Melanoma Immunotherapy: Next-Generation Biomarkers.
Hogan Sabrina A,Levesque Mitchell P,Cheng Phil F
Frontiers in oncology
The recent emergence of cancer immunotherapies initiated a significant shift in the clinical management of metastatic melanoma. Prior to 2011, melanoma patients only had palliative treatment solutions which offered little to no survival benefit. In 2018, with immunotherapy, melanoma patients can now contemplate durable or even complete remission. Treatment with novel immune checkpoint inhibitors, anti-cytotoxic T-lymphocyte protein 4 and anti-programmed cell death protein 1, clearly result in superior median and long-term survivals compared to standard chemotherapy; however, more than half of the patients do not respond to immune checkpoint blockade. Currently, clinicians do not have any effective way to stratify melanoma patients for immunotherapies. Research is now focusing on identifying biomarkers which could predict a patient's response prior treatment initiation (or very early during treatment course), in order to maximize therapeutic efficacy, avoid unnecessary costs, and undesirable heavy side effects for the patient. Given the rapid developments in this field and the translational potential for some of the biomarkers, we will summarize the current state of biomarker research for immunotherapy in melanoma, with an emphasis on omics technologies such as next-generation sequencing and mass cytometry (CyTOF).
10.3389/fonc.2018.00178
PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers.
Yarchoan Mark,Albacker Lee A,Hopkins Alexander C,Montesion Meagan,Murugesan Karthikeyan,Vithayathil Teena T,Zaidi Neeha,Azad Nilofer S,Laheru Daniel A,Frampton Garrett M,Jaffee Elizabeth M
JCI insight
BACKGROUND:PD-L1 expression and tumor mutational burden (TMB) have emerged as important biomarkers of response to immune checkpoint inhibitor (ICI) therapy. These biomarkers have each succeeded and failed in predicting responders for different cancer types. We sought to describe the PD-L1 expression landscape across the spectrum of ICI-responsive human cancers, and to determine the relationship between PD-L1 expression, TMB, and response rates to ICIs. METHODS:We assessed 9887 clinical samples for PD-L1 expression and TMB. RESULTS:PD-L1 expression and TMB are not significantly correlated within most cancer subtypes, and they show only a marginal association at the tumor sample level (Pearson's correlation 0.084). Across distinct tumor types, PD-L1 expression and TMB have nonoverlapping effects on the response rate to PD-1/PD-L1 inhibitors and can broadly be used to categorize the immunologic subtypes of cancer. CONCLUSION:Our results indicate that PD-L1 expression and TMB may each inform the use of ICIs, point to different mechanisms by which PD-L1 expression regulates ICI responsiveness, and identify new opportunities for therapeutic development. FUNDING:Funding was provided by Foundation Medicine Inc., the Johns Hopkins Bloomberg-Kimmel Institute for Cancer Immunotherapy, the Viragh Foundation, the National Cancer Institute Specialized Program of Research Excellence (SPORE) in Gastrointestinal Cancers (P50 CA062924), the NIH Center Core Grant (P30 CA006973), the Norman & Ruth Rales Foundation, and the Conquer Cancer Foundation.
10.1172/jci.insight.126908
Distinct Cellular Mechanisms Underlie Anti-CTLA-4 and Anti-PD-1 Checkpoint Blockade.
Wei Spencer C,Levine Jacob H,Cogdill Alexandria P,Zhao Yang,Anang Nana-Ama A S,Andrews Miles C,Sharma Padmanee,Wang Jing,Wargo Jennifer A,Pe'er Dana,Allison James P
Cell
Immune-checkpoint blockade is able to achieve durable responses in a subset of patients; however, we lack a satisfying comprehension of the underlying mechanisms of anti-CTLA-4- and anti-PD-1-induced tumor rejection. To address these issues, we utilized mass cytometry to comprehensively profile the effects of checkpoint blockade on tumor immune infiltrates in human melanoma and murine tumor models. These analyses reveal a spectrum of tumor-infiltrating T cell populations that are highly similar between tumor models and indicate that checkpoint blockade targets only specific subsets of tumor-infiltrating T cell populations. Anti-PD-1 predominantly induces the expansion of specific tumor-infiltrating exhausted-like CD8 T cell subsets. In contrast, anti-CTLA-4 induces the expansion of an ICOS Th1-like CD4 effector population in addition to engaging specific subsets of exhausted-like CD8 T cells. Thus, our findings indicate that anti-CTLA-4 and anti-PD-1 checkpoint-blockade-induced immune responses are driven by distinct cellular mechanisms.
10.1016/j.cell.2017.07.024
High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy.
Nature medicine
Immune-checkpoint blockade has revolutionized cancer therapy. In particular, inhibition of programmed cell death protein 1 (PD-1) has been found to be effective for the treatment of metastatic melanoma and other cancers. Despite a dramatic increase in progression-free survival, a large proportion of patients do not show durable responses. Therefore, predictive biomarkers of a clinical response are urgently needed. Here we used high-dimensional single-cell mass cytometry and a bioinformatics pipeline for the in-depth characterization of the immune cell subsets in the peripheral blood of patients with stage IV melanoma before and after 12 weeks of anti-PD-1 immunotherapy. During therapy, we observed a clear response to immunotherapy in the T cell compartment. However, before commencing therapy, a strong predictor of progression-free and overall survival in response to anti-PD-1 immunotherapy was the frequency of CD14CD16HLA-DR monocytes. We confirmed this by conventional flow cytometry in an independent, blinded validation cohort, and we propose that the frequency of monocytes in PBMCs may serve in clinical decision support.
10.1038/nm.4466
The PD-1 expression balance between effector and regulatory T cells predicts the clinical efficacy of PD-1 blockade therapies.
Kumagai Shogo,Togashi Yosuke,Kamada Takahiro,Sugiyama Eri,Nishinakamura Hitomi,Takeuchi Yoshiko,Vitaly Kochin,Itahashi Kota,Maeda Yuka,Matsui Shigeyuki,Shibahara Takuma,Yamashita Yasuho,Irie Takuma,Tsuge Ayaka,Fukuoka Shota,Kawazoe Akihito,Udagawa Hibiki,Kirita Keisuke,Aokage Keiju,Ishii Genichiro,Kuwata Takeshi,Nakama Kenta,Kawazu Masahito,Ueno Toshihide,Yamazaki Naoya,Goto Koichi,Tsuboi Masahiro,Mano Hiroyuki,Doi Toshihiko,Shitara Kohei,Nishikawa Hiroyoshi
Nature immunology
Immune checkpoint blockade has provided a paradigm shift in cancer therapy, but the success of this approach is very variable; therefore, biomarkers predictive of clinical efficacy are urgently required. Here, we show that the frequency of PD-1CD8 T cells relative to that of PD-1 regulatory T (T) cells in the tumor microenvironment can predict the clinical efficacy of programmed cell death protein 1 (PD-1) blockade therapies and is superior to other predictors, including PD ligand 1 (PD-L1) expression or tumor mutational burden. PD-1 expression by CD8 T cells and T cells negatively impacts effector and immunosuppressive functions, respectively. PD-1 blockade induces both recovery of dysfunctional PD-1CD8 T cells and enhanced PD-1 T cell-mediated immunosuppression. A profound reactivation of effector PD-1CD8 T cells rather than PD-1 T cells by PD-1 blockade is necessary for tumor regression. These findings provide a promising predictive biomarker for PD-1 blockade therapies.
10.1038/s41590-020-0769-3
Clonal replacement of tumor-specific T cells following PD-1 blockade.
Nature medicine
Immunotherapies that block inhibitory checkpoint receptors on T cells have transformed the clinical care of patients with cancer. However, whether the T cell response to checkpoint blockade relies on reinvigoration of pre-existing tumor-infiltrating lymphocytes or on recruitment of novel T cells remains unclear. Here we performed paired single-cell RNA and T cell receptor sequencing on 79,046 cells from site-matched tumors from patients with basal or squamous cell carcinoma before and after anti-PD-1 therapy. Tracking T cell receptor clones and transcriptional phenotypes revealed coupling of tumor recognition, clonal expansion and T cell dysfunction marked by clonal expansion of CD8CD39 T cells, which co-expressed markers of chronic T cell activation and exhaustion. However, the expansion of T cell clones did not derive from pre-existing tumor-infiltrating T lymphocytes; instead, the expanded clones consisted of novel clonotypes that had not previously been observed in the same tumor. Clonal replacement of T cells was preferentially observed in exhausted CD8 T cells and evident in patients with basal or squamous cell carcinoma. These results demonstrate that pre-existing tumor-specific T cells may have limited reinvigoration capacity, and that the T cell response to checkpoint blockade derives from a distinct repertoire of T cell clones that may have just recently entered the tumor.
10.1038/s41591-019-0522-3
Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy.
Gide Tuba N,Quek Camelia,Menzies Alexander M,Tasker Annie T,Shang Ping,Holst Jeff,Madore Jason,Lim Su Yin,Velickovic Rebecca,Wongchenko Matthew,Yan Yibing,Lo Serigne,Carlino Matteo S,Guminski Alexander,Saw Robyn P M,Pang Angel,McGuire Helen M,Palendira Umaimainthan,Thompson John F,Rizos Helen,Silva Ines Pires da,Batten Marcel,Scolyer Richard A,Long Georgina V,Wilmott James S
Cancer cell
Cancer immunotherapies provide survival benefits in responding patients, but many patients fail to respond. Identifying the biology of treatment response and resistance are a priority to optimize drug selection and improve patient outcomes. We performed transcriptomic and immune profiling on 158 tumor biopsies from melanoma patients treated with anti-PD-1 monotherapy (n = 63) or combined anti-PD-1 and anti-CTLA-4 (n = 57). These data identified activated T cell signatures and T cell populations in responders to both treatments. Further mass cytometry analysis identified an EOMESCD69CD45RO effector memory T cell phenotype that was significantly more abundant in responders to combined immunotherapy compared with non-responders (n = 18). The gene expression profile of this population was associated with longer progression-free survival in patients treated with single agent and greater tumor shrinkage in both treatments.
10.1016/j.ccell.2019.01.003
Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade: A Systematic Review and Meta-analysis.
JAMA oncology
IMPORTANCE:PD-L1 (programmed cell death ligand 1) immunohistochemistry (IHC), tumor mutational burden (TMB), gene expression profiling (GEP), and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) assays have been used to assess pretreatment tumor tissue to predict response to anti-PD-1/PD-L1 therapies. However, the relative diagnostic performance of these modalities has yet to be established. OBJECTIVE:To compare studies that assessed the diagnostic accuracy of PD-L1 IHC, TMB, GEP, and mIHC/IF in predicting response to anti-PD-1/PD-L1 therapy. EVIDENCE REVIEW:A search of PubMed (from inception to June 2018) and 2013 to 2018 annual meeting abstracts from the American Association for Cancer Research, American Society of Clinical Oncology, European Society for Medical Oncology, and Society for Immunotherapy of Cancer was conducted to identify studies that examined the use of PD-L1 IHC, TMB, GEP, and mIHC/IF assays to determine objective response to anti-PD-1/PD-L1 therapy. For PD-L1 IHC, only clinical trials that resulted in US Food and Drug Administration approval of indications for anti-PD-1/PD-L1 were included. Studies combining more than 1 modality were also included. Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines were followed. Two reviewers independently extracted the clinical outcomes and test results for each individual study. MAIN OUTCOMES AND MEASURES:Summary receiver operating characteristic (sROC) curves; their associated area under the curve (AUC); and pooled sensitivity, specificity, positive and negative predictive values (PPV, NPV), and positive and negative likelihood ratios (LR+ and LR-) for each assay modality. RESULTS:Tumor specimens representing over 10 different solid tumor types in 8135 patients were assayed, and the results were correlated with anti-PD-1/PD-L1 response. When each modality was evaluated with sROC curves, mIHC/IF had a significantly higher AUC (0.79) compared with PD-L1 IHC (AUC, 0.65, P < .001), GEP (AUC, 0.65, P = .003), and TMB (AUC, 0.69, P = .049). When multiple different modalities were combined such as PD-L1 IHC and/or GEP + TMB, the AUC drew nearer to that of mIHC/IF (0.74). All modalities demonstrated comparable NPV and LR-, whereas mIHC/IF demonstrated higher PPV (0.63) and LR+ (2.86) than the other approaches. CONCLUSIONS AND RELEVANCE:In this meta-analysis, tumor mutational burden, PD-L1 IHC, and GEP demonstrated comparable AUCs in predicting response to anti-PD-1/PD-L1 treatment. Multiplex immunohistochemistry/IF and multimodality biomarker strategies appear to be associated with improved performance over PD-L1 IHC, TMB, or GEP alone. Further studies with mIHC/IF and composite approaches with a larger number of patients will be required to confirm these findings. Additional study is also required to determine the most predictive analyte combinations and to determine whether biomarker modality performance varies by tumor type.
10.1001/jamaoncol.2019.1549