What is already known about this topic? Medication nonadherence is a known risk factor for diabetes and cardiovascular disease complications. Cost of medication is the most common reason for nonadherence; however, few studies have focused on nonadherence secondary to financial need. What is added by this report? We investigated how nonadherence that results from financial barriers contributes to mortality among patients with diabetes, cardiovascular disease, and hypertension. We found that people who experienced costrelated nonadherence between 2000 and 2014 experienced 15% to 22% higher all-cause mortality and 8% to 18% higher disease-specific mortality than people who did not experience cost-related nonadherence. What are the implications for public health practice? Efforts to increase medication affordability and accessibility may reduce mortality among people living with diabetes, cardiovascular disease, and hypertension.

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are enriched in the HER2 subtype of breast cancer and are associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induced antitumor adaptive immune responses and CD4+ T cell–mediated, antigen-specific tumor growth inhibition. Although polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected, suggesting that APOBEC-mediated genetic heterogeneity limits antitumor adaptive immune responses. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to anti–CTLA-4 checkpoint inhibition and led to a complete response to combination anti–CTLA-4 and anti-HER2 therapy. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures and clonality as biomarkers predicting immunotherapy response in HER2-positive (HER2+) breast cancers.

Blood group antigens are inherited traits that may play a role in immune and inflammatory processes. We investigated associations between blood groups and circulating inflammation-related molecules in 3537 non-Hispanic white participants selected from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Whole-genome scans were used to infer blood types for 12 common antigen systems based on well-characterized single-nucleotide polymorphisms. Serum levels of 96 biomarkers were measured on multiplex fluorescent bead-based panels. We estimated marker associations with blood type using weighted linear or logistic regression models adjusted for age, sex, smoking status, and principal components of population substructure. Bonferroni correction was used to control for multiple comparisons, with two-sided p values < 0.05 considered statistically significant. Among the 1152 associations tested, 10 were statistically significant. Duffy blood type was associated with levels of CXCL6/GCP2, CXCL5/ENA78, CCL11/EOTAXIN, CXCL1/GRO, CCL2/MCP1, CCL13/MCP4, and CCL17/TARC, whereas ABO blood type was associated with levels of sVEGFR2, sVEGFR3, and sGP130. Post hoc pairwise t -tests showed that individuals with type Fy(a+b−) had the lowest mean levels of all Duffy-associated markers, while individuals with type A blood had the lowest mean levels of all ABO-associated markers. Additional work is warranted to explore potential clinical implications of these differences.

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.