Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression.

Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.

Advancing LED technology: the FDCSP element's breakthrough in mini and micro-LED packaging and backlight module enhancement.

In this research, we introduce an advanced methodology for the calculation of bulk light sources tailored for free-form surface design, focusing on the principle of energy conservation. This method is especially relevant for the evolving needs of micro-LED packaging, highlighting its potential in this burgeoning field. Our work includes the development of an algorithm for creating freeform-designed chip-scale package (FDCSP) components. These components seamlessly integrate LEDs and lenses, underscoring our commitment to advancing free-form surface design in chip-level packaging. By adhering to the principle of energy conservation, our approach facilitates a meticulous comparison of simulation outcomes with predefined target functions. This enables the iterative correction of discrepancies, employing layering techniques to refine the design until the simulated results closely align with our goals, as demonstrated by an appropriate difference curve. The practical application of these simulations leads to the innovative design of FDCSP devices. Notably, these devices are not just suitable for traditional applications in backlight modules but are explicitly optimized for the emerging sector of micro-LED packaging. Our successful demonstration of these FDCSP devices within backlight modules represents a significant achievement. It underscores the effectiveness of our design strategy and its expansive potential to transform micro-LED packaging solutions. This research not only contributes to the theoretical understanding of energy conservation in lighting design but also paves the way for groundbreaking applications in micro-LED and backlight module technologies.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring.

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins.

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, termed ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss (ML) estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively. Data consisted of test-day records collected during January 2021 through March 2022 from 265 herds in Hokkaido, Japan. From these records, we extracted records between 7 to 305 d in milk (DIM) in the first lactation to fit the RRTDM. The model included the random effect of herd-test-day, the fixed effect of year-month, fixed lactation curves nested with calving age groups, and random regressions with Legendre polynomials of order 3 for additive genetic and permanent environmental effects. The analysis was performed using Gibbs sampling with Gibbsf90+ software. The averages (ranges) of the daily heritability estimates over lactation were 0.086 (0.075-0.095) for SCS, 0.104 (0.073-0.127) for ML_SCS_DSCC, 0.137 (0.014-0.297) for SCS_4_DSCC_65_binary, and 0.138 (0.115-0.185) for ML_SCS_DSCC_binary; the heritability curve for SCS_4_DSCC_65_binary was erratic. Genetic correlations within the trait decreased as the DIM interval widened, especially for those integrating DSCC, indicating that these traits should be analyzed using RRTDM rather than repeatability models. The averages (ranges) of genetic correlations with milk yield over lactation were 0.01 (-0.22 to 0.28) for SCS, -0.05 (-0.40 to 0.13) for ML_SCS_DSCC, -0.08 (-0.17 to 0.09) for SCS_4_DSCC_65_binary, and -0.08 (-0.22 to 0.27) for ML_SCS_DSCC_binary. Compared with SCS, the newly defined traits exhibited slightly stronger negative genetic correlations with milk yield. Especially in late lactation stages, the genetic correlation between ML_SCS_DSCC and milk yield was significantly below zero, with a posterior median of -0.40. Furthermore, the new traits showed positive correlations with SCS, having estimates varying from 0.68 to 0.85 for ML_SCS_DSCC, 0.14 to 0.47 for SCS_4_DSCC_65_binary, and 0.61 to 0.66 for ML_SCS_DSCC_binary, depending on DIM. Considering that ML_SCS_DSCC and ML_SCS_DSCC_binary have relatively high heritability (compared with SCS) and favorable genetic correlations with milk production traits and SCS, their incorporation into breeding programs appears promising. Nevertheless, their genetic relationships with (sub)clinical mastitis require further investigation.

Pathogen and severity-dependent immune responses in bovine mastitis: highlight the dynamics of differential somatic cell count.

Immune responses in bovine clinical mastitis (CM) probably differ depending on the causative pathogen and disease severity. The observational study aimed to investigate whether both factors are associated with the dynamics of immune indicators, including somatic cell score (SCS), white blood cell count (WBC), serum albumin/globulin (A/G) ratio, and differential somatic cell count (DSCC). We collected blood and milk samples 0, 3, 5, 7, 14, and 21 days after CM occurred in 38 cows, and grouped the cases (n=49) by disease severity and pathogen. We analyzed data using a linear mixed model considering the effects of pathogens and severity, calculated estimated-marginal means for indicators at each time point, and compared the means between groups. The dynamics of WBC varied depending on both pathogen and severity. WBC changed drastically in either severe or coliform-caused CM, slightly elevated in streptococcal mastitis, but unchanged in staphylococcal mastitis. This possibly relates to the deficiency in innate immune response toward staphylococci. The A/G ratio also changed depending on severity, as it dropped sharply only in severe CM. We observed a non-linear relationship between DSCC and SCS, possibly due to mammary epithelial cells shedding in milk when CM occurred. When cows recovering from Streptococcus dysgalatiae mastitis, DSCC decreased while SCS remained high, suggesting a healing process requiring more macrophages. Our results demonstrate that both the severity and pathogen are associated with immune responses in CM, providing insights into mastitis pathogenesis.

Estimating the nonlinear interaction between somatic cell score and differential somatic cell count on milk production by parity using generalized additive models.

This observational study aimed to use somatic cell score (SCS) and differential somatic cell count (DSCC), the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells, to investigate how mastitis affected milk production. Using generalized additive models, we analyzed 50,618 test-day records from 8,081 lactations from 7,912 cows in 197 herds between January 2021 and March 2022 to estimate the nonlinear interaction between SCS and DSCC, and the effects of lactation stages and seasons on milk yield, milk component percentages, and milk component yields by parity of cows. The results show that the interaction between SCS and DSCC on these traits was significant, nonlinear, and complex. When DSCC was high, the negative effects of SCS were minimal, even when SCS reached 8 (i.e., 3,200,000 somatic cells/mL). Cows with high DSCC could have milk yields similar to healthy cows, implying that these cows may have been in the early stages of mastitis and that the milk yield had yet to be affected. Contrastingly, when DSCC was low, milk loss due to high SCS was drastic, especially for cows in third or later lactations, whose milk yield could reduce from more than 35 kg/d to less than 15 kg/d (-59.9%). This tremendous milk loss in high-parity cows was likely due to their higher milk yield and higher risks of chronic mastitis. High SCS and low DSCC also led to a pronounced change in milk composition. The decrease in the percentage of lactose can be directly related to the damage of inflammation to the mammary gland, while the increase in fat and protein percentages was more attributable to the concentration effect resulting from the reduced milk yield. Compared with analyses based on categorized SCS and DSCC values, modeling these 2 indices directly helps us more precisely assess mastitis effects on milk yield and milk composition. For efficient milk production, our results indicate that we should prevent high-parity cows from entering a state of high SCS and low DSCC.

A comprehensively prognostic and immunological analysis of chloride intracellular channel protein 5 (CLIC5) in pan-cancer and identification in ovarian cancer.

CLIC5 encoded protein associates with actin-based cytoskeletal and is increasingly thought to play significant roles in human cancers. We use TCGA and GEO to explore CLIC5 expression differences, mutation and DNA methylation, TMB, MSI, and immune cell infiltration. We verified the mRNA expression of CLIC5 in human ovarian cancer cells by real-time PCR and detected the expression of CLIC5 as well as immune marker genes in ovarian cancer by immunohistochemistry. The pan-cancer analysis showed that CLIC5 is highly expressed in several malignant tumors. In some cancers, CLIC5 expression in tumor samples is associated with poorer overall survival. For example, patients with ovarian cancer with high expression of CLIC5 have a poor prognosis. CLIC5 mutation frequency increased in all tumor types. The CLIC5 promoter is hypomethylated in most tumors. CLIC5 was associated with tumor immunity and different immune cells of different tumor types, such as CD8 + T cells, tumor-associated fibroblasts, macrophages, etc. CLIC5 was positively correlated with various immune checkpoints, and TMB and MSI were correlated with dysregulation of CLIC5 in tumors. The expression of CLIC5 in ovarian cancer was detected by qPCR and IHC, and the results were consistent with the bioinformatics results. There were a strong positive correlation between CLIC5 expression and M2 macrophage (CD163) infiltration and a negative correlation with CD8 + T-cell infiltration. In conclusions, our first pan-cancer analysis offered a detailed grasp of the cancerogenic functions of CLIC5 in a variety of malignancies. CLIC5 participated in immunomodulation and performed a crucial function in the tumor microenvironment.

Mass spectrometry-based proteomics for advancing solid organ transplantation research.

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.

Association between differential somatic cell count and California Mastitis Test results in Holstein cattle.

The California Mastitis Test (CMT) has been used to estimate total somatic cell count (SCC) levels in milk; however, milk with similar SCC levels occasionally shows inconsistent CMT results, which limits the use of the CMT. This observational study aimed to investigate how differential cell counts in milk influence the CMT in Holstein cattle through the novel parameters differential somatic cell count (DSCC) and macrophage proportion (MAC). We performed the CMT on d 0, 3, 5, 7, 14, and 21 after identifying mastitis, and simultaneously measured SCC, DSCC, and MAC at the quarter level. We followed 58 mastitis events occurring in 41 cows and obtained 307 quarter-level records after data cleaning. We transformed SCC to somatic cell score (SCS) and MAC to its logarithm to fit the normal distribution and analyzed the data using the cumulative logit mixed model. Results showed that both an increase in SCS (odds ratio: 3.66, 95% confidence interval: 2.89-4.64) and the logarithm of MAC (odds ratio: 4.35, 95% confidence interval: 1.91-9.91) can contribute to a higher CMT score. During the healing process of mastitis, MAC tends to increase as SCC decreases; thus, even samples with low SCC can cause positive CMT reactions. We recommend that practitioners avoid making treatment decisions based on the CMT alone. We also noted that the CMT is sensitive to subclinical mastitis with high MAC, hence it could be considered an alternative to detecting high MAC (chronic) mastitis.

Tyrosine phosphatase activity is restricted by basic charge substituting mutation of substrates.

Phosphorylation controls important cellular signals and its dysregulation leads to disease. While most phospho-regulation studies are focused on kinases, phosphatases are comparatively overlooked. Combining peptide arrays with SAMDI mass spectrometry, we show that tyrosine phosphatase activity is restricted by basic amino acids adjacent to phosphotyrosines. We validate this model using two ß-catenin mutants associated with cancer (T653R/K) and a mouse model for intellectual disability (T653K). These mutants introduce a basic residue next to Y654, an established phosphorylation site where modification shifts ß-catenin from cell-cell adhesions and towards its essential nuclear role as Wnt-signaling effector. We show that T653-basic mutant ß-catenins are less efficiently dephosphorylated by phosphatases, leading to sustained Y654 phosphorylation and elevated Wnt signals, similar to those observed for Y654E phospho-mimic mutant mice. This model rationalizes how basic mutations proximal to phosphotyrosines can restrict counter-regulation by phosphatases, providing new mechanismistic and treatment insights for 6000+ potentially relevant cancer mutations.

Effect of selective dry cow therapy on dry period intramammary infection dynamics and their association with management factors in Japan.

Selective dry cow therapy (SDCT) allocates antibiotics in the dry period to cows or quarters with a high risk of intramammary infection (IMI), potentially improving antibiotic stewardship. However, SDCT has not been used in Japan, possibly due to concerns of negative impacts on udder health. This research aims to evaluate how the SDCT use affected dry period IMI dynamics in Japan. Additionally, the effects of management factors were also considered. At dry-off, 44 cows received antibiotics plus external teat sealant or external sealant in isolation based on their IMI risk, which was assessed using milk culture, a modified California mastitis test (CMT), and mastitis records. The SDCT approach allowed antibiotic use to be reduced by 33.7%. However, quarters with a low risk of infection who received no antibiotics had a numerically higher prevalence of IMI before calving than those who received antibiotics (28.6% vs. 19.2%). In addition, an increased risk of IMI in quarters without antibiotics was also attributed to poor herd hygiene and a shorter duration of external teat sealant adherence. The result suggests that these factors influence the outcome of an SDCT program. Therefore, a uniform recommendation for dry cow herd management may not be optimal.

Non-genomic rewiring of vitamin D receptor to p53 as a key to Alzheimer's disease.

Observational epidemiological studies have associated vitamin D deficiency with Alzheimer's disease (AD). However, whether vitamin D deficiency would result in some impacts on the vitamin D binding receptor (VDR) remains to be characterized in AD. Vitamin D helps maintain adult brain health genomically through binding with and activating a VDR/retinoid X receptor (RXR) transcriptional complex. Thus, we investigated the role of VDR in AD using postmortem human brains, APP/PS1 mice, and cell cultures. Intriguingly, although vitamin D was decreased in AD patients and mice, hippocampal VDR levels were inversely increased. The abnormally increased levels of VDR were found to be colocalized with Aß plaques, gliosis and autophagosomes, implicating a non-genomic activation of VDR in AD pathogenesis. Mechanistic investigation revealed that Aß upregulated VDR without its canonical ligand vitamin D and switched its heterodimer binding-partner from RXR to p53. The VDR/p53 complex localized mostly in the cytosol, increased neuronal autophagy and apoptosis. Chemically inhibiting p53 switched VDR back to RXR, reversing amyloidosis and cognitive impairment in AD mice. These results suggest a non-genomic rewiring of VDR to p53 is key for the progression of AD, and thus VDR/p53 pathway might be targeted to treat people with AD.

Phase analysis on the error scaling of entangled qubits in a 53-qubit system.

We have studied carefully the behaviors of entangled qubits on the IBM Rochester with various connectivities and under a "noisy" environment. A phase trajectory analysis based on our measurements of the GHZ-like states is performed. Our results point to an important fact that entangled qubits are "protected" against environmental noise by a scaling property that impacts only the weighting of their amplitudes. The reproducibility of most measurements has been confirmed within a reasonably short gate operation time. But there still are a few combinations of qubits that show significant entanglement evolution in the form of transitions between quantum states. The phase trajectory of an entangled evolution, and the impact of the sudden death of GHZ-like states and the revival of newly excited states are analyzed in details. All observed trajectories of entangled qubits arise under the influences of the newly excited states in a "noisy" intermediate-scale quantum (NISQ) computer.

Reverse expression of α2,6-sialic acid ratios on IgG, IgM, and IgG/IgM autoantibodies correlates with mouse arthritis and rheumatoid arthritis disease activity.

BACKGROUND: Sialic acids (SIAs), for example, α2,6-SIAs, can link to conserved N-glycans of immunoglobulin G (IgG). In this study, we investigated the correlation between α2,6-SIA on IgG and IgM and the disease activity of arthritis and rheumatoid arthritis (RA) in mice. METHODS: We measured α2,6-SIA levels in IgGs and IgMs in collagen-induced arthritis (CIA). Additionally, α2,6-SIA levels in rheumatoid factors (RFs) and anti-cyclic citrullinated peptide (anti-CCP) antibodies in RA patients were measured. Correlations between α2,6-SIA on Igs and CIA were analyzed and also in RA patients by utilizing the disease activity score 28 (DAS28). The ability to differentiate RA progression by Ig and autoantibody α2,6-SIA levels was examined. RESULTS: In CIA mice, plasma IgG-α2,6-SIA/IgG ratios decreased, whereas plasma IgM-α2,6-SIA/IgM ratios increased. Moreover, arthritis was not observed in collagen-injected mice with decreased IgG-α2,6-SIA/IgG ratios and without increased IgM-α2,6-SIA/IgM ratios. Isolated IgG-α2,6-SIA/IgG ratios displayed a significant inverse correlation with DAS28 scores (r = -0.383, p = 0.037). In contrast, isolated IgM-α2,6-SIA/IgM ratios correlated positively with DAS28 (r = 0.351, p = 0.009). Isolated IgG-anti-CCP-α2,6-SIA/plasma IgG-anti-CCP ratios were differentiated into either the remission (higher ratios) or the nonremission (lower ratios) category (p = 0.061), which is similar to the pattern for C-reactive protein (CRP) (p = 0.041) but different from that for the erythrocyte sedimentation rate (ESR) (p = 0.421). Using multiple linear regression analysis, plasma IgMRF-α2,6-SIA/IgMRF ratios displayed a correlation with DAS28 (p = 0.006), which was also observed in the ESR (p = 0.005), but was different from that for CRP (p = 0.222). CONCLUSION: Concurrent reverse expression of α2,6-SIA ratios on IgM and IgG correlated with the occurrence of CIA and RA disease activity. Thus, α2,6-SIA ratios on IgG-anti-CCP antibodies and IgMRF are potential markers for evaluating RA disease activities.

Profiling Protein Tyrosine Phosphatase Specificity with Self-Assembled Monolayers for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry and Peptide Arrays.

The opposing activities of phosphatases and kinases determine the phosphorylation status of proteins, yet kinases have received disproportionate attention in studies of cellular processes, with the roles of phosphatases remaining less understood. This Research Article describes the use of phosphotyrosine-containing peptide arrays together with matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to directly profile phosphatase substrate selectivities. Twenty-two protein tyrosine phosphatases were characterized with the arrays to give a profile of their specificities. An analysis of the data revealed that certain residues in the substrates had a conserved effect on activity for all enzymes tested, including the general rule that inclusion of a basic lysine or arginine residue on either side of the phosphotyrosine decreased activity. This insight also provides a new perspective on the role of a R1152Q mutant in the insulin receptor, which is known to exhibit a lower phosphorylation level and which this work suggests may be due to an increased activity toward phosphatase enzymes. The use of self-assembled monolayers for matrix-assisted laser desorption/ionization mass spectrometry (SAMDI-MS) to provide a rapid and quantitative assay of phosphatase enzymes will be important to gaining a more complete understanding of the biochemistry and biology of this important enzyme class.

Combining SAMDI Mass Spectrometry and Peptide Arrays to Profile Phosphatase Activities.

Phosphatases, the enzymes responsible for dephosphorylating proteins, play critical roles in many cellular processes. While their importance is widely recognized, phosphatase activity and regulation remain poorly understood. Currently, there are few assays available that are capable of directly measuring phosphatase activity and specificity. We have previously introduced SAMDI (self-assembled monolayers on gold for matrix-assisted laser desorption/ionization) mass spectrometry as a technique to profile the substrate specificities of enzymes. SAMDI mass spectrometry assays are well suited to examine phosphatase activities and offer many advantages over current methods. This technique uses monolayers that terminate with a peptide or molecular enzyme substrate and allows for enzyme reactions to be performed on a surface that can easily be rinsed and analyzed by mass spectrometry without the need for analyte labeling. In this chapter, we describe the process of combining SAMDI mass spectrometry with peptide arrays to study the substrate specificities of two protein tyrosine phosphatases.

Correction: A high quality liquid-type quantum dot white light-emitting diode.

Correction for 'A high quality liquid-type quantum dot white light-emitting diode' by Chin-Wei Sher et al., Nanoscale, 2016, 8, 1117-1122.

A Bottom-Up Proteomic Approach to Identify Substrate Specificity of Outer-Membrane Protease OmpT.

Identifying peptide substrates that are efficiently cleaved by proteases gives insights into substrate recognition and specificity, guides development of inhibitors, and improves assay sensitivity. Peptide arrays and SAMDI mass spectrometry were used to identify a tetrapeptide substrate exhibiting high activity for the bacterial outer-membrane protease (OmpT). Analysis of protease activity for the preferred residues at the cleavage site (P1, P1') and nearest-neighbor positions (P2, P2') and their positional interdependence revealed FRRV as the optimal peptide with the highest OmpT activity. Substituting FRRV into a fragment of LL37, a natural substrate of OmpT, led to a greater than 400-fold improvement in OmpT catalytic efficiency, with a kcat /Km value of 6.1×106  L mol-1 s-1 . Wild-type and mutant OmpT displayed significant differences in their substrate specificities, demonstrating that even modest mutants may not be suitable substitutes for the native enzyme.

MicroRNA-302b-3p Suppresses Cell Proliferation Through AKT Pathway by Targeting IGF-1R in Human Gastric Cancer.

BACKGROUND/AIMS: MiR-302b is a major microRNA found in human embryonic stem cells and induced pluripotent stem cells. However, its function in gastric cancer progression remains unclear. METHODS: Quantitative reverse transcription-PCR was performed to detect the expression levels of miR-302b-3p in gastric cancer tissues. MTT, colony formation, and flow cytometer analyses were conducted to explore the function of miR-302b-3p in MKN-45/SGC-7901 cells. A dual-luciferase reporter was used to validate the bioinformatics-predicted target gene of miR-302b-3p. Western blotting and RNA interference were used to evaluate the expression of the AKT signaling pathway and determine the mechanisms underlying miR-302b-3p-induced anti-tumor effects. RESULTS: MiR-302b-3p expression was decreased in gastric cancer tissues and cell lines. Enforced expression of miR-302b suppressed cell proliferation and cell cycle G1-S transition and induced apoptosis. IGF-1R was found to be a direct target of miR-302b-3p, and silencing of IGF-1R resulted in the same biological effects as those induced by miR-302b-3p overexpression in gastric cancer cells. Importantly, both overexpression of miR-302b-3p and silencing of IGF-1R decreased AKT phosphorylation, which modulated AKT related cell cycle regulators (cyclin A2, cyclin D1, CDK2, and CDk6) and apoptotic protein Bax/Bcl-2. CONCLUSION: These results indicate the tumor suppressor role of miR-302b-3p in the pathogenesis of gastric cancer.