 2012 to 2016 at a tertiary cancer care hospital in India. RESULTS: Data from 203 study participants with advanced-stage HL were analyzed. Positron emission tomography-computed tomography (PET-CT) was done at baseline and after 2 cycles for response assessment. The median age at presentation was 32 yr [interquartile range (IQR): 26-46]. Early metabolic response (after 2 cycles) and delayed metabolic response (after 4 or 6 cycles) were observed in 74.4 and 25.6 per cent of individuals, respectively. With a median follow up of 52 months (IQR: 40-67), the five-year event-free survival (EFS), local failure-free survival (LFFS) and overall survival (OS) were 83.2, 95.1 and 94.6 per cent, respectively. On univariate analysis, extranodal disease was associated with inferior EFS (P=0.043). Haemoglobin <10.5 g/dl (P=0.002) and Hasenclever index >3 (P=0.00047) were associated with poorer OS. Relapses were observed in 28/203 (13.8%) study participants with predominance at central nodal stations. The median time to relapse was 19.4 months (IQR: 13-33). Local relapse alone (at the irradiated site) was observed in 5/28 study participants, systemic (distant) relapse in 14/28 individuals, while both systemic and local relapse was observed in 9/28 participants. Extranodal disease (P=0.05), bulky disease (P=0.005) and haemoglobin concentration ≤10.5 g/dl (P=0.036) were significant predictors for disease relapse. INTERPRETATION CONCLUSIONS: Individuals with advanced-stage HL treated with anthracycline-based chemotherapy (anthracycline-based chemotherapy with doxorubicin, bleomycin, vinblastine and dacarbazine regimen) and CRT had excellent long-term outcomes. As isolated infield failures are uncommon, selective consolidation with conformal RT to high-risk sites improves final disease outcomes.

Toxicological safety evaluation of 3,3'-diselenodipropionic acid (DSePA), a pharmacologically important derivative of selenocystine.

Diselenodipropionic acid (DSePA), a pharmacologically important derivative of selenocystine was evaluated for acute toxicity, mutagenic safety and metabolic stability. The estimated median oral lethal dose (LD50) cut-off of DSePA in mice and rat models was ∼200 mg/kg and ∼25 mg/kg respectively, which is considerably higher than the reported oral LD50 dose of its parent compound. Subsequently DSePA treatment in absence and presence of rat liver S9 fraction was found to be non-mutagenic at the tested doses up to 1 mM in rifampicin resistance assay and up to 6 mM in Ames test. In vitro degradation studies indicated that DSePA was more stable in S9 fraction of human compared to rat. The kinetic parameters Km and Vmax of DSePA degradation estimated using rat S9 fraction was 9.81 µM and 1.06 nmol/ml/min respectively. Further, DSePA treatment (1-50 µM) with or without rat S9 fraction did not induce any toxicity in human intestinal epithelial cells (Int 407) while showing comparable bioactivity of glutathione peroxidase (GPx) level. In conclusion, superior metabolic stability of DSePA in human S9 fraction with a concomitant lack of mutagenic effects suggests that it may be a suitable derivative of selenocytine for future biological studies.

Histological spectrum of oligodendroglial tumors: Only a subset shows 1p/19q codeletion.

BACKGROUND: Canonical oligodendroglial tumors (ODGs) are characterized genetically by chromosomes 1p/19q codeletion. AIMS: This study was essentially aimed at the detection of frequency of 1p/19q codeletion in the different histological spectrum of ODG tumors in a large cohort of Indian patients. MATERIALS AND METHODS: All the ODG tumors evaluated for 1p/19q by fluorescence in-situ hybridization (FISH) during 2009-2015 were correlated with histology, immunohistochemical expression for p53 protein and clinical features. RESULTS: A total of 676 cases included both pediatric (n = 18) and adult (n = 658) patients. Histologically, 346 pure ODGs [oligodendroglioma (OD) and anaplastic oligodendroglioma (AOD)] and 330 mixed ODGs [oligoastrocytomas (OA), anaplastic oligoastrocytomas (AOA) and glioblastoma with oligodendroglioma component (GBM-O)] were included. 1p/19q co-deletion was noted in 69% (60/87), 55.9% (145/259), 18.2% (18/99), 10.5% (18/172), and in 5.1% (3/59) cases of OD, AOD, OA, AOA, and GBM-O, respectively. In the pediatric age-group, 1p/19q codeletion was seen in 25% (2/8) of pure ODGs and in 10% (1/10) of mixed ODGs. In adults, it was observed in 60% (203/338) cases of pure ODGs and in 11.9% (38/320) cases of mixed ODGs. In adults, pure ODG histology (P = 0.00), frontal location (P = 0.004), calcification [in pure ODGs] (P = 0.03), and lack of p53 protein overexpression (P = 0.00) showed significant statistical correlation with 1p/19q codeletion. CONCLUSIONS: This study is unique in being one of the largest on ODGs for 1p/19q co-deletion including both pediatric and adult age groups of Indian patients. The results showed co-deletion in 60% of adult ODGs and 25% of pediatric pure ODGs. This reemphasizes the occurrence of 1p/19q codeletion, even though rare, in the pediatric age group.

Targeting the AKT pathway: Repositioning HIV protease inhibitors as radiosensitizers.

Cellular resistance in tumour cells to different therapeutic approaches has been a limiting factor in the curative treatment of cancer. Resistance to therapeutic radiation is a common phenomenon which significantly reduces treatment options and impacts survival. One of the mechanisms of acquiring resistance to ionizing radiation is the overexpression or activation of various oncogenes like the EGFR (epidermal growth factor receptor), RAS (rat sarcoma) oncogene or loss of PTEN (phosphatase and tensin homologue) which in turn activates the phosphatidyl inositol 3-kinase/protein kinase B (PI3-K)/AKT pathway responsible for radiation resistance in various tumours. Blocking the pathway enhances the radiation response both in vitro and in vivo. Due to the differential activation of this pathway (constitutively activated in tumour cells and not in the normal host cells), it is an excellent candidate target for molecular targeted therapy to enhance radiation sensitivity. In this regard, HIV protease inhibitors (HPIs) known to interfere with PI3-K/AKT signaling in tumour cells, have been shown to sensitize various tumour cells to radiation both in vitro and in vivo. As a result, HPIs are now being investigated as possible radiosensitizers along with various chemotherapeutic drugs. This review describes the mechanisms by which PI3-K/AKT pathway causes radioresistance and the role of HIV protease inhibitors especially nelfinavir as a potential candidate drug to target the AKT pathway for overcoming radioresistance and its use in various clinical trials for different malignancies.

Nanomedicine as a multimodal therapeutic paradigm against cancer: on the way forward in advancing precision therapy.

Recent years have witnessed dramatic improvements in nanotechnology-based cancer therapeutics, and it continues to evolve from the use of conventional therapies (chemotherapy, surgery, and radiotherapy) to increasingly multi-complex approaches incorporating thermal energy-based tumor ablation (e.g. magnetic hyperthermia and photothermal therapy), dynamic therapy (e.g. photodynamic therapy), gene therapy, sonodynamic therapy (e.g. ultrasound), immunotherapy, and more recently real-time treatment efficacy monitoring (e.g. theranostic MRI-sensitive nanoparticles). Unlike monotherapy, these multimodal therapies (bimodal, i.e., a combination of two therapies, and trimodal, i.e., a combination of more than two therapies) incorporating nanoplatforms have tremendous potential to improve the tumor tissue penetration and retention of therapeutic agents through selective active/passive targeting effects. These combinatorial therapies can correspondingly alleviate drug response against hypoxic/acidic and immunosuppressive tumor microenvironments and promote/induce tumor cell death through various multi-mechanisms such as apoptosis, autophagy, and reactive oxygen-based cytotoxicity, e.g., ferroptosis, etc. These multi-faced approaches such as targeting the tumor vasculature, neoangiogenic vessels, drug-resistant cancer stem cells (CSCs), preventing intra/extravasation to reduce metastatic growth, and modulation of antitumor immune responses work complementary to each other, enhancing treatment efficacy. In this review, we discuss recent advances in different nanotechnology-mediated synergistic/additive combination therapies, emphasizing their underlying mechanisms for improving cancer prognosis and survival outcomes. Additionally, significant challenges such as CSCs, hypoxia, immunosuppression, and distant/local metastasis associated with therapy resistance and tumor recurrences are reviewed. Furthermore, to improve the clinical precision of these multimodal nanoplatforms in cancer treatment, their successful bench-to-clinic translation with controlled and localized drug-release kinetics, maximizing the therapeutic window while addressing safety and regulatory concerns are discussed. As we advance further, exploiting these strategies in clinically more relevant models such as patient-derived xenografts and 3D organoids will pave the way for the application of precision therapy.

Dosimetric Impact of Voluntary Deep Inspiration Breath Hold (DIBH) in Mediastinal Hodgkin Lymphomas: A Comparative Evaluation of Three Different Intensity Modulated Radiation Therapy (IMRT) Delivery Methods Using Voluntary DIBH and Free Breathing Techniques.

Hodgkin lymphomas are radiosensitive and curable tumors that often involve the mediastinum. However, the application of radiation therapy to the mediastinum is associated with late effects including cardiac and pulmonary toxicities and secondary cancers. The adoption of conformal IMRT and deep inspiration breath- hold (DIBH) can reduce the dose to healthy normal tissues (lungs, heart and breast). We compared the dosimetry of organs at risk (OARs) using different IMRT techniques for two breathing conditions, i.e., deep inspiration breath hold (DIBH) and free breathing. Twenty-three patients with early-stage mediastinal Hodgkin lymphomas were accrued in the prospective study. The patients were given treatment plans which utilized full arc volumetric modulated arc therapy (F-VMAT), Butterfly VMAT (B-VMAT), and fixed field IMRT (FF-IMRT) techniques for both DIBH and free breathing methods, respectively. All the plans were optimized to deliver 95% of the prescription dose which was 25.2 Gy to 95% of the PTV volume. The mean dose and standard error of the mean for each OAR, conformity index (CI), and homogeneity index (HI) for the target using the three planning techniques were calculated and compared using Student's t-test for parametric data and Wilcoxon signed-rank test for non-parametric data. The HI and CI of the target was not compromised using the DIBH technique for mediastinal lymphomas. The mean values of CI and HI for both DIBH and FB were comparable. The mean heart doses were reduced by 2.1 Gy, 2.54 Gy, and 2.38 Gy in DIBH compared to FB for the F-VMAT, B-VMAT, and IMRT techniques, respectively. There was a significant reduction in V5Gy, V10Gy, and V15Gy to the heart (p < 0.005) with DIBH. DIBH reduced the mean dose to the total lung by 1.19 Gy, 1.47 Gy, and 1.3 Gy, respectively. Among the 14 female patients, there was a reduction in the mean right breast dose with DIBH compared to FB (4.47 Gy vs. 3.63 Gy, p = 0.004). DIBH results in lower heart, lung, and breast doses than free breathing in mediastinal Hodgkin Lymphoma. Among the different IMRT techniques, FF-IMRT, B-VMAT, and F-VMAT showed similar PTV coverage, with similar conformity and homogeneity indices. However, the time taken for FF-IMRT was much longer than for the F-VMAT and B-VMAT techniques for both breathing methods. B-VMAT and F-VMAT emerged as the optimal planning techniques able to achieve the best target coverage and lower doses to the OARs, with less time required to deliver the prescribed dose.

Patterns of Care in Craniopharyngioma: Clinical Outcomes After Surgery and Radiation Therapy in a Real-World Setting.

OBJECTIVE: Craniopharyngioma (CP) is a benign neuroepithelial tumor generally treated with maximal safe resection and radiation therapy (RT) in incompletely resected CP or in recurrent tumors to achieve long-term control. We analyzed the clinical outcomes of patients with CPs treated with a multimodality approach. PATIENTS AND METHODS: A retrospective clinical audit of histologically proven CPs registered between 2008 and 2019 at a specialized neuro-oncology center in India was performed. Time-to-event outcomes (overall survival [OS] and progression-free survival [PFS]) were analyzed. RESULTS: One hundred and twenty-two patients with CP were analyzed. The median age of the population was 14 years (interquartile range [IQR], 8-26) with a significant male preponderance. Gross total resection was achieved in only 25% of patients. At a median follow-up of 57.1 months (IQR, 27.8-87.8), 5-year estimates of PFS and OS were 52% (95% confidence interval, 46%-63.4%) and 85.8% (95% confidence interval, 78.6%-93%), respectively. Recurrence or progression was observed in 48 of 122 patients (39.3%) at a median time of 84.4 months (IQR, 24.7-174.8). On multivariate analysis, the absence of residual disease (P = 0.004), near-total resection (P = 0.035), and use of up-front adjuvant RT (P < 0.001) significantly improved the 5-year PFS, whereas the absence of extracavernous extension (P = 0.058) and any use of postoperative RT (P = 0.026) significantly improved the 5-year OS. CONCLUSIONS: This study represents one of the largest single-institutional series of CPs, showing improved PFS with up-front adjuvant RT in most cases of CP. Deferring adjuvant RT should be considered only in patients with no evidence of residual disease (as shown on dedicated sellar imaging) after primary surgery.

Can multiparametric MRI and FDG-PET predict outcome in diffuse brainstem glioma? A report from a prospective phase-II study.

PURPOSE: To study the impact of multiparametric MRI and (18)F-FDG-PET on the outcome of children with diffuse intrinsic pontine gliomas (DIPG). MATERIALS AND METHODS: Imaging data from a phase-II prospective therapeutic study in children with newly diagnosed DIPG were considered for evaluation. They included baseline MRI with contrast enhancement before treatment. Functional imaging included MR spectroscopy, MR perfusion and FDG-PET studies. All patients (n = 20) had baseline MRI and 11 patients had FDG-PET. Response was assessed by MRI and PET 4 weeks after therapy. Baseline imaging findings were correlated with survival. Presence or absence of adverse parameters on MRI (heterogeneous contrast enhancement, hyperperfusion or increased choline:NAA ratio) was used to develop a cumulative radiological prognostic index (RPI). Sensitivity and specificity of each imaging modality in tumour grading was estimated. RESULTS: The cumulative RPI was able to classify the patients into different grades and was predictive of overall survival (p = 0.02). MR perfusion also predicted survival (p = 0.039). Sensitivity and specificity of MRI and FDG-PET to detect low-grade gliomas were low to moderate (33-66%), but moderate to high in detecting high-grade gliomas (50-100%). Baseline FDG uptake on PET scan did not correlate with survival (p = 0.7). CONCLUSIONS: Cumulative RPI was able to classify tumours into different grades and predicted clinical outcome. At baseline, MR hyperperfusion indicated a shorter survival for DIPG patients. Sensitivity and specificity of imaging modalities to detect low-grade gliomas were poor.

Insight into lipid-based nanoplatform-mediated drug and gene delivery in neuro-oncology and their clinical prospects.

Tumors of the Central nervous System (CNS) are a spectrum of neoplasms that range from benign lesions to highly malignant and aggressive lesions. Despite aggressive multimodal treatment approaches, the morbidity and mortality are high with dismal survival outcomes in these malignant tumors. Moreover, the non-specificity of conventional treatments substantiates the rationale for precise therapeutic strategies that selectively target infiltrating tumor cells within the brain, and minimize systemic and collateral damage. With the recent advancement of nanoplatforms for biomaterials applications, lipid-based nanoparticulate systems present an attractive and breakthrough impact on CNS tumor management. Lipid nanoparticles centered immunotherapeutic agents treating malignant CNS tumors could convene the clear need for precise treatment strategies. Immunotherapeutic agents can selectively induce specific immune responses by active or innate immune responses at the local site within the brain. In this review, we discuss the therapeutic applications of lipid-based nanoplatforms for CNS tumors with an emphasis on revolutionary approaches in brain targeting, imaging, and drug and gene delivery with immunotherapy. Lipid-based nanoparticle platforms represent one of the most promising colloidal carriers for chemotherapeutic, and immunotherapeutic drugs. Their current application in oncology especially in brain tumors has brought about a paradigm shift in cancer treatment by improving the antitumor activity of several agents that could be used to selectively target brain tumors. Subsequently, the lab-to-clinic transformation and challenges towards translational feasibility of lipid-based nanoplatforms for drug and gene/immunotherapy delivery in the context of CNS tumor management is addressed.

Oncolytic immunovirotherapy for high-grade gliomas: A novel and an evolving therapeutic option.

Glioblastoma is one of the most difficult tumor types to manage, having high morbidity and mortality with available therapies (surgery, radiotherapy and chemotherapy). Immunotherapeutic agents like Oncolytic Viruses (OVs), Immune Checkpoint Inhibitors (ICIs), Chimeric Antigen Receptor (CAR) T cells and Natural Killer (NK) cell therapies are now being extensively used as experimental therapies in the management of glioblastoma. Oncolytic virotherapy is an emerging form of anti-cancer therapy, employing nature's own agents to target and destroy glioma cells. Several oncolytic viruses have demonstrated the ability to infect and lyse glioma cells by inducing apoptosis or triggering an anti-tumor immune response. In this mini-review, we discuss the role of OV therapy (OVT) in malignant gliomas with a special focus on ongoing and completed clinical trials and the ensuing challenges and perspectives thereof in subsequent sections.

Institutional Patterns of Care of Diffuse Intrinsic Pontine Glioma.

Background and Aim: Despite recent advances, the outcomes of diffuse intrinsic pontine glioma (DIPG) remain dismal. This is a retrospective study to understand the pattern of care and its impact on DIPG patients diagnosed over 5 years in a single institute. Subjects and Methods: DIPGs diagnosed between 2015 and 2019 were retrospectively reviewed to understand the demographics, clinical features, patterns of care, and outcomes. The usage of steroids and response to treatment were analyzed as per the available records and criteria. The re-irradiation cohort was propensity matched with patients with a progression-free survival (PFS) >6 months treated with supportive care alone based on PFS and age as a continuous variable. Survival analysis was performed using the Kaplan-Meier method, and Cox regression model was used to identify any potential prognostic factors. Results: One hundred and eighty-four patients were identified with demographic profiles similar to western population-based data in the literature. Of them, 42.4% were residents from outside the state of the institution. About 75.2% of patients completed their first radiotherapy treatment, of which only 5% and 6% had worsening clinical symptoms and persistent need for steroids 1 month posttreatment. On multivariate analysis, Lansky performance status <60 (P = 0.028) and cranial nerve IX and X (P = 0.026) involvement were associated with poor survival outcomes while receiving radiotherapy with better survival (P < 0.001). In the cohort of patients receiving radiotherapy, only re-irradiation (reRT) was associated with improved survival (P = 0.002). Conclusion: Many patient families still do not choose radiotherapy treatment, although it has a consistent and significant positive association with survival and steroid usage. reRT further improves outcomes in the selective cohorts. Involvement of cranial nerves IX and X needs improved care.

Computerized tomography-based first order tumor texture features in non-small cell lung carcinoma treated with concurrent chemoradiation: A simplistic and potential surrogate imaging marker for survival.

Objectives: This study examines the role of tumor texture on computed tomography (CT) images as a complement to clinical prognostic factors in predicting survival in patients of non-small cell lung carcinoma (NSCLC) treated with radical chemo-radiation (CRT). Methods: A total of 93 patients with confirmed NSCLC treated with CRT accrued in a study approved by the institutional ethics committee were analyzed for CT-based radiomic features. Pretreatment CT images were used to contour the primary tumor and texture features were computed by the image filtration method to differentially highlight fine to coarse textures. Texture parameters included mean intensity, entropy, kurtosis, standard deviation, and mean positive pixel and skewness. Optimal threshold cut-off values of the above tumor texture features were analyzed. These features were explored as imaging biomarkers to predict survival using Kaplan-Meier and Cox proportional hazard model. Results: Median follow-up of the entire cohort was 23.5 months [Interquartile range, IQR: 14-37] while for alive patients, median follow-up was 31 months (IQR: 23-49), 47 (50.6%) patients had died at the last follow-up. Univariate analysis revealed certain features like age, gender, response to therapy, and texture features like mean and kurtosis in CT images to be significant predictors of survival. In multivariate analysis, age (P = 0.006), gender (P = 0.004), treatment response (P< 0.0001), and two CT texture parameters: mean (P = 0.027) and kurtosis (P= 0.002) were independent prognostic factors of survival. Interpretation and Conclusion: CT-derived tumor heterogeneity (mean and kurtosis) complements clinical factors for predicting survival in NSCLC patients treated with CRT. Tumor radiomics warrants further validation as potential prognostic biomarkers for these patients.

Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain.

Grading of gliomas is a piece of critical information related to prognosis and survival. Classifying glioma grade by semantic radiological features is subjective, requires multiple MRI sequences, is quite complex and clinically demanding, and can very often result in erroneous radiological diagnosis. We used a radiomics approach with machine learning classifiers to determine the grade of gliomas. Eighty-three patients with histopathologically proven gliomas underwent MRI of the brain. Whenever available, immunohistochemistry was additionally used to augment the histopathological diagnosis. Segmentation was performed manually on the T2W MR sequence using the TexRad texture analysis softwareTM, Version 3.10. Forty-two radiomics features, which included first-order features and shape features, were derived and compared between high-grade and low-grade gliomas. Features were selected by recursive feature elimination using a random forest algorithm method. The classification performance of the models was measured using accuracy, precision, recall, f1 score, and area under the curve (AUC) of the receiver operating characteristic curve. A 10-fold cross-validation was adopted to separate the training and the test data. The selected features were used to build five classifier models: support vector machine, random forest, gradient boost, naive Bayes, and AdaBoost classifiers. The random forest model performed the best, achieving an AUC of 0.81, an accuracy of 0.83, f1 score of 0.88, a recall of 0.93, and a precision of 0.85 for the test cohort. The results suggest that machine-learning-based radiomics features extracted from multiparametric MRI images can provide a non-invasive method for predicting glioma grades preoperatively. In the present study, we extracted the radiomics features from a single cross-sectional image of the T2W MRI sequence and utilized these features to build a fairly robust model to classify low-grade gliomas from high-grade gliomas (grade 4 gliomas).

Clinical utility of CAR T cell therapy in brain tumors: Lessons learned from the past, current evidence and the future stakes.

The unprecedented clinical success of Chimeric Antigen Receptor (CAR) T cell therapy in hematological malignancies has led researchers to study its role in solid tumors. Although, its utility in solid tumors especially in neuroblastoma has begun to emerge, preclinical studies of its efficacy in other solid tumors like osteosarcomas or gliomas has caught the attention of oncologist to be tried in clinical trials. Malignant high-grade brain tumors like glioblastomas or midline gliomas in children represent some of the most difficult malignancies to be managed with conventionally available therapeutics, while relapsed gliomas continue to have the most dismal prognosis due to limited therapeutic options. Innovative therapies such as CAR T cells could give an additional leverage to the treating oncologists by potentially improving outcomes and ameliorating the toxicity of the currently available therapies. Moreover, CAR T cell therapy has the potential to be integrated into the therapeutic paradigm for aggressive gliomas in the near future. In this review we discuss the challenges in using CAR T cell therapy in brain tumors, enumerate the completed and ongoing clinical trials of different types of CAR T cell therapy for different brain tumors with special emphasis on glioblastoma and also discuss the future role of CAR T cells in Brain tumors.

Classifying primary central nervous system lymphoma from glioblastoma using deep learning and radiomics based machine learning approach - a systematic review and meta-analysis.

Background: Glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) are common in elderly yet difficult to differentiate on MRI. Their management and prognosis are quite different. Recent surge of interest in predictive analytics, using machine learning (ML) from radiomic features and deep learning (DL) for diagnosing, predicting response and prognosticating disease has evinced interest among radiologists and clinicians. The objective of this systematic review and meta-analysis was to evaluate the deep learning & ML algorithms in classifying PCNSL from GBM. Methods: The authors performed a systematic review of the literature from MEDLINE, EMBASE and the Cochrane central trials register for the search strategy in accordance with PRISMA guidelines to select and evaluate studies that included themes of ML, DL, AI, GBM, PCNSL. All studies reporting on ML algorithms or DL that for differentiating PCNSL from GBM on MR imaging were included. These studies were further narrowed down to focus on works published between 2018 and 2021. Two researchers independently conducted the literature screening, database extraction and risk bias assessment. The extracted data was synthesised and analysed by forest plots. Outcomes assessed were test characteristics such as accuracy, sensitivity, specificity and balanced accuracy. Results: Ten articles meeting the eligibility criteria were identified addressing use of ML and DL in training and validation classifiers to distinguish PCNSL from GBM on MR imaging. The total sample size was 1311 in the included studies. ML approach was used in 6 studies while DL in 4 studies. The lowest reported sensitivity was 80%, while the highest reported sensitivity was 99% in studies in which ML and DL was directly compared with the gold standard histopathology. The lowest reported specificity was 87% while the highest reported specificity was 100%. The highest reported balanced accuracy was 100% and the lowest was 84%. Conclusions: Extensive search of the database revealed a limited number of studies that have applied ML or DL to differentiate PCNSL from GBM. Of the currently published studies, Both DL & ML algorithms have demonstrated encouraging results and certainly have the potential to aid neurooncologists in taking preoperative decisions in the future leading to not only reduction in morbidities but also be cost effective.

Bio-polymeric transferrin-targeted temozolomide nanoparticles in gel for synergistic post-surgical GBM therapy.

Spatiotemporal targeting of anti-glioma drugs remains a pressing issue in glioblastoma (GBM) treatment. We challenge this issue by developing a minimally invasive in situ implantable hydrogel implant comprising transferrin-targeted temozolomide-miltefosine nanovesicles in the surgically resected GBM cavity (tumour bed). Injection of the "nanovesicle in hydrogel system" in orthotopic GBM-bearing mice improved drug penetration into the peri-cavitary region (∼4.5 mm in depth) with the potential to act as a bridge therapy in the immediate postoperative period, before the initiation of adjuvant radiotherapy. The controlled and sustained release of temozolomide over a month in the surgical cavity eradicated the microscopic GBM cells present within the tumour bed, thereby augmenting the efficacy of adjuvant therapy. The drug (temozolomide and miltefosine) combination was tolerable and efficiently inhibited tumour growth, causing significant prolongation of the survival of tumour-bearing mice compared to that with the free drug. Direct implantation at the target site in the brain resulted in spatiotemporal anti-glioma activity with minimal extracranial and systemic distribution. Nanovesicle in flexible hydrogel systems can be used as potential platforms for the post-surgical management of GBM before initiating adjuvant radiation therapy.

Combinatorial approaches to effective therapy in glioblastoma (GBM): Current status and what the future holds.

The aggressive and recurrent nature of glioblastoma is multifactorial and has been attributed to its biological heterogeneity, dysfunctional metabolic signaling pathways, rigid blood-brain barrier, inherent resistance to standard therapy due to the stemness property of the gliomas cells, immunosuppressive tumor microenvironment, hypoxia and neoangiogenesis which are very well orchestrated and create the tumor's own highly pro-tumorigenic milieu. Once the relay of events starts amongst these components, eventually it becomes difficult to control the cascade using only the balanced contemporary care of treatment consisting of maximal resection, radiotherapy and chemotherapy with temozolamide. Over the past few decades, implementation of contemporary treatment modalities has shown benefit to some extent, but no significant overall survival benefit is achieved. Therefore, there is an unmet need for advanced multifaceted combinatorial strategies. Recent advances in molecular biology, development of innovative therapeutics and novel delivery platforms over the years has resulted in a paradigm shift in gliomas therapeutics. Decades of research has led to emergence of several treatment molecules, including immunotherapies such as immune checkpoint blockade, oncolytic virotherapy, adoptive cell therapy, nanoparticles, CED and BNCT, each with the unique proficiency to overcome the mentioned challenges, present research. Recent years are seeing innovative combinatorial strategies to overcome the multifactorial resistance put forth by the GBM cell and its TME. This review discusses the contemporary and the investigational combinatorial strategies being employed to treat GBM and summarizes the evidence accumulated till date.

Glioblastoma is a form of brain tumor which typically leads to death in almost all patients. Over the last two decades, traditional treatment strategies such as surgery, radiotherapy and chemotherapy have been combined as standard therapy. Together, these aggressive treatment strategies have provided modest survival benefit with acceptable toxicity. However, relapse is the invariable norm resulting in death in the overwhelming majority of patients. Relapse occurs due to multiple factors such as inability of drugs to cross blood­brain barrier, immunosuppressive tumor microenvironment, stemness nature of glioma cells, tumor heterogeneity and enhanced hypoxia and angiogenic factors. Therefore, there is an urgent need to develop an innovative treatment approach to treat glioblastoma. Recently, several treatment strategies known as immunotherapies including CAR T cell therapy, dendritic cell vaccines, immune checkpoints blockade and oncolytic virus, nano particles and gene editing/silencing technology have demonstrated promising results in preclinical and few clinical trials. Furthermore, to increase the efficacy of these novel strategies, combinatorial approaches are being implemented for the treatment. This includes CAR T cell therapy in combination with small molecules, immune checkpoint inhibitors and oncolytic virus and nanoparticles plus gene editing, silencing or immune checkpoints inhibitors. These treatments have shown exciting results in preclinical settings and few of these trials are in progress. The review summarizes these combinatorial novel approaches and discusses them in detail.

Machine-learning approach to predict molecular subgroups of medulloblastoma using multiparametric MRI-based tumor radiomics.

OBJECTIVE: Image-based prediction of molecular subgroups of Medulloblastoma (MB) has the potential to optimize and personalize therapy. The objective of the study is to distinguish between broad molecular subgroups of MB using MR-Texture analysis. METHODS: Thirty-eight MB patients treated between 2007 and 2020 were retrospectively analyzed. Texture analysis was performed on contrast enhanced T1(T1C) and T2 weighted (T2W) MR images. Manual segmentation was performed on all slices and radiomic features were extracted which included first order, second order (GLCM - Grey level co-occurrence matrix) and shape features. Feature enrichment was done using LASSO (Least Absolute Shrinkage and Selection Operator) regression and thereafter Support Vector Machine (SVM) and a 10-fold cross-validation strategy was used for model development. The area under Receiver Operator Characteristic (ROC) curve was used to evaluate the model. RESULTS: A total of 174 and 170 images were obtained for analysis from the Axial T1C and T2W image datasets. One hundred and sixty-four MR based texture features were extracted. The best model was arrived at by using a combination of 30 GLCM and six shape features on T1C MR sequence. A 10-fold cross-validation demonstrated an AUC of 0.93, 0.9, 0.93, and 0.93 in predicting WNT, SHH, Group 3, and Group 4 MB subgroups, respectively. CONCLUSION: Radiomic analysis of MR images in MB can predict molecular subgroups with acceptable degree of accuracy. The strategy needs further validation in an external dataset for its potential use in ab initio management paradigms of MBs. ADVANCES IN KNOWLEDGE: Medulloblastoma can be classified into four distinct molecular subgroups using radiomic feature classifier from non-invasive Multiparametric Magnetic resonance imaging. This can have future ramifications in the extent of surgical resection of Medulloblastoma which can ultimately result in reduction of morbidity.

Long-Term Clinical Outcomes and Sequelae of Therapy in Early-Stage Orbital Mucosa-Associated Lymphoid Tissue Lymphoma.

INTRODUCTION: Orbital mucosa-associated lymphoid tissue (MALT) lymphoma, which are rare and indolent, often present at an early stage. We report the efficacy and safety outcomes of treatment in these patients. METHODS: We analyzed adult patients with stage IE or IIE orbital MALT lymphoma between 1999 and 2017 treated at our institute. We assessed local control (LC) rates, overall survival (OS), relapse-free survival (RFS) using Kaplan Meier method and the incidence of late toxicities. RESULTS: Seventy patients were analyzed for clinical outcomes. The median age at diagnosis was 52 years (IQR-45-62 years). Radiotherapy was offered to 97% of patients and the dose ranged from 36 to 45 Gy. Chemotherapy was administered in 5(7.1%) patients. Relapse occurred in 8 patients (local: 2, distant: 6). At a median follow-up of 101 months (IQR-47-146 months), the median OS and RFS was not reached. 8-year OS, RFS and LC rates were 96.5%, 88.5%, 96.7% respectively. Univariate analysis showed age ≤60 years and lacrimal involvement significantly correlated with better OS (P = .01 and .04, respectively). Cataract was the most common sequelae observed in 31 patients (44.3%). CONCLUSION: Moderate doses of radiotherapy are curative in early-stage orbital MALT lymphoma with favorable clinical outcomes. Lower doses of radiation can reduce the toxicity further, without compromising efficacy.

Predicting IDH subtype of grade 4 astrocytoma and glioblastoma from tumor radiomic patterns extracted from multiparametric magnetic resonance images using a machine learning approach.

Background and purpose: Semantic imaging features have been used for molecular subclassification of high-grade gliomas. Radiomics-based prediction of molecular subgroups has the potential to strategize and individualize therapy. Using MRI texture features, we propose to distinguish between IDH wild type and IDH mutant type high grade gliomas. Methods: Between 2013 and 2020, 100 patients were retrospectively analyzed for the radiomics study. Immunohistochemistry of the pathological specimen was used to initially identify patients for the IDH mutant/wild phenotype and was then confirmed by Sanger's sequencing. Image texture analysis was performed on contrast-enhanced T1 (T1C) and T2 weighted (T2W) MR images. Manual segmentation was performed on MR image slices followed by single-slice multiple sampling image augmentation. Both whole tumor multislice segmentation and single-slice multiple sampling approaches were used to arrive at the best model. Radiomic features were extracted, which included first-order features, second-order (GLCM-Grey level co-occurrence matrix), and shape features. Feature enrichment was done using LASSO (Least Absolute Shrinkage and Selection Operator) regression, followed by radiomic classification using Support Vector Machine (SVM) and a 10-fold cross-validation strategy for model development. The area under the Receiver Operator Characteristic (ROC) curve and predictive accuracy were used as diagnostic metrics to evaluate the model to classify IDH mutant and wild-type subgroups. Results: Multislice analysis resulted in a better model compared to the single-slice multiple-sampling approach. A total of 164 MR-based texture features were extracted, out of which LASSO regression identified 14 distinctive GLCM features for the endpoint, which were used for further model development. The best model was achieved by using combined T1C and T2W MR images using a Quadratic Support Vector Machine Classifier and a 10-fold internal cross-validation approach, which demonstrated a predictive accuracy of 89% with an AUC of 0.89 for each IDH mutant and IDH wild subgroup. Conclusion: A machine learning classifier of radiomic features extracted from multiparametric MRI images (T1C and T2w) provides important diagnostic information for the non-invasive prediction of the IDH mutant or wild-type phenotype of high-grade gliomas and may have potential use in either escalating or de-escalating adjuvant therapy for gliomas or for using targeted agents in the future.