Biology subjects

Jimenez Garcia, L.

Publications and source records attributed to Jimenez Garcia, L..

3 recordsLinked to original sources

bioRxiv2026

SCANBIT facilitates identification of tumor cell populations in scRNAseq data using pseudobulked SNV calls

MotivationSingle cell RNAseq (scRNAseq) is an ideal tool to characterize the heterogeneity within the tumor microenvironment, however, accurate identification of tumor cells can be a challenge. Reference-based methods can be inaccurate, if reference datasets are even available. Current purpose-built methods can be inaccurate, particularly with highly heterogeneous tumor types. Improved methods are needed. We explored the use of genetic variants to distinguish tumor from normal cells within scRNAseq data. ResultsWe characterized the limitations inherent to calling variants from scRNAseq data, quantifying how data sparsity precludes genetic distance calculation between single cells. As a novel workaround, we pooled data from transcriptionally similar cell clusters to call high quality variants and then calculated pairwise differences between cell populations and performed hierarchical clustering. We quantified confidence in genetic divergence between tumor and normal cell populations using bootstrapping. We performed extensive validation to assess accurate identification of tumor cells using ground-truth datasets. Application of our method to human scRNAseq samples highlighted the utility of our approach and revealed how mutational burden influences successful tumor cell identification. Improved cell type assignment in scRNAseq data will facilitate analysis of tumor samples and, in turn, accelerate our understanding of the mechanisms underlying tumor progression and reveal potential biological vulnerabilities that can be exploited to develop improved treatment options. Availability and implementationOur method is publicly available as an R package: SCANBIT (Single Cell Altered Nucleotide Based Inference of Tumor) https://github.com/kidcancerlab/scanBit.

bioinformatics↗

bioRxiv2024

Metastasis-initiating osteosarcoma subpopulations establish paracrine interactions with both lung and tumor cells to create a metastatic niche

Osteosarcoma is an aggressive and deadly bone tumor, primarily afflicting children, adolescents, and young adults. Poor outcomes for osteosarcoma patients are intricately linked with the development of lung metastasis. While lung metastasis is responsible for nearly all deaths caused by osteosarcoma, identification of biologically defined, metastasis-targeting therapies remains elusive because the underlying cellular and molecular mechanisms that govern metastatic colonization of circulating tumor cells to the lung remains poorly understood. While thousands of tumor cells are released into circulation each day, very few can colonize the lung. Herein, using a combination of a novel organotypic metastasis in vitro model, single-cell RNA sequencing, human xenograft, and murine immunocompetent osteosarcoma models, we find that metastasis is initiated by a subpopulation of hypo-proliferative cells with the unique capacity to sustain production of metastasis promoting cytokines such as IL6 and CXCL8 in response to lung-epithelial derived IL1. Critically, genomic and pharmacologic disruption of IL1 signaling in osteosarcoma cells significantly reduces metastatic progression. Collectively, our study supports that tumor-stromal interactions are important for metastasis, and suggests that metastatic competency is driven, in part, by the tumor cells ability to respond to the metastatic niche. Our findings support that disruption of tumor-stromal signaling is a promising therapeutic approach to disrupt metastasis progression.

cancer biology↗

bioRxiv2024

Aberrant activation of wound healing programs within the metastatic niche facilitates lung colonization by osteosarcoma cells

PurposeLung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. The purpose of this study is to identify metastasis-specific therapeutic vulnerabilities by delineating the cellular and molecular mechanisms underlying osteosarcoma lung metastatic niche formation. Experimental designUsing single-cell transcriptomics (scRNA-seq), we characterized genome- and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence and spatial transcriptomics. Based on these findings, we evaluated the ability of nintedanib, a kinase inhibitor used to treat patients with pulmonary fibrosis, to impair metastasis progression in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models. Single-nucleus and spatial transcriptomics was used to perform molecular pharmacodynamic studies that define the effects of nintedanib on tumor and non-tumor cells within the metastatic microenvironment. ResultsOsteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially differentiated epithelial intermediates and macrophages. Our data demonstrated that nintedanib prevented metastatic progression in multiple murine and human xenograft models by inhibiting osteosarcoma-induced fibrosis. ConclusionsFibrosis represents a targetable vulnerability to block the progression of osteosarcoma lung metastasis. Our data support a model wherein interactions between osteosarcoma cells and epithelial cells create a pro-metastatic niche by inducing tumor deposition of extracellular matrix proteins such as fibronectin that is disrupted by the anti-fibrotic TKI nintedanib. Our data shed light on the non-cell autonomous effects of TKIs on metastasis and provide a roadmap for using single-cell and spatial transcriptomics to define the mechanism of action of TKI on metastases in animal models. Statement of translational relevanceTherapies that block metastasis have the potential to save the majority of lives lost due to solid tumors. Disseminated tumor cells must integrate into the foreign, inhospitable microenvironments they encounter within secondary organs to facilitate metastatic colonization and progression. Our study elucidated that disseminated osteosarcoma cells survive within the lung by co-opting and amplifying the lungs endogenous wound-healing response program. This osteosarcoma-induced wound response results in fibrosis of the surrounding microenvironment. Our data implicates fibrosis and abnormal wound healing as key drivers of osteosarcoma lung metastasis that can be targeted therapeutically to disrupt metastasis progression.

cancer biology↗