Citations

Abstract Introduction Tumefactive multiple sclerosis (MS) and glioblastoma (GBM) can be difficult to differentiate. Clinical presentations are nonspecific and may occur in patients with both diseases. Magnetic resonance imaging (MRI) scans are routinely used to generate an initial differential diagnosis. Although imaging features can help distinguish these entities, there are no pathognomonic signs, neither on traditional nor advanced MRI. Moreover, the ability to differentiate these entities depends on the radiologists’ experience. Ensuring the correct diagnosis has important therapeutic and prognostic implications, as the management of these diseases is very different. To date, a brain biopsy often represents the only option to obtain a diagnosis, but it may be inconclusive and could add unnecessary morbidity. We hypothesize that a machine-learning tool based on routinely performed MRI scans could guarantee a more reliable, fast, and reproducible diagnosis. Methods Only patients with a histological diagnosis were included in the study. Patients that underwent any form of radiation therapy before the surgery were excluded to avoid confounding factors due to treatment-related effects. A total of 99 MS and 257 GBMs were included, and preoperative T2-weighted images were collected. For each patient, the lesions' segmentation was performed, including both the contrast-enhancing and non-enhancing areas of the lesions. The segmentation masks were used to extract radiomic features from the T2-weighted sequences. All MRI images were standardized to the same mean and standard deviation before feature extraction and resampled to a voxel size of 1.0 × 1.0 × 1.0 mm. Features extraction was performed using Pyradiomics (v. 3.0.1) and included first order, shape, and texture features, totaling 100 features. The classifier consisted of a support vector machine (SVM) model. Patients were randomly assigned to the training and test sets with an 80-20% proportion for each class. To select the best hyperparameters for the SVM classifier, a grid-search analysis was performed on the training set using a nested cross-validation scheme (k=5). All experiments were performed using Python (v. 3.5) and the Scikit-learn library (v. 0.23.1). Results The mean accuracy and area under the ROC curve for the best set of hyperparameters on the validation set were 0.83 and 0.86, respectively. The weighted-average precision, recall, and F1 scores on the test set were 0.78, 0.76, and 0.77, respectively. Conclusions Radiomic features extracted from a routinely acquired MRI sequence showed promising results in differentiating tumefactive multiple sclerosis from glioblastoma, opening the possibility to obtain a reliable diagnosis without the need for a brain biopsy. Future experiments Future experiments will focus on using post-contrast T1-weighted images for the radiomic features extractions, testing multiple machine learning models and features selection algorithms, and including more diagnostic classes (i.e., metastasis, lymphomas). Citation Format: Gian Marco Conte, Jeanette E. Eckel-Passow, W. Oliver Tobin, Paul Decker, Daniel H. Lachance, Robert B. Jenkins, Bradley J. Erickson. Differentiation of tumefactive multiple sclerosis and glioblastoma using radiomics features extracted from magnetic resonance imaging and machine learning [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-023.

AbstractBackgroundCutaneous squamous cell carcinomas (CSCC) involving the head and neck are common, but initial presentation or recurrence limited to the cranial nerves is rare.MethodsWe conducted a retrospective study of 21 patients with clinical perineural invasion (PNI) from CSCC and no measurable disease by RECIST 1.1. Patients treated with radiotherapy or chemoradiotherapy were included.ResultsThe median time from symptom onset until diagnosis was 13.0 months (2.6–83.1). All patients received radiotherapy. Fourteen received concurrent systemic therapy. The median follow‐up time was 30.5 months (1.1–106.0). Ten patients recurred, with the majority being locoregional. The 2‐year overall survival rate was 85%. The median progression‐free survival (PFS) was 21.5 months with an estimated 2‐year PFS of 44.5% (95%CI: 22.3–66.8).ConclusionsCSCCs with clinical PNI alone are difficult to diagnose and can have a long interval between appearance of symptoms and diagnosis. They can successfully be treated with chemoradiotherapy. However, many patients still suffer from locoregional recurrences.

Posterior fossa (PF) diffuse gliomas in pediatric patients frequently harbor the H3 K27M mutation. Among adults, PF diffuse gliomas are rare, with limited data regarding molecular features and clinical outcomes. We identified 28 adult PF diffuse glioma patients (17 males; median: 50 y, range: 19 to 78 y), with surgery performed at our institution (13 brainstem; 15 cerebellum). Histologic subtypes included anaplastic astrocytoma (n=21), glioblastoma (n=6), and diffuse astrocytoma (n=1). Immunohistochemistry was performed for H3 K27M (n=26), IDH1-R132H (n=28), and ATRX (n=28). A 150-gene neuro-oncology-targeted next-generation sequencing panel was attempted in 24/28, with sufficient informative material in 15 (51.7%). Tumors comprised 4 distinct groups: driver mutations in H3F3A (brainstem=4; cerebellum=2), IDH1 (brainstem=4; cerebellum=4), TERT promotor mutation (brainstem=0; cerebellum=3), and none of these (n=5), with the latter harboring mutations of TP53 , PDGFRA , ATRX , NF1 , and RB1 . All TERT promoter–mutant cases were IDH-wild-type and arose within the cerebellum. To date, 20 patients have died of disease, with a median survival of 16.3 months, 1-year survival of 67.5%. Median survival within the subgroups included: H3F3A =16.4 months, IDH mutant=113.4 months, and TERT promoter mutant=12.9 months. These findings suggest that PF diffuse gliomas affecting adults show molecular heterogeneity, which may be associated with patient outcomes and possible response to therapy, and supports the utility of molecular testing in these tumors.

Objective An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. Design To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. Results We identified 13 loci that reached genome-wide significance (p<5×10 −8 ) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. Conclusion Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Abstract Background: Inherited susceptibility is an important contributor to colorectal cancer risk, and rare variants in key genes or pathways could account in part for the missing proportion of colorectal cancer heritability. Methods: We conducted an exome-wide association study including 2,327 cases and 2,966 controls of European ancestry from three large epidemiologic studies. Single variant associations were tested using logistic regression models, adjusting for appropriate study-specific covariates. In addition, we examined the aggregate effects of rare coding variation at the gene and pathway levels using Bayesian model uncertainty techniques. Results: In an exome-wide gene-level analysis, we identified ST6GALNAC2 as the top associated gene based on the Bayesian risk index (BRI) method [summary Bayes factor (BF)BRI = 2604.23]. A rare coding variant in this gene, rs139401613, was the top associated variant (P = 1.01 × 10–6) in an exome-wide single variant analysis. Pathway-level association analyses based on the integrative BRI (iBRI) method found extreme evidence of association with the DNA repair pathway (BFiBRI = 17852.4), specifically with the nonhomologous end joining (BFiBRI = 437.95) and nucleotide excision repair (BFiBRI = 36.96) subpathways. The iBRI method also identified RPA2, PRKDC, ERCC5, and ERCC8 as the top associated DNA repair genes (summary BFiBRI ≥ 10), with rs28988897, rs8178232, rs141369732, and rs201642761 being the most likely associated variants in these genes, respectively. Conclusions: We identified novel variants and genes associated with colorectal cancer risk and provided additional evidence for a role of DNA repair in colorectal cancer tumorigenesis. Impact: This study provides new insights into the genetic predisposition to colorectal cancer, which has potential for translation into improved risk prediction.

Abstract Objectives To evaluate SATB2 expression and prognostic implications in a large cohort of thoracic neuroendocrine tumors. Methods Surgical pathology files (1995-2017) and an institutional thymic epithelial tumor database (2010-2020) were searched for resected neuroendocrine tumors. Cases were stained with SATB2 (clone EP281). Percent SATB2-positive tumor cells and expression intensity were scored. Results In the lung, SATB2 was expressed in 5% or more of tumor cells in 29 (74.4%) of 39 small cell carcinomas and 9 (22.5%) of 40 atypical and 26 (40.6%) of 64 typical carcinoid tumors. SATB2 percent tumor cell expression and intensity were higher in small cell carcinomas than in carcinoid tumors (both P &lt; .001, respectively). After adjusting for tumor subtype, SATB2 expression did not correlate with outcome. In the thymus, four (100%) of four atypical carcinoid tumors and one large cell neuroendocrine carcinoma but no small cell carcinoma (n = 2) expressed SATB2 in 5% or more of tumor cells. Conclusions SATB2 (clone EP281) is expressed in a large subset of pulmonary and thymic neuroendocrine tumors and therefore does not appear to be a useful marker to identify the origin of neuroendocrine tumors. Validation studies are needed, specifically including thymic neuroendocrine tumors, as the expression pattern might be different in those tumors.

Abstract Context. —Intratumoral heterogeneity of HER2 gene amplification has been well documented and represents subclonal diversity within the tumor. The reported incidence of intratumor HER2 amplification genetic heterogeneity ranges in the literature from approximately 5% to 30%. The presence of HER2 genetic heterogeneity may increase subjectivity in HER2 interpretation by the pathologist. Objectives. —To define HER2 genetic heterogeneity and to provide practice guidelines for examining and reporting breast tumors with genetic heterogeneity for improvement of HER2 testing in breast cancer. Design. —We convened an expert panel to discuss HER2 gene amplification testing by fluorescence in situ hybridization. Components addressed included a definition of HER2 amplification heterogeneity, practice guidelines for examination of the tissue, and reporting criteria for this analysis. Results. —Genetic heterogeneity for amplification of HER2 gene status in invasive breast cancer is defined and guidelines established for assessing and reporting HER2 results in these cases. These guidelines are additive to and expand those published in 2007 by the American Society of Clinical Oncology and the College of American Pathologists. Conclusion. —Standardized methods for analysis will improve the accuracy and consistency of interpretation of HER2 gene amplification status in breast cancer.

AbstractAimsLong‐term lithium therapy (LTLT) has been associated with kidney insufficiency in bipolar disorder (BD). We aimed to investigate the risk factors of chronic kidney disease (CKD) development and progression among BD patients receiving LTLT.MethodsWe included adult patients with BD on LTLT (≥1 year) who were enrolled in the Mayo Clinic Bipolar Biobank, Rochester, Minnesota. We reviewed electronic medical records to extract information related to lithium therapy and kidney‐related data to assess changes in the estimated glomerular filtration rate (eGFR). CKD severity was assessed based on eGFR.ResultsAmong 154 patients who received LTLT, 41 patients (27%) developed CKD, of whom 20 (49%) patients continued lithium (continuers) and 19 (46%) discontinued it (discontinuers). The median time to stage 3 CKD development was 21.7 years from the start of Li treatment. Type‐2 diabetes mellitus and benzodiazepine use were independent predictors for CKD development in the survival analysis, after controlling for age. The subsequent CKD progression rate did not differ between continuers and discontinuers (mean GFR 48.6 vs. 44.1, p = 0.13) at the end of follow‐up duration (mean duration: 3.5 ± 4.4 years for continuers and 4.9 ± 5.3 years for discontinuers).ConclusionCKD was observed in one fourth of patients with BD receiving LTLT. There was no significant difference in the progression of CKD among Li continuers versus discontinuers, at the mean follow‐up duration of 4.2 years, after the CKD diagnosis. Progression of CKD could be influenced by existing comorbidities and may not necessarily be due to lithium alone.

One in a hundred babies, or 1.3 million per year around the world, are born with congenital heart defects (CHD), of which over 70% will require medical or surgical treatment within their first year of life. In low- and middle-income countries, the majority does not receive the treatment they need or receive suboptimal care. Despite a higher pediatric cardiac surgical disease burden, low-income countries only have 0.07 pediatric cardiac surgeons per million pediatric population, compared to 9.51 per million in high-income countries. Here, we perform a stakeholder analysis of existing advocacy bodies within the field of pediatric global cardiac surgery and identify gaps and opportunities in advocating for cardiac care for children with CHD. We propose a framework to optimize civil society messaging in order to more effectively advocate domestically and internationally to hold national and international policy makers accountable for existing gaps and disparities in CHD care around the world.