Functional Expression Research Articles

Membrane-bound chemoreception of bitter bile acids and peptides is mediated by the same subset of bitter taste receptors

The vertebrate sense of taste allows rapid assessment of the nutritional quality and potential presence of harmful substances prior to ingestion. Among the five basic taste qualities, salty, sour, sweet, umami, and bitter, bitterness is associated with the presence of putative toxic substances and elicits rejection behaviors in a wide range of animals including humans. However, not all bitter substances are harmful, some are thought to be health-beneficial and nutritious. Among those compound classes that elicit a bitter taste although being non-toxic and partly even essential for humans are bitter peptides and l-amino acids. Using functional heterologous expression assays, we observed that the 5 dominant human bitter taste receptors responsive to bitter peptides and amino acids are activated by bile acids, which are notorious for their extreme bitterness. We further demonstrate that the cross-reactivity of bitter taste receptors for these two different compound classes is evolutionary conserved and can be traced back to the amphibian lineage. Moreover, we show that the cross-detection by some receptors relies on “structural mimicry” between the very bitter peptide l-Trp-Trp-Trp and bile acids, whereas other receptors exhibit a phylogenetic conservation of this trait. As some bile acid-sensitive bitter taste receptor genes fulfill dual-roles in gustatory and non-gustatory systems, we suggest that the phylogenetic conservation of the rather surprising cross-detection of the two substance classes could rely on a gene-sharing-like mechanism in which the non-gustatory function accounts for the bitter taste response to amino acids and peptides.

One-shot design elevates functional expression levels of a voltage-gated potassium channel.

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamic channels and receptors may be enhanced through one-shot design calculations.

Dealing With Variable Drug Exposure DuetoVariable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment.

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

A preliminary study on the effects of Xiaoyao San on neurological function and 5-HT2A mRNA expression in mice with Tourette syndrome

A preliminary study on the effects of Xiaoyao San on neurological function and 5-HT2A mRNA expression in mice with Tourette syndrome

Performance analysis of the FSO communication system with random jamming over a composite Málaga turbulence fading channel

The performance analysis of a free space optical (FSO) communication system in the presence of random jamming is presented over a Málaga (M) distributed channel model with pointing errors and atmospheric attenuation. Firstly, the probability density function expressions of the transmission channel, signal-to-jamming ratio, and signal-to-noise ratio are derived. Then, considering the probability of the jammer and Gaussian white noise, the closed-form expressions for the ergodic channel capacity, outage probability, and average bit error rate are derived. Moreover, asymptotic expressions for the aforementioned performance metrics are also derived to ascertain the diversity gain of the system. Extensive Monte Carlo simulations are performed to demonstrate the credibility of this theoretical analysis. Results indicate that the adverse impact of random jamming is higher than that of Gaussian noise for the FSO communication system. Besides, this observation highlights the pulsating nature of the jamming effect, showcasing that within high signal-to-jamming ratio regions, a low probability jammer exerts the most significant impact on the FSO system.

Trace metals coupled with plasticisers in microplastics strengthen the denitrification function of the soil microbiome in the Qinghai Tibetan Plateau

Due to the lack of research on the co-effects of microplastics and trace metals in the environment on nitrogen cycling-related functional microorganisms, the occurrence of microplastics and one of their plasticisers, phthalate esters, as well as trace metals, were determined in soils and river sediments in the Qinghai-Tibet Plateau. Relationship between microplastics and phthalate esters in the area was determined; the co-effects of these potentially toxic materials, and key factors and pathways affecting nitrogen functions were further explored. Significant correlations between fibre- and film-shaped microplastics and phthalate esters were detected in the soils from the plateau. Copper, lead, cadmium and di-n-octyl phthalate detected significantly affected nitrogen cycling-related functional microorganisms. The co-existence of di-n-octyl phthalate and copper in soils synergistically stimulated the expression of denitrification microorganisms nirS gene and “nitrate_reduction”. Additionally, di-n-octyl phthalate and dimethyl phthalate more significantly affected the variation of nitrogen cycling-related functional genes than the number of microplastics. In a dimethyl phthalate- and cadmium-polluted area, nitrogen cycling-related functional genes, especially nirK gene, were more sensitive and stressed. Overall, phthalate esters originated from microplastics play a key role in nitrogen cycling-related functions than microplastics themselves, moreover, the synergy between di-n-octyl phthalate and copper strengthen the expression of denitrification functions.

Twisted spatiotemporal optical vortex beams in dispersive media

We derive a closed-form expression for the mutual coherence function (MCF) of a twisted spatiotemporal optical vortex (STOV) beam after propagating a distance z in a linear dispersive medium. A twisted STOV beam is a partially coherent optical field that possesses a coherent STOV and a stochastic twist coupling its space and time dimensions. These beams belong to a special class of space–time-coupled light fields that carry transverse (to the direction of propagation) orbital angular momentum, making them potentially useful in numerous applications including quantum optics, optical manipulation, and optical communications. After presenting the derivation, we validate our new general MCF by showing that it simplifies to the MCFs for two example beams from the literature. Lastly, we present and analyze space–time beam profiles and complex arguments (phases) of the MCF at multiple z and differing amounts of material dispersion, field correlation or coherence, and beam twist to gain insight into how twisted STOV beams evolve in dispersive media. We conclude with a brief summary.

Beyond the Spectrum: Unleashing the Potential of Infrared Radiation in Poultry Industry Advancements.

The poultry industry is dynamically advancing production by focusing on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic alternatives. Infrared (IR) radiation is utilized to improve the well-being of humans, animals, and poultry through various operations. IR radiation occurs via electromagnetic waves with wavelengths ranging from 760 to 10,000 nm. The biological applications of IR radiation are gaining significant attention and its utilization is expanding rapidly across multiple sectors. Various IR applications, such as IR heating, IR spectroscopy, IR thermography, IR beak trimming, and IR in computer vision, have proven to be beneficial in enhancing the well-being of humans, animals, and birds within mechanical systems. IR radiation offers a wide array of health benefits, including improved skin health, therapeutic effects, anticancer properties, wound healing capabilities, enhanced digestive and endothelial function, and improved mitochondrial function and gene expression. In the realm of poultry production, IR radiation has demonstrated numerous positive impacts, including enhanced growth performance, gut health, blood profiles, immunological response, food safety measures, economic advantages, the mitigation of hazardous gases, and improved heating systems. Despite the exceptional benefits of IR radiation, its applications in poultry production are still limited. This comprehensive review provides compelling evidence supporting the advantages of IR radiation and advocates for its wider adoption in poultry production practices.

Physics‐constrained symbolic model discovery for polyconvex incompressible hyperelastic materials

AbstractWe present a machine learning framework capable of consistently inferring mathematical expressions of hyperelastic energy functionals for incompressible materials from sparse experimental data and physical laws. To achieve this goal, we propose a polyconvex neural additive model (PNAM) that enables us to express the hyperelastic model in a learnable feature space while enforcing polyconvexity. An upshot of this feature space obtained via the PNAM is that (1) it is spanned by a set of univariate basis functions that can be re‐parametrized with a more complex mathematical form, and (2) the resultant elasticity model is guaranteed to fulfill the polyconvexity, which ensures that the acoustic tensor remains elliptic for any deformation. To further improve the interpretability, we use genetic programming to convert each univariate basis into a compact mathematical expression. The resultant multi‐variable mathematical models obtained from this proposed framework are not only more interpretable but are also proven to fulfill physical laws. By controlling the compactness of the learned symbolic form, the machine learning‐generated mathematical model also requires fewer arithmetic operations than its deep neural network counterparts during deployment. This latter attribute is crucial for scaling large‐scale simulations where the constitutive responses of every integration point must be updated within each incremental time step. We compare our proposed model discovery framework against other state‐of‐the‐art alternatives to assess the robustness and efficiency of the training algorithms and examine the trade‐off between interpretability, accuracy, and precision of the learned symbolic hyperelastic models obtained from different approaches. Our numerical results suggest that our approach extrapolates well outside the training data regime due to the precise incorporation of physics‐based knowledge.

Complete biosynthesis of QS-21 in engineered yeast

QS-21 is a potent vaccine adjuvant and remains the only saponin-based adjuvant that has been clinically approved for use in humans1,2. However, owing to the complex structure of QS-21, its availability is limited. Today, the supply depends on laborious extraction from the Chilean soapbark tree or on low-yielding total chemical synthesis3,4. Here we demonstrate the complete biosynthesis of QS-21 and its precursors, as well as structural derivatives, in engineered yeast strains. The successful biosynthesis in yeast requires fine-tuning of the host’s native pathway fluxes, as well as the functional and balanced expression of 38 heterologous enzymes. The required biosynthetic pathway spans seven enzyme families—a terpene synthase, P450s, nucleotide sugar synthases, glycosyltransferases, a coenzyme A ligase, acyl transferases and polyketide synthases—from six organisms, and mimics in yeast the subcellular compartmentalization of plants from the endoplasmic reticulum membrane to the cytosol. Finally, by taking advantage of the promiscuity of certain pathway enzymes, we produced structural analogues of QS-21 using this biosynthetic platform. This microbial production scheme will allow for the future establishment of a structure–activity relationship, and will thus enable the rational design of potent vaccine adjuvants.

Correlation functions of scalar field theories from homotopy algebras

We present expressions for correlation functions of scalar field theories in perturbation theory using quantum A∞ algebras. Our expressions are highly explicit and can be used for theories both in Euclidean space and in Minkowski space including quantum mechanics. Correlation functions at a given order of perturbation theory can be calculated algebraically without using canonical quantization or the path integral, and we demonstrate it explicitly for φ3 theory. We show that the Schwinger-Dyson equations are satisfied as an immediate consequence of the form of the expressions based on quantum A∞ algebras.

The prognostic value and immunological role of MVP in pan-cancer study.

Major Vault Protein (MVP) has emerged as a potential prognostic and immunological biomarker in various cancer types. This pan-cancer study aimed to investigate expression of MVP and its correlation with clinical outcomes and immune infiltration across diverse cancer types. We conducted an analysis of extensive transcriptomic and clinical data from publicly available databases. Our findings unveiled a significant association between MVP expression and cancer progression, with higher expression levels predicting poorer overall survival in multiple cancer types. Importantly, MVP expression demonstrated a close relationship with immune infiltration in the tumor microenvironment, showing that higher expression levels were associated with increased immune cell infiltration. We further validated expression of MVP and function in cancer cell lines A549 and AGS. These compelling results suggest that MVP holds promise as a valuable biomarker for prognostic assessment and the development of immunotherapeutic strategies across various cancer types. Consequently, targeting MVP may offer a compelling therapeutic approach in the treatment of human cancers.

Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis

AbstractImaging spectroscopy is emerging as a leading remote sensing method for quantifying plant biodiversity. The spectral variation hypothesis predicts that variation in plant hyperspectral reflectance is related to variation in taxonomic and functional identity. While most studies report some correlation between spectral and field‐based (i.e., taxonomic and functional) expressions of biodiversity, the observed strength of association is highly variable, and the utility in applying spectral community properties to examine environmental drivers of communities remains unknown. We linked hyperspectral data acquired by airborne imaging spectrometers with precisely geolocated field plots to examine the spectral variation hypothesis along a temperate‐to‐boreal forest gradient in southern Québec, Canada. First, we examine the degree of association between spectral and field‐based dimensions of canopy tree composition and diversity. Second, we ask whether the relationships between field‐based community properties and the environment are reproduced when using spectral community properties. We found support for the spectral variation hypothesis with the strength of association generally greater for the functional than taxonomic dimension, but the strength of relationships was highly variable and dependent on the choice of method or metric used to quantify spectral and field‐based community properties. Using a multivariate approach (comparisons of separate ordinations), spectral composition was moderately well correlated with field‐based composition; however, the degree of association increased when univariately relating the main axes of compositional variation. Spectral diversity was most tightly associated with functional diversity metrics that quantify functional richness and divergence. For predicting canopy tree composition and diversity using environmental variables, the same qualitative conclusions emerge when hyperspectral or field‐based data are used. Spatial patterns of canopy tree community properties were strongly related to the turnover from temperate‐to‐boreal communities, with most variation explained by elevation. Spectral composition and diversity provide a straightforward way to quantify plant biodiversity across large spatial extents without the need for a priori field observations. While commonly framed as a potential tool for biodiversity monitoring, we show that spectral community properties can be applied more widely to assess the environmental drivers of biodiversity, thereby helping to advance our understanding of the drivers of biogeographical patterns of plant communities.

N2O emission in temperate seagrass meadows: Fluxes, pathway and molecular mechanism

Seagrass meadows act as filters for nitrogen in coastal areas, but whether they are a source or sink for N2O has been still controversy. Additionally, the production pathways of N2O as well as the microbial driving mechanism in seagrass meadows are seldom reported. In this study, the air-sea fluxes, sediment release potential, and production pathway of N2O in a temperate Zostera marina and Z. japonica mixed meadow were investigated by using gas chromatography and 15N isotopic tracing methods. The qPCR and metagenome sequencing were used to compare the difference in functional gene abundance and expression between seagrass vegetated and non-grass sediments. The results showed that the N2O air-sea fluxes in the meadow ranged from −1.97 to −1.77 nmol m⁻2 h⁻1, which was slightly lower in the seagrass region than in the adjacent bare region. Seagrass sediment N2O release potential dramatically increased after warming and nitrogen enrichment treatments. Heterotrophic nitrification was firstly investigated in seagrass meadows, and the process (26.80%–62.41%) and denitrification (37.55%–72.83%) contributed significantly to N2O production in the meadow, affected deeply by sediment organic content, while the contribution of autotrophic nitrification can be neglected. Compared with the bare sediments, the ammonia monooxygenase genes amoA, amoB and amoC, and nitrite oxidoreductase genes nxrA and nxrB, as well as nitrite reductase gene nirS and nitric oxide reductase gene norB were down-regulated, while the nitrous oxide reductase gene nosZ was up-regulated in the seagrass sediments, explaining less N2O emission in seagrass regions from the perspective of molecular. The nosZII-bearing bacteria like Bacteroidia, Polyangia, Anaerolineae, and Verrucomicrobiae could play important roles in N2O reduction in the seagrass meadow. The result is of great significance for highlighting the ability of seagrass meadows to mitigate climate changes.

Motion state factor driven for doubly-curved shallow shell deformation reconstruction

The conventional shape sensing method, based on C0 continuity, is recognized for its computational efficiency. However, it is prone to shear locking due to low-order polynomial interpolation in shell analysis, introducing two primary challenges. Firstly, it lacks consideration for C1 continuity. Secondly, existing high-order polynomial interpolation methods significantly increase the number of degrees of freedom (DOF), reducing computational efficiency. Therefore, a brand-new real-time structural health monitoring (SHM) method driven by motion state factor instead of nodal factors is proposed. This method accommodates all deformation modes of shallow shells with C1 continuity and improves the shape function's order without additional DOF. It begins with deriving motion states from compatibility equations, leading to a polynomial shape function expression. Subsequently, conversion equations for real constants and DOF are developed, establishing a least-squares model for theoretical strains and measured values. Following that, the higher-order element formula, optimized for minimal DOF, is then inferred from varied displacement data. Finally, simulations and experiments demonstrate this method's effectiveness, accuracy, and reliability in analyzing shallow shell elements.

Analysis of the Dynamics in Linear Chain Models by means of Generalized Langevin Equations

We analyse the motion of one particle in a polymer chain. For this purpose, we use the framework of the exact (non-stationary) generalized Langevin equation that can be derived from first principles via the projection-operator method. Our focus lies on determining memory kernels from either exact expressions for autocorrelation functions or from simulation data. We increase the complexity of the underlying system starting out from one-dimensional harmonic chains and ending with a polymer driven through a polymer melt. Here, the displacement or the velocity of an individual particle in the chain serves as the observable. The central result is that the time-window in which the memory kernels show structure before they rapidly decay decreases with increasing complexity of the system.

Are cities genuinely healthy? Diagnosis of urban development from the perspective of adaptive capacity

As urban diseases continue to emerge with the acceleration of urbanization, the transformation of urban governance concepts and systems must be urgently promoted. In dealing with the complex systemic problem of city governance, the concept of adaptation in complex adaptative system (CAS) theory has shown obvious advantages. This approach provides a new perspective for solving this problem in the face of the unprecedented complexity of current disasters. However, research on urban adaptation is currently hindered by imprecise terminology, significant bias, and insufficient empirical evidence. This study reinterprets the concept of urban adaptation in conjunction with CAS theory. The formula for the functional expression of urban adaptation is derived using dissipative structure theory. Indicators are then selected to describe the system of urban adaptive capacity. An adaptive decision support framework is established that covers 29 quantitative and 8 qualitative indicators. The adaptive performance of 12 sample cities is analyzed. Finally, this study provides corresponding planning paths for optimizing urban adaptation based on the evaluation results. The research findings can assist city managers in comprehending the actual situation of cities and provide a basis for formulating targeted governance programs.

Effect of static compression on near-field tsunami waves: Three-dimensional solution

An analytical solution of three-dimensional surface wave profiles due to arbitrary spatio-temporal disturbance of a circular ocean bottom in a compressible ocean is obtained by incorporating the influence of the static ocean background compression under the assumptions of linearized water wave theory. Time-domain simulations of the surface profile in three dimensions and the pressure distribution within the water column for a circular uniform rise and tilt are shown. The corresponding animation movies depict the temporal evolution of the surface profile and pressure field inside the water column eloquently, which was not shown in earlier literature. The impact of static compression is also discussed through the simulations. A novel analytical expression of the potential function for a generic tilted motion (rmcos(mθ),m∈Z) of the circular ocean floor is derived. An efficient numerical code is developed to find surface elevation and pressure distribution, implementing the inverse Fourier integral as matrix multiplication. Validation is performed for the specific case of a rising flat ocean floor, showing the oscillations due to acoustic-gravity modes. Initially, a simplified problem of a flat rising ocean bottom is solved using the eigenfunction matching method, which involves finding a particular solution for the nonhomogeneous ocean bottom condition and the solution for its homogeneous counterpart. Solutions are obtained using a newly developed inner product between the depth-dependent functions. Later, a Green function technique is used to incorporate the impact of the arbitrary spatio-temporal motion of the circular portion of the ocean bed. The solution obtained from the eigenfunction matching method is utilized to obtain the analytical form of Green’s function and, eventually, an expression of surface elevation and pressure distribution inside the ocean water column.

Effects of N-acetylcysteine on the expressions of UCP1 and factors related to thyroid function in visceral adipose tissue of obese adults: a randomized, double-blind clinical trial

BackgroundEvidences have shown that obesity is influenced by various factors, including various hormones such as thyroid hormones and the body’s metabolism rate. It seems that practical solutions such as weight loss diets and common drugs can affect these potential disorders. In this study, we investigate one of these common drugs, N-Acetylcysteine (NAC), on expressions of UCP1 and factors related to thyroid function in adults with obesity.Methods and analysisThe current investigation was carried out as a randomized clinical trial (RCT) including 43 adults with obesity who were potential candidates for bariatric surgery. These individuals were randomly divided into two groups: 600 mg of NAC (n = 22) or placebo (n = 21) for a duration of 8 weeks. Visceral adipose tissue was utilized in the context of bariatric surgery to investigate the gene expression of UCP1 and thyroid function. Polymerase chain reaction (PCR) was performed in duplicate for UCP1, DIO2, DIO3, THRα and β, and 18s RNA (as an internal control) using the provided instructions to investigate the expression of the respective genes.ResultsOur findings revealed that after 8 weeks compared to placebo, NAC caused a significant decrease in the expression of the DIO3 gene as one of the genes related to thyroid function and metabolism. However, regarding other related genes, no statistically significant was found (despite the increase in UCP1, DIO2, and THRα expression and decrease in THRβ expression). In addition, after adjustment of possible confounders, no significant effect was observed on anthropometric factors and serum levels of thyroid hormones.ConclusionThe results of this study indicate that, following an 8-week period, NAC effectively decreases the expression of the DIO3 gene in the visceral fat tissue, in comparison to the placebo.

Abstract PO5-24-11: An integrated approach for comprehensive molecular and tumor microenvironment characterization of invasive lobular carcinoma

Abstract Introduction: Although recent studies have shown that invasive lobular carcinoma (ILC) is associated with worse long-term outcomes compared to invasive breast cancer of no special type (NST), they are treated in a similar manner. Therefore, classification approaches to help understand the molecular characteristics associated with the different BC subtypes are needed to personalize therapy. Here, we describe an integrated analytical approach to comprehensively characterize ILC samples. Methods: We collected genomic and transcriptomic data for 16,087 ILC and NST samples, with clinical and pathological annotation, from 59 datasets and used an internally developed algorithm based on clustering performed after gene expression analysis to classify them into 5 intrinsic subtypes: Basal, Luminal A (LumA), Luminal B (LumB), HER2 high, and HER2 low. We performed gene set enrichment analyses and utilized the DESeq2 algorithm to perform differential expression analysis of RNA-seq data. We performed molecular grade subtyping using methods described by Antysheva et al. (Cancer Res., 2022). Samples that were listed as ILC or had an inactivated CDH1 gene by mutation, deletion or low expression (< −2.5 MAD after median scaling) were defined as having an ILC histomolecular subtype. Using methods described by Bagaev et. al. (Cancer Cell, 2021), 29 functional gene expression signatures were selected, and unsupervised dense Louvain clustering was performed to identify TME subtypes. The Mann-Whitney U test was used for statistical analysis. The tertiary lymphoid structures (TLS) gene signature was evaluated using methods described by Sautès-Fridman et al. (Nat. Rev. Cancer, 2019). Results: In the ILC samples (n=1,887), we identified LumA (46%), LumB (40%), Basal (8%,), HER2 high (3%), and HER2 low (3%) subtypes. In contrast, the NST samples were classified as LumB (41%), LumA (25%), Basal (19%), HER2 high (9%), and HER2 low (5%). Molecular grade subtyping revealed that 67% of ILC samples were low grade and 33% were high grade, compared to NST where 55% were high grade and 45% were low grade. Notably, among high-grade ILC, LumB (64%) and Basal (23%) subtypes were predominant. Key differentially expressed genes included downregulated CDH1 and upregulated MMP23B, IGF1, and TFAP2B across LumA and LumB ILC samples. Further analysis revealed downregulation of TACSTD2 and CDH3 in the Basal subtype for ILC samples compared to NST samples. Transcriptomic-based TME subtyping revealed distinct TME distributions across the BC subtypes and molecular grades for ILC samples (Table 1). In high-grade ILC LumB samples, 38% had a Desert (D; predictive of poor immunotherapy response) and 39% had an Immune-Enriched (IE; predictive of favorable immunotherapy response) TME. In low-grade ILC LumB samples we found that while 51% had a D TME, only 14% had an IE TME. We found an overrepresentation of the TLS signature [Solid TLS] in ILC compared to NST samples, and higher matrix remodeling and CAF signatures in LumA compared to the LumB subtype among low-grade ILC samples. Samples with high CD274 expression levels had higher percentages of T cells and M1 macrophages, and LumA samples had significantly higher (p < 0.001) CD274 expression compared to the other BC subtypes. Conclusion: These results provide in-depth molecular and tumor microenvironment characterization of ILC. Further optimization of this analytical approach could lead to the development of more effective therapeutic strategies. Table 1. ILC subtypes classification Citation Format: Jason Mouabbi, Konstantin Chernyshov, Oleg Baranov, Vladimir Kushnarev, Polina Turova, Anna Butusova, Sofia Menshikova, Jessica Brown, Nikita Kotlov, Patrick Clayton, Krystle Nomie, Nathan Fowler, Debu Tripathy. An integrated approach for comprehensive molecular and tumor microenvironment characterization of invasive lobular carcinoma [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 PO5-24-11.