The Need for RNAi Screening Standards

February 3rd, 2012 by pauld-cellecta No comments »
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A couple of months ago at the CHI Discovery on Target Conference, Hakim Djaballah, Director of the HTS Core Facility at the Memorial Sloan Kettering Cancer Center, gave a unique and insightful presentation highlighting the challenges RNAi screening to identify lethal loss of function interaction in oncogenic systems.

For the exceptional benefits RNAi offers as a targeted tool to elucidate gene function, it is still a relatively new technology with limitations, potential, and idiosyncrasies that remain somewhat undefined.  These features are especially evident when RNAi is adapted for large-scale screening of gene function where small details in the set-up, screening process, quality of the reagents, and types of cells can significantly affect the variation and consistency in the large amount of data generated.  By highlighting some disappointing follow-up results from initially exciting high-profile publications, Dr. Djaballah identified a few critical benchmarks for evaluating RNAi screening.

Dr. Djaballah’s group looked at three potentially high value cancer targets identified in independent loss-of-function RNAi screens.  In addition to the publications, his group reviewed the primary screening data in more detail to evaluate the procedure and statistical significance of the data. The first screen, published in May 2009 in Cell (Scholl, et al.), identified STK33 as required for KRAS oncogenic activity.  Initially, a very exciting discovery, a number of groups pursued STK33 as a potential therapeutic target.  However, subsequent groups (Barbie, et al. and Luo, et al.) failed to find the STK33 among the strong hits in similar screens.  A recent publication in September 2011 by Babij, et al. in Cancer Research, which also does not see STK33 as a hit in a similar shRNA screen, presents compelling data indicating STK33 is not, in fact, generally essential for survival KRAS-dependant cells.  Although, based on recent letters to the editor in Cancer Research, this does not seem to be the end of the discussion between these two groups, the initial excitement of STK33 seems to have been premature at best.

The KRAS synthetic lethal screens by Barbie et al. mentioned above that did not pick-up STK33 as a strong hit their screen did, however,  identify another potentially interesting gene—the IκB kinase TBK1—that appeared essential for, but previously unknown to be involved in,  KRAS lethality.  This target was not found by other groups and has yet to be confirmed, but Dr. Djaballah had some reservations as to whether statistical analysis of the data really supported this as a true “hit” or simply an outlier.  Dr. Djaballah also had similar concerns with a recent Nature Letter in Oct. 2011 by Zuber et al that identified Brd4 as an essential gene and possible therapeutic target in acute myeloid leukemia cells.  A more detailed review of the data from this screen revealed some issues with the confidence of this hit, as there was significant variability in the CV values and a couple of the shRNAs were enriched by as much as million fold.

Dr. Djaballah’s discussion was clearly not intended to disparage any specific study, but rather to demonstrate the slippery potential of over-interpreting the extensive data produced by such a powerful approach.  Based on the amount of resources and effort put into a complex screen, it can be difficult to maintain the reserve required to coldly and rigorously analyze the experimental design and results in a detached manner and properly assess which candidates really meet the criteria for follow up.  As a relatively new screening technology without much in the way of standards and defined good practices, it is easy to prematurely “fall in love” with potentially interesting targets that may be just noise in the data.  From his analysis, Dr. Djaballah suggests paying particular attention to the following three aspects:

  1. Do the infections at the appropriate MOI and with sufficient cells to assess the effect. Although Dr. Djaballah was primarily talking about arrayed screens (with single shRNA plasmids in wells), the points is also very valid for pooled screening.  It is critical to ensure there are each cells containing each shRNA to be assayed to generate reliable reproducible results.
  2. Use correct passage times. Whether the screen requires looking at knockdowns or survival, it is important that the cells are maintained for a long enough passage number to produce a significant differential between affected and non-affected cells.  Conversely, too many passages will introduce too much noise.
  3. Pay attention to general data and overall results. It is important to see if the overall screening results make sense.  For example, are known lethal genes showing up in the hits?

While pointing out the importance of these considerations in evaluating a screening, Dr. Djaballah contended overall that there are currently few standards of practice to provide guidelines around these and similar procedural details.  We at Cellecta would agree, having focused most of our effort in the last several years toward optimizing the many subtleties of pooled shRNA screening to enable consistent, robust, and interpretable results.

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Posted in Conferences, Pooled shRNA Library, RNAi Screening, Technical

Tissue Targeting May Offer an Alternative Therapeutic Approach for Difficult-to-Treat Diseases

October 13th, 2011 by pauld-cellecta No comments »
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We recently received a phase II of our SBIR grant Exploiting Synthetic Lethality of Hematopoietic Lineage Cells to Develop Novel Targets from the NIH. Rather than trying to identify potential drug targets in oncogenic hematopoietic cells, much of the effort for this project focuses on trying to develop a pharmacologic approach to identify and kill off all hematopoietic cells (see recent press release). This sort of capability may offer an alternative therapeutic approach relying on tissue ablation and renewal to treat hematopoietic cancers such as leukemia and lymphoma.

Clinical approaches exist to regrow and regenerate portions of many essential tissues. For serious diseases, this capability offers a somewhat aggressive treatment possibility where affected tissues are completely eliminated and replaced by new healthy tissue. Blood is one such tissue where that can be regenerated with current clinical procedures. Though risky, a patient’s blood can be regenerated from a bone marrow cell graft through autologous hematopoietic stem cell transplantation and this is a currently a treatment of last resort for individuals suffering with life-threatening blood or bone marrow cancers. However, there is also much focus on regenerative approaches with other tissues, such as bone and skin. In addition, loss of other tissues such as thymus, prostate, and ovary do not have a significant negative impact on the quality of life. As research advances, it is reasonable to assume regenerative approaches will be available for an increasing range of cell types and tissues.

Since all cells of one tissue or lineage type are removed and replaced using this approach, the specific pathology is not particularly significant for ablative and regenerative treatments. Rather than targeting specific cells based on certain disease biology, eradication of all cells in a particular class eliminates the disorder regardless of its nature. This opens up a real opportunity to develop effective therapies for a range of diseases for which there are currently limited treatment options. As clinical technology develops, stem cell therapies improves, more tissue regeneration protocols are established, and in vitro tissue and organ culture technology becomes routine, ablative/replacement treatments may become the preferred therapeutic approach to treat any number of a broad range of disease states.

A major hurdle with this sort of therapy, however, is the in situ eradication step of the diseased cell or tissue. Currently, the principal ways to eliminate damaged cells types or tissues are through localized excision via surgery or radioactive ablation. For example, with autologous hematopoietic stem cell transplantation mentioned above, much of the toxicity of the treatment is associated with the general full-body radiation treatments to which patients are subjected to ablate an individual’s endogenous bone marrow before grafting in new healthy tissue. More precisely targeted approaches to eliminate affected cells are necessary if tissue replacement is to become a generally useful treatment option. Pharmacologicals that target and kill specific types of cells would provide a much needed solution for this problem, and may be easier to develop than drugs that specifically target only diseased, but not healthy, cells. The first step in developing these sorts of targeted molecules is identifying unique tissue-specific markers and potential drug targets as we are attempting for hematopoietic cells with this project.

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Posted in Cancer, NIH, Pooled shRNA Library, RNAi Screening, Synergistic Lethality, Synthetic Lethality

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Screening for Synergistically Lethal Knockdown Combinations in Cancer Cells

August 31st, 2011 by pauld-cellecta No comments »
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Therapeutic approaches using multiple drug combinations have become a standard treatment model for many types of cancer. Due to the tremendous genetic complexity and adaptive nature of most human malignancies, the use of multiple drugs acting on different targets increases the efficacy and helps thwart the development of drug resistance. However, the search for new treatment options and expanding number of drug candidates create a demand for better understanding and prediction of the most effective combinations to expedite evaluation and application in clinical settings.

To help address this challenge, Cellecta responded to an NIH contract request to develop new tools that help assess the effect of combinatorially silencing pairs of genes. We developed a variation of our RNAi pooled screening that systematically identifies and prioritizes gene pairs that, when knocked down, significantly inhibit cancer cell growth. In other words, rather than simply identifying which individual genes are essential for growth of cancer cell lines, we identify which pairs that, when silenced, most significantly inhibit cancer cell proliferation.

In some cases, the loss of two genes may be additive and strongly impair cell growth much more significantly than the loss of either gene independently. In fact, sometimes either gene independently may not have any negative effect on cells but, when both are knocked down, there is a synergistic effect that is very lethal to cells. Conversely, losing the function of two known essential genes may not, in fact, have any more of an adverse affect on cell proliferation than the loss either separately. As a result, then, it is very difficult to predict the effect of a loss of a pair of genes so each combination must be tested.

For this project, we made a specialized lentiviral vector containing two shRNA expression cassettes so the construct expresses two different shRNAs from independent promoters. A library of shRNAs was cloned into each of these shRNA expression cassettes to make a pooled heterogeneous population that expressed all paired combinations of shRNAs. With some cloning tricks, we were able to incorporate a short uniquely identifiable sequence (i.e., a “bar-code”) that identified which two shRNAs were in each vector.

The data below were generated with four shRNAs designed against each of 40 DNA damage and repair genes (160 shRNAs total) so, on completion, there were 25,600 different combinations—160 in the first shRNA position vs. 160 in the second. Using this library, we ran an RNAi lethality screen with an isogenic panel of immortalized human mammary epithelial (HMEC) cells using our standard procedures. We have validated several of the pairs and confirmed the combinatorial effect on cell growth. The approach can be reasonably extended to systematically test all combinations of approximately 200 targets in a single screen.

 
Cytotoxicity level of shRNA combinations identified in synergistic lethality screen with 27K DDR library in HMEC-TERT cells.
 

Cytotoxicity (bar-code depletion) level of bispecific shRNA constructs identified in SL screen with 27K DDR library in HMEC-TERT cells. Control – shRNA targeting luciferase gene.
 

Obviously, this approach provides an alternative to what would otherwise be extremely time consuming and expensive pair-wise individual assays to assess lethal gene knockdown combinations in large numbers of target genes. Moreover, it demonstrates the power and flexibility of pooled library screens to address the challenges of elucidating the multiple functional roles and importance of various genes in the variety of biological model systems used in life science and drug discovery research.

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Posted in Cancer, NIH, Pooled shRNA Library, RNAi Screening, Synergistic Lethality

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shRNA Design Results – How good is your algorithm?

August 3rd, 2011 by pauld-cellecta No comments »
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The last blog entry discussed how hairpin structural features affect representation and effectiveness of shRNA sequences in pooled libraries. However, it is clear that the nucleotide sequence is possibly the major factor that determines the efficiency at which a particular siRNA or shRNA knocks down a target.
Despite a large amount of research over the last several years on various features that affect knockdown potential, a priori prediction of most effective siRNA/shRNA sequences continues to be very much “hit and miss.” As anyone familiar with RNAi is aware, there are numerous design algorithms available online from a variety of commercial and academic sources. For example, several publicly available prediction algorithms are listed and described at Protocol Online and on the Charité-Universitätsmedizin Berlin website.

Cellecta, of course, has also focused a large amount of effort divining the critical parameters to effectively predict shRNA. With a pooled screening, even small improvements in our proportion of effective sequences produces significant differences in screening results. We have been using an approach that assesses a number of parameters related to GC composition and distribution. This approach has been quite effective as the data from a recent set of designed shRNA shows (see below). In this case, we designed 5 shRNA to each of 29 gene targets. For all but one of the targets, at least one shRNA construct generated greater than 70% knockdown of the targeted transcript (measured by qRT-PCR) and, for 23 of the targets there were multiple constructs generating >70% knockdown for each target.

result of new shRNA design on knockdown efficiency

The results of the project shown here were produced using a relatively straightforward approach. Recently, as part of an NIH grant, we have coupled knockdown data and results from phenotypic screens with a self-learning algorithm to produce a more sophisticated analysis that assesses over a hundred characteristics in a tree like process to identify “good” shRNA. This sort of analysis has increased the fraction of effective shRNA (shRNA that knockdown that target by >70%) by about 10%–from about 65%-70% to close to 80%. Access to this design algorithm will soon be available on the Decipher Project website. In the end, the improvement seems to be a result of eliminating the worst performers, rather than improving the prediction of the best shRNA. This indicates that improvements in effective prediction may not lie with identifying which parameters enhance or promote effective RNA inhibition, but rather, in identifying which parameters can potentially disrupt inhibition.

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Posted in DECIPHER, Pooled shRNA Library, shRNA, shRNA Design, shRNA Validation, Technical

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The Importance of shRNA Structural Design for Pooled Libraries

June 23rd, 2011 by pauld-cellecta No comments »
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We have done a significant amount of evaluation to identify features of the optimal shRNA structure necessary to ensure our complex libraries maintain and express representative and effective shRNA. Independent from particular targeting sequences, structural variations such as defined mismatches, loop sizes, and stem lengths have significant affect on both the cloning and maintenance of the hairpin-coding insert in the heterogeneous library, as well as subsequent stability of the insert to integrate and stably express in the host cell. To provide comprehensive screening, it is critical to optimize the structure so that the library can maintain a representative copy number of all shRNA sequences with minimal bias through cloning, amplification, packaging, transduction, and selection.

For the initial structural analysis, we made use of an shRNA-testing reporter construct using a destabilized green fluorescent protein (GFP). A description of this reporter system can be found in the Technology section of our website and more details will be available for publication shortly. I would just point out that, by combining this reporter construct with our library screening technology, we were able to analyze the effects of 40 different design variations of 150 different shRNA targeting sequences. Subsequent analysis by qRT-PCR of the best 10 designs showed significant variation as you can see from the data below that shows three examples of 10 variations of shRNA targeting the same region of the p53 gene. In the end, the best structure was a 25-base stem containing a few precise mismatches and a 7-nt loop.
 

p53 knockdown percentage for various shRNA structures

 
One question we often get asked when presenting this optimization strategy is how the miRNA structure compares. In fact, we did not include miRNA variations in this study because we previously found that they anecdotally did not perform as well as shRNA. Cellular processing of miRNA to form the RNA-induced silencing complex requires digestion with both the Drosha and Dicer enzymes. Intuitively, the addition of the extra Drosha processing might be expected to make the effective concentration of the active siRNA form somewhat lower in the cells and also make it less universally effective across different cell lines since it depends on the effective activity of two enzymes instead of just the one. Anecdotally, we did find a lot of variation with miRNA forms that we tested. Published results from a CGAP-sponsored inhibition study of the shRNAmir miRNA variation also found similar results in terms of effectiveness and variation. The study contained a lot of interesting data presented many ways but the finding that particularly stood out what that, across more than 100 genes, only about 37% of expressed shRNAmir produced >75% knockdown in OVCAR-8 cells and just 12% provided 75% knockdown in MCF7 cells (See CGAP Study Figure 1). Hairpin shRNA structures routinely generated much better knockdown rates.
 

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Posted in miRNA, Pooled shRNA Library, shRNA, shRNA Design, shRNA Validation, Technical

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RNAi Screening with An Inducible Promoter: Is There an Advantage?

May 12th, 2011 by pauld-cellecta No comments »
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Inducible expression is often desirable for functional genetic testing to establish clear cause and effect for a specific phenotype. A particular phenotype can be demonstrably linked to expression of a specific cDNA by showing it disappears when transcription is suppressed. Although less direct, similar logic applies to shRNA expression, where a phenotype appears when an shRNA is expressed and disappears when the same shRNA is repressed. To facilitate these types of analyses, we developed inducible versions of both the H1 and U6 RNA polymerase III promoters using the tetracycline repressor element. These promoter constructs were optimized so that the addition of tetracycline (actually, a tetracycline-analog doxycycline) induces expression of the shRNA by inhibiting the tetracycline-element-specific repressor (TetR) from binding and blocking transcription. An example of induced repression of GFP can be seen in the figure below.

Fluorescent cell images indicating inducible shRNA inhibiting GFP expression

We routinely use tetracycline-inducible shRNA promoters to validate the effectiveness of individual shRNA sequences identified in our screenings. In particular, with potentially lethal shRNA that target essential genes for cell viability, it is almost a requirement to prevent expression of the shRNA until the cells are established so that the phenotype of cell arrest, necrosis, or apoptosis can be clearly observed and specifically linked to expression of the shRNA. Since the purpose of a majority of our screens is to identify essential genes required for cell proliferation, these inducible shRNA constructs are essential for validating the identified “hits.”

For general functional shRNA screening, however, inducibility is not always desirable. Although it is often assumed by research groups with whom we interact that a library with an inducible shRNA promoter would produce more reproducible and quantitative hits from a genetic screen, our experience indicates this is not necessarily the case. For example, with viability screens, where we are simply looking for which shRNA sequences inhibit cell proliferation (i.e., shRNAs that are depleted in the overall cell population after several divisions), the need to induce the expression of the library by adding doxycycline to the cells complicates the screening procedure and can introduce some unnecessary variation in the system. Of course, with some screens, it may be preferable or even necessary to use an inducible library. For example, screens to identify genes which repress a particular reporter may be easier to carry out when shRNA expression in the library is repressed until sometime after infection and selection of a baseline population. Also, for in vivo screening, using an inducible library may be almost essential so that significant library shRNA expression and selection does not occur until the cells are established in the mouse model. However, there is no clear benefit to including a defined induction step in any particular screen.

As with most experimental options, choosing between inducible vs. constitutive shRNA expression for a library requires careful consideration of the experimental setup. While the disadvantages are not always so obvious, there are often unforeseen drawbacks in adding seemingly small variables into what is already a technically challenging assay.

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Posted in Pooled shRNA Library, RNAi Screening, Technical

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Ensuring Comprehensive Screening with Pooled shRNA Expression Libraries

April 3rd, 2011 by pauld-cellecta No comments »
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Researchers are often interested in using a pooled shRNA library for genome-wide RNAi screening to cast a very “wide and unbiased net to identify any and all genes functionally involved in some pathway”. Although it is not difficult to make an shRNA library targeting all human or mouse genes, it is practically very difficult to comprehensively screen using such a library. Careful consideration of starting cell numbers and handling of cells during propagation is essential to ensure thorough screening of pooled shRNA expression libraries, minimize false negatives, and obtain consistent and reproducible results.

First, there is an issue of library complexity since it is necessary to have several shRNAs designed to target each gene. The effectiveness of “validated” shRNA varies from cell-to-cell, and no effective shRNA has been identified for many genes. For these reasons, it is necessary to incorporate several shRNAs for each gene to ensure reasonable knockdown of a high percentage of targets. Cellecta typically designs 5-6 shRNA against each target gene, so more than 25,000 shRNA are required to target 5,000 genes. A library targeting the entire human genome, estimated at just over 23,000 genes, requires approximately 115,000 individual shRNA constructs. While it is not particularly difficult to construct libraries of this complexity, this number of unique shRNA sequences creates technical challenges with representative screening.

Pooled shRNA library screens require quantification of changes in the fraction of each shRNA sequence in selected vs. control cells or starting library. A “hit” occurs when selected cells have significantly more or less of a particular shRNA sequence. Whether one is looking at enrichment of specific shRNA in the selected cells vs. the control (positive selection) or depletion of shRNA in selected cells vs. the control (negative selection), it is critical that the screen begin with sufficient numbers of each shRNA to ensure measured changes in the fraction an shRNA sequence are statistically significant. This means that, if there are very low numbers of specific shRNAs at the start of the screen, small random changes in a drifting population may be difficult to differentiate from significant trends. Simply put, a loss of 2 shRNA is a 20% change if there are only 10 initially vs. 2% if there are 100. For this reason, a least a few hundred cells need to be infected with each shRNA to initiate a good screening. This is demonstrated in the data below where starting with a smaller population of just 50 cells per shRNA (third bar) leads to more variance than starting with a population of 200 cells per shRNA (first bar). This means that starting a screen involves infecting 100 times more cells than the complexity of the library. For a library with 25,000 shRNAs, the starting population should be 2.5 million infected cells, and for a library with 115,000 shRNAs, the starting population should be over 11 million infected cells.
 

Graph of Reproducibility in Triplicates for RNAi Library Viability Screen

 
To screen a heterogenous mixture of shRNA expression constructs, however, it is important to have 2-3 times more cells than viral particles to help ensure that most cells are only infected with one shRNA-carrying virus (i.e., a multiplicity of infection [MOI] of 0.3-0.5), so you need to have 2-3 times more cells than the number targeted for infection. Thus, 6-8 million cells are needed to start a screen with libraries of 25,000 shRNAs, and a whole genome library of 115,000 shRNAs would require 25-35 million cells. Since each screen should be done in duplicate, or better, triplicate, the number of cells needed makes a full genome screen with a redundant shRNA library impractical.

Finally, to ensure a comprehensive screen, it is not simply sufficient to start with the right amount of cells. During the screening process, incorrect propagating the cells can completely undercut the representation set up at the initiation of the screen. This is especially true for a negative selection screen, such as a viability screen where one is interested in identifying shRNA that kill or inhibit proliferation of cells, and, therefore, drop out of the population. It is critical to maintain the full library representation that was initially used at the start of the screen. If a portion of propagating cells are removed during propagation (e.g., cells are split), the representation of the library can be skewed in the sample. By doing so, this introduces significant noise. This effect is readily seen in the first two bars of the figure where the effect of starting with sufficient cells (200 cells per shRNA) is completely undercut by splitting cells during propagation so that that the final count of cells after 10 days is the same as the initial number of cells. The correlation between triplicates falls dramatically when the cells are split.

Library representation is often overlooked, especially when the desire is for large-scale unbiased screens. However, without careful consideration in designing screening procedures that reflect the complexity of the library, results of these large-scale screens can produce relatively meaningless data with anecdotal results at best. So, what about genome-wide screening? Our approach with the DECIPHER Project is to provide modules, each targeting approximately 5,000 genes with 27,500 shRNA, which enable comprehensive screening. We are more than half way finished building a series of 5 modules that will target all human genes, and 4 modules targeting all mouse genes. For more information on these libraries, visit the DECIPHER Project website.

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SBS 2011 Schedule, March 30th

March 30th, 2011 by cellectablog No comments »
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Take the opportunity at SBS 2011 to learn about Cellecta’s cancer drug target discovery services. Come visit us at booth #522, and be sure not to miss our oral presentation and tutorial on Wednesday, March 30:

11:00-11:30am
HT RNAi Screening of Anti-Cancer Targets With Pooled shRNA Libraries
Speaker: Alex Chenchik, Ph.D.

Alex Chenchik1, Donato Tedesco1, Kyle Bonneau1, Mikhail Makhanov1, Costas G. Frangou2, Peiqing Sun3, Andrei Gudkov4
1Cellecta, Inc., Mountain View, CA; 2Fred Hutchinson Cancer Research Center, Seattle, WA; 3The Scripps Research Institute, La Jolla, CA; 4Roswell Park Cancer Institute, Buffalo, NY.

High throughput (HT) genetic screening using genome-wide pooled bar-coded lentiviral-based shRNA libraries in combination with HT sequencing has been used to identify genes modulating proliferation and survival in prostate, leukemia, and a panel of isogenic mammary epithelial cells (HMEC). Gene targets identified in these screens have been subsequently shown to lead to cell death in vitro when suppressed, and thus have potential as therapeutic targets. In addition to identifying specific single targets, the screening platform has been adapted to screen large sets of genes for synergistic combinations that generate a synthetic lethal phenotype when knocked down simultaneously. Advantages and limitations of pooled format genetic screens with genome-wide pooled shRNA libraries will be discussed.

12:30-1:25pm
Tutorial: RNAi Genetic Screening for Drug Target Discovery
Presenter: Paul Diehl, Ph.D.
Location: Osceola 5–6 (Food and beverages will be served.)

Lentiviral-based pooled shRNA libraries enable rapid and reliable identification of genes regulating most cell responses and potential drug targets. The silencing effects of shRNAs targeting thousands of genes can be assayed in a single screen using representative shRNA libraries and HT sequencing. We will describe applications of Cellecta’s RNAi screening platform with data from several cancer cell viability screens.

View the complete SBS Program here: http://www.slas.org/events/sbs11/FinalProgram.pdf

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AACR-NCI Systems Biology Conference

March 11th, 2011 by pauld-cellecta No comments »
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Alex Chenchik, Cellecta’s founder and Scientific Director, and Paul Diehl, Director of Business Development, attended the AACR-NCI Systems Biology : Confronting the Complexity of Cancer Conference in San Diego last week and presented two posters: Identification and Analysis of Essential Genes in Leukemic Cell Lines Using RNAi Screening and HT Screening for Bioactive Peptides that Increase Radiation Tolerance Using a Pooled Lentiviral Peptide Scanning Library. Although the poster session was relatively short for a small meeting, both posters were received well. Most of the interest was on the Identification of Essential Genes in Leukemic Cells poster as the shRNA library screening technique described in this study is generally applicable for validating pathways, identifying genes modulating cellular responses, and finding putative drug targets and biomarkers, which were the main interests of most of the attendees.

Almost all the talks at the conference were fascinating and many somewhat overwhelming in terms of the experimental work and data analysis involved. Researchers are struggling with the challenge to integrate and make sense of new experimental results in light of the massive amounts of expression profiling, protein-protein interaction, SNP analysis, genomic amplification, and other available profiling data for the range of genes, transcripts, proteins, and metabolites in a range of cell lines, tissues, and tumors. There exist numerous tools and approaches to synthesize and apply established results with new data but, clearly, much more work is necessary before a comprehensive and holistic understanding of the biological mechanisms controlling the many forms of cancer and tumorigenesis emerges.
 

Highlights and shRNA Library Screens

One of the highlights of the conference included the opening address from Stephen Friend of Sage Bionetworks during which he discussed top-down approaches to integrate these disparate data and ways to integrate and organize data sharing between various groups to develop more comprehensive mechanistic models. Also, Louis Staudt from the NCI talked about identification of a novel drug target for B-cell lymphoma using in vivo screening of mice with tet-regulated shRNA expression libraries. In another session, Michael Hemann from the MIT Koch Institute, used in vivo shRNA screening to investigate the mechanisms of various inhibitor drugs in vivo in the B-ALL Burkett’s lymphoma mouse model and, after starting with a pooled 2,200 shRNA expression library, was able to predict the mechanism of action for various compounds with just an 8-shRNA signature.

Unrelated to shRNA profiling, Jennifer Pietenpol from the Vanderbilt-Ingram Cancer Center gave an exceptional presentation of her thorough work genetically grouping, characterizing, and identifying driver genes in triple-negative breast cancers (ER-, progesterone-, and PR-) without HER2 amplification. In the same session, Valerie Weaver from UCSF discussed the often overlooked role of interactions between tumors and extracellular matrix proteins, and how this contributes to structural changes that lead to breast cancer tumor aggressiveness and pathology. In a different session, Ernest Fraenkel from the MIT presented work showing how information from protein-protein assays and expression profiles can be integrated using a Steiner Tree algorithm to work out functionally coherent pathways and aberrant interactions in EGFR networks in glioblastoma. Also, Todd Golub from the Broad Institute distilled vast amounts of expression profiles down to a list of 1,000 “landmark genes” that can be used to infer the expression levels of almost all other genes, so a complete expression profile can be generated that’s over 80% accurate just by measuring levels of 5% of the transcripts.
 

Software Tools and Resources

From a very practical perspective, many of the presenters highlighted numerous web-based software and database resources to assist in building, dissecting, and analyzing pathways. Paul Spellman from the Lawrence Berkeley National Laboratory discussed on-going work of The Cancer Genome Atlas (TCGA) Project that uses HT sequencing to genotype many dozens of cancer-derived cells lines across multiple cancer types. Andrea Califano from Columbia University discussed the use of the Master Regulator Analysis module of the Genomics Workbench ge(Workbench) to eludicate mechanisms of aberrant signal transduction in various cancer sub-types. Douglas Lauffenburger, also from MIT, discussed several cell network modeling approaches from simple relational to more structured logical and mechanistic with examples of how they could be used to analyze various type of data and pathways.

Other presenters referenced a variety of quite sophisticated tools and resources for cancer research and pathway analysis, links to some of these are listed below:
 

Paradigm—Pathway Analysis Software (UCSC)

ICGC— International Cancer Genome Consortium

ENCODE—Encyclopedia of DNA Elements (UCSC)

COSMIC—Catalog of Somatic Mutations in Cell Cancer (Sanger Center)

Biology Workbench— Database searching, analysis, and modeling tools (UCSC)

cBio Cancer Genomics Portal—Access to large-scale genomic cancer sets (MSKCC)

dbGap—Database of Genotypes and Phenotypes (NCBI)

ARACNe— Algorithm for the Reconstruction of Accurate Cellular Networks (Columbia)

MINDy— Modulator Inference by Network Dynamics to module modulator gene interference of a network (Columbia)

NetPhorest—Analysis for phosphorylation-dependent signaling motifs

NetWorKIN—Predicting in vivo kinase-substrate relationships

mFINDER—Network motifs detection tool (Weizmann Institute)

PTMScout— Analyze mass spec and other protein data for post-translational proteomics modifications
 

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Posted in Cancer, Conferences, Peptides, Software

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The DECIPHER Project’s New Human Module Targets 5,000 More Genes

February 24th, 2011 by pauld-cellecta No comments »
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We are excited to have just completed the launch of the 3rd Module of the DECIPHER Project Human Lentiviral RNAi Library. As many of you may know, the DECIPHER Project is an open access platform that provides researchers from academic and non-profit institutions with free pooled shRNA libraries and software for genome-wide RNAi screening. It was established by Cellecta, Inc. in October 2010 under collaboration and joint grants with the Fred Hutchinson Cancer Research Center, the Roswell Park Cancer Institute, and The Scripps Research Institute.

The addition of the 3rd DECIPHER Human shRNA Expression Library Module to the DECIPHER pooled shRNA library collection adds approximately 5,000 new cell surface, extracellular, and DNA binding target genes to the 10,000 well-annotated signal transduction and disease-associated genes targeted by the other two Human shRNA expression library modules that have been available since last October. Combined, all three human modules enable functional screening of over 15,000 expressed transcripts—the majority of annotated human genes. This puts us significantly closer to our goal of providing 5 modules that target the entire genome.

The DECIPHER Project libraries are made to the same standards as all Cellecta libraries. Each individual library module targets approximately 5,000 well-annotated genes with 27,500 shRNAs (~ 5-6 shRNA target each transcript). The shRNA template oligonucleotides used to make the libraries are produced using Agilent’s array-based oligo synthesis platform which ensures relatively even representation of each oligo since each is synthesized on its own “spot” in situ on a glass surface. In addition, each shRNA insert in each of the libraries includes a unique bar-code identifier that enables its accurate identification by HT sequencing. This allows precise quantification of all shRNA species in the library and reliable measurement of shRNA quantities after screening. We essentially measure the frequency of each of the 27,500 shRNA sequences in the library. As a result, we know if any are missing after the cloning and packaging steps, and that greater than 95% of the shRNA sequences in each of our pooled shRNA libraries are present at sufficient levels to ensure statistically accurate results.

More information about Cellecta’s library and screening technology is available from Cellecta (www.cellecta.com) or through the DECIPHER Project website (www.decipherproject.net).

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