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Background: Bone metastatic prostate cancer (BMPCa), despite the initial responsiveness to androgen deprivation therapy (ADT), inevitably becomes resistant. Recent clinical trials with upfront treatment of ADT combined with chemotherapy or novel hormonal therapies (NHTs) have extended overall patient survival. These results indicate that there is significant potential for the optimization of standard-of-care therapies to delay the emergence of progressive metastatic disease. Methods: Here, we used data extracted from human bone metastatic biopsies pre- and post-abiraterone acetate/prednisone to generate a mathematical model of bone metastatic prostate cancer that can unravel the treatment impact on disease progression. Intra-tumor heterogeneity in regard to ADT and chemotherapy resistance was derived from biopsy data at a cellular level, permitting the model to track the dynamics of resistant phenotypes in response to treatment from biological first-principles without relying on data fitting. These cellular data were mathematically correlated with a clinical proxy for tumor burden, utilizing prostate-specific antigen (PSA) production as an example. Results: Using this correlation, our model recapitulated the individual patient response to applied treatments in a separate and independent cohort of patients (n = 24), and was able to estimate the initial resistance to the ADT of each patient. Combined with an intervention-decision algorithm informed by patient-specific prediction of initial resistance, we propose to optimize the sequence of treatments for each patient with the goal of delaying the evolution of resistant disease and limit cancer cell growth, offering evidence for an improvement against retrospective data. Conclusions: Our results show how minimal but widely available patient information can be used to model and track the progression of BMPCa in real time, offering a clinically relevant insight into the patient-specific evolutionary dynamics of the disease and suggesting new therapeutic options for intervention. Trial registration: NCT # 01953640. Funding: Funded by an NCI U01 (NCI) U01CA202958-01 and a Moffitt Team Science Award. CCL and DB were partly funded by an NCI PSON U01 (U01CA244101). AA was partly funded by a Department of Defense Prostate Cancer Research Program (W81XWH-15-1-0184) fellowship. LC was partly funded by a postdoctoral fellowship (PF-13-175-01-CSM) from the American Cancer Society.

ObjectivesTo quantify the bias of shear wave speed (SWS) measurements between different commercial ultrasonic shear elasticity systems and a magnetic resonance elastography (MRE) system in elastic and viscoelastic phantoms.MethodsTwo elastic phantoms, representing healthy through fibrotic liver, were measured with 5 different ultrasound platforms, and 3 viscoelastic phantoms, representing healthy through fibrotic liver tissue, were measured with 12 different ultrasound platforms. Measurements were performed with different systems at different sites, at 3 focal depths, and with different appraisers. The SWS bias across the systems was quantified as a function of the system, site, focal depth, and appraiser. A single MRE research system was also used to characterize these phantoms using discrete frequencies from 60 to 500 Hz.ResultsThe SWS from different systems had mean difference 95% confidence intervals of ±0.145 m/s (±9.6%) across both elastic phantoms and ± 0.340 m/s (±15.3%) across the viscoelastic phantoms. The focal depth and appraiser were less significant sources of SWS variability than the system and site. Magnetic resonance elastography best matched the ultrasonic SWS in the viscoelastic phantoms using a 140 Hz source but had a − 0.27 ± 0.027‐m/s (−12.2% ± 1.2%) bias when using the clinically implemented 60‐Hz vibration source.ConclusionsShear wave speed reconstruction across different manufacturer systems is more consistent in elastic than viscoelastic phantoms, with a mean difference bias of < ±10% in all cases. Magnetic resonance elastographic measurements in the elastic and viscoelastic phantoms best match the ultrasound systems with a 140‐Hz excitation but have a significant negative bias operating at 60 Hz. This study establishes a foundation for meaningful comparison of SWS measurements made with different platforms.

Summary: Breast implant–associated anaplastic large cell lymphoma (BIA-ALCL) is an emerging and highly treatable cancer of the immune system that can form around textured-surface breast implants. Although the underlying cause has yet to be elucidated, an emerging theme—linking pathogenesis to a chronic inflammatory state—continues to dominate the current literature. Specifically, the combination of increasing mutation burden and chronic inflammation leads to aberrant T-cell clonal expansion. However, the impetus remains largely unknown. Proposed mechanisms include a lipopolysaccharide endotoxin response, oncogenic transformation related to viral infection, associated trauma to the breast pocket, particulate matter digestion by capsular macrophages, chronic allergic inflammation, and genetic susceptibility. The Janus kinase–signal transducer and activator of transcription 3 (JAK-STAT3) pathway is a major signaling pathway that regulates a variety of intracellular growth and survival processes. Constitutive activation of JAK-STAT3 has been implicated in several malignancies, including lymphomas, and has recently been identified as a potential key mediator in BIA-ALCL. The purpose of this article is to review the cellular and molecular mechanisms of BIA-ALCL with a focus on the role of oncogenic JAK-STAT3 signaling in BIA-ALCL tumorigenesis and progression. Selected experimental work from the authors’ group on aberrant JAK-STAT3 signaling in BIA-ALCL is also included. The authors discuss how an inflammatory microenvironment may facilitate malignant transformation through the JAK-STAT3 pathway—highlighting its potential mechanistic role. The authors’ hope is that further investigation of this signaling pathway will reveal avenues for using JAK-STAT3 signaling as a prognostic indicator and novel therapeutic target in the case of advanced disease.

AbstractPopulation‐based genomic screening has the potential to improve health outcomes by identifying genetic causes of disease before they occur. While much attention has been paid to supporting the needs of the small percentage of patients who will receive a life‐altering positive genomic screening result that requires medical attention, little attention has been given to the communication of negative screening results. As there are currently no best practices for returning negative genomic screening results, we drew on experiences across the electronic medical records and genomics (eMERGE) III Network to highlight the diversity of reporting methods employed, challenges encountered in reporting negative test results, and “lessons learned” across institutions. A 60‐item survey that consisted of both multiple choice and open‐ended questions was created to gather data across institutions. Even though institutions independently developed procedures for reporting negative results, and had very different study populations, we identified several similarities of approach, including but not limited to: returning results by mail, placing results in the electronic health record via an automated process, reporting results to participants' primary care provider, and providing genetic counseling to interested patients at no cost. Differences in procedures for reporting negative results included: differences in terminology used to describe negative results, definitions of negative results, guidance regarding the meaning of negative results for participants and their family members, and recommendations for clinical follow up. Our findings highlight emerging practices for reporting negative genomic screening results and highlight the need to create patient education and clinical support tools for reporting negative screening results.

AbstractTumor‐infiltrating lymphocytes in colorectal cancer (CRC) predict better survival. However, associations between T‐lymphocyte count in histologically normal tissues from patients with CRC and survival remain uncertain. We examined associations of CD3+ T‐cells in colorectal tumor and histologically normal tissues with CRC‐specific and all‐cause mortality in the prospective Iowa Women's Health Study. Tissue microarrays were constructed using paraffin‐embedded colorectal tissue samples from 464 women with tumor tissues and 314 women with histologically normal tissues (55–69 years at baseline) diagnosed with incident CRC from 1986 to 2002 and followed through 2014 (median follow‐up 20.5 years). Three tumor and two histologically normal tissue cores for each patient were immunostained using CD3+ antibody and quantified, and the counts were averaged across the cores in each tissue. Cox proportional hazards regression estimated hazard ratios (HR) and 95% confidence interval (CI) for CRC‐specific and all‐cause mortality. After adjustment for age at diagnosis, body mass index, smoking status, tumor grade, and stage, HRs (95% CI) for the highest versus lowest tertile of tumor CD3+ score were 0.59 (0.38–0.89) for CRC‐specific mortality and 0.82 (0.63–1.05) for all‐cause mortality; for histologically normal CD3+ score, the corresponding HRs (95% CI) were 0.47 (0.19–1.17) and 0.50 (0.27–0.90), respectively. The CD3+ score combining the tumor and histologically normal scores was inversely associated with CRC‐specific and all‐cause mortality. Although the association between tumor CD3+ score and all‐cause mortality was not significant, both higher CD3+ T‐lymphocyte counts in tumor and histologically normal scores tended to be associated with lower CRC‐specific and all‐cause mortality.

The COVID-19 pandemic has accelerated many changes in medicine including the transition from providing care in person to providing care via technology enabled telemedicine. The benefits of telemedicine visits with a Pediatric Rehabilitation Medicine (PRM) provider, also known as telerehabilitation medicine visits, are numerous. Telerehabilitation medicine provides an opportunity to deliver timely, patient and family-centric rehabilitation care while maintaining physical distance and reducing potential COVID-19 exposure for our patients, their caregivers and medical providers. Telerehabilitation medicine also allows for access to PRM care in rural areas or areas without medical specialty, virtual in-home equipment evaluation, and reduced travel burden. Because of these and many other benefits, telerehabilitation medicine will likely become part of our ongoing model of care if barriers to telemedicine continue to be lowered or removed. This paper is intended to establish a foundation for pediatric telerehabilitation medicine visit efficiency and effectiveness in our current environment and into the future.

Abstract Cancer is a disease of aging and, as the world's population ages, the number of older persons with cancer is increasing and will make up a growing share of the oncology population in virtually every country. Despite this, older patients remain vastly underrepresented in research that sets the standards for cancer treatments. Consequently, most of what we know about cancer therapeutics is based on clinical trials conducted in younger, healthier patients, and effective strategies to improve clinical trial participation of older adults with cancer remain sparse. For this systematic review, the authors evaluated published studies regarding barriers to participation and interventions to improve participation of older adults in cancer trials. The quality of the available evidence was low and, despite a literature describing multifaceted barriers, only one intervention study aimed to increase enrollment of older adults in trials. The findings starkly amplify the paucity of evidence‐based, effective strategies to improve participation of this underrepresented population in cancer trials. Within these limitations, the authors provide their opinion on how the current cancer research infrastructure must be modified to accommodate the needs of older patients. Several underused solutions are offered to expand clinical trials to include older adults with cancer. However, as currently constructed, these recommendations alone will not solve the evidence gap in geriatric oncology, and efforts are needed to meet older and frail adults where they are by expanding clinical trials designed specifically for this population and leveraging real‐world data.