Cell Type-Specific Biomarkers of Systemic Sclerosis Disease Severity Capture Cell-Intrinsic and Cell-Extrinsic Circuits.

OBJECTIVE: Systemic sclerosis (SSc) is a multifactorial autoimmune fibrotic disorder involving complex rewiring of cell-intrinsic and cell-extrinsic signaling coexpression networks involving a range of cell types. However, the rewired circuits as well as corresponding cell-cell interactions remain poorly understood. To address this, we used a predictive machine learning framework to analyze single-cell RNA-sequencing data from 24 SSc patients across the severity spectrum as quantified by the modified Rodnan skin score (MRSS). METHODS: We used a least absolute shrinkage and selection operator (LASSO)-based predictive machine learning approach on the single-cell RNA-sequencing data set to identify predictive biomarkers of SSc severity, both across and within cell types. The use of L1 regularization helps prevent overfitting on high-dimensional data. Correlation network analyses were coupled to the LASSO model to identify cell-intrinsic and cell-extrinsic co-correlates of the identified biomarkers of SSc severity. RESULTS: We found that the uncovered cell type-specific predictive biomarkers of MRSS included previously implicated genes in fibroblast and myeloid cell subsets (e.g., SFPR2+ fibroblasts and monocytes), as well as novel gene biomarkers of MRSS, especially in keratinocytes. Correlation network analyses revealed novel cross-talk between immune pathways and implicated keratinocytes in addition to fibroblast and myeloid cells as key cell types involved in SSc pathogenesis. We then validated the uncovered association of key gene expression and protein markers in keratinocytes, KRT6A and S100A8, with SSc skin disease severity. CONCLUSION: Our global systems analyses reveal previously uncharacterized cell-intrinsic and cell-extrinsic signaling coexpression networks underlying SSc severity that involve keratinocytes, myeloid cells, and fibroblasts.

How patients experience endocrine therapy for breast cancer: an online survey of side effects, adherence, and medical team support.

PURPOSE: Many patients with hormone receptor-positive (HR+) breast cancer do not adhere to endocrine therapy (ET), and treatment-related side effects are often discussed by participants in online breast cancer forums. Our aim was to survey this unique group of patients about their ET-related experiences. METHODS: We partnered with patients active in breast cancer social media communities to develop a survey assessing ET-related side effects and medical team communication. Patients with a history of HR+ breast cancer who had received a recommendation to take ET were eligible to participate in the anonymous, online survey. RESULTS: Respondents included 2353 women and 54 men. Aromatase inhibitors were the most commonly used medication. Side effects were reported by 91.2%, were more often experienced by women than men (p < 0.001), and were primarily related to medication type. Approximately one-third of respondents discontinued therapy early. While most felt supported by their medical team, 31.5% reported that their side effects were dismissed or minimized. Survey respondents most frequently reported that a healthy diet and exercise, yoga/acupuncture, and vitamins/supplements were helpful in managing ET-related side effects. CONCLUSIONS: ET-related side effects are very common, and one-third discontinued treatment early. Lifestyle changes and complementary therapies can be important tools for side effect management. One-third of patients did not feel that their side effects were taken seriously. IMPLICATIONS FOR CANCER SURVIVORS: This is the largest survey of ET use by participants in online breast cancer communities. Further research is needed to identify strategies to improve treatment adherence and to better manage ET-related side effects.