Postovit, L. M. | bioRxiv Science

bioRxiv2022

Targeted Proteomics and Support Vector Classification Reveal Potential Biomarkers for the Early Detection of High-grade Serous Ovarian Cancer

PurposeThe five-year prognosis for patients with late-stage high-grade serous carcinoma (HGSC) remains dismal, underscoring the critical need for identifying early-stage biomarkers. This study explores the potential of extracellular vesicles (EVs) circulating in blood, which are believed to harbor proteomic cargo reflective of the HGSC microenvironment, as a source for biomarker discovery. Experimental DesignWe conducted a comprehensive proteomic profiling of EVs isolated from blood plasma, ascites, and cell lines of patients, employing both data-dependent (DDA) and data-independent acquisition (DIA) methods to construct a spectral library tailored for targeted proteomics. Our investigation aimed at uncovering novel biomarkers for the early detection of HGSC by comparing the proteomic signatures of EVs from women with HGSC to those with benign gynecological conditions. The initial cohort, comprising 9-10 donors, utilized DDA proteomics for spectral library development. The subsequent cohort, involving 30 HGSC patients and 30 control subjects, employed DIA proteomics for a similar purpose. Support vector machine (SVM) classification was applied in both cohorts to identify combinatorial biomarkers with high specificity and sensitivity (ROC-AUC > 0.90). ResultsNotably, MUC1 emerged as a significant biomarker in both cohorts when used in combination with additional biomarkers. Validation through an ELISA assay on a subset of benign (n=18), Stage I (n=9), and stage II (n=9) plasma samples corroborated the diagnostic utility of MUC1 in the early-stage detection of HGSC. ConclusionsThis study highlights the value of EV-based proteomic analysis in the discovery of combinatorial biomarkers for early ovarian cancer detection.

cancer biology↗

bioRxiv2020

ADAM protease inhibition overcomes resistance of breast cancer stem-like cells to γδ T cell immunotherapy

Breast cancer stem cells (BCSC) are highly resistant to current therapies, and are responsible for metastatic burden and relapse. Gamma delta T cells ({gamma}{delta}Tc) are immunosurveillance cells with tremendous anti-tumoral activity, and a growing number of clinical trials have confirmed the safety of {gamma}{delta}Tc immunotherapy for various malignancies. Herein, we demonstrate that {gamma}{delta}Tc can kill BCSC, but to a lesser extent than non-cancer stem cells (NSC). Immune evasion was orchestrated by several mechanisms. The BCSC secretome rendered {gamma}{delta}Tc hypo-responsive by reducing proliferation, cytotoxicity and IFN-{gamma} production, while increasing expression of co-inhibitory receptors on {gamma}{delta}Tc. BCSC and target cells surviving {gamma}{delta}Tc cytotoxicity had higher PD-L1 co-inhibitory ligand expression, and blocking PD-1 on {gamma}{delta}Tc significantly overcame BCSC resistance to {gamma}{delta}Tc killing. Fas/FasL signaling was dysfunctional in BCSC due to upregulation of the anti-apoptotic protein MCL-1, which could be partially overcome using dMCL1-2, an MCL-1 degrader. Moreover, the BCSC fraction shed higher levels of the NKG2D ligand MICA compared to NSC. Inhibiting MICA shedding using the ADAM inhibitor GW280264X overcame BCSC resistance to {gamma}{delta}Tc killing, rendering BCSC as sensitive to {gamma}{delta}Tc cytotoxicity as NSC. Collectively, our data unravel multiple mechanisms exploited by BCSC to evade {gamma}{delta}Tc killing, which may also come into play in BCSC resistance to other cytotoxic lymphocytes. Developing strategies to overcome this resistance will increase the efficacy of cancer immunotherapy and lead to improved outcomes for cancer patients. One Sentence SummaryBreast cancer stem-like cells are resistant to {gamma}{delta} T cell targeting, which can be overcome by inhibiting ADAM proteases that facilitate MICA/B shedding.

immunology↗