FGFR1 amplifi cation and the progression of non-invasive to invasive breast cancer

The incidence of invasive breast cancer (IBC) can be dramatically reduced by improving our abilities to detect and treat ductal carcinoma in situ (DCIS). Progress will be based on a detailed understanding of molecular mechanisms responsible for tumor progression. An interesting study by Jang and colleagues evaluated and compared the frequency of amplification of four oncogenes (HER2, c-MYC, CCND1 and FGFR1) in large cohorts of pure DCIS, in the DCIS component of IBC, and in corresponding IBC. Of particular interest, they found a twofold increase in FGFR1 amplification in IBC versus pure DCIS, and significantly reduced disease-free survival in amplified versus unamplified IBC - leading the authors to conclude that FGFR1 plays an important role in the development and progression of IBC. These observations indeed provide hints that FGFR1 is important in this setting, although the issue is very complex and far from resolved

Spatial Imaging and Screening for Regime Shifts

Screening is a strategy for detecting undesirable change prior to manifestation of symptoms or adverse effects. Although the well-recognized utility of screening makes it commonplace in medicine, it has yet to be implemented in ecosystem management. Ecosystem management is in an era of diagnosis and treatment of undesirable change, and as a result, remains more reactive than proactive and unable to effectively deal with today’s plethora of non-stationary conditions. In this paper, we introduce spatial imaging-based screening to ecology. We link advancements in spatial resilience theory, data, and technological and computational capabilities and power to detect regime shifts (i.e., vegetation state transitions) that are known to be detrimental to human well-being and ecosystem service delivery. With a state-of-the-art landcover dataset and freely available, cloud-based, geospatial computing platform, we screen for spatial signals of the three most iconic vegetation transitions studied in western USA rangelands: (1) erosion and desertification; (2) woody encroachment; and (3) annual exotic grass invasion. For a series of locations that differ in ecological complexity and geographic extent, we answer the following questions: (1) Which regime shift is expected or of greatest concern? (2) Can we detect a signal associated with the expected regime shift? (3) If detected, is the signal transient or persistent over time? (4) If detected and persistent, is the transition signal stationary or non-stationary over time? (5) What other signals do we detect? Our approach reveals a powerful and flexible methodology, whereby professionals can use spatial imaging to verify the occurrence of alternative vegetation regimes, image the spatial boundaries separating regimes, track the magnitude and direction of regime shift signals, differentiate persistent and stationary transition signals that warrant continued screening from more concerning persistent and non-stationary transition signals, and leverage disciplinary strength and resources for more targeted diagnostic testing (e.g., inventory and monitoring) and treatment (e.g., management) of regime shifts. While the rapid screening approach used here can continue to be implemented and refined for rangelands, it has broader implications and can be adapted to other ecological systems to revolutionize the information space needed to better manage critical transitions in nature

Bison movements change with weather: Implications for their continued conservation in the Anthropocene

Animal movement patterns are affected by complex interactions between biotic and abiotic landscape conditions, and these patterns are being altered by weather variability associated with a changing climate. Some animals, like the American plains bison (Bison bison L.; hereafter, plains bison), are considered keystone species, thus their response to weather variability may alter ecosystem structure and biodiversity patterns. Many movement studies of plains bison and other ungulates have focused on point-pattern analyses (e.g., resource-selection) that have provided information about where these animals move, but information about when or why these animals move is limited. For example, information surrounding the influence of weather on plains bison movement in response to weather is limited but has important implications for their conservation in a changing climate. To explore how movement distance is affected by weather patterns and drought, we utilized 12-min GPS data from two of the largest plains bison herds in North America to model their response to weather and drought parameters using generalized additive mixed models. Distance moved was best predicted by air temperature, wind speed, and rainfall. However, air temperature best explained the variation in distance moved compared to any other single parameter we measured, predicting a 48% decrease in movement rates above 28°C. Moreover, severe drought (as indicated by 25-cm depth soil moisture) better predicted movement distance than moderate drought. The strong influence of weather and drought on plains bison movements observed in our study suggest that shifting climate and weather will likely affect plains bison movement patterns, further complicating conservation efforts for this wide-ranging keystone species. Moreover, changes in plains bison movement patterns may have cascading effects for grassland ecosystem structure, function, and biodiversity. Plains bison and grassland conservation efforts need to be proactive and adaptive when considering the implications of a changing climate on bison movement patterns

The origins of estrogen receptor alpha-positive and estrogen receptor alpha-negative human breast cancer

Current hormonal therapies have benefited millions of patients with breast cancer. Their success, however, is often temporary and limited to a subset of patients whose tumors express estrogen receptor alpha (ER). The therapies are entirely ineffective in ER-negative disease. Recent studies suggest that there are many biological pathways and alterations involved in determining whether ER is expressed and how it is regulated during breast cancer evolution. Improving hormonal therapies, in addition to perfecting current strategies, will also target these newly discovered pathways and alterations, and others yet to be found. The present commentary will briefly highlight a few important observations and unanswered questions regarding ER status and growth regulation during breast cancer evolution, which hopefully will help to stimulate new thinking and progress in this important area of medial research

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

Steroid receptor coactivator 2 is required for female fertility and mammary morphogenesis: insights from the mouse, relevance to the human

Although the importance of the progesterone receptor (PR) to female reproductive and mammary gland biology is firmly established, the coregulators selectively co-opted by PR in these systems have not been clearly delineated. A selective gene-knockout approach applied to the mouse, which abrogates gene function only in cell types that express PR, recently disclosed steroid receptor coactivator 2 (SRC-2, also known as TIF-2 or GRIP-1) to be an indispensable coregulator for uterine and mammary gland responses that require progesterone. Uterine cells positive for PR (but devoid of SRC-2) were found to be incapable of facilitating embryo implantation, a necessary first step toward the establishment of the materno-fetal interface. Importantly, such an implantation defect is not exhibited by knockouts for SRC-1 or SRC-3, underscoring the unique coregulator importance of SRC-2 in peri-implantation biology. Moreover, despite normal levels of PR, SRC-1 and SRC-3, progesterone-dependent branching morphogenesis and alveologenesis fails to occur in the murine mammary gland in the absence of SRC-2, thereby establishing a critical coregulator role for SRC-2 in signaling cascades that mediate progesterone-induced mammary epithelial proliferation. Finally, the recent detection of SRC-2 in the human endometrium and breast suggests that this coregulator may represent a new clinical target for the future management of female reproductive health and/or breast cancer

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

An intraductal human-in-mouse transplantation model mimics the subtypes of ductal carcinoma in situ

Introduction: Human models of noninvasive breast tumors are limited, and the existing in vivo models do not mimic inter- and intratumoral heterogeneity. Ductal carcinoma in situ (DCIS) is the most common type (80%) of noninvasive breast lesions. The aim of this study was to develop an in vivo model whereby the natural progression of human DCIS might be reproduced and studied. To accomplish this goal, the intraductal human-in-mouse (HIM) transplantation model was developed. The resulting models, which mimicked some of the diversity of human noninvasive breast cancers in vivo, were used to show whether subtypes of human DCIS might contain distinct subpopulations of tumor-initiating cells.Methods The intraductal models were established by injection of human DCIS cell lines (MCF10DCIS.COM and SUM-225), as well as cells derived from a primary human DCIS (FSK-H7), directly into the primary mouse mammary ducts via cleaved nipple. Six to eight weeks after injections, whole-mount, hematoxylin and eosin, and immunofluorescence staining were performed to evaluate the type and extent of growth of the DCIS-like lesions. To identify tumor-initiating cells, putative human breast stem/progenitor subpopulations were sorted from MCF10DCIS.COM and SUM-225 with flow cytometry, and their in vivo growth fractions were compared with the Fisher's Exact test. Results: Human DCIS cells initially grew within the mammary ducts, followed by progression to invasion in some cases into the stroma. The lesions were histologically almost identical to those of clinical human DCIS. This method was successful for growing DCIS cell lines (MCF10DCIS.COM and SUM-225) as well as a primary human DCIS (FSK-H7). MCF10DCIS.COM represented a basal-like DCIS model, whereas SUM-225 and FSK-H7 cells were models for HER-2[super]+ DCIS. With this approach, we showed that various subtypes of human DCIS appeared to contain distinct subpopulations of tumor-initiating cells. Conclusions: The intraductal HIM transplantation model provides an invaluable tool that mimics human breast heterogeneity at the noninvasive stages and allows the study of the distinct molecular and cellular mechanisms of breast cancer progression

Ki67 Proliferation Index as a Tool for Chemotherapy Decisions During and After Neoadjuvant Aromatase Inhibitor Treatment of Breast Cancer: Results From the American College of Surgeons Oncology Group Z1031 Trial (Alliance)

To determine the pathologic complete response (pCR) rate in estrogen receptor (ER) –positive primary breast cancer triaged to chemotherapy when the protein encoded by the MKI67 gene (Ki67) level was > 10% after 2 to 4 weeks of neoadjuvant aromatase inhibitor (AI) therapy. A second objective was to examine risk of relapse using the Ki67-based Preoperative Endocrine Prognostic Index (PEPI)