Category Archives: genetic engineering

T cell fitness and genetic engineering

This is a subject we have been thinking about in great detail and this publication in Cell was a trigger for me to start organizing those thoughts. Here is the full reference to the paper discussed: In press, Roth et al., Pooled Knockin Targeting for Genome Engineering of Cellular Immunotherapies, Cell (2020).

My thanks to Mark Paris from Daiichi Sankyo for his tip to read this paper.

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This publication ( is by Theodore Roth and colleagues from Alexander Marson’s lab at UCSF.  They present a nice technological advance, the development of a process by which a pool of genes are knocked into a locus, allowing one to examine the consequence of altering the responsiveness of a cell, in this case, a T cell. This type of work springs from a long lineage of genetic manipulation strategies, from random mutagenesis, to random then targeted gene knockouts (in cells and animals) and gene knockins (what we once called transgenics) and elegant gene-editing technologies (gene therapy, CRISPR/Cas-9, cell therapy, gene-delivery) and so on.

The focus in this paper is on optimizing T cell activity in the setting of solid tumors, something we think about every waking hour at Aleta Biotherapeutics ( So, let’s see what we’ve got here.

The pooled knockin strategy relies on two key elements – DNA barcoding, a well-developed technology that has its roots in high throughput library screening technologies, and locus targeting via HDR, which can be achieved using CRISPR/Cas9 and guide templates. Put these two things together and you now have the ability to mix and match genes of interest (following these via their specific barcodes) and place then into the desired locus – here that locus is the TRAC (the TCR locus). They also knocked in a defined TCR (for NY-ESO-1). So, this is a nice system with a known TCR and various immune modifications. There are some limitations. Only 2000-3000 base pairs will fit into the targeting vector (here using a non-viral method). It appears that only a fraction of the targeted T cells are functionally transfected (around 15% per Figure C and note that not every knocked-in cell has both the TCR and the extra gene). The expression level in primary human T cells is high, but I’m guessing expression is of limited duration (although at least 10 days, Figure S5). This is used here as a screening tool, where the goal is to identify critical pathways that reduce or enhance T cell activities (proliferation, effector function, release from immunosuppression).

The authors used a pooling approach to introduce one or two coding sequences from a short list of proteins implicated in T cell biology. Some sequences were modified to be dominant-negative or to be “switch receptors”, where the extracellular domain of the receptor is coupled to a T cell-relevant signaling component (eg. FAS-CD28, TGFβRII-4-1BB). Here are the components they used for their library:

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As we can see from the list there are interesting immune checkpoints, death receptors, cytokine receptors and signaling components that can be mixed and matched. The pool is made and transfected into primary T cells that are then put under selective pressure. The T cells that are enriched under that selective pressure are then analyzed by barcode sequencing to see who the “winners” are, as shown in this schematic from Figure 1A:

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The first screen was simple TCR stimulation (anti-CD3/anti-CD28) which rather robustly showed that a FAS truncation allowed for better cell proliferation (Figure 3B in the paper). This is an expected result – activated T cells undergo FAS-mediated cell death (activation-induced cell death, AICD) that is triggered by FAS-ligand expression, ie. activated T cells kill each other using this pathway. Since there are only T cells in this TCR stimulation culture a lot of other pathways are rendered irrelevant and therefore don’t appear (PD-1 for example):

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The key data are on the far right, showing a 2-4 fold increase in T cell number relative to input. The knockins in light blue showed a statistically meaningful increase vs. input number, across 4 different donor T cells (each circle is a different donor).

The second selective pressure was to stimulate the T cells in the presence of soluble TGFβ (see Figure 3D). As one might guess, the TGFβRII dominant-negative (dn) and switch receptors now come into play: TGFβRII-MyD88, TGFβRII-4-1BB, TGFβRII-dn. The FAS-dn and switch receptors are also represented as are two T cell proliferative components: the IL2RA and TCF-7 (aka TCF-1). These latter hits suggest that amping up T cell proliferation can allow the pool to outrun TGFβ-mediated immunosuppression, at least in vitro. Again, refer to Figure 3D in the paper for the results.

Several other selective pressures were applied in vitro, including tumor cytotoxicity using the NY-ESO-expressing melanoma cell line A375. Of more interest, the A375 cell line was used to establish a xenograft tumor in immunodeficient NSG mice, and the knockin pools of transfected T cells were injected into the mice after the tumor had established. A technical note here – 10 million T cells were injected, of which approximately 1 million were transfected – and 5 days later the tumors were removed and the TIL (tumor-infiltrating lymphocytes) were isolated by screening for the TCR. Bar-code analysis of the TCR-positive TIL allowed the team to identify which transfected T cells got in and expanded. This is tricky, because you’ve allowed time for extensive proliferation (so T cells that are dividing quickly will dominate) and you don’t know what you lost when the T cell pool encountered NY-ESO-positive tumor cells (did some die or did some traffic out of the tumor?). We should expect these data to be noisy and they are, but clear “winners” emerge, namely the TCF-7 transfectants, the TGFβRII-dn, and TGFβRII switch receptors with 4-1BB and also with the TLR signaling component MyD88. Since A375 melanoma cells do not make TGFβ (as far as I know) we have to assume that the T cells themselves are making this, and this is the TGFβ that is triggering these potent (NF-κB triggering) signaling components.

The TGFβRII-dn and switch receptors supported increased IL-2 and IFNγ production – note that IFNγ should have induced PD-L1 on the melanoma cells, but none of the PD-1 based cassettes had any notable effect (from Figure 6B):

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As with the PD-1 pathway, neither the FAS switch receptors nor the FAS-dn construct seemed to play a role in this setting. It’s not clear if FAS-L was upregulated in the tumor model, so that might explain the result.

There was a stark difference in T cell phenotype induced by TCF-7 versus the TGFβRII synthetic constructs. They are in fact polar opposites in some ways (CCR7 expression, Granzyme B expression, IFNγ expression – see Figure 6 E in the paper). Finally, the authors made a bona fide, polycistronic, TCR construct expressing the TGFβRII-4-1BB cassette or the TCF-7 sequence, used this to transduce donor T cells and then tested these for anti-tumor efficacy in vivo (Figure 7). T cells expressing the NY-ESO TCR and the TGFβRII-4-1BB cassette were able to clear the tumor completely. So that’s a very nice result.

Let’s put this into broader context. The table below is a small representation of the literature on genes associated with T cell anti-tumor responses, presented in no particular order. In the left column is the technology used to do the work, then the target, the result, the DOI if you want to read more and then some notes where applicable. I left off a lot of papers, my apologies to those labs.

Technology Target Result notes Reference
dominant-negative transgene FAS increased T cell persistence  and anti-tumor activity 10.1172/JCI121491
transgene overexpression c-Jun reversed tonic-signal induced exhaustion in T cells AP-1 driven 10.1038/s41586-019-1805-z
knockout  Reginase-1 increased T cell persistence, fitness, and anti-tumor activity > Batf and < PTPN2, SOCS1 10.1038/s41586-019-1821-z
knockout PTPN2 increased Lck, STAT5 signaling, and anti-tumor responses multiple papers 10.15252/embj.2019103637
disruption by random integration TET-2 improved CAR-CD19 clinical outcome   10.1172/JCI130144
CRISPR screen (CD8) Dhx37 increased tumor infiltration and effector function multiple papers 10.1016/j.cell.2019.07.044
dominant-negative transgene TGFβRII increased T cell proliferation, effector function, persistence, and anti-tumor activity multiple papers 10.1016/j.ymthe.2018.05.003
integration site association TGFβRII associated with positive clinical outcomes many other sites also identified 10.1172/JCI130144
pooled shRNA screen PP2r2d increased TCR activation, cytokine secretion, T cell trafficking into tumor   10.1038/nature12988
knockout NR4a complex increased CD8 effector T cell function and solid tumor control linked to Nf-kB, AP-1 activity, multiple papers 10.1038/s41586-019-0985-x
T cell profiling Tcf1/TCF-7 increased T cell stemness and anti-tumor activity (with anti-PD-1) multiple papers 10.1016/j.immuni.2018.11.014

I won’t go through all these but there are a few things to note here. One is the appearance of the three pathways we just discussed in the context of the pooled KI paper: FAS, TGFβRII and TCF-7. As mentioned earlier the FAS/FAS-L connection to AICD has been known for a long time, and that information has already been exploited in the context of CAR T cell engineering. Elaboration of the roles of TGFβ in mediating tumor resistance to immune therapy is a more recent advance, but now well established. As noted above I think one interesting question raised by this paper is the source of the TGFβ in the in vitro and in vivo tumor models. I’ve assumed this is T cell derived and understanding the trigger for TGFβ activation in these settings would be very interesting. The role of Tcf1 (aka TCF-7) in anti-tumor immunity has recently been explored in detail in the context of T cell “stemness” leading to the hypothesis that anti-PD-(L)-1 therapeutics work by releasing these T cell with stem-like properties, and allowing their maturity into effector T cell populations (see 10.1016/j.immuni.2018.12.021 and 10.1016/j.immuni.2018.11.014 for examples). It seems that in this knockin, enforcing TCF-7 (Tcf1) expression locked the T cells into a sort of limbo, proliferating, homing into the tumor, but failing to mature into effector cells with anti-tumor functions. A very interesting result. Development of a model in which canonical PD-1/PD-L1 immunosuppressive biology could be examined in order to probe for synergies would be a welcome next step.

Finally, word or two about some of the other targets. As shown in the paper, and as recently shown in the clinical setting (10.1126/science.aba7365), knockins are, at this time, an imperfect tool. Some of the targets listed in the table are associated with autoimmunity (eg. PTPN2) or T cell leukemia (eg. c-Jun, NR4a) and so care is needed when exploiting these targets. Safely engineering specific targets for improved cellular therapeutics will be an important advance on the road to durable and curative solid tumor therapy.

Stay tuned.

Hematological Malignancies – who will win the battle for patients? Part 2: BiTEs & CARTs targeting CD19

 We talked last time about the potential of Macrogenic’s DART bi-specific technology and we focused primarily on the T cell engaging bi-specifics, such as DART006, a CD3 x CD123 therapeutic. Lets just quickly state the hypothesis:

Bi-specific modalities will allow the targeting of the patients T-cell driven immune       system to a precise (tumor-expressed) antigen.

Other outcomes are possible. For example, the drugs might not work at all, or they might not be as specific as designed, or they act in ways we have not anticipated. In the context of the Macrogenics platform, we actually don’t know yet, as DART006 is very early in clinical development. BiTEs (Bi-specific T cell Engagers), Micromet’s version of a bi-specific technology, have been around a while and are further advanced. Acute Lymphocytic Leukemia (ALL) patients are now being recruited into Phase 3 clinical trials for blinatumomab, the anti-CD3 x anti-CD19 BiTE, with study completion due in July 2017. Micromet was acquired for 1.2BB dollars in January 2012 by Amgen. At the time Amgen R&D head Roger Perlmutter pointed to the Phase 2 clinical trial results in ALL as driving Amgen’s interest in the technology. Indeed, blinatumomab has produced some remarkable data in ALL. Historically, chemotherapy treated ALL patients had a complete response rate (CR) of about 38% and a median overall survival (OS) of 5 months. Rituximab (anti-CD20) didn’t perform much better than chemo. In the blinatumomab Phase 2 trial of adult relapsed/refractory (r/r) ALL, patients received a continuous IV infusion of blinatumomab for 28 days followed by 14-days off drug. Patients who responded could re-up for 3 more cycles of treatment or proceed to allogeneic stem cell transplantation (HCST). There was a very high rate CR of ~70% and the apparent absence of minimal residual disease (MRD) in many patients. Blinatumomab also impacted overall survival (OS) in ALL, as reported at the American Society of Hematology conference (ASH) in 2012 (Abstract #670). The CR was still 69% with most patients being MRD negative. The OS for responders was 14.1 months while the OS for non-responders was 6.6 months (so median OS = 9.8 months). Thirteen of the 36 patients enrolled were able to receive allogeneic HSCT.

The most common adverse events (AEs) were fever, headaches, tremors, and fatigue. Some patients experienced severe AEs (SAEs) such as cytokine release syndrome (CRS) and central nervous system events, including seizures and encephalopathy. One patient stopped treatment due to fungal infection leading to death. So, there is tox to consider.

A smaller study directed to salvaging patients with MRD despite prior treatments showed even more dramatic results: 16/21 patients became MRD negative and the probability for relapse-free survival was 78% at a median follow-up of 405 days. This is a remarkable result. An SAE led to one drug discontinuation.

Last year at ASH (Abstract #1811) we saw early results from an open label phase 2 study in r/r Non-Hodgkin’s Lymphoma (NHL), specifically, Diffuse Large B cell Lymphoma (DLBCL). Blinatumomab was administered by continuous IV for 8 weeks. Patients received either stepwise blinatumomab dosing of 9, 28, and 112 μg/d during weeks 1, 2, and thereafter, or received 112 μg/d throughout. All patients received prophylactic dexamethasone. So you can see some dose modifications here designed to reduce SAEs. After a 4-weeks off drug, patients who had responded could receive a 4-week consolidation cycle. 11 patients had been enrolled, 7 patients were evaluable for response. These patients had failed >2 prior therapies, including some patients who had relapsed after HSCT. The overall response rate (ORR) was 57% (14% CR plus 43% partial response (PR); 30% had progressive disease (all from the stepwise dose regimen). Note this is a very small sample size so every patient has a large impact on the response numbers. Ten of 11 patients had at least one grade ≥3 AE with 2 patients having grade 4 AEs (one patient with neutropenia and leucopenia; one with respiratory insufficiency). There were no drug related fatalities. Ten of 11 patients had central nervous system (CNS) AEs, mostly tremor, speech disorder and disorientation: in 5 patients these CNS toxicities were grade 3. The overall benefit/risk assessment suggested stepwise dosing (9, 28, 112 μg/d) to be the recommended dose.

Well first of all let’s point out here that blinatumomab has orphan drug status for ALL and NHL. That’s just to remind ourselves that these are pretty rare diseases with high unmet need. For ALL in particular this seems a good risk/benefit scenario. Within the diseases that make up NHL, DLBCL is not the most treatable (nor the least), and we note also that there is no attempt in the open-label phase 2 to characterize DLBCL into its subclasses – these have different oncogenic drivers and different outcomes for patients. Blinatumomab has also been in Phase in in other NHL classes, including Mantle Cell Lymphoma and Follicular lymphoma. Response rates were generally below current standard of care. Similarly, we can go back to look at rituximab, ofatumumab, and even ibrutinib, idelalisib and ABT-199 in NHL and likely find better treatment paradigms for r/rDLBCL than this, although maybe not as a monotherapy (see those earlier posts here:

Given the modality (CD3 x CD19 bi-specific) maybe the most interesting comparison is with Novartis’ CAR-T CD19 technology CTL019. CTL019 is the product of genetic engineering technology developed by Carl June’s group at U Penn, and is currently advancing in close to 20 clinical trials. The most advanced is a Phase 2 trial in r/r ALL, with a primary outcome completion due in July of 2015. As a quick reminder, CARs combine a single chain variable fragment (scFv) of an antibody (e.g. anti-CD19) with intracellular signaling domains from CD3 and 4-1BB into a single genetically engineered chimeric protein. The CD19-specific version of this technology is termed CTL019. Patient’s T cells are lentivirally transduced with a CAR, expanded ex vivo then infused back into the patient. Infusion of these cells results in 100 to 100,000x in vivo T cell proliferation, anti-tumor activity, and prolonged persistence in patients carrying CD19+ B cell tumors. Results from a pilot study in pediatric and adult r/r ALL were presented at ASH in 2013 (Abstract #67). Most patients received lymphocyte-depleting chemotherapy just a few days prior to infusion. This helps de-bulk the malignancy. In this small trial, 82% achieved a CR, 18% did not respond. Of the patients achieving CR, 20% subsequently relapsed. The rest of the patients are being followed and there has been no update. Responding patients all developed CRS, and about 30% of patients were treated with the IL6-receptor antagonist tocilizumab plus corticosteroids to control CRS symptoms.

We have a little more data on CTL019 from NHL studies, specifically r/r CLL. In December 2013, Phase 2 data were presented at ASH (Abstract #873).  Patients with r/r CLL received lymphocyte depleting chemotherapy and then one of several doses of transduced T cells (this is a dose study in that regard, although, cutting to the chase, no dose response was seen, so lets skip over that). Median follow-up for analysis was 3 months at which time the ORR = 40% (20% CR plus 20% PR, with clearance of CLL from the blood and bone marrow and at least a 50% reduction in lymphadenopathy. The toxicity profile was similar to that described above, dominated by treatable CRS. In a small Phase 1 study (Abstract #168), adult patients with r/r NHL including patients with chemotherapy-refractory primary mediastinal B cell lymphoma and DLBCL were enrolled. They received chemo to reduce disease burden and then an infusion of CTL019. 12 of 13 evaluable patients responded (ORR = 93%), the CR = 54% and PR = 38%. These are outstanding responses.

So let’s take a step back. It is a bit hard to compare these regimens head-to-head as they are in different stages of clinical development, the trails are generally small, and in the case of NHL, we have limited data on different types of lymphomas. At the same time we have to consider the larger landscape of therapies available, and ask ourselves how patients will best be served. In the case of the T cell engaging bispecific antibody landscape, it is very clear that robust anti-tumor responses are generated with very low concentrations of antibody. It seems to me very likely that there will be malignancies or subsets of malignancies where this technology will be very useful, including ALL, as we just saw. It will be important to either improve the antibody construction or alter the dose regimen sufficiently to reduce the toxicities associated with the BiTE therapeutic and competing modalities, including the DARTs. Now, people will claim that the tox is not so bad, and that it is only efficacy that matters, and that’s fine, but in the face of competition from CTL019 and other therapeutics, maybe this becomes a differentiating issue. This might also be different for the pediatric population (a critically important population in ALL) versus the adult population. When we look at the CAR T cell transduction technologies we need longer follow-up on the phase 2 studies but certainly anecdotal evidence from smaller trials suggests that some patients will experience long-lasting remissions. If this observational information holds up in the larger clinical trials than the technology will cement itself a place in ALL therapy, and perhaps in other diseases as well. We don’t know yet whether the BiTE therapeutic blinatumomab or the CAR therapeutic CTL019 will have a top-tier profile in NHL. This may change as more data become available, as some of the small studies are very encouraging. One of the interesting twists to the CAR technology is the question of how to make it widely available. In host-institutions (The U Penn system, MD Anderson, NCI) this is a centralized procedure, and in medical institutions world-wide, core patient cell facilities are commonplace. However it is rumored that Novartis at least wants to maintain the core facility model, as they picked up the Dendreon facility in Morris Plains New Jersey (at a bargain price) specifically to support CAR technology, and plan to duplicate those capabilities in Basel and in Singapore. Perhaps yesterday’s pickup of Israel’s Gamida Cell also plays into this centralized cell handling model. None of these complexities will bother the bi-specific therapeutics as these are injectable – that said, I’m not sure anyone will choose walking around with an IV pump for two months if they can avoid it.

So while these therapies and those like them are very potent, we will have to see how patients and providers ultimately use them.

Now, we’ve unfairly used blinatumomab and CTL019 to illustrate what are both pretty large areas of therapeutic development. We’ll come back to talk about the other players in the bispecific antibody and CAR spaces very soon.

stay tuned.

CRISPR Technology and Therapeutic Gene Editing – TJ Cradick

A Guest Post from Thomas (TJ) Cradick, Director of the Protein Engineering Facility, Georgia Institute of Technology; @NucleaseLab

Genome editing has remained a therapeutic goal since before specific, disease-causing mutations were discovered. Introducing mutations into cell lines and model organisms have also created very useful research reagents. The rate of both processes is greatly enhanced by creating nearby DNA breaks. These effects were first shown with meganucleases, which are very specific but have proved very difficult to convert to targeting novel sequences. The first readily engineered nuclease group was ZFNs (zinc-finger nucleases), followed by TALENs (transcription activator-like effector nucleases), and most recently CRISPRs (clustered regularly interspersed short palindromic repeats). The DNA breaks caused by these nucleases are repaired by the cellular DNA repair machinery and can lead to precise modification. Genome editing is no longer science fiction, though issues remain on delivery and specificity.

TALENs are easier to design than Zinc Finger Nucleases due to straightforward rules linking DNA binding repeats to a target sequence [1,2]. These rules don’t help pick the highest activity sites, though a new program, SAPTA, helps pick sites that can be targeted with high activity and specificity [3]. Several groups have developed high-throughput cloning methods to assemble the DNA binding repeats in TALENs, though new proteins must be assembled for each target [4,5].

For each target, CRISPR systems have the advantage of using identical proteins identified as a means for bacteria to fend off pathogens. These gene-editing systems are called clustered regularly interspaced short palindromic repeats (CRISPR) and pronounced “crisper”. Cas (CRISPR-associated) proteins clone a piece of the foreign DNA into the CRISPR genomic locus between the repeats. Many of these foreign DNAs are saved in the daughter cells. One bacterial protein called Cas9 and a guide strand RNA expressed from these saved DNA pieces allow targeting complementary sequences if the foreign DNA is encountered again. The key is that CRISPR works by cutting DNA complementary to the “guide strand” RNA. Directing cleavage to a new target site only requires cloning a pair of annealed oligos into the guide strand expression cassette [6,7]. This saves the very difficult step of designing and cloning new DNA binding proteins, as are required for ZFNs or TALENs.

In the beginning of 2013 papers began describing genome editing in mammalian cells [7,8]. A number of labs made their plasmids available on Addgene and several created websites and online forums to spread the word. A new company, Editas Medicine, founded by five world leaders in genome editing was founded to use CRISPR and TALENS as treatments for genetic diseases.

One of the big concerns with each type of nuclease is “off-target mutation” in different region of the genome. Several programs help verify and optimize specificity by listing putative off-target cleavage sites, including PROGNOS for ZFNs and TALENs [9]. Others have also found ZFN and TALEN off-target sites, primarily through experimentally guided off-target searches. Currently, there are limited data indicating that TALENs have improved specificity over ZFNs and lower cytotoxicity [10-12]. A number of publications have described the high level of off-target cleavage possible using CRISPR [13,14] and chromosomal deletions or re-arrangements [15]. Although ZFNs and TALENs have off-target cleavage as well, the high levels seen with current CRISPR methods has many groups scurrying to develop newer, safer methods. Use of pairs of Cas proteins that each cut only one strand holds promise, though has yet to be optimized for gene repair [16,17]. It is also likely that improved CRISPR systems will be developed that provide more specificity, though they may have decreased targeting efficiency. For many applications, the ease and speed of the current generation of CRISPR systems will provide a valuable research tool while the work on CRISPR 2.0 continues.

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2. Moscou MJ, Bogdanove AJ (2009) A simple cipher governs DNA recognition by TAL effectors. Science 326: 1501.
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