Journal Thoracic Oncology

Abstracts Journal of Thoracic Oncology • Volume 12 Issue S1 January 2017
10. Kitazono S, Fujiwara Y, Tsuta K, Utsumi H, Kanda S, Horinouchi H,
Nokihara H, Yamamoto N, Sasada S, Watanabe S, Asamura H, Tamura T, Ohe Y.
Reliability of Small Biopsy Samples Compared With Resected Specimens for
the Determination of Programmed Death-Ligand 1 Expression in Non--Smalldoublet
of gefitinib and TPCA-1, was highly synergistic and abrogated STAT3,
and Src-YAP1-Notch signalling. Implications: Treatment with single EGFR
TKI can no longer be considered adequate for patients with EGFR mutant
NSCLC. Our findings ultimately suggest that a clinical trial evaluating the
co-targeted inhibition of STAT3 and Src is warranted. As a result, STAT3 and
YAP1 mRNA levels could become important predictive biomarkers.References:
We searched PubMed for English language reports published up to December,
2015 using the terms “non-small-cell lung cancer”, “STAT3”, “interleukin-6”,
“NF-κB”, “aldehyde-dehydrogenase (ALDH)”, “integrin-linked kinase (ILK)”,
“glycoprotein 130 (gp130)”, “Src-homology 2 domain-containing phosphatase
2 (SHP2)”, “the complement C1r/C1s, Uegf, Bmp1 (CUB) domain-containing
protein-1 (CDCP1)”, “AXL”, “ephrin type-A receptor-2 (EphA2)”, “Src family
kinases (SFK)”, “YES-associated protein 1 (YAP1)”, “Notch”, “cell migration,
invasion and metastases” and “STAT3 inhibitors”.
Keywords: STAT3, EGFR TKI, YAP1, NSCLC
SESSION MTE24: IMMUNOHISTOCHEMICAL ASSESSMENT
OF BIOMARKERS FOR IMMUNE CHECKPOINT INHIBITORS
(TICKETED SESSION)
WEDNESDAY, DECEMBER 7, 2016 - 07:30-08:30
MTE24.01 IMMUNOHISTOCHEMICAL ASSESSMENT OF
BIOMARKERS FOR IMMUNE CHECKPOINT INHIBITORS
Vera Capelozzi
Pathology, Faculty of Medicine, University of SÃo Paulo, SÃo Paulo/Brazil
Immune checkpoint inhibitors in cancer immunotherapy. Programmed
death receptor-1 (PD-1) is a type 1 membrane protein of the immunoglobulin
superfamily that has an important role in restrincting immune-mediated
tissue danage secondary to inflammation and/or infection (1). The clinical
advantage of antibodies that target either PD-1 or PD-L1 to block this
ligand-receptor interface, allowing cancer killing by T cells became clear
when CTLA4, an antagonist against the T-cell, such as ipilimumab, and
afterward PD-1, showed an increase survival in patients with metastatic
melanoma (2). Clinical investigations in lung cancer have demonstrated the
benefit of PD-1 inhibitors pembrolizumab in advanced non–small cell lung
cancer (NSCLC) and nivolumab in advanced squamous and nonsquamous
NSCLC; both approved as second-line therapies by the US Food and Drug
Administration (FDA) (3-5). Others PD-L1 inhibitors such as atezolizumab and
durvalumab have demonstrated effectiveness in several tumor types (6-7)
but they were not approved for clinical use until now. PD-1 inhibitors induce
around of 20% of complete response frequency in patients with NSCLC, and
persistent response in a subgroup of patients treated by immune checkpoint
inhibitors. Garon et al (3) showed that tumors with PD-L1 expression ≥ 50%
by immunohistochemistry (IHC) were significantly more expected to respond
to pembrolizumab than those with less than 50% malignant cell expression.
In contrast, response rates to nivolumab are significantly greater in patients
with nonsquamous NSCLC, showing ≥ 1% tumor cell positivity (5). These
differences are related to the combination of antibody clone and detection
system as a companion diagnostic for selecting lung cancer patients for
pembrolizumab therapy. Previous investigations reported response taxes
in PD-L1–positive tumors of 31% to 52%, but particularly more than 16% of
PD-L1–negative tumors also showed treatment response (1). This finding
indicates that PD-L1 expression improves for responders but the absence of
expression is not a complete indicator of advantage. PD-L1 expression did not
predict differential response to nivolumab in lung squamous cell carcinoma as
compared with docetaxel (4).
Immunohistochemical Assessment of Immune Checkpoint Inhibitors. PD-L1
in NSCLC is expressed on the membrane of tumor cells, and/or on immune
infiltrating cells dendritic cells, antigen-presenting cells and T lymphocyte.
PD-1, the PDL1 receptor, is expressed on tumor infiltrating lymphocytes,
mainly CD4 T cells, T and B regulatory, NK, monocytes and DC. Concerning
PD-L1 binding, PD-1 inhibits kinases involved in T cell activation. Two potential
mechanisms are involved in expression of immune checkpoints on tumor cells
and their immune stromal component: oncogenic signaling, and response to
inflammatory signals (8). 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 commitment leads to HSP-2 phosphatase
activity which dephosphorylates Pi3K and thus downregulate AKT (8).
The positive score on tumor cells has not been evaluated nor enhanced or
standardized (3; 8). Brambilla and Ming (8) assessed a score of positivity for
prognosis analysis using E1L3N Cell Signaling antibody commercially available.
They 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. There was no prognostic relevance of PD-L1
(tumor cells or stroma) whatever cut off by 10% increment or linear scoring
was used. Only immune PD-L1 expression was correlated with a highly intense
immune infiltrations. 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 different antibodies, cutoffs, patient series, ethnicities and contribution
of oncogene driven cancers, initial resection sample or contemporary biopsy
rendered their interpretation extremely problematic. Global result was
supporting a poor prognosis of “PD-L1 positivity” on tumor cells.
PD-L1 as a Predictive Biomarker for Checkpoint Inhibitors. Most of phase
I trials works with four antibodies targeting PD-1 or its primary ligand PD-
L1, response taxes appear higher in patients with increased tumor PD-L1
membrane expression by IHC. However, different antibody assays, absence
of standardization, different score to determine PD-L1 positivity, companion
test type, and a short number of specimens available for testing, accopled
to the variability of the intervals between biopsy and test, has certainly
disadvantaged the conclusion and prevent consensus to be reached (10). The
best threshold was provided by Garon et al, with ≥ 50% of tumor cells PD-L1
positive to allow the highest response rate of 45% to pembrolizumab (3). In
most trial series, biopsies or resected specimen were used and considerable
difference between these samples occurs due to tumor heterogeneity. The
reliability of small biopsy samples is questioned (10). Indeed lung tumor
heterogeneity is characteristic and PD-L1 is typically heterogeneous in its
distribution in the tumor majority as is PD-L1 positive immune cells. Multiple
questions are still addressed before PD-L1 is considered as a definitive
molecular predictor of effectiveness. 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 best cut off was not revealed.
Conclusion. PDL1 expression predicts response to immune checkpoint
inhibitors. Concordant results showing a better response if PDL1 + in several
trials, using drug specific test and for Nivolumab also histology specific.
We should evaluate membranous staining in tumor sample with at least
100 tumors cells and immune cells. Perspective for upgrading includes:
1) heterogeneity of the expression of PDL1 within tumor, primitive vs
metastases number and size of samples; 2) surgical tissue versus biopsy and 3)
archival versus new biopsy and 4) standardize the assays. Published abstracts
showed high rates of concordance between primary and metastases (81%).
Obtaining multiple biopsies from different areas of the tumor would enhance
the validity of the results of IHC evaluation (160 patients=48% discordance).
References
1. Sholl LM, Aisner DL, Allen TC, Beasley MB, Borczuk AC, Cagle PT, Capelozzi
V, Dacic S, Hariri L, Kerr KM, Lantuejoul S, Mino-Kenudson M, Raparia K,
Rekhtman N, Roy-Chowdhuri S, Thunnissen E, Tsao MS, Yatabe. Programmed
Death Ligand-1 Immunohistochemistry--A New Challenge for Pathologists: A
Perspective From Members of the Pulmonary Pathology Society. Arch Pathol
Lab Med. 2016;140(4):341-4.
2.Couzin-Frankel J. Breakthrough of the year 2013: cancer immunotherapy.
Science 2013;342:1432–1433.
3.Garon EB, Rizvi NA, Hui R, et al. Pembrolizumab for the treatment of non–
small-cell lung cancer. N Engl J Med 2015;372:2018–2028.
4.Brahmer J, Reckamp KL, Baas P, et al. Nivolumab versus docetaxel
in advanced squamous-cell non-small-cell lung cancer. N Engl J Med
2015;373:123–135.
5.Borghaei H, Paz-Ares L, Horn L, et al. Nivolumab versus docetaxel in
advanced nonsquamous non-small-cell lung cancer. N Engl J Med 2015;373:
1627–1639.
6. Herbst RS, Soria JC, Kowanetz M, et al. Predictive correlates of response
to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 2014;
515:563–567.
7.Stewart R, Morrow M, Hammond SA, et al. Identification and
characterization of MEDI4736, an antagonistic anti-PD-L1 monoclonal
antibody. Cancer Immunol Res 2015;3:1052–1062.
8. Brambilla E, Le Teuff G, Marguet S, Lantuejoul S, Dunant A, Graziano S,
Pirker R, Douillard JY, Le Chevalier T, Filipits M, Rosell R, Kratzke R, Popper
H, Soria JC, Shepherd FA, Seymour L, Tsao MS. Prognostic Effect of Tumor
Lymphocytic Infiltration in Resectable Non-Small-Cell Lung Cancer. J Clin
Oncol. 2016;34:1223-30.
9. Soria JC, Marabelle A, Brahmer JR, Gettinger S. Immune checkpoint
modulation for non-small cell lung cancer. Clin Cancer Res. 2015;21: 2256-62.
S90 Journal of Thoracic Oncology • Volume 12 Issue S1 January 2017