Category Archives: PD-1

Fidgeting about TIGIT

January 30, 2021immuno-oncology, immunotherapy, PD-1, PD-L1, TGFbeta, TIGIT, UncategorizedPaul Rennert

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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 (https://www.emdgroup.com/en/news/bintrafusp-alfa-037-update-20-01-2021.html). 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)…?” (http://www.sugarconebiotech.com/?p=841). 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 nejm.org/doi/full/10.1056/NEJMoa1917346. 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

December 28, 2020Aleta Biotherapeutics, CAR T cells, immuno-oncology, immunology, immunotherapy, oncology, Pathways for Drug Development, PD-1Paul Rennert

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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 (www.aletabio.com).

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: https://doi.org/10.1038/s41577-019-0221-9) 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.

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

September 26, 2016immunotherapy, PD-1, PD-L1Paul Rennert

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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.

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

December 1, 2015Enumeral, immunotherapy, PD-1, pembrolizumab, TIM-3, tumor microenvironmentPaul Rennert

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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

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-1^hi/TIM-3^lo expression, PD-1 blockade strongly upregulated TIM-3 expression (~5% to ~30%, see Figure 2).

Figure 2

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

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

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

July 31, 20154-1BB, cancer, CD27, CTLA4, GITR, IDO, immunotherapy, ipilimumab, lirilumab, MEDI4736, monoclonal antibodies, MPDL3280A, News, nivolumab, oncology, OX40, PD-1, PD-L1, pembrolizumab, T regulatory cells, TAMs, TGFbeta, TIGIT, TIM-3, TNF receptors, tumor microenvironmentPaul Rennert

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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)

Some Adjacencies in Immuno-oncology

April 27, 20154-1BB, Aduro Biotech, Alligator Bioscience, Bellicum Pharmaceuticals, Biogen, BioNovion, Bristol Myers Squibb, cancer, CD27, CLDX, Coronado, CTLA4, Enumeral, Genentech, GITR, GITR Inc, HALO, Halozyme, immunology, immunotherapy, Innate Pharma, monoclonal antibodies, Novartis, oncology, OX40, PD-1, Pelican Therapeutics, Pfizer, Roche, Tekmira, TG Therapeutics, TNF receptors, tumor microenvironmentPaul Rennert

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Some thoughts to fill the space between AACR and ASCO (and the attendant frenzied biopharma/biotech IO deals).

Classical immune responses are composed of both innate and adaptive arms that coordinate to drive productive immunity, immunological expansion, persistence and resolution, and in some cases, immunological memory. The differences depend on the “quality” of the immune response, in the sense that the immunity is influenced by different cell types, cytokines, growth factors and other mediators, all of which utilize diverse intracellular signaling cascades to (usually) coordinate and control the immune response. Examples of dysregulated immune responses include autoimmunity, chronic inflammation, and ineffective immunity. The latter underlies the failure of the immune system to identify and destroy tumor cells.

Let’s look at an immune response as seen by an immunologist, in this case to a viral infection:

Of note are the wide variety of cell types involved, a requirement for MHC class I and II responses, the presence of antibodies, the potential role of the complement cascade, direct lysis by NK cells, and the potentially complex roles played by macrophages and other myeloid cells.

In the immune checkpoint field we have seen the impact of very specific signals on the ability of the T cell immune response to remain productive. Thus, the protein CTLA4 serves to blunt de novo responses to (in this case) tumor antigens, while the protein PD-1 serves to halt ongoing immune responses by restricting B cell expansion in the secondary lymphoid organs (spleen, lymph nodes and Peyer’s Patches) and by restricting T cell activity at the site of the immune response, thus, in the tumor itself. Approved and late stage drugs in the immune checkpoint space are those that target the CTLA4 and PD-1 pathways, as has been reviewed ad nauseum. Since CTLA4 and PD-1 block T cell-mediated immune responses at different stages it is not surprising that they have additive or synergistic activity when both are targeted. Immune checkpoint combinations have been extensively reviewed as well.

We’ll not review those subjects again today.

If we step back from those approved drugs and look at other pathways, it is helpful to look for hints that we can reset a productive immune response by reengaging the innate and adaptive immune systems, perhaps by targeting the diverse cell types and/or pathways alluded to above.

One source of productive intelligence comes from the immune checkpoint field itself, and its’ never-ending quest to uncover new pathways that control immune responses. Indeed, entire companies are built on the promise of yet to be appreciated signals that modify immunity: Compugen may be the best known of these. It is fair to say however that we remain unclear how best to use the portfolio of checkpoint modulators we already have in hand, so perhaps we can look for hints there to start.

New targets to sift through include the activating TNF receptor (TNFR) family proteins, notably 4-1BB, OX40, and GITR; also CD40, CD27, TNFRSF25, HVEM and others. As discussed in earlier posts this is a tricky field, and antibodies to these receptors have to be made just so, otherwise they will have the capacity to signal aberrantly either because the bind to the wrong epitope, or they mediate inappropriate Fc-receptor engagement (more on FcRs later). At Biogen we showed many years ago that “fiddling” with the properties of anti-TNFR antibodies can profoundly alter their activity, and using simplistic screens of “agonist” activity often led to drug development disaster. Other groups (Immunex, Amgen, Zymogenetics, etc) made very similar findings. Careful work is now being done in the labs of companies who have taken the time to learn such lessons, including Amgen and Roche/Genentech, but also BioNovion in Amsterdam (the step-child of Organon, the company the originally created pembrolizumab), Enumeral in Cambridge US, Pelican Therapeutics, and perhaps Celldex and GITR Inc (I’ve not studied their signaling data). Of note, GITR Inc has been quietly advancing it’s agonist anti-GITR antibody in Phase 1, having recently completed their 8th dose cohort without any signs of toxicity. Of course this won’t mean much unless they see efficacy, but that will come in the expansion cohort and in Phase 2 trials. GITR is a popular target, with a new program out of Wayne Marasco’s lab at the Dana Farber Cancer Institute licensed to Coronado and Tg Therapeutics. There are many more programs remaining in stealth for now.

More worrisome are some of the legacy antibodies that made it into the clinic at pharma companies, as the mechanisms of action of some of these agonist antibodies are perhaps less well understood. But lets for the sake of argument assume that a correctly made anti-TNFR agonist antibody panel is at hand, where would we start, and why? One obvious issue we confront is that the functions of many of these receptors overlap, while the kinetics of their expression may differ. So I’d start by creating a product profile, and work backward from there.

An ideal TNFR target would complement the immune checkpoint inhibitors, an anti-CTLA4 antibody or a PD-1 pathway antagonist, and also broaden the immune response, because, as stated above, the immune system has multiple arms and systems, and we want the most productive response to the tumor that we can generate. While cogent arguments can be made for all of the targets mentioned, at the moment 4-1BB stands as a clear frontrunner for our attention.

4-1BB is an activating receptor for not only T cells but also NK cells, and in this regard the target provides us with an opportunity to recruit NK cells to the immune response. Of note, it has been demonstrated by Ron Levy and Holbrook Khort at Stanford that engagement of activating Fc receptors on NK cells upregulates 4-1BB expression on those cells. This gives us a hint of how to productively combine antibody therapy with anti-4-1BB agonism. Stanford is already conducting such trials. Furthermore we can look to the adjacent field of CAR T therapeutics and find that CAR T constructs containing 4-1BB signaling motifs (that will engage the relevant signaling pathway) confer upon those CAR T cells persistence, longevity and T cell memory – that jewel in the crown of anti-tumor immunity that can promise a cure. 4-1BB-containing CAR T constructs developed at the University of Pennsylvania by Carl June and colleagues are the backbone of the Novartis CAR T platform. It is a stretch to claim that the artificial CAR T construct will predict similar activity for an appropriately engineered anti-4-1BB agonist antibody, but it is suggestive enough to give us some hope that we may see the innate immune system (via NK cells) and an adaptive memory immune response (via activated T cells) both engaged in controlling a tumor. Pfizer and Bristol Myers Squibb have the most advanced anti-4-1BB agonist antibody programs; we’ll see if these are indeed best-in-class therapeutics as other programs advance.

Agonism of OX40, GITR, CD27, TNFRSF25 and HVEM will also activate T cells, and some careful work has been done by Taylor Schreiber at Pelican to rank order the impact of these receptors of CD8+ T cell memory (the kind we want to attack tumors). In these studies TNFRSF25 clearly is critical to support CD8 T cell recall responses, and may provide yet another means of inducing immune memory in the tumor setting. Similar claims have been made for OX40 and CD27. Jedd Wolchok and colleagues recently reviewed the field for Clinical Cancer Research if you wish to read further.

Looking again beyond T cells another very intriguing candidate TNFR is CD40. This activating receptor is expressed on B cells, dendritic cells, macrophages and other cell types involved in immune responses – it’s ligand (CD40L) is normally expressed on activated T cells. Roche/Genentech and Pfizer have clinical stage agonist anti-CD40 programs in their immuno-oncology portfolios. Agonist anti-CD40 antibodies would be expected to activated macrophages and dendritic cells, thus increasing the expression of MHC molecules, costimulatory proteins (e.g. B7-1 and B7-2) and adhesion proteins like VCAM-1 and ICAM-1 that facilitate cell:cell interactions and promote robust immune responses.

I mentioned above that interaction of antibodies with Fc receptors modulates immune cell activity. In the case of anti-CD40 antibodies, Pfizer and Roche have made IgG2 isotype antibodies, meaning they will have only weak interaction with FcRs and will not activate the complement cascade. Thus all of the activity of the antibody should be mediated by it’s binding to CD40. Two other agonist anti-CD40 antibodies in development are weaker agonists, although it is unclear why this is so; much remains to be learned regarding the ideal epitope(s) to target and the best possible FcR engagement on human cells. Robert Vonderheide and Martin Glennie tackled this subject in a nice review in Clinical Cancer Research in 2013 and Ross Stewart from Medimmune did likewise for the Journal of ImmunoTherapy of Cancer, so I won’t go on about it here except to say that it has been hypothesized that crosslinking via FcgRIIb mediates agonist activity (in the mouse). Vonderheide has also shown that anti-CD40 antibodies can synergize with chemotherapy, likely due to the stimulation of macrophages and dendritic cells in the presence of tumor antigens. Synergy with anti-CTLA4 has been demonstrated in preclinical models.

One of the more interesting CD40 agonist antibodies recently developed comes from Alligator Biosciences of Lund, Sweden. This antibody, ADC-1013, is beautifully characterized in their published work and various posters, including selection for picomolar affinity and activity at the low pH characteristic of the tumor microenvironment (see work by Thomas Tötterman, Peter Ellmark and colleagues). In conversation the Alligator scientists have stated that the antibody signals canonically, i.e. through the expected NF-kB signaling cascade. That would be a physiologic signal and a good sign indeed that the antibody was selected appropriately. Not surprisingly, this company is in discussion with biopharma/biotech companies about partnering the program.

Given the impact of various antibody/FcR engagement on the activity of antibodies, it is worth a quick mention that Roghanian et al have just published a paper in Cancer Cell showing that antibodies designed to block the inhibitory FcR, FcgRIIB, enhance the activity of depleting antibodies such as rituximab. Thus we again highlight the importance of this sometimes overlooked feature of antibody activity. Here is their graphical abstract:

The idea is that engagement of the inhibitory FcR reduces the effectiveness of the (in this case) depleting antibody.

Ok, moving on.

Not all signaling has to be canonical to be effective, and in the case of CD40 we see this when we again turn to CAR T cells. Just to be clear, T cells do not normally express CD40, and so it is somewhat unusual to see a CAR T construct containing CD3 (that’s normal) but also CD40. We might guess that there is a novel patent strategy at work here by Bellicum, the company that is developing the CAR construct. The stated goal of having a CD40 intracellular domain is precisely to recruit NF-kB, as we just discussed for 4-1BB. Furthermore, the Bellicum CAR T construct contains a signaling domain from MYD88, and signaling molecule downstream of innate immune receptors such as the TLRs that signal via IRAK1 and IRAK4 to trigger downstream signaling via NF-kB and other pathways.

Here is Bellicum’s cartoon:

If we look through Bellicum’s presentations (see their website) we see that they claim increased T cell proliferation, cytokine secretion, persistence, and the development of long-term memory T cells. That’s a long detour around 4-1BB but appears very effective.

The impact of innate immune signaling via typical TLR-triggered cascades brings us to the world of pattern-recognition receptors, and an area of research explored extensively by use of TLR agonists in tumor therapy. Perhaps the most notable recent entrant in this field is the protein STING. This pathway of innate immune response led to adaptive T cell responses in a manner dependent on type I interferons, which are innate immune system cytokines. STING signals through IRF3 and TBK1, not MYD88, so it is a parallel innate response pathway. Much of the work has come out of a multi-lab effort at the University of Chicago and has stimulated great interest in a therapeutic that might be induce T cell priming and also engage innate immunity. STING agonists have been identified by the University of Chicago, Aduro Biotech, Tekmira and others; the Aduro program is already partnered with Novartis. They published very interesting data on a STING agonist formulated as a vaccine in Science Translational Medicine on April 15th (2 weeks ago). Let’s remember however that we spent several decades waiting for TLR agonists to become useful, so integration of these novel pathways may take a bit of time.

This emerging mass of data suggest that the best combinations will not necessarily be those that combine T cell immune checkpoints (anti-CTLA4 + anti-PD-1 + anti-XYZ) but rather those that combine modulators of distinct arms of the immune system. Recent moves by biopharma to secure various mediators of innate immunity (see Innate Pharma’s recent deals) and mediators of the immunosuppressive tumor microenvironment (see the IDO deals and the interest in Halozyme’s enzymatic approach) suggest that biopharma and biotech strategists are thinking along the same lines.

The twisted tale of neoantigens and anti-tumor immune responses

March 13, 2015Astra Zenenca, Bristol Myers Squibb, CTLA4, Genentech, immunotherapy, ipilimumab, Merck, nivolumab, PD-1, PD-L1, pembrolizumab, Roche, T regulatory cells, TCR therapy, TILsPaul Rennert

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Two papers out this week add to a pile of data addressing the role of neoantigens in tumor therapy. While these papers address tumor neoantigen “load” in the context of immune checkpoint therapy the results have implications for TIL therapeutics, TCR therapeutics and onco-vaccine development.

A really dramatic paper from diverse groups at the University of Pennsylvania and their collaborators, just published in Nature (link-1), explores the complex interplay of radiation therapy and anti-CTLA4 antibody therapy (ipilimumab, from BMS) in patients with stage IV metastatic melanoma (relapsed or previously untreated). In this Phase 1/2 clinical trial (NCT01497808) patients with multiple melanoma metastases received various doses of radiation therapy delivered to a single metastasis, termed the “index lesion”. They then received 4 doses of ipilimumab (3 mg/kg, i.v., once every 3 weeks) and non-irradiated lesions were evaluated within 2 months of the last dose.

Although the sample size reported is small (n=22) some interesting lessons emerged from the study. The response rate was low, and the progression free survival (PFS: 3.8 months) and overall survival (OS: 10.7 months) data bear this out. It appears that just shy of 40% of patients were still alive at ~30 months (see Figure 1c in the paper). It is too early to tell if there will be a “long-tail” effect going forward. In the original ipilimumab study a very small percentage of patients lived for a very long time, “pulling” the PFS and OS curves to the right. Regardless, most patients in this study did not respond and the questions posed in this paper are directed to the mechanisms of resistance.

The mouse B16-F10 melanoma model was used to model resistance. Mice with tumors were locally irradiated then treated with an anti-mouse-CTLA4 antibody, to mimic the clinical trial. Only 17% of the treated mice responded. Two predictors of response/non-response were elucidated: 1) the ratio of effector T cells (Teff) to regulatory T cells (Treg) and 2) a gene signature in the tumor cells that is dominated by the expression of PD-L1 and IFNgamma regulated genes. In short, if the melanoma cells are expressing PD-L1 and the tumor infiltrating lymphocyte (TIL) population is dominated by Tregs (which are PD-1+), then the radiation + anti-CTLA4 therapy failed.

To further subset TIL into active Teff versus non-responsive “exhausted” Teff, the authors used an expression profile of PD-1+/Eomes+ to identify exhausted Teff and PD-1+/Eomes+/Ki67+/GzmB+ for active Teff. Importantly, exhausted Teff could be reanimated upon treatment with PD-1 pathway antagonists: anti-PD-1 antibody or anti-PD-L1 antibody. This reanimation led to an improved CD8+ Teff/Treg ratio and led to tumor control in the majority of the mice (up to 80%) when the treatment consisted of irradiation plus anti-CTLA4 plus anti-PD-L1. Of note, radiation plus anti-PD-L1 did not achieve this effect; the triple therapy was required (see Figure 2d).

The striking conclusion is that upregulation of PD-L1 on tumor cells can subvert the effect of anti-CTLA4 antibody therapy, and this therefore qualifies as a mechanism of resistance.

What about the role of irradiation? In both the patients and the mouse model irradiation was local, not systemic. Further, this local irradiation was required to achieve complete responses in the mouse model. What is going on here? Irradiation was linked to a modest increase in TIL infiltration of melanoma tumors in the mouse model, but sequencing of the T cell receptors (TCR) revealed that there was an increase in the diversity of TCRs, meaning that more antigens were being recognized and responded to by TIL after irradiation. In this context then, anti-CTLA4 reduced the Treg population, anti-PD-L1 allowed CD8+ TIL expansion, and irradiation set the antigenic landscape for response.

Returning to the patients armed with this information from the mouse study, the authors find that low PD-L1 expression on the melanoma cells correlates with productive response to irradiation plus ipilimumab therapy, while PD-L1 high expressing tumors were associated with persistent T cell exhaustion. In addition, monitoring the state of the CD8+ T cell population (PD-1+/Eomes+ versus PD-1+/Eomes+/Ki67+/GzmB+) suggested that these phenotypes might be useful as peripheral blood biomarkers. The patient numbers are very small for this analysis however, which awaits further validation.

The conclusion: irradiation combined with ipilimumab plus anti-PD-L1 antibody therapy should be a productive therapeutic combination in PD-L1+ stage IV melanoma. Similar strategies may be beneficial in other solid tumor types. This is interesting news for companies developing anti-PD-L1 antibodies, including BMS-936559 (also from BMS), MPDL3280A (Roche/Genentech), MEDI4736 (AZN) and MSB0010718C (Merck Serono).

A second paper (link) bring our focus back to PD-1, in the context of non-small cell lung cancer (NSCLC). Using the anti-PD-1 antibody pembrolizumab (from Merck) a group from the Memorial Sloan-Kettering Cancer Center sought to determine correlates of response of NSCLC patients to anti-PD-1 therapy. Their findings again hone in on neoantigen load, as the best predictors of response were the non-synonymous mutational burden of tumors, including neoantigen burden and mutations in DNA repair pathways. What all this means is that mutations that change the amino acid sequence (thus, are non-synonymous) can produce neoantigens that can be recognized by CD8+ T cells; mutations in the DNA repair pathways increase the rate that such mutations go uncorrected by a cell.

The authors sequenced the exomes (expressed exons – these encode proteins) from tumors versus normal tissue, as a measure of non-synonymous mutational burden that could produce neoantigens. Patients were subsetted based on response: those with durable clinical benefit (DCB) and those with no durable benefit (NDB). High mutational burden was correlated with clinical efficacy: DCB patients averaged 302 such mutations, while NDB patients averaged 148; ORR, PFS and OS also tracked with mutational burden. In a validation cohorts the number of non-synonymous mutations was 244 (DCB) versus 125 (NDB).

Examination of the pattern of exome mutations across both cohorts was studied in an attempt to discern a pattern of response to pembrolizumab treatment. The mutational landscape was first refined using an algorithm that predicts neoepitopes that can be expressed in the context of each patients specific class I HLA repertoire – these are the molecules that bring antigens to cell surfaces and present them to T cells for recognition (I’m simplifying this process but that is the gist of it). The algorithm identified more potential neoepitopes in the DCB patient tumors than in the NDB cohort, more impressively, a dominant T cell epitope was identified in an individual patient using a high-throughput HLA multimer screen. At the start of therapy this T cell clone represented 0.005% of peripheral blood T cells, after therapy the population had risen 8-fold, to 0.04% of peripheral blood T cells. Note that most of this clone of T cell would be found in the tumor, not in circulation, so that 8-fold increase is impressive. The T cells were defined as activated CD8+ Teff cells by expression markers: CD45RA-/CCR7-/LAG3-. As in the first paper we discussed, it is useful that these markers of systemic response to immunotherapy treatment are being developed.

There is an interesting biology at work here. It is often noted that high mutational burden is associated with better outcome, for example to chemotherapy in ovarian cancer, and irrespective of therapy across different tumor types (link-2). This suggests that tumor neoepitopes are stimulating an ongoing immune response that is stifled by active immunosuppression, yet is still beneficial. Once unleashed by immune checkpoint blockade, the immune system can rapidly expand it’s efforts.

We recently reviewed the importance of neoantigens in anti-tumor therapy (link-3) although the focus then was on cellular therapeutics rather than on immune checkpoint modifiers such as anti-CTLA4 and anti-PD-1 or PD-L1 antibodies. We can mow add that our ability to track neoantigens and the immune response to neoantigens is opening new avenues for investigating immuno-oncology therapeutics and their efficacy.

Reading List – day 2, #JPM15 edition – The Power of Immunotherapy

January 12, 2015Bristol Myers Squibb, CTLA4, immunotherapy, PD-1, PD-L1Paul Rennert

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BMY today announced that an open-label, randomized Phase 3 study (CheckMate-017; NCT0164200) evaluating Opdivo vs docetaxel in previously treated patients with advanced, squamous NSCLC was stopped early because an assessment concluded that the study met its endpoint, demonstrating superior overall survival in patients receiving Opdivo.

CheckMate-017 is a Phase 3, open-label, randomized study. Patients who had failed prior platinum doublet-based chemotherapy received either nivolumab 3 mg/kg intravenously every two weeks or docetaxel 75 mg/m2 intravenously every three weeks (N = 272, randomized).

The primary endpoint is overall survival. Secondary endpoints include objective response rate and progression free survival. The initial time frame was 38 months from enrollment. The trial opened in 2012 and was scheduled for primary outcome measurement in January 2016, so this halt is a year early. An association between PD-L1 expression and efficacy measures (ORR, OS PFS) will be explored post hoc.

Arms

Assigned Interventions

Experimental: Arm A: Nivolumab

Nivolumab 3 mg/kg solution intravenously every 2 weeks until documented disease progression, discontinuation due to toxicity, withdrawal of consent or the study ends

Biological: Nivolumab

Other Name: BMS-936558

Experimental: Arm B: Docetaxel

Docetaxel 75 mg/m2 solution intravenously every 3 weeks until documented disease progression, discontinuation due to toxicity, withdrawal of consent or the study ends

Drug: Docetaxel

Other Name: Taxotere®

Key Inclusion Criteria:

Adult subjects with Stage IIIB/IV disease or with recurrent or progressive squamous cell NSCLC who present with disease following multimodal therapy (radiation therapy, surgical resection or definitive chemoradiation therapy for locally advanced disease)
Disease recurrence or progression during/after one prior platinum doublet-based chemotherapy regimen for advanced or metastatic disease
Evaluable by imaging (CT/MRI) per RECIST 1.1 criteria
ECOG performance status ≤1
Formalin fixed, paraffin-embedded tumor tissue block or unstained slides of tumor sample (archival or recent) available for biomarker evaluation. Biopsy is excisional, incisional or core needle.

Key Exclusion Criteria:

Subjects with untreated central nervous system (CNS) metastases are excluded. Subjects are eligible if CNS metastases are treated and subjects are neurologically returned to baseline for at least 2 weeks prior to enrollment. In addition, subjects must be either off corticosteroids, or on a stable or decreasing dose of ≤10 mg daily prednisone (or equivalent)
Subjects with active, known or suspected autoimmune disease (except for type I diabetes mellitus, hypothyroidism only requiring hormone replacement, vitiligo, psoriasis, or alopecia not requiring systemic treatment, or conditions not expected to recur in the absence of an external trigger).
Subjects with a condition requiring systemic treatment with either corticosteroids or other immunosuppressive medications within 14 days of randomization
Prior therapy with anti- PD-1, anti-PD-L1, anti- PD-L2, anti-CD137, or anti-CTLA-4 antibody (including ipilimumab or any other antibody or drug specifically targeting T-cell co-stimulation or checkpoint pathways)
Prior treatment with Docetaxel
Subjects with interstitial lung disease that is symptomatic or may interfere with the detection or management of suspected drug-related pulmonary toxicity
Treatment with any investigational agent within 14 days of first administration of study treatment

So stopping this trial early is great news. What can we anticipate in addition to the report of ORR, OS, PFS etc that we will likely get at ASCO? The answer lies in the details regarding the Checkmate-017 trial.

A few pointers:

1) there is no inclusion biomarker, ie., there is no specified use of PD-1 staining of biopsy tissue that puts patients into the trial. This is in line with the confusion surrounding use of PD-1 as a biomaker.

2) there is a requirement that pretreatment biopsy specimens be available, as these will be used retrospectively to associate response with expression of biomarkers, including PD-L1 (the PD-1 ligand). No doubt many other biomarkers will be explored.

3) if you have autoimmune disease or interstitial lung disease (a broad term) you are out of luck. So patients with RA, MS, IBD, lupus, and a whole host of other autoimmune diseases need not apply. If you have Type 1 Diabetes though, your good to go (which among other things reminds us just how damn puzzling T1D autoimmunity is).

4) you also cannot be immunosuppressed (corticosteroids) or have had prior treatment with with anti- PD-1, anti-PD-L1, anti-PD-L2, anti-CD137, anti-CTLA-4 antibody (including ipilimumab), or docetaxel. This last one excludes patients who may have gotten docetaxel as second line therapy, which is a setting in which it is commonly used. This tells us that the risk of toxicity in patients is deemed too high.

5) the study halt, being based on efficacy, does not mention toxicity, so we’ll have to wait and see.

Now back to the reading list. In the context of biomarker investigation this story has some resonance:

Day 2 – Immunotherapy: back to those biomarkers of response

Genetic Evolution of T-cell Resistance in the Course of Melanoma Progression

Sucker et al 2014. Clin Cancer Res; 20(24); 6593–604

This interesting paper outlines a technique for tracking the evolution of immune resistance, an essential part of the so-called immune editing process, using in vitro analysis of patient-derived (PDX) samples.

Three consecutive melanoma lesions obtained within one year of developing stage IV disease were analyzed for their recognition by autologous T cells.

One skin and two lymph node metastases were initially analyzed for T-cell infiltration. Then, melanoma cell lines established from the respective lesions. T-cell–stimulatory capacity, expression of cell surface molecules involved in T-cell activation, and specific genetic alterations affecting the tumor–T-cell interactions were identified.

Sampled skin lesions were infiltrated by T cells. The T cell infiltrate was diminished in the lymph node metastatic samples which were found to be HLA class I–negative due to an inactivating mutation in one allele of the beta-2-microglobulin (B2M) gene and concomitant loss of the other allele by a deletion on chromosome 15q. This is an impressive response to avoid immune detection.

The study reveals a progressive loss in melanoma immunogenicity during metastasis. Screening tumors for this and other genetic alterations that cause acquired immune resistance will be clinically relevant in terms of predicting patient responses and designing combinatorial approaches to immunotherapy.

Day 2 – Immunotherapy: back to those tox issues: it’s hard to control ipilimumab-induced tox

In the trial above we noted two things: no current corticosteroid use and no prior ipilimumab. Turns out these don’t play well together either

http://clincancerres.aacrjournals.org/content/early/2014/12/23/1078-0432.CCR-14-2353.abstract

Min et el. 2014. Systemic high dose corticosteroid treatment does not improve the outcome of ipilimumab-related hypophysitis: a retrospective cohort study

Purpose To examine the onset and outcome of ipilimumab-related hypophysitis and the response to treatment with systemic high dose corticosteroids. Patient and Methods Twenty-five patients who developed ipilimumab-related hypophysitis were analyzed for the incidence, time to onset, time to resolution, frequency of resolution, and the effect of systemic high-dose corticosteroids on clinical outcome. To calculate the incidence, the total number (187) of patients with metastatic melanoma treated with ipilimumab at Dana-Farber Cancer Institute (DFCI) was retrieved from the DFCI oncology database. Comparisons between corticosteroid treatment groups were performed using Fisher’s exact test. The distributions of overall survival were based on the method of Kaplan-Meier. Results The overall incidence of ipilimumab-related hypophysitis was 13%, with a higher rate in males (16.1%) than females (8.7%). The median time to onset of hypophysitis after initiation of ipilimumab treatment was 9 weeks (range: 5-36 weeks). Resolution of pituitary enlargement, secondary adrenal insufficiency, secondary hypothyroidism, male secondary hypogonadism, and hyponatremia occurred in 73%, 0%, 64%, 45%, and 92% of patients, respectively. Systemic high dose corticosteroid treatment did not improve the outcome of hypophysitis as measured by resolution frequency and time to resolution. One-year overall survival in the cohort of patients was 83%, and while slightly higher in patients who did not receive high dose corticosteroids, there was no statistically significant difference between treatment arms. Conclusion Systemic high dose corticosteroid therapy in patients with ipilimumab-related hypophysitis may not be indicated. Instead, supportive treatment of hypophysitis-related hormone deficiencies with the corresponding hormone replacement should be given.

Tumor Neo-Epitopes

December 16, 2014CTLA4, immunotherapy, ipilimumab, melanoma, oncology, PD-1, Roche, TILsPaul Rennert

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I’m asked a lot about the onco-vaccine field, and if immune checkpoint inhibitors will be the key to unlocking the potential of this long-suffering therapeutic class. The answer is never simple, since we are often looking at thin patient data that can contain compelling hints of efficacy – those immunized late-stage patients who not only regressed but stay in remission, month after month and year after year. The problem for companies and investors is that such observational data can be very misleading, and the vaccine candidates most often go on to fail in later and larger clinical trials, sometimes spectacularly. These big failures burden the field with a high evidentiary bar.

Data have emerged that suggest several issues with most vaccines, and these issues are both distinct and related.

At the end of November Nature published two interesting papers that asked a very simple question: what immunogenic antigens are present in common mouse tumor models. Yadav et al from Genentech and Immatics Biotechnologies (link 1) used a genome-wide exome and transcriptome sequence analyses, mass spectrometry and structural modeling to identify immunogenic neo-antigens in the widely used MC-38 and TRAMP-C1 mouse syngeneic tumor models. These models are considered poorly immunogenic in wild-type syngeneic (C57Bl6) mice. The sequencing analysis was used to identify mutated proteins that were present at >20% allelic frequency. From the MC-38 model, 1290 expressed mutations were identified of which 170 were considered to be neo-epitopes, that is, modeling suggested they would be expressed by MHCI and sufficient residues would be solvent exposed to allow immunogenicity. Only 67 expressed mutations were found in the TRAMP-C1 model, and of these 6 were considered to be potential neo-epitopes. Of this total of 170 (MC-38) and 6 (TRAMP-C1) only 6 bound MHC1 by Mass Spec, with a predicted IC50 for MHCI < 500nM. Of these, 3 were actually immunogenic in vivo (using C57Bl/6 mice) and could protect wild-type mice from tumor challenge. The neo-epitopes were found in the proteins Dpagt1, Reps1 and Adpgk. Here is a schematic of the filtering scheme:

Working the other way, the authors confirmed the immunogenicity of neo-epitope peptides by analyzing tumor-infiltrating lymphocytes (TIL) and staining with peptide–MHCI dextramers to identify bound T cells. CD8+ T cells specific for Reps1, Adpgk and Dpagt1 were enriched in the tumor. Using the Adpgk neo-epitope, the TIL were further investigated and found to express PD-1 and TIM-3, inhibitory receptors associated with anergic or “exhausted” CD8+ T cells, showing that the murine immune system had indeed recognized and responded to the neo-epitopes, a response that was then actively immunosuppressed in the tumor microenvironment. Importantly, none of the identified neo-epitopes would qualify as tumor-antigens, that is, they are not specifically overexpressed at a sufficient level to qualify. The neo-antigen-specific TIL are also pretty rare, suggesting that use of tumor lysate as an immunogen to elicit an anti-tumor response may “miss” by failing to present enough of the right antigen to the immune system.

We noted at the top that this paper came out of labs at Genentech and Immatics. An agreement between Roche/Genentech and Immatics will focus on the use of this technology. The two companies will develop new tumor-associated peptides (the neo-epitopes as cancer vaccine candidates, initially targeting gastric, prostate and non-small cell lung cancer. The most advanced candidate is IMA942, a peptide vaccine for the treatment of gastric cancer, in late preclinical development. Immatics CEO Paul Higham has publicly stated that a Phase I study of IMA942 with Roche’s PD-L1 inhibitor MPDL3280A in gastric cancer will be initiated soon. Immatics will also conduct research to identify neo-antigens for the additional indications. For those keeping score, Immatics received $17 million upfront, committed research funding, and potential milestones

The second work, led by Schreiber’s group at Wash U, used mouse models to ask a different but related question: what tumor antigens are recognized after immune checkpoint blockade with anti-PD-1 or anti-CTLA4 antibodies (link 2). The sarcoma lines d42m1-T3 and F244 were rejected in wild-type mice treated with either anti-PD-1 or anti-CTLA4 antibodies, in a CD4/CD8/IFNy/DC-dependent manner. As in the first paper, a filtering system built from diverse technologies was used to identify potential neo-epitopes. Mutations were identified by cDNA sequencing, translated to corresponding protein sequences, then tested against MHCI binding algorithms. Neo-epitopes were ranked by predicted median binding affinities and likelihood of productive immunoproteasome processing and antigen display. Using these methods, two MHCI restricted neo-epitopes were identified in Alg8 and Lama4.

As in the first paper, the authors then turned the system around, asking what neo-epitopes could be identified through analysis of TIL. Alg8 and Lama4 were found in tumor TIL and their frequency was increased by treatment with anti-PD-1 or anti-CTLA4. The neo-epitopes could successfully be used to induce anti-tumor immune responses. As in the first paper, these are not neo-epitopes that would qualify as tumor-antigens using the traditional criteria of selective and high expression.

So these are our two distinct but related issues with the current tumor vaccine landscape: those that have selected antigens have likely selected the wrong ones, while those that use lysates are likely too dilute.

Importantly, we can now compare these model systems to actual data from human patients treated with anti-CTLA4 antibody, as published recently in NEJM (link 3). The clinical group from Memorial Sloan Kettering Cancer Center obtained tumor tissue from melanoma patients treated with anti-CTLA4 antibodies (ipilimumab or tremelimumab). As in the mouse study, whole-exome sequencing was performed, somatic mutations identified and potential neo-antigens were characterized. Here is their schematic:

Baseline analyses showed that there was a significant difference in mutational load between patients with long-term clinical benefit and those with a minimal or no benefit, with higher mutational load associated with response. However the relationship was correlative, since some tumors with a high mutational burden were not responsive to anti-CLTA4 therapy. Using peptides predicted to bind to MHCI with a binding affinity ≤ 500 nM, the authors focused on mutated peptide sequences shared by multiple tumors and shared by patients having long-term clinical benefit. From this analysis a neo-epitope “signature” was derived, consisting of a distinct pattern of mutated peptide sequences. One of the peptide signatures identified matched an amino acid sequence in MART1, a known melanoma antigen. However the bulk of predicted neoantigens were tetrapeptide sequences shared across antigenic peptides, that is, they were encoded by diverse genes (you have to go into the huge supplemental data file to find this list, suffice to say it is very long). To make sense of this curious result the authors note that the some of the predicted sequences have high homology to viral and bacterial antigens, citing a CMV antigenic sequence as an example. They speculate, and here we quote from the paper: ” These data suggest that the neoepitopes in patients with strong clinical benefit from CTLA-4 blockade may resemble epitopes from pathogens that T cells are likely to recognize.”

The unstated null hypothesis is that there is no relationship between the shared tetrapeptide sequences and clinical response and that the association between the two phenomena is due to a productive immune system response to anti-CTLA4 antibody therapy which has released the anti-tumor response as well as many otherwise quiescent immune responses, such as those to pathogenic viruses and bacteria (and to self antigens, as shown by the autoimmune toxicity associated with anti-CTLA4 antibody treatment). The in vitro response assay data sheds no real light on this, since these assays cannot distinguish anti-tumor responses from other immune responses. So we are left with an intriguing correlation, and a nagging sense that only a very few of the vast number of predicted neo-epitopes will actually trigger bona-fide anti-tumor T cells responses. Indeed the weakness of the paper is the reliance on predictive rather than experimental identification of productive peptide/MHC interaction. As we say in the mouse studies the majority of predicted interactions are not confirmed experimentally.

Regardless, the paper is a remarkable and important step forward, and shows us (as do the mouse studies) the level of investigation required to identify neo-antigens that might expand be used to expand patient TIL populations, as we have discussed in other posts. Returning to onco-vaccines, these three papers together show us that neo-antigen anonymity, rarity and variability from patient to patient are critical issues that will need to be addressed if we are to efficiently develop this therapeutic class.

Last Week’s Immune Checkpoint Papers In Nature Are Complicated!

December 4, 2014CTLA4, immunotherapy, MPDL3280A, PD-1, PD-L1, pembrolizumab, T regulatory cells, TILs, tumor microenvironmentPaul Rennert

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Last week we were treated to a barrage of good news regarding PD-1/PD-L1 therapeutics and the ability to select responders. The centerpiece was a trio of papers in Nature.

Powles et al. presented data on the use of MPDL3280A, an anti-PD-L1 IgG1 antibody that has been engineered to lack all ADCC function (link 1). The antibody blocks the interaction of PD-L1 with PD-1 and with CD80, two receptors found primarily on lymphocytes. The paper focused on the application of ‘3280’ therapy in chemotherapy-resistant metastatic urothelial bladder cancer (UBC). Nearly all patients (93%) had failed platinum-based chemotherapy; 72% had failed 2 or more lines of prior therapy. 75% had visceral metastases, most had poor renal function and the majority (59%) had a performance score of 1 (very poor). In a word, these patients were incurable. Preliminary Phase 1 data demonstrating efficacy in UBC was presented at ASCO and led to breakthrough designation for ‘3280 for the treatment of UBC in June 2014.

The original Phase 1 trial had enrolled UBC patients whose resection or biopsy tissue demonstrated the presence of tumor-infiltrating lymphocytes (TIL) with dark staining (score 2 or 3) for PD-L1. The expansion cohort allowed for the enrollment of patients whose tissue specimens contained TIL which were PD-L1 dim (score = 1) or negative. 205 patient tissues were analyzed (see table 1 in the paper). 67 patients were enrolled and evaluable with PD-L1 staining results as follows:

A total of 17 patients responded and 16/17 responses were ongoing (i.e. durable) at the time of data cutoff. The longest duration of response was a remarkable 30 weeks in the cohort with the brightest PD-L1 TIL staining, although the range was broad (from 1 week to 30). Median duration of treatment was 9 weeks, so this is really an early snapshot. Regardless, the ability to invoke an anti-tumor response in a cohort of patients that are this ill, and deemed incurable, is remarkable.

With reference to the staining pattern of PD-L1 and the relevance of PD-L1 expression to successful response, the authors came to the following conclusions:

1) therapy triggered expansion of the circulation CD8+ T cell population, and transient elevation of IL-18 and IFNgamma was observed; these systemic changes reflect the proposed mechanism of action of ‘3280 but did not correlate with response.

2) expression of PD-L1 on TIL, but not on tumor cells, was predictive of response to therapy. On note, this was true whether the available tissue sample was new acquired or archival (up to 10 years old). This suggests that there is an ongoing and futile immune response in these PD-L1+/TIL+ tumors. The lack of association with tumor PD-L1+ status is discussed more extensively in the companion paper (see below).

3) the efficacy of PD-L1-directed therapy in UBC and also NSCLC and melanoma, all tumors with very high mutational burdens, suggests that antigen diversity or antigen “burden” may be important for successful induction of an anti-tumor immune response in ‘3280-treated patients.

The UBC cohort was part of a much larger clinical trial that included diverse solid tumors. A companion paper by Herbst et al. investigates the utility of PD-L1 TIL expression in other cohorts (link 2). The focus of this work is on the biomarker application, particularly with respect to PD-L1+ TIL staining, as defined in the prior paper. Patients (n=277) with advanced incurable cancers were enrolled in a ‘3280 dose ranging study, given drug iv every 3 weeks. Across tumor types high PD-L1 expression on TIL, but not tumor cells, was associated with response and increased PFS. Note here that the PFS gain, while encouraging, does not suggest that we will see a high percentage of truly durable (“long tail”) responses in this particular patient population, even in those patients with PD-L1 bright (score of 3) staining:

There were some interesting additional analyses. In NSCLC patients who had been smokers, 43% responded to therapy, while only 10% of non-smokers responded. Such data have been reported before, and are often taken to mean that the higher mutational burden seen in smokers with NSCLC biases their tumor toward immune recognition (this echoes the mutational diversity/mutational burden argument made in the Powles UBC paper). Sticking with NSCLC, 83% of patients with a PDL1+ TIL staining score of 3 (lots of cells and therefore dense/dark staining) responded versus 38% of patients with a PDL1+ TIL staining score of 2 (diffuse staining, fewer cells). Response was positively correlated with CTLA4+ staining on TIL, and negatively correlated with fractalkine expression. In melanoma (but not NSCLC or RCC) response was associated with elevated IFNgamma and IDO1 and CXCL9 that are induced by IFN gamma. Strikingly, positive anti-tumor responses were not associated with a measureable change in FoxP3 expression, suggesting the T regulatory T cells were not playing a role in the setting of ‘3280 therapy.

What about the non-responders, as these make up the majority of the patients across indications? Progressing tumors were characterized into three classes:

1) few or no TIL present – “immune ignorance”

2) TIL present but little or no PD-L1 expression – “non-functional immune response”

3) TIL present and PD-L1+ but located on the edge of the tumor – “excluded infiltrate”

Missing here I think is an analysis of tumors with PD-L1+ TIL with high staining scores (2 or 3) that progressed, i.e. did not respond to therapy. It seem to me unlikely that these all fell into category “3” above, so this analysis may be coming in a follow-up paper.

The authors make a very interesting point about this data, which is that they seem to refute the consensus model of “immune resistance” in which it is postulated that CD8+ T cells infiltrating tumors secrete IFNgamma and other cytokines that induce PD-L1 expression on the tumor cells themselves, and these tumor cells in turn produce factors that create an immunosuppressive environment that includes potently immunosuppressive, PD-L1 bright T regulatory cells. The “immune resistance” model further postulates that the expression of PD-L1 on tumor cells and T regulatory cells is responsible for shutting down CD8+ T cells by binding to PD-1.

There are several key messages in this paper – first, responses in these incurable patients are measureable and remarkable, if they respond (most do not). Second, CD8+/PD-L1+ TIL are highlighted as a potential prognostic indicator of the potential for response the ‘3280 therapy. Finally, it is clear that other signals will have to be disabled or enhanced in order to induce a productive and durable immune response in more patients and/or move PD-1/PD-L1-directed therapies to front line.

Now, the final paper in this triad turns things upside down. Tumeh et al. analyzed tumor tissue samples from 46 metastatic melanoma patients treated with pembrolizumab, an anti-PD-1 antibody (link 3). The analytic methods used are elegant and overlap but also extend the analyses used in the prior 2 papers: quantitative immunohistochemistry, quantitative multiplex immunofluorescence, and TCR deep sequencing (NGS).

This paper is strictly about melanoma. The ORR in this small study was 48% (22/46). The authors focused on expression of PD-L1 on tumor cells and of PD-1 on CD8+ T cells. Doing so they come to strikingly different conclusions than the papers discussed above. Responders in this study had PD-1+ CD8 T cells massed on the tumor margin, adjacent to PD-1+ tumor cells. Response was associated with infiltration of the tumor by those CD8+ T cells, which also increased in density (proliferated). Therefore the paper specifically supports the “immune resistance” model in which tumor-expressed PD-L1 suppresses PD-1+ CD8 T cells. CD8 T cell proliferation was associated with expression of granzyme B within the tumor and phosphorylated STAT1 at the tumor margin where CD8+ T cells were infiltrating (phospho-STAT1 in induced by IFNgamma receptor signaling). Finally, response was associated with T cell (TCR) clonality, i.e. the fewer tumor antigens, and thus the lower the antigen burden that is invoking a response, the better. This is a different take than we got from the prior papers.

So, perhaps melanoma is distinctly different.

Aside from that, these papers provide critical take-home messages and perhaps even more critical questions to be addressed:

1) CD8 T cells are good. That’s pretty clear, whatever they are expressing. We can argue more about their geography, but if they are not present, you will not respond.

2) IFNgamma is good. We see this especially in the melanoma setting as detailed in two of the papers.

Neither of these conclusions is novel nor surprising.

3) Biomarker development beyond CD8+ T cell staining remains complex.

4) Regardless of their biomarker status most patients still do not respond and we do not know why. As we consider combination therapy, will other markers be used to further sort patients into rational combination buckets, or will this simply too complex to be useful?

5) Finally, what about those T regulatory cells we’ve been obsessed with for the last decade? These are hardly mentioned in the context of PD-1/PD-L1 therapeutics in the three studies.

next time:

>>> back to those tumor antigens? New papers, preclinical and clinical, shed some light… and

>>> those T regulatory cells may be important in some settings, but were betting on the tumor microenvironment to yield interesting new targets for therapy

stay tuned