Publications by authors named "K Scott Baker"

2,279 Publications

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Targeting TREM2 on tumor-associated macrophages enhances immunotherapy.

Cell Rep 2021 Oct;37(3):109844

Pionyr Immunotherapeutics, South San Francisco, CA 94080, USA. Electronic address:

Converting checkpoint inhibitor (CPI)-resistant individuals to being responsive requires identifying suppressive mechanisms. We identify TREM2 tumor-associated macrophages (TAMs) as being correlated with exhausted CD8 tumor-infiltrating lymphocytes (TILs) in mouse syngeneic tumor models and human solid tumors of multiple histological types. Fc domain-enhanced anti-TREM2 monoclonal antibody (mAb) therapy promotes anti-tumor immunity by elimination and modulation of TAM populations, which leads to enhanced CD8 TIL infiltration and effector function. TREM2 TAMs are most enriched in individuals with ovarian cancer, where TREM2 expression corresponds to disease grade accompanied by worse recurrence-free survival. In an aggressive orthotopic ovarian cancer model, anti-TREM2 mAb therapy drives potent anti-tumor immunity. These results highlight TREM2 as a highly attractive target for immunotherapy modulation in individuals who are refractory to CPI therapy and likely have a TAM-rich tumor microenvironment.
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http://dx.doi.org/10.1016/j.celrep.2021.109844DOI Listing
October 2021

A Pilot Randomized Controlled Trial of a Fitbit- and Facebook-Based Physical Activity Intervention for Young Adult Cancer Survivors.

J Adolesc Young Adult Oncol 2021 Oct 22. Epub 2021 Oct 22.

Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, Washington, USA.

Most young adult cancer survivors (YACS) do not meet physical activity (PA) guidelines. Although PA can improve health and quality of life (QOL), few randomized controlled trials (RCTs) of PA interventions for YACS exist. We conducted a pilot RCT to test feasibility of a PA intervention among YACS. We recruited 18-39-year-olds (≥1 and <5 years postcancer therapy) from Seattle Cancer Care Alliance. The 12-week intervention involved a wrist-worn PA-tracking device (Fitbit), a peer-based Facebook support group, step count goal setting, and a self-selected support "buddy." Controls received Fitbit only. Baseline assessments occurred before randomization; follow-up assessments occurred during intervention weeks 10-12. Feasibility criteria are listed below. Exploratory outcomes included PA, sedentary time (ST), QOL measures (e.g., fatigue), and self-determination theory (SDT) construct measures. All feasibility criteria were met: We recruited 50 YACS, intervention participants wore the Fitbit on the majority of intervention days (82.9%), ≥75% of participants completed questionnaires at baseline (100%) and follow-up (93.9%). Exploratory analyses, adjusted for wave, accelerometer wear time, race, and income, showed significant group differences for change in ST (-52.4 vs. 2.5 minutes/day;  = 0.002) but no change in moderate-to-vigorous intensity PA (0.0 vs. -0.2 minutes/day;  = 0.40), comparing intervention participants to controls. The intervention (vs. control) group had a greater increase in fatigue interference ( = 0.03). No other significant differences in SDT or QOL measures were found. This Fitbit and Facebook-based PA intervention was feasible to YACS, with promising effects on reducing ST, and warrants a fully powered RCT. Clinical Trial Registration no.: NCT03233581.
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http://dx.doi.org/10.1089/jayao.2021.0056DOI Listing
October 2021

Placement of a Double-Lumen Endotracheal Tube.

N Engl J Med 2021 10;385(16):e52

From Massachusetts General Hospital and Harvard Medical School, Boston.

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http://dx.doi.org/10.1056/NEJMvcm2026684DOI Listing
October 2021

Late health outcomes after dexrazoxane treatment: A report from the Children's Oncology Group.

Cancer 2021 Oct 13. Epub 2021 Oct 13.

Oishei Children's Hospital, Roswell Park Comprehensive Center, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Buffalo, New York.

Background: The objective of this study was to examine long-term outcomes among children newly diagnosed with cancer who were treated in dexrazoxane-containing clinical trials.

Methods: P9404 (acute lymphoblastic leukemia/lymphoma [ALL]), P9425 and P9426 (Hodgkin lymphoma), P9754 (osteosarcoma), and Dana-Farber Cancer Institute 95-01 (ALL) enrolled 1308 patients between 1996 and 2001: 1066 were randomized (1:1) to doxorubicin with or without dexrazoxane, and 242 (from P9754) were nonrandomly assigned to receive dexrazoxane. Trial data were linked with the National Death Index, the Organ Procurement and Transplantation Network, the Pediatric Health Information System (PHIS), and Medicaid. Osteosarcoma survivors from the Childhood Cancer Survivor Study (CCSS; n = 495; no dexrazoxane) served as comparators in subanalyses. Follow-up events were assessed with cumulative incidence, Cox regression, and Fine-Gray methods.

Results: In randomized trials (cumulative prescribed doxorubicin dose, 100-360 mg/m ; median follow-up, 18.6 years), dexrazoxane was not associated with relapse (hazard ratio [HR], 0.84; 95% confidence interval [CI], 0.63-1.13), second cancers (HR, 1.19; 95% CI, 0.62-2.30), all-cause mortality (HR, 1.07; 95% CI, 0.78-1.47), or cardiovascular mortality (HR, 1.45; 95% CI, 0.41-5.16). Among P9754 patients (all exposed to dexrazoxane; cumulative doxorubicin, 450-600 mg/m ; median follow-up, 16.6-18.4 years), no cardiovascular deaths or heart transplantation occurred. The 20-year heart transplantation rate among CCSS osteosarcoma survivors (mean doxorubicin, 377 ± 145 mg/m ) was 1.6% (vs 0% in P9754; P = .13). Among randomized patients, serious cardiovascular outcomes (cardiomyopathy, ischemic heart disease, and stroke) ascertained by PHIS/Medicaid occurred less commonly with dexrazoxane (5.6%) than without it (17.6%; P = .02), although cardiomyopathy rates alone did not differ (4.4% vs 8.1%; P = .35).

Conclusions: Dexrazoxane did not appear to adversely affect long-term mortality, event-free survival, or second cancer risk.
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http://dx.doi.org/10.1002/cncr.33974DOI Listing
October 2021

Estimated pulse wave velocity improves risk stratification for all-cause mortality in patients with COVID-19.

Sci Rep 2021 10 12;11(1):20239. Epub 2021 Oct 12.

Biosciences Institute, International Centre for Life, Vascular Biology and Medicine Theme, Faculty of Medical Sciences, Newcastle University, Central Parkway, Newcastle upon Tyne, NE1 3BZ, UK.

Accurate risk stratification in COVID-19 patients consists a major clinical need to guide therapeutic strategies. We sought to evaluate the prognostic role of estimated pulse wave velocity (ePWV), a marker of arterial stiffness which reflects overall arterial integrity and aging, in risk stratification of hospitalized patients with COVID-19. This retrospective, longitudinal cohort study, analyzed a total population of 1671 subjects consisting of 737 hospitalized COVID-19 patients consecutively recruited from two tertiary centers (Newcastle cohort: n = 471 and Pisa cohort: n = 266) and a non-COVID control cohort (n = 934). Arterial stiffness was calculated using validated formulae for ePWV. ePWV progressively increased across the control group, COVID-19 survivors and deceased patients (adjusted mean increase per group 1.89 m/s, P < 0.001). Using a machine learning approach, ePWV provided incremental prognostic value and improved reclassification for mortality over the core model including age, sex and comorbidities [AUC (core model + ePWV vs. core model) = 0.864 vs. 0.755]. ePWV provided similar prognostic value when pulse pressure or hs-Troponin were added to the core model or over its components including age and mean blood pressure (p < 0.05 for all). The optimal prognostic ePWV value was 13.0 m/s. ePWV conferred additive discrimination (AUC: 0.817 versus 0.779, P < 0.001) and reclassification value (NRI = 0.381, P < 0.001) over the 4C Mortality score, a validated score for predicting mortality in COVID-19 and the Charlson comorbidity index. We suggest that calculation of ePWV, a readily applicable estimation of arterial stiffness, may serve as an additional clinical tool to refine risk stratification of hospitalized patients with COVID-19 beyond established risk factors and scores.
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http://dx.doi.org/10.1038/s41598-021-99050-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511157PMC
October 2021
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