Category Archives: immunotherapy

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.

Screen Shot 2020-05-04 at 9.01.39 AM

This publication (https://doi.org/10.1016/j.cell.2020.03.039) 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 (www.aletabio.com). 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:

Screen Shot 2020-05-04 at 9.05.55 AM

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:

Screen Shot 2020-05-04 at 9.30.06 AM

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):

Screen Shot 2020-05-04 at 9.32.16 AM

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):

Screen Shot 2020-05-04 at 9.32.16 AM

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.

THE NEXT GREAT DRUG HUNT: Integrins, TGF-beta and Drug Development in Oncology and Fibrosis

PART 1: Integrin αvβ8

Advances in our understanding of the regulation and function of TGF-β is driving novel drug development for the treatment of diverse diseases. This is a field I’ve followed for a long time and of course in the development of cell therapeutics we (www.aletabio.com) always have an eye on immunosuppressive pathways – indeed, the immunotherapy and cell therapy fields cross-fertilize often and productively (see http://www.sugarconebiotech.com/?m=202002).

Several new papers in this space have caught my eye and I’m keen to share some key findings. This will be a multi-part post and today I want to talk about an integrin.

Long time readers will appreciate the importance of alpha v-integrin-mediated regulation of TGF-β release from the latent complex (http://www.sugarconebiotech.com/?p=1073). The model that first emerged around 2010 was elegant: various signaling pathways triggered GPCRs that could activate an integrin beta strand (paired with an alpha v integrin) and coordinate the release of TGF-β from the cell surface. Soluble TGF-β, free from restraint, could diffuse across nearby cells and trigger TGF-β-receptor activation. Three integrins have been linked to the regulation of TGF-β release: αvβ6, αvβ8 and αvβ3. The mechanism for releasing TGF-β from the latent complex on the cell surface requires a conformation change in the integrin structure. From this insight emerged diverse drug development efforts targeting specific integrins, targeting the ligands for specific GPCRs and so on. Notable examples include the anti-αvβ6 antibody STX-100 (Biogen), the autotaxin inhibitor GLPG1690 (Galapagos), small molecule inhibitors designed to block integrin conformational change, and isoform-specific anti-TGF-β biologics, among many others. The mechanism of action of these drugs includes reduction of free, active TGF-β and therefore reduced TGF-β-receptor signaling. STX-100 was withdrawn from clinical development due to toxicity – more on this another time. GLPG1690 is now in a Phase III trial (in IPF) having shown anti-fibrotic activity in earlier clinical trials – this drug has had an interesting life, originally partnered by Galapagos with Johnson & Johnson, later returned, and now part of the mega-partnership with Gilead. I’ve previously discussed these and many other drugs in development in the context of fibrosis pathogenesis (http://www.sugarconebiotech.com/?p=1073). We’ll look at novel TGF-β-directed antagonists and their role in immune-oncology in part 2, as part of a long-running thread (http://www.sugarconebiotech.com/?m=201811).

So back to integrins. The dogma that emerged based on work from disparate labs was that an activated integrin was required to release TGF-β from the latent (inactive) complex on cell surfaces, allowing for precise regulation of TGF-β activity. More specifically, this model refers to the release of two of the three isoforms of TGF-β – isoforms 1 and 3. Isoform 2 regulation is different and relies on physical force acting directly on cells to trigger release. Of note, isoform 2 antagonism contributes to the toxicity associated with pan-TGF-β blockade but does not appear to contribute significantly to disease pathology either in fibrosis or in oncology. Therefore, specifically antagonizing TGF-β-1/3 without antagonizing TGF-β-2 is ideal – and the model we’ve just outlined allows for this specificity by targeting specific integrins.

The model that alpha v integrins mediated release of free, active TGF-β has held firm for nearly a decade. Now however there is a fascinating update to this model that involves the αvβ8 integrin. Work from the labs of Yifan Cheng and Steve Nishimura at UCSF has revealed a novel mechanism of TGF-β regulation that has interesting implications for drug development (https://doi.org/10.1016/j.cell.2019.12.030). Uniquely, integrin αvβ8 lacks critical intracellular binding domains that allow an integrin to anchor to actin fibers within the cell. As a result, binding to αvβ8 does not cause the release of TGF-β from the latent complex on the cell surface but rather presents an active form of TGF-β on that cell surface, without release from the latent complex. Importantly the complex formed between αvβ8 and TGF-β is conformationally stable and relies (in their experimental system) on trans-interaction between one cell expressing αvβ8 and a second cell expressing TGF-β as displayed on a latent protein complex (here, containing the GARP protein), and expressing the TGF-β receptors. In this system TGF-β remains anchored to the GARP-complex, but the conformational rotation caused by αvβ8 binding allows anchored TGF-βto interact with TGF-β-RII, thereby recruiting TGF-β-RI and inducing signaling.

The focus on GARP (aka LRRC32) relates to this groups long-standing interest with T-regulatory cells, which uniquely express GARP. Biotech investors will recall the Abbvie/Argenx deal on this target, which is in clinical development (https://clinicaltrials.gov/ct2/show/NCT03821935). A related protein called LRRC33 has been discovered on myeloid lineage cells.

More important, in my view, is that αvβ8 is expressed widely on tumor cells and has been variably reported to correlate with metastases (depending on the indication). This suggests that one means that tumor cells have of inducing TGF-β activation on interacting cells (eg. lymphocytes, myeloid cells and perhaps stromal cells) is via αvβ8 activity. The dependent hypothesis would be that such activation is immunosuppressive for those tumor-interacting cells. This is consistent with the known effects of TGF-β on immune cells in particular, but also stromal cells like fibroblasts. As an aside I like this model as one way of accounting for the appearance of T-regulatory cells and myeloid lineage suppressor cells in the tumor microenvironment as result of, rather than the cause of, immunosuppression, that is, these cells may be epi-phenomena of broad TGF-β-mediated immunosuppression. This may in turn explain why targeting such cells as T-regs and MDSCs has been largely unsuccessful to date as a therapeutic strategy for cancer.

There are some other implications. As the authors point put, the integrin/TGF-β complex is stable, and the binding domain that mediates the interaction is buried with the protein complex. It is unclear whether anti-TGF-β antagonists that target the canonical integrin binding cleft would be able to access this site within the complex. It’s possible that some of these drugs (whether antibodies or small molecules) can’t work in this setting. On the other hand, antibodies to αvβ8 clearly prevent the complex from forming and should block TGF-β-mediated immunosuppressive signaling in settings where αvβ8 expression is dominant. An anti-αvβ8 antibody strategy is being pursued by Venn Therapeutics (disclosure: I sit on Venn’s SAB). Further, the structural features identified in the paper include well-defined pockets that might be suitable for small molecule drugs. Indeed, one of the structural features in the b8 protein, consisting of hydrophobic residues, appears to account for the differential binding of various integrins (β6, β1, β2, β4, β7) to TGF-β, a remarkable finding. Analyses of the differences between the structure of β8 and other β integrins has been extensive across laboratories (see https://www.nature.com/articles/s41467-019-13248-5 for another important paper). Small molecule drug discovery is well underway in this field (see for example Pliant Therapeutics and Morphic Therapeutics) and one might imagine that these novel results found an interested audience in many bio-pharma labs.

Next: what has Scholar Rock been up to, and what can we learn from their work?

Stay tuned.

Updates from #CowenHealthCare 2020 – CAR T and it’s competitors

If you work in cell therapy you have follow all kinds of therapeutic developments in indications of interest which for us at Aleta Biotherapeutics (www.aletabio.com) includes specific solid tumor indications, and several hematologic malignancies.

Over the last few days we’ve gotten interesting updates regarding diverse hematologic malignancies, including news about therapeutics for front line (newly treated) or relapsed or refractory (r/r) Non-Hodgkin Lymphoma (NHL), multiple myeloma (MM) and acute myeloid leukemia (AML) patients and the myelodysplastic syndromes (MDS). Note here that the reference to different lines of therapy – front line or early line vs r/r, because the treatment paradigms change as patients fail earlier lines of therapy, ie. as they become refractory to or relapse from their current therapy. This can become a long and arduous battle for patients who repeatedly fail treatment. Unfortunately, this is often the case in r/r MM, r/r AML and MDS and in some subtypes of r/r NHL.

On Monday (2 March 2020) I attended the “Cell Therapy & Myeloma” panel at the 40th Annual Cowen Heath Care Conference. This panel covered much more than the title implies, and I really liked the format which is built on the back of questions posed to the audience, to an (unnamed) group of specialists in the field who were polled in advance, and to the seated key opinion leaders (KOLs), in this case Dr Deepu Madduri (Mt Sinai) and Dr Jacob Soumerai (MGH).

They covered a lot of ground.

The first series of questions sought to pin down trends in r/r Follicular lymphoma (FL) a subtype of NHL that can become difficult to treat if patients fail successive lines of treatment. The Leukemia Lymphoma Society has a primer here -https://lymphoma.org/aboutlymphoma/nhl/fl/relapsedfl/.  There has been brisk drug development in r/r NHL including FL. Novel drug classes include CAR-CD19 T cells, bispecific T cell engagers, small molecule drugs (targeting PI3K, Bcl2, BTK, EZH2) and new antibodies. The Cowen panel worked through a series of questions regarding this landscape and there were several key takeaways.

One was the clear preference, by the anonymously polled specialists and by the seated panelists, for CAR-CD19 therapy as the most exciting new drug for r/r FL. The driver here is the durability of response (DOR) in really late line patients and the sense that both overall response rate (ORR) and DOR will only improve as these cell therapeutics move to earlier lines of therapy. It was striking that several classes of bispecific antibodies (the CD3 x CD20 and CD3 x CD19 bispecifics) elicited strong enthusiasm from the audience (mostly analysts and investors) but only muted enthusiasm from the KOLs. This lack of enthusiasm had 2 distinct bases: 1) limited data to date, and 2) “I can give a bispecific after I give a CAR T, but not the other way around”, which was a very interesting thought (and given despite of the few case reports of CD3 x CD20 bispecific therapy working in several relapsed CAR-T patients). I think that in later line patients these clinicians want to keep their options open as long as possible.

Among the other classes of therapeutics, Epizyme’s EZH2 inhibitor tazemetostat received significant support based on the ability to select EZH2-mutated patients, and on good DOR and on good tolerability, the latter thought to be better than the PI3Kdelta class inhibitors, BTK inhibitors or BCl2 inhibition. The consensus was that tazemetostat could see up to 20% market penetration in third line FL after the expected launch in June 2020.

Among the PI3Kdelta inhibitors, Bayer’s copanlisib was singled out as best-in-class with little differentiation among the others (from Gilead, Verastem, MEI, Incyte, or TG Therapeutics). Finally, in this setting of r/r FL, both venetoclax (a Bcl2-inhibitor) and polatuzumab vedotin (a CD79b antibody-drug conjugate), were relegated to minor use by the specialists and panelists.

The uptake of CAR-CD19 therapies has been brisk, and the panelists highlighted quicker payor approvals and the accelerating pace of referrals to cell therapy centers. The consensus is for 30% increase in patient number treated in 2020 (so roughly 1350 patients in the US, vs 1050 treated last year).

The discussion stayed on CAR-CD19 therapeutics to touch on some of the newer trials and entrants. Kite/Gilead is running a Phase III trial of axi-cel (axicabtagene ciloleucel, brand name Yescarta) in second line DLBCL patients vs a standard of care regimen of high dose chemotherapy followed by an autologous stem cell transplant. Data are anticipated in the second half of 2020. The Cowen moderators passed the question: will this trial show a progression free survival (PSF) benefit?  Mind you, this is a low bar since overall survival – the shining triumph of cell therapy – is not part of the question. The audience (again, mainly investors and analysts) was overwhelming positive, giving about 70% odds of a positive impact on PFS. Here the panelists agreed, citing the fact that this trial was enrolling high-risk patients and therefore the comparator arm of the trial (chemo + ASCT) should do very poorly. Success with this trial would move axi-cel up a line of therapy (from 3rd or later to 2nd or later) and bolster the health care value argument that patients may avoid ASCT altogether.  We are apparently already seeing this effect, as a talk at #TCMT20 highlighted the steep decline in transplants being done in DLBCL.

Sticking with axi-cel, this CAR-CD19 cell therapy was highlighted as the one most likely to be the market leader by 2023, based on the (currently) much shorter manufacturing and turnaround time as compared to tisa-cel (tisagenlecleucel from Novartis, brand name Kymriah). The panelists agreed with the specialist poll, despite the fact that they also felt that tisa-cel may be better tolerated by patients overall. Further, the panelists did note that the difference in manufacturing turnaround was likely to diminish as Novartis improves its product workflow. So we’ll have to wait and see.

Competition may also play a role.  The long-awaited Juno > Celgene > BristolMyers Squibb CAR-CD19 liso-cel (lisocabtagene maraleucel) should see its first approval soon, and several allogeneic and non-T cell based programs are advancing. Cowen’s moderators highlighted a number of these for discussion. Allogene CAR-CD19, called ALLO-501 is currently in a Phase 1 trial enrolling r/r diffuse large B cell lymphoma (DLBCL) and r/r FL patients, with initial data expected later this year. The moderators put forward the question: what percent of (responding) patients have to show a durable response for this to be an exciting option to the autologous CAR-CD19 products. It’s a complex question since the current approved CAR-CD19s show about a 50% durable response rate within the responders, where a goodly proportion of the patients that do not have a durable response are relapsing after a response, sometimes with CD19-negative lymphoma or leukemia (ie. the cancer has undergone natural selection and loses target antigen expression). The polled specialists and the panelists wanted to see a pretty high durable response rate, 35-40% (specialists) up to 50% (the panelists). If the field were to see responses as good as axi-cel, tisa-cel and liso-cel, this would be “a huge advance”, according to Dr Soumerai of MGH.

Of note, Allogene itself was a bit more cautious at their public company presentation later in the day. Dr David Chang, Allogene’s CEO, provided some guidance and set expectations. He noted that the company would report early data form the ALLO-501 program at #ASCO20 and/or #EHA20 but stressed the readouts of safety and degree of lymphodepletion from up to 3 dose cohorts, and with several different doses of their lymphodepletion agent ALLO-647, and anti-CD52 antibody. In the ALLO-501 trial this is given along with the lymphodepeleting chemotherapy combination of cyclophosphamide and fludarabine (Cy-Flu). Among the other allogeneic and off-the-shelf CAR-CD19 programs several were highlighted either by the audience (Fate Therapeutics induced CAR-NKs) or the panelists (the Takeda/MD Anderson NK program). Other programs from Atara, CRISPR, and Precision all would have to show some or more data in order to get the specialists or the panelists to take notice.

Notably, there was consensus among the audience, polled specialists and panelists that CD3 x CD20 bispecifics would be less efficacious than CAR T cells, regardless of the specific therapeutics (eg. from Roche or Regeneron or Genmab). Further, Dr Madduri expressed concern at the need to keep dosing patients both because of inconvenience and possible safety over time. Her view is that patients prefer a single dose CAR.

Finally in the r/r DLBCL space, both polled specialists and the panelists saw minimal roles for the anti-CD79b-drug conjugate polatuzumab vedotin (brand name Polivy, from Roche) or the anti-CD19-ADCC competent antibody tafasitamab (from Morphosys, which now has a 30 August PDUFA date with FDA).  Both of these biologics need to be given in combination with other therapeutics and there did not appear to be a benefit over standard combinations. More specifically, polatuzumab vedotin is given with rituximab and bendamustine and was considered “tolerable” but perhaps best used in a bridge to transplantation setting or a bridge to CAR-CD19 cell therapy. Tafasitamab was recently written up by Jabob Plieth here: https://www.evaluate.com/vantage/articles/analysis/why-2020-spotlight-will-fall-tafasitamab.

Turning to r/r MM there were a series of questions about lines of therapy and which were preferred. For newly diagnosed patients and for second-line patients the clearly favored standard of care was an ‘ImID’ (immunomodulatory agent, eg. revlimid) plus the anti-CD38 antibody daratumumab (brand name Darzalex, from Johnson & Johnson’s Janssen division) plus dexamethasone (aka triple therapy) with perhaps a proteasome inhibitor added (thus, a quad). The use of daratumumab in early line therapy will continue to grow as it is payor-approved for early-line use.

For later line therapy, the moderators first brought up selinexor (brand name Xpovio, from Karyopharm Therapeutics), a first-in-class, oral Selective Inhibitor of Nuclear Export (SINE), which was granted accelerated approval last year for use in in combination with dexamethasone for adult r/r MM patients who received at least four prior therapies and whose disease is refractory to at least two proteasome inhibitors, at least two ImIDs, and an anti-CD38 monoclonal antibody. There was a consensus view that this drug will see flat to diminishing use due to poor tolerability. Dr Madduri noted that she gives this drug once week rather than twice a day (as labeled) in an effort to improve patient tolerance and only used it as a bridge to clinical trial enrollment (ie. on something else, for example, CAR-BCMA cellular therapy. Curiously there were no questions about isatuximab-irfc (brand name Sarclisa, from Sanofi-Aventis), newly approved in combination with pomalidomide and dexamethasone for adult patients with r/r/ MM and at least two prior therapies (see this SITC writeup: https://www.sitcancer.org/aboutsitc/press-releases/2020/isatuximab-irfc).

As for CAR T cells for multiple myeloma, the panelists were hesitant to pick a winner between the two advanced CAR-BCMA programs: bb2121 (Bluebird) and JNJ-4528 (from J&J, formally called LCAR-B38M) until J&J updated PFS data. At their public company presentation Nick Leschly, Bluebird’s CEO, noted that they will file the BLA for bb2121 (now called idecabtagene vicleucel or ide-cel) in the first half of this year, and would release longer-term follow-up data from the ide-cel clinical trials KarMMa and CRB-401 in the second half of the year. The BLA will be filed despite the “slow-down” from FDA necessitated by the agency’s request for additional lentivirus production characterization information from their chosen cell suspension manufacturing method (no details given). What the FDA has asked for apparently is both different from and more than the EU agency (EMA) wanted.

On the allogeneic CAR T cell front, Dr Chang at Allogene noted that they would have early data on ALLO-715 (their version of a CAR-BCMA therapy) at #ASH20. Here he noted they are considering dropping the Cy-Flu lymphodepletion and just using their anti-CD52 antibody to lymphodeplete, we’ll see (this doesn’t strike me as realistic).

In general both the polled specialists and the panelists were more enthusiastic about CAR-BCMA therapy than several other modalities, including belantamab mafodotin (from GSK), an antibody-drug conjugate, composed of an anti-BCMA monoclonal antibody bound to auristatin F. This drug was thought to be not quite good enough given the unmet need, there remain concerns about the ocular toxicity (the bane of ADC technology) and keen disappointment that the response rate dropped below 30% ORR in daratumumab-refractory patients. Clearly this therapeutic will see some use in late line therapy, and further clinical development has yielded results in earlier line as reported on 2 March (see https://www.evaluate.com/vantage/articles/news/trial-results/karyopharm-comes-boston-springtime). A similar wait-and-see approach is being taken by these specialists and panelists to the CD3 x BCMA bispecifics, which are currently viewed as best for community hospital settings without CAR T cell capacity or for patients who cannot wait for the cell therapy production.

One theme in r/r MM is the concern that patients are still not being cured, even with cell therapies. The gradual relapse from CAR-BCMA treatment that one sees in all the clinical studies has been linked either to CAR T persistence being limited or to diminished BCMA antigen expression on the cancer cells. Of course, these two things may be related. One desire expressed by Dr Madduri was for a CAR-BCMA therapy with better persistence properties.

Two short notes while we’re here. Gilead stated at their public company presentation during Cowen Health Care that the value driver for the Forty Seven acquisition was the MDS data (https://xconomy.com/san-francisco/2020/03/02/gilead-boosts-cancer-drug-pipeline-with-4-9b-deal-for-forty-seven/). And hematologic drug heavyweight venetoclax (the Bcl-2 inhibitor from Abbvie) scored a miss in an AML confirmatory trial (https//pharmaphorum.com/news/abbvie-roches-venclexta-fails-in-confirmatory-aml-trial/). In summary, a busy couple of days.

As many readers know, Aleta Biotherapeutics builds cellular therapeutics with exemplary persistence and fitness properties. We have two cell therapy programs heading for the clinic now. One will treat r/r AML patients both in the pediatric and adult patient populations. Our solid tumor program is designed to treat patients relapsing from breast or lung cancer with brain metastases. We also have a biologics program specifically created to ‘rescue’ CAR-CD19 T cells in patients relapsing from therapy. You can find out more at www.aletabio.com or email me at paul.rennert@aletabio.com or just call me at 1-508-282-6370 and of course follow me on Twitter @PDRennert and @BioAleta.

That’s it for now.  Stay tuned.

Radical optimism: considering the future of immunotherapy

I wrote recently about the sense of angst taking hold in the next-generation class of immuno-therapeutics – those targets that have come after the anti-CTLA4 and anti-PD-(L)-1 classes, and raised the hope that combination immunotherapy would broadly raise response rates and durability of response across cancer indications.

There are diverse next-generation immuno-therapeutics including those that target T cells, myeloid cells, the tumor stromal cells, innate immune cells and so on. A few examples are given here (and note that only a few programs are listed for each target):

Screen Shot 2018-11-05 at 8.31.33 PM

There are of course many other therapeutic targets – OX40/CD134, Glutaminase, ICOS, TIM-3, LAG-3, TIGIT, RIG-1, the TLRs, various cytokines, NK cell targets, etc.

In the last year – since SITC 2017 – there has been a constant stream of negative results in the next generation immuno-therapy space, with few exceptions. Indeed, each program listed in the table has stumbled in the clinic, with either limited efficacy or no efficacy in the monotherapy setting or the combination therapy setting, typically with an anti-PD-(L)-1 (ie. an anti-PD-1 or an anti-PD-L-1  antibody). This is puzzling since preclinical modeling data (in mouse models and with human cell assays) and in some cases, translation medicine data (eg. target association with incidence, mortality, or clinical response to therapy), suggest that all of these targets should add value to cancer treatment, especially in the combination setting. I’ve discussed the limitations of these types of data sets here, nonetheless the lack of success to date has been startling.

With SITC 2018 coming up in a few days (link) I think it is a good time to step back and ask: “what are we missing?”

One interesting answer comes from the rapidly emerging and evolving view of tumor microenvironments (TME), and the complexity of those microenvironments across cancer indications, within cancer indications and even within individual patient tumors. TME complexity has many layers, starting with the underlying oncogenic drivers of specific tumor types, and the impact of those drivers on tumor immunosuppression. Examples include activation of the Wnt-beta catenin pathway and MYC gain of function mutations, which mediate one form of immune exclusion from the tumor (see below), and T cell immunosuppression, respectively (review). In indications where both pathways can be operative (either together or independently, eg. colorectal cancer, melanoma and many others) it is reasonable to hypothesize that different strategies would be needed for combination immuno-therapy to succeed, thereby producing clinical responses above anti-CTLA4 or anti-PD-(L)-1 antibody treatment alone.

A second and perhaps independent layer of complexity is TME geography, which has been roughly captured by the terms immune infiltrated, immune excluded, and immune desert (review). These TME types are illustrated simply here:

Screen Shot 2018-11-05 at 8.45.19 PM

The different states would appear to be distinct and self-explanatory: there are immune cells in the tumor (infiltrated), or they are pushed to the periphery (excluded), or they are absent (desert). The latter two states are often referred to as “cold” as opposed to the “hot” infiltrated state. It is common now to propose as a therapeutic strategy “turning cold tumors hot”. The problem is that these illustrated states are necessary over-simplifications. Thus, immune infiltration might suggest responsiveness to immune checkpoint therapy with anti-PD-(L)-1 antibodies, and indeed, one biomarker of tumor responsiveness is the presence of CD8+ T cells in the tumor. But in reality, many tumors are infiltrated with T cells that fail to respond to immune checkpoint therapy at all. The immune excluded phenotype, alluded to above with reference to the Wnt-beta catenin pathway, can be driven instead by TGF beta signaling, or other pathways. The immune desert may exist because of active immune exclusion, lack of immune stimulation (eg. MHC-negative tumors) or because of physical barriers to immune infiltration. Therefore, all three states represent diverse biologies within and across tumor types. Further, individual tumors have different immune states in different parts of the tumor, and different tumors within the patient can also have diverse phenotypes.

There are yet other layers of complexity: in the way tumors respond to immune checkpoint therapy (the “resistance” pathways, see below), the degree to which immune cells responding to the tumor cells are “hardwired” (via epigenetic modification), the metabolic composition of the TME, and so on. Simply put, our understanding remains limited. The effect of this limited understanding is evident: if we challenge tumors with a large enough immune attack we can measure a clinical impact – this is what has been achieved, for example, with the anti-PD-(L)-1 class of therapeutics. With a lesser immune attack we can see immune correlates of response (so something happened in the patient that we can measure as a biomarker) but the clinical impact is less. This is what has happened with nearly all next-generation immuno-therapeutics. As a side note, unless biomarker driven strategies are wedded to a deep understanding of specific tumor responsiveness to the therapeutic they can be red herrings - one example may be ICOS expression, although more work is needed there. Understanding specific tumor responsiveness is critical regardless of biomarker use, due to the layered complexity of each indication, and even each patient’s tumors within a given indication.

So why should we be optimistic?

I propose that some of the next generation immuno-therapeutics will have their day, and soon, due to several key drivers: first, for some of these classes, improved drugs are moving through preclinical and early clinical pipelines (eg. A2AR, STING). Second, the massive amount of effort being directed toward understanding the immune status of diverse tumors ought to allow more specific targeting of next generation immuno-therapeutics to more responsive tumor types. The TGF beta signature presents a particularly interesting example. Genentech researchers recently published signatures of response and resistance to atezolizumab (anti-PD-L1) in bladder cancer (link). In bladder cancer about 50% of tumors have an excluded phenotype, and about 25% each have an immune infiltrated or immune desert phenotype. The response rate to treatment with atezolizumab was 23% with a complete response rate of 9% (note that responses did not correlate with PD-L1 expression but did correlate with both tumor mutational burden and a CD8+ T cell signature). Non-responding patients were analyzed for putative resistance pathways. One clear signature of resistance emerged – the TGF beta pathway, but only in those patients whose tumor showed the immune excluded phenotype. The pathway signature was associated with fibroblasts, but not myeloid cells, in multiple tumor types. The T cells were trapped by collagen fibrils produced by the fibroblasts:

Screen Shot 2018-11-05 at 9.04.16 PM

(The image is a screenshot from Dr Turley’s talk at CICON18 last month).

It follows that a combination of a TGF beta inhibitor and a PD-(L)-1 inhibitor for the treatment of bladder and perhaps other cancers should be used in patients whose tumors show the immune excluded TME phenotype, and perhaps also show a fibroblast signature in that exclusion zone. Indeed, in a recent paper, gene expression profiling of melanoma patients was used to demonstrate that a CD8-related gene signature could predict response to immuno-therapy – but only if the TGF beta signature was low (link).

There are other immunotherapy resistance pathways – some we know and some are yet to be discovered. We should eventually be able in future to pair specific pathway targeting drugs to tumors whose profile includes that pathway’s signature – this has been done, retrospectively, with VEGF inhibitors and anti-PD-(L)-1 therapeutics. This will require a more comprehensive analysis of biopsy tissue beyond CD8+ T cell count and PD-1 or PD-L1 expression – perhaps immunohistochemistry and gene transcript profiling – but these are relatively simple technologies to develop, and adaptable for a hospital clinical lab settings. Not every next generation immuno-therapeutic will succeed as the clinical prosecution becomes more targeted, but some certainly will (we might remain hopeful about adenosine pathway inhibitors, STING agonists, and oncolytic virus therapeutics, to name a few examples).

Another driver of success will be cross-talk with other technologies within immuno-oncology – notably cell therapy (eg. CAR-T) and oncolytic virus technologies. We have already seen the successful adaptation of cytokines, 4-1BB signaling, OX40 signaling and other T cell stimulation pathways into CAR T cell designs, and the nascent use of PD-1 and TGF beta signaling domains in cell therapy strategies designed to thwart immuno-suppression (we should note here that CAR T cells, like tumor infiltrating T cells, will face  barriers to activity in different tumor indications). The example of local (and potentially safer) cytokine secretion by engineered CAR-T cells has helped drive the enormous interest in localized cytokine technologies. Most recently, the combination of CAR-T, oncolytic virus and immune checkpoint therapy has shown remarkable preclinical activity.

SITC 2018 – #SITC18 on Twitter – will feature sessions on  immunotherapy resistance and response, the tumor microenvironment, novel cytokines and other therapeutics, cell-based therapies, and lessons from immuno-oncology trials (often, what went wrong). We can expect lots of new information, much of it now focused on understanding how better to deploy the many next generation immuno-therapeutics that have been developed.

So, I would argue that “radical optimism” for next generation immunotherapy and immunotherapy combinations is warranted, despite a year or more of clinical setbacks. Much of the underlying science is sound and it is targeted clinical translation that is often lagging behind. Progress will have to come from sophisticated exploratory endpoint analysis (who responded, and why), sophisticated clinical trial inclusion criteria (who to enroll, and why) and eventually, personalized therapeutic application at the level of the indication and eventually the patient.

In the meantime, stay tuned.

Immuno-oncology (IO) combination therapy- why the angst?

Thoughts triggered by discussions over the last month or two, perceived sentiment on social media, reaction to clinical updates, and pre-AACR butterflies.

In 2015 Gordon Freeman of the Dana Farber Cancer Institute, one of the discoverers of the PD-1/PD-L1 axis, rang me up and asked if I would help write a review with he and Kathleen Mahoney, an oncologist doing a research rotation in his lab. We ambitiously laid out the argument that PD-1/PD-L1 directed therapeutics would be the backbone of important combination therapies and reviewed the classes of potential combinatorial checkpoints (http://www.nature.com/nrd/journal/v14/n8/full/nrd4591.html). We covered new immune checkpoint pathways within the Ig superfamily, T cell stimulatory receptors in the TNF receptor superfamily, stimulatory and inhibitory receptors on NK cells and macrophages, targets in the tumor microenvironment (TME), and so on. Importantly we also stopped to consider combinations with “traditional” cancer treatments, e.g. chemotherapy and radiation therapy, and also with “molecular” therapeutics, those directed to critical proteins that make cells cancerous. Regardless, it’s fair to say that we believed that pairing an anti-PD-1 mAb or an anti-PD-L1 mAb with another immuno-modulatory therapeutic would quickly yield impressive clinical results. A massive segment of the IO ecosystem (investors, oncologists, biopharma) shared this belief, and largely still does. Those stakeholders are betting clinical and R&D resources plus huge amounts of money on the promise of IO combinations. After all, the first IO combination of anti-CTLA4 mAb ipilimumab and anti-PD-1 mAb nivolumab has dramatically improved clinical response in advanced melanoma patients and to a lesser extent in advanced lung cancer patients. The downside is additive toxicity, and so the palpable feeling has been that new IO combinations would give a similar efficacy bump, perhaps even with less toxicity.

It’s now about two and a half years since we began drafting that paper and the inevitable letdown has set in. What happened? Let’s cover a few issues:

- Several marque IO combinations have been disappointing so far. Last year we saw unimpressive results from urelumab (anti-4-1BB) in combination with nivolumab (anti-PD-1) and of epacadostat (an IDO inhibitor) paired with pembrolizumab (anti-PD-1).

- Monotherapy trials of therapeutics directed to hot new targets (OX40, CSF1R, A2AR etc.) did not produce any dramatic results, forcing a reevaluation of the potential for truly transformative clinical synergy in the IO combination setting.

- These first two points also reminded the field of how limited preclinical mouse modeling can be.

- Combinations of standard of care with anti-CTLA4 mAb ipilimumab and with PD-1 pathway inhibitors have begun to show promising results, raising the efficacy bar in a variety of indications. There have been several startling examples: the combination of pembrolizumab plus chemotherapy in first line lung cancer, which doubled response rates over pembrolizumab alone; the combination of cobimetinib (a MEK inhibitor) with atezolizumab (anti-PD-L1 mAb) in colorectal cancer (MSS-type) which produced clinical responses in patient population generally non-responsive to anti-PD-1 pathway inhibition; the combination of atezolizumab plus bevacizumab (anti-VEGF) in renal cell carcinoma, showing promising early results; and so on.

- We can add the realization that relapses are a growing issue in the field, with approximately 30% of anti-CTLA4 or anti-PD-1 pathway treated patients eventually losing the anti-tumor response.

Note here that all of this is happening in a rapidly evolving landscape and is subject to snap-judgment reevaluation as clinical data continue to come in. For example, rumors that IDO inhibition is working well have been spreading in advance of the upcoming AACR conference. Indeed the clinical work on all of the immuno-modulatory pathways and IO combinations has increased, and the race to improve care in diverse indications continues. There will be additional success stories.

Why the perception of angst then? The sentiment has been summed up as “everything will work a little, so what do we research/fund/advance? How do we choose? How will we differentiate”? Such sentiment puts intense pressure on discovery, preclinical and early clinical programs to show robust benefit or, and perhaps this is easier, benefit in particular indications or clinical settings. I started thinking about this recently when a friend of mine walked me through a very pretty early stage program targeting a novel pathway. It was really quite impressive but it was also apparent that the hurdles the program would have to clear were considerable. Indeed it seemed likely that validation of the therapeutic hypothesis (that this particular inhibitor would be useful in IO) would not come from preclinical data in mice (no matter how pretty), nor from a Phase 1 dose escalation safety study, nor from a Phase 1 expansion cohort, but would require Phase 2 data from a combination study with an anti-PD-1 pathway therapeutic. That is, 5+ years from now, assuming all went smoothly. To advance such a therapeutic will take intense focus in order to build a fundable narrative, and will require stringent stage-gates along the way. Even then it will be very hard to pull it off. If this reminds you of the “valley of death” we used to talk about in the biotech realm, well, it should.

What should we look for to shake up this landscape? As mentioned, this is a rapidly evolving space. We have already seen a shift in language (“step on the gas” vs. “make a cold tumor hot” is one good example), but let’s list a few:

- “Cold tumors” have no immune response to stimulate. Making them “hot” is a hot field that includes oncolytic virus therapeutics, vaccines, “danger signals” (TLRs, STING, etc), and, to loop back around, chemotherapy and radiation therapy.

- Relapsed patients – as noted above we are seeing ~30% relapse rate in immunotherapy treated patients. Understanding the basis for relapse is a promising field and one that an emerging therapeutic could (and very likely will) productively target.

- Targeting the TME in cold tumors and in unresponsive tumors (the difference is the unresponsive tumors look like they should respond, in that they contain T cells). This is a vast field that covers tumor cell and stromal cell targets, secreted factors, tumor and T cell metabolism and on and on. One can imagine a setting in which a particular TME is characterized (by IHC, Txp or other means) and the appropriate immuno-modulatory therapeutics are applied. We see this paradigm emerging in some indications already. This would certainly be useful as a personalized medicine approach and could be an excellent way to position an emerging therapeutic.

We could go further to talk about the neoantigen composition of particular tumor types, the role of the underlying mutanome, the plasticity of the TME (it’s a chameleon), metabolic checkpoints, and other, potentially novel, targets.

All of this is under intense and active investigation and important data will emerge in time. Until then, nascent immunotherapy programs need to tell a clear and compelling story in order to attract the interest of investors, biopharma and ultimately, oncology clinical trialists. Those that fail to develop a compelling narrative are likely to struggle.

I’ll just end on a few narratives I really like for IO combinations going forward:

- the role of innate immunity in activating immune responses and expanding existing responses (e.g. immune primers like STING agonists and NK cell activators like lirilumab)

- the role of adenosine in maintaining an immunosuppressed (ie. non-responsive) TME (thus inhibitors of A2AR, CD39, CD73)

- the role of beta-catenin signaling in non-responsive tumors (while carefully selecting the mode of inhibition)

- the role of TGF-beta activity in resistance to PD-1 pathway therapeutics (again, with care in selecting the mode of inhibition)

of course at Aleta we’ve charted a different course, ever mindful of the need to focus where we see clear yet tractable unmet need. so we’ll see, starting with AACR in early April, kicking off an active medical conference season.

stay tuned.

Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival

A Few Day 1 Highlights

Ton Schumacher (Netherlands Cancer Institute), abstract IA04 ,has discovered a novel regulator of PDL1 expression called PD-L1M1. PD-L1M1 associates with PD-L1 and modulates the T cell inhibitory function of PD-L1. The protein is expressed ubiquitously, so unclear if this finding has therapeutic implication.

Michael Peled and Adam Mor (NYU School of Medicine), abstract A059, had a poster on molecules that interact with the cytoplasmic tail of PD-1 using high resolution Mass Spec. Two proteins were highlighted on their poster: EFHD2 and SH2D1A. EFHD2 co-localized with PD-1 and was essential for clustering and signal transduction (thus, ablation of EFHD2 blocks PD-1 mediated inhibitory activity). SH2D1A had the opposite function as evidenced by increased PD-1 inhibitory signaling when SH2D1A was knocked down and reduced PD-1 inhibitory signaling when overexpressed. SH2D1A physically competed with SHP2 for access to the PD-1 cytoplasmic tail.

Dario Vignali (U. Pitt School of Medicine), abstract IA05, focused on several emerging immune checkpoints. The first, IL-35, was investigated using anti-IL-35 antibody in various tumor models, with very nice results (similar to anti-PD-1). I liked the neuropilin story – this is a Sema4a binding protein and was offered up as a central control node for Treg activity. NRP1 controls Treg T cell expression of IFNgamma, acting in cis and in trans (so self-regulation and neighborhood regulation). Of interest he identified subsets of melanoma and H&N cancer patients having high levels of NRP1 in the TME, so this is perhaps an actionable finding.

Susan Kaech (Yale Univ Med School), abstract 1A07, presented data showing that the PEPCK overexpression ups the anti-tumor activity of T cells in the TME, thus showing that T cells – if given the tools – can co-opt the same metabolic pathways (lactate, fatty acids) used by tumor cells in the tumor microenvironment (TME). A consequence of this metabolic checkpoint is the upregulation of PD-1 via fatty acid signaling through the PPARs, delta I think. Of interest is that the metabolic switch is supported by gross upregulation of CD36, a fatty acid active transporter, on T cells in the TME.

Greg Delgoffe (U Pitt Cancer Inst), abstract IA08, picked up this general theme, demonstrating that T cells dividing in the TME rapidly lose mitochondrial (MT) mass, and therefore their ability to metabolize glucose ( a T cells preferred energy source). This is a failure of MT biogenesis, due to the downregulation of PGC1alpha, which is required for the process. In the TME, T cell PGC1alpha expression is regulated by AKT – robust AKT signaling leads to PGC1alpha downregulation. If note, PGC1alpha transgenic T cells retain high proliferative activity, do not lose MT, and are highly active Teffector cells.

Novel Immunotherapeutic Approaches to the Treatment of Cancer: Drug Development and Clinical Application

Our new immunotherapy book has been published by Springer:

http://www.springer.com/us/book/9783319298252

I want to take a moment to acknowledge the stunning group of authors who made the book a success. I’d also like to promote our fund raising effort in memory of Holbrook Kohrt, to whom the volume is dedicated – 5% of net sales will be donated by me, on behalf of all of our authors, the the Cancer Research Institute in New York. So please consider buying the book or just the chapters you want (they can be purchased individually through the link given above.

Now, the authors:

from Arlene Sharpe and her lab (Harvard Medical School, Boston):

Enhancing the Efficacy of Checkpoint Blockade Through Combination Therapies

from Taylor Schreiber (Pelican Therapeutics, Heat Biologics):

Parallel Costimulation of Effector and Regulatory T Cells by OX40, GITR, TNFRSF25, CD27, and CD137: Implications for Cancer Immunotherapy

from Russell Pachynski (Washington University St Louis) and Holbrook Kohrt (Stanford University Medical Center)

NK Cell Responses in Immunotherapy: Novel Targets and Applications

from Larry Kane and Greg Delgoffe (University of Pittsburgh School of Medicine):

Reversing T Cell Dysfunction for Tumor Immunotherapy

from Josh Brody and Linda Hammerich (Icahn School of Medicine, Mt Sinai, NYC)

Immunomodulation Within a Single Tumor Site to Induce Systemic Antitumor Immunity: In Situ Vaccination for Cancer

From Sheila Ranganath and AnhCo (Cokey) Nguyen (Enumeral Inc, Cambridge MA)

Novel Targets and Their Assessment for Cancer Treatment

From Thomas (TJ) Cradick, CRISPR Therapeutics, Cambridge MA):

Cellular Therapies: Gene Editing and Next-Gen CAR T Cells

From Chris Thanos (Halozyme Inc, San Diego) and myself:

The New Frontier of Antibody Drug Conjugates: Targets, Biology, Chemistry, Payload

and a second topic covered by Chris Thanos (Halozyme):

Targeting the Physicochemical, Cellular, and Immunosuppressive Properties of the Tumor Microenvironment by Depletion of Hyaluronan to Treat Cancer

and finally, my solo chapter (and representing Aleta Biotherapeutics, Natick MA and SugarCone Biotech, Holliston MA):

Novel Immunomodulatory Pathways in the Immunoglobulin Superfamily

Please spread the word that all sales benefit cancer research and more specifically, cancer clinical trial development and execution through the Cancer research Institute, and as I said, consider buying the book, or the chapters you want to read.

cheers-

Paul

CAR T updates – tangled tales unwound

Last month we saw a biomedical media campaign go a bit off the rails. A press release from the American Association for the Advancement of Science (AAAS: see for example https://www.sciencenews.org/article/memory-cells-enhance-strategy-fighting-blood-cancers) and the Fred Hutchinson Cancer Center, was picked up by multiple media outlets who quickly spun the story of CAR-T-cell mediated rapid and complete clearance of B cell leukemias and some lymphomas from very ill patients and turned it into the “cancer cured” sort of headlines that serve as great click-bait but don’t do much to really educate the reader.

But what first caught my eye was an odd distortion of the data as presented in the session entitled “Fighting Cancer and Chronic Infections with T Cell Therapy: Promise and Progress” (see https://aaas.confex.com/aaas/2016/webprogram/Session12231.html). Several credible sources were telling very different stories about the progress presented. To take one example, BioWorld Today told the story of the clear benefit of using naive T cells as the recipient for cellular therapy, while FierceBiotech (and many other outlets) focused on the benefit of using memory T cells instead (see http://bit.ly/1UdLqDs). Indeed the claim was made that even a single memory T cell could affect a cure – which was not really the point, or an important conclusion of the presented works.

It follows that the pressers were used to talk up CAR T cell company stocks, which have been languishing along with the rest of biotech.

All of this came across as garbled and confusing. I found it all very frustrating.

So now I’ve gone through the abstracts presented at AAAS and some of the primary literature, and I’ve a Cliff Notes version of what data were actually presented and what the data mean and don’t mean. I seems clear that the confusion regarding the results arose from the oversimplified weaving of two talks (by Dirk Busch and by Steven Riddell) into one tangled “story”. Lets untangle the knot and follow the threads.

Riddell’s work is closely followed in the CAR T field – not surprising as Dr. Riddell, from the Fred Hutchinson Cancer Center in Seattle, is a technology leader and a cofounder of Juno Inc. The story presented at the AAAS symposium is interesting but perhaps more controversial than one might have gathered from the press reports. Some of the work was recently published (http://www.nature.com/leu/journal/v30/n2/full/leu2015247a.html). They start with the observation that in all reported CAR-19 clinical trials, patients have received back a random assortment of their (now CAR-transduced) T cells, meaning that the cell population is a collection of naive T cells, effector T cells and memory T cells representing both the CD4 and CD8 T cell lineages. This introduces a variable into therapy, as different patients are likely to have different percentages of these various T cell subsets. Indeed there is quite a list of variables that may impact the efficacy of CAR T cell treatment including baseline immune competence, prior treatments and antigen load. With this in mind Riddell and colleagues are trying to control the one variable that they can, which is the composition of the transduced T cells going into the patient. By analyzing CAR cell subsets for tumor cell killing function they arrive at the “most potent” combination of CD4+ T cells and CD8+ T cells and conclude that the findings will be important for the formulation of CAR T cells therapeutics for use in patients.

The data in the paper are derived from normal donor and cancer patient PBMC samples that are tested in vitro using cell culture assays and in vivo using humanized mice (NOD/SCID/yc-deficient mice; NSG) reconstituted with T cells and tumor target cells (Raji) that express CD19. The CAR T construct is a “generation 3″ CAR having CD28, 41BB and CD3 signaling domains downstream of the well-studied FMC63-derived anti-CD19 scFv.

Some results:

- substantial differences were seen in the T cell populations between normal donors and cancer patients, with most patients having a higher percentage of CD8+ than CD4+ T cells.

- patient samples also contained more memory T cells than did normal donor samples. A further refinement to the memory T cell definition allows one to identify effector memory and central memory T cells. The latter are a long-sustained population of antigen-educated T cells that contribute to immunological memory, such as one retains after a vaccination against a virus for example.

- both CD4+ and CD8+ T cells were readily transduced with the CAR-19 construct, and when presented with target cells in vitro both cell types responded. CD8 T cells mediated target cell lysis more effectively than CD4+ T cells, but the latter proliferated more vigorously and produced more pro-inflammatory cytokines such as IFNy and IL-2.

- among the CD4+ subset, naive T cells (those not previously antigen-activated) produced more cytokines than the memory cell subsets. In vivo, naive T cells were more potent in controlling tumor growth than central memory T cells which were in turn more potent than effector memory cells.

- similar analyses of CD8+ cells revealed that, of the three subsets, central memory CD8+ T cells were the most potent in vivo, a result that was most closely associated with the enhanced proliferation and expansion of this subset.

- the activity of CD8+ central memory T cells was further enhanced by the addition of CD4+ T cells, notably those of the naive subset. This effect was seen using cells from normal donors and cells from B cell lymphoma patients (specifically, Non-Hodgkin Lymphoma (NHL) patients). The improved in vivo activity was due to enhanced proliferation and expansion of T cells in the NSG mouse model, specifically an increase in the peak of CD8+ cell expansion, in line with clinical results (see below). I’ll note as a reminder that all of the available clinical results are from CAR T cell populations that had not been sorted into naive and memory subsets. Also, many researchers in the field believe that naive T cells (CD4 and CD8) have the best proliferative capacity and potency.

Regardless, the Riddell work suggests a straightforward improvement in the ability to create more potent CAR T cell preparations for use in the clinical setting. There are some caveats however. In the in vitro and in vivo models used, antigen (CD19) is abundant, even in the NSG mouse, due to robust expression of rapidly dividing CD19+ Raji cells. As noted earlier, antigen availability may be an important limiting feature for some patients, and may be more important than the composition of the T cell subset tested. Fortunately the relative importance of these variables could easily be examined in vivo by using sub-optimal Raji cell numbers, or using transfected cells with different levels of CD19 expression, to vary the antigen load.

The Busch study at the same symposium was notable for dispensing with CD4+ T cells altogether and using just CD8+ central memory T cells to control CMV infection (that can occur following allogeneic hematopoietic stem cell transplantation). Nearly all of this work has been performed in mouse models, with a small number of patients treated under compassionate use protocols (see e.g. http://www.bloodjournal.org/content/124/4/628). In the mouse models very small numbers of antigen-specific memory T cells can expand to control viral infection, and this has been taken as evidence (in the popular press mainly) that similar technology could be applied in the CAR T setting. However, numerous studies have shown conclusively that very large-scale expansion is required to achieve optimal potency, to a degree that would seem beyond the capacity of a small number of cells or a single cell. Further, studies in acute lymphocytic leukemia patients presented by Carl June last fall at the Inaugural International Immunotherapy meeting in NY showed that clonal selection and perhaps competition was a component of successful therapy for some patients, a process that would be eliminated or reduced by using a limited cell number in preparing the CAR T cells. The Busch study makes the further argument that central memory CD8+ T cells themselves possess “stem-ness”, that is, they can give rise to functionally diverse CD8+ T cell lineages and as such should have no limit to their proliferative capabilities. While this was demonstrated convincingly in mouse models it would seem a difficult finding to translate to the CAR T setting, although the work may find utility in the adoptive cell transfer setting (e.g. of selected but not transduced T cells, such as tumor infiltrating T cells).

The “stem-ness” concept reminded me of older literature that aimed to dissect the basis for long-lived CD8+ T cell memory in the context of viral immunity (see here for a recent review: http://journal.frontiersin.org/article/10.3389/fimmu.2012.00357/abstract). There were at one time two broad classes of thought – first, that such memory required a consistent supply of antigen, for example, a depot that periodically re-stimulated the antigen-specific T cell population. The second school of thought, more reminiscent of the Busch finding, was that memory CD8+ T cells were self-renewing, and therefore did not require life-long antigen stimulus. The “big bang” hypothesis of T cell memory development, a hypothesis that the work of Dr. Busch and colleagues has definitively supported (see: http://www.bloodjournal.org/content/124/4/476?sso-checked=true) holds that once stem-like T cell memory is created, these cells can be used just like stem cells, i.e. to reconstitute cellular function, in this case, the ability to control viral infection.

Let’s get back to CAR T cells. Recent work has demonstrated clearly that the establishment of persistence in cellular therapy requires a robust response to abundant antigen. Only then can CD8+ T cell memory develop and from that point on be maintained. This observation informs the next set of studies, presented at the Clinical Application of CAR T Cells conference (#CART16 – https://www.mskcc.org/event/car-t-cell) held at the Memorial Sloan Kettering Cancer Center, the Adoptive T-Cell Therapy Congress held in London (http://tcellcongress.com/resource-center/) and the Advanced Cell Therapy Symposium (https://www.immunology.org/document.doc?id=1807) held at Guy’s and St Thomas’ NHS Foundation Trust and King’s College, also in London. Much of the work presented highlighted at these meetings addressed attempts to move CAR T cells into solid tumors.

Here I am a little hamstrung, as I’m relying on information presented on slides (as shared on Twitter by @JacobPlieth @VikramKhanna and others). Let’s try to define some themes here regardless.

Jacob has reviewed some #CART16 data: http://epvantage.com/Universal/View.aspx?type=Story&id=627150&isEPVantage=yes. Please see that link for his viewpoints.

First, to stick with CAR19 therapeutics, we have some posted Novartis data on responses in Non-Hodgkin Lymphoma (NHL). NHL is comprised of diverse B cell lymphomas, some of which are highly refractory to treatment. Examples of the refractory class include diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL) among others. Here we see some rather impressive results treating these lymphomas:

Screen Shot 2016-03-20 at 9.55.18 AM

The data are hard to read, but let’s pull out some numbers from the table. Note that essentially all patients got the optimal dose of 5 x 10e8 cells (1 exception) and that the peak cellularity is defined as %CD3+/CAR19+ cells in peripheral blood. We can therefore look at expansion, time to peak cellularity and outcome:

Screen Shot 2016-03-20 at 10.00.38 AM

There seems no correlation between day to peak and outcome, unless it is very short – day 1 or 2 – and even then that is likely due to abortive expansion. If we arbitrarily set 10% as an exploratory setting with which to parse the %CD3+/CAR19+ data we quickly see that above 10% (black line), half of the patients responded, which below 10% only a third of patients responded.  So expansion is important, as we already knew. With respect to the earlier discussion, we do not know the critical variable at work here, be it CAR T cell persistence (likely), CAR T cellular composition (per Riddell), patient variability, antigen density, or something else.

The FL data are a little bit more confusing:

Screen Shot 2016-03-20 at 10.05.07 AM

Again we can pull out some of the data:

Screen Shot 2016-03-20 at 10.07.43 AM

And now we are really hard-pressed to see any correlation between outcome and peak cellularity, no matter where we might draw the arbitrary line for analysis. What data is missing? I suspect it is a measure CAR T cell persistence over time, as this is most often associated with positive response. We should note that CD19 is an unusual target antigen in that it is expressed on the cancer cells (B cell leukemia or lymphoma) and on normal B cells that we can deplete without undue harm to the patient.

Other B cell antigen targets are under development as CARs, including CD22 and BCMA. BCMA is expressed on plasma cells (relatively uncommon B cells that secrete antibodies) and on essentially all multiple myeloma cells. Early promising results generated using a BCMA CAR to treat multiple myeloma were presented at ASH (http://www.ascopost.com/issues/march-10-2016/car-t-cell-therapy-may-have-role-in-treating-multiple-myeloma/).

Screen Shot 2016-03-20 at 9.39.58 AM

Updated results are a little less encouraging as the complete response patient (#10) has since relapsed as was reported at #CART16. It is unclear if advanced multiple myeloma is simply more refractory to CAR treatment, if the lower cell number infused led to poor persistence, if the CAR were different, or if antigen load was too low. Thus we are again faced with multiple variables to assess.

So now we can ask what happens when there is little or no persistence, which is the case with most CARs directed to solid tumors. This is data from Nabil Ahmed and Stephen Gottschalk from Baylor College of Medicine. This group is collaborating with Celgene on cellular therapeutics. Here we see the results of treatment of HER2+ advanced solid tumors with CAR-HER2 T cells. The response is minimal.

Screen Shot 2016-03-20 at 10.12.07 AM

This is very likely due to the very short persistence of the CAR-HER2 T cells, in most cases gone in a week or so.

Screen Shot 2016-03-20 at 10.12.27 AM

Interestingly, analysis of resected or biopsied tumor after treatment revealed that the CAR T cells had migrated preferentially into the tumor, but had not proliferated extensively. Novartis presented nearly identical data on an EGFRvIII targeting CAR T cell study at the Boston PBSS Immuno-Oncology Workshop (http://www.pbss.org/aspx/homeBoston.aspx), and similar data has been presented on a host of solid tumor targets.

To return briefly to CD19+ tumors, it was reported recently that the response to CAR19 therapy in chronic lymphocytic leukemia was about 25%, but that all of those responders were durable complete responders (i.e. potential cures). Why the seemingly digital nature of response here? Again this is most likely due to CAR T cell persistence which itself is most likely a reflection of antigen load (among other variables). With this in mind I was struck by a slide from Seattles Childrens Hospital (I’m not sure from which meeting):

Screen Shot 2016-03-20 at 10.17.40 AM

In point #3 the presenter is basically suggesting injecting an artificial antigen presenting cell expressing CD19, i.e. increasing the antigen load.

We can conclude by saying that there is a fundamental issue with CAR T cell antigens – those that are tumor specific are either not abundantly expressed and/or have been removed during the course of therapy. This is an issue that may not be solved by adding 4-1BB or IL-12 or anti-PD-1 antibody or whatever other immunological “help” one might envision. This issue impacts the entire field, which is why we now see analysts who once talked of the emergence of dominant CAR T platform companies now wondering who will win the CAR19 race to the finish line. That is still a noble race to run, but the patient numbers cannot justify the number of companies competing for the prize. Yet change will come and progress will be made…

What to do?

stay tuned.

ps. thanks again @JacobPlieth @VikramKhanna and others for kindly sharing slides (and getting great seats at conferences!)

thoughts on attending the Immuno-oncology Biopartnering conference in NYC

Thought bubbles on the way back from the Sach’s IO Biopartnering meeting, a very interesting event:

(http://www.sachsforum.com/4th-annual-cancer-biopartnering–investment-forum-24th-february-2016-new-york-academy-of-sciences.html)

-  The Sach’s Conferences are small, focused and diverse. Sach’s is much better known in Europe than in the US, and the NYC location brings European firms and companies into the fold. Therefore you meet interesting people you might otherwise never come across.

Investors:

-  When in provincial Cambridge Massachusetts, i.e. the village of Kendall Square and environs, we visualize investors as the VCs that are in the square, across the river in Boston, or out in Waltham. With more experience one might add investment and hedge funds and the associated bankers of greater Boston. What you find in NY is an entirely new investment ecosystem, one that is very active and a good crowd to know. fyi, you won’t find these guys at Area 4 or Voltage.

-  It follows that similar ecosystems exist on the west coast, in Europe (France stands out), England’s golden triangle (London >>> Cambridge >>> Oxford), and in diverse far flung locales (Tel Aviv, Singapore, Hong Kong to name just a few). While many firms have preferred investment geographies, all of them are aggressively spreading their money further afield. It is well worth getting to know as many investors as possible, worldwide.

Science and deals:

-  The conference cliche was “good science wins”. This sounds trite but contains an essential kernel of truth applicable to the suddenly challenging financial landscape. We should remember that, since 2014, VCs and other investors raised massive funding rounds. This money will need to be invested during each fund’s life cycle (these average about 5 years). Equally large hordes of cash are sitting inside of large biopharma and on the balance sheets of newly IPO’d companies. The upshot of all this is that “good science” has a good chance of attracting financing.

-  A second theme, less of a cliche and more of a hope, was that M&A activity will surge in 2016 due to the suddenly more affordable valuations of small and midsize biotech.  In this scenario the biggest biopharmas will get bigger by buying up a bunch of smaller companies – but do we believe they will all buy “good science”? Investors may harbor a doubt about this, but we’ll see.

Good science:

-  So what is “good science”: I’d argue that in the IO space good science in small biotechs has one or more of the following qualities:

  • Novel IO assets, IO combinations and bispecific antibodies that will synergize with existing checkpoint inhibitors.
  • Next generation vaccines, oncolytics, small molecule inhibitors that have tumor cell cytotoxic activity and/or immune activating activity. This is a broad class with assets of diverse MOA and quality, but winners will emerge here.
  • CAR-T and TCR 5.0 (or 6.0) – whatever that will be.
  • Personalized medicine solutions that guide treatment choices.

What can we observe now? Can we recognize “good science”?

Lets dial back a week or so to the response to three talks given in the cellular therapy session at the recent AAAS meeting:                           (https://aaas.confex.com/aaas/2016/webprogram/Session12231.html).

The three talks were widely (wildly in some cases) misrepresented, misinterpreted or both as documented in detail on social media  - see for example                 http://www.healthnewsreview.org/2016/02/aaas-stories-hype-immunotherapy-cancer-saliva-test/ …

and  http://scienceblog.cancerresearchuk.org/2016/02/16/immunotherapy-cancer-cure-headlines-distract-from-fascinating-science/ …

and  https://acspressroom.wordpress.com/2016/02/16/car-t/ …

Fortunately two of the three presentations are now represented by publications. The papers are in advanced publication at Leukemia (paper-1) and Nature Biotechnology (paper-2). I’ll review these papers and comment on how these data reflect back on the public perceptions of the AAAS presentations, and how they fit into other recent findings in the field, in the next post.

stay tuned

comments are welcome

Enumeral update – guest post by Cokey Nguyen, VP, R&D

Paul’s introduction:  Enumeral has been sending ’round some interesting updates to several of their programs and I asked for some more detail. Below is a quick primer sent along by Cokey Nguyen. More detail is available in Enumeral’s recent 8K filings, including one that dropped this morning. Also the company will present this and other work at the AACR Tumor Microenvironment Meeting in January (http://www.aacr.org/Meetings/Pages/MeetingDetail.aspx?EventItemID=73#.VlyGS7_QO2k - see below).

New data from Enumeral, by Cokey Nguyen

PD-1 biology in human lung cancer is an active area of research, as these cancers have shown PD-1 blockade responsiveness in clinical trials.  Enumeral has a drug discovery effort aimed at generating novel anti-PD-1 antibodies to develop into potential therapeutic candidates.  Using a proprietary antibody discovery platform, two classes of PD-1 antagonist antibodies were discovered:  the canonical anti-PD-1 antibody which blocks PD-L1/PD-1 interactions and a second class of antibody which is non-competitive with PD-L1 binding to PD-1.  These antibodies were validated first in a pre-clinical model of NSCLC using NSG mice with a humanized immune system and a patient derived NSCLC xenograft (huNSG/PDX) (Figure 1).  Here either class of antibody demonstrated activity on par with pembrolizumab, confirming that PD-1 blockade can slow tumor growth.

Figure 1

Figure 1

In order to confirm these pre-clinical findings, Enumeral began proof of concept studies with NSCLC samples.  The first question was if resident TILs, as found in tumors, could be reinvigorated (Paukken and Wherry, 2015) or if PD-1 blockade is mainly a phenomenon that affects lymph node-specific T cells that have yet to traffic to the tumor.  In these studies, Enumeral found PD-1 blockade can, in fact, increase effector T cell function, as readout by IFNg, IL-12, TNFa and IL-6.  In addition, in a NSCLC sample that showed PD-1hi/TIM-3lo expression, PD-1 blockade strongly upregulated TIM-3 expression (~5% to ~30%, see Figure 2).

Figure 2

Screen Shot 2015-12-01 at 6.07.24 AM

In these NSCLC-based studies, it was also found that an anti-PD-1 antibody (C8) which does not bind to PD-1 in the same manner as nivolumab or pembrolizumab (PD-L1 binding site) displays differentiated biology:  increased IFNg production and significantly higher levels of IL-12 in these bulk (dissociated) tumor cultures (Figure 3).  As IL-12 is thought to be a myeloid derived cytokine, this mechanism of action is not yet well understood, but has been now observed in multiple NSCLC samples as well as in MLR assays.

Figure 3

Screen Shot 2015-12-01 at 6.08.35 AM

In these NSCLC studies, while a subset of patient samples demonstrates PD-1 blockade responsiveness, the co-expression of TIM-3 on NSCLC TILs suggests this is a validated path forward to increase the response rate in lung cancer.  As with the PD-1 program, armed with a substantial portfolio of diverse anti-TIM-3 binders, Enumeral is actively testing single and dual checkpoint blockade on primary human lung cancer samples.

Look for the companies 2 posters at AACR/TME in January

Screen Shot 2015-12-01 at 6.11.08 AM