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Roussos Torres, E.

Publications and source records attributed to Roussos Torres, E..

3 recordsLinked to original sources

Intratumoral CXCL12 Gradients Contextualize Tumor Cell Invasion, Migration and Immune Suppression in Breast Cancer

Although the CXCL12/CXCR4 pathway has been prior investigated for its prometastatic and immuno- suppressive roles in the tumor microenvironment, evidence on the spatiotemporal regulation of these hallmarks has been lacking. Here, we demonstrate that CXCL12 forms a gradient specifically around cancer cell intravasation doorways, also known as Tumor Microenvironment of Metastasis (TMEM) doorways, thus facilitating the chemotactic translocation of prometastatic tumor cells expressing CXCR4 toward the perivascular TMEM doorways for subsequent entry into peripheral circulation. Fur- thermore, we demonstrate that the CXCL12-rich micro-environment around TMEM doorways may cre- ate immunosuppressive niches, whereby CD8+ T cells, despite being attracted to these regions, often exhibit reduced effector functions, limiting their efficacy. While the CXCL12/CXCR4 pathway can mini- mally influence the overall composition of immune cell populations, it biases the distribution of CD8+ T cells away from TMEM doorways, justifying its prior-established role as immunosuppressive factor for CD8+ T cells. Our research suggests that the complex interactions between CXCL12 and the various tumor and immune cell types contributes not only to the completion of the initial steps of the metastatic cascade, but also offers an immunological "sanctuary" to prometastatic tumor cells homed around TMEM doorways. Overall, our study enhances our current understanding on the mechanisms, via which CXCL12 orchestrates tumor cell behavior and immune dynamics, potentially guiding future thera- peutic strategies to combat breast cancer metastasis and improve anti-tumor immunity.

cancer biology↗

Targeting circadian transcriptional programs in triple negative breast cancer through a cis-regulatory mechanism

Circadian clock genes are emerging targets in many types of cancer, but their mechanistic contributions to tumor progression are still largely unknown. This makes it challenging to stratify patient populations and develop corresponding treatments. In this work, we show that in breast cancer, the disrupted expression of circadian genes has the potential to serve as biomarkers. We also show that the master circadian transcription factors (TFs) BMAL1 and CLOCK are required for the proliferation of metastatic mesenchymal stem-like (mMSL) triple-negative breast cancer (TNBC) cells. Using currently available small molecule modulators, we found that a stabilizer of cryptochrome 2 (CRY2), the direct repressor of BMAL1 and CLOCK transcriptional activity, synergizes with inhibitors of proteasome, which is required for BMAL1 and CLOCK function, to repress a transcriptional program comprising circadian cycling genes in mMSL TNBC cells. Omics analyses on drug-treated cells implied that this repression of transcription is mediated by the transcription factor binding sites (TFBSs) features in the cis-regulatory elements (CRE) of clock-controlled genes. Through a massive parallel reporter assay, we defined a set of CRE features that are potentially repressed by the specific drug combination. The identification of cis-element enrichment might serve as a new concept of defining and targeting tumor types through the modulation of cis-regulatory programs, and ultimately provide a new paradigm of therapy design for cancer types with unclear drivers like TNBC.

cancer biology↗

Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies reveal the prevalence of intra-and inter-tumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intra-and inter-tumor molecular heterogeneity. We devised a new algorithm, Expression Variation Analysis in Single Cells (EVAsc), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVAsc has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. We then apply EVAsc to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics, i.e. immunogenicity, cancer subtypes, and metastasis. Immune pathway heterogeneity in hematopoietic cell populations in breast tumors corresponded to the amount diversity present in the T-cell repertoire of each individual. In head and neck squamous cell carcinoma (HNSCC) patients, we found dramatic differences in pathway dysregulation across basal primary tumors. Within the basal primary tumors we also identified increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. Moreover, cells in HNSCC primary tumors had significantly more heterogeneity across pathways than cells in metastases, consistent with a model of clonal outgrowth. These results demonstrate the broad utility of EVAsc to quantify inter-and intra-tumor heterogeneity from scRNA-seq data without reliance on low dimensional visualization.

bioinformatics↗