Biology subjects

Ginestier, C.

Publications and source records attributed to Ginestier, C..

6 recordsLinked to original sources

bioRxiv2025

LeGO-Teknik reveals that the neurogenesis pathway is a clone-specific hallmark of brain metastasis in breast cancer

Breast cancer exhibits substantial inter- and intra-patient heterogeneity. Yet the molecular features underlying this diversity and their roles in tumour progression are not yet fully elucidated. Within a primary tumour, certain clones possess a unique capacity to metastasize to distant organs, such as the brain, and this propensity may be associated with specific gene expression profiles. To investigate this phenomenon, we developed a new optical barcoding library, LeGO-Teknik, compatible with high resolution imaging, flow cytometry, single-cell RNA sequencing and machine learning computational methods. Using this new tool, we systematically assessed the fitness and organ tropism of multiple human breast cancer clones in spontaneous metastasis assays. Linking transcriptomic profiles of individual cancer cells to their clonal identities and metastatic behaviours, we identified that clones predisposed to forming brain metastases exhibit distinct molecular signatures. Notably, individual cells from these clones showed enriched expression of neurogenesis-related genes. Using SCENIC transcription factor analysis, we found that some of these features are driven by the transcription factor SOX4. This hallmark, likely due to a process of cellular reprogramming, is a remarkable example of organ mimicry during clonal selection. Together, this work provides critical insights into brain metastasis and highlights the potential for identifying predictive biomarkers and therapeutic targets for metastatic breast cancer.

cancer biology↗

bioRxiv2025

Genetic barcoding uncovers the clonal makeup of solid and liquid biopsies

Intra-tumoral heterogeneity (ITH) is fueling tumor progression in breast cancer, as specific clones present within a tumor may have a selective advantage to colonize distant organs and escape therapy. Accurate sampling of ITH is therefore a pressing challenge in clinical oncology, to adequately predict recurrence and inform rational and personalized therapies. Here we used cellular barcoding to track the spatio-temporal composition of human breast cancer clones in six preclinical models - across two cell lines and four patient derived xenografts (PDXs). This allowed direct side-by-side quantitative comparison not only of intra-tumor clonal composition, but also of how that composition was reflected in needle biopsies and cell-free DNA (cfDNA). These analyses highlighted several clinically relevant findings. First, the use of orthogonal genetic and optical barcoding revealed that clonal diversity in the center of non-necrotic primary tumors was significantly higher compared to their periphery. Second, cfDNA barcode analysis suggested that DNA shedding in the vasculature varied largely, not only depending on necrosis and tumor burden, but also between models. Third, combining information captured in both solid and liquid biopsies can provide a more robust assessment of tumor clonal composition. Taken together, these results showcases the utility of these barcoded models to optimize the use of solid and liquid biopsies as surrogate markers of ITH.

cancer biology↗

bioRxiv2021

Cancer/Testis genes are predictive of breast tumor subtypes

Breast cancer is the most prevalent type of cancer in women worldwide. Within breast tumors, the basal-like subtype has the worst prognosis and no dedicated therapy, therefore new tools to understand, detect, and treat these tumors are needed. Certain germline genes are re-expressed in tumors, and constitute the Cancer/Testis genes; their misexpression has diagnostic and therapeutic applications. Here, we designed a new approach to examine Cancer/ Testis gene misexpression in breast tumors. We identify several new markers in Luminal and HER-2 positive tumors, some of which predict response to chemotherapy. We then use machine learning to identify the 2 Cancer/Testis genes most associated with basal-like breast tumors: HORMAD1 and CT83. We show that these genes are expressed by tumor cells but not the microenvironment, and that they are not expressed by normal breast progenitors, in other words their activation occurs de novo. We find these genes are epigenetically repressed by DNA methylation, and that their activation upon DNA demethylation is irreversible, providing a memory of past epigenetic disturbances. Basal-like tumors expressing both genes have a poorer outcome than tumors expressing either gene alone or neither gene. Therefore, these findings suggest a potential synergistic effect between Cancer/Testis genes in basal breast tumors; these findings have consequences for the understanding, diagnosis, and therapy of the breast tumors with the worse outcomes.

cancer biology↗

bioRxiv2021

CD95 expression in triple negative breast cancer blocks induction of an inflammatory state through differential regulation of NF-kB Signaling

CD95L is expressed by tumor-infiltrating lymphocytes to eliminate CD95-expressing tumor cells and thereby CD95 loss by tumor cells is often considered as a consequence of an immunoediting process. Nonetheless CD95 expression is maintained in most triple negative breast cancers (TNBCs), and we recently reported that CD95 loss in TNBC cells triggers the induction of a pro-inflammatory program promoting the recruitment of cytotoxic NK and CD8+ T-cells and impairing tumor growth. Using a comprehensive proteomic approach, we have identified two yet unknown CD95 interaction partners, Kip1 ubiquitination-promoting complex protein 2 (KPC2) and p65. KPC2 contributes to the partial degradation of p105 (NF{kappa}B1) and the subsequent generation of p50 homodimers, which transcriptionally represses pro-inflammatory NF-{kappa}B-driven gene expression. Mechanistically, KPC2 directly interacts with the C-terminal region of CD95 and links the receptor to RelA (p65) and KPC1, the catalytic subunit of the KPC complex that acts as E3 ubiquitin-protein ligase promoting the partial degradation of p105 into p50. Loss of CD95 in TNBC cells releases KPC2, limiting the formation of the NF-{kappa}B inhibitory homodimer complex (p50/p50), promoting NF-{kappa}B activation and the production of pro-inflammatory cytokines including CSF1, CSF2, CXCL1 and IL1 members, known to promote recruitment and differentiation of certain adaptive and innate immune effector cells.

cancer biology↗

bioRxiv2021

Tumor expressed CD95 causes suppression of anti-tumor activity of NK cells in a model of triple negative breast cancer

The apoptosis inducing receptor CD95/Fas has multiple tumorigenic activities. Stimulation by its cognate ligand CD95L on many cancer cells increases their growth, motility, ability to invade and/or their cancer stemness. Using genetically engineered mouse models of ovarian and liver cancer, we previously reported that deletion of CD95 in the tumor cells strongly reduced their ability to grow in vivo [1, 2]. Using a combination of immune-deficient and immune-competent mouse models, we now establish that loss of CD95 in metastatic triple negative breast cancer cells prevents tumor growth by modulating the immune landscape. CD95 deficient but not wild-type tumors barely grow in an immune-competent environment and show an increase in immune infiltrates into the tumor. This growth reduction is caused by NK cells and does not involve CD8+ T cells. On the other hand, in immune compromised mice CD95 k.o. cells are not growth inhibited, but they fail to form metastases. In summary, we demonstrate that in addition to its tumor and metastasis promoting activities, CD95 expression by tumor cells can exert immune suppressive activities providing a new target for immune therapy.

cancer biology↗

bioRxiv2019

miRViz: a novel webserver application to visualize and interpret microRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in the regulation of major pathways in eukaryotic cells through repression of their target genes at the post-transcriptional level1. While high-throughput approaches are broadly used to decipher the biological relevance of miRNAs, extraction of significant information from large miRNA datasets remains challenging. For example, sequencing technologies can quantify the relative expression of up to thousands of mature miRNAs under various experimental conditions. However, in such datasets, small subsets of miRNAs can often show significant differential expression, and deciding which one(s) should be further analyzed can prove difficult. Thus, the current challenge resides in objective analysis, interpretation and visualization of these large datasets, for which specifically suited methods are lacking.

genomics↗