Antitumor potential of dark sweet cherry sweet (Prunus avium) phenolics in suppressing xenograft tumor growth of MDA-MB-453 breast cancer cells

This study investigated in vivo the antitumor activity of dark sweet cherry (DSC) whole extracted phenolics (WE) and fractions enriched in anthocyanins (ACN) or proanthocyanidins (PCA) in athymic mice xenografted with MDA-MB-453 breast cancer cells. Mice were gavaged with WE, ACN or PCA extracts (150 mg/kg body weight/day) for 36 days.Results showed that tumor growth was suppressed at similar levels by WE, ACN and PCA compared to control group (C) without signs of toxicity or significant changes in mRNA oncogenic biomarkers in tumors or mRNA invasive biomarker in distant organs. Tumor protein analyses showed that WE, ACN and PCA induced at similar levels the stress-regulated ERK1/2 phosphorylation, known to be linked to apoptosis induction. However, ACN showed enhanced antitumor activity through down-regulation of total oncogenic and stress-related Akt, STAT3, p38, JNK and NF-kB proteins. In addition, immunohistochemistry analysis of Ki-67 revealed inhibition of tumor cell proliferation with potency WE ≥ ACN ≥ PCA. Differential quantitative proteomic high-resolution nano-HPLC tandem mass spectrometry analysis of tumors from ACN and C groups revealed the identity of 66 proteins associated with poor breast cancer prognosis that were expressed only in C group (61 proteins) or differentially up-regulated (P<.05) in C group (5 proteins). These findings revealed ACN-targeted proteins associated to tumor growth and invasion and the potential of DSC ACN for breast cancer treatment. Results lead to a follow-up study with highly immunodeficient mice/invasive cell line subtype and advanced tumor development to validate the anti-invasive activity of DSC anthocyanins.     

Characterisation of uterine sarcoma cell lines exhibiting MDR phenotype by vibrational spectroscopy

Multidrug resistance (MDR) enables cancer cells to escape cytotoxic insults of anticancer drugs. Rapid identification of cells exhibiting the MDR phenotype is very important since it can lead to an effective and individual patient based treatment plan. We have investigated a combined vibrational spectroscopic approach, using both micro-Raman and FTIR techniques, in order to characterise a sensitive human uterine sarcoma cell line MES-SA and its multidrug-resistant derivative Garf. In this study, these two complementary methods have been evaluated via the use of principal components analysis (PCA), for discrimination of cells exhibiting the MDR phenotype. Our results indicate that, though they inherently have different sensitivities, both Raman and IR methods can provide a good differentiation of cell phenotypes.     

Combined Fourier transform infrared and Raman spectroscopic approach for identification of multidrug resistance phenotype in cancer cell lines

Cancer cells escape cytotoxic effects of anticancer drugs by a process known as multidrug resistance (MDR). Identification of cell status by less time-consuming methods can be extremely useful in patient management and treatment. This study aims at evaluating the potentials of vibrational spectroscopic methods to perform cell typing and to differentiate between sensitive and resistant human cancer cell lines, in particular those that exhibit the MDR phenotype. Micro-Raman and Fourier transform infrared (FTIR) spectra have been acquired from the sensitive promyelocytic HL60 leukemia cell line and two of its subclones resistant to doxorubicin (HL60/DOX) and daunorubicin (HL60/DNR), and from the sensitive MCF7 breast cancer cell line and its MDR counterpart resistant to verapamil (MCF7/VP). Principal components analysis (PCA) was employed for spectral comparison and classification. Our data show that cell typing was feasible with both methods, giving two distinct clusters for HL60- and MCF7-sensitive cells. In addition, phenotyping of HL60 cells, i.e., discriminating between the sensitive and MDR phenotypes, was attempted by both methods. FTIR could not only delineate between the sensitive and resistant HL60 cells, but also gave two distinct clusters for the resistant cells, which required a two-step procedure with Raman spectra. In the case of MCF7 cell lines, both the sensitive and resistant phenotypes could be differentiated very efficiently by PCA analysis of their FTIR and Raman point spectra. These results indicate the prospective applicability of FTIR and micro-Raman approaches in the differentiation of cell types as well as characterization of the cell status, such as the MDR phenotype exhibited in resistant leukemia cell lines like HL60 and MCF7.     

Principal Components Analysis as a Tool to Summarise Biotransformation Data: Influence on Cells of Solvent Type and Phase Ratio

The effect of some solvents, present in different amounts, upon whole cells of Rhodococcus erythropolis DCL14 carrying out the biotransformation of (-)-carveol to (-)-carvone was studied. The solvents tested were ethyl butyrate, n-hexane, cyclohexane, iso-octane, n-dodecane, dimethyl sulfoxide, bis(2-ethylhexyl) phthalate and FC-70. The volumes of each solvent corresponded to organic:aqueous phase ratios of 0.0005, 0.0025, 0.005, 0.025 and 0.2. To assess any potential solvent protection towards substrate toxicity, assays were carried out at two initial carveol concentrations (15 and 50 mM). Carvone accumulation was followed by gas chromatography. Cell viability, several aspects of cell morphology and the ability to form clusters were monitored by fluorescence microscopy. Principal components analysis (PCA) was used as a tool to explain the differences in the observations of the multidimensional data set obtained from the multiple conditions. PCA using the different volumes of each solvent as variable suggests that the variability of the observations can be summarised in six components which represent 79.4% of the variance of the data. Conversely, using cell and solvent data to perform the PCA, 97.1% of the variance of the data can be summarised in three components, the first two capturing 91.0% of the information. These components seem to represent solvent toxicity and a protective effect of the solvent from carveol toxicity.     

Butanol-extractable and detergent-solubilized cell surface components from murine large cell lymphoma cells associated with adhesion to organ microvessel endothelial cells.

Metastatic variant cell lines of the murine RAW117 large cell lymphoma were used to study the cell surface components involved in syngeneic tumor cell/microvessel endothelial cell interactions. Poorly liver-metastatic parental RAW117-P cell line adhered to murine hepatic sinusoidal endothelial cell monolayers at significantly lower rates than the liver-selected, highly liver-metastatic RAW117-H10 line and both cell lines were poorly adherent to lung microvessel and bovine aorta endothelial cells. Viable, 2% 1-butanol-treated RAW117-H10 tumor cells formed fewer liver tumor nodules in experimental metastasis assays than untreated H10 cells and were significantly less adherent to murine hepatic sinusoidal endothelial cell monolayers. When 2% 1-butanol extracts of metabolically labeled or CHAPS detergent lysates of cell surface-labeled tumor cells were analyzed for their ability to bind to fixed microvessel endothelial cell monolayers, quantitative differences were found in the extractable tumor cell surface components that bound to the different organ-derived microvessel endothelial cells. Cell surface components (1-butanol extractable), of Mr approximately 85,000-90,000 and approximately 37,000-40,000 bound to hepatic sinusoidal endothelial cell monolayers to a greater extent than to murine lung microvessel endothelial or bovine aortic endothelial cell monolayers, whereas tumor cell surface components of Mr approximately 45,000, approximately 33,000, and approximately 25,000 bound similarly to endothelial cells regardless of origin. The results suggest but do not prove that tumor cell/endothelial cell adhesion involves multiple tumor cell surface components, some of which commonly bind to various endothelial cells and others for which binding may be dictated by the tissue origin and type of endothelial cell. Particular RAW117 butanol-extractable cell membrane components were associated with tumor cell-endothelial cell adhesion, and these components could be responsible, in part, for the preferential adhesion of RAW117 cells to liver sinusoidal endothelial cells and metastasis to liver.     

Stochastic convex sparse principal component analysis

Principal component analysis (PCA) is a dimensionality reduction and data analysis tool commonly used in many areas. The main idea of PCA is to represent high-dimensional data with a few representative components that capture most of the variance present in the data. However, there is an obvious disadvantage of traditional PCA when it is applied to analyze data where interpretability is important. In applications, where the features have some physical meanings, we lose the ability to interpret the principal components extracted by conventional PCA because each principal component is a linear combination of all the original features. For this reason, sparse PCA has been proposed to improve the interpretability of traditional PCA by introducing sparsity to the loading vectors of principal components. The sparse PCA can be formulated as an ? ₁ regularized optimization problem, which can be solved by proximal gradient methods. However, these methods do not scale well because computation of the exact gradient is generally required at each iteration. Stochastic gradient framework addresses this challenge by computing an expected gradient at each iteration. Nevertheless, stochastic approaches typically have low convergence rates due to the high variance. In this paper, we propose a convex sparse principal component analysis (Cvx-SPCA), which leverages a proximal variance reduced stochastic scheme to achieve a geometric convergence rate. We further show that the convergence analysis can be significantly simplified by using a weak condition which allows a broader class of objectives to be applied. The efficiency and effectiveness of the proposed method are demonstrated on a large-scale electronic medical record cohort.     

1H NMR Spectroscopy Profiling of Metabolic Reprogramming of Chinese Hamster Ovary Cells upon a Temperature Shift during Culture

We report an NMR based approach to determine the metabolic reprogramming of Chinese hamster ovary cells upon a temperature shift during culture by investigating the extracellular cell culture media and intracellular metabolome of CHOK1 and CHO-S cells during culture and in response to cold-shock and subsequent recovery from hypothermic culturing. A total of 24 components were identified for CHOK1 and 29 components identified for CHO-S cell systems including the observation that CHO-S media contains 5.6 times the level of glucose of CHOK1 media at time zero. We confirm that an NMR metabolic approach provides quantitative analysis of components such as glucose and alanine with both cell lines responding in a similar manner and comparable to previously reported data. However, analysis of lactate confirms a differentiation between CHOK1 and CHO-S and that reprogramming of metabolism in response to temperature was cell line specific. The significance of our results is presented using principal component analysis (PCA) that confirms changes in metabolite profile in response to temperature and recovery. Ultimately, our approach demonstrates the capability of NMR providing real-time analysis to detect reprogramming of metabolism upon cellular perception of cold-shock/sub-physiological temperatures. This has the potential to allow manipulation of metabolites in culture supernatant to improve growth or productivity.     

Unique natural antioxidants (NAOs) and derived purified components inhibit cell cycle progression by downregulation of ppRb and E2F in human PC3 prostate cancer cells

Prostate cancer (PCA) is the leading cause of cancer mortality among older men in Western countries. Epidemiological studies have shown correlation between a lower risk of PCA and a higher consumption of antioxidants. However, the mechanism by which antioxidants exert their effects is still unknown. In the present study, we explored the signaling mechanism through which unique natural antioxidant derived from spinach extract (NAO) exerts their beneficial effects in the chemoprevention of PCA using human PC3 cells. Probing into the effect of NAO and its derived polyphenols on cell-cycle G1 arrest, we found that they cause cell-cycle prolongation. NAO and its two derived purified components exhibited a significant increase in the level of p21cip1 expression after 36 h of starvation, followed by 18 h of treatment with NAO in the presence of serum. In addition, under similar conditions, the expressed level of Cyclin A and CDK-2 in the PC3 cells was significantly reduced after treatment with NAO or its purified components. Immunoblot analysis demonstrated a significant increase in the hypophosphorylated form of pRb and a decrease in ppRb. NAO and its purified derived components were found to downregulate the protein expression of another member of the pRb family, p107, as well as that of E2F-1. These results suggest that NAO-induced G1 delay and cell cycle prolongation are caused by downregulation of the protein expression of ppRb and E2F in the human PCA cell line PC3.     

Principal Components Analysis as a Tool to Summarise Biotransformation Data: Influence on Cells of Solvent Type and Phase Ratio

The effect of some solvents, present in different amounts, upon whole cells of Rhodococcus erythropolis DCL14 carrying out the biotransformation of (?)-carveol to (?)-carvone was studied. The solvents tested were ethyl butyrate, n-hexane, cyclohexane, iso-octane, n-dodecane, dimethyl sulfoxide, bis(2-ethylhexyl) phthalate and FC-70. The volumes of each solvent corresponded to organic:aqueous phase ratios of 0.0005, 0.0025, 0.005, 0.025 and 0.2. To assess any potential solvent protection towards substrate toxicity, assays were carried out at two initial carveol concentrations (15 and 50 mM). Carvone accumulation was followed by gas chromatography. Cell viability, several aspects of cell morphology and the ability to form clusters were monitored by fluorescence microscopy. Principal components analysis (PCA) was used as a tool to explain the differences in the observations of the multidimensional data set obtained from the multiple conditions. PCA using the different volumes of each solvent as variable suggests that the variability of the observations can be summarised in six components which represent 79.4% of the variance of the data. Conversely, using cell and solvent data to perform the PCA, 97.1% of the variance of the data can be summarised in three components, the first two capturing 91.0% of the information. These components seem to represent solvent toxicity and a protective effect of the solvent from carveol toxicity.     

Principal component analysis based methods in bioinformatics studies

In analysis of bioinformatics data, a unique challenge arises from the high dimensionality of measurements. Without loss of generality, we use genomic study with gene expression measurements as a representative example but note that analysis techniques discussed in this article are also applicable to other types of bioinformatics studies. Principal component analysis (PCA) is a classic dimension reduction approach. It constructs linear combinations of gene expressions, called principal components (PCs). The PCs are orthogonal to each other, can effectively explain variation of gene expressions, and may have a much lower dimensionality. PCA is computationally simple and can be realized using many existing software packages. This article consists of the following parts. First, we review the standard PCA technique and their applications in bioinformatics data analysis. Second, we describe recent 'non-standard' applications of PCA, including accommodating interactions among genes, pathways and network modules and conducting PCA with estimating equations as opposed to gene expressions. Third, we introduce several recently proposed PCA-based techniques, including the supervised PCA, sparse PCA and functional PCA. The supervised PCA and sparse PCA have been shown to have better empirical performance than the standard PCA. The functional PCA can analyze time-course gene expression data. Last, we raise the awareness of several critical but unsolved problems related to PCA. The goal of this article is to make bioinformatics researchers aware of the PCA technique and more importantly its most recent development, so that this simple yet effective dimension reduction technique can be better employed in bioinformatics data analysis.     

Investigation of cell wall composition related to stem lodging resistance in wheat (Triticum aestivum L.) by FTIR spectroscopy

We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.     

Clinicodemographic aspect of resectable pancreatic cancer and prognostic factors for resectable cancer

ABSTRACT: BACKGROUND: Pancreatic adenocarcinoma (PCA) is one of the most lethal human malignancies, and radical surgery remains the cornerstone of treatment. After resection, the overall 5-year survival rate is only 10% to 29%. At the time of presentation, however, about 40% of patients generally have distant metastases and another 40% are usually diagnosed with locally advanced cancers. The remaining 20% of patients are indicated for surgery on the basis of the results of preoperative imaging studies; however, about half of these patients are found to be unsuitable for resection during surgical exploration. In the current study, we aimed to determine the clinicopathological characteristics that predict the resectability of PCA and to conduct a prognostic analysis of PCA after resection to identify favorable survival factors. METHODS: We retrospectively reviewed the medical files of 688 patients (422 men and 266 women) who had undergone surgery for histopathologically proven PCA in the Department of Surgery at Chang Gung Memorial Hospital in Taiwan from 1981 to 2006. We compared the clinical characteristics of patients who underwent resection and patients who did not undergo resection in order to identify the predictive factors for successful resectability of PCA, and we conducted prognostic analysis for PCA after resection. RESULTS: A carbohydrate antigen 19-9 (CA 19-9) level of 37 U/ml or greater and a tumor size of 3 cm or more independently predicted resectability of PCA. In terms of survival after resection, PCA patients with better nutritional status (measured as having an albumin level greater than 3.5 g/dl), radical resection, early tumor stage and better-differentiated tumors were associated with favorable survival. CONCLUSIONS: Besides traditional imaging studies, preoperative CA 19-9 levels and tumor size can also be used to determine the resectability of PCA. Better nutritional status, curative resection, early tumor stage and well-differentiated tumors predict the favorable prognosis of PCA patients after resection.     

Isolation of line 10 hepatoma-cell membrane by the water extraction method and immunochemical analysis

Water extraction method was applied to isolate the cell membrane from line 10 hepatoma cells and normal liver cells in strain 2 guinea pig. The materials isolated by this method were further analyzed by different immunochemical techniques including SDS-PAGE, crossed immunoelectrophoresis and crossed affino immunoelectrophoresis to demonstrate the major components and their antigenicities. Five major glycoproteins of apparent molecular weights of 44, 46, 62, 64, and 68 kDa were prominent in line 10 tumor cell materials, whereas one band of molecular weight of 82 kDa was prominent in the materials from normal liver cells. Also four minor components from line 10 tumor cells were found to be glycoprotein in nature.     

Association Test Based on SNP Set: Logistic Kernel Machine Based Test vs. Principal Component Analysis

GWAS has facilitated greatly the discovery of risk SNPs associated with complex diseases. Traditional methods analyze SNP individually and are limited by low power and reproducibility since correction for multiple comparisons is necessary. Several methods have been proposed based on grouping SNPs into SNP sets using biological knowledge and/or genomic features. In this article, we compare the linear kernel machine based test (LKM) and principal components analysis based approach (PCA) using simulated datasets under the scenarios of 0 to 3 causal SNPs, as well as simple and complex linkage disequilibrium (LD) structures of the simulated regions. Our simulation study demonstrates that both LKM and PCA can control the type I error at the significance level of 0.05. If the causal SNP is in strong LD with the genotyped SNPs, both the PCA with a small number of principal components (PCs) and the LKM with kernel of linear or identical-by-state function are valid tests. However, if the LD structure is complex, such as several LD blocks in the SNP set, or when the causal SNP is not in the LD block in which most of the genotyped SNPs reside, more PCs should be included to capture the information of the causal SNP. Simulation studies also demonstrate the ability of LKM and PCA to combine information from multiple causal SNPs and to provide increased power over individual SNP analysis. We also apply LKM and PCA to analyze two SNP sets extracted from an actual GWAS dataset on non-small cell lung cancer.     

Partial characterization of nervous system-specific cell surface antigen(s) NS-2.

Partial biochemical characterization of several neural tissue specific antigens isolated from a murine glioblastoma cell line was accomplished by means of radioiodination of intact cells followed by immunoprecipitation of the cell lysate with a rabbit serum specific for neural tissue antigens. Polyacrylamide gel electrophoresis of the immunoprecipitate in sodium dodecyl sulfate resolved the labeled antigens into several major components: two proteins (or glycoproteins) having apparent m.w.'s of 84,000 and 120,000 and lipid associated components which may be heterogeneous. The protein and lipid associated components apparently possess independent antigenicity because after chloroformmethanol extraction the protein components can be immunoprecipitated from the aqueous phase and the lipid associated component can be immunoprecipitated from the organic phase. Despite their independent antigenicity it is not known whether the components may be noncovalently associated on the cell surface. Although some of these antigens can be isolated from brain or glioma cells (a related tumor), non can be demonstrated in lymphoid tissues or C1300 neuroblastoma cells using identical methods. Therefore, these studies confirm our previous findings concerning the specificity of the anti-NS-2 antiserum by using cytotoxicity tests.     

A new method for detection of tumor driver‐dependent changes of protein sialylation in a colon cancer cell line reveals nectin‐3 as TGFBR2 target

Protein‐linked glycans play key roles in cell differentiation, cell–cell interactions, cell growth, adhesion and immune response. Aberrant glycosylation is a characteristic feature of tumor cells and is involved in tumor growth, escape from apoptosis, metastasis formation, and resistance to therapy. It can serve as cancer biomarker and treatment target. To enable comprehensive screening for the impact of tumor driving mutations in colorectal cancer cells we present a method for specific analysis of tumor driver‐induced glycome changes. The strategy is based on a combination of three technologies, that is recombinase‐mediated cassette exchange (RMCE), Click‐It chemistry and mass spectrometry. The new method is exemplified by the analysis of the impact of inactivating mutations of the TGF‐ß‐receptor type II (TGFBR2) on sialic acid incorporation into protein‐linked glycans of the colon cancer cell line HCT116. Overall, 70 proteins were found to show de novo sialic acid incorporation exclusively upon TGFBR2 expression whereas 7 proteins lost sialylation upon TGFBR2 reconstitution. Validation of detected candidate glycoproteins is demonstrated with the cell surface glycoprotein nectin‐3 known to be involved in metastasis, invasion and prognosis of various cancers. Altogether, our new approach can help to systematically puzzle out the influence of tumor‐specific mutations in a major signaling pathway, as exemplified by the TGFBR2 tumor suppressor, on the tumor glycome. It facilitates the identification of glycan‐based tumor markers that could be used for diagnostic and therapeutic applications. In principle the outlined strategy can be adapted to any cancer cell line, tumor driver mutation and several glycan‐building blocks.     

Study of tumor cell invasion by Fourier transform infrared microspectroscopy

Lung cancer is usually fatal once it becomes metastatic. However, in order to develop metastases, a tumor usually invades the basal membrane and enters the vascular or lymphatic system. In this study, a three-dimensional artificial membrane using collagen type I, one of the main components of basal membranes, was established in order to investigate tumor cell invasion. Lung cancer cell line CALU-1 was seeded on this artificial membrane and cell invasion was studied using the Fourier transform infrared (FTIR) imaging technique. This approach allowed identification of tumor cells invading the collagen type I membrane by means of their infrared spectra and images. The mapping images obtained with FTIR microspectroscopy were validated with standard histological section analysis. The FTIR image produced using a single wavenumber at 1080 cm(-1), corresponding to PO2- groups in DNA from cells, correlated well with the histological section, which clearly revealed a cell layer and invading cells within the membrane. Furthermore, the peaks corresponding to amide A, I, and II in the spectra of the invading cells shifted compared to the noninvading cells, which may relate to the changes in conformation and/or heterogeneity in the phenotype of the cells. The data presented in this study demonstrate that FTIR microspectroscopy can be a fast and reliable technique to assess tumor invasion in vitro.     

HuH-7 reference genome profile: complex karyotype composed of massive loss of heterozygosity

Human cell lines represent a valuable resource as in vitro experimental models. A hepatoma cell line, HuH-7 (JCRB0403), has been used extensively in various research fields and a number of studies using this line have been published continuously since it was established in 1982. However, an accurate genome profile, which can be served as a reliable reference, has not been available. In this study, we performed M-FISH, SNP microarray and amplicon sequencing to characterize the cell line. Single cell analysis of metaphases revealed a high level of heterogeneity with a mode of 60 chromosomes. Cytogenetic results demonstrated chromosome abnormalities involving every chromosome in addition to a massive loss of heterozygosity, which accounts for 55.3% of the genome, consistent with the homozygous variants seen in the sequence analysis. We provide empirical data that the HuH-7 cell line is composed of highly heterogeneous cell populations, suggesting that besides cell line authentication, the quality of cell lines needs to be taken into consideration in the future use of tumor cell lines.     

Suppression of Tumor Growth by Pleurotus ferulae Ethanol Extract through Induction of Cell Apoptosis,and Inhibition of Cell Proliferation and Migration

Cancer is the second leading cause of death worldwide. Edible medicinal mushrooms have been used in traditional medicine as regimes for cancer patients. Recently anti-cancer bioactive components from some mushrooms have been isolated and their anti-cancer effects have been tested. Pleurotus ferulae, a typical edible medicinal mushroom in Xinjiang China, has also been used to treat cancer patients in folk medicine. However, little studies have been reported on the anti-cancer components of Pleurotus ferulae. This study aims to extract bioactive components from Pleurotus ferulae and to investigate the anti-cancer effects of the extracts. We used ethanol to extract anti-cancer bioactive components enriched with terpenoids from Pleurotus ferulae. We tested the anti-tumour effects of ethanol extracts on the melanoma cell line B16F10, the human gastric cancer cell line BGC 823 and the immortalized human gastric epithelial mucosa cell line GES-1 in vitro and a murine melanoma model in vivo. Cell toxicity and cell proliferation were measured by MTT assays. Cell cycle progression, apoptosis, caspase 3 activity, mitochondrial membrane potential (MMP), migration and gene expression were studied in vitro. PFEC suppressed tumor cell growth, inhibited cell proliferation, arrested cells at G0/G1 phases and was not toxic to non-cancer cells. PFEC also induced cell apoptosis and necrosis, increased caspase 3 activity, reduced the MMP, prevented cell invasion and changed the expression of genes associated with apoptosis and the cell cycle. PFEC delayed tumor formation and reduced tumor growth in vivo. In conclusion, ethanol extracted components from Pleurotus ferulae exert anti-cancer effects through direct suppression of tumor cell growth and invasion, demonstrating its therapeutic potential in cancer treatment.