Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS: Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS: The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION: The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

Evolving Barriers to Clinical Trial Enrollment and Clinical Care in Neuro-oncology in the Face of COVID-19.

The lack of treatments with durable response in neuro-oncology highlights the critical need for clinical trials to advance patient care. The intersection of relatively low incidence, evolving classification schema, and entrenched community, healthcare provider, and organizational factors have been historic challenges against successful trial enrollment and implementation. The additional need for multidisciplinary, often tertiary-level care, further magnifies latent national and international health inequities with rural and under-served populations. The COVID-19 pandemic both unveiled fundamental weaknesses in historical approaches and prompted the necessity of new approaches and systems for conducting clinical trials. Here, we provide an overview of traditional barriers to clinical trial enrollment in neuro-oncology, the effect of COVID-19 on these barriers, and the discovery of additional systemic weaknesses. Finally, we discuss future directions by reflecting on lessons learned with strategies to broaden access of care and streamline clinical trial integration into clinical practice.

Proteomic clusters underlie heterogeneity in preclinical Alzheimer's disease progression.

Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-ß (Aß)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aß42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.

Homologous Recombination Deficiency (HRD) in Cutaneous Oncology.

Skin cancers, including basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (SCC), and melanoma, are the most common malignancies in the United States. Loss of DNA repair pathways in the skin plays a significant role in tumorigenesis. In recent years, targeting DNA repair pathways, particularly homologous recombination deficiency (HRD), has emerged as a potential therapeutic approach in cutaneous malignancies. This review provides an overview of DNA damage and repair pathways, with a focus on HRD, and discusses major advances in targeting these pathways in skin cancers. Poly(ADP-ribose) polymerase (PARP) inhibitors have been developed to exploit HRD in cancer cells. PARP inhibitors disrupt DNA repair mechanisms by inhibiting PARP enzymatic activity, leading to the accumulation of DNA damage and cell death. The concept of synthetic lethality has been demonstrated in HR-deficient cells, such as those with BRCA1/2 mutations, which exhibit increased sensitivity to PARP inhibitors. HRD assessment methods, including genomic scars, RAD51 foci formation, functional assays, and BRCA1/2 mutation analysis, are discussed as tools for identifying patients who may benefit from PARP inhibitor therapy. Furthermore, HRD has been implicated in the response to immunotherapy, and the combination of PARP inhibitors with immunotherapy has shown promising results. The frequency of HRD in melanoma ranges from 18% to 57%, and studies investigating the use of PARP inhibitors as monotherapy in melanoma are limited. Further research is warranted to explore the potential of PARP inhibition in melanoma treatment.

Cerebrospinal fluid neurofilament light chain is a marker of aging and white matter damage.

BACKGROUND: Cerebrospinal fluid (CSF) neurofilament light chain (NfL) reflects neuro-axonal damage and is increasingly used to evaluate disease progression across neurological conditions including Alzheimer disease (AD). However, it is unknown how NfL relates to specific types of brain tissue. We sought to determine whether CSF NfL is more strongly associated with total gray matter, white matter, or white matter hyperintensity (WMH) volume, and to quantify the relative importance of brain tissue volume, age, and AD marker status (i.e., APOE genotype, brain amyloidosis, tauopathy, and cognitive status) in predicting CSF NfL. METHODS: 419 participants (Clinical Dementia Rating [CDR] Scale > 0, N = 71) had CSF, magnetic resonance imaging (MRI), and neuropsychological data. A subset had amyloid positron emission tomography (PET) and tau PET. Pearson correlation analysis was used to determine the association between CSF NfL and age. Multiple regression was used to determine which brain volume (i.e., gray, white, or WMH volume) most strongly associated with CSF NfL. Stepwise regression and dominance analyses were used to determine the individual contributions and relative importance of brain volume, age, and AD marker status in predicting CSF NfL. RESULTS: CSF NfL increased with age (r = 0.59, p < 0.001). Elevated CSF NfL was associated with greater total WMH volume (p < 0.001), but not gray or white matter volume (p's > 0.05) when considered simultaneously. Age and WMH volume were consistently more important (i.e., have greater R2 values) than AD markers when predicting CSF NfL. CONCLUSIONS: CSF NfL is a non-specific marker of aging and white matter integrity with limited sensitivity to specific markers of AD. CSF NfL likely reflects processes associated with cerebrovascular disease.

Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease.

Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-ß42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-ß42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.

Network dysfunction in cognitively normal APOE ε4 carriers is related to subclinical tau.

INTRODUCTION: Apolipoprotein E (APOE) ε4 allele status is associated with amyloid and tau-related pathological changes related to Alzheimer's disease (AD). However, it is unknown whether brain network changes are related to amyloid beta (Aß) and/or tau-related pathology in cognitively normal APOE ε4 carriers with subthreshold Aß accumulation. METHODS: Resting state functional connectivity measures of network integrity were evaluated in cognitively normal individuals (n = 121, mean age 76.6 ± 7.8 years, 15% APOE ε4 carriers, 65% female) with minimal Aß per cerebrospinal fluid (CSF) or amyloid positron emission tomography. RESULTS: APOE ε4 carriers had increased lateralized connections relative to callosal connections within the default-mode, memory, and salience networks (P = .02), with significant weighting on linear regression toward CSF total tau (P = .03) and CSF phosphorylated tau at codon 181 (P = .03), but not CSF Aß42 . DISCUSSION: Cognitively normal APOE ε4 carriers with subthreshold amyloid accumulation may have network reorganization associated with tau.

Correction of distortion in flattened representations of the cortical surface allows prediction of V1-V3 functional organization from anatomy.

Several domains of neuroscience offer map-like models that link location on the cortical surface to properties of sensory representation. Within cortical visual areas V1, V2, and V3, algebraic transformations can relate position in the visual field to the retinotopic representation on the flattened cortical sheet. A limit to the practical application of this structure-function model is that the cortex, while topologically a two-dimensional surface, is curved. Flattening of the curved surface to a plane unavoidably introduces local geometric distortions that are not accounted for in idealized models. Here, we show that this limitation is overcome by correcting the geometric distortion induced by cortical flattening. We use a mass-spring-damper simulation to create a registration between functional MRI retinotopic mapping data of visual areas V1, V2, and V3 and an algebraic model of retinotopy. This registration is then applied to the flattened cortical surface anatomy to create an anatomical template that is linked to the algebraic retinotopic model. This registered cortical template can be used to accurately predict the location and retinotopic organization of these early visual areas from cortical anatomy alone. Moreover, we show that prediction accuracy remains when extrapolating beyond the range of data used to inform the model, indicating that the registration reflects the retinotopic organization of visual cortex. We provide code for the mass-spring-damper technique, which has general utility for the registration of cortical structure and function beyond the visual cortex.

Functional magnetic resonance imaging adaptation reveals a noncategorical representation of hue in early visual cortex.

Color names divide the fine-grained gamut of color percepts into discrete categories. A categorical transition must occur somewhere between the initial encoding of the continuous spectrum of light by the cones and the verbal report of the name of a color stimulus. Here, we used a functional magnetic resonance imaging (fMRI) adaptation experiment to examine the representation of hue in the early visual cortex. Our stimuli varied in hue between blue and green. We found in the early visual areas (V1, V2/3, and hV4) a smoothly increasing recovery from adaptation with increasing hue distance between adjacent stimuli during both passive viewing (Experiment 1) and active categorization (Experiment 2). We examined the form of the adaptation effect and found no evidence that a categorical representation mediates the release from adaptation for stimuli that cross the blue-green color boundary. Examination of the direct effect of stimulus hue on the fMRI response did, however, reveal an enhanced response to stimuli near the blue-green category border. This was largest in hV4 and when subjects were engaged in active categorization of the stimulus hue. In contrast with a recent report from another laboratory (Bird, Berens, Horner, & Franklin, 2014), we found no evidence for a categorical representation of color in the middle frontal gyrus. A post hoc whole-brain analysis, however, revealed several regions in the frontal cortex with a categorical effect in the adaptation response. Overall, our results support the idea that the representation of color in the early visual cortex is primarily fine grained and does not reflect color categories.

The fine-scale functional correlation of striate cortex in sighted and blind people.

To what extent are spontaneous neural signals within striate cortex organized by vision? We examined the fine-scale pattern of striate cortex correlations within and between hemispheres in rest-state BOLD fMRI data from sighted and blind people. In the sighted, we find that corticocortico correlation is well modeled as a Gaussian point-spread function across millimeters of striate cortical surface, rather than degrees of visual angle. Blindness produces a subtle change in the pattern of fine-scale striate correlations between hemispheres. Across participants blind before the age of 18, the degree of pattern alteration covaries with the strength of long-range correlation between left striate cortex and Broca's area. This suggests that early blindness exchanges local, vision-driven pattern synchrony of the striate cortices for long-range functional correlations potentially related to cross-modal representation.

A systematic framework for predictive biomarkers in immune effector cell-associated neurotoxicity syndrome.

Chimeric antigen receptor (CAR)-T cell therapy has revolutionized the management of several life-threatening malignancies, often achieving durable sustained responses. The number of patients treated with this new class of cell-based therapy, along with the number of Food and Drug Association (FDA) approved indications, are growing significantly. Unfortunately Immune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) can often occur after treatment with CAR-T cells, and severe ICANS can be associated with significant morbidity and mortality. Current standard treatments are mainly steroids and supportive care, highlighting the need for early identification. In the last several years, a range of predictive biomarkers have been proposed to distinguish patients at increased risk for developing ICANS. In this review, we discuss a systematic framework to organize potential predictive biomarkers that builds on our current understanding of ICANS.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways.

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Gut microbiome composition may be an indicator of preclinical Alzheimer's disease.

Alzheimer's disease (AD) pathology is thought to progress from normal cognition through preclinical disease and ultimately to symptomatic AD with cognitive impairment. Recent work suggests that the gut microbiome of symptomatic patients with AD has an altered taxonomic composition compared with that of healthy, cognitively normal control individuals. However, knowledge about changes in the gut microbiome before the onset of symptomatic AD is limited. In this cross-sectional study that accounted for clinical covariates and dietary intake, we compared the taxonomic composition and gut microbial function in a cohort of 164 cognitively normal individuals, 49 of whom showed biomarker evidence of early preclinical AD. Gut microbial taxonomic profiles of individuals with preclinical AD were distinct from those of individuals without evidence of preclinical AD. The change in gut microbiome composition correlated with ß-amyloid (Aß) and tau pathological biomarkers but not with biomarkers of neurodegeneration, suggesting that the gut microbiome may change early in the disease process. We identified specific gut bacterial taxa associated with preclinical AD. Inclusion of these microbiome features improved the accuracy, sensitivity, and specificity of machine learning classifiers for predicting preclinical AD status when tested on a subset of the cohort (65 of the 164 participants). Gut microbiome correlates of preclinical AD neuropathology may improve our understanding of AD etiology and may help to identify gut-derived markers of AD risk.

Comparison of amyloid burden in individuals with Down syndrome versus autosomal dominant Alzheimer's disease: a cross-sectional study.

BACKGROUND: Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people. METHODS: In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid ß42 (Aß42) to Aß40 (Aß42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aß42/40 was evaluated. FINDINGS: 192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aß42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p<0·0001) and in people with Down syndrome (n=32; r=-0·801; p<0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome. INTERPRETATION: Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome. FUNDING: The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.

Case report: Real-world experience using a personalized cancer-specific circulating tumor DNA assay in different metastatic melanoma scenarios.

Circulating-tumor DNA (ctDNA) has emerged as an important biomarker for monitoring disease status in cancer patients. Different ctDNA testing platforms have shown promising results in the early detection of disease, monitoring response to treatment, and prognostication in metastatic melanoma. However, several challenges exist, including the reduced shedding of ctDNA into the bloodstream in the metastatic setting, differences in sensitivity among various ctDNA assays, and the inherent inability to distinguish tumor-specific mutations from other mutations that are not related to the cancer of interest. Using a ctDNA assay that is designed to detect multiple single-nucleotide variants (SNVs) that are specific to the tumor itself may allow for more accurate monitoring of disease status in metastatic melanoma. In this case series, we describe a real-world experience using a personalized, tumor-informed ctDNA assay to monitor the clinical trajectories of four patients with metastatic melanoma. Our report highlights potential benefits and limitations using ctDNA in this setting to inform clinical decision-making. This report provides a proof of concept of the technique using an mPCR-NGS-based ctDNA assay (Signatera TM) in the clinical context and in adjunct with other radiological information. Large cohort prospective trials would be needed to validate the utility and validity of this approach.

Corrigendum: Identification and management of aggressive meningiomas.

[This corrects the article DOI: 10.3389/fonc.2022.851758.].

Identification and Management of Aggressive Meningiomas.

Meningiomas are common primary central nervous system tumors derived from the meninges, with management most frequently entailing serial monitoring or a combination of surgery and/or radiation therapy. Although often considered benign lesions, meningiomas can not only be surgically inaccessible but also exhibit aggressive growth and recurrence. In such cases, adjuvant radiation and systemic therapy may be required for tumor control. In this review, we briefly describe the current WHO grading scale for meningioma and provide demonstrative cases of treatment-resistant meningiomas. We also summarize frequently observed molecular abnormalities and their correlation with intracranial location and recurrence rate. We then describe how genetic and epigenetic features might supplement or even replace histopathologic features for improved identification of aggressive lesions. Finally, we describe the role of surgery, radiotherapy, and ongoing systemic therapy as well as precision medicine clinical trials for the treatment of recurrent meningioma.

Prolonged response of recurrent IDH-wild-type glioblastoma to laser interstitial thermal therapy with pembrolizumab.

Despite the improved understanding of the molecular and genetic heterogeneity of glioblastoma, there is still an unmet need for better therapeutics, as treatment approaches have remained unchanged in recent years. Research into the role of the immune microenvironment has generated enthusiasm for testing immunotherapy (specifically, immune checkpoint inhibitors). However, to date, trials of immunotherapy in glioblastoma have not demonstrated a survival advantage. Combination approaches aimed at optimally inducing response to immune checkpoint inhibitors with radiotherapy are currently being investigated. Herein, the authors describe their experience of the potential benefit and clinical outcomes of using combination pembrolizumab (an immune checkpoint inhibitor) and laser interstitial thermal therapy in a case series of patients with recurrent IDH-wild-type glioblastoma.

Assessment of Pretreatment and Posttreatment Evolution of Neurofilament Light Chain Levels in Patients Who Develop Immune Effector Cell-Associated Neurotoxicity Syndrome.

Importance: Determining whether neurofilament light chain (NfL) elevations in patients who develop immune effector cell-associated neurotoxicity syndrome (ICANS) occur before or after infusion of cellular product is important to identify high-risk patients and inform whether neuroaxonal injury is latent or a consequence of treatment. Objective: To quantify serial NfL levels in patients undergoing cellular therapy. Design, Setting, and Participants: This retrospective 2-center study examined plasma NfL levels in 30 patients with detailed medical and treatment history, including all major pretreatment and posttreatment risk factors. Exclusion criteria included dementia and severe, symptomatic central nervous system (CNS) involvement. Main Outcomes and Measures: Patients' NfL levels were measured at 7 time points: baseline (prelymphodepletion), during lymphodepletion, postinfusion day (D) 1, D3, D7, D14, and D30. Prediction accuracy for the development of ICANS was next modeled using receiver operating characteristic (ROC) classification. Finally, univariate and multivariate modeling examined the association between NfL levels, ICANS, and potential risk factors including demographic (age, sex), oncologic (tumor burden, history of CNS involvement), neurologic (history of nononcologic CNS disease or neuropathy), and neurotoxic exposure histories (vincristine, cytarabine, methotrexate, or CNS radiotherapy). Results: A total of 30 patients (median [range] age, 64 [22-80] years; 12 women [40%] and 18 men [60%]) were included. Individuals who developed ICANS had elevations in NfL prior to lymphodepletion and chimeric antigen receptor T-cell infusion compared with those who did not develop ICANS (no ICANS: 29.4 pg/mL, vs any ICANS: 87.6 pg/mL; P < .001). Baseline NfL levels further predicted ICANS development with high accuracy (area under the ROC curve, 0.96), sensitivity (0.91), and specificity (0.95). Levels of NfL remained elevated across all time points, up to 30 days postinfusion. Baseline NfL levels correlated with ICANS severity but not demographic factors, oncologic history, nononcologic neurologic history, or history of exposure to neurotoxic therapies. Conclusions and Relevance: In a subset of patients in this cross-sectional study, the risk of developing ICANS was associated with preexisting neuroaxonal injury that was quantifiable with plasma NfL level. This latent neuroaxonal injury was present prior to drug administration but was not associated with historic neurotoxic therapies or nononcologic neurologic disease. Preinfusion NfL may further permit early screening and identification of patients most at risk for ICANS. Additional studies are needed to determine NfL's utility as a predictive biomarker for early (preemptive or prophylactic) intervention and to delineate the origin of this underlying neural injury.

A randomized feasibility study evaluating temozolomide circadian medicine in patients with glioma.

Background: Gliomas are the most common primary brain tumor in adults. Current treatments involve surgery, radiation, and temozolomide (TMZ) chemotherapy; however, prognosis remains poor and new approaches are required. Circadian medicine aims to maximize treatment efficacy and/or minimize toxicity by timed delivery of medications in accordance with the daily rhythms of the patient. We published a retrospective study showing greater anti-tumor efficacy for the morning, relative to the evening, administration of TMZ in patients with glioblastoma. We conducted this prospective randomized trial to determine the feasibility, and potential clinical impact, of TMZ chronotherapy in patients with gliomas (NCT02781792). Methods: Adult patients with gliomas (WHO grade II-IV) were enrolled prior to initiation of monthly TMZ therapy and were randomized to receive TMZ either in the morning (AM) before 10 am or in the evening (PM) after 8 pm. Pill diaries were recorded to measure compliance and FACT-Br quality of life (QoL) surveys were completed throughout treatment. Study compliance, adverse events (AE), and overall survival were compared between the two arms. Results: A total of 35 evaluable patients, including 21 with GBM, were analyzed (18 AM patients and 17 PM patients). Compliance data demonstrated the feasibility of timed TMZ dosing. There were no significant differences in AEs, QoL, or survival between the arms. Conclusions: Chronotherapy with TMZ is feasible. A larger study is needed to validate the effect of chronotherapy on clinical efficacy.