Risk-stratification for treatment de-intensification in WNT-pathway medulloblastoma: finding the optimal balance between survival and quality of survivorship.

INTRODUCTION: Advances in molecular biology have led to consensus classification of medulloblastoma into four broad molecular subgroups - wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4, respectively. Traditionally, children >3 years of age, with no/minimal residual tumor (<1.5 cm2) and lack of metastasis were classified as average-risk disease with >80% long-term survival. Younger age (<3 years), large residual disease (≥1.5 cm2), and leptomeningeal metastases either alone or in combination were considered high-risk features yielding much worse 5-year survival (30-60%). This clinico-radiological risk-stratification has been refined by incorporating molecular/genetic information. Contemporary multi-modality management for non-infantile medulloblastoma entails maximal safe resection followed by risk-stratified adjuvant radio(chemo)therapy. Aggressive multi-modality management achieves good survival but is associated with substantial dose-dependent treatment-related toxicity prompting conduct of subgroup-specific prospective clinical trials. AREAS COVERED: We conducted literature search on PubMed from 1969 till 2023 to identify putative prognostic factors and risk-stratification for medulloblastoma, including molecular subgrouping. Based on previously published data, including our own institutional experience, we discuss molecular risk-stratification focusing on WNT-pathway medulloblastoma to identify candidates suitable for treatment de-intensification to strike the optimal balance between survival and quality of survivorship. EXPERT OPINION: Prospective clinical trials and emerging biological information should further refine risk-stratification in WNT-pathway medulloblastoma.

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.

Clinico-Radiological Outcomes in WNT-Subgroup Medulloblastoma.

Medulloblastoma (MB) comprises four broad molecular subgroups, namely wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4, respectively, with subgroup-specific developmental origins, unique genetic profiles, distinct clinico-demographic characteristics, and diverse clinical outcomes. This is a retrospective audit of clinical outcomes in molecularly confirmed WNT-MB patients treated with maximal safe resection followed by postoperative standard-of-care risk-stratified adjuvant radio(chemo)therapy at a tertiary-care comprehensive cancer centre. Of the 74 WNT-MB patients registered in a neuro-oncology unit between 2004 to 2020, 7 patients accrued on a prospective clinical trial of treatment deintensification were excluded, leaving 67 patients that constitute the present study cohort. The median age at presentation was 12 years, with a male preponderance (2:1). The survival analysis was restricted to 61 patients and excluded 6 patients (1 postoperative mortality plus 5 without adequate details of treatment or outcomes). At a median follow-up of 72 months, Kaplan-Meier estimates of 5-year progression-free survival and overall survival were 87.7% and 91.2%, respectively. Traditional high-risk features, large residual tumour (≥1.5 cm2), and leptomeningeal metastases (M+) did not significantly impact upon survival in this molecularly characterized WNT-MB cohort treated with risk-stratified contemporary multimodality therapy. The lack of a prognostic impact of conventional high-risk features suggests the need for refined risk stratification and potential deintensification of therapy.

Epilepsia Partialis Continua as a Sequelae of Measles Infection in Children With Hematolymphoid Malignancies.

PURPOSE: To share our clinical experience with the diagnosis and management of children with hematolymphoid malignancies presenting with epilepsia partialis continua (EPC) as a sequelae of measles infection. MATERIALS AND METHODS: In December 2022, a series of children in our hemato-oncology unit presented with focal status epilepticus with no conclusive evidence pointing toward any underlying etiology. One such child had a typical measles rash a few weeks before the onset of this focal status epilepticus. After a series of cases with a similar presentation, a clinical pattern suspicious for measles became evident. cerebrospinal fluid polymerase chain reaction was positive for measles virus with measles immunoglobin M detected in the serum. This led to the diagnosis of measles inclusion-body encephalitis in a series of children who presented with EPC over a period of 3 months. EPC is a rare manifestation of measles that is seen only in immunocompromised patients. RESULTS: Among the 18 children reported in this series, only 10 had a history of rashes. The rash was mostly transient and elicited only on retrospective history taking. Five of the 18 children who did not lose consciousness during the prolonged seizure episode survived the disease but had residual neurologic sequelae. Among the 18 children, two were unimmunized and immunization status could not be confirmed in three other children. CONCLUSION: This case series highlights the threats posed by measles infection in children with cancer who are immunosuppressed because of the underlying disease and ongoing chemotherapy. Loss of herd immunity because of declining measles immunization rates secondary to vaccine hesitancy and COVID-19 lockdown pose a greater risk of measles infection and its complications for patients with deficient immune systems.

CDKN2A/B deletion in IDH-mutant astrocytomas: An evaluation by Fluorescence in-situ hybridization.

INTRODUCTION: CDKN2A/B homozygous deletion is one of the defining features of grade 4 in IDH-mutant astrocytic tumours. AIM: To evaluate CDKN2A/B-deletion in IDH-mutant astrocytic tumours and its clinicopathological impact. MATERIALS AND METHODS: CDKN2A/B-deletion was evaluated by Fluorescence in-situ hybridisation (FISH) and interpreted by two recently accepted methods. RESULTS: Eighty-three out of 94 cases (histologically-grade 2: 3, grade 3: 46, grade 4: 34) were interpretable on FISH. Concordant CDKN2A/B-deletion was observed in 71% (27/38) of lower-grade tumours (n = 49) and 90% (27/30) of histological grade 4 tumours (n = 34). Both the interpretation methods showed good agreement (Kappa = 0.75). CDKN2A/B-deletion showed an inverse correlation for < 10% MIB-1 labeling index (p = 0.01) while that by method-2 showed a significant correlation for grade 4 (p = 0.02). No significant correlation was observed for any other clinicopathological parameters. Twenty-four patients showed progression/recurrence (including deaths), and no significant difference in frequency of CDKN2A/B deletion was observed among cases with disease progression across different histological grades. CONCLUSIONS: CDKN2A/B-deletion was observed across all the histological grades of IDH-mutant astrocytic tumours, expectedly more in the higher grade. FISH, as a method, can be used for the detection of CDKN2A/B homozygous deletion, when there is concordant interpretation.

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.

High-Grade Gliomas from Subventricular Zone: Proteomic Drivers of Aggressiveness Using Fluorescence-Guided Multiple Sampling.

High-grade gliomas (HGGs) are among the most aggressive brain tumors and are characterized by dismally low median survival time. Of the many factors influencing the survival of patients with HGGs, proximity to the subventricular zone (SVZ) is one of the key influencers. In this context, 5-amino levulinic acid fluorescence-guided multiple sampling (FGMS) offers the prospect of understanding patient-to-patient molecular heterogeneity driving the aggressiveness of these tumors. Using high-resolution liquid chromatography-mass spectrometry (MS)/MS proteomics for HGGs from seven patients (four SVZ associated and three SVZ nonassociated), this study aimed to uncover the mechanisms driving the aggressiveness in SVZ-associated (SVZ+) HGGs. Differential proteomics analysis revealed significant dysregulation of 11 proteins, of which 9 proteins were upregulated and 2 were downregulated in SVZ+ HGGs compared to SVZ-non-associated (SVZ-) HGGs. The gene set enrichment analysis (GSEA) of the proteomics dataset revealed enrichment of MYC targets V1 and V2, G2M checkpoints, and E2F targets in SVZ+ HGGs. With GSEA, we also compared the pathways enriched in glioma stem cell subpopulations and observed a similar expression trend for most pathways in our data. In conclusion, this study reveals new and emerging insights on pathways that may potentially contribute to greater aggressiveness in SVZ+ HGGs. Future studies using FGMS in larger cohorts are recommended to help uncover the proteomics and molecular basis of aggressiveness and stemness in HGGs.

BRAF V600E Mutations and Beyond: A Molecular Perspective of Melanoma from a Tertiary Cancer Referral Center of India.

Vaibhavi VengurlekarObjectives Malignant melanoma demonstrates frequently occurring mutations of genes in the serine/threonine kinase pathway, namely BRAF, NRAS, and neurofibromin 1. There is rare documentation of a detailed analysis of these mutations in cases of melanoma among Indian patients. We present molecular features in cases of malignant melanoma, diagnosed at a tertiary cancer referral center in India, over a period of 8 years (2011-2018). Materials and Methods This study was performed on formalin fixed paraffin embedded tissues of 88 histologically confirmed cases of malignant melanoma. BRAF gene alterations were studied by both Sanger sequencing and real-time polymerase chain reaction techniques ( n = 74). Molecular testing for BRAF and NRAS gene alterations was accomplished in 74/88 cases (80%). Molecular test results were correlated with clinicopathological features using IBM SPSS Statistical software 25.0. Results The age ranged from 13 to 79 years (median = 57), with a M:F ratio of 1.4:1. BRAF mutations were observed in 12/74 (16.21%) patients, including V600E ( n = 7), A594T ( n = 1), T599 = ( n = 2), V600K ( n = 1), and Q612P ( n = 1), while NRAS mutations were observed in 6/38 (15.7%) patients. Among various subtypes, nodular melanoma was the most frequent subtype (33%) among cutaneous malignant melanomas. Among non-cutaneous melanomas, mucosal melanomas were observed in 37.5% of cases. Conclusion This constitutes one of the few reports on comprehensive analysis of molecular alterations underlying melanomas in Indian patients. A larger sample size, with more extensive molecular markers, would yield additional information on the disease manifestation.

Integrated Meta-Omics Analysis Unveils the Pathways Modulating Tumorigenesis and Proliferation in High-Grade Meningioma.

Meningioma, a primary brain tumor, is commonly encountered and accounts for 39% of overall CNS tumors. Despite significant progress in clinical research, conventional surgical and clinical interventions remain the primary treatment options for meningioma. Several proteomics and transcriptomics studies have identified potential markers and altered biological pathways; however, comprehensive exploration and data integration can help to achieve an in-depth understanding of the altered pathobiology. This study applied integrated meta-analysis strategies to proteomic and transcriptomic datasets comprising 48 tissue samples, identifying around 1832 common genes/proteins to explore the underlying mechanism in high-grade meningioma tumorigenesis. The in silico pathway analysis indicated the roles of extracellular matrix organization (EMO) and integrin binding cascades in regulating the apoptosis, angiogenesis, and proliferation responsible for the pathobiology. Subsequently, the expression of pathway components was validated in an independent cohort of 32 fresh frozen tissue samples using multiple reaction monitoring (MRM), confirming their expression in high-grade meningioma. Furthermore, proteome-level changes in EMO and integrin cell surface interactions were investigated in a high-grade meningioma (IOMM-Lee) cell line by inhibiting integrin-linked kinase (ILK). Inhibition of ILK by administrating Cpd22 demonstrated an anti-proliferative effect, inducing apoptosis and downregulating proteins associated with proliferation and metastasis, which provides mechanistic insight into the disease pathophysiology.

Deep learning based clinico-radiological model for paediatric brain tumor detection and subtype prediction.

Aim: Early diagnosis of paediatric brain tumors significantly improves the outcome. The aim is to study magnetic resonance imaging (MRI) features of paediatric brain tumors and to develop an automated segmentation (AS) tool which could segment and classify tumors using deep learning methods and compare with radiologist assessment. Methods: This study included 94 cases, of which 75 were diagnosed cases of ependymoma, medulloblastoma, brainstem glioma, and pilocytic astrocytoma and 19 were normal MRI brain cases. The data was randomized into training data, 64 cases; test data, 21 cases and validation data, 9 cases to devise a deep learning algorithm to segment the paediatric brain tumor. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the deep learning model were compared with radiologist's findings. Performance evaluation of AS was done based on Dice score and Hausdorff95 distance. Results: Analysis of MRI semantic features was done with necrosis and haemorrhage as predicting features for ependymoma, diffusion restriction and cystic changes were predictors for medulloblastoma. The accuracy of detecting abnormalities was 90%, with a specificity of 100%. Further segmentation of the tumor into enhancing and non-enhancing components was done. The segmentation results for whole tumor (WT), enhancing tumor (ET), and non-enhancing tumor (NET) have been analyzed by Dice score and Hausdorff95 distance. The accuracy of prediction of all MRI features was compared with experienced radiologist's findings. Substantial agreement observed between the classification by model and the radiologist's given classification [K-0.695 (K is Cohen's kappa score for interrater reliability)]. Conclusions: The deep learning model had very high accuracy and specificity for predicting the magnetic resonance (MR) characteristics and close to 80% accuracy in predicting tumor type. This model can serve as a potential tool to make a timely and accurate diagnosis for radiologists not trained in neuroradiology.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.

BACKGROUND: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. METHODS: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. RESULTS: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. CONCLUSIONS: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Primary central nervous system lymphoma: Comprehension of cell-of-origin subtypes.

Primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) is an uncommon extranodal lymphoma that accounts for more than 95% of all the CNS lymphomas. Unlike its systemic/nodal counterpart, which is currently subtyped into cell-of origin (COO) subtypes, its feasibility and utility are largely debatable in PCNS-DLBCL. Objectives: To classify PCNS-DLBCL into COO-subtypes based on immunohistochemical algorithms by Hans and Choi and evaluate concordance between the two. A further aim is to investigate the clinicoradiological and histomorphological parameters of the subtypes thus obtained. Materials and Methods: As many as 143 cases of primary CNS lymphoma were evaluated by immunohistochemistry for CD10, BCL6, MUM1, GCET, and FOXP1 and based on which the said 143 cases were further classified into COO subtypes using Hans and Choi algorithms. Results: Mean age was 53.8 years with marginal male preponderance and predominantly centroblastic morphology (75.5%). CD 10 was positive in 8.9% of the cases, BCL6 in 58.6%, MUM1 in 89.9%, GCET in 32.9%, and FOXP1 in 79.5%. As much as 84.9% cases were of non-germinal center B-cell (GCB) subtype and 15.1% cases were of GCB subtype as determined based on Hans algorithm. Furthermore, 90.7% cases were of activated B-cell (ABC) subtype and 9.3% cases were of GCB subtype according to Choi algorithm. A 91.8% concordance was observed between Hans and Choi algorithms. Among the 6 discordant cases, 5 cases were subtyped as GCB by Hans and ABC by Choi and 1 case as ABC by Hans and GCB by Choi. Conclusion: Most of PCNS-DLBCLs are of non-GCB/ABC COO subtype, but inconsistences abound in the utility of IHC algorithms in PCNS-DLBCL COO subtypes.

Outcomes and prognostic factors of patients with Extranodal NK T cell lymphoma (ENKTL).

The staging, prognostication, and treatment of ENKTL has evolved over the years with better understanding of the disease biology. There is significant heterogeneity in the treatment followed across the world. Literature from India have been few with small number of patients. We studied the outcomes and prognostic factors of patients with ENKTL treated between May 2010 and December 2021 at our center. A total of 78 patients diagnosed with ENKTL were treated at our center. L-asparaginase based chemotherapy was administered in 84% of the patients. Close to 2/3rd patients received SMILE chemotherapy. After a median follow-up of 30 months (18.5-41.4 months), the median relapse free survival and overall survival for the overall population was 45 months (12-118 months) and 45 months (14-118 months) respectively. By multivariate analysis, PINK score of 2-4, non-receipt of RT and non-achievement of CR were associated with poor survival.

Mature Teratoma with Somatic-Type Malignancy: An Entity of Unacquaintance-A Case Report.

Primary intracranial teratomas are nongerminomatous germ cell tumors. They are infrequent lesions along the craniospinal axis, with their malignant transformation extremely uncommon. A 50-year-old-male patient presented with one episode of generalized tonic-clonic seizure (GTCS), without any neurological deficit. Radiological imaging revealed a large lesion in the pineal region. He underwent gross total excision of the lesion. Histopathological examination was representative of teratoma with adenocarcinomatous malignant transformation. He underwent adjuvant radiation therapy and had an excellent clinical outcome. The present case highlights the rarity of malignant transformation of the primary intracranial mature teratoma.

Primary Intracranial Germ Cell Tumors: A Study with an Integrated Clinicopathological Approach.

Background and Objective: Primary intracranial germ cell tumors (ICGCTs) are rare and are histologically classified as germinomas and non-germinomatous with distinctive prognostic and therapeutic implications. ICGCTs, essentially due to the inherent difficulty of surgical access, pose different challenges and management connotations than their extracranial counterparts. This is a retrospective analysis of histologically verified ICGCTs, which was undertaken to evaluate various clinicopathological features and their implications on patient management. Materials and Methods: Eighty-eight histologically diagnosed cases (over 14 years) of ICGCT at our institute formed the study cohort and were classified into germinoma and non-germinomatous germ cell tumors (NGGCTs). Additionally, germinomas were further subdivided on the basis of 1) tumor marker (TM) levels, as germinoma with normal TM, mildly elevated TM, and markedly elevated TM and 2) radiology features, as germinomas with typical radiology and atypical radiological features. Results: ICGCT with age ≤6 years (P = 0.049), elevated TM (P = 0.047), and NGGCT histology (P < 0.001) showed significantly worse outcomes. Furthermore, germinomas with markedly elevated TM and certain atypical radiological features showed prognosis akin to NGGCT. Conclusions: Analysis of our largest single cancer center Indian patient cohort of ICGCT shows that inclusion of age ≤6 years, raised TM, and certain radiological features may assist clinicians in overcoming the limitations of surgical sampling, with better prognostication of histologically diagnosed germinomas.

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).

Deep proteome investigation of high-grade gliomas reveals heterogeneity driving differential metabolism of 5-aminolevulinic acid.

Background: Fluorescence-guided surgery (FGS) using 5-aminolevulinic acid (5-ALA) as adjunct for high-grade gliomas (HGGs) has been on the rise in recent years. Despite being largely effective, we observed multiple histologically similar sub-regions of the same tumor from a few individuals with varying protoporphyrin IX (PpIX) levels. The current study aims at understanding the proteomic changes driving differential metabolism of 5-ALA in HGGs. Methods: Biopsies were histologically and biochemically assayed. Following this, a deep proteomics investigation was carried out using high resolution liquid chromatography-mass spectrometry (HR LC-MS) to identify protein expression in differentially fluorescing regions of HGGs. Results: Our analysis identified 5437 proteins with high confidence. Differential analysis in the subgroup with HGGs carrying IDH mutation (IDH mt.) revealed 93 differentially regulated proteins (raw p-value ≤ 0.05 and absolute FC ≥ 1.5). Similar analysis in the IDH wild type (IDH wt.) subgroup revealed 20 differentially regulated proteins. Gene set enrichment analysis (GSEA) identified key pathways like ion channel transport, trafficking of AMPA receptors, and regulation of heme-oxygenase-1 in the IDH wt. subgroup. Pathways such as scavenging of heme, signaling by NOTCH4, negative regulation of PI3-AKT pathway, and iron uptake and transport were observed to be differentially regulated in the IDH mt. subgroup. Conclusions: Tumor regions from the same patient exhibiting differential fluorescence following 5-ALA administration were observed to have different proteome profiles. Future studies aimed at a better molecular understanding of 5-ALA metabolism in HGGs hold the potential to increase the efficacy of FGS and the use of 5-ALA as a theragnostic tool.

Pearls & Oy-sters: Primary Diffuse Leptomeningeal Melanocytosis: A Diagnostic Conundrum.

Primary diffuse leptomeningeal melanocytosis (PDLM) is an extremely rare CNS tumor with nonspecific clinicoradiologic features that overlap considerably with aseptic meningitis posing significant diagnostic and therapeutic challenges. We present one such case report of a patient treated empirically at first presentation as aseptic viral meningitis based on MRI and CSF analysis. Diagnosis of PDLM was established subsequently through meningeal biopsy that demonstrated a melanocytic tumor with fine granular melanin pigment without significant mitoses. Her systemic and ocular examination was unremarkable. Whole-body 18F-fluorodeoxyglucose PET/CT (FDG-PET/CT) did not identify any other primary site. Following ventriculoperitoneal shunt to relieve hydrocephalus, she was treated with definitive craniospinal irradiation plus whole-brain boost and remains stable on periodic clinicoradiologic surveillance. Optimal management of PDLM lacks consensus with role of radiotherapy, chemotherapy, targeted therapy and immunotherapy being controversial.

Targeted molecular profiling of solid tumours-Indian tertiary cancer centre experience.

PURPOSE: Molecular Profiling of solid tumours is extensively used for prognostic, theranostic, and risk prediction. Next generation sequencing (NGS) has emerged as powerful method for molecular profiling. The present study was performed to identify molecular alterations present in solid tumours in Indian tertiary cancer centre. METHODS: Study included 1140 formalin Fixed paraffin embedded samples. NGS was performed using two targeted gene panels viz. Ampliseq Focus panel and Sophia Solid Tumor Plus Solution. Data was analyzed using Illumina's Local Run Manager and SOPHiA DDM software. Variant interpretation and annotations were done as per AMP/ACMG guidelines. RESULTS: Total 896 cases were subjected to NGS after excluding cases with suboptimal nucleic acid quality/quantity. DNA alterations were detected in 64.9% and RNA fusions in 6.9% cases. Among detected variants, 86.7% were clinically relevant aberrations. Mutation frequency among different solid tumours was 70.8%, 67.4%, 64.4% in non-small cell lung (NSCLC), lung squamous cell carcinomas and head neck tumours respectively. EGFR, KRAS, BRAF, ALK and ROS1were commonly altered in NSCLC. Gastrointestinal tumours showed mutations in 63.6% with predominant alterations in pancreatic (88.2%), GIST (87.5%), colorectal (78.7%), cholangiocarcinoma (52.9%), neuroendocrine (45.5%), gall bladder (36.7%) and gastric adenocarcinomas (16.7%). The key genes affected were KRAS, NRAS, BRAF and PIK3CA. NGS evaluation identified co-occurring alterations in 37.7% cases otherwise missed by conventional assays. Resistance mutations were detected in progressive lung tumours (39.5%) against EGFR TKIs and ALK/ROS inhibitors. CONCLUSION: This is the largest Indian study on molecular profiling of solid tumours providing extensive information about mutational signatures using NGS.