8 criteria for selecting your ELISA kits

Biomarkers specialists are often asked to select an ELISA kit for researchers: with thousands of ELISA references available on the market, the choice can be tricky regarding proteins for which several kits available.

When researchers have to choose a new ELISA kit, the price is regularly the first parameter of selection. But my experience with long term projects shows that it should in fact be the very last one…

[Read more…]

Vive la différence! To pool or not to pool…

In a previous post on whether samples should be pooled or not for proteomic profiling, we discussed this approach, which can be quite cost-wise, while still allowing to see the main biomarkers differentiating one physiological condition from another (e.g. disease vs healthy control).

In real life, however, this discrimination between physiological conditions may be difficult to define. Let’s take, for example, a study aimed at studying the differential immune response to an infection, and how this can be used to design more efficient therapies in different population subgroups. [Read more…]

Discovery of functional serum biomarkers

Lung cancer is one of the most common malignancies, and the leading cause of cancer-related fatality. Current diagnostic practices for common cancers rely heavily on imaging technologies. These methods are quite accurate, but still have a probability of having false-positive findings. Also, there is a substantial need for non-invasive ways to test whether the nodules are benign or malignant.

Blood-based biomarkers have potential in cancer screening, and their role could extend further from general population risk assessment to treatment response evaluation and recurrence monitoring. However, despite much research effort, biomarkers able to predict disease onset and evolution are not always easy to find, or distinctive enough. [Read more…]

Biomarker profiling or multiplex quantification for everyone

Many researchers would be keen to identify new targets for their research project: add a new cytokine to the classical inflammatory panels, find the missing link between 2 phosphorylation pathways, dig into the miRNA to find a new therapeutic target…
They expect they’ll need dedicated (and expensive) new equipment. Not necessarily! Let’s take a look at assays that use existing and quite common readers, or that can easily be outsourced to reliable labs…

[Read more…]

Direct access to Biomarker Profiling identification tools

Profiling tools have an increasing interest for identifying new biomarkers. Different tools are available, from classical gene profiling on DNA chips, RT-qPCR arrays, Protein arrays for secretome or transcriptome, mRNA arrays and finally miRNA arrays. All these techniques sometimes require specific material for reading arrays, and some bioanalytics to extract valuable markers of interest.

Expand your knowledge – a new visionArrays - Blog Thumbnail

The increasing focus on these tools is obvious as they help to expand scientific knowledge on sometimes well-known pathways. Why restrict your analysis to classical markers instead of checking the impact on more than 100 biomarkers… at a similar cost? Value of results is obvious as well, as it offers a convenient way to identify original pathways.

The “Start smart” attitude

Facing a new project is always a stressful situation. Biomarkers chosen are generally based on literature, which may lead to duplicating, more or less, already existing information. Searching for innovative pathways looks more like a cherry-picking, highly risky strategy. At the end, this may lead to rather conservative conclusions. A striking example concerns Western blots (WB) which everybody knows may be time consuming, rather expensive and for sure limited in number for a given project. Nobody will ever make the decision to perform more than 100 WB to explore all the potential targets available. Lab’s budgets can’t survive such a strategy, and probably the time allocated to a project cannot suffer such delays…

Protein profiling on secretome or transcriptome now allows you to study more than 1000  targets from a single sample at once. Pricing is equivalent to 10 to 20 WB traditional WB. Results obtained are of top value as they immediately orientate research focus to appropriate pathways without having the risk of missing crucial information. This helps to speed up projects, focus research towards original biomarkers and at the end deeply differentiate published results.

But not everybody has the appropriate material to perform these assays, nor is used to handling these arrays. This generally needs adapted scanners to perform readouts and once results are obtained, spots need to be further analyzed to guarantee final quality. It requires some skill. One can understand the reluctance to jump into these technologies when they are only of occasional need.

So where’s the solution?

For these reasons, tebu-bio has developed over these last years a complete Profiling – Biomarker identification platform that offers researchers access to various solutions. With a complete offer including RT-qPCR arrays, protein arrays for soluble or signal transduction markers, mRNA and miRNA arrays, we help researchers to immediately identify biomarkers involved in their domains. This information, which often appears as the initial step in project management, drives studies in the appropriate direction, rapidly and in a cost effective way.

The service process is extremely simple. After defining the most appropriate solution regarding goals of interest, your samples are tested and results sent back. Time frame is generally 2 to 4 weeks depending on starting material. A dedicated project manager is always available for any questions throughout the project. There is no license involved in these studies, which are performed in our own, European-based labs near Paris.

For those who don’t have access to cell culture facilities, our cell culture platform is also ready to collaborate, with access to a large stock of primary cells.

And the next step…

Well, if you’re curious to know how this could help boost your research, get in touch to see exactly how it can work! Just leave your question or comments below.

Glycosylation studies in the inflammasome

In a previous post on tumour microenvironment (TME) and glycosylation, we indicated that new tools for studies on glycosylation of proteins were being developed. We are happy to announce that they are now available!

UntitledThese new tools are directed at studying the glycosylation of proteins in the secretome and inflammasome. This is related to TME, but also to many other processes where factors such as cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors and soluble adhesion molecules are relevant. [Read more…]

Tips for data interpretation in profiling arrays

One of the questions we usually get in the Biomarkers team, once researchers or clinicians have done profiling arrays (e.g. for secretome and kinome), is how to interpret, biologically speaking, the obtained data.

It’s not the scope of this post to give a general overview of what has been published so far, but you can always have a look at publications using profiling arrays to see how other people have presented their results. The aim of this post is to give some general “rules” or ideas to help you analyse your data… even before you do your experiment. [Read more…]

Profiling of secretome biomarkers – pancreatic cancer

Following a post on tools for discovery of secretome biomarkers in biological samples, a recent publication by Torres et al. depicts how some of these tools (i.e. antibody arrays) can be used to find new biomarkers relevant for pancreatic cancer.

In this study, Torres and co-workers used an antibody array that detects 507 human secretome markers, anBiotin Label Flow Chart_bisd they compared serum of patients with pancreatic cancer vs. healthy controls.

They found a series of new biomarkers, of which the most relevant ones were Fibroblast Growth Factor 10 (FGF-10), Keratinocyte Growth Factor-2 (KGF-2), 11 Interferon Inducible T-cell alpha Chemokine (I-TAC), chemokine [C-X-C motif] ligand 11 (CXCL11), Oncostatin M (OSM), Osteoactivin/Glycoprotein Nonmetastatic Melanoma Protein B, and Stem Cell Factor (SCF), which were significantly overexpressed.

Moreover, they also found some markers which were differentially expressed in response to treatment with Gemcitabine and Erlotinib (CD30 ligand/Tumor Necrosis Factor superfamily Member 8 (TNFSF8), Chordin-like 2, FGF-10/KGF-2, Growth/Differentiation Factor 15, I-TAC/CXCL11, OSM, and SCF).

Congratulations to the whole team (specially Sonia and Carolina) for this nice publication that helps advancing in the fight against cancer!

Would you like to share your experiences using antibody arrays for biomarker discovery? Add your comments below!

 

Pooling samples for proteomics – biomarker profiling case studies

To pool or not to pool biological samples? This question might pop up in the mind of anyone designing biomarker discovery approaches!

Much debate has been raised on biomarker discovery from clinical cohort studies, since the first experiments linking SNPs to disease phenotypes, to the current and new proteomic and miRNA technologies. The answer to this question strictly depends on clinical data, patient group characteristics and… financial means.

[Read more…]

Secretome biomarker identification: tech tips for selecting the most suitable tools

In a previous post, I mentioned that the secretome is becoming a very hot topic in the world of proteome analysis, and even a crucial study subject. Today, I’d like go a step further and shed some light on how to analyse it.

Let’s see what the options are…

[Read more…]