Characterization Of Landscape Research Articles

Effect of global shrinkage parameter of horseshoe prior in compressed sensing

This study investigates the effect of the global shrinkage parameter τ of a horseshoe prior, one of the global–local shrinkage priors, on linear regression in sparse signal processing. Statistical mechanics methods are employed to examine the accuracy of signal estimation. The phase diagram of the success and failure of signal recovery in noiseless compressed sensing with varying τ is discussed from the viewpoint of dynamic characterization of approximate message passing (AMP) as a solving algorithm and static characterization of the free-energy landscape. It is found that there exists a parameter region where the AMP algorithm can hardly recover the true signal, even though the true signal is locally stable. The analysis of the free-energy landscape also provides important insight into the optimal choice of τ.

Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape.

Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitness needs to be measured for any one protein. Deep learning may help to predict the fitness of many genotypes from a smaller neural network training sample of genotypes with experimentally measured fitness. Here I use a recently published experimentally mapped fitness landscape of more than 260,000 protein genotypes to ask how such sampling is best performed. I show that multilayer perceptrons, recurrent neural networks (RNNs), convolutional networks, and transformers, can explain more than 90 percent of fitness variance in the data. In addition, 90 percent of this performance is reached with a training sample comprising merely ≈103 sequences. Generalization to unseen test data is best when training data is sampled randomly and uniformly, or sampled to minimize the number of synonymous sequences. In contrast, sampling to maximize sequence diversity or codon usage bias reduces performance substantially. These observations hold for more than one network architecture. Simple sampling strategies may perform best when training deep learning neural networks to map fitness landscapes from experimental data. The fitness landscape data analyzed here is publicly available as described previously (Papkou, et al., 2023). All code used to analyze this landscape is publicly available at https://github.com/andreas-wagner-uzh/fitness_landscape_sampling. Supplementary data are available at Bioinformatics online.

Shifts in the functional capacity and metabolite composition of the gut microbiome during recovery from enteric infection.

While enteric pathogens have been widely studied for their roles in causing foodborne infection, their impacts on the gut microbial community have yet to be fully characterized. Previous work has identified notable changes in the gut microbiome related to pathogen invasion, both taxonomically and genetically. Characterization of the metabolic landscape during and after enteric infection, however, has not been explored. Consequently, we investigated the metabolome of paired stools recovered from 60 patients (cases) during and after recovery from enteric bacterial infections (follow-ups). Shotgun metagenomics was applied to predict functional microbial pathways combined with untargeted metametabolomics classified by Liquid Chromatography Mass Spectrometry. Notably, cases had a greater overall metabolic capacity with significantly higher pathway richness and evenness relative to the follow-ups (p<0.05). Metabolic pathways related to central carbon metabolism, amino acid metabolism, and lipid and fatty acid biosynthesis were more highly represented in cases and distinct signatures for menaquinone production were detected. By contrast, the follow-up samples had a more diverse metabolic landscape with enhanced richness of polar metabolites (p<0.0001) and significantly greater richness, evenness, and overall diversity of nonpolar metabolites (p<0.0001). Although many metabolites could not be annotated with existing databases, a marked increase in certain clusters of metabolites was observed in the follow-up samples when compared to the case samples and vice versa. These findings suggest the importance of key metabolites in gut health and recovery and enhance understanding of metabolic fluctuations during enteric infections.

Integrated Approach of Historical Landscape Characterisation Techniques and Remote Sensing for the Definition of Predictive Models and Scenario Analysis in the Planning of Archaeological Areas

This study explores the synergistic integration of remote sensing (RS) and Historical Landscape Characterisation (HLC) methodology as an innovative, multi-scalar and holistic approach to enhance archaeological planning. The goal is to maximize the effectiveness of the investigations, optimizing data collection and improving the contextual understanding of the sites. In fact, these methodologies can significantly contribute to the documentation, conservation, planning and valorisation of archaeological areas. By integrating RS data with features detected by HLC, a complete picture is obtained that facilitates a deeper understanding of the landscape and historical dynamics. This article will explain the combined approach of RS and HLC, presenting some methodologies key to improving the precision and effectiveness of archaeological planning. This integration facilitates the sustainable preservation of archaeological resources and contributes to the conscious management of cultural heritage in the context of contemporary development. The paper demonstrates, through a case study, how the application of the two methodologies (RS and HLC) in an integrated form can provide an exhaustive interpretation of the territory in which the archaeological area is located, which can represent an exhaustive knowledge base on which to set up effective processes for the strategic territorial planning of archaeological areas.

Landscaping characterization of the campus at the UEMG Ituiutaba, Minas Gerais, Brazil

The purpose of this work was to characterize the landscape of the campus at the University of the Minas Gerais State (in portuguese, Universidade do Estado de Minas Gerais - UEMG), located at Ituiutaba. As for such, the local plants were identified ranging from herbaceous to shrub type, due to them being the most commonly employed to perform alterations for landscape purposes. Subsequently, some areas of the campus were photographed to create a landscape characterization of the scenery in regard to its landscape's composition and vegetation. 102 species of herbaceous, subshrub, and shrub plants were found belonging to 39 families; 38.23% being native and the other 61.77% being non-native (cultivated, naturalized, and exotic). In regard to the landscape’s composition in loco, the principles of message, equilibrium, scale, dominance, harmony, and climax were contemplated. Furthermore, in regard to the guiding principles for the selection of vegetable species, it was observed that aesthetic, functional and temporal attributes were incorporated in all the analyzed areas. In conclusion, the landscape’s composition of the campus at the UEMG Ituiutaba fulfills its aesthetic, functional and ecological roles, however it’s worth highlighting that the adequate handling can be the defining factor in assuring the continuity of these functions.

Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment

Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.

Abstract PO4-15-06: Genomic landscape characterization after exposure to cyclin dependent kinase 4/6 inhibitors: a retrospective multi-institutional consortium analysis

Abstract Background: Limited data are available to determine the best therapeutic strategy for hormone-receptor positive (HR+) HER2 negative (HER2-) advanced breast cancer (ABC) after progression on cyclin dependent kinase 4/6 inhibitors (CDK4/6i). The aim of this study was to characterize the genomic and prognostic profile of patients (pts) that experienced disease progression after first-line therapy with a CDK4/6i. Methods: The study retrospectively analyzed a multi-institutional cohort of 75 patients (pts) with HR+/HER2- ABC after experiencing progression on first-line endocrine therapy (ET) with CDK4/6i and characterized by circulating tumor DNA (ctDNA) next-generation sequencing (Guardant 360). Oncogenic pathways (i.e., RTK, RAS, RAF, MEK, NRF2, ER, WNT, MYC, p53, cell cycle, notch, and PI3K) were defined based on previous research (Sanchez-Vega et al. Cell, 2018). Associations across single nucleotide variations (SNVs), copy number variations (CNVs), and pathway classification were tested by uni- and multivariable logistic regression with respect to a CDK4/6i naïve group comprising 247 patients with HR+/HER2- ABC (control). Prognosis was analyzed through Cox regression for overall survival (OS). Result: Our study cohort included 75 ABC pts who experienced progression after first line CDK4/6i plus ET: 43 pts (57.3%) were treated with ET while 31 (41.3%) with a non-ET- second line therapy. The most common histology was invasive ductal carcinoma (70.6%), 37.3% of pts were negative for progesterone expression and 26.7% had de novo metastatic disease. The PI3K (33.3%), p53 (28%) and ER (25.3%) pathways were the most mutated in the CDK4/6i-treated cohort. Comparing our population with a CDK4/6i naïve cohort (N=247), the multivariate analysis showed a higher prevalence in the study cohort of SNVs mutations in: i) ESR1 gene [Odds ratio (OR) 2.93; p=0.005]; ii) cell-cycle pathway (OR 4.24; p=0.033); iii) ER pathway (OR 2.04; p= 0.034). Moreover, in the study cohort a numerical but not significant increase of RB1 SNVs was also observed. Multivariable analyses of the 43 pts that received ET second line therapy showed a negative prognostic impact with TP53 SNVs in both progression-free survival (PFS) [Hazard ratio (HR) = 3.34; 95% CI: 1.15-9.66, p=0.026] and OS (HR = 3.85; 95% CI: 1.52-9.77, p=0.005). The prognostic role of p53 pathway mutations was also confirmed for both PFS (HR = 4.71, 95% CI: 1.64-13.50; p=0.004) and OS (HR = 3.25; 95% CI: 1.27-8.3; p=0.014). The potential interaction between the prognostic oncogenic pathways and the outcome was investigated according to the treatment strategy (ET vs non-ET). A consistent impact was observed across the above prognostic pathways both for PFS and OS. A numerical difference was observed in terms of PFS in pts with p53 pathway mutations that underwent non-ET second line. Conclusions: The genomic landscape of progressive disease after CDK4/6i exposure is significantly different from the genomic alterations detectable in treatment-naïve pts, which could potential impact future treatment strategies for patients with disease progression after adjuvant CDK4/6i exposure. Our data suggest that the choice of second-line treatment could potentially be guided by the identification of actionable mutation by ctDNA, although further prospective studies are needed to validate the clinical utility of this approach. Citation Format: Letizia Pontolillo, Carolina Reduzzi, Andrew Davis, Lorenzo Gerratana, Arielle Medford, Katherine Clifton, Whitney L. Hensing, Marko Velimirovic, Ami N. Shah, Jeannine Donahue, Laura Munoz Arcos, Charles S. Dai, Jennifer Keenan, Amir Behdad, William Gradishar, Emilio Bria, Cynthia Ma, Aditya Bardia, Massimo Cristofanilli. Genomic landscape characterization after exposure to cyclin dependent kinase 4/6 inhibitors: a retrospective multi-institutional consortium analysis [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 PO4-15-06.

Gut microbial genomes with paired isolates from China illustrate probiotic and cardiometabolic effects.

The gut microbiome displays genetic differences among populations, and characterization of the genomic landscape of the gut microbiome in China remains limited. Here, we present the Chinese Gut Microbial Reference (CGMR) set, comprising 101,060 high-quality metagenomic assembled genomes (MAGs) of 3,707 nonredundant species from 3,234 fecal samples across primarily rural Chinese locations, 1,376 live isolates mainly from lactic acid bacteria, and 987 novel species relative to worldwide databases. We observed region-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. Preliminary mouse experiments suggest a probiotic effect of two Faecalibacillus intestinalis isolates in alleviating constipation, cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and isolates from the genera Parabacteroides and Lactobacillus in host lipid metabolism. Our study expands the current microbial genomes with paired isolates and demonstrates potential host effects, contributing to the mechanistic understanding of host-microbe interactions.

Combining multisensor images and social network data to assess the area flooded by a hurricane event.

In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image. Both, the Sentinel-1 and Sentinel-2 images were obtained after Willa landfall. While the LULC map reached an accuracy of 92%, validated using data collected during field surveys, the flood map achieved 90% overall accuracy, validated using locations extracted from social network data, that were manually georeferenced. The agriculture class was the dominant land use (about 2,624 km2), followed by deciduous forest (1,591 km2) and sub-perennial forest (1,317 km2). About 1,608 km2 represents the permanent wetlands (mangrove, salt marsh, lagoon and estuaries, and littoral classes), but only 489 km2 of this area belongs to aquatic surfaces (lagoons and estuaries). The flooded area was 1,225 km2, with the agricultural class as the most impacted (735 km2). Our analysis detected the saltmarsh class occupied 541 km2in the LULC map, and around 328 km2 were flooded during Hurricane Willa. Since the water flow receded relatively quickly, obtaining representative imagery to assess the flood event was a challenge. Still, the high overall accuracies obtained in this study allow us to assume that the outputs are reliable and can be used in the implementation of effective strategies for the protection, restoration, and management of wetlands. In addition, they will improve the capacity of local governments and residents of Marismas Nacionales to make informed decisions for the protection of vulnerable areas to the different threats derived from climate change.

Spatial dissection of the immune landscape of solid tumors to advance precision medicine.

Chemotherapeutics, radiation, targeted therapeutics and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment (TME). Spatial multi-OMICs technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the TME cellular architecture and the functional phenotype of tumor, immune and stromal cells. An in-depth spatial characterization of the heterogenous tumor immune landscape can improve not only the prognosis, but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and how these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

Characterisation of Portuguese radiotherapy departments: Organisation, occupational exposure values and diagnostic reference levels for breast and prostate computed tomography planning

IntroductionPortugal currently hosts 24 active radiotherapy departments, 8 public and 16 privates, presenting potential radiation exposure risks to multidisciplinary teams. Patients in these treatments also face ionising radiation during treatment planning and verification. MethodsAuthorisation and ethical approval were secured for a national online survey, disseminated to radiotherapy departments across Portugal. The survey encompassed three sections: equipment, staff, and radiographer role characterisation; occupational exposure values for one month; and exposure parameters, including computed tomography (CT) dose values [CT dose index (CTDIvol) and dose length product (DLP)] for breast and prostate cancer CT planning. Local Diagnostic Reference Levels (DRLs) derived were based on the 75th percentile of median dose values. ResultsThe study garnered a 50% response rate from public institutions, 12,5% from private and 25% from all active radiotherapy institutions in Portugal. All departments employ Three-Dimensional Conformal Radiation Therapy (3D–CRT) and incorporate Intensity Modulated Radiation Therapy (IMRT) and/or Volumetric Modulated Arc Therapy (VMAT) irradiation techniques. Additionally, half of the departments also perform Brachytherapy (BT). Radiographers demonstrated an occupational dose of zero mSv. CT planning dose values were 13 mGy and 512 mGy cm for breast CT and 16 mGy and 689 mGy cm for prostate CT, pertaining to CTDIvol and DLP, respectively. ConclusionMost aspects of national radiotherapy characterisation align with the established literature. Occupational exposure values exhibited consistency across radiotherapy modalities. An approach to national DRLs was formulated for breast and prostate CT planning, yielding values congruent with recent European studies. Implications for practiceThis study offers vital insights for analysing occupational contexts and risk prevention, serving as the initial characterisation of the national radiotherapy landscape. It also pioneers the calculation of DRLs for CT planning in radiotherapy to optimise procedures.

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

Integrating Heritage and Environment: Characterization of Cultural Landscape in Beijing Great Wall Heritage Area

The neuroblastoma tumor microenvironment: From an in-depth characterization towards novel therapies

Neuroblastoma is a cancer of the sympathetic nervous system that develops in young children, either as low-risk or high-risk disease. The tumor microenvironment (TME) is now recognized as an important player of the tumor ecosystem that may promote drug resistance and immune escape. Targeting the TME in combination with therapies directly targeting tumor cells therefore represents an interesting strategy to prevent the emergence of resistance in cancer and improve patient’s outcome. The development of such strategies however requires an in-depth understanding of the TME landscape, due to its high complexity and intra and inter-tumoral heterogeneity. Various approaches have been used in the last years to characterize the immune and non-immune cell populations present in tumors of neuroblastoma patients, both quantitatively and qualitatively, in particular with the use of single-cell transcriptomics. It is anticipated that in the near future, both genomic and TME information in tumors will contribute to a precise approach to therapy in neuroblastoma. Deciphering the mechanisms of interaction between neuroblastoma cells and stromal or immune cells in the TME is key to identify novel therapeutic combinations. Over the last decade, numerous in vitro studies and in vivo pre-clinical experiments in immune-competent and immune-deficient models have identified therapeutic approaches to circumvent drug resistance and immune escape. Some of these studies have formed the basis for early phase I and II clinical trials in children with recurrent and refractory high-risk neuroblastoma. This review summarizes recently published data on the characterization of the TME landscape in neuroblastoma and novel strategies targeting various TME cellular components, molecules and pathways activated as a result of the tumor-host interactions.

Xenopus tropicalis osteoblast-specific open chromatin regions reveal promoters and enhancers involved in human skeletal phenotypes and shed light on early vertebrate evolution

While understanding the genetic underpinnings of osteogenesis has far-reaching implications for skeletal diseases and evolution, a comprehensive characterization of the osteoblastic regulatory landscape in non-mammalian vertebrates is still lacking. Here, we compared the ATAC-Seq profile of Xenopus tropicalis (Xt) osteoblasts to a variety of non mineralizing control tissues, and identified osteoblast-specific nucleosome free regions (NFRs) at 527 promoters and 6747 distal regions. Sequence analyses, Gene Ontology, RNA-Seq and ChIP-Seq against four key histone marks confirmed that the distal regions correspond to bona fide osteogenic transcriptional enhancers exhibiting a shared regulatory logic with mammals. We report 425 regulatory regions conserved with human and globally associated to skeletogenic genes. Of these, 35 regions have been shown to impact human skeletal phenotypes by GWAS, including one trps1 enhancer and the runx2 promoter, two genes which are respectively involved in trichorhinophalangeal syndrome type I and cleidocranial dysplasia. Intriguingly, 60 osteoblastic NFRs also align to the genome of the elephant shark, a species lacking osteoblasts and bone tissue. To tackle this paradox, we chose to focus on dlx5 because its conserved promoter, known to integrate regulatory inputs during mammalian osteogenesis, harbours an osteoblast-specific NFR in both frog and human. Hence, we show that dlx5 is expressed in Xt and elephant shark odontoblasts, supporting a common cellular and genetic origin of bone and dentine. Taken together, our work (i) unravels the Xt osteogenic regulatory landscape, (ii) illustrates how cross-species comparisons harvest data relevant to human biology and (iii) reveals that a set of genes including bnc2, dlx5, ebf3, mir199a, nfia, runx2 and zfhx4 drove the development of a primitive form of mineralized skeletal tissue deep in the vertebrate lineage.

Genome-wide characterization of the mutational landscape of proliferative verrucous leukoplakia

ObjectiveProliferative verrucous leukoplakia (PVL) is a rare but highly aggressive variant of oral leukoplakia that almost inevitably progresses to oral squamous cell carcinoma (OSCC). The aims of this study were to perform whole exome sequencing of a cohort of patients diagnosed with PVL and identify potential mutational profiles and pathways in this disorder. Study DesignA total of 12 oral cavity mucosal biopsies from 6 patients with oral lesions clinically compatible with PVL were used. Of these, 9 were diagnosed as dysplasia, 1 OSCC and 2 hyperkeratosis/hyperplasia. Exome sequencing used the Ion AmpliSeq Exome platform. Ion Reporter software was used for variant calling, annotation and filtering. Analysis and visualization of somatic mutations was carried out using the MAFtools R package. ResultsFollowing exome sequencing and mutational profiling we analyzed the profiles for cancer associated genes and signatures. Genes previously associated with OSCC including HYDIN, MUC16, MAML3, CDKN2A, FAT1 and CASP8 were mutated in multiple samples. Several DNA damage repair genes including PARP1 were mutated in PVL samples. NOTCH and Hippo pathways were the most frequently impacted by mutation. ConclusionThis genome wide characterization of premalignant PVL identifies both known and potentially novel oncogenic mechanisms in this disorder.

Characterization of Mitoribosomal Small Subunit unit genes related immune and pharmacogenomic landscapes in renal cell carcinoma.

Mitoribosomes are essential for the production of biological energy. The Human Mitoribosomal Small Subunit unit (MRPS) family, responsible for encoding mitochondrial ribosomal small subunits, is actively engaged in protein synthesis within the mitochondria. Intriguingly, MRPS family genes appear to play a role in cancer. A multistep process was employed to establish a risk model associated with MRPS genes, aiming to delineate the immune and pharmacogenomic landscapes in clear cell renal cell carcinoma (ccRCC). MRPScores were computed for individual patients to assess their responsiveness to various treatment modalities and their susceptibility to different therapeutic targets and drugs. While MRPS family genes have been implicated in various cancers as oncogenes, our findings reveal a contrasting tumor suppressor role for MRPS genes in ccRCC. Utilizing an MRPS-related risk model, we observed its excellent prognostic capability in predicting survival outcomes for ccRCC patients. Remarkably, the subgroup with high MRPS-related scores (MRPScore) displayed poorer prognosis but exhibited a more robust response to immunotherapy. Through in silico screening of 2183 drug targets and 1646 compounds, we identified two targets (RRM2 and OPRD1) and eight agents (AZ960, carmustine, lasalocid, SGI-1776, AZD8055_1059, BPD.00008900_1998, MK.8776_2046, and XAV939_1268) with potential therapeutic implications for high-MRPScore patients. Our study represents the pioneering effort in proposing that molecular classification, diagnosis, and treatment strategies can be formulated based on MRPScores. Indeed, a high MRPScore profile appears to elevate the risk of tumor progression and mortality, potentially through its influence on immune regulation. This suggests that the MRPS-related risk model holds promise as a prognostic predictor and may offer novel insights into personalized therapeutic strategies.

Towards Transdisciplinary Heritage Assessment: An Analysis of the Use of Landscape Study Methods as a Holistic Toolbox for Cultural Site Characterisation in the Spanish Context

This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its main objective is to search for innovative tools that other disciplines can contribute to the work of architects specialising in heritage studies. To this end, the research explores the main methodologies, maps, guides, and registers of landscape and historic landscape characterisation developed in Europe, particularly in Spain, over the last 40 years. Considering this intense and profound evolution of landscape analysis, useful strategies for the assessment of cultural sites from their conception in the 21st century arise. Nevertheless, landscape characterisation methods have been mainly developed and applied by geographers and are absent in many urban and territorial heritage studies. In response, this article proposes a new methodological approach focusing on contextual values to be used in the assessment of architectural heritage at the territorial scale.

Abstract 3933: Comprehensive molecular characterization of mitochondrial mutational landscape across the evolution of lung adenocarcinoma

Abstract The human mitochondrial genome is prone to genetic alterations, which lead to somatic mutations, changes in mtDNA copy number and altered expression of respiratory chain subunits. This is in part due to the fact that mtDNA has a limited ability to repair itself when it is damaged. Although a buildup of somatic mutations in mtDNA has been associated with increased cancer risk, the role of mtDNA alterations in malignant transformation of lung adenocarcinoma has not been addressed. Therefore, a clear understanding of changes in mtDNA along the pathway of lung tumorigenesis is critical for identifying molecular biomarkers related to carcinogenesis and tumor progression. Like all solid tumors, lung adenocarcinoma is thought to be initiated and to progress through a series of genetic alterations, including changes in mtDNA. Lungs resected for primary adenocarcinomas often harbor minute discrete foci of cytologically atypical pneumocyte proliferations designated as atypical adenomatous hyperplasia (AAH). Evidence suggests that AAH represents an initial step in the progression to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and ultimately fully invasive adenocarcinoma (ADA). In this study we used a unique cohort of 52 patients with matched specimens (n=133) representing different steps of disease progression (AAH, AIS, and MIA) coupled with novel ultra-deep mitochondrial sequencing (mtDNA-Seq) method to assess the mtDNA mutational landscape throughout the continuum of lung adenocarcinoma development. Utilizing a custom bioinformatics workflow, somatic mutations were detected in a subset of the premalignant non-invasive lesions, with overall higher mutational load observed in MIA and ACA specimens. Additionally, large degree of inter-patient heterogeneity were observed for mtDNA copy numbers in conjunction with the clonal histological evolution of pulmonary neoplasia. Moreover, an appreciable number of coding and non-coding mutations from regulatory regions of the mtDNA were detectable in the precursor AAH lesions and the continuum of LUAD progression. Majority of shared mutations showed heteroplasmic transition with increase in fractional abundance in ADA, compared to the AHH lesions, thereby indicating spatial clonal expansion as they progressed histologically. Here we report the first comprehensive characterization of mitochondrial mutational landscape in dynamic evolution of lung adenocarcinoma, and provide insight into the heterogeneity of clonal events associated with the progression from noninvasive to malignant disease. Citation Format: Alka Singh, Santanu Dasgupta, Ashwin L. Koppayi, Lisa Rooper, Vasudha Mishra, David Sidransky, Nishant Agrawal, Karthik Suresh, Evgeny Izumchenko. Comprehensive molecular characterization of mitochondrial mutational landscape across the evolution of lung adenocarcinoma [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 3933.

Abstract 6931: Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells

Abstract Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution. Citation Format: Muchun Niu, Yang Zhang, Jiayi Luo, Jefferson C. Sinson, Alastair M. Thompson, Chenghang Zong. Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells [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 6931.

Abstract 6853: Spatial proteomic and transcriptomic characterization of the inflammatory landscape of formalin fixed paraffin embedded Barrett’s esophagus tissues

Abstract Esophageal adenocarcinoma (EAC), a significant cause of morbidity and mortality, develops from its metaplastic precursor lesion termed Barrett’s esophagus (BE). BE progresses to EAC within an inflammation rich environment, however a detailed understanding of the types of inflammatory cells present, how that population changes over time or diagnosis, and the related immunomodulatory pathways that may mediate BEs progression is still understudied. Traditional immunohistochemistry is often inadequate to provide detailed information about a broad number of cells, local cellular proportions, and cellular heterogeneity; while bulk or single cell RNA sequencing lose the spatial context and relationships between the stroma and epithelium. Utilizing modern multiplex profiling technologies such as Nanostring’s GeoMx digital Profiler (DSP) aid in identifying both cellular composition and distribution of cells within the epithelium and stroma. Therefore, our aim of this study was to determine the suitability of the DSP platform for analyzing formalin fixed paraffin embedded (FFPE) endoscopic samples of BE and determine any differences between non-dysplastic BE (NDBE) samples from patients who eventually progressed (progressors) compared to those who did not (non-progressors), with the goal to gain deeper insights about cellular composition and spatial distribution of immune cells that may dictate progression of BE. Our secondary goal was to investigate the relationship of these cells to the BE epithelial cells through understanding the immune signaling and regulatory pathways. Our pilot study utilizing a 49-plex antibody panel on 7 NDBE samples from progressors and 8 NDBE samples from non-progressors showed good quality metrics and deciphered an immune rich microenvironment in BE with several immune markers including CD66b (neutrophils), CD14 (monocytes), CD68 (macrophages) and CD56 (NK cells) being overexpressed in the stroma of progressors compared with non-progressors, corrected p value less than 0.05. The myeloid activation marker CD80 was overexpressed in the BE epithelial cells of progressors. To determine how spatial transcriptomic profiling performed in FFPE endoscopic samples, 1,812 transcripts within 48 regions of interest of four BE, HGD, and EAC samples was interrogated. Only 36 (2%) probes fell below the limit of detection quality threshold. Thus, our pilot results show that robust proteomic and transcriptomic profiling can be obtained from endoscopic BE biopsies using this system. Based on these results, we systematically interrogated the immune cell makeup and distribution as well as their related inflammatory and immunoregulatory pathways in 40 NDBE biopsies (20 progressors and 20 with stable non-progressing disease) within discrete compartments (stroma and epithelium) through spatial whole transcriptome profiling. Citation Format: Qurat ul Ain, Nicola Frei, Amir M. Khoshiwal, Pim Stougie, Robert Odze, Sophie Camilleri-Broet, Lorenzo Ferri, Lucas C. Duits, Jacques Bergman, Matthew D. Stachler. Spatial proteomic and transcriptomic characterization of the inflammatory landscape of formalin fixed paraffin embedded Barrett’s esophagus tissues [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 6853.