The Search for Immune-Specific Biomarkers Is in Full Swing

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Oncology Live®May 2015
Volume 16
Issue 5

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An improved understanding of how the immune system recognizes and eradicates cancer cells, along with advances in drugs that effectively promote antitumor immune responses, is revolutionizing the field of cancer therapy.

Howard L. Kaufman,

MD, FACS

Associate Director, Clinical Science

Chief Surgical Officer

Ann W. Silk, MD

Medical Oncologist

Rugters Cancer Institute of New Jersey

An improved understanding of how the immune system recognizes and eradicates cancer cells, along with advances in drugs that effectively promote antitumor immune responses, is revolutionizing the field of cancer therapy. During the past four years, several randomized clinical trials have demonstrated significant improvements in both objective response rates and overall survival for several tumor immunotherapy agents.1

There are now an increasing number of immunotherapy agents available for the treatment of advanced cancers, including six FDA-approved drugs for melanoma (interferon, pegylated interferon, interleukin-2 [IL-2], ipilimumab, pembrolizumab, and nivolumab); two in renal cell carcinoma (interferon, IL-2); and one each in lung cancer (nivolumab) and prostate cancer (sipuleucel-T).

In contrast to targeted therapies that tend to mediate tumor regression quickly and in a large number of patients, immunotherapy tends to mediate tumor regression more slowly and in a smaller number of patients. Perhaps the most important difference, however, is that immunotherapy is often associated with durable responses and an associated improvement in overall survival. Thus, a major focus in the field has centered on identifying predictive biomarkers that might allow appropriate patient selection for immunotherapy.

The use of biomarkers to select appropriate drugs for individual patient treatment has been well established for genomic targeting. This is exemplified by the emergence of “precision medicine” programs throughout major academic centers and even in some community oncology practices. Such programs rely on genomic sequencing of a patient’s tumor to identify therapeutic approaches based on an analysis of mutated genes within an individual tumor.

In essence, specific genetic mutations, especially driver mutations that are known to maintain tumor growth, serve as predictive biomarkers that are used to guide therapeutic selection. Patients with certain cancer types, such as BRAF-mutated melanoma and ALK-rearranged non—small cell lung carcinoma, have a high likelihood of responding to targeted therapy. Targeted therapies have succeeded in improving overall survival when tested in patients known to have tumors with the specified mutations.

Tumor-Immune Interaction as Biomarker

Given that many patients may benefit from both targeted therapy and immunotherapy, the identification of predictive biomarkers for immunotherapy response has become an important priority for tumor immunotherapists.

Thus, we recently coined the term precision immunology to profile the tumor-immune system interaction within a particular patient and then select the best option for treatment from the widening array of tumor immunotherapy approaches.2 Although precision immunology is in its infancy, there are already tantalizing clues that we may be able to use information from the host antitumor immune response as a biomarker for cancer diagnosis, prognosis, and response to individual therapeutic approaches.

According to the immune surveillance hypothesis, single cells or clusters of cells with dysregulated growth are eliminated by the host immune system before they become clinically relevant cancers.3 As described by Schreiber et al, this process has been termed the cancer immunoediting concept and involves three discrete stages: elimination, equilibrium, and escape.4

During early neoplastic transformation, the innate and adaptive immune systems are able to eliminate cancer cells by recognizing new tumor-associated antigens that emerge as part of the dysregulated gene expression characteristic of tumor cells. After a period of time, the mutation rate in cancer cells may increase and be matched by the rate in which an immune response can be generated against new or neoantigens. At this point, equilibrium is reached and tumors may exist but will not be able to increase or decrease in size.

Over time, tumor cells may be able to evade detection or utilize local immune suppressive mechanisms to avoid natural immune surveillance, and this is referred to as tumor escape. Cancer may become detectable only after tumor escape has occurred and Weinberg has recently added tumor escape as a major hallmark of cancer.5

The goal of immunotherapy is to target the defects in the immune system and restore tumor elimination or even equilibrium so that tumors are unable to progress. This is in contrast to almost all other therapeutic modalities, including surgical resection, radiation therapy, cytotoxic chemotherapy, and targeted therapy that directly target the tumor. Based on this concept, is there any evidence that the host immune system does indeed contribute to the natural history of cancer outcomes in patients?

Lymphocyte-Predominant Phenotypes

In many types of cancer, patients who have tumors that are infiltrated with lymphocytes (lymphocyte-predominant) tend to have more favorable survival.6 This phenomenon has been reported in patients with colorectal cancer, melanoma, renal cell carcinoma, lung cancer, breast cancer, gastric cancer, and ovarian cancer. This suggests that the natural immune response is important, even when not completely effective, and that immunotherapy may be beneficial, even in cancers in which immunotherapy is not currently used, such as ovarian cancer and colorectal cancer.

In addition to the mere number of lymphocytes present in the tumor microenvironment, specific characteristics of infiltrating immune cells may be more predictive of prognosis and tumor response to immunotherapy. While further studies are needed to validate immune infiltration as a prognostic factor for cancer outcomes, the ability to uniformly detect specific immune cells and identify cell sur- face and secreted factors as biomarkers may allow better selection of patients for immunotherapy.

This is being actively pursued based on recent data that tumors may be classified into two major categories–tumors that are detected by the immune system (lymphocyte-predominant) and tumors that evade the immune system altogether (lymphocyte-depleted).7

Tumors that have a lymphocyte-predominant phenotype tend to have a broad cytokine profile, and a type I interferon signature indicative of innate immune activation. This is characteristic of many patients with melanoma, in which spontaneous regression of tumors is well described. However, the tumor infiltrating lymphocytes (TILs) usually cannot completely eradicate the cancer cells because the tumor exerts suppressive effects on the immune system in order to survive.

One explanation for the ability of tumors to progress despite the presence of immune cells nearby is that the tumor contains exhausted T cells or regulatory T cells. This is the basis for T-cell checkpoint inhibitor therapy in which negative regulators of T-cell activation can be blocked to prevent T-cell exhaustion and unresponsiveness. The cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed cell death-1 (PD-1) are two of the more important T-cell surface receptors that mediate T-cell inhibition and are used as markers of exhausted T cells.

Interestingly, many tumor cells co-opt natural negative regulators of T-cell function by expressing the ligands, such as programmed cell death ligand-1 (PD-L1), which can inhibit infiltrating PD-1—positive T cells. Tumors with lymphocyte-predominant infiltrates do seem to benefit more from tumor immunotherapy than cancers without TILs.8

More recently, there have been reports that PD- L1—expressing tumors may also identify tumors more likely to respond to treatment with PD-1 and PD-L1 blockade.9 These findings require further validation and studies have been complicated by the use of different antibodies and variable definitions of “positive” staining. While an association has been seen, it has also been intriguing that some patients without high levels of PD-L1 tumor expression may respond to treatment with PD-1/ PD-L1 blockade, suggesting that other mechanisms may allow effective therapy even in the absence of PD-L1 expression.

Another mechanism that may allow tumors to escape immune elimination is a narrow T-cell receptor repertoire. In a recent report, tumors that expressed a particular 4-amino acid peptide sequence were more likely to respond to CTLA-4 blockade therapy.10 The short peptides were new and not detected in normal cells, and could thus act as neoantigens for recognition by T cells. The authors hypothesized that this may lead to the generation of a broader T-cell repertoire.

This is perhaps a bit surprising but may provide an important insight into how T-cell checkpoint inhibitors mediate tumor regression. If this proves to be true, the use of precision vaccines that target neo- antigens may be a useful adjunct to sustaining T-cell responses following checkpoint blockade, although further research is needed to confirm this hypothesis.

Lymphocyte-Depleted Phenotype

The second broad category of tumors consists of cancers that do not have a lymphocyte-predominant phenotype, generally lack TILs, and are not associated with high response rates to tumor immunotherapy. This is characteristic of prostate cancer. These tumors evade the immune system by becoming invisible through a variety of mechanisms.

Tumors can downregulate their expression of major histocompatibility complex (MHC) class I expression, which results in poor tumor-associated antigen exposure and lack of visibility to the surrounding immune cells. Tumors can secrete suppressive cytokines and express ligands for inhibitory receptors on natural killer cells and others. Patients with cancer have high levels of myeloid-derived suppressor cells in the blood, which also secrete suppressive cytokines to promote immune ignorance.

There are multiple promising strategies for converting a lymphocyte-depleted tumor into a lymphocyte-predominant tumor. These strategies include radiation therapy, direct injection of oncolytic viruses into the tumor microenvironment, and even the use of targeted therapy such as vemurafenib, which has been reported to induce T-cell infiltrates into the melanoma tumor microenvironment.11

Role of the Tumor Genome

Similar to targeted therapy, the tumor genome may play a role in predicting response to tumor immu- notherapy. Patients with NRAS-mutated melanoma have a better response to IL-2 and other immunotherapy drugs compared with patients with NRAS wild-type tumors.12 Mutational density may also be an independent predictor of PD-1 blockade in non—small cell lung cancer.10,13

The association of genome-wide mutations both within tumors and the natural polymorphisms within host immune cell genomes has only recently been recognized as an important area of research. Further work in this area may hold significant promise for identifying innate and tumor-derived genomic factors that may influence the interactions of emerging tumor cells and the host immune system, and may also help identify genetic signatures predictive of effective therapeutic options for patients with evolving cancers.

For example, in patients with melanoma and non—small cell lung cancer vaccinated with a MAGEA3 vaccine, a genetic signature related to interferon gamma signaling predicted favorable clinical outcomes if a particular vaccine adjuvant was used but not another.14

Taking the Next Step

The classification of tumors into two broad categories of tumor escape based on cellular and molecular characteristics of the tumor microenvironment may be the first step in realizing the potential of precision immunology. Ideally, the next steps are to dissect the specific defects that have led to immune silencing and design individualized treatment plans that “fix” or replace that particular immune defect.

Combination approaches in which immunotherapy is paired with other immunotherapy agents or used in conjunction with radiation therapy may be needed to fully overcome the suppressive effects of many established tumors that have been fully immunoedited.

In summary, we posit that dissecting out immune defects in the host and tumor microenvironment and re-engaging a patient’s immune system based on that information is a promising approach for patients with cancer, and precision immunology needs to be incorporated into the larger precision medicine strategies in contemporary development for the treatment of cancer.

Howard L. Kaufman, MD, FACS, is president of the Society for Immunotherapy of Cancer. This work was supported in part by NCI grant UM1 CA186716-01.

References

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  2. Kaufman HL. Precision immunology: the promise of immunotherapy for the treatment of cancer [published online January 20, 2015]. J Clin Oncol. 2015;33(12):1315-1317.
  3. Dunn GP, Old LJ, Schreiber RD. The three Es of cancer immuno-editing. Annu Rev Immunol. 2004;22:329-360.
  4. Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science. 2011;331(6024):1565-1570.
  5. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646-674.
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  9. Herbst RS, Soria JC, Kowanetz M, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014;515(7528):563-567.
  10. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma [published online November 19, 2014]. N Engl J Med. 2014;371(23):2189-2199.
  11. Wilmott JS, Long GV, Howle JR, et al. Selective BRAF inhibitors induce marked T-cell infiltration into human metastatic melanoma [published online December 12, 2011]. Clin Cancer Res. 2012;18(5):1386-1394.
  12. Johnson DB, Lovly CM, Flavin M, et al. Impact of NRAS mutations for patients with advanced melanoma treated with immune therapies. Cancer Immunol Res. 2015;3(3):288-295.
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