Department of Biochemistry

Background: Adjuvant trastuzumab is the standard of care for HER2+ breast cancer (BC) patients. However, >50% of patients become resistant. This study aimed at the identification of the molecular factors associated with disease relapse and their further investigation as therapeutically exploitable targets. Methods: Analyses were conducted on formalin-fixed paraffin-embedded tissues of the primary tumors of relapsed (cases) and not relapsed (controls) HER2+ BC patients treated with adjuvant trastuzumab. The nCounter Human Breast Cancer Panel 360 was used. Logistic regression and partitioning around medoids were employed to identify the genes associated with disease recurrence. Cytotoxicity experiments using trastuzumab-resistant cell lines and a network pharmacology approach were carried out to investigate drug efficacy. Results: A total of 52 patients (26 relapsed and 26 not relapsed) were analyzed. We found that a higher expression of HDAC6 was significantly associated with an increased risk of recurrence, with an adjusted OR of 3.20 (95% CI 1.38–9.91, p = 0.016). Then, we investigated the cytotoxic activity of the selective HDAC6 inhibitor Nexturastat A (NextA) on HER2+ cell lines, which were both sensitive and trastuzumab-resistant. A sub-cytotoxic concentration of NextA, combined with trastuzumab, showed a synergistic effect on BC cell lines. Finally, using a network pharmacology approach, we identified HSP90AA1 as the putative molecular candidate responsible for the synergism observed in vitro. Conclusions: Our findings encourage the exploration of the role of HDAC6 as a prognostic factor and the combinatorial use of HDAC6 selective inhibitors combined with trastuzumab in HER2+ BC, in particular for those patients experiencing drug resistance.

Ion channels of T cells (Kv1.3, KCa3.1, and CRAC) participate in the regulation of activation and effector functions via modulation of the Ca2+-dependent pathway. T cells expressing chimeric antigen receptors (CAR T cells) showed a remarkable role in anti-tumor therapy, especially in the treatment of chemotherapy-resistant liquid cancers. Nevertheless, many challenges remain to be overcome to improve the treatment for solid tumors. In this study, we assessed the expression and role of ion channels in CAR T cells. We found that HER2-specific CAR T cells had higher KCa3.1 conductance compared to the non-transduced (NT, control) cells, which was more prominent in the CD8+ population (CD4+ cell also showed elevation). Conversely, the Kv1.3 expression level was the same for all cell types (CD4+, CD8+, CAR, and NT). Single-cell Ca2+ imaging revealed that thapsigargin-induced SOCE via CRAC is suppressed in CD8+ CAR T cells, unlike for CD4+ and CD8+ NT cells. To dissect the functional role of Kv1.3 and KCa3.1, we used specific antagonists (Kv1.3: Vm24; KCa3.1: TRAM-34): the target cell elimination capacity of the CD8+ CAR T cells was improved either by blocking KCa3.1 or Kv1.3. These results imply that ion channels could be a target in CAR T cell immunotherapy elaboration.

Background: Our aim was to investigate the predictability of postoperative meningioma resection status based on clinical features. Methods: We examined 23 clinical features to assess their effectiveness in distinguishing gross total resections (GTR) from subtotal resections (STR). We analyzed whether GTR/STR cases are better predictable if the classification is based on the Simpson grading or the postoperative operative tumor volume (POTV). Results: Using a study cohort comprising a total of 157 patients, multivariate models for the preoperative prediction of GTR/STR outcome in relation to Simpson grading and POTV were developed and subsequently compared. Including only two clinical features, our models showed a notable discriminatory power in predicting postoperative resection status. Our final model, a straightforward decision tree applicable in daily clinical practice, achieved a mean AUC of 0.885, a mean accuracy of 0.866, a mean sensitivity of 0.889, and a mean specificity of 0.772 based on independent test data. Conclusions: Such models can be a valuable tool both for surgical planning and for early planning of postoperative treatment, e.g., for additional radiotherapy/radiosurgery, potentially required in case of subtotal resections.