[FG] Weber Walter Paul

Imported from Grants Tool 4725653

According to the Swiss Certified Breast Center Database, 1580 implant-based breast reconstructions (IBBR) were performed at Swiss certified breast cancer centers in 2017. The optimal positioning of the breast implant above (pre-pectoral) or below the pectoralis major muscle (sub-pectoral) is currently not clear when performing IBBR after nipple- or skin-sparing mastectomy (NSM, SSM) for breast cancer treatment or prevention. Pre-pectoral positioning respects the anatomic position of the mammary gland and avoids surgery-induced alterations of the pectoralis major muscle. Therefore, it offers a variety of potential advantages including improved physical well-being, easier recovery, and no animation deformity caused by muscle movement. However, the lack of muscle coverage may create its own set of problems, including a higher risk of complications like capsular contracture and rippling of the implant.Sub-pectoral IBBR is still standard care in many countries, but pre-pectoral IBBR is increasingly performed. However, despite this change in practice, there is no clear evidence to support the assumption that pre-pectoral positioning offers relevant improvements in patient-relevant outcomes after surgery in the long term. We hypothesize that pre-pectoral IBBR is associated with improved quality of life compared to sub-pectoral IBBR by improving long-term physical well-being of the chest. We propose a multicenter, randomized superiority trial with 24 months follow-up to test this hypothesis. We designed the trial to be fit for that purpose by applying the PRECIS-2 requirements for pragmatism. The trial will include 372 patients undergoing NSM or SSM and IBBR for prevention or treatment of breast cancer at least 13 Swiss and six non-Swiss OPBC study sites. Randomization will be stratified by center and uni- versus bilateral surgery. Patients will be randomized 1:1 to the experimental group with pre-pectoral IBBR and the control group with sub-pectoral IBBR. Patient advocates have helped develop the protocol and select the primary endpoint, which will be patient-reported long-term physical well-being of the chest measured by the BREAST-Q scale "physical well-being: chest" 24 months after NSM or SSM and IBBR. Secondary endpoints will include safety, overall quality of life, patient satisfaction, objective aesthetic outcomes and burden on patients. We believe that this trial is original, relevant as it addresses a specific clinical research field that is important and under-investigated, and is feasible for the following reasons: First, the corresponding applicant is an oncoplastic surgeon with experience in performing multicenter randomized trials. Second, he developed this proposal with the help of his co-applicant, a reconstructive breast surgeon specialized in breast reconstruction, and a team of patient advocates and experienced clinical research partners from all relevant disciplines. Third, a strong network of recruiting centers from public and private settings that has proved to operate well together in the past will ensure sufficient patient accrual.

Each year 1.4 million new cases of breast cancer will occur among women worldwide and 50,000 women will die from this disease. In most cases, metastasis is the cause of death. Although progress has been made in broadly understanding the biology of breast tumors and metastases, most of the relevant molecules and pathways remain undefined. Moreover, the integration of multiple signaling pathways into networks and an understanding of their dynamic changes during progression to metastases are still missing. The design and development of new therapies require a more thorough systems level understanding of the quantitative behavior of breast cancer growth and progression to metastases that arises from the dynamic interplay of cancer cell subpopulations and of signaling networks. The predominant goal of this project is to use a systems biology approach to unravel, integrate and mathematically model the cellular and molecular determinants of breast cancer progression to metastasis . We will use pathophysiologically relevant models of metastatic breast cancer and validate our findings using clinical specimens and data on patients' outcome. We propose three interweaved and complementary approaches . The first will use transcriptomic, phosphoproteomic, and single-cell mass cytometry to identify signaling networks driving the different stages of breast tumor progression to metastases and to assess the cellular heterogeneity in the various stages of the metastatic process. The second approach will use these datasets, to mathematically infer and model molecular and cellular dynamics during tumor progression and generate experimentally testable hypotheses and eventually identify the metastasis-initiating cells and their signaling network. Finally, proof of concept experiments using cellular systems in vitro and animal models in vivo will validate the predictions of the mathematical models and test the merit of candidate pathways and molecules as targets for therapy interfering with metastatic spread. The combined use of pathophysiologically relevant models of metastatic breast cancer, clinical specimens, state-of-the-art technologies for analyzing global signaling networks at the single cell level, and high end computational and mathematical tools put our complementary team in a unique position for: a) modeling changes in cellular heterogeneity and signaling networks specific for each breast tumor cell subpopulation during tumor growth and progression to metastasis and b) assessing the clinically relevant molecular determinant of metastasis. We not only use state-of-the-art technologies, but also cross the boundaries between dry and wet laboratories and the ward. The mathematical model will allow computer simulation, generate experimentally testable predictions, and will ultimately pinpoint novel network-based targets for therapy that will improve the clinical management of patients with metastatic breast cancer.

Each year 1.4 million new cases of breast cancer will occur among women worldwide and 450,000 women will die from this disease. In most cases, metastasis is the cause of death. Although progress has been made in broadly understanding the biology of breast tumors and metastases, most of the relevant molecules and pathways remain undefined. Moreover, the integration of multiple signaling pathways into networks and their dynamic changes during progression to metastases is still missing. The design and development of new therapies require a more thorough systems level understanding of the quantitative behavior of breast cancer growth and progression to metastases that arises from the dynamic interplay of cancer cell subpopulations and of signaling networks. The predominant goal of this project is to use a systems biology approach to unravel, integrate and mathematically model the cellular and molecular determinants of breast cancer progression to metastases . We will use pathophysiologically relevant models of metastatic breast cancer and validate our findings by investigating patient histopathology and blood specimens and corresponding clinical outcome data. We propose three interweaved and complementary approaches . The first will use transcriptomic, phosphoproteomic, and single-cell mass cytometry to identify signaling networks driving the different stages of breast tumor progression to metastases and to assess the cellular heterogeneity in the various stages of the metastatic process. The second approach will use these datasets, to mathematically infer and model molecular and cellular dynamics during tumor progression and generate experimentally testable hypotheses and eventually identify the metastasis-initiating cells and their signaling network. Finally, proof of concept experiments using cellular systems in vitro and animal models in vivo will validate the predictions of the mathematical models and test the merit of candidate pathways and molecules as targets for therapy interfering with metastatic spread. The combined use of pathophysiologically relevant models of metastatic breast cancer, clinical specimens and outcome data, state-of-the-art technologies for analyzing global signaling networks at the single cell level, and high end computational and mathematical tools put our complementary team in a unique position for: a) modeling changes in cellular heterogeneity and signaling networks specific for each breast tumor cell subpopulation during tumor growth and progression to metastases and b) assessing the clinically relevant molecular determinant of metastasis. We not only use state-of-the-art technologies, but also cross the boundaries between the dry and wet labs and the ward. The mathematical model will allow computer simulation, generate experimentally testable predictions, and will ultimately pinpoint novel network-based targets for therapy that will improve the clinical management of patients with metastatic breast cancer.

Surgical Site Infections (SSI) are the most common hospital-acquired infections among surgical patients and are the cause of a substantial disease burden. The administration of surgical antimicrobial prophylaxis (SAP) reduces the risk of SSI in many types of surgical procedures. The optimal timing for this procedure, however, is still a matter of debate. While most studies suggest that SAP should be given as close to the incision time as possible, others conclude that this may be too late for optimal prevention of SSI. A large observational study conducted in Switzerland suggests that SAP should be administered 74 to 30 minutes before surgery. We propose to conduct a bicenter prospective randomized controlled trial (RCT) at two tertiary referral centers in Switzerland, the University Hospital of Basel and the Cantonal Hospital of Aarau. We plan to compare two different delivery modi for SAP, which will result in different average administration times: SAP delivery in the anesthesia room (more than 30 minutes before incision) vs SAP delivery in the operating room (less than 30 minutes before incision). We hypothesize that the rate of SSI is significantly lower with administration of SAP more than 30 minutes before the scheduled incision (in the anesthesia room) as compared with less than 30 minutes before the scheduled incision (in the operating room). We plan to include 5000 patients undergoing visceral, vascular and trauma procedures -2500 per treatment arm- and assess the occurrence of SSI during a 30 day follow-up period (1 year if an implant is in place). When assuming a 5% SSI risk with administration of SAP in the operating room, the planned study size has 80% power to detect a relative risk reduction for SSI of 33% when administering SAP in the anesthesia room (with a two-sided type I error of 5%). We expect the study to be completed within 3 years. The following factors underscore our competence to perform this RCT: First, we have extensive experience in SSI prevention and control. We have conducted several observational and interventional studies on this topic that resulted in publications in high-impact journals. Second, an electronic SSI surveillance system has been introduced as an accurate tool to register in-hospital SSI at the University Hospital of Basel and will be established at the Aarau study site by mid 2011. Third, the routine use of a single-shot, single-drug SAP regime at the two study sites facilitates the conduct of the proposed RCT. The results of the proposed RCT will have an important impact on current international guidelines for infection control strategies in the hospital. In addition, the results of this RCT are of significant interest for patient safety and healthcare economics.