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Lung cancer is one of the most common malignant tumours worldwide and its high mortality rate makes it a leading cause of cancer-related deaths. To address this daunting challenge, we need a comprehensive understanding of the pathogenesis and progression of lung cancer in order to adopt more effective therapeutic strategies. In this regard, integrating multi-omics data of the lung provides a highly promising avenue. Multi-omics approaches such as genomics, transcriptomics, proteomics, and metabolomics have become key tools in the study of lung cancer. The application of these methods not only helps to resolve the immunotherapeutic mechanisms of lung cancer, but also provides a theoretical basis for the development of personalised treatment plans. By integrating multi-omics, we have gained a more comprehensive understanding of the process of lung cancer development and progression, and discovered potential immunotherapy targets. This review summarises the studies on multi-omics and immunology in lung cancer, and explores the application of these studies in early diagnosis, treatment selection and prognostic assessment of lung cancer, with the aim of providing more personalised and effective treatment options for lung cancer patients.

BackgroundColorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development.MethodsWe analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics.ResultsMR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene.ConclusionThis study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

Breast cancer (BC) is one of the most common and fatal malignancies among women worldwide. Circadian rhythms have emerged in recent studies as being involved in the pathogenesis of breast cancer. In this paper, we reviewed the molecular mechanisms by which the dysregulation of the circadian genes impacts the development of BC, focusing on the critical clock genes, brain and muscle ARNT-like protein 1 (BMAL1) and circadian locomotor output cycles kaput (CLOCK). We discussed how the circadian rhythm disruption (CRD) changes the tumor microenvironment (TME), immune responses, inflammation, and angiogenesis. The CRD compromises immune surveillance and features and activities of immune effectors, including CD8+ T cells and tumor-associated macrophages, that are important in an effective anti-tumor response. Meanwhile, in this review, we discuss bidirectional interactions: age and circadian rhythms, aging further increases the risk of breast cancer through reduced vasoactive intestinal polypeptide (VIP), affecting suprachiasmatic nucleus (SCN) synchronization, reduced ability to repair damaged DNA, and weakened immunity. These complex interplays open new avenues toward targeted therapies by the combination of clock drugs with chronotherapy to potentiate the immune response while reducing tumor progression for better breast cancer outcomes. This review tries to cover the broad area of emerging knowledge on the tumor-immune nexus affected by the circadian rhythm in breast cancer.

Melanoma, a malignant skin cancer arising from melanocytes, exhibits rapid metastasis and a high mortality rate, especially in advanced stages. Current treatment modalities, including surgery, radiation, and immunotherapy, offer limited success, with immunotherapy using immune checkpoint inhibitors (ICIs) being the most promising. However, the high mortality rate underscores the urgent need for robust, non-invasive biomarkers to predict patient response to adjuvant therapies. The immune microenvironment of melanoma comprises various immune cells, which influence tumor growth and immune response. Melanoma cells employ multiple mechanisms for immune escape, including defects in immune recognition and epithelial-mesenchymal transition (EMT), which collectively impact treatment efficacy. Single-cell analysis technologies, such as single-cell RNA sequencing (scRNA-seq), have revolutionized the understanding of tumor heterogeneity and immune microenvironment dynamics. These technologies facilitate the identification of rare cell populations, co-expression patterns, and regulatory networks, offering deep insights into tumor progression, immune response, and therapy resistance. In the realm of biomarker discovery for melanoma, single-cell analysis has demonstrated significant potential. It aids in uncovering cellular composition, gene profiles, and novel markers, thus advancing diagnosis, treatment, and prognosis. Additionally, tumor-associated antibodies and specific genetic and cellular markers identified through single-cell analysis hold promise as predictive biomarkers. Despite these advancements, challenges such as RNA-protein expression discrepancies and tumor heterogeneity persist, necessitating further research. Nonetheless, single-cell analysis remains a powerful tool in elucidating the mechanisms underlying therapy response and resistance, ultimately contributing to the development of personalized melanoma therapies and improved patient outcomes.

Abstract Background & aims The effects of SARS-CoV-2 infection can be more complex and severe in patients with hepatocellular carcinoma (HCC) as compared to other cancers. This is due to several factors, including pre-existing conditions such as viral hepatitis and cirrhosis, which are commonly associated with HCC. Methods We conducted an analysis of epigenomics in SARS-CoV-2 infection and HCC patients, and identified common pathogenic mechanisms using weighted gene co-expression network analysis (WGCNA) and other analyses. Hub genes were identified and analyzed using LASSO regression. Additionally, drug candidates and their binding modes to key macromolecular targets of COVID-19 were identified using molecular docking. Results The epigenomic analysis of the relationship between SARS-CoV-2 infection and HCC patients revealed that the co-pathogenesis was closely linked to immune response, particularly T cell differentiation, regulation of T cell activation and monocyte differentiation. Further analysis indicated that CD4+ T cells and monocytes play essential roles in the immunoreaction triggered by both conditions. The expression levels of hub genes MYLK2, FAM83D, STC2, CCDC112, EPHX4 and MMP1 were strongly correlated with SARS-CoV-2 infection and the prognosis of HCC patients. In our study, mefloquine and thioridazine were identified as potential therapeutic agents for COVID-19 in combined with HCC. Conclusions In this research, we conducted an epigenomics analysis to identify common pathogenetic processes between SARS-CoV-2 infection and HCC patients, providing new insights into the pathogenesis and treatment of HCC patients infected with SARS-CoV-2.

Background: In the past, many meta-analyses (MAs) suggested that elemene injection (EI) played a complementary and alternative role in cancer treatment. However, some results were contradictory and a lot of evidences weren’t classified. Thus, their clinical guidance effect was very limited. Methods: Two reviewers independently retrieved 8 databases from their origin to May 19, 2023 and appropriate MAs were taken into consideration. A pooled analysis was conducted to merge results extracted from trials of included MAs. The methodological quality of MAs and the evidence certainty of pooled results were assessed. Results: 31 MAs were taken into analysis with poor methodological quality. The main weaknesses were in the areas of heterogeneity analysis, bias risk, and literature selection. According to the present evidence, on the one hand, compared with conventional treatment (CT) alone, EI combined with CT may significantly enhance short-term or long-term efficacy and reduce adverse reactions caused by CT in multiple cancers. On the other hand, using EI alone also can improve ORR in the malignant (pleural) effusion and lessen the recurrence rate in bladder cancer obviously with fewer adverse reactions compared with CT alone. However, this evidence was rated as moderate to very low certainty mainly due to the risk of bias in clinical trials. Conclusion: EI may be a viable medication for the treatment of cancer although more convincing trials are still required to demonstrate its alternative and complementary benefits. Besides, it seems to have a broad potential for further development in immunotherapy, drug delivery technique, and predictive factor.

Abstract As a kind of carcinoma with increasing morbidity, poor prognosis, and high mortality, esophageal squamous cell carcinoma (ESCC) is challenging for clinical management. Chemotherapy has been the standard treatment for ESCC over decades, while its clinical outcomes remain unsatisfying. And the regimen that combine standard chemotherapy with targeted therapy also demonstrates little effect. However, the advent of immune checkpoint inhibitors (ICI) proved to be a game changer in cancer treatment. Recent clinical trials had sprung up to evaluate the combined effect of ICI and chemotherapy regarding first‐line ESCC treatment. What's more, researchers attempt to explore the possibility to implement ICI monotherapy regarding second‐line ESCC treatment. In conclusion, most of the first‐line trails present inspiring achievement, while ICI monotherapy indicates little improvement for ESCC treatment. To point out the heterogenicity that could be the potential reasons biasing the pooled results, the differences of PD‐L1 immunohistochemistry (IHC) assays, geographic regions, chemotherapy regimens, and sex disparity among these trails are discussed respectively. In addition, the adverse events occurred during the trails are summarized, which confirm the safety of immunotherapy and chemoimmunotherapy. The article comprehensively reviews the representative explorations of using chemoimmunotherapy strategies in ESCC, as well as the deficiencies among them. Moreover, we highlight some feasible approaches. It will be beneficial for conducting more precise clinical trials on chemoimmunotherapy for ESCC in the future, including the use of more appropriate PD‐L1 IHC assays, careful consideration of the heterogeneity of the enrolled population and the optimal combination of chemotherapy and ICI.

Background: Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with late diagnosis; therefore, the identification of new early biomarkers could help reduce mortality. Efferocytosis, a process in which one cell engulfs another cell, including macrophages, dendritic cells, NK cells, etc., plays a complex role in tumorigenesis, sometimes promoting and sometimes inhibiting tumor development. However, the role of efferocytosis-related genes (ERGs) in HCC progression has been poorly studied, and their regulatory effects in HCC immunotherapy and drug targeting have not been reported.Methods: We downloaded efferocytosis-related genes from the Genecards database and screened for ERGs that showed significant expression changes between HCC and normal tissues and were associated with HCC prognosis. Machine learning algorithms were used to study prognostic gene features. CIBERSORT and pRRophetic R packages were used to evaluate the immune environment of HCC subtypes and predict treatment response. CCK-8 experiments conducted on HCC cells were used to assess the reliability of drug sensitivity prediction.Results: We constructed a prognostic prediction model composed of six genes, and the ROC curve showed good predictive accuracy of the risk model. In addition, two ERG-related subgroups in HCC showed significant differences in tumor immune landscape, immune response, and prognostic stratification. The CCK-8 experiment conducted on HCC cells confirmed the reliability of drug sensitivity prediction.Conclusion: Our study emphasizes the importance of efferocytosis in HCC progression. The risk model based on efferocytosis-related genes developed in our study provides a novel precision medicine approach for HCC patients, allowing clinicians to customize treatment plans based on unique patient characteristics. The results of our investigation carry noteworthy implications for the development of individualized treatment approaches involving immunotherapy and chemotherapy, thereby potentially facilitating the realization of personalized and more efficacious therapeutic interventions for HCC.

Background: Hepatocellular carcinoma (HCC) is a malignant tumor harmful to human health. Ganji Fang (GJF) has good clinical efficacy in the treatment of HCC, but its mechanism is still unclear.Objective: The aim of this study was to investigate the mechanism of action of GJF in the treatment of HCC through network pharmacology, molecular docking and in vitro experiments.Methods: A series of network pharmacology methods were used to identify the potential targets and key pathways of GJF in the treatment of HCC. Then, molecular docking technology was used to explore the binding ability of key active ingredients and targets in GJF. Multiple external databases were used to validate the key targets. In in vitro experiments, we performed MTT assays, wound-healing assays, cell cycle assays, apoptosis assays and RT‒qPCR to verify the inhibitory effect of GJF on the Human hepatoma G2 (HepG2) cells.Result: A total of 162 bioactive components and 826 protein targets of GJF were screened, and 611 potential targets of HCC were identified. Finally, 63 possible targets of GJF acting on HCC were obtained. KEGG enrichment analyses showed that the top five pathways were the cell cycle, cellular senescence, p53 signaling pathway, PI3K/Akt signaling pathway, and progesterone-mediated oocyte maturation. Among them, we verified the PI3K/Akt signaling pathway. CCNE1, PKN1, CCND2, CDK4, EPHA2, FGFR3, CDK6, CDK2 and HSP90AAI were enriched in the PI3K/Akt pathway. The molecular docking results showed that the docking scores of eight active components of GJF with the two targets were all less than -5.0, indicating that they had certain binding activity. In vitro cell experiments showed that GJF could inhibit the proliferation and migration of HepG2 cells, block the cell cycle and induce apoptosis of HepG2 cells, which may be related to the PI3K/Akt signaling pathway. In summary, EPHA2 may be an important target of GJF in HCC, and pachymic acid may be an important critical active compound of GJF that exerts anticancer activity.Conclusion: In general, we demonstrated, for the first time, that the molecular mechanism of GJF in HCC may involve induction of G0/G1 phase cycle arrest through inhibition of the PI3K/Akt signaling pathway and promote apoptosis of hepatoma cell lines. This study provides a scientific basis for the subsequent clinical application of GJF and the in-depth study of its mechanism.

Abstract Accurate prognosis prediction is the key to achieving precision treatment and guiding the selection of adjuvant chemotherapy in high‐risk stage II/III colorectal cancer (CRC) patients. Here we developed a novel machine learning method, the random non‐negative matrix factorization (RNMF) algorithm, which outperformed traditional non‐negative matrix factorization in terms of computational speed, accuracy, and robustness in simulated data sets. Moreover, based on multidimensional data from CRC patients from The Cancer Genome Atlas database and DNA methylation data from those from Sun Yat‐sen University cancer center, we further demonstrated the excellent performance of a novel prognostic computational framework based on the RNMF (PCF_RNMF), which is capable of integrating multidimensional training while allowing survival prediction when single dimensional data for validation is provided. This novel algorithm has great potential to mitigate the challenge of integrating various types of data in public databases with clinically available single‐dimensional data to allow cost‐effective survival prediction for CRC patients in clinical practice.

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

Background Durable efficacy of immune checkpoint blockade (ICB) occurred in a small number of patients with metastatic gastric cancer (mGC) and the determinant biomarker of response to ICB remains unclear.Methods We developed an open-source TMEscore R package, to quantify the tumor microenvironment (TME) to aid in addressing this dilemma. Two advanced gastric cancer cohorts (RNAseq, N=45 and NanoString, N=48) and other advanced cancer (N=534) treated with ICB were leveraged to investigate the predictive value of TMEscore. Simultaneously, multi-omics data from The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) and Asian Cancer Research Group (ACRG) were interrogated for underlying mechanisms.Results The predictive capacity of TMEscore was corroborated in patient with mGC cohorts treated with pembrolizumab in a prospective phase 2 clinical trial (NCT02589496, N=45, area under the curve (AUC)=0.891). Notably, TMEscore, which has a larger AUC than programmed death-ligand 1 combined positive score, tumor mutation burden, microsatellite instability, and Epstein-Barr virus, was also validated in the multicenter advanced gastric cancer cohort using NanoString technology (N=48, AUC=0.877). Exploration of the intrinsic mechanisms of TMEscore with TCGA and ACRG multi-omics data identified TME pertinent mechanisms including mutations, metabolism pathways, and epigenetic features.Conclusions Current study highlighted the promising predictive value of TMEscore for patients with mGC. Exploration of TME in multi-omics gastric cancer data may provide the impetus for precision immunotherapy.

Aiming at the limited mechanical properties of general thermoplastic 3D printed models, a 3D printing process method for selective enhancement of continuous carbon fiber composite material is proposed. Firstly, the selective enhanced double nozzle working mechanism and crafts planning process are put forward. Then, based on the double nozzle carbon fiber 3D printing device, test samples are printed by polylactic acid (PLA) and carbon fiber material, and the test samples are enhanced by inserting layers of continuous carbon fiber material. The performance test of the samples is carried out. Experiment results show that when the volume fraction of continuous carbon fiber material increases gradually from 5% to 40%, the tensile strength increases from 51.22 MPa to 143.11 MPa. The performance improvement curve is fitted through experimental data. Finally, field scanning electron microscopy is used to observe the microscopic distribution of continuous fibers in the samples. The results of the research lay the foundation for the performance planning of 3D printed models.

BACKGROUND: Currently, many studies suggest that cancer stem cells (CSCs) are responsible for tumor initiation, tumorigenesis, metastasis and recurrence. CSCs have been identified from various human and murine tumors. The identification of CSCs allows us to develop strategies to target the CSCs. METHODS AND RESULTS: In this study, we used ALDEFLUOR as a single marker to isolate the CSCs from the human lung cancer cell line H460. We then characterized the CSCs by testing their sphere formation ability and tumorigenicity. Furthermore, we used CSC lysate-pulsed dendritic cells to stimulate CD8+T cells as a treatment strategy. Our study demonstrated that ALDEFLUOR could be used as a single marker to identify CSCs from the human lung cancer cell line H460. The ALDHhigh cells could form more spheres and were more tumorigenic than the ALDHlow cells. Further study demonstrated that ALDHhigh-CD8+T cells conferred more significant antitumor effects, resulting in the inhibition of tumor growth and prolonged survival. And the ALDHhigh-CD8+T cells-mediated anti-tumor immunity might be due to the directly targeting against ALDHhigh cancer stem cells (CSCs). CONCLUSIONS: This study shows that ALDHhigh-CD8+T cells mediate anti-tumor immunity by selectively targeting cancer stem cells, which result in inhibiting tumor growth and prolonging the survival of tumor-bearing mice, which provides a new strategy using ALDHhigh-CD8+T cells to treat tumors.

The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis. [ABSTRACT FROM AUTHOR]

Loss of tumor suppressor adenomatous polyposis coli (APC) activates β-catenin to initiate colorectal tumorigenesis. However, β-catenin (CTNNB1) activating mutations rarely occur in human colorectal cancer (CRC). We found that APC loss also results in up-regulation of IL-6 signal transducer (IL-6ST/gp130), thereby activating Src family kinases (SFKs), YAP, and STAT3, which are simultaneously up-regulated in the majority of human CRC. Although, initial YAP activation, which stimulates IL6ST gene transcription, may be caused by reduced serine phosphorylation, sustained YAP activation depends on tyrosine phosphorylation by SFKs, whose inhibition, along with STAT3-activating JAK kinases, causes regression of established colorectal tumors. These results explain why APC loss is a more potent initiating event than the mere activation of CTNNB1. [ABSTRACT FROM AUTHOR]

Cathepsin L (CTSL) is a lysosomal cysteine protease that has been found to be overexpressed in ovarian cancer (OC). The aim of the present study was to investigate the possible involvement of CTSL in the development of OC. In this study, RNA interference with a CTSL small hairpin RNA (CTSL-shRNA), and a plasmid carrying CTSL were used to identify the effects of this enzyme on the regulation of the malignant behavior of OC cells. OV-90 and SKOV3 human ovarian cancer cell lines were selected as cell models in vitro and in vivo. The results showed that downregulation of CTSL significantly inhibits the proliferative and invasive capability of SKOV3 cells, and that upregulation of CTSL in OV-90 cells leads to opposite effects. Compared with parental OC cells, cells in which CTSL was silenced exhibited a reduced capacity to develop into tumors in nude mice, while the growth of tumor xenografts derived from these cells was markedly constrained. In conclusion, the results suggested that CTSL contributes to the proliferation and metastasis of OC, and that CTSL may be a novel molecular target for OC treatment. [ABSTRACT FROM AUTHOR]

Nanosized micelles based on cationic, amphiphilic polytethylene glycol)-poly(ω-pentadecalactone-co -N-methyldiethyleneamine-co-sebacate) (PEG-PPMS) block copolymers have been successfully developed to serve as a new type of biodegradable non-viral vectors for DNA delivery. PEG-PPMS copolymers with various compositions were synthesized in one step via lipase-catalyzed copolymerization of ω-pentadecalactone (PDL), N-methyldiethanolamine (MDEA) and diethyl sebacate (DES) with polytethylene glycol) methyl ether (MeO-PEG-OH). The effects of PEG molecular weight, PEG and PDL contents on the biological properties (including the gene transfection efficiency) of the copolymer micelles were investigated. The LucDNA-loaded micelles formed from the copolymers with 30-50 wt% PEG showed high stability in serum-containing aqueous medium, which is in sharp contrast to rapid aggregation of LucDNA/PPMS polyplex particles. The conjugation of PEG to PPMS chains significantly reduces the cytotoxicity and hemolysis activity of the PEG-PPMS micelles. Compared to PEG-free PPMS, the micelles of PEG-PPMS copolymers with optimal compositions (e.g., 42%PEG5K-PPMS-10%PDL and 42%PEG5K-PPMS-20%PDL) exhibited enhanced capability to condense and protect DNA. Although the optimized micelles showed comparable or slightly lower gene transfection efficacy than the reference PPMS in vitro, the efficiency of LucDNA/42%PEG5K-PPMS-20%PDL micelles in transfecting tumor cells in mice was twice as high as that of LucDNA/PPMS polyplex particles due to their strong DNA condensation ability and excellent stability under physiological conditions. The PEG-PPMS micelle system with improved properties is a family of potentially promising non-viral vectors for in vivo delivery of therapeutic genes to treat tumors. [ABSTRACT FROM AUTHOR]