Breast cancer is currently classified by immunohistochemistry. However, technological advances in the detection of circulating tumor DNA (ctDNA) have made new options available for diagnosis, classification, biological knowledge, and treatment selection. Breast cancer is a heterogeneous disease and ctDNA can accurately reflect this heterogeneity, allowing us to detect, monitor, and understand the evolution of the disease. Breast cancer patients have higher levels of circulating DNA than healthy subjects, and ctDNA can be used for different objectives at different timepoints of the disease, ranging from screening and early detection to monitoring for resistance mutations in advanced disease. In early breast cancer, ctDNA clearance has been associated with higher rates of complete pathological response after neoadjuvant treatment and with fewer recurrences after radical treatments. In metastatic disease, ctDNA can help select the optimal sequencing of treatments. In the future, thanks to new bioinformatics tools, the use of ctDNA in breast cancer will become more frequent, enhancing our knowledge of the biology of tumors. Moreover, deep learning algorithms may also be able to predict breast cancer evolution or treatment sensitivity. In the coming years, continued research and the improvement of liquid biopsy techniques will be key to the implementation of ctDNA analysis in routine clinical practice.

Cancer stem-like cells (CSC) play key roles in long-term tumor propagation and metastasis, but their dynamics during disease progression are not understood. Tumor relapse in patients with initially excised skin squamous cell carcinomas (SCC) is characterized by increased metastatic potential, and SCC progression is associated with an expansion of CSC. Here, we used genetically and chemically-induced mouse models of skin SCC to investigate the signaling pathways contributing to CSC function during disease progression. We found that CSC regulatory mechanisms change in advanced SCC, correlating with aggressive tumor growth and enhanced metastasis. β-catenin and EGFR signaling, induced in early SCC CSC, were downregulated in advanced SCC. Instead, autocrine FGFR1 and PDGFRα signaling, which have not been previously associated with skin SCC CSC, were upregulated in late CSC and promoted tumor growth and metastasis, respectively. Finally, high-grade and recurrent human skin SCC recapitulated the signaling changes observed in advanced mouse SCC. Collectively, our findings suggest a stage-specific switch in CSC regulation during disease progression that could be therapeutically exploited by targeting the PDGFR and FGFR1 pathways to block relapse and metastasis of advanced human skin SCC.

Advanced and undifferentiated skin squamous cell carcinomas (SCCs) exhibit aggressive growth and enhanced metastasis capability, which is associated in mice with an expansion of the cancer stem-like cell (CSC) population and with changes in the regulatory mechanisms that control the proliferation and invasion of these cells. Indeed, autocrine activation of PDGFRα induces CSC invasion and promotes distant metastasis in advanced SCCs. However, the mechanisms involved in this process were unclear. Here, we show that CSCs of mouse advanced SCCs (L-CSCs) express CXCR4 and CXCR7, both receptors of SDF-1. PDGFRα signaling induces SDF-1 expression and secretion, and the autocrine activation of this pathway in L-CSCs. Autocrine SDF-1/CXCR4 signaling induces L-CSC proliferation and survival, and mediates PDGFRα-induced invasion, promoting in vivo lung metastasis. Validation of these findings in patient samples of skin SCCs shows a strong correlation between the expression of SDF1, PDGFRA, and PDGFRB, which is upregulated, along CXCR4 in tumor cells of advanced SCCs. Furthermore, PDGFR regulates SDF-1 expression and inhibition of SDF-1/CXCR4 and PDGFR pathways blocks distant metastasis of human PD/S-SCCs. Our results indicate that functional crosstalk between PDGFR/SDF-1 signaling regulates tumor cell invasion and metastasis in human and mouse advanced SCCs, and suggest that CXCR4 and/or PDGFR inhibitors could be used to block metastasis of these aggressive tumors.

Triple-negative breast cancer (TNBC) is a highly aggressive subtype with limited therapeutic options, leading to higher relapse rates and mortality. Identifying prognostic biomarkers like caveolin-1 (CAV1) is crucial for personalized treatment. CAV1 influences tumor progression and chemotherapy response, particularly through its interaction with the tumor microenvironment (TME) and cancer metabolism. Understanding the prognostic value of CAV1 in different cellular compartments is essential for its clinical application in TNBC. In the methods section CAV1 gene expression in TNBC was evaluated using in silico analysis, followed by the immunohistochemical staining of tumor cytoplasm (cCAV1) and stromal cells (sCAV1) in 58 early-stage TNBC patients. Statistical analyses were performed to correlate CAV1 expression with clinicopathological features and survival. In the results section, in silico analysis revealed higher CAV1 expression in TNBC, correlating with shorter overall survival. In the patient samples, cCAV1 was observed in 10.3% of cases, and was associated with larger tumors, higher grades, and poorer prognoses. sCAV1 was detected in 42% of cases, associated with less proliferative and less aggressive tumors, but did not significantly impact prognoses. In conclusion, cCAV1 expression is a significant prognostic marker in early-stage TNBC, highlighting the importance of assessing CAV1 in different cellular compartments. Further research is needed to explore the mechanisms and clinical implications of cCAV1.

Acquired resistance to poly(ADP-ribose) polymerase inhibitors (PARPi) remains a major barrier to durable clinical benefit in patients with high-grade serous ovarian cancer (HGSOC), yet the profiles of tumors at resistance remain poorly understood. We profiled longitudinal HGSOC patient tumors spanning diagnosis, post-neoadjuvant therapy, and progression on PARPi with complementary spatial transcriptomics platforms, integrating single-cell–resolution Xenium analysis in paired longitudinal cases with cohort-level Visium profiling. PARPi failure was associated with spatial remodeling of the tumor microenvironment, marked by hypoxia-associated malignant transcriptional programs, increased stromal compartmentalization, and exclusion of effector immune cells. Together, these findings indicate that PARPi resistance in HGSOC is accompanied by reproducible spatial niche remodeling, underscoring the tumor microenvironment as a key contextual determinant of therapeutic failure.