Shedding Light into the Tumor Microenvironment

Tumors are 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 tumor growth and progression, while also perturbing the immunologic surveillance of developing tumors. Cancerous cells express their own profile of cytokines and chemokines that facilitate inflammation, cell growth, and recruitment of new blood vessels, while also recruiting accessory cell populations for their survival and immunologic avoidance. Collectively, these local changes promote the developing tumor microenvironment (TME). 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, enabling detection of a diversity of novel cytokine interactions in tumor 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.

Keeping Tumors at Bay

Tumor immunosurveillance is best described as the identification and elimination of cancer cells by the immune system (Figure 1). 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 (Figure 2). Effective immunosurveillance requires the innate immune system’s recognition of the tumor’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-tumor APCs capable of activating all forms of tumor-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+ polarization and reinforcing the anti-tumor 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 tumor 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.

Figure 1: Tumor-Suppressing Inflammation Model

Tumor-Suppressing Inflammation Model

Related Products:

  1. Human Th1/Th2/Th17 Array Q1
    (detecting IFN-γ, IL-6, and IL-12 amongst others)
  2. Human Chemokine Array C1/G1
    (detecting 38 chemokines including CXCL9 and CXCL10)
  3. Human Inflammation Array C1/G1 & C2/G2
    (detecting IL-1α, GCSF, GM-CSF, RANTES and KC)
  4. Human Cytokine Array C1/G1
    (detecting Several Interleukins, GRO, MCP-1 and TGF-β)
  5. Human Growth Factor Array C1/G1
    (detecting VEGF, EGFR, TGF-β and M-CSF)
  6. Mouse Cytokine Array Q1
    (detecting IL-1α, IL-1β, IL-6, and IL-12)
  7. Mouse Cytokine Array C1
    (detecting IFN-γ, TNF-α, and IL-6)

View Larger Image

Th1 lymphocytes and M1 macrophages 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 Th1cells. 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 ofM1 macrophages, effector CD4+ T cells, and CD8+ cells, as well as the recruitment of NK cells.

Figure 2: Tumor-Supporting Immune Cell Interactions

Tumor-Supporting Immune Cell Interactions

Related Products:

  1. Human Th1/Th2/Th17 Array C1/G1
    (detecting TNF-α, IL-12, IL-6, IFN-γ and IL-1β)
  2. Human Inflammation Array Q1 & Q2
    (detecting IL-4, IL-6, IL-10, TNFα)
  3. Human Cytokine Array Q1000
    (detecting 80 cytokines including Interleukins, IL-12p40 and p70, and IL-17)
  4. Mouse Inflammation Array C1/G1
    (detecting IL-10, SDF-1α, IL-12p70 and IL-17p40/70)
  5. Mouse Inflammation Array Q1
    (detecting KC, MIP-1α, MCP-1, IL-1β and IFN-γ)
  6. Mouse Interleukin Array Q1
    (detecting G-CSF, IL-1β, IL-2, IL-4, IL-6, IL-10, and IFN-γ)

View Larger Image

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 macrophages 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.

When Immunosurveillance Fails

As summarized in Figure 3, tumor escape involves many potential steps, including loss of expression or alterations of immunologically recognized tumor associated antigens (TAAs), decreased expression of NK and/or CTL recognized activation markers or increased expression of cytolytic inhibitory markers (NKG2D, MHC I, KLRG1, CTLA4), secretion of immunosuppressive cytokines (TGF-β, IL10), or recruitment of immunomodulatory cell populations to the tumor microenvironment (cancer-associated fibroblasts, monocyte-derived suppressor cells). Immunologic pressure on the growing tumor selects for increased survival of those cancer cells expressing fewer TAAs on surface MHC molecules, leading to poorer recognition by immunosurveying T cells. Reduced antigen recognition can lead to reduced cytolysis by CTLs and NK cells, but also reduces IFN-γ expression that normally promotes local inflammation and differentiation of M1 Mφs. Increased tumor cell shedding of MHC homologues can block NKG2D mediated NK cell activation, further masking the tumor cell from the innate immune system. Coupled with surface expression of CTLA4 and PD-1, molecules with known immunosuppressive functions, the tumor cell can directly interact with cancer-specific T cells and quell their cytolytic and/or cytokine-driven anti-tumor functions. Finally, reduced surface expression of the apoptotic receptors FAS and TRAIL-RI/II on the tumor surface can make the cell much more resistant to these cell death signals, especially when coupled with increased Bcl-2 or Bcl-xL levels or decreased Bim levels, together allowing the tumor to survive, evade, suppress, and even extinguish the anti-tumor response.

Figure 3: A Model of Immunoediting in Tumor Progression

Tumor Progression Immunoediting

Related Products:

  1. Human Apoptosis Array C1/G1
    (detecting Bad, Bax, Bcl-2, Bid, Bim, Casp-3, Casp-8, and Cytochrome C)
  2. Human Angiogenesis Array Q1/Q2/Q3
    (detecting : Angiogenin, Angiopoietin 2, TGF-β, and PLGF)
  3. Human Growth Factor Array Q1
    (detecting SCF, VEGF-D, M-SCF and HGH)
  4. Human Chemokine Array C1/G1
    (detecting MIP-1α, CXCL9 and CXCL10)
  5. Human MMP Array C1
    (detecting MMP-1, -2, -3, -8, -9, -10, -13, and TIMP-1, -2, and TIMP-5)
  6. Mouse Angiogenesis Array C1/G1
    (detecting M-CSF, G-CSF, GM-CSF, SDF-1α and IL-12)
  7. Mouse Cytokine Array C4/G4
    (detecting bFGF, MMP2, MMP3, VEGF, IGF-1 and IGF-2)
  8. Mouse Cytokine Array Q3000
    (detecting 160 targets including: IGF-1, IGFBP-2, VEGF-A, PLGF-2, HGF, IL-1α, IL-6, and IL-10)

View Larger Image

Normal cells may become nascent tumors by evading tumor suppression after carcinogenic mutation and/or apoptosis that would normally result from gross chromosomal changes. Pro-inflammatory and pro-angiogenic factors can help to establish blood supply for the growing nascent tumor. Activation of the adaptive or native immune response can eliminate the nascent tumor, the tumor may remain in equilibrium as an occult tumor, or the tumor may escape immunosurveillance to create a viable tumor-supportive microenvironment. Innate and adaptive immune responses may still work to eliminate the tumor via immunosurveillance. Tumors may also metastasize to move to another location; this may be an additional mechanism of avoiding immunosurveillance by evacuation of the “hostile” TME. Green color denotes processes potentially leading to tumor eradication, while red color means promoting tumor escape and progression.

Tumor Recruitment of Accomplices

Immunoediting of cytokine signals provides another array of pathways which tumors utilize to evade and potentially escape from immunological targeting (Figure 4). Briefly, TGF-β, VEGF, angiogenic chemokines, and T helper 2 polarizing cytokines form a nexus of signals that promote tumorigenesis in certain settings. While TGF-β may indeed induce cell cycle arrest, it has many different effects within the tumor microenvironment (TME). Primed CD8 T cells receiving TGF-β signaling can block priming into fully mature CTLs, and also drive the differentiation of CD4 T cells towards a tumor-supporting T-helper 2 phenotype (Th2) or regulatory T cell poptulation (Treg), rather than a more anti-tumor Th1 phenotype. This CD4 Th2 phenotype is characterized mainly by expression of IL-4, IL-5, IL-6 and IL-10, opposite the inflammatory and anti-tumor phenotype of Th1 CD4 T cells expressing IFN-γ, TNF-α, and IL-2. Th2 polarization within the TME is further promoted by the expression of IL-10, TGF-β, and VEGF, which facilitates recruitment and differentiation of myeloid-derived suppressor cells (MDSCs), a myeloid progenitor elevated in virtually all experimental malignancies. MDSCs promote the TME in response to TGF-β signaling by expressing multiple angiogenic chemokines including CXCL-1, -2,-3, -5, -8, and -12 (amongst others), helping provide continued sustenance to the growing tumor. Increased TGF-β signaling, resulting in the conversion of CD4 T cells into a Treg poplation may promote further immunosuppressive functions, though their potential role(s) in tumorigenesis remains to be determined. VEGF is an additional pleiotropic cytokine produced inside the TME, and possesses potent immunosuppressive, inflammatory and proangiogenic capacities. The hypoxic nature of the TME results in increased HIF-1α expression which leads to increased inflammatory conditions characterized by TNFα, IL-6, and IL-8. Conveniently, these same inflammatory factors promote elevated levels of VEGF, resulting in a feedback loop of VEGF signaling, further promoting a favorable TME. VEGF is also a chemoattractant for Mφs, and with other signals surrounding the TME, these Mφs are often further primed into the MDSC population, which feeds back to promotes the immunosuppressive nature of the TME, and facilitates tumor immunosurveillance evasion.

Figure 4: Cooperativity of Cancer-Promoting Immune Cells in the TME

Cooperativity of Cancer-Promoting Immune Cells in the TME

Related Products:

  1. Human Growth Factor Array Q1
    (detecting TGF-β1, TGF-β2, TGF-β3, VEGF-A, VEGF-B and VEGF-C)
  2. Human Cytokine Array Q4000
    (detecting CD40L, CD30, Axl, IL-4, IL-10)
  3. Human Chemokine Array Q1
    (detecting MIF, Lymphotactin, 6Ckine, TSLP, and TARC)
  4. Human Angiogenesis Arrays
    (detecting Angiogenin, Thrombopoietin, TGF-β, and PLGF)
  5. Human Cytokine Array C2000
    (detecting 174 cytokines: Angiogenin, Axl, IGFBP and PDGF family members, Eotaxin, MIF, and several interleukins)
  6. Human MMP Array Q1
    (detecting MMP-1, -2, -3, -8, -9, -10, -13, and TIMP-1, -2, and TIMP-5)
  7. Mouse Cytokine Array C1000/G1000
    (detecting bFGF, MMP2, MMP3, IL-6, IL-10, IL-1α, VEGF, IGF-1 and IGF-2)
  8. Mouse Cytokine Array Q4000
    (detecting 200 targets including: MMP2, MMP3, MMP10, Flt3L, VEGF, IL4, IL-10, IL-6, CD40, CD40L, and TNF-α)

View Larger Image

In the TME, a positive feedback loop of cytokine signals that proceeds as follows: First, TGF-β, COX2, PGE2, Th2- associated inflammatory factors and proangiogenic proteins are secreted by cancer cells, CAFs and other cell types in the nascent tumor recruit Th2 lymphocytes, M2 macrophages (TAMs) andN2 neutrophils (TANs). Then, Th2 lymphocytes, TAMs and TANs secrete additional inflammatory and proangiogenic proteins that suppress maturation of DCs and proliferation and activation of cytotoxic cells. As a result, antigen presentation and cytotoxic activities plummet, practically eliminating immunosurveillance in the tumor milieu. Additionally, B cells proliferate, but are not activated, turning them into tumor-promoting BREGs. M2macrophages recruit MDSCs to the TME, further reinforcing the positive feedback loop of Th2, M2, and N2 proliferation and activation, resulting in substantial increases in tumor-promoting inflammation and concomitant angiogenesis.

Antibody Microarrays for Cancer Biomarker Discovery

Interrogation of the tumor environment’s niche of cell signals, growth factors, and cytokines, as well as the TME recruitment of accessory cell population and their cytokines, requires a global view of all these factors together. While a piecemeal approach may prove effective if the hypothesis is sufficiently narrow, a broad view of cancer will be needed for biomarker discovery and diagnostics moving forward. We believe that a type of “immunoscoring” may be warranted, whereby we can monitor the changes in a patient’s immune response, either globally or within the TME, as a routine measure of efficacy, prognosis, or disease state for cancer patients. Such a score would be heavily facilitated by the use of antibody microarrays which allow for upwards of 1000 proteins to be measured from any sample. The multiplex platform may reveal new cytokine interactions, define new complex growth factor pathways or angiogenesis mechanisms that could help open the doors to new techniques or strategies in battling this worldwide… for lack of a better word… cancer.

How Can RayBiotech Help You?

RayBiotech’s antibody array platforms and ELISAs afford you the opportunity to view the complex TME and interrogate TME-specific cytokine evasion strategies, cancer accomplice cell populations, and TME-specific signaling. The RayBio® C-Series and G-Series Arrays can semi-quantitatively detect up to 274 targets, while our Quantibody® platform can quantify up to 400 proteins targets simultaneously. Our arrays use antibody pairs against human, rhesus, mouse, rat, porcine, bovine, feline, canine, and equine cytokines. All of the aforementioned products utilize the sandwich-based ELISA technique.

Not enough targets? Consider then our L-Series Arrays, which feature a direct sample labeling technique. The L-Series allows detection of your labeled samples with single antibodies rather than a pair, allowing a much broader panel of targets to be included within 1 array. Detect up to 1000 Human proteins, 308 Mouse proteins, or 90 Rat proteins in a single sample. Additionally, we can print antibodies YOU request that are not in our current library, allowing an even more expansive array specific to your interests.

Is that too many, or do our arrays not contain some targets you are interested in? Customize it! You tell us your targets of interest, and RayBiotech will provide you with a customized array (utilizing available antibodies of your choosing).

Maybe instead you are interested in protein:protein interactions? Consider our Protein Arrays which contain up to 487 recombinant Human proteins (or 176 Mouse proteins) to capture protein interactions you are interested in.

Aren’t sure what you need, what we have, or what we are capable of? Just call us! 1-888-494-8555. You can also email us at We are more than happy to help you discover more.

Finding Improved Markers of Acute Kidney Injury

Finding Improved Markers of Acute Kidney Injury

In the January 2014 Issue of Clinical Laboratory News, published by the AACC (American Association for Clinical Chemistry), one of the cover stories was The Search for Improved Markers of Acute Kidney Injury.

KidneyThe article’s main points are that:

  1. The current markers used to assess acute kidney injury (AKI), creatinine and total urinary protein, are inadequate;
  2. AKI is a risk factor for chronic kidney disease (CKD); and
  3. Monitoring changes in recently identified urinary AKI biomarkers seem to be more appropriate for detecting early signs of AKI.

The latter is easily achieved by using RayBiotech’s Acute Kidney Injury Panels for Human and Rat or Custom Quantibody Arrays

Problems with Previous AKI Markers

Detection of creatinine in urine and in blood has been a diagnostic tool of medicine for more than 100 years. Urinary creatinine levels are used to determine the estimated glomerular filtration rate (eGFR), a measure of kidney function. Although creatinine is useful to determine the magnitude of AKI, it is neither sensitive enough as an early indicator of AKI, nor useful in determining the underlying cause(s) of kidney injury. Also, it is less accurate for patients with low muscle mass and is subject to dietary changes and abnormalities. Moreover, there is sometimes a delay in the appearance of increased urinary creatinine following AKI.

Elevated protein content in urine (or proteinuria) is considered a sensitive marker of kidney injury and is a good marker for monitoring recovery in patients with AKI and CKD. However, it is not very specific and gives little information as to the source or mechanism of kidney injury. Urinary protein levels can increase due to the use of some non-steroidal anti-inflammatory medications, as well as due to the presence of cancers, lupus or rheumatoid arthritis.

Promising New Biomarkers

Several putative urinary biomarkers have been proposed for AKI, including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1) and liver-type fatty acid-binding protein (L-FABP) [1,2]. ). Of these, KIM-1 and NGAL appear to hold the most promise as early AKI biomarkers in clinical applications.

KIM-1 (also known as TIM-1) is a transmembrane tubular protein that is a promising early-stage urinary biomarker of AKI. KIM-1 is extremely attractive as an early marker of AKI, as its expression is undetectable at the gene or protein level in normal kidneys but is rapidly and highly up-regulated in ischemic kidneys and AKI induced by toxins [3,4].

NGAL levels in urine also rise rapidly (within 2–4 hours) following AKI [5], and elevated levels of NGAL may be an independent risk factor for CKD patients [6]. Thus, urinary NGAL levels may help to identity CKD patients that are most likely to experience further deterioration of kidney function. Detection of circulating NGAL has also been suggested as a potential early marker of AKI [7,8].

L-FABP is also excreted rapidly in urine (within 4 hours) and was identified as an independent risk factor for AKI among cardiac bypass surgery patients [9]. Moreover, preoperative levels of urinary L-FABP may be a predictor of potential risk for AKI resulting from cardiac bypass surgery [10].

Need for More Research & Development for Markers of AKI and CKD

The article on kidney injury biomarkers in Clinical Laboratory News underscores the fact that, despite the promise of these markers in detecting AKI, more research is needed. The most obvious reason is that most of these studies of early biomarkers for AKI have been done in relatively small numbers of patients and need to be validated in larger patient populations. Second, many of these studies have considered these putative urinary biomarkers individually, not in combination with other putative markers, which may improve their diagnostic and prognostic capabilities. Also, many of these studies have been done with frozen urine that has been well-stored under tightly controlled conditions… conditions that may be different from the fresh urine used in typical clinical labs that may be held at room temperature (or varying temperatures during transit) for hours before testing.

Importantly, there is mounting evidence that the connection between AKI and the risk of future deterioration of kidney function, manifesting as CKD, may be tighter than previously thought [See also Venkatachalam, et al. Am J Physiol Renal Physiol. 2010;298:F1078-F1094.]. However, the mechanisms and potential biomarkers for the role of the natural history of AKI in CKD have yet to be explored in any detail. Therefore, some investigators have called for studies involving long-term follow-up of AKI patients [11].

Additionally, there is growing realization that CKD may be a major contributing factor in cardiovascular diseases (CVD). As such, finding predictive and prognostic biomarkers of transitions from AKI to CKD and CKD to CVD are unmet needs in clinical applications of urinary and serum/plasma biomarkers for kidney disease.

Tools for Detection of AKI Biomarkers in Urine and Blood

Investigation of other NGAL, KIM-1, L-FABP and other markers potentially useful as early markers of AKI have become a high priority for the US FDA and the European Medicines Agency [12,13]. Additional next-generation biomarkers that have been identified for early AKI include urinary and/or plasma levels of Cystatin C [14], Albumin [15,16], Clusterin [17,18], Trefoil Factor 3 [16], beta-2-microglobulin [18], and Osteopontin [19].

RayBiotech’s Acute Kidney Injury Arrays for Human detect all of the markers mentioned above. These are available as C-Series (membranes), which use chemiluminescent detection, like a Western Blot, G-Series (glass slides), which use fluorescence scanning, like a gene microarray. RayBiotech also has similar arrays for detecting AKI in Rats.

In addition, RayBiotech’s Custom Quantibody Arrays (quantitatitive multiplex ELISA on glass slide), which may be customized to detect the markers of your choice in urine, serum or plasma.

To Order or Receive Technical Assistance with RayBiotech’s Products:
In the U.S. and Canada, call 1-888-494-8555 or contact us at
In other countries worldwide, please visit:

1. Han WK, Wagener G, Zhu Y, Wang S, Lee HT. Urinary biomarkers in the early detection of acute kidney injury after cardiac surgery. CJASN. 2009;4(5):873–882. doi:10.2215/CJN.04810908. [link]
2. Devarajan P. Biomarkers for the early detection of acute kidney injury. Curr Opin Pediatr. 2011;23(2):194–200. doi:10.1097/MOP.0b013e328343f4dd. [link]
3. Han WK, Bailly V, Abichandani R, Rhadhani R, Bonventre JV. Kidney injury molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury. Kidney Int. 2002;62(1):237–244. doi:10.1046/j.1523-1755.2002.00433.x. [link]
4. Bonventre JV. Kidney injury molecule-1 (KIM-1): a urinary biomarker and much more. Nephrol Dial Transplant. 2009;24(11):3265–3268. doi:10.1093/ndt/gfp010. [link]
5. Bennett M, Dent CL, Ma Q, Dastrala S, Grenier F, et al. Urine NGAL predicts severity of acute kidney injury after cardiac surgery: a prospective study. CJASN. 2008;3(3):665–673. doi: 10.2215/​CJN.04010907. [link]
6. Liu KD, Yang W, Anderson AH, Feldman HI, Demirjian S, et al. Urine neutrophil gelatinase–associated lipocalin levels do not improve risk prediction of progressive chronic kidney disease. Kidney Int. 2013;83:909–914. doi:10.1038/ki.2012.458. [link]
7. Constantin JM, Futier E, Perbet S, Roszyk L, Lautrette A, et al. Plasma neutrophil gelatinase-associated lipocalin is an early marker of acute kidney injury in adult critically ill patients: A prospective study. J Crit Care. 2010;25(1):e1–176.e6. doi:10.1016/j.jcrc.2009.05.010. [link]
8. Cruz DN, de Cal M, Garzotto F, Perazella MA, Lentini P, et al. Plasma neutrophil gelatinase-associated lipocalin is an early biomarker for acute kidney injury in an adult ICU population. J Intensive Care Med. 2010;36(3):444–451. doi:10.1007/s00134-009-1711-1. [link]
9. Portilla D, Dent C, Sugaya T, Nagothu KK, Kundi I, et al. Liver fatty acid-binding protein as a biomarker of acute kidney injury after cardiac surgery. Kidney Int. 2008;73:465–472. doi:10.1038/ [link]
10. Matsui K, Kamijo-Ikemori A, Sugaya T, Yasuda T, Kimura K. Usefulness of urinary biomarkers in early detection of acute kidney injury after cardiac surgery in adults. Circulation J. 2012;76(1):213–220. doi:10.1253/circj.CJ-11-0342. [link]
12. Schiff H, Lang SM, Fischer R. Long-term outcomes of survivors of ICU acute kidney injury requiring renal replacement therapy: a 10-year prospective cohort study. Clin Kidney J. 2012;5(4):297–302. doi:10.1093/ckj/sfs070. [link]
12. Carlson TH, Sethi AA. A kidney injury biomarker initiative: biomarker research holds the potential for developing new, more accurate and powerful IVDs. IVD Technology. May 18, 2011. Last accessed: February 6, 2014.
13. Bonventre JV, Vaidya VS, Schmouder R, Feig P, Dieterle F. Next-generation biomarkers for detecting kidney toxicity. Nat Biotechnol. 2010;28(5):426–440. doi:10.1038/nbt0510-436. [link]
14. Koyner JL, Bennett MR, Worcester EM, Ma Q, Raman J, et al. Urinary cystatin C as an early biomarker of acute kidney injury following adult cardiothoracic surgery. Kidney Int. 2008;74:1059–1069. doi:10.1038/ki.2008.341. [link].
15. Bolisetty S, Agarwal A. Urine albumin as a biomarker in acute kidney injury. Am J Physiol Renal Physiol. 2011;300(3):F626–F627. doi:10.1152/ajprenal.00004.2011. [link].
16. Yu Y, Jin H, Holder D, Ozer JS, Villarreal S, et al. Urinary biomarkers trefoil factor 3 and albumin enable early detection of kidney tubular injury. Nat Biotechnol. 2010;28:470–477. doi:10.1038/nbt.1624. [link].
17. Vinken P, Starcks S, Barale-Thomas A, Sonee M, et al. Tissue Kim-1 and urinary clusterin as early indicators of cisplatin-induced acute kidney injury in rats. Toxicol Pathol. 2012;40(7):1049–1062. doi:10.1177/0192623312444765. [link].
18. Dieterle F, Perentes E, Cordier A, Roth ER, Verdes P, et al. Urinary clusterin, cystatin C, beta-2-microglobulin and total protein as markers to detect drug-induced kidney injury. Nat Biotechnol. 2010;28:463–469. doi:10.1038/nbt.1622. [link].
19. Lorenzen JM, Hafer C, Faulhaber–Walter R, Kümpers P, et al.Osteopontin predicts survival in critically ill patients with acute kidney injury. Nephrol Dial Transplant. 2011;26(2):531–537. doi:10.1093/ndt/gfq498. [link].

Rapid ELISA-Based Measurement of Protein Phosphorylation

Immunoblotting is frequently used for immunodetection of phosphoproteins, in some cases following immunoprecipitation of the cellular extract. The signals from each probe can then be compared and phospho-specific fractions visually assessed or quantified by densitometry. However, the time and effort required in these protocols has driven many researchers to seek out ELISA-based methods, which offer a faster, higher throughput alternative.

In this article, we present a study in which the phosphorylation of two proteins, STAT1 (Tyr701) and Mek1 (Ser217/221), is detected in response to various agonists. Data from the RayBio Phosphorylation ELISA kits will be compared to traditional immunoblotting.


The detection of the phosphorylation of a specific protein is usually accomplished by immunological methods, in which the researcher can measure the fraction of phosphorylated target protein relative to total levels of expressed target protein in the cell. By comparing the phosphorylated fractions in cellular extracts under various experimental conditions, one can identify to what degree and what condition activates or blocks an important signaling pathway. This approach requires the use of a phospho-specific antibody in parallel with a “loading control” to assess relative levels of total cellular protein. Typically, the loading control may be incorporated by using either the corresponding “pan”
antibody (recognizing the target protein in both its phosphorylated and non-phosphorylated states), or alternatively an antibody against a “housekeeping” protein such as β-actin or GAPDH. The signals from each antibody can then be compared between samples. This methodology has largely replaced the classical, laborious techniques of directly radiolabeling phosphoproteins with 32P-orthophosphate, followed by SDS-PAGE gel separation and subsequent autoradiographic analysis.

Assay Format, Procedure and Application

RayBio Phosphorylation ELISA kits contain antibodies for both phosphorylated and total protein (loading control) detection in parallel. Each kit includes a positive control, which is a cell lysate specially prepared to produce a strong phospho-positive signal. The positive control is intended to be used as a reference sample rather than an actual calibration standard, and it’s inclusion in the assay protocol is optional.

In a single microplate, up to 24 different samples may be simultaneously tested in duplicate (including positive controls, if used), producing both phosphorylated and total protein signal outputs. The protocol involves pipetting fresh or thawed lysates into an antibody-coated 96-well microplate, followed by washes and subsequent incubation with anti-phosphorylated antibody or anti-pan antibody. After further washing, an HRP-conjugated secondary antibody is added. Colorimetric detection of captured protein is carried out using TMB substrate solution where blue color intensity develops in proportion to the amount of phosphorylated protein or pan protein bound.

Some researchers may be interested in screening for only phosphorylated protein signals rather than total and phosphorylated in parallel. For this application, each Phosphorylation ELISA kit is also available in “phospho-only” format, containing only a phospho-specific antibody pair. This format allows the researcher to screen more conditions (48 duplicates per plate) for a lower cost compared to the “phospho plus total” readout format.

The assay procedure has minimal hands-on time and hundreds of samples can be assayed by a single technician in one day. Thus, the RayBio Phosphorylation ELISA represents a more rapid and efficient alternative to multi-step phospho-protein detection by immunoblot analysis, which requires a minimum of two days processing time. Below, we present two examples of analyses using the Phosphorylation ELISA kits.

Site-Specific STAT1 Activation

STAT is a transcription factor implicated in programming gene expression for biological events as diverse as embryonic development, programmed cell death, organogenesis, innate immunity, adaptive immunity and cell growth regulation1. In the study presented here, cultured A431 cells (an epidermoid carcinoma cell line) were treated with recombinant human epidermal growth factor (EGF) to induce EGFR-mediated signaling cascades and JAK-STAT signaling. Cell lysates were analyzed by both RayBio Phospho-STAT1 (Tyr701) ELISA (Figure 1A) and traditional immunoblot (Figure 1B). After EGF treatment, a robust and rapid phosphorylation of STAT1 at Tyr701 was observed in parallel with total STAT1 levels by both detection methods (Figure 1). We note that immunoblots were incubated with anti-phospho-STAT1 (Tyr701) and anti-pan STAT1 (the same antibodies used in the RayBio Phosphorylation ELISA kit).

To compare the sensitivity of the ELISA kit to traditional Western blot analysis, EGF-treated A431 cell lysates were serially diluted and assayed by each approach. Both methods exhibited similar sensitivity, with lowest detectable limits well below 1 µg/ml of total lysate protein (Figure 2), concluding that the ELISA kit is equally sensitive as traditional immunoblot, but can be completed inside 6 hours.

Site-Specific Mek1 Activation

Mek1 is a protein kinase that functions in the mitogen-activated protein kinase (MAPK) signaling
cascade, and is involved in the regulation of normal cell proliferation, survival and differentiation. In this study, HeLa cells were treated with tetradecanoylphorbol-13-acetate (TPA), a potent activator of protein kinase-C (PKC) pathways. Cell lysates were analyzed using both RayBio® Phospho-Mek1 (Ser217/221) ELISA, and by immunoblot. After TPA treatment, a robust and rapid phosphorylation of Mek1 was detected in parallel with total Mek1 levels by both methods, concluding that the Phospho-Mek1 (Ser217/221) ELISA has similar sensitivities to the immunoblot method (Figure 3). Immunoblots were incubated with anti-phospho-Mek1 (the same antibodies used in the RayBio Phosphorylation ELISA kit).


RayBio® Phosphorylation ELISA kits are a rapid, sensitive, high-throughput, cost-effective and convenient method for monitoring the activation of important biological pathways in cells or tissues.Unlike immunoblots, which require several days processing to obtain parallel signals for phosphorylated and total target protein, the Raybiotech’s ELISA method achieves comparable sensitivity within 6 hours processing time. Up to 24 different experimental conditions can be simultaneously screened in duplicate on one plate with phosphorylated and total (pan) protein readouts assayed. In this format, several hundred samples can be assayed by a single technician in one day.

Phospho-ELISA_kit_1Figure 1: Detection of relative Phopho-STAT1 levels in A431 Cells following stimulation with Epidermal Growth Factor (EGF). A431 cells were treated with 100 ng/ml recombinant human EGF for 10 minutes. (A) Analysis of cell lysates using Human/Mouse Phospho-STAT1 (Y701) and Total STAT1 ELISA (cat # PEL-STAT1-Y701-002). (B) Immunoblot analysis of lysates using antibodies against phospho-STAT1 and STAT1 (the same antibodies used in the ELISA kit). ***=P<0.001, n=3.


Phospho-ELISA_kit_2Figure 2: Comparative sensitivity of the detection of Phopho-STAT1 levels in A431 Cells following stimulation with Epidermal Growth Factor (EGF) by RayBio Phospho-STAT1 (Tyr701) ELISA and by traditional immunoblot techniques. A431 cells were treated with 100 ng/mL recombinant human EGF for 20 minutes to induce phosphorylation of STAT1. Serial dilutions of lysates were analyzed by (A) RayBio Human/Mouse Phospho-STAT1 (Y701) and Total STAT1 ELISA (cat # PEL-STAT1-Y701-002) and (B) by immunoblot. Immunoblots were incubated with anti-phospho-STAT1 (the same antibody used in the ELISA kit).

Phospho-ELISA_kit_3Figure 3: Detection of relative Phospho-Mek levels in HeLa Cells following stimulation with TPA. HeLa cells were treated with TPA for 15 minutes. Cell lysates were analyzed using (A) Human/Mouse/Rat Phospho-Mek (S217/S221) & Total Mek ELISA (cat # PEL-MEK-S217-002) and (B) by immunoblot. Immunoblots were incubated with anti-Mek1 or anti-phospho-Mek1 (the same antibodies used in the ELISA kit). *=P<0.05, n=3.


RayBio® Phosphorylation ELISA is a rapid, convenient and sensitive sandwich ELISA for the in vitro measurement of key signaling pathway phosphoproteins in cell or tissue extracts. Over 20 different kits are available for well-studied pathway molecules such as EGFR, Akt, Erk1/2, p38 alpha, Mek1, STAT1, STAT3, and Met. RayBio Phosphorylation ELISA also features site-specific phospho-antibodies which can detect a single phosphorylated residue (for example, Tyr1086 of EGFR). This method is an improvement on traditional labor-intensive immunoblotting protocols that require 2-3 days of processing time.

1. Horvath, CM. STAT proteins and transcriptional responses to extracellular signals. Trends Biochem Sci 25(10), 496-502 (2000).
2. Roberts PJ, Der CJ. Targeting the Raf-MEK-ERK mitogen-activated protein kinase cascade for the treatment of cancer. Oncogene 26, 3291–3310 (2007).

To Order or Receive Technical Assistance
In the U.S. and Canada, call 1-888-494-8555 or contact us at
In other countries worldwide, please visit:

Preparing cell or tissue lysates for ELISA Kits

ELISA_kit_6RayBiotech manufactures over 1,000 high fully validated, GMP-compliant ELISA kits.  In this blog post we explain how to prepare cell or tissue lysates for ELISA Kits.


Preparing cell or tissue lysates for ELISA Kits

Cell or tissue lysates for use with RayBio® ELISA kits can be prepared using most conventional methods, e.g. homogenization of cell or tissue in RayBio® Lysis Buffer.  You may also use your own lysis buffer, such as RIPA or other formulations optimized for immunoprecipitation.

Please note the following guidelines on lysis buffer composition:

  1. Avoid using >0.1% SDS or other strongly denaturing detergents. In general, non-ionic detergents such as Triton X-100 or NP-40 are best, although zwitterionic detergents such as CHAPS, or mild ionic detergents such as sodium deoxycholate will work.
  2. Use no more than 2% v/v total detergent
  3. Avoid the use of sodium azide
  4. Avoid using >10 mM reducing agents, such as dithiothreitol or mercaptoethanols

We strongly recommend adding a protease inhibitor cocktail to the lysis buffer prior to homogenization. Most general biochemical supply companies including Roche, Sigma-Aldrich, Pierce, and Calbiochem stock a wide variety of these products. Since susceptibility to proteolytic cleavage and the type of proteases present in the lysate vary, we do not recommend a specific product.  Instead, your choice of which combination of protease inhibitors to use should be based upon a literature search for your protein(s) of interest and/or tissue or cell type.  Phosphatase inhibitors may be used but are not necessary unless the antibodies used in the kit specifically recognize phosphorylated forms of the protein.

Choices of the method for lysis and homogenization include glass-bead “smash,” douncing, freeze-thaw, sonication and crushing frozen tissue with a mortar and pestle, or even a combination of these. There is no best method for all sample types; your choice of method should be made following a brief search of the literature to see how samples similar to yours have been prepared in previous investigations.

After homogenization, centrifuge the lysates to remove cell/tissue debris (5 min @ 10,000 x g or 10 min @ 5,000 x g) and save the supernatant. Unless testing fresh, lysates should be frozen as soon as possible and stored at -20°C (or -80°C, if possible). Centrifuge them again before incubating with any immunoassay. Next, determine the protein concentration of your lysates using a total protein assay not inhibited by detergents (such as the Bicinchoninic acid (BCA) assay) and normalize the volume of each sample used to deliver the same amount of total protein for each assay.

Note: The Bradford assay is not recommended as it can be inhibited by the presence of detergents. 

Since different cells and tissues may contain different amounts of protein, as starting point, we suggest using 500 µL of lysis buffer per 1×106 cells or 10 mg tissue. You may have to adjust this based upon your results. Your target total protein concentration of the homogenate should be at least 1,000 µg/mL, but 2,000 µg/mL or more would be better.

Regardless of the sample type you have, it is strongly recommended that you sub-aliquot all samples after preparation to minimize protein degradation from multiple freeze-thaw cycles.  This also ensures availability of sample for further experiments.

For more information about our ELISA Kits and sample preparation, visit

Search ELISAs

How to Prepare Urine Samples for ELISA Kits

ELISA KitRayBiotech manufactures over 1,000 high fully validated, GMP-compliant ELISA kits.  In this blog post we explain how to prepare urine samples for ELISA Kits.


Preparing urine samples for ELISA Kits

1.   Collect urine without adding stabilizers.

2.   Centrifuge the samples hard (eg. 10,000 x g for 1 min or 5,000 x g for 2 min).

3.  Aliquot, quick freeze in dry ice/methanol bath, and store at -80°C until use.

 Regardless of the sample type you have, it is strongly recommended that you sub-aliquot all samples after preparation to minimize protein degradation from multiple freeze-thaw cycles.  This also ensures availability of sample for further experiments. 

For more information about our ELISA Kits and sample preparation, visit

ELISA Kits: Preparing plasma and serum samples


RayBiotech manufactures over 1,000 high fully validated, GMP-compliant ELISA kits.  In this blog post we explain how to prepare plasma and serum samples for ELISA Kits.

How to Prepare plasma and serum samples for ELISA Kits

For plasma:

  1. Collect whole blood into an EDTA, Citrate or Sodium heparin tube (e.g. BD vacutainer, Cat # 8001302 or 16852).
  2. Centrifuge 10 minutes at 3,000 rpm
  3. Aliquot into small tubes and store at -80°C until use.

For serum:

  1. Collect whole blood into a tube without additives (e.g. BD vacutainer, Cat # 8002527).
  2. Keep at room temperature for 20 minutes.
  3. Centrifuge 10 minutes at 3,000 rpm.
  4. Aliquot into small tubes and store at -80°C until use.

 Regardless of the sample type you have, it is strongly recommended that you sub-aliquot all samples after preparation to minimize protein degradation from multiple freeze-thaw cycles.  This also ensures availability of sample for further experiments. 

For more information about our ELISA Kits and sample preparation, visit

ELISA Kits: Preparing Conditioned Media Samples


RayBiotech manufactures over 1,000 high quality, rigorously tested ELISA kits.  In this blog post we explain how to prepare conditioned media samples for your ELISA Kit.

How to Prepare Conditioned Media Samples

We recommend preparing serum-free or low-serum medium samples, as serum tends to contain cytokines which may produce significant background signals. If it is necessary to test serum containing medium, we recommend also running an uncultured media blank to assess baseline signals. This baseline can then be subtracted from the cultured media sample data.

  • On day 0, seed ~1 million cells in 100 mm tissue culture plate with complete medium.*
  • On day 3, remove medium and replace medium with 6-8 ml of serum-free or low serum containing medium (e.g. medium containing 0.2% calf serum).
  • On day 5, collect medium into 15 ml tube. Centrifuge at 2,000 rpm in centrifuge at 4ºC for 10 minutes. Save the supernatant. Transfer the supernatant into 1.5 ml Eppendorf tubes. Store supernatant at -80ºC until experiment. Most samples can be stored this way for at least a year.

*The optimal number of seeded cells varies from one cell type to another and may need to be empirically determined.

Note: In case follow-up experiments are needed, it is strongly recommended to sub-aliquot all samples after preparation to minimize cytokine degradation from multiple freeze-thaw cycles. 

For more information about our ELISA Kits and sample preparation, visit