Role of Nef in HIV Pathogenesis–Revisited

HIV transmission-2

I came across a review article in Nature Reviews Microbiology this morning, describing recent advances in our understanding of how HIV is spread. The article also allowed me to revisit the role of the Nef gene/protein in HIV pathogenesis. I worked on HIV Nef in the early 1990s in the laboratory of Dr. J. Victor Garcia at St. Jude Children’s Research Hospital.

The name Nef is an abbreviation of “negative factor” It was so named because early experiments suggested that the protein had a negative effect on virus replication.  It was soon found that Nef was also a positive virulence factor that contributed to pathogenesis and disease progression in vivo.

HIV genome Nef

The most striking early finding regarding the function of Nef was its ability to cause the removal or downregulation of CD4 from surface of T cells expressing it. The presence of Nef alone was sufficient to produce this effect; no other viral genes were necessary. This led to speculation that the pathogenic role of Nef may result from the downregulation of CD4 expression and/or the disruption of p56Lck signaling in CD4 T cells.

Since then a number of interactions with important host cellular proteins has been discovered, including

  • effects on vesicular transport
  • effects on signal transduction
  • protection of infected cells from lysis by cytotoxic T cells or natural killer cells
  • prevention of superinfection
  • modification of  host cell responses to increase cell survival and thereby increase production of infectious progeny virions.

Now it appears that one of the most significant functions of Nef is to inhibit migration and mobility of HIV-infected cells. For example, Nef-expressing T cells exhibit decreased lymph node homing and decreased extravasation through high endothelial venules (HEVs).  Evidence suggests that this effect may be due, at least in part, to interference with actin function in the cytoplasm of infected cells.

One might speculate that the reduced mobility of infected T cells may promote the interaction of infected cells with uninfected target cells thus increasing the likelihood of virus spreading from cell to cell. Further elucidation of the role of Nef in the mobility of infected cells, and what role this plays in cell to cell transmission, and in viral pathogenesis, will require the development and implementation of new in vivo and in vitro techniques such as multi-transgenic mice, intravital microscopy, and 3D tissue and organ cultures systems. Fortunately significant advances in these areas are being made rapidly.  █

The review article contains a more detailed description of the role of HIV Nef in motility and migration, as well as advances in our understanding of species-specific host factors and cell to cell transmission of HIV-1. Use the link below to access the article.

Adding new dimensions: towards an integrative understanding of HIV-1 spread.
Fackler OT, Murooka TT, Imle A, and Mempel TR. 2014. Nat Rev Microbiol. Jul 16;12(8):563-74.

http://www.nature.com/nrmicro/journal/v12/n8/full/nrmicro3309.html

9 Exciting Advances in Tissue Engineering

bioreactor-600pxw1

Recent advances in tissue engineering are nothing short of miraculous. Several different cells, tissues, and organs have been engineered in the laboratory using techniques ranging from stem cell differentiation to 3D printing. The results achieved to date give hope that even neuronal cells and tissues can be regenerated and used to repair damaged tissues in patients. Here I describe a few exciting examples of recent discoveries and technological advances that I have come across in the science literature within the last few weeks. Continue reading “9 Exciting Advances in Tissue Engineering”

Three Exciting Concepts in Tumor Immunology and Immunotherapy

Report from the Inflammation, Infection, and Cancer and Immune Evolution in Cancer Joint Keystone Symposia, March 9-14, 2014 at Whistler, BC. These symposia focused primarily on the development and immunology of solid tumors. However, there were some very interesting discussions about progress in the treatment of B-CLL and other hematopoietic tumors. 

The mechanisms of survival and progression of solid tumors can be loosely divided into two types: those that affect the tumor itself, and those that affect the immune response to the tumor. Chronic, sub-clinical, asymptomatic inflammation is a conducive microenvironment for tumor development. The effect of tumor factors is contextual and obviously complicated. Factors affecting tumor progression vary from tissue to tissue, tumor to tumor, and individual to individual. Tumors are very good at suppressing immune response, and have evolved multiple mechanisms with which to accomplish this. Some mechanisms may be passive, and some more aggressive. Each different mechanism is quite intricate. As a result there is no one-size-fits-all therapy. Successful treatment requires finding the dominant mechanism in each patient and each tumor. Immunological selection also is involved in tumor establishment and progression. As one investigator put it, we can’t control all the mechanisms, but we can try to control the major ones and hope the rest fall in line.

Following are the three concepts that I found most exciting from the meeting.

1. The tumor vasculature appears to block the infiltration of CD8 T cells into the core of the tumor. Infiltration of CD8 T cells is critical for maintaining tumor “stasis”. In some cases T cells become activated, but can’t infiltrate the tumor.Tumor barrier Several mechanisms by which tumor vasculature can restrict or block access to the core of the tumor were discussed. One possible mechanism that has been observed is that ADAM17 on the surface of Myeloid Derived Suppressor Cells (MDSCs) cleaves L-selectin from the surface of T cells, preventing extravasation of CD8 T cells and entry into the tumor. HMGB1 inhibition decreases ADAM17 on MDSCs and restores L-selectin expression on T cells, providing an opportunity for therapeutic intervention. [Suzanne Ostrand-Rosenberg (1)]. In other cases, tumor endothelial cells have been shown to express FASL on their surfaces. Contact of infiltrating T cells expressing FAS with FASL-expressing tumor vasculature thus leads to death of the T cells when they reach the endothelium. [G. Coukos, (2,3)].

Vascular targeting

2. Targeting cytokines locally. With regard to cytokines, some work which I found particularly exciting was the specific targeting of cytokines to tumor vasculature using the vascular homing peptide RGR conjugated to a cytokine.  (RGR peptide has been shown to associate with angiogenic vessels, 4). This approach results in a more localized effect requiring much less cytokine than systemic administration.  For example, IL-2-RGR leads to prolonged T cell survival within tumors, and primes other immune cells locally. This approach also may be useful for adoptive cell therapy. Another potential and extremely clever use of targeted cytokine therapy is to induce the development of HEV within a tumor essentially creating an ectopic lymph node within the tumor. This would involve the use of the cytokine LIGHT coupled to RGR. [R. Ganss (5)]

3. Adoptive T Cell therapy  with CAR-expressing T cells. Adoptive T Cell Therapy uses ex vivo-activated autologous T cells engineered to express an artificial chimeric antigen receptor (CAR).  CARs target the T cells and their effector functions to specific tumor antigens.  CAR T cellsCAR T Cell Adoptive Immunotherapy has been used successfully for treatment of B-CLL and other hematopoietic tumors, and is currently being evaluated for the treatment of solid tumors. [C. June (6,7)].

Closing Comments

Each individual tumor is unique and shaped by our immune response, which is itself unique to us, and by the initiating mutation or mutations. There are as many mechanisms as there are tumors, and the effect of tumor factors is contextual. However, each mechanism of tumor promotion, escape from the immune system, and metastasis provides a unique opportunity for therapeutic intervention and treatment. The most effective treatments will most likely involve a combination of targets unique to a particular tumor or family of tumors. We may need to treat underlying inflammation, as well as targeting the tumor stroma and vasculature as well as the tumor cells themselves and modulating the immune response. █

1. Hanson EM, Clements VK, Sinha P, Ilkovitch D, and Ostrand-Rosenberg S. 2009. Myeloid-Derived Suppressor Cells Down-Regulate L-Selectin Expression on CD4+ and CD8+ T Cells. J Immunol. 183(2): 937–944.

2. Sata, M. and Walsh, K. 1998. TNFa regulation of Fas ligand expression on the vascular endothelium modulates leukocyte extravasation. Nature Med. 4: 415–420.

3. Sata M, Luo Z, and Walsh K. 2001. Fas Ligand Overexpression on Allograft Endothelium Inhibits Inflammatory Cell Infiltration and Transplant-Associated Intimal Hyperplasia. J. Immunol. 166: 6964-6971.

4. Joyce JA, Laakkonen P, Bernasconi M, Bergers G, Ruoslahti E, and Hanahan D. 2003. Stage-specific vascular markers revealed by phage display in a mouse model of pancreatic islet tumorigenesis. Cancer Cell 4: 393–403.

5. Johansson A, Juliana Hamzah J, Payne CJ, and Ganss R. 2012. Tumor-targeted TNFα stabilizes tumor vessels and enhances active immunotherapy. PNAS 109 (20): 7841–7846.

6. Porter DL, Levine BL, Kalos M, Bagg A, June CH. 2011. Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N Engl J Med. 365 (8): 725-33.

7. Grupp SA, Kalos M, Barrett D, Aplenc R, Porter DL, Rheingold SR, Teachey DT, Chew A, Hauck B, Wright JF, Milone MC, Levine BL, June CH. 2013. Chimeric antigen receptor-modified T cells for acute lymphoid leukemia. N Engl J Med. 368 (16):1509-18.

Matched Unrelated Donor Allogeneic Transplantation For Relapsed Diffuse Large B-Cell Lymphoma: Redux

The BMTinfonet group (www.bmtinfonet.org) shared a link to this paper on their Facebook page recently. It’s about the use of allo-stem cell transplant in the treatment of Diffuse Large B cell Lymphoma (DLBCL). The paper was written for scientific and medical professionals who are experts in this field. Even as a scientist with a biomedical background I found the paper difficult to read. The authors use a lot of acronyms and statistical analyses. If you are not a medical professional with a background in bone marrow transplantation, running clinical trials, and/or statistics, you would have a very difficult time plowing through this paper

In this article I will paraphrase the main points of the paper to make it easier to understand. I am not attempting to add anything to the original paper, or to claim any credit for the data, results, or conclusions presented. The original paper is available for purchase at the journal’s website, here:

http://www.nature.com/bmt/journal/vaop/ncurrent/abs/bmt20144a.html.

I also have created a list of acronyms used in the paper, and their definitions, which I will post at the end of this article.

This paper describes a retrospective analysis of DLBCL patients that have received stem cell transplants from either siblings or matched unrelated donors. A retrospective study means it is a historical study. It looks back on, and combines data from, studies that were done in the past. The purpose of this study is to look back on data collected from DLBCL patients evaluated in other studies and see if allo-SCT is a viable treatment option for these patients.

Allogeneic lymphocyte mismatch in a lymph node

In the summary, the authors say that data from 172 unrelated donor hematopoietic cell transplant (URD-HCT) recipients and 301 sib-HCT recipients are compared. This data was extracted from several previous clinical studies and combined. The median follow-up time for which data was available for all the patients was 45 months, or about 4 years. Results of the new data analyses show that the 3-year progression-free survival (PFS) rate was approximately 35% for both groups. Overall survival (OS) was 42% for the sib-HCT group and 37% for the URD group, but these numbers were not statistically different from one another (NS), meaning that no difference between the two groups was found.

The authors note that allo-HCT has only been used for patients that are not good candidates for auto-SCT. This could be because of factors such as extent of disease, resistance to chemotherapy, bone marrow involvement, or those who have failed a previous autograft. Allo-HCT tends to have lower relapse rates compared with auto-SCT, but has a greater risk of complications and mortality other than relapse (non-relapse mortality, NRM). Despite the history of shying away from allo-HCT as a treatment for DLBCL, its use has been on the rise recently due to use of reduced-intensity conditioning (RIC) and better unrelated donor selection.

The main conclusion from this study is that URD-HCT is just as good as sib-HCT for the treatment of DLBCL. This is an important finding because it provides an additional treatment option for patients that do not have a matched sibling available as a donor. This finding also provides doctors with a new opportunity to treat and possibly cure many patients who would not otherwise be considered for allo-HCT.

Original Paper

Avivi I, Canals C, Vernant J-P, Wulf G, Nagler A, Hermine O, Petersen E, Yakoub-Agha I, Craddock C, Schattenberg A, Niederwieser D, Thomson K, Blaise D, Attal M, Pfreundschuh M, Passweg J, Russell N, Dreger P and Sureda A, on behalf of the EBMT Lymphoma Working Party. 2014. Matched unrelated donor allogeneic transplantation provides comparable long-term outcome to HLA-identical sibling transplantation in relapsed diffuse large B-cell lymphoma. Bone Marrow Transplantation (2014), 1–8, advance online publication, 10 February 2014; doi:10.1038/bmt.2014.4.

http://www.nature.com/bmt/journal/vaop/ncurrent/abs/bmt20144a.html

[starbox]

Allo-HCT Table

 

Effects of Performance-Enhancing Drugs: You Can’t Put In What God Left Out

Effect of increasing power output on climbing ability for cyclists. The fictitious climb is 8 miles from bottom to top, at an 8% grade, similar to a climb you find in a major stage race. The graphic compares an elite cyclist climbing with a constant power output of 400 watts (w) to identical cyclists with 1% (396w), 5% (380w), or 10% (360w) less power. The rider at 225w represents my own climbing ability, and 250w would be 11% above my current ability, on a similar climb.  Values preceded by “+” indicate the amount of time each rider would lose to the rider at 400w, that is, how much longer it would take each other rider to get to the top (in min:sec).  The dark green lines show the approximate position of each other rider on the climb when the first rider finished.  http://bikecalculator.com/index.html
Effect of increasing power output on climbing ability for cyclists. The fictitious climb is 8 miles from bottom to top, at an 8% grade, similar to a climb you find in a major stage race. The graphic compares an elite cyclist climbing with a constant power output of 400 watts (w) to identical cyclists with 1% (396w), 5% (380w), or 10% (360w) less power. The rider at 225w represents my own climbing ability, and 250w would be 11% above my current ability, on a similar climb. Values preceded by “+” indicate the amount of time each rider would lose to the rider at 400w, that is, how much longer it would take each other rider to get to the top (in min:sec). The dark green lines show the approximate position of each other rider on the climb when the first rider finished. http://bikecalculator.com/index.html

I originally created this graphic for an article I was writing about performance-enhancing drugs (PEDs). The premise is that PEDs only increase performance by a few percentage points, say 1-5%. Given that, how much of an effect would doping have on the results of an event like the Tour de France? Using power output (watts) as my measure of performance, I asked what the difference would be in finishing time on a single climb such as one you might see in a stage of the Tour. I compared the expected performance of an elite cyclist climbing at an output of 400 watts to the same cyclist at 99, 95, and 90% of his maximum power, or a decrease in performance of 1%, 5%, or 10%.  For contrast I used my own power output to show how doping might affect my ability to keep up with the elite riders. Since power translates directly into speed, which in turn translates into time, I used this relationship to determine how much time each rider would gain or lose during the climb. The graphic also shows where (distance) each rider would be on the climb relative to the leader when he finished the climb. As shown in the figure, a 5-10% decrease in power results in a 1-4 min loss of time on an 8 mile climb with an 8% grade.  Thus, if doping enhances performance by 5% it would result in a significant advantage to the rider. At 1%, the loss would be about 20 sec, which could be made up, but would still take its toll over the course of the Tour.  On the other hand, no amount of testosterone, EPO, or HGH is going to make me an elite cyclist. I would be a little past halfway up the climb as the leaders finished, and lose almost 30 min on a single climb. If I increased my performance by 10%, I would still lose over 20 min on a climb of this difficulty.