Citations

T cells show tremendous efficacy as cellular therapeutics. However, obtaining primary T cells from human donors is expensive and variable. Pluripotent stem cells (PSCs) have the potential to provide a renewable source of T cells, but differentiating PSCs into hematopoietic progenitors with T cell potential remains an important challenge. Here, we report an efficient serum- and feeder-free system for differentiating human PSCs into hematopoietic progenitors and T cells. This fully defined approach allowed us to study the impact of individual proteins on blood emergence and differentiation. Providing DLL4 and VCAM1 during the endothelial-to-hematopoietic transition enhanced downstream progenitor T cell output by ~80-fold. These two proteins synergized to activate notch signaling in nascent hematopoietic stem and progenitor cells, and VCAM1 additionally promoted an inflammatory transcriptional program. We also established optimized medium formulations that enabled efficient and chemically defined maturation of functional CD8αβ + , CD4 − , CD3 + , TCRαβ + T cells with a diverse TCR repertoire.

ObjectiveSome patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID‐19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID‐19 ARDS in this population and to create a simple risk score calculator for use in clinical settings.MethodsData were derived from the COVID‐19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID‐19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier.ResultsThe study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67‐0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%‐83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator.ConclusionWe were able to predict ARDS with good sensitivity using information readily available at COVID‐19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID‐19 disease progression.

AbstractQualified medical physicists (QMPs) are in a unique position to influence the creation and application of key performance indicators (KPIs) across diverse practices in health care. Developing KPIs requires the involvement of stakeholders in the area of interest. Fundamentally, KPIs should provide actionable information for the stakeholders using or viewing them. During development, it is important to strongly consider the underlying data collection for the KPI, making it automatic whenever possible. Once the KPI has been validated, it is important to setup a review cycle and be prepared to adjust the underlying data or action levels if the KPI is not performing as intended. Examples of specific KPIs for QMPs of common scopes of practice are provided to act as models to aid in implementation. KPIs are a useful tool for QMPs, regardless of the scope of practice or practice environment, to enhance the safety and quality of care being delivered.

BackgroundTo evaluate risk factors (treatment‐related, comorbidities, and lifestyle) for breast cancer–related lymphedema (BCRL) within the context of a Prospective Surveillance and Early Intervention (PSEI) model of care for subclinical BCRL.MethodsThe parent randomized clinical trial assigned patients newly diagnosed with breast cancer to PSEI with either bioimpedance spectroscopy (BIS) or tape measurement (TM). Surgical, systemic and radiation treatments, comorbidities, and lifestyle factors were recorded. Detection of subclinical BCRL (change from baseline of either BIS L‐Dex ≥6.5 or tape volume ≥ 5% and < 10%) triggered an intervention with compression therapy. Volume change from baseline ≥10% indicated progression to chronic lymphedema and need for complex decongestive physiotherapy. In this secondary analysis, multinomial logistic regressions including main and interaction effects of the study group and risk factors were used to test for factor associations with outcomes (no lymphedema, subclinical lymphedema, progression to chronic lymphedema after intervention, progression to chronic lymphedema without intervention). Post hoc tests of significant interaction effects were conducted using Bonferroni‐corrected alphas of .008; otherwise, an alpha of .05 was used for statistical significance.ResultsThe sample (n = 918; TM = 457; BIS = 461) was female with a median age of 58.4 years. Factors associated with BCRL risk included axillary lymph node dissection (ALND) (p < .001), taxane‐based chemotherapy (p < .001), regional nodal irradiation (RNI) (p ≤ .001), body mass index >30 (p = .002), and rurality (p = .037). Mastectomy, age, hypertension, diabetes, seroma, smoking, and air travel were not associated with BCRL risk.ConclusionsWithin the context of 3 years of PSEI for subclinical lymphedema, variables of ALND, taxane‐based chemotherapy, RNI, body mass index >30, and rurality increased risk.

Abstract Seven different anti-PD-1 and PD-L1 monoclonal antibodies are now widely used in the US to treat a variety of cancer types, but there have been no clinical trials comparing them directly. Furthermore, because many of these antibodies do not cross react between mouse and human proteins, no preclinical models exist in which to consider these types of questions. Thus, we produced humanized PD-1 and PD-L1 mice in which the extracellular domains of both mouse PD-1 and PD-L1 were replaced with the corresponding human sequences. Using this new model, we sought to compare the strength of the immune response generated by FDA-approved antibodies. To do this, we performed an in vivo T cell priming assay in which anti-PD-1/L1 therapies were given at the time of T cell priming against surrogate tumor antigen (OVA), followed by subsequent B16-OVA tumor challenge. We found that anti-PD-1/L1-treated mice exhibited significantly better tumor rejection than controls, although both the control and antibody-treated mice generated comparable numbers of OVA-specific T cells at the time of priming. To determine what could mediate this strong antitumor immune response, we identified the increased production of CX3CR1+PD-1+CD8+ cytotoxic T cells in the anti-PD-1/L1-treated mice, the same subset of effector T cells known to increase in clinical responders to PD-1/L1 therapy. Thus, our model permits the direct comparison of FDA-approved anti-PD-1/L1 monoclonal antibodies and further correlates successful tumor rejection with the level of CX3CR1+PD-1+CD8 + T cells, making this model a critical tool for future studies to optimize and better utilize anti-PD-1/L1 therapeutics.

Radiotherapy (RT) of colorectal cancer (CRC) can prime adaptive immunity against tumor-associated antigen (TAA)–expressing CRC cells systemically. However, abscopal tumor remissions are extremely rare, and the postirradiation immune escape mechanisms in CRC remain elusive. Here, we found that irradiated CRC cells used ATR-mediated DNA repair signaling pathway to up-regulate both CD47 and PD-L1, which through engagement of SIRPα and PD-1, respectively, prevented phagocytosis by antigen-presenting cells and thereby limited TAA cross-presentation and innate immune activation. This postirradiation CD47 and PD-L1 up-regulation was observed across various human solid tumor cells. Concordantly, rectal cancer patients with poor responses to neoadjuvant RT exhibited significantly elevated postirradiation CD47 levels. The combination of RT, anti-SIRPα, and anti–PD-1 reversed adaptive immune resistance and drove efficient TAA cross-presentation, resulting in robust TAA-specific CD8 T cell priming, functional activation of T effectors, and increased T cell clonality and clonal diversity. We observed significantly higher complete response rates to RT/anti-SIRPα/anti–PD-1 in both irradiated and abscopal tumors and prolonged survival in three distinct murine CRC models, including a cecal orthotopic model. The efficacy of triple combination therapy was STING dependent as knockout animals lost most benefit of adding anti-SIRPα and anti–PD-1 to RT. Despite activation across the myeloid stroma, the enhanced dendritic cell function accounts for most improvements in CD8 T cell priming. These data suggest ATR-mediated CD47 and PD-L1 up-regulation as a key mechanism restraining radiation-induced immune priming. RT combined with SIRPα and PD-1 blockade promotes robust antitumor immune priming, leading to systemic tumor regressions.

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70–180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70–180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: −1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (−1.5% [−2.4% to −0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (−8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

Abstract Background: Colorectal cancer has a strong epigenetic component that is accompanied by frequent DNA methylation (DNAm) alterations in addition to heritable genetic risk. It is of interest to understand the interrelationship of germline genetics, DNAm, and colorectal cancer risk. Methods: We performed a genome-wide methylation quantitative trait locus (meQTL) analysis in 1,355 people, assessing the pairwise associations between genetic variants and lymphocytes methylation data. In addition, we used penalized regression with cis-genetic variants ± 1 Mb of methylation to identify genome-wide heritable DNAm. We evaluated the association of genetically predicted methylation with colorectal cancer risk based on genome-wide association studies (GWAS) of over 125,000 cases and controls using the multivariate sMiST as well as univariately via examination of marginal association with colorectal cancer risk. Results: Of the 142 known colorectal cancer GWAS loci, 47 were identified as meQTLs. We identified four novel colorectal cancer–associated loci (NID2, ATXN10, KLHDC10, and CEP41) that reside over 1 Mb outside of known colorectal cancer loci and 10 secondary signals within 1 Mb of known loci. Conclusions: Leveraging information of DNAm regulation into genetic association of colorectal cancer risk reveals novel pathways in colorectal cancer tumorigenesis. Our summary statistics-based framework sMiST provides a powerful approach by combining information from the effect through methylation and residual direct effects of the meQTLs on disease risk. Further validation and functional follow-up of these novel pathways are needed. Impact: Using genotype, DNAm, and GWAS, we identified four new colorectal cancer risk loci. We studied the landscape of genetic regulation of DNAm via single-SNP and multi-SNP meQTL analyses.

Abstract Background The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. Methods We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2– or 3–degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. Results The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2–degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P &lt; 1.2 × 10−4). Conclusion Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.

Abstract Background: Currently known associations between common genetic variants and colorectal cancer explain less than half of its heritability of 25%. As alcohol consumption has a J-shape association with colorectal cancer risk, nondrinking and heavy drinking are both risk factors for colorectal cancer. Methods: Individual-level data was pooled from the Colon Cancer Family Registry, Colorectal Transdisciplinary Study, and Genetics and Epidemiology of Colorectal Cancer Consortium to compare nondrinkers (≤1 g/day) and heavy drinkers (&gt;28 g/day) with light-to-moderate drinkers (1–28 g/day) in GxE analyses. To improve power, we implemented joint 2df and 3df tests and a novel two-step method that modifies the weighted hypothesis testing framework. We prioritized putative causal variants by predicting allelic effects using support vector machine models. Results: For nondrinking as compared with light-to-moderate drinking, the hybrid two-step approach identified 13 significant SNPs with pairwise r2 &gt; 0.9 in the 10q24.2/COX15 region. When stratified by alcohol intake, the A allele of lead SNP rs2300985 has a dose–response increase in risk of colorectal cancer as compared with the G allele in light-to-moderate drinkers [OR for GA genotype = 1.11; 95% confidence interval (CI), 1.06–1.17; OR for AA genotype = 1.22; 95% CI, 1.14–1.31], but not in nondrinkers or heavy drinkers. Among the correlated candidate SNPs in the 10q24.2/COX15 region, rs1318920 was predicted to disrupt an HNF4 transcription factor binding motif. Conclusions: Our study suggests that the association with colorectal cancer in 10q24.2/COX15 observed in genome-wide association study is strongest in nondrinkers. We also identified rs1318920 as the putative causal regulatory variant for the region. Impact: The study identifies multifaceted evidence of a possible functional effect for rs1318920.