bluuebunny/crossref_metadata_2025_split huggingface dataset:
BIOM-48. UTILITY OF CIRCULATING TUMOR DNA (CTDNA) FROM CEREBROSPINAL FLUID (CSF) FOR PROGNOSIS OF PATIENTS WITH RECURRENT HIGH-GRADE GLIOMA
Authors: Miller Alexandra M , Nandakumar Subhiksha , Holle Bridget M , Kreitzer Christoph , Song Timothy , Tartaro Marlene , Hertz Charli Ann J , Rafailov Johnathan , Campos Carl , Brannon A Rose , Solit David B , Pasquini Luca , Meng Alicia , Reiner Anne , Young Robert , Socci Nicholas D , Arcila Maria E , Berger Michael F , Schultz Nikolaus , Mellinghoff Ingo K 
Published: November 2024

Abstract
High-grade gliomas (HGGs) are the most aggressive primary brain tumors, and molecular characterization is vital for their diagnosis and treatment. Due to their location, tumor sampling is often challenging. Therefore, developing minimally invasive diagnostic methods is urgently needed. Here we report that circulating tumor DNA (ctDNA) from cerebrospinal fluid (CSF) can identify key genomic alterations and track clonal evolution in HGGs. Detection of CSF ctDNA correlates with leptomeningeal disease and overall survival, indicating its potential for integration into clinical decision-making. Our study includes 313 samples from 253 patients with recurrent glioma treated at MSKCC who underwent CSF collection using the MSK-IMPACT targeted sequencing assay. 37% of genomic alterations were detected using our less stringent variant calling criteria and Gaussian Mixture Model to call copy number events. CSF ctDNA positivity was determined by the presence of at least one oncogenic disease-defining alteration or any shared alteration with the tumor. We found 212 CSF ctDNA positive (68%) and 101 CSF ctDNA negative (32%) samples. CSF ctDNA positivity was the highest amongst histone mutant tumors (96%). We noticed 44% of alterations shared between the tumor and the CSF, additionally, we noted considerable tumor evolution particularly within the growth signaling pathways (e.g. PDGFRA). Our cohort demonstrated that patients with positive CSF ctDNA had a significantly shorter overall survival compared to those who were CSF ctDNA negative (4.83 months vs 14.14 months, HR 2.4, p &lt; 0.001). Radiographic findings such as enhancing disease and contact of the tumor with the ventricular space were positively associated with CSF ctDNA positivity. Additionally, CSF ctDNA was associated with positive cytology in 12/12 cases (100%). With our improved pipeline, we hypothesize CSF ctDNA may be used as a prognostic biomarker for survival, but confirmation requires further validation in a prospective study.
BIOM-56. HEAT SHOCK PROTEINS PREDICT CLINICAL RESPONSE AND POTENTIATE LOCAL IMMUNOGENICITY AFTER LITT FOR GLIOBLASTOMA
Authors: Chandar Jay , Berke Chandler , Seetharam Deepa , Govindarajan Vasundara , Bhatia Shovan , Valdez Mynor Mendez , Desgraves Jelisah , Jaman Emade , Lu Victor , Castro Jesus , Hudson Anna , Ramsoomair Christian , Ivan Michael , Komotar Ricardo , Shah Ashish 
Published: November 2024

Abstract
Glioblastoma (GBM) remains one of the deadliest cancers despite advances in therapies. Laser interstitial thermal therapy (LITT) is a minimally invasive technique used to ablate intra-axial brain tumors. Non-ablative LITT-induced hyperthermia (33-43˚C) increases intra-tumoral mutational burden and neoantigen production, promoting neoantigen presentation via heat shock proteins (HSPs). HSPs are protein-folding chaperones that present novel intracellular antigens for immune recognition. We investigated HSPs as predictors of local immune response and clinical outcomes of GBM patients undergoing LITT. We conducted immune deconvolution of bulk RNA-sequencing data from The Cancer Genome Atlas to determine the correlation between 97 unique HSPs and tumor infiltration of CD8+, CD4+, B, macrophage, neutrophil, and dendritic cells. We evaluated the association between HSP expression and overall survival (OS). Pre-LITT biopsies from 9 patients (responders and non-responders) were analyzed via immunohistochemistry (IHC) to identify spatial HSP expression. Next-generation sequencing was utilized to validate findings and identify other predictive biomarkers. We identified two HSPs for further investigation: SACS and HSPA5. SACS was associated with improved survival based on TCGA data (14.9 vs. 11 months, HR:1.3, p&lt;0.0001). HSPA5 was associated with worse outcomes (12.1 vs. 15.0 months, HR:0.73, p&lt;0.0001). Immune deconvolution showed HSPA5 positively correlated with dendritic cell infiltration (r=0.50, p=6.1E-27) and SACS with CD8+ infiltration (r=0.31, p=6.8E-11). IHC of 9 patients demonstrated high SACS expression was associated with improved OS (p&lt;0.05) after LITT. Multiplex IHC illustrated that immune cell infiltration was associated with therapeutic response post-LITT. Our ongoing immunohistochemical and genomic analyses aim to clarify the role of HSPs in enhancing immunogenicity in GBM. Further investigation into SACS and immune cell infiltration may reveal how hyperthermia via LITT improves response through neoantigen presentation.
BIOM-58. RE-INDUCTION OF INTRATHECAL CHEMOTHERAPY IN PRIOR RESPONDERS AND CORRELATION WITH CEREBROSPINAL FLUID CIRCULATING TUMOR CELLS
Authors: Yazzie Skye Dawn , Orosco Heather , Turpin Tiffany , Bazhenova Lyudmila , Shatsky Rebecca , Schulte Jessica , Piccioni David 
Published: November 2024

Abstract

INTRODUCTION
Leptomeningeal carcinomatosis (LMC) is an aggressive form of metastasis, with a historically poor median overall survival. Newer therapies and treatment strategies are improving outcomes, and more long-term responders exist. However, there are limited options for intrathecal (IT) chemotherapy, and re-induction in prior responders may be a reasonable treatment strategy. In addition, quantitative cerebrospinal fluid circulating tumor cells (CSF CTCs) are a valuable tool in LMC, for both surveillance of recurrence and evaluation of response.

METHODS
We retrospectively identified 10 patients with LMC who showed a response to IT chemotherapy and were followed with quantitative CSF CTCs on a commercially available platform. At progression, patients underwent re-induction of IT chemotherapy, on a twice a week schedule, and were evaluated for response.

RESULTS
All 10 patients were treated with re-induction IT chemotherapy. Six patients were re-challenged with topotecan, 3 with topotecan + trastuzumab, and 1 with pemetrexed + trastuzumab. Six patients had a primary diagnosis of breast cancer, three with lung cancer and one with ovarian cancer. The median KPS was 70. Eight were female. Prior to re-induction, all 10 had an increase in quantitative CSF CTCs. Only 1/10 had new symptoms, and 5/10 showed imaging changes on MRI. At the time of re-induction, 3/10 also received stereotactic radiosurgery to brain metastases and 2/10 had a change in systemic chemotherapy. 9/10 had improved CSF CTC counts on the next restaging, typically at 8 weeks. The median overall survival from re-challenge was 12.7 months.

CONCLUSION
Quantitative CSF CTCs were a more sensitive predictor of recurrence than symptoms or imaging, and were a marker of response to re-induction IT chemotherapy. Re-induction showed a durable survival benefit, and is a reasonable treatment strategy in patients who were prior responders
BIOM-67. DIFFERENTIAL DNA METHYLATION PATTERNS IN THE CSF OF PATIENTS WITH DIFFUSE GLIOMAS
Authors: Wang Daniel , Shah Mauli , Arjuna Srividya , Dono Antonio , Patel Chirag , Huse Jason , Kerrigan Brittany Parker , Nguyen Sophia , Lang Frederick , Esquenazi Yoshua , Ballester Leomar 
Published: November 2024

Abstract
Studies have shown that different central nervous system (CNS) tumor types exhibit unique DNA methylation profiles. DNA methylation-based machine learning classification of CNS tumor tissue has been demonstrated to be highly-accurate in differentiating between tumor types, including between diffuse glioma subtypes. While similar analyses have been performed using cell-free DNA (cfDNA) from blood, few studies have looked at the potential of DNA methylation as a biomarker for diffuse gliomas using CSF-derived cfDNA. In this study, we analyzed CSF cfDNA methylation patterns in diffuse glioma patients. DNA methylation profiling of CSF of patients with glioblastoma, IDH-wildtype (GBM) (n=37), IDH-mutant diffuse gliomas (n=12), and non-neoplastic conditions (n=5) was performed using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). Methylation quantification was estimated for each genomic region. Significance testing was performed between diagnostic groups to discover differentially-methylated regions (DMRs). The 300 most differentially-methylated regions (DMRs) for each comparison (IDH-wildtype vs. IDH-mutant, IDH-mutant vs. control, IDH-wildtype vs. control), for a total of 900 DMRs, were utilized as features in dimensionality reduction analysis and machine learning. Out of ~1×107 defined genomic regions, there were ~7×105 DMRs between GBM and control samples and ~1.5×106 DMRs between GBM and IDH-mutant samples, accounting for ~7% and ~15% of the genome, respectively. Uniform manifold approximation and projection (UMAP) and hierarchical clustering analysis revealed that samples were mostly clustered by diagnosis. Random forest analysis of the 900 DMRs with an 80/20 train/test split resulted in an overall accuracy of 0.815. In conclusion, CSF cfDNA methylation profiles of diffuse glioma patients exhibit differential methylation patterns between IDH-mutant and IDH-wildtype tumors, as well as between tumor and control, and could be informative biomarkers for the diagnosis of patients with diffuse gliomas.
BIOM-68. OUTCOMES IN PATIENTS WITH HIGH-GRADE MENINGIOMA (HGM): A MULTI-INSTITUTIONAL STUDY
Authors: Mohammed Nasser , Patel Chirag , Balar Ashish , Van Buskirk Samuel , McGovern Susan , Raza Shaan , DeMonte Franco , Ballester Leomar , Youssef Michael , Kamiya-Matsuoka Carlos 
Published: November 2024

Abstract

BACKGROUND
High-grade meningiomas (HGMs) are associated with increased risk of recurrence after primary treatment. This study aimed to evaluate factors affecting survival.

METHODS
We performed a multi-institutional retrospective chart review study of patients with HGM (defined as grade 2 or 3 meningioma) whose tumor had undergone next-generation sequencing. Statistical testing was performed in Stata/MP version 16.1 (StataCorp, College Station, TX) on the patients’ demographic, anatomic, clinical, and survival data (using Kaplan-Meier survivor function and long-rank test). Data are presented as mean±SD, median [interquartile range], or percent. Age/time reported in years.

RESULTS
There were 46 patients (45.7% female) with an age of 57.9±14.0 at initial HGM diagnosis. The most frequent HGM sites were middle cranial fossa (37.0%), frontal (28.3%), parietal (15.2%), posterior fossa (13.0%), parasagittal (10.9%), and petrous (10.9%). The most common presenting symptoms were headache (37.0%), seizure (23.9%), weakness (21.7%), vision changes (19.6%), memory issues (10.9%), and diplopia (10.9%). The most frequent gene mutations were in NF2 (58.7%), CDKN2A (13.0%), and TERT (8.7%). Median follow-up was 2.85 [1.4-7], during which time 65.2% of patients experienced recurrence. mPFS was 2.7 [0.83-6]. Kaplan-Meier analysis showed a mPFS of 5 [1.2-9] and 2.3 [0.8-3] in females and males, respectively (p=0.26). Age and Ki67 proliferative index at diagnosis did not significantly predict PFS. mOS was not reached (NR) [7-NR]. NF2 mutation status and presence of extracranial invasion did not significantly separate the PFS Kaplan-Meier curves on log-rank testing. However, the presence of NF2 mutation [mOS NR (5.2-NR) vs. NR (7-NR), p&lt;0.0001], extracranial invasion [mOS 10 (2.4-NR) vs. NR (NR-NR), p&lt;0.0001], and HGM recurrence [mOS NR (2.7-NR) vs. NR (7-NR), p&lt;0.0001], were associated with shorter mOS.

CONCLUSIONS
These HGM patients experienced a high recurrence rate during the follow-up period. The presence of NF2 mutation, extracranial invasion, and recurrent HGM were associated with shorter OS.
BIOM-69. THE ONCOGENIC FLIP IN PATIENTS WITH LEPTOMENINGEAL METASTATIC DISEASE (LMD): LONGITUDINAL DETECTION IN CEREBROSPINAL FLUID TUMOR CELLS (CSF-TCS) REVEALS IMPLICATIONS FOR DIFFERENTIAL TREATMENT OF THE LMD TUMOR
Authors: Tripathy Arushi , Corkos Perry , Blouw Barbara , Moore Melissa , LaFrance Norman , Hedrick Marc , Youssef Michael , Piccioni David , Nagpal Seema , Kumthekar Priya 
Published: November 2024

Abstract

INTRODUCTION
Patients with LMD have poor prognosis and limited treatment options. Oncogene amplification of primary, metastatic, and CNS metastatic tumors can be heterogeneous. Therefore, patients with LMD may benefit from assessment of clinically relevant biomarkers in CSF, which may guide the choice of a targeted therapy specifically for the LMD tumor. CNSide is a CLIA-validated laboratory-developed test ordered commercially at the discretion of physicians for CSF-TC enumeration, immunocytochemical (ICC) and fluorescence in situ hybridization (FISH) analysis of oncogene amplification. We longitudinally analyze oncogenes in CSF-TCs in patients with LMD of various primary cancers.

METHODS
CSF was collected from patients with suspected or confirmed LMD; 613 tests were ordered on 218 individual patients with breast (N=105 patients), lung (N=65), gastrointestinal (N=10), and other cancers. Using CNSide, CSF-TCs were isolated and tested via ICC (ER, PD-L1, and PR), and FISH (ALK, cMET, cMyc, EGFR, FGFR1, HER2, NTRK1, NTRK3, PTEN, RET, and ROS1).

RESULTS
In patients with lung cancer, ALK was detected in 14% (17/118) of samples, CMET in 61% (78/128), HER2 in 73% (16/22), and RET in 4% (4/90). In patients with breast cancer, HER2 was detected in 39% (65/168) of samples, FGFR1 in 32% (19/60), ER in 26% (44/168) and PR in 4% (5/120). 66 patients underwent 2+ CSF draws; 24 underwent 5+. Among these, there were 13 ICC flips (7 acquired mutations) and 58 FISH probe detection flips (26 acquired mutations). 20/66 patients (30.3%) had at least one flip in their ordered biomarkers.

CONCLUSION
CNSide can be used to detect oncogene amplification on CSF-TCs of patients with LMD, and mutational status of the LMD tumor may differ from the original tumor biopsy. CSF-TC analysis may provide therapeutic insights that vary from the original tumor and could open the door to additional treatment targets for patients struck with LMD.
BIOM-70. CSF TUMOR CELL (CSF-TC) DETECTION, QUANTIFICATION AND BIOMARKER ASSESSMENT HELPS IN CLINICAL MANAGEMENT OF BREAST CANCER AND NON-SMALL CELL LUNG CANCER PATIENTS HAVING LEPTOMENINGEAL DISEASE (FORESEE STUDY, NCT05414123)
Authors: Kumthekar Priya , Youssef Michael , Yang Jonathan , Piccioni David , Beruti Sue , Gillis Laura , Gordon Kelly , Blouw Barbara , Moore Melissa , LaFrance Norman , Hedrick Marc , Nagpal Seema 
Published: November 2024

Abstract
Leptomeningeal metastases (LM) or the presence of cancer cells in the cerebrospinal fluid (CSF)/pia remains a challenging disease to diagnosis and treat. Current standard of care methods to diagnose or assess treatment response of LM (Clinical Evaluation, MRI and Cytology) have limited sensitivity and specificity and are poorly quantifiable. This creates challenges for physicians to manage LM or determine the best course of treatment. The FORESEE Study was a multi-center, prospective clinical trial evaluating a novel diagnostic platform, CNSide, that aimed to overcome these challenges. The FORESEE study enrolled patients with breast or non-Small Cell Lung Cancer (NSCLC) with suspicion of or confirmed LM. CNSide can detect and quantify tumor cells in the CSF from patients with breast cancer or NSCLC having a suspicious or confirmed LM. This platform also is able to identify actionable mutations in the CSF via Fluorescent In Situ Hybridization (FISH) and next-generation sequencing. The primary end point of the FORESEE study was clinical utility and the impact of CNSide on physician treatment decisions. Secondary endpoints included evaluating the clinical performance of CNSide vs. cytology in tumor cell detection (sensitivity, specificity, PPV and NPV). The study enrolled 40 patients (22 breast cancer and 18 NSCLC). Each patient underwent standard of care diagnostic evaluations at baseline and at three follow up timepoints through their treatment. CNSide aided clinical decision making in 93% (50/54) of the clinical decisions. At baseline 39 patients were assessed and confirmed a positive LM diagnosis in 15% (6/39), a negative LM diagnosis in 8% (3/39), progression in 15% (6/39), resolution in 15% (6/39) and no progression, or resolution in 36% (14/39) of the patients. CNSide informed the specific drug selected for treatment in 26% (10/39) patients at baseline and demonstrated clinical high utility. The FORESEE data is undergoing ongoing analysis; updated analysis will be presented at the meeting.
BIOM-75. MRI FLAIR SIGNAL ASSESSMENT IN NEURO-ONCOLOGY (SANO) AS A MEASURABLE TIMEPOINT FOR INTERVENTIONAL THERAPY PRIOR TO PROGRESSION IN HIGH GRADE GLIOMAS: A WINDOW OF OPPORTUNITY
Authors: Gatson Na Tosha , Chen Shuyi , Ornelas Sara , Bross Shane 
Published: November 2024

Abstract

BACKGROUND
There are no validated clinical or radiographic assessments for response to therapy in glioblastoma (GBM). Offering interventions at the time of progression using our current assessment tools is likely too late as second-line therapies have failed to significantly delay progression and extend survival. In 2020, our team was first in the US to publish the largest and most comprehensive retrospective review identifying the T2/FLAIR MRI signal assessment protocol as an early indicator of progressive GBM. We proposed that the time of FLAIR signal abnormality within the resection cavity (RC) anticipated GBM progression by nearly 4 months and if used as a timepoint for therapeutic intervention could reshape glioma clinical trial design.

METHODS
To support validation of SANO, a prospective assessment of 146 GBM patients between 2019-2021 yielded 71 cases meeting resection and imaging inclusion criteria. We analyzed sequential brain MRIs from initial diagnosis to first progression for development of T2 FLAIR signal intensity (SI) within the RC as previously reported (Gatson et al 2020) and included cases with ventricle associated surgery as a comparator. PFS and OS were evaluated using Kaplan-Meier curves stratified by SI.

RESULTS
Development of SI occurred in 80.3% (n=57) GBM patients on average 2.8 months before RANO-assessed progression. A faster time to progression from SI development occurred in cases with ventricle associated RC. SI-positivity again portended poorer outcomes for PFS and OS as compared to SI-negative cases. Use of the eye (globe) for FLAIR assessment, instead of the ventricles, to qualitatively discern the presence of SI in ventricle associated RC.

CONCLUSIONS
This small prospective review supports our initial findings to validate a highly sensitive brain tumor imaging biomarker, SI, and should at least supplement existing response assessment criteria to improve declaration of GBM progression. Furthermore, use of SANO might also offer an earlier window of opportunity for salvage therapy intervention and offer new avenues for glioma clinical trial design.
BIOS-06. MACHINE LEARNING MODEL INDEPENDENTLY IDENTIFIES CLINICAL FEATURES ASSOCIATED WITH WILD-TYPE GLIOBLASTOMA VERSUS MUTANT GRADE 4 ASTROCYTOMA
Authors: Abdelmoneum Farida , Stoller Jared , Muldoon Leslie , Ambady Prakash , Jr Ramon Barajas 
Published: November 2024

Abstract

BACKGROUND
Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, presents significant clinical challenges due to its invasive nature and high recurrence rates. Understanding the clinical demographic factors associated with IDH wild-type (IDH-wt) versus mutant grade 4 astrocytoma (IDH-Mut) is critical for prognosis and treatment strategies. This study aimed to utilize a novel machine learning method to identify key clinical and demographic factors linked to IDH status.

METHODS
The Cancer Imaging Archive dataset included 617 patients but required preprocessing and cleaning. The cleaning process ensured data completeness and consistency by removing non-relevant variables like date and time, resulting in 20 potential predictors and 317 observations. A random forest model using Gini impurity score was built to classify patient IDH status. The dataset was split into a training set (two-thirds) and a test set (one-third). A variable importance plot identified significant variables based on the mean decrease in the Gini index.

RESULTS
Our machine learning model achieved 98% accuracy on the test set, outperforming the previously published model of 80% accuracy. A variable importance plot identified age at diagnosis, gender, ethnicity, and race as key predictors of IDH status, with age being the most important. Age was the most important predictor, but race (Caucasian) and ethnicity (not Hispanic or Latino) were also significant.

CONCLUSIONS
We present a highly accurate machine learning model for differentiating glioma IDH molecular status based only on patient clinical and demographic factors; improving upon prior published models. Future work will use a generalized logistic model to explore variable interactions and predict IDH-wt versus IDH-Mut status. These steps are vital for enhancing predictive accuracy and supporting personalized treatment strategies. Furthermore, we will define associations and interactions between these variables with other biological and therapeutic variables in predicting clinical outcome.
BIOS-07. GRADUAL METABOLIC ALTERATIONS RESTRUCTURE THE SPATIAL ARCHITECTURE AND IMMUNITY IN GLIOBLASTOMA
Authors: Kueckelhaus Jan , Kada-Benotmane Jasim , Schnell Oliver , Beck Jürgen , Villa Giulia , Heiland Dieter-Henrik 
Published: November 2024

Abstract
The organized layered structure of the human neocortex contrasts sharply with the chaotic architecture of malignant CNS tumors. The heterogenous nature of glioblastoma (GBM) poses significant challenges to research and treatment, given that effective strategies require consistent biological patterns. Here, we leverage recent advances in spatial biology, integrating spatially resolved transcriptomics and metabolomics to identify drivers of GBM-specific architectural evolution. We performed spatial metabolomics (MALDI) and transcriptomics (Visium n=43 and MERFISH n=25) on glioblastoma patients, with computational analysis conducted using the SPATA2 R package. Our findings reveal that most spatial recurrent patterns in glioblastoma emerge in a gradient-like organization, particularly influenced by proximity to areas of necrosis and hypoxia. Samples without hypoxic regions demonstrated less spatial organization. Metabolomic and transcriptomic profiling indicated enhanced responses to hypoxia, reduced cell proliferation, and elevated expression indicative of the S phase in cell division near necrotic regions. The vicinity to hypoxic areas was associated with increased extracellular matrix remodeling and epithelial-to-mesenchymal transition, suggesting that the invasive capabilities of GBM cells originate from these hypoxic niches. By further integrating spatially resolved TCR-sequencing, we identified that hypoxic gradients drive defined T cell responses with a higher likelihood of T cell dysfunction within a distance of 235 µm (sd: 132 µm) to hypoxia. This suggests that the presence of necrosis, hypoxia, and hypoxia-associated metabolites could serve as potential predictive markers for T-cell behavior and exhaustion in glioblastoma. Our study offers an in-depth analysis of the influence of two prevalent niches in glioblastoma: necrosis and hypoxia. We reveal that the complex architecture of glioblastoma is not solely dictated by genetic randomness and stochastic occurrences but is significantly influenced by spatial proximity to key factors like necrosis and hypoxia. This insight contributes to an evolving model that seeks to unravel the intricate biology underpinning this formidable disease.