Multiplatform Approach Research Articles

BIOM-72. INTEGRATION OF ULTRASENSITIVE ELECTROLUMINESCENT IMMUNOASSAY AND CELL-FREE DNAMETHYLATION ANALYSIS FOR NON-INVASIVE MONITORING OF ADULT DIFFUSE GLIOMAS

Abstract Gliomas are highly aggressive brain tumors with nearly universal recurrence rate. Despite this, the ability to accurately predict and identify tumor recurrence relies solely on serial MRI imaging, which is marred by treatment effects such as radiation necrosis, and necessarily identifies progression retrospectively. It is believe that tumor undergo molecular changes upon tumor progression, however the resampling of tumors upon recurrence imposes significant risks. This highlights the need for novel non-invasive biomarkers capable of identifying tumor recurrence. Due to the low accuracies of individual biomarkers, we have proposed the use of an integrated, multi-platform approach to biomarker discovery. A cohort of 107 glioma plasma samples, including 30 pairs, underwent plasma proteomic analysis, consisting of a panel of serum proteins (FABP4, GFAP, NFL, Tau and MMP3,4 &7) quantified through ultrasensitive electrochemiluminescence multiplexed immunoassays, and plasma DNA methylation analysis, captured through cell-free methylated DNA immunoprecipitation and high-throughput sequencing. Unsupervised hierarchal clustering revealed robust separation of primary and recurrent tumors through plasma proteomics, associated with a distinct plasma methylation signature. NFL, Tau and MMP3 levels differed between primary and recurrent samples; pair-wise analysis revealed increased in NFL and Tau concentrations upon recurrence. Tau levels predicted outcome independent of WHO Grade and IDH status. A predictive generalized linear regression model created through the integration of the proteomic and methylation signatures allowed for the discrimination of primary and recurrent samples in 83% of cases. This work suggests that the combination of DNA methylation and plasma proteomics may improve the ability of these techniques for the serial monitoring of gliomas patients.

Resolving the ubiquitous small-scale semi-permanent features of the general ocean circulation: a multiplatform observational approach

Abstract Based on twenty years of Argo and ship/animal-borne/glider hydrographic profile data, we derive a new high resolution hydrographic Atlas and associated circulation field for the oceans above 2000 dbar. Satellite altimetric observations are used to explicitly regress out eddy noise in the fit, greatly reducing one of the major sources of noise. Geostrophic shears are found from the fitted geopotential anomaly fields. Ekman velocities are estimated using satellite wind stresses. Both Argo trajectory observations at 1000 dbar and surface drifter observations are used to reference geostrophic shears derived from the Atlas hydrography. Surface drifter velocities are analyzed with an additional wind-friction term to remove the wind-related flow. Agreement between the surface geostrophic (referenced to Argo trajectories) and drifter-based surface velocity is high at both large and mesoscales, lending confidence to the derived geostrophic circulation fields. The Atlas reveals standing mesoscale eddies and meanders in western boundary systems, and the braided jet structure of the Antarctic Circumpolar Current. In the interior, the upper ocean flow consists of a highly baroclinic large-scale Sverdrup flow and smaller scale (~200 km width) semi-zonal jets, which are more barotropic (low vertical shear) and have an average zonal width of around 2000 km. These semi-zonal jets are globally ubiquitous - found in all basins pole-to-pole. The many permanent mesoscale features of the mean general circulation contrasts with that predicted by theories of the large-scale flow in simplified flat-bottomed domains. The new Atlas presents a new opportunity to benchmark modern high resolution ocean and climate models.

Multi-platform metabolic profiling of the stages of production of locally made lambanog, a traditional Philippine alcoholic beverage

Traditional alcoholic beverages contain a diverse range of metabolites that determine their taste and aroma profiles, as well as potential health benefits and possible toxicities. Furthermore, the metabolite levels can vary with the growing conditions of the raw materials and the production process, giving distinct profiles to products from different sources. Thus, the profiling of metabolites present in traditional alcoholic beverages is important for quality control, safety, and authentication purposes. In this study, the various metabolites that can be found in lambanog, a traditional Filipino coconut wine, are profiled using a multi-platform approach, together with the raw material and intermediates across the production process. Proton nuclear magnetic resonance (1H NMR) spectroscopy, liquid chromatography–mass spectrometry (LC–MS), and gas chromatography–mass spectrometry (GC–MS), were used to tentatively identify the metabolites present in samples from the different stages of lambanog production. 1H NMR spectroscopy has revealed the presence of ethanol, pyruvate, uracil, and sugars such as glycerol, fructose, mannitol, and glucose. GC–MS studies revealed potential compounds that may influence organoleptic properties in the different stages of lambanog production. Identifying and monitoring the identified metabolite components along the production process can aid future product and process developments, quality control, and authentication of lambanog and other traditional alcoholic beverages.

Be bold, start cold! cold formalin fixation of colorectal cancer specimens granted superior DNA and RNA quality for downstream molecular analysis

The use of cold formalin fixation (CFF; i.e., fixating tissue samples with 4 °C precooled formalin) recently attracted further attention owing to its putative improved ability to preserve nucleic acid compared with standard room temperature formalin (SFF). In this study, we aimed to assess the effect of four formalin-based fixation protocols (SFF, CFF, delayed formalin fixation-DFF, and cold formalin hyperfixation; CFH) on both DNA and RNA quality. We collected 97 colorectal cancer (CRC) and analyzed 23 metrics of nucleic acid quantity and quality yield using a multiplatform approach by combining spectrophotometric, fluorimetric, electrophoretic, and polymerase chain reaction (PCR) assays. Following confirmation of fixation-protocol-related different effects via clustering analysis, CFF presented best metrics compared with all protocols, specifically positive coefficients of DV1000-60000, DV2/DV1, DNA λ ratio 260/230, and ABL gene expression absolute copies, and negative coefficient of DV150-1000. The SFF subgroup presented a positive coefficient of DV150-1000 and negative coefficients for DV1000-60000, DV2/DV1, RNA λ ratio 260/230, RNA QuBit concentration, DV100/200, RNA electrophoresis concentration and absolute quantity, and ABL copies. Overall, we confirmed the superior yield performances of CFF preservation for both DNA and RNA compared with the other protocols in our series of CRC samples. Pending further validations and clarification of the specific mechanisms behind these findings, our study supports the implementation of CFF in the pathology unit routine specimen management for tumor tissue molecular profiling.

Aplikasi Multiplatform Sayur Kita untuk Meningkatkan Efisiensi Pedagang Pasar

Markets are an essential part of the economic ecosystem, often facing various challenges for traders. One of the issues they encounter is the limited time for conducting transactions with both consumers and suppliers. This condition significantly impacts business performance and the quality of stock, influenced by various factors such as weather, time constraints, and the shipping process. This research aims to determine and analyze the development of applications that make buying and selling easier between traders and suppliers online, which can be accessed at any time. This application is integrated into various platforms, both via mobile and web, to enable traders to carry out transactions quickly, effectively and efficiently in terms of time, ef-fort and cost. Apart from that, this research is to facilitate transactions between market traders and suppliers, as well as expand the reach of online markets, especially regarding time con-straints and stock availability. By adopting an integrated multiplatform application develop-ment approach, this research aims to facilitate transactions between market traders and suppli-ers, as well as expand the market reach online, particularly addressing time limitations and stock availability. The development method used is the Waterfall method, which includes re-quirements analysis, system design, implementation, testing, and maintenance. The result of this research is an application called "Sayur Kita," a cross-platform application that helps traders con-duct transactions quickly and efficiently through mobile and web platforms, usable on various devices. Testing was conducted using the black box method, and the results showed that all fea-tures operated as expected. Therefore, this application can help improve the efficiency of market traders in conducting transactions with suppliers and traders online.

Generation of deposit-derived pyroclastic density currents by repeated crater rim failures at Stromboli Volcano (Italy)

The gravitational instability of hot material deposited during eruptive activity can lead to the formation of glowing avalanches, commonly known as deposit-derived pyroclastic density currents (PDCs). These currents can travel hundreds of metres to several kilometres from the source at exceptionally high temperatures, posing a catastrophic hazard to areas surrounding steep-slope volcanoes. The occurrence of deposit-derived PDCs is often associated with crater rim failure, which can be triggered by various factors such as magma thrust from dike injection, magma fingering, bulging or less commonly, powerful explosions. Here, the in-depth study of data from the multi-parametric monitoring network operating on Stromboli (Italy), including video surveillance, seismicity and ground deformation data, complemented by remote topographic sensing data, has facilitated the understanding of the events leading to the crater rim collapse on 9 October and 4 December 2022. The failures resulted in the remobilisation of 6.4 ± 1.0 × 103 m3 and 88.9 ± 26.7 × 103 m3 of material for the 9 October and the 4 December 2022, respectively, which propagated as PDCs along the NW side of the volcano and reached the sea in a few tens of seconds. These events were characterised by a preparatory phase marked by an increase in magmatic pressure in the preceding weeks, which correlated with an increase in the displacement rate of the volcano’s summit. There was also an escalation in explosive degassing, evidenced by spattering accompanied by seismic tremors in the hours before the collapse.These events have been interpreted as an initial increase in magma vesicularity, followed by the release of gas once percolation threshold was reached. The degassing process induced densification of the magma, resulting in increased thrust on the conduit walls due to increased magmastatic pressure. This phase coincided with crater rim collapse, often followed or accompanied by the onset of lava overflow phases. A mechanism similar to the one proposed may shed light on similar phenomena observed at other volcanoes. The analysis performed in this study highlights the need for a multi-parametric and multi-platform approach to fully understand such complex phenomena. By integrating different data sources, including seismic, deformation and remote sensing data, it is possible to identify the phenomena associated with the different phases leading to crater rim collapse and the subsequent development of deposit-derived PDCs.

Managing the Pandemic in Digitized Spaces: Assessing the Social Media Approaches of Scandinavian Public Health Authorities

In response to the COVID-19 pandemic, health- and civil-contingency agencies—referred to here as public health authorities (PHAs)—in Sweden, Norway, and Denmark turned to social media to disseminate pandemic recommendations and information. This study explores the social media crisis management strategies employed by Scandinavian PHAs. Specifically, we apply a multiplatform research approach to assess communication objectives (Instruct, Support, Manage Reputation, and Solicit Interaction) across three social media platforms—Facebook, Instagram, and Twitter (currently known as X). Introducing a series of hypotheses based on previous scholarship, we detail the prevalence of different objectives across platforms and countries. The results indicate prominent use of reputational management, particularly on Twitter, while instructive information emerged as a highly used communication objective in Sweden and Denmark. Overall, the communicative trends remained parallel across nations, despite Sweden implementing a more relaxed crisis management strategy. The main distinction in Sweden’s approach manifested in a relatively lower emphasis on the pandemic by its PHAs compared to Denmark and Norway. National differences in crisis communication objectives indicate that Norwegian PHAs stand out in terms of using reputational management, while Sweden stands out in employing more supportive information on Instagram.

Identification of tumor-marker gangliosides for early cancer detection: A multi-platform approach.

e17551 Background: Tumor-marker gangliosides (TMGs) have enormous potential for early-stage cancer detection as diagnostic biomarkers despite being relatively understudied in this context. AOA Dx is focused on the analytical development of three separate platforms for the quantitation of TMGs in human serum. The development of these platforms for TMG quantitation may allow for the identification of diagnostic signatures for early-stage cancer detection. Methods: First, we are developing a pipeline of antibody-based assays to target TMGs. To aid in development of multiple immunoassays, we collected specificity and affinity data on commercial and proprietary antibodies targeting TMGs using glycoarrays. We are also currently using two immune-based platforms to target TMGs. We have developed an enzyme-linked immunosorbent assay (ELISA) and we have implemented high-performance thin-layer chromatography (HPTLC) to detect individual and total gangliosides. Additionally, we are applying both targeted and untargeted mass spectrometry to human serum from confirmed cancer diagnoses. Results: The specificity and affinity data from the glycoarrays confirm that our TMG antibodies have negligible cross-reactivity and are suitable for diagnostic platform development. Additionally, our developed ELISA allows for the quantification of TMGs in diverse and complex matrices including human serum and plasma, cell lines, and exosomes. HPTLC also detects individual and total gangliosides in each of these matrices, which allows for high-throughput analysis for TMG quantitation. Finally, the application of both targeted and untargeted mass spectrometry has identified multiple TMGs characterized by unique lipid tails. Notably, MS analysis shows that the serum of melanoma and ovarian cancer patients exhibited significantly increased levels of several ganglioside species compared to age-matched healthy serum, further highlighting the potential of TMGs as a promising avenue for cancer diagnosis. Further experiments will focus on refining all platforms. We will also expand the demographic representation of our human serum sample cohort to confirm the initial findings from our mass spectrometry experiments and continue to use this platform to identify additional TMGs of interest. Conclusions: AOA Dx is advancing the development of a multi-platform approach for the detection of TMGs. Our objective is the identification of a diagnostic disease signature for early-stage cancer detection. The validation of this type of diagnostic panel would allow for expedited diagnosis and treatment of cancers currently diagnosed at late stages, ultimately reducing healthcare costs and increasing survival rates. Future research will aim to validate these biomarkers in independent prospective studies.

A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes

Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.

P.102 Integration of Ultrasensitive electroluminescent immunoassay and cell-free DNA methylation analysis for the non-invasive discrimination of adult diffuse gliomas

Background: Gliomas are highly aggressive brain tumors with nearly universal recurrence rate. Despite this, the ability to accurately predict tumor recurrence relies solely on serial MRI imaging, highlighting the need for prognostic biomarkers. Due to the low accuracies of individual serum markers, we have proposed the use of an integrated, multi-platform approach to biomarker discovery. Methods: A cohort of 107 glioma plasma samples, including 30 pairs, underwent plasma proteomic, consisting of a panel of serum proteins (FABP4, GFAP, NFL, Tau and MMP3,4 &7) quantified through ultrasensitive electrochemiluminescence multiplexed immunoassays, and plasma DNA methylation analysis, captured through cell-free methylated DNA immunoprecipitation and high-throughput sequencing. Results: Unsupervised hierarchal clustering revealed robust separation of primary and recurrent tumors through plasma proteomics, associated with a distinct plasma methylation signature. NFL, Tau and MMP3 levels differed between primary and recurrent samples; pair-wise analysis revealed increased in NFL and Tau concentrations upon recurrence. Tau levels predicted outcome independent of WHO Grade and IDH status. A predictive model created through the integration of the proteomic and methylation signatures revealed an AUC of 0.83. Conclusions: The combination of DNA methylation and plasma proteomics showcases that an integrative approach may improve the ability of these techniques for the serial monitoring of gliomas patients.

Abstract PO1-13-04: Distinct immune signatures discriminate between patients defined as exceptional survivors of metastatic breast cancer compared to those with rapidly progressing treatment resistant breast cancers

Abstract Background: "Atypical responders" can encompass three sub- categories of patients: "exceptional responders" (those with an unusually favourable treatment response), "rapid progressors" (unusually poor or no response), and "exceptional/long-term survivors" (outlived initial prognosis). Here, we aim to investigate the drivers of immune surveillance mechanisms (local, lymphoid and peripheral) and the nature of immunological tumour recognition in exceptional survivors of stage 4 metastatic disease following standard-of-care chemo- and targeted therapies. Methods: We conducted a complementary multi-platform immune profiling study to define differences in the phenotypic immune landscape including mass-spectrometry-based proteomics on peripheral blood mononuclear cells (PBMCs), multiplex cytokine profiling of patient serum, and high-dimensional flow cytometry on whole blood samples. By staining 500μl of whole blood using 2 panels, 353 immune-cell-related parameters were obtained for comparisons among the following groups: "exceptional survivors," "exceptional responders," "rapid progressors," "non-exceptional metastatic patients," "early breast cancer patients," and "healthy volunteers". Patients were matched for age, breast cancer receptor status, and sites of metastases where possible. Results: Preliminary analysis of serum biomarkers and proteome of the PBMCs of the exceptional survivors showed elevated levels of NK-cell-related proteins such as KCTD10 and RBBP7. Flow cytometry analysis revealed the presence of increased activated CD56dim NK cells, CD56bright NK cells, and central memory (CM) (CD45RA-CD27+) CD8 T cells in both the exceptional survivors and the rapid progressors. However, expression of CD25 appears to be the main mode of activation in rapid progressors compared with increased NKG2D expression in exceptional survivors. Additionally, activation of the unconventional gd T cells was evident in both groups with terminally differentiated effector memory cells re-expressing CD45RA (TEMRA) Vd1 cell predominating in the exceptional survivors. In the rapid progressors, the increased CD25+ TEMRA Vd2 cells coupled with elevated serum IL-17A and IL-1b suggest their ability to generate IL-17. Th2 cytokines, IL-5 and IL-13 were also enriched in rapid progressors and concomitant increase in CD25+ Th2 cells reveals a strong Th2-driven immune signature in these patients. Finally increased CD86+ atypical double negative (DN) B cells, mostly comprised of the DN2 subset were also significantly enriched in the rapid progressors compared to the exceptional survivors where DN1 B cells were prevalent. Conclusion: The multi-platform approach to investigating immune responses present in atypical responders has identified several distinct immunophenotypes in which the extreme outliers differ in their potential immune surveillance mechanisms. Functional validation of these findings through activation and cytotoxicity assays is currently underway and future work aims to understand the spatial biology of these circulating immune cells within the context of their primary tumours, metastases, and lymph nodes. Citation Format: Helen Kakkassery, Thanussuyah Alaguthurai, Zuza Kozik, Paul Buckley, Ruifang Lu, Esme Carpenter, Rosalind Graham, Gheed Alhity, Farhana Hossain, Sadiyah Mukhtar, Syed Haider, Jyoti Choudhary, Sheeba Irshad. Distinct immune signatures discriminate between patients defined as exceptional survivors of metastatic breast cancer compared to those with rapidly progressing treatment resistant breast cancers [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 PO1-13-04.

Integrated Multiplatform Analysis and Separation of Thirteen Flavonoids and Anthraquinones in Seven Medicinal Cassia Species.

Cassia (Family: Fabaceae) species are a large group of flowering plants rich in bioactive anthraquinone and flavonoids used in botanical supplements and nutraceuticals. A simple and reliable high-performance liquid chromatography-photodiode array (HPLC-PDA) method was developed and validated for separating and quantifying 13 anthraquinone and flavonoids. These compounds were further confirmed using an LC-based electrospray ionization mass spectrometry (ESI-MS/MS) method in the leaves and flowers of selected Cassia species. A simple and rapid HPTLC method was developed for chemical fingerprint analysis of all Cassia species. All 13 compounds were chromatographically separated on a Zorbax TC18 (4.6 × 250, 5 μm particle size) analytical column, and 0.1% formic acid and acetonitrile as elution solvents at a flow rate of 0.8 mL/min with detection at 259 nm. For HPTLC fingerprinting, the mobile phase compositions of toluene, ethyl acetate, and formic acid (5.5:4.2:0.6, v/v/v) were optimized to separate and identify all compounds using silica gel 60F254 aluminum plates. The validation data for the developed HPLC-PDA method for 13 compounds showed good linearity (r2 >0.99) with a sensitive LOD (0.082-1.969 μg/mL), LOQ (0.250-5.967 μg/mL), and excellent recoveries (85.22-100.32%). The quantification results were found to be precise and accurate (<5.0% and relative error), -0.77-0.44 with ESI-MS/MS confirmation in the Cassia samples. The novel HPTLC method was excellent separation for 13 compounds, with Rf values ranging between 0.12 and 0.61. The developed HPLC-PDA method was simple and precise and could separate and quantify anthraquinones and flavonoids along with confirmation, using a novel LC-based ESI-MS/MS. The HPTLC method was found to be simple and precise, with excellent separation capabilities for these compounds. This novel multiplatform approach successfully identified and quantified 13 compounds simultaneously using an integration of data strategy in seven medicinally important Cassia species' leaves and flowers.

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach.

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

A multiparameter liquid biopsy approach allows to track melanoma dynamics and identify early treatment resistance

Melanoma heterogeneity is a hurdle in metastatic disease management. Although the advent of targeted therapy has significantly improved patient outcomes, the occurrence of resistance makes monitoring of the tumor genetic landscape mandatory. Liquid biopsy could represent an important biomarker for the real-time tracing of disease evolution. Thus, we aimed to correlate liquid biopsy dynamics with treatment response and progression by devising a multiplatform approach applied to longitudinal melanoma patient monitoring. We conceived an approach that exploits Next Generation Sequencing (NGS) and droplet digital PCR, as well as the FDA-cleared platform CellSearch, to analyze circulating tumor DNA (ctDNA) trend and circulating melanoma cell (CMC) count, together with their customized genetic and copy number variation analysis. The approach was applied to 17 stage IV melanoma patients treated with BRAF/MEK inhibitors, followed for up to 28 months. BRAF mutations were detected in the plasma of 82% of patients. Single nucleotide variants known or suspected to confer resistance were identified in 70% of patients. Moreover, the amount of ctDNA, both at baseline and during response, correlated with the type and duration of the response itself, and the CMC count was confirmed to be a prognostic biomarker. This work provides proof of principle of the power of this approach and paves the way for a validation study aimed at evaluating early ctDNA-guided treatment decisions in stage IV melanoma. The NGS-based molecular profile complemented the analysis of ctDNA trend and, together with CMC analysis, revealed to be useful in capturing tumor evolution.

Utilizing Social Networks to Improve Success Metrics in Social E-Commerce

Social e-commerce highlights the current trend of companies strategically using a multi-platform approach for their marketing plans and selling needs. This approach often consists of a company utilizing one or more social networks, along with a social e-commerce, to create an online community around their products. However, there is limited holistic research on how companies use social networks to maximize their branding and marketing efforts. This study theorizes the strategic social network actions of a social e-commerce platform. We collected data from a random sample of 1,458 social e-commerce users and their chosen social networks, including Instagram, Pinterest, Facebook, and X (formerly known as Twitter). This unique data set and analysis assessed the impact of social network marketing from firms across a wide variety of industries and platforms. The study provides empirical evidence on follower growth and sales and identifies impactful marketing strategies in a multi-platform web environment.

Abstract 6006: Modeling antibody drug conjugate sensitivity using urothelial carcinoma patient-derived models

Abstract Introduction: Enfortumab Vedotin (EV), an antibody-drug conjugate (ADC) targeting Nectin-4, has emerged as a new standard-of-care for patients with metastatic urothelial cancer (UC). Promising results have also been observed in bladder cancer (BLCA) patients with ADCs targeting HER2. To identify predictive biomarkers of ADC sensitivity, we characterized a large and expanding biobank of patient-derived organoid (PDO) and xenograft (PDX) models for Nectin-4 and HER2 expression, and Nectin-4 and HER2-targeted ADC sensitivity. Methods: We generated 19 PDOs and 34 PDXs that reflect the genomic and biologic heterogeneity of human UC. A subset of these models was further characterized using a multiplatform approach, including bulk and single-cell DNA and RNA sequencing and immunoblot for Nectin-4 and HER2 expression. We leveraged these models to study the biologic determinants of sensitivity to EV and the HER2-targeted ADC trastuzumab deruxtecan (T-DXd). PDX models were treated with EV (5 mg/kg IV on day 1, 3, 6) or T-DXd (10 mg/kg IV on day 1, 21, 42) or vehicle only as control. We also studied sensitivity to T-DXd and EV, as well as to their cytotoxic payloads (exatecan and vedotin) in vitro using paired PDO models. Results: We observed high degree of variability of HER2 and Nectin-4 expression across UC PDOs and PDXs. In PDO models, sensitivity to EV correlated strongly with Nectin-4 expression, whereas HER2 expression was not strongly correlated with sensitivity to T-DXd. We also noted a poor correlation between Nectin-4 expression in PDOs and PDXs derived from the same patient. A subset of models, for example, SMBO-104 (ERBB2 wildtype with low HER2 expression), exhibited significantly greater sensitivity to EV than to T-DXd. Conversely, T-DXd was significantly more active than EV in SMBO-170, a model with ERBB2 amplification (~40 copies) and HER2 3+ expression. Sensitivity to exatecan, an analogue of the T-DXd payload deruxtecan, as measured by inhibition of cell proliferation and induction of apoptosis, was more predictive of T-DXd sensitivity than HER2 expression level. Conclusion: In this study, we generated and biologically characterized UC patient-derived models with the goal of identifying predictive biomarkers of sensitivity to Nectin-4 and HER2-targeted ADCs. We observed significant heterogeneity of HER2 and Nectin-4 expression across models. Models were identified in which T-DXd was superior to EV, and vice versa. Sensitivity to the T-DXd cytotoxic payload was more predictive of PDX response than HER2 expression levels, with significant tumor regression observed with T-DXd in BLCA models with low HER2 expression. Our data suggest that clinical trials of HER2-targeted ADCs such as T-DXd should not be restricted to patients with HER2 overexpression and that novel biomarkers will be needed to identify those UC patients most likely to benefit from FDA-approved and investigational ADCs. Citation Format: Xinran Tang, Ziyu Chen, Jasmine Thomas, Karan Nagar, John Christin, Naryan Rustgi, Sizhi Gao, Elisa de Stanchina, Jonathan Coleman, Michael Shen, Hikmat Al-Ahmadie, Gopa Iyer, Kwanghee Kim, David Solit. Modeling antibody drug conjugate sensitivity using urothelial carcinoma patient-derived models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6006.

An integrated approach for the benthic habitat mapping based on innovative surveying technologies and ecosystem functioning measurements

Among marine ecosystems globally, those in the Mediterranean Sea, are facing many threats. New technologies are crucial for enhancing our understanding of marine habitats and ecosystems, which can be complex and resource-intensive to analyse using traditional techniques. We tested, for the first time, an integrated multi-platform approach for mapping the coastal benthic habitat in the Civitavecchia (northern Latium, Italy) coastal area. This approach includes the use of an Unmanned Surface Vehicle (USV), a Remote Operated Vehicle (ROV), and in situ measurements of ecosystem functionality. The echosounder data allowed us to reconstruct the distribution of bottom types, as well as the canopy height and coverage of the seagrass Posidonia oceanica. Our study further involved assessing the respiration (Rd) and net primary production (NCP) rates of P. oceanica and its associated community through in situ benthic chamber incubation. By combining these findings with the results of USV surveys, we were able to develop a preliminary spatial distribution model for P. oceanica primary production (PP-SDM). The P. oceanica PP-SDM was applied between the depths of 8 and 10 m in the studied area and the obtained results showed similarities with other sites in the Mediterranean Sea. Though in the early stages, our results highlight the significance of multi-platform observation data for a thorough exploration of marine ecosystems, emphasizing their utility in forecasting biogeochemical processes in the marine environment.

Determination of the radiative transition rates in Ta VII using a multiplatform approach

Tantalum (Z=73) is an element that is produced in the neutron-induced transmutation of tungsten (Z=74) which in turn will compose the divertors in Tokamaks. As a consequence, their sputtering may generate ionic impurities of all possible charge states in the deuterium-tritium plasma that could contribute to radiation losses in controlled nuclear devices. The radiative properties of these ions have therefore potential important applications in this field. In this context, a multiplatform approach has been adopted in order to compute the Ta VII radiative rates and estimate their accuracy. The oscillator strengths and transition probabilities have been calculated for the 237 electric dipole (E1) transitions of the Ta VII spectrum as classified by Ryabtev et al. (2014). Three independent atomic structure models have been used; one based on the semi-empirical pseudo-relativistic Hartree–Fock (HFR) method and two based on the fully relativistic ab initio multiconfiguration Dirac–Hartree–Fock (MCDHF) method.

Developing Programming Competence Among Physics Education Students With Multi-Platform E-Learning During COVID-19

This research examines the effectiveness of a multi-platform e-learning approach in developing programming competence among physics education students at Mataram University's Faculty of Teaching and Education during the COVID-19 pandemic. The R2D2 model, an iterative and cyclical constructivist learning design process emphasizing creative learning experiences, serves as the methodological framework. Data collection employs questionnaires and tests. The research yields two primary findings: the development of a multi-platform e-learning media for a computer programming course by combining features from SIA, SPADA Unram, YouTube Channel, Google Drive, and WhatsApp groups; and student learning outcomes falling within the "satisfaction" category. Statistical analysis of class A and B data (means and standard deviations: 76.429/0.782 and 74.57/1.06, respectively) reveals insufficient evidence to conclude a significant difference in data variability between the two groups. Keywords: Programming Competence, Multi-platform e-Learning, Physics Education Students, Covid-19.

Analysis of Pixar Movie Marketing Strategy Based on 5T Theory: Take Turning Red as an Example

This study introduces the brand background of Pixar Animation Film Company and analyzes its marketing strategy using the 5T theory. This study chooses Turning Red as a case study, and through the analysis of its marketing strategy, some shortcomings are found. First, through the analysis of Tools, "Turning Red" failed to meet the audience in cinemas, which led to the disappointment of some fans. Although Pixar and Disney used multi-platform and multi-channel promotional tools, their marketing effect was reduced due to some limitations. Second, for Tracking, although Pixar registered separate social media accounts for each movie, there was relatively little in-depth analysis and response to user feedback. This makes it difficult for the company to fully understand the audience's needs and expectations. Based on these findings, this study makes some recommendations to improve Pixar's marketing strategy. This study makes recommendations to strengthen the multi-platform and multi-channel marketing approach and enhance user feedback analysis. These recommendations are expected to help Pixar further improve the marketing effectiveness of its films, increase audience engagement and satisfaction, and contribute to the company's continued growth.