Biology subjects

Redon, C.

Publications and source records attributed to Redon, C..

4 recordsLinked to original sources

bioRxiv2025

SCLC-TumorMiner: A Directly Accessible Genomics Resource for Precision Oncology: Big Data for Small Cells

Small cell lung cancer (SCLC) is among the most aggressive malignancies. Unlike many other cancers, it is not represented in The Cancer Genome Atlas, and available datasets are fragmented across institutions, disease stages, and treatment settings. RNA sequencing provides a powerful and cost-effective approach, but the high dimensionality of transcriptomic data and the heterogeneity of patient cohorts pose significant challenges. To address such challenges, we developed SCLC TumorMiner (https://discover.nci.nih.gov/SclcTumorMinerCDB/), which includes 50 tumor samples from relapse patients at the National Cancer Institute (NCI) and 154 samples from untreated patients at the University of Cologne and Tongji University. SCLC TumorMiner enables molecular classification, genomic pathway analyses, risk stratification, identification of predictive cell-surface biomarkers such as DLL3 or TROP2, and drug-response biomarkers such as SLFN11. SCLC TumorMiner illustrates profound differences between untreated and relapse patient samples. Additionally, "MyPatient", one of SCLC TumorMiners modules, is presented as a medical assistant application prototype.

cancer biology↗

bioRxiv2025

Lamin A/C Deficiency Drives Genomic Instability and Poor Survival in Small-Cell Lung Cancer through Increased R-loop Accumulation

Lamin A/C (LMNA), a key component of the nuclear envelope, is essential for maintaining nuclear integrity and genome organization [1]. While LMNA dysregulation has been implicated in genomic instability across cancer and aging, the underlying mechanisms remain poorly understood [2]. Here, we investigate LMNAs role in small-cell lung cancer (SCLC), a highly aggressive malignancy characterized by extreme genomic instability [3, 4]. We demonstrate that LMNA depletion promotes R-loop accumulation, transcription-replication conflicts, replication stress, DNA breaks, and micronuclei formation. Mechanistically, LMNA loss disrupts nuclear pore complex distribution, reducing phenylalanine-glycine (FG)-nucleoporin incorporation and impairing RNA export efficiency. Furthermore, we show that LMNA expression is epigenetically repressed by EZH2 during SCLC differentiation from neuroendocrine (NE) to non-NE states. Clinically, low LMNA levels correlate with significantly worse survival in SCLC patients. These findings uncover a novel role for LMNA in safeguarding genome integrity and shaping tumor heterogeneity, with broad implications for cancer and aging. Significance StatementLamin A/C, a key structural component of the nuclear envelope, is frequently lost or mutated in cancer, laminopathies, and aging-related disorders. Lamin A/C loss is associated with genomic instability, but the underlying mechanisms remain incompletely understood. We demonstrate that LMNA loss drives genomic instability by promoting R-loop accumulation through disrupted nuclear pore dynamics and impaired RNA export. These findings reveal a previously unrecognized link between LMNA loss, nuclear envelope dysfunction, and genome instability. Targeting this pathway could help mitigate genomic instability in aging and laminopathies, while leveraging R-loop accumulation may enhance the efficacy of DNA-damaging therapies in cancer.

cancer biology↗

bioRxiv2024

Metastatic organotropism in small cell lung cancer

Metastasis is the leading cause of cancer-related deaths, yet its regulatory mechanisms are not fully understood. Small-cell lung cancer (SCLC) is the most metastatic form of lung cancer, with most patients presenting with widespread disease, making it an ideal model for studying metastasis. However, the lack of suitable preclinical models has limited such studies. We utilized rapid autopsy-derived tumors to develop xenograft models that mimic key features of SCLC, including histopathology, rapid and widespread development of metastasis to the liver, brain, adrenal, bone marrow, and kidneys within weeks, and response to chemotherapy. By integrating in vivo lineage selection with comprehensive bulk and single cell multiomic profiling of transcriptomes and chromatin accessibility, we identified critical cellular programs driving metastatic organotropism to the liver and brain, the most common sites of SCLC metastasis. Our findings reveal the key role of nuclear-cytoskeletal interactions in SCLC liver metastasis. Specifically, the loss of the nuclear envelope protein lamin A/C, encoded by the LMNA gene, increased nuclear deformability and significantly increased the incidence of liver metastasis. Human liver metastases exhibited reduced LMNA expression compared to other metastatic sites, correlating with poorer patient outcomes and increased mortality. This study introduces novel preclinical models for SCLC metastasis and highlights pathways critical for organ-specific metastasis, offering new avenues for the development of targeted therapies to prevent or treat metastatic disease.

cancer biology↗

bioRxiv2019

BAMscale: quantification of DNA sequencing peaks and generation of scaled coverage tracks

BAMscale is a one-step tool that processes DNA sequencing datasets from chromatin binding (ChIP-seq) and chromatin state changes (ATAC-seq, END-seq) experiments to DNA replication data (OK-seq, NS-seq and replication timing). The outputs include normalized peak scores in text format and scaled coverage tracks (BigWig) which are directly accessible to data visualization programs. BAMscale (available at https://github.com/ncbi/BAMscale) effectively processes large sequencing datasets (~100Gb size) in minutes, outperforming currently available tools.

bioinformatics↗