Sensitizing multidrug-resistant leukemia cells to common cytostatics by an aluminium-salen complex that has high-apoptotic effects in leukemia, lymphoma and mamma carcinoma cells

We investigated the aluminium-salen complex MBR-8 as a potential anti-cancer agent. To see apoptotic effects induced by MBR-8, alone and in combination with common cytostatic drugs, DNA-fragmentations were studied using the flow cytometric analysis. Western blot analysis and measurement of the mitochondrial membrane potential with a JC-1 dye were employed to identify the pathway of apoptosis. An impressive overcoming of multidrug-resistance in leukemia (Nalm6) cells was observed. Additionally, solid tumor cells including Burkitt-like lymphoma (BJAB) and mamma carcinoma cells (MCF-7) are affected by MBR-8 in the same way. Western blot analysis revealed activation of caspase-3. MBR-8 showed very pronounced selectivity with regard to tumor cells and high synergistic effects in Nalm6 and daunorubicin-resistant Nalm6 cells when administered in combination with vincristine, daunorubicin and doxorubicin. The aluminium-salen complex MBR-8 showed very promising anti-cancer properties which warrant further development towards a cytostatic agent for future chemotherapy. Studies on aluminium compounds for cancer therapy are rare, and our report adds to this important body of knowledge.

Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model

PURPOSE

To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches.

METHODS

Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples.

RESULTS

Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74-0.76) and SP (0.67, 95%CI: 0.65-0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77-0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created.

CONCLUSIONS

INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.

Predicting the risk of locoregional recurrence after early breast cancer: an external validation of the Dutch INFLUENCE-nomogram with clinical cancer registry data from Germany

Purpose

Follow-up after breast cancer treatment aims for an early detection of locoregional breast cancer recurrences (LRR) to improve the patients’ outcome. By estimating individual’s 5-year recurrence-risks, the Dutch INFLUENCE-nomogram can assist health professionals and patients in developing personalized risk-based follow-up pathways. The objective of this study is to validate the prediction tool on non-Dutch patients.

Material and methods

Data for this external validation derive from a large clinical cancer registry in southern Germany, covering a population of 1.1 million. Patients with curative resection of early-stage breast cancer, diagnosed between 2000 and 2012, were included in the analysis (n = 6520). For each of them, an individual LRR-risk was estimated by the INFLUENCE-nomogram. Its predictive ability was tested by comparing estimated and observed LRR-probabilities using the Hosmer–Lemeshow goodness-of-fit test and C-statistics.

Results

In the German validation-cohort, 2.8% of the patients developed an LRR within 5 years after primary surgery (n = 184). While the INFLUENCE-nomogram generally underestimates the actual LRR-risk of the German patients (p < 0.001), its discriminative ability is comparable to the one observed in the original Dutch modeling-cohort (C-statistic German validation-cohort: 0.73, CI 0.69–0.77 vs. C-statistic Dutch modeling-cohort: 0.71, CI 0.69–0.73). Similar results were obtained in most of the subgroup analyses stratified by age, type of surgery and intrinsic biological subtypes.

Conclusion

The outcomes of this external validation underline the generalizability of the INFLUENCE-nomogram beyond the Dutch population. The model performance could be enhanced in future by incorporating additional risk factors for LRR.