Search Results (16)

Lung adenocarcinoma (LUAD) is characterized by substantial genetic heterogeneity, making it challenging to identify reliable biomarkers for diagnosis and treatment. Tumor mutational burden (TMB) is widely recognized as a predictive biomarker due to its association with immune response and treatment efficacy. In this study, we take a different approach by treating TMB as a response variable to uncover its genetic drivers using multiomics data. We conducted a thorough evaluation of recent feature selection methods through extensive simulations and identified three top-performing approaches: projection correlation screening (PC-Screen), distance correlation sure independence screening (DC-SIS), and Wasserstein distance-based screening (WD-Screen). Unlike traditional approaches that rely on simple statistical tests or dataset splitting for validation, we adopt a method-based validation strategy, selecting top-ranked features from each method and identifying consistently selected genes across all three. Using The Cancer Genome Atlas (TCGA) dataset, we integrated copy number alteration (CNA), mRNA expression, and DNA methylation data as predictors and applied our selected methods. In the two-platform analysis (mRNA + CNA), we identified 13 key genes, including both previously reported LUAD-associated genes (CCNG1, CKAP2L, HSD17B4, SHROOM1, TIGD6, and TMEM173) and novel candidates (DTWD2, FLJ33630, NME5, NUDT12, PCBD2, REEP5, and SLC22A5). Expanding to a three-platform analysis (mRNA + CNA + methylation) further refined our findings, with PCBD2 and TMEM173 emerging as the robust candidates. These results highlight the complexity of multiomics integration and the need for advanced feature selection techniques to uncover biologically meaningful patterns. Our multiomics strategy and robust selection approach provide insights into the genetic determinants of TMB, offering potential biomarkers for targeted LUAD therapies and demonstrating the power of Wasserstein distance-based feature selection in complex genomic analysis. Full article

Osteoarthritis (OA) is a debilitating joint disorder characterized by cartilage degradation and disruption of chondrocyte homeostasis. Although retinoic acid (RA) has been used in OA models, its precise targets are not clear. A translational framework was employed, integrating RNA-sequencing results, network pharmacology prediction, computational ligand-receptor molecular docking, and biological experimental validation, to systematically elucidate RA’s disease-modifying targets in OA pathogenesis. RNA-sequencing of RA-treated chondrocytes revealed 656 differentially expressed genes (DEGs). Protein–protein interaction (PPI) network analysis and functional enrichment [Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG)] highlighted key pathways, including extracellular matrix (ECM) reorganization and PI3K-Akt-mediated mechanotransduction and others. Network pharmacology analysis identified 42 shared targets between RA and OA. PPI analysis and functional enrichment (GO/KEGG) highlighted pathways including the renin–angiotensin system and the neuroactive ligand–receptor interaction, among others. Molecular docking ranked candidate targets by binding affinity of RA in descending order as MAPK14 (p38α), PTGER3 (PGE2 receptor), CA2 (CA2), and others. Five intersecting targets CA2, ACE, PTGS1 (COX-1), PGR, and EDNRA (ETAR) were identified by integrating RNA-sequencing (RNA-seq) results and network pharmacology predictions. These interactions were experimentally validated via western blot, RT-qPCR and immunofluorescence. RA increased the expression of MMP13, CA2 and ACE, and decreased the expression of COL2A1 in chondrocytes. siRNA-mediated knockdown of both CA2 (human CA2 homolog) and ACE (human ACE homolog) inhibit cartilage degradation through downregulating MMP13 and upregulating COL2A1. This study not only elucidates potential molecular mechanisms by which RA modulates chondrocyte catabolism but also offers a valuable reference for the development of novel OA therapeutics. Full article

Cervical cancer ranks as the fourth most prevalent cancer and cause of cancer-related mortality among women globally. It exhibits a recurrence/metastasis rate of approximately 30% and a dismal 5-year survival of only 17% in metastatic cases. Despite significant advancements in surgical techniques, chemoradiotherapy, and targeted therapies, effective treatment options for metastatic cervical cancer remain limited. This study explored Polyphyllin I (PPI), which is a monomeric compound derived from the Rhizoma of Paris Polyphyllin, as a potential inhibitor of cervical cancer metastasis. Mechanistically, PPI directly interacted with β-catenin at the Ser552 site, inhibiting its phosphorylation and subsequent nuclear translocation, thereby suppressing TCF/LEF transcriptional activity and downstream EMT transcription factors (ZEB1, Slug, Snail, and Twist). Notably, PPI promoted β-catenin degradation via the autophagy–lysosomal pathway, as confirmed by CHX chase assays and the detection of the p62 and LC3 proteins, without altering the mRNA levels of β-catenin. In vitro experiments demonstrated that PPI effectively suppressed the migration and invasion of HO-8910PM cells by reversing the process of EMT. Additionally, PPI effectively inhibited TCF/LEF signaling, leading to a reduction in the transcription levels of EMT-associated transcription factors (EMT-TFs), which was mediated by the TCF/LEF family downstream of β-catenin. Furthermore, PPI exhibited inhibitory effects on proliferation, migration, and invasion in both HPV-positive (SiHa) and HPV-negative (C33A) cervical cancer cells. In vivo, PPI significantly suppressed peritoneal metastasis in a luciferase-labeled HO-8910PM xenograft mouse model. These findings reveal the dual role of PPI in blocking β-catenin signaling and inducing β-catenin depletion, thereby effectively restraining metastatic progression. This study underscores the potential of PPI as a promising therapeutic candidate for targeting cervical cancer metastasis through autophagy-mediated β-catenin regulation, offering a novel strategy to address current treatment limitations. Full article

Colorectal cancer (CRC) is a commonly fatal cancer and ranks as the fourth most prevalent in men and third in women worldwide. While early-stage survival rates are high, they significantly decrease with recurrence and metastasis. Thus, the early detection and treatment of metastasis-related factors can significantly improve survival rates. In this study, the transmembrane 7 superfamily member 2 (TM7SF2) gene was validated as a biomarker for predicting metastasis in CRC. Immunohistochemical staining was performed on 236 CRC tissues, and the clinicopathological factors of patients with CRC were analyzed. This evaluation revealed that TM7SF2 expression is associated with the clinical stage. Kaplan–Meier analysis confirmed the relationship between the survival rate of CRC patients and TM7SF2 expression, showing a decrease in survival rate with TM7SF2 overexpression (log-rank, p < 0.001). TM7SF2 expression was also confirmed in two pairs of primary and metastatic cell lines (SW480 and SW620). TM7SF2 knockdown was executed using siRNAs in SW480 and SW620 cells, which exhibit high expression levels. The knockdown was verified using RT-PCR and immunoblotting. Functional studies investigated the effects of TM7SF2 on cell proliferation, migration, invasion, and colony formation, revealing that all these functions were suppressed in the CRC cell lines following TM7SF2 knockdown. Therefore, TM7SF2 shows promise as a biomarker for the prevention of colorectal cancer. Full article

Background/Objectives: In this study, HECP2k polymer, polyethylenimine2k (PEI2k)-modified hydroxyethyl cellulose (HEC) was utilized to form the nanocomplexes with receptor activator of nuclear factor k-B (RANK) siRNA and zoledronate (Zol) for osteoclast inhibition. HECP2k/(RANK siRNA + Zol) nanocomplexes prepared by simple mixing were anticipated to overcome the low transfection efficiency of siRNA and the low bioavailability of Zol. Methods: The characterization of both HECP2k/(pDNA + Zol) nanocomplexes and HECP2k/(RANK siRNA + Zol) nanocomplexes was performed. Results: The nanocomplexes were successfully formed even in the presence of Zol, showing about 200 nm sizes and about 20 mV of positive zeta potential values suitable for efficient cellular uptake. They also possessed high endosome buffering ability by PEI and Zol, suggesting the potential for efficient endosomal escape. It was found that the low cytotoxic nanocomplexes (>90% cell viability) displayed greater transfection efficiency than PEI25k and even HECP2k polyplexes. Finally, it was found by tartrate-resistant acid phosphatase (TRAP) assay and qPCR analysis that HECP2k/(RANK siRNA + Zol) nanocomplexes could inhibit the TRAP to about 50% value and another characteristic osteoclastic gene expression, increasing FAS gene expression to about 16 times higher than control and more efficiently (about 3 times and 5 times higher, respectively) than HECP2k/siRNA polyplexes and Zol only. Conclusions: HECP2k/(RANK siRNA + Zol) nanocomplexes formed by simple mixing showed great potential for inhibiting osteoclast differentiation and osteoclast activity, inducing the apoptosis via combinatorial effects of RANK siRNA and Zol. Full article

Whole-genome sequencing has revealed that TP53, NOTCH1, ATM, SF3B1, BIRC3, ABL, NXF1, BCR, and ZAP70 are often mutated in CLL, but not consistently across all CLL patients. This paper employs a statistical thermodynamics approach in combination with the systems biology of the CLL protein–protein interaction networks to identify the most significant participant proteins in the cancerous transformation. Betti number (a topology of complexity) estimates highlight a protein hierarchy, primarily in the Wnt pathway known for aberrant CLL activation. These individually identified proteins suggest a network-targeted strategy over single-target drug development. The findings advocate for a multi-target inhibition approach, limited to several key proteins to minimize side effects, thereby providing a foundation for designing therapies. This study emphasizes a shift towards a comprehensive, multi-scale analysis to enhance personalized treatment strategies for CLL, which could be experimentally validated using siRNA or small-molecule inhibitors. The result is not just the identification of these proteins but their rank-order, offering a potent signal amplification in the context of the 20,000 proteins produced by the human body, thus providing a strategic basis for therapeutic intervention in CLL, underscoring the necessity for a more holistic, cellular, chromosomal, and genome-wide study to develop tailored treatments for CLL patients. Full article

Background: Neural Wiskott–Aldrich Syndrome Protein (N-WASP) is a key regulator of the actin cytoskeleton and is implicated in various cellular processes, including cell motility and invasion. In cancer biology, the role of N-WASP in cell motility and metastasis is of particular interest, yet its specific functions in breast cancer remain to be fully understood. Method: To investigate the impact of N-WASP on breast cancer cell behaviour, we employed siRNA to knock down N-WASP expression in the MDA-MB-231 breast cancer cell line. After the knockdown, proteomic changes in the cells were analysed using mass spectrometry. Notable alterations in the genes present in both total and phosphorylated proteins were further analysed. Results: The proteomic data analysis ranked 50 genes that exhibited the most up-regulation and down-regulation in total and phosphorylated proteins. These 200 genes were further examined using the REACTOME database to identify affected signalling pathways. Knockdown of N-WASP led to significant changes in the RHOD, RHOF, and RHOG GTPase cycles (p = 0.015, p = 0.01, and p = 0.027), pathways closely associated with cell motility and actin cytoskeleton organisation. These cycles are crucial in modulating cellular dynamics, impacting a range of processes from immune response to neuronal development, wound healing, and, particularly, cancer metastasis. Furthermore, the findings highlighted the role of non-integrin membrane–ECM interactions in cell motility and cytoskeleton dynamics (p = 0.021). The altered protein expression patterns suggest a link between N-WASP, non-integrin membrane–ECM interactions, and the cytoskeletal changes essential for cell migration and invasion—key factors in cancer metastasis. Conclusions: Our findings reinforce the critical role of N-WASP in regulating the cytoskeleton and influencing cell motility, invasion, and metastasis in breast cancer. This study not only provides deeper insights into the molecular mechanism of breast cancer progression but also highlights N-WASP as a potential therapeutic target for intervention strategies in breast cancer treatment. Full article

Background: Gastric cancer, ranked as the fifth most common cancer worldwide, presents multiple treatment challenges. These obstacles often arise due to cancer stem cells, which are associated with recurrence, metastasis, and drug resistance. While dendritic cell (DC)-based immunotherapy has shown promise as a therapeutic strategy, its efficacy can be limited by the tumor microenvironment and certain inhibitory immune checkpoint molecules, such as B7H7. SiRNA-medicated knockdown of B7H7 in tumor cell lysate-pulsed DCs can increase cytokine secretion and autologous T lymphocyte expansion. This study aimed to evaluate the impact of B7H7 suppression in gastric cancer cell lysate-pulsed DCs on the stimulatory potential of autologous CD3⁺ T lymphocytes. Methods: Peripheral blood mononuclear cells (PBMCs) were isolated and monocytes were obtained; then, they were differentiated to immature DCs (iDCs) by GM-CSF and IL-4. Tumor cell lysates from human gastric cancer cell lines were harvested, and iDCs were transformed into mature DCs (mDCs) by stimulating iDCs with tumor cell lysate and lipopolysaccharide. B7H7-siRNA was delivered into mDCs using electroporation, and gene silencing efficiency was assessed. The phenotypic characteristics of iDCs, mDCs, and B7H7-silenced mDCs were evaluated using specific surface markers, an inverted light microscope, and flow cytometry. CD3⁺ T cells were isolated via magnetically activated cell sorting. They were labeled with CFSE dye and co-cultured with mDCs and B7H7-silenced mDCs to evaluate their ability to induce T-cell proliferation. T-cell proliferation was assessed using flow cytometry. The concentration of TGF-β, IL-4, and IFN-γ secreted from CD3⁺ T cells in the co-cultured supernatant was evaluated to investigate the cytokine secretory activity of the cells. Results: Transfection of B7H7 siRNA into mDCs was performed in optimal conditions, and the siRNA transfection effectively reduced B7H7 mRNA expression in a dose-dependent manner. SiRNA-mediated B7H7 knockdown in mDCs enhanced maturation and activation of the DCs, as demonstrated by an increased surface expression of CD11c, CD86, and CD40. Co-culture experiments revealed that B7H7-silenced mDCs had more capacity to induce T cell proliferation compared to non-transfected mDCs. The cytokine production patterns of T cells were also altered. Upon examining the levels of TGF-β, IL-4, and IFN-γ released by CD3⁺ T cells in the co-culture supernatant, we found that silencing B7H7 in mDCs resulted in a rise in IL-4 secretion and a reduction in TGF-β levels compared to mDCs that were not transfected. Conclusions: The study found that suppressing B7H7 expression in DCs significantly enhances their maturation and stimulatory activity when exposed to gastric cancer cell lysate. These B7H7-silenced DCs can substantially increase cytokine production and promote co-cultured T-cell expansion. Consequently, inhibiting B7H7 in DCs may offer a practical strategy to enhance the ability of DCs to initiate T lymphocyte responses and improve the effectiveness of DC-based cell therapy for cancer patients. Full article

Background: Despite advances in diagnostic and therapeutic technologies, the prognosis of patients with gastric cancer (GC) remains poor, necessitating further search for more effective therapeutic targets and markers for prognosis prediction. Circular RNA (circRNA) plays a role in various diseases, including GC. Methods: CircRNA expression in GC tissues was detected by circRNA microarray and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The correlation between circRNA-0044301 and patient survival was analyzed by log-rank test and Cox regression analysis. Next, in vitro characterization and functional analysis of circRNA-0044301 was done by various assays using RNase R, actinomycin D, and RNA fluorescence in situ hybridization, as well as investigations into its use as a drug to treat tumors in a subcutaneous tumorigenesis model. RNA immunoprecipitation and dual-luciferase reporter assays were used to identify circRNA-0044301-related miRNA (miRNA-188-5p), key proteins of the related pathway (ERK1/2), and the downstream target DAXX. Finally, we investigated the relationship between circRNA-0044301 and ravoxertinib (GDC-0994) and 5-fluorouracil (5-FU) using qRT-PCR, Western blotting, and CCK8 assays. Results: CircRNA-0044301 was upregulated in tissues and cancer cells compared to its levels in controls, related to patient prognosis, and its specific siRNA-vivo could slow tumor growth. On the mechanism, it acted as a sponge of miRNA-188-5p, could regulate the downstream target DAXX, and modulated the effect of GDC-0994 on ERK1/2 and 5-FU in cells. Conclusions: CircRNA-0044301/miRNA-188-5p/DAXX (ERK1/2) may be a key axis in GC progression, and circRNA-0044301 has immense potential to be a therapeutic target for GC. Full article

DNA vaccination has been extensively studied as a promising strategy for tumor treatment. Despite the efforts, the therapeutic efficacy of DNA vaccines has been limited by their intrinsic poor cellular internalization. Electroporation, which is based on the application of a controlled electric field to enhance DNA penetration into cells, has been the method of choice to produce acceptable levels of gene transfer in vivo. However, this method may cause cell damage or rupture, non-specific targeting, and even degradation of pDNA. Skin irritation, muscle contractions, pain, alterations in skin structure, and irreversible cell damage have been frequently reported. To overcome these limitations, in this work, we use a microfluidic platform to generate DNA-loaded lipid nanoparticles (LNPs) which are then characterized by a combination of dynamic light scattering (DLS), synchrotron small-angle X-ray scattering (SAXS), and transmission electron microscopy (TEM). Despite the clinical successes obtained by LNPs for mRNA and siRNA delivery, little is known about LNPs encapsulating bulkier DNA molecules, the clinical application of which remains challenging. For in vitro screening, LNPs were administered to human embryonic kidney 293 (HEK-293) and Chinese hamster ovary (CHO) cell lines and ranked for their transfection efficiency (TE) and cytotoxicity. The LNP formulation exhibiting the highest TE and the lowest cytotoxicity was then tested for the delivery of the DNA vaccine pVAX-hECTM targeting the human neoantigen HER2, an oncoprotein overexpressed in several cancer types. Using fluorescence-activated cell sorting (FACS), immunofluorescence assays and fluorescence confocal microscopy (FCS), we proved that pVAX-hECTM-loaded LNPs produce massive expression of the HER2 antigen on the cell membrane of HEK-293 cells. Our results provide new insights into the structure–activity relationship of DNA-loaded LNPs and pave the way for the access of this gene delivery technology to preclinical studies. Full article

Nasopharyngeal carcinoma (NPC) is an Epstein–Barr virus (EBV)-associated malignancy ranking as the 23rd most common cancer globally, while its incidence rate ranked the 9th in southeast Asia. Tumor metastasis is the dominant cause for treatment failure in NPC and metastatic NPC is yet incurable. The Wnt/β-catenin signaling pathway plays an important role in many processes such as cell proliferation, differentiation, epithelial–mesenchymal transition (EMT), and self-renewal of stem cells and cancer stem cells (CSCs). Both the EMT process and CSCs are believed to play a critical role in cancer metastasis. We here investigated whether the specific CBP/β-catenin Wnt antagonist, IGC-001, affects the metastasis of NPC cells. We found that ICG-001 treatment could reduce the adhesion capability of NPC cells to extracellular matrix and to capillary endothelial cells and reduce the tumor cell migration and invasion, events which are closely associated with distant metastasis. Through a screening of EMT and CSC-related microRNAs, it was found that miR-134 was consistently upregulated by ICG-001 treatment in NPC cells. Very few reports have mentioned the functional role of miR-134 in NPC, except that the expression was found to be downregulated in NPC. Transient transfection of miR-134 into NPC cells reduced their cell adhesion, migration, and invasion capability, but did not affect the growth of CSC-enriched tumor spheres. Subsequently, we found that the ICG-001-induced miR-134 expression resulting in downregulation of integrin β1 (ITGB1). Such downregulation reduced cell adhesion and migration capability, as demonstrated by siRNA-mediated knockdown of ITGB1. Direct targeting of ITGB1 by miR-134 was confirmed by the 3′-UTR luciferase assay. Lastly, using an in vivo lung metastasis assay, we showed that ICG-001 transient overexpression of miR-134 or stable overexpression of miR-134 could significantly reduce the lung metastasis of NPC cells. Taken together, we present here evidence that modulation of Wnt/β-catenin signaling pathway could inhibit the metastasis of NPC through the miR-134/ITGB1 axis. Full article

In this research, we applied deep learning to rank the effectiveness of candidate drug compounds in combating viral cells, in particular, SARS-Cov-2 viral cells. For this purpose, two different datasets from Recursion Pharmaceuticals, a siRNA image dataset (RxRx1), which were used to build and calibrate our model for feature extraction, and a SARS-CoV-2 dataset (RxRx19a) was used to train our model for ranking efficacy of candidate drug compounds. The SARS-CoV-2 dataset contained healthy, uninfected control or “mock” cells, as well as “active viral” cells (cells infected with COVID-19), which were the two cell types used to train our deep learning model. In addition, it contains viral cells treated with different drug compounds, which were the cells not used to train but test our model. We devised a new cascade transfer learning strategy to construct our model. We first trained a deep learning model, the DenseNet, with the siRNA set, a dataset with characteristics similar to the SARS-CoV-2 dataset, for feature extraction. We then added additional layers, including a SoftMax layer as an output layer, and retrained the model with active viral cells and mock cells from the SARS-CoV-2 dataset. In the test phase, the SoftMax layer outputs probability (equivalently, efficacy) scores which allows us to rank candidate compounds, and to study the performance of each candidate compound statistically. With this approach, we identified several compounds with high efficacy scores which are promising for the therapeutic treatment of COVID-19. The compounds showing the most promise were GS-441524 and then Remdesivir, which overlapped with these reported in the literature and with these drugs that are approved by FDA, or going through clinical trials and preclinical trials. This study shows the potential of deep learning in its ability to identify promising compounds to aid rapid responses to future pandemic outbreaks. Full article

Cisplatin-based neoadjuvant chemotherapy (NAC) is recommended prior to radical cystectomy for muscle-invasive bladder cancer (MIBC) patients. Despite a 5–10% survival benefit, some patients do not respond and experience substantial toxicity and delay in surgery. To date, there are no clinically approved biomarkers predictive of response to NAC and their identification is urgently required for more precise delivery of care. To address this issue, a multi-methods analysis approach of machine learning and differential gene expression analysis was undertaken on a cohort of 30 MIBC cases highly selected for an exquisitely strong response to NAC or marked resistance and/or progression (discovery cohort). RGIFE (ranked guided iterative feature elimination) machine learning algorithm, previously demonstrated to have the ability to select biomarkers with high predictive power, identified a 9-gene signature (CNGB1, GGH, HIST1H4F, IDO1, KIF5A, MRPL4, NCDN, PRRT3, SLC35B3) able to select responders from non-responders with 100% predictive accuracy. This novel signature correlated with overall survival in meta-analysis performed using published NAC treated-MIBC microarray data (validation cohort 1, n = 26, Log rank test, p = 0.02). Corroboration with differential gene expression analysis revealed cyclic nucleotide-gated channel, CNGB1, as the top ranked upregulated gene in non-responders to NAC. A higher CNGB1 immunostaining score was seen in non-responders in tissue microarray analysis of the discovery cohort (n = 30, p = 0.02). Kaplan-Meier analysis of a further cohort of MIBC patients (validation cohort 2, n = 99) demonstrated that a high level of CNGB1 expression associated with shorter cancer specific survival (p < 0.001). Finally, in vitro studies showed siRNA-mediated CNGB1 knockdown enhanced cisplatin sensitivity of MIBC cell lines, J82 and 253JB-V. Overall, these data reveal a novel signature gene set and CNGB1 as a simpler proxy as a promising biomarker to predict chemoresponsiveness of MIBC patients. Full article

Introduction: Cancer is one of the top-ranked noncommunicable diseases causing deaths to nine million people and affecting almost double worldwide in 2018. Tremendous advancement in surgery, chemotherapy, radiation and targeted immunotherapy have improved the rate of cure and disease-free survival. As genetic mutations vary in different cancers, potential of customized treatment to silence the problem gene/s at the translational level is being explored too. Yet delivering therapeutics at the required dosage only to the affected cells without affecting the healthy ones, is a big hurdle to be overcome. Scientists worldwide have been working to invent a smart drug delivery system for targeted delivery of therapeutics to tumor tissues only. As part of such an effort, few organic nanocarriers went to clinical trials, while inorganic nanoparticles (NPs) are still in development stage despite their many customizable properties. Carbonate apatite (CA), a pH sensitive nanocarrier has emerged as an efficient delivery system for drugs, plasmids and siRNAs in preclinical models of breast and colon cancers. Like hydroxyapatite (HA) which serves as a classical tool for delivery of genetic materials such as siRNA and plasmid, CA is an apatite-based synthetic carrier. We developed simplified methods of formulating CA-in-DMEM and a DMEM-mimicking buffer and HA in a HEPES-buffered solution and characterized them in terms of size, stability, protein corona (PC) composition, cytotoxicity, siRNA delivery efficiency in breast cancer cells and siRNA biodistribution profile in a mouse model of breast cancer. Methods: Particle growth was analyzed via spectrophotometry and light microscopy, size was measured via dynamic light scattering and scanning electron microscopy and confirmation of functional groups in apatite structures was made by FT-IR. siRNA-binding was analyzed via spectrophotometry. Stability of the formulation solutions/buffers was tested over various time points and at different temperatures to determine their compatibility in the context of practical usage. Cellular uptake was studied via fluorescence microscopy. MTT assay was performed to measure the cytotoxicity of the NPs. Liquid chromatography—mass spectrometry was carried out to analyze the PC formed around all three different NPs in serum-containing media. To explore biodistribution of all the formulations, fluorescence-labeled siRNA-loaded NPs were administered intravenously prior to analysis of fluorescence intensity in the collected organs and tumors of the treated mice. Results: The size of NPs in 10% serum-containing media was dramatically different where CA-in-DMB and HA were much larger than CA-in-DMEM. Effect of media was notable on the PC composition of all three NPs. All three NPs bound albumin and some common protease inhibitors involved in bone metabolism due to their compositional similarity to our bone materials. Moreover, CA also bound heme-binding proteins and opsonins. Unlike CA, HA bound different kinds of keratins. Difference in PC constitution was likely to influence accumulation of NPs in various organs including those of reticuloendothelial system, such as liver and spleen and the tumor. We found 10 times more tumor accumulation of CA-in-DMB than CA-in-DMEM, which could be due to more stable siRNA-binding and distinct PC composition of the former. Conclusion: As a nanocarrier CA is more efficient than HA for siRNA delivery to the tumor. CA prepared in a buffer containing only the mere constituents was potentially more efficient than classical CA prepared in DMEM, owing to the exclusion of interference attributed by the inorganic ions and organic molecules present in DMEM. Full article

The oncogenic properties of heterogeneous nuclear ribonucleoprotein H1 (hnRNP H1) have been reported, although the tumor-promoting mechanism remains unclear. We herein report the mechanism underlying colorectal cancer cell progression mediated by hnRNP H1. The growth of colorectal cancer cells was suppressed by hnRNP H1 downregulation. A terminal deoxynucleotidyl transferase dUTP nick-end labeling assay revealed the anti-apoptotic effect of hnRNP H1 in colorectal cancer cells. An RNA immunoprecipitation assay revealed that hnRNP H1 bound to sphingosine-1-phosphate lyase 1 (SGPL1). Reverse transcription-polymerase chain reaction revealed the high expression of hnRNP H1 mRNA in colorectal cancer cells and Spearman’s rank correlation coefficient showed a strong positive correlation between hnRNP H1 mRNA and SGPL1 mRNA. An siRNA of hnRNP H1 decreased SGPL1 mRNA expression in colorectal cancer cells, but not in non-tumorous cells. These findings suggested that hnRNP H1 increased SGPL1 mRNA expression specifically in cancer cells through direct binding. Targeted knockdown of hnRNP H1 or SGPL1 with siRNAs upregulated p53 phosphorylation and p53-associated molecules, resulting in cell growth inhibition, while hnRNP H1 upregulated the mRNA of SGPL1 and inhibited p53 activation, thereby promoting tumor cell growth. This is a novel mechanism underlying colorectal cancer cell progression mediated by hnRNP H1–SGPL1 mRNA stabilization. Full article