Monthly Archives: March 2015

The twisted tale of neoantigens and anti-tumor immune responses

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.