Citations

Deregulated inflammatory signaling via STAT family transcription factors, particularly STAT1, underlies a variety of immune-related diseases, including inflammatory bowel disease. Whereas activation of STATs by JAKs via canonical receptor-driven JAK–STAT signaling is well understood, little is known about JAK-independent mechanisms of STAT activation. Here, we identify the understudied nonreceptor tyrosine kinase TNK1 as a therapeutically targetable, JAK-independent activator of STAT signaling. Using a multiomics approach, we mapped a network of TNK1 substrates associated with protein condensates and proinflammatory signaling, including STAT1. We found that TNK1, but not its sister kinase ACK1, directly phosphorylates STATs at well described STAT-activating JAK sites. In cells, TNK1-mediated STAT1 phosphorylation and activation occurs independently of JAKs. Imaging and interactomics data suggest that TNK1 interacts with STAT1 in cytosolic condensates, which likely compartmentalize TNK1-substrate interactions. We show that an intrinsically disordered proline-rich region in TNK1, which includes a 14-3-3 docking phosphorylation site, is required for the formation of kinase-active TNK1 condensates and STAT1 phosphorylation. Mutations within the proline-rich region that eliminate 14-3-3 binding increase formation of TNK1 condensates, suggesting a model in which 14-3-3 acts as a clamp that constrains the flexible PRR to inhibit condensate formation and STAT1 activation. Finally, we show that TNK1 is a targetable driver of STAT1-mediated inflammation in the gut as inhibition of TNK1 reduces active STAT1 in the colon and ameliorates colitis symptoms in mice.

Abstract IDH-wildtype diffuse astrocytic gliomas with lower-grade histological features alongside specific genomic alterations (e.g., TERT promoter mutation, EGFR amplification, gain Chr7/loss Chr10) are presently diagnosed as glioblastoma, IDH-wildtype (GBM) under WHO 2021 criteria. Previous analyses categorized these into “early/evolving” or “surgically undersampled” GBMs. However, it remains unclear whether these tumors share identical clinical and prognostic features with histologic GBM. Data from IDH-wt molecular GBMs across six institutions were aggregated. Astrocytic IDH-wt tumors of any grade that lacked necrosis or microvascular proliferation on initial histopathology yet exhibited molecular alterations consistent with WHO 2021 GBM diagnosis, were included. Recursive partitioning analysis (RPA) was used to categorize patients into risk groups based on overall survival (OS). Among the 264 patients included, the median age was 60 years (IQR: 51-67), with 162 (61%) being male. Additionally, 210 (80%) were diagnosed since 2016, and 216 (82%) received chemoradiation plus adjuvant temozolomide (GBM-SOC). The median follow-up period was 3.9 years (95% CI: 3.4, 4.6). Identified univariate risk factors for worse survival included older age, biopsy-only status, EGFR amplification, absence of initial adjuvant treatment, low post-operative KPS, and tumor histologic grade of 3. RPA divided patients into four distinct survival groups (p<0.0001). The “best” risk group comprised lower grade (<=2) tumors (n=58, median OS (mOS): 40 months (95% CI: 33, NA)). The “second best” group included Grade 3 patients receiving GBM-SOC without steroids during initial RT (n=139, mOS: 25 months (95% CI: 22, 28)). The “second worst” group encompassed Grade 3 patients who were on steroids during initial RT while receiving GBM-SOC (n=38, mOS: 15 months (95% CI: 13, 20)). The “worst” group contained Grade 3 tumors that had not undergone SOC (n=29, mOS: 9 months (95% CI: 4, 26)). These data show that histologic features and treatment are strong indicators of patient outcomes.

Abstract Oligodendrogliomas are initially slow-growing brain tumors that are prone to malignant transformation despite surgery and cytotoxic therapy. Understanding of oligodendroglioma evolution and new treatments for patients have been encumbered by a paucity of patient-matched newly diagnosed and recurrent tumor samples for multiplatform analyses, and by a lack of preclinical models for interrogation of therapeutic vulnerabilities that drive oligodendroglioma growth. Here we integrate spatial and functional analyses of tumor samples and patient-derived organoid co-cultures to show that synaptic connectivity is a hallmark of oligodendroglioma evolution and recurrence. We find that patient-matched recurrent oligodendrogliomas are enriched in synaptic gene expression programs irrespective of previous therapy or histologic grade. Analyses of spatial, single-cell, and clinical data reveal epigenetic misactivation of synaptic genes that are concentrated in regions of cortical infiltration and can be used to predict eventual oligodendroglioma recurrence. To translate these findings to patients, we show that local field potentials from tumor-infiltrated cortex at the time of resection and neuronal hyperexcitability and synchrony in patient-derived organoid co-cultures are associated with oligodendroglioma proliferation and recurrence. In preclinical models, we find that neurophysiologic drugs block oligodendroglioma growth and pathologic electrophysiology. These results elucidate mechanisms underlying oligodendroglioma evolution from an indolent tumor to a fatal disease and shed light on new biomarkers and new treatments for patients.

AbstractBackgroundMany treatments targeting frontotemporal lobar degeneration (FTLD) are in the developmental pipeline, but the rarity of the disease, coupled with the behavioral and motor features of FTLD, make it challenging to identify sufficient trial participants who can attend frequent in‐person visits. Decentralized clinical trial designs with remote evaluations are attractive alternatives but require validated tools for symptom tracking. Our previous cross‐sectional analyses showed that cognitive tasks deployed via the ALLFTD Mobile App are reliable and sensitive to early stages of disease. The current study seeks to evaluate whether unsupervised smartphone cognitive tests are sensitive to longitudinal changes that occur with increasing FTLD disease stage.MethodThe study included 194 participants (mean baseline age 54.30, SD = 15.66; mean education = 16.52, SD = 2.31; 55.2% women) who were asymptomatic (Clinical Dementia Rating plus FTLD (CDR®+NACC‐FTLD) = 0 [n = 109; 43 carriers of FTLD‐associated genetic variants]), prodromal (CDR®+NACC‐FTLD = 0.5 [n = 39]), or symptomatic (CDR®+NACC‐FTLD>0.5 [n = 46]) at baseline. Participants completed ALLFTD Mobile App smartphone versions of Stroop, flanker, and 2‐back tasks, as well as an adaptive associative memory task, every six months for up to two years. Linear‐mixed effects models investigated the effect of disease severity on cognitive trajectories by testing the interaction of baseline CDR®+NACC‐FTLD box score and time on smartphone test scores. Analyses were repeated in the subsample of asymptomatic/prodromal CDR®+NACC‐FTLD<1) familial FTLD mutation carriers (C9orf72, n = 27; MAPT, n = 16). All models controlled for age, education, and sex.ResultGreater baseline disease severity was associated with lower cognitive scores across all tasks (β range: ‐0.28 to ‐0.13; p’s < 0.001), and faster rates of decline on the memory and 2‐back tasks (β range: ‐0.15 to ‐0.07; p’s<0.04). When the sample was restricted to asymptomatic and prodromal individuals (CDR®+NACC FTLD<1), greater baseline disease severity was still associated with lower scores across most tasks (β range: ‐0.48 to ‐0.27; p’s<0.002; 2‐back: β = ‐0.19, p = 0.26). When the sample was restricted to asymptomatic/prodromal mutation carriers, disease severity remained associated with the memory and flanker tasks (β range: ‐0.85 to ‐0.45; p’s<0.01).ConclusionThis study provides initial evidence that longitudinal smartphone‐based cognitive measurements capture the accelerated cognitive worsening that accompanies increasing disease progression in FTLD.

AbstractBackgroundFrontotemporal dementia (FTD) is a diverse spectrum of neurodegenerative disorders impacting the frontal and temporal lobes, primarily manifesting as behavioral and/or language issues. Accurate diagnosis is crucial for effective management, potential treatment, and care planning. While speech analysis has shown promise in detecting cognitive markers of Alzheimer’s disease (AD), its exploration in FTD is limited. This study examined if linguistic features from remote, app‐based speech collection can differentiate healthy controls (HC) from individuals with behavioral variant FTD (bvFTD), the most common FTD variant.MethodParticipants included 15 bvFTD (mean age = 64.3, SD = 9.1 years) and 19 HC (mean = 55.8, SD = 14.2) from the ALLFTD Consortium. Participants were prompted to talk freely about a happy memory; audio recordings were collected with the ALLFTD Mobile App, transcribed using OpenAI’s large Whisper model, and manually quality‐checked. We extracted 98 linguistic features using our in‐house pipeline (Fig 1). Features were selected for classification analysis if they differed between groups based on a MANCOVA adjusted for age, sex/gender, and education, with feature reduction in case of collinearity. We then determined if these features could classify groups using multi‐variable logistic regression models, and subsequently calculated its ROC‐AUC score to measure sensitivity/specificity.ResultBased on the MANCOVA, three features were selected for classification analysis: average seconds of non‐speech (i.e., silence), ratio of number of complex nominal clauses to total clauses, and number of restarts (i.e., disfluency). The logistic model showed that this set could distinguish between groups (Omnibus p = .001; Nagelkerke R2 = .499), and their saved prediction probabilities indicated a ROC‐AUC score of 84.8% accuracy (Fig 2).ConclusionLeveraging a flexible speech capture app with remote accessibility and state‐of‐the‐art automated speech analysis, we identified linguistic features that can distinguish HC from bvFTD. This approach presents a promising screening tool for detecting bvFTD, offering quick, easily administered assessments with the potential for scalable implementation outside of clinical settings. Next steps are to investigate linguistic changes in presymptomatic mutation carriers and compare speech profiles between FTD and AD. These results hold meaningful implications for addressing current challenges in FTD therapeutics, potentially offering sensitive outcome measures for clinical trials and future tools for personalized cognitive assessment and long‐term monitoring.

AbstractBackgroundFrontotemporal dementia (FTD) is a common young‐onset dementia. Challenges to in‐person FTD evaluations (e.g., behavioral symptoms, disease rarity), highlight the need to develop remote, low‐burden assessment techniques. A growing literature supports passive digital phenotyping for monitoring neurobehavioral change. Thus, we examined the utility of passively collected data from smartphones to detect prodromal or symptomatic FTD compared to that of the Montreal Cognitive Assessment (MoCA), a common cognitive screener.Method199 adults enrolled in the ALLFTD Mobile App study (mean age = 53.4 [SD = 15.2]; 58% women) completed up to 6 months of passive smartphone monitoring via the ALLFTD Mobile App. 55% were unimpaired [CDR®+NACC FTLD = 0], 22% had prodromal FTD [CDR®+NACC FTLD = 0.5], and 23% had symptomatic FTD [CDR®+NACC FTLD≥1] with a variety of syndromic presentations. Battery percentage was collected frequently (median interval = 45 min), and total daily battery usage was calculated as a proxy for smartphone use (higher battery usage = more smartphone use). Daily step counts were also passively collected. Logistic regression classified prodromal or symptomatic FTD vs. unimpaired as a function of: MoCA score [Model 1]; 7 passive features characterizing average, inter‐day variability, and changes over time in smartphone use and movement [Model 2]; or passive smartphone features and MoCA [Model 3]. Analyses were repeated excluding participants with symptomatic FTD to detect prodromal FTD vs. unimpaired.ResultThe area under the curves (AUCs) for detecting prodromal or symptomatic FTD (vs. unimpaired) from the MoCA alone [Model 1] and passive smartphone features alone [Model 2] were 0.77 (95%CI: 0.70‐0.85) and 0.77 (95%CI: 0.70‐0.84), respectively. Their combination [Model 3] resulted in a significantly improved AUC of 0.86 (95%CI: 0.80‐0.92) compared to Model 1 (p = 0.001). Significant Model 3 predictors included average daily battery usage (p = 0.02), slopes of change in step count (p = 0.04), and MoCA score (p<0.01). When distinguishing prodromal FTD from unimpaired, passive smartphone features alone (AUC = 0.75) were significantly better than the MoCA alone (AUC = 0.66; p<0.01), and their combination had the largest AUC (0.80).ConclusionResults support the utility of novel passively collected information from smartphones for detecting and monitoring FTD without contributing to assessment burden. With continued validation, passive digital monitoring methodologies have potential to increase access to dementia care.

Abstract Genomic alterations and molecular subgroups between extracranial disease sites and brain metastases often differ, yet the prevalence and clinical significance of divergent evolution in brain metastases is not fully understood. This study examined genomic alterations and molecular subgroup divergence rates between matched brain metastases and extracranial disease sites. A retrospective, two-center study was conducted on patients who underwent resection of brain metastases between 2014-2022 with clinical and matched genomic data and/or molecular markers available. The overall cohort comprised 256 patients with matched tumors from multiple cancer types, most commonly from breast (n=108, 42.2%), melanoma (n=83, 32.4%), and NSCLC (n=43, 16.8%). Targeted next-generation sequencing of over 500 oncogenes was performed on resected tumors as part of clinical care (n=41 patients with matched specimens). Molecular subgroups for breast, melanoma, and non-small cell lung cancer were also assessed by immunohistochemistry to evaluate rates of molecular subgroup discordance between sites. Subgroup discordance by immunohistochemistry was observed most frequently across breast cancer (22.2%, n=24/108) with loss of the estrogen receptor (ER) and progesterone receptor (PR) and gain of HER2 most frequently observed within brain metastases. Molecular subgroup discordance was rare within melanoma (7.3%, n=6/82) and NSCLC (14.0%, n=6/43) patients. When evaluating oncogenomic alterations from targeted DNA sequencing in 41 patients with matched specimens, 80.5% (33/41) of brain metastases demonstrated a unique oncogene alteration profile compared to an extracranial disease site. Fourteen patients (34.1%) had a gain of at least 1 targetable alteration within a brain metastasis that was not observed in an extracranial disease site. Brain metastases demonstrated high rates of genomic divergence compared to primary and extracranial metastatic disease sites. This data supports obtaining brain metastasis tissue and conducting molecular profiling of this tissue to help select optimal CNS penetrant systemic therapies for each patient.

Abstract Current standard of care for IDH-wildtype glioblastoma (GBM) includes maximal safe resection, adjuvant radiation, and chemotherapy with the alkylating agent temozolomide. A subset of gliomas treated with temozolomide develop somatic hypermutation with a predominance of C&gt;T transitions due to the alkylation effects on DNA. However, the frequency of occurrence, clinical ramifications, and predictive biomarkers for developing temozolomide-induced hypermutation (TMZ-HM) in GBM are unknown. Here we performed comprehensive histopathologic, genomic, and epigenomic evaluation of paired initial and recurrent GBM from 106 patients. Seven patients (7%) developed hypermutation at time of first recurrence, while an additional five patients (5%) developed hypermutation at a subsequent recurrence. Patients who developed TMZ-HM had a significantly longer interval between initial surgery and first recurrence (27.8 vs. 9.9 months, p&lt;0.001). In contrast to IDH-mutant gliomas where TMZ-HM is associated with poor prognosis, those patients with IDH-wildtype GBM who developed TMZ-HM had significantly longer overall survival from both initial surgery (67.9 vs. 20.3 months, p&lt;0.001) and from time of recurrence after development of hypermutation (30.9 vs. 9.5 months, p=0.001). There was no difference in oncogenic alteration frequency in initial GBM that subsequently developed TMZ-HM. However, 4 specific CpG sites out of 12 total interrogated sites in the promoter region of MGMT (a DNA repair enzyme) and 5 specific CpG sites in the promoter region of KCNQ1DN (a negative regulator of c-Myc) were significantly more hypermethylated in those GBM that developed TMZ-HM. We then generated a weighted risk score across these CpG sites that can be used to prospectively identify GBM likely to develop TMZ-HM associated with favorable survival. In summary, patients with GBM that develop TMZ-HM follow a more favorable clinical course, and specific MGMT and KCNQ1DN promoter hypermethylation patterns could serve as a biomarker to identify these patients who may potentially benefit from extended alkylating chemotherapy treatment.

Abstract Harnessing the neuroplastic potential of the human brain is being increasingly recognized as an important neuro-oncological paradigm to facilitate safe resection of brain tumors while preserving neurological function and quality of life. Interventional neurorehabilitation, employing both invasive and noninvasive neuromodulation techniques, represents an important emerging therapeutic strategy to induce or enhance neural plasticity to promote functional recovery in brain tumor patients. This study aimed to conduct a comprehensive review of interventional neurorehabilitation techniques for glioma patients. Methods In accordance with PRISMA guidelines, searches of Medline, Embase, Web of Science, APA PsycINFO, and Cochrane were undertaken from database inception to November 28, 2023. Studies reporting on neuromodulation applied to glioma patients were included. Results Seven studies reporting findings from 118 patients met the inclusion criteria. Three neuromodulation techniques were identified and included transcranial magnetic stimulation (TMS) reported in 5 out of 7 (71.4%) studies; transcranial direct current stimulation (tDCS); and continuous cortical electrical stimulation (cCES) using grid electrodes, reported in one study each. All studies applying noninvasive stimulation to ameliorate postoperative deficits demonstrated an improvement on at least one outcome measure. The 2 studies applying tDCS and cCES to induce plasticity reported evidence of functional reorganization. Conclusions There is emerging evidence of benefits of neuromodulation to improve postoperative outcome in glioma patients. In the current literature, noninvasive stimulation has shown to have a favorable safety profile. Large-scale, double-blind, sham-controlled trials are warranted to further investigate the effectiveness of these interventions for modulating different cognitive networks in patients undergoing glioma surgery.