In a previous post dedicated to Quantitative arrays (Quantibody), I introduced our L-Series aimed at a broad one shot profiling of up to 1000 markers at once. This relative quantitation technology allows you to perform a first screen of your samples of interest versus a control, before you go on to targeted profiling using either pathway specific arrays, or a custom array including the targets of interest identified with the initial L-series screen. [Read more…]
Early in 2015, researchers of The University of Queensland Diamantina Institute (Australia) have shown a very sensible approach to the discovery of new biomarkers associated to transition from non-metastatic tumours to metastatic tumours in osteosarcoma. Not to be a spoiler, but they found that the uPA/uPAR axis is crucial for this, and can be used as a prognostic biomarker. In fact, inhibition of this axis can inhibit the metastasis in this type of tumours. (Endo-Muñoz et al. DOI: 10.1371/journal.pone.0133592).
I don’t want to focus on the biomarker per se, but rather, on the process that this lab followed to discover this new biomarker. [Read more…]
A crosstalk between cancer and immune cells is established during cancers. The immune system is able to fight against tumour cells (see my previous post “Immunosurveillance: Crosstalk between cancer and immune cells”). But what happens when immunosurveillance fails?
This is the subject of this new post. A selection of validated immunoassays allowing you to monitor cytokines and signal transduction biomarkers involved in these “loops” is also introduced.
Tumours are composed by a heterogeneous group of cells from diverse organs, ranging from stem cells and endothelial cells, to a wide range of immune cells. The plethora of secretory signals from cancer cells have numerous effects that help promote tumour growth and progression, while also perturbing the immunologic surveillance of developing tumours.
Cancerous cells express their own profile of cytokines and chemokines that facilitate inflammation, cell growth, and recruitment of new blood vessels. It is also recruiting accessory cell populations for their survival and immunologic avoidance. Collectively, these local changes promote the developing tumour microenvironment (TME). As we have seen in previous posts, multiplexed immunoassays remain the best and most complete means to study the proteomic changes within the TME, as they afford the most global view of protein changes from numerous and disparate cell populations.
High-density protein expression profiling is now possible with the latest advancements in multiplex ELISA platforms. They enable the detection of a diversity of novel cytokine interactions in tumour cell populations. As these unique pathways are determined, more traditional biomolecular studies can then define these networks. Multiplex ELISAs and antibody arrays therefore represent powerful tools for the identification of new cancer biomarkers, either from the local TME, or from the cancer cells themselves.
This post is the first one of a series aiming at describing the mechanisms of TME and immunosurveillance and at introducing the reliable immunoassays to analyse cellular crosstalks at the protein level. Thanks to Jarad Wilson, from Raybiotech Inc., for his help on making this series!
Tumour immunosurveillance crosstalks – the main actors to monitor
Tumour immunosurveillance is the identification and elimination of cancer cells by the immune system. This process is predominantly mediated by CD8+ cytotoxic T lymphocytes (CTLs), natural killer cells (NK), neutrophils, and several subtypes of effector CD4+ T cells (CD4s), with accessory roles performed by antibody producing B cells and macrophages (Mφ) amongst others.
Effective immunosurveillance requires the innate immune system’s recognition of the tumour’s presence and the subsequent full activation and maturation of antigen presenting cell (APC) populations, namely the dendritic cell (DC) population. This maturation process increases APC surface expression of MHC-antigen complexes, increases APC endocytic sampling, upregulates cytokines that recruit T cell populations (IL-6, IL-12), and increases surface expression of T cell costimulatory ligands (CD80,CD86, ICOS).
Fully mature DC populations are potent anti-tumour APCs capable of activating all forms of tumour-specific T cell populations. Activated CD8 T cells differentiate to form CTLs which have profound inflammatory and cytolytic functions, while activated effector CD4 T cells secrete cytokines that have immunostimulatory and chemotactic effects.
Specifically, effector CD4 T cells develop into a T helper 1 (Th1) population which secretes IL-2 to promote CTL and further CD4 T expansion, TNF-α to inflame the site and recruit other immune cells, and IFN-γ which has anti-tumor and inflammatory functions. IFN-γ also functions to activate and drive Mφ populations into an M1 phenotype, which further produce IL-1α and IL-1β, feeding back to promote Th1 effector CD4+ polarisation and reinforcing the anti-tumour immune programming.
Collectively, these targeted immune responses are capable of shrinking the cancer population, but such a targeted measure can create selective pressures on those tumour cells capable of avoiding this surveillance program. The development of tumorigenesis requires the eventual subversion of immunosurveillance, a multi-step process leading to eventual escape from immunologic recognition and control.
Th1 lymphocytes and M1 Mφ are the primary sources of pro-inflammatory cytokines that promote cancer immunosurveillance and cytotoxicity. Their interactions are mutually reinforcing: Secretion IFN-γ by Th1 cells results in the recruitment and maintenance of M1, while IL-12 produced by M1 macrophages recruits, activates and maintains Th1 cells. Secretion of MIG/CXCL9 and IP-10/CXCL10 also promotes the recruitment of Th1 cells and CTLs and inhibits angiogenesis. IL-1α, IL-1β and IL-6 form an autocrine feedback loop by stimulation of myeloid differentiation primary response gene 88 (MyD88)-mediated activation of NF-κB signaling. TNF-α, also released by the activation of NF-κB signaling, which activates APC functions of DCs and the recruitment and cytotoxic activation of M1 macrophages, effector CD4+ T cells, and CD8+ cells, as well as the recruitment of NK cells.
Th2 lymphocytes, M2 macrophages and MDSCs mutually reinforce the proliferation and phenotypes of one another, as well as maintaining tumor-promoting inflammation and angiogenesis. These cells, along with T Regulatory lymphocytes (TREGs) suppress the activity and proliferation of tumor-suppressing cells, including Th1, M1 and cytotoxic T cells and NK cells.
It should be noted that M1 &M2 Mφ can interconvert, but these phenotypes are stable as the M1 and M2 expression profiles reinforce their own macrophage phenotypes, while suppressing the other. Similarly, Th1 & Th2 lymphocytes, as well as TREG & Th17 lymphocytes tend to self-reinforce their own activation profiles and inhibit the other.
Having a look at this picture, one would think that the immune system controls the growth and dissemination of cancer cells. We know that, unfortunately, this is not always true.
So…what happens when immunosurveillance fails and why does it fail? Stay tuned for our next post!
Looking for validated immunoassays to analyse tumour crosstalks? Please do not hesitate to leave a message below.
Searching for predictive biomarkers lies in the heart of the concept of Personalised Medicine. Leaving aside some ethical aspects such as whether you want to know (or having other people knowing) your genetic disposition and/or the impact that your life style / environment will have in your future health (not to mention that these tools are still only accessible to a small percentage of the world’s population), we mention here some points that should be addressed if you want to start a study to find new predictive biomarkers. [Read more…]
For secretome biomarker profiling, several solutions, including arrays allowing to screen up to 1,000 factors, have been available for some time now. These profiling solutions, however, were semi-quantitative so far. Quantitative solutions were available for “only” up to 400 factors.
Recently, a new array allowing to quantify 640 human secretome factors has been released. This array is available as a product (to use in your lab), or you can have the array performed for you (tebu-bio’s laboratories, located near Paris). [Read more…]
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…
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…]
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…]
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…