Determining individual suitability for neoadjuvant systemic therapy in breast cancer patients through deep learning.

BACKGROUND: The survival advantage of neoadjuvant systemic therapy (NST) for breast cancer patients remains controversial, especially when considering the heterogeneous characteristics of individual patients. OBJECTIVE: To discern the variability in responses to breast cancer treatment at the individual level and propose personalized treatment recommendations utilizing deep learning (DL). METHODS: Six models were developed to offer individualized treatment suggestions. Outcomes for patients whose actual treatments aligned with model recommendations were compared to those whose did not. The influence of certain baseline features of patients on NST selection was visualized and quantified by multivariate logistic regression and Poisson regression analyses. RESULTS: Our study included 94,487 female breast cancer patients. The Balanced Individual Treatment Effect for Survival data (BITES) model outperformed other models in performance, showing a statistically significant protective effect with inverse probability treatment weighting (IPTW)-adjusted baseline features [IPTW-adjusted hazard ratio: 0.51, 95% confidence interval (CI), 0.41-0.64; IPTW-adjusted risk difference: 21.46, 95% CI 18.90-24.01; IPTW-adjusted difference in restricted mean survival time: 21.51, 95% CI 19.37-23.80]. Adherence to BITES recommendations is associated with reduced breast cancer mortality and fewer adverse effects. BITES suggests that patients with TNM stage IIB, IIIB, triple-negative subtype, a higher number of positive axillary lymph nodes, and larger tumors are most likely to benefit from NST. CONCLUSIONS: Our results demonstrated the potential of BITES to aid in clinical treatment decisions and offer quantitative treatment insights. In our further research, these models should be validated in clinical settings and additional patient features as well as outcome measures should be studied in depth.

Defoliation Significantly Suppressed Plant Growth Under Low Light Conditions in Two Leguminosae Species.

Seedlings in regenerating layer are frequently attacked by herbivorous insects, while the combined effects of defoliation and shading are not fully understood. In the present study, two Leguminosae species (Robinia pseudoacacia and Amorpha fruticosa) were selected to study their responses to combined light and defoliation treatments. In a greenhouse experiment, light treatments (L+, 88% vs L-, 8% full sunlight) and defoliation treatments (CK, without defoliation vs DE, defoliation 50% of the upper crown) were applied at the same time. The seedlings' physiological and growth traits were determined at 1, 10, 30, and 70 days after the combined treatment. Our results showed that the effects of defoliation on growth and carbon allocation under high light treatments in both species were mainly concentrated in the early stage (days 1-10). R. pseudoacacia can achieve growth recovery within 10 days after defoliation, while A. fruticosa needs 30 days. Seedlings increased SLA and total chlorophyll concentration to improve light capture efficiency under low light treatments in both species, at the expense of reduced leaf thickness and leaf lignin concentration. The negative effects of defoliation treatment on plant growth and non-structural carbohydrates (NSCs) concentration in low light treatment were significantly higher than that in high light treatment after recovery for 70 days in R. pseudoacacia, suggesting sufficient production of carbohydrate would be crucial for seedling growth after defoliation. Plant growth was more sensitive to defoliation and low light stress than photosynthesis, resulting in NSCs accumulating during the early period of treatment. These results illustrated that although seedlings could adjust their resource allocation strategy and carbon dynamics in response to combined defoliation and light treatments, individuals grown in low light conditions will be more suppressed by defoliation. Our results indicate that we should pay more attention to understory seedlings' regeneration under the pressure of herbivorous insects.