Bilateral Oophorectomy and All-Cause Mortality in Women With BRCA1 and BRCA2 Sequence Variations.

Importance: Preventive bilateral salpingo-oophorectomy is offered to women at high risk of ovarian cancer who carry a pathogenic variant in BRCA1 or BRCA2; however, the association of oophorectomy with all-cause mortality has not been clearly defined. Objective: To evaluate the association between bilateral oophorectomy and all-cause mortality among women with a BRCA1 or BRCA2 sequence variation. Design, Setting, and Participants: In this international, longitudinal cohort study of women with BRCA sequence variations, information on bilateral oophorectomy was obtained via biennial questionnaire. Participants were women with a BRCA1 or BRCA2 sequence variation, no prior history of cancer, and at least 1 follow-up questionnaire completed. Women were followed up from age 35 to 75 years for incident cancers and deaths. Cox proportional hazards regression was used to estimate the hazard ratios (HRs) and 95% CIs for all-cause mortality associated with a bilateral oophorectomy (time dependent). Data analysis was performed from January 1 to June 1, 2023. Exposures: Self-reported bilateral oophorectomy (with or without salpingectomy). Main Outcomes and Measures: All-cause mortality, breast cancer-specific mortality, and ovarian cancer-specific mortality. Results: There were 4332 women (mean age, 42.6 years) enrolled in the cohort, of whom 2932 (67.8%) chose to undergo a preventive oophorectomy at a mean (range) age of 45.4 (23.0-77.0) years. After a mean follow-up of 9.0 years, 851 women had developed cancer and 228 had died; 57 died of ovarian or fallopian tube cancer, 58 died of breast cancer, 16 died of peritoneal cancer, and 97 died of other causes. The age-adjusted HR for all-cause mortality associated with oophorectomy was 0.32 (95% CI, 0.24-0.42; P < .001). The age-adjusted HR was 0.28 (95% CI, 0.20-0.38; P < .001) and 0.43 (95% CI, 0.22-0.90; P = .03) for women with BRCA1 and BRCA2 sequence variations, respectively. For women with BRCA1 sequence variations, the estimated cumulative all-cause mortality to age 75 years for women who had an oophorectomy at age 35 years was 25%, compared to 62% for women who did not have an oophorectomy. For women with BRCA2 sequence variations, the estimated cumulative all-cause mortality to age 75 years was 14% for women who had an oophorectomy at age 35 years compared to 28% for women who did not have an oophorectomy. Conclusions and Relevance: In this cohort study among women with a BRCA1 or BRCA2 sequence variation, oophorectomy was associated with a significant reduction in all-cause mortality.

MRI Surveillance and Breast Cancer Mortality in Women With BRCA1 and BRCA2 Sequence Variations.

Importance: Magnetic resonance imaging (MRI) surveillance is offered to women with a pathogenic variant in the BRCA1 or BRCA2 gene who face a high lifetime risk of breast cancer. Surveillance with MRI is effective in downstaging breast cancers, but the association of MRI surveillance with mortality risk has not been well defined. Objective: To compare breast cancer mortality rates in women with a BRCA1 or BRCA2 sequence variation who entered an MRI surveillance program with those who did not. Design, Setting, and Participants: Women with a BRCA1 or BRCA2 sequence variation were identified from 59 participating centers in 11 countries. Participants completed a baseline questionnaire between 1995 and 2015 and a follow-up questionnaire every 2 years to document screening histories, incident cancers, and vital status. Women who had breast cancer, a screening MRI examination, or bilateral mastectomy prior to enrollment were excluded. Participants were followed up from age 30 years (or the date of the baseline questionnaire, whichever was later) until age 75 years, the last follow-up, or death from breast cancer. Data were analyzed from January 1 to July 31, 2023. Exposures: Entrance into an MRI surveillance program. Main Outcomes and Measures: Cox proportional hazards modeling was used to estimate the hazard ratios (HRs) and 95% CIs for breast cancer mortality associated with MRI surveillance compared with no MRI surveillance using a time-dependent analysis. Results: A total of 2488 women (mean [range] age at study entry 41.2 [30-69] years), with a sequence variation in the BRCA1 (n = 2004) or BRCA2 (n = 484) genes were included in the analysis. Of these participants, 1756 (70.6%) had at least 1 screening MRI examination and 732 women (29.4%) did not. After a mean follow-up of 9.2 years, 344 women (13.8%) developed breast cancer and 35 women (1.4%) died of breast cancer. The age-adjusted HRs for breast cancer mortality associated with entering an MRI surveillance program were 0.20 (95% CI, 0.10-0.43; P < .001) for women with BRCA1 sequence variations and 0.87 (95% CI, 0.10-17.25; P = .93) for women with BRCA2 sequence variations. Conclusion and Relevance: Results of this cohort study suggest that among women with a BRCA1 sequence variation, MRI surveillance was associated with a significant reduction in breast cancer mortality compared with no MRI surveillance. Further studies of women with BRCA2 sequence variations are needed to ascertain these women obtain the same benefits associated with MRI surveillance.

Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer.

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene expression. This raises the question of how to fuse information, in particular, if there is disagreement. It is the primary domain of Dempster-Shafer decision theory (DST) to deal with contradicting evidence on the same item (here: receptor status), obtained through different techniques. DST is widely used in technical settings, such as self-driving cars and aviation, and is also promising to deliver significant advantages in medicine. Using data from breast cancer patients already presented in previous work, we focus on comparing DST with classical statistics in this work, to pave the way for its application in medicine. First, we explain how DST not only considers probabilities (a single number per sample), but also incorporates uncertainty in a concept of 'evidence' (two numbers per sample). This allows for very powerful displays of patient data in so-called ternary plots, a novel and crucial advantage for medical interpretation. Results are obtained according to conventional statistics (ODDS) and, in parallel, according to DST. Agreement and differences are evaluated, and the particular merits of DST discussed. The presented application demonstrates how decision theory introduces new levels of confidence in diagnoses derived from medical data.

Decision theory for precision therapy of breast cancer.

Correctly estimating the hormone receptor status for estrogen (ER) and progesterone (PGR) is crucial for precision therapy of breast cancer. It is known that conventional diagnostics (immunohistochemistry, IHC) yields a significant rate of wrongly diagnosed receptor status. Here we demonstrate how Dempster Shafer decision Theory (DST) enhances diagnostic precision by adding information from gene expression. We downloaded data of 3753 breast cancer patients from Gene Expression Omnibus. Information from IHC and gene expression was fused according to DST, and the clinical criterion for receptor positivity was re-modelled along DST. Receptor status predicted according to DST was compared with conventional assessment via IHC and gene-expression, and deviations were flagged as questionable. The survival of questionable cases turned out significantly worse (Kaplan Meier p < 1%) than for patients with receptor status confirmed by DST, indicating a substantial enhancement of diagnostic precision via DST. This study is not only relevant for precision medicine but also paves the way for introducing decision theory into OMICS data science.

7T CEST MRI: A potential imaging tool for the assessment of tumor grade and cell proliferation in breast cancer.

OBJECTIVES: To investigate the feasibility of chemical exchange saturation transfer (CEST) MRI in patients with breast carcinomas and possible correlations between magnetization transfer asymmetry (MTRasym) values and histological features, such as tumor grade and the Ki-67 proliferation index. MATERIALS AND METHODS: Nine healthy subjects and 18 female patients were enrolled for this study. The imaging protocol for the patients consisted of diffusion-weighted imaging (DWI), CEST imaging, and T1-weighted, contrast-enhanced (CE)-MRI. CEST was performed using a 3D gradient echo (GRE) sequence, employing eight pre-saturation pulses of a duration of 50 ms and a duty cycle (DC) of 80%, with a mean amplitude of the saturation pulse train of 1 µT. The Z-spectrum was plotted and MTRasym values calculated for the frequency of the maximum of MTRasym curve, were correlated with the Ki-67 proliferation index and apparent diffusion coefficient (ADC). Patient data were statistically assessed using the Games-Howell post-hoc and Pearson's correlation test. RESULTS: Different tumor types had asymmetry peaks at different positions of Z-spectrum. MTRasym (mean ±â€¯SD) (%) calculated for G1 (3.0 ±â€¯0.3; range: 2.70-3.50) was not significantly lower than for G2 (4.50 ±â€¯1.30; range: 3.20-6.50; p = 0.066). In contrast, the increase in MTRasym between G1 and G3 (6.40 ±â€¯1.70; range: 4.80-9.80) lesions was significant (p = 0.007). No significant difference was observed between G2 and G3 with regard to MTRasym (p = 0.089). There was a strong positive correlation between the MTRasym, and Ki-67 proliferation index (r = 0.890; p = 0.001), while there was a moderate negative correlation between MTRasym and ADC values (r = -0.506; p = 0.027). CONCLUSIONS: Calculated MTRasym demonstrates a strong positive correlation with tumor proliferation and has the potential to become a valuable biomarker for breast tumor characterization.

Modern Risk Assessment for Individualizing Treatment Concepts in Early-stage Breast Cancer.

Validated prognostic and predictive factors currently play an important role in treatment planning for patients with early-stage breast cancer. The role of personalized medicine has led to the search for markers that can be applied to individual patients to optimize treatment regimens. In addition to traditional clinicopathologic measures, scores and gene tests have been developed to independently predict risk of patients in the neoadjuvant and adjuvant settings. The discovery of these markers provides the opportunity to identify patients at such low risk of recurrence that toxic therapy side effects are not justified. Selection and management of patients with early-stage, hormone receptor-positive breast cancer who are appropriately treated with endocrine therapy alone after receiving locoregional therapy but do not necessarily require adjuvant chemotherapy is currently problematic. This article reviews the current state-of-theart biomarker assessment methods and discusses the potential role for the prediction of chemotherapy benefit focusing on endocrine sensitive disease.

Assessment of a six gene panel for the molecular detection of circulating tumor cells in the blood of female cancer patients.

BACKGROUND: The presence of circulating tumor cells (CTC) in the peripheral blood of cancer patients has been described for various solid tumors and their clinical relevance has been shown. CTC detection based on the analysis of epithelial antigens might be hampered by the genetic heterogeneity of the primary tumor and loss of epithelial antigens. Therefore, we aimed to identify new gene markers for the PCR-based detection of CTC in female cancer patients. METHODS: Gene expression of 38 cancer cell lines (breast, ovarian, cervical and endometrial) and of 10 peripheral blood mononuclear cell (PBMC) samples from healthy female donors was measured using microarray technology (Applied Biosystems). Differentially expressed genes were identified using the maxT test and the 50% one-sided trimmed maxT-test. Confirmatory RT-qPCR was performed for 380 gene targets using the AB TaqMan® Low Density Arrays. Then, 93 gene targets were analyzed using the same RT-qPCR platform in tumor tissues of 126 patients with primary breast, ovarian or endometrial cancer. Finally, blood samples from 26 healthy women and from 125 patients (primary breast, ovarian, cervical, or endometrial cancer, and advanced breast cancer) were analyzed following OncoQuick enrichment and RNA pre-amplification. Likewise, hMAM and EpCAM gene expression was analyzed in the blood of breast and ovarian cancer patients. For each gene, a cut-off threshold value was set at three standard deviations from the mean expression level of the healthy controls to identify potential markers for CTC detection. RESULTS: Six genes were over-expressed in blood samples from 81% of patients with advanced and 29% of patients with primary breast cancer. EpCAM gene expression was detected in 19% and 5% of patients, respectively, whereas hMAM gene expression was observed in the advanced group (39%) only. Multimarker analysis using the new six gene panel positively identified 44% of the cervical, 64% of the endometrial and 19% of the ovarian cancer patients. CONCLUSIONS: The panel of six genes was found superior to EpCAM and hMAM for the detection of circulating tumor cells in the blood of breast cancer, and they may serve as potential markers for CTC derived from endometrial, cervical, and ovarian cancers.

Predicting the efficacy of trastuzumab-based therapy in breast cancer: current standards and future strategies.

Breast cancer is the most common female malignancy in many industrialized countries. Approximately one fourth of all women diagnosed with early breast cancer present with tumors that are characterized by erbB2 amplification. While the associated Her-2/neu receptor overexpression results in a high risk of relapse and poor prognosis, these tumors also represent a target for a selective monoclonal antibody therapy with trastuzumab (Herceptin). The combination of trastuzumab with chemotherapy has led to a considerable reduction of recurrences and to a significant reduction in breast cancer mortality both in the adjuvant and metastatic setting. Unfortunately, despite Her-2/neu overexpression, not all patients equally benefit from trastuzumab treatment, and almost all women with metastatic breast cancer eventually progress during antibody therapy. Moreover, trastuzumab is burdened with cardiotoxicity, thus increasing the risk of symptomatic congestive heart failure. In addition, the marginal costs for a 1 year therapy of trastuzumab-based therapy, which is currently considered to be the most effective treatment regimen in the adjuvant setting, may amount for up to US$ 40.000. Testing for erbB2 oncogene amplification by fluorescence in situ hybridization (FISH) and chromogenic in situ hybridization (CISH), respectively, and staining for Her-2/neu receptor overexpression by immunohistochemistry (IHC) represent the current standard for determining patient eligibility for trastuzumab-based therapy. However, while the negative predictive value of these assays for predicting the absence of benefit from trastuzumab-based therapy is sufficiently high, their positive predictive value remains insufficient, i.e. only a proportion of patients selected by these tests substantially benefit from trastuzumab-containing regimen. Accordingly, over the last years a number of biomarkers have been evaluated in their potential to predict response to trastuzumab-based therapies. These include markers auf activation of Her-2/neu (e.g., tyrosine phosphorylated Her-2/neu in tissue and cleaved Her-2/neu extracellular domain in serum) and its dimerization partners (e.g., EGFR), respectively, but also components of Her-2/neu-induced downstream signaling pathways that are crucial for the growth inhibitory effects of trastuzumab (e.g., PTEN and PI3K). Other parameters, such as topoisomerase-II alpha and c-myc co-amplifications, have also been identified as potentially useful predictors of response to trastuzumab-based chemotherapy regimen. While the benefit of these predictive biomarkers in the metastatic setting is currently explored, their usefulness in the adjuvant setting is still largely unknown. It is, however, undisputable that, within the group of Her-2/neu overexpressing tumors, further response predictors are needed in order to minimize trastuzumab-associated side effects, and to reduce the considerable societal costs that are associated with trastuzumab-based treatment regimen.