Remodeling of the Tumor Extracellular Matrix Activates YAP in Fibroblasts to Produce Cancer Associated Fibroblasts

When cells undergo transformation and initiate the formation of a solid tumor mass, they cause profound changes on the phenotypes of the cells that surround them1. However, in addition to the changes in cellular phenotype, there is a change in the extracellular matrix that coincides with tumor formation1. It has been demonstrated that the majority of solid tumors have increased stiffness in their extracellular matrix (ECM), which may lead to increased activation of pro-tumor signaling pathways, such as Src, FAK, and RhoA2-4. Recently, it was discovered that increased matrix stiffness may also lead to increased activity of the oncogenic YAP/TAZ complex, which is connected to the Hippo signaling pathways, transcriptional regulators that increase cellular proliferation, decreased cellular contact inhibition, increased cancer stem cell phenotype, and increased metastasis5. However, in a fibroblastrecent edition of Nature Cell Biology Calvo et al. demonstrated that 6.  Not only do the authors demonstrate that YAP/TAZ is active in CAFs, but YAP/TAZ is necessary for CAF development6. They show that CAF activation leads to matrix remodeling towards increased stiffness, via myosin light chain 2 (MYL9/MLC) expression, establishing a feed-forward loop where the ECM plays a vital role6.

The authors first isolated fibroblasts in different stages towards becoming a CAF and saw that both mechanical-responsive signaling machinery (SMA, FN1, Paxillin, MYL9, MYH10, DIAH1 & F-actin) and mechanical tension were increased in populations containing CAFs. Moreover, tumor cell invasion, and angiogenesis of the tumor microenvironment (shown via endomucin and second-harmonic microscopy) were increased in samples that contained more tumor-associated-like fibroblasts (indicated by vimentin)6.

Because of the role of cell-cell and cell-ECM contact in the Hippo signaling pathway, the authors sought to understand whether this pathway is activated in CAFs. They found that YAP, and its co-factor, TAZ to be only upregulated and co-localized in the nucleus of transformed fibroblasts; the target of the activated YAP-TAZ complex6.  Furthermore, upon depletion of YAP, the ability for CAFs to cause matrix stiffness by contraction lessened as well as CAFs ability to form collagen networks and facilitate angiogenesis. Interestingly, when TAZ was inhibited, there was no change in functionality, which may lead to a TAZ-independent function for YAP.

Upon microarray analysis of CAFs treated with siRNA that targets YAP, Calvo et al. found that the expression of many of the genes involved in mechanosensing and motility to be diminished6. Furthermore, when these individual genes were silenced, there was an overall decrease in the amount of cellular invasion of tumors. Many of the YAP-mediated genes, such as ANLN and DIAPH3, were involved in matrix remodeling and cellular invasion. Interestingly, modification of only one protein overexpression resulted in high amounts of matrix-remodeling and invasion: myosin regulatory light polypeptide 9 (MYL9). While not transcriptionally controlled by the YAP/TAZ complex, the authors demonstrate that YAP/TAZ is able to control MYL9 by post-translational modifications, placing YAP as a critical factor in regulating matrix-remodeling and invasion through MYL96.

Calvo et al. next posited that YAP/TAZ activation may not be exclusive to CAFs, but may also occur in normal fibroblasts when placed in a cancerous environment6. They found that fibroblasts placed in culture with tumor conditioned media had higher nuclear translocation of YAP, and higher gel contraction (akin to matrix stiffening) comparable to known promoters of pro-contractile function: L-alpha-lysophosphatidic acid (LPA) and transforming growth factor-beta (TGFβ). However, actomyosin inhibition (by blebbistatin) could not be rescued with LPA and TGFβ. Therefore, while soluble factors may activate matrix contraction, a functional cytoskeleton is essential for matrix contraction. Because of the necessary role of the cytoskeleton, the authors tested whether inhibition of RhoA kinase (ROCK), a kinase involved in regulating translocation and structure of the cell by the cytoskeleton, would affect the nuclear localization of YAP6. Inhibition of ROCK decreased YAP nuclearization and decreased the matrix stiffness. Of note, like ROCK inhibition, inhibition of Src also affected the nuclear localization of YAP as well as complex formation with TEAD1 and TEAD4. However, Src modulation of YAP is downstream of cytoskeletal changes in tension since Src inhibition did not affect stress fibers6.

Since activation of YAP in CAFs  is connected to actomycin-mediated matrix stiffness, and this activation of YAP expresses MYL9, and expression of MYL9 results in matrix-remodeling towards stiffness, the authors posit that this pathway forms a feed-forward loop6. This loop could lead to constitutive activation of YAP pathway in CAFs, causing a robust response and stabilizing the CAF phenotype. However, it is not known what other mechanisms, as well as regulatory mechanisms of YAP, are involved in this process as well as whether the YAP-ECM tension pathway may play a regulatory role in normal fibroblasts.

References:

1. Boudreau, A., van’t Veer, L. J. & Bissell, M. J. An “elite hacker”: breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity. Cell adhesion & migration 6, 236-248, doi:10.4161/cam.20880 (2012).

2. Levental, K. R. et al. Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891-906, doi:10.1016/j.cell.2009.10.027 (2009).

3. Guilluy, C. et al. The Rho GEFs LARG and GEF-H1 regulate the mechanical response to force on integrins. Nature cell biology 13, 722-727, doi:10.1038/ncb2254 (2011).

4. Sawada, Y. et al. Force sensing by mechanical extension of the Src family kinase substrate p130Cas. Cell 127, 1015-1026, doi:10.1016/j.cell.2006.09.044 (2006).

5. Harvey, K. F., Zhang, X. & Thomas, D. M. The Hippo pathway and human cancer. Nature reviews. Cancer 13, 246-257, doi:10.1038/nrc3458 (2013).

6. Calvo, F. et al. Mechanotransduction and YAP-dependent matrix remodelling is required for the generation and maintenance of cancer-associated fibroblasts. Nature cell biology 15, 637-646, doi:10.1038/ncb2756 (2013).

 

Upcoming Immunology Conferences: October – December, 2013

I previously posted on Immunology Conferences: July – September, 2013 and 2013 Conferences in Tumor Immunology and Cancer ImmunotherapyThis post lists upcoming Immunology-related conferences from October – December, 2013.

conferencesOctober
Aegean Conference: 6th International Conference on Autoimmunity: Mechanisms & Novel Treatments

October 2 – 7, 2013.

Corfu, Greece

Early registration deadline: July 25, 2013.

Abstract submission deadline: July 25, 2013.

Travel award application deadline: June 30, 2013.

 

IL-1-mediated inflammation and diabetes: From basic science to clinical applications

October 10 – 11, 2013.

Nijmegen, The Netherlands

Abstract submission deadline: August 1, 2013.

 

European Macrophage & Dendritic Cell Society Meeting: Myeloid Cells: Microenvironment, Microorganisms & Metabolism From Basic Science to Clinical Applications

October 10 – 12, 2013.

Erlangen, Germany

 

13th International Workshop on Langerhans Cells

October 10-13, 2013

Royal Tropical Institute, Amsterdam, The Netherlands

Early Registration deadline: August 1, 2013.

Abstract submission deadline: August 19, 2013.

 

The International Symposium on Immunotherapy

October 11-12, 2013

London, UK

Early Registration deadline: August 9, 2013.

Abstract submission deadline: August 9, 2013.

 

46th Annual Meeting of the Society for Leukocyte Biology

October 20-22, 2013

Newport Marriott, Newport, RI, USA

Late Breaking Abstract submission deadline: August 6, 2013.

Online Registration deadline: October 7, 2013.

 

16th Annual New York State Immunology Conference

October 20-23, 2013

Sagamore Resort and Conference Center, Bolton Landing, NY, USA

Abstract submission deadline: July 31, 2013.

Registration deadline: September 6, 2013.

 

Cold Spring Harbor Asia Conference: Tumour Immunology and Immunotherapy

October 28 – November 1, 2013.

Suzhou, China

Abstract submission deadline: August 16, 2013.

Early Registration deadline: August 16, 2013.

 

Keystone Symposium: Advancing Vaccines in the Genomics Era

October 31 – November 4, 2013.

Rio de Janeiro, Brazil

Abstract Deadline: July 30, 2013.

Early Registration Deadline: August 29, 2013.

 

November

The Lancet and Cell: What Will it Take to Achieve an AIDS-free World?

November 3–5, 2013.

San Francisco, California, USA.

Abstract submission deadline: July 26, 2013.

Early Registration Deadline: September 13, 2013.

 

International Primary Immunodeficiencies Congress

November 7–8, 2013.

Lisbon, Portugal

Early Registration deadline: July 19, 2013.

 

Asia Pacific Congress of Allergy, Asthma and Clinical Immunology

November 14–17, 2013.

Taipei City, Taiwan

Abstract Submission Deadline: July 31, 2013.

Early Registration: August 30, 2013.

Registration Deadline: October 25, 2013.

 

Cold Spring Harbor Asia Conference: Bacterial Infection and Host Defence

November 18–22, 2013.

Suzhou, China

Abstract submission deadline: September 6, 2013.

Early Registration Deadline: September 6, 2013.

 

6th Autoimmunity Congress Asia

November 20–22, 2013.

Hong Kong

Abstract Submission Deadline: July 20, 2013.

Early Registration deadline: August 6, 2013.

 

Harnessing Immunity to Prevent and Treat Disease

November 20–23, 2013.

Cold Spring Harbor Laboratory, New York, USA

Abstract submission deadline: September 6, 2013.

 

11th Annual UC Irvine Immunology Fair
November 21–22, 2013.

Irvine, California, USA

Abstract submission deadline: October 19, 2013.

Poster contest deadline: November 2, 2013.

 

December

EMBO Workshop: Complex Systems in Immunology

December 2–4, 2013.

Biopolis, Singapore

Abstract submission deadline: September 1, 2013.

Registration deadline: September 1, 2013.

 

British Society for Immunology Congress

December 2–5, 2013.

Liverpool, UK

Abstract submission deadline: September 6, 2013.

Early Registration deadline: September 30, 2013.

 

Annual Scientific Meeting of the Australasian Society for Immunology

December 2–5, 2013.

Wellington, New Zealand

Abstract submission deadline: September 1, 2013.

Early Registration deadline: September 1, 2013.

 

UK Primary Immunodeficiency Network Forum

December 6–7, 2013.

Liverpool, UK

Abstract submission deadline: September 6, 2013.

Early Registration deadline: September 30, 2013.

 

2013 American Society for Cell Biology Annual Meeting

December 14-18, 2013

New Orleans, LA, USA

Abstract submission deadline (Minisymposium Talk, ePoster Talk, and/or Poster Presentation): July 30, 2013.

Abstract submission deadline (Poster Presentation Only): September 4, 2013.

Early Registration deadline: October 10, 2013.

 

Websites that list upcoming Conferences & Events in Immunology, Tumor Immunology, and Cancer Immunotherapy:

The American Association of Immunologists (AAI) Meetings and Events Calendar

Nature Reviews Immunology’s list of conferences

Cancer Immunity Journal’s List of Conferences

FASEB Scientific Research Conferences Calendar

Highlight: A silver bullet against bacteria?

The development of multi-resistant bacterial strains is a major medical problem, especially in hospitals. New antibiotics are constantly under development, but the success rate seems to have slowed down in recent years. However, two recent publications suggest that instead of finding novel antibiotics, an alternative strategy could be to increase the sensitivity of the bacteria to the antibiotics already in use.s12sIn the first report [1], the authors demonstrated that silver ions interfered with several metabolic pathways and increased the permeability of the cell membrane, both made the bacteria much more susceptible to antibiotics. The use of silver to combat bacteria is not unprecedented and actually has been used at least since Grecian times to treat wounds and to preserve water. However, with the advent of potent antibiotics in the 1940s their use fell out of favor.

The authors uncovered two independent mechanisms of how silver is beating up bacteria. They studied E. coli a Gram-negative bacteria that is especially difficult to treat with many drugs due to its thick cell wall.

First, when exposed to silver ions the bacteria produced more reactive oxygen species (ROS). ROS are chemically highly reactive molecules that can bind unspecifically to closeby proteins and DNA and thereby irreversibly alter or damage those structures. Small amounts of ROS are constantly produced during several chemical reactions of the normal metabolism, but cell stress in any of its forms can greatly increase their production. The widespread damage that ROS can inflict weakens the cell and if the damage is too severe it can ultimately lead to cell death.

The second mechanism of silver is its ability to affect two metabolic pathways of the bacterial cells. On the one hand, the ability of the bacteria to maintain their iron level was disturbed. On the other hand, the formation of disulfide bonds, which are crucial for the structural integrity and function of many proteins, was affected in the presence of the silver ions. Both of these actions can be understood as severe forms of cell stress.

As a result of the ROS production and the metabolic impairment, the bacterial cell wall became more permeable. This is important as Gram-negative bacteria have a thick extra cell coating that prevents large molecules to enter. Many antibiotics are too big to enter through this bacterial cell wall, but the silver treatment allowed the antibiotic to enter the cells. By gaining access to the cell, the gram-negative bacteria became sensitive to large molecule antibiotics that usually work only with Gram-positive bacteria that lack such a thick cell coating. This finding greatly expands the arsenal of antibiotics that can be used against Gram-negative bacteria.

Importantly, bacteria that were weakened and made permeable by the silver ions became highly susceptible to even low amounts of antibiotics. The authors tested this in vivo with a mouse model of urinary tract infection. When the antibiotic treatment of the infected mice was supplemented with small amounts of silver ions, the silver greatly augmented the efficiency of the antibiotic: 10 fold to up to 1,000 fold. In one experiment, only 10% of the infected mice that were treated with the antibiotic alone survived, but when treated additional with the silver ions 90% survived!

This silver sensitization was also effective with two types of infections that are particular difficult to treat: dormant bacteria that remain inactive during the antibiotic treatment and rebound afterwards, and bacteria that produce slime layers, called biofilms. Biofilms can be visualized as huge amounts of extra coating produced by the bacteria that make them stick to surfaces (e.g. catheters in the clinic) and provides them with an extra shielding against antibiotics.

However, before somebody now starts grinding his silver spoons into his food, the caveat has to be noted that silver has some side effects: it can accumulate in your body, e.g. in the skin and when it is then exposed to sun can turn you into a smurf, quite literally, as the skin turns irreversible blue-grayish. The medical term is ‘Argyria’ and one stunning example is Paul Karason. Although the concentrations of silver used by Morones-Ramirez et al. were much lower, it still shows that the use of silver will likely be very limited in humans.

In a similar vein to the report by Morones-Ramirez et al., another recent study [2] showed that very high doses of vitamin C also could trigger the production of above-mentioned ROS in the bacterium Mycobacterium tuberculosis, the causative agent of tuberculosis. Thereby, vitamin C was able to kill the bacteria, either directly or in concert with antibiotics. Similar to the case above, the efficiency of the antibiotic was greatly increased when applied together with the vitamin C. However, starting to eat now vitamin C in bucket loads might be a bit premature too.

Vitamin C structure
Vitamin C structure

Nonetheless, both reports can be viewed as proof-of-principle studies. In both studies agents that by themselves are rather harmless to bacteria could massively increase their sensitivity towards antibiotics! Having established such potential it is likely that other substances will be described in the near future that are safer and still have this prominent potential to boost the efficiency of antibiotics.

References:

[1] Morones-Ramirez, J. R., Winkler, J. A., Spina, C. S. & Collins, J. J. Silver Enhances Antibiotic Activity Against Gram-Negative Bacteria. Science Translational Medicine 5, 190ra81–190ra81 (2013).

[2] Vilchèze, C., Hartman, T., Weinrick, B. & Jacobs, W. R. Mycobacterium tuberculosis is extraordinarily sensitive to killing by a vitamin C-induced Fenton reaction. Nat Commun 4, 1881 (2013).

A NEW MOLECULAR TARGET FOR BREAST CANCER THERAPY

Over expression of estrogen receptor (ER) has been implicated in over 70% of breast cancers. Thus therapy targeting ER directly or indirectly is the most important modality in the two-thirds of patients with an ER-positive early breast cancer. The mainstay of endocrine therapy targeting ER in postmenopausal women that are currently available includes selective ER modulators such as tamoxifen and raloxifene, and the ‘third-generation’ aromatase inhibitors (AIs), anastrozole, exemestane and letrozole (click here for more information: http://www.cancer.gov/cancertopics/understandingcancer/targetedtherapies/breastcancer_htmlcourse/page2).

Even though endocrine therapy is the most effective treatment for ER-positive metastatic breast cancer, its effectiveness is limited by high rates of innate (intrinsic) and acquired resistance during treatment. Only about 30% of patients with metastatic disease have objective regression of tumor with initial endocrine treatment, while another 20% have prolonged stable disease.Estrogen_Receptor_Positive_Breast_Cancer-3

Even though mutations of ER are rarely reported, other mechanisms such as ER-phosphorylation has been implicated in resistance to tamoxifen.  In addition, several clinical studies suggested potential mechanisms of resistance to endocrine therapy. Some of the mechanisms implicated include loss of ER, loss of progesterone receptor (PR), upregulation of HER-2, and response to sequential endocrine therapy.

Using a high throughput screening, a recent study by Stebbing et al.  identified a regulator of ER-α, Lemur tyrosine kinase 3 (LMTK3), and noted that LMTK3 gene amplification in both circulating free DNA and primary tumors are predictive of resistance to tamoxifen. Using an orthotopic breast cancer model with tamoxifen-resistant breast cancer cells BT474 that overexpress LMTK3, Stebbing and his colleagues noted that tamoxifen treatment along with LMTK3 knock-down resulted in significant inhibition of tumor growth compared to untreated control mice. To evaluate the clinical relevance of this observation, levels of LMTK3 were determined by immunohistochemistry in tumor samples from ER-positive breast cancer patients treated with endocrine therapy. High levels of LMTK3 were observed in non-responders compared to responders suggesting the association of LMTK3 in limiting efficacy of endocrine therapy. To identify genes and signaling pathways affected by LMTK3, a genome-wide gene expression analysis was performed using BT747 cells. One gene whose expression was found to be significantly regulated by LMTK3 was HSPB8 (heat shock 22kD protein 8). Both overexpression of HSPB8 in breast cancer and potential involvement in tamoxifen resistance have been reported by other studies. Taken together, these results suggests that LMTK3 can contribute to tamoxifen resistance.

ER targeted therapy has improved the quality of life and survival of millions of women around the world, however, resistance to therapy continues to be a major problem. Identification of the role LMTK3 in resistance would facilitate to formulate strategies to overcome this problem.

Further Reading:

http://www.cancer.gov/cancertopics/understandingcancer/targetedtherapies/breastcancer_htmlcourse/page2.

Ali S, Coombes RC. Endocrine-responsive breast cancer and strategies for combating resistance. Nat Rev Cancer. 2002;2(2):101-112.

Osborne CK, Schiff R. Mechanisms of endocrine resistance in breast cancer. Annu Rev Med. 2011;62:233-247.

Stebbing J, Filipovic A, Lit LC, et al. LMTK3 is implicated in endocrine resistance via multiple signaling pathways. Oncogene. 2013;32(28):3371-3380.

 

 

Using Mass Spectrometry for Mass T cell Epitope Discovery

Time of Flight Mass Cytometry (CyTOF) is a relatively new multiparametric technology that is far outpacing standard fluorescence-based flow cytometry in the number of parameters that can be simultaneously assessed on a single cell.  In CyTOF, rare transition element isotope-conjugated antibodies are used to label cellular antigens of interest, the magnitude of which is then quantitated by a time of flight mass cytometer, as discussed previously. Previous studies assessing 34 cell surface and intracellular proteins by this technology demonstrated the existence of high dimensional complexity in the heterogeneity of human bone marrow and CD8+ T cell populations.  In a July 2013 article in Nature Biotechonology, Newell et al., move CyTOF and the field of immunology another technological step forward by utilizing CyTOF to measure the frequencies of Rotavirus antigen-specific T cells in human peripheral blood mononuclear cells (PBMCs) and jejunal tissue with peptide-MHC tetramers.

In CyTOF, the theoretical maximum number of simultaneously assessable parameters is 100-200 depending on the instrument.  This vastly outnumbers the assessable parameters of standard fluorescence-based flow cytometry.  To date however, only approximately 40 metal ions have been utilized for antibody labeling, and the development of further metal-chelating technologies is awaited in order to utilize the maximum capacity of the CyTOF instrument.  In the current study, the authors circumvent this limitation by using a “bar-coding” methodology in which a variant combination of three out of ten metal ions are used for labeling each tetramer, allowing for up to 120 different metal combinations.

In this study, the authors sought to identify Rotavirus epitopes recognized by human CD8+ T cells in the context of the MHC class I allele, HLA-A*0201.  To date, only two Rotavirus epitopes recognized by T cells have been identified, and little is known about the phenotypic and functional diversity of antigen-specific T cells for any particular pathogen.  The technical difficulties in proper epitope prediction along with the limited number of cells attainable from human blood samples contribute to these issues.  Thus, this method represents a huge leap forward in the potential to identify significantly more antigen-specific T cell epitopes and to extensively classify these cells functionally.  Using an MHC-prediction algorithm, 77 possible Rotavirus peptides were identified that bound to HLA-A*0201.  An additional 32 positive and negative control tetramers were added for a total of 109 labeled tetramers used to stain each sample simultaneously.  This was further combined with 23-27 metal-chelated antibodies specific for cell surface and intracellular antigens to phenotypically characterize the T cells. A specialized Matlab script was used to analyze the high-dimensional data obtained following mass spectrometry of PBMC and jejunal samples.

On average, CD8 T cell populations specific for two Rotavirus-peptides plus 6-7 peptides from other viruses including influenza, EBV, and CMV, were identified on average across PBMCs from the 17 healthy donors analyzed.  These antigen-specific T cell populations were further phenotypically characterized by expression of surface and intracellular markers.   CD8 T cells specific for six Rotavirus epitopes that included the two previously identified epitopes, were recurrently detected in PBMCs from at least two individuals.  Of these, CD8 cells specific for a Rotavirus peptide from the VP3 protein were most common among healthy donor PBMCs and were phenotypically unique, being of the effector memory subtype compared with a central memory phenotype typical of the T cells specific for the other Rotavirus peptides.  VP3-specific T cells were also uniquely present in jejunal tissue obtained from obese patients that had undergone gastric bypass surgeries.  Thus, this methodology discovered at least 4 new Rotavirus peptides as well as unique characteristics of the different antigen-specific CD8 T cell populations.

In summary, this methodology of combining CyTOF technology with tetramer “bar-coding” paves the way for a vast expansion over fluorescent-based flow cytometry techniques for identifying antigen-specific T cell populations.  As vaccine strategies are an ongoing goal for treatment and prevention of infectious diseases and cancer, it is important to not only identify the peptides that can elicit T cell responses, but also functionally characterize these T cells in order to maximally promote desired immune responses.

Further  Reading:

Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization.  Newell EW, Sigal N, Nair N, Kidd BA, Greenberg HB, Davis MM. Nat Biotechnol. 2013 Jul;31(7):623-9. doi: 10.1038/nbt.2593. Epub 2013 Jun 9.

Cracking the code of human T-cell immunity.  Harvey CJ, Wucherpfennig KW. Nat Biotechnol. 2013 Jul 9;31(7):609-10. doi: 10.1038/nbt.2626.

Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity. 2012 Jan 27;36(1):142-52. doi: 10.1016/j.immuni.2012.01.002.

Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.  Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Science. 2011 May 6;332(6030):687-96. doi: 10.1126/science.1198704.

FIRST TARGETED THERAPEUTIC APPROACH FOR CHRONIC LYMPHOCYTIC LEUKEMIA

Chronic lymphocytic leukemia (CLL) is a slow-growing cancer in which a large number of immature lymphocytes (white blood cells) are found mostly in the blood and bone marrow. It is the most common leukemia in the Western world with incidence rates as high as ~4 per 100,000 individuals in the USA. According to the National Cancer Institute (NCI) it is estimated that in 2013, approximately 15,680 people (9,720 men and 5,960 women) will be diagnosed with CLL and 4,580 men and women will die of CLL. Even though few durable remissions were noted following treatment with chemotherapeutic agents such as chlorambucil, cyclophosphamide, and fludarabine, in the majority of cases these agents are effective for palliation but do not improve survival. An alternative treatment option using chemoimmunotherapy (combination of a chemotherapeutic agent with an anti-CD20 antibody rituximab) was found to have limited efficacy and increased toxicity. In addition, treatment options for CLL are further limited by lack of common genetic target. Nonetheless, many studies reported the association of B-cell receptor (BCR) signaling in the survival of CLL tumor-cells. A downstream component of BCR signaling, a receptor tyrosine kinase, Burton’s tyrosine kinase (BTK) was noted for activation of the Akt, ERK, NF-κB pathways associated with CLL-cell survival.

Bruton’s tyrosine kinase is essential for B-cell development and function. BTK deficiency in man or mice results in the B-cell specific immunodeficiencies X-linked agammaglobulinemia (XLA) or x-linked immune deficiency (xid), respectively. It is also implicated in the pathogenesis of B-cell cancers. Studies suggest that the levels of BTK represent a rate-limiting step in BCR signaling and thereby B-cell activation and survival. Therefore, inhibition of BTK in CLL could serve as an effective treatment strategy. In vitro studies reported that following inhibition of BTK with selective inhibitor CLL cells lose their resistance to apoptosis. Preclinical studies also demonstrated that that BTK-deficiency completely abrogated CLL development in mice.IBRUTINIBWith the accumulating evidence of the role of BCR pathway involving BTK in CLL, first targeted therapeutic approach for CLL was tested clinically with BTK inhibitors. A study published recently in The New England Journal of Medicine (July 4, 2013) by Byrd et al. reported a high frequency of durable remissions in patients with relapsed or refractory CLL with a BTK inhibitor, ibrutinib. A phase I study of ibrutinib (previously known as PCI-32765) showed mild-to-moderate toxicity and clinical antitumor activity in patients with relapsed or refractory B-cell cancers; 11 of the 16 patients in the study had CLL or small lymphocytic lymphoma. These preliminary results prompted the initiation of a phase Ib–II study of ibrutinib in CLL; this study involved two different therapeutic doses in patients with relapsed or refractory disease.

In the phase Ib-II multicenter study of ibrutinib, Byrd et al. (2013) assessed the safety, efficacy, and pharmacokinetics of this inhibitor in patients with CLL or small lymphocytic lymphoma (ClinicalTrials.gov number NCT01105247). Among 85 patients enrolled in this study, 51 received 420 mg and 34 received 840 mg ibrutinib orally once daily. In both cohorts the overall response rate was 71%. This treatment resulted in durable response were the 26-month estimated progression-free survival was 75% and the rate of overall survival was 83%. The pharmacodynamic study showed that ibrutinib was able to successfully inhibit BTK. However, disease progression was noted in 13% patients during follow-up. The most common toxicities observed during ibrutinib treatment were diarrhea, fatigue, and upper respiratory tract infection.

As compared to other single agent therapies for relapsed CLL this targeted therapy of BTK inhibition exhibited more durable responses. The durable remissions observed in this study suggest that many patients may be treated successfully with ibrutinib.

References:

1. Gribben, J.G. and S. O’Brien, Update on therapy of chronic lymphocytic leukemia. J Clin Oncol, 2011. 29(5): p. 544-50.

2.  Advani, R.H., et al., Bruton tyrosine kinase inhibitor ibrutinib (PCI-32765) has significant activity in patients with relapsed/refractory B-cell malignancies. J Clin Oncol, 2013. 31(1): p. 88-94.

3. Byrd, J.C., et al., Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med, 2013. 369(1): p. 32-42.

 

 

 

Whole Blood Phospho-flow: Direct Ex Vivo Measurement of Signaling in PBMC

I previously discussed phospho-flow cytometry, a method to study intracellular protein phosphorylation events in peripheral blood mononuclear cells (PBMC) at the single cell level.  In standard phospho-flow cytometry protocols, prior to performing assays, PBMCs are first isolated from blood using density gradient centrifugation methods such as Ficoll.  However, there may be times when it is advantageous to study signaling pathways in relatively unmanipulated cells directly ex vivo.  For this, Chow et al. have established a protocol for performing phospho-flow cytometry on PBMCs directly in whole blood.

phospho_flow_cytometry

There are many advantages to isolating and cryopreserving PBMCs with the intention of later studying signaling events by methods including standard phospho-flow cytometry.  In particular, when comparisons are desired between patient groups and healthy controls, there is likely to be less confounding contributions of experimental variability to the results if all of the comparative samples are assayed together.  However, as discussed by Chow et al., pharmacodynamic monitoring as well as evaluation of constitutively activated signaling pathways in PBMCs would be best studied on cells having undergone the least manipulation.  Some signaling pathway responses may be more robust in whole blood PBMCs as well.  For example, I have found in my own assays that signaling responses to IL-6 are strongest in whole blood PBMCs compared with PBMCs following Ficoll or culture in the incubator for any amount of time.  This method can also be used to study bone marrow immune cell signaling as well as expression of intracellular molecules that are exposed by the permeabilization method chosen. In addition, looking at signaling events in murine PBMCs is difficult to do if PBMCs need to be isolated first, given the very small amount of blood that can be obtained from a mouse.  In these cases, anti-coagulated whole blood phospho-flow cytometry should be considered.

Whole blood phospho-flow cytometry is a relatively easy method.  Using 100 ul of whole blood is enough for this assay, and the stimulus (cytokine or other activating signaling molecule) is added directly to the whole blood for the preferred amount of time.  PBMCs are then fixed with formaldehyde and a Triton X-100 based buffer is added to lyse the red blood cells and permeabilize the white blood cells.  This is followed with a few washes and finally the cells can be treated with methanol to unmask phospho-epitopes, similarly to the standard phospho-flow cytometry method by Nolan and colleagues.  Chow et al. include an optional step in which the PBMCs can be stored in a freezing buffer prior to methanol treatment.  However, I have successfully stored PBMCs in 90-100% methanol at -20 or -80 ºC until staining for flow cytometry, similarly to what is done for the standard phospho-flow cytometry method by Nolan and colleagues.

As with all protocols involving treatment of cells with reagents such as methanol or Triton X-100, some epitopes may be lost and thus will not be evaluable if staining is done following these treatments.  Thus, there is an alternate method included in the protocol to stain for some antigens up front.  As a reminder however, some fluorophores are sensitive to methanol, for instance V500, and thus cannot be used to stain PBMCs prior to such treatments.  Finally, in a prior article, Chow et al. (2005), tested different methods of fixation, permeabilization and alcohol unmasking, and I have included the link to that article below as an excellent reference in the case that modulation of the protocol is required for optimal assessment of your antigens of interest.

Further Reading:

Whole blood processing for measurement of signaling proteins by flow cytometry.  Chow S, Hedley D, Shankey TV. Curr Protoc Cytom. 2008 Oct;Chapter 9:Unit 9.27.

Whole blood fixation and permeabilization protocol with red blood cell lysis for flow cytometry of intracellular phosphorylated epitopes in leukocyte subpopulations.  Chow S, Hedley D, Grom P, Magari R, Jacobberger JW, Shankey TV. Cytometry A. 2005 Sep;67(1):4-17.

Single-cell phospho-protein analysis by flow cytometry. Schulz KR, Danna EA, Krutzik PO, Nolan GP.Curr Protoc Immunol. 2012 Feb;Chapter 8:Unit 8.17.1-20.

 

 

Finding the Right Cancer Culprits Using Mutational Heterogeneity

Imagine this: you are a police officer on patrol and you receive a call that multiple 30-year-old Caucasian males were seen breaking and entering; stealing heirlooms from a nearby neighborhood. The suspects were last seen entering a convention center and, to your dismay, you arrive to find the entire convention center is an antique show containing several 30-year-old Caucasian males carrying heirlooms. What do you do to apprehend your perpetrators?  You could arrest everyone that fits the description and interrogate them. On the other hand, you could scan the crowd for clues that there is a group of people that do not belong, or also radio to the police station for more information to narrow down the crowd. Needless to say, without gaining more contextual information for prudent discernment of the situation, you may arrest the wrong men and let the criminals go free.genomes

This is where cancer genomics is today; the sophistication of sequencing techniques have allowed for datasets that can detect every genomic mutation within cancer cells. Unfortunately, mutation rates are not equal among all genes. While this may seem a non-issue, this could lead scientists to ascertain that a mutated gene is associated with cancer when, in fact, the gene that “matches the description” is more susceptible to mutation, but has no role in oncogenesis. This is exactly what occurred to researchers who found high mutation rates of olfactory genes within lung cancer1. Doubtful of the role of olfactory genes in lung tumorigenesis, these scientists ultimately concluded that the mutation of olfactory genes had no role in the transformation of the lung epithelial cells1.

In Nature, Lawrence et al. further explored this issue, showing that failure to correct for the variability of mutation rates across the genome could lead to false positives for cancer associated genes1. To illustrate the importance of incorporating heterogeneity into the methodologies of data analysis, the authors compared a datasets with similar mutation frequencies to datasets that had different average mutation frequencies and found, when failing to take into account variability of mutations, there was an increase false categorization of cancer associated genes. Furthermore, the authors demonstrate that an analysis of an increasing sample size, as seen in the “big data” datasets of  American Society of Clinical Oncology’s “CancerLinQ™”2 and the Cancer Genome Atlas3, without correcting mutation rates, may exacerbate  the amount of false positives for cancer associated genes by decreasing the threshold needed to reach statistical significance. Lawrence postulated that heterogeneity may affect the detection of appropriate cancers by failing to correct for three contextual events: heterogeneity in mutation rates amongst samples of the same cancer type (patient-specific context), heterogeneity in mutation rates based on nucleotides surrounding a sequence (sequence-specific context), and heterogeneity in mutation rates based on the time that the gene is replicated or transcribed (replication/transcription-specific context).  Using the mutated olfactory genes mentioned above, along 3083 tumor-control pairs spanning 27 different cancer types, the authors demonstrate the importance of these contextually-discerning mutation rates and construct an algorithm for further context-based analysis, called MutSigCV.

Lawrence et al. studied cancer samples of the same cancer type (3,083 tumor-normal pairs across 27 tumor types) with variable average mutation rate. The authors found that, among all pairs and tumor types, there was a 1,000-fold variance in median frequency of mutations within the sample size. In these samples, the lowest variances were amongst hematological and pediatric cancers while the highest were among tumors induced by environmental factors, such as smoking and radiation. Given the importance of having accurate knowledge of the variability of rate of mutation, this underscores the importance in treating different cancer types, as well as patients with the same cancer, with a context-specific treatment protocol.

However, correcting for mutational frequencies attributed to tissue types, and mutations caused by known carcinogens and differences in cancer types, the authors still found that there was high mutational variability within certain samples of the same cancer type. Since mutation variance cannot be wholly accounted for by carcinogens, Lawrence et al. postulated that nucleotide makeup of the gene sequence may play a role in the mutation rate variability. The authors tested mutational heterogeneity in multiple tumors by assaying for 96 possible mutations (taking into account flanking bases) that were simplified into a radial chart for analysis1. Lawrence et al found that certain tumor types clustered into certain mutated sequences with the same flanking nucleotides (for instance lung cancers had a really high C to A mutations) was predominate, but still varied, within a certain cancer type.

While both variance in median mutation rates, and predominance of a specific sequence mutation, within specific cancer types was significant, the most important aspect in mutational heterogeneity seems to be in regional areas across a whole genome of cancer types, attributing to an excess of fivefold differences in median mutation rates1. Lawrence et al. credited this to two factors: the amount a gene is transcribed for the time the DNA section is replicated. The authors discovered that mutation rates are highest in genes with low rates of transcription and late DNA replication events. Comparing falsely-implicated olfactory receptor genes to known cancer associated genes, Lawrence et al. demonstrate different transcription rates and different replication times, with olfactory genes being expressed at cells with lower rates and later replication times. In contrast, cancer associated genes have higher transcription rates and earlier replication times.  In other words, while normal and cancer associated genes are both gaining mutations, the events that lead to these mutations are different. Thus, without parsing out mutational rates compared to replication and transcription, one may falsely assume that similar mutation levels must determine a cancer associated genes.

In the end, the authors surmised that “the rich variation in mutational spectrum across tumours underscores the problems with using an overly simplistic model of the average mutational process for a tumour type and failing to account for heterogeneity within a tumor type.” They state that their new analysis algorithm, MutSigCV, takes into account these context dependent nuances, allowing for cancer genomic analysis of mutations that eliminates these false positives. Using MutSigCV, Lawrence et al. was able to take a list of 450 suspected cancer associated genes in lung carcinoma and narrow the list to 11 suspected genes; genes shown to be linked to cancer1. This underscores the importance of context-specific analysis of big data in terms of cancer genomics. Without such a process, the use of whole genome sequencing for mutation rates for novel drug targets may be inadequate, sending many pharmaceutical and biotech companies toward therapeutic targets that, while look like the right suspect, are just an innocent bystanders that “fit the description”.

 

References:

1          Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature, doi:10.1038/nature12213 (2013).

2          DeMartino, J. K. & Larsen, J. K. Data Needs in Oncology: “Making Sense of The Big Data Soup”. Journal of the National Comprehensive Cancer Network 11, S-1-S-12 (2013).

3          Network, C. G. A. R. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519-525, doi:10.1038/nature11404 (2012).

 

ISSCR 2013 Meeting Updates: Can Alzheimer’s Disease be modeled in a dish?

Human pluripotent stem cells (hPSCs) can differentiate into all cell types of the body, and can thereby serve as great models to examine the pathological mechanisms of various human diseases.  At the International Society for Stem Cell Research (ISSCR) 11th Annual Meeting, various stem cell experts highlighted the current human stem cell models for Alzheimer’s disease, and discussed the potential future directions of the field.

Alzheimer’s disease (AD) is the most common neurodegenerative dementia, affecting ~30 million people worldwide.  AD occurs in two main forms:  early-onset, familial AD (FAD) and late-onset, sporadic AD (SAD).  Both 40004_webare characterized by extensive neuronal loss and the aggregation of two proteins in the brain: amyloid β peptide (Aβ) and tau.  Aβ peptide is derived from the amyloid precursor protein (APP) via cleavage by two proteases, β-secretase and γ-secretase.  According to the amyloid cascade hypothesis, elevated levels of Aβ are necessary and sufficient to trigger disease 1.  Tau is synthesized in neurons and normally functions in binding to tubulin and stabilization of microtubules.  However, in AD, tau is hyper-phosphorylated, resulting in dissociation from microtubules, aggregation, and formation of neurofibrillary tangles (NFTs).  Although the pathological hallmarks of AD consist of these amyloid plaques and NFTs, how the two are related to each other and how they contribute to clinical onset and progression of AD is still under investigation.  By the time a patient manifests symptoms of a mild dementia, there is already significant neuronal loss and substantial accumulation of plaques and tangles.  One major limitation to our understanding of AD has been the lack of live, patient-specific neurons to examine disease progression.

With recent advances in reprogramming technology, scientists can now generate induced pluripotent stem cells (iPSCs), and thereby use live, patient-specific models to examine disease phenotypes in a dish.  At the ISSCR meeting, Larry Goldstein presented his lab’s recent work on using hiPSC models to study AD.  They generated iPSCs from two patients with FAD caused by a duplication of the APP gene, two patients with SAD, and two control individuals.  Next, neurons were generated from the iPSC lines by directed differentiation and fluorescence-activated cell sorting (FACS) purification 2.  Neurons from one SAD and two FAD patients demonstrated significantly higher levels of secreted Aβ and phosphorylated tau (p-tau) 3.  To determine whether there is an association between APP processing and elevated p-tau levels, they treated iPSC-derived neurons with γ-secretase and β-secretase inhibitors.  Interestingly, pharmacologic inhibition of β-secretase resulted in a significant reduction in the levels of Aβ and p-tau.  Treatment with the γ-secretase inhibitor only reduced Aβ levels, but not p-tau levels.  This suggests that products of APP processing other than Aβ might contribute to elevated p-tau levels, highlighting a potential weakness with the amyloid cascade hypothesis.

Other groups have proposed alternative hypotheses to explain AD pathogenesis.  Haruhisa Inoue presented his group’s work on using human iPSC models to examine how intracellular Aβ oligomers contribute to AD.  They generated iPSCs from one patient with FAD caused by the APP-E693Δ mutation, two patients with SAD, and three control individuals.  Corticol neurons were derived using small molecule inhibitors of bone morphogenic protein (BMP) and activin/nodal signaling as previously described 4.  Aβ oligomers accumulated in neurons derived from the FAD patient and one SAD patient, but not in the control neurons 5.  Specifically, the Aβ oligomers accumulated in the endoplasmic reticulum (ER), and triggered ER and oxidative stress in the neurons.  In addition, treatment with docosahexaenoic acid (DHA) alleviated the stress responses.  Although the drug has previously failed in some clinical trials of AD treatment, Inoue’s work suggests that DHA might be effective for a subset of patients.

In summary, Goldstein and Inoue presented convincing evidence that human iPSC models can be used to study early AD pathogenesis and patient-specific drug responses.  Although it can take decades for symptoms to manifest in patients, disease phenotypes can be observed using iPSC models.  However, the fact that only one out of two SAD patients generated a disease phenotype highlights the need of future iPSC studies to examine larger numbers of patients to account for the observed heterogeneity in AD pathogenesis.

References:

1          Hardy, J. & Selkoe, D. J. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297, 353-356, doi:10.1126/science.1072994 (2002).

2          Yuan, S. H. et al. Cell-surface marker signatures for the isolation of neural stem cells, glia and neurons derived from human pluripotent stem cells. PLoS One 6, e17540, doi:10.1371/journal.pone.0017540 (2011).

3          Israel, M. A. et al. Probing sporadic and familial Alzheimer’s disease using induced pluripotent stem cells. Nature 482, 216-220, doi:10.1038/nature10821 (2012).

4          Morizane, A., Doi, D., Kikuchi, T., Nishimura, K. & Takahashi, J. Small-molecule inhibitors of bone morphogenic protein and activin/nodal signals promote highly efficient neural induction from human pluripotent stem cells. J Neurosci Res 89, 117-126, doi:10.1002/jnr.22547 (2011).

5          Kondo, T. et al. Modeling Alzheimer’s disease with iPSCs reveals stress phenotypes associated with intracellular Abeta and differential drug responsiveness. Cell Stem Cell 12, 487-496, doi:10.1016/j.stem.2013.01.009 (2013).