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Monoclonal Antibody Therapy and Market

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Genome Biology, Personalized and Precision Medicine & Genomic Research, Translational Science, tagged , , , , on October 14, 2015| Leave a Comment »

Monoclonal Antibody Therapy and Market

Curator: Demet Sag, PhD, CRA, GCP 

 

Monoclonal Antibody treatment means a biological therapy where monoclonal antibodies is used to initiate development of specific antibodies (protein molecules produced by the B cells as a primary immune defense), so that they can fight against antigens (substances that are capable of inducing a specific immune response) specifically to kill extracellular/ cell surface target.  Thus, the application of this types of therapies are not limited to cancer but also rheumatoid arthritis, multiple sclerosis, Alzheimer’s disease, and some infectious diseases such as Ebola.

To eliminate or reduce the effects of chemotherapeutic agents. Thus chemotherapeutics agents attached to monoclonal antibodies.

Diagnostic process:

Monoclonal antibodies again used as a vehicle to locate the tumorigenic cancer cells in the body. There can be several methods but one of them is carrying radioactive substances to cancer cells so that they can be labelled in vivo.  However, there are less invasive ways to do as well. As a result, there are new combination of methods such as:

  • nuclear imaging,
  • surgical mapping, and
  • direct therapy in multiple settings either alone, or in conjunction with chemotherapeutic agents, adjuvant.

How do monoclonal antibody drugs work?

 525px-Monoclonal_antibodies.svg

  1. Naked monoclonal antibodies:
  • Make the cancer cell more visible to the immune system.

Action is to boost immune system.

Example: Alemtuzumab (Campath®), chronic lymphocytic leukemia (CLL) by binding to the CD52 antigen on lymphocytes.

 

T cell targets for immunoregulatory antibody therapy

  • Block immune checkpoint inhibitor proteins

        

 Treatments that target PD-1 or PD-L1.

 PD-1 is a checkpoint protein on T cells, called “off switch” of T cells since PD-1 prevents from attacking other cells in the body. Yet, when it is overexpressed on the cancer cells, tumors escape from immune system, because when PD-1 binds to PD-L1, T cells thinks these cells are body’s own normal cells.

http://www.nature.com/nature/journal/v515/n7528/images/515496a-f1.jpg

Checkpoint blockade activates antitumour immunity.

a, Tumour cells express both cancer-driving mutations and ‘passenger’ mutations that cause the expression of neoantigens — ‘new’ molecular structures that, when presented by MHC proteins on the cell surface, are recognized by T cells of the immune system as being foreign, leading to an immune response against the tumour. However, interactions between the receptor PD-1 and its ligand PD-L1, which are expressed on tumour cells, T cells and other immune cells such as macrophages, activate signalling pathways that inhibit T-cell activity and thus inhibit the antitumour immune response. b, Antibodies that block the PD-1 pathway by binding to PD-1 or PD-L1 can reactivate T-cell activity and proliferation, leading to enhanced antitumour immunity.

Examples are:

  • Pembrolizumab (Keytruda®)
  • Nivolumab (Opdivo®)

There is a possibility of developing an autoimmune reaction. The most common side effects include fatigue, cough, nausea, skin rash, and itching. Rarely more serious problems in the lungs, intestines, liver, kidneys, hormone-making glands, or other organs may occur.

 Treatments that target CTLA-4

 Another protein is CTLA-4 to control T cells, “off switch”.

Generation and regulation of anti-tumor immunity Biologic activities of CTLA-4 antibody blockade

Example: Ipilimumab (Yervoy®) is a monoclonal antibody that attaches to CTLA-4 and stops it from working. This can boost the body’s immune response against cancer cells.

  • Block antigens on cancer cells (or other nearby cells).

Example: Trastuzumab, when HER2 is activated, binds to these proteins and stops antigens from becoming active in breast and stomach cancer cells.

Example: Rituxan specifically attaches to CD20 that is found only on B cells so when these labelled B cells can be visible to immune system. There are certain types of lymphomas predisposed due to malfunctioning B cells.

  • Block growth signals. Prevent signal amplification for cell growth.

The cells like to amplify their message in danger or during certain metabolisms so they secrete or produce a type of chemicals called growth factors.  These factors then attaches to specific receptors on the surface of normal cells and cancer cells. Thus, signaling the cells to grow faster than the normal cells. The action is preventing the signals to be received by monoclonal.

 Example:

Cetuximab (Erbitux), targets epidermal growth factor. Thus its function utilized to cure colon cancer, head and neck cancers.

  • Stop new blood vessels from forming.

Tumors needs to grow so in the body they need blood vessel formation to feed the cell growth (angiogenesis)

Example; Bevacizumab (Avastin) targets vascular endothelial growth factor (VEGF) and blocks the angiogenesis.

  1. Conjugated monoclonal antibodies (tagged, labeled, or loaded antibodies).

 Deliver chemotherapy to cancer cells.

They are monoclonal antibodies (mAbs) joined to a chemotherapy drug or to a radioactive particle to locate cancer cells directly through targeting specific antigen after circulating in the bloodstream. They are used as a homing device.

Chemo-labeled antibodies: Also called as antibody-drug conjugates (ADCs) and provide powerful chemotherapy (or other) drugs attached to them.

  • Brentuximab vedotin (Adcetris®), an antibody that targets the CD30 antigen on lymphocytes, attached to MMAE (a chemo drug) against Hodgkin lymphoma and anaplastic large cell lymphoma.
  • Ado-trastuzumab emtansine (Kadcyla®, also called TDM-1), an antibody that targets the HER2 protein, attached to DM1 (a chemo drug) against cells overexpressing HER2 in breast cancer

 Toxin attached protein: Denileukin diftitox (Ontak®) is not an antibody but it is a protein, cytokine known as interleukin-2 (IL-2) and attached to diphtheria toxin that recognizes CD25 antigen to treat lymphoma of the skin (cutaneous T-cell lymphoma).

 Radiolabeled antibodies: Deliver radiation to cancer cells.

The other method, less preferred, is radiation-linked monoclonal antibodies.  This time low radiation in long term used to target the cancer cells but it is suggested that this method has elevated outcome to kill the cancer cells than conventional high-dose external beam radiation.

Example; Ibritumomab (Zevalin), is an approved treatment.  The targeted disease is for non-Hodgkin’s lymphoma.

Treatment with this type of antibody also referred as radioimmunotherapy (RIT).

  1. Bispecific monoclonal antibodies

 If the drug contains two parts of 2 different mAbs, meaning they can attach to 2 different proteins at the same time, they are called Bispecific monoclonal antibodies since they attack two proteins at the same time.

 

Example:  Blinatumomab (Blincyto), can attach CD 19 which is found on some leukemia and lymphoma cells and CD3 on T cells.  Thus, brings opponents, immune and malignant cancer cells, to defeat cancer.

  nature_graphic_immune-system_08.01.15

THE OTHER SIDE OF THE COIN: SAFETY

 Possible side effects of monoclonal antibodies

 Delivery is intravenously and since Mabs are themselves are proteins sometimes presents side effects like an allergic reaction yet compared to chemotherapy drugs these effects are much less. .

  • Fever
  • Chills
  • Weakness
  • Headache
  • Nausea
  • Vomiting
  • Diarrhea
  • Low blood pressure
  • Rashes

Examples:

  • Bevacizumab (Avastin®), high blood pressure, bleeding, poor wound healing, blood clots, and kidney damage.
  • Cetuximab (Erbitux®), serious rashes in some people.

Manufacturing of Monoclonal Antibodies and Market

“Since 2000, the therapeutic market for monoclonal antibodies has grown exponentially. The current “big 5” therapeutic antibodies on the market are bevacizumab, trastuzumab (both oncology), adalimumab, infliximab (both autoimmune and inflammatory disorders, ‘AIID’) and rituximab (oncology and AIID) accounted for 80% of revenues in 2006. In 2007, eight of the 20 best-selling biotechnology drugs in the U.S. are therapeutic monoclonal antibodies. Scolnik, Pablo A. (2009). “mAbs: A business perspective”. MAbs 1 (2): 179–184. doi:10.4161/mabs.1.2.7736. PMC 2725420. PMID 20061824.

This rapid growth in demand for monoclonal antibody production has been well accommodated by the industrialization of mAb manufacturing”. Kelley, Brian (2009). “Industrialization of mAb production technology”. MAbs 1 (5): 443–452. doi:10.4161/mabs.1.5.9448. PMC 2759494. PMID 20065641.

mabs0105_0443_fig001http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759494/bin/mabs0105_0443_fig001.jpg

Model mAb production plant design and capabilities. A model large scale mAb production plant employs multiple bioreactors configured to supply a single purification train. A plant having six individual 15 kL bioreactors is potentially capable of supplying 10 tons of purified mAb per year using conventional technologies, or 4–5 products with 1 ton demands. This enormous capacity per plant would result in a marked decrease in drug substance production costs, and results in significant excess capacity throughout the biopharmaceutical industry.

Production:

Production capacity estimates for mammalian cell-derived mAbsa

Year CMO Product company Total Capacity at 2 g/L Capacity at 5 g/L
2007 500 kL 1,800 kL 2,300 kL 70 tons/yr 170 tons/yr
2010 700 kL 2,700 kL 3,400 kL 100 tons/yr 255 tons/yr
2013 1,000 kL 3,000 kL 4,000 kL 120 tons/yr 300 tons/yr

aCapacity estimates from ref. Ransohoff TC, Ecker DM, Levine HL, Miller J. Cell culture manufacturing capacity: trends and outlook through 2013. PharmSource. 2008

mabs0105_0443_fig002

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759494/bin/mabs0105_0443_fig003.jpg

Estimated demand for therapeutic mAbs and Fc-fusion products in 2009. The total demand for the top 15 mAbs and Fc-fusions in 2009 is estimated to be approximately 7 tons, with the four largest volume products requiring approximately one ton per year. More than half of the products were estimated to require less than 200 kg per year.

mabs0105_0443_fig004 mabs0105_0443_fig003

Distribution of average wholesale prices for mAb and Fc-fusions in 2008. The average U.S. wholesale prices per gram for 15 commercial mAbs and Fc-fusions are shown. The minimum is approximately $2,000 per gram, and the median is approximately $8,000 per gram. Note that a significant price erosion (50% of the minimum shown here) for a product with modest demand (100 kg/yr) could result in an unprofitable market, as revenues for the therapeutic product ($100 million/yr) may never provide a positive return on investment.

Sensitivity analysis of mAb drug substance COGs for the model plant (six 15kL bioreactors)

Titer (g/L) Plant capacity (tons/yr) Raw materials ($/gm) Depreciation & labor ($/gm)b Fill/Finish costs per vial ($) Total Drug Product Cost ($/vial)
Cell culturea Purification 100 mg 1 gm
0.5 1 20 100 22 134
2 4 4 4 25 10 13 43
5 10 2 10 12 26

aAssumes medium cost of $8/L.

bBased on the model plant ($500 M capital investment + 250 staff = $100 M per year).

Estimated cost breakdown for three production scenarios

Model large-scale plant Small-scale plant using disposables CMO
Basis: 5 g/L 6 × 15 kL n × 2 kL 15 kL
Capital Investmenta $500 M $125 M – Difference in annual cost for two best alternatives ($M/yr)
Depreciationb($/yr) $50 M $12.5 M –
Raw Materialsc $10/gm $20/gm $10/gm
Labor ($/yr)d $50 M $20 M –
CMO – – $3 M/batche
COGs $/gm 10 ton/yr 20 23 60 $30 M
1 ton/yr 110 53 60 $7 M
0.1 ton/yr 1,010 345 60 $29 M

aThe new facility based on disposables is assumed to cost just one-quarter of model plant to build, and uses only the number of bioreactors (‘n’) needed to satisfy the demand.

bA 10-year straight line depreciation is used to estimate the depreciation costs.

cRaw material costs per gram are assumed to be slightly higher for the disposable facility.

dLabor costs for the new facility are assumed to be just 40% of the model plant (100 vs 250 staff, respectively).

eA constant cost per batch is assumed for the CMO, all-inclusive of production, testing and release.

Sales and Marketing

PMC full text: MAbs. 2009 Mar-Apr; 1(2): 179–184.

FDA-approved marketed mAbs

Name Structure Target Indication Path Approval (Y) Sales % Top 20
Generic Trade Landing Expansion
First Tier (U.S. $B)
infliximab Remicade® Ch TNF CD RA O, A, P, F 4.6 $5.0 9.84
AS
PA
UC
PP
rituximab Rituxan®, Ch CD20 NHL RA O, P 5.1 $4.9 9.62
MabThera® DLBC
1-NHL
trastuzumab Herceptin® Hm HER2 mBC BC F, P 7.5 $4.3 8.45
bevacizumab Avastin® Hm VEGF mCRC mCRC F, P 7.1 $3.6 7.15
NSCLC
HER2- BCa
adalimumab Humira® Hu TNF RA RA O 3.7 $3.1 6.04
JIA
PA
AS
CD
PP
cetuximab Erbitux® Ch EGFR mCRC SCCHN A, P 9.7 $1.4 2.73
ranibizumab Lucentis® Hm VEGF AMD P 6.8 $1.2 2.39
palivizumab Synagis® Hm RSV RSV P 3.6 $1.1 2.25
Second Tier (U.S. $M)
tositumomab Bexxar® Mu CD20 NHLb NHLc 13.7 $10.3 0.02
alemtuzumab Campath® Hm CD52 B-CLL B-CLLd A, P, F 10.4e $108.0 0.21
certolizumab pegol Cimzia® Hm TNF CD P n/a n/a n/a
gemtuzumab ozogamicin Mylotarg® Hm CD33 AML P, A, O 6.5 $60.0 0.12
muromonab-CD3 Orthoclone Okt3® Mu CD3 OR OR n/a $150.0 0.30
efalizumab Raptçiva® Hm CD11a PS 10e $163.0 0.32
abciximab ReoPro® Ch GP IIb/IIIa AC CI O n/a $380.0 0.75
basiliximab Simulect® Ch CD25 OR O, P n/a $300.0 0.59
eculizumab Soliris® Hm C5 PNH O, P n/a $230.0 0.45
natalizumab Tysabri® Hm a-4 integrin MS CD A 10.6e $100.0 0.20
panitumumab Vectibix® Hu EGFR mCRC A, P, F 7.4 $365.0 0.72
omalizumab Xolair® Hm IgE AA 9.7 $472.0 0.93
daclizumab Zenapax® Hm CD25 OR ORp O, P n/a $60.0 0.12
ibritumomab tiuxetan Zevalin® Mu CD20 NHL P, A, O, F 10.2 $17.0 0.03

Abbreviations: Structure: Ch, chimeric; Hm, humanized; Hu, human; Mu, murine. Regulatory Path: A, accelerated approval; F, fast-track; P, priority review; O, orphan indication. 1-, first-line therapy; a, conditional approval; b, rituximab refractory; c, refractory to chemotherapy; d, single-agent; e, estimate; m, metastatic; n/a, information not available; p, prophylaxis. Sources: 20 Compounds that defined biotech, Signals online magazine at www.signalsmag.com; ReCap database; Biopharmaceutical Products in the U.S. and European markets 6th edition, Ronald A. Rader, ed; Pharma Sales and BioPharmInsights databases; Reichert JM, Ph. D.; personal communications. Development times and sales estimates for some Second Tier mAbs are based on limited information.

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Dolgin E. FDA narrows drug label usage. Nature. 2009 Aug 27;460(7259):1069. doi: 10.1038/4601069a. PubMed PMID: 19713906.

Ellis LM, Reardon DA. Cancer: The nuances of therapy. Nature. 2009 Mar 19;458(7236):290-2. doi: 10.1038/458290a. PubMed PMID: 19295595.

Izumi Y, Xu L, di Tomaso E, Fukumura D, Jain RK. Tumour biology: herceptin acts as an anti-angiogenic cocktail.  Nature. 2002 Mar 21;416(6878):279-80. PubMed PMID: 11907566.

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Cobbold SP, Waldmann H. Therapeutic potential of monovalent monoclonal antibodies. Nature. 1984 Mar 29-Apr 4;308(5958):460-2. PubMed PMID: 6608694.

Shouval D, Shafritz DA, Zurawski VR Jr, Isselbacher KJ, Wands JR. Immunotherapy in nude mice of human hepatoma using monoclonal antibodies against hepatitis B virus. Nature. 1982 Aug 5;298(5874):567-9. PubMed PMID: 7099252.

Thorpe PE, Mason DW, Brown AN, Simmonds SJ, Ross WC, Cumber AJ, Forrester JA. Selective killing of malignant cells in a leukaemic rat bone marrow using an antibody-ricin conjugate. Nature. 1982 Jun 17;297(5867):594-6. PubMed PMID: 7088145.

Beverley PC. Antibodies and cancer therapy. Nature. 1982 Jun 3;297(5865):358-9. PubMed PMID: 7078646.

Trowbridge IS. Cancer monoclonals.  Nature. 1981 Nov 19;294(5838):204. PubMed PMID: 7300906.

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Waldmann, Thomas A. (2003). “Immunotherapy: past, present and future”. Nature Medicine 9 (3): 269–277. doi:10.1038/nm0303-269. PMID 12612576.

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Selected FDA Approved Mab Drugs:

(John, Martin et al. 2005, Robert, Ann et al. 2006, Albert, Edvardas et al. 2012, Claro, Karen et al. 2012, Gideon, Nancy et al. 2013, Michael, Ke et al. 2013, Thomas, Albert et al. 2013, Hyon-Zu, Barry et al. 2014, Larkins, Scepura et al. 2015, Sandra, Ibilola et al. 2015, Sean, Gideon et al. 2015)

Albert, D., K. Edvardas, G. Joseph, C. Wei, S. Haleh, L. L. Hong, D. R. Mark, B. Satjit, W. Jian, G. Christine, B. Julie, B. B. Laurie, R. Atiqur, S. Rajeshwari, F. Ann and P. Richard (2012). “U.S. Food and Drug Administration Approval: Ruxolitinib for the Treatment of Patients with Intermediate and High-Risk Myelofibrosis.” Clinical Cancer Research: 3212-3217.

Claro, R. A. d., M. Karen, K. Virginia, B. Julie, K. Aakanksha, H. Bahru, O. Yanli, S. Haleh, L. Kyung, K. Kallappa, R. Mark, S. Marjorie, B. Francisco, C. Kathleen, C. Xiao Hong, B. Janice, A. Lara, K. Robert, K. Edvardas, F. Ann and P. Richard (2012). “U.S. Food and Drug Administration Approval Summary: Brentuximab Vedotin for the Treatment of Relapsed Hodgkin Lymphoma or Relapsed Systemic Anaplastic Large-Cell Lymphoma.” Clinical Cancer Research: 5845-5849.

Gideon, M. B., S. S. Nancy, C. Patricia, C. Somesh, T. Shenghui, S. Pengfei, L. Qi, R. Kimberly, M. P. Anne, T. Amy, E. K. Kathryn, G. Laurie, L. R. Barbara, C. W. Wendy, C. Bo, T. Colleen, H. Patricia, I. Amna, J. Robert and P. Richard (2013). “First FDA approval of dual anti-HER2 regimen: pertuzumab in combination with trastuzumab and docetaxel for HER2-positive metastatic breast cancer.” Clinical cancer research : an official journal of the American Association for Cancer Research: 4911-4916.

Hyon-Zu, L., W. M. Barry, E. K. Virginia, R. Stacey, D. Pedro, S. Haleh, G. Joseph, B. Julie, F. Jeffry, M. Nitin, K. Chia-Wen, N. Lei, S. Marjorie, T. Mate, C. K. Robert, K. Edvardas, J. Robert, T. F. Ann and P. Richard (2014). “U.S. Food and drug administration approval: obinutuzumab in combination with chlorambucil for the treatment of previously untreated chronic lymphocytic leukemia.” Clinical cancer research : an official journal of the American Association for Cancer Research: 3902-3907.

John, R. J., C. Martin, S. Rajeshwari, C. Yeh-Fong, M. W. Gene, D. John, G. Jogarao, B. Brian, B. Kimberly, L. John, H. Li Shan, C. Nallalerumal, Z. Paul and P. Richard (2005). “Approval Summary for Erlotinib for Treatment of Patients with Locally Advanced or Metastatic Non–Small Cell Lung Cancer after Failure of at Least One Prior Chemotherapy Regimen.” Clinical Cancer Research 11(18).

Larkins, E., B. Scepura, G. M. Blumenthal, E. Bloomquist, S. Tang, M. Biable, P. Kluetz, P. Keegan and R. Pazdur (2015). “U.S. Food and Drug Administration Approval Summary: Ramucirumab for the Treatment of Metastatic Non-Small Cell Lung Cancer Following Disease Progression On or After Platinum-Based Chemotherapy.” The oncologist.

Michael, A., L. Ke, J. Xiaoping, H. Kun, W. Jian, Z. Hong, K. Dubravka, P. Todd, D. Zedong, R. Anne Marie, M. Sarah, K. Patricia and P. Richard (2013). “U.S. Food and Drug Administration approval: vismodegib for recurrent, locally advanced, or metastatic basal cell carcinoma.” Clinical cancer research : an official journal of the American Association for Cancer Research: 2289-2293.

Robert, C. K., T. F. Ann, S. Rajeshwari and P. Richard (2006). “United States Food and Drug Administration approval summary: bortezomib for the treatment of progressive multiple myeloma after one prior therapy.” Clinical cancer research : an official journal of the American Association for Cancer Research: 2955-2960.

Sandra, J. C., F.-A. Ibilola, J. L. Steven, Z. Lillian, J. Runyan, L. Hongshan, Z. Liang, Z. Hong, Z. Hui, C. Huanyu, H. Kun, D. Michele, N. Rachel, K. Sarah, K. Sachia, H. Whitney, K. Patricia and P. Richard (2015). “FDA Approval Summary: Ramucirumab for Gastric Cancer.” Clinical cancer research : an official journal of the American Association for Cancer Research: 3372-3376.

Sean, K., M. B. Gideon, Z. Lijun, T. Shenghui, B. Margaret, F. Emily, H. Whitney, L. Ruby, S. Pengfei, P. Yuzhuo, L. Qi, Z. Ping, Z. Hong, L. Donghao, T. Zhe, H. Ali Al, B. Karen, K. Patricia, J. Robert and P. Richard (2015). “FDA approval: ceritinib for the treatment of metastatic anaplastic lymphoma kinase-positive non-small cell lung cancer.” Clinical cancer research : an official journal of the American Association for Cancer Research: 2436-2439.

Thomas, M. H., D. Albert, K. Edvardas, C. K. Robert, M. K. Kallappa, D. R. Mark, H. Bahru, B. Julie, D. B. Jeffrey, H. Jessica, R. P. Todd, J. Josephine, A. William, M. Houda, B. Janice, D. Angelica, S. Rajeshwari, T. F. Ann and P. Richard (2013). “U.S. Food and Drug Administration Approval: Carfilzomib for the Treatment of Multiple Myeloma.” Clinical Cancer Research: 4559-4563.

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Humanized Mice May Revolutionize Cancer Drug Discovery

Posted in BioTechnology - Venture Creation, BioTechnology - Venture Creation, Venture Capital, Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Monoclonal Immunotherapy, Patents, Pharmaceutical Drug Discovery, Pharmacodynamics and Pharmacokinetics, tagged , , , , , , , , , , , , , , on October 9, 2015| Leave a Comment »

Humanized Mice May Revolutionize Cancer Drug Discovery

Curator: Stephen J. Williams, Ph.D.

Humanized Mice May Revolutionize Cancer Drug Discovery

Word Cloud by Zach Day

Decades ago cancer research and the process of oncology drug discovery was revolutionized by the development of mice deficient in their immune system, allowing for the successful implantation of human-derived tumors. The ability to implant human tumors without rejection allowed researchers to study how the kinetics of human tumor growth in its three-dimensional environment, evaluate potential human oncogenes and drivers of oncogenesis, and evaluate potential chemotherapeutic therapies. Indeed, the standard preclinical test for antitumor activity has involved the subcutaneous xenograft model in immunocompromised (SCID or nude athymic) mice. More detail is given in the follow posts in which I describe some early pioneers in this work as well as the development of large animal SCID models:

Heroes in Medical Research: Developing Models for Cancer Research

The SCID Pig: How Pigs are becoming a Great Alternate Model for Cancer Research

The SCID Pig II: Researchers Develop Another SCID Pig, And Another Great Model For Cancer Research

This strategy (putting human tumor cells into immunocompromised mice and testing therapeutic genes and /or compounds) has worked extremely well for most cytotoxic chemotherapeutics (those chemotherapeutic drugs with mechanisms of action related to cell kill, vital cell functions, and cell cycle). For example the NCI 60 panel of human tumor cell lines has proved predictive for the chemosensitivity of a wide range of compounds.

Even though the immunocompromised model has contributed greatly to the chemotherapeutic drug discovery process. using these models to develop the new line of immuno-oncology products has been met with challenges three which I highlight below with curated database of references and examples.

From a practical standpoint development of a mouse which can act as a recipient for human tumors yet have a humanized immune system allows for the preclinical evaluation of antitumoral effect of therapeutic antibodies without the need to use neutralizing antibodies to the comparable mouse epitope,   thereby reducing the complexity of the study and preventing complications related to pharmacokinetics.

Champions Oncology Files Patents for Use of PDX Platform in Immune-Oncology

Hackensack, NJ – August 17, 2015 – Champions Oncology, Inc. (OTC: CSBR), engaged in the development of advanced technology solutions and services to personalize the development and use of oncology drugs, today announced that it has filed two patent applications with the United States Patent and Trademark Office (USPTO) relating to the development and use of mice with humanized immune systems to test immune-oncology drugs and therapeutic cancer vaccines.

Dr. David Sidransky, the founder and Chairman of Champions Oncology commented, “Drug development ‎in the immune-oncology space is fundamentally changing our approach to cancer treatment. These patents represent potentially invaluable tools for developing and personalizing immune therapy based on cutting edge sequence analysis, bioinformatics and our unique in vivo models.”

Joel Ackerman, Chief Executive Officer of Champions Oncology stated, “Developing intellectual property related to our Champions TumorGraft® platform has been an important component of strategy. The filing of these patents is an important milestone in leveraging our research and development investment to expand our platform and create proprietary tools for use by our pharmaceutical partners. We continue to look for additional revenue streams to supplement our fee-for-service business and we believe these patents will help us capture more of the value we create for our customers in the future.”

The first patent filing covers the methodology used by the Company to create a mouse model, containing a humanized immune system and a human tumor xenograft, which is capable of testing the efficacy of immune-oncology agents, both as single agents and in combination with anti-neoplastic drugs. The second patent filing relates to the detection of neoantigens and their role in the development of anti-cancer vaccines.

Keren Pez, Chief Scientific Officer, explained, “In the last few years, there has been a significant increase in cancer research that focuses on exploring the power of the human immune system to attack tumors. However, it’s challenging to test immune-oncology agents in traditional animal models due to the major differences between human and murine immune systems. The Champions ImmunoGraft™ platform has the unique ability of mimicking a human adaptive immune response in the mice, which allows us to specifically evaluate a variety of cancer therapeutics that modulate human immunity.

“Therapeutic vaccines that trigger the immune system to mount a response against a growing tumor are another area of intense interest. The development of an effective vaccine remains challenging but has an outstanding curative potential. Tumors harbor mutations in DNA that result in the translation of aberrant proteins. While these proteins have the potential to provoke an immune response that destructs early-stage cancer development, often the immune response becomes insufficient. Vaccines can trigger it by proactively challenging the system with these specific mutated peptides. Nevertheless, developing anti-cancer vaccines that effectively inhibit tumor growth has been complicated, partially due to challenges in finding the critical mutations, among others difficulties. With the more recent advances in genome sequencing, it’s now possible to identify tumor-specific antigens, or neoantigens, that naturally develop as an individual’s tumor grows and mutates,” she continued.

Traumatic spinal cord injury in mice with human immune systems.

Carpenter RS, Kigerl KA, Marbourg JM, Gaudet AD, Huey D, Niewiesk S, Popovich PG.

Exp Neurol. 2015 Jul 17;271:432-444. doi: 10.1016/j.expneurol.2015.07.011. [Epub ahead of print]

Inflamm Bowel Dis. 2015 Jul;21(7):1652-73. doi: 10.1097/MIB.0000000000000446.

Use of Humanized Mice to Study the Pathogenesis of Autoimmune and Inflammatory Diseases.

Koboziev I1, Jones-Hall Y, Valentine JF, Webb CR, Furr KL, Grisham MB.

Author information

Abstract

Animal models of disease have been used extensively by the research community for the past several decades to better understand the pathogenesis of different diseases and assess the efficacy and toxicity of different therapeutic agents. Retrospective analyses of numerous preclinical intervention studies using mouse models of acute and chronic inflammatory diseases reveal a generalized failure to translate promising interventions or therapeutics into clinically effective treatments in patients. Although several possible reasons have been suggested to account for this generalized failure to translate therapeutic efficacy from the laboratory bench to the patient’s bedside, it is becoming increasingly apparent that the mouse immune system is substantially different from the human. Indeed, it is well known that >80 major differences exist between mouse and human immunology; all of which contribute to significant differences in immune system development, activation, and responses to challenges in innate and adaptive immunity. This inconvenient reality has prompted investigators to attempt to humanize the mouse immune system to address important human-specific questions that are impossible to study in patients. The successful long-term engraftment of human hematolymphoid cells in mice would provide investigators with a relatively inexpensive small animal model to study clinically relevant mechanisms and facilitate the evaluation of human-specific therapies in vivo. The discovery that targeted mutation of the IL-2 receptor common gamma chain in lymphopenic mice allows for the long-term engraftment of functional human immune cells has advanced greatly our ability to humanize the mouse immune system. The objective of this review is to present a brief overview of the recent advances that have been made in the development and use of humanized mice with special emphasis on autoimmune and chronic inflammatory diseases. In addition, we discuss the use of these unique mouse models to define the human-specific immunopathological mechanisms responsible for the induction and perpetuation of chronic gut inflammation.

J Immunother Cancer. 2015 Apr 21;3:12. doi: 10.1186/s40425-015-0056-2. eCollection 2015.

Human tumor infiltrating lymphocytes cooperatively regulate prostate tumor growth in a humanized mouse model.

Roth MD1, Harui A1.

Author information

Abstract

BACKGROUND:

The complex interactions that occur between human tumors, tumor infiltrating lymphocytes (TIL) and the systemic immune system are likely to define critical factors in the host response to cancer. While conventional animal models have identified an array of potential anti-tumor therapies, mouse models often fail to translate into effective human treatments. Our goal is to establish a humanized tumor model as a more effective pre-clinical platform for understanding and manipulating TIL.

METHODS:

The immune system in NOD/SCID/IL-2Rγnull (NSG) mice was reconstituted by the co-administration of human peripheral blood lymphocytes (PBL) or subsets (CD4+ or CD8+) and autologous human dendritic cells (DC), and animals simultaneously challenged by implanting human prostate cancer cells (PC3 line). Tumor growth was evaluated over time and the phenotype of recovered splenocytes and TIL characterized by flow cytometry and immunohistochemistry (IHC). Serum levels of circulating cytokines and chemokines were also assessed.

RESULTS:

A tumor-bearing huPBL-NSG model was established in which human leukocytes reconstituted secondary lymphoid organs and promoted the accumulation of TIL. These TIL exhibited a unique phenotype when compared to splenocytes with a predominance of CD8+ T cells that exhibited increased expression of CD69, CD56, and an effector memory phenotype. TIL from huPBL-NSG animals closely matched the features of TIL recovered from primary human prostate cancers. Human cytokines were readily detectible in the serum and exhibited a different profile in animals implanted with PBL alone, tumor alone, and those reconstituted with both. Immune reconstitution slowed but could not eliminate tumor growth and this effect required the presence of CD4+ T cell help.

CONCLUSIONS:

Simultaneous implantation of human PBL, DC and tumor results in a huPBL-NSG model that recapitulates the development of human TIL and allows an assessment of tumor and immune system interaction that cannot be carried out in humans. Furthermore, the capacity to manipulate individual features and cell populations provides an opportunity for hypothesis testing and outcome monitoring in a humanized system that may be more relevant than conventional mouse models.

Methods Mol Biol. 2014;1213:379-88. doi: 10.1007/978-1-4939-1453-1_31.

A chimeric mouse model to study immunopathogenesis of HCV infection.

Bility MT1, Curtis A, Su L.

Author information

Abstract

Several human hepatotropic pathogens including chronic hepatitis C virus (HCV) have narrow species restriction, thus hindering research and therapeutics development against these pathogens. Developing a rodent model that accurately recapitulates hepatotropic pathogens infection, human immune response, chronic hepatitis, and associated immunopathogenesis is essential for research and therapeutics development. Here, we describe the recently developed AFC8 humanized liver- and immune system-mouse model for studying chronic hepatitis C virus and associated human immune response, chronic hepatitis, and liver fibrosis.

PMID:

25173399

[PubMed – indexed for MEDLINE]

PMCID:

PMC4329723

Free PMC Article

Immune humanization of immunodeficient mice using diagnostic bone marrow aspirates from carcinoma patients.

Werner-Klein M, Proske J, Werno C, Schneider K, Hofmann HS, Rack B, Buchholz S, Ganzer R, Blana A, Seelbach-Göbel B, Nitsche U, Männel DN, Klein CA.

PLoS One. 2014 May 15;9(5):e97860. doi: 10.1371/journal.pone.0097860. eCollection 2014.

From 2015 AACR National Meeting in Philadelphia

LB-050: Patient-derived tumor xenografts in humanized NSG mice: a model to study immune responses in cancer therapy
Sunday, Apr 19, 2015, 3:20 PM – 3:35 PM
Minan Wang1, James G. Keck1, Mingshan Cheng1, Danying Cai1, Leonard Shultz2, Karolina Palucka2, Jacques Banchereau2, Carol Bult2, Rick Huntress2. 1The Jackson Laboratory, Sacramento, CA; 2The Jackson Laboratory, Bar Harbor, ME

References

  1. Paull KD, Shoemaker RH, Hodes L, Monks A, Scudiero DA, Rubinstein L, Plowman J, Boyd MR. J Natl Cancer Inst. 1989;81:1088–1092. [PubMed]
  2. Shi LM, Fan Y, Lee JK, Waltham M, Andrews DT, Scherf U, Paull KD, Weinstein JN. J Chem Inf Comput Sci. 2000;40:367–379. [PubMed]
  3. Monks A, Scudiero D, Skehan P, Shoemaker R, Paull K, Vistica D, Hose C, Langley J, Cronise P, Vaigro-Wolff A, et al. J Natl Cancer Inst. 1991;83:757–766. [PubMed]
  4. Potti A, Dressman HK, Bild A, et al. Genomic signatures to guide the use of chemotherapeutics. Nat Med. 2006;12:1294–1300. [PubMed]
  5. Baggerly KA, Coombes KR. Deriving chemosensitivity from cell lines: forensic bioinformatics and reproducible research in high-throughput biology. Ann Appl Stat. 2009;3:1309–1334.
  6. Carlson, B. Putting Oncology Patients at Risk Biotechnol Healthc. 2012 Fall; 9(3): 17–21.
  7. Salter KH, Acharya CR, Walters KS, et al. An Integrated Approach to the Prediction of Chemotherapeutic Response in Patients with Breast Cancer. Ouchi T, ed. PLoS ONE. 2008;3(4):e1908. NOTE RETRACTED PAPER

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Guidelines for the welfare and use of animals in cancer research

Model mimicking clinical profile of patients with ovarian cancer @ Yale School of Medicine

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Tumor Associated Macrophages: The Double-Edged Sword Resolved?

Posted in Cancer and Current Therapeutics, CANCER BIOLOGY & Innovations in Cancer Therapy, Immuno-Oncology & Genomics, tagged , , , , , , , , , , , , , , , on September 15, 2015| Leave a Comment »

Tumor Associated Macrophages: The Double-Edged Sword Resolved?

Writer/Curator: Stephen J. Williams, Ph.D.

UPDATED 10/04/2021 TAMs Enhance Tumor Hypoxia and Aerobic Glycolysis

Cell-based immunity is vital for our defense against pathologic insult but recent evidence has shown the role of cell-based immunity, especially macrophages to play an important role in both the development and hindrance of tumor growth, including role in ovarian, hematologic cancers, melanoma, and breast cancer.  In the past half century, new immunological concepts of cancer initiation and progression have emerged, including the importance of the harnessing the immune system as a potential anti-cancer strategy. However, as our knowledge of the immune system and tumor biology has grown, the field has realized an immunological conundrum: how can an immune system act to both prevent tumor growth and promote the tumor’s growth?

As discussed in the lower section of this post, authors of a paper in the journal Science show how different populations of tumor-associated macrophages (TAMs) may exert both positive and negative effects on tumor cells, producing a sort of ying-yang war between the tumor and the immune system.

The Immune System: Brief Overview and Role in Cancer

celllineageimmunesystem

Figure. Cell lineage of the immune system. A description of the different cell types can be found here.

Histologic evaluation of multiple tumor types, especially solid tumors, reveal the infiltration of diverse immunological cell types, including myeloid and lymphoid cell lineages, such as macrophages and NK, T cell and B cells respectively.

The immunological conundrum

immuncecancerconundrum

Figure. Potential inflammatory signaling pathways in breast cancer stem cells.
Breast cancer stem cells may be regulated by chemokine- and/or cytokine-mediated inflammatory signaling in an autocrine or paracrine manner. (from University of Tokyo at http://www.ims.u-tokyo.ac.jp/system-seimei/en/research2_e.htm)

Role of Tumor Associated Macrophages

There are conflicting reports as to the functional consequence of these infiltrating tumor-associated macrophages (TAMs). TAMs have been shown to secrete mediators such as interleukins and cytokines in a paracrine manner such as CCL2, IL10 and TGFβ. In certain instances these cytokines and mediators actually promote the growth of the surrounding tumors.

J Leukoc Biol 2009 Nov 86(5) 1065-73, Figure 1

Figure.  TAMs can be divided into subpopulations with distinctive functions and secretogogues.

For Further Reference

Tumor-associated macrophages and the profile of inflammatory cytokines in oral squamous cell carcinoma. http://www.ncbi.nlm.nih.gov/pubmed/23089461 anti-inflamm IL10 and TGFB

Tumor-associated macrophage-derived IL-6 and IL-8 enhance invasive activity of LoVo cells induced by PRL-3 in a KCNN4 channel-dependent manner

TAMscytokines

Figure 2: TAM functions in tumor progression. Tumor cells and stromal cells, which produce a series of chemokines and growth factors, induce monocytes to differentiate into macrophages. In the tumor, most macrophages are M2-like, and they express some cytokines, chemokines, and proteases, which promote tumor angiogenesis, metastasis, and immunosuppression. From Macrophages in Tumor Microenvironments and the Progression of Tumors

ICB-14-NC-BRONTE-V2

Macrophages integrate metabolic and environmental signals to promote tumor growth. Area within dotted rectangle indicates proposed mechanisms of action. ARG, arginase; HIF, hypoxia-inducible factor; MCT, monocarboxylate transporter; NADH, nicotine adenine dinucleotide, reduced; PKM2, M2 isoform of pyruvate kinase; VEGF, vascular endothelial growth factor from Tumor cells hijack macrophages via lactic acid adapted from Colegio OR, Chu N-Q, Szabo AL, Chu T, Rhebergen AM, Jairam V et al. Functional polarization of tumour-associated macrophages by tumour-derived lactic acid. Nature (e-pub ahead of print 13 July 2014; doi:10.1038/nature13490). | Article |

Depletion of M2-Like Tumor-Associated Macrophages Delays Cutaneous T-Cell Lymphoma Development In Vivo

Targeting tumor-associated macrophages in an orthotopic murine model of diffuse malignant mesothelioma

Crosstalk between colon cancer cells and macrophages via inflammatory mediators and CD47 promotes tumour cell migration

Tumor-Associated Macrophages Regulate Murine Breast Cancer Stem Cells Through a Novel Paracrine EGFR/Stat3/Sox-2 Signaling Pathway

Science Paper: Different Populations of TAMS Have Different Tumor Effects

The cellular and molecular origin of tumor-associated macrophages Eric G. Pamer1 Ruth A. Franklin1,2, Will Liao3, Abira Sarkar1, Myoungjoo V. Kim1,2, Michael R. Bivona1, Kang Liu4, Ming O. Li1, Science 23 May 2014: Vol. 344 no. 6186 pp. 921-925

A recent Science paper from Cornel has investigated the origin, function, and characterization of TAMs on breast cancer growth. In summary, their efforts and research suggest different populations of TAMs with varied tumorigenic effects, a finding which may help explain the immunologic conundrum with respect to solid tumors.

The authors characterized the infiltrating immune cell types in a MMTV-PyMt model of breast cancer.

The MMTV-PyMt mouse breast cancer model:

is a transgenic model where mammary gland expression of the polyoma middle T antigen (PyMT) is driven by the Mouse Mammary Tumor Virus promoter (MMTV).

Microbiol. Mol. Biol. Rev. 2009 Sep 73(3) 542-63, FIG. 5

For a review of mouse models of breast cancer please see

Mouse models of breast cancer metastasis. Anna Fantozzi1 and Gerhard Christofori. Breast Cancer Res. 2006; 8(4): 212.

Results

1.     Macrophages constitute the predominate myeloid cell population in MMTV-PyMT mammary tumors

Tumor infiltrating immune cells included

  • Myeloid cells comprised 50% of CD45+ infiltrating leukocytes.
  • The CD45 antigen, also known as Protein tyrosine phosphatase, receptor type, C (PTPRC) is an enzyme that, in humans, is encoded by the PTPRC gene, and acts as a regulator of B and T-lymphocytes.
  • Authors noted three types of cells classified as Type I, II, and III based on
  1. Cell morphology
  2. Major histocompatibility complex
  • Infiltrating monocytes and neutrophils
  • Cells with dendritic and macrophage markers

2. TAMS differentiate from CCR2+ inflammatory monocytes

  • To determine whether Ly6C+CCR2+ inflammatory monocytes contributed to TAMs and MTMs, authors crossed PyMT mice to Ccr2−/− mice and found MTMs (mammary tumor macrophages) were significantly reduced in Ccr2−/− PyMT mice, implying that MTMs are constitutively repopulated by inflammatory monocytes
  • To determine whether inflammatory monocytes were required for TAM maintenance, we generated CCR2DTR PyMT mice expressing diphtheria toxin receptor (DTR) under control of the Ccr2 locus DT treatment resulted in 96% depletion of tumor-associated monocytes compared to 80% depletion in Ccr2−/− mice
  • To investigate whether monocytes could differentiate into TAMs in vivo, we transferred CCR2+ bone marrow cells isolated from CCR2GFP reporter mice into congenically marked CCR2DTR PyMT mice depleted of endogenous monocytes, we observed transferred cells in developing tumors demonstrate that tumor growth induces the differentiation of CCR2+ monocytes into TAMs.

3.     TAMs are phenotypically distinct from AAMs (M2 or alternatively activated macrophages)

  • Gene-expression profiling revealed the integrin CD11b (Itgam) was expressed at lower levels in TAMs than in MTMs while several other integrins and the integrin receptor Vcam1 were up-regulated in TAMs
  • AM population did not express AAM markers such as Ym1, Fizz1, and Mrc1; instead, MTMs more closely resembled AAMs. The authors detected Vcam1 up-regulation on TAMs as a late differentiation event

4.    RBPJ-dependent TAMs modulate the adaptive immune response

  • In DCs, canonical Notch signaling mediated by the key transcriptional regulator RBPJ controls lineage commitment and terminal differentiation. To explore whether Notch signaling played a role in TAM differentiation, authors used CD11ccre mice that efficiently deleted floxed DNA sequences to a greater extent in TAMs than MTMs, but not in monocytes or neutrophils (fig. S14). CD11ccreRbpjfl/fl PyMT mice exhibited a selective loss of MHCIIhiCD11blo TAMs ( 4A). However, a MHCIIhiCD11bhi population still remained
  • Transcriptional profiling comparing this population to WT TAMs confirmed a loss of the Notch-dependent program in RBPJ-deficient cells revealing that in the absence of RBPJ, inflammatory monocytes are unable to terminally differentiate into TAMs.

UPDATED 10/04/2021 TAMs Enhance Tumor Hypoxia and Aerobic Glycolysis

Tumor-Associated Macrophages Enhance Tumor Hypoxia and Aerobic Glycolysis

From:

Tumor-Associated Macrophages Enhance Tumor Hypoxia and Aerobic Glycolysis
Hoibin Jeong, Sehui Kim, Beom-Ju Hong, Chan-Ju Lee, Young-Eun Kim, Seoyeon Bok, Jung-Min Oh, Seung-Hee Gwak, Min Young Yoo, Min Sun Lee, Seock-Jin Chung, Joan Defrêne, Philippe Tessier, Martin Pelletier, Hyeongrin Jeon, Tae-Young Roh, Bumju Kim, Ki Hean Kim, Ji Hyeon Ju, Sungjee Kim, Yoon-Jin Lee, Dong-Wan Kim, Il Han Kim, Hak Jae Kim, Jong-Wan Park, Yun-Sang Lee, Jae Sung Lee, Gi Jeong Cheon, Irving L. Weissman, Doo Hyun Chung, Yoon Kyung Jeon and G-One Ahn
Cancer Res February 15 2019 (79) (4) 795-806; DOI: 10.1158/0008-5472.CAN-18-2545

Abstract

Tumor hypoxia and aerobic glycolysis are well-known resistance factors for anticancer therapies. Here, we demonstrate that tumor-associated macrophages (TAM) enhance tumor hypoxia and aerobic glycolysis in mice subcutaneous tumors and in patients with non–small cell lung cancer (NSCLC). We found a strong correlation between CD68 TAM immunostaining and PET 18fluoro-deoxyglucose (FDG) uptake in 98 matched tumors of patients with NSCLC. We also observed a significant correlation between CD68 and glycolytic gene signatures in 513 patients with NSCLC from The Cancer Genome Atlas database. TAM secreted TNFα to promote tumor cell glycolysis, whereas increased AMP-activated protein kinase and peroxisome proliferator-activated receptor gamma coactivator 1-alpha in TAM facilitated tumor hypoxia. Depletion of TAM by clodronate was sufficient to abrogate aerobic glycolysis and tumor hypoxia, thereby improving tumor response to anticancer therapies. TAM depletion led to a significant increase in programmed death-ligand 1 (PD-L1) expression in aerobic cancer cells as well as T-cell infiltration in tumors, resulting in antitumor efficacy by PD-L1 antibodies, which were otherwise completely ineffective. These data suggest that TAM can significantly alter tumor metabolism, further complicating tumor response to anticancer therapies, including immunotherapy.

Significance: These findings show that tumor-associated macrophages can significantly modulate tumor metabolism, hindering the efficacy of anticancer therapies, including anti-PD-L1 immunotherapy.

Introduction

Tumor hypoxia and glycolysis have long been recognized as major resistance factors contributing to failures of chemo- and radiotherapy (1, 2). Traditionally, tumor hypoxia is known to occur by two mechanisms: chronic or acute hypoxia (2). Chronic hypoxia occurs as a result of rapid proliferation of cancer cells and hence being constantly forced away from blood vessels beyond the oxygen diffusion distance of approximately 150 μm (2). Acute hypoxia on the other hand occurs by a temporary cessation of the blood flow due to highly disorganized tumor vasculature (2). Regardless of the mechanism, tumor hypoxia has been extensively documented for their contribution to resistance to all anticancer therapies including chemotherapy (2), surgery (3), radiotherapy (2), and recently immunotherapy (4).

Aerobic glycolysis, also known as Warburg effect, is a phenomenon whereby many types of tumors exhibit a preference of glucose over the oxygen for their energy substrate (5), and this has allowed us to track solid tumors in patients with PET using 18fluoro-deoxyglucose (FDG) radioactive tracer (6). Although several mechanisms for Warburg effect have been suggested including mitochondrial defects, adaptation to hypoxia [hence activation of hypoxia-inducible factor (HIF)], and oncogenic signals such as MYC and RAS (7), the exact mechanism is still controversial. Tumor glycolysis has also been reported to influence the therapy outcome (8). Preclinical studies have suggested that glycolysis can increase DNA repair enzyme expressions including Rad51 and Ku70, which can facilitate radiation-induced DNA double-strand break repair (9). Lactate, a major byproduct of glycolysis, has recently been shown to be utilized as a fuel source for oxidative phosphorylation in nearby cancer cells (10), which can promote the tumor recurrence following anticancer therapies.

Tumor-associated macrophages (TAM) are bone marrow–derived immune cells recruited to tumors and have been extensively reported for their protumoral role (11). Recruited to tumors by various tumor-secreting factors including stromal cell–derived factor-1 (SDF1; ref. 12), VEGF (13), semaphorin 3A (14), and colony-stimulating growth factor-1 (CSF1; ref. 15), TAMs have been shown to produce various growth factors and proteases necessary for tumor survival (11) or immunosuppressive cytokines inhibiting antitumor immune responses (16). Macrophages in general are known to be polarized to either classically activated M1 macrophages or alternatively activated M2 phenotype depending on the cytokine milieu in which they are exposed (17). Bacterial-derived products such as lipopolysaccharide have been shown to polarize macrophages toward M1 phenotype (17), while parasite-associated signals such as IL4 and IL13 can lead to M2-polarized macrophages with increased tissue repair abilities (17). It has been suggested that TAMs are M2-like, although various subpopulations of TAM have been also identified including TIE2-positive macrophages (18), programmed cell death protein-1 (PD-1)–expressing TAM (19), and C-C chemokine receptor type-2 (CCR2)–expressing TAM (20).

In this study, we demonstrate clinically and preclinically that TAMs are a novel contributor to tumor hypoxia and aerobic glycolysis by competing oxygen and glucose with cancer cells. We further observed that TAM can significantly interfere with T-cell infiltration thereby masking programmed death-ligand 1 (PD-L1) expression in the tumors. We believe that our results have an important clinical implication such that patients with high infiltration of TAM in their tumors may poorly respond to all anticancer therapies, including the latest immunotherapy.

Figure 1.
Figure 1.

Strong correlations between TAM infiltration and glycolysis in patients with NSCLC. A, Representative PET/CT images for FDG uptake (top) and immunostaining of CD68 (bottom) from paired tumors of patients with NSCLC. Top, yellow circles, location of tumors. Bottom, red arrowheads, CD68-positive TAM. Scale bar, 100 μm. B, Correlation between glycolysis and CD68-positive TAM in 98 patients with NSCLC paired results as in A. Glycolysis was analyzed as FDG maximal standardized uptake value (FDG SUVmax; left) or 40% total lesion glycolysis (TLG; right). C, FDG SUVmax values for CD68low (n = 49) or CD68Hi (n = 49) NSCLC tumors. D, Subgroup analyses of FDG uptake in adenocarcinomas (n = 48; left) or squamous cell carcinomas (n = 50; right) of NSCLC. *, P < 0.05; ***, P < 0.001 in C and D as determined by the Student t test. Data are the mean ± SEM. E, TCGA analysis between CD68 and SLC2A1 (left) or HK2 (right) in 513 patients with adenocarcinoma NSCLC. P values are indicated in each plot.

TAMs make tumors more glycolytic

Figure 2.
Figure 2.

TAMs make tumors more glycolytic. A, Left, PET/MRI images for FDG uptake in LLC tumors in mice before (D0, top) and after (D2, bottom) Veh or Clod treatment. Yellow circles, tumors. Right, T2-weighted MR images of LLC tumors treated with Veh or Clod pre (top)- or post (bottom)- contrast. Red arrowheads in Veh tumor, ferumoxytol-labeled TAM. B, FDG uptake SUVmax in A. **, P < 0.01, determined by two-way ANOVA. C, FACS plot indicating HoechstbrightKeratin+ (red boxes) population of cells sorted as aerobic cancer cells. D, Fold changes in gene expression in FACS-sorted aerobic cancer cells from LLC tumors treated with Clod or Veh. E, Glucose uptake (left) and lactate production (right) from the sorted aerobic cancer cells as in C. Data in D and E are the mean ± SEM from at least triplicate samples. *, P < 0.05; ***, P < 0.001 by the Student t test. F, Western blot of FACS-sorted aerobic cancer cells in C for GLUT1. β-Actin was used as the loading control. G, Oxygen consumption kinetics in FACS-sorted aerobic cancer cells as described in C. H, LLC tumor growth in mice treated with Veh, Clod, Veh + metformin (Veh + Met), or Clod + metformin (Clod + Met). *, P < 0.05; **, P < 0.01; ***, P < 0.001, determined by two-way ANOVA. I, LLC tumor growth in mice treated with Veh, Clod, Veh + 2-DG, or Clod + 2-DG. Data in H and I are the mean ± SEM, with number of animals indicated in the graphs.

TAMs secrete TNFα to promote tumor glycolysis

Figure 3.
Figure 3.

Macrophages secrete TNFα to facilitate glycolysis in cancer cells. A, Gene expression changes in LLC cocultured with (LLC+BMDM) or without (LLC) BMDM. Data are the mean ± SEM from at least triplicate determinations. B, Glucose uptake (left) and lactate production (right) in LLC cocultured with or without BMDM. Data are the mean ± SEM for triplicate samples per group. **, P < 0.01 by Student t test. C, Glucose uptake in LLC cultured alone, cocultured with BMDM, or cocultured with BMDM with glucose added back to the LLC compartment of the coculture system. Data are the mean ± SEM for n = 4 replicates per group. *, P < 0.05; **, P < 0.01 by one-way ANOVA. D, Antibody cytokine arrays in the supernatant obtained from BMDM culture with (BMDM+LLC) or without (BMDM) LLC. Red boxes indicate those cytokines whose expressions were increased in BMDM cocultured with LLC compared with BMDM alone. Blue box, CXCL1, a cytokine produced by LLC cancer cells themselves (Supplementary Fig. S2D). E, Luminex cytokine assays for TNFα in the supernatant from culture media, LLC alone, BMDM alone, or BMDM cocultured with LLC. Data are the mean ± SEM for n = 3 replicates per group. ***, P < 0.001 by one-way ANOVA. F, Glucose uptake in LLC alone (none), LLC cocultured with BMDM (+BMDM), or LLC treated with TNFα (+TNFα) or with IFNγ (+IFNγ). Data are the mean ± SEM from n = 3 samples per group. **, P < 0.01; ***, P < 0.001 by one-way ANOVA. G, Western blot for LLC cells treated with increasing concentrations of recombinant TNFα protein for GLUT1, HK2, or PGC-1α. β-Actin was used as the loading control. H, TNFα concentrations in the supernatant from LLC cultured with (+BMDM) or without (alone) BMDM, or in BMDM cultured with (+LLC) or without (alone) LLC, measured by ELISA. BD, below the detection limit. **, P < 0.01 by Student t test. I, Immunostaining of TNFα (red) and CD68 (green) in LLC tumors grown in mice. Nuclei are shown in blue with DAPI counterstaining. The inset shows magnified regions where indicated with the asterisk (*). White arrowheads, CD68-positive TAM-expressing TNFα. Scale bar, 100 μm. J, TNFα concentrations measured by ELISA in the supernatant from CD11b and F4/80 double-positive TAM sorted by FACS. Data are the mean ± SEM from triplicate determinations. ***, P < 0.001, determined by one-way ANOVA. K, TCGA analysis of clinical correlations between CD68 and TNF (left) or between TNF and HK2 (right) in 513 patients with adenocarcinoma NSCLC. P values are indicated in each plot.

TAMs exacerbate tumor hypoxia

Figure 4.
Figure 4.

TAMs directly contribute to tumor hypoxia. A, Immunostaining of LLC tumors grown in mice for TAM by using S100A8 (red) and hypoxia by using pimonidazole (PIMO; green) antibodies. Nuclei are shown in blue with DAPI counterstaining. B, FACS analysis demonstrating that CD11b and F4/80 double-positive TAMs are pimonidazole-positive. C, Gene expression in CD11b and F4/80 double-positive TAM isolated from LLC tumors compared with those in cultured BMDM. Data are the mean ± SEM from triplicate determinations. D, Two-photon microscopy images of the dorsal window chamber whereby 5 × HRE-GFP–expressing LLC tumors had been implanted. Images were taken at 24 hours after a single intratumoral injection of PBS (+PBS) or PBS containing FACS-sorted TAM (+TAM). Scale bars in A and D, 100 μm. E, Representative FACS plots demonstrating HoechstbrightKeratin+ as aerobic tumor cells (red boxes) and HoechstdimKeratin+ as hypoxic tumor cells in LLC tumors grown in mice treated with Veh or Clod. F, Quantification of aerobic or hypoxic tumor cells in E. Data are the mean ± SEM for n = 6 mice per group. *, P < 0.05 by Student t test. G, TCGA analysis between CD68 and HIF1A in 513 patients with adenocarcinoma NSCLC. P value is indicated in the graph. H, Growth of LLC tumor treated with Veh or Clod immediately prior to a single dose of 20 Gy ionizing irradiation. *, P < 0.05 by two-way ANOVA.

 

Other posts on this site on Immunology and Cancer include

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Innovations in Tumor Immunology

T cell-mediated immune responses & signaling pathways activated by TLRs

Vaccines, Small Peptides, aptamers and Immunotherapy [9]

Report on Cancer Immunotherapy Market & Clinical Pipeline Insight

Molecular Profiling in Cancer Immunotherapy: Debraj GuhaThakurta, PhD

Immunotherapy in Cancer: A Series of Twelve Articles in the Frontier of Oncology by Larry H Bernstein, MD, FCAP

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The Human Proteome Map Completed

Posted in Big Data, BioIT: BioInformatics, Cancer - General, Cancer and Current Therapeutics, Cancer Genomics, Cancer Informatics, cancer metabolism, Cell Biology, Signaling & Cell Circuits, Curated, Genomic Expression, Inflammasome, KRAS Mutation, Metastasis Process, Proteins, Proteomics, TP53 - Germline mutations, Transcriptomics, tagged , , , , , on August 28, 2014| Leave a Comment »

The Human Proteome Map Completed

Reporter and Curator: Larry H. Bernstein, MD, FCAP

UPDATED 6/02/2024

The genetic, pharmacogenomic, and immune landscapes associated with protein expression across human cancers.

Source: Chen C, Liu Y, Li Q, Zhang Z, Luo M, Liu Y, Han L. The Genetic, Pharmacogenomic, and Immune Landscapes Associated with Protein Expression across Human Cancers. Cancer Res. 2023 Nov 15;83(22):3673-3680. doi: 10.1158/0008-5472.CAN-23-0758. PMID: 37548539; PMCID: PMC10843800.

Abstract

Proteomics is a powerful approach that can rapidly enhance our understanding of cancer development. Detailed characterization of the genetic, pharmacogenomic, and immune landscape in relation to protein expression in cancer patients could provide new insights into the functional roles of proteins in cancer. By taking advantage of the genotype data from The Cancer Genome Atlas (TCGA) and protein expression data from The Cancer Proteome Atlas (TCPA), we characterized the effects of genetic variants on protein expression across 31 cancer types and identified approximately 100,000 protein quantitative trait loci (pQTL). Among these, over 8000 pQTL were associated with patient overall survival. Furthermore, characterization of the impact of protein expression on more than 350 imputed anticancer drug responses in patients revealed nearly 230,000 significant associations. In addition, approximately 21,000 significant associations were identified between protein expression and immune cell abundance. Finally, a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), was developed featuring multiple modules that enable researchers to explore, visualize, and browse multidimensional data. This detailed analysis reveals the associations between the proteomic landscape and genetic variation, patient outcome, the immune microenvironment, and drug response across cancer types, providing a resource that may offer valuable clinical insights and encourage further functional investigations of proteins in cancer.

Introduction

Functional proteomics is a powerful approach that helps us understand cancer pathophysiology and identify potential therapeutic strategies (). Functional protein analysis using reverse-phase protein arrays (RPPA) has already proven highly effective in studying large numbers of TCGA samples, especially when integrated with genomic, transcriptomic, and clinical information (). Previous works demonstrated that a QTL mapping approach is effective to understand the genetic basis of multiple molecular features in human diseases (). Identifying the sequence determinants of protein levels (pQTLs) may guide the search for causal genes and facilitate understanding the underlying mechanisms of human diseases. However, it remains challenging to further understand the functional roles of protein expression in cancers. For example, it is unclear whether proteins are associated with drug response and/or immune features in patients. In this study, we systematically investigated the effects of genetic variants on protein expression and characterized the impact of protein expression on imputed drug responses and immune cell abundances from different sources (Fig. 1). To facilitate broad access of these data for the biomedical research community, we developed a user-friendly database, GPIP (https://hanlaboratory.com/GPIP). We expect this study to have a significant clinical impact on the future development of protein-based targeted therapies.

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Impact of genetic variants on protein expression.

A Workflow of GPIP to identify pQTLs and survival-associated pQTLs. B The number of pQTLs identified for each cancer type. C Association between CYCLINB1 protein expression level and rs12576855 in LUAD patients. D Association between CYCLINB1 protein expression level and rs2722796 in LGG patients. E The number of survival-associated pQTLs identified for each cancer type. F Kaplan–Meier plot showing the association between rs10918659 (pQTL of HER2_pY1248) genotypes and overall survival times of STAD patients. G Kaplan–Meier plot showing the association between rs13158796 (pQTL of HER2_pY1248) genotypes and overall survival times of STAD patients.

Identification of protein–drug associations

To investigate potential associations between protein expression and drug response, we calculated the Spearman rank correlation between protein expression data and drug response from DrVAEN and cancerRxTissue. These two datasets employed distinct predictive models that integrated omics data from CCLE and drug response data from GDSC to predict drug response in TCGA samples (Fig. 2A) (,). Association with |Rs| > 0.3 and FDR < 0.05 were considered as significant associations in each cancer type.

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Exploring the pharmacogenomics of protein in human cancer.

A Workflow of GPIP to identify Drug-associated proteins. B The number of protein-drug response pairs identified from DrVAEN (left) and cancerRxTissue (right) for each cancer type. C Visualization of the associations between proteins and drugs (DrVAEN) within and across different cancer signaling pathways. Blue links represent associations within a single pathway, while orange links represent associations cross pathways. D Enrichment analysis of drug target pathways among significant protein-drug response pairs. The color represents the log2 (odds ratio) of Fisher’s exact test. The size represents the FDR value.

Identification of protein–immune cell associations

To examine the relationship between protein expression and immune cell abundance, we utilized Spearman rank correlation coefficient to calculate the associations between protein expression data and immune cell abundance data from TIMER, CIBERSORT, ImmuneCellAI, and ImmuneCellGSVA (Fig. 3). These datasets utilized different methods to evaluate immune cell abundance by leveraging immune gene signatures as a proxy (–). We considered correlations with |Rs| > 0.3 and FDR < 0.05 as significant associations.

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Exploring the immune landscapes of protein in human cancer.

A Workflow of GPIP to identify Immune cell-associated proteins. B The number of protein-drug response pairs identified from ImmuneCellsGSVA (purple), ImmuCellAI (yellow), TIMER (red) and CIBERSORT (green) for each cancer type. C The top 10 proteins with the highest number of significantly associated immune cell types in HNSC. The color represents the Rs between protein expression and immune cell abundance (ImmuneCellGSVA). The size represents the FDR value. D Association between PREX1expression and impute MDSC abundance in HNSC patients.

Database construction

GPIP was developed using Python Flask-RESTful API frameworks (https://flask-restful.readthedocs.io/), AngularJS (https://angularjs.org), and Bootstrap (https://getbootstrap.com/). The database for GPIP was implemented using the NoSQL database program MongoDB (https://www.mongodb.com/). The user-friendly interface of the GPIP web application was served through the Apache HTTP Server, allowing users to access the database and perform queries and analysis through a web browser.

Data availability

All results generated in this study can be found in GPIP database, (https://hanlaboratory.com/GPIP). Publicly available data generated by others were used by the authors in this study: The genotype data and clinical data were obtained from The Cancer Genome Atlas (TCGA) data portal at https://tcga-data.nci.nih.gov/tcga/. The reverse-phase protein array (RPPA) protein expression data was obtained from The Cancer Proteome Atlas (TCPA) data portal at https://www.tcpaportal.org/. The imputed pharmacogenomic data were obtained from DrVAEN at https://bioinfo.uth.edu/drvaen/ and cancerRxTissue at https://manticore.niehs.nih.gov/cancerRxTissue/. The immune-cell infiltration data were obtained from Tumor Immune Estimation Resource (TIMER) at http://timer.cistrome.org/, Immune Cell Abundance Identifier (ImmuCellAI) at http://bioinfo.life.hust.edu.cn/ImmuCellAI/, and CIBERSORT at https://cibersort.stanford.edu/.

A comprehensive data portal

We developed a user-friendly data portal, GPIP (https://hanlaboratory.com/GPIP), to facilitate visualizing, searching, and browsing of our results by the biomedical research community (Fig. 4A). GPIP contains four main modules: Protein-QTLs, Surivial-QTLs, Drug Response, and Immune Infiltration (Fig. 4B). Querying can be easily performed by selecting cancer type, protein, drug, immune cell abundance, or entering the SNP ID of interest (Fig. 4C). For example, in the Protein-QTLs and Survival-QTLs modules, users can search for pQTLs by selecting a cancer type (e.g., LUAD) and entering a protein name (e.g., CYCLINB1) or an SNP ID (e.g., rs12576855). In the Drug Response module, users can search for protein-drug response associations by selecting a data source for imputed drug response (e.g., DrVAEN) and selecting an anticancer drug (e.g., Talazoparib) or a protein (e.g., PARP1). In the Immune Infiltration module, users can search for protein-immune infiltration pairs by selecting a data source for imputed immune cell abundance (e.g., ImmuneCellsGSVA), and selecting an immune cell type (e.g., Activated B cell) or a protein (e.g., PDL1). In addition, on the bottom of the main page, we developed a cancer type module where users can click on a specific cancer type (e.g., BLCA) to search for related information across all 4 modules (Fig. 4D). The search results for each module included a table to list related information accordingly (Fig. 4E). A “Details” button for each result item was clicked for generating a box plot in protein-QTLs module (Fig. 4F), a Kaplan–Meier plot in Survival-QTLs module (Fig. 4G) and a scatter plot in Drug Response and Immune Infiltration modules, respectively (Fig. 4H, ​,I).I). Our database provides a valuable resource for cancer research and will be of great interest to the research community.

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Content and interface of GPIP.

A GPIP homepage and browser bar. B The four main modules of GPIP. C Search boxes in the pQTLs module. D Search boxes in the cancer type-specific search module. E An example of resulting list in the pQTL module. F An example of boxplot for the pQTLs module result. G An example of Kaplan–Meier plot for the Survival protein-QTLs module result. H An example of scatter plot for the Drug Response module result. I An example of scatter plot for the Immune Infiltration module result.

Discussion

Proteomics plays a crucial role in identifying potential therapeutic strategies and understanding cancer pathophysiology (). In this study, we investigated the effects of genetic variants on protein expression and characterized the impact of protein expression on imputed drug responses and immune cell abundances across human cancers. We also developed the user-friendly data portal, GPIP, to provide access to these results. Our study provides a comprehensive analysis of protein expression in different cancer types and their association with drug response and immune cell abundance.

Identifying genetic variants associated with cancer has revolutionized our understanding of the disease and holds promise for improved diagnosis and treatment. In GPIP, we identified ~100,000 pQTLs across 31 cancer types and 8.8% of them were found to be associated with patient survival (Fig. 1). These genetic variants hold significant promise for unraveling the underlying biological mechanisms of disease progression and response to treatments. For example, a survival-associated pQTL may help to identify a genetic variant that controls the expression of a protein crucial for tumor growth or immune response, thus impacting patient survival. Our results suggest that pQTLs have the potential to serve as prognostic biomarkers and aid in the development of precision medicine.

Despite the promising implications, it is crucial to consider potential limitations of pQTL identification. One limitation is the small number of tumor samples in rare cancers, which limits statistical power and the detection of significant pQTLs. For example, only 8 proteins with pQTLs were found in CHOL, likely due to the small sample size (Table S1). Additionally, we observed that some cancer types with large sample sizes identified only a small number of pQTLs (e.g., BRAC), possibly due to the data quality of protein abundance. Tumors originating from different tissues may have variations in protein extraction quality or protein measurement accuracy (). Furthermore, cancer type heterogeneity can impact pQTL identification, as tumors from different tissues exhibit distinct protein expression profiles and genetic landscapes. Addressing these limitations is necessary to ensure valid and reliable results.

Protein expression levels in tumors can impact response of cancer cells to therapeutic drugs due to their role as targets of drug action, with alterations in expression potentially modifying drug sensitivity or resistance. In GPIP, we utilized the imputed drug response and protein expression data in TCGA patients to identify the potential associations between protein expression and drug response (Fig. 2). Our results revealed that certain proteins were significantly associated with drug sensitivity or resistance, suggesting that protein expression levels could potentially be used as biomarkers to predict drug response in cancer patients. Recent studies have shown that the impact of genetic variants on drug response can be mediated through protein-protein interaction (PPI) networks (,). Integrating genetic variants and PPI to further understand the associations between protein expression and drug response may provide further insights.

The protein expression level in tumors is crucial in the context of tumor immune microenvironment and immunotherapy, as it might impact immune cell abundance and response, and potentially improve the efficacy of immunotherapy. In GPIP, we examined the association between protein expression levels and imputed immune cell abundance across multiple cancer types. Our study identified ~21,000 significant correlations between proteins and immune cell types, highlighting the potential role of protein expression levels in shaping the tumor immune microenvironment (Fig. 3). Our results offer a promising avenue for future research to understand the interplay between protein expression and the tumor immune microenvironment, leading to personalized immunotherapy strategies and better treatment outcomes for cancer patients.

In summary, GPIP is a comprehensive and multifaceted data platform designed to aid functional and clinical research on protein in cancer patients. As more relevant datasets become available, we will continually update GPIP to ensure its relevance and usefulness to the research community.

​

Significance:

Comprehensive characterization of the relationship between protein expression and the genetic, pharmacogenomic, and immune landscape of tumors across cancer types provides a foundation for investigating the role of protein expression in cancer development and treatment.

Researchers Produce First Map of Human Proteome, and Reveal New
Significance in The Human Proteome

HAHNE, TECHNISCHE UNIVERSITÄT MÜNCHENTwo international teams have
independently produced the first drafts of the human proteome. These curated
catalogs of the proteins expressed in most non-diseased human tissues and
organs can be used as a baseline to better understand changes that occur in
disease states. Their findings were published today (May 29) in Nature.

Both teams uncovered new complexities of the human genome, identifying novel
proteins from regions of the genome previously thought to be non-coding.

“the real breakthrough with these two projects is the comprehensive coverage of
more than 80 percent of the expected human proteome” said Hanno Steen, director
of proteomics at Boston Children’s Hospital, who was not involved in the work.

The human proteome map provides a catalog of proteins expressed in nondiseased tissues and organs to use as baseline in understanding changes that occur in disease

Given the growing importance of proteins in medical laboratory testing,

Experts are comparing this to the first complete map of the human genome

  • and this information provides for rapid advances
  • in understanding transcriptomics and metabolomics

Map of Human Proteome Expected to Advance Medical Science

“Housekeeping genes” that are expressed in all tissues and cell types

  • have been thought to be involved in basic cellular functions.

Two teams developing a Human Proteome Map

  • detected proteins encoded by 2,350 genes
  • across all human cells and tissues.

The corresponding housekeeping proteins comprised
about 75% of total protein mass.

  •  histones,
  • ribosomal proteins,
  • metabolic enzymes, and
  • cytoskeletal proteins

The two international teams produced

  • the first drafts of the human protoeome,
  • a catalog of proteins expressed in most
  • nondiseased human issues and organs.

The evidence suggests there is translation from DNA regions

  • that were not thought to be translated—including
  • more than 400 translated long, intergenic non-coding RNAs (lincRNAs)—
    found by the Küster team—and
  • 193 new proteins—uncovered by the Pandey team.

This proteome map can be used as a baseline to understand

  • changes that occur in the disease state

These studies are part of the Human Proteome Project,

  1. an international effort by the Human Proteome Organization
  2. to revolutionize our understanding of the human proteome
  3. by coordinating research at laboratories around the world directed
  4. at mapping the entire human proteome.

This new information about the human proteome

  • is expected to trigger rapid advances in medical science
  • and a better understanding of the underlying causes of human diseases.

One Study Team Was at Johns Hopkins University

  • In one study, which was headed by Ahilesh Pandey, M.D.,
    at Johns Hopkins University in Baltimore,
  • and colleague Harsha Gowda, Ph.D.,
    of the Institute of Bioinformatics in Bangalore, India,
  • the research team used an advanced form of mass spectrometry to analyze proteins
  • to create the human proteome map,

according to a report published in NIH Research Matters.

The research team examined

  1. 30 normal human tissue and cell types:
  2. 17 adult tissues,
  3. 7 fetal tissue and
  4. 6 blood cell types.

Samples from three people per tissue type

  • were processed through several steps.

The protein fragments, or peptides, were analyzed on

The amino acid sequences were

  • then compared to known sequences.

Their results were published in the May 28, 2014, issue of Nature.

The resulting draft map of the human proteome map includes

  • proteins encoded by more than 17,000 genes,
  • noted the Research Matters article.

Among these are hundreds of proteins from regions

  • previously thought to be non-coding.

This study also provided a new understanding of

  • how genes are expressed.

For example, almost 200 genes begin in locations

  • other than those predicted based on genetic sequence.

“The fact that 193 of the proteins came from DNA sequences

  • predicted to be non-coding means that
  • we don’t fully understand how cells read DNA,
  • since the sequences code for proteins

This study also produced the Human Proteome Map,

  • an interactive online portal.

This can be accessed at this link.

The study data will soon be accessible through

German’s ProteomicsDB Analyzed a Mix of Available and New Tissue Data

The other study was conducted by a team lead by  Bernhard Küster
of the Technische Universität München in Germany.

Küster and his colleagues created a

This database contains 92% of the

  • estimated 19,629 human proteins,

noted The Scientist article.

Küster’s team also used mass spectrometry

  • to analyze human tissue samples.

This team’s approach differed from Johns Hopkins’ in that

  • it compiled about 60% of the information
  • in the ProteomicsDB database
  1. by using existing raw mass spec (MS) data
  2. from databases and colleagues’ contributions.

To fill data gaps, the Küster lab generated its own
MS data after analyzing

  1. 60 human tissues,
  2. 13 body fluids, and
  3. 147 cancer cell lines.

High-resolution public data

  • was selected and computationally processed
  • for strict quality

The database for ProteomicsDB is

  • public and searchable.

It can be accessed at this link.

German Study Added New Insights to Transcription Process

Comparing the ratio of protein to mRNA levels for every protein globally,

  • the Küster lab found that the translation rate
  • is a constant feature of each mRNA transcript. 

The proteomics community has viewed

  • transcriptome and proteome data as two sides of a coin.

But this analysis shows that at least, at steady state,

  • once the ratio for an mRNA/protein pair has been calculated,
  1. protein levels can be determined
  2. just from specific mRNA levels.

Proteomics researchers in Toronto maintaining ionic balance and in Boston commented on the
importance of the findings, even a “new paradigm” because of

  • the fixed ratio of protein to mRNA

This is quite in keeping with what we have been learning

  • with respect to homeostasis.

In 2003, the Human Genome Project created a

  • draft map of the human genome—
  • all the genes in the human body.

Genomics has since driven many advances in medical science.

This was a progress from the classic discovery of Watson and Crick –

  • the classical dogma holds that
  • DNA makes RNA makes protein.
  • no constraints are place on this

But the cell is functioning in contact with other cells,

  • immersed in interstitial fluid
  • maintaining cationic and anionic balance
  • and mitochondrial energy balance and ubiquitin systems interact
  • and protein interacts with the chromatin and transcriptional RNA

So the restriction that has been discovered has credence,

  • the classical diagram has to be redrawn

Deeper Knowledge of Proteome to Improve Diagnostics and Therapeutics

In the two projects is:

  • the comprehensive coverage of more than 80% of
  • the expected human proteome,

These studies indicate that to get to

  • a deep level of proteome coverage,
  • many different tissue types must be probed.

the  studies are  complimentary.

  1. The Hopkins group provided a survey of human proteins from a single source, which allows for easy comparisons within their data.
  2. The ProteomeDB effort connected new information with existing data

A deeper knowledge of the human proteome could help

  • fill the gap between genomes and phenotypes.

As this occurs, it has the potential to transform

  • the way diagnostics and therapeutics are developed,
  •  enhancing overall biomedical research and healthcare,

it was noted in a report presented to scientific leaders at a NIH workshop

  • on advances in proteomics and its applications.

Having completed a draft map of the human proteome—
the set of all proteins in the human body

  • It opens another window to cell function.

It has been ASSUMED –

  • genes control the most basic functions of the cell,
  • including what proteins to make and when.
  • but we have assumed for too much in assigning
    full control to the genome

Researchers have identified more than 20,000 protein- coding genes.

However, scientific understanding of the proteome has

  • lagged behind that of the genome,
  • partly because of the proteome’s complexities.

The relationship between genes and proteins isn’t a simple matter of

  • one gene coding for one protein.

Stretches of DNA can be read and translated

  • into proteins in different ways.

Proteins are also more difficult to sequence than genes.

The importance of these latest studies to pathologists and Ph.D.s working

  • in molecular diagnostics laboratories is that
  • this information will expedite further research into the human proteome.

Such research is expected to lead to

  • novel methods of diagnosis and complex
  • “multi-analyte” clinical laboratory tests that
  • look for multiple proteins in a single assay.

“The prevalent view was that information transfer was from genome to transcriptome to proteome.
What these efforts show is that it’s a two-way road— proteomics can be used to annotate the genome.
The importance is that, using these datasets, we can improve the annotation of the genome and the
algorithms that predict transcription and translation,” said Steen. “The genomics field can now hugely
benefit from proteomics data.”

Wilhelm et al., “Mass-spectrometry- based draft of the human proteome,”
Nature,  http://dx.doi.doi:/10.1038/nature13319, 2014

M.S. Kim et al. “A draft map of the human proteome,”
Nature,  http://dx.doi.org:/10.1038/nature13302, 2014.

Tags

proteomics, noncoding RNA, human research, human proteome project, human genetics and genomics

http://www.the-scientist.com/?articles.view/articleNo/40083/title/Human-Proteome-Mapped/

 

__Patricia Kirk

__by Harrison Wein, Ph.D.

__by Anna Azvolinsky

Related Information:

Revealing The Human Proteome

Human Proteome Mapped

The human proteome – a scientific opportunity for transforming diagnostics, therapeutics, and healthcare

Reference: A draft map of the human proteome.
Kim MS, Pinto SM, Getnet D, Nirujogi RS, Manda SS, Donahue CA, Gowda H, Pandey A.
Nature. 2014 May 29;509(7502):575-81. http://dx.doi.org:/10.1038/nature13302. PMID: 24870542

Funding: NIH’s National Institute of General Medical Sciences (NIGMS), National Cancer Institute (NCI),
and National Heart, Lung, and Blood Institute (NHLBI); the Sol Goldman Pancreatic Cancer Research Center;
India’s Council of Scientific and Industrial Research; and Wellcome Trust/DBT India Alliance.

http://nihprod.cit.nih.gov/researchmatters/june2014/06092014proteome.htm

 

 

 

 

 

 

 

 

 

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Upcoming Meetings on Cancer Immunogenetics

Posted in Academic Publishing, BioSimilars, CANCER BIOLOGY & Innovations in Cancer Therapy, Health Economics and Outcomes Research, Human Immune System in Health and in Disease, Immunodiagnostics, Innovation in Immunology Diagnostics, Monoclonal Immunotherapy, Scientific & Biotech Conferences: Press Coverage, tagged , , , , , , , , , , , , on August 22, 2014| Leave a Comment »

Upcoming Meetings on Cancer Immunogenetics

 

Curator: Stephen J. Williams, Ph.D.

Below is a curation of upcoming 2014-15 Cancer Immunogenetics symposia. Some listed have CME credits.

August 2014

Target Discovery for T Cell Therapy Symposium
Next Step to Advance Immunotherapies
August 14, 2014 | Part of ImVacS – The Immunotherapies and Vaccine Summit
Learn more | View Agenda PDF | Register by July 18 & SAVE up to $200

 

Q&A with Dr. Adrian Bot of Kite Pharma

 

SITC 2014 Meetings

The Society for Immunotherapy of Cancer (SITC) is a 501 (c)(3) non-profit society of medical professionals. Recent advances in immunology and biology have opened up new horizons in the field of cancer therapy, with an upsurge in the integration of new biologic agents into clinical practice. With several high-caliber scientific meetings with a focus on clinical and translational aspects of biologic approaches to cancer treatment and numerous networking opportunities unique to this organization, the Society for Immunotherapy of Cancer (SITC) has developed into the premier destination for interaction and innovation in the cancer biologics community.

Upcoming SITC Meetings and Activities

sitc banner

Advances in Cancer Immunotherapy™ (ACI™) Regional CME-Certified Programs

  • La Jolla, CA – Friday, August 22, 2014
  • Portland, OR – Friday, October 3, 2014
    Charlotte, NC – Friday, October 3, 2014
  • Tampa, FL – Friday, December 5, 2014

 ACI

September 2014

 

 aacrmeetinghemoto2014
  Hematologic Malignancies: Translating Discoveries to Novel Therapies
    September 20-23, 2014 • Sheraton Philadelphia Downtown • Philadelphia, PA

The AACR is proud to announce our conference focused on the blood-based cancers and associated disorders categorized as hematologic malignancies. Sessions will include presentations on leukemia, lymphoma, myeloma, myelodysplastic syndrome, and myeloproliferative neoplasms.

 

Advances in Melanoma: From Biology to Therapy

Loews Philadelphia • Philadelphia, PA • September 20-23, 2014

With so many recent advances in treating metastatic melanoma, including approaches like immunotherapies, targeted therapies, and combination therapies, melanoma research is at a critical point where it is extremely important for the field to have a continuous exchange of information. Despite the success of various “targeted” inhibitors, therapeutic responses in melanoma patients are often short-lived due to rapidly acquired drug resistance. Therefore, it is essential that melanoma researchers translate the novel understanding of melanoma biology to decipher the mechanisms of innate and acquired drug resistance for the development of improved therapeutic options. To bridge the gap between scientists and clinician-scientists’ professional practice, this conference will provide a platform for discussion and potential collaborations for the discovery of new therapeutic targets.

 
 proimmunegif

The 4th Mastering Immunogenicity Summit

September 15-16, 2014

British Consulate-General, Boston MA, USA

Join leaders in the immunogenicity field for a two day conference to learn what constitutes a successful strategy for managing immunogenicity risk, and explore the business case for introducing immunogenicity assessment into your program.

  • Learn about the latest strategies and exciting new technologies
  • Discuss current and developing challenges and exchange new ideas
  • Improve the outcome of your R&D programs

Our 4th Mastering Immunogenicity Conference will continue to have a strong focus on immunogenicity sciences, particularly on what basic research needs to be carried out to improve our understanding of immune regulation to biotherapeutics. We will review progress made in correlating data from pre-clinical predictive tools to clinical outcomes, as well as continuing our discussions surrounding the benefits that Quality by Design has on reduced immunogenicity, considering subsequent patient benefits as well as competitive advantage. Presentations by experts will provide an overview of the wide range of technologies currently used for immunogenicity risk management and how they can be incorporated for a ‘quality by design’ approach.

 

Immunogenomics 2014

September 29 – October 1, 2014

HudsonAlpha Biotechnology Campus
Huntsville, Alabama, USA

The HudsonAlpha-Science Conference on Immunogenomics will bring together preeminent leaders and thinkers at the intersection of genomics and immunology.

October 2014

canerrersinstlogo

Cancer Immunotherapy: Out of the Gate

October 06, 2014 Grand Hyatt New York Hotel at Grand Central, New York, NY

The Cancer Research Institute (CRI) will host its 22nd Annual International Cancer Immunotherapy Symposium October 6-8, 2014 at The Grand Hyatt in New York City. Attracting clinicians, laboratory scientists, postdoctoral fellows, and graduate students, the symposium will feature plenary presentations from leaders in immunology and cancer immunotherapy, a poster session, and numerous networking opportunities.

This year’s CRI symposium, entitled Cancer Immunotherapy: Out of the Gate, will harness the excitement and enthusiasm generated by recent clinical successes to explore new and emerging areas of basic, translational, and clinical research. Topics such as the use of genomic methods to catalogue cancer heterogeneity, mechanistic studies of checkpoint blockage antibodies, new views on immunosurveillance and immunoregulation, and emerging therapies that are altering the landscape of cancer treatment will be discussed.

– See more at: http://www.cancerresearch.org/grants-programs/conferences-meetings/annual-international-cancer-immunotherapy-symposia/2014-symposium#sthash.PnY56e5E.dpuf

Cytokines 2014

October 26–29, Melbourne, Australia

EMBO Conference: Innate Lymphoid Cells
September 29–October 1, Paris, France

Recommended reading

Laurie Dempsey

 

November 2014

SITC 2014 – November 6-9, 2014

  • Gaylord National Hotel & Convention Center, National Harbor, MD
  • SITC 29th Annual Meeting
  • SITC Workshop on Combination Immunotherapy: Where Do We Go From Here?
  • SITC Primer on Tumor Immunology and Cancer Immunotherapy™
  • SITC Hot Topic Symposium – including two topics explored concurrently:
    • Accelerating Tumor Immunity with Agonist Antibodies
    • Engineered T Cell Toxicities
  • Professional Development Session: A Roadmap for Thriving in Your Career

The Fourth International Conference on Regulatory T cells and TH Subsets and Clinical Application in Human Diseases
November 1–4, Shanghai, China

Recommended reading
Olive Leavy

 

eortspainmeeting

 

 

Keystone Symposium: Cell Death Signaling in Cancer and the Immune System
October 28-November 2, Sao Paolo, Brazil

Recommended reading

December 2014

Tumor Immunology and Immunotherapy: A New Chapter
Co-Chairpersons: Robert H. Vonderheide, Nina Bhardwaj, Stanley Riddell, and Cynthia L. Sears
December 1-4, 2014 • Orlando, FL

2015 Conferences

Keystone Symposia on Molecular and Cellular Biology

Tumor Immunology: Multidisciplinary Science Driving Combination Therapy 

February 8—13, 2015

Fairmont Banff Springs, Banff, Alberta, Canada

 

· March 2015

  1. 8–13, Montreal, Quebec, Canada
  2. 22–27, Banff, Alberta, Canada
  3. 29–3 April, Snowbird, Utah, USA

9th World Immune Regulation Meeting

Keystone Symposium: The Golden Anniversary of B Cell Discovery
Recommended reading

Keystone Symposium: T Cells: Regulation and Effector Function
Recommended reading

 

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Tang Prize for 2014: Immunity and Cancer

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Discovery process, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Drug Toxicity, Evolutionary cognition, Experimental validation, Human Immune System in Health and in Disease, International Global Work in Pharmaceutical, Monoclonal Immunotherapy, Pharmaceutical Analytics, Pharmacologic toxicities, Proteomics, Technology Transfer: Biotech and Pharmaceutical, Translational Effectiveness, Translational Research, Translational Science, tagged , , , , , , , , , on June 20, 2014| Leave a Comment »

Tang Prize for 2014: Immunity and Cancer

Curator: Larry Bernstein, MD, FCAP

 

 

2014 Tang Prize in Biopharmaceutical Sciences awards to James P. Allison and Tasuku Honjo For the discoveries of CTLA-4 and PD-1 as immune inhibitory molecules that led to their applications in cancer immunotherapy 2014/06/19.

Founded by Dr. Samuel Yin in December 2012, the Tang Prize recognizes scholars conducting revolutionary research in the four major fields of Sustainable Development, Biopharmaceutical Science, Sinology, and the Rule of Law. The Prize is awarded with each category a cash reward of over US$1 million (NT$50 million). The Tang Prize Foundation hopes that recipients of the Prize will continue to innovate while cultivating and nurturing new talent in their respective fields.
Academia Sinica was commissioned by the Tang-Prize Foundation to administer the selection of Tang-Prize Laureates for the category of Biopharmaceutical Science, recognizing original biopharmaceutical or biomedical research that has led to significant advances towards preventing, diagnosing and/or treating major human diseases to improve human health.
James P. Allison and Tasuku Honjo were chosen among nearly a hundred nominees for their discoveries of CTLA-4 and PD-1 as immune inhibitory molecules, revealing ways to harness our incredibly powerful immune system to fight cancer and marking the beginning of the immunotherapy revolution.
A critical process in the immune response involves presentation of antigens to T cells by antigen-presenting cells, two key cell types in our immune system. This process is highly regulated by molecules that stimulate the response to ensure our mounting a sufficient immune response, especially in the event of invasion by pathogens, but also by molecules that inhibit the process to ensure the response is not excessive. Indeed, there is now a family of proteins on T cells involved in this regulatory process, which is designated the “CD28 receptor family” co-receptors, as CD28 is the first protein identified to have such function. They are divided into co-receptors transmitting stimulatory signals and co-receptors transmitting inhibitory signals. Each of these has its counterpart (ligand) on antigen-presenting cells belonging to the “B7 family”. Two most prominent inhibitory receptors on T cells are called CTLA-4 (cytotoxic T lymphocyte antigen-4, as it is first identified on cytotoxic T lymphocytes) and PD-1 (program death-1, as it is first identified to be associated with a type of cell death process called programmed cell death). Their ligands are designated as B7-1/B7-2 and PD-L1/PD-L2, respectively. These are also referred to as immune checkpoint receptors and ligands.
Our immune system is not perfect and at times, the regulatory mechanisms might be faulty, which in fact may be the basis of a variety of diseases. For example, autoimmune diseases may be related to the suppressive mechanism becoming weak and the individuals can mount excessive immune responses even to their own cells and tissues. Also, our immune system is capable of recognizing cancer cells and attacking them, in a process called immune surveillance. However, cancer cells are also equipped with machineries to evade the host anti-tumor activity, which is described as immune escape. For example, cancer cells can also express B7 family ligands on their surfaces and, by engaging the co-receptors transmitting inhibitory signals on T cells, they can inhibit the host anti-tumor T cell activity. By recognizing how cancer cells escape the immune surveillance, scientists have developed novel approaches to interfere with the ability of cancer cells to suppress the immune response, thus enhancing the ability of the host immune system to inhibit cancer cell growth.
Dr. James Allison, Chairman, Department of Immunology and Executive Director, Immunotherapy Platform at the University of Texas, MD Anderson Cancer Center, is one of two scientist to identify CTLA-4 as an inhibitory receptor on T-cells in 1995 and was the first to recognize it as a potential target for cancer therapy.  His team then developed an antibody that blocks CTLA-4 activity and showed in 1996 that this antibody is able to help reject several different types of tumors in mouse models. This subsequently led to development of a monoclonal antibody drug, which has undergone clinical trials against stage 4 melanoma and been approved for treatment of melanoma by the U.S. FDA in 2011.
Dr. Tasuku Honjo, Professor, Department of Immunology and Genomic Medicine, Kyoto University, discovered PD-1 in 1992. His group subsequently established that PD-1 is an inhibitor regulator of the T cell response. Additional studies from his and other laboratories established that this protein plays a critical role in the regulation of tumor immunity and stimulated many groups to generate its blocker for the treatment of cancer. Antibodies against PD-1 have been approved by the U.S. FDA as an investigational new drug and developed for the treatment of cancer. One such antibody produced complete or partial responses in non-small-cell lung cancer, melanoma, and renal-cell cancer in clinical trials, and is predicted to be launched in 2015 for treatment of non-small cell lung cancer; this has been stated by some as having the potential to “change the landscape” of the treatment for lung cancer. Another antibody, shown to achieve a substantial response rate also in patients with non-small cell lung cancer, is currently in clinical trial for many types of cancers. In addition, combination therapy (anti-CTLA-4 plus anti-PD-1) has been shown to dramatically improve the long-term survival rates in cancer patients.
This is an exciting time in our fight against cancer. The discoveries by Dr. Allison and Dr. Honjo have spurred additional development of therapeutic approaches along the line of immunotherapy and brought new hope that many types of cancers can be cured.
In addition, dysregulation in immune checkpoint pathways may be intimately involved in other illnesses, such as allergy, infectious diseases, and autoimmune diseases. Thus, the approach of targeting immune stimulatory and inhibitory molecules also promises to lead to the development of new therapies for these diseases.
Dr. Allison’s and Dr. Honjo’s discoveries have opened a new therapeutic era in medicine.

 

Supplementary figure:

unleashes immune system to attack cancer cells

unleashes immune system to attack cancer cells

 

 

 

 

 

 

 

 

 

 

 

 

 

Dr. Samuel Yin, founder of the Tang Prize, is currently chairman of the Ruentex Group and chief development officer, chief technology officer, and chief engineer of Ruentex Construction & Development. He is also an adjunct professor in the department of civil engineering at National Taiwan University and a professor at Peking University, where he advises PhD students.

Dr. Yin read history at Chinese Culture University. He received a master’s degree in business administration at National Taiwan University and a doctorate in business administration at National Chengchi University.

In addition to his academic background in the humanities and business administration, Dr. Yin’s great interest in and devotion to interdisciplinary studies have made him an award-winning civil engineer and educator.

In 2004, Dr. Yin was named fellow of the Chinese Institute of Civil and Hydraulic Engineering. In 2008, he was invited to join Russia’s International Academy of Engineering and also awarded the Engineering Prowess Medal, the academy’s highest honour. In 2010, Dr. Yin received the Henry L. Michel Award for Industry Advancement of Research by the prestigious American Society of Civil Engineers (ASCE) for his contribution in the area of construction technology research. He was the first person without an academic background in engineering to receive the award.

Driven by a firm belief that he should give back to the society that has enabled him to achieve so much, Dr. Yin has been investing in philanthropy and education for a long time, in the hope of creating a positive force in society and making a better world.

Dr. Yin’s biggest dream was to set up an international award. He has long had great respect and admiration for the Nobel Prize, so he established an award modeled on the Nobel. The Tang Prize rewards excellent research in the areas of Sustainable Development, Biopharmaceutical Science, Sinology (excluding literary works), and Rule of Law. Dr. Yin hopes to encourage experts to dedicate themselves to innovative research in these fields and to spur human development with first-class research.

Dr. Yin’s relentless enthusiasm for philanthropy was instilled through his upbringing, particularly the example set by his late father Yin Shu-Tien. Dr. Yin established a foundation in memory of his grandfather, Yin Xun-Ruo, to provide scholarships to students of families originating in Shandong Province to study Chinese literature and history. When Yin senior passed away, Dr. Yin also set up the Kwang-Hua Education Foundation to help with China’s higher education programs.

In the past few years, Dr. Yin has set up a number of foundations to serve people on both sides of the Taiwan Strait and to foster more talented people for the nation (the Yin Xun-Ruo Educational Foundation, the Yin Shu-Tien Medical Foundation, the Kwang-Hua Education Foundation, and the Guanghua School of Management of Peking University). In 2012, Dr. Yin set up a global award, the Tang Prize, to spread his philanthropy across the world.

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The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Posted in Advanced Drug Manufacturing Technology, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Prevention: Research & Programs, Cell Biology, Chemical Genetics, Components and IRB related issues, Disease Biology, Genome Biology, Methods, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Signaling & Cell Circuits, Small Molecules in Development of Therapeutic Drugs, Stem Cells for Regenerative Medicine, tagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , on August 4, 2013| 1 Comment »

The Delicate Connection:  IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

Author and Curator: Demet Sag, PhD, CRA, GCP      

Table of Contents:

  1. Abstract
  2. Dual role for IDO
  3. Immune System and IDO
  4. Autoimmune disorders and IDO
  5. Cancer and Ido
  6. Clinical Interventions
  7. Clinical Trials
  8. Future Actions for Molecular Dx and Targeted Therapies:
  9. Conclusion
  10. References

TABLE 1- IDO Clinical Trials

TABLE 2- Kyn induced Genes

TABLE 3 Possible biomarkers and molecular diagnostics targets

TABLE 4: Current Interventions ______________________________________________________________________________________________________________

ABSTRACT:

Overall purpose is to find a method to manipulate IDO for clinical applications, mainly the focus of this review is is cancer prevention and treatment.  The first study proving the connection between IDO and immune response came from, a very natural event, a protection of pregnancy in human. This led to discover that high IDO expression is a common factor in cancer tumors. Thus, attention promoted investigations on IDO’s role in various disease states, immune disorders, transplantation, inflammation, women health, mood disorders.
Many approaches, vaccines and adjuvants are underway to find new immunotherapies by combining the power of DCs in immune response regulation and specific direction of siRNA.  As a result, with this unique qualities of IDO, DCs and siRNA, we orchestrated a novel intervention for immunomodulation of IDO by inhibiting with small interference RNA, called siRNA-IDO-DCvax.  Proven that our DCvax created a delay and regression of tumor growth without changing the natural structure and characterization of DCs in melanoma and breast cancers in vivo. (** The shRNA IDO- DCvax is developed by Regen BioPhrama, San Diego, CA ,  Thomas Ichim, Ph.D, CSO. and David Koos, CEO)

______________________________________________________________________________________________________________

Double-Edged Sword of IDO: The Good and The Bad for Clinical intervention and Developments

IDO almost has a dual role. There is a positive side of high expression of IDO during pregnancy (29; 28; 114), transplants (115; 116; 117; 118; 119), infectious diseases (96) and but this tolerance is negative during autoimmune-disorders (120; 121; 122), tumors of cancer (123; 124; 117; 121; 125; 126; 127) (127), and mood disorders (46). The increased IDO expression has a double-edged sword in human physiology provides a positive role during protection of fetus and grafts after transplantations but becomes a negative factor during autoimmune disorders, cancer, sepsis and mood disorders.

Prevention of allogeneic fetal rejection is possible by tryptophan metabolism (26) rejecting with lack of IDO but allocating if IDO present (29; 28; 114). These studies lead to find “the natural regulation mechanism” for protecting the transplants from graft versus host disease GVHD (128) and getting rid of tumors.

The plasticity of  mammary and uterus during reproduction may hold some more answers to prevent GVHD and tumors of cancer with good understanding of IDO and tryptophan mechanism (129; 130). After allogeneic bone marrow transplants the risk of solid tumor development increased about 80% among 19,229 patients even with a greater risk among patients under 18 years old (117).  The adaptation of tolerance against host mechanism is connected to the IDO expression (131). During implantation and early pregnancy IDO has a role by making CD4+CD25+Foxp3+ regulatory T cells (Tregs) and expressing in DCs and  MQs  (114; 132; 133).

Clonal deletion mechanism prevents mother to react with paternal products since female mice accepted the paternal MHC antigen-expressing tumor graft during pregnancy and rejected three weeks after delivery (134). CTLA-4Ig gene therapy alleviates abortion through regulation of apoptosis and inhibition of spleen lymphocytes (135).  

 Immune System and IDO DCs are the orchestrator of the immune response (56; 57; 58) with list of functions in uptake, processing, and presentation of antigens; activation of effector cells, such as T-cells and NK-cells; and secretion of cytokines and other immune-modulating molecules to direct the immune response. The differential regulation of IDO in distinct DC subsets is widely studied to delineate and correct immune homeostasis during autoimmunity, infection and cancer and the associated immunological outcomes. Genesis of antigen presenting cells (APCs), eventually the immune system, require migration of monocytes (MOs), which is originated in bone marrow. Then, these MOs move from bloodstream to other tissues to become macrophages and DCs (59; 60).

Initiation of immune response requires APCs to link resting helper T-cell with the matching antigen to protect body. DCs are superior to MQs and MOs in their immune action model. When DCs are first described (61) and classified, their role is determined as a highly potent antigen-presenting cell (APC) subset with 100 to 1000-times more effective than macrophages and B-cells in priming T-cells. Both MQs and monocytes phagocytize the pathogen, and their cell structure contains very large nucleus and many internal vesicles. However, there is a nuance between MQ and DCs, since DCs has a wider capacity of stimulation, because MQs activates only memory T cells, yet DCs can activate both naïve and memory T cells.

DCs are potent activators of T cells and they also have well controlled regulatory roles. DC properties determine the regulation regardless of their origin or the subset of the DCs. DCs reacts after identification of the signals or influencers for their inhibitory, stimulatory or regulatory roles, before they express a complex repertoire of positive and negative cytokines, transmembrane proteins and other molecules. Thus, “two signal theory” gains support with a defined rule.  The combination of two signals, their interaction with types of cells and time are critical.

In short, specificity and time are matter for a proper response. When IDO mRNA expression is activated with CTL40 ligand and IFNgamma, IDO results inhibition of T cell production (4).  However, if DCs are inhibited by 1MT, an inhibitor of IDO, the response stop but IgG has no affect (10).  In addition, if the stimulation is started by a tryptophan metabolite, which is downstream of IDO, such as 3-hydroxyantranilic or quinolinic acids, it only inhibits Th1 but not Th2 subset of T cells (62).

Furthermore, inclusion of signal molecules, such as Fas Ligand, cytochrome c, and pathways also differ in the T cell differentiation mechanisms due to combination, time and specificity of two-signals.  The co-culture experiments are great tool to identify specific stimuli in disease specific microenvironment (63; 12; 64) for discovering the mechanism and interactions between molecules in gene regulation, biochemical mechanism and physiological function during cell differentiation.

As a result, the simplest differential cell development from the early development of DCs impact the outcome of the data. For example, collection of MOs from peripheral blood mononuclear cells (PBMCs) with IL4 and GM-CSF leads to immature DCs (iDCs). On next step, treatment of iDCs with tumor necrosis factor (TNF) or other plausible cytokines (TGFb1, IFNgamma, IFNalpha,  IFNbeta, IL6 etc.) based on the desired outcome differentiate iDCs  into mature DCs (mDCs). DCs live only up to a week but MOs and generated MQs can live up to a month in the given tissue. B cells inhibit T cell dependent immune responses in tumors (65).

AutoImmune Disorders:

The Circadian Clock Circuitry and the AHR

The balance of IDO expression becomes necessary to prevent overactive immune response self-destruction, so modulation in tryptophan and NDA metabolisms maybe essential.  When splenic IDO-expressing CD11b (+) DCs from tolerized animals applied, they suppressed the development of arthritis, increased the Treg/Th17 cell ratio, and decreased the production of inflammatory cytokines in the spleen (136).

The role of Nicotinamide prevention on type 1 diabetes and ameliorates multiple sclerosis in animal model presented with activities of  NDAs stimulating GPCR109a to produce prostaglandins to induce IDO expression, then these PGEs and PGDs converted to the anti-inflammatory prostaglandin, 15d-PGJ(2) (137; 138; 139).  Thus, these events promotes endogenous signaling mechanisms involving the GPCRs EP2, EP4, and DP1 along with PPARgamma. (137).

Modulating the immune response at non-canonical at canonocal pathway while keeping the non-canonical Nf-KB intact may help to mend immune disorders. As a result, the targeted blocking in canonical at associated kinase IKKβ and leaving non-canonocal Nf-kB pathway intact, DCs tips the balance towards immune supression. Hence, noncanonical NF-κB pathway for regulatory functions in DCs required effective IDO induction, directly or indirectly by endogenous ligand Kyn and negative regulation of proinflammatory cytokine production. As a result, this may help to treat autoimmune diseases such as rheumatoid arthritis, type 1 diabetes, inflammatory bowel disease, and multiple sclerosis, or allergy or transplant rejection.

While the opposite action needs to be taken during prevention of tumors, that is inhibition of non-canonical pathway.  Inflammation induces not only relaxation of veins and lowering blood pressure but also stimulate coagulopathies that worsen the microenvironment and decrease survival rate of patients after radio or chemotherapies.Cancer Generating tumor vaccines and using adjuvants underway (140).

Clinical correlation and genetic responses also compared in several studies to diagnose and target the system for cancer therapies (127; 141; 131).  The recent surveys on IDO expression and human cancers showed that IDO targeting is a candidate for cancer therapy since IDO expression recruiting Tregs, downregulates MHC class I and creating negative immune microenvironment for protection of development of tumors (125; 27; 142).  Inhibition of IDO expression can make advances in immunotherapy and chemotherapy fields (143; 125; 131; 144).

IDO has a great importance on prevention of cancer development (126). There are many approaches to create the homeostasis of immune response by Immunotherapy.  However, given the complexity of immune regulations, immunomodulation is a better approach to correct and relieve the system from the disease.  Some of the current IDO targeted immunotherapy or immmunomodulations with RNA technology for cancer prevention (145; 146; 147; 148; 149; 150) or applied on human or animals  (75; 151; 12; 115; 152; 9; 125) or chemical, (153; 154) or  radiological (155).  The targeted cell type in immune system generally DCs, monocytes (94)T cells (110; 156)and neutrophils (146; 157). On this paper, we will concentrate on DCvax on cancer treatments.

T-reg, regulatory T cells; Th, T helper; CTLA-4, cytotoxic T lymphocyte-associated antigen 4; TCR, T cell receptor; IDO, indoleamine 2,3-dioxygenase. (refernece: http://www.pnas.org/content/101/28/10398/suppl/DC)

T-reg, regulatory T cells; Th, T helper; CTLA-4, cytotoxic T lymphocyte-associated antigen 4; TCR, T cell receptor; IDO, indoleamine 2,3-dioxygenase. (refernece: http://www.pnas.org/content/101/28/10398/suppl/DC)

IDO and the downstream enzymes in tryptophan pathway produce a series of immunosuppressive tryptophan metabolites that may lead into Tregs proliferation or increase in T cell apoptosis (62; 16; 27; 158), and some can affect NK cell function (159).

The interesting part of the mechanism is even without presence of IDO itself, downstream enzymes of IDO in the kynurenine tryptophan degradation still show immunosuppressive outcome (160; 73) due to not only Kyn but also TGFbeta stimulated long term responses. DC vaccination with IDO plausible (161) due to its power in immune response changes and longevity in the bloodstream for reversing the system for Th17 production (162).

Clinical Interventions are taking advantage of the DC’s central role and combining with enhancing molecules for induction of immunity may overcome tolerogenic DCs in tumors of cancers (163; 164).

The first successful application of DC vaccine used against advanced melanoma after loading DCs with tumor peptides or autologous cell lysate in presence of adjuvants keyhole limpet hematocyanin (KLH) (165).  Previous animal and clinical studies show use of DCs against tumors created success (165; 166; 167) as well as some problems due to heterogeneity of DC populations in one study supporting tumor growth rather than diminishing (168).

DC vaccination applied onto over four thousand clinical trial but none of them used siRNA-IDO DC vaccination method. Clinical trials evaluating DCs loaded ex vivo with purified TAAs as an anticancer immunotherapeutic interventions also did not include IDO (Table from (169). This table presented the data from 30 clinical trials, 3 of which discontinued, evaluating DCs loaded ex vivo with TAAs as an anticancer immunotherapy for 12 types of cancer [(AML(1), Breast cancer (4), glioblastoma (1), glioma (2), hepatocellular carcinoma (1), hematological malignancies (1), melanoma (6), neuroblastoma sarcoma (2), NSCLC (1), ovarian cancer (3), pancreatic cancer (3), prostate cancer (10)] at phase I, II or I/II.

Tipping the balance between Treg and Th17 ratio has a therapeutic advantage for restoring the health that is also shown in ovarian cancer by DC vaccination with adjuvants (161).  This rebalancing of the immune system towards immunogenicity may restore Treg/Th17 ratio (162; 170) but it is complicated. The stimulation of IL10 and IL12 induce Treg produce less Th17 and inhibiting CTL activation and its function (76; 171; 172) while animals treated with anti-TGFb before vaccination increase the plasma levels of IL-15 for tumor specific T cell survival in vivo (173; 174) ovarian cancer studies after human papilloma virus infection present an increase of IL12 (175).

Opposing signal mechanism downregulates the TGFb to activate CTL and Th1 population with IL12 and IL15 expression (162; 173).  The effects of IL17 on antitumor properties observed by unique subset of CD4+ T cells (176) called also CD8+ T cells secrete even more IL17 (177).

Using cytokines as adjuvants during vaccination may improve the efficacy of vaccination since cancer vaccines unlike infections vaccines applied after the infection or disease started against the established adoptive immune response.  Adjuvants are used to improve the responses of the given therapies commonly in immunotherapy applications as a combination therapy (178).

Enhancing cancer vaccine efficacy via modulation of the microenvironment is a plausible solution if only know who are the players.  Several molecules can be used to initiate and lengthen the activity of intervention to stimulate IDO expression without compromising the mechanism (179).  The system is complicated so generally induction is completed ex-vivo stimulation of DCs in cell lysates, whole tumor lysates, to create the microenvironment and natural stimulatory agents. Introduction of molecules as an adjuvants on genetic regulation on modulation of DCs are critical, because order and time of the signals, specific location/ tissue, and heterogeneity of personal needs (174; 138; 180). These studies demonstrated that IL15 with low TGFb stimulates CTL and Th1, whereas elevated TGFb with IL10 increases Th17 and Tregs in cancer microenvironments.

IDO and signaling gene regulation

For example Ret-peptide antitumor vaccine contains an extracellular fragment of Ret protein and Th1 polarized immunoregulator CpG oligonucleotide (1826), with 1MT, a potent inhibitor of IDO, brought a powerful as well as specific cellular and humoral immune responses in mice (152).

The main idea of choosing Ret to produce vaccine in ret related carcinomas fall in two criterion, first choosing patients self-antigens for cancer therapy with a non-mutated gene, second, there is no evidence of genetic mutations in Ret amino acids 64-269. Demonstration of proliferating hemangiomas, benign endothelial tumors and often referred as hemangiomas of infancy appearing at head or neck, express IDO and slowly regressed as a result of immune mediated process.

After large scale of genomic analysis show insulin like growth factor 2 as the key regulator of hematoma growth (Ritter et al. 2003). We set out to develop new technology with our previous expertise in immunotherapy and immunomodulation (181; 182; 183; 184), correcting Th17/Th1 ratio (185), and siRNA technology (186; 187).  We developed siRNA-IDO-DCvax. Patented two technologies “Immunomodulation using Altered DCs (Patent No: US2006/0165665 A1) and Method of Cancer Treatments using siRNA Silencing (Patent No: US2009/0220582 A1).

In melanoma cancer DCs were preconditioned with whole tumor lysate but in breast cancer model pretreatment completed with tumor cell lysate before siRNA-IDO-DCvax applied. Both of these studies was a success without modifying the autanticity of DCs but decreasing the IDO expression to restore immunegenity by delaying tumor growth in breast cancer (147) and in melanoma (188).  Thus, our DCvax specifically interfere with Ido without disturbing natural structure and content of the DCs in vivo showed that it is possible to carry on this technology to clinical applications.

Furthermore, our method of intervention is more sophisticated since it has a direct interaction mechanism with ex-vivo DC modulation without creating long term metabolism imbalance in Trp/Kyn metabolite mechanisms since the action is corrective and non-invasive.

There were several reasons.

First, prevention of tumor development studies targeting non-enzymatic pathway initiated by pDCs conditioned with TGFbeta is specific to IDO1 (189).

Second, IDO upregulation in antigen presenting cells allowing metastasis show that most human tumors express IDO at high levels (123; 124).

Third, tolerogenic DCs secretes several molecules some of them are transforming growth factor beta (TGFb), interleukin IL10), human leukocyte antigen G (HLA-G), and leukemia inhibitory factor (LIF), and non-secreted program cell death ligand 1 (PD-1 L) and IDO, indolamine 2.3-dioxygenase, which promote tumor tolerance. Thus, we took advantage of DCs properties and Ido specificity to prevent the tolerogenicity with siRNA-IDO DC vaccine in both melanoma and breast cancer.

Fourth, IDO expression in DCs make them even more potent against tumor antigens and create more T cells against tumors. IDOs are expressed at different levels by both in broad range of tumor cells and many subtypes of DCs including monocyte-derived DCs (10), plasmacytoid DCs (142), CD8a+ DCs (190), IDO compotent DCs (17), IFNgamma-activated DCs used in DC vaccination.  These DCs suppress immune responses through several mechanisms for induction of apoptosis towards activated T cells (156) to mediate antigen-specific T cell anergy in vivo (142) and for enhancement of Treg cells production at sites of vaccination with IDO-positive DCs+ in human patients (142; 191; 192; 168; 193; 194). If DCs are preconditioned with tumor lysate with 1MT vaccination they increase DCvax effectiveness unlike DCs originated from “normal”, healthy lysate with 1MT in pancreatic cancer (195).  As a result, we concluded that the immunesupressive effect of IDO can be reversed by siRNA because Treg cells enhances DC vaccine-mediated anti-tumor-immunity in cancer patients.

Gene silencing is a promising technology regardless of advantages simplicity for finding gene interaction mechanisms in vitro and disadvantages of the technology is utilizing the system with specificity in vivo (186; 196).  siRNA technology is one of the newest solution for the treatment of diseases as human genomics is only producing about 25,000 genes by representing 1% of its genome. Thus, utilizing the RNA open the doors for more comprehensive and less invasive effects on interventions. Thus this technology is still improving and using adjuvants. Silencing of K-Ras inhibit the growth of tumors in human pancreatic cancers (197), silencing of beta-catenin in colon cancers causes tumor regression in mouse models (198), silencing of vascular endothelial growth factor (VGEF) decreased angiogenesis and inhibit tumor growth (199).

Combining siRNA IDO and DCvax from adult stem cell is a novel technology for regression of tumors in melanoma and breast cancers in vivo. Our data showed that IDO-siRNA reduced tumor derived T cell apoptosis and tumor derived inhibition of T cell proliferation.  In addition, silencing IDO made DCs more potent against tumors since treated or pretreated animals showed a delay or decreased the tumor growth (188; 147)

 

Clinical Trials:

First FDA approved DC-based cancer therapies for treatment of hormone-refractory prostate cancer as autologous cellular immunotherapy (163; 164).  However, there are many probabilities to iron out for a predictive outcome in patients.

Table 2 demonstrates the current summary of clinical trials report.  This table shows 38 total studies specifically Ido related function on cancer (16), eye (3), surgery (2), women health (4), obesity (1), Cardiovascular (2), brain (1), kidney (1), bladder (1), sepsis shock (1), transplant (1),  nervous system and behavioral studies (4), HIV (1) (Table 4).  Among these only 22 of which active, recruiting or not yet started to recruit, and 17 completed and one terminated.

Most of these studies concentrated on cancer by the industry, Teva GTC ( Phase I traumatic brain injury) Astra Zeneca (Phase IV on efficacy of CRESTOR 5mg for cardiovascular health concern), Incyte corporation (Phase II ovarian cancer) NewLink Genetics Corporation Phase I breast/lung/melanoma/pancreatic solid tumors that is terminated; Phase II malignant melanoma recruiting, Phase II active, not recruiting metastatic breast cancer, Phase I/II metastatic melanoma, Phase I advanced malignancies) , HIV (Phase IV enrolling by invitation supported by Salix Corp-UC, San Francisco and HIV/AIDS Research Programs).

Many studies based on chemotherapy but there are few that use biological methods completed study with  IDO vaccine peptide vaccination for Stage III-IV non-small-cell lung cancer patients (NCT01219348), observational study on effect of biological therapy on biomarkers in patients with untreated hepatitis C, metastasis melanoma, or Crohn disease by IFNalpha and chemical (ribavirin, ticilimumab (NCT00897312), polymorphisms of patients after 1MT drug application in treating patients with metastatic or unmovable refractory solid tumors by surgery (NCT00758537), IDO expression analysis on MSCs (NCT01668576), and not yet recruiting intervention with adenovirus-p53 transduced dendric cell vaccine , 1MT , radiation, Carbon C 11 aplha-methyltryptophan- (NCT01302821).

Among the registered clinical trials some of them are not interventional but  observational and evaluation studies on Trp/Kyn ratio (NCT01042847), Kyn/Trp ratio (NCT01219348), Kyn levels (NCT00897312, NCT00573300),  RT-PCR analysis for Kyn metabolism (NCT00573300, NCT00684736, NCT00758537), and intrinsic IDO expression of mesenchymal stem cells in lung transplant with percent inhibition of CD4+ and CD8+ T cell proliferation toward donor cells (NCT01668576), determining polymorphisms (NCT00426894). These clinical trials/studies are immensely valuable to understand the mechanism and route of intervention development with the data collected from human populations   

Future Actions for Molecular Dx and Targeted Therapies:

Viable tumor environment. Tumor survival is dependent upon an exquisite interplay between the critical functions of stromal development and angiogenesis, local immune suppression and tumor tolerance, and paradoxical inflammation. TEMs: TIE-2 expressing monocytes; “M2” TAMs: tolerogenic tumor-associated macrophages; MDSCs: myeloid-derived suppressor cells; pDCs: plasmacytoid dendritic cells; co-stim.: co-stimulation; IDO: indoleamine 2,3-dioxygenase; VEGF: vascular endothelial growth factor; EGF: epidermal growth factor; MMP: matrix metaloprotease; IL: interleukin; TGF-β: transforming growth factor-beta; TLRs: toll-like receptors. (reference: http://www.hindawi.com/journals/cdi/2012/937253/fig1/)

Viable tumor environment. Tumor survival is dependent upon an exquisite interplay between the critical functions of stromal development and angiogenesis, local immune suppression and tumor tolerance, and paradoxical inflammation. TEMs: TIE-2 expressing monocytes; “M2” TAMs: tolerogenic tumor-associated macrophages; MDSCs: myeloid-derived suppressor cells; pDCs: plasmacytoid dendritic cells; co-stim.: co-stimulation; IDO: indoleamine 2,3-dioxygenase; VEGF: vascular endothelial growth factor; EGF: epidermal growth factor; MMP: matrix metaloprotease; IL: interleukin; TGF-β: transforming growth factor-beta; TLRs: toll-like receptors. (reference: http://www.hindawi.com/journals/cdi/2012/937253/fig1/)

Current survival or response rate is around 40 to 50 % range.  By using specific cell type, selected inhibition/activation sequence based on patient’s genomic profile may improve the efficacy of clinical interventions on cancer treatments. Targeted therapies for specific gene regulation through signal transduction is necessary but there are few studies with genomics based approach.

On the other hand, there are surveys, observational or evaluations (listed in clinical trials section) registered with www.clinicaltrials.gov that will provide a valuable short-list of molecules.  Preventing stimulation of Ido1 as well as Tgfb-1gene expression by modulating receptor mediated phosphorylation between TGFb/SMAD either at Mad-Homology 1 (MH1) or Mad-Homology 1 (MH2) domains maybe possible (79; 82; 80). Within Smads are the conserved Mad-Homology 1 (MH1) domain, which is a DNA binding module contains tightly bound Zinc atom.

Smad MH2 domain is well conserved and one the most diverse protein-signal interacting molecule during signal transduction due to two important Serine residues located extreme distal C-termini at Ser-Val-Ser in Smad 2 or at pSer-X-PSer in RSmads (80). Kyn activated orphan G protein–coupled receptor, GPR35 with unknown function with a distinct expression pattern that collides with IDO sites since its expression at high levels of the immune system and the gut (63) (200; 63).  

The first study to connect IDO with cancer shows that group (75).  The directly targeting to regulate IDO expression is another method through modulating ISREs in its promoter with RNA-peptide combination technology. Indirectly, IDO can be regulated through Bin1 gene expression control over IDO since Bin1 is a negative regulator of IDO and prevents IDO expression.  IDO is under negative genetic control of Bin1, BAR adapter–encoding gene Bin1 (also known as Amphiphysin2). Bin1 functions in cancer suppression since attenuation of Bin1 observed in many human malignancies (141; 201; 202; 203; 204; 205; 206) .  Null Bin-/- mice showed that when there is lack of Bin1, upregulation of IDO through STAT1- and NF-kB-dependent expression of IDO makes tumor cells to escape from T cell–dependent antitumor immunity.

This pathway lies in non-enzymatic signal transducer function of IDO after stimulation of DCs by TGFb1.  The detail study on Bin1 gene by alternative spicing also provided that Bin1 is a tumor suppressor.  Its activities also depends on these spliced outcome, such as  Exon 10, in muscle, in turn Exon 13 in mice has importance in role for regulating growth when Bin1 is deleted or mutated C2C12 myoblasts interrupted due to its missing Myc, cyclinD1, or growth factor inhibiting genes like p21WAF1 (207; 208).

On the other hand alternative spliced Exon12A contributing brain cell differentiation (209; 210). Myc as a target at the junction between IDO gene interaction and Trp metabolism.  Bin1 interacts with Myc either early-dependent on Myc or late-independent on Myc, when Myc is not present. This gene regulation also interfered by the long term signaling mechanism related to Kynurenine (Kyn) acting as an endogenous ligand to AHR in Trp metabolite and TGFb1 and/or IFNalpha and IFNbeta up regulation of DCs to induce IDO in noncanonical pathway for NF-kB and myc gene activations (73; 74).  Hence, Trp/Kyn, Kyn/Trp, Th1/Th17 ratios are important to be observed in patients peripheral blood. These direct and indirect gene interactions place Bin1 to function in cell differentiation (211; 212; 205).

Regulatory T-cel generation via reverse and non-canonical signaliing to pDCs

Table 3 contains the microarray analysis for Kyn affect showed that there are 25 genes affected by Kyn, two of which are upregulated and 23 of them downregulated (100). This list of genes and additional knowledge based on studies creating the diagnostics panel with these genes as a biomarker may help to analyze the outcomes of given interventions and therapies. Some of these molecules are great candidate to seek as an adjuvant or co-stimulation agents.  These are myc, NfKB at IKKA, C2CD2, CREB3L2, GPR115, IL2, IL8, IL6, and IL1B, mir-376 RNA, NFKB3, TGFb, RelA, and SH3RF1. In addition, Lip, Fox3P, CTLA-4, Bin1, and IMPACT should be monitored.

In addition, Table 4 presents the other possible mechanisms. The highlights of possible target/biomarkers are specific TLRs, conserved sequences of IDO across its homologous structures, CCR6, CCR5, RORgammat, ISREs of IDO, Jak, STAT, IRFs, MH1 and MH2 domains of Smads. Endothelial cell coagulation activation mechanism and pDC maturation or immigration from lymph nodes to bloodstream should marry to control not only IDO expression but also genesis of preferred DC subsets. Stromal mesenchymal cells are also activated by these modulation at vascular system and interferes with metastasis of cancer. First, thrombin (human factor II) is a well regulated protein in coagulation hemostasis has a role in cell differentiation and angiogenesis.

Protein kinase activated receptors (PARs), type of GPCRs, moderate the actions. Second, during hematopoietic response endothelial cells produce hematopoietic growth factors (213; 214). Third, components of bone marrow stroma cells include monocytes, adipocytes, and mesenchymal stem cells (215). As a result, addressing this issue will prevent occurrence of coagulapathologies, namely DIC, bleeding, thrombosis, so that patients may also improve response rate towards therapies. Personal genomic profiles are powerful tool to improve efficacy in immunotherapies since there is an influence of age (young vs. adult), state of immune system (innate vs. adopted or acquired immunity). Table 5 includes some of the current studies directly with IDO and indirectly effecting its mechanisms via gene therapy, DNA vaccine, gene silencing and adjuvant applications as an intervention method to prevent various cancer types.

CONCLUSION

IDO has a confined function in immune system through complex interactions to maintain hemostasis of immune responses. The genesis of IDO stem from duplication of bacterial IDO-like genes.  Inhibition of microbial infection and invasion by depleting tryptophan limits and kills the invader but during starvation of trp the host may pass the twilight zone since trp required by host’s T cells.  Thus, the host cells in these small pockets adopt to new microenvironment with depleted trp and oxygen poor conditions. Hence, the cell metabolism differentiate to generate new cellular structure like nodules and tumors under the protection of constitutively expressed IDO in tumors, DCs and inhibited T cell proliferation.

On the other hand, having a dichotomy in IDO function can be a potential limiting factor that means is that IDOs impact on biological system could be variable based on several issues such as target cells, IDO’s capacity, pathologic state of the disease and conditions of the microenvironment. Thus, close monitoring is necessary to analyze the outcome to prevent conspiracies since previous studies generated paradoxical results.

Current therapies through chemotherapies, radiotherapies are costly and effectiveness shown that the clinical interventions require immunotherapies as well as coagulation and vascular biology manipulations for a higher efficacy and survival rate in cancer patients. Our siRNA and DC technologies based on stem cell modulation will provide at least prevention of cancer development and hopefully prevention in cancer.

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Innovations in Tumor Immunology

Posted in Human Immune System in Health and in Disease, Systemic Inflammatory Response Related Disorders, tagged , , , , , , , on April 12, 2013| Leave a Comment »

Reporter: Aviva Lev-Ari, PhD, RN

 

The healing element is also the enemy – an enigma probed by Hebrew University Lautenberg Center researchers

April 3, 2013

Jerusalem – The same factor in our immune system that is instrumental in enabling us to fight off severe and dangerous inflammatory ailments is also a player in doing the opposite at a later stage, causing the suppression of our immune response.

Why and how this happens and what can be done to mediate this process for the benefit of mankind is the subject of an article published online in the journal Immunity by Ph.D. student Moshe Sade-Feldman and Professor Michal Baniyash of the Lautenberg Center for General and Tumor Immunology at The Hebrew University Faculty of Medicine.
Chronic inflammation poses a major global health problem and is common to different pathologies — such as autoimmune diseases (diabetes, rheumatoid arthritis, lupus and Crohn’s), chronic inflammatory disorders, chronic infections (HIV, leprosy, leishmaniasis) and cancer. Cumulative data indicate that at a certain stage of each of these diseases, the immune system becomes suppressed and results in disease progression.
In their previous work, The Hebrew University researchers had shown that in the course of chronic inflammation, unique immune system cells with suppressive features termed myeloid derived suppressor cells (MDSCs) are generated in the bone marrow and migrate into the body’s organs and blood, imposing a general immune suppression.
A complex network of inflammatory compounds persistently secreted by the body’s normal or cancerous cells support MDSC accumulation, activation and suppressive functions. One of these compounds is tumor necrosis factor-a (TNF-a), which under acute immune responses (short episodes), displays beneficial effects in the initiation of immune responses directed against invading pathogens and tumor cells.
However, TNF-a also displays harmful features under chronic responses, as described in pathologies such as rheumatoid arthritis, psoriasis, type II diabetes, Crohn’s disease and cancer, leading to complications and disease progression. Therefore, today several FDA- approved TNF-a blocking reagents are used in the clinic for the treatment of such pathologies.
What has remained unclear until now, however, is just how TNF-a plays its deleterious role in manipulating the host’s immune system towards the generation of a suppressive environment.
In their work, The Hebrew University researchers discovered the mechanisms underlying the TNF-a  function, a key to controlling this factor and manipulating it, perhaps, for the benefit of humans.  Using experimental mouse models, they showed unequivocally how TNF-a is critical in the induction of immune suppression generated during chronic inflammation. The TNF-a was seen to directly affect the accumulation and suppressive function of MDSCs, leading to an impaired host’s immune responses as reflected by the inability to respond against invading pathogens or against developing tumors.
Further, the direct role of how TNF-a works in humans was mimicked by injecting the FDA-approved anti-TNF-a drug, etanercept, into mice at the exacerbated stage of an inflammatory response, when MDSC accumulation was observed in the blood. The etanercept treatment changed the features of MDSCs and abolished their suppressive activity, leading to the restoration of the host’s immune function.
Taken together, the results show clearly how the TNF-a-mediated inflammatory response, whether acute or chronic, will dictate its beneficial or harmful consequence on the immune system. While during acute inflammation TNF-a is vital for immediate immune defense against pathogens and clearance of tumor cells, during chronic inflammation — under conditions where the host is unable to clear the pathogen or the tumor cells — TNF-a is harmful due to the induction of immune suppression.
These results, providing new insight into the relationship between TNF-a and the development of an immune suppression during chronic inflammation, may aid in the generation of better therapeutic strategies against various pathologies when elevated TNF-a and MDSC levels are detected, as seen, for example, in tumor growths.

 

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