Archival single-cell genomics reveals persistent subclones during DCIS progression.

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery.

To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRß chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A∗02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

Structure-based classification predicts drug response in EGFR-mutant NSCLC.

Epidermal growth factor receptor (EGFR) mutations typically occur in exons 18-21 and are established driver mutations in non-small cell lung cancer (NSCLC)1-3. Targeted therapies are approved for patients with 'classical' mutations and a small number of other mutations4-6. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown1,3,7-10. Here we characterize the mutational landscape in 16,715 patients with EGFR-mutant NSCLC, and establish the structure-function relationship of EGFR mutations on drug sensitivity. We found that EGFR mutations can be separated into four distinct subgroups on the basis of sensitivity and structural changes that retrospectively predict patient outcomes following treatment with EGFR inhibitors better than traditional exon-based groups. Together, these data delineate a structure-based approach for defining functional groups of EGFR mutations that can effectively guide treatment and clinical trial choices for patients with EGFR-mutant NSCLC and suggest that a structure-function-based approach may improve the prediction of drug sensitivity to targeted therapies in oncogenes with diverse mutations.

EMT activates exocytotic Rabs to coordinate invasion and immunosuppression in lung cancer.

Epithelial-to-mesenchymal transition (EMT) underlies immunosuppression, drug resistance, and metastasis in epithelial malignancies. However, the way in which EMT orchestrates disparate biological processes remains unclear. Here, we identify an EMT-activated vesicular trafficking network that coordinates promigratory focal adhesion dynamics with an immunosuppressive secretory program in lung adenocarcinoma (LUAD). The EMT-activating transcription factor ZEB1 drives exocytotic vesicular trafficking by relieving Rab6A, Rab8A, and guanine nucleotide exchange factors from miR-148a-dependent silencing, thereby facilitating MMP14-dependent focal adhesion turnover in LUAD cells and autotaxin-mediated CD8+ T cell exhaustion, indicating that cell-intrinsic and extrinsic processes are linked through a microRNA that coordinates vesicular trafficking networks. Blockade of ZEB1-dependent secretion reactivates antitumor immunity and negates resistance to PD-L1 immune checkpoint blockade, an important clinical problem in LUAD. Thus, EMT activates exocytotic Rabs to drive a secretory program that promotes invasion and immunosuppression in LUAD.

Netie: inferring the evolution of neoantigen-T cell interactions in tumors.

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8+ T cell interactions in tumors. Netie was systematically validated and applied to examine the molecular patterns of 3,219 tumors, compiled from a panel of 18 cancer types. We showed that tumors with an increase in immune selection pressure over time are associated with T cells that have an activation-related expression signature. We also identified a subset of exhausted cytotoxic T cells postimmunotherapy associated with tumor clones that newly arise after treatment. These analyses demonstrate how netie enables the interrogation of the relationship between individual neoantigen repertoires and the tumor molecular profiles. We found that a T cell inflammation gene expression profile (TIGEP) is more predictive of patient outcomes in the tumors with an increase in immune pressure over time, which reveals a curious synergy between T cells and neoantigen distributions. Overall, we provide a new tool that is capable of revealing the imprints left by neoantigens during each tumor's developmental process and of predicting how tumors will progress under further pressure of the host's immune system.

A novel statistical method for decontaminating T-cell receptor sequencing data.

The T-cell receptor (TCR) repertoire is highly diverse among the population and plays an essential role in initiating multiple immune processes. TCR sequencing (TCR-seq) has been developed to profile the T cell repertoire. Similar to other high-throughput experiments, contamination can happen during several steps of TCR-seq, including sample collection, preparation and sequencing. Such contamination creates artifacts in the data, leading to inaccurate or even biased results. Most existing methods assume 'clean' TCR-seq data as the starting point with no ability to handle data contamination. Here, we develop a novel statistical model to systematically detect and remove contamination in TCR-seq data. We summarize the observed contamination into two sources, pairwise and cross-cohort. For both sources, we provide visualizations and summary statistics to help users assess the severity of the contamination. Incorporating prior information from 14 existing TCR-seq datasets with minimum contamination, we develop a straightforward Bayesian model to statistically identify contaminated samples. We further provide strategies for removing the impacted sequences to allow for downstream analysis, thus avoiding any need to repeat experiments. Our proposed model shows robustness in contamination detection compared with a few off-the-shelf detection methods in simulation studies. We illustrate the use of our proposed method on two TCR-seq datasets generated locally.

Nuclear miR-451a activates KDM7A and leads to cetuximab resistance in head and neck squamous cell carcinoma.

Cetuximab resistance has been a major challenge for head and neck squamous cell carcinoma (HNSCC) patients receiving targeted therapy. However, the mechanism that causes cetuximab resistance, especially microRNA (miRNA) regulation, remains unclear. Growing evidence suggests that miRNAs may act as "nuclear activating miRNAs" for targeting promoter regions or enhancers related to target genes. This study elucidates a novel mechanism underlying cetuximab resistance in HNSCC involving the nuclear activation of KDM7A transcription via miR-451a. Herein, small RNA sequencing, quantitative real-time polymerase chain reaction (qRT‒PCR) and fluorescence in situ hybridization (FISH) results provided compelling evidence of miR-451a nuclear enrichment in response to cetuximab treatment. Chromatin isolation via RNA purification, microarray analysis, and bioinformatic analysis revealed that miR-451a interacts with an enhancer region in KDM7A, activating its expression and further facilitating cetuximab resistance. It has also been demonstrated that the activation of KDM7A by nuclear miR-451a is induced by cetuximab treatment and is AGO2 dependent. Logistic regression analyses of 87 HNSCC samples indicated the significance of miR-451a and KDM7A in the development of cetuximab resistance. These discoveries support the potential of miR-451a and KDM7A as valuable biomarkers for cetuximab resistance and emphasize the function of nuclear-activating miRNAs.

Cancer plasticity in therapy resistance: Mechanisms and novel strategies.

Therapy resistance poses a significant obstacle to effective cancer treatment. Recent insights into cell plasticity as a new paradigm for understanding resistance to treatment: as cancer progresses, cancer cells experience phenotypic and molecular alterations, corporately known as cell plasticity. These alterations are caused by microenvironment factors, stochastic genetic and epigenetic changes, and/or selective pressure engendered by treatment, resulting in tumor heterogeneity and therapy resistance. Increasing evidence suggests that cancer cells display remarkable intrinsic plasticity and reversibly adapt to dynamic microenvironment conditions. Dynamic interactions between cell states and with the surrounding microenvironment form a flexible tumor ecosystem, which is able to quickly adapt to external pressure, especially treatment. Here, this review delineates the formation of cancer cell plasticity (CCP) as well as its manipulation of cancer escape from treatment. Furthermore, the intrinsic and extrinsic mechanisms driving CCP that promote the development of therapy resistance is summarized. Novel treatment strategies, e.g., inhibiting or reversing CCP is also proposed. Moreover, the review discusses the multiple lines of ongoing clinical trials globally aimed at ameliorating therapy resistance. Such advances provide directions for the development of new treatment modalities and combination therapies against CCP in the context of therapy resistance.

Abnormal global alternative RNA splicing in COVID-19 patients.

Viral infections can alter host transcriptomes by manipulating host splicing machinery. Despite intensive transcriptomic studies on SARS-CoV-2, a systematic analysis of alternative splicing (AS) in severe COVID-19 patients remains largely elusive. Here we integrated proteomic and transcriptomic sequencing data to study AS changes in COVID-19 patients. We discovered that RNA splicing is among the major down-regulated proteomic signatures in COVID-19 patients. The transcriptome analysis showed that SARS-CoV-2 infection induces widespread dysregulation of transcript usage and expression, affecting blood coagulation, neutrophil activation, and cytokine production. Notably, CD74 and LRRFIP1 had increased skipping of an exon in COVID-19 patients that disrupts a functional domain, which correlated with reduced antiviral immunity. Furthermore, the dysregulation of transcripts was strongly correlated with clinical severity of COVID-19, and splice-variants may contribute to unexpected therapeutic activity. In summary, our data highlight that a better understanding of the AS landscape may aid in COVID-19 diagnosis and therapy.

Quantum Interference and Coherent Population Trapping in a Double Quantum Dot.

Quantum interference is a natural consequence of wave-particle duality in quantum mechanics, and is widely observed at the atomic scale. One interesting manifestation of quantum interference is coherent population trapping (CPT), first proposed in three-level driven atomic systems and observed in quantum optical experiments. Here, we demonstrate CPT in a gate-defined semiconductor double quantum dot (DQD), with some unique twists as compared to the atomic systems. Specifically, we observe CPT in both driven and nondriven situations. We further show that CPT in a driven DQD could be used to generate adiabatic state transfer. Moreover, our experiment reveals a nontrivial modulation to the CPT caused by the longitudinal driving field, yielding an odd-even effect and a tunable CPT. Our results broaden the field of CPT, and open up the possibility of quantum simulation and quantum computation based on adiabatic passage in quantum dot systems.

Paradoxical action of PP2A inhibition and its potential for therapeutic sensitization.

The protein phosphatase 2A (PP2A), a serine/threonine phosphatase, is recognized as a tumor suppressor involved in diverse cellular processes and essential for maintaining cell viability in vivo. However, endogenous inhibitors of PP2A such as cancerous inhibitor of PP2A (CIP2A) and endogenous nuclear protein inhibitor 2 of PP2A (SET) counteract the anticancer function of PP2A, promoting tumorigenesis, development, and drug resistance in tumors. Surprisingly though, contrary to conventional understanding, inhibition of the tumor suppressor gene PP2A with exogenous small molecule compounds can enhance the efficacy of cancer treatment and achieve superior tumor inhibition. Moreover, exogenous PP2A inhibitors resensitize cancers to treatment and provide novel therapeutic strategies for drug-resistant tumors, which warrant further investigation.

The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma.

The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

DeepCG: A cell graph model for predicting prognosis in lung adenocarcinoma.

Lung cancer is the first leading cause of cancer-related death in the United States, with lung adenocarcinoma as the major subtype accounting for 40% of all cases. To improve patient survival, image-based prognostic models were developed due to the ready availability of pathological images at diagnosis. However, the application of these models is hampered by two main challenges: the lack of publicly available image datasets with high-quality survival information and the poor interpretability of conventional convolutional neural network models. Here, we integrated matched transcriptomic and H&E staining data from TCGA (The Cancer Genome Atlas) to develop an image-based prognostic model, termed Deep-learning based Cell Graph (DeepCG) model. Instead of survival data, we used a gene signature to predict patient prognostic risks, which was then used as labels for training DeepCG. Importantly, by employing graph structures to capture cell patterns, DeepCG can provide cell-level interpretation, which was more biologically relevant than previous region-level insights. We validated the prognostic values of DeepCG in independent datasets and demonstrated its ability to identify prognostically informative cells in images.

Stereotactic ablative radiotherapy with or without immunotherapy for early-stage or isolated lung parenchymal recurrent node-negative non-small-cell lung cancer: an open-label, randomised, phase 2 trial.

BACKGROUND: Stereotactic ablative radiotherapy (SABR) is the standard treatment for medically inoperable early-stage non-small-cell lung cancer (NSCLC), but regional or distant relapses, or both, are common. Immunotherapy reduces recurrence and improves survival in people with stage III NSCLC after chemoradiotherapy, but its utility in stage I and II cases is unclear. We therefore conducted a randomised phase 2 trial of SABR alone compared with SABR with immunotherapy (I-SABR) for people with early-stage NSCLC. METHODS: We did an open-label, randomised, phase 2 trial comparing SABR to I-SABR, conducted at three different hospitals in TX, USA. People aged 18 years or older with histologically proven treatment-naive stage IA-IB (tumour size ≤4 cm, N0M0), stage IIA (tumour size ≤5 cm, N0M0), or stage IIB (tumour size >5 cm and ≤7 cm, N0M0) as per the American Joint Committee on Cancer version 8 staging system or isolated parenchymal recurrences (tumour size ≤7 cm) NSCLC (TanyNanyM0 before definitive surgery or chemoradiotherapy) were included in this trial. Participants were randomly assigned (1:1; using the Pocock & Simon method) to receive SABR with or without four cycles of nivolumab (480 mg, once every 4 weeks, with the first dose on the same day as, or within 36 h after, the first SABR fraction). This trial was unmasked. The primary endpoint was 4-year event-free survival (local, regional, or distant recurrence; second primary lung cancer; or death). Analyses were both intention to treat (ITT) and per protocol. This trial is registered with ClinicalTrials.gov (NCT03110978) and is closed to enrolment. FINDINGS: From June 30, 2017, to March 22, 2022, 156 participants were randomly assigned, and 141 participants received assigned therapy. At a median 33 months' follow-up, I-SABR significantly improved 4-year event-free survival from 53% (95% CI 42-67%) with SABR to 77% (66-91%; per-protocol population, hazard ratio [HR] 0·38; 95% CI 0·19-0·75; p=0·0056; ITT population, HR 0·42; 95% CI 0·22-0·80; p=0·0080). There were no grade 3 or higher adverse events associated with SABR. In the I-SABR group, ten participants (15%) had grade 3 immunologial adverse events related to nivolumab; none had grade 3 pneumonitis or grade 4 or higher toxicity. INTERPRETATION: Compared with SABR alone, I-SABR significantly improved event-free survival at 4 years in people with early-stage treatment-naive or lung parenchymal recurrent node-negative NSCLC, with tolerable toxicity. I-SABR could be a treatment option in these participants, but further confirmation from a number of currently accruing phase 3 trials is required. FUNDING: Bristol-Myers Squibb and MD Anderson Cancer Center Alliance, National Cancer Institute at the National Institutes of Health through Cancer Center Core Support Grant and Clinical and Translational Science Award to The University of Texas MD Anderson Cancer Center.

Highly Efficient Oral Iguratimod/Polyvinyl Alcohol Nanodrugs Fabricated by High-Gravity Nanoprecipitation Technique for Treatment of Rheumatoid Arthritis.

Rheumatoid arthritis (RA), a systemic autoimmune disease, poses a significant human health threat. Iguratimod (IGUR), a novel disease-modifying antirheumatic drug (DMARD), has attracted great attention for RA treatment. Due to IGUR's hydrophobic nature, there's a pressing need for effective pharmaceutical formulations to enhance bioavailability and therapeutic efficacy. The high-gravity nanoprecipitation technique (HGNPT) emerges as a promising approach for formulating poorly water-soluble drugs. In this study, IGUR nanodrugs (NanoIGUR) are synthesized using HGNPT, with a focus on optimizing various operational parameters. The outcomes revealed that HGNPT enabled the continuous production of NanoIGUR with smaller sizes (ranging from 300 to 1000 nm), more uniform shapes, and reduced crystallinity. In vitro drug release tests demonstrated improved dissolution rates with decreasing particle size and crystallinity. Notably, in vitro and in vivo investigations showcased NanoIGUR's efficacy in inhibiting synovial fibroblast proliferation, migration, and invasion, as well as reducing inflammation in collagen-induced arthritis. This study introduces a promising strategy to enhance and broaden the application of poorly water-soluble drugs.

Amino Acid Variation at Hemagglutinin Position 193 Impacts the Properties of H9N2 Avian Influenza Virus.

Despite active control strategies, including the vaccination program in poultry, H9N2 avian influenza viruses possessing mutations in hemagglutinin (HA) were frequently isolated. In this study, we analyzed the substitutions at HA residue 193 (H3 numbering) of H9N2 and investigated the impact of these mutations on viral properties. Our study indicated that H9N2 circulating in the Chinese poultry have experienced frequent mutations at HA residue 193 since 2013, with viruses that carried asparagine (N) being replaced by those with alanine (A), aspartic acid (D), glutamic acid (E), glycine (G), and serine (S), etc. Our results showed the N193G mutation impeded the multiple cycles of growth of H9N2, and although most of the variant HAs retained the preference for human-like receptors as did the wild-type N193 HA, the N193E mutation altered the preference for both human and avian-like receptors. Furthermore, these mutations substantially altered the antigenicity of H9N2 as measured by both monoclonal antibodies and antisera. In vivo studies further demonstrated that these mutations showed profound impact on viral replication and transmission of H9N2 in chicken. Viruses with D, E, or S at residue 193 acquired the ability to replicate in lungs of the infected chickens, whereas virus with G193 reduced its transmissibility in infected chickens to those in direct contact. Our findings demonstrated that variations at HA residue 193 altered various properties of H9N2, highlighting the significance of the continued surveillance of HA for better understanding of the etiology and effective control of H9N2 in poultry. IMPORTANCE H9N2 are widespread and have sporadically caused clinical diseases in humans. Extensive vaccinations in poultry helped constrain H9N2; however, they might have facilitated the evolution of the virus. It is therefore of importance to monitor the variation of the circulating H9N2 and evaluate its risk to both veterinary and public health. Here, we found substitutions at position 193 of HA from H9N2 circulated since 2013 and assessed the impact of several mutations on viral properties. Our data showed these mutations resulted in substantial antigenic change. N193E altered the binding preference of HA for human-like to both avian and human-like receptors. More importantly, N193G impaired the growth of H9N2 and its transmission in chickens, whereas mutations from N to D, E, and S enhanced the viral replication in lungs of chickens. Our study enriched the knowledge about H9N2 and may help implement an effective control strategy for H9N2.

Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer.

BACKGROUND: Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response. CONTENT: The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes. SUMMARY: The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.

Mycorrhizal effects on crop yield and soil ecosystem functions in a long-term tillage and fertilization experiment.

It is well understood that agricultural management influences arbuscular mycorrhizal (AM) fungi, but there is controversy about whether farmers should manage for AM symbiosis. We assessed AM fungal communities colonizing wheat roots for three consecutive years in a long-term (> 14 yr) tillage and fertilization experiment. Relationships among mycorrhizas, crop performance, and soil ecosystem functions were quantified. Tillage, fertilizers and continuous monoculture all reduced AM fungal richness and shifted community composition toward dominance of a few ruderal taxa. Rhizophagus and Dominikia were depressed by tillage and/or fertilization, and their abundances as well as AM fungal richness correlated positively with soil aggregate stability and nutrient cycling functions across all or no-tilled samples. In the field, wheat yield was unrelated to AM fungal abundance and correlated negatively with AM fungal richness. In a complementary glasshouse study, wheat biomass was enhanced by soil inoculum from unfertilized, no-till plots while neutral to depressed growth was observed in wheat inoculated with soils from fertilized and conventionally tilled plots. This study demonstrates contrasting impacts of low-input and conventional agricultural practices on AM symbiosis and highlights the importance of considering both crop yield and soil ecosystem functions when managing mycorrhizas for more sustainable agroecosystems.

Slow conduction velocity predicts atrial fibrillation recurrence after radiofrequency ablation.

OBJECTIVE: To evaluate the progression of electrophysiological phenomena in atrial fibrillation (AF) and elucidate the association between the left atrial conduction velocity (LACV) and AF recurrence after pulmonary vein isolation. METHODS: A total of 188 AF patients (121 paroxysmal AF and 67 persistent AF) who underwent PVI for the first time were enrolled in this prospective study. The left atrium was mapped using a 20-pole electrode catheter combined with the CARTO3 system. The conduction distances and conduction times of the left atrium from the Bachmann bundle area to the mitral isthmus were calculated. Anterior, posterior, and septal LACV were calculated as conduction distance divided by conduction time. RESULTS: The anterior, posterior, and septal LACVs in the AF recurrence group were slower than those in the nonrecurrence group (anterior: 0.807 [0.766, 0.848] and 1.048 [1.000, 1.093] m/s, p < .05; posterior: 1.037 [0.991, 1.084] vs. 1.315 [1.249, 1.380] m/s, p < .05; septal: 0.904 [0.862, 0.946] vs. 1.163 [1.107, 1.219] m/s, p < .05). The best cut-off value of anterior LACV for predicting AF recurrence was 0.887 m/s (sensitivity 73.9% and specificity 76.5%). Multivariate analysis showed slow anterior LACV <0.887 m/s was an independent predictor of AF recurrence with an adjusted odds ratio of 1.42 (1.04, 1.94). CONCLUSIONS: Slowing conduction velocity is a predictor of AF recurrence after pulmonary vein isolation.

Relationship between sodium-glucose cotransporter 2 inhibitors and atrial fibrillation recurrence after pulmonary vein isolation in patients with type 2 diabetes and persistent atrial fibrillation.

BACKGROUND: The impact of sodium-glucose cotransporter 2 (SGLT2) inhibitors on the postoperative recurrence of atrial fibrillation (AF) in patients with persistent AF undergoing an initial radiofrequency ablation is not yet established. The objective of this study is to assess the impact of SGLT2 inhibitors on the recurrence of AF after radiofrequency ablation in patients with type 2 diabetes complicated persistent AF. METHODS: A total of 182 patients with type 2 diabetes and persistent AF, who underwent their first radiofrequency ablation for AF at our center, were enrolled and divided into two groups: the SGLT2 inhibitor group and the non-SGLT2 inhibitor group. The main outcome of the follow-up was the postoperative recurrence of AF. RESULTS: A total of 49 participants experienced AF recurrence. The use of SGLT2 inhibitors in patients with type 2 diabetes who underwent AF ablation was associated with a significantly lower risk of AF recurrence (adjusted hazard ratio: 0.65; 95% confidence interval: 0.28-0.83; p < .01). CONCLUSIONS: The use of SGLT2 inhibitors is associated with a decreased risk of arrhythmia recurrence after AF ablation in patients with type 2 diabetes complicated with persistent AF.