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Cell lines derived from circulating tumor cells (CTCs) in the blood provide important biological information on cancer metastasis. CTC-ITB-01 is a CTC cell line derived from a patient with metastatic estrogen receptor-alpha (ER-alpha) positive breast cancer two months before the death of the patient. After a LC-MC/MS based proteomics analysis of CTC-ITB-01, we found extraordinary high levels of the poorly characterized protein SUSD2 (sushi domain-containing protein 2) in CTC-ITB-01. Expression of SUSD2 on subsets of CTCs was validated on clinical blood samples of patients with metastatic breast cancer. SUSD2-positive CTCs could be captured specifically by a MACS-based approach. We overexpressed SUSD2 in the poorly-metastatic cell line MCF-7. This resulted in upregulation of ER-alpha, the tumor progression protein GRP78 (78-kDa glucose-regulated protein) and downregulation of the tumor suppressor protein PDCD4 (programmed cell death protein 4). We observed downregulation of SUSD2 and PDCD4 after hypoxia and simulation of re-oxygenation in the blood in MCF-7 and MDA-MB-468, while in CTC-ITB-01 SUSD2 levels remained unchanged, and only PDCD4 was downregulated under hypoxia. In conclusion, we show, for the first time, that SUSD2 is expressed in CTCs and appears to affect key proteins in tumor progression and survival. [ABSTRACT FROM AUTHOR]

BackgroundPeripartum depression and anxiety disorders are highly prevalent and are correlated with adverse maternal and neonatal outcomes. Antenatal care in Germany does not yet include structured screening and effective low-threshold treatment options for women facing peripartum depression and anxiety disorders. Mindfulness-based interventions (MBIs) are increasingly becoming a focus of interest for the management of such patients. Studies have shown a decrease in pregnancy-related stress and anxiety in expectant mothers following mindfulness programs. ObjectiveThe aim of this study was to explore the clinical effectiveness of a 1-week electronic course of mindfulness on prenatal depression and anxiety in hospitalized, high-risk pregnant women. We hypothesized that participating in a 1-week electronic MBI (eMBI) could alleviate symptoms of depression and anxiety during the hospital stay. MethodsA prospective pilot study with an explorative study design was conducted from January to May 2019 in a sample of 68 women hospitalized due to high-risk pregnancies. After enrolling into the study, the participants were given access to an eMBI app on how to deal with stress, anxiety, and symptoms of depression. Psychometric parameters were assessed via electronic questionnaires comprising the Edinburgh Postnatal Depression Scale (EPDS), State-Trait Anxiety Inventory (STAI-S), and abridged version of the Pregnancy-Related Anxiety Questionnaire (PRAQ-R). ResultsWe observed a high prevalence of peripartum depression and anxiety among hospitalized high-risk pregnant women: 39% (26/67) of the study participants in the first assessment and 41% (16/39) of the participants in the second assessment achieved EPDS scores above the cutoff value for minor/major depression. The number of participants with anxiety levels above the cutoff value (66% [45/68] of the participants in the first assessment and 67% [26/39] of the participants in the second assessment) was significantly more than that of the participants with anxiety levels below the cutoff value, as measured with the STAI-S. After completing the 1-week electronic course on mindfulness, the participants showed a significant reduction in the mean state anxiety levels (P

Background: Early identification of quality of life (QoL) loss and side effects is a key challenge in breast cancer therapy. Digital tools can be helpful components of therapeutic support. Enable, a smartphone app, was used in a multicenter, prospective randomized controlled trial in 3 breast cancer centers. The app simultaneously serves as a therapy companion (eg, by displaying appointments), a tool for documenting QoL (eg, by enabling data collection for QoL questionnaires), and documentation of patient-reported side effects. The need for digital tools is continually rising. However, evidence of the effects of long-term use of mobile health (mHealth) apps in aftercare for patients with breast cancer is limited. Therefore, evaluating the usability and understanding the user experience of this mHealth app could potentially contribute valuable insights in this field. Objective: A usability study was conducted to explore how patients with breast cancer receiving neoadjuvant, adjuvant, or palliative outpatient treatment rated their engagement with the app, the user experience, and the benefits of using the app. Methods: A mixed methods approach was chosen to combine subjective and objective measures, including an eye-tracking procedure, a standardized usability questionnaire (mHealth App Usability Questionnaire), and semistructured interviews. Participants were surveyed twice during the study period. Interviews were transcribed verbatim and analyzed using thematic analysis. Analysis of the eye-tracking data was carried out using the tracker-integrated software. Descriptive analysis was conducted for the quantitative data. Results: The mHealth App Usability Questionnaire results (n=105) indicated good overall usability for 2 different time points (4 wk: mean 89.15, SD 9.65; 20 wk: mean 85.57, SD 12.88). The qualitative analysis of the eye-tracking recordings (n=10) and interviews (n=16) showed that users found the Enable app easy to use. The design of the app, information about therapies and side effects, and usefulness of the app as a therapy companion were rated positively. Additionally, participants contributed requests for additional app features and suggestions for improving the content and usability of the app. Relevant themes included optimization of the appointment feature, updating the app's content regularly, and self-administration. In contrast to the app's current passive method of operation, participants expressed a desire for more active engagement through messaging, alarms, or emails. Conclusions: The results of this study demonstrate the good usability of the Enable app as well as the potential for further development. We concluded from patients' feedback and requests that mHealth apps could benefit from giving patients a more active role (eg, being able to actively document side effects as they occur). Additionally, regular updates of app content could further contribute to encouraging continued use of mHealth apps. Our findings may also assist other researchers in tailoring their mHealth apps to the actual needs of patients undergoing breast cancer therapy. [ABSTRACT FROM AUTHOR]

Introduction: Significant progress has been made in the targeted therapy of metastatic breast cancer (mBC) in recent years. In this context, new biomarkers enable personalized therapy management and individualized therapy monitoring. Therefore, the systemic treatment is based increasingly on the biological characteristics of the tumor disease. Given the challenges of obtaining fresh tumor tissue through biopsies, the significance of liquid biopsies for assessing circulating tumor cells (CTCs) or circulating tumor DNA is of growing importance for the detection of prognostic and predictive biomarkers. Multiple studies have shown that the number of CTCs decreases under therapy, especially under anti-HER2-targeted therapy, and that the expression of the HER2 status on CTCs could play a role in predicting therapy response and therapeutic monitoring. The aim of this study was to analyze the HER2 status of CTCs in mBC patients before and after 3 months of systemic therapy to evaluate changes in the number of HER2-positive CTCs. The study focuses on HER2-low, which plays an increasingly important role in clinical practice due to new developments of HER2 targeting antibody-drug conjugates. In this context, temporal and spatial heterogeneity of the disease represent a major diagnostic challenge. Methods: A total of 324 patients with complete immunohistochemistry of biopsied metastases were divided into five groups: HER2 negative (−)/hormone receptor (HR) negative (−), HER2 −/HR positive (+), HER2 +/HR±, HER2-low/HR+, and HER2-low/HR−. Before and after 3 months of a new therapeutic line for mBC, CTCs were enumerated and analyzed for HER2 expression using the CellSearch® system. Overall survival of all subgroups was calculated. Results: The analyses revealed a discrepancy between the HER2 status of CTCs and corresponding tumor tissues in 98 patients (30.2%). The number of CTCs in general and the number of HER2+ CTCs decreased during systemic treatment, mainly in HER2+ tumors, but also in the other subgroups. Conclusions: Discrepancy in the HER2 status of the metastases and of CTCs was observed in approximately one-third of patients. Measuring HER2 on CTCs could potentially offer a means to longitudinally monitor HER2 status during therapy and simultaneously address challenges such as tumor heterogeneity. Therefore, the predictive value of HER2 on CTCs should be further investigated in clinical trials. [ABSTRACT FROM AUTHOR]

The presence of circulating tumor cells (CTCs), detected as a form of liquid biopsy is associated with poor survival in both early and metastatic breast cancer. Monitoring tumor biology based on intrinsic subtypes delivers treatment-relevant information on the heterogeneity or biomarker conversion between primary and metastatic tumors. This study aimed to correlate the change of the apoptotic and intact CTC counts with mRNA-assessed intrinsic subtype change. Thirty-four breast cancer patients with available triplets of primary tumors, distant metastasis biopsies and data on intact and apoptotic CTC dynamics were included in the analysis. The intrinsic subtype was determined per RT-qPCR quantification of the gene expression ESR1, PGR, ERBB2 and MKI67. Both luminal (p = 0.038) and triple negative (p = 0.035) patients showed a significant downregulation of apoptotic CTCs. Repeated biopsies of distant metastatic sites, as well as determining a potential shift of the intrinsic subtype, combined with data on intact and apoptotic CTC dynamics from liquid biopsies might help personalize systemic therapy and generate additional surrogate markers for successful systemic therapy. [ABSTRACT FROM AUTHOR]

Background/aim: The loss of breast cancer cell differentiation during metastatic progression leads to a down-regulation of class 1 human leukocyte antigen (HLA) expression, which in turn hinders cytotoxic T lymphocytes from effectively preventing tumor cell proliferation. Consequently, one would expect that decreased HLA expression would correlate with decreased 5-year survival. However, estrogen receptor alpha (ESR1) is known to be positively associated with overall survival. The study aimed to determine the expression levels of HLA-A, HLA-B/C, and ESR1 and to assess their influence on distant disease-free survival (DDFS)., Materials and Methods: This retrospective subgroup analysis of the initial prospective, single-center, double-blind cohort study included a total of 34 patients who underwent a new treatment line for metastatic breast cancer (MBC). The MBC cells were examined using RT-qPCR., Results: The acquired data and the subsequent survival and ROC analyses indicated a positive association of reduced expression of HLA-A and HLA-B/C with DDFS. A statistically significant association of ESR1 with DDFS could not be shown., Conclusion: A potential positive association between reduced expression of HLA-A and HLA-B/C and DDFS is observed. This contrasts with the generally observed association between HLA expression loss and poor prognosis, as reported in previous protein-based studies. In metastatic settings, reduced expression of particular HLA subsets, measured at the mRNA level, might have a protective effect against disease progression., (Copyright © 2025 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Purpose: Toxicity to systemic cancer treatment represents a major anxiety for patients and a challenge to treatment plans. We aimed to develop machine learning algorithms for the upfront prediction of an individual's risk of experiencing treatment-relevant toxicity during the course of treatment., Methods: Clinical records were retrieved from a single-center, consecutive cohort of patients who underwent neoadjuvant treatment for early breast cancer. We developed and validated machine learning algorithms to predict grade 3 or 4 toxicity (anemia, neutropenia, deviation of liver enzymes, nephrotoxicity, thrombopenia, electrolyte disturbance, or neuropathy). We used 10-fold cross-validation to develop two algorithms (logistic regression with elastic net penalty [GLM] and support vector machines [SVMs]). Algorithm predictions were compared with documented toxicity events and diagnostic performance was evaluated via area under the curve (AUROC)., Results: A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The performance improved significantly when adding referenced treatment information (referenced regimen, referenced summation dose intensity product) in addition to patient and tumor variables: GLM AUROC 0.59 versus 0.75, P = .02; SVM AUROC 0.64 versus 0.75, P = .01., Conclusion: The individual risk of treatment-relevant toxicity can be predicted using machine learning algorithms. We demonstrate a promising way to improve efficacy and facilitate proactive toxicity management of systemic cancer treatment.

Background/aim: Loss of differentiation of breast cancer cells in association with a down-regulated class I human leukocyte antigen (HLA) expression can lead to proliferation unhampered by cytotoxic T lymphocytes, which has been proven to be of prognostic relevance. The objective of this study was to determine the levels of HLA-A and HLA-B/C expression in metastatic breast cancer (MBC) cells and their usefulness for predicting 5-year survival., Materials and Methods: This prospective double-blinded cohort study analyzed patients starting a new line of therapy for MBC. RT-qPCR was used to determine the levels of HLA-A and B/C expression in MBC cells and the mRNA-based tumor intrinsic subtype. Two receiver operating characteristic curves (ROC) were constructed in order to determine whether HLA-A and HLA-B/C expression levels can be used for predicting 5-year survival. Youden J points, and sensitivity and specificity optimized cut-off points were determined for both ROC curves., Results: We enrolled 34 patients. The ROC curve for HLA-B/C had the highest AUC compared to HLA-A (0.55 vs. 0.42). High levels of HLA-A and HLA-B/C expression (40-ΔΔCT of 33.5 and 31.9, respectively) were highly specific (reaching 87.5% for HLA-A and even 100% specificity for HLA-B/C) yet insensitive for five-year survival in our study., Conclusion: High expression of certain class I HLA molecule subtypes by MBCs, in particular high HLA-A or B/C expression by MBC cells seems very specific in predicting the 5-year survival. We determined cut-off values for these HLA molecule clusters with high specificity, which might help identify patients with a favorable prognosis as prognosticators of a 5-year overall survival if their sensitivity is improved in larger prospective cohorts., (Copyright © 2023 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)