Purines and purinergic receptors in primary tumors of the central nervous system.

Purine nucleotides and nucleosides play critical roles in various pathological conditions, including tumor cell growth. Adenosine triphosphate (ATP) activates pro-tumor receptors, while adenosine (ADO) is a potent immunosuppressant and modulator of cell growth. This study aims to analyze the purinergic actions of ATP and its metabolites, associated enzymes, and P1 or P2 class receptors in primary central nervous system tumors. Additionally, we sought to correlate the levels of nucleosides and the density of P1, P2X, and P2Y receptors in cells with tumor progression. The results indicate that purinergic signaling depends on the receptor concentration and signaling molecules specific to each cell type, tissue, and tumor histology. The purinergic system may function as either a tumor-promoting agent or an antitumor factor, depending on the microenvironmental conditions and the concentrations of receptors and their respective activators. Notably, ATP emerges as the most significant extracellular signal, capable of being converted into other cellular stimulators pertinent to neoplasms, such as adenosine diphosphate, adenosine monophosphate, adenosine, and inosine. Consequently, a cascade of responses to these stimuli promotes tumor development, cell division, and metastasis. Purine nucleotides in central nervous system tumors are pivotal in cellular responses in glioblastoma multiforme, vestibular schwannoma, medulloblastoma, adenomas, gliomas, meningiomas, and pineal tumors. These findings hold the potential for developing novel therapeutic strategies and aiding in therapeutic management.

The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis.

BACKGROUND: Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management. METHODS: Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications. RESULTS: 457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups. CONCLUSIONS: Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis.

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

A comprehensive genomic study of 390 H3F3A-mutant pediatric and adult diffuse high-grade gliomas, CNS WHO grade 4.

Malignant brain tumors, known as H3K27-altered diffuse midline glioma (DMG) and H3G34-mutant diffuse hemispheric glioma (DHG), can affect individuals of all ages and are classified as CNS WHO grade 4. We comprehensively characterized 390 H3F3A-mutant diffuse gliomas (201 females, 189 males) arising in pediatric patients (under 20 years old) and adults (20 years and older) evaluated by the CGP program at Foundation Medicine between 2013 and 2020. We assessed information from pathology reports, histopathology review, and clinical data. The cohort included 304 H3K27M-mutant DMG (156 females, 148 males) and 86 H3G34-mutant DHG (45 females, 41 males). Median patient age was 20 years (1-74 years). The frequency of H3K27M-mutant DMG was similar in both pediatric and adult patients in our cohort-48.6% of the patients were over 20 years old, 31.5% over 30, and 18% over 40 at initial diagnosis. FGFR1 hotspot point mutations (N546K and K656E) were exclusively identified in H3K27M-mutant DMG tumors (64/304, 21%; p = 0.0001); these tend to occur in older patients (median age: 32.5 years) and mainly arose in the diencephalon. H3K27M-mutant DMG had higher rates of mutations in NF1 (31.0 vs 8.1%; p = 0.0001) and PIK3CA/PIK3R1 (27.9% vs 15.1%; p = 0.016) compared to H3G34-mutant DHG. However, H3G34-mutant DHG had higher rates of targetable alterations in cell-cycle pathway genes (CDK4 and CDK6 amplification; CDKN2A/B deletion) (27.0 vs 9.0%). Potentially targetable PDGFRA alterations were identified in ~ 20% of both H3G34-mutant DHG and H3K27M-mutant DMG. Overall, in the present study H3K27M-mutant DMG occurred at similar rates in both adult and patient patients. Through our analysis, we were able to identify molecular features characteristic of DMG and DHG. By identifying the recurrent co-mutations including actionable FGFR1 point mutations found in nearly one-third of H3K27M-mutant DMG in young adults, our findings can inform clinical translational studies, patient diagnosis, and clinical trial design.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 3-Summary of Imaging Findings on Glioneuronal and Neuronal Tumors.

The fifth edition of the World Health Organization classification of central nervous system tumors published in 2021 reflects the current transitional state between traditional classification system based on histopathology and the state-of-the-art molecular diagnostics. This Part 3 Review focuses on the molecular diagnostics and imaging findings of glioneuronal and neuronal tumors. Histological and molecular features in glioneuronal and neuronal tumors often overlap with pediatric-type diffuse low-grade gliomas and circumscribed astrocytic gliomas (discussed in the Part 2 Review). Due to this overlap, in several tumor types of glioneuronal and neuronal tumors the diagnosis may be inconclusive with histopathology and genetic alterations, and imaging features may be helpful to distinguish difficult cases. Thus, it is crucial for radiologists to understand the underlying molecular diagnostics as well as imaging findings for application on clinical practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 2-Summary of Imaging Findings on Pediatric-Type Diffuse High-Grade Gliomas, Pediatric-Type Diffuse Low-Grade Gliomas, and Circumscribed Astrocytic Gliomas.

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. This Part 2 review focuses on the molecular diagnostics and imaging findings of pediatric-type diffuse high-grade gliomas, pediatric-type diffuse low-grade gliomas, and circumscribed astrocytic gliomas. Each tumor type in pediatric-type diffuse high-grade glioma mostly harbors a distinct molecular marker. On the other hand, in pediatric-type diffuse low-grade gliomas and circumscribed astrocytic gliomas, molecular diagnostics may be extremely complicated at a glance in the 2021 WHO classification. It is crucial for radiologists to understand the molecular diagnostics and imaging findings and leverage the knowledge in clinical practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1-Key Points of the Fifth Edition and Summary of Imaging Findings on Adult-Type Diffuse Gliomas.

The fifth edition of the World Health Organization (WHO) classification of central nervous system tumors published in 2021 advances the role of molecular diagnostics in the classification of gliomas by emphasizing integrated diagnoses based on histopathology and molecular information and grouping tumors based on genetic alterations. Importantly, molecular biomarkers that provide important prognostic information are now a parameter for establishing tumor grades in gliomas. Understanding the 2021 WHO classification is crucial for radiologists for daily imaging interpretation as well as communication with clinicians. Although imaging features are not included in the 2021 WHO classification, imaging can serve as a powerful tool to impact the clinical practice not only prior to tissue confirmation but beyond. This review represents the first of a three-installment review series on the 2021 WHO classification for gliomas, glioneuronal tumors, and neuronal tumors and implications on imaging diagnosis. This Part 1 Review focuses on the major changes to the classification of gliomas and imaging findings on adult-type diffuse gliomas. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 3.

Imaging in a new pediatric brain tumor-a supratentorial neuroepithelial tumor with PLAGL1 fusion.

Molecular diagnostics have dramatically influenced the classification of tumor groups in the 2021 WHO CNS tumor classification. Studies focusing on molecular diagnostics continue to identify new tumors. Soon after the summary of the new classification was published, "Supratentorial Neuroepithelial Tumor with PLAGL1 Fusion" was described as a distinct entity. Although this new entity is defined pathologically, its imaging features are undefined. This case report discusses the imaging findings and possible differential diagnosis of the new tumor.

Cytological features of cranial and paraspinal nerve Tumours.

The 2021 World Health Organization Classification of Central Nervous System Tumours introduced significant revisions to the categorization of paraspinal and nerve sheath tumours. This updated system encompasses seven tumour types: schwannoma, neurofibroma, perineurioma, hybrid nerve sheath tumours, malignant melanotic nerve sheath tumour, malignant peripheral nerve sheath tumour and cauda equina neuroendocrine tumour. This review provides an image-rich cytologic reference of these tumours, with particular emphasis on intraoperative smear preparations. Knowledge of the key cytological features of these tumours and their differential diagnoses will help guide classification of these challenging entities.

Review of the Recent Changes in the WHO Classification for Pediatric Brain and Spinal Cord Tumors.

BACKGROUND: Periodic updates to the World Health Organization (WHO) classification system for central nervous system (CNS) tumors reflect advances in the pathological diagnosis, categorization, and molecular underpinnings of primary brain, spinal cord, and peripheral nerve tumors. The 5th edition of the WHO Classification of CNS Tumors was published in 2021. This review discusses the guiding principles of the revision, introduces the more common new diagnostic entities, and describes tumor classification and nomenclature changes that are relevant for pediatric neurological surgeons. SUMMARY: Revisions to the WHO CNS tumor classification system introduced new diagnostic entities, restructured and renamed other entities with particular impact in the diffuse gliomas and CNS embryonal tumors, and expanded the requirements for incorporating both molecular and histological features of CNS tumors into a unified integrated diagnosis. Many of the new diagnostic entities occur at least occasionally in pediatric patients and will thus be encountered by pediatric neurosurgeons. New nomenclature impacts the terminology that is applied in communication between pathologists, surgeons, clinicians, and patients. Requirements for molecular information in tumor diagnosis are expected to refine diagnostic categories while also introducing practical considerations for intraoperative consultation, preliminary histological evaluation, and triaging of neurosurgical tissue samples for histology, molecular testing, and clinical trial requirements. KEY MESSAGES: Pediatric brain tumor diagnosis and clinical management are a multidisciplinary effort that is rapidly advancing in the molecular era. Interdisciplinary collaboration is critical for providing the best care for pediatric CNS tumor patients. Pediatric neurosurgeons and their local neuropathologists and neuro-oncologists must work collaboratively to put the most current CNS tumor diagnostic guidelines into standard practice.

Approaches to Incidental Intradural Tumors of the Spine in the Pediatric Population.

BACKGROUND: Incidental intradural tumors of the spine in the pediatric population are rare lesions whose management remains unclear. Surgeons must balance the risks of iatrogenic deficits and complications after surgical resection against the risks from progressive growth of the tumor. Moreover, the natural history of an incidental finding can be difficult to predict. Here, we review the literature on incidental intradural tumors of the spine and present considerations for their management. SUMMARY: Growth of the tumor or changes in radiographic features are usually indications for resection. Asymptomatic lesions can be found in patients with genetic syndromes that predispose to tumor formation, such as neurofibromatosis type 1 and 2, schwannomatosis, and Von-Hippel-Lindau syndrome, and careful workup of a genetic cause is warranted in any patient presenting with multiple tumors and/or cutaneous features. Close follow-up is generally favored given the heavy tumor burden; however, some recommend pre-emptive resection to prevent permanent neurological deficits. Incidental intradural tumors can also occur in association with hydrocephalus, significant syringomyelia, and cord compression, and surgical treatment is usually warranted. Tumors may also be discovered as part of the workup for scoliosis, where they are not truly incidental to the scoliosis but rather are contributing to curve deformation. KEY MESSAGES: Thorough workup of patients for associated genetic syndromes or comorbidities should be undertaken in pediatric patients with incidental intradural tumors. Further research is needed into the natural history of these incidental lesions. Incidental tumors can often be managed conservatively with close follow-up, with surgical intervention warranted for expanding tumors or new-onset symptoms.

Intracranial leptomeningeal CNS ganglioneuroblastoma. First report and review of the literature.

BACKGROUND: CNS ganglioneuroblastoma in an extremely rare embryonal tumour, specifically in the pediatric population. Bad prognosis is documented due to aggressiveness and absence of protocolized treatment at the moment. CLINICAL DESCRIPTION: We present the case of a 5-year-old boy who presented with sudden loss of consciousness. CT scan was performed showing a large posterior fossa lesion with several intraventricular focal lesions, suggesting metastases, the largest one located inside the III ventricle. The patient underwent a posterior fossa resection of the lesion and a subtotal resection of the III ventricle lesion, with adjuvant chemotherapy. The evolution was poor and the patient finally died 3 months after diagnosis. CONCLUSION: Ganglioneuroblastoma is extremely likely to recur quickly and extensively. There is little knowledge about treatment options but is documented that gross total resection followed by adjuvant radiotherapy and chemotherapy is the best management in these patients.

Tumors of the central nervous system among women treated with fertility drugs: a population-based cohort study.

PURPOSE: To investigate the association between fertility drugs and tumors of the central nervous system (CNS). METHODS: This cohort study was based on The Danish Infertility Cohort and included 148,016 infertile women living in Denmark (1995-2017). The study cohort was linked to national registers to obtain information on use of specific fertility drugs, cancer diagnoses, covariates, emigration, and vital status. Cox proportional hazard regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for all CNS tumors and separately for gliomas, meningiomas and diverse benign tumors of the brain and other parts of the CNS. RESULTS: During a median 11.3 years of follow-up, 328 women were diagnosed with CNS tumors. No marked associations were observed between use of the fertility drugs clomiphene citrate, gonadotropins, gonadotropin-releasing hormone receptor modulators and progesterone and CNS tumors. However, use of human chorionic gonadotropin was associated with a decreased rate of meningiomas (HR 0.49 95% CI 0.28-0.87). No clear associations with CNS tumors were observed according to time since first use or cumulative dose for any of the fertility drugs. CONCLUSION: No associations between use of most types of fertility drugs and CNS tumors were observed. However, our findings only apply to premenopausal women and additional studies with longer follow-up time are necessary.

Pediatric neurological cancer incidence and trends in the United States, 2000-2018.

OBJECTIVE: To characterize the epidemiological trends and sociodemographic variation of pediatric and adolescent neurological cancers by histological subtypes over time in the USA. METHODS: A total of 16,511 patients aged 0-19 years diagnosed with neurological cancers between 2000 and 2018, including 13,024 with central nervous system (CNS) neoplasms and 3,487 with neuroblastomas, were identified from 18 registries of the National Cancer Institute's Surveillance, Epidemiology, and End Results Program. Incidence trends over time and incidence rate ratios by race/ethnicity, sex, and age were calculated for histological subtype. Age-standardized incidence rates (ASIR) by year of diagnosis and average annual percent changes (AAPC) were calculated to measure incidence rates. ASIR by race/ethnicity, sex, and age were calculated to examine the incidence variation by these factors. RESULTS: Overall, age-standardized annual incidence per 100,000 person-years increased from 2.20 in 2000 to 3.21 in 2018 with an AAPC of 1.4% (95% confidence interval or CI: 0.5% to 2.4%); however, that of Hispanic decreased from 2.93 in 2000 to 2.59 in 2018 with an AAPC of - 0.8% (95% CI: - 1.2% to - 0.3%). Non-Hispanic Black children and adolescents had a statistically significantly lower incidence than non-Hispanic White peers both for CNS neoplasms (incidence rate ratio or IRR: 0.67; 95% CI: 0.63 to 0.71) and neuroblastomas (IRR: 0.75; 95% CI: 0.68 to 0.83). Females generally had a lower incidence than males, especially among those with intracranial and intraspinal embryonal tumors (IRR: 0.69; 95% CI: 0.64 to 0.75). The highest incidence rate of neuroblastoma was among newborns aged less than 1 year, and the highest incidence rate of CNS neoplasms was among children aged 1-4 years. CONCLUSION: The incidence of neurological cancers has increased among children and adolescents from 2000 to 2018, with wide variation across demographic groups.

The clinical significance of adenomatous polyposis coli (APC) and catenin Beta 1 (CTNNB1) genetic aberrations in patients with melanoma.

BACKGROUND: Melanoma-intrinsic activated ß-catenin pathway, the product of the catenin beta 1 (CTNNB1) gene, has been associated with low/absent tumor-infiltrating lymphocytes, accelerated tumor growth, metastases development, and resistance to anti-PD-L1/anti-CTLA-4 agents in mouse melanoma models. Little is known about the association between the adenomatous polyposis coli (APC) and CTNNB1 gene mutations in stage IV melanoma with immunotherapy response and overall survival (OS). METHODS: We examined the prognostic significance of somatic APC/CTNNB1 mutations in the Cancer Genome Atlas Project for Skin Cutaneous Melanoma (TCGA-SKCM) database. We assessed APC/CTNNB1 mutations as predictors of response to immunotherapies in a clinicopathologically annotated metastatic patient cohort from three US melanoma centers. RESULTS: In the TCGA-SKCM patient cohort (n = 434) presence of a somatic APC/CTNNB1 mutation was associated with a worse outcome only in stage IV melanoma (n = 82, median OS of APC/CTNNB1 mutants vs. wild-type was 8.15 vs. 22.8 months; log-rank hazard ratio 4.20, p = 0.011). APC/CTNNB1 mutation did not significantly affect lymphocyte distribution and density. In the 3-melanoma institution cohort, tumor tissues underwent targeted panel sequencing using two standards of care assays. We identified 55 patients with stage IV melanoma and APC/CTNNB1 genetic aberrations (mut) and 169 patients without (wt). At a median follow-up of more than 25 months for both groups, mut compared with wt patients had slightly more frequent (44% vs. 39%) and earlier (66% vs. 45% within six months from original diagnosis of stage IV melanoma) development of brain metastases. Nevertheless, time-to-development of brain metastases was not significantly different between the two groups. Fortunately, mut patients had similar clinical benefits from PD-1 inhibitor-based treatments compared to wt patients (median OS 26.1 months vs. 29.9 months, respectively, log-rank p = 0.23). Less frequent mutations in the NF1, RAC1, and PTEN genes were seen in the mut compared with wt patients from the 3-melanoma institution cohort. Analysis of brain melanoma tumor tissues from a separate craniotomy patient cohort (n = 55) showed that melanoma-specific, activated ß-catenin (i.e., nuclear localization) was infrequent (n = 3, 6%) and not prognostic in established brain metastases. CONCLUSIONS: APC/CTNNB1 mutations are associated with a worse outcome in stage IV melanoma and early brain metastases independent of tumor-infiltrating lymphocyte density. However, PD1 inhibitor-based treatments provide comparable benefits to both mut and wt patients with stage IV melanoma.

Creation of a successful multidisciplinary course in pediatric neuro-oncology with a systematic approach to curriculum development.

BACKGROUND: The St Jude Global Academy Neuro-Oncology Training Seminar (NOTS) is a hybrid course in pediatric neuro-oncology specifically designed for physicians from low-income and middle-income countries. METHODS: The curriculum for the course was created by conducting a targeted needs assessment that evaluated 11 domains of care for children with central nervous system (CNS) tumors. The targeted needs assessment was completed by 24 institutions across the world, and the data were used to define 5 core elements included in the 2 components of the NOTS: a 9-week online course and a 7-day in-person workshop. Participant acquisition of knowledge and changes in clinical behavior were evaluated as measures of success. RESULTS: Teams from 8 institutions located in 8 countries enrolled in the online course, and it was successfully completed by 36 participants representing 6 specialties. On the basis of their performance in the online course, 20 participants from 7 institutions took part in the on-site workshop. The participants exhibited improved knowledge in core elements of treating children with CNS tumors, including barriers of care, possible solutions, and steps for project implementation (P < .0001). All participants expressed a belief that they acquired new concepts and knowledge, leading to changes in their clinical practice. Those present at the workshop created an international multidisciplinary group focused on treating CNS tumors in low-income and middle-income countries. CONCLUSIONS: By using a hybrid online and in-person approach, the authors successfully created a multidisciplinary course focused on pediatric CNS tumors for resource-limited settings. Their experience supports this strategy as a feasible mechanism for driving further global collaborations.

Efficacy of Neratinib Plus Capecitabine in the Subgroup of Patients with Central Nervous System Involvement from the NALA Trial.

BACKGROUND: Neratinib has efficacy in central nervous system (CNS) metastases from HER2-positive metastatic breast cancer (MBC). We report outcomes among patients with CNS metastases at baseline from the phase III NALA trial of neratinib plus capecitabine (N + C) versus lapatinib plus capecitabine (L + C). MATERIALS AND METHODS: NALA was a randomized, active-controlled trial in patients who received two or more previous HER2-directed regimens for HER2-positive MBC. Patients with asymptomatic/stable brain metastases (treated or untreated) were eligible. Patients were assigned to N + C (neratinib 240 mg per day, capecitabine 750 mg/m2 twice daily) or L + C (lapatinib 1,250 mg per day, capecitabine 1,000 mg/m2 twice daily) orally. Independently adjudicated progression-free survival (PFS), overall survival (OS), and CNS endpoints were considered. RESULTS: Of 621 patients enrolled, 101 (16.3%) had known CNS metastases at baseline (N + C, n = 51; L + C, n = 50); 81 had received prior CNS-directed radiotherapy and/or surgery. In the CNS subgroup, mean PFS through 24 months was 7.8 months with N + C versus 5.5 months with L + C (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.41-1.05), and mean OS through 48 months was 16.4 versus 15.4 months (HR, 0.90; 95% CI, 0.59-1.38). At 12 months, cumulative incidence of interventions for CNS disease was 25.5% for N + C versus 36.0% for L + C, and cumulative incidence of progressive CNS disease was 26.2% versus 41.6%, respectively. In patients with target CNS lesions at baseline (n = 32), confirmed intracranial objective response rates were 26.3% and 15.4%, respectively. No new safety signals were observed. CONCLUSION: These analyses suggest improved PFS and CNS outcomes with N + C versus L + C in patients with CNS metastases from HER2-positive MBC. IMPLICATIONS FOR PRACTICE: In a subgroup of patients with central nervous system (CNS) metastases from HER2-positive breast cancer after two or more previous HER2-directed regimens, the combination of neratinib plus capecitabine was associated with improved progression-free survival and CNS outcomes compared with lapatinib plus capecitabine. These findings build on previous phase II and III studies describing efficacy of neratinib in the prevention and treatment of CNS metastases, and support a role for neratinib as a systemic treatment option in the management of patients with HER2-positive brain metastases following antibody-based HER2-directed therapies.

Investigation of the Relationship between CMYC Gene Polymorphisms and Glioma Susceptibility in Chinese Children.

Glioma is a common central nervous system tumors in children. CMYC has a range of functions that are disrupted in various tumor cells, and may contribute to the occurrence and development of glioma. Two CMYC single nucleotide polymorphisms (rs4645943C>T and rs2070583 A>G) were genotyped in 190 cases and 248 controls from Wenzhou and Guangzhou hospitals. After adjusting for age and sex, odds ratio and 95% confidence interval values were calculated by logistic regression to evaluate the correlation between CMYC gene polymorphisms and glioma risk; no significant associations were detected. These results require future validation in a larger sample cohort.

Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.

BACKGROUND: Differential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is useful to guide treatment strategies. PURPOSE: To investigate the use of a convolutional neural network (CNN) model for differentiation of PCNSL and GBM without tumor delineation. STUDY TYPE: Retrospective. POPULATION: A total of 289 patients with PCNSL (136) or GBM (153) were included, the average age of the cohort was 54 years, and there were 173 men and 116 women. FIELD STRENGTH/SEQUENCE: 3.0 T Axial contrast-enhanced T1 -weighted spin-echo inversion recovery sequence (CE-T1 WI), T2 -weighted fluid-attenuation inversion recovery sequence (FLAIR), and diffusion weighted imaging (DWI, b = 0 second/mm2 , 1000 seconds/mm2 ). ASSESSMENT: A single-parametric CNN model was built using CE-T1 WI, FLAIR, and the apparent diffusion coefficient (ADC) map derived from DWI, respectively. A decision-level fusion based multi-parametric CNN model (DF-CNN) was built by combining the predictions of single-parametric CNN models through logistic regression. An image-level fusion based multi-parametric CNN model (IF-CNN) was built using the integrated multi-parametric MR images. The radiomics models were developed. The diagnoses by three radiologists with 6 years (junior radiologist Y.Y.), 11 years (intermediate-level radiologist Y.T.), and 21 years (senior radiologist Y.L.) of experience were obtained. STATISTICAL ANALYSIS: The 5-fold cross validation was used for model evaluation. The Pearson's chi-squared test was used to compare the accuracies. U-test and Fisher's exact test were used to compare clinical characteristics. RESULTS: The CE-T1 WI, FLAIR, and ADC based single-parametric CNN model had accuracy of 0.884, 0.782, and 0.700, respectively. The DF-CNN model had an accuracy of 0.899 which was higher than the IF-CNN model (0.830, P = 0.021), but had no significant difference in accuracy compared to the radiomics model (0.865, P = 0.255), and the senior radiologist (0.906, P = 0.886). DATA CONCLUSION: A CNN model can differentiate PCNSL from GBM without tumor delineation, and comparable to the radiomics models and radiologists. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques.

OBJECTIVES: Despite the robust diagnostic performance of MRI-based radiomic features for differentiating between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) reported on prior studies, the best sequence or a combination of sequences and model performance across various machine learning pipelines remain undefined. Herein, we compare the diagnostic performance of multiple radiomics-based models to differentiate GBM from PCNSL. METHODS: Our retrospective study included 94 patients (34 with PCNSL and 60 with GBM). Model performance was assessed using various MRI sequences across 45 possible model and feature selection combinations for nine different sequence permutations. Predictive performance was assessed using fivefold repeated cross-validation with five repeats. The best and worst performing models were compared to assess differences in performance. RESULTS: The predictive performance, both using individual and a combination of sequences, was fairly robust across multiple top performing models (AUC: 0.961-0.977) but did show considerable variation between the best and worst performing models. The top performing individual sequences had comparable performance to multiparametric models. The best prediction model in our study used a combination of ADC, FLAIR, and T1-CE achieving the highest AUC of 0.977, while the second ranked model used T1-CE and ADC, achieving a cross-validated AUC of 0.975. CONCLUSION: Radiomics-based predictive accuracy can vary considerably, based on the model and feature selection methods as well as the combination of sequences used. Also, models derived from limited sequences show performance comparable to those derived from all five sequences. KEY POINTS: • Radiomics-based diagnostic performance of various machine learning models for differentiating glioblastoma and PCNSL varies considerably. • ML models using limited or multiple MRI sequences can provide comparable performance, based on the chosen model. • Embedded feature selection models perform better than models using a priori feature reduction.