Category Archives: Pathways for Drug Development

Fidgeting about TIGIT

Part 1 of 2

Pathways and targets covered: TGF-beta, PD-L1, PD-1, TIGIT

Companies mentioned: Merck KgaA, GSK, Roche, Merck, Mereo, iTeos, BMS, Arcus/Gilead, Compugen, Seagen, Beigene, Innovent, Agenus

Last week we had the bad news that Merck KGaA and GSK had thrown in the towel on bintrafusp alfa therapy for first-line advanced NSCLC.  Bintrafusp alfa is an anti-PD-L1/TGFbR2 TRAP therapeutic designed to selectively antagonize TGF-beta isoforms 1 and 3 while also blocking PD-L1, thereby delivering two-for-one anti-immunosuppression.  Bintrafusp alfa was being tested in a head-to-head trial vs. pembrolizumab and showed no added benefit in a patient population selected for PD-L1-high tumor expression (50%+ of cells in the tumor biopsy sample positive for expression).

This stirred up a fair amount of discussion, as TGF-beta blocking therapies are in vogue for immuno-oncology (IO), with small molecules, biologics, RNA-antagonists and genetic knockouts (in CAR T cells) all in the pipeline. I have high hopes for this space, despite the news out of Darmstadt. And to be fair, the press release stressed the ongoing bintrafusp alfa trials in bladder cancer, cervical cancer, and NSCLC using various drug combinations, and noted new trials in urothelial cancer and TNBC (  Still, the failure stung, due mainly to the promise of the early (open label) Phase 1 expansion cohort data that had suggested significant benefit from the therapy.

This got me thinking about TIGIT, another hot IO target.  The last time I wrote about TIGIT I ended with this question: “How to select patients who should respond to anti-TIGIT co-therapy (or anti-TIM-3 or anti-LAG-3)…?” ( This is a question we should ask about any pathway – including TGF-beta of course – particularly as we are now in the post-immune-checkpoint era, that is, in a setting where many patients in the most IO-responsive indications like melanoma and NSCLC will have already been treated with an anti-PD-1 or anti-PD-L1.  So, is there anything known about TIGIT expression that can guide us in patient (or indication) selection?

Roche leads the field with tiragolumab an anti-TIGIT Fc-competent IgG1 that has shown activity in combination with the anti-PD-L1 antibody atezolizumab in first-line NSCLC, and only in patients with PD-L1- expressing tumors (> 1% of cells in the tumor biopsy sample positive for expression).  We can pause here to recall that this is about where we started the discussion above regarding the TGF-beta TRAP/anti-PD-L1 asset from Merck KGaA, being trialed in the PD-L1-high (>50%) setting in NSCLC.

In front-line NSCLC (EGFR and ALK wildtype), Roche reported responses higher than with atezolizumab alone. Data were shown at AACR and then updated at ASCO.  Here are some of the ASCO data:


The response rate with dual therapy looks rather better than atezo alone, especially in the PD-L1 high cohort (middle panel).  Atezo alone appears to have underperformed, with an ORR = 21% (left panel, all patient data (ITT)).  In the comparable phase 3 trial of atezo vs chemotherapy in front-line NSCLC (also EGFR and ALK wildtype) the ORR = 38.3% in the atezo arm (n=285) and 28.6% in the chemotherapy arm (n=287), see Regardless the 66% response rate in the PD-L1-high cohort (middle panel) attracted attention.

The PFS data were also striking when compared to the prior trial.  This is tiragolumab plus atezolizumab / PD-L1 high cohort:


We can go back and compare this to the atezo alone Phase 3 interim data shown at ESMO in 2019 (I was stuck in the overflow “room” which was a curtained space on the floor of the Barcelona convention center).  This is the PD-L1-high cohort:


Here the median PFS is 8 months, certainly shorter than what is shown for tiragolumab plus atezolizumab, but again, note the disparity with the atezo alone arm of the study (medPFS for = 4 months).

Just to be clear, here are the PD-L1-high patient data compared:


We’re left with the always troubling question of variability between trials and the possibility that the tiragolumab plus atezolizumab results are a fluke.  Unfortunately, we will have to wait and see.

There are two features here worth noting.  One is that TIGIT, the target, is expressed on T cells, along with PD-1.  So far this makes sense – they might very well synergize, particularly given the function of DNAM-1 in the context of T cell signaling (see part 2).  But the anti-TIGIT antibody is an IgG1 isotype, thought to trigger ADCC and CDC-mediated target cell (ie. the T cell) death.  But we want the T cells, that’s the whole point of blocking PD-L1 with atezo.  So what the heck is going on here?

Merck seems to have an answer, but first, some more data.  Merck’s anti-TIGIT antibody, vibostolimab, like Roche’s tiragolumab, is a wildtype IgG1.  Early data on the combination of vibostolimab and pembrolizumab (anti-PD-1), presented at ESMO2020, looked promising in immune checkpoint naïve patients (75% had prior chemotherapy, the rest were treatment naïve):



We can benchmark these results to monotherapy, just as we did with the Roche data, focusing on the PD-L1-positive subset (here we can see data using a cutoff of >1% or >50% of cells positive in the tumor biopsy):



The results compare favorably with pembro-alone using the >1% PD-L1 cutoff and are similar to pembro-alone using the >50% PD-L1 cutoff.  As usual it is difficult to compare between trials, but the signal is encouraging.

Preclinically, Merck has addressed the MOA, stressing the requirement for the intact Fc functionality imparted by the IgG1 antibody isotype.  As mentioned earlier, the mechanistic puzzle is that canonical IgG1 activity includes the triggering of target cell killing via ADCC and CDC mediated cytotoxicity.  Of course, TIGIT is expressed on the very T cells we want to preserve and activate, not kill.  Given this reality we need alternate hypotheses for the action of the IgG1 antibodies.  The predominant hypothesis is that anti-TIGIT antibodies are selectively depleting T-regulatory cells that are TIGIT-bright and immunosuppressive.  This is reminiscent of the now-T-regulatory cells that are TIGIT-bright and immunosuppressive.  It’s an easy hypothesis to advance, similar to the now-debunked arguments made on behalf of anti-CTLA4 and anti-GITR antibodies, and very likely incorrect.

Merck has demonstrated in preclinical models that antagonistic anti-TIGIT antibodies having a  FcgR-engaging isotype induce strong anti-tumor efficacy whereas anti-tumor activity is drastically reduced when using the same anti-TIGIT antibodies that are null for FcgR-engagement (doi: 10.3389/fimmu.2020.573405). These results are consistent with data presented by multiple groups, eg. Mereo and iTeos.  The Merck team further showed shown that FcgR engagement persistently activated myeloid lineage antigen-representing cells APCs, including the induction of proinflammatory cytokines and chemokines while TIGIT blockade simultaneously enhanced T cell activation including elevated secretion of granzyme B and perforin, which synergizes with anti-PD-1 antagonism.  I favor this hypothesis.  Nb. This suggests we’ve a lot to learn still about the best way to engage Fcg receptors, a theme I introduced in the last post (link).

Where does this hypothesis leave everyone else in the TIGIT space?  Let’s line them up:


A few quick notes: EMD Serono/Merck KGaA and Innovent have anti-TIGIT programs without disclosed isotype information; Arcus has disclosed a second, Fc-competent, anti-TIGIT program (AB308); Agenus is developing both IgG1 and IgG4 anti-TIGIT antibodies.

A question: is Seagen’s hyper-killing IgG1 a step too far?

In summary, we have preliminary data in NSCLC that suggest that anti-TIGIT may synergize with anti-PD-1 or anti-PD-L1 therapies, consistent with the expression of TIGIT on PD-1 positive (ie. activated) T cells.  We have several hypotheses addressing the Fc-end of the therapeutics, and some information on why blocking TIGIT may enhance T cell responses.

Other than selecting patients with PD-L1-positive tumors, can we gate on TIGIT expression?  Apparently not, at least not in NSCLC, as just reported at the World Conference on Lung Cancer (abstract P77.02 – Efficacy of Tiragolumab + Atezolizumab in PD-L1 IHC and TIGIT Subgroups in the Phase II CITYSCAPE Study in First-Line NSCLC).

Here’s their text:

“Among the 135 enrolled patients with PD-L1-positive NSCLC (intent-to-treat [ITT] population), 113 had results from the SP263 assay and 105 had results from the TIGIT assay. The biomarker-evaluable populations (BEP) for both of these assays were similar to the ITT population. Comparable PFS improvement with tira + atezo relative to atezo monotherapy was seen in PD-L1–high (≥50% TC) subgroups defined by SP263 (PFS HR 0.23, 95% CI: 0.10–0.53) when compared with PD-L1-high subgroups defined by 22C3. However, for patients whose tumors were defined as TIGIT-high (≥5% IC), no strong association with PFS improvement was observed.

Biomarker subgroup Subgroup, n (BEP, N) PFS HR (CI) relative to atezo monotherapy arm
ITT (PD-L1 IHC 22C3 >1% TPS) 135 (135) 0.58 (0.39–0.88)
PD-L1 IHC 22C3 (≥50% TPS) 58 (135) 0.30* (0.15–0.61)
PD-L1 IHC SP263 (≥50% TC) 45 (113) 0.23* (0.10–0.53)
TIGIT IHC (≥5% IC) 49 (105) 0.62* (0.30–1.32)
*Unstratified HR

Prevalence of PD-L1 subgroups in the BEP was comparable with previous reports for both IHC assays. The PFS benefit observed with tira + atezo in patients with tumors defined as PD-L1-high by 22C3 was also observed using the SP263 IHC assay, but not in tumors classified as TIGIT-high using an exploratory TIGIT IHC assay. Our results suggest that PD-L1 expression, assessed by 22C3 or SP263, may be a biomarker for tira + atezo combination therapy in metastatic PD-L1-positive untreated NSCLC.”

So that the answer to the question we started with, can we pick patients, is ‘no’ for TIGIT expression, at least in this indication.

Regardless, to actually understand what blocking TIGIT does, we need to better understand the pathway.

That will be discussed in Part 2, coming soon.

Stay tuned.

A few things I Iearned in 2020: an immune-oncology perspective

Teaching immune cells how to kill, and other things I learned in 2020

Therapeutics and targets mentioned: 4-1BB, Bispecific-engagers, CAR-T, CD39/CD73/A2AR, CD47, FcαRI, FcγRIIa, Flt3L, GM-CSF, IL-2, Immune Checkpoints, LILBR2/ILT-4, OX40, PD-1, Siglec10/CD24, STING, TIGIT/DNAM-1, TIL, TLR7/8  & 9.

Companies mentioned: Agenus, Aleta Biotherapeutics, Alkermes, Alligator, Apexigen, AstraZeneca, Celldex, GSK, IgM Biosciences, I-Mab, Immune-Onc, Iovance, Jounce, Merck, Nektar, Seagen, Roche.

Two talks given at SITC 2019 session set me thinking about the quality of immune cell interactions, the outcomes for the interacting cells and the implications for cancer immunotherapy. These talks, by Ron Germain and Michael Dustin, presented the lives of immune cells in a series of diverse locations with a complex cast of characters.  Learnings regarding immune geography and cell:cell contact are increasingly important as we consider how best to advance cell therapies for diverse hematologic malignancies and solid tumors (

These investigators work to understand the cell biology that supports a productive immune encounter, and this depends in part on location as much as it does on cell type. The bio-pharma field has focused on T cells as the major target cell type for cancer immunotherapy, but it is clear that B cells, myeloid cells, dendritic cells, NK cells and neutrophils can play unique and critical roles.  Immunology insights gained in 2020 will influence how we think about immune-checkpoint therapeutics, cell therapeutics and tumor resistance to therapy.  Historically, we can link these lessons back to two of the very earliest “applied” immune-therapeutics, the cytokines IL-2 and GM-CSF, that trigger distinct subsets of immune cells.

Part 1: Location, location, location.

In January 2020 four papers were published that described the correlation between the presence of tertiary lymphoid organs and B cells with successful immune checkpoint therapy in diverse cancer indications (see here).  This was an interesting finding and one that I think remains under-appreciated by the immuno-oncology drug development field.

These papers raised an interesting question – why are tertiary lymphoid structures (TLS) and by extension, secondary lymphoid organs such as lymph nodes, spleen, and Peyers patches, important for successful immune checkpoint blockade therapy (ICB)?  Aren’t we just waking up exhausted T cells, or moving T cells from the tumor margin into the tumor bed?  Isn’t that how anti-PD-1/anti-PD-L1 antibodies work?  Why should you need a TLS or lymph node?

These questions compel us to once again deconstruct the tumor and its surroundings.  One might start with the immediate tumor microenvironment (TME) under direct control by tumor cells, stroma and stroma-embedded fibroblasts and myeloid cells.  A second view might consider the vascularized tumor bed, with access to blood vessels and lymphatics.  A third view: the invasive tumor margin, where tumor cells are invading normal tissue.  A fourth: sites within the tumor where immune cells are present, either active or immobilized.  Fifth: associated lymphoid tissues and organs.  And so on, although it won’t help to make things too complicated.  Not by coincidence the list overlaps with the phases of the tumor-immunity cycle (Chen & Mellman, 2013).

 As to why you need a TLS or lymph node, the answer probably lies in the quality of the T cell pool.  As we learned from the work of many labs (reviewed here: T cell exhaustion is a complex state, with subsets of cells having distinct functionality and fates.  Indeed, ‘exhaustion’ may be too broad a term.  For example, we know from Stephen Rosenberg’s work that TILs can be isolated from bulk tumor tissue, expanded using IL-2, and thereby “re-animated” ex vivo. Therefore, TILs are not always terminally exhausted.  Iovance has successfully exploited these findings and shown efficacy in late-stage clinical trials using patient-derived TILs to treat melanoma and cervical cancer.

These efforts can be traced back to the approval of high dose IL-2 for the treatment of renal cell carcinoma in 1992 and metastatic melanoma in 1998.  That 1992 date is notable, as IL-2 was discovered only 16 years earlier in Dr Robert Gallo’s lab (link).  Those approvals also are the basis of extensive efforts to produce less toxic variants of IL-2 by engineering selective IL-2 receptor engagement, as exemplified by the drug development work of Nektar, Alkermes, Roche and many others.  IL-2 is also used in the expansion of NK cells, indicating the pleiotropic activities of this cytokine.

Of note, TILs expanded in the presence of IL-2 can exhibit a differentiated phenotype that can shorten their long-term persistence and survival in vivo.  Recent analyses of successful TIL therapy have stressed the importance of a “stem-like” T cell population that has both proliferative and self-renewal capacity and fosters the development of long-lived memory T cells (Rosenberg lab: here).  I note in passing that their analyses suggest that strategies aimed at the CD39/CD73/A2AR pathway may have limited clinical impact.  A similar population of T cells has been associated with successful ICB therapy (discussed: link) and may play a role in productive CAR-T cell expansion.

A specific type of dendritic cell (DC) has been identified as a critical component of ICB therapy and this brings us back to lymph nodes and to TLS.  The cDC1 dendritic cell subset is implicated in the support of T cell mediated anti-tumor immunity (discussed by Gajewski & Cron here).  These are interesting cells that can be found in lymphoid organs, in inflamed tissues and within tumors.  Tumor antigens can make their way into lymphoid tissues by direct antigen drainage (review) with specific regions within lymph nodes supporting distinct DC populations and supporting distinct T cell responses (it turns out that B cells help with this spatial organization).  Tumor antigens can also be carried from the tumor into the lymph nodes by cDC1 themselves (link).  So now we have a narrative that accounts for the benefit of having lymphoid tissue in the context of anti-PD-1/PD-L1 therapy – this organized lymphoid tissue amplifies any existing anti-tumor response with a de novo response, sending additional T cell soldiers to the tumor front lines.

There are additional puzzles hidden within this narrative.  Possibly the one that bothers me the most is seeming failure of therapies that target T cell agonist pathways – notably 4-1BB and OX40 – to improve the response unleashed by ICB therapy.  Without burrowing deep into an immunology rabbit hole, I propose that anti-4-1BB and anti-OX40 agonist antibodies fail because they amplify signals in the wrong place or at the wrong time.  The immune system is tightly regulated and unkind to inappropriate signals.  Along these lines it is worth noting that completely blocking PD-1 will also backfire, as has been shown in disparate experimental systems (example).  This is translationally important, as PD-1-knockout CAR-T cells were eliminated in patients, either by active elimination or due to competitive disadvantage (paper, and presentation by Carl June, ASGCT 2020).  In contrast, signals that activate the DC compartment – GM-CSF, Flt3L and agonists that target CD40 (see Roche, Apexigen, Alligator, Seagen, Celldex and others) – do appear to augment anti-tumor immunity, and this may be the ideal way to think about boosting ICB therapies and perhaps CAR T cell therapies (hint).  A historical note: GM-CSF expression is a critical component of the T-VEC oncolytic viral therapy approved in 2015, just about 20 years after the first amino acid sequence data became available from the labs of Metcalf, Burgess, Dunn and colleagues during 1984-5 (here is a history by Glenn Dranoff).

Part 2: Knocking on other doors.

If location is critical, perhaps it’s time to move back to the TME.  I’ve thought for a long time that some TME-directed efforts are misguided.  I suspect several cell types commonly associated with the TME are epiphenomena that perhaps amplify, but do not create, the immunosuppressive microenvironment.  T-regulatory cells (T-regs) are one such cell type, and suppressive myeloid cells may be another.  The immuno-oncology drug development field has, to date, fallen short in attempts to deplete or alter these cell types for clinical benefit.

This should be surprising since T-regs and myeloid suppressor cells are abundant in TMEs across indications, but I would argue that tumor cells themselves and associated cell types in the tumor stroma, notably fibroblasts, are dominant.  ICB resistance signatures include VEGF, beta-catenin and TGF-beta – these factors appear to create the immunosuppressive milieu and subvert incoming immune cells.  Depleting T-regs or attempting to convert immunosuppressive myeloid cells (eg. ‘M2s’) to pro-inflammatory myeloid cells (eg. ‘M1s’) does not address the underlying immunosuppressive TME, which has arisen as a result of selective pressure on the tumor cell population.  I’ve discussed ICB resistance previously (see here and here).

However, the immunosuppressive TME and its attendant cell types can be upended, most notably by triggering evolutionarily ancient pathways that trump the immunosuppressive signals.  Many of these pathways are well known – the TLR7/8 and TLR9 agonists, the STING agonists, and the CD47 pathway inhibitors being prosecuted by many companies (see eg. AstraZeneca’s MEDI9197, a TLR7/8 agonist, Glaxo’s GSK3745417 STING agonist, I-Mab’s CD47 program, among many others).  Of note, localization of agonist signaling is critical in this space as well.  For example, TLR signaling is generally targeted at tumor cells directly, whereas it is debated whether STING agonists should target myeloid-lineage cells within the TME, tumor cells themselves, or both.

I particularly like the idea of engineering CD47 antagonism into other modalities, eg. T cell engagers.  Indeed, blocking CD47 to induce myeloid cell phagocytic activity is an active field, and this has encouraged a search for similar signals, for example, the Siglec10/CD24 pathway.  Moving even further afield we encounter quite novel myeloid cell signals and can consider pathways that are not as widely targeted.  One is the ILT (aka LILBR) system, where most activity is centered on antibodies to ILT2 and ILT4.  Here we begin to intersect with multiple cell types, as ILT2 is expressed by monocytes, macrophages, DC, B cells, and subsets of T cells and NK cells, and ILT4 is expressed by neutrophils, myeloid cells and DCs. These proteins have inhibitory signaling domains that are triggered by MHC binding, including to the HLA-G protein, normally expressed on myeloid lineage antigen-presenting cells (macrophages, DCs) where expression serves to immune-suppress interacting cells.  HLA-G is also overexpressed on many tumor cell types.  Thus, the ILT/HLA-G system appears to be another immune checkpoint, perhaps with a broader range of activity than the PD-1 system.  Merck has shown early positive clinical data using an antagonist anti-ILT4 antibody, MK-4830 (from Agenus), in combination with pembrolizumab (anti-PD-1) in heavily pretreated cancer patients (presented at ESMO 2020).  Jounce Therapeutics and Immune-Onc showed preclinical data at SITC 2020 on their anti-LILBR2 (ILT-4) programs, and there are additional efforts underway.  I suspect this field will grow quickly, and perhaps match the TIGIT/DNAM-1 space in interest and complexity.

Part 3. Fc-hacking immune responses.

As mentioned above, the immune system has strict rules and regulations, and can be resistant to having these over-ridden by therapeutics.  Hacks are possible of course, as shown by the success of CAR-T cells and the T-cell engager bispecifics.  Along these lines, decades of work on the Fc-domains of antibodies has allowed fine tuning of biologic therapies.  We are all familiar with optimization of ADCC and CDC activity (up or down), but more recent advances are less widely known.  I want to explore two examples – one will bring us back to LN and cDC1 activation, the other will advance the discussion on myeloid cell activation and will introduce the interaction of myeloid cells and neutrophils as a novel component of the anti-cancer immune response.

Jeffrey Ravitch’s lab recently published a method for Fc engineering of IgG antibodies for selective high-affinity binding to the activating Fcγ receptor FcγRIIa (paper).  In a viral respiratory model (in mice having human FcγRs) this Fc-hack resulted in an enhanced ability to prevent or treat lethal viral respiratory infection, with increased maturation of dendritic cells and the induction of anti-viral CD8+ T cell responses. Specifically, they noted up-regulation of CD40 expression in the cDC1 subset—the dendritic cell population specialized for cross-presentation and CD8 T cell stimulation in the lung virus model, and the very same DC subset we discussed earlier in the context of TLS and LN-mediated anti-tumor responses.  Just to close the circle, Fumito Ito and colleagues used irradiation, Flt3L, TLR and CD40 stimulation to demonstrate cDC1 induction of stem-cell line CD8+ T cells in a variety of murine tumor models (linked here).  It follows that engineering antibodies with the selectivity demonstrated in the Ravetch paper will find utility in the anti-tumor field.

I started off by referencing presentations from Ron Germain and Michael Dustin at SITC 2019, over a year ago.  Dr Germain presented a story that really struck a chord for me (see Uderhardt et al. 2019).  In tissue injury and pathogen infection models, neutrophils comprise the first line of defense, as innate immune signals cause them to swarm at the affected site. Early infiltrating neutrophils undergo activation induced cell death, which can drastically amplify the response and potentially cause tissue damage. In order to terminate this potent immune response tissue-resident macrophages rapidly sense neutrophil activity and cell death and extend membrane processes to limit the damage.  This ‘‘cloaking’’ mechanism thus limits neutrophil activation.  Of note, neutrophils can be abundant in tumors where they have been linked to diverse activities ranging from potent anti-tumor immunity to immune-suppression.  Neutrophils, like myeloid cells and NK cells, can be hacked using Fc-receptor engagement.  Neutrophils express FcγRIIA, just discussed in the context of cDC1 activation, and therefore it will be interesting to examine the activation of these (and other the FcγRIIA-expressing cells) in the context of IgG Fc-engineering.  Neutrophils and myeloid cells also express FcαRI, a very interesting receptor that when engaged by IgA-isotype antibodies triggers targeted cell killing.  Neutrophils will engage in phagocytosis, degranulation and reactive oxygen production to mediate killing after FcαRI engagement, while myeloid cells will be triggered to engulf targeted cells. The specific responses induced depend on the valency of IgA (monomeric, dimeric, aggregated) but it seems likely that the Fc-domain can be hacked in order to optimize productive engagement.  With a recent spotlight shown on IgM as an Fc-engaging platform (see IgM Biosciences) we can anticipate accelerated drug development across all of these diverse Ig-classes.

To wrap up – as we move forward in the related disciplines of immuno-oncology and cell therapy, we should consider these principles:  optimizing T cell/DC interactions, localizing immune checkpoint therapy to lymphoid tissues, and engaging additional cells to bring the full power of the immune system to the anti-tumor battle.

Stay tuned.

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 ( 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:

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 ( always have an eye on immunosuppressive pathways – indeed, the immunotherapy and cell therapy fields cross-fertilize often and productively (see

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 ( 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 ( 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 (

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 ( 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 ( 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 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.

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 ( 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.

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 ( - 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

The Tumor Microenvironment “Big Tent” series continues (part 4)


The Tumor Microenvironment (TME) series to date is assembled here containing parts 1-3

I’m happy to point you to the most recent content, posted on Slideshare:

In this deck I review the challenges of the TME particularly with reference to Pancreatic and Ovarian cancers. A few targets are shown below.

Feedback most welcome.

Screen Shot 2015-08-27 at 7.20.21 AM


“Combination Cancer Immunotherapy and New Immunomodulatory Targets” published in Nature Reviews Drug Discovery

Part of the Article Series from Nature Reviews Drug Discovery, our paper hit the press today

Combination cancer immunotherapy and new immunomodulatory targets. Nature Reviews Drug Discovery 14, 561–584. 2015.  doi:10.1038/nrd4591

by Kathleen Mahoney, Paul Rennert, Gordon Freeman.

a prepublication version is available here: nrd4591 (1)

Brodalumab for Psoriasis – what a mess

Let’s agree that the headline “Suicide Stunner” – penned by John Carroll for FierceBiotech – can never auger anything but very bad news, and never more so then when it is used to describe clinical trial results. Released on the Friday before the long US holiday weekend, bookended to the announcement of positive news on it’s PSCK9 program, Amgen stated that it was walking away from an expensive co-development program with AstraZeneca, basically washing it’s hands of the anti-IL-17 receptor (IL-17R) antibody brodalumab because of suicidal tendencies and actual suicides that occurred in the Phase 3 psoriasis trials. Brodalumab is under development for the treatment of plaque psoriasis, psoriatic arthritis and axial spondyloarthritis. Amgen stated that they believed that the approval label for brodalumab would contain warning language regarding suicide risk, and this would limit the success of the drug. By using such language while pulling the plug Amgen has essentially put AstraZeneca in the position of having to prove to the FDA that there is no suicide risk.

Holy crap.

Note here that we are not talking about a psychiatric drug, where the risk of suicide might be the consequence of trying to re-align an aberrant central nervous system. Instead we are talking about a drug that targets autoimmune disorders by blocking the action of T cells. This is not a biology linked to psychiatric health, at least not as we understand it today (more on this later).

Backing up: in April 2012, AstraZeneca and Amgen announced a collaboration to jointly develop and commercialize five clinical-stage monoclonal antibodies from Amgen’s inflammation portfolio: AMG 139, AMG 157, AMG 181, AMG 557 and brodalumab (aka AMG 827). The drivers for the collaboration were Amgen’s biologics expertise, the strong respiratory, inflammation and asthma development expertise of MedImmune (AstraZeneca’s biologics division), AstraZeneca’s global commercial reach in respiratory and gastrointestinal diseases, and the shared resources of two experienced R&D organizations

Under the terms of the agreement, AstraZeneca paid Amgen a $50MM upfront payment and the companies shared development costs. The breakout was as follows: AstraZeneca was responsible for approximately 65 percent of costs for the 2012-2014 period, and the companies now split costs equally. Amgen was to book sales globally and retain a low single-digit royalty for brodalumab. Amgen retained a mid single-digit royalty for the rest of the portfolio with remaining profits to be shared equally between the partners.

It gets even more complicated. Amgen was to lead the development and commercialization of brodalumab (and AMG 557, see below). Amgen was to assume promotion responsibility for brodalumab in dermatology indications in North America, and in rheumatology in North America and Europe. AstraZeneca was to assume promotion responsibility in respiratory and dermatology indications ex-North America. AstraZeneca remains responsible for leading the development and commercialization of AMG 139, AMG 157 and AMG 181. We’ll touch on these other antibodies at the very end.

Back to brodalumab. On balance, Amgen was on the hook for the development and commercialization costs, direct, indirect and ongoing, for dermatology indications in the US and also rheumatology, which in this case refers to psoriatic arthritis and axial spondyloarthritis. On the other hand, AstraZeneca was on the hook for commercialization in respiratory indications worldwide, and dermatology ex-US. This is interesting because brodalumab failed in its’ respiratory indication, moderate to severe asthma, and failed late, in a Phase 2b patient subset trial. So, on balance, much of the overall development cost seems to have shifted back onto Amgen over time (this is not to say that the companies would not have changed terms mid-term, they may have).

Two weeks ago I chaired a session on “Biologics for Autoimmune Disease” at the PEGS conference on Boston. In my opening remarks I used psoriasis as an example of an indication in which we were making clear and important progress, including with IL-17-directed therapeutics. Indeed, psoriasis is now a “crowded” indication commercially, with antibodies and receptor fusion proteins targeting the TNFs, IL-6, IL-12, IL-17, and IL-23 pathways all showing at least some activity. Notably, IL-17 and IL-23 targeting drugs appear to offer the greatest benefit in clearing psoriatic plaques. These pathways intersect in myriad ways, not all of which are well understood. This cartoon shows the effector cytokines and the receptors are expressed by diverse cell types, including dendritic cells, macrophages, T cells, and keratinocytes in the dermis.

IL-17 and friends

In simplistic terms, IL-6 triggers IL-12 and IL-23, and IL-23 triggers IL-17. As mentioned, the IL-17 and IL-23 targeting agents have great efficacy in psoriasis. Amgen and AstraZeneca were preparing an NDA (new drug application) for FDA submission based on results from three large Phase 3 studies. Here are the listed Phase 3 programs for brodalumab:

broda 1

I suppose those Phase 3 studies in psoriatic arthritis will now be tabled or transferred to AstraZeneca. For the sake of completeness here are the earlier studies:

broda 2

Certainly the clinical program was a robust one. So, what went wrong? Amgen R&D head Sean Harper summed up Amgen’s thinking about the suicide issue in the press release: “During our preparation process for regulatory submissions, we came to believe that labeling requirements likely would limit the appropriate patient population for brodalumab.”

The news aggregator and commentary website UpdatesPlus had this to add, questioning whether this result was “bad luck, bad target or victim of brodalumab’s efficacy: Despite high efficacy in Phase 3 studies, whispers of suicidality associated with brodalumab started to emerge at AAD.  At the time Amgen suggested this was related to disease however the company refused to comment on total rates and whether events were seen across arms … The question is whether Amgen is being hyper-cautious or whether the risk of suicidality is especially concerning.  Questions also emerge around the cause of risk – is this a spurious cluster of events unrelated to brodalumab; is suicidality perhaps related to relapse from the excellent efficacy associated with brodalumab after withdrawal (remember most patients exhibited at least PASI 90 on treatment but durability was very poor upon withdrawal); or perhaps suicidality is related to blocking the IL-17RA (note that suicidality has not to our knowledge been reported for the IL-17A ligand mAb Cosentyx) … One final point is whether regulators will now reevaluate suicide risk of IL-17 related molecules as a class – much greater clarity of brodalumab data is required to make a judgement.” That’s quite a nice summary from UpdatesPlus.

FierceBiotech’s report added “AstraZeneca would face some stiff competition if it decides to move forward solo on the drug. Novartis is already well in front with its IL-17 program for secukinumab, approved in January as Cosentyx. Eli Lilly has also been racking up positive late-stage studies for its IL-17-blocking ixekizumab, trailed by Merck’s MK-3222 and Johnson & Johnson’s IL-23 inhibitor guselkumab.”

Still, brodalumab demonstrated remarkable efficacy in psoriasis – Amgen and AstraZeneca went so for as to include a PASI100 score in one of their trials, meaning 100% clearance of psoriatic plaques, and the drug would have shown well against the best of breed, which today is likely Novartis’ anti-IL-17 antibody secukinumab. It is crowded space however, with antagonists targeting multiple nodes in the IL-17/IL-23 axis, alongside the biologics mentioned earlier.

Here is the current landscape from CiteLine (including brodalumab):


All in all, a tough crowd, and one that Amgen likely felt it could not face with a compromised label.

Let’s go back to the question posed above: bad luck, bad target or victim of superior efficacy? “Bad luck” suggests a statistical fluke in the data, potentially caused by the generally higher rates of suicidal tendencies observed in the moderate to severe psoriasis patient population. “Victim of superior efficacy” is in a sense a related issue, since the suggestion is that the loss of responsiveness to the drug, or a relapse, triggers a suicidal response as plaques return. Neither of these statements is really formulated as a hypothesis, and it doesn’t matter, as we don’t have the actual trial data yet with which to perform hypothesis testing.

“Bad target” is the most worrisome suggestion, and this can be formulated as a hypothesis, formally, the null hypothesis is that targeting the IL-17 receptor does not cause suicidal tendencies. Unfortunately, we still can’t test the hypothesis, and it seems likely that having the actual data won’t really help, that is, the study is probably not powered to reject that particular null hypothesis. So, what do we know? A few things, as it turns out.

First is that a link between the immune system and the nervous system is well established, although much of the focus has been on the role of neuronal enervation on immune responses. But clinically at least, the picture is muddier than that. High dose IL-2 can cause neurotoxicity, even hallucinations, according to Dr. Kathleen Mahoney, an oncologist at Beth Israel Deaconess and the Dana Farber. But what is really interesting is what else happens: “Some IL-2 treated patients can have odd dreams, really crazy dreams, and they last for weeks after treatment, long past the time when IL-2 would still be present in the body”, Dr. Mahoney said. Interferon alpha therapy is associated with pathological (severe) fatigue and also depressive symptoms that develop after 4–8 weeks of treatment. Of note, preventive treatment with anti-depressants, in particular serotonin reuptake inhibition attenuates IFN-alpha-associated symptoms of depression, anxiety, and neurotoxicity. Some researchers have suggested (controversially) that anti-TNF antibodies can control depression. Such anecdotal clinical observations suggest that we really do not yet understand the immune system connection to CNS activity.

On the other hand, antagonism of cytokine activity, and particularly of the cytokines IL-6, IL-17 and IL-23, has not been associated with neurological symptoms. For example the anti-IL-6 receptor antibody tocilizumab has shown a positive impact in rheumatoid arthritis patients quality of life scoring, which includes fatigue, anxiety, depression and a number of other factors. More to the point, the anti-IL-17 antibody secukinumab, that targets the IL-17 ligand (rather than the receptor), has not shown a link to suicide.

Clearly more data are needed, and it would not be surprising if the FDA began a drug class review if the data in the brodalumab trials warrant. They could cast quite a wide net given the complexity of this pathway, which overlaps with IL-6, IL-12 and IL-23. This casts a pall over the dermatology and particularly the rheumatology landscape, which is really waiting for novel therapeutics to move them successfully into new and important indications such as lupus and Type-1 Diabetes. The IL-17/IL-23 axis was to be that next great hope, and with luck we will still see these drugs moving out of their core indications of psoriasis and inflammatory bowel disease into new indications.

One last thing.

Those other antibodies – where are they now? A quick scorecard:


It is readily seen that none of these are beyond early Phase 2, so it’s fair to say that the rest of the Amgen/AstraZeneca partnership has a long way to go. I, for one, wish the ongoing collaboration the very best of luck, particularly in the lupus indications, where we can really use some good news.

stay tuned.