A prognostic neural epigenetic signature in high-grade glioma.

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

Transcriptomic and epigenetic dissection of spinal ependymoma (SP-EPN) identifies clinically relevant subtypes enriched for tumors with and without NF2 mutation.

Ependymomas encompass multiple clinically relevant tumor types based on localization and molecular profiles. Tumors of the methylation class "spinal ependymoma" (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, their developmental origin is ill-defined, molecular data are scarce, and the potential heterogeneity within SP-EPN remains unexplored. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations, but neither types and frequency of these alterations nor their clinical relevance have been described in a large, epigenetically defined series. Transcriptomic (n = 72), epigenetic (n = 225), genetic (n = 134), and clinical data (n = 112) were integrated for a detailed molecular overview on SP-EPN. Additionally, we mapped SP-EPN transcriptomes to developmental atlases of the developing and adult spinal cord to uncover potential developmental origins of these tumors. The integration of transcriptomic ependymoma data with single-cell atlases of the spinal cord revealed that SP-EPN display the highest similarities to mature adult ependymal cells. Unsupervised hierarchical clustering of transcriptomic data together with integrated analysis of methylation profiles identified two molecular SP-EPN subtypes. Subtype A tumors primarily carried previously known germline or sporadic NF2 mutations together with 22q loss (bi-allelic NF2 loss), resulting in decreased NF2 expression. Furthermore, they more often presented as multilocular disease and demonstrated a significantly reduced progression-free survival as compared to SP-EP subtype B. In contrast, subtype B predominantly contained samples without NF2 mutation detected in sequencing together with 22q loss (monoallelic NF2 loss). These tumors showed regular NF2 expression but more extensive global copy number alterations. Based on integrated molecular profiling of a large multi-center cohort, we identified two distinct SP-EPN subtypes with important implications for genetic counseling, patient surveillance, and drug development priorities.

Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas.

The diagnosis of ependymoma has moved from a purely histopathological review with limited prognostic value to an integrated diagnosis, relying heavily on molecular information. However, as the integrated approach is still novel and some molecular ependymoma subtypes are quite rare, few studies have correlated integrated pathology and clinical outcome, often focusing on small series of single molecular types. We collected data from 2023 ependymomas as classified by DNA methylation profiling, consisting of 1736 previously published and 287 unpublished methylation profiles. Methylation data and clinical information were correlated, and an integrated model was developed to predict progression-free survival. Patients with EPN-PFA, EPN-ZFTA, and EPN-MYCN tumors showed the worst outcome with 10-year overall survival rates of 56%, 62%, and 32%, respectively. EPN-PFA harbored chromosome 1q gains and/or 6q losses as markers for worse survival. In supratentorial EPN-ZFTA, a combined loss of CDKN2A and B indicated worse survival, whereas a single loss did not. Twelve out of 200 EPN-ZFTA (6%) were located in the posterior fossa, and these tumors relapsed or progressed even earlier than supratentorial tumors with a combined loss of CDKN2A/B. Patients with MPE and PF-SE, generally regarded as non-aggressive tumors, only had a 10-year progression-free survival of 59% and 65%, respectively. For the prediction of the 5-year progression-free survival, Kaplan-Meier estimators based on the molecular subtype, a Support Vector Machine based on methylation, and an integrated model based on clinical factors, CNV data, and predicted methylation scores achieved balanced accuracies of 66%, 68%, and 73%, respectively. Excluding samples with low prediction scores resulted in balanced accuracies of over 80%. In sum, our large-scale analysis of ependymomas provides robust information about molecular features and their clinical meaning. Our data are particularly relevant for rare and hardly explored tumor subtypes and seemingly benign variants that display higher recurrence rates than previously believed.

Classification of Brain Tumors by Nanopore Sequencing of Cell-Free DNA from Cerebrospinal Fluid.

BACKGROUND: Molecular brain tumor diagnosis is usually dependent on tissue biopsies or resections. This can pose several risks associated with anesthesia or neurosurgery, especially for lesions in the brain stem or other difficult-to-reach anatomical sites. Apart from initial diagnosis, tumor progression, recurrence, or the acquisition of novel genetic alterations can only be proven by re-biopsies. METHODS: We employed Nanopore sequencing on cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) and analyzed copy number variations (CNV) and global DNA methylation using a random forest classifier. We sequenced 129 samples with sufficient DNA. These samples came from 99 patients and encompassed 22 entities. Results were compared to clinical diagnosis and molecular analysis of tumor tissue, if available. RESULTS: 110/129 samples were technically successful, and 50 of these contained detectable circulating tumor DNA (ctDNA) by CNV or methylation profiling. ctDNA was detected in samples from patients with progressive disease but also from patients without known residual disease. CNV plots showed diagnostic and prognostic alterations, such as C19MC amplifications in embryonal tumors with multilayered rosettes or Chr.1q gains and Chr.6q losses in posterior fossa group A ependymoma, respectively. Most CNV profiles mirrored the profiles of the respective tumor tissue. DNA methylation allowed exact classification of the tumor in 22/110 cases and led to incorrect classification in 2/110 cases. Only 5/50 samples with detected ctDNA contained tumor cells detectable through microscopy. CONCLUSIONS: Our results suggest that Nanopore sequencing data of cfDNA from CSF samples may be a promising approach for initial brain tumor diagnostics and an important tool for disease monitoring.

Molecular refinement of pilocytic astrocytoma in adult patients.

AIM: Pilocytic astrocytomas (PA) in adults are rare and may be challenging to identify based only on histomorphology. Compared to their paediatric counterparts, they are reportedly molecularly more diverse and associated with a worse prognosis. We aimed to describe the characteristics of adult PAs more precisely by comprehensively profiling a series of 79 histologically diagnosed adult cases (≥18 years). METHODS: We performed global DNA methylation profiling and DNA and RNA panel sequencing, and integrated the results with clinical data. We further compared the molecular characteristics of adult and paediatric PAs that had a significant match to one of the established PA methylation classes in the Heidelberg brain tumour classifier. RESULTS: The mean age in our cohort was 33 years, and 43% of the tumours were located supratentorially. Based on methylation profiling, only 39% of the cases received a significant match to a PA methylation class. Sixteen per cent matched a different tumour type and 45% had a Heidelberg classifier score <0.9 with an affiliation to diverse established methylation classes in t-SNE analyses. Although the KIAA1549::BRAF fusion was found in 98% of paediatric PAs, this was true for only 27% of histologically defined and 55% of adult PAs defined by methylation profiling. CONCLUSIONS: A particularly high fraction of adult tumours with histological features of PA do not match current PA methylation classes, indicating ambiguous histology and an urgent need for molecular profiling. Moreover, even in adult PAs with a match to a PA methylation class, the distribution of genetic drivers differs significantly from their paediatric counterparts (p<0.01).

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability.

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. High-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

Atypical neurofibromas reveal distinct epigenetic features with proximity to benign peripheral nerve sheath tumor entities.

BACKGROUND: Plexiform neurofibromas can transform into atypical neurofibromas (ANF) and then further progress to aggressive malignant peripheral nerve sheath tumors (MPNST). ANF have been described to harbor distinct histological features and frequent loss of CDKN2A/B. However, histological evaluation may be rater-dependent, and detailed knowledge about the molecular mechanisms of malignant transformation is scarce. In general, malignant transformation can be accompanied by significant epigenetic changes, and global DNA methylation profiling is able to differentiate relevant tumor subgroups. Therefore, epigenetic profiling might provide a valuable tool to distinguish and characterize ANF with differing extent of histopathological atypia from neurofibromas and MPNST. METHODS: We investigated 40 tumors histologically diagnosed as ANF and compared their global methylation profile to other peripheral nerve sheath tumors. RESULTS: Unsupervised class discovery and t-SNE analysis indicated that 36/40 ANF cluster with benign peripheral nerve sheath tumors with clear separation from MPNST. 21 ANF formed a molecularly distinct cluster in proximity to schwannomas. Tumors in this cluster had a frequent heterozygous or homozygous loss of CDKN2A/B and significantly more lymphocyte infiltration than MPNST, schwannomas, and NF. Few ANF clustered closely with neurofibromas, schwannomas, or MPNST, raising the question, whether diagnosis based on histological features alone might pose a risk to both over- and underestimate the aggressiveness of these lesions. CONCLUSIONS: Our data suggest that ANF with varying histological morphology show distinct epigenetic similarities and cluster in proximity to benign peripheral nerve sheath tumor entities. Future investigations should pay special respect to correlating this methylation pattern to clinical outcomes.

Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncology.

The large diversity of central nervous system (CNS) tumor types in children and adolescents results in disparate patient outcomes and renders accurate diagnosis challenging. In this study, we prospectively integrated DNA methylation profiling and targeted gene panel sequencing with blinded neuropathological reference diagnostics for a population-based cohort of more than 1,200 newly diagnosed pediatric patients with CNS tumors, to assess their utility in routine neuropathology. We show that the multi-omic integration increased diagnostic accuracy in a substantial proportion of patients through annotation to a refining DNA methylation class (50%), detection of diagnostic or therapeutically relevant genetic alterations (47%) or identification of cancer predisposition syndromes (10%). Discrepant results by neuropathological WHO-based and DNA methylation-based classification (30%) were enriched in histological high-grade gliomas, implicating relevance for current clinical patient management in 5% of all patients. Follow-up (median 2.5 years) suggests improved survival for patients with histological high-grade gliomas displaying lower-grade molecular profiles. These results provide preliminary evidence of the utility of integrating multi-omics in neuropathology for pediatric neuro-oncology.

Risk prediction in early childhood sonic hedgehog medulloblastoma treated with radiation-avoiding chemotherapy: Evidence for more than 2 subgroups.

BACKGROUND: The prognostic impact of clinical risk factors and DNA methylation patterns in sonic hedgehog (SHH)-activated early childhood desmoplastic/nodular medulloblastoma (DMB) or medulloblastoma with extensive nodularity (MBEN) were evaluated to better identify patients at risk for relapse. METHODS: One hundred and forty-four patients with DMB (n = 99) or MBEN (n = 45) aged <5 years and treated with radiation-sparing approaches, including intraventricular methotrexate in 132 patients were evaluated. RESULTS: Patients with DMB had less favorable 5-year progression-free survival than MBEN (5y-PFS, 71% [DMB] vs. 93% [MBEN]). Patients aged >3 years were associated with more unfavorable 5y-PFS (47% [>3 years] vs. 85% [<1 year] vs. 84% [1-3 years]). DNA methylation profiles available (n = 78) were reclassified according to the 2021 WHO classification into SHH-1 (n = 39), SHH-2 (n = 38), and SHH-3 (n = 1). Hierarchical clustering delineated 2 subgroups among SHH-2: SHH-2a (n = 19) and SHH-2b (n = 19). Patients with SHH-2b medulloblastoma were older, predominantly displayed DMB histology, and were more often located in the cerebellar hemispheres. Chromosome 9q losses were more frequent in SHH-2b, while few chromosomal alterations were observed in SHH-2a. SHH-2b medulloblastoma carried a significantly increased relapse risk (5y-PFS: 58% [SHH-2b] vs. 83% [SHH-1] vs. 95% [SHH-2a]). Subclassification of SHH-2 with key clinical and cytogenetic characteristics was confirmed using 2 independent cohorts (total n = 188). Gene mutation analysis revealed a correlation of SHH-2a with SMO mutations. CONCLUSIONS: These data suggest further heterogeneity within early childhood SHH-DMB/MBEN: SHH-2 splits into a very low-risk group SHH-2a enriched for MBEN histology and SMO mutations, and SHH-2b comprising older DMB patients with a higher risk of relapse.

Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

AIM: Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and neuropathologists, which is time-consuming, labour-intensive and subjective. METHODS: We, therefore, developed an image analysis approach based on expert annotations of 123,181 digitised CSF objects from 78 patients corresponding to 15 clinically relevant categories and trained a multiclass convolutional neural network (CNN). RESULTS: The CNN classified the 15 categories with high accuracy (mean AUC 97.3%). By using explainable artificial intelligence (XAI), we demonstrate that the CNN identified meaningful cellular substructures in CSF cells recapitulating human pattern recognition. Based on the evaluation of 511 cells selected from 12 different CSF samples, we validated the CNN by comparing it with seven board-certified neuropathologists blinded for clinical information. Inter-rater agreement between the CNN and the ground truth was non-inferior (Krippendorff's alpha 0.79) compared with the agreement of seven human raters and the ground truth (mean Krippendorff's alpha 0.72, range 0.56-0.81). The CNN assigned the correct diagnostic label (inflammatory, haemorrhagic or neoplastic) in 10 out of 11 clinical samples, compared with 7-11 out of 11 by human raters. CONCLUSIONS: Our approach provides the basis to overcome current limitations in automated cell classification for routine diagnostics and demonstrates how a visual explanation framework can connect machine decision-making with cell properties and thus provide a novel versatile and quantitative method for investigating CSF manifestations of various neurological diseases.

Amplification of the PLAG-family genes-PLAGL1 and PLAGL2-is a key feature of the novel tumor type CNS embryonal tumor with PLAGL amplification.

Pediatric central nervous system (CNS) tumors represent the most common cause of cancer-related death in children aged 0-14 years. They differ from their adult counterparts, showing extensive clinical and molecular heterogeneity as well as a challenging histopathological spectrum that often impairs accurate diagnosis. Here, we use DNA methylation-based CNS tumor classification in combination with copy number, RNA-seq, and ChIP-seq analysis to characterize a newly identified CNS tumor type. In addition, we report histology, patient characteristics, and survival data in this tumor type. We describe a biologically distinct pediatric CNS tumor type (n = 31 cases) that is characterized by focal high-level amplification and resultant overexpression of either PLAGL1 or PLAGL2, and an absence of recurrent genetic alterations characteristic of other pediatric CNS tumor types. Both genes act as transcription factors for a regulatory subset of imprinted genes (IGs), components of the Wnt/ß-Catenin pathway, and the potential drug targets RET and CYP2W1, which are also specifically overexpressed in this tumor type. A derived PLAGL-specific gene expression signature indicates dysregulation of imprinting control and differentiation/development. These tumors occurred throughout the neuroaxis including the cerebral hemispheres, cerebellum, and brainstem, and were predominantly composed of primitive embryonal-like cells lacking robust expression of markers of glial or neuronal differentiation (e.g., GFAP, OLIG2, and synaptophysin). Tumors with PLAGL1 amplification were typically diagnosed during adolescence (median age 10.5 years), whereas those with PLAGL2 amplification were diagnosed during early childhood (median age 2 years). The 10-year overall survival was 66% for PLAGL1-amplified tumors, 25% for PLAGL2-amplified tumors, 18% for male patients, and 82% for female patients. In summary, we describe a new type of biologically distinct CNS tumor characterized by PLAGL1/2 amplification that occurs predominantly in infants and toddlers (PLAGL2) or adolescents (PLAGL1) which we consider best classified as a CNS embryonal tumor and which is associated with intermediate survival. The cell of origin and optimal treatment strategies remain to be defined.

Anaplastic ganglioglioma-A diagnosis comprising several distinct tumour types.

AIMS: Anaplastic ganglioglioma is a rare tumour, and diagnosis has been based on histological criteria. The 5th edition of the World Health Organization Classification of Tumours of the Central Nervous System (CNS WHO) does not list anaplastic ganglioglioma as a distinct diagnosis due to lack of molecular data in previous publications. We retrospectively compiled a cohort of 54 histologically diagnosed anaplastic gangliogliomas to explore whether the molecular profiles of these tumours represent a separate type or resolve into other entities. METHODS: Samples were subjected to histological review, desoxyribonucleic acid (DNA) methylation profiling and next-generation sequencing. Morphological and molecular data were summarised to an integrated diagnosis. RESULTS: The majority of tumours designated as anaplastic gangliogliomas resolved into other CNS WHO diagnoses, most commonly pleomorphic xanthoastrocytoma (16/54), glioblastoma, isocitrate dehydrogenase protein (IDH) wild type and diffuse paediatric-type high-grade glioma, H3 wild type and IDH wild type (11 and 2/54), followed by low-grade glial or glioneuronal tumours including pilocytic astrocytoma, dysembryoplastic neuroepithelial tumour and diffuse leptomeningeal glioneuronal tumour (5/54), IDH mutant astrocytoma (4/54) and others (6/54). A subset of tumours (10/54) was not assignable to a CNS WHO diagnosis, and common molecular profiles pointing to a separate entity were not evident. CONCLUSIONS: In summary, we show that tumours histologically diagnosed as anaplastic ganglioglioma comprise a wide spectrum of CNS WHO tumour types with different prognostic and therapeutic implications. We therefore suggest assigning this designation with caution and recommend comprehensive molecular workup.

Comprehensive profiling of myxopapillary ependymomas identifies a distinct molecular subtype with relapsing disease.

BACKGROUND: Myxopapillary ependymoma (MPE) is a heterogeneous disease regarding histopathology and outcome. The underlying molecular biology is poorly understood, and markers that reliably predict the patients' clinical course are unknown. METHODS: We assembled a cohort of 185 tumors classified as MPE based on DNA methylation. Methylation patterns, copy number profiles, and MGMT promoter methylation were analyzed for all tumors, 106 tumors were evaluated histomorphologically, and RNA sequencing was performed for 37 cases. Based on methylation profiling, we defined two subtypes MPE-A and MPE-B, and explored associations with epidemiological, clinical, pathological, and molecular characteristics of these tumors. RESULTS: MPE-A occurred at a median age of 27 years and were enriched with tumors demonstrating papillary morphology and MGMT promoter hypermethylation. Half of these tumors could not be totally resected, and 85% relapsed within 10 years. Copy number alterations were more common in MPE-A. RNA sequencing revealed an enrichment for extracellular matrix and immune system-related signatures in MPE-A. MPE-B occurred at a median age of 45 years and included many tumors with a histological diagnosis of WHO grade II and tanycytic morphology. Patients within this subtype had a significantly better outcome with a relapse rate of 33% in 10 years (P = 3.4e-06). CONCLUSIONS: We unraveled the morphological and clinical heterogeneity of MPE by identifying two molecularly distinct subtypes. These subtypes significantly differed in progression-free survival and will likely need different protocols for surveillance and treatment.

Pleomorphic xanthoastrocytoma is a heterogeneous entity with pTERT mutations prognosticating shorter survival.

Pleomorphic xanthoastrocytoma (PXA) in its classic manifestation exhibits distinct morphological features and is assigned to CNS WHO grade 2 or grade 3. Distinction from glioblastoma variants and lower grade glial and glioneuronal tumors is a common diagnostic challenge. We compared a morphologically defined set of PXA (histPXA) with an independent set, defined by DNA methylation analysis (mcPXA). HistPXA encompassed 144 tumors all subjected to DNA methylation array analysis. Sixty-two histPXA matched to the methylation class mcPXA. These were combined with the cases that showed the mcPXA signature but had received a histopathological diagnosis other than PXA. This cohort constituted a set of 220 mcPXA. Molecular and clinical parameters were analyzed in these groups. Morphological parameters were analyzed in a subset of tumors with FFPE tissue available. HistPXA revealed considerable heterogeneity in regard to methylation classes, with methylation classes glioblastoma and ganglioglioma being the most frequent mismatches. Similarly, the mcPXA cohort contained tumors of diverse histological diagnoses, with glioblastoma constituting the most frequent mismatch. Subsequent analyses demonstrated the presence of canonical pTERT mutations to be associated with unfavorable prognosis among mcPXA. Based on these data, we consider the tumor type PXA to be histologically more varied than previously assumed. Histological approach to diagnosis will predominantly identify cases with the established archetypical morphology. DNA methylation analysis includes additional tumors in the tumor class PXA that share similar DNA methylation profile but lack the typical morphology of a PXA. DNA methylation analysis also assist in separating other tumor types with morphologic overlap to PXA. Our data suggest the presence of canonical pTERT mutations as a robust indicator for poor prognosis in methylation class PXA.

Fibroblast Activation Protein-Specific PET/CT Imaging in Fibrotic Interstitial Lung Diseases and Lung Cancer: A Translational Exploratory Study.

Interstitial lung diseases (ILDs) comprise over 200 parenchymal lung disorders. Among them, fibrosing ILDs, especially idiopathic pulmonary fibrosis, are associated with a poor prognosis, whereas some other ILDs, such as sarcoidosis, have a much better prognosis. A high proportion manifests as fibrotic ILD (fILD). Lung cancer (LC) is a frequent complication of fILD. Activated fibroblasts are crucial for fibrotic processes in fILD. The aim of this exploratory study was to evaluate the imaging properties of static and dynamic fibroblast activation protein (FAP) inhibitor (FAPI) PET/CT in various types of fILD and to confirm FAP expression in fILD lesions by FAP immunohistochemistry of human fILD biopsy samples and of lung sections of genetically engineered (Nedd4-2-/- ) mice with an idiopathic pulmonary fibrosislike lung disease. Methods: PET scans of 15 patients with fILD and suspected LC were acquired 10, 60, and 180 min after the administration of 150-250 MBq of a 68Ga-labeled FAPI tracer (FAPI-46). In 3 patients, dynamic scans over 40 min were performed instead of imaging after 10 min. The SUVmax and SUVmean of fibrotic lesions and LC were measured and CT-density-corrected. Target-to-background ratios (TBRs) were calculated. PET imaging was correlated with CT-based fibrosis scores. Time-activity curves derived from dynamic imaging were analyzed. FAP immunohistochemistry of 4 human fILD biopsy samples and of fibrotic lungs of Nedd4-2-/- mice was performed. Results: fILD lesions as well as LC showed markedly elevated 68Ga-FAPI uptake (density-corrected SUVmax and SUVmean 60 min after injection: 11.12 ± 6.71 and 4.29 ± 1.61, respectively, for fILD lesions and 16.69 ± 9.35 and 6.44 ± 3.29, respectively, for LC) and high TBR (TBR of density-corrected SUVmax and SUVmean 60 min after injection: 2.30 ± 1.47 and 1.67 ± 0.79, respectively, for fILD and 3.90 ± 2.36 and 2.37 ± 1.14, respectively, for LC). SUVmax and SUVmean decreased over time, with a stable TBR for fILD and a trend toward an increasing TBR in LC. Dynamic imaging showed differing time-activity curves for fILD and LC. 68Ga-FAPI uptake showed a positive correlation with the CT-based fibrosis index. Immunohistochemistry of human biopsy samples and the lungs of Nedd4-2-/- mice showed a patchy expression of FAP in fibrotic lesions, preferentially in the transition zone to healthy lung parenchyma. Conclusion:68Ga-FAPI PET/CT imaging is a promising new imaging modality for fILD and LC. Its potential clinical value for monitoring and therapy evaluation of fILD should be investigated in future studies.

Two Pituitary Neuroendocrine Tumors (PitNETs) with Very High Proliferation and TP53 Mutation - High-Grade PitNET or PitNEC?

We report two pituitary neuroendocrine tumors (PitNETs) with very high Ki67 labeling indices, many mitoses and TP53 mutation (nearly all tumor cell nuclei were positive for p53). One of the tumors had bone and liver metastases. One was a corticotroph cell tumor; the other was a lactotroph tumor. The classification of these tumors is the subject of this discussion. Traditionally, pituitary carcinomas are only diagnosed by demonstration of metastases according to the 2017 WHO classification. In contrast, neuroendocrine neoplasms of the gastrointestinal tract and pancreas are classified as either well differentiated NETs that are graded as G1, G2, and G3 based on proliferation as determined by Ki67 indices of ≤ 3, 3-20 and > 20%, and/or < 2, 2-20, and > 20 mitoses per 10 high-power field respectively, or as neuroendocrine carcinomas (NECs) that are poorly differentiated neoplasms with mitoses > 20/HPF and/or a Ki67 index > 20%. With the reclassificiation of PitNETs, in our opinion, the adequate term for the well-differentiated corticotroph tumor that we report is a PitNET G3, whereas the undifferentiated prolactin tumor should be classified as PitNEC. This report expands the spectrum of pituitary neuroendocrine neoplasms.