Urinary proteomics reveals biological processes related to acute kidney injury in Bothrops atrox envenomings.

Acute kidney injury (AKI) is a critical systemic complication caused by Bothrops envenoming, a neglected health problem in the Brazilian Amazon. Understanding the underlying mechanisms leading to AKI is crucial for effectively mitigating the burden of this complication. This study aimed to characterize the urinary protein profile of Bothrops atrox snakebite victims who developed AKI. We analyzed three groups of samples collected on admission: healthy subjects (controls, n = 10), snakebite victims who developed AKI (AKI, n = 10), and those who did not evolve to AKI (No-AKI, n = 10). Using liquid-chromatography tandem mass spectrometry, we identified and quantified (label-free) 1190 proteins. A panel of 65 proteins was identified exclusively in the urine of snakebite victims, with 32 exclusives to the AKI condition. Proteins more abundant or exclusive in AKI's urine were associated with acute phase response, endopeptidase inhibition, complement cascade, and inflammation. Notable proteins include serotransferrin, SERPINA-1, alpha-1B-glycoprotein, and NHL repeat-containing protein 3. Furthermore, evaluating previously reported biomarkers candidates for AKI and renal injury, we found retinol-binding protein, beta-2-microglobulin, cystatin-C, and hepcidin to be significant in cases of AKI induced by Bothrops envenoming. This work sheds light on physiological disturbances caused by Bothrops envenoming, highlighting potential biological processes contributing to AKI. Such insights may aid in better understanding and managing this life-threatening complication.

Proteogenomics Reveals Orthologous Alternatively Spliced Proteoforms in the Same Human and Mouse Brain Regions with Differential Abundance in an Alzheimer's Disease Mouse Model.

Alternative splicing (AS) may increase the number of proteoforms produced by a gene. Alzheimer's disease (AD) is a neurodegenerative disease with well-characterized AS proteoforms. In this study, we used a proteogenomics strategy to build a customized protein sequence database and identify orthologous AS proteoforms between humans and mice on publicly available shotgun proteomics (MS/MS) data of the corpus callosum (CC) and olfactory bulb (OB). Identical proteotypic peptides of six orthologous AS proteoforms were found in both species: PKM1 (gene PKM/Pkm), STXBP1a (gene STXBP1/Stxbp1), Isoform 3 (gene HNRNPK/Hnrnpk), LCRMP-1 (gene CRMP1/Crmp1), SP3 (gene CADM1/Cadm1), and PKCßII (gene PRKCB/Prkcb). These AS variants were also detected at the transcript level by publicly available RNA-Seq data and experimentally validated by RT-qPCR. Additionally, PKM1 and STXBP1a were detected at higher abundances in a publicly available MS/MS dataset of the AD mouse model APP/PS1 than its wild type. These data corroborate other reports, which suggest that PKM1 and STXBP1a AS proteoforms might play a role in amyloid-like aggregate formation. To the best of our knowledge, this report is the first to describe PKM1 and STXBP1a overexpression in the OB of an AD mouse model. We hope that our strategy may be of use in future human neurodegenerative studies using mouse models.

Cross-linking mass spectrometry reveals structural insights of the glutamine synthetase from Leishmania braziliensis

BACKGROUND Leishmaniasis is a neglected tropical disease caused by the parasite Leishmania braziliensis, commonly found in Brazil and associated with cutaneous and visceral forms of this disease. Like other organisms, L. braziliensis has an enzyme called glutamine synthetase (LbGS) that acts on the synthesis of glutamine from glutamate. This enzyme plays an essential role in the metabolism of these parasites and can be a potential therapeutic target for treating this disease. OBJECTIVES Investigate LbGS structure and generate structural models of the protein. METHODS We use the method of crosslinking mass spectrometry (XLMS) and generate structural models in silico using I-TASSER. FINDINGS 42 XLs peptides were identified, of which 37 are explained in a monomeric model with the other five indicating LbGS dimerization and pentamers interaction region. The comparison of 3D models generated in the presence and absence of XLMS restrictions probed the benefits of modeling with XLMS highlighting the inappropriate folding due to the absence of spatial restrictions. MAIN CONCLUSIONS In conclusion, we disclose the conservation of the active site and interface regions, but also unique features of LbGS showing the potential of XLMS to probe structural information and explore new drugs.

Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow.

BACKGROUND: Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that produce the nipple aspirate fluid (NAF). In cancer patients, this secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging because of inter-individual variability. We introduced a paired-proteomic shotgun strategy that relies on NAF analysis from both breasts of patients with unilateral breast cancer and extended PatternLab for Proteomics software to take advantage of this setup. METHODS: The software is based on a peptide-centric approach and uses the binomial distribution to attribute a probability for each peptide as being linked to the disease; these probabilities are propagated to a final protein p-value according to the Stouffer's Z-score method. RESULTS: A total of 1227 proteins were identified and quantified, of which 87 were differentially abundant, being mainly involved in glycolysis (Warburg effect) and immune system activation (activated stroma). Additionally, in the estrogen receptor-positive subgroup, proteins related to the regulation of insulin-like growth factor transport and platelet degranulation displayed higher abundance, confirming the presence of a proliferative microenvironment. CONCLUSIONS: We debuted a differential bioinformatics workflow for the proteomic analysis of NAF, validating this secretome as a treasure-trove for studying a paired-organ cancer type.

Comprehensive identification of protein disulfide bonds with pepsin/trypsin digestion, Orbitrap HCD and Spectrum Identification Machine.

Disulfide bonds (SS) are post-translational modifications important for the proper folding and stabilization of many cellular proteins with therapeutic uses, including antibodies and other biologics. With budding advances of biologics and biosimilars, there is a mounting need for a robust method for accurate identification of SS. Even though several mass spectrometry methods have emerged for this task, their practical use rests on the broad effectiveness of both sample preparation methods and bioinformatics tools. Here we present a new protocol tailored toward mapping SS; it uses readily available reagents, instruments, and software. For sample preparation, a 4-h pepsin digestion at pH 1.3 followed by an overnight trypsin digestion at pH 6.5 can maximize the release of SS-containing peptides from non-reduced proteins, while minimizing SS scrambling. For LC/MS/MS analysis, SS-containing peptides can be efficiently fragmented with HCD in a Q Exactive Orbitrap mass spectrometer, preserving SS for subsequent identification. Our bioinformatics protocol describes how we tailored our freely downloadable and easy-to-use software, Spectrum Identification Machine for Cross-Linked Peptides (SIM-XL), to minimize false identification and facilitate manual validation of SS-peptide mass spectra. To substantiate this optimized method, we've comprehensively identified 14 out of 17 known SS in BSA. SIGNIFICANCE: Comprehensive and accurate identification of SS in proteins is critical for elucidating protein structures and functions. Yet, it is far from routine to accomplish this task in many analytical or core laboratories. Numerous published methods require complex sample preparation methods, specialized mass spectrometers and cumbersome or proprietary software tools, thus cannot be easily implemented in unspecialized laboratories. Here, we describe a robust and rapid SS mapping approach that utilizes readily available reagents, instruments, and software; it can be easily implemented in any analytical core laboratories, and tested for its impact on the research community.

Comparing intestinal versus diffuse gastric cancer using a PEFF-oriented proteomic pipeline.

Gastric cancer is the fifth most common malignant neoplasia and the third leading cause of cancer death worldwide. Mac-Cormick et al. recently showed the importance of considering the anatomical region of the tumor in proteomic gastric cancer studies; more differences were found between distinct anatomical regions than when comparing healthy versus diseased tissue. Thus, failing to consider the anatomical region could lead to differential proteins that are not disease specific. With this as motivation, we compared the proteomic profiles of intestinal and diffuse adenocarcinoma from the same anatomical region, the corpus. To achieve this, we used isobaric labeling (iTRAQ) of peptides, a 10-step HILIC fractionation, and reversed-phase nano-chromatography coupled online with a Q-Exactive Plus mass spectrometer. We updated PatternLab to take advantage of the new Comet-PEFF search engine that enables identifying post-translational modifications and mutations included in neXtProt's PSI Extended FASTA Format (PEFF) metadata. Our pipeline then uses a text-mining tool that automatically extracts PubMed IDs from the proteomic result metadata and drills down keywords from manuscripts related with the biological processes at hand. Our results disclose important proteins such as apolipoprotein B-100, S100 and 14-3-3 proteins, among many others, highlighting the different pathways enriched by each cancer type. SIGNIFICANCE: Gastric cancer is a heterogeneous and multifactorial disease responsible for a significant number of deaths every year. Despite the constant improvement of surgical techniques and multimodal treatments, survival rates are low, mostly due to limited diagnostic techniques and late symptoms. Intestinal and diffuse types of gastric cancer have distinct clinical and pathological characteristics; yet little is known about the molecular mechanisms regulating these two types of gastric tumors. Here we compared the proteomic profile of diffuse and intestinal types of gastric cancer from the same anatomical location, the corpus, from four male patients. This methodological design aimed to eliminate proteomic variations resulting from comparison of tumors from distinct anatomical regions. Our PEFF-tailored proteomic pipeline significantly increased the identifications as when compared to previous versions of PatternLab.

Considerations about gastric cancer proteomics.

The frequency of molecular studies aimed to analyze promoter methylation of tumor suppressor genes and global proteomics in gastric carcinogenesis is increasing. Nonetheless, only a few considered the different types of stomach cells, the tumor location and the influence of Helicobacter pylori and Epstein Barr virus infection (EBV). Molecular differences relating to anatomical and histological tumor areas were also recently described. The authors propose a molecular classification of gastric cancer, dividing it into four subtypes: tumors positive for EBV; microsatellite unstable tumors; genomically stable tumors and tumors with chromosomal instability. RESUMO A frequência de estudos moleculares visando a analisar os promotores de metilação de genes supressores de tumor e proteômica globais na carcinogênese gástrica está aumentando. No entanto, apenas alguns consideraram os diferentes tipos de células do estômago, a localização do tumor e a influência da infecção por Helicobacter pylori e pelo vírus Epstein-Barr (EBV). Diferenças moleculares relacionadas com áreas tumorais anatômicas e histológicas também foram recentemente descritas. Os autores propõem uma classificação molecular de câncer gástrico, dividindo-o em quatro subtipos: tumores positivos para o EBV; tumores microssatélite instáveis; tumores genomicamente estáveis ​​e tumores com instabilidade cromossômica.

A Time-Based and Intratumoral Proteomic Assessment of a Recurrent Glioblastoma Multiforme.

Tumors consist of cells in different stages of transformation with molecular and cellular heterogeneity. By far, heterogeneity is the hallmark of glioblastoma multiforme (GBM), the most malignant and aggressive type of glioma. Most proteomic studies aim in comparing tumors from different patients, but here we dive into exploring the intratumoral proteome diversity of a single GBM. For this, we profiled tumor fragments from the profound region of the same patient's GBM but obtained from two surgeries a year's time apart. Our analysis also included GBM's fragments from different anatomical regions. Our quantitative proteomic strategy employed 4-plex iTRAQ peptide labeling followed by a four-step strong cation chromatographic separation; each fraction was then analyzed by reversed-phase nano-chromatography coupled on-line with an Orbitrap-Velos mass spectrometer. Unsupervised clustering grouped the proteomic profiles into four major distinct groups and showed that most changes were related to the tumor's anatomical region. Nevertheless, we report differentially abundant proteins from GBM's fragments of the same region but obtained 1 year apart. We discuss several key proteins (e.g., S100A9) and enriched pathways linked with GBM such as the Ras pathway, RHO GTPases activate PKNs, and those related to apoptosis, to name a few. As far as we know, this is the only report that compares GBM fragments proteomic profiles from the same patient. Ultimately, our results fuel the forefront of scientific discussion on the importance in exploring the richness of subproteomes within a single tissue sample for a better understanding of the disease, as each tumor is unique.

Colorectal cancer DNA methylation patterns from patients in Manaus, Brazil.

BACKGROUND: DNA methylation is commonly linked with the silencing of the gene expression for many tumor suppressor genes. As such, determining DNA methylation patterns should aid, in times to come, in the diagnosis and personal treatment for various types of cancers. Here, we analyzed the methylation pattern from five colorectal cancer patients from the Amazon state in Brazil for four tumor suppressor genes, viz.: DAPK, CDH1, CDKN2A, and TIMP2 by employing a polymerase chain reaction (PCR) specific to methylation. Efforts in the study of colorectal cancer are fundamental as it is the third most of highest incidence in the world. RESULTS: Tumor biopsies were methylated in 1/5 (20%), 2/5 (40%), 4/5 (80%), and 4/5 (80%) for CDH1, CDKN2A, DAPK, and TIMP2 genes, respectively. The margin biopsies were methylated in 3/7 (43%), 2/7 (28%), 7/7 (100%), and 6/7 (86%) for CDH1, CDKN2A, DAPK, and TIMP2, respectively. CONCLUSIONS: Our findings showed DAPK and TIMP2 to be methylated in most samples from both tumor tissues and adjacent non-neoplastic margins; thus presenting distinct methylation patterns. This emphasizes the importance of better understanding of the relation of these patterns with cancer in the context of different populations.

Using PepExplorer to Filter and Organize De Novo Peptide Sequencing Results.

PepExplorer aids in the biological interpretation of de novo sequencing results; this is accomplished by assembling a list of homolog proteins obtained by aligning results from widely adopted de novo sequencing tools against a target-decoy sequence database. Our tool relies on pattern recognition to ensure that the results satisfy a user-given false-discovery rate (FDR). For this, it employs a radial basis function neural network that considers the precursor charge states, de novo sequencing scores, the peptide lengths, and alignment scores. PepExplorer is recommended for studies addressing organisms with no genomic sequence available. PepExplorer is integrated into the PatternLab for proteomics environment, which makes available various tools for downstream data analysis, including the resources for quantitative and differential proteomics.

Proteomic profiling of nipple aspirate fluid (NAF): Exploring the complementarity of different peptide fractionation strategies.

NAF is a breast fluid that is closely related to the tumor microenvironment and a valuable sample for studying breast cancer. To perform an in-depth proteomic analysis of this sample, aliquots of a single NAF digest were analyzed by the following peptide-centric fractionation strategies: a) 30-cm reversed-phase (RP) column on-line with an LTQ-Orbitrap XL; b) off-line strong cation-exchange (SCX) column; and c) pI-based OFFGEL fractionation. All fractions from approaches (b) and (c) were further analyzed on a 10-cm RP column hyphenated to the same mass spectrometer. The RP-30cm, SCX/RP-10cm, and OFFGEL/RP-10cm approaches identified 1676, 2930, and 3240 peptides, which corresponded to 193, 390 and 528 proteins, respectively. In our cumulative dataset, 4466 distinct NAF peptides corresponded to a total of 557 proteins, of which only 34% were identified by all three approaches. No exclusive protein identification was associated to the RP-30cm approach, while SCX/RP-10cm and OFFGEL/RP-10cm contributed to 28 and 166 exclusive identifications, respectively. Each approach provided additional information related to energy metabolism (fermentation process/carbohydrate biosynthesis). In conclusion, the pre-fractionation platforms used were complementary for the comprehensive characterization of NAF and our work provides methodological information for future quantitative cancer-related NAF sample studies. BIOLOGICAL SIGNIFICANCE: High-resolution peptide separation is a sine qua non condition for achieving extensive proteome coverage. Various techniques have been employed to improve peptide fractionation prior to LC-MS/MS, thus allowing a comprehensive characterization of complex biological samples. Although fractionation efficiency is very sample-dependent, this issue is commonly overlooked, and a "cookbook" approach is routinely used during this critical step. The present study provides a systematic comparison of analytical information needed for the successful large-scale differential proteomic analysis of NAF samples from breast cancer patients, a precious and volume-limited biological sample. It reinforces the importance of optimizing sample-specific fractionation protocols for information retrieval from mass spectrometric analysis.

Colorectal cancer DNA methylation patterns from patients in Manaus, Brazil

BACKGROUND: DNA methylation is commonly linked with the silencing of the gene expression for many tumor suppressor genes. As such, determining DNA methylation patterns should aid, in times to come, in the diagnosis and personal treatment for various types of cancers. Here, we analyzed the methylation pattern from five colorectal cancer patients from the Amazon state in Brazil for four tumor suppressor genes, viz.: DAPK, CDH1, CDKN2A, and TIMP2 by employing a polymerase chain reaction (PCR) specific to methylation. Efforts in the study of colorectal cancer are fundamental as it is the third most of highest incidence in the world. RESULTS: Tumor biopsies were methylated in 1/5 (20 %), 2/5 (40 %), 4/5 (80 %), and 4/5 (80 %) for CDH1, CDKN2A, DAPK, and TIMP2 genes, respectively. The margin biopsies were methylated in 3/7 (43 %), 2/7 (28 %), 7/7 (100 %), and 6/7 (86 %) for CDH1, CDKN2A, DAPK, and TIMP2, respectively. CONCLUSIONS: Our findings showed DAPK and TIMP2 to be methylated in most samples from both tumor tissues and adjacent non-neoplastic margins; thus presenting distinct methylation patterns. This emphasizes the importance of better understanding of the relation of these patterns with cancer in the context of different populations.

HI-bone: a scoring system for identifying phenylisothiocyanate-derivatized peptides based on precursor mass and high intensity fragment ions.

Peptide sequence matching algorithms used for peptide identification by tandem mass spectrometry (MS/MS) enumerate theoretical peptides from the database, predict their fragment ions, and match them to the experimental MS/MS spectra. Here, we present an approach for scoring MS/MS identifications based on the high mass accuracy matching of precursor ions, the identification of a high intensity b1 fragment ion, and partial sequence tags from phenylthiocarbamoyl-derivatized peptides. This derivatization process boosts the b1 fragment ion signal, which turns it into a powerful feature for peptide identification. We demonstrate the effectiveness of our scoring system by implementing it on a computational tool called "HI-bone" and by identifying mass spectra of an Escherichia coli sample acquired on an Orbitrap Velos instrument using Higher-energy C-trap dissociation. Following this strategy, we identified 1614 peptide spectrum matches with a peptide false discovery rate (FDR) below 1%. These results were significantly higher than those from Mascot and SEQUEST using a similar FDR.

Tools and challenges for diversity-driven proteomics in Brazil.

Our current knowledge in biology has been mostly derived from studying model organisms and cell lines in which only a small fraction of all described species have been extensively studied. Although these model organisms are amenable to genetic manipulations, this blinds researchers to the true variability of life. Groundbreaking discoveries are often achieved by analyzing "noncanonical" species; for example, the characterization of Taq polymerase from Thermus aquaticus ultimately led to a revolution in the field of molecular biology. Brazil possesses a rich biodiversity and a considerable fraction of Brazilian groups use current proteomic techniques to explore this natural treasure-trove. However, in our opinion, much more than the widely adopted peptide spectrum match approach is required to explore this rich "proteomosphere." Here, we provide a critical overview of the available strategies for the analysis of proteomic data from "noncanonical" biological samples (e.g. proteins from unsequenced genomes or genomes with high levels of polymorphisms), and demonstrate some limitations of existing approaches for large-scale protein identification and quantitation. An understanding of the premises behind these computational tools is necessary to properly deal with their limitations and draw accurate conclusions.

Proteomic profiling of the influence of iron availability on Cryptococcus gattii.

Iron is essential and ubiquitous in living organisms. The competition for this micronutrient between the host and its pathogens has been related to disease establishment. Cryptococcus gattii is an encapsulated yeast that causes cryptococcosis mainly in immunocompetent individuals. In this study, we analyzed the proteomic profile of the C. gattii R265 Vancouver Island isolate under iron-depleted and -repleted conditions by multidimensional protein identification technology (MudPIT) and by 2D-GE. Proteins and key mechanisms affected by alteration of iron levels such as capsule production, cAMP-signaling pathway, response to stress, and metabolic pathways related to mitochondrial function were identified. Our results also show both proteomic methodologies employed to be complementary.

Anti-thrombin as a prognostic biomarker candidate for patients with recurrent glioblastoma multiform under treatment with perillyl alcohol.

Perillyl alcohol (POH) is a naturally occurring monoterpene with antiangiogenic and anti-tumoral properties. This chemotherapeutic agent has proven effectiveness in several clinical trials, including an ongoing phase I, comprising patients with recurrent glioblastoma multiform (GBM) under treatment with POH by intranasal administration. Proteomics offers tools to distinguish states of biological systems according to protein expression differences and therefore, can be used to gain pathological insights and to search for disease follow-up biomarkers. In this work, a differential gel electrophoresis (DIGE) proteomic approach was used to search for plasma proteins that correlated with the disease progression in 10 of these patients. Our results pointed antithrombin (down) and fibrinogen (up) regulated after a four months treatment deserving to be further verified as prognostic markers for this treatment. Possible links between tumor progression and anti-thrombin expression level are also discussed.

Differential protein expression patterns obtained by mass spectrometry can aid in the diagnosis of Hodgkin's disease.

More than 90% of patients with cancer, if diagnosed early, can be promptly treated; however diagnosis usually occurs after cancer cells have metastasized. Recent technological advances in mass spectrometry challenges the field of machine learning to model such high dimensional datasets for clinical diagnosis and prognosis. Here we use support vector machines recursive feature elimination to hunt for protein expression patterns in the serum mass spectra of Hodgkin's disease (HD) patients and control subjects (CS) that could aid in diagnosing-the disease. Based on eight selected features, support vector machines was able to correctly classify among all CS and HD patients based on the leave-one-out. We also correctly classified an independent dataset, acquired from the same samples, with the previously generated SVM model.

Marcadores sérios e espectrometria de massa no diagnótico do câncer / Serum markers and mass spectrometry in the diagnosis of cancer

Esta revisão abrange as principais técnicas, limitações e utilidades da espectrometria de massa aplicada à análise de fluidos biológicos para buscar biomarcadores com potencialidade de diagnóstico médico. Atualmente esse método é capaz de discernir, em segundos, padrões moleculares diferencialmente expressos entre indivíduos controles e com câncer. Resultados da literatura apontam a espectrometria de massa como metodologia promissora no futuro do diagnóstico.

This manuscript reviews mass spectrometry methods and limitations for analisys of biological fluids in the search for biomarkers that can aid medical diagnosis. Currently, mass spectrometry has the ability to discriminate differentially expressed molecular patterns among cancer patients and control subjects. Results in the literature point mass spectrometry as having a major role in the future of medical diagnosis.

Effects of perillyl alcohol and heat shock treatment in gene expression of human lung adenocarcinoma cell line A549.

The K-Ras protein is found mutated in 42.4% of lung adenocarcinoma cases, evidencing its importance as a chemotherapeutic target. The Ras protein becomes functional after farnesylation, a post-transduction modification, allowing its attachment to the cellular membrane permitting signal transduction. Perillyl alcohol (POH) has been shown to inhibit the farnesylation of small G-proteins such as Ras. HSP70, a protein known to appear after heat shock (HS), is found over expressed in lung cancer and modifies chemotherapeutic effects. In this work, the effect of POH and HS in the gene expression of human adenocarcinoma lung cells (A549) is studied. Cells incubated with POH followed by 42 degrees C HS presented a 20.7% cellular viability decrease compared to the ones kept at 37 degrees C. A different pattern synthesis was observed for each sequences of cell treatment. Independent of the heat treatment, the amount of HSP70 was decrease by POH without modification in the amount of p53. Here it is shown that HS modified the POH effects in the ERK activation pathway by altering the phosphorylation of p44/42 in human adenocarcinoma lung cells.

Efeito do álcool perílico na expressão gênica de células de adenocarcinoma de pulmão humano / Effect of perillyl alcohol on gene expression of human pulmonary adenocarcinoma cells

OBJETIVO: Estudar a ação do álcool perílico na expressão gênica de células de adenocarcinoma de pulmão humano. MÉTODOS: Incubaram-se células de adenocarcinoma de pulmão com álcool perílico em diluições que variaram entre 0,03 por cento e 0,0003 por cento por 48 horas. Observaram-se as alterações na morfologia celular e quantificou-se a viabilidade celular pelo método do MTT (3-(4,5-dimetiltiazol-2-yl)-2,5 difeniltertrazolim brometo). Analisou-se a síntese de proteínas das amostras previamente marcadas radioativamente com 35S, através de eletroforese em gel de poliacrilamida. Determinou-se a expressão das proteínas p53 e p42/44 através do método de Western Blot. RESULTADOS: Após 48 horas de incubação, observaram-se alterações na morfologia celular para a diluição de 0,03 por cento de álcool perílico, as quais foram pouco verificadas em diluições superiores a 0,003 por cento. A inibição da viabilidade celular foi de 60,17 por cento (p < 0,001), 15,62 por cento (p < 0,001) e 11,53 por cento (p < 0,05) para as diluições de 0,03 por cento, 0,003 por cento e 0,0003 por cento de álcool perílico, respectivamente. Os resultados mostram a indução de proteínas de 110 kDa, 42 kDa e 28 kDa. Não se observou variação estatisticamente significativa para a expressão da proteína p53. Em comparação com a expressão de alfa-tubulina, a diluição de 0,003 por cento de álcool perílico provocou uma diminuição marcante da fosforilação da p44 e um aumento da fosforilação da p42. CONCLUSÃO: Os resultados apresentados sugerem novos caminhos metabólicos da ação do álcool perílico em células de adenocarcinoma de pulmão humano.

OBJECTIVE: To study the effect of perillyl alcohol on the gene expression of human pulmonary adenocarcinoma cells. METHODS: Pulmonary adenocarcinoma cells were incubated with perillyl alcohol in dilutions ranging from 0.03 percent to 0.0003 percent for 48 hours. Alterations were observed in the cell morphology, and cell viability was quantified using [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assays. Protein synthesis of samples previously targeted with S35 was analyzed using electrophoresis on a polyacrylamide gel. Expression of the proteins p53 and p44/42 was determined using the Western blot method. RESULTS: After 48 hours of incubation, greater nsumbers of morphological alterations were observed in cells treated with the 0.03 percent perillyl alcohol dilution than in those treated with perillyl alcohol diluted to 0.003 percent or further. Treatment with perillyl alcohol dilutions of 0.03 percent, 0.003 percent and 0.0003 percent inhibited cellular viability by 60.17 percent (p < 0.001), 15.62 percent (p < 0.001) and 11.53 percent (p < 0.05), respectively. The results show that 28-kDa, 42-kDa and 110-kDa proteins were induced. No statistically significant effect on p53 expression was observed. In comparison with the expression of alpha-tubulin, the 0.003 percent perillyl alcohol dilution induced an increase in p42 phosphorylation and a marked decrease in p44 phosphorylation. CONCLUSION: The results suggest that there are other, previously undescribed, metabolic pathways for perillyl alcohol effects in human pulmonary adenocarcinoma cells.