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PubMed2006

GARBAN II: an integrative framework for extracting biological information from proteomic and genomic data.

Genomic and proteomic analyses generate a massive amount of data that requires specific bioinformatic tools for its management and interpretation. GARBAN II, developed from the previous GARBAN platform, provides an integrated framework to simultaneously analyse and compare multiple datasets from DNA microarrays and proteomic studies. The general architecture, gene classification and comparison, and graphical representation have been redesigned to ensure a user-friendly feature and to improve the capabilities and efficiency of this system. Additionally, GARBAN II has been extended with new applications to display networks of coexpressed genes and to integrate access to BioRag and MotifScanner so as to facilitate the holistic analysis of users' data.

Animals↗
PubMed2005

Age-dependent variations of cell response to oxidative stress: proteomic approach to protein expression and phosphorylation.

We investigated the protein profiles of variously aged rat astrocytes in response to oxidative stress. After H2O2-exposure of cells at 100 microM for 30 min, the relative intensity of ten protein spots changed on two-dimensional (2-D) gels compared with control gels after silver staining. Matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) analysis after in-gel digestion revealed that six of these spots corresponded to three kinds of proteins, each of which was composed of a protein and its modified form with a different isoelectric point (pI). These three proteins were identified as peroxiredoxins (PRDXs) II and III, and calpactin I light chain (p11). H2O2-exposure increased the intensity of the spot with lower pI and simultaneously decreased that of the spot with higher pI for both PRDXs II and III. In addition, the expression of annexin VII, S-adenosyl-L-homocysteine hydrolase, elongation factor II fragment (EF-II), and adenosine deaminase was increased by H2O2-exposure in astrocytes from variously aged rats. Using the Pro-Q Diamond staining, heat shock protein 60 kDa (Hsp 60) and alpha-tubulin were observed to be phosphorylated upon H2O2-exposure. While phosphorylation of alpha-tubulin was correlated positively with age, the changes in abundance of ten protein spots as described above were independent of age. These results suggest that aging does not suppress the responses aimed at limiting injury and promoting repair brought about by severe oxidative stress, and might affect cell dynamics including the formation of microtubules.

Animals↗
PubMed2003

New cancer biomarkers deriving from NCI early detection research.

Cancer is not a single disease but an accumulation of several events, genetic and epigenetic, arising in a single cell over a long time interval. A high priority in the cancer field is to identify these events. This can be achieved by characterizing cancer-associated genes and their protein products. Identifying the molecular alterations that distinguish any particular cancer cell from a normal cell will ultimately help to define the nature and predict the pathologic behavior of that cancer cell. It will also indicate the responsiveness to treatment of that particular tumor. Understanding the profile of molecular changes in any particular cancer will be extremely useful as it will become possible to correlate the resulting phenotype of that cancer with molecular events. Achieving these goals and knowledge will provide an opportunity for discovering new biomarkers for early cancer detection and developing prevention approaches. This will also help us identify new targets for therapeutic development. Advancement in technology includes methods and tools that enable research including, but not limited to, instrumentation, techniques, devices, and analysis tools (e.g., computer software). Resources such as databases, reagents, and tissue repositories are different than technologies. The identification and definition of the molecular profiles of cancer will require the development and dissemination of high-throughput molecular analysis technologies, as well as elucidation of all of the molecular species embedded in the genome of cancer and normal cells. The main challenge in cancer control and prevention is to detect the cancer early. This could then enable effective interventions and therapies contributing to reduction in mortality and morbidity. At a specific time, biomarkers serve as molecular signposts of the physiologic state of a cell. These signposts are the result of genes, their products (proteins) and other organic chemicals made by the cell. Biomarkers could prove to be vital for the identification of early cancer and subjects at risk of developing cancer as a normal cell progresses through the complex process of transformation to a cancerous state. This chapter discusses ongoing research in genetic and proteomic approaches to identify molecular signatures such as protein profiles, microsatellite instability, hypermethylation, and single nucleotide polymorphisms. Other topics covered here include the use of genomics and proteomics as high-throughput technology platforms to facilitate biomarker-aided detection of early cancer. Other areas covered include issues surrounding the analysis, validation, and predictive value of biomarkers using such technologies. Recent advances in noninvasive techniques, such as buccal cell isolates serving as viable sources of biomarkers, complementary to traditional sources such as serum or plasma, are also presented. The review also brings attention to the efforts of the Early Detection Research Network (EDRN) at the National Cancer Institute (NCI), in bringing together scientific expertise from leading national and international institutions, to identify and validate biomarkers for the detection of precancerous and cancerous cells in determining risk for developing cancer. The network's serious determined efforts in linking discovery to process development, resulting in early detection tests and clinical assessment, are also discussed.

Biomarkers, Tumor↗
PubMed2003

A proteome study of secreted prostatic factors affecting osteoblastic activity: identification and characterisation of cyclophilin A.

Prostate cancer cells metastasise to bone causing a predominantly osteosclerotic response. It has previously been shown that PC3 cells secrete factors which stimulate the mitogenic activity of human bone marrow stromal (hBMS) cells. Some of these mitogens have been found to be proteins with a molecular weight between 20 and 30 kDa. Even though a number of investigations have been performed to identify the osteoblastic mitogenic factor or factors produced by prostate cancer cells, it is still unknown what causes the mitogenic activation of osteoblasts. Therefore, the aim of this study was to characterise the protein profile of conditioned medium (CM) from PC3 cells in the molecular weight range of 5-30 kDa using proteome analysis. A protein profile of the CM from PC3 cells was performed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Thirty protein spots with molecular weights ranging from 5 to 30 kDa were analysed by matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF MS). One of these spots was identified as cyclophilin A. We examined whether cyclophilin A alone or in combination with insulin-like growth factor-I (IGF-I) had any effects on the proliferation or differentiation of hBMS cells. Cyclophilin A at 1, 10, and 100 nM and cyclophilin A at 10 nM combined with 10 ng/ml IGF decreased the proliferation of hBMS cells up to 49+/-30, 38+/-29, 50+/-8 and 60+/-16%, respectively [mean (treated/control)+/-standard error of the means (SEM)] of control. IGF-I did not significantly affect these decreases. Cyclophilin A alone or in combination with IGF-I did not have any effect on differentiation (assessed by measuring the activity of alkaline phosphatase (ALP)). In conclusion, these results suggest cyclophilin A is not involved in the osteosclerotic effects seen when prostate cancer metastasises to bone.

Adult↗
PubMed2026

Integrative proteomics reveals MSH6 to modulate PARP inhibitor sensitivity in BRCA1/2-proficient ovarian cancer.

Ovarian cancer remains a leading cause of gynecologic cancer-related deaths worldwide. Deficiencies in BRCA1/2 are well-established biomarkers that predict sensitivity to poly(ADP-ribose) polymerase inhibitors (PARPis). However, emerging evidence indicates that a subset of BRCA-proficient tumors also responds to PARPi therapy, suggesting the presence of additional molecular mechanisms. We hypothesized that the composition of the PARP1 protein complex and PARylation-mediated signaling contribute to PARPi response in BRCA-proficient HGSOC. We assessed PARPi response across a panel of BRCA-proficient ovarian cancer cell lines and identified distinct sensitive and resistant groups. Chemical proteomics with rucaparib revealed different PARP1 complexes including higher enrichment of MSH6 in sensitive cells. Co-immunoprecipitation analyses further confirmed differential assembly of PARP1-MSH6-PARP2 complexes between sensitive and resistant models. To explore PARylation signaling, we performed ADP-ribosylation proteomics using clickable NAD⁺ analogs, revealing distinct PARylation profiles between sensitive and resistant cell lines. CHAF1A, a known MSH6 interactor and PARP1 substrate, showed more pronounced reduction in ADP-ribosylation in PARPi-sensitive cells. Targeting MSH6 using CRISPR or siRNA decreased PARPi sensitivity. In addition, mTOR signaling was reduced in sensitive, but increased in resistant cells, following rucaparib treatment. Notably, MSH6 knockdown led to increased CHAF1A expression regardless of rucaparib treatment. Importantly, knockdown of CHAF1A significantly impaired cell viability, especially in A2780 cells, and suppressed mTOR signaling, suggesting that CHAF1A acts downstream of MSH6 to regulate the mTOR axis. Furthermore, co-treatment with mTORC1 inhibitors enhanced the cellular effects of rucaparib in resistant cells, suggesting a therapeutic potential of targeting downstream mTOR effectors to overcome intrinsic resistance. In conclusion, this study identifies the PARP1-MSH6 interaction to modulate PARPi sensitivity via CHAF1A-mTOR signaling in BRCA-proficient ovarian cancer. By integrating chemical proteomics and ADP-ribosylation proteomics, we delineate the interplay between PARP1 complex composition and signaling dynamics, highlighting MSH6 as a critical modulator of PARPi response and potential biomarker to enhance therapeutic efficacy in BRCA-proficient HGSOC.

Humans↗
PubMed2004

Use of proteomic analysis to monitor responses to biological therapies.

Proteomics has the potential to revolutionise diagnosis and disease management. Serum protein pattern profiling by surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF) mass spectrometry is emerging as a novel approach to discover protein patterns capable of distinguishing disease and disease-free states with high sensitivity and specificity. This method has shown great promise for early diagnosis of ovarian cancer and is being applied to a range of pathological states. Protein microarray technology is being evaluated as a new means to track biological responses to therapy. Through the measurement of key protein phosphorylation sites at different stages of disease progression or before and after treatment, protein signal pathways can be mapped and thus become the starting point for individualised therapy. Laser capture microdissection (LCM) coupled with immunostaining of protein microarrays allows isolation of pure cell populations and relative quantitation of phosphorylated and non-phosphorylated forms of the cell's key signalling proteins. This technology is currently in use at the National Institutes of Health in Phase II clinical trials of metastatic breast and ovarian cancer. Cell survival and apoptotic protein pathways are monitored as biological markers of disease progression in these clinical trials. Proteomic technologies, such as serum protein pattern profiling, combined with protein microarray technologies, constitute a new paradigm for detecting disease and monitoring disease response to therapy. Ultimately, proteomics and genomics will become integrated into cancer patient management through the design and tracking of individualised therapy.

Animals↗
PubMed2006

Protein profiling of sickle cell versus control RBC core membrane skeletons by ICAT technology and tandem mass spectrometry.

A proteomic approach using a cleavable ICAT reagent and nano-LC ESI tandem mass spectrometry was used to perform protein profiling of core RBC membrane skeleton proteins between sickle cell patients (SS) and controls (AA), and determine the efficacy of this technology. The data was validated through Peptide/Protein Prophet and protein ratios were calculated through ASAPratio. Through an ANOVA test, it was determined that there is no significant difference in the mean ratios from control populations (AA1/AA2) and sickle cell versus control populations (AA/SS). The mean ratios were not significantly different from 1.0 in either comparison for the core skeleton proteins (alpha spectrin, beta spectrin, band 4.1 and actin). On the natural-log scale, the variation (standard deviation) of the method was determined to be 14.1% and the variation contributed by the samples was 13.8% which together give a total variation of 19.7% in the ratios.

Anemia, Sickle Cell↗
PubMed2026

Photocatalytic Golgi Proteomics Reveals Palmitoylation-Regulated Golgiphagy.

The Golgi apparatus (GA) orchestrates protein modification, trafficking, and secretion through highly dynamic remodeling, yet its proteomic complexity remains difficult to resolve in living systems. Here, we report CAT-Golgi, a genetically independent and light-controlled photocatalytic proximity labeling strategy for in situ spatiotemporal mapping of the Golgi-associated proteome. Combining a cysteine-conjugated eosin photocatalyst (GolgiCat) with an aniline probe, CAT-Golgi enables rapid and precise protein labeling within minutes under mild green light, requiring no genetic manipulation and operating efficiently in hard-to-transfect and primary cells. Leveraging our extensive efforts in organelle-targeted photocatalytic systems, we extended this chemistry to the highly dynamic and reversible Golgi apparatus. CAT-Golgi achieved quantitative and comparative proteomics in HeLa, K562, Jurkat and primary HEKa cells, revealing both conserved and cell-type-specific profiles. Under Brefeldin A-induced Golgiphagy, CAT-Golgi captured large-scale proteome remodeling and identified palmitoyl-protein thioesterase 1 (PPT1) as a potential regulatory component. PPT1 downregulation enhanced ULK1 and TRPML1 palmitoylation, disrupted redox balance, and activated Golgiphagy. CAT-Golgi provides a broadly applicable chemical platform for decoding organelle dynamics, offering both conceptual and technical foundations for extending photocatalytic proteomics to other transient organelles and illuminating molecular mechanisms of organelle plasticity and disease progression.

Golgi Apparatus↗
PubMed2002

De novo peptide sequencing and quantitative profiling of complex protein mixtures using mass-coded abundance tagging.

Proteomic studies require efficient, robust, and practical methods of characterizing proteins present in biological samples. Here we describe an integrated strategy for systematic proteome analysis based on differential guanidination of C-terminal lysine residues on tryptic peptides followed by capillary liquid chromatography-electrospray tandem mass spectrometry. The approach, termed mass-coded abundance tagging (MCAT), facilitates the automated, large-scale, and comprehensive de novo determination of peptide sequence and relative quantitation of proteins in biological samples in a single analysis. MCAT offers marked advantages as compared with previously described methods and is simple, economic, and effective when applied to complex proteomic mixtures. MCAT is used to identify proteins, including polymorphic variants, from complex mixtures and measure variation in protein levels from diverse cell types.

Algorithms↗
PubMed2004

Construction of representative transcript and protein sets of human, mouse, and rat as a platform for their transcriptome and proteome analysis.

The number of mammalian transcripts identified by full-length cDNA projects and genome sequencing projects is increasing remarkably. Clustering them into a strictly nonredundant and comprehensive set provides a platform for functional analysis of the transcriptome and proteome, but the quality of the clustering and predictive usefulness have previously required manual curation to identify truncated transcripts and inappropriate clustering of closely related sequences. A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2). Here we propose an alternative method that is more robust, requires less manual curation, and is applicable to other organisms in addition to mouse. RTPSs of human, mouse, and rat have been produced by this method and used for validation. Their comprehensiveness and quality are discussed by comparison with other clustering approaches. The RTPSs are available at .

Animals↗
PubMed2004

Pharmacoproteomic approach to the study of drug mode of action, toxicity, and resistance: applications in diabetes and cancer.

Proteomics is a powerful technique for investigating protein expression profiles in biological systems and their modifications in response to stimuli or to particular physiological or pathophysiological conditions. It is therefore a technique of choice for the study of drug mode of action, side-effects, toxicity and resistance. It is also a valuable approach for the discovery of new drug targets. All these proteomic applications to pharmacological issues may be called pharmacoproteomics. The pharmacoproteomic approach could be particularly useful for the identification of molecular alterations implicated in type 2 diabetes and for further characterization of existing or new drugs. In oncology, proteomics is widely used for the identification of tumour-specific protein markers, and pharmacoproteomics is used for the evaluation of chemotherapy, particularly for the characterization of drug-resistance mechanisms. The large amount of data generated by pharmacoproteomic screening requires the use of bioinformatic tools to insure a pertinent interpretation. Herein, we review the applications of pharmacoproteomics to the study of type 2 diabetes and to chemoresistance in different types of cancer and the current state of this technology in these pathologies. We also suggest a number of bioinformatic solutions for proteomic data management.

Animals↗
PubMed2003

PROCEED: A proteomic method for analysing plasma membrane proteins in living mammalian cells.

Elucidating the profile of extracellular integral membrane proteins on live cells is vital for uncovering diagnostic disease biomarkers, therapeutic agents and drug receptor candidates. Exploring the realm of these proteins has proved to be an intricate task, mainly due to their hydrophobic nature and low abundance. Furthermore, the level of purity achieved by classical methods of purification and cell fractionation is insufficient. These restrictions pose major limitations for gel electrophoresis or chromatography-based separation techniques as the preferred methodologies for high-throughput analysis. Mass spectrometry has alleviated most of the difficulties in the identification of proteins in general; however, the Achilles' heel is still the isolation and separation of membrane proteins. In order to circumvent these limitations, a high-throughput platform has been devised, whereby proteases are applied to whole intact living cells. The resulting peptide fragments are then analysed by liquid chromatology followed by tandem MS (LC-MS/MS) technology to provide a detailed profile of proteins exposed on the surface of the plasma membrane. This kind of protein trimming offers the advantages that no prior manipulation or fractionation of the cell is required, contaminating proteins are remarkably reduced and the procedure is adequate for high-throughput purposes. This method, referred to as PROCEED (PROteome of Cell Exposed Extracellular Domains) is compatible with isotope labelling techniques which facilitate comparative protein expression studies. The methodology is extendable to all cell types including yeast and bacteria. Finally, the advantages and the limitations of PROCEED are discussed in view of other current technologies.

Animals↗
PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗
PubMed2024

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Journal Article↗
PubMed2026

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25 years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine↗
PubMed2003

Proteomic sensitivity to dietary manipulations in rainbow trout.

Changes in dietary protein sources due to substitution of fish meal by other protein sources can have metabolic consequences in farmed fish. A proteomics approach was used to study the protein profiles of livers of rainbow trout that have been fed two diets containing different proportions of plant ingredients. Both diets control (C) and soy (S) contained fish meal and plant ingredients and synthetic amino acids, but diet S had a greater proportion of soybean meal. A feeding trial was performed for 12 weeks at the end of which, growth and protein metabolism parameters were measured. Protein growth rates were not different in fish fed different diets; however, protein consumption and protein synthesis rates were higher in the fish fed the diet S. Fish fed diet S had lower efficiency of retention of synthesised protein. Ammonia excretion was increased as well as the activities of hepatic glutamate dehydrogenase and aspartate amino transferase (ASAT). No differences were found in free amino acid pools in either liver or muscle between diets. Protein extraction followed by high-resolution two-dimensional electrophoresis, coupled with gel image analysis, allowed identification and expression of hundreds of protein. Individual proteins of interest were then subjected to further analysis leading to protein identification by trypsin digest fingerprinting. During this study, approximately 800 liver proteins were analysed for expression pattern, of which 33 were found to be differentially expressed between diets C and S. Seventeen proteins were positively identified after database searching. Proteins were identified from diverse metabolic pathways, demonstrating the complex nature of gene expression responses to dietary manipulation revealed by proteomic characterisation.

Amino Acids↗
PubMed2003

A proteome study of secreted prostatic factors affecting osteoblastic activity: galectin-1 is involved in differentiation of human bone marrow stromal cells.

Prostate cancer cells metastasize to bone causing a predominantly osteosclerotic response. It has been shown that cells from the human prostate cancer cell line PC3 secrete factors that influence the behavior of osteoblast-like cells. Some of these factors with mitogenic activity have been found to be proteins with molecular weights between 20 and 30 kDa, but the identity of the osteoblastic mitogenic factor or factors produced by prostate cancer cells is still unknown. Therefore, the aim of this study was to characterize the protein profile of conditioned medium (CM) from PC3 cells in the molecular weight range from 5 to 30 kDa using proteome analysis. A protein profile of the CM from PC3 cells was performed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Thirty protein spots with molecular weights ranging from 5 to 30 kDa were analyzed by matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). One of these spots was identified as galectin-1. We examined whether PC3 CM, recombinant galectin-1 alone, or combined with insulin-like growth factor-I (IGF-I) had any effects on the proliferation or differentiation of human bone marrow stromal (hBMS) cells. Furthermore, we tested whether adhesion of PC3 cells to plastic, laminin, fibronectin, and collagen type I was influenced by lactose, which inhibits galectin-1. Galectin-1 (1000 ng/ml) inhibited the proliferation of hBMS cells up to 70 +/- 12% (treated/control) of control in contrast to PC3 CM, which induced hBMS cell proliferation by 3-fold. This effect was abolished by IGF-I. PC3 CM and galectin-1 in concentrations of 10 and 1000 ng/ml increased the alkaline phosphatase (ALP) activity of hBMS cells up to 175 +/- 27%, 137 +/- 8%, and 131 +/- 11%, respectively, compared with ALP activity of untreated cells, and inhibited the secretion of osteocalcin (OC) up to 81 +/- 3%, 93 +/- 1%, and 58 +/- 2%, respectively, compared with OC secretion of untreated cells. These effects were affected by IGF-I. Lactose inhibited adhesion of PC3 cells to plastic, fibronectin, laminin, and collagen type I up to 58 +/- 4%, 30 +/- 12, 72 +/- 9%, and 86 +/- 4%. In conclusion, galectin-1 modulated osteoblastic proliferation and differentiation. These effects were affected by IGF-I. Thus, galectin-1 is likely be involved in the osteoblastic response, caused by prostate cancer cells metastasizing into bone, by affecting the matrix mineralization.

Bone Marrow Cells↗