Citations

OBJECTIVE Scoliosis is a degenerative disease with a 3D deformity in the alignment of the spinal column. Surgical spinal correction outcomes are heavily dependent on the surgeon’s expertise and use of visual cues because of time requirements, lack of automation, and radiation exposure associated with current intraoperative measurement techniques. In this study, the authors sought to validate a novel, nonradiographic, and semiautomated device that measures spinal alignment intraoperatively using deep learning and computer vision. METHODS To obtain spinal alignment metrics intraoperatively, the surgeon placed 3D-printed markers made of acrylonitrile butadiene styrene (ABS) plastic at designated locations in the surgical field. With the high-definition camera of the device, the surgeon can take an image of the markers in the surgical field. Images are processed through a computer vision model that detects the location of the markers and calculates the Cobb angle and coronal plumb line. The marker detection model was trained on 100 images and tested on 130 images of the ABS markers in various conditions. To verify the Cobb angle calculation, 50 models of angle templates from 0° to 180° in 3.6735° increments were created for testing. To verify the plumb line calculation, 21 models of plumb line measurements from −10 to +10 cm in increments of 1 cm were created for testing. A validation study was performed on a scoliotic cadaver model, and the radiographic calculations for Cobb angle and plumb line were compared with the device’s calculations. RESULTS The area under the curve for the marker detection model was 0.979 for Cobb angle white, 0.791 for Cobb angle black, and 1 for the plumb line model. The average absolute difference between expected and measured Cobb angles on the verification models was 1.726° ± 1.259°, within the clinical acceptable error of 5°. The average absolute difference between the expected and measured plumb lines on the verification models was 0.415 ± 0.255 cm. For the cadaver validation study, the differences between the radiographic and device calculations for the Cobb angle and plumb line were 2.78° and 0.29 cm, respectively. CONCLUSIONS The authors developed and validated a nonradiographic, semiautomated device that utilizes deep learning and computer vision to measure spinal metrics intraoperatively.

We show how switching from a regular diet to an HCHF increases cholesterol absorption in patients with normal weight and obesity. The decrease in cholesterol absorption from an HCHF to an LCLF, on the other hand, was only seen in normal-weight controls, underlining the importance of body weight in this regulation. In addition, changes in caloric and fat content had an immediate and direct effect on hepatic bile acid production.

Objective To determine whether radioiodine remnant ablation (RRA) reduces cause-specific mortality (CSM) or tumor recurrence rates (TRR) after potentially curative bilateral thyroidectomy (BT) in low-risk adult papillary thyroid carcinoma (APTC) patients, we compared postoperative outcomes in 1836 pTNM stage I APTC patients having BT alone with 832 having BT+RRA during two consecutive 25-year periods. Methods The THEN cohort (consecutively managed during 1966–1990) comprised 809 patients (36% having BT+RRA) and the NOW cohort (1991–2015) comprised 1859 patients (29% BT+RRA). Analyses of differences in occurrence rates between BT alone and BT+RRA patients were performed with SAS software. Results During 1966–1990, when RRA rates rose ten-fold, 20-year CSM after BT alone was 0.6% and after BT+RRA was 1.2% ( P = 0.66); during 1991–2015, when RRA rates progressively fell, no PTC deaths occurred in 1859 patients. In the THEN cohort, RRA did not significantly improve TRR at local, regional, or distant sites ( P > 0.1), when compared to BT alone. RRA in NOW cohort was administered to 49% of node-positive (pN1) patients and 17% of node-negative (pN0/NX) patients ( P < 0.0001); TRR therefore, were examined separately for pN0/NX and pN1 patients. In 1157 pN0/NX cases, 20-year locoregional TRR were 3.1% after BT and were higher ( P = 0.049) at 8.6% after BT+RRA. In four pN1 groups, stratified by metastatic nodal burden, RRA did not significantly reduce the locoregional TRR observed after BT with curative intent ( P > 0.5). Conclusions In a 5-decade experience, RRA administered postoperatively to stage I APTC patients did not reduce either CSM or TRR and should probably not be indicated when such patients undergo potentially curative BT.

Abstract Background: Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett esophagus (BE), explaining a small portion of heritability. Methods: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene-expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression. Results: Although the standard approach did not identify significant signals, the eQTL set–based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641, and HSP90AA1). Conclusions: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set–based genetic association approach. Impact: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set–based genetic association approach as an alternative method for TWAS analysis.

Abstract Interpretation of the clinical significance of somatic gene variants in cancer remains a major challenge in cancer diagnosis, prognosis and treatment response prediction. We will report on progress and plans of the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG). The CDWG membership consists of over 150 multi-disciplinary experts in cancer biology, oncology, pathology, genetics, genomics and informatics. The mission of the ClinGen Somatic Cancer CDWG is to facilitate the development of data curation guidelines and standards to determine the clinical significance of somatic alterations in cancer, thereby enhancing the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other knowledgebases including CIViC, ClinVar, and the Variant Interpretation for Cancer Consortium (VICC) MetaKB. Our goal is to create high-quality assertions of the clinical significance of specific somatic variants in cancer by leveraging the CIViC curation interface, adapting the germline procedures of ClinGen to somatic variant interpretation, and implementing the interoperability standards of the Global Alliance for Genomics and Health (GA4GH). The ClinGen Somatic effort is overseen by the Somatic CDWG and reports progress to the overall ClinGen consortium. There are Somatic Cancer subdomains focused on particular clinically important domains of cancer variant interpretation including three Task Forces (covering Pediatric Cancer, Hematologic Cancer, and Solid Tumors) and a growing number of Somatic Cancer Variant Curation Expert Panels (SC-VCEPs). To improve quality and consistency of clinical interpretations, each candidate somatic cancer VCEP must complete a four step approval process adapted from ClinGen’s work in Germline disease domains. The Somatic CDWG works to ensure that each group is aware of available training materials and detailed standard operating procedures. Each SC-VCEP also coordinates with the ClinGen Cancer Variant Interpretation Committee (CVI) whose goal is to support development of granular specifications for the AMP/ASCO/CAP guidelines for somatic variant interpretation. New SC-VCEPs are anticipated to focus on specific clinically relevant genes, pathways, disease entities, variant classes or treatment modalities. Currently, three SC-VCEPs have begun to work through the four step process (focused on FGFR mutations, NTRK fusions, and FLT3 mutations respectively), and two more SC-VCEPs are in the planning stage (Histone H3 and Ph-like ALL). To date, ClinGen Somatic groups have contributed 619 evidence lines into CIViC from 353 published papers and 21 assertions of clinical significance. Input from the AACR community is critical for the establishment of new SC-VCEPs that address areas of variant interpretation with the greatest need. Citation Format: Jason Saliba, Gordana Raca, Angshumoy Roy, Ian King, Shamini Selvarajah, Xinjie Xu, Rashmi Kanagal-Shamanna, Laveniya Satgunaseelan, David Meredith, Mark Evans, Alanna Church, Panieh Terraf, Yassmine Akkari, Heather E. Williams, Wan-Hsin Lin, Chimene Kesserwan, Deborah I. Ritter, Kilannin Krysiak, Arpad Danos, Alex Wagner, Marilyn M. Li, Dmitriy Sonkin, Jonathan S. Berg, Sharon E. Plon, Heidi L. Rehm, Shashikant Kulkarni, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith, on behalf of the ClinGen Somatic CDWG. The Clinical Genome Resource (ClinGen) somatic cancer clinical domain working group [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1192.

2038 Background: Glioblastoma (GBM) is the most common malignant brain tumor with poor clinical prognosis. Management of GBM is hampered by the lack of an accurate test that can be used for differential diagnosis of tumor progression from inflammatory pseudoprogression. Plasma extracellular vesicles (EVs) has been shown to be a promising source for biomarker identification. In this project, we aimed to identify GBM plasma EV markers that could serve as the basis of a liquid biopsy. Methods: Sample preparation, assay controls and instrument calibration were performed following MIFlowCyt-EV guideline. Plasma samples were subjected to 2-step centrifugations to remove cell debris and platelets. 10ul of plasma sample was diluted with 90ul filtered PBS, then stained for EV surface markers including CD9, CD31, CD45, CD41a and CD11b, as well as actin phalloidin. Stained plasma samples were purified using IZON qEV1/70nm column, then EV fractions were analyzed using full spectrum Cytek Aurora flow cytometer. Clustering analysis was performed on EV events (CD9 +/ actin phalloidin -) using t-SNE and FlowSOM extensions from FlowJo plugins. Results: Compared to normal donors, GBM plasma EVs were bigger in size (higher SSC value) and expressed higher levels of CD9, CD31, CD45 and CD11b while ND plasma EVs had higher CD41a expression. t-SNE and FlowSOM analysis demonstrated that GBM plasma EVs had a unique surface marker expression profile compared to ND EVs. It also showed 10 EV sub-populations that differed in size as well as various surface marker expression levels. Four of these subpopulations were enriched in GBM EVs, while three of these were enriched in ND EVs. Conclusions: This multiparametric analysis revealed that GBM plasma EVs had a unique surface marker expression profile compared to ND plasma EVs. Further separation and molecular profiling analysis based on each sub population could reveal EV biomarkers that are unique to each sample population.

1504 Background: Trial recruitment that requires specific actionable mutations based on next-generation sequencing (NGS) is challenging. Barriers can include competing studies, physician study awareness, site proximity, mutation incidence, among other concerns. Methods: This study (NCT04432454) opened clinical sites using two methods during the COVID-19 pandemic. The “Traditional” approach included site selection, IRB and contract approval, and trial activation prior to a patient being identified for enrollment. The second approach used the Tempus “TIME” Trials network that would only open a site after identifying a patient with a mutation of interest and eligible for the trial. Results: The first patient enrolled was on 10/12/20 and the last patient was on 6/24/21. A total of 16 sites (6 Traditional and 10 TIME) participated. All Traditional sites, and none of the TIME sites, were affiliated with major academic institutions. Duration for full CTA execution for Traditional sites averaged 200.5 days (range 142 to 257) and for TIME sites averaged 7.6 days (range 2 to 14). IRB approval time average for Traditional sites was 27.5 days (range 12 to 71) and TIME sites was 3.0 days (range 1 to 12 days). Days from site selection to activation letter for Traditional sites was on average 250.0 days (range 187 to 281) and for TIME sites was 131.6 days (range 22 to 248). Time from study activation to first consent was 33.3 days (range 18 to 58) for Traditional sites and 8.8 days (range 1 to 35) for TIME sites. The first patient on-study was at a TIME site 115 days prior to a Traditional site and the first 7 patients enrolled were at TIME sites. Traditional sites consented 23 and enrolled 16 patients while the TIME sites consented 16 and enrolled 13. The trial enrolled all 29 patients in 8 months with the anticipated enrollment duration being 12 to 18 months. Conclusions: Although the Traditional and TIME programs had different operational models, they both contributed a significant number of patients and reduced the projected enrollment timeline. TIME sites enrolled the initial patients. These results demonstrate that the “Just-in-Time model,” in conjunction with a Traditional model, can reduce projected overall time to enrollment in biomarker-driven studies. [Table: see text]

Abstract Glioblastoma (GBM) is a rapidly fatal malignancy typically treated with radiation and temozolomide (TMZ), an alkylating chemotherapeutic. These cytotoxic therapies cause oxidative stress and DNA damage, yielding a senescent-like state of replicative arrest in surviving tumor cells. Unfortunately, recurrence is inevitable and may be driven by surviving tumor cells eventually escaping senescence. A growing number of so-called “senolytic” drugs have been recently identified that are defined by their ability to selectively eliminate senescent cells. A growing inventory of senolytic drugs is under consideration for several diseases associated with aging, inflammation, DNA damage, as well as cancer. Ablation of senescent tumor cells after radiation and chemotherapy could help mitigate recurrence by decreasing the burden of residual tumor cells at risk of recurrence. This strategy has not been previously explored for GBM. We evaluated a panel of 10 previously described senolytic drugs to determine whether any could exhibit selective activity against human GBM persisting after exposure to radiation or TMZ. Three of the 10 drugs have known activity against BCL-XL and preferentially induced apoptosis in radiated or TMZ-treated glioma. This senolytic activity was observed in 12 of 12 human GBM cell lines. Efficacy could not be replicated with BCL-2 inhibition or senolytic agents acting against other putative senolytic targets. Knockdown of BCL-XL decreased survival of radiated GBM cells, whereas knockdown of BCL-2 or BCL-W yielded no senolytic effect. Implications: These findings imply that molecularly heterogeneous GBM lines share selective senescence-induced BCL-XL dependency increase the significance and translational relevance of the senolytic therapy for latent glioma.