Impact of coronavirus disease 2019 on cancer care: How the pandemic has changed cancer utilization and expenditures.

PURPOSE: Since identified in December 2019, the novel coronavirus disease 2019 (COVID-19) has had a global impact on medical resource use and costs for patients with cancer in South Korea. This study aimed to identify the medical use and costs among patients with cancer during the COVID-19 pandemic, to predict these patterns in South Korea in the future. METHODS: We conducted a secondary claims data analysis using the National Health Insurance Service database for the calendar period of 2019-2020. Monthly relative percent changes in cancer incidence, medical use, and billing costs for medical care utilization by cancer type were calculated. Then, the medical use and costs after January 2020 were predicted using a time series model with data before the COVID-19 outbreak (2014-2019). RESULTS: The incidence of cancer diagnoses has seen a notable decline since the outbreak of the COVID-19 in 2020 as compared to 2019. Despite the impact of COVID-19, there hasn't been a distinct decline in outpatient utilization when compared to inpatient utilization. While medical expenses for both inpatient and outpatient visits have slightly increased, the number of patients treated for cancer has decreased significantly compared to the previous year. In June 2020, overall outpatient costs experienced the highest increase (21.1%), while individual costs showed the most significant decrease (-4.9%) in June 2020. Finally, the number of hospitalisations and outpatient visits increased slightly from June-July in 2020, reducing the difference between the actual and predicted values. The decrease in the number of inpatient hospitalisations (-22~-6%) in 2020 was also high. CONCLUSIONS: The overall use of medical services by patients with cancer decreased in 2020 compared with that in the pre-COVID-19 pandemic period. In the future, the government should consider how to recover from the COVID-19 pandemic, and establish permanent health policies for patients with cancer.

Trends in National Pharmaceutical Expenditure in Korea during 2011 - 2020.

BACKGROUND: This study aimed to identify the trends in pharmaceutical expenditure (PE), share of PE in health expenditure (HE), and trends in expenditure by pharmacological groups (ATC level 1 classification) in Korea for a 10-year period (2011 - 2020) and compare the data with those of other Organisation for Economic Co-operation and Development (OECD) countries. Using the findings, we determined the current status of pharmaceutical expenditure (PE) management in Korea and derived the implications for establishing future macroscopic policies on PE. MATERIALS AND METHODS: We analyzed the OECD Health Statistics and the Korean national health insurance claims database from January 2011 through December 2020. The outcome measures were HE, PE, and pharmaceutical sales data for ATC level 1 medicines from OECD Health Statistics data during 2011 - 2020. As OECD collects limited ATC level 1 data, we used the HIRA health insurance claims data for PEs of ATC level-1 classification, including D, L, P, and S. RESULTS: PE in Korea increased by 38.5% from 19.9 billion USD in 2011 to 27.6 billion USD in 2020, whereas the share of PE in HE decreased by 6.3%p from 26.4% in 2011 to 20.1% in 2020. In 2020, Korea ranked third in PE per capita (760.9 USD PPP) and had the highest share of PE (20.1%) among the 19 OECD countries studied. By ATC level 1 class, the highest PE was A (alimentary tract and metabolism) at 4.3 billion USD, and L (antineoplastic and immunomodulating agents) had the highest increase at 13.4%; in contrast, J (anti-infectives for systemic use) had the lowest increase in annual average PE at -0.2% in 2020 relative to 2011. Among the 17 OECD countries, Korea had the highest and the third-highest expenditures for ATC codes A and J, respectively. CONCLUSION: PE in Korea has continued to increase between 2011 and 2020, indicating the need for macroscopic management of PE. Our results on PE by ATC code may help health authorities in establishing future policies on PE.

DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer.

Some of the recent studies on drug sensitivity prediction have applied graph neural networks to leverage prior knowledge on the drug structure or gene network, and other studies have focused on the interpretability of the model to delineate the mechanism governing the drug response. However, it is crucial to make a prediction model that is both knowledge-guided and interpretable, so that the prediction accuracy is improved and practical use of the model can be enhanced. We propose an interpretable model called DRPreter (drug response predictor and interpreter) that predicts the anticancer drug response. DRPreter learns cell line and drug information with graph neural networks; the cell-line graph is further divided into multiple subgraphs with domain knowledge on biological pathways. A type-aware transformer in DRPreter helps detect relationships between pathways and a drug, highlighting important pathways that are involved in the drug response. Extensive experiments on the GDSC (Genomics of Drug Sensitivity and Cancer) dataset demonstrate that the proposed method outperforms state-of-the-art graph-based models for drug response prediction. In addition, DRPreter detected putative key genes and pathways for specific drug-cell-line pairs with supporting evidence in the literature, implying that our model can help interpret the mechanism of action of the drug.

Analysis of the Korean generic medicine market: Factors affecting the market share of generic medicines.

This study probed the market share of generic medicines by patients' age and sex, type of medical facilities, route of administration, number of generic brands, market size (drug expenditure), and therapeutic class and investigated factors associated with a high market share of generic medicines in Korea. We analyzed using national health insurance data between 2010 and 2019. The dependent variable was the generic medicine market share, measured as the number of prescriptions and expenditures. Multivariable regression analysis was conducted using the numbers of generic brands, market size by each ingredient and therapeutic class, relative price, the number of prescriptions, and therapeutic class. Total pharmaceutical expenditures have increased due to the high use of single-source drugs. The number of prescriptions and expenditures for generic medicines were 0.3 billion prescriptions and $7.8 billion, respectively, accounting for 46.5% and 46% of the total market. Multivariate analysis showed that the number of prescriptions (>20 thousand) and the market size of main active ingredients (>$1 million) were associated with an increased market share, whereas the number of generic brands (compared to <3) was associated with reduced generic medicine market share. In conclusion, we found that supply policies to promote the market entry of generic medicines by mandating price consistency between generic medicines and off-patent original medicines had limitations in increasing the generic medicine market share. Policy should be put in place both to ensure the timely market entry of generic medicines and to promote the use of cheaper generic medicines.

Machine Learning Approach Using Routine Immediate Postoperative Laboratory Values for Predicting Postoperative Mortality.

BACKGROUND: Several prediction models have been proposed for preoperative risk stratification for mortality. However, few studies have investigated postoperative risk factors, which have a significant influence on survival after surgery. This study aimed to develop prediction models using routine immediate postoperative laboratory values for predicting postoperative mortality. METHODS: Two tertiary hospital databases were used in this research: one for model development and another for external validation of the resulting models. The following algorithms were utilized for model development: LASSO logistic regression, random forest, deep neural network, and XGBoost. We built the models on the lab values from immediate postoperative blood tests and compared them with the SASA scoring system to demonstrate their efficacy. RESULTS: There were 3817 patients who had immediate postoperative blood test values. All models trained on immediate postoperative lab values outperformed the SASA model. Furthermore, the developed random forest model had the best AUROC of 0.82 and AUPRC of 0.13, and the phosphorus level contributed the most to the random forest model. CONCLUSIONS: Machine learning models trained on routine immediate postoperative laboratory values outperformed previously published approaches in predicting 30-day postoperative mortality, indicating that they may be beneficial in identifying patients at increased risk of postoperative death.

Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach.

The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass spectrometry (DIA-MS) to identify the serum proteins that are closely associated with COVID-19 prognosis. Twenty-seven proteins were differentially expressed between severely ill COVID-19 patients with an adverse or favorable prognosis. Ingenuity Pathway Analysis revealed that 15 of the 27 proteins might be regulated by cytokine signaling relevant to interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF), and their differential expression was implicated in the systemic inflammatory response and in cardiovascular disorders. We further evaluated practical predictors of the clinical prognosis of severe COVID-19 patients. Subsequent ELISA assays revealed that CHI3L1 and IGFALS may serve as highly sensitive prognostic markers. Our findings can help formulate a diagnostic approach for accurately identifying COVID-19 patients with severe disease and for providing appropriate treatment based on their predicted prognosis.

Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma.

PTEN is one of the most frequently altered tumor suppressor genes in malignant tumors. The dominant-negative effect of PTEN alteration suggests that the aberrant function of PTEN mutation might be more disastrous than deletion, the most frequent genomic event in glioblastoma (GBM). This study aimed to understand the functional properties of various PTEN missense mutations and to investigate their clinical relevance. The genomic landscape of PTEN alteration was analyzed using the Samsung Medical Center GBM cohort and validated via The Cancer Genome Atlas dataset. Several hotspot mutations were identified, and their subcellular distributions and phenotypes were evaluated. We established a library of cancer cell lines that overexpress these mutant proteins using the U87MG and patient-derived cell models lacking functional PTEN. PTEN mutations were categorized into two major subsets: missense mutations in the phosphatase domain and truncal mutations in the C2 domain. We determined the subcellular compartmentalization of four mutant proteins (H93Y, C124S, R130Q, and R173C) from the former group and found that they had distinct localizations; those associated with invasive phenotypes ('edge mutations') localized to the cell periphery, while the R173C mutant localized to the nucleus. Invasive phenotypes derived from edge substitutions were unaffected by an anti-PI3K/Akt agent but were disrupted by microtubule inhibitors. PTEN mutations exhibit distinct functional properties regarding their subcellular localization. Further, some missense mutations ('edge mutations') in the phosphatase domain caused enhanced invasiveness associated with dysfunctional cytoskeletal assembly, thus suggesting it to be a potent therapeutic target.

Comparative Analysis of the Productivity and Immunogenicity of an Attenuated Classical Swine Fever Vaccine (LOM) and an Attenuated Live Marker Classical Swine Fever Vaccine (Flc-LOM-BErns) from Laboratory to Pig Farm.

Herein, we compared the productivity of pigs inoculated with one of two classical swine fever (CSF) vaccines (low virulent of Miyagi (LOM) or Flc-LOM-BErns) plus the swine erysipelothrix rhusiopathiae (SE) vaccine. The feed intake and weight increase of the pigs inoculated with Flc-LOM-BErns + SE were normal. However, the feed intake of the pigs inoculated with LOM + SE dropped sharply from four days post-vaccination (dpv). In addition, the slaughter date was an average of eight days later than that of the pigs inoculated with Flc-LOM-BErns + SE. All pigs inoculated with the Flc-LOM-BErns + SE vaccine were completely differentiated at 14 days against CSF Erns antibody and at approximately 45 days against the bovine viral diarrhea virus (BVDV) Erns antibody; the titers were maintained until slaughter. Leucopenia occurred temporarily in the LOM + SE group, but not in the Flc-LOM-BErns + SE group. Expression of tumor necrosis factor (TNF)-α and IFN-γ was significantly (p < 0.05) higher in the LOM + SE group than in the mock (no vaccine) group. When conducting the same experiment on a breeding farm, the results were similar to those of the laboratory experiments. In conclusion, the biggest advantage of replacing the CSF LOM vaccine with the Flc-LOM-BErns vaccine is improved productivity.

Efficacy of orally administered porcine epidemic diarrhea vaccine-loaded hydroxypropyl methylcellulose phthalate microspheres and RANKL-secreting L. lactis.

Here, we examined the efficacy of are combinant subunit antigen-based oral vaccine for preventing porcine epidemic diarrhea virus (PEDV). First, we generated a soluble recombinant partial spike S1 protein (aP2) from PEDV in E. coli and then evaluated the utility of aP2 subunit vaccine-loaded hydroxypropyl methylcellulose phthalate microspheres (HPMCP) and RANKL-secreting L. lactis (LLRANKL) as a candidate oral vaccine in pregnant sows. Pregnant sows were vaccinated twice (with a 2 week interval between doses) at 4 weeks before farrowing. Titers of virus-specific IgA antibodies in colostrum, and neutralizing antibodies in serum, of sows vaccinated with HPMCP (aP2) plus LL RANKL increased significantly at 4 weeks post-first vaccination. Furthermore, the survival rate of newborn suckling piglets delivered by sows vaccinated with HPMCP (aP2) plus LL RANKL was similar to that of piglets delivered by sows vaccinated with a commercial killed porcine epidemic diarrhea virus (PED) vaccine. The South Korean government promotes a PED vaccine program (live-killed-killed) to increase the titers of IgA and IgG antibodies in pregnant sows and prevent PEDV. The oral vaccine strategy described herein, which is based on a safe and efficient recombinant subunit antigen, is an alternative PED vaccination strategy that could replace the traditional strategy, which relies on attenuated live oral vaccines or artificial infection with virulent PEDV.

Secretome analysis of patient-derived GBM tumor spheres identifies midkine as a potent therapeutic target.

Glioblastoma (GBM) is the most lethal primary brain tumor with few treatment options. The survival of glioma-initiating cells (GICs) is one of the major factors contributing to treatment failure. GICs frequently produce and respond to their own growth factors that support cell proliferation and survival. In this study, we aimed to identify critical autocrine factors mediating GIC survival and to evaluate the anti-GBM effect of antagonizing these factors. Proteomic analysis was performed using conditioned media from two different patient-derived GBM tumor spheres under a growth factor-depleted status. Then, the antitumor effects of inhibiting an identified autocrine factor were evaluated by bioinformatic analysis and molecular validation. Proteins secreted by sphere-forming GICs promote cell proliferation/survival and detoxify reactive oxygen species (ROS). Among these proteins, we focused on midkine (MDK) as a clinically significant and pathologically relevant autocrine factor. Antagonizing MDK reduced the survival of GBM tumor spheres through the promotion of cell cycle arrest and the consequent apoptotic cell death caused by oxidative stress-induced DNA damage. We also identified PCBP4, a novel molecular predictor of resistance to anti-MDK treatment. Collectively, our results indicate that MDK inhibition is an important therapeutic option by suppressing GIC survival through the induction of ROS-mediated cell cycle arrest and apoptosis.

In situ solvent recovery by using hydrophobic/oleophilic filter during wet lipid extraction from microalgae.

While lipid extraction from wet microalgae has attracted attention as an economical method for microalgal biofuel production, few studies have focused the actual separation of extract phase from the emulsified extraction mixture. Here, a novel approach which utilizes hydrophobic/oleophilic filter was developed for the efficient solvent recovery. The filter was surface-modified by coating a functional polymer via initiated vapor deposition for the selective solvent permeability. While acid-treated Chlorella sorokiniana HS1 and n-hexane was stirred for lipid extraction, tubular filter module was immersed into the mixture for separation. The mixture was kept stirred during the separation to inhibit the buildup of cell debris on the filter by inducing crossflow on the filter. Extract phase was separated directly from the raffinate phase with high separation efficiency (> 98.3%) while maintaining permeation flux. The place-, space- and energy-efficient strategy reported here could be a useful tool for the solvent extraction process.

Comparative analysis of differentially secreted proteins in serum-free and serum-containing media by using BONCAT and pulsed SILAC.

Despite the increased interest in secretomes associated with paracrine/autocrine mechanisms, the majority of mass spectrometric cell secretome studies have been performed using serum-free medium (SFM). On the other hand, serum-containing medium (SCM) is not recommended very much because the secretome obtained with SCM is easily contaminated with fetal bovine serum (FBS) proteins. In this study, through the combination of bioorthogonal non-canonical amino acid tagging (BONCAT) and pulsed-SILAC (pSILAC), we analyzed differentially secreted proteins between SFM and SCM in a cancer-derived human cell, U87MG, and a mesenchymal stem cell derived from human Wharton's jelly (hWJ-MSCs). In most cases, the bioinformatic tools predicted a protein to be truly secretory when the secretion level of the protein was more in SCM than in SFM. In the case of hWJ-MSCs, the amount of proteins secreted in SCM for 24 hours was larger than that of SFM (log2 fold change = 0.96), even considering different cell proliferation rates. hWJ-MSCs proteins secreted more in SCM included several positive markers of MSC paracrine factors implicated in angiogenesis, neurogenesis and osteogenesis, and upstream regulators of cell proliferation. Our study suggests the analysis of the secretome should be processed in SCM that promotes cell proliferation and secretion.

Genetic characterization of bovine coronavirus in Vietnam.

A maximum clade credibility tree constructed using the full-length spike (S) and hemagglutinin-esterase genes revealed that Vietnamese Bovine coronavirus (BCoV) strains belong to a single cluster (C1); therefore, they might share a common origin with Cuban and Chinese BCoV strains. The omega values of cluster 1 (C1) and cluster 2 (C2) were 0.15734 and 0.11613, respectively, and naive empirical bayes analysis identified two amino acid positions (179 and 501) in the S protein in C1 and three amino acid positions (113, 501, and 525) in that of C2 that underwent positive selection (p > 99%). The evolutionary rate of C1 was estimated to be 7.6206 × 10-4 substitutions/site/year, and the most recent common ancestor (tMRCA) of Vietnamese BCoVs was estimated to date back to 1962 (95% HPD 1950-1973). The effective population sizes of C1 and C2 underwent a rapid reduction after 2000 and 2004, respectively.

Dedifferentiated Schwann cells secrete progranulin that enhances the survival and axon growth of motor neurons.

Schwann cells (SCs), the primary glia in the peripheral nervous system (PNS), display remarkable plasticity in that fully mature SCs undergo dedifferentiation and convert to repair SCs upon nerve injury. Dedifferentiated SCs provide essential support for PNS regeneration by producing signals that enhance the survival and axon regrowth of damaged neurons, but the identities of neurotrophic factors remain incompletely understood. Here we show that SCs express and secrete progranulin (PGRN), depending on the differentiation status of SCs. PGRN expression and secretion markedly increased as primary SCs underwent dedifferentiation, while PGRN secretion was prevented by administration of cAMP, which induced SC differentiation. We also found that sciatic nerve injury, a physiological trigger of SC dedifferentiation, induced PGRN expression in SCs in vivo. These results suggest that dedifferentiated SCs express and secrete PGRN that functions as a paracrine factor to support the survival and axon growth of neighboring neurons after injury.

K6 linked polyubiquitylation of FADD by CHIP prevents death inducing signaling complex formation suppressing cell death.

Fas-associated death domain (FADD) is an adaptor protein recruiting complexes of caspase 8 to death ligand receptors to induce extrinsic apoptotic cell death in response to a TNF superfamily member. Although, formation of the complex of FADD and caspase 8 upon death stimuli has been studied in detail, posttranslational modifications fine-tuning these processes have yet to be identified. Here we revealed that K6-linked polyubiquitylation of FADD on lysines 149 and 153 mediated by C terminus HSC70-interacting protein (CHIP) plays an important role in preventing formation of the death inducing signaling complex (DISC), thus leading to the suppression of cell death. Cells depleted of CHIP showed higher sensitivity toward death ligands such as FasL and TRAIL, leading to upregulation of DISC formation composed of a death receptor, FADD, and caspase 8. CHIP was able to bind to FADD, induce K6-linked polyubiquitylation of FADD, and suppress DISC formation. By mass spectrometry, lysines 149 and 153 of FADD were found to be responsible for CHIP-mediated FADD ubiquitylation. FADD mutated at these sites was capable of more potent cell death induction as compared with the wild type and was no longer suppressed by CHIP. On the other hand, CHIP deficient in E3 ligase activity was not capable of suppressing FADD function and of FADD ubiquitylation. CHIP depletion in ME-180 cells induced significant sensitization of these cells toward TRAIL in xenograft analyses. These results imply that K6-linked ubiquitylation of FADD by CHIP is a crucial checkpoint in cytokine-dependent extrinsic apoptosis.

Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS.

Non-small-cell lung cancer (NSCLC) constitutes approximately 80% of all diagnosed lung cancers, and diagnostic markers detectable in the plasma/serum of NSCLC patients are greatly needed. In this study, we established a pipeline for the discovery of markers using 9 transcriptome datasets from publicly available databases and profiling of six lung cancer cell secretomes. Thirty-one out of 312 proteins that overlapped between two-fold differentially expressed genes and identified cell secretome proteins were detected in the pooled plasma of lung cancer patients. To quantify the candidates in the serum of NSCLC patients, multiple-reaction-monitoring mass spectrometry (MRM-MS) was performed for five candidate biomarkers. Finally, two potential biomarkers (BCHE and GPx3; AUC = 0.713 and 0.673, respectively) and one two-marker panel generated by logistic regression (BCHE/GPx3; AUC = 0.773) were identified. A validation test was performed by ELISA to evaluate the reproducibility of GPx3 and BCHE expression in an independent set of samples (BCHE and GPx3; AUC = 0.630 and 0.759, respectively, BCHE/GPx3 panel; AUC = 0.788). Collectively, these results demonstrate the feasibility of using our pipeline for marker discovery and our MRM-MS platform for verifying potential biomarkers of human diseases.

Shift of EMT gradient in 3D spheroid MSCs for activation of mesenchymal niche function.

Despite the wide use of mesenchymal stromal cells (MSCs) for paracrine support in clinical trials, their variable and heterogeneous supporting activity pose major challenges. While three-dimensional (3D) MSC cultures are emerging as alternative approaches, key changes in cellular characteristics during 3D-spheroid formation remain unclear. Here, we show that MSCs in 3D spheroids undergo further progression towards the epithelial-mesenchymal transition (EMT), driven by upregulation of EMT-promoting microRNAs and suppression of EMT-inhibitory miRNAs. The shift of EMT in MSCs is associated with widespread histone modifications mimicking the epigenetic reprogramming towards enhanced chromatin dynamics and stem cell-like properties, but without changes in their surface phenotype. Notably, these molecular shifts towards EMT in 3D MSCs caused enhanced stem cell niche activity, resulting in higher stimulation of hematopoietic progenitor self-renewal and cancer stem cell metastasis. Moreover, miRNA-mediated induction of EMT in 2D MSCs were sufficient to mimic the enhanced niche activity of 3D spheroid MSCs. Thus, the molecular hierarchy in the EMT gradient among phenotypically indistinguishable MSCs revealed the previously unrecognized functional parameters in MSCs, and the EMT-enhanced "naïve" mesenchymal state represents an 'activated mesenchymal niche' in 3D spheroid MSCs.

The efficacy and safety of Danggui-Sayuk-Ga-Osuyu-Saenggang-tang on Korean patients with cold hypersensitivity in the hands: study protocol for a pilot, double-blind, randomized, placebo-controlled, parallel-group clinical trial.

BACKGROUND: In recent years, cold hypersensitivity in the hands (CHH) has become a common ailment of women in Korea. It can lead to gynecological problems such as irregular menstruation, miscarriage, and infertility. Traditionally, Korean herbal medicine has been the primary treatment method used to balance thermoregulation in the human body; however, its effectiveness has not been confirmed through systematic study. Thus, in this trial, we will investigate the feasibility of a full randomized clinical trial, Danggui-Sayuk-Ga-Osuyu-Saenggang-tang (DSGOST) in Korean women with CHH. METHODS: This study will be a pilot, multicenter, double-blind, randomized, parallel-group, two-arm, placebo-controlled clinical trial. A total of 66 participants will be randomly divided into two groups, a DSGOST treatment group and a placebo control group, in a 1:1 ratio using a web-based randomization system. Each group will take DSGOST or placebo three times daily for 6 weeks. The primary outcome will be measured using Visual Analogue Scale (VAS) scores of CHH. Secondary outcomes will include changes in skin temperature of the hands, Clinical Global Impressions (CGI) scale scores, recovery rate of skin temperature of the hands after the cold stress test, and the Korean version of the WHO Quality of Life Scale, abbreviated version (WHOQOL-BREF). DISCUSSION: This trial will be the first trial to reflect the newly defined disease range of CHH which was compiled by Korean medicine expert consensus. This study will provide considerable evidence for further large-scale trials and general clinical guidelines for CHH in the Korean medical field. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov, ID: NCT02645916 . Registered on 30 December 2015.

One-Step Synthesis of Cross-Linked Ionic Polymer Thin Films in Vapor Phase and Its Application to an Oil/Water Separation Membrane.

In spite of the huge research interest, ionic polymers could not have been synthesized in the vapor phase because the monomers of ionic polymers contain nonvolatile ionic salts, preventing the monomers from vaporization. Here, we suggest a new, one-step synthetic pathway to form a series of cross-linked ionic polymers (CIPs) in the vapor phase via initiated chemical vapor deposition (iCVD). 2-(Dimethylamino)ethyl methacrylate (DMAEMA) and 4-vinylbenzyl chloride (VBC) monomers are introduced into the iCVD reactor in the vapor phase to form a copolymer film. Simultaneously in the course of the deposition process, the tertiary amine in DMAEMA and benzylic chloride in VBC undergo a Menshutkin nucleophilic substitution reaction to form an ionic ammonium-chloride complex, forming a highly cross-linked ionic copolymer film of p(DMAEMA-co-VBC). To the best of our knowledge, this is the first report on the synthesis of CIP films in the vapor phase. The newly developed CIP thin film is further applied to the surface modification of the membrane for oil/water separation. With the hydrophilic and underwater oleophobic membrane whose surface is modified with the CIP film, excellent separation efficiency (>99%) and unprecedentedly high permeation flux (average 2.32 × 105 L m-2 h-1) are achieved.