Citations

Abstract Background Intracranial mesenchymal tumors, FET::CREB fusion-positive (ICMT), show fusions involving FET RNA-binding protein family genes (EWSR1 or FUS) and CREB family of transcription factors (ATF1, CREB1, or CREM). The methylation signature(s), gene expression characteristics, and clinical behavior of this important tumor type require further characterization. Methods We study the methylation profiles of 81 ICMT cases (61 newly profiled cases and 20 cases from publicly available sources). Clinicopathologic and genomic data were recorded for each case when available. Results ICMT showed a relatively distinct methylation signature compared to related tumors. Among the 65 cases where fusion types were documented, the identified fusions included EWSR1::ATF1 (25 cases), EWSR1::CREB1 (12 cases), EWSR1::CREM (21 cases), FUS::CREM (3 cases), and SMARCA2::CREM (4 cases). We confirmed the prior description of 2 distinct subgroups of ICMT (subclasses A and B). The majority of the cases belonged to subclass A (n = 69; 85%), which showed a higher median age compared to subclass B patients (26 years vs. 15 years). Subclass B cases (n = 12; 15%) showed shorter progression-free survival (P < 0.01). Gene expression analysis of ICMT showed key overexpressed markers in ICMT, with significant CREM overexpression regardless of fusion type, when compared to either meningioma alone or a larger group of CNS tumors. Conclusions This work provides further characterization of ICMT as an important CNS mesenchymal neoplasm that is prone to tumor recurrence, showing 2 prognostically relevant methylation subclasses and warranting diagnostic distinction from other epigenetically and histologically related tumors. ICMTs show substantial overexpression of the CREM gene, independent of fusion type.

Abstract Computer vision now enables deep learning models to link histopathologic features to molecular features in a quantitative manner not previously achievable by human pathologists. However, human interpretability is often limited. We trained a deep neural network to predict gene expression from digital whole slide images (WSIs) using 848 central nervous system (CNS) tumors with paired WSI and RNA-sequencing data. We used inferred RNA expression levels as a surrogate for protein expression of the CNS tumor lineage markers GFAP, OLIG2, and SSTR2, as well as the proliferation marker MKI67 (Ki67). We established thresholds for categorizing the inferred expression levels as positive or negative based on levels observed in cross-validation testing in select tumor types to approximate routine clinical interpretation of immunohistochemical (IHC) staining. We tested the sensitivity and specificity of our ‘virtual’ IHC on an independent, multi-institutional cohort of over 2,000 CNS tumors with objective diagnostic labels derived from DNA methylation-based tumor classification. As a dichotomous variable, inferred GFAP expression showed a sensitivity of 74% and a specificity of 99% as a glial marker in a cohort of gliomas and meningiomas. In the same cohort, OLIG2 showed a sensitivity of 75% and a specificity of 97% as a glial marker, while SSTR2 showed a sensitivity of 83% and a specificity of 97% as a marker of meningioma. In a cohort of ependymomas and gliomas, virtual IHC for OLIG2 showed a sensitivity of 75% and a specificity of 82% in distinguishing ependymomas from gliomas. Finally, in a cohort of gliomas, inferred expression of MKI67 demonstrated a trend consistent with what would be expected by actual IHC, with increasing MKI67 expression with increasing tumor grade. Our model provides the basis for a human interpretable and clinically applicable deep neural network to aid human pathologists in the diagnosis and grading of CNS tumors.

10556 Background: The coexistence of interstitial lung diseases (ILD) and lung cancer (LC) presents a clinical challenge. ILD, including idiopathic pulmonary fibrosis (IPF) and non-IPF entities, is associated with an elevated risk of LC. However, the clinical features, treatment patterns, and survival outcomes of ILD-LC, especially IPF-LC, remain underexplored. We aimed to comprehensively evaluate survival outcomes and risk factors for mortality of ILD-LC patients based on a real-world long-term clinical cohort. Methods: A total of 1,341 eligible patients for this study were drawn from the Epidemiology and Genetics of Lung Cancer research program database (Mayo Clinic) including 96 IPF-LC, 111 Non-IPF ILD-LC, 99 ILD-only, and 1,035 propensity-matched LC-only patients (Controls). Data were collected on demographics, comorbidities, tumor features, treatment, and patient outcomes. Survival analyses used Kaplan-Meier methods; risk factors were assessed via Cox Proportional Hazards models. All comparisons reported below were statistically significant with p-values≤0.001 unless specified. Results: Among the 20,470 primary LC patients who were diagnosed from 1997 through 2016 and followed to 2021, 207 (1.0%) had ILD-LC, of which 96 (46.4%) had IPF. Comparing to Controls, ILD-LC patients were 4 years older at the time of LC diagnosis, 63.8% (vs. 52.8%) male, had a higher rate of former smokers (60.4% vs. 47.3%), a lower proportion of adenocarcinoma (37.7% vs. 57.5%), and a higher proportion of squamous cell (28.0% vs. 20.3%) and small cell carcinoma (13.5% vs. 8.4%). Although no significant differences in either LC stage or grade, ILD-LC patients had a significantly higher mortality rate (90.3% vs. 78.8%), particularly among IPF-LC patients (97.9% vs. 83.8%). ILD-LC patients were less likely to undergo surgery or receiving pharmacological treatments (73.9% vs. 93.5%). The median 5-year overall survival rate (OS, months) were 49.5 for Controls, 35.2 for Non-IPF ILD-LC patients, and 15.9 for IPF-LC patients. Analysis of six most common comorbidities revealed that pulmonary hypertension was associated with worse OS in ILD-LC patients compared to those without it (11.9% vs. 20.1%, P < 0.05); however unexpectedly, hypertension in ILD-LC patients was associated with better OS (21.3% vs. 14.4%) and emphysema in IPF-LC patients with better OS (7.9% vs. 3.4%, P < 0.05) when compared to those without the two comorbidities, respectively. Conclusions: This study highlights the poorer survival outcomes in ILD-LC patients, particularly IPF-LC patients, emphasizing the need for further investigation into optimized therapies and comorbidity management. Our findings also call for attention to two unexpected associations of hypertension and emphysema, warranting in-depth research on the possible biological and physiological mechanisms.

Inositol 1,4,5-trisphosphate (IP3) receptor type 1 ( ITPR1 ), 2 ( ITPR2 ), and 3 ( ITPR3 ) encode the IP3 receptor (IP3R), a key player in intracellular calcium release. In four unrelated patients, we report that an identical ITPR3 de novo variant—NM_002224.3:c.7570C>T, p.Arg2524Cys—causes, through a dominant-negative effect, a complex multisystemic disorder with immunodeficiency. This leads to defective calcium homeostasis, mitochondrial malfunction, CD4 + lymphopenia, a quasi-absence of naïve CD4 + and CD8 + cells, an increase in memory cells, and a distinct TCR repertoire. The calcium defect was recapitulated in Jurkat knock-in. Site-directed mutagenesis displayed the exquisite sensitivity of Arg 2524 to any amino acid change. Despite the fact that all patients had severe immunodeficiency, they also displayed variable multisystemic involvements, including ectodermal dysplasia, Charcot-Marie-Tooth disease, short stature, and bone marrow failure. In conclusion, unlike previously reported ITPR1-3 deficiencies leading to narrow, mainly neurological phenotypes, a recurrent dominant ITPR3 variant leads to a multisystemic disease, defining a unique role for IP3R3 in the tetrameric IP3R complex.

Abstract Background: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.