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Results for “mutation scanning”

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At least 19 recordsLinked to original sources

PubMed2026

Deep mutational scan of the pore of the cold-sensing TRPM8 channel.

Members of the Transient Receptor Potential (TRP) family of ion channels have a nearly ubiquitous role in human physiology, tuning cell signaling to remarkably diverse physical and chemical stimuli. Although there is extensive structural data on TRP channels, a systematic and unbiased interrogation of structure-function relations in these proteins is required to fully elucidate their mechanisms of function. By focusing on a critical pore region of the TRPM8 channel, which is the main detector of cold and cooling agents in sensory neurons, we show how deep mutational scanning can be used in combination with the available structural data to understand how TRP channels respond to stimuli. We define a novel mechanism whereby the extracellular pore loop, which has only been resolved in structures representing desensitized states of the channel, plays an essential role in the response of TRPM8 to menthol or cold by coordinating the movement of the S6 helices that line and gate the pore, and the ion-selectivity filter that binds permeant cations. Moreover, our screen reveals sequence determinants along the S6 helices that explain how their architecture sustains gating and, together, provide strong support for a structural mechanism of TRPM8 pore opening in response to menthol and cold.

Journal Article↗

PubMed2025

Mutational scanning of TnpB reveals latent activity for genome editing.

TnpB is a diverse family of RNA-guided endonucleases associated with prokaryotic transposons. Due to their small size and putative evolutionary relationship to CRISPR-Cas12, TnpB enzymes hold significant potential for genome editing. However, most TnpBs lack robust gene editing activity, and unbiased profiling of mutational effects on editing activity has not been explored. Here, we mapped comprehensive sequence-function landscapes of a TnpB ribonucleoprotein and discovered many activating mutations in both the protein and RNA. One- and two-position RNA mutants outperform existing variants, highlighting the utility of systematic RNA scaffold mutagenesis. Leveraging the protein's mutational landscape, we identified enhanced TnpB variants from a combinatorial library of activating mutations. These variants enhanced editing in human cells, N. benthamiana, pepper, and rice, with up to a fifty-fold increase compared to wild-type TnpB. These findings highlight previously unknown elements critical for regulating TnpB endonuclease activity and reveal surprising latent activity accessible through mutation.

Journal Article↗

PubMed2025

Phenotypic pleiotropy of missense variants in human B cell confinement receptor P2RY8.

Missense variants can have pleiotropic effects on protein function, and predicting these effects can be difficult. We performed near-saturation deep mutational scanning of P2RY8, a G protein-coupled receptor that promotes germinal center B cell confinement. We assayed the effect of each variant on surface expression, migration, and proliferation. We delineated variants that affected both expression and function, affected function independently of expression, and discrepantly affected migration and proliferation. We also used cryo-electron microscopy to determine the structure of activated, ligand-bound P2RY8, providing structural insights into the effects of variants on ligand binding and signal transmission. We applied the deep mutational scanning results to both improve computational variant effect predictions and to characterize the phenotype of germline variants and lymphoma-associated variants. Together, our results demonstrate the power of integrating deep mutational scanning, structure determination, and in silico prediction to advance the understanding of a receptor important in human health.

Humans↗

PubMed2023

Towards mechanistic models of mutational effects: Deep learning on Alzheimer's Aβ peptide.

Deep Mutational Scanning (DMS) has enabled multiplexed measurement of mutational effects on protein properties, including kinematics and self-organization, with unprecedented resolution. However, potential bottlenecks of DMS characterization include experimental design, data quality, and depth of mutational coverage. Here, we apply deep learning to comprehensively model the mutational effect of the Alzheimer's Disease associated peptide Aβ42 on aggregation-related biochemical traits from DMS measurements. Among tested neural network architectures, Convolutional Neural Networks and Recurrent Neural Networks are found to be the most cost-effective models with high performance even under insufficiently-sampled DMS studies. While sequence features are essential for satisfactory prediction from neural networks, geometric-structural features further enhance the prediction performance. Notably, we demonstrate how mechanistic insights into phenotype may be extracted from the neural networks themselves suitably designed. This methodological benefit is particularly relevant for biochemical systems displaying a strong coupling between structure and phenotype such as the conformation of Aβ42 aggregate and nucleation, as shown here using a Graph Convolutional Neural Network (GCN) developed from the protein atomic structure input. In addition to accurate imputation of missing values (which here ranged up to 55% of all phenotype values at key residues), the mutationally-defined nucleation phenotype generated from a GCN shows improved resolution for identifying known disease-causing mutations relative to the original DMS phenotype. Our study suggests that neural network derived sequence-phenotype mapping can be exploited not only to provide direct support for protein engineering or genome editing but also to facilitate therapeutic design with the gained perspectives from biological modeling.

Alzheimer's disease↗

PubMed2025

Robustness of Ancestral Sequence Reconstruction to Among-site and Among-lineage Evolutionary Heterogeneity.

Ancestral sequence reconstruction is typically performed using homogeneous evolutionary models, which assume that the same substitution propensities affect all sites and lineages. These assumptions are routinely violated: heterogeneous structural and functional constraints favor different amino acids at different sites, and these constraints often change among lineages as epistatic substitutions accrue at other sites. To evaluate how violations of the homogeneity assumption affect ancestral sequence reconstruction under realistic conditions, we developed site-specific substitution models and parameterized them using data from deep mutational scanning experiments on three protein families; we then used these models to perform ancestral sequence reconstruction on the empirical alignments and on alignments simulated under heterogeneous conditions derived from the experiments. Extensive among-site and -lineage heterogeneity is present in these datasets, but the sequences reconstructed from empirical alignments are almost identical when heterogeneous or homogeneous models are used for ancestral sequence reconstruction. Using models fit to deep mutational scanning data from distantly related proteins in which mutational effects are very different also has a minimal impact on ancestral sequence reconstruction. The rare differences occur primarily where phylogenetic signal is weak-at fast-evolving sites and nodes connected by long branches. When ancestral sequence reconstruction is performed on simulated data, errors in the reconstructed sequences become more likely as branch lengths increase, but incorporating heterogeneity into the model does not improve accuracy. These data establish that ancestral sequence reconstruction is robust to unincorporated realistic forms of evolutionary heterogeneity, because the primary determinant of ancestral sequence reconstruction is phylogenetic signal, not the substitution model. The best way to improve accuracy is therefore not to develop more elaborate models but to apply ancestral sequence reconstruction to densely sampled alignments that maximize phylogenetic signal at the nodes of interest.

Phylogeny↗

PubMed2026

Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1.

BACKGROUND: Drug resistance is a constantly evolving challenge. The allosteric inhibitor asciminib is a novel therapy for chronic myelogenous leukemia (CML) that targets the myristoyl pocket of the BCR::ABL1 kinase. While it can overcome resistance to active-site inhibitors like imatinib, new resistance mutations to asciminib are emerging. The complete landscape of these mutations, particularly those outside the kinase domain or those arising from epistatic interactions between mutations, are not well understood. METHODS: This study employed a dual functional genomics approach in CML cell line models. A high-throughput adenosine base editing (ABE) screen was used to identify broad hotspots of asciminib resistance across the entire BCR::ABL1 protein. Deep mutational scanning (DMS) was then used to create a high-resolution map of all possible amino acid changes within these hotspots. An "edit-on-edit" screen was performed to investigate epistasis by introducing a library of mutations into a cell line that was pre-edited to incorporate the common imatinib-resistance mutation, Y253H. Finally, a novel Förster resonance energy transfer (FRET) biosensor was developed to measure the conformational state of BCR::ABL1 in live cells and link it to drug sensitivity. RESULTS: The screens identified 279 asciminib resistance mutations and revealed resistance hotspots distributed across the SH3, SH2, and kinase domains, in contrast to imatinib resistance, which is largely confined to the kinase domain. The study uncovered a potent epistatic interaction between a mutation in the SH3 domain (V73A) and a mutation in the kinase domain P-loop (Y253H), which synergistically conferred high-level resistance. The FRET biosensor demonstrated that asciminib resistance mutations tend to destabilize the "closed" inactive conformation of the ABL1 kinase. CONCLUSIONS: The landscape of asciminib resistance is broader and more complex than previously appreciated, involving mutations across multiple domains that disrupt ABL1 autoinhibition. Epistasis between mutations acquired during sequential therapies can create unexpected and potent resistance. However, these diverse genetic resistance mechanisms converge on a single biophysical measurement of the openness of the active ABL1 conformation. This provides a unified framework for understanding asciminib resistance and underscores the need for routine clinical resistance monitoring to include the SH3 and SH2 domains in first line and later line therapy.

Fusion Proteins, bcr-abl↗

PubMed2026

A two-factor authentication mechanism licenses pilins for pilus assembly in gram-positive bacteria.

Gram-positive bacteria display virulence-associated pili that facilitate adhesion and biofilm formation. These pili are covalently polymerized by class C sortase enzymes, which selectively recognize their cognate pilin substrates amid numerous cell wall sorting signal (CWSS)-bearing proteins. The molecular basis for this stringent substrate specificity has remained unclear. Here, we develop a rapid, quantitative fluorescence-activated cell sorting assay to monitor pilus assembly in Corynebacterium diphtheriae, enabling high-throughput analysis of SpaA pilin and SrtA sortase variants. Using this platform, together with molecular modeling and dynamics simulations, we show that SrtA engages nearly the entire SpaA CWSS to form a membrane-embedded complex that incorporates not only the LPXTG motif but also its connector and transmembrane helix elements. Formation of this interface displaces an inhibitory active-site lid and activates the enzyme to load the pilin substrate. Systematic CWSS swapping experiments and deep mutational scanning further support this model, demonstrating that noncognate pilins are excluded because they fail to form the required interface. Conversely, SrtA variants with an artificially unlatched lid bypass the need for this interface, indicating that membrane-driven complex formation is important for substrate licensing. Together, these findings define a "two-factor authentication" mechanism for pilus assembly in gram-positive bacteria: class C sortases first verify pilin identity by forming a membrane-embedded interface that activates the enzyme, then they recognize the LPXTG motif to initiate loading and crosslinking. This work provides a unified molecular framework for selective pilin incorporation in gram-positive bacteria and identifies potential vulnerabilities in the licensing machinery that may be exploited therapeutically.

Fimbriae, Bacterial↗

PubMed2024

Molecular basis for antibody recognition of multiple drug-peptide/MHC complexes.

The HapImmuneTM platform exploits covalent inhibitors as haptens for creating major histocompatibility complex (MHC)-presented tumor-specific neoantigens by design, combining targeted therapies with immunotherapy for the treatment of drug-resistant cancers. A HapImmune antibody, R023, recognizes multiple sotorasib-conjugated KRAS(G12C) peptides presented by different human leukocyte antigens (HLAs). This high specificity to sotorasib, coupled with broad HLA-binding capability, enables such antibodies, when reformatted as T cell engagers, to potently and selectively kill sotorasib-resistant KRAS(G12C) cancer cells expressing different HLAs upon sotorasib treatment. The loosening of HLA restriction could increase the patient population that can benefit from this therapeutic approach. To understand the molecular basis for its unconventional binding capability, we used single-particle cryogenic electron microscopy to determine the structures of R023 bound to multiple sotorasib-peptide conjugates presented by different HLAs. R023 forms a pocket for sotorasib between the VH and VL domains, binds HLAs in an unconventional, angled way, with VL making most contacts with them, and makes few contacts with the peptide moieties. This binding mode enables the antibody to accommodate different hapten-peptide conjugates and to adjust its conformation to different HLAs presenting hapten-peptides. Deep mutational scanning validated the structures and revealed distinct levels of mutation tolerance by sotorasib- and HLA-binding residues. Together, our structural information and sequence landscape analysis reveal key features for achieving MHC-restricted recognition of multiple hapten-peptide antigens, which will inform the development of next-generation therapeutic antibodies.

Humans↗

PubMed2025

Decoding missense variants pleiotropy in the immune GPCR P2RY8.

G protein-coupled receptors (GPCRs) form the largest family of cell surface receptors and remain a central focus in pharmacology and drug discovery. Despite extensive structural and pharmacological studies, the functional impact of missense variation across GPCRs remains poorly understood, particularly for receptors involved in immune regulation. In this issue of Cell Genomics, LaFlam et al.1 systematically map P2RY8 variant functions using deep mutational scanning (DMS) combined with structural biology approaches, revealing pleiotropy and mechanisms linking GPCR variation to B cell confinement and lymphoma.

Humans↗

PubMed2026

Discovery and Engineering of a Rat Endogenous Retrovirus Reverse Transcriptase for Efficient Prime Editing.

CRISPR-based prime editors (PEs) install precise edits into genomic DNA without generating double-strand breaks. Their editing efficiency is highly dependent on reverse transcriptases (RTs), but efficient RT candidates remain limited. Here, we identified 19 novel active RTs by screening 558 candidates. Among them, RERV-RT, derived from Rattus norvegicus, exhibited the highest activity. Through structure-guided engineering and deep mutational scanning, we developed an optimized variant, enRERV-RT, which outperforms conventional M-MLV-RT-based PE systems by 1.20-fold in mammalian and plant cells, and by 1.88-fold at hard-to-edit loci, while enabling precise multiplex editing of functionally relevant genes. Additionally, we developed a high-throughput platform, TRAP-seq-PE, to systematically evaluate prime editor performance. Across diverse mutation types, we found that PE systems based on enRERV-RT exhibited higher editing efficiencies than those based on M-MLV-RT. Collectively, our work establishes a versatile, high-efficiency PE system, thereby facilitating advances in clinical gene therapy and precise crop breeding.

Animals↗

PubMed2025

Dosa: A method to covalently barcode proteins for high throughput biochemistry.

Deep mutational scanning couples a protein's activity to DNA sequencing for high throughput assessment of the effects of all single amino acid substitutions, but it largely uses indirect assays, like growth, as proxy for protein activity. Here, we covalently link variant proteins in vivo to an RNA barcode by fusing them to E. coli tRNA (m5U54) methyltransferase TrmA (E358Q), which forms a covalent bond with a tRNA stem-loop. Following cell lysis, variant proteins are separated in vitro according to their biochemical properties and identified by their barcodes. We use this method, Dosa, to analyze a large pool of FLAG epitope variants for binding to an anti-FLAG antibody, to profile the cleavage preferences of variants of enteropeptidase and human rhinovirus 3C protease, and to measure the solubility of several hundred Aβ(1-42) variants. This method should be amenable to numerous biochemical assays with proteins produced in E. coli or mammalian cells.

Protein display↗

PubMed2026

LDLR Variant Classification Through Activity-Normalized Prime Editing Screening.

BACKGROUND: Inherited variants in the LDL (low-density lipoprotein) receptor (LDLR) gene are the most common cause of familial hypercholesterolemia, significantly increasing coronary artery disease risk. Early identification of pathogenic LDLR variants enables prompt lipid-lowering therapy and cascade testing of at-risk relatives; however, most LDLR variants observed in the population have uncertain or absent clinical classifications, leaving many patients without actionable information. METHODS: We developed the first activity-normalized prime editing screening pipeline to measure the impact of 5184 LDLR coding variants on LDL-cholesterol (LDL-C) uptake. Each prime editing guide RNA is paired with a genotypic outcome reporter to correct for variable editing efficiency, overcoming a key limitation of previous pooled genome editing screens. A statistical framework further improves variant effect estimates by jointly analyzing all missense variants at each amino acid position. RESULTS: We show that prime editing of the reporter construct correlates with endogenous variant installation frequency, validating the activity normalization approach. The resulting scores capture a continuous spectrum of functional effects, robustly separate pathogenic versus benign ClinVar variants, and show concordance with LDL-C levels in UK Biobank participants. We calibrate functional evidence strengths to the ACMG/AMP variant interpretation framework, enabling integration into a clinical variant classification workflow. By combining functional, computational, population, and contextual evidence, 322 of 434 LDLR variants currently classified as variants of uncertain significance, conflicting, or absent from ClinVar appear to meet evidence thresholds for reclassification and can be prioritized for expert review, substantially expanding the pool of actionable variant classifications. The screen also reveals a cluster of gain-of-function variants in LDLR class A repeat 5, at least some of which enhance LDL-C uptake through increased apolipoprotein B interaction, with implications for therapeutic genome editing. Last, prime editing uniquely detects splice-altering coding variants missed by cDNA-based screens and pathogenicity predictors, revealing an advantage of endogenous variant installation. CONCLUSIONS: Altogether, activity-normalized prime editing provides a scalable framework for LDLR variant classification that substantially expands the proportion of variants with evidence for genetic diagnosis and reveals novel biology with therapeutic relevance.

CRISPR screening↗

PubMed2025

Structural and thermodynamic impact of oncogenic mutations on the nucleosome core particle.

The nucleosome core particle is essential for chromatin structure and function, serving as the fundamental unit of eukaryotic chromatin. Oncogenic mutations in core histones disrupt chromatin dynamics, altering DNA repair and transcription processes. Here, we investigate the molecular consequences of two mutations-H2BE76K and H4R92T-using 36 μs of all-atom molecular dynamics simulations and experimental biophysical assays. These mutations destabilize the H2B-H4 interface by disrupting critical salt bridges and hydrogen bonds, reducing binding free energy at this interface. Principal-component analysis reveals altered helix conformations and increased interhelical distances in mutant systems. Thermal stability assays and differential scanning calorimetry confirm that these mutations lower the dimer dissociation temperature and reduce enthalpy compared with the wild-type. Taken together, our results elucidate how these mutations compromise nucleosome stability and propose mechanisms through which they could modulate chromatin accessibility and gene dysregulation in cancer.

Nucleosomes↗

PubMed2024

Comparative Studies on Bulky DNA Damage Binding by Nucleotide Excision Repair Proteins Using Surface Plasmon Resonance, Differential Scanning Fluorometry, and DNase I Footprinting.

Nucleotide excision repair is a crucial cellular mechanism that ensures genomic stability, thereby preventing mutations that can lead to cancer. The human XPC and its yeast ortholog Rad4 protein complexes are central to this process and were the focus of the study. We used surface plasmon resonance and differential scanning fluorimetry to study the binding characteristics of XPC and Rad4 when bound to the bulky cluster di-FAAF-containing 55-mer duplex DNA. Our findings revealed that XPC binds 10 times more significant affinity to control and di-FAAF-modified DNA than Rad4 with greater protein-DNA interactions. Differential scanning fluorimetry indicates that Rad4 causes comparatively more significant conformational changes upon complexation with the damaged DNA. We conducted DNase I footprinting of the Rad4/DNA complex for the first time by determining the regions protected from DNase I digestion. The DNA at the lesion is entirely resistant to digestion by DNase I in the absence of Rad4 several nucleotides to the 3'-side of the first FAAF lesion. The lack of DNase I cleavage at the lesions did not change upon adding Rad4. However, in the presence of Rad4, a footprint is observed on the 7-nucleotide region (5'-TGGTGAT-3') of the complementary strand to the 3' side of the lesion.

Surface Plasmon Resonance↗

PubMed2026

Sexual selection purges mutation load, but not overall genetic diversity, decreasing vulnerability to extinction.

Theory suggests sexual selection will enhance population viability by purging deleterious alleles. However, direct genomic evidence for this fundamental idea is scarce and contradictory. We combined long-term experimental evolution with whole-genome resequencing to directly test how sexual selection affects mutation load, genomic divergence, and extinction risk in small populations (maximum Ne = 40) of Tribolium castaneum. After 156 generations, populations evolving under strong sexual selection carried substantially fewer deleterious alleles than populations under weak sexual selection, based on both individual-level estimates of missense and nonsense variants and population-level Rxy analyses, indicating more efficient purging of deleterious alleles. In contrast, nucleotide diversity and runs of homozygosity were similar across treatments, indicating that purging acted most strongly on deleterious variation, and that reduced mutation load in these small populations under strong sexual selection was not explained by demographic effects. Importantly, population-level mutation load estimates best explained extinction risk under inbreeding, directly linking sexual selection to purging and population viability. Genome scans of high and low sexual selection populations revealed peaks of divergence, which included genes involved in courtship, sex discrimination, and seminal fluid proteins. Our results provide direct genomic evidence that sexual selection can reduce mutation load without eroding standing genetic diversity and thus adaptive potential, while driving adaptive divergence in reproductive traits. This beneficial purging may help explain the widespread prevalence of sexual reproduction in nature despite inherent costs and have important ramifications as to how we manage populations of conservation concern.

Animals↗

PubMed2026

EscaPRRS-ORF5: a structure-aware evolutionary framework for prioritizing immune escape-prone variants in porcine reproductive and respiratory syndrome virus.

MOTIVATION: Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is a rapidly evolving RNA virus causing significant economic losses, posing a formidable challenge to vaccine efficacy due to its high mutational variability and immune escape. As the viral mutants evolve, their ability to sustain in population is driven by a range of host biology factors such as receptor binding, fusion, and uncoating. Existing tools that predict viral fitness and escape propensities rely heavily on extensive, up-to-date sequence data and lack integration of biochemical host interactions, limiting mechanistic understanding of the mutational landscape. We introduce Esca, a sequence-only toolchain framework that identifies immune escape-prone residues by exhaustively scanning each residue position for all amino acid substitutions using a Bayesian Variational Autoencoder (VAE) trained on protein language model embeddings. We demonstrate Esca on the GP5(ORF5) glycoprotein of PRRSV (EscaPRRS-ORF5) by training on ESM-2 embeddings of 32 146 GP5 sequences (2015-2022) spanning 140 sub-lineages. RESULTS: Despite being trained only on GP5 sequence data, EscaPRRS-ORF5 recovered 85.7% of the surface-exposed receptor binding interfaces as escape-prone regions. We use a mutation-sensitive fitness scoring scheme that goes beyond Hamming distances, to predict antibody escape tendencies, supporting surveillance of (re) emerging PRRSV variants. We do not claim that ORF5 alone captures PRRSV evolution or serves as a surveillance endpoint; rather, Esca offers a scalable path toward whole-genome, structure-aware surveillance. AVAILABILITY AND IMPLEMENTATION: EscaPRRS-ORF5 is freely available at https://doi.org/10.6084/m9.figshare.32661033 with an interactive Colab notebook at https://colab.research.google.com/drive/1TEgzAhPwvNAZ01VXeJbIFibfri2jnDA5? usp=sharing.

Porcine respiratory and reproductive syndrome viru↗

PubMed2026

SCAN: A sample-to-answer cross-priming isothermal assay for on-site virus detection with RT-qPCR sensitivity and genomically similar virus differentiation specificity.

Genomically similar viruses often differ in pathogenicity and host tropism due to specific mutations, and failure to distinguish them risks misdiagnosis and ineffective control. Molecular methods can differentiate such viruses but require laboratory settings and skilled personnel, while field-deployable immunological methods suffer from cross-reactivity. To address this challenge, we developed SCAN (Sample-to-answer Cross-priming isothermal amplification Assay with Nucleic acid strip), a general framework for on-site detection of genomically similar viruses. Comparative bioinformatics of isolation and sequencing data identifies key conserved differential determinants for primer design, ensuring specificity and reducing non-specific amplification. A one-tube cross-priming isothermal amplification (CPA) enables rapid target amplification without thermal cycling, and the products are visually detected on a nucleic acid strip. All steps are integrated into a handheld, lightweight device (9.9 × 4.4 × 3.3 cm, <200 g) that also prevents aerosol contamination. Using transmissible gastroenteritis virus (TGEV) and porcine respiratory coronavirus (PRCV), the latter a natural mutant of TGEV, as a model, SCAN achieves a detection limit of 102 copies/μL with sensitivity comparable to RT-qPCR and supports sample-to-answer testing within 80 min and simple operations. With verified high sensitivity, specificity, and accuracy, as well as field usability, SCAN provides a generalizable route for developing point-of-care tests (PoCT) that require precise field differentiation of closely related pathogens.

Cross-priming isothermal amplification↗

PubMed2026

Role of ctDNA Tumor Fraction in Selecting Immunotherapy-Based Regimens in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Immune checkpoint blockers (ICB) have transformed advanced non-small cell lung cancer (aNSCLC) treatment, but identifying patients who benefit from adding chemotherapy remains challenging, especially in PD-L1 ≥ 50%. PD-L1 is an imperfect biomarker, highlighting the need for better selection tools. EXPERIMENTAL DESIGN: Liquid biopsy (LBx) assessment was performed using hybrid capture-based next-generation sequencing of plasma cell-free DNA. LBx data, molecular profile, and clinicopathologic data were collected. The predictive and prognostic values of tumor fraction (TF) were assessed using a deidentified nationwide (US-based) NSCLC clinicogenomic database [Clinico-Genomic Database (CGDB)]. An independent cohort with aNSCLC from Gustave Roussy was used to validate the findings and to study the correlation of circulating tumor DNA (ctDNA) TF and total metabolic tumor volume and its molecular correlates. RESULTS: In the CGDB database (n = 965), elevated ctDNA TF was prognostic for worse outcomes on ICBs and, when ≥5%, predictive of benefit from ICB + chemotherapy [HR for real-world progression-free survival 0.58 (0.41-0.82); P = 0.002]. The 5% cutoff for TF was validated in an independent cohort from Gustave Roussy. In 283 patients with paired PET scans, ctDNA TF correlated with metabolic tumor volume (rho = 0.46; P < 0.001) and was influenced by TP53/RB1 mutations. CONCLUSIONS: ctDNA TF integrates disease burden and biology. Patients with high ctDNA TF derive greater benefit from chemoimmunotherapy, supporting its use as a biomarker to guide treatment intensification.

Humans↗