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Biomarkers and multiple drug resistance in breast cancer.

Breast cancer, the most common form of cancer among women in North America and almost all of Europe, is a significant health problem in terms of both morbidity and mortality. It is estimated that each year this disease is diagnosed in over one million people worldwide and is the cause of more than 400,000 deaths. Although chemotherapy forms part of a successful treatment regime in many cases, as few as 50% patients may benefit from this, as a result of intrinsic or acquired multiple drug resistance (MDR). Through the use of in vitro cell culture models, a number of mechanisms of MDR have been identified; many, if not all, of which may contribute to breast cancer resistance in the clinical setting. This phenomenon is complicated by the likely multi-factorial nature of clinical resistance combined with the fact that, although apparently studied extensively in breast cancer, reported analyses have been performed using a range of analytical techniques; many on small sub-groups of patients, with different clinicopathological characteristics and receiving a range of therapeutic approaches. Larger defined studies, using standardised genomic and proteomics profiling approaches followed by functional genomics studies, are necessary in order to definitively establish the degree of complexity contributing to drug resistance and to identify novel therapeutic approaches - possibly involving chemotherapy, drug resistance modulators, and novel targeted therapies - to combat this disease.

Antineoplastic Agents↗

Independent prognostic value of semaphorin-4D, interleukin-1β and complement activation in newly diagnosed multiple myeloma patients.

Multiple myeloma represents a systemic disease of the bone marrow (BM) niche, in which immune and skeletal pathways are tightly interconnected. However, the independent prognostic significance of bone and immune-related markers in newly diagnosed multiple myeloma (NDMM) remains incompletely understood. Semaphorin (Sema) 4D, activin-A, and periostin ELISA, LEGENDplex™ Human Bone Metabolism Panel and proteomic analysis for novel biomarker identification were conducted in 71 consecutive samples from NDMM patients. In 25 patients, genomic analysis was performed on sorted clonal plasma cells. NDMM patients had a median age at diagnosis of 65 years and a median follow-up of 2.5 years. Interleukin (IL)-1β and Sema4D levels predicted progression-free survival (PFS), highlighting their role in disease relapse. Proteomic profiling revealed a systemic signature associated with worse prognosis, enriched in complement activation components. Complement C5 significantly affected PFS and time to progression (TTP). IL-1β and C5 predicted PFS independently of the second revision of the International Staging System (R2-ISS) stage, and a similar trend was noted for Sema4D. Myeloma bone disease (MBD) did not significantly affect overall survival, PFS, or TTP, suggesting that contemporary treatments mitigate its impact. Genomic analyses identified variants associated with inferior PFS, including HLA-DRB5 (c.300_306delinsCGGG) and HLA-DQB1 (c.317_319delinsCGG). Sema4D and the IL-1β-complement cascade emerged as key drivers of disease progression, independent of R2-ISS stage, representing potential prognostic and therapeutic targets in NDMM.

Journal Article↗

Treatment of ductal carcinoma in situ of the breast: review of recent advances and future prospects.

Ductal carcinoma in situ (DCIS) is a heterogeneous disease characterized by noninvasive clonal proliferation of malignant epithelial cells arising from the mammary ducts and terminal ductal-lobular units. Its reported incidence is rising due to the wide adoption of screening mammography. The combination of nuclear grade and presence of necrosis is currently the best predictor of biological behavior. Approximately 25-50% of DCIS lesions progress to invasive disease if left untreated. The treatment options for DCIS include total mastectomy with or without immediate breast reconstruction (IBR), local excision (LE) plus adjuvant radiotherapy (RT), and LE alone. Total mastectomy is associated with lowest rates of local recurrence and breast cancer-specific mortality. If IBR is considered, then skin-sparing mastectomy (SSM) combined with autologous myocutaneous flap reconstruction can achieve excellent cosmesis without compromising local control. The role of adjuvant radiotherapy (RT) after LE remains controversial. Three recent randomized controlled trials have demonstrated that adjuvant RT after LE of localized DCIS significantly reduces the incidence of local recurrence. However, these trials did not identify any subgroups of patients where RT could be safely omitted and were criticized for lack of emphasis on standardized and meticulous tissue processing and pathological evaluation. Retrospective studies indicate that RT can be safely omitted after adequate LE (margin width > or = 1 cm) of small (< 15 mm), non-high grade DCIS not associated with necrosis. The role of tamoxifen in the treatment of DCIS continues to evolve. Formal axillary dissection is not appropriate for DCIS; however, the potential role of the sentinel node biopsy (SNB) in selected high-risk cases requires further evaluation. Areas of ongoing and future research include the potential role of third-generation aromatase inhibitors and third- and fourth-generation selective estrogen receptor modulators in women with hormone-sensitive DCIS; the potential role of cyclo-oxygenase type 2 inhibitors in DCIS treatment and prevention; the value of magnetic resonance and nuclear medicine imaging; and the clinical relevance of gene expression profiling, proteomics, radiofrequency or LASER ablation and mammary ductoscopy in the management of DCIS.

Breast Neoplasms↗

[Biomarkers in breast cancer].

Biomarkers are measured in the management of breast cancer patients for the following purposes. (1) Early detection of breast cancer: blood tumor markers such as CA 15-3 are useless for this detection because of a low sensitivity. Proteomics profiling has recently been investigated using blood or nipple aspirate fluid for the detection. Measurement of CEA and HER 2 in abnormal nipple discharge has been approved for diagnosis of breast cancer in Japan. (2) Monitoring of breast cancer patients: serum tumor markers are routinely measured for early detection of recurrent diseases, evaluation of therapeutic response and monitoring outcome of patients by a majority of breast cancer experts in Japan. Study results investigated by the Study Group of the Japanese Breast Cancer Society in 2001 are presented with regard to the questionnaire survey on the present status of tumor marker measurement and the clinical study on usefulness of tumor markers for the evaluation for therapeutic response. (3) Prognostic factors: new biomarkers have been investigated to select patients at high risk for distant metastases, which could not be selected by classic prognostic factors. Three prognostic factors (UPA/PAI-1, cyclin E, gene profiling), which were discussed at the 8th St. Gallen International Consensus Meeting last year, are mainly discussed. (4) Predictive factors for therapeutic response: hormone receptors (HR) have been used as reliable predictive factors for response to endocrine therapy. Other biomarkers have been investigated to select patients with tumors HR-positive but unresponsive to endocrine therapy. Current status, clinical significance, problems and future directions on predictive factors for response to cytotoxic chemotherapy are also discussed.

Biomarkers, Tumor↗

[The fight against doping: today and tomorrow].

Since Antiquity, sport persons have used doping methods to improve their performance. The methods used today are increasingly specific and professional As a corrolary, doping is becoming extremely difficult to detect: because many prohibited drugs are rapidly metabolized (short half life); it is often impossible to distinguish between the natural and recombinant hormone products; several prohibited substances are not screened for; therapeutic use authorization (TUA)--a recent recommendation from the World antidoping agency (WADA)--and advances in gene therapy are giving cheaters new possibilities. It is necessary to promote a new approach to doping detection by determining potential specific links between changes in human biological profiles (proteom, transcriptom, metabonom), and the use of a given drug. Developments in nanotechnology, and notably" labs on a chip" should prove useful in this respect.

Doping in Sports↗

[Expression and catalysis of glucokinase of Thermoanaerobacter tengcongensis at different temperatures].

According to analysis of proteomic profiling for Thermoanaerobacter tencongensis, TTE0090 could be a novel gene of glucokianse (GLK), though no GLK gene was annotated in the genomic data. With the methods of cloning and expression in vitro, the recombinant TTE0090 was successfully expressed and purified. The recombinant TTE0090 exhibited the catalysis of GLK, even at high temperatures. Detection of expression levels and catalysis of TTE0090 in vivo was furthermore carried out at different temperatures. The expression of TTE0090 was attenuated during the culture temperature elevated; however, the specific activity was positively correlated to temperature raised. This leads a possibility that the metabolic capacity of glycolysis in T. tencongensis is relatively constant at different temperatures. All the results herein demonstrate that TTE0090 is a novel gene of GLK. The studies on TTE0090 and its protein product, thus, may deepen our understanding of the adaptation mechanism of thermophilic bacteria living in harsh environment.

Bacterial Proteins↗

Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells.

Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.

Biomarkers, Tumor↗

Alterations in DNA Methylation, Proteomic, and Metabolomic Profiles in African Ancestry Populations with APOL1 Risk Alleles.

KEY POINTS: We aimed to elucidate potential methylation, proteomic, and metabolomic mechanisms by which APOL1 variants may be linked to kidney disease. We report distinct methylation profiling between APOL1 risk allele carriers and noncarriers, many near APOL gene family. We report higher APOL1 protein and lower C18:1 cholesteryl ester in two risk allele carriers. BACKGROUND: The APOL1 high-risk haplotype has been associated with CKD and the deterioration of kidney function, particularly in populations with West African ancestry. However, the mechanisms by which APOL1 risk variants increase the risk for kidney disease and its progression have not been fully elucidated. METHODS: We compared methylation (N=3191; 715 [22%] carriers), proteomic (N=1240; 169 [14%] carriers), and metabolomic (N=6309; 674 [11%] carriers) profiles in African and Hispanic/Latino carriers of two APOL1 high-risk alleles (G1/G1, G2/G2, G1/G2) and noncarriers (G0/G0), excluding heterozygotes (G0/G1, G0/G2), from the Population Architecture using Genomics and Epidemiology Consortium and UK Biobank. In each study, the associations between the APOL1 high-risk haplotype and up to 722,719 cytosine-phosphate-guanine (CpG) sites, 2923 proteins, or 836 metabolites were estimated using covariate-adjusted linear regression models, followed by fixed-effects sample size&#x2013;weighted meta-analyses. RESULTS: Significant associations were observed between APOL1 high-risk haplotype and methylation at 52 CpG sites, with 48 located on chromosome 22 and 18 in the vicinity of APOL1&#x2013;4 and MYH9. All significant CpG sites near APOL2 were hypomethylated, whereas those near APOL3 and APOL4 were hypermethylated. APOL1-associated CpG sites were also identified in genes involved in ion transport and mitochondrial stress pathways. Sensitivity analyses indicated consistent yet attenuated effects among heterozygotes, supporting an additive effect of APOL1 risk alleles. Further analyses of the 52 CpG sites identified two near APOL4 exhibiting G1-specific effects, eight associated with CKD but none with eGFR, and three showing heterogeneity by CKD status. In addition, carrying two APOL1 risk alleles was associated with higher plasma APOL1 protein (&#x3b2;=1.12, PFDR = 2.26e-70) and lower C18:1 cholesteryl ester metabolite (Z=&#x2212;4.50, PFDR = 4.83e-3). CONCLUSIONS: Our results demonstrate differential methylation, proteomic, and metabolomic profiles associated with APOL1 high-risk haplotypes.

APOL1↗

From genome to proteome in tumor profiling: molecular events in colorectal cancer genesis.

Biomedical research has advanced rapidly in recent years with the sequencing of the human genome and the availability of technologies such as global gene and protein expression profiling using different chip platforms. However, this progress has not yet been transferred to the bedside. While detection of cancer at early stages is critical for curative treatment interventions, efficient diagnostic and therapeutic markers for the majority of malignancies still seem to be lacking. Comprehensive tumor profiling has therefore become a field of intensive research aiming at identifying biomarkers relevant for improved diagnostics and therapeutics. This chapter will demonstrate a genomic and proteomic approach while focusing on tumor profiling during colorectal cancer development.

Animals↗

Translation control: bridging the gap between genomics and proteomics?

mRNA profiling enables the expression levels of thousands of transcripts in a cell to be monitored simultaneously. Nevertheless, analyses in yeast and mammalian cells have demonstrated that mRNA levels alone are unreliable indicators of the corresponding protein abundances. This discrepancy between mRNA and protein levels argues for the relevance of additional control mechanisms besides transcription. As translational control is a major mechanism regulating gene expression, the use of translated mRNA in profiling experiments might depict the proteome more closely than does the use of total mRNA. This would combine the technical potential of genomics with the physiological relevance of proteomics.

Gene Expression Profiling↗

Correlation of proteomic and transcriptomic profiles of Staphylococcus aureus during the post-exponential phase of growth.

A combined proteomic and transcriptomic analysis of Staphylococcus aureus strain N315 was performed to study a sequenced strain at the system level. Total protein and membrane protein extracts were prepared and analyzed using various proteomic workflows including: 2-DE, SDS-PAGE combined with microcapillary LC-MALDI-MS/MS, and multidimensional liquid chromatography. The presence of a protein was then correlated with its respective transcript level from S. aureus cells grown under the same conditions. Gene-expression data revealed that 97% of the 2'596 ORFs were detected during the post-exponential phase. At the protein level, 23% of these ORFs (591 proteins) were identified. Correlation of the two datasets revealed that 42% of the identified proteins (248 proteins) were amongst the top 25% of genes with highest mRNA signal intensities, and 69% of the identified proteins (406 proteins) were amongst the top 50% with the highest mRNA signal intensities. The fact that the remaining 31% of proteins were not strongly expressed at the RNA level indicates either that some low-abundance proteins were identified or that some transcripts or proteins showed extended half-lives. The most abundant classes identified with the combined proteomic and transcriptomic approach involved energy production, translational activities and nucleotide transport, reflecting an active metabolism. The simultaneous large-scale analysis of transcriptomes and proteomes enables a global and holistic view of the S. aureus biology, allowing the parallel study of multiple active events in an organism.

Bacterial Proteins↗

Proteomic analysis of individual variation in normal livers of human beings using difference gel electrophoresis.

Normal Chinese Liver Proteome Expression Profile is one of the major parts of Human Liver Proteome Project. Before starting the studies, it is necessary to examine the interindividual variation of normal liver proteome and evaluate the minimal size of samples for proteomic analysis. In this study, normal liver samples from ten individual volunteers were collected and the proteome profiles of these samples were analyzed using 2-D difference gel electrophoresis (DIGE) combined with MALDI-TOF/TOF MS. The individual liver tissue lysates were labeled with Cy3 and Cy5 while the pooled sample was labeled with Cy2 as an internal standard, which minimized gel-to-gel variation. After analysis by the DeCyder software, up to 2056 protein spots were detected on the master gel. The CV of standardized abundance was calculated for the protein spots that were matched across all ten gels. The CV values of these protein spots ranged from 6.4 to 108.5% and the median CV was approximately 19%, which demonstrated that the protein expression of normal liver among different individuals was relatively stable. The eight proteins with CV values over 50% were identified which would be a caveat when considering these proteins as potential disease-related markers. Moreover, the one-way ANOVA feature showed a correlation between sample size and individual variations. The results showed that when the sample size exceeded 7, the individual variations were not significant to the whole pool. Our results are an important basis for liver protein expression profiles and comparative proteomics of liver disease.

Electrophoresis, Gel, Two-Dimensional↗

Proteomic and metabolomic profiling reveals dysregulation of immune states, mucin-type glycosylation and steroid metabolism in extramammary Paget's disease.

BACKGROUND: Extramammary Paget's disease is a rare cutaneous adenocarcinoma characterized by mucin-rich Paget cells and chronic inflammation, yet its molecular basis remains unclear. OBJECTIVE: To systematically characterize the proteomic and metabolomic landscape of EMPD, uncover immune heterogeneity, and identify molecular pathways underlying tumor progression and microenvironment remodeling. METHODS: We performed integrated proteomic and metabolomic analyses on 92 male tumor patients and 30 healthy controls, identifying 10,217 proteins and 1466 metabolites. RESULTS: Extramammary Paget's disease lesions exhibited broad activation of inflammatory pathways. Immune profiling further uncovered substantial inflammatory heterogeneity, delineating immune-cold and immune-hot subtypes, with the latter associated with stronger invasive potential. Aberrant mucin-type glycosylation was also prominent, featuring Tn-modified MUC1 and MUC5AC accompanied by elevated GALNT7, GALNT6, GALNT4, and ST6GAL1, which correlated with inflammatory intensity. Metabolomic data demonstrated elevated levels of testosterone, dehydroepiandrosterone, and related intermediates in tumor tissues, indicating an androgen-enriched metabolic profile in extramammary Paget's disease. CONCLUSION: These findings reveal immune, glycoproteomic, and metabolomic pathways in extramammary Paget's disease pathogenesis and provide novel insights for molecular classification and therapeutic targeting.

Humans↗

Rapid antibody quantification and generation of whole proteome antibody response profiles using LIPS (luciferase immunoprecipitation systems).

The application of LIPS to the rapid quantification of antibody responses to infectious agents is described. Chimeric genes encoding pathogen antigens fused to Renilla luciferase are expressed in mammalian cells; crude extracts are prepared and, without purification, employed in immunoprecipitation assays to quantify pathogen-specific antibodies. In cross-sectional and longitudinal studies, antibody levels to the MSG-14 antigen of Pneumocystis jirovecii measured by this assay correlated well with levels previously obtained with an optimized ELISA. We also correctly predicted Hepatitis B (HBV), Hepatitis C (HCV), and HIV infection status in all but 2 of 99 assays analyzing 33 patient sera. We then used 15 HIV-encoded proteins comprising the whole HIV proteome to generate antibody response profiles for these 33 sera. Each HIV antigen was recognized by antibodies in serum from at least one HIV-infected individual. Data generated with these simple, quantitative antibody-detection assays have both clinical and research applications.

Antibodies↗

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans↗

Proteomic and gene profiling approaches to study host responses to bacterial infection.

Infectious disease is the result of an intimate relationship between the pathogen and host, which involves cross-talk. After an initial flood of mainly descriptive reports on the influence of acute bacterial infection on cells, transcriptome and proteome studies are now becoming more refined in their approach, and are shedding light on the role of pathogen-specific mechanisms/structures in pathogenesis. In addition, studies of gene expression in vivo have shed new light on how the host influences the niche occupied by bacteria. Elegant refinements to proteomics using beads coated with bacterial invasins, or purifying subcellular fractions are producing a picture of invasion specific processes. Such approaches combined with modern functional genomics technologies such as RNAi represent the next phase in understanding host-bacteria interactions.

Animals↗

Emerging Trends in Mass Spectrometry-Based Quantitative Proteome and Phosphoproteome Profiling in Maize.

Maize (Zea mays) is both an agronomically important crop and a reference model organism that has enabled the dissection of the molecular basis of plant development and environmental responses. Mass spectrometry-based proteomics provides a powerful approach to identify and quantify proteins and their post-translational modifications, facilitating the discovery of molecular mechanisms underlying complex biological processes. Unlike the study of gene expression using transcriptomics, analysis of the proteome and phosphoproteome provides direct measurement of proteins, which are responsible for driving or regulating nearly all cellular processes, thus offering a more complete picture of the cell's functional state. Over the past two decades, advancements in mass spectrometry have enabled large-scale profiling of protein abundance and phosphorylation sites in maize, improving our understanding of various biological phenomena. Here, we briefly summarize some of the major biological insights gained from maize proteome and phosphoproteome studies, and provide an overview of mass spectrometry sample preparation and acquisition/analysis workflows for the quantitative and reproducible analysis of protein abundance and phosphorylation dynamics in maize.

Zea mays↗