Virtual Library

 x 
My Library Virtual Library FAQ

Start Your Search

P. Dennis

Moderator of

  • +

    MS 21 - Immunotherapy Predictive Biomarkers (ID 39)

    • Event: WCLC 2015
    • Type: Mini Symposium
    • Track: Biology, Pathology, and Molecular Testing
    • Presentations: 4
    • +

      MS21.01 - Overview of Immunotherapy (ID 1941)

      14:20 - 14:40  |  Author(s): J.R. Brahmer

      • Abstract
      • Presentation

      Abstract not provided

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

    • +

      MS21.02 - PD1/PDL1 Biomarker Strategies (ID 1942)

      14:40 - 15:00  |  Author(s): E. Brambilla

      • Abstract
      • Presentation

      Abstract:
      Introduction: Cancer cells express antigens that potentially differentiate them from normal cells. These are known to be numerous in lung cancer and characterized by a high mutational rate (7-11 mutations / MegaBase), especially in relation with smoking derived genetic instability, P53 mutations, and/or the presence of targetable mutations in adenocarcinoma. These tumor antigens should confer immunogenicity to lung cancer transformed cells. However, immune-editing occurs in most lung cancer along a three phases sequence: 1) Elimination, where transformed cells are destroyed by the immune system; 2) Equilibrium, equivalent to a functional state of dormancy in which tumor cells growth is controlled by adaptive immunity, a state characterized by typically dense lymphocytic infiltration rich in CD8 cytotoxic cells (E. Brambilla et al. JCO, under review); 3) Escape from immune surveillance. PD-L1 in NSCLC is expressed on the membrane of tumor cells, and/or on immune infiltrating cells dendritic cells (DC), other antigen presenting cells (APC) and T lymphocytes. PD-1, the PDL1 receptor, is expressed on tumor infiltrating lymphocytes (TILS), mainly CD4 T cells, T regulatory (T-reg) and B, NK, monocytes and DC. Upon PD-L1 binding, PD-1 inhibits kinases involved in T cell activation. There are two mechanisms of expression of immune checkpoints on tumor cells and their immune stromal counterparts: oncogenic signaling, and response to inflammatory signals, both of which occur potentially in lung cancer. Tumor cells express multiple ligands and receptors and antitumor immune response can be enhanced by multi-level blockade of immune checkpoints. PD-1/PD-L1 engagement leads to HSP-2 phosphatase activity which dephosphorylates Pi3K and thus downregulate AKT. The necessary patient selection for immunotherapy has stressed the search for predictive biomarker of PD-1/PD-L1 pathway inhibition. The cutoff for positivity on tumor cells[1–3]: The cutoff for positivity in and out of trials on tumor cells has never been assessed nor optimized or standardized. The percentage of PD-L1 membrane staining considered as the cutoff for positivity was from ≥1%, ≥5%, ≥10%, ≥50% and the intensity was or not defined and taking into account (any intensity, 1+, 2+, 3+, or a scale from 1 to 3+/H Score , or 2+3+only). At least, most if not all reports considered only membrane staining on tumor cells, although cytoplasmic staining was also considered with AQUA techniques. Stromal expression of PD-L1 on immune infiltrate (T cells, macrophages, DC) is also needed for scoring. Whereas DC and macrophages display a clear cytoplasmic membrane stain, this is not appreciated on lymphocytes. We have set up a study to assess a cutoff of positivity for prognosis analysis (1500 randomized early stage operable NSCLC patients with or without adjuvant cisplatin therapy after surgery) using E1L3N Cell Signaling antibody commercially available. We found that 20% of lung tumors cell expressed PD-L1 (≥20% intensity 2+3+), and 29% the immune stromal cells (T, macrophages, DC ) ≥10% intensity 2+3+. PD-L1 positivity in both tumor and immune cells were seen in only 9% of NSCLC, 20,7% were both negative . We double-check the scoring cells with Ming Tsao. The best concordance was for intensity 2+ /3+ (83%) although the intensity 1 was not reproducible ( 40%) . There was no prognostic relevance of PD-L1 (tumor cells or stroma) in the control arm and pooled analysis, whatever cutoff by 10% increment or linear scoring was used. There was no statistical correlation between PDL1 expression (Tumor or Immune cells ) with clinicopathological criteria or histology . Only immune PD-L1 expression was correlated with a highly intense immune infiltrations (TILs ) ( P = 002 ). Not surprisingly, previous published evaluations of prognostic value were discordant likely because immune checkpoints modulators play both positive and negative roles in the immune inhibitory pathways with some redundancy, and patients series and assays were not comparable .The two meta-analyses with their numerous biases ( different antibodies, cutoffs, patient series composition in early and advanced stage, ethnicities and contribution of oncogene driven cancers, time of use of the initial resection sample or contemporary biopsy…) rendered their interpretation extremely problematic . Global result was favoring a poor prognosis of “PD-L1 positivity” on tumor cells. PD-L1 expression as a predictive biomarker in cancer immunotherapy[1,4–7]: In the majority of phase I trials with four antibodies targeting the co-inhibitory receptor PD-1 or its primary ligand PD-L1 (Table 1), response rates appear higher in patients with increased tumor PD-L1 membrane expression by immunohistochemistry (IHC). However, different antibody assays, lack of standardization, different cutoff point to determine PD-L1 positivity, the usual various pharmaceutic companies to recommend their companion test, and the small number of specimens available for testing, in addition with the variability of the intervals between biopsy and test, has surely hampered the conclusion and prevent consensus to be reached[7,8]. The most pertinent threshold was provided by Garon et al, with ≥50% of tumor cells PD-L1 positive to allow the highest response rate of 45% in pembrolizumab treated patients in the validation group[1]. In most trial series, biopsies or resected specimen were used restropectively although considerable difference between these samples occurs due to tumor heterogeneity. The reliability of small biopsy samples is questionned[9]. Indeed lung tumor heterogeneity is exemplary , and PD-L1 is typically heterogeneous in its distribution in the tumor bulk as is PD-L1 positive immune cells . Multiple issues are yet addressed before PD-L1 is considered as a robust and definitive molecular predictor of efficacy. Various clones are currently being evaluated in and out of clinical trials (Ventana SP263, SP6242, Dako 28-8 and 22C3, Cell Signaling E1L3N). As for prognostic evaluations, thresholds of ≥1%, ≥5%, ≥10%, ≥50% or continuous H score have been used. In addition in a few trials, PD-L1 expression in TILs was predictive more than PD-L1 on tumor cells but the cutoff was not disclosed. IASLC pathology panel is leading a large multicentric reproducibility study ( Fred Hirsch )with lung pathologists of the IASLC Pathology Committee to address these questions. Alternative regulations of PD-1/PD-L1 pathway The ability of cancer cells to evade immunosurveillance results from the production of immunosuppressive chemokines by the tumor cells, loss of MHC antigen expression, a higher number of T-reg cells in the tumor microenvironment and inhibitory pathways referred to as immune checkpoints, which result in a link of inhibitory ligands to their receptors (CTLA~4~-PD-1, PD-L1/PD-L2-PD-1) are unfrequently upregulated in lung cancer. Moreover immune-editing was associated with the illegitimate expression of tumor germ cell (testis /placenta) antigens[10], normally absent in normal tissue but testis and placenta, inducing a state of immune escape when aberrantly expressed in lung cancer correlating with highly and metastatic aggressive behavior. While patients with PD-L1 overexpression based on different assays, cutoff, tumor material, have more robust response to PD-L1 (67-100% ORR), PD-L1 negative NSCLC ranges from 0 to 15%, suggesting that PD-L1 IHC is not a clear and exclusive predictive biomarker. This is not surprising due to multiple regulations at the two clinically relevant immunologic synapses: the tumor-T cell interface, and the APC-T cell interface, both playing role in tumor control. In all cohorts, PD-L1 in tumor cells was observed with or without immune infiltration. TILs intense infiltration occurred in 10% of NSCLC across histology and was a statistically significant good prognosis factor although the oncogene driven adenocarcinomas lack immune infiltrate. EGFR pathway upregulates PD-L1 as well as PTEN loss[11–14]. In addition the 2 synapses are functionally affected by HLA loss (>50% of NSCLC), EGFR signaling, PTEN loss, the density of CD8 in infiltrate available for cytotoxicity and even more CD8 +/PD1+ exhausted cytotoxic T cells among TILs . The best predictive biomarker might not be simply binary . Biopsies may underevaluate the pertinent tumor-stroma interface , PD-L1 biologically relevant ( more than 1-10% of tumor cell ! ) has already taken place and destroyed the potentially reactive CD8 T cells. Indeed secondary biomarkers may drive the tumor in association or independently of PD-1/PD-L1 pathway. Table 1: Prevalence of PD-L1 in NSCLC:

      Percent tumor samples expressing PD-L1 Tumor surface expression cutoff for positivity PD-L1 detection antibody Reference
      49% 5% 28-8 Grosso et al. JCO, 2013
      52% NR R&D B7-H1 Gatalica et al. Cancer Epidemiology biomarkers prevention, 2014
      95% >10% 5H1 Dong et al. Nature Medicine, 2002
      50% 11% MIH1 Konishi et al. CCR, 2004
      21% (squamous only) >1% vs >5% vs H-score 5H1 Marti et al. JCO, 2014
      60% 5% DAKO IHC Gettinger et al. JCO, 2014
      50% 1% NR Sun et al. JCO, 2014
      25% ≥50% NR Garon et al. NEJM, 2015
      References: 1. Garon EB, et al. Pembrolizumab for the treatment of NSCLC. N Engl J Med. 2015;372(21):2018-2028. 2. Sorensen S, et al. PD-L1 expression and survival among advances NSCLC patients treated with chemotherapy. Ann Oncol. (25 (Supplement 4)). 3. Soria J-C, et al. Clinical activity, safety and biomarkers of PD-L1 blockade in NSCLC: Additional analyses from a clinical study of the engineered antibody MPDL3280A (anti-PDL1). 4. Patel SP, Kurzrock R. PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy. Mol Cancer Ther. 2015;14(4):847-856. 5. Taube JM, et al. Association of PD-1, PD-1 ligands, and other features of the tumor immune microenvironment with response to anti-PD-1 therapy. CCR. 2014;20(19):5064-5074. 6. Herbst RS, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014;515(7528):563-567. 7. Soria J-C, et al. Immune checkpoint modulation for non-small cell lung cancer. CCR. 2015;21(10):2256-2262. 8. Brahmer JR, et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. NEJM. 2012;366(26):2455-2465. 9. Kitazono S, et al. Reliability of Small Biopsy Samples Compared With Resected Specimens for the Determination of PD-L1 Expression in NSCLC. Clin Lung Cancer. 2015. 10. Rousseaux S, et al. Ectopic activation of germline and placental genes identifies aggressive metastasis-prone lung cancers. Sci Transl Med. 2013;5(186):186ra66. 11. Akbay EA, et al. Activation of the PD-1 pathway contributes to immune escape in EGFR-driven lung tumors. Cancer Discov. 2013;3(12):1355-1363. 12. D’Incecco A, Andreozzi M, Ludovini V, et al. PD-1 and PD-L1 expression in molecularly selected NSCLC patients. Br J Cancer. 2015;112(1):95-102. 13. Chen N, et al. Upregulation of PD-L1 by EGFR Activation Mediates the Immune Escape in EGFR-Driven NSCLC: Implication for Optional Immune Targeted Therapy for NSCLC Patients with EGFR Mutation. J Thorac Oncol. 2015 14. Lin C, et al. Programmed Death-Ligand 1 Expression Predicts TKI Response and Better Prognosis in a Cohort of Patients With EGFR Mutation-Positive Lung Adenocarcinoma. Clin Lung Cancer. 2015.

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

    • +

      MS21.03 - Assessment of Immune Cells in Tumor Biopsies as a Biomarker (ID 1943)

      15:00 - 15:20  |  Author(s): I.I. Wistuba, E. Parra, J. Rodrigiuez-Canales

      • Abstract
      • Presentation

      Abstract:
      Multiple genetic and epigenetic changes in several cancer types cause resistance to immune attack of tumors by inducing specific T cells tolerance and by expressing ligands that engage inhibitory receptors and block T cells activation, all resulting on T-cells anergy or exhaustion within the tumor microenvironment (1). In this process, programmed death 1 (PD-1) protein, a T-cell co-inhibitory receptor, and one of its ligands, PD-L1 (B7-H1 or CD274), play a pivotal role in the ability of tumor cells to evade the host’s immune system. Antibody-mediated blockade PD-1/PD-L1 induced durable tumor regression and prolonged disease stabilization in non-small cell carcinoma (NSCLC) (2). Although these studies have reported correlations between PD-L1 immunohistochemical (IHC) expression levels on NSCLC tumor cells and clinical responses to PD-1 and PD-L1 inhibitors, there are patients with negative PD-L1 expression tumors who have showed similar responses than patients with positive expression. Recently, it has been shown that across multiple cancer types, including NSCLC, responses to anti-PD-L1 therapy were observed in patients with tumors expressing high levels of PD-L1, especially when PD-L1 was expressed by tumor-associated infiltrating cells (TAICs). Altogether, these findings suggest that there are other factors in the tumor microenvironment, including tumor infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs) that may drive responses to anti-PD-1/PD-L1 therapies, and be involved in lung cancer pathogenesis and progression. A number of studies have characterized the PD-L1 protein expression by immunohistochemistry (IHC) or immunofluorescence (IF) in all NSCLC stages using formalin-fixed and paraffin-embedded (FFPE) tumor tissues, and correlated those findings with patient’s outcome, and in a limited number of cases with response to immunotherapy (3, 4). Those studies differ on the type of specimens (whole histology sections vs. tissue microarrays [TMAs]), the protein expression analysis (IHC vs. IF), and the quantification assessment (image analysis vs. microscope observation). Only few studies have attempted to correlate the expression of PD-L1 and TAICs, particularly TILs, using a limited number of IHC markers (e.g., CD8, CD45) (5). Up to date, there is no published study in which a comprehensive panel of immune markers, including PD-L1, has been performed attempting to develop a clinical relevant immuno-score system in surgically resected NSCLCs and explore their role as predictive markers of response to immunotherapy. We will present data on the characterization of TAICs in lung cancer tumor specimens using a large panel of markers (PD-L1, PD-1, CD3, CD4, CD8, CD45RO, CD57, Granzyme B, FOXP3, OX-40, and CD68) examined by both uniplex IHC and multiple immunofluorescence (IF) methodologies, and quantitated using image analysis systems (Aperio, Vectra and MultiOmyx). In surgically resected NSCLC tumor tissues the analysis was performed at both peri-tumoral and intra-tumoral compartments, and those data provided interesting data on the spatial distribution of TAICs and the expression of immune checkpoints in lung tumors. Our approach allowed us to devise an immuno-score system for lung cancer tissue specimens using both surgically resected and small diagnostic biopsies (core needle biopsies, CNBs) that correlated with clinical, pathological and molecular features of tumors. References: 1. Mellman I, Coukos G, Dranoff G: Cancer immunotherapy comes of age. Nature 2011, 480:480-9. 2. Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, Leming PD, Spigel DR, Antonia SJ, Horn L, Drake CG, Pardoll DM, Chen L, Sharfman WH, Anders RA, Taube JM, McMiller TL, Xu H, Korman AJ, Jure-Kunkel M, Agrawal S, McDonald D, Kollia GD, Gupta A, Wigginton JM, Sznol M: Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. The New England journal of medicine 2012, 366:2443-54. 3. Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O, Gordon MS, Sosman JA, McDermott DF, Powderly JD, Gettinger SN, Kohrt HE, Horn L, Lawrence DP, Rost S, Leabman M, Xiao Y, Mokatrin A, Koeppen H, Hegde PS, Mellman I, Chen DS, Hodi FS: Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 2014, 515:563-7. 4. Taube JM, Klein A, Brahmer JR, Xu H, Pan X, Kim JH, Chen L, Pardoll DM, Topalian SL, Anders RA: Association of PD-1, PD-1 Ligands, and Other Features of the Tumor Immune Microenvironment with Response to Anti-PD-1 Therapy. Clinical cancer research : an official journal of the American Association for Cancer Research 2014, 20:5064-74. 5. Schalper KA, Brown J, Carvajal-Hausdorf D, McLaughlin J, Velcheti V, Syrigos KN, Herbst RS, Rimm DL. Objective measurement and clinical significance of TILs in non-small cell lung cancer. J Natl Cancer Inst. 2015 Feb 3;107(3).

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

    • +

      MS21.04 - Search for Genetic/Molecular Predictors of Immune Checkpoint Therapy - Role of KRAS, LKB1, Other Genetic Markers as Predictors for Immunotherapy (ID 1944)

      15:20 - 15:40  |  Author(s): S.N. Gettinger

      • Abstract
      • Presentation

      Abstract not provided

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.