Recent advancements in wearable activity monitor technology have provided oncologists with new opportunities to monitor their patients' daily activity in real-world settings. The integration of wearable activity monitors into cancer care will help increase our understanding of the associations between physical activity and the prevention and management of the disease, in addition to other important cancer outcomes.

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An objective evaluation of patient performance status (PS) is difficult because patients spend the majority of their time outside of the clinic, self-report to providers, and undergo dynamic changes throughout their treatment experience. Real-time, objective activity data may allow for a more accurate assessment of PS and physical function, while reducing the subjectivity and bias associated with current assessments. Consenting patients with advanced cancer wore a wearble activity monitor for three consecutive visits in a prospective, single-cohort clinical trial. Provider-assessed PS (ECOG/Karnofsky) and NIH PROMIS® patient-reported outcomes (PROs) were assessed at each visit. Associations between wearable activity monitor metrics (steps, distance, stairs) and PS, clinical outcomes (adverse events, hospitalizations, survival), and PROs were assessed using correlation statistics and in multivariable logistic regression models. Thirty-seven patients were evaluated (54% male, median 62 years). Patients averaged 3700 steps, 1.7 miles, and 3 flights of stairs per day. Highest correlations were observed between average daily steps and ECOG-PS and KPS ( r = 0.63 and r = 0.69, respectively p < 0.01). Each 1000 steps/day increase was associated with reduced odds for adverse events (OR: 0.34, 95% CI 0.13, 0.94), hospitalizations (OR: 0.21 95% CI 0.56, 0.79), and hazard for death (HR: 0.48 95% CI 0.28–0.83). Significant correlations were also observed between activity metrics and PROs. Our trial demonstrates the feasibility of using wearable activity monitors to assess PS in advanced cancer patients and suggests their potential use to predict clinical and patient-reported outcomes. These findings should be validated in larger, randomized trials.

The human fallopian tube harbors the cell of origin for the majority of high-grade serous ''ovarian'' cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We perform single-cell transcriptomic profiling of around 53,000 individual cells from 12 primary fallopian specimens to map their major cell types. We identify 10 epithelial subpopulations with diverse transcriptional programs. Based on transcriptional signatures, we reconstruct a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3 high intermediate. Computational deconvolution of advanced HGSCs identifies the ''early secretory'' population as a likely precursor state for the majority of HGSCs. Its signature comprises both epithelial and mesenchymal features and is enriched in mesenchymal-type HGSCs (p = 6.7 3 10 À27 ), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.

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