Biology subjects

Lee, H.-J.

Publications and source records attributed to Lee, H.-J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Baculoviral COVID-19 Delta DNA vaccine cross-protects against SARS-CoV2 variants in K18-ACE2 transgenic mice

After severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) made the world tremble with a global pandemic, SARS-CoV2 vaccines were developed. However, due to the coronaviruss intrinsic nature, new variants emerged, such as Delta and Omicron, refractory to the vaccines derived using the original Wuhan strain. We developed an HERV-enveloped recombinant baculoviral DNA vaccine against SARS-CoV2 (AcHERV-COVID19S). A non-replicating recombinant baculovirus that delivers the SARS-CoV2 spike gene showed a protective effect against the homologous challenge in a K18-hACE2 Tg mice model; however, it offered only a 50% survival rate against the SARS-CoV2 Delta variant. Therefore, we further developed the AcHERV-COVID19 Delta vaccine (AcHERV-COVID19D). Cross-protection experiments revealed that mice vaccinated with the AcHERV-COVID19D showed 100% survival upon challenge with Delta and Omicron variants and 71.4% survival against prototype SARS-CoV2. These results support the potential of the viral vector vaccine, AcHERV-COVID19D, in preventing the spread of coronavirus variants such as Omicron and SARS-CoV2 variants. Author SummaryAfter the SARS-CoV2 pandemic, it is known that the existing vaccine has diminished efficacy against the emerging variants. We developed a baculoviral COVID19 DNA vaccine for the Delta variant (AcHERV-COVIS19D). Compared to AcHERV-COVID19S, designed to protect from the prototype of SARS-CoV2, AcHERV-COVID19D elicited higher humoral and cellular immunity and showed perfect protection against SARS-CoV2 delta strain and Omicron challenge. The broad and robust cellular immunity of the AcHERV-COVID19D vaccine appears to have played a significant role in the cross-protection of the Omicron variant. Our AcHERV-COVID19D can be a potential vaccine against emerging SARS-CoV2 variants.

immunology↗

bioRxiv2022

linc-mipep and linc-wrb encode micropeptides that regulate chromatin accessibility in vertebrate-specific neural cells

Thousands of long intergenic non-coding RNAs (lincRNAs) are transcribed throughout the vertebrate genome. A subset of lincRNAs enriched in developing brains has recently been found to contain cryptic open reading frames and are speculated to encode micropeptides. However, systematic identification and functional assessment of these transcripts have been hindered by technical challenges caused by their small size. Here we show that two putative lincRNAs (linc-mipep and linc-wrb) encode micropeptides with homology to the vertebrate-specific chromatin architectural protein, Hmgn1, and demonstrate that they are required for development of vertebrate-specific brain cell types. Specifically, we show that NMDA receptor-mediated pathways are dysregulated in zebrafish lacking these micropeptides and that their loss preferentially alters the gene regulatory networks that establish cerebellar cells and oligodendrocytes - evolutionarily newer cell types that develop postnatally in humans. These findings highlight the power of screening for unexplored micropeptide functions by revealing a key missing link in the evolution of vertebrate brain cell development and illustrating a genetic basis for how some neural cell types are more susceptible to chromatin disruptions, with implications for neurodevelopmental disorders and disease.

developmental biology↗

bioRxiv2022

Visual stimuli modulate local field potentials but drive no high-frequency activity in human auditory cortex

Neuroimaging studies suggest cross-sensory visual influences in human auditory cortices. Whether these influences reflect active visual processing in human auditory cortices (ACs), which drives neuronal firing and concurrent broadband high-frequency activity (BHFA; >70 Hz), or whether they merely modulate sound processing is still debatable. Here, we presented auditory, visual, and audiovisual stimuli to 16 participants (7 women, 9 men) with stereo-EEG depth electrodes implanted near ACs for presurgical monitoring. Anatomically normalized group analyses were facilitated by inverse modeling of intracranial source currents. Analyses of intracranial event-related potentials (iERP) suggested cross-sensory responses to visual stimuli in ACs, which lagged the earliest auditory responses by several tens of milliseconds. Visual stimuli also modulated the phase of intrinsic low-frequency oscillations and triggered 15-30-Hz event-related desynchronization in ACs. However, BHFA, a putative correlate of neuronal firing, was not significantly increased in ACs after visual stimuli, not even when they coincided with auditory stimuli. Intracranial recordings demonstrate cross-sensory modulations, but no indication of active visual processing in human ACs. Significance StatementVisual information has a profound influence on auditory processing, particularly in noisy conditions. These "cross-sensory" influences start already in auditory cortices, the brain area that processes sound signals. It has, however, been unclear whether auditory cortex actively processes visual information or whether visual signals only change the way sounds are processed. We studied this question by neurophysiological recordings from 16 participants with epilepsy who had electrodes implanted in their brains due to medical reasons. Using these intracranial recordings, we show that cross-sensory visual information modulates sound processing but triggers no high-frequency activity -- a correlate of local neuronal firing -- in auditory cortex. This result provides important information on the role of sensory areas in multisensory processing in the human brain.

neuroscience↗

bioRxiv2021

NGSpop: A desktop software that supports population studies by identifying sequence variations from next-generation sequencing data

Next-generation sequencing (NGS) is widely used in all areas of genetic research, such as for genetic disease diagnosis and breeding, and it can produce massive amounts of data. The identification of sequence variants is an important step when processing large NGS datasets; however, currently, the process is complicated, repetitive, and requires concentration, which can be taxing on the researcher. Therefore, to support researchers who are not familiar with bioinformatics in identifying sequence variations regularly from large datasets, we have developed a fully automated desktop software, NGSpop. NGSpop includes functionalities for all the variant calling and visualization procedures used when processing NGS data, such as quality control, mapping, filtering details, and variant calling. In the variant calling step, the user can select the GATK or DeepVariant algorithm for variant calling. These algorithms can be executed using pre-set pipelines and options or customized with the user-specified options. NGSpop is implemented using JavaFX (version 1.8) and can thus be run on Unix like operating systems such as Ubuntu Linux (version 16.04, 18.0.4). Although there are several pipelines and visualization tools available for NGS data analysis, most integrated environments do not support batch processes; thus, variant detection cannot be automated for population-level studies. The NGSpop software, developed in this study, has an easy-to-use interface and helps in rapid analysis of multiple NGS data from population studies.

bioinformatics↗

bioRxiv2021

An interactome landscape of SARS-CoV-2 virus-human protein-protein interactions by protein sequence-based multi-label classifiers

The new coronavirus species, SARS-CoV-2, caused an unprecedented global pandemic of COVID-19 disease since late December 2019. A comprehensive characterization of protein-protein interactions (PPIs) between SARS-CoV-2 and human cells is a key to understanding the infection and preventing the disease. Here we present a novel approach to predict virus-host PPIs by multi-label machine learning classifiers of random forests and XGBoost using amino acid composition profiles of virus and human proteins. Our models harness a large-scale database of Viruses.STRING with >80,000 virus-host PPIs along with evidence scores for multi-level evidence prediction, which is distinct from predicting binary interactions in previous studies. Our multi-label classifiers are based on 5 evidence levels binned from evidence scores. Our best model of XGBoost achieves 74% AUC and 68% accuracy on average in 10-fold cross validation. The most important amino acids are cysteine and histidine. In addition, our model predicts experimental PPIs with higher accuracy than text mining-based PPIs by 4% despite their smaller data size by more than 6-fold. We then predict evidence levels of [~]2,000 SARS-CoV-2 virus-human PPIs from public experimental proteomics data. Interactions with SARS-CoV-2 Nsp7b show high evidence. We also predict evidence levels of all pairwise PPIs of [~]550,000 between the SARS-CoV-2 and human proteomes to provide a draft virus-host interactome landscape for SARS-CoV-2 infection in humans in a comprehensive and unbiased way in silico. Most human proteins from 140 highest evidence predictions interact with SARS-CoV-2 Nsp7, Nsp1, and ORF14, with significant enrichment in the top 2 pathways of vascular smooth muscle contraction (CALD1, NPR2, CALML3) and Myc targets (CBX3, PES1). Our prediction also suggests that histone H2A components are targeted by multiple SARS-CoV-2 proteins.

systems biology↗

bioRxiv2021

Dynamic metabolic network modeling of a mammalian cell cycle using time-course multi-omics data

Cell cycle is a fundamental process for cell growth and proliferation, and its dysregulation leads to many diseases. How metabolic networks are regulated and rewired during the cell cycle is unknown. Here we apply a dynamic genome-scale metabolic modeling framework (DFA) to simulate a cell cycle of cytokine-activated murine pro-B cells. Phase-specific reaction activity predicted by DFA using time-course metabolomics were validated using matched time-course proteomics and phospho-proteomics data. Our model correctly predicted changes in methionine metabolism at the G1/S transition and the activation of lysine metabolism, nucleotides synthesis, fatty acid elongation and heme biosynthesis at the critical G0/G1 transition into cell growth and proliferation. Metabolic fluxes predicted from proteomics and phosphoproteomics constrained metabolic models were highly consistent with DFA fluxes and revealed that most reaction fluxes are regulated indirectly. Our model can help predict the impact of changes in nutrients, enzymes, or regulators on this critical cellular process.

systems biology↗

bioRxiv2021

Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle

In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a "co-expression pattern recognizer" (CEPR) and "module classifier". The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering. Author summaryA graph neural network is a good alternative algorithm for WGCNA module clustering. Even though the graph-based learning methods have been widely applied in bioinformatics, most studies on WGCNA did not use graph neural network for module clustering. In addition, existing methods depend on topological overlap measure of gene pairs. This can degrade similarity of expression not only between modules, but also within module. On the other hand, the proposed gmcNet, which works similar to message-passing operation of graph neural network, simultaneously addresses single-level expression and topological overlap measure. We observed the higher performance of gmcNet comparing to existing methods for WGCNA module clustering. To adopt gmcNet as clustering algorithm of WGCNA, it remains future research issues to add noise filtering and optimal k search on gmcNet. This further research will extend our proposed method to be a useful module clustering algorithm in WGCNA. Furthermore, our findings will be of interest to computational biologists since the studies using graph neural networks to WGCNA are still rare.

bioinformatics↗

bioRxiv2021

Multi-omic Characterization of Pancreatic Cancer-Associated Macrophage Polarization Reveals Deregulated Metabolic Programs Driven by the GMCSF-PI3K Pathway

The pancreatic ductal adenocarcinoma (PDA) microenvironment is composed of a variety of cell types and marked by extensive fibrosis and inflammation. Tumor-associated macrophages (TAM) are abundant, and they are important mediators of disease progression and invasion. TAMs are polarized in situ to a tumor promoting and immunosuppressive phenotype via cytokine signaling and metabolic crosstalk from malignant epithelial cells and other components of the tumor microenvironment (TME). However, the specific distinguishing features and functions of TAMs remain poorly defined. Here, we generated tumor-educated macrophages (TEM) in vitro and performed detailed, multi-omic characterization (i.e. transcriptomics, proteomics, metabolomics). Our results reveal unique genetic and metabolic signatures of TEMs, the veracity of which were queried against our in-house single cell RNA sequencing (scRNA-seq) dataset of human pancreatic tumors. This analysis identified expression of novel, metabolic TEM markers in human pancreatic TAMs, including ARG1, ACLY, and TXNIP. We then utilized our TEM model system to study the role of mutant Kras signaling in cancer cells on TEM polarization. This revealed an important role for GM-CSF and lactate on TEM polarization, molecules released from cancer cells in a mutant Kras-dependent manner. Lastly, we demonstrate that GM-CSF dysregulates TEM gene expression and metabolism through PI3K-AKT pathway signaling. Collectively, our results define new markers and programs to classify pancreatic TAMs, how these are engaged by cancer cells, and the precise signaling pathways mediating polarization.

cancer biology↗

bioRxiv2021

A redox cycle with complex II promotes sulfide quinone oxidoreductase dependent H2S oxidation

The dueling roles of H2S as an endogenously synthesized respiratory substrate and as a toxin, raise questions as to how it is cleared when the electron transport chain is inhibited. Sulfide quinone oxidoreductase (SQOR) is a mitochondrial inner membrane flavoprotein that catalyzes the first step in the H2S oxidation pathway and uses coenzyme Q (CoQ) as an electron acceptor. However, complex IV poisoning by H2S inhibits complex III-dependent recycling of CoQH2, which is needed to sustain H2S oxidation. We have discovered that under these conditions, reversal of complex II activity using fumarate as an electron acceptor, establishes a new redox cycle with SQOR. The purine nucleotide cycle and the malate aspartate shuttle are sources of fumarate in H2S treated cells, which accumulate succinate. Complex II knockdown decreases the efficiency of H2S clearance and increases recovery time to the basal respiration rate in H2S treated cells. In contrast, attenuation of complex I, which is a major competitor for the mitochondrial CoQ pool, has the opposite effects. Targeted knockout of complex II in murine intestinal epithelial cells that are routinely exposed to microbiota derived H2S, decreases serum, urine, and fecal thiosulfate, a product of H2S oxidation. Our study identifies a metabolic reprogramming response to H2S that furnishes fumarate as an alternate electron acceptor and supports H2S oxidation independent of complex IV activity. Complex II-linked redox cycling of SQOR has important implications for gut H2S metabolism as colonocytes are routinely exposed to high concentrations of this gas derived from the microbiota. One Sentence SummaryReversal of complex II sustains and prioritizes H2S oxidation when respiration is poisoned.

biochemistry↗

bioRxiv2021

Effects of Platycodon grandiflorum on Gut Microbiota and Immune System of Immunosuppressed Mouse

Platycodon grandiflorum (PG) has been used as a traditional remedy to control immune related diseases. However, there is limited information about its immune stimulating effects on the immunosuppressed model. The main bioactive components such as saponins are known to con-tribute to controlling immune activity. Thus, we developed an aged red PG (PGS) with 2.6 times of platycodin D, one of the saponins. We treated PG and PGS (PG-diets) to immunosuppressed mice via cyclophosphamide (CPA) injection. After 2weeks of the supplement, 16S rRNA sequencing was performed to investigate the effects of PG-diets on the gut microbiota and immune system in the immune suppressed model. PG-diets groups showed an increased abundance of microorganism in immune-deficient mice compared to the control NC group, indicating PG-diets have a distinct effect on microbial communities. Detection of specific genera related to the immune related biomarkers in PG-diets groups can support their effects on the immune system. Especially, the Akkermansia showed a significant decrease of abundance in response to the CPA treatment in the NC group at the genus level, but its abundance increased in response to the PG-diets treatment in the PG-diets groups. We also found that the modulation of gut microbiome by PG-diets was correlated with body weight as one of important immune biomarkers, though not much difference was found between PG and PGS effects. The results demonstrate that PG-diets may improve the health benefits of immune suppressed mice by altering the gut microbiome.

microbiology↗

bioRxiv2021

Network controllability enrichment analysis reveals that SARS-CoV-2 infection tends to target indispensable nodes of a directed human protein-protein interaction network

The COVID-19 disease has been a global threat caused by the new coronavirus species, SARS-CoV-2, since early 2020 with an urgent need for therapeutic interventions. In order to provide insight into human proteins targeted by SARS-CoV-2, here we study a directed human protein-protein interaction network (dhPPIN) based on our previous work on network controllability of virus targets. We previously showed that human proteins targeted by viruses tend to be those whose removal in a dhPPIN requires more control of the network dynamics, which were classified as indispensable nodes. In this study we introduce a more comprehensive rank-based enrichment analysis of our previous dhPPIN for SARS-CoV-2 infection and show that SARS-CoV-2 also tends to target indispensable nodes in the dhPPIN using multiple proteomics datasets, supporting validity and generality of controllability analysis of viral infection in humans. Also, we find differential controllability among SARS-CoV-2, SARS-CoV-1, and MERS-CoV from a comparative proteomics study. Moreover, we show functional significance of indispensable nodes by analyzing heterogeneous datasets from a genome-wide CRISPR screening study, a time-course phosphoproteomics study, and a genome-wide association study. Specifically, we identify SARS-CoV-2 ORF3A as most frequently interacting with indispensable proteins in the dhPPIN, which are enriched in TGF-beta signaling and tend to be sources nodes and interact with each other. Finally, we built an integrated network model of ORF3A-interacting indispensable proteins with multiple functional supports to provide hypotheses for experimental validation as well as therapeutic opportunities. Therefore, a sub-network of indispensable proteins targeted by SARS-CoV-2 could serve as a prioritized network of drug targets and a basis for further functional and mechanistic studies from a network controllability perspective.

systems biology↗

bioRxiv2021

Multi-omics approach to identify bacterial polyynes and unveil their antifungal mechanism against Candida albicans

Bacterial polyynes are highly active natural products with a broad-spectrum of antimicrobial activities. However, their detailed mechanism of action remains unclear. Through integrating comparative genomics, transcriptomics, functional genetics, and metabolomics analysis, we identified a unique polyyne resistance gene, masL (encoding acetyl-CoA acetyltransferase), from the biosynthesis gene cluster (BGC) dominant for the production of antifungal polyynes (massilin A, massilin B, collimonin C, and collimonin D) in Massilia sp. YMA4. Phylogenic and chemotaxonomic analyses characterized the core architecture of bacterial polyyne BGC. The crystallographic analysis of the MasL-collimonin C complex indicated that bacterial polyynes serve as a covalent inhibitor of acetyl-CoA acetyltransferase. Moreover, we confirmed that the bacterial polyynes disrupted cell membrane integrity and inhibited cell viability of Candida albicans by targeting ERG10 (homolog of MasL). Overall, understanding of the antifungal mechanism of bacterial polyynes presented herein will be useful for the development of polyynes for fungal infections.

microbiology↗

bioRxiv2020

Hemodynamic changes in response to excitatory and inhibitory modulations by transcranial magnetic stimulation at the human sensorimotor cortex

Transcranial magnetic stimulation (TMS) can non-invasively induce both excitatory and inhibitory neuronal activity. However, the neurophysiological basis for both kinds of modulation remains elusive. In this study, with a controlled dosage over the 30-s interval, we elicited excitatory and inhibitory TMS modulations over the human primary motor cortex (M1) with TMS bursts of high (10-Hz and 30-Hz) and low frequency (0.5-Hz), respectively, and took functional magnetic resonance images (fMRI). Excitatory and inhibitory modulations were evidenced by changes in motor evoked potentials (MEP). Significantly increased fMRI signal at M1 was only detected under excitatory high-frequency TMS but not during inhibitory low-frequency TMS. The supplementary motor area (SMA) had significant fMRI signal changes after both excitatory and inhibitory TMS. The topology of the activated M1 and SMA matched the activated sensorimotor network during voluntary movement. The precuneus was selectively activated with bursts of five TMS pulses. These findings demonstrated the asymmetric hemodynamic responses to excitatory and inhibitory TMS modulations with region-dependent relationships between the local fMRI signal changes and TMS dosage over different time scales.

neuroscience↗

bioRxiv2020

The deacylase SIRT5 supports melanoma viability by regulating chromatin dynamics

Cutaneous melanoma remains the most lethal skin cancer, and ranks third among all malignancies in terms of years of life lost. Despite the advent of immune checkpoint and targeted therapies, only roughly half of patients with advanced melanoma achieves a durable remission. SIRT5 is a member of the sirtuin family of protein deacylases that regulate metabolism and other biological processes. Germline Sirt5 deficiency is associated with mild phenotypes in mice. Here we show that SIRT5 is required for proliferation and survival across all cutaneous melanoma genotypes tested, as well as uveal melanoma, a genetically distinct melanoma subtype that arises in the eye and is incurable once metastatic. Likewise, SIRT5 is required for efficient tumor formation by melanoma xenografts and in an autochthonous mouse Braf;Pten-driven melanoma model. Via metabolite and transcriptomic analyses, we find that SIRT5 is required to maintain histone acetylation and methylation levels in melanoma cells, thereby promoting proper gene expression. SIRT5-dependent genes notably include MITF, a key lineage-specific survival oncogene in melanoma, and the c-MYC proto-oncogene. SIRT5 may represent a novel, druggable genotype-independent addiction in melanoma.

cancer biology↗

bioRxiv2020

Distributed source modeling of intracranial stereoelectroencephalographic measurements

Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, sEEG group analyses are complicated because the electrode implantations differ greatly across individuals. Here, using an auditory experiment as the test case, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we also estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. The source models accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope{approx}-3.6). The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized group analyses of both iERP and HBBG.

neuroscience↗

bioRxiv2020

Recognition memory via repetition suppression in mouse hippocampal dorsal CA2 pyramidal neurons expressing the vasopressin 1b receptor

Recognition memory, often compromised in psychiatric disorders, is a major component of declarative memory, which permits the realization that an event, object or social subject has been previously encountered. The CA2 region of the dorsal hippocampus (dCA2) is involved in social memory and responds to novel objects, in time and space. However, it remains unclear how these neurons encode either social or inanimate object recognition. Here, we show that in dCA2, encoding of social recognition memory entails suppression of pyramidal neurons activity leading to a sparse representation of the familiar conspecific. We discuss the neural coding scheme by which dCA2 pyramidal neurons contribute to social memory.

neuroscience↗

bioRxiv2020

Mitochondrial Complex II In Intestinal Epithelial Cells Regulates T-cell Mediated Immunopathology

Intestinal epithelial cell (IEC) damage by T cells contributes to alloimmune, autoimmune and iatrogenic diseases such as graft-versus-host disease (GVHD), inflammatory bowel disease (IBD) and immune checkpoint blockade (ICB) mediated colitis, respectively. Despite significant advances in understanding the aberrant biology of T cells in these diseases, little is known about how the fundamental biological processes of the target IECs influence the disease severity. Here, through analyses of metabolic pathways of IECs, we identified disruption of oxidative phosphorylation without a concomitant change in glycolysis and an increase in succinate levels in several distinct in vivo models of T cell mediated gastrointestinal damage such as GVHD, IBD and ICB mediated colitis. Metabolic flux studies, complemented by imaging and protein analyses identified a critical role for IEC intrinsic succinate dehydrogenase A (SDHA), a component of mitochondrial complex II, in causing these metabolic alterations that contributed to the severity of intestinal damage. The critical mechanistic role of IEC intrinsic SDHA was confirmed by complementary chemical and genetic reduction of SDHA and with IEC specific deletion of SDHA. Further in vitro and in vivo mechanistic studies demonstrated that loss of SDHA in IECs was mediated by the perforin-granzyme from the T cells. The loss of SDHA was also validated in human clinical samples. These data identify a critical role for the alteration of the IEC specific mitochondrial complex II component SDHA in the regulation of the severity of T cell mediated intestinal diseases.

immunology↗

bioRxiv2020

Differential risk of incident cancer in patients with heart failure: A nationwide population-based cohort study

BackgroundHeart failure (HF) and cancer are currently two leading causes of mortality, and sometimes coexist. However, the relationship between them is not completely elucidated. We aimed to investigate whether patients with HF are predisposed to cancer development using the large Korean National Health Insurance claims database. Methods and findingsThis study included 128,441 HF patients without a history of cancer and 642,205 age- and sex-matched individuals with no history of cancer and HF between 1 January 2010 and 31 December 2015. During a median follow-up of 4.06 years, 11,808 patients from the HF group and 40,805 participants from the control were newly diagnosed with cancer (cumulative incidence, 9.2% vs. 6.4%, p<0.0001). Patients with HF presented a higher risk for cancer development compared to controls in multivariable Cox analysis (hazard ratio [HR] 1.64, 95% confidence interval [CI] 1.61 - 1.68). The increased risk was consistent for all site-specific cancers. To minimize potential surveillance bias, additional analysis was performed by eliminating participants who developed cancer within the initial 2 years of HF diagnosis (i.e. 2-year lag analysis). In the 2-year lag analysis, the higher risk of overall cancer remained significant in patients with HF (HR 1.09, 95% CI 1.05 - 1.13), although the association was weaker. Among the site-specific cancers, three types of cancer (lung, liver/biliary/pancreas, and hematologic malignancy) were consistently at higher risk in patients with HF. ConclusionsCancer incidence is higher in patients with HF than in the general population. Active surveillance of coexisting malignancy needs to be considered in these patients.

cancer biology↗