Citations

Abstract Chimeric antigen receptor T-cell (CAR-T cell) therapy directed at CD19 produces durable remissions in the treatment of relapsed/refractory non-Hodgkin lymphoma (NHL). Nonetheless, many patients receiving CD19 CAR-T cells fail to respond for unknown reasons. To reveal changes in 4-1BB–based CD19 CAR-T cells and identify biomarkers of response, we used single-cell RNA sequencing and protein surface marker profiling of patient CAR-T cells pre- and postinfusion into patients with NHL. At the transcriptional and protein levels, we note the evolution of CAR-T cells toward a nonproliferative, highly differentiated, and exhausted state, with an enriched exhaustion profile in CAR-T cells of patients with poor response marked by TIGIT expression. Utilizing in vitro and in vivo studies, we demonstrate that TIGIT blockade alone improves the antitumor function of CAR-T cells. Altogether, we provide evidence of CAR-T cell dysfunction marked by TIGIT expression driving a poor response in patients with NHL. Significance: This is the first study investigating the mechanisms linked to CAR-T patient responses based on the sequential analysis of manufactured and infused CAR-T cells using single-cell RNA and protein expression data. Furthermore, our findings are the first to demonstrate an improvement of CAR-T cell efficacy with TIGIT inhibition alone. This article is highlighted in the In This Issue feature, p. 1825

Abstract Context Thyroid nodule risk stratification allows clinicians to standardize the evaluation of thyroid cancer risk according to ultrasound features. Objective To evaluate interrater agreement among clinicians assessing thyroid nodules ultrasound features and thyroid cancer risk categories. Design, setting, and participants We surveyed Endocrine Society and Latin American Thyroid Society members to assess their interpretation of composition, echogenicity, shape, margins, and presence of echogenic foci of 10 thyroid nodule cases. The risk category for thyroid cancer was calculated following the American College of Radiology-Thyroid Imaging Reporting & Data System (ACR-TIRADS) framework from individual responses. Main Outcomes and Measures We used descriptive statistics and Gwet’s agreement coefficient (AC1) to assess the primary outcome of interrater agreement for ACR-TIRADS risk category. As secondary outcomes, the interrater agreement for individual features and a subgroup analysis of interrater agreement for the ACR-TIRADS category were performed (ultrasound reporting system, type of practice, and number of monthly appraisals). Results A total of 144 participants were included, mostly endocrinologists. There was moderate level of agreement for the absence of echogenic foci (AC1 0.53, 95% CI 0.24-0.81) and composition (AC1 0.54, 95% CI 0.36-0.71). The agreement for margins (AC1 0.24, 95% CI 0.15-0.33), echogenicity (AC1 0.34, 95% CI 0.22-0.46), and shape assessment (AC1 0.42, 95% CI 0.13-0.70) was lower. The overall agreement for ACR-TIRADS assessment was AC1 0.29, (95% CI 0.13-0.45). The AC1 of ACR-TIRADS among subgroups was similar. Conclusions This study found high variation of judgments about ACR-TIRADS risk category and individual features, which poses a potential challenge for the widescale implementation of thyroid nodule risk stratification.

Abstract This study aimed to explore the prognostic impact of spatial distribution of tumor‐infiltrating lymphocytes (TILs) quantified by deep learning (DL) approaches based on digitalized whole‐slide images stained with hematoxylin and eosin in patients with colorectal cancer (CRC). The prognostic impact of spatial distributions of TILs in patients with CRC was explored in the Yonsei cohort ( n = 180) and validated in The Cancer Genome Atlas (TCGA) cohort ( n = 268). Two experienced pathologists manually measured TILs at the most invasive margin (IM) as 0–3 by the Klintrup–Mäkinen (KM) grading method and this was compared to DL approaches. Inter‐rater agreement for TILs was measured using Cohen's kappa coefficient. On multivariate analysis of spatial TIL features derived by DL approaches and clinicopathological variables including tumor stage, microsatellite instability, and KRAS mutation, TIL densities within 200 μm of the IM (f_im200) remained the most significant prognostic factor for progression‐free survival (PFS) (hazard ratio [HR] 0.004 [95% confidence interval, CI, 0.0001–0.15], p = 0.0028) in the Yonsei cohort. On multivariate analysis using the TCGA dataset, f_im200 retained prognostic significance for PFS (HR 0.031 [95% CI 0.001–0.645], p = 0.024). Inter‐rater agreement of manual KM grading was insignificant in the Yonsei ( κ = 0.109) and the TCGA ( κ = 0.121) cohorts. The survival analysis based on KM grading showed statistically significant different PFS in the TCGA cohort, but not the Yonsei cohort. Automatic quantification of TILs at the IM based on DL approaches shows prognostic utility to predict PFS, and could provide robust and reproducible TIL density measurement in patients with CRC.

Abstract Inhibitory receptors have a critical role in the regulation of immunity. Siglecs are a family of primarily inhibitory receptors expressed by immune cells that recognize specific sialic acid modifications on cell surface glycans. Many tumors have increased sialic acid incorporation. Overexpression of the sialyltransferase ST8Sia6 on tumors led to altered immune responses and increased tumor growth. In this study, we examined the role of ST8Sia6 on immune cells in regulating antitumor immunity. ST8Sia6 knockout mice had an enhanced immune response to tumors. The loss of ST8Sia6 promoted an enhanced intratumoral activation of macrophages and dendritic cells, including upregulation of CD40. Intratumoral regulatory T cells exhibited a more inflammatory phenotype in ST8Sia6 knockout mice. Using adoptive transfer studies, the change in regulatory T cell phenotype was not cell intrinsic and depended on the loss of ST8Sia6 expression in APCs. Thus, ST8Sia6 generates ligands for Siglecs that dampen antitumor immunity.

Abstract Background and Aims Although many studies revealed transcriptomic subtypes of HCC, concordance of the subtypes are not fully examined. We aim to examine a consensus of transcriptomic subtypes and correlate them with clinical outcomes. Approach and Results By integrating 16 previously established genomic signatures for HCC subtypes, we identified five clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features, but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta‐Catenin with high Male predominance) is characterized by prominent β‐catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high hepatocyte nuclear factor 4A activity. We also developed and validated a robust predictor of consensus subtype with 100 genes and demonstrated that five subtypes were well conserved in patient‐derived xenograft models and cell lines. By analyzing serum proteomic data from the same patients, we further identified potential serum biomarkers that can stratify patients into subtypes. Conclusions Five HCC subtypes are correlated with genomic phenotypes and clinical outcomes and highly conserved in preclinical models, providing a framework for selecting the most appropriate models for preclinical studies.

Background Inhaled corticosteroids (ICSs) are important in asthma management, but there are concerns regarding associated risk of pneumonia. While studies in asthmatic adults have shown inconsistent results, this risk in asthmatic children is unclear. Objective Our aim was to determine the association of ICS use with pneumonia risk in asthmatic children. Methods A nested case-control study was performed in the Mayo Clinic Birth Cohort. Asthmatic children (<18 years) with a physician diagnosis of asthma were identified from electronic medical records of children born at Mayo Clinic from 1997 to 2016 and followed until 31 December 2017. Pneumonia cases defined by Infectious Disease Society of America were 1:1 matched with controls without pneumonia by age, sex and asthma index date. Exposure was defined as ICS prescription at least 90 days prior to pneumonia. Associations of ICS use, type and dose (low, medium and high) with pneumonia risk were analysed using conditional logistic regression. Results Of the 2108 asthmatic children eligible for the study (70% mild intermittent and 30% persistent asthma), 312 children developed pneumonia during the study period. ICS use overall was not associated with risk of pneumonia (adjusted OR: 0.94, 95% CI: 0.62 to 1.41). Poorly controlled asthma was significantly associated with the risk of pneumonia (OR: 2.03, 95% CI: 1.35 to 3.05; p<0.001). No ICS type or dose was associated with risk of pneumonia. Conclusion ICS use in asthmatic children was not associated with risk of pneumonia but poorly controlled asthma was. Future asthma studies may need to include pneumonia as a potential outcome of asthma management.

Abstract Background: The etiology of colorectal cancer is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 &gt; 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini–Hochberg FDR (BH-FDR) &lt; 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10−8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR &lt; 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10−11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het &lt; 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer. Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact: The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.

AbstractBackgroundAlthough racial and ethnic identities are associated with a multitude of disparate medical outcomes, surveillance of these subpopulations in the occupational clinic setting could benefit enormously from a more detailed and nuanced recognition of racial and ethnic identity.MethodsThe research group designed a brief questionnaire to capture several dimensions of this identity and collected data from patients seen for work‐related conditions in four occupational medicine clinics from May 2019 through March 2020. Responses were used to calculate the sensitivity and specificity of extant racial/ethnic identity data within our electronic health records system, and were compared to participants' self‐reported industry and occupation, coded according to North American Industry Classification System and Standard Occupational Classification System listings.ResultsOur questionnaire permitted collection of data that defined our patients' specific racial/ethnic identity with far greater detail, identified patients with multiple ethnic identities, and elicited their preferred language. Response rate was excellent (94.2%, n = 773). Non‐White participants frequently selected a racial/ethnic subcategory (78.1%–92.2%). Using our race/ethnicity data as a referent, the electronic health record (EHR) had a high specificity (>87.1%), widely variable sensitivity (11.8%–82.2%), and poorer response rates (75.1% for race, 82.5% for ethnicity, as compared to 93.8% with our questionnaire). Additional analyses revealed some industries and occupations disproportionately populated by patients of particular racial/ethnic identities.ConclusionsOur project demonstrates the usefulness of a questionnaire which more effectively identifies racial/ethnic subpopulations in an occupational medicine clinic, permitting far more detailed characterization of their occupations, industries, and diagnoses.