Spatial Heterogeneity Research Articles

[18F]AlF-NOTA-PCP2: a novel PET/CT tracer for enhanced PD-L1 heterogeneity imaging and comparative analysis with [18F]AlF-NOTA-WL12 in glioblastoma xenografts.

The unsatisfactory efficacy of PD-L1 antibodies in glioblastoma (GBM) is largely due to the temporal and spatial heterogeneity of PD-L1 expression. Molecular imaging can enhance understanding of the tumor immune microenvironment and guide immunotherapy. However, highly sensitive imaging agents capable of effectively visualizing PD-L1 heterogeneity are limited. This study introduces a novel PET tracer, offering improved imaging of PD-L1 heterogeneity in GBM xenografts, with a comparative analysis to [18F]AlF-NOTA-WL12. [18F]AlF-NOTA-PCP2 was synthesized with high purity and its affinity for PD-L1 was characterized using surface plasmon resonance (SPR) and cell binding assays. Its specificity for PD-L1 was evaluated both in vitro using various cell lines and in vivo with GBM xenograft models in NOD/SCID mice. PET/CT imaging was conducted to evaluate the tracer's biodistribution, pharmacokinetics, and ability to quantify tumoral spatial heterogeneity of PD-L1 expression. A focused comparative analysis between [18F]AlF-NOTA-PCP2 and [18F]AlF-NOTA-WL12 was conducted, examining binding affinity, biodistribution, pharmacokinetics, and imaging effectiveness in GBM xenografts. Additionally, human radiation dosimetry estimates compared the safety profiles of both tracers. [18F]AlF-NOTA-PCP2 demonstrated high radiochemical purity (> 95%) and a strong affinity for PD-L1, comparable to [18F]AlF-NOTA-WL12. In vitro and in vivo studies confirmed its specificity for PD-L1, with increased uptake in PD-L1 expressing cells and tumors. Toxicological profiles indicated no significant abnormalities in serum biochemical indicators or major organ tissues. MicroPET/CT imaging showed [18F]AlF-NOTA-PCP2's effectiveness in visualizing PD-L1 expression levels and spatial heterogeneity in GBM xenografts. Comparative studies revealed [18F]AlF-NOTA-PCP2's improved pharmacokinetic properties, including higher tumor-to-blood ratios and lower nonspecific liver uptake, as well as reduced radiation exposure compared to [18F]AlF-NOTA-WL12. [18F]AlF-NOTA-PCP2 distinguishes itself as an exceptionally sensitive PET/CT tracer, adept at non-invasively and accurately quantifying PD-L1 expression and its spatial heterogeneity in tumors, especially in GBM. Its favorable pharmacokinetic properties, safety profile, and high affinity for PD-L1 highlight its potential for enhancing the precision of cancer immunotherapy and guiding individualized treatment strategies. While promising, its clinical translation, especially in brain imaging, necessitates further validation in clinical trials.

Assessing spatiotemporal risks of nonpoint source pollution via soil erosion: a coastal case in the Yellow River Delta, China.

Nonpoint source pollution (NPSP) has always been the dominant threat to regional waters. Based on empirical models of the revised universal soil loss equation and the phosphorus index, an NPSP risk assessment model denoted as SL-NPSRI was developed. The surface soil pollutant loss was estimated by simulating the rain-runoff topographic process, and the influence of path attenuation was quantified. A case study in the Yellow River Delta and corresponding field surveys of soil pollutants and water quality showed that the established model can be applied to evaluate the spatial heterogeneity of NPSP. NPSP usually occurs during high-intensity rainfall periods and in larger estuaries. Summer rainfall increased pollutant transport into the sea from late July to mid-August and caused estuarine dilution. Higher NPSP risks often correspond to coastal areas with lower vegetation coverage, higher soil erodibility, and higher soil pollutant concentrations. Agricultural NPSP originating from cropland significantly increase the pollutant fluxes. Therefore, area-specific land use management and vegetation coverage improvement, and temporal-specific strategies can be explored for NPSP control during source-transport hydrological processes. This research provides a novel insight for coastal NPSP simulations by comprehensively analyzing the soil erosion process and its associated pollutant loss effects, which can be useful for targeted spatiotemporal solutions.

Deciphering spatial heterogeneity of maritime accidents considering impact scale variations

ABSTRACT Ensuring maritime safety has ascended as a preeminent concern within the global maritime sector. Understanding how factors affect maritime accidents’ consequences in different water areas would be of great benefit to preventing the occurrence or reducing the consequences. This study thus employed a multi-scale geographically weighted regression (MGWR) model on the accident dataset from Fujian waters in the East China Sea, to quantify the influences of different factors as well as the spatial heterogeneity in the effects of key factors on maritime accident consequence. The performances of MGWR are compared with multiple linear regression (MLR) and GWR. As expected, MGWR outperforms the other two models in terms of its ability to clearly capture the unobserved spatial heterogeneity in the effects of factors. Results reveal notably distinct influences of some factors on maritime accident consequences in different locations. An intuitive indication by MGWR is that approximately 50% of the accidents present positive coefficients of good visibility while other locations are negative, which are failed to recognize by MLR. The outcomes provide insights for making appropriate safety countermeasures and policies customized for different water areas.

A high-frequency digital economy index: text analysis and factor analysis based on big data

ABSTRACT We propose a high-frequency digital economy index by combining official white papers and big data. It aims to resolve the discrepancy between the new economic reality and old economic indicators used by decision-makers and policymakers. We have demonstrated a significant effect due to keyword rotations on the indices. Further analysis of the Dagum-Gini coefficient shows that spatial heterogeneity and temporal variation of the digital economy indices can be mainly attributed to between-group inequality.

Ecological impact of a generalist invader in the aquatic food web is mediated by environmental context

Abstract Freshwater ecosystems are threatened by the introduction of invasive species. Generalist invaders often compete with native species for shared resources, resulting in possible native species niche displacement. However, environmental heterogeneity may modulate the level of individual specialisation in invasive species, altering the outcome of interspecific competition between invasive and native species. The objectives of our study were to (1) evaluate the environmental context of dietary specialisation and trophic position of an invasive species according to the Environmental Matching Hypothesis (EMH), and (2) consider how the environmental context of invasive species dietary resource use may influence the dietary niche of native species competing for similar resources. Resource use, trophic position and dietary niche were determined using gut content and stable isotope analyses for the invasive round goby (Negobius melanostomus) and the native yellow perch (Perca flavescens), along environmental gradients in an invaded fluvial ecosystem. Our results were in support of EMH for the invader diet and resource specialisation, but not trophic position. Under environmental conditions of high water‐conductivity, round gobies were generalists feeding mostly on pelagic prey. Under more challenging environmental conditions of low water‐conductivity, the invader specialised on preferred high‐quality benthic prey. The ecological impact of the round goby was greatest at low water‐conductivity sites where the invader was a benthic specialist; there was a greater relative dietary niche overlap between the invader and the native species. Our study uniquely illustrates how invasive species’ resource specialisation can be modulated by spatial environmental heterogeneity within ecosystems, and how this can subsequently alter the ecological impact of the invader on native species in aquatic food webs.

Complex environmental control of growth in a dominant Mediterranean‐alpine shrub species

Abstract Mediterranean‐alpine plants are exposed to harsh conditions, forcing them to perform with well‐adapted physiological strategies to withstand the dual stressors that arise from winter cold and summer drought. Such growth strategies are not yet fully understood, although they gain importance with regard to the resilience of species in the face of ongoing climate variability. Here, we aimed at understanding shrub growth in a widespread Mediterranean‐alpine species, Cytisus galianoi Talavera & Gibbs. Using long‐term time series of stem diameter change obtained from dendrometer measurements across the species´ range, we were able to characterise its spatiotemporal growth plasticity. Furthermore, separating water‐related fluctuations in stem diameter from irreversible stem increment allowed us to disentangle the species´ seasonal growth patterns. Using fine‐scale measurements of on‐site environmental conditions, we were then able to identify micro‐ecological drivers controlling the species´ growth processes by applying correlation analysis and partial least squares regressions. We show the species´ adaptation to the spatial heterogeneity across its range for the first time. Our findings highlight that the combination of bimodality and overall high growth plasticity likely allows the species to cover a wide geographical range across alpine areas and over a wide range of weather conditions. We show the environmental control of bimodal growth in C. galianoi, and the importance of pre‐growth environmental control, leading to pronounced carry‐over effects. These lead to a major advantage in resisting adverse growth conditions and adapting to changing conditions. Synthesis: Overall, our findings improve the understanding of the species´ ecological niche and show that preceding photosynthetic activity helps C. galianoi to perform even under unfavourable conditions in winter and during the active growth phase, challenging the general assumption on the coupling of growth to specific seasons and suggesting that the species is capable of adapting to future climate variability.

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis.

Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and education, the collective contribution of these elements, as manifestations of structural racism, has been less explored. Milwaukee County, Wisconsin, with its racial and socioeconomic diversity, provides a unique context for this multifactorial investigation. This research aimed to delineate the association between structural racism and mental health disparities in Milwaukee County, using a combination of geospatial and deep learning techniques. We used secondary data sets where all data were aggregated and anonymized before being released by federal agencies. We compiled 217 georeferenced explanatory variables across domains, initially deliberately excluding race-based factors to focus on nonracial determinants. This approach was designed to reveal the underlying patterns of risk factors contributing to poor mental health, subsequently reintegrating race to assess the effects of racism quantitatively. The variable selection combined tree-based methods (random forest) and conventional techniques, supported by variance inflation factor and Pearson correlation analysis for multicollinearity mitigation. The geographically weighted random forest model was used to investigate spatial heterogeneity and dependence. Self-organizing maps, combined with K-means clustering, were used to analyze data from Milwaukee communities, focusing on quantifying the impact of structural racism on the prevalence of poor mental health. While 12 influential factors collectively accounted for 95.11% of the variability in mental health across communities, the top 6 factors-smoking, poverty, insufficient sleep, lack of health insurance, employment, and age-were particularly impactful. Predominantly, African American neighborhoods were disproportionately affected, which is 2.23 times more likely to encounter high-risk clusters for poor mental health. The findings demonstrate that structural racism shapes mental health disparities, with Black community members disproportionately impacted. The multifaceted methodological approach underscores the value of integrating geospatial analysis and deep learning to understand complex social determinants of mental health. These insights highlight the need for targeted interventions, addressing both individual and systemic factors to mitigate mental health disparities rooted in structural racism.

Stability analysis of a delayed SEIRQ epidemic model with diffusion

In this paper, we investigate the effect of spatial diffusion and delay on the dynamical behavior of the SEIRQ epidemic model. The introduction of the delay in this model makes it more realistic and modelizes the latency period. In addition, the consideration of an SEIRQ model with diffusion aims to better understand the impact of the spatial heterogeneity of the environment and the movement of individuals on the persistence and extinction of disease. First, we determined a threshold value $R_0$ of the delayed SEIRQ model with diffusion. Next, By using the theory of partial functional differential equations, we have shown that the unique disease-free equilibrium is asymptotically stable , what is proven by the numericals scchema. Moreover,we search under their condition the endemic equilibrium is asymptotically stable .

Abstract PO2-13-03: Spatial HER2 heterogeneity on HER2-PET in HER2-low and negative disease: potential biomarker for antibody-drug conjugate effect

Abstract Background: Anti-HER2 antibody drug conjugates (ADCs) can assert an effect in part of patients with HER2-low breast cancer. In light of patient burden and financial sustainability, biomarkers to select responding patients are urgently needed, but so far, none have been identified. In the IMPACT trial (NCT01957332), patients with newly diagnosed and non-rapidly progressive metastatic breast cancer (MBC) of all subtypes (including HER2-negative, -low, and –positive disease) were included. We assessed the performance of Zirconium-89 (89Zr)-trastuzumab positron emission tomography (HER2-PET) in HER2-low and negative MBC. Methods: All patients received extensive workup, including a metastasis biopsy and HER2-PET at baseline. HER2 status was determined by immunohistochemistry (IHC) and in situ hybridization. ⁸⁹Zr-trastuzumab uptake was quantified as maximum and mean standardized uptake values (SUVmax, SUVmean) in metastases and healthy background tissue. Quantitative ⁸⁹Zr-trastuzumab uptake of all metastases and corresponding biopsied metastasis, was related to HER2 IHC status. Results: In 200 patients, ⁸⁹Zr-trastuzumab uptake was quantified in 5,163 metastases. With increasing HER2 IHC status, uptake was higher (geometric mean SUVmax 7.0, 7.6, 7.3, and 17.4 with HER2 IHC 0, 1, 2, or 3+, in respectively 71, 71, 20, and 24 biopsied metastases (P  0.001 between IHC 0 and 3+). SUVmax in lesions was heterogeneous within and between patients for all HER2 IHC groups. All HER2 IHC groups, also HER2-negative and -low, had uptake exceeding that of the healthy background (geometric mean tumor-to-background ratio SUVmax >1 in all groups, increasing with higher HER2 IHC). Of patients with a HER2 IHC 0 biopsy, 27.8% had at least one metastasis elsewhere in the body, with uptake exceeding the overall 90th SUVmax percentile of 14.6; in HER2 low IHC1+ and 2+, this was 31.9% and 30%. Conclusions: In this largest series with HER2-PET in patients with MBC, we show that ±30% of patients with HER2-low or -negative IHC in the biopsy, in fact, have metastases with high HER2 uptake elsewhere in the body. This spatial heterogeneity provides novel insights into HER2-negative and -low disease compared to standard HER2 IHC of a single biopsy. As HER2-PET uptake is related to ADC response in HER2 positive MBC1, HER2-PET is a potential biomarker for anti-HER2 ADC effect in HER2-low and -negative MBC as well. Reference: 1. Gebhart G, et al. Ann Oncol 2016;27(4): 619-624. Supported by the Dutch Cancer Society grant 2012-5565 Citation Format: Carolien Schroder, Jasper van Geel, Bertha Eisses, Adrienne Brouwers, Sjoerd Elias, Frederike Bensch, Evelien Kuip, Agnes Jager, Andor Glaudemans, Bert van der Vegt, Willemien Menke-van der Houven van Oordt, Elisabeth de Vries. Spatial HER2 heterogeneity on HER2-PET in HER2-low and negative disease: potential biomarker for antibody-drug conjugate effect [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-13-03.

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.

GWmodelS: a standalone software to train geographically weighted models

ABSTRACT With the recent increase in studies on spatial heterogeneity, geographically weighted (GW) models have become an essential set of local techniques, attracting a wide range of users from different domains. In this study, we demonstrate a newly developed standalone GW software, GWmodelS using a community-level house price data set for Wuhan, China. In detail, a number of fundamental GW models are illustrated, including GW descriptive statistics, basic and multiscale GW regression, and GW principle component analysis. Additionally, functionality in spatial data management and batch mapping are presented as essential supplementary activities for GW modeling. The software provides significant advantages in terms of a user-friendly graphical user interface, operational efficiency, and accessibility, which facilitate its usage for users from a wide range of domains.

Abstract PS05-04: [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity

Abstract Introduction: Molecular imaging of human epidermal receptor 2 (HER2) aims to overcome limitations of traditional HER2 assessment through biopsy, including invasiveness and inability to detect intra and inter-tumoral spatial heterogeneity. Prior human studies suggest that [89Zr]Trastuzumab-positron emission tomography (PET) imaging can effectively differentiate HER2 lesions (Dehdashti et al, Breast Cancer Res. Treat. 2018). Commonly, CT complements PET for anatomical reference, however, integrating MRI enables the sensitivity of soft-tissue contrast required for anatomic and morphological breast imaging and can provide for quantitative multiparametric characterization. Diffusion weighted-MRI (DW-MRI) contributes to tumor characterization by assessing intratumoral cellularity via the apparent diffusion coefficient (ADC), and can be combined with molecular expression from HER2-PET. We present preliminary results in 13 patients with HER2 PET/MRI to define tumor and normal tissue imaging metrics. Methods: A phase II clinical trial assessing the feasibility of [89Zr]trastuzumab-PET with simultaneous quantitative DW-MRI to enhance understanding of tumor heterogeneity in patients with HER2-positive metastatic breast cancer. 13 patients (ages 40-70; mean 60) with HER2-positive breast cancer based on prior biopsy underwent whole-body [89Zr]trastuzumab-PET/MR imaging (5 ± 1 days post-injection of radiopharmaceutical) during the course of HER2-directed therapy. Normal organ and tumor regions of interest (ROI) were identified on concurrently acquired whole-body T1-weighted MRI for ADC (cellularity) and standardized uptake value (SUV, PET uptake) mean quantification. Tumor presence was confirmed via bone scintigraphy, FDG-PET/CT, or contrast-enhanced MRI. Non-parametric T-tests compared lesions to normal organs. Lesions greater than 30 mm in diameter underwent multiparametric intratumoral habitat analysis. Using the median HER2 values, tumors were evaluated for heterogeneity of high and low HER2 expression in conjunction with ADC. Long-term treatment response evaluation is ongoing. Results: Mean [89Zr]trastuzumab uptake, SUV, and ADC values for normal tissue were summarized in Table 1. All tumors demonstrated higher overall uptake of [89Zr]trastuzumab (bone: p=0.019, brain: p=0.014, breast: p=0.069, juxtapulmonary: p=0.026) and increased ADCmean values (bone: p=0.002, brain: p=0.5, breast: p=0.03, juxtapulmonary: p=0.037), in comparison to matched normal organs. Notably, one of five patients with a breast lesion, who completely responded to HER2 targeted therapy, exhibited the highest breast lesion SUVmean. Brain and lymph node lesions demonstrated intratumoral heterogeneity of HER2 expression. Conclusion: Our study demonstrates the potential value of quantitative MRI along with molecular imaging to characterize metastatic HER2+ breast cancer and evaluate intratumoral heterogeneity. We underscore the importance of standardizing processing techniques and contribute to this effort by summarizing [89Zr]trastuzumab uptake and cellularity values of normal physiological uptake. Higher SUVmean and ADC mean values observed in lesions, compared to normal tissue, highlight their potential roles in intratumoral classification. While studies have shown the utility of [89 Zr]trastuzumab-PET/CT, our findings demonstrate that integrated DW-MRI can aid in tumor classification. Table 1: Physiological 89Zr-Trastuzumab Uptake (SUVmean) and Apparent Diffusion Coefficient (ADCmean) in Healthy Tissues Citation Format: Ameer Mansur, Moozhan Nikpanah, Johnathan McConathy, Erica Stringer-Reasor, Gabrielle Rocque, Ahmed Elkhanany, Katia Khoury, Nusrat Jahan, Suzanne Lapi, Anna Sorace. [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-04.

Does digital economy agglomeration promote green economy efficiency? A spatial spillover and spatial heterogeneity perspective

Does digital economy agglomeration promote green economy efficiency? A spatial spillover and spatial heterogeneity perspective

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability.

Abstract PS16-10: SPATIAL IMMUNE CELL DISTRIBUTION CAN REFINE PROGNOSIS IN EARLY-STAGE ER+/HER2-/LN- BREAST CANCER

Abstract Lymphocytic infiltrate is a known prognostic biomarker in estrogen receptor(ER)-negative breast cancers (BCs). Comparatively ER+ disease is putatively cold, however, there exists an infiltrate-rich subset of ER+ tumours with significant spatial heterogeneity and unknown clinical impact. Using serial sections taken from early-stage, ER+/HER2- breast tumours of Irish patients enrolled in the TAILORx trial (n=450), we aimed to investigate the prognostic potential of markers encompassing tumour architecture. Immunohistochemistry for Ki67 and CD45 (leukocyte common-antigen), and staining for haematoxylin and eosin was applied to all sections [1]. Classifiers for stromal fraction (SF), stromal-infiltrate (sTIL), Ki67-LI, and their spatial relationships within the tumour were generated using QuPath [2] and R Studio. Trained marker classifiers were validated against an expert pathologist (R2 of M-Score to: CD45%: 0.968, Ki67-LI: 0.814, sTIL: 0.864) to define observed lymphocytes as tumour or stromal-infiltrating, retain only tumour Ki67+ density, and to investigate SF. Cohort mean SF was 67.69% (range 16.35 – 98.29%), with marginally significant differences in recurrence prediction for cohort high v low SF by mean (c-index = 0.58, p< 0.032), and luminal A disease (p=0.037) only. sTILs did not differ significantly between high/low mean SF (Mann-Whitney p=0.6201), though sTIL was prognostic in the OncotypeDx intermediate Recurrence Score (RS) category overall (p=0.0076). This trend appeared strongest in intermediate RS patients receiving chemo-endocrine therapy (HT+CT) (p < 0.0001) vs endocrine therapy (HT) alone (p=0.86). Investigating the effects of prescribed therapy on sTIL-derived recurrence risk also revealed significant trends in those patients receiving HT+CT only (p < 0.00001) vs HT alone (p=0.26). Spatial analysis of sTILs suggest that tumours become more immune excluded as Oncotype Dx RS increases - particularly from intermediate to high RS (Wilcoxon Intermediate v High: p=0.0077), with significant differences in survival for high/low tumour-immune hotspots observed in Intermediate RS, HT+CT treated patients (p=0.0052). Further spatial analysis suggests that high normalised frequency of infiltrate [method adapted from 3] (within 7um of tumour cells) have negative prognostic impact for premenopausal patients (p=0.017), and inter-sectional analysis identifies niche tumour environments where high Ki67-LI colocalize with immune infiltrates[methods adapted from 4, 5], most notable in Intermediate RS tumours.. Overall these data suggest immune-spatial subsets can be used to refine risk stratification of ER+ breast cancer.

Multiplexed Imaging Mass Cytometry Analysis Characterizes the Vascular Niche in Pancreatic Cancer.

Oncogenesis and progression of pancreatic ductal adenocarcinoma (PDAC) is driven by complex interactions between the neoplastic component and the tumor microenvironment (TME), which includes immune, stromal, and parenchymal cells. In particular, most PDACs are characterized by a hypovascular and hypoxic environment that alters tumor cell behavior and limits the efficacy of chemotherapy and immunotherapy. Characterization of the spatial features of the vascular niche could advance our understanding of inter- and intra-tumoral heterogeneity in PDAC. Here, we investigated the vascular microenvironment of PDAC by applying imaging mass cytometry using a 26-antibody panel on 35 regions of interest (ROIs) across 9 patients, capturing over 140,000 single cells. The approach distinguished major cell types, including multiple populations of lymphoid and myeloid cells, endocrine cells, ductal cells, stromal cells, and endothelial cells. Evaluation of cellular neighborhoods identified 10 distinct spatial domains, including multiple immune and tumor-enriched environments as well as the vascular niche. Focused analysis revealed differential interactions between immune populations and the vasculature and identified distinct spatial domains wherein tumor cell proliferation occurs. Importantly, the vascular niche was closely associated with a population of CD44-expressing macrophages enriched for a pro-angiogenic gene signature. Together, this study provides insights into the spatial heterogeneity of PDAC and suggests a role for CD44-expressing macrophages in shaping the vascular niche.

Abstract PS09-08: Genomic characterization of endocrine resistance in ER+HER2+ breast cancers in the POETIC Trial

Abstract Background: Mechanisms of resistance to endocrine therapy are not well understood within ER+HER2+ breast cancer (BC). Our prior work suggested that intrinsic HER2-Enriched (HER2E) molecular subtype predicts early resistance to aromatase inhibitors (AI) (Bergamino eBioMedicine 2022) and high on-treatment (on-Txt) Ki67 levels predict poor survival (Smith Lancet Oncol 2020). Improved early detection of persistent proliferating tumor cells with endocrine resistance pathways could be targeted by pre-emptive personalized therapy and reduction in recurrence. In this study, we proposed to further identify additional alterations/features from genomic and spatial data to provide unprecedented new insight into intrinsic and adaptive resistant pathways in tumor cells that may assist to identify molecular targets for treatment. Materials: POETIC was a phase III trial of post-menopausal patients with ER/PR+ invasive BC (n = 4480) randomized 2:1 to 2 weeks of peri-operative AI (POAI) vs control, followed by standard-of-care treatment. Ki67 was assessed by IHC and intra-tumor heterogeneity was evaluated (5-15 regions) for all the POETIC POAI samples (N = 2487). ER+HER2+ samples were classified as good responders (GR) or poor responders (PR) based on a reduction in Ki67 between pre-treatment (pre-Txt) and 2-week on-Txt samples. Tumor-infiltrating lymphocytes were assessed; multiplex Immunofluorescence (mIF) was performed to measure immune cell densities in tumor and stroma compartments (CD3, CD20, CD68, FOXP3, and CD3 FOXP3 co-expression). Gene expression profiles by BC360™ (Nanostring) on all 210 pairs of POAI treated ER+/HER2+; whole exome sequencing (WES, 100X) were performed on pre-Txt tumor and blood samples from 13 GR, 17 PR, and 9 HER2E GR. We performed GeoMx Whole Transcriptome on 4 pairs (pre-Txt and on-Txt) of GR and GeoMx Proteins (77 including IO proteins) on 6 pairs of GRs and 6 pairs of PRs. Results: The most frequently mutated genes were TP53, PIK3CA, GATA3, and CHD4. Only TP53 was associated with PR (Fisher’s exact p=0.01). TP53 mutated cases had higher expression of TP53 mutant-like gene expression signature compared to wild-type cases (Wilcoxon test p=0.001), mIF FOXP3 (Wilcoxon test p = 0.0005), and CD68 (Wilcoxon test p = 0.019) density score. However, within the HER2-E subset, we found that TP53 mutations were associated with GR (Fisher’s exact p=0.02). We found spatial heterogeneity of Ki67 IHC levels across POAI samples. Examining IHC, while there was higher heterogeneity of Ki67 in the ER+HER2- samples (n = 2264) with 3% of pre-Txt and 9% on-Txt, 6% of ER+HER2+ samples (13/223, 6 LumA, 5 LumB, and 2 HER2E) showed heterogeneity of Ki67 exclusively on-Txt. Even in GR tumors with Ki67 < 10% on-Txt, we identified hotspots with retained proliferating Ki67+ cells after 2 weeks of POAI. The lobular tumors were GR and had characteristic CDH1 mutations. Importantly, cases with persistent areas of Ki67+ cells, regardless of Her2 status, were associated with late relapse. To further explore intratumoral heterogeneity, we performed spatial whole transcriptomics profiling on 95 regions from 4 pairs of GR samples (Ki67 > 10% at baseline and Ki67 < 10% on-Txt) and found low intratumoral heterogeneity in the pre-Txt samples that increased at 2 weeks on-Txt. In a larger set of samples including both GR and PR with the GeoMx protein method, we found increased intratumoral heterogeneity in the PR vs GR. Conclusion: While TP53 mutation was generally a predictor of poor response; in HER2-E it paradoxically was associated with a good early response to aromatase inhibitor which warrants further investigation. Ki67 levels in ER+HER2+ showed higher intratumoral heterogeneity in a subset of patients on treatment suggesting the potential of persistent, proliferating cells leading to later recurrence. Our spatial RNA and protein data further observe the intratumoral heterogeneity that identifies pathways for use as potential spatial biomarkers. Citation Format: Maggie Chon U Cheang, Xixuan Zhu, Orsolya Sipos, Anastasia Alataki, Mikayla Feldbauer, Elena López-Knowles, Holly Tovey, Lucy Kilburn, Milana Bergamino Sirvén, Dhrusti Patel, Hui Xiao, Perry Maxwell, Anthony Skene, Chris Holcombe, Manuel Salto-Tellez, Nicholas Turner, Andrew Dodson, Ian Smith, John Robertson, Judith Bliss, Gene Schuster, Roberto Salgado, Mitch Dowsett, Katherine A Hoadley. Genomic characterization of endocrine resistance in ER+HER2+ breast cancers in the POETIC Trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS09-08.

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying

Pharmaceutical twin-screw wet granulation is a multifaceted and intricate process pivotal to drug product development. Accurate modeling of this process is indispensable for optimizing manufacturing parameters and ensuring product quality. The fluid bed dryer, an integral component of this granulation process, significantly influences the granular critical quality attributes. This study builds upon prior research by integrating experimental findings on granule segregation during fluid bed drying into an existing compartmental model, enhancing its predictive capabilities. An additional model layer on granule segregation behavior is composed and integrated into the existing model structure in this study. The added model compartment describes probability distributions on the vertical position of granules within each granule size class considered. To beware of overfitting, predictions of both the moisture content after drying and the granule bed temperature throughout drying are discussed in this study relative to experimental data from earlier published studies. These independent analyses demonstrated a marked improvement in prediction accuracy compared to earlier published model structures. The refined model accurately predicts the residual moisture content after drying for an untrained formulation. Moreover, it simultaneously makes accurate predictions of the granular bed temperature, which emboldens its structural correctness. This advancement makes it a powerful tool for predicting the behavior of the pharmaceutical fluid bed drying, which holds significant promise to facilitate pharmaceutical product development.

Underway pCO2 Surveys Unravel CO2 Invasion of Lake Superior From Seasonal Variability

AbstractThis study observed seasonal trends and inferred drivers of CO2 biogeochemistry at the air‐water interface of Lake Superior. Underway carbon dioxide partial pressure (pCO2) was measured in surface water during 69 transects spanning ice free seasons of 2019‐2022. These data comprise the first multiannual pCO2 time series in the Laurentian Great Lakes. Surface water pCO2 was closely tied to increasing atmospheric pCO2 over a 100‐day CO2 equilibration timescale, while seasonal variability was controlled equally by thermal and non‐thermal drivers during the ice‐free season. Comparison to previous modeling efforts indicated that Lake Superior surface pCO2 increased with two decades of rising atmospheric CO2. Spatial heterogeneity in CO2 dynamics was highlighted by a conductivity‐based delineation of “riverine” and “pelagic” regimes, each of which was associated with net CO2 influx over Julian days 100–300 on the order of 25 Gmol C. These findings refine previous estimates of Lake Superior C fluxes, support predictions of anthropogenic CO2 invasion during the ice‐free season, point to new observation strategies for large lakes, and highlight an urgent need for studies of changes to lacustrine C cycling.

Transport accessibility and hospital attributes: A nonlinear analysis of their impact on Women's prenatal care seeking behavior

Ensuring women receive vital prenatal care is crucial for maternal and newborn health. Limited research explores factors influencing prenatal care-seeking from a geospatial perspective. This study, based on a substantial Wuhan dataset (23,947 samples), investigates factors influencing prenatal care-seeking, focusing on transport accessibility and hospital attributes. Findings indicate a nuanced relationship: (1) A non-linear trend, resembling an inverted “U,” reveals the complex interplay between transport accessibility, hospital attributes, and prenatal care visits. Hospital attributes have a more pronounced impact than transport accessibility. (2) Interaction analysis underscores that lower prenatal care visits relate to low-income and education levels, despite reasonable public transport accessibility. (3) Spatial disparities are significant, with suburban areas facing increased obstacles compared to urban areas, particularly for those in suburban rural areas. This study enhances understanding by emphasizing threshold effects and spatial heterogeneity, offering valuable perspectives for refining prenatal care policies and practices.