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AbstractBackgroundAlzheimer’s disease (AD) pathologic changes (e.g. amyloid and tau aggregation), and cerebrovascular disease often coexist, and it remains unclear whether these are mechanistically linked processes (Graff‐Radford, Brain 2019; Provenzano, JAMA Neurol 2013). Most studies evaluating these associations are cross‐sectional; however, establishing temporal relationships may provide additional insight into potential mechanistic associations. One method to assess the temporal evolution of a biomarker is the Accelerated Failure Time (AFT) model, which assumes a common pattern of progression for a given biomarker that is shifted earlier or later in time for each individual (Therneau, Neuroimage 2021). In this work we investigate the relationship of disease trajectories of cerebrovascular disease (via white matter hyperintensity, WMH, volume) and AD biomarkers (via amyloid and tau PET).MethodsWe included Mayo Clinic Study of Aging (MCSA) and Mayo Alzheimer’s Disease Research Center (ADRC) participants with amyloid PET, tau PET, and MRI, age > 50 years, and a clinical diagnosis of cognitively unimpaired (CU), mild cognitive impairment (MCI) or Alzheimer’s disease dementia. The AFT model was fit with amyloid PET (PiB) global meta‐ROI SUVR, tau PET (flortaucipir) temporal meta‐ROI SUVR, and WMH volume as the tri‐variate endpoints, with APOE genotype, sex, education, total intracranial volume, and referral/population subject as covariates. A per subject/endpoint random effect represents individual adjustments for each biomarker to indicate if the subject's biomarker became abnormal earlier or later relative to their demographic peers, accounting for the covariates.ResultsThe study included 1144 participants (Table 1). There was a strong correlation between earlier onset of amyloid and earlier onset of tau (r=0.64, CI=0.60‐0.67) (Figure 1, Table 2); early/late amyloid timing explained nearly half (0.642 = 41%) of the variation in tau onset. There were only weak associations between an individual’s WMH and amyloid PET onset adjustments (r=0.10, 1.0%) and WMH and tau PET onset adjustments (r=‐0.07, 0.5%).ConclusionThis analysis supports a strong mechanistic relationship between amyloid and tau aggregation, as reported by others. However, our findings do not support a mechanistic association between WMH and amyloid or tau PET.

Background. The age of a liver transplant (LT) candidate is one of many variables used in the transplant selection process. Most research about the age at transplant has used prespecified age ranges or categories in assessing associations with transplant outcomes. However, there is a lack of knowledge about the age at transplant and survival. This study aimed to examine associations of age at transplant as a continuous variable, in conjunction with other patient and disease-related factors, with patient and graft survival after LT. Methods. We used the Standard Transplant Analysis and Research data to identify LT recipients between January 2002 and June 2018. Cox regression models with a restricted cubic spline term for age examined associations with graft and patient survival after LT. We assessed the interactions of age with recipients’ sex, race/ethnicity, region, indication for transplant, body mass index, model for end-stage liver disease score, diabetes, functional status at transplant, and donor risk index. Results. Age at the time of LT showed a nonlinear association with both graft and patient survival. Each demographic, clinical, transplant-related, and donor-related factor influenced these relationships differently. Conclusions. Our results suggest that some older LT candidates may be better than some younger candidates and that clinicians should not exclusively use age to determine who receives LT.

Abstract Gliomas are genomically heterogeneous tumors that may harness a convergent and therapeutically targetable set of metabolic pathways. At present, the metabolic landscape of in situ human gliomas remains incompletely characterized, hampering translational progress. To that end, we are leveraging the previously untapped potential of high molecular weight microdialysis to determine the global extracellular metabolic profiles of live human gliomas. Under an investigational device exemption, HMW microdialysis (< 100 kDa) was performed at 2.0 μL/min in an initial discovery cohort of five patients in glioma and adjacent brain during neurosurgical resection; a subsequent cohort of five patients was independently analyzed to critically evaluate results from the discovery group. Untargeted metabolomics via ultra-performance liquid chromatography-tandem mass spectrometry revealed over 300 named metabolites and five drugs from only 20 μL of microdialysate, representing a short and feasible 10 minutes of intraoperative collection time. Enrichment analysis of each patient’s tumor vs. brain ranked extracellular metabolome highlighted marked metabolic convergence within the most aggressive regions of molecular diverse tumors (FDR = 0). Pathway analysis revealed significant enrichment for large neutral amino acid pathways, including valine, leucine, and isoleucine biosynthesis (p=1.6E-9) and degradation (p=0.001) and glycine, serine, and threonine metabolism (p=4.7E-5). Notably, this amino acid signature was not as abundantly present in nonenhancing tumor when compared to enhancing tumor (Average tumor/brain: 1.9x vs. 4.3x, respectively), suggesting upregulation of neutral amino acid transporters in enhancing tumor or delivery from plasma into the CNS via a disrupted BBB. Interestingly, guanidinoacetate (GAA) was our most highly conserved and upregulated metabolite (128.9x in tumor vs. brain). Given its co-production with ornithine, the precursor to protumorigenic polyamines, we posit that GAA may serve as a biomarker of increased ODC activity in live human gliomas. In conclusion, intraoperative HMW microdialysis feasibly offers improved opportunities to perform glioma metabolic biomarker and therapeutic discovery.

Abstract BACKGROUND Glioblastoma diagnostic criteria have been redefined with the 5th edition of WHO classification of tumors of the central nervous system. Glioblastomas are defined as IDH wildtype diffuse astrocytic glioma tumors with one of the following features: microvascular proliferation, or necrosis, or TERT promoter mutation, or EGFR gene amplification, or +7/-10 chromosome copy number changes. The aim of this study is to establish the impact of extent of resection in overall survival (OS) and progression free survival (PFS) in glioblastoma, IDH-wildtype (WT), WHO grade 4 (WHO 2021). METHODS Systematic literature search was performed using the following databases: PubMed, Web of Science, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and ClinicalTrials.gov to identify studies comparing OS and PFS after gross total resection (GTR) vs subtotal resection (STR) or biopsy for glioblastoma IDH-WT. Prognostic hazard ratios (HR) for OS and PFS were analyzed using a random-effects model. RESULTS We identified 1439 publications. Nine studies met inclusion/exclusion criteria. 788 patients underwent GTR out of 1818. The meta-analysis showed a significant increase in OS and PFS duration when undergoing GTR for glioblastoma IDH-WT with a median OS of 20 months 95% CI (17-25) compared to 12 months 95% CI (9-15) for STR or biopsy and a median PFS of 11 months 95% CI (9-12) for GTR compared to 7 months 95% CI (5-7) for STR or biopsy respectively. GTR showed a 49% significant reduction of mortality risk HR=0.51 95%CI (0.42-0.59) and a 44% significant reduction of progression risk HR=0.56 95%CI (0.41-0.71) compared to STR or biopsy. CONCLUSIONS This systematic review indicates that GTR may be associated with improved OS and PFS compared to STR or biopsy for Glioblastoma, IDH-WT, WHO grade 4 (WHO 2021). However, this is limited by variable study design and significant clinical and methodological heterogeneity among studies.

Abstract BACKGROUND Glioblastoma (GBM) has dismal outcome of 14-16 months. One of the challenges of drug development in GBM is lack of requisite circulating-free (cfDNA) in blood samples to develop biomarker driven targeted therapy trials. The Exablate focused ultrasound with circulating microbubble resonators uses the concept of real-time imaging to treat small target spots focusing energy in a non-invasive manner, thereby disrupting the Blood-Brain Barrier (BBBD) with potential to increase cfDNA in blood. METHODS LIBERATE is a prospective, multi-center, self-controlled pivotal ongoing clinical trial in subjects with suspected GBM evaluating the safety and effectiveness of Exablate Model 4000 to disrupt BBB to achieve a greater proportion of cfDNA in samples taken post-BBB disruption as compared to the sample taken before BBBD. Fifty eligible subjects with suspected GBM who are scheduled to undergo brain tumor resection or biopsy at 10 centers in the U.S. will participate in this study. The primary endpoint is defined for each subject as ratio between his/her cfDNA amount found in the blood sample 1-hour post-BBBD procedure compared to the cfDNA amount found in the blood sample collected pre-BBBD procedure. This study proposes to demonstrate that on average there is at least 2-fold increase in cfDNA (measured by central laboratory) at 1 hour post BBBD. Confirmatory secondary analysis will evaluate correlation between patterns obtained in panel of biomarkers evaluated in the resected tumor tissue and/or biopsy sample and blood sample collected 1-hour post-BBBD. Exploratory endpoints will include: (1) sensitivity of detection of known somatic mutations in the circulating blood samples (circulating tumor DNA) before and after BBBD, (2) time of greatest yield of cfDNA in the samples collected post BBBD blood samples (at 30 min, 1-hour, 2-hour and 3-hour) to determine time of greatest yield, (3) correlation of biomarkers between the imaging and the post-BBBD biomarker samples. (NCT05383872)

Abstract The relative inaccessibility of a patient’s glioma throughout their disease course precludes individualized insights into tumor biology and responses thereof to therapeutic challenge. We propose that serial cerebrospinal fluid (CSF) samples can be used to perform glioma espionage in the form of biomarker discovery for analytes that are sensitive to tumor burden (for monitoring) and candidate therapies (for biological impact). To that end, we are routinely leveraging neurosurgical access to the CNS to collect CSF samples intraoperatively and from chronically implanted Ommaya reservoirs for longitudinal CSF access (NCT04692337, NCT04692324). Global proteomic analysis of CSF was performed on the Somalogic platform – an aptamer-based technology for highly sensitive and specific analysis of over 7,000 proteins. Using each patient’s ranked protein list (glioma vs. 3 control patients), enrichment analysis was performed in a discovery cohort of five patients to identify conserved proteins of glioma. To reveal candidate glioma monitoring, further enrichment analysis was performed to identify proteins that decreased with resection and increased with recurrence, using two sets of paired patient samples. Forty-four proteins met these enrichment criteria; this candidate high-grade glioma proteomic signature was highly significantly enriched in an independent cohort of twelve glioma patients (FDR=0 for all patients). The HGG signature decreased in abundance following resection in serial samples from two other patients, confirming decreased tumor burden. Top proteins included LANC2, DPYL3, Sorcin, Integrin A1B1, and lactate dehydrogenase (FC of glioma vs. control: 145.3x, 113.9x, 78.0x, 71.6x, and 62.7x, respectively). Interestingly, despite having explicitly chosen samples with little-to-no hemoglobin in the discovery cohort, this HGG signature was highly enriched for plasma-like proteins (FDR=0), suggesting a potential biological impact of blood-brain barrier disruption on the glioma extracellular proteome. In conclusion, our data demonstrate that the glioma extracellular proteome can feasibly be accessed to perform biomarker discovery (“espionage”) via serially-acquired CSF samples.

Abstract Diffuse gliomas are aggressive brain tumors that lack effective therapies. Despite advances in the molecular characterization of gliomas, targeted treatments have failed to improve patient outcomes to date. Here, we employed a functional genomics approach to rapidly identify therapeutic vulnerabilities and provide a strategy to individualize patient treatment. Our process combined comprehensive genomic and transcriptomic tumor profiling, custom algorithms and visualization software for data integration, and preclinical 3-dimensional ex vivo models (mcancers) for drug screening to assess response to therapeutic agents targeting specific molecular alterations. A total of 32 cases, including 5 oligodendrogliomas (1 primary and 4 recurrent), 5 astrocytomas (1 primary and 4 recurrent), and 22 glioblastomas (5 primary and 17 recurrent), were included in the study. Immunohistochemistry and integrated genomics confirmed that mcancers maintain key molecular alterations, including mutations, chromosomal rearrangements and focal amplifications, cellularity, and heterogeneity, faithfully recapitulating the original tumor. A total of 119 single drugs and 183 combinations were tested, including a panel of 26-brain penetrant targeted agents (18 single drugs and 8 combinations) that was curated to target common glioma oncogenic pathways and was tested across all cases. A strong correlation was observed between therapeutic vulnerabilities of glioma mcancers to targeted agents (EGFR, MET, PDGFR, HDAC inhibitors, etc.) and clinical experience. Single agent activity of panel compounds in the ex vivo setting was generally poor, with only 35% mCancers exhibiting > 70% growth inhibition at Cmax. In contrast, combination strategies, especially ones including epigenetic drugs, were significantly more effective (affecting 22 out of 32 mCancers), underscoring the molecular complexity of gliomas and the need for clinical trials testing combination treatments. Our data identified a number of novel combination treatments with significant efficacy across glioma subtypes and molecular profiles, suggesting that our functional genomics pipeline can guide treatment selection and inform clinical trial enrollment for gliomas.

PURPOSE To describe a newly established international registry recruiting diverse patients with advanced prostate cancer across academic and community practices to address unmet needs in this population. PATIENTS AND METHODS Initiated in 2017, IRONMAN (International Registry for Men with Advanced Prostate Cancer) is a prospective cohort of patients with advanced prostate cancer. The study will enroll 5,000 patients with metastatic hormone-sensitive prostate cancer (mHSPC) or castration-resistant prostate cancer (CRPC), recruited from Australia, the Bahamas, Barbados, Brazil, Canada, Ireland, Jamaica, Kenya, Nigeria, Norway, South Africa, Spain, Sweden, Switzerland, the United Kingdom, and the United States. The study is collecting datatypes to study variation in care and treatment of advanced prostate cancer across countries and across academic, community-based, and government practices with a focus on clinical outcomes, patient-reported outcomes, epidemiologic data, biologic subtypes, and clinician questionnaires. RESULTS Through July 2022, 2,682 eligible patients were enrolled in 11 of 12 active countries. Sixty-six percent of patients have mHSPC, and 34% have CRPC. On the basis of self-report, 11% of patients are Black and 9% are Hispanic. Five Veterans Affairs Medical Centers are enrolling patients. Globally, 23% of patients report being veterans of military service. CONCLUSION To our knowledge, this is the first international cohort of people newly diagnosed with advanced prostate cancer designed to describe variations in patient management, experiences, and outcomes. IRONMAN aims to identify optimal treatment sequences to improve survival, understand patient-reported outcomes, and explore novel biomarkers to understand treatment resistance mechanisms. Insights from IRONMAN will inform and guide future clinical management of people with mHSPC and CRPC. This cohort study will provide real-world evidence to facilitate a better understanding of the survivorship of people with advanced prostate cancer.

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Abstract AIMS Rapid, detailed feedback is needed to understand the individualized biological impacts of novel glioma therapies. We are performing glioma biomarker discovery by serial cerebrospinal fluid (CSF) sampling from Ommaya reservoirs to determine how the CSF proteome can reveal early longitudinal intelligence regarding glioma status, biology, and therapeutic response. METHOD Global proteomic analysis of CSF was performed on the Somalogic platform – an aptamer-based technology for highly sensitive and specific analysis of over 7,000 proteins. Discovery analysis comprised of the top-500 ranked proteins in CSF from seven patients with high-grade gliomas (HGG) versus non-glioma controls. The top-500 HGG proteins were then preliminarily filtered to include only proteins that met two additional criteria of decrease with resection and increase with recurrence in individual paired patient samples. RESULTS Proteomic enrichment analysis revealed a conserved HGG CSF proteomic signature defined by 79 proteins, including ones known to be over-expressed in solid tumor malignancies, such as retinoblastoma binding protein 4, heat shock protein 90, and sorcin. The HGG proteomic signature was consistently enriched in an independent validation cohort consisting of 13 gliomas diverse in primary versus recurrent status, subtype, and grade, when compared to control CSF samples. Encouragingly, proteins in the HGG signature decreased in the two patients for whom CSF was collected prior to and after resection (both at POD16 and POD18) with decreased tumor burden. CONCLUSION Our data demonstrate the ability to gain detailed, individualized insights regarding glioma biology, tumor burden, and evolution through global CSF proteomics acquired from longitudinal access to gliomas via Ommaya reservoirs.