Assessment of body composition in breast cancer patients: concordance between transverse computed tomography analysis at the fourth thoracic and third lumbar vertebrae.

Introduction: Specific body composition markers derived from L3 axial computed tomography (CT) images predict clinical cancer outcomes, including chemotherapy toxicity and survival. However, this method is only applicable to those undergoing lumbar (L3) CT scanning, which is not universally conducted in early breast cancer cases. This study aimed to evaluate CT analysis at T4 as a feasible alternative marker of body composition in breast cancer. Method: All patients participated in the Investigating Outcomes from Breast Cancer: Correlating Genetic, Immunological, and Nutritional (BeGIN) Predictors observational cohort study (REC reference number: 14/EE/1297). Staging chest-abdomen-pelvic CT scan images from 24 women diagnosed with early breast cancer at University Hospital Southampton were analysed. Adipose tissue, skeletal muscle, and muscle attenuation were measured from the transverse CT slices' cross-sectional area (CSA) at T4 and L3. Adipose tissue and skeletal muscle area measurements were adjusted for height. Spearman's rank correlation coefficient analysis was used to determine concordance between body composition measurements using CT analysis at L3 and T4 regions. Results: Derived estimates for total adipose tissue, subcutaneous adipose tissue, and intramuscular adipose tissue mass following adjustment for height were highly concordant when determined from CSAs of CT slices at T4 and L3 (Rs = 0.821, p < 0.001; Rs = 0.816, p < 0.001; and Rs = 0.830, p < 0.001). In this cohort, visceral adipose tissue (VAT) and skeletal muscle estimates following height adjustment were less concordant when measured by CT at T4 and L3 (Rs = 0.477, p = 0.039 and Rs = 0.578, p = 0.003). The assessment of muscle attenuation was also highly concordant when measured by CT at T4 and L3 (Rs = 0.840, p < 0.001). Discussion: These results suggest that the CT analysis at T4 and L3 provides highly concordant markers for total adipose, subcutaneous adipose, and intramuscular adipose estimation, but not VAT, in this breast cancer population. High concordance between T4 and L3 was also found when assessing skeletal muscle attenuation. Lower concordance was observed for the estimates of skeletal muscle area, potentially explained by differences in the quantity and proportions of axial and appendicular muscle between the thorax and abdomen. Future studies will determine the value of T4 metrics as predictive tools for clinical outcomes in breast cancer.

Protein mimetic 2D FAST rescues alpha synuclein aggregation mediated early and post disease Parkinson's phenotypes.

Abberent protein-protein interactions potentiate many diseases and one example is the toxic, self-assembly of α-Synuclein in the dopaminergic neurons of patients with Parkinson's disease; therefore, a potential therapeutic strategy is the small molecule modulation of α-Synuclein aggregation. In this work, we develop an Oligopyridylamide based 2-dimensional Fragment-Assisted Structure-based Technique to identify antagonists of α-Synuclein aggregation. The technique utilizes a fragment-based screening of an extensive array of non-proteinogenic side chains in Oligopyridylamides, leading to the identification of NS132 as an antagonist of the multiple facets of α-Synuclein aggregation. We further identify a more cell permeable analog (NS163) without sacrificing activity. Oligopyridylamides rescue α-Synuclein aggregation mediated Parkinson's disease phenotypes in dopaminergic neurons in early and post disease Caenorhabditis elegans models. We forsee tremendous potential in our technique to identify lead therapeutics for Parkinson's disease and other diseases as it is expandable to other oligoamide scaffolds and a larger array of side chains.

Impact of Anti-Estrogen Therapy on Early Cardiovascular Referrals, Tests and Medications in Premenopausal Women with Operable Breast Cancer.

INTRODUCTION: Premenopausal women with high-risk hormone receptor (HR)-positive breast cancer often receive ovarian function suppression (OFS) and anti-estrogen therapy which induces near complete estrogen deprivation (NCED). This treatment improves recurrence-free survival but may increase cardiovascular risk. We sought to identify patterns of cardiovascular care and outcomes in premenopausal women with operable breast cancer. METHODS: Premenopausal women ≤ 50 years of age with stage I-III HR-positive or triple negative breast cancer (TNBC) were identified by retrospective review. We categorized women into 3 groups based on anti-estrogen therapy approach: NCED (HR + OFS), anti-estrogen therapy without OFS (HRnoOFS), and no anti-estrogen therapy (TNBC). Baseline characteristics, post-diagnosis cardiovascular events and cardiovascular actions (tests, referrals and medications) were recorded. Categorical variables were compared among the groups using chi-square and Fisher's exact tests; continuous outcomes were compared using ANOVA. RESULTS: 82, 83, and 52 women were identified in the HR + OFS, HRnoOFS, and TNBC groups respectively; mean follow-up was 5.0 years. Mean number of cardiovascular actions per year were highest in the HR + OFS group compared with HRnoOFS and TNBC groups (0.35 vs. 0.20 and 0.27, respectively; P = .036). The HR + OFS group had significantly more referrals and tests per year than the other groups. Cardiovascular medication initiation did not differ among groups. CONCLUSIONS: In this early follow-up period, there were meaningful numbers of cardiovascular actions, with women on NCED experiencing the most per year. Future work should seek to further understand the impact of anti-estrogen therapy on the cardiovascular health of premenopausal women and test strategies to mitigate cardiotoxicity.

Cardiovascular impact of near complete estrogen deprivation in premenopausal women with breast cancer: The CROWN study.

Survival with operable breast cancer has improved markedly in recent decades, however, treatment-related cardiovascular toxicities threaten to offset these gains. Ovarian function suppression paired with aromatase inhibition, for premenopausal women with hormone receptor (HR)-positive breast cancer, is a newer widely adopted therapy with the potential for significant long-term cardiovascular toxicity. Abrupt estrogen deprivation for non-cancer reasons is associated with accelerated coronary artery disease. Women with breast cancer treated with aromatase inhibition in addition to ovarian function suppression experience a dual hit with regards to estrogen exposure. The CaRdiac Outcomes With Near-complete estrogen deprivation (CROWN) study seeks to understand the early, subclinical natural history of cardiovascular compromise in young women undergoing near-complete estrogen deprivation (NCED) therapy. It is critical to understand the early subclinical development of cardiovascular disease to identify a window for therapeutic intervention before overt cardiovascular events occur. This three-site regional study (Atrium Health Wake Forest, Duke, and Virginia Commonwealth University) uses serial stress cardiac magnetic resonance (CMR) imaging and cardiac computed tomography angiography (CCTA) obtained during the initial two years of NCED therapy to study myocardial prefusion reserve (MPR), large cardiovascular vessel changes, left ventricular function, and other cardiovascular parameters. The CROWN cohort will consist of 90 premenopausal women with breast cancer, 67 with HR-positive disease receiving NCED and 23 comparators with HR-negative disease. Participants will undergo three annual CMR scans and 2 CCTA scans during the 2-year study period. After initial activation hurdles, accrual has been brisk, and the study is expected to complete accrual in December 2024. Efforts are in place to encourage participant retention with the study primary outcome, change in MPR between the two groups, to be reported in 2026 to 2027. The results of this study will enable premenopausal women with breast cancer to balance the health burdens of cancer at a young age and treatment-related cardiovascular morbidity. Finally, the tools developed here can be utilized to study cardiovascular risk across a range of cancer types and cancer therapies with the ultimate goals of both developing generalizable risk stratification tools as well as validating interventions which prevent overt cardiovascular compromise.

Characterizing breast cancer response to neoadjuvant therapy based on biophysical modeling and multiparametric magnetic resonance imaging data.

Personalized medicine efforts are focused on identifying biomarkers to guide individualizing neoadjuvant therapy regimens. In this work, we aim to validate a previously developed image data-driven mathematical modeling approach for dynamic characterization of breast cancer response to neoadjuvant therapy using a large, multi-site cohort. We retrospectively analyzed patients enrolled in the BMMR2 ACRIN 6698 subset at 10 institutions. Patients enrolled received four MRI examinations during neoadjuvant therapy with acquisitions at baseline (T 0 ), 3-weeks/early-treatment (T 1 ), 12-weeks/mid-treatment (T 2 ), and completion of therapy prior to surgery (T 3 ). A biophysical mathematical model of tumor growth is used extract metrics to characterize the dynamics of treatment response. Using predicted response at therapy conclusion and histogram summary metrics to quantify estimated tumor proliferation maps, we found univariate model-based metrics able to predict pathological response, with area under the receiver operating characteristic curve (AUC) ranging from 0.58 and 0.69 analyzing between T 0 and T 1 , and AUCs ranging from 0.72-0.76 analyzing between T 0 and T 2 . For hormone receptor (HR)-negative, human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients our model-based metrics achieved an AUC of 0.9 analyzing between T 0 and T 1 and AUC of 1.0 analyzing between T 0 and T 2 . This data shows the significant promise in developing these imaging-based biophysical mathematical modeling methods of dynamic characterization into a clinical decision support tool for individualizing treatment regimens based on patient-specific response.

Cultural and linguistic adaptation of a telephone-based cognitive-behavioral therapy (CBT) intervention to treat depression and anxiety in Hispanic cancer survivors.

PURPOSE/OBJECTIVES: The purpose of this study was to transcreate a manualized cognitive-behavioral therapy (CBT) intervention to address depression and anxiety among Hispanic cancer survivors. DESIGN/RESEARCH APPROACH: Stakeholders reviewed the CBT workbook for language, content, and cultural relevance. We designed semi-structured interview guides to elicit intervention feedback. SAMPLE/PARTICIPANTS: Stakeholder participants were Hispanic cancer survivors (n = 4), bilingual mental health providers (n = 2), and oncology professionals (n = 4). METHODS: Transcreation was conducted by initial translation of the workbook followed by incorporation of stakeholder feedback. A bilingual (Spanish and English) interviewer conducted stakeholder interviews. The study team discussed themes/suggestions before refining the workbook. FINDINGS: Stakeholders reported enthusiasm for the intervention. We gathered significant feedback regarding wording, images, and resources for the workbook. CONCLUSION: Development of culturally appropriate mental health resources for Hispanic cancer survivors is critical. IMPLICATIONS FOR PSYCHOSOCIAL PROVIDERS OR POLICY: By broadening research on psychosocial care to the Hispanic population, we increase the reach of evidence-based psychological care. Future research should fully evaluate the adapted CBT intervention among Hispanic survivors.

Myocardial Elasticity Imaging Correlates with Histopathology in a Model of Anthracycline-Induced Cardiotoxicity.

Background: There is considerable focus on developing strategies for identifying subclinical cardiac decline prior to cardiac failure. Myocardial tissue elasticity changes may precede irreversible cardiac damage, providing promise for an early biomarker for cardiac decline. Biomarker strategies are of particular interest in cardio-oncology due to cardiotoxic effects of anti-neoplastic therapies, particularly anthracycline-based chemotherapeutics. Current clinical methods for diagnosing cardiotoxicity are too coarse to identify cardiac decline early enough for meaningful therapeutic intervention, or too cumbersome for clinical implementation. Methods: Utilizing changes in myocardial elasticity as a biomarker for subclinical cardiac decline, we developed a biomechanical model-based elasticity imaging methodology (BEIM) to estimate spatial maps of left ventricle (LV) myocardial elasticity. In this study, we employ this methodology to assess changes in LV elasticity in a non-human primate model of doxorubicin-induced cardiotoxicity. Cardiac magnetic resonance imaging of five African Green monkeys was acquired at baseline prior to doxorubicin administration, 6-weeks, and 15-weeks after final doxorubicin dose and histopathological samples of the LV were taken at 15-weeks after final doxorubicin dose. Spatial elasticity maps of the mid-short axis plane of the LV were estimated at each image acquisition. Global and regional LV elasticity were calculated and changes between imaging time points was assessed. LV elasticity at baseline and final time point were compared to cardiomyocyte size and collagen volume fraction measurements calculated from histopathological staining of archived tissue bank samples and study endpoint tissue samples utilizing Pearson's correlation coefficients. Results: We identify significant changes in LV elasticity between each imaging time point both globally and regionally. We also demonstrate strong correlation between LV elasticity and cardiomyocyte size and collagen volume fraction measurements. Results indicate that LV elasticity estimates calculated using BEIM correlate with histopathological changes that occur due to doxorubicin administration, validating LV elasticity solutions and providing significant promise for use of BEIM to non-invasively elucidate cardiac injury. Conclusions: This methodology can show progressive changes in LV elasticity and has potential to be a more sensitive indicator of elasticity changes than current clinical measures of cardiotoxicity. LV elasticity may provide a valuable biomarker for cardiotoxic effects of anthracycline-based chemotherapeutics and cardiac disease detection.

Climate Change and Cancer Care-Feeling the Heat.

This Viewpoint describes how climate change and air pollution markedly affect cancer incidence, care delivery, and patient outcomes.

"Common-Precursor" Protein Mimetic Approach to Rescue Aß Aggregation-Mediated Alzheimer's Phenotypes.

Abberent protein-protein interactions (aPPIs) are associated with an array of pathological conditions, which make them important therapeutic targets. The aPPIs are mediated via specific chemical interactions that spread over a large and hydrophobic surface. Therefore, ligands that can complement the surface topography and chemical fingerprints could manipulate aPPIs. Oligopyridylamides (OPs) are synthetic protein mimetics that have been shown to manipulate aPPIs. However, the previous OP library used to disrupt these aPPIs was moderate in number (∼30 OPs) with very limited chemical diversity. The onus is on the laborious and time-consuming synthetic pathways with multiple chromatography steps. We have developed a novel chromatography-free technique to synthesize a highly diverse chemical library of OPs using a "common-precursor" approach. We significantly expanded the chemical diversity of OPs using a chromatography-free high-yielding method. To validate our novel approach, we have synthesized an OP with identical chemical diversity to a pre-existing OP-based potent inhibitor of Aß aggregation, a process central to Alzheimer's disease (AD). The newly synthesized OP ligand (RD242) was very potent in inhibiting Aß aggregation and rescuing AD phenotypes in an in vivo model. Moreover, RD242 was very effective in rescuing AD phenotypes in a post-disease onset AD model. We envision that our "common-precursor" synthetic approach will have tremendous potential as it is expandable for other oligoamide scaffolds to enhance affinity for disease-relevant targets.

Rare subtypes of triple negative breast cancer: Current understanding and future directions.

Rare subtypes of triple-negative breast cancers (TNBC) are a heterogenous group of tumors, comprising 5-10% of all TNBCs. Despite accounting for an absolute number of cases in aggregate approaching that of other less common, but well studied solid tumors, rare subtypes of triple-negative disease remain understudied. Low prevalence, diagnostic challenges and overlapping diagnoses have hindered consistent categorization of these breast cancers. Here we review epidemiology, histology and clinical and molecular characteristics of metaplastic, triple-negative lobular, apocrine, adenoid cystic, secretory and high-grade neuroendocrine TNBCs. Medullary pattern invasive ductal carcinoma no special type, which until recently was a considered a distinct subtype, is also discussed. With this background, we review how applying biological principals often applied to study TNBC no special type could improve our understanding of rare TNBCs. These could include the utilization of targeted molecular approaches or disease agnostic tools such as tumor mutational burden or germline mutation-directed treatments. Burgeoning data also suggest that pathologic response to neoadjuvant therapy and circulating tumor DNA have value in understanding rare subtypes of TNBC. Finally, we discuss a framework for advancing disease-specific knowledge in this space. While the conduct of randomized trials in rare TNBC subtypes has been challenging, re-envisioning trial design and technologic tools may offer new opportunities. These include embedding rare TNBC subtypes in umbrella studies of rare tumors, retrospective review of contemporary trials, prospective identification of patients with rare TNBC subtypes entering on clinical trials and querying big data for outcomes of patients with rare breast tumors.

Simultaneous Detection of Multiple Tumor-targeted Gold Nanoparticles in HER2-Positive Breast Tumors Using Optoacoustic Imaging.

Purpose To develop optoacoustic, spectrally distinct, actively targeted gold nanoparticle-based near-infrared probes (trastuzumab [TRA], TRA-Aurelia-1, and TRA-Aurelia-2) that can be individually identifiable at multispectral optoacoustic tomography (MSOT) of human epidermal growth factor receptor 2 (HER2)-positive breast tumors. Materials and Methods Gold nanoparticle-based near-infrared probes (Aurelia-1 and 2) that are optoacoustically active and spectrally distinct for simultaneous MSOT imaging were synthesized and conjugated to TRA to produce TRA-Aurelia-1 and 2. Freshly resected human HER2-positive (n = 6) and HER2-negative (n = 6) triple-negative breast cancer tumors were treated with TRA-Aurelia-1 and TRA-Aurelia-2 for 2 hours and imaged with MSOT. HER2-expressing DY36T2Q cells and HER2-negative MDA-MB-231 cells were implanted orthotopically into mice (n = 5). MSOT imaging was performed 6 hours following the injection, and the Friedman test was used for analysis. Results TRA-Aurelia-1 (absorption peak, 780 nm) and TRA-Aurelia-2 (absorption peak, 720 nm) were spectrally distinct. HER2-positive human breast tumors exhibited a significant increase in optoacoustic signal following TRA-Aurelia-1 (28.8-fold) or 2 (29.5-fold) (P = .002) treatment relative to HER2-negative tumors. Treatment with TRA-Aurelia-1 and 2 increased optoacoustic signals in DY36T2Q tumors relative to those in MDA-MB-231 controls (14.8-fold, P < .001; 20.8-fold, P < .001, respectively). Conclusion The study demonstrates that TRA-Aurelia 1 and 2 nanoparticles operate as a spectrally distinct HER2 breast tumor-targeted in vivo optoacoustic agent. Keywords: Molecular Imaging, Nanoparticles, Photoacoustic Imaging, Breast Cancer Supplemental material is available for this article. © RSNA, 2023.

Metaplastic Breast Cancer: Current Understanding and Future Directions.

Metaplastic breast cancers (MBC) encompass a group of highly heterogeneous tumors which share the ability to differentiate into squamous, mesenchymal or neuroectodermal components. While often termed rare breast tumors, given the relatively high prevalence of breast cancer, they are seen with some frequency. Depending upon the definition applied, MBC represents 0.2% to 1% of breast cancers diagnosed in the United States. Less is known about the epidemiology of MBC globally, though a growing number of reports are providing information on this. These tumors are often more advanced at presentation relative to breast cancer broadly. While more indolent subtypes exist, the majority of MBC subtypes are associated with inferior survival. MBC is most commonly of triple-negative phenotype. In less common hormone receptor positive MBCs, hormone receptor status appears not to be prognostic. In contrast, relatively rare HER2-positive MBCs are associated with superior outcomes. Multiple potentially targetable molecular features are overrepresented in MBC including DNA repair deficiency signatures and PIK3/AKT/mTOR and WNT pathways alterations. Data on the prevalence of targets for novel antibody-drug conjugates is also emerging. While chemotherapy appears to be less active in MBC than in other breast cancer subtypes, efficacy is seen in some MBCs. Disease-specific trials, as well as reports of exceptional responses, may provide clues for novel approaches to this often hard-to-treat breast cancer. Strategies which harness newer research tools, such as large data and artificial intelligence hold the promise of overcoming historic barriers to the study of uncommon tumors and could markedly advance disease-specific understanding in MBC.

Prediction of Postoperative Day 1 Hemoglobin Level after Cesarean Delivery.

OBJECTIVE: To create a prediction model for postoperative hemoglobin levels after cesarean delivery, which could reduce routine use of postoperative laboratory test. STUDY DESIGN: This was a secondary analysis of a retrospective cohort study of all women who underwent cesarean delivery (primary or repeat) at or more than 23 weeks' gestation at a single academic center. The cohort was randomly divided into a training cohort to develop a prediction model and a validation cohort to test the model in a 2:1 ratio. Variables with p-value <0.10 were considered for the mixed multivariable linear regression model in a backward stepwise fashion. We obtained the best cut-off point of the predicted hemoglobin level to detect severe anemia (postoperative hemoglobin level less than 7.0 g/dL) in the training cohort. A receiver operating characteristic curve with the area under a curve was created. We calculated the sensitivity and specificity of the model in the validation cohort using the best cut-off point obtained in the training cohort as well as postoperative hemoglobin of 10.0 g/dL. RESULTS: Of 2,930 women, 1,954 (66.6%) and 976 (33.3%) were randomly allocated to training and validation cohorts. The final model included preoperative hemoglobin level, preoperative platelet level, quantitative blood loss, height, weight, magnesium administration, labor, and general anesthesia. The best cut-off to predict severe anemia was predicted hemoglobin level of 8.57 g/dL in the training cohort. Using this cut-off, the sensitivity and specificity in the validation cohort were 77% (95% confidence interval [CI]: 56-91%) and 87% (95% CI: 85-89%), respectively. The use of postpartum hemorrhage yielded the sensitivity of 58% (95% CI: 37-77%) and specificity 79% (95% CI: 76-81%), respectively. CONCLUSION: We developed a validated model to predict the postoperative day 1 hemoglobin levels after cesarean delivery that could assist with identifying women who may not need postoperative laboratory tests. KEY POINTS: · Postoperative laboratory tests are routine.. · A prediction model may allow reduce routine tests.. · We developed an accurate mathematical model..

Expanding access to early phase trials: the CATCH-UP.2020 experience.

BACKGROUND: Disparities in cancer outcomes persist for underserved populations; one important aspect of this is limited access to promising early phase clinical trials. To address this, the National Cancer Institute-funded Create Access to Targeted Cancer Therapy for Underserved Populations (CATCH-UP.2020) was created. We report the tools developed and accrual metrics of the initial year of CATCH-UP.2020 with a focus on racial, ethnic, geographic, and socioeconomically underserved populations. METHODS: CATCH-UP.2020 is a P30 supplement awarded to 8 National Cancer Institute-designated cancer centers with existing resources to rapidly open and accrue to Experimental Therapeutics Clinical Trials Network (ETCTN) trials with emphasis on engaging patients from underserved populations. Sites used patient-based, community-based, investigator-based, and program-based tools to meet specific program goals. RESULTS: From September 2020 to August 2021, CATCH-UP.2020 sites opened 45 ETCTN trials. Weighted average trial activation time for the 7 sites reporting this was 107 days. In the initial year, sites enrolled 145 patients in CATCH-UP.2020 with 68 (46.9%) representing racial, ethnic, rural, and socioeconomically underserved populations using the broader definition of underserved encompassed in the grant charge. During the initial year of CATCH-UP.2020, a time impacted by the COVID-19 pandemic, 15.8% (66 of 417) and 21.4% (31 of 145) of patients enrolled to ETCTN trials at network and at CATCH-UP sites, respectively, were from racial and ethnic minority groups, a more limited definition of underserved for which comparable data are available. CONCLUSION: Targeted funding accelerated activation and accrual of early phase trials and expanded access to this therapeutic option for underserved populations.

Reproducibility assessment of a biomechanical model-based elasticity imaging method for identifying changes in left ventricular mechanical stiffness.

Purpose: Cardiotoxicity of antineoplastic therapies is increasingly a risk to cancer patients treated with curative intent with years of life to protect. Studies highlight the importance of identifying early cardiac decline in cancer patients undergoing cardiotoxic therapies. Accurate tools to study this are a critical clinical need. Current and emerging methods for assessing cardiotoxicity are too coarse for identifying preclinical cardiac degradation or too cumbersome for clinical implementation. Approach: In the previous work, we developed a noninvasive biomechanical model-based elasticity imaging methodology (BEIM) to assess mechanical stiffness changes of the left ventricle (LV) based on routine cine cardiac magnetic resonance (CMR) images. We examine this methodology to assess methodological reproducibility. We assessed a cohort of 10 participants that underwent test/retest short-axis CMR imaging at baseline and follow-up sessions as part of a previous publicly available study. We compare test images to retest images acquired within the same session to assess within-session reproducibility. We also compare test and retest images acquired at the baseline imaging session to test and retest images acquired at the follow-up imaging session to assess between-session reproducibility. Results: We establish the within-session and between-session reproducibility of our method, with global elasticity demonstrating repeatability within a range previously demonstrated in cardiac strain imaging studies. We demonstrate increased repeatability of global elasticity compared to segmental elasticity for both within-session and between-session. Within-subject coefficients of variation for within-session test/retest images globally for all modulus directions and a mechanical fractional mechanical stiffness anisotropy metric ranged from 11% to 28%. Conclusions: Results suggest that our methodology can reproducibly generate estimates of relative mechanical elasticity of the LV and provides a threshold for distinguishing true changes in myocardial mechanical stiffness from experimental variation. BEIM has applications in identifying preclinical cardiotoxicity in breast cancer patients undergoing antineoplastic therapies.

An FDA-Approved Antifungal, Ketoconazole, and Its Novel Derivative Suppress tGLI1-Mediated Breast Cancer Brain Metastasis by Inhibiting the DNA-Binding Activity of Brain Metastasis-Promoting Transcription Factor tGLI1.

The goal of this study is to identify pharmacological inhibitors that target a recently identified novel mediator of breast cancer brain metastasis (BCBM), truncated glioma-associated oncogene homolog 1 (tGLI1). Inhibitors of tGLI1 are not yet available. To identify compounds that selectively kill tGLI1-expressing breast cancer, we screened 1527 compounds using two sets of isogenic breast cancer and brain-tropic breast cancer cell lines engineered to stably express the control, GLI1, or tGLI1 vector, and identified the FDA-approved antifungal ketoconazole (KCZ) to selectively target tGLI1-positive breast cancer cells and breast cancer stem cells, but not tGLI1-negative breast cancer and normal cells. KCZ's effects are dependent on tGLI1. Two experimental mouse metastasis studies have demonstrated that systemic KCZ administration prevented the preferential brain metastasis of tGLI1-positive breast cancer and suppressed the progression of established tGLI1-positive BCBM without liver toxicities. We further developed six KCZ derivatives, two of which (KCZ-5 and KCZ-7) retained tGLI1-selectivity in vitro. KCZ-7 exhibited higher blood-brain barrier penetration than KCZ/KCZ-5 and more effectively reduced the BCBM frequency. In contrast, itraconazole, another FDA-approved antifungal, failed to suppress BCBM. The mechanistic studies suggest that KCZ and KCZ-7 inhibit tGLI1's ability to bind to DNA, activate its target stemness genes Nanog and OCT4, and promote tumor proliferation and angiogenesis. Our study establishes the rationale for using KCZ and KCZ-7 for treating and preventing BCBM and identifies their mechanism of action.

Creating and Implementing a Principal Investigator Tool Kit for Enhancing Accrual to Late Phase Clinical Trials: Development and Usability Study.

BACKGROUND: Accrual to oncology clinical trials remains a challenge, particularly during the COVID-19 pandemic. For late phase clinical trials funded by the National Cancer Institute, the development of these research protocols is a resource-intensive process; however, mechanisms to optimize patient accrual after trial activation are underdeveloped across the National Clinical Trial Network (NCTN). Low patient accrual can lead to the premature closure of clinical trials and can ultimately delay the availability of new, potentially life-saving therapies in oncology. OBJECTIVE: The purpose of this study is to formally create an easily implemented tool kit of resources for investigators of oncology clinical trials within the NCTN, specifically the NRG Oncology cooperative group, in order to optimize patient accrual. METHODS: NRG Oncology sought to formally develop a tool kit of resources to use at specific time points during the lifetime of NRG Oncology clinical trials. The tools are clearly described and involve the facilitation of engagement of the study principal investigator with the scientific and patient advocate community during the planning, activation, and accrual periods. Social media tools are also leveraged to enhance such engagement. The principal investigator (PI) tool kit was created in 2019 and thereafter piloted with the NRG Oncology/Alliance NRG-LU005 phase II or III trial in small-cell lung cancer. The PI tool kit was developed by the NRG Oncology Protocol Operations Management committee and was tested with the NRG/Alliance LU005 randomized trial within the NCTN. RESULTS: NRG Oncology/Alliance NRG-LU005 has seen robust enrollment, currently 127% of the projected accrual. Importantly, many of the tool kit elements are already being used in ongoing NRG Oncology trials, with 56% of active NRG trials using at least one element of the PI tool kit and all in-development trials offered the resource. This underscores the feasibility and potential benefits of deploying the PI tool kit across all NRG Oncology trials moving forward. CONCLUSIONS: While clinical trial accrual can be challenging, the PI tool kit has been shown to augment accrual in a low-cost and easily implementable fashion. It could be widely and consistently deployed across the NCTN to improve accrual in oncology clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT03811002; https://clinicaltrials.gov/ct2/show/NCT03811002.

Dynamic characterization of breast cancer response to neoadjuvant therapy using biophysical metrics of spatial proliferation.

Current tools to assess breast cancer response to neoadjuvant chemotherapy cannot reliably predict disease eradication, which if possible, could allow early cessation of therapy. In this work, we assessed the ability of an image data-driven mathematical modeling approach for dynamic characterization of breast cancer response to neoadjuvant therapy. We retrospectively analyzed patients enrolled in the I-SPY 2 TRIAL at the Atrium Health Wake Forest Baptist Comprehensive Cancer Center. Patients enrolled on the study received four MR imaging examinations during neoadjuvant therapy with acquisitions at baseline (T0), 3-weeks/early-treatment (T1), 12-weeks/mid-treatment (T2), and completion of therapy prior to surgery (T3). We use a biophysical mathematical model of tumor growth to generate spatial estimates of tumor proliferation to characterize the dynamics of treatment response. Using histogram summary metrics to quantify estimated tumor proliferation maps, we found strong correlation of mathematical model-estimated tumor proliferation with residual cancer burden, with Pearson correlation coefficients ranging from 0.88 and 0.97 between T0 and T2, representing a significant improvement from conventional assessment methods of change in mean apparent diffusion coefficient and functional tumor volume. This data shows the significant promise of imaging-based biophysical mathematical modeling methods for dynamic characterization of patient-specific response to neoadjuvant therapy with correlation to residual disease outcomes.