Biology subjects

Didier, J.

Publications and source records attributed to Didier, J..

3 recordsLinked to original sources

bioRxiv2024

Radiotherapy triggers pro-angiogenic signaling in human lung

Radiotherapy is one of the main therapeutic options for the treatment of lung cancer. Although highly efficient, radiation cause severe damages to normal tissue and radio-induced toxicities vary from mild pneumonitis to pulmonary fibrosis. The mechanism leading to these toxicities remain unclear. To investigate the molecular responses of human lung to radiotherapy, we analyzed, by single cell RNAseq, lung tissue resected in the vicinity of the tumor (i.e. treated with radiation) and compared the transcriptional profiles of the distinct lung populations from the same patient removed at distance from the tumor (i.e. non-treated with radiation). Analysis of six lung samples from patients suffering from Pancoast tumor, a rare lung malignancy that requires neo-adjuvant radiotherapy before surgery, revealed a strong induction of VEGF signaling after radiotherapy. Expression of VEGFA, one of the canonical pro-angiogenic ligands, was found upregulated in multiple cell populations in lung exposed to high doses of radiation. Irradiated capillaries, particularly gCap cells, expressing KDR/VEGFR2, present transcriptional profile similar to tip cells, characterized by sprouting and motility capacities. In addition, we identified a sub-population of alveolar macrophages expressing FLT1/VEGFR1, a receptor for VEGFA, in lung tissues treated by radiotherapy. Cell-Cell communication analysis revealed that FLT1/VEGFR1 positive macrophages interact with tip cells after radiotherapy through IL1B-IL1R signaling. Lastly, analysis of mouse single cell dataset confirmed the increase in the proportion of gCap cells presenting a tip-like phenotype after radiation injury. Altogether, this study describes, at the single cell level, the pro-angiogenic responses of human lung after radiotherapy. These results will lead to a better understanding of the physiopathology of lung radiation injury and may pave the way to optimize treatments to improve patients quality of life.

cancer biology↗

bioRxiv2024

Circadian clock features define novel breast cancer subtypes and shape drug sensitivity

The circadian clock regulates key physiological processes, including cellular responses to DNA damage. Circadian-based therapeutic strategies optimize treatment timing to enhance drug efficacy and minimize side effects, offering potential for precision cancer treatment. However, applying these strategies in cancer remains limited due to limited understanding of the clocks function across cancer types and incomplete insights into how the circadian clock affects drug responses. To address this, we conducted deep circadian phenotyping across a panel of breast cancer cell lines using two complementary reporters. Observing diverse circadian dynamics, we developed metrics to assess circadian rhythm strength and stability. This led to the identification of four distinct circadian-based phenotypes in breast cancer: functional, weak, unstable, and dysfunctional clocks. Furthermore, we demonstrate that the circadian clock plays a critical role in shaping pharmacological responses to various anti-cancer drugs and identify circadian features that accurately predict drug sensitivity. Collectively, our findings establish a foundation for advancing the use of chronotherapeutic strategies in breast cancer treatment, expanding their potential application to improve therapeutic outcomes in breast cancer.

cancer biology↗

bioRxiv2023

Time-of-day effects of drugs revealed by high-throughput deep phenotyping

The circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a novel high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devised a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.

cancer biology↗