Immunity. 2023 Jul 4:S1074-7613(23)00265-0. doi: 10.1016/j.immuni.2023.06.008. Online ahead of print.

ABSTRACT

Infancy and childhood are critical life stages for generating immune memory to protect against pathogens; however, the timing, location, and pathways for memory development in humans remain elusive. Here, we investigated T cells in mucosal sites, lymphoid tissues, and blood from 96 pediatric donors aged 0-10 years using phenotypic, functional, and transcriptomic profiling. Our results revealed that memory T cells preferentially localized in the intestines and lungs during infancy and accumulated more rapidly in mucosal sites compared with blood and lymphoid organs, consistent with site-specific antigen exposure. Early life mucosal memory T cells exhibit distinct functional capacities and stem-like transcriptional profiles. In later childhood, they progressively adopt proinflammatory functions and tissue-resident signatures, coincident with increased T cell receptor (TCR) clonal expansion in mucosal and lymphoid sites. Together, our findings identify staged development of memory T cells targeted to tissues during the formative years, informing how we might promote and monitor immunity in children.

PMID:37421943 | DOI:10.1016/j.immuni.2023.06.008

Cell Rep. 2023 Jul 7;42(7):112735. doi: 10.1016/j.celrep.2023.112735. Online ahead of print.

ABSTRACT

Mitochondrial Ca2+ overload is proposed to regulate cell death via opening of the mitochondrial permeability transition pore. It is hypothesized that inhibition of the mitochondrial Ca2+ uniporter (MCU) will prevent Ca2+ accumulation during ischemia/reperfusion and thereby reduce cell death. To address this, we evaluate mitochondrial Ca2+ in ex-vivo-perfused hearts from germline MCU-knockout (KO) and wild-type (WT) mice using transmural spectroscopy. Matrix Ca2+ levels are measured with a genetically encoded, red fluorescent Ca2+ indicator (R-GECO1) using an adeno-associated viral vector (AAV9) for delivery. Due to the pH sensitivity of R-GECO1 and the known fall in pH during ischemia, hearts are glycogen depleted to decrease the ischemic fall in pH. At 20 min of ischemia, there is significantly less mitochondrial Ca2+ in MCU-KO hearts compared with MCU-WT controls. However, an increase in mitochondrial Ca2+ is present in MCU-KO hearts, suggesting that mitochondrial Ca2+ overload during ischemia is not solely dependent on MCU.

PMID:37421627 | DOI:10.1016/j.celrep.2023.112735

Clin Exp Med. 2023 Jul 8. doi: 10.1007/s10238-023-01124-y. Online ahead of print.

ABSTRACT

Multiple myeloma (MM) is a cancer of terminally differentiated plasma cells. MM remains incurable, but overall survival of patients has progressively increased over the past two decades largely due to novel agents such as proteasome inhibitors (PI) and the immunomodulatory agents. While these therapies are highly effective, MM patients can be de novo resistant and acquired resistance with prolonged treatment is inevitable. There is growing interest in early, accurate identification of responsive versus non-responsive patients; however, limited sample availability and need for rapid assays are limiting factors. Here, we test dry mass and volume as label-free biomarkers to monitor early response of MM cells to treatment with bortezomib, doxorubicin, and ultraviolet light. For the dry mass measurement, we use two types of phase-sensitive optical microscopy techniques: digital holographic tomography and computationally enhanced quantitative phase microscopy. We show that human MM cell lines (RPMI8226, MM.1S, KMS20, and AMO1) increase dry mass upon bortezomib treatment. This dry mass increase after bortezomib treatment occurs as early as 1 h for sensitive cells and 4 h for all tested cells. We further confirm this observation using primary multiple myeloma cells derived from patients and show that a correlation exists between increase in dry mass and sensitivity to bortezomib, supporting the use of dry mass as a biomarker. The volume measurement using Coulter counter shows a more complex behavior; RPMI8226 cells increase the volume at an early stage of apoptosis, but MM.1S cells show the volume decrease typically observed with apoptotic cells. Altogether, this cell study presents complex kinetics of dry mass and volume at an early stage of apoptosis, which may serve as a basis for the detection and treatment of MM cells.

PMID:37421589 | DOI:10.1007/s10238-023-01124-y

Entropy (Basel). 2022 Oct 1;24(10):1402. doi: 10.3390/e24101402.

ABSTRACT

This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field.

PMID:37420422 | DOI:10.3390/e24101402

Entropy (Basel). 2022 Sep 27;24(10):1368. doi: 10.3390/e24101368.

ABSTRACT

Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.

PMID:37420388 | DOI:10.3390/e24101368

Neuromuscul Disord. 2023 Jun 11:S0960-8966(23)00147-5. doi: 10.1016/j.nmd.2023.05.010. Online ahead of print.

ABSTRACT

Myotonic dystrophy type 1 is characterized by neuromuscular degeneration. Our objective was to compare change in white matter microstructure (fractional anisotropy, radial and axial diffusivity), and functional/clinical measures. Participants underwent yearly neuroimaging and neurocognitive assessments over three-years. Assessments encompassed full-scale intelligence, memory, language, visuospatial skills, attention, processing speed, and executive function, as well as clinical symptoms of muscle/motor function, apathy, and hypersomnolence. Mixed effects models were used to examine differences. 69 healthy adults (66.2% women) and 41 DM1 patients (70.7% women) provided 156 and 90 observations, respectively. There was a group by elapsed time interaction for cerebral white matter, where DM1 patients exhibited declines in white matter (all p<0.05). Likewise, DM1 patients either declined (motor), improved more slowly (intelligence), or remained stable (executive function) for functional outcomes. White matter was associated with functional performance; intelligence was predicted by axial (r = 0.832; p<0.01) and radial diffusivity (r = 0.291, p<0.05), and executive function was associated with anisotropy (r = 0.416, p<0.001), and diffusivity (axial: r = 0.237, p = 0.05 and radial: r = 0.300, p<0.05). Indices of white matter health are sensitive to progression in DM1. These results are important for clinical trial design, which utilize short intervals to establish treatment efficacy.

PMID:37419717 | DOI:10.1016/j.nmd.2023.05.010

Kidney Int. 2023 Jul 5:S0085-2538(23)00487-8. doi: 10.1016/j.kint.2023.06.029. Online ahead of print.

ABSTRACT

Fabry disease is a rare disorder caused by variations in the alpha-galactosidase gene. To a degree, Fabry disease is manageable via enzyme replacement therapy (ERT). By understanding the molecular basis of Fabry nephropathy (FN) and ERT's long-term impact, here we aimed to provide a framework for selection of potential disease biomarkers and drug targets. We obtained biopsies from eight control individuals and two independent FN cohorts comprising 16 individuals taken prior to and after up to ten years of ERT, and performed RNAseq analysis. Combining pathway-centered analyses with network-science allowed computation of transcriptional landscapes from four nephron compartments and their integration with existing proteome and drug-target interactome data. Comparing these transcriptional landscapes revealed high inter-cohort heterogeneity. Kidney compartment transcriptional landscapes comprehensively reflected differences in FN cohort characteristics. With exception of a few aspects, in particular arteries, early ERT in patients with classical Fabry could lastingly revert FN gene expression patterns to closely match that of control individuals. Pathways nonetheless consistently altered in both FN cohorts pre-ERT were mostly in glomeruli and arteries and related to the same biological themes. While keratinization-related processes in glomeruli were sensitive to ERT, a majority of alterations, such as transporter activity and responses to stimuli, remained dysregulated or reemerged despite ERT. Inferring an ERT-resistant genetic module of expressed genes identified 69 drugs for potential repurposing matching the proteins encoded by 12 genes. Thus, we identified and cross-validated ERT-resistant gene product modules that, when leveraged with external data, allowed estimating their suitability as biomarkers to potentially track disease course or treatment efficacy and potential targets for adjunct pharmaceutical treatment.

PMID:37419447 | DOI:10.1016/j.kint.2023.06.029

Sci Total Environ. 2023 Jul 5:165330. doi: 10.1016/j.scitotenv.2023.165330. Online ahead of print.

ABSTRACT

The use of antibacterial and disinfection products is increasing in recent years. Para-chloro-meta-xylenol (PCMX), a widely used antimicrobial agent, has been detected in various environments. Herein, the impacts of PCMX with long-term exposure on anaerobic sequencing batch reactors were investigated. The high concentration (50 mg/L, GH group) PCMX severely inhibited the nutrient removal process, and the low concentration group (0.5 mg/L, GL group) slightly affected the removal efficiency which was recovered after 120 days of adaptation compared to the control group (0 mg/L, GC group). Cell viability tests indicated that PCMX inactivated the microbes. A significant reduction in bacterial α-diversity was observed in the GH but not the GL group. The microbial communities were shifted upon PCMX exposure, among which Olsenella, Novosphingobium, and Saccharibacteria genera incertae Sedis became the predominant genera in the GH groups. Network analyses showed that PCMX significantly reduced the complexity and interactions of the microbial communities, consistent with the negative impacts on bioreactor performance. Real-time PCR analysis indicated that PCMX affected the behavior of antibiotic resistance genes (ARGs), and the relationship between ARGs and bacterial genera gradually became complicated after long-term exposure. Most detected ARGs decreased on Day 60 but increased on Day 120 especially in the GL group, implying the potential risk of environment-relevant concentration of PCMX in the ecosystems. This study provides new insights into the understanding of the impacts and risks of PCMX on wastewater treatment processes.

PMID:37419339 | DOI:10.1016/j.scitotenv.2023.165330

Microb Pathog. 2023 Jul 5:106236. doi: 10.1016/j.micpath.2023.106236. Online ahead of print.

ABSTRACT

Salmonella enterica serovar Gallinarum causes Fowl Typhoid in poultry, and it is host-specific to avian species. The reasons why S. Gallinarum is restricted to avians, and at the same time predominately cause systemic infections in these hosts, are unknown. In the current study, we developed a surgical approach to study gene expression inside the peritoneal cavity of hens to shed light on this. Strains of the host-specific S. Gallinarum, the cattle-adapted S. Dublin and the broad host range serovar, S. Enteritidis, were enclosed in semi-permeable tubes and surgically placed for 4 h in the peritoneal cavity of hens, and for control in a minimal medium at 41.2 °C. Global gene-expression under these conditions was compared between serovars using tiled-micro arrays with probes representing the genome of S. Typhimurium, S. Dublin and S. Gallinarum. Among other genes, genes of SPI-13, SPI-14 and the macrophage survival gene mig-14 were specifically up-regulated in the host-specific serovar, S. Gallinarum, and further studies into the role of these genes in host-specific infection are highly indicated. Analysis of pathways and GO-terms, which were enriched in the host specific S. Gallinarum without being enriched in the two other serovars indicated that host-specificity was characterized by a metabolic fine-tuning as well as unique expression of virulence associated pathways. The cattle adapted serovar S. Dublin differed from the two other serovars by a lack of up-regulation of genes encoded in the virulence associated pathogenicity island 2, and this may explain the inability of this serovar to cause disease in poultry.

PMID:37419218 | DOI:10.1016/j.micpath.2023.106236

Curr Opin Microbiol. 2023 Jul 4;75:102357. doi: 10.1016/j.mib.2023.102357. Online ahead of print.

ABSTRACT

Arbuscular mycorrhizal fungi (AMF) have accompanied the majority of land plants since their evolution in the Devonian period with a symbiotic alliance centered on nutrient exchanges. The exploration of AMF genomes is providing clues to explain major questions about their biology, evolution, and ecology. The dynamics of nuclei across the fungal life cycle, the abundance of transposable elements, and the epigenome landscape are emerging as sources of intraspecific variability, which can be especially important in organisms with no or rare sexual reproduction such as AMF. These features have been hypothesized to support AMF adaptability to a wide host range and to environmental changes. New insights on plant-fungus communication and on the iconic function of phosphate transport were also recently obtained that overall contribute to a better understanding of this ancient and fascinating symbiosis.

PMID:37419003 | DOI:10.1016/j.mib.2023.102357

PLoS One. 2023 Jul 7;18(7):e0288102. doi: 10.1371/journal.pone.0288102. eCollection 2023.

ABSTRACT

Plate-based proteomic sample preparation offers a solution to the large sample throughput demands in the biotechnology field where hundreds or thousands of engineered microbes are constructed for testing is routine. Meanwhile, sample preparation methods that work efficiently on broader microbial groups are desirable for new applications of proteomics in other fields, such as microbial communities. Here, we detail a step-by-step protocol that consists of cell lysis in an alkaline chemical buffer (NaOH/SDS) followed by protein precipitation with high-ionic strength acetone in 96-well format. The protocol works for a broad range of microbes (e.g., Gram-negative bacteria, Gram-positive bacteria, non-filamentous fungi) and the resulting proteins are ready for tryptic digestion for bottom-up quantitative proteomic analysis without the need for desalting column cleanup. The yield of protein using this protocol increases linearly with respect to the amount of starting biomass from 0.5-2.0 OD*mL of cells. By using a bench-top automated liquid dispenser, a cost-effective and environmentally-friendly option to eliminating pipette tips and reducing reagent waste, the protocol takes approximately 30 minutes to extract protein from 96 samples. Tests on mock mixtures showed expected results that the biomass composition structure is in close agreement with the experimental design. Lastly, we applied the protocol for the composition analysis of a synthetic community of environmental isolates grown on two different media. This protocol has been developed to facilitate rapid, low-variance sample preparation of hundreds of samples and allow flexibility for future protocol development.

PMID:37418444 | DOI:10.1371/journal.pone.0288102

PLoS One. 2023 Jul 7;18(7):e0288174. doi: 10.1371/journal.pone.0288174. eCollection 2023.

ABSTRACT

In systems biology, the accurate reconstruction of Gene Regulatory Networks (GRNs) is crucial since these networks can facilitate the solving of complex biological problems. Amongst the plethora of methods available for GRN reconstruction, information theory and fuzzy concepts-based methods have abiding popularity. However, most of these methods are not only complex, incurring a high computational burden, but they may also produce a high number of false positives, leading to inaccurate inferred networks. In this paper, we propose a novel hybrid fuzzy GRN inference model called MICFuzzy which involves the aggregation of the effects of Maximal Information Coefficient (MIC). This model has an information theory-based pre-processing stage, the output of which is applied as an input to the novel fuzzy model. In this preprocessing stage, the MIC component filters relevant genes for each target gene to significantly reduce the computational burden of the fuzzy model when selecting the regulatory genes from these filtered gene lists. The novel fuzzy model uses the regulatory effect of the identified activator-repressor gene pairs to determine target gene expression levels. This approach facilitates accurate network inference by generating a high number of true regulatory interactions while significantly reducing false regulatory predictions. The performance of MICFuzzy was evaluated using DREAM3 and DREAM4 challenge data, and the SOS real gene expression dataset. MICFuzzy outperformed the other state-of-the-art methods in terms of F-score, Matthews Correlation Coefficient, Structural Accuracy, and SS_mean, and outperformed most of them in terms of efficiency. MICFuzzy also had improved efficiency compared with the classical fuzzy model since the design of MICFuzzy leads to a reduction in combinatorial computation.

PMID:37418430 | DOI:10.1371/journal.pone.0288174

J Proteome Res. 2023 Jul 7. doi: 10.1021/acs.jproteome.3c00005. Online ahead of print.

ABSTRACT

Recent advances in nucleic acid sequencing now permit rapid and genome-scale analysis of genetic variation and transcription, enabling population-scale studies of human biology, disease, and diverse organisms. Likewise, advances in mass spectrometry proteomics now permit highly sensitive and accurate studies of protein expression at the whole proteome-scale. However, most proteomic studies rely on consensus databases to match spectra to peptide and protein sequences, and thus remain limited to the analysis of canonical protein sequences. Here, we develop ProteomeGenerator2 (PG2), based on the scalable and modular ProteomeGenerator framework. PG2 integrates genome and transcriptome sequencing to incorporate protein variants containing amino acid substitutions, insertions, and deletions, as well as noncanonical reading frames, exons, and other variants caused by genomic and transcriptomic variation. We benchmarked PG2 using synthetic data and genomic, transcriptomic, and proteomic analysis of human leukemia cells. PG2 can be integrated with current and emerging sequencing technologies, assemblers, variant callers, and mass spectral analysis algorithms, and is available open-source from https://github.com/kentsisresearchgroup/ProteomeGenerator2.

PMID:37418425 | DOI:10.1021/acs.jproteome.3c00005

J Bioenerg Biomembr. 2023 Jul 7. doi: 10.1007/s10863-023-09966-7. Online ahead of print.

ABSTRACT

The individual study of [Formula: see text] and [Formula: see text] dynamics respectively in a [Formula: see text]-cell has yielded limited information about the cell functions. But the systems biology approaches for such studies have received very little attention by the research workers in the past. In the present work, a system-dynamics model for the interdependent [Formula: see text] and [Formula: see text] signaling that controls insulin secretion in a [Formula: see text]-cell has been suggested. A two-way feedback system of [Formula: see text] and [Formula: see text] has been considered and one-way feedback between [Formula: see text] and insulin has been implemented in the model. The finite element method along with the Crank-Nicolson method have been applied for simulation. Numerical results have been used to analyze the impact of perturbations in [Formula: see text] and [Formula: see text] dynamics on insulin secretion for normal and Type-2 diabetic conditions. The results reveal that Type-2 diabetes comes from abnormalities in insulin secretion caused by the perturbation in buffers and pumps (SERCA and PMCA).

PMID:37418135 | DOI:10.1007/s10863-023-09966-7

Elife. 2023 Jul 7;12:e79812. doi: 10.7554/eLife.79812. Online ahead of print.

ABSTRACT

Much of biochemical regulation ultimately controls growth rate, particularly in microbes. Although time-lapse microscopy visualises cells, determining their growth rates is challenging, particularly for those that divide asymmetrically, like Saccharomyces cerevisiae, because cells often overlap in images. Here we present the Birth Annotator for Budding Yeast (BABY), an algorithm to determine single-cell growth rates from label-free images. Using a convolutional neural network, BABY resolves overlaps through separating cells by size and assigns buds to mothers by identifying bud necks. BABY uses machine learning to track cells and determine lineages and estimates growth rates as the rates of change of volumes. Using BABY and a microfluidic device, we show that bud growth is likely first sizer- then timer-controlled, that the nuclear concentration of Sfp1, a regulator of ribosome biogenesis, varies before the growth rate does, and that growth rate can be used for real-time control. By estimating single-cell growth rates and so fitness, BABY should generate much biological insight.

PMID:37417869 | DOI:10.7554/eLife.79812

Front Plant Sci. 2023 Jun 21;14:1227490. doi: 10.3389/fpls.2023.1227490. eCollection 2023.

NO ABSTRACT

PMID:37416883 | PMC:PMC10321657 | DOI:10.3389/fpls.2023.1227490

iScience. 2023 Jun 14;26(7):107115. doi: 10.1016/j.isci.2023.107115. eCollection 2023 Jul 21.

ABSTRACT

The histone methyltransferase EZH2 has been studied most extensively in the context of PRC2-dependent gene repression. Accumulating evidence indicates non-canonical functions for EZH2 in cancer contexts including promoting paradoxical gene expression through interactions with transcription factors, including NF-κB in triple negative breast cancer (TNBC). We profile EZH2 and NF-κB factor co-localization and positive gene regulation genome-wide, and define a subset of NF-κB targets and genes associated with oncogenic functions in TNBC that is enriched in patient datasets. We demonstrate interaction between EZH2 and RelA requiring the recently identified transactivation domain (TAD) which mediates EZH2 recruitment to, and activation of certain NF-κB-dependent genes, and supports downstream migration and stemness phenotypes in TNBC cells. Interestingly, EZH2-NF-κB positive regulation of genes and stemness does not require PRC2. This study provides new insight into pro-oncogenic regulatory functions for EZH2 in breast cancer through PRC2-independent, and NF-κB-dependent regulatory mechanisms.

PMID:37416481 | PMC:PMC10319845 | DOI:10.1016/j.isci.2023.107115

Mol Plant. 2023 Jul 5:S1674-2052(23)00178-8. doi: 10.1016/j.molp.2023.07.002. Online ahead of print.

ABSTRACT

Survival of living organisms is fully dependent on their maintenance of genome integrity, being permanently threatened by replication stress in proliferating cells. Although the plant DNA damage response (DDR) regulator SOG1 has been demonstrated to cope with replicative defects, accumulating evidence points to other pathways functioning independently of SOG1. Here, we have studied the role of the Arabidopsis E2FA and EF2B transcription factors, two well-characterized regulators of DNA replication, in the response to replication stress. Through a combination of reverse genetics and chromatin-immunoprecipitation approaches, we show that E2FA and E2FB share many target genes with SOG1, providing evidence for their involvement in the DDR. Analysis of double and triple mutant combinations revealed that E2FB, rather than E2FA, plays the most prominent role in sustaining growth in the presence of replicative defects, either operating antagonistically or synergistically with SOG1. Reversely, SOG1 aids in overcoming the replication defects of E2FA/E2FB-deficient plants. Our data reveal a complex transcriptional network controlling the replication stress response, in which both E2Fs and SOG1 act as key regulatory factors.

PMID:37415334 | DOI:10.1016/j.molp.2023.07.002

Adv Drug Deliv Rev. 2023 Jul 4:114992. doi: 10.1016/j.addr.2023.114992. Online ahead of print.

ABSTRACT

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. Traditional methods are limited in characterizing these responses to NPs, whereas omics approaches can analyze whole sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and the analytical tools used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

PMID:37414362 | DOI:10.1016/j.addr.2023.114992

Cell Metab. 2023 Jun 28:S1550-4131(23)00215-2. doi: 10.1016/j.cmet.2023.06.005. Online ahead of print.

ABSTRACT

Tumor cell phenotypes and anti-tumor immune responses are shaped by local metabolite availability, but intratumoral metabolite heterogeneity (IMH) and its phenotypic consequences remain poorly understood. To study IMH, we profiled tumor/normal regions from clear cell renal cell carcinoma (ccRCC) patients. A common pattern of IMH transcended all patients, characterized by correlated fluctuations in the abundance of metabolites and processes associated with ferroptosis. Analysis of intratumoral metabolite-RNA covariation revealed that the immune composition of the microenvironment, especially the abundance of myeloid cells, drove intratumoral metabolite variation. Motivated by the strength of RNA-metabolite covariation and the clinical significance of RNA biomarkers in ccRCC, we inferred metabolomic profiles from the RNA sequencing data of ccRCC patients enrolled in 7 clinical trials, and we ultimately identifyied metabolite biomarkers associated with response to anti-angiogenic agents. Local metabolic phenotypes, therefore, emerge in tandem with the immune microenvironment, influence ongoing tumor evolution, and are associated with therapeutic sensitivity.

PMID:37413991 | DOI:10.1016/j.cmet.2023.06.005