Mariana Boroni

Osteopontin-c gene expression and subcellular localization in ovarian cancer cells: Implications for prognosis and therapeutic responses

Background Osteopontin is a glycophosphoprotein aberrantly expressed in several tumor types, which exhibits several isoforms generated by post-translational and post-transcriptional mechanisms, including alternative splicing. Among total osteopontin (tOPN), the osteopontin-c (OPN-c) splice variant has been the most explored with an oncogenic role described for a range of tumor types. Especially in ovarian cancer (OC) cells, OPN-c is found overexpressed, presenting both diagnostic and prognostic implications. Objective In this review article, we aim to outline OPN-c roles in cancer, particularly in OC, in which it has been reported as a diagnostic biomarker. Methods We used PubMed search, and experimental procedures were summarized at the Figure legends. Results We identified cytoplasmic, perinuclear, and nuclear OPN-c in OC cells that overexpress this OPN splice variant. Moreover, we report that OPN-c splicing isoform is found highly expressed in endometrioid OC patients’ samples, compared to non-neoplastic ovarian tissues. Also, OPN-c expression levels have been associated with worse overall survival and worse progression-free survival in patients with both endometrioid and serous OC. Furthermore, OPN-c may be involved in a wide range of tumor features evoked by signaling pathways, such as AKT, ERK, and FAK. Conclusions Therefore, a better comprehension of OPN-c roles in OC can further contribute to its application as a biomarker as well as a target for putative treatment strategies, especially those aiming to sensitize tumor cells to chemotherapeutic agents currently used in the OC treatment.

Single-cell resolution characterization of myeloid-derived cell states with implication in cancer outcome

AbstractTumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.