PD-L1 IHC in NSCLC with a global and methodological perspective

Development of Ex Vivo Analysis for Examining Cell Composition, Immunological Landscape, Tumor and Immune Related Markers in Non-Small-Cell Lung Cancer

NSCLC is a very aggressive solid tumor, with a poor prognosis due to post-surgical recurrence. Analysis of the specific tumor and immune signatures of NSCLC samples is a critical step in prognostic evaluation and management decisions for patients after surgery. Routine histological assays have some limitations. Therefore, new diagnostic tools with the capability to quickly recognize NSCLC subtypes and correctly identify various markers are needed. We developed a technique for ex vivo isolation of cancer and immune cells from surgical tumor and lung tissue samples of patients with NSCLC (adenocarcinomas and squamous cell carcinomas) and their examination on ex vivo cell preparations and, parallelly, on histological sections after Romanovsky-Giemsa and immunofluorescent/immunochemical staining for cancer-specific and immune-related markers. As a result, PD-L1 expression was detected for some patients only by ex vivo analysis. Immune cell profiling in the tumor microenvironment revealed significant differences in the immunological landscapes between the patients' tumors, with smokers' macrophages with simultaneous expression of pro- and anti-inflammatory cytokines, neutrophils, and eosinophils being the dominant populations. The proposed ex vivo analysis may be used as an additional diagnostic tool for quick examination of cancer and immune cells in whole tumor samples and to avoid false negatives in histological assays.

Current status and progress of PD-L1 detection: guiding immunotherapy for non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths and represents a substantial disease burden worldwide. Immune checkpoint inhibitors combined with chemotherapy are the standard first-line therapy for advanced NSCLC without driver mutations. Programmed death-ligand 1 (PD-L1) is currently the only approved immunotherapy marker. PD-L1 detection methods are diverse and have developed rapidly in recent years, such as improved immunohistochemical detection methods, the application of liquid biopsy in PD-L1 detection, genetic testing, radionuclide imaging, and the use of machine learning methods to construct PD-L1 prediction models. This review focuses on the detection methods and challenges of PD-L1 from different sources, and discusses the influencing factors of PD-L1 detection and the value of combined biomarkers. Provide support for clinical screening of immunotherapy-advantage groups and formulation of personalized treatment decisions.

Detection of PD‑L1 expression and epithelial‑mesenchymal transition of circulating tumor cells in non‑small cell lung cancer

The present study aimed to assess the roles of peripheral circulating tumor cell (CTC) count, CTC subtypes and programmed death ligand 1 (PD-L1) expression in the clinical staging and prognosis of patients with non-small cell lung cancer (NSCLC). A total of 100 patients with NSCLC with available tumor tissues were enrolled in the present study, and 7.5 ml peripheral blood was collected. Patients were divided into PD-L1-positive and PD-L1-negative groups according to PD-L1 immunohistochemical staining. Peripheral blood samples from both groups were analyzed to determine the CTC count, epithelial-type CTCs (E-CTCs), mesenchymal-type CTCs (M-CTCs) and PD-L1 expression. Clinical data were collected, and patients were followed up for a maximum of 36 months, with patient death as the endpoint event. Patients with PD-L1-positive tumors had a worse prognosis compared with those with PD-L1-negative tumors (P=0.045). The PD-L1-positive group exhibited significantly higher numbers of CTCs and M-CTCs compared with the PD-L1-negative group (P≤0.05). However, the number of E-CTCs did not differ significantly between the two groups (P>0.05). PD-L1-positive patients with higher CTC and M-CTC counts had relatively poorer prognoses (P≤0.05), while the number of E-CTCs had no significant effect on prognosis (P>0.05). Compared with the early-stage NSCLC group, the late-stage NSCLC group exhibited a significant increase in the CTC count (P≤0.05), while E-CTC and M-CTC counts did not significantly differ between the two groups (P>0.05). The PD-L1-positive group exhibited a significant increase in the number of PD-L1+ CTCs and PD-L1+ M-CTCs compared with the PD-L1-negative group (P≤0.05), while PD-L1+ E-CTC counts did not differ significantly between the two groups (P>0.05). The PD-L1-positive patients with a higher number of PD-L1+ CTCs and PD-L1+ M-CTCs had relatively poorer prognoses (P≤0.05), while the PD-L1+ E-CTC count had no significant effect on prognosis (P>0.05). Compared with the early-stage NSCLC group, the late-stage NSCLC group exhibited a significant increase in the number of PD-L1+ CTCs and PD-L1+ M-CTCs (P≤0.05), while PD-L1+ E-CTC counts did not significantly differ between the two groups (P>0.05). Based on univariate and multivariate analyses, the number of PD-L1+ M-CTCs was identified as an independent prognostic factor for NSCLC. In conclusion, the presence of CTCs in peripheral blood, particularly PD-L1+ M-CTC subtype, indicated poorer clinical staging and prognosis in patients with NSCLC. These findings suggested that CTCs, specifically the PD-L1+ M-CTC subtype, could serve as a monitoring indicator for the clinical staging and prognosis of patients with NSCLC.

Predictive Value of Combined Positive Score and Tumor Proportion Score for Immunotherapy Response in Advanced NSCLC

Introduction

In advanced-stage NSCLC, tumor proportion score (TPS) is typically used to predict the efficacy of immune checkpoint inhibitors (ICIs). Nevertheless, in other cancer types, the combined positive score (CPS), which covers programmed death-ligand 1 (PD-L1) expression on both tumor and surrounding immune cells, is used. We investigated the predictive value of CPS in comparison to TPS in advanced NSCLC.

Methods

A monocenter, retrospective study was performed in patients with advanced NSCLC treated with ICI monotherapy between 2015 and 2021. Hematoxylin and eosin and PD-L1 were stained on baseline tumor biopsy samples to score PD-L1 by both TPS and CPS. Positivity for TPS and CPS was defined as a score of 1% or above. Progression-free survival and overall survival (OS) were assessed for TPS and CPS scores.

Results

Among the 187 included patients, PD-L1 positivity was found in 112 patients (59.9%) by TPS and 135 patients (72.2%) by CPS. There was no significant difference in OS between TPS- and TPS+ patients (p = 0.20). Nevertheless, CPS+ patients did have a longer OS than CPS- patients (p = 0.006). OS was superior in both TPS-/CPS+ and TPS+/CPS+ as compared with TPS-/CPS- cases (p = 0.018 and p = 0.015, respectively), whereas no considerable differences in OS were found between TPS-/CPS+ and TPS+/CPS+ cases.

Conclusions

This retrospective real-world population study revealed that CPS differentiated OS better than TPS in patients with advanced NSCLC with ICI monotherapy. Remarkably, this was driven by the performance of the TPS-/CPS+ subgroup, indicating that CPS may be a better predictive biomarker for ICI efficacy.

Automating Access to Real World Evidence

Introduction

Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process. Whereas NLP offers a faster solution than manual methods of extraction, the validity of extracted data remains in question. The current study compared manual and automated data extraction from the EHR of patients with advanced lung cancer.

Methods

Previously, we extracted EHRs from 1209 patients diagnosed with advanced lung cancer (stage IIIB or IV) between January 2015 and December 2017 at Princess Margaret Cancer Centre (Toronto, Canada) using the commercially available artificial intelligence engine, DARWEN (Pentavere, Ontario, Canada). For comparison, 100 of 333 patients that received systemic therapy were randomly selected and clinical data manually extracted by two trained abstractors using the same accepted gold standard feature definitions, including patient, disease characteristics, and treatment data. All cases were re-reviewed by an expert adjudicator. Accuracy and concordance between automated and manual methods are reported.

Results

Automated extraction required considerably less time (<1 day) than manual extraction (∼225 person-hr). The collection of demographic data (age, sex, diagnosis) was highly accurate and concordant with both methods (96%–100%). Accuracy (for either extraction approach) and concordance were lower for unstructured data elements in EHR, such as performance status, date of diagnosis, and smoking status (NLP accuracy: 88%–94%; Manual accuracy: 78%–94%; concordance: 71%–82%). Concurrent medications (86%–100%) and comorbid conditions (96%–100%), were reported with high accuracy and concordance. Treatment details were also accurately captured with both methods (84%–100%) and highly concordant (83%–99%). Detection of whether biomarker testing was performed was highly accurate and concordant (96%–98%), although detection of biomarker test results was more variable (accuracy 84%–100%, concordance 84%–99%). Features with syntactic or semantic variation requiring clinical interpretation were extracted with slightly lower accuracy by both NLP and manual review. For example, metastatic sites were more accurately identified through NLP extraction (NLP: 88%–99%; manual: 71%–100%; concordance: 70%–99%) with the exception of lung and lymph node metastases (NLP: 66%–71%; manual: 87%–92%; concordance: 58%) owing to analogous terms used in radiology reports not being included in the accepted gold standard definition.

Conclusions

Automated data abstraction from EHR is highly accurate and faster than manual abstraction. Key challenges include poorly structured EHR and the use of analogous terms beyond the accepted gold standard definition. The application of NLP can facilitate real-world evidence studies at a greater scale than could be achieved with manual data extraction

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

BACKGROUND

Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications.

MATERIALS AND METHODS

Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values.

RESULTS

Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples.

CONCLUSIONS

Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

False-negative programmed death-ligand 1 immunostaining in ethanol-fixed endobronchial ultrasound-guided transbronchial needle aspiration specimens of non-small-cell lung cancer patients

AIMS

Programmed death-ligand 1 (PD-L1) immunostaining is used to predict which non-small-cell lung cancer (NSCLC) patients will respond best to treatment with programmed cell death protein 1/PD-L1 inhibitors. PD-L1 immunostaining is sometimes performed on alcohol-fixed cytological specimens instead of on formalin-fixed paraffin-embedded (FFPE) biopsies or resections. We studied whether ethanol prefixation of clots from endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) results in diminished PD-L1 immunostaining as compared with formalin fixation.

METHODS AND RESULTS

FFPE cell blocks from EBUS-TBNA specimens of 54 NSCLC patients were identified. For each case, paired samples were available, consisting of clots directly immersed in formalin and clots prefixed in Fixcyt (50% ethanol). Serial sections were immunostained for PD-L1 by use of the standardised SP263 assay and the 22C3 antibody as a laboratory-developed test (LDT). PD-L1 positivity was determined with two cut-offs (1% and 50%). Concordance of PD-L1 positivity between the formalin-fixed (gold standard) and ethanol-prefixed material was assessed. When the 22C3 LDT was used, 30% and 36% of the ethanol-prefixed specimens showed false-negative results at the 1% and 50% cut-offs, respectively (kappa 0.64 and 0.68). When SP263 was used, 22% of the ethanol-prefixed specimens showed false-negative results at the 1% cut-off (kappa 0.67). At the 50% cut-off, concordance was higher (kappa 0.91), with 12% of the ethanol-prefixed specimens showing false-negative results.

CONCLUSION

Ethanol fixation of EBUS-TBNA specimens prior to formalin fixation can result in a considerable number of false-negative PD-L1 immunostaining results when a 1% cut-off is used and immunostaining is performed with SP263 or the 22C3 LDT. The same applies to use of the 50% cut-off when immunostaining is performed with the 22C3 LDT.

Programmed death ligand-1 (PD-L1) as a predictive marker for immunotherapy in solid tumours: a guide to immunohistochemistry implementation and interpretation

Immunotherapy with checkpoint inhibitors is well established as an effective treatment for non-small cell lung cancer and melanoma. The list of approved indications for treatment with PD-1/PD-L1 checkpoint inhibitors is growing rapidly as clinical trials continue to show their efficacy in patients with a wide range of solid tumours. Clinical trials have used a variety of PD-L1 immunohistochemical assays to evaluate PD-L1 expression on tumour cells, immune cells or both as a potential biomarker to predict response to immunotherapy. Requests to pathologists for PD-L1 testing to guide choice of therapy are rapidly becoming commonplace. Thus, pathologists need to be aware of the different PD-L1 assays, methods of evaluation in different tumour types and the impact of the results on therapeutic decisions. This review discusses the key practical issues relating to the implementation of PD-L1 testing for solid tumours in a pathology laboratory, including evidence for PD-L1 testing, different assay types, the potential interchangeability of PD-L1 antibody clones and staining platforms, scoring criteria for PD-L1, validation, quality assurance, and pitfalls in PD-L1 assessment. This review also explores PD-L1 IHC in solid tumours including non-small cell lung carcinoma, head and neck carcinoma, triple negative breast carcinoma, melanoma, renal cell carcinoma, urothelial carcinoma, gastric and gastroesophageal carcinoma, colorectal carcinoma, hepatocellular carcinoma, and endometrial carcinoma. The review aims to provide pathologists with a practical guide to the implementation and interpretation of PD-L1 testing by immunohistochemistry.

Sarcopenia and high NLR are associated with the development of hyperprogressive disease after second-line pembrolizumab in patients with non-small-cell lung cancer

The aim of this multi-center retrospective study was to evaluate the incidence of hyperprogressive disease (HPD) after second-line treatment with pembrolizumab in patients (n = 167) with metastatic non-small-cell lung cancer (NSCLC) whose tumors expressed programmed cell death ligand 1 (PD-L1) in ≥ 1% and to search for hematological and imaging biomarkers associated with its development. Prior to chemotherapy, neutrophil : lymphocyte ratio (NLR1) and platelet : lymphocyte ratio (PLR1), and prior to immunotherapy, NLR2 and PLR2 were retrospectively analyzed. The psoas major muscle area (PMMA) was calculated at the L3 position on computed tomography before chemotherapy (PMMA1) and before immunotherapy (PMMA2) (n = 112). Patients with ∆PMMA (1-PMMA2/PMMA1) × 100 ≥ 10% were considered to have sarcopenia (low muscle mass). After treatment with pembrolizumab on the first computerized tomography (CT) scan evaluation, patients were subdivided as follows as: hyperprogressors (HPs), progressors (Ps), non-progressors (NPs) and pseudoprogressors (PPs). HPs had significantly higher ∆PMMA levels, NLR2 and PLR2 than the other patients. Moreover, in multinomial logistic regression analysis, higher levels of ∆PMMA were associated with a decreased likelihood of being a P [odds ratio (OR) = 0·81; 95% confidence interval (CI) = 0·65-0·99; P = 0·047] or an NP (OR = 0·76; 95% CI = 0·62-0·94; P = 0·012) versus an HP. Higher NLRs tended to decrease the likelihood of being a P versus an HP (OR = 0·66; 95% CI = 0·42-1·06; P = 0·09) and significantly decreased the likelihood of being an NP versus an HP (OR = 0·44; 95% CI = 0·28-0·69; P < 0·0001). Our data suggest that a high pre-immunotherapy NLR2 and the presence of sarcopenia are potential risk factors for the development of HPD.

PD-L1 in Lung Adenocarcinoma: Insights into the Role of 18F-FDG PET/CT

Purpose

This study aimed to evaluate the role of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) in expression of tumor programmed death ligand-1 (PD-L1) expression and prognostic significance of ¹⁸F-FDG PET/CT at different PD-L1 status in patients with lung adenocarcinoma.

Patients and Methods

Seventy-three patients with primary lung adenocarcinoma who received ¹⁸F-FDG PET/CT before treatment were retrospectively included in this study. Expression of tumor PD-L1, programmed death-1 (PD-1) and glucose metabolic parameters were evaluated.

Results

Tumor PD-L1 expression was positively correlated with maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), hexokinase II (HK-II) and glucose transporter 1 (GLUT-1) (P<0.0001 for all). SUVmax was a unique independent predictor of tumor PD-L1 expression, with an optimal cut-off value of 9.5. For all the patients, tumor stage (P<0.001) and SUVmax (P=0.009) were independent prognostic indicators of disease-free survival (DFS)/progression-free survival (PFS) while carcino-embryonic antigen (CEA) (P=0.003), Ki67 (P=0.042), PD-L1 (P=0.048) and TLG (P=0.004) were independent prognostic indicators of overall survival (OS). Tumor stage (P=0.004) and SUVmax (P=0.022) were independent prognostic indicators of DFS/PFS while TLG (P=0.012) and CEA (P=0.045) were independent prognostic indicators of OS in the PD-L1-positive group. In the PD-L1-negative group, tumor stage (P=0.002) and CEA (P=0.006) were unique independent prognostic indicators of DFS/PFS and OS, respectively.

Conclusion

¹⁸F-FDG PET/CT may potentially predict tumor PD-L1 expression and play a role in predicting prognosis of PD-L1/PD-1 immunotherapy in lung adenocarcinoma.

Influence of preanalytical variables on performance of delta-like protein 3 (DLL3) predictive immunohistochemistry

DLL3 might become a predictive immunohistochemical marker in small cell carcinoma of the lung (SCLC). We investigated the influence of pre-analytical handling of samples on the performance of DLL3 immunohistochemistry (IHC) using DLL3 SP347 ready to use assay (Ventana). DLL3 positive cell lines were subjected to different experimental conditions mimicking the pre-analytical variation in daily clinical practice. Formalin fixation of 24 h led to the most optimal results of DLL3 IHC. Longstanding fixation in Cytolyt, methanol-based fixative for cytology samples, but also decalcification using a mix of formic- and hydrochloracid resulted in decreased DLL3 staining. Postponed staining of blanc slides for 3 months also decreased DLL3 IHC. Postponed fixation of the SCLC cell lines did not influence the performance of DLL3 IHC, although this might be different in the tissues than in the cell lines. In conclusion, different pre-analytical variables decrease the performance of DLL3 IHC. These findings are essential for implementing novel predictive immunohistochemical biomarkers in daily pathology practice.

Tumor microenvironment predicts local tumor extensiveness in PD-L1 positive nasopharyngeal cancer

Tumor microenvironment have been implicated in many kind of cancers to hold an important role in determining treatment success especially with immunotherapy. In nasopharyngeal cancer, the prognostic role of this immune cells within tumor microenvironment is still doubtful. We conducted a study that included 25 nasopharyngeal cancer biopsy specimens to seek a more direct relationship between tumor infiltrating immune cells and tumor progression. Apart from that, we also checked the PD-L1 protein through immunohistochemistry. The PD-L1 was positively expressed in all our 25 samples with nasopharyngeal cancer WHO type 3 histology. Majority samples have >50% PD-L1 expression in tumor cells. We also found that denser local tumor infiltrating immune cells population have relatively much smaller local tumor volume. The inverse applied, with the mean local tumor volumes were 181.92 cm3 ± 81.45 cm3, 117.13 cm3 ± 88.72 cm3, and 55.13 cm3 ± 25.06 cm3 for mild, moderate, and heavy immune cells infiltration respectively (p = 0.013). Therefore, we concluded that tumor infiltrating immune cells play an important role in tumor progression, hence evaluating this simple and predictive factor may provide us with some valuable prognostic information.

Quantification of PD-L1 Expression with 18F-BMS-986192 PET/CT in Patients with Advanced-Stage Non-Small Cell Lung Cancer

The aim of this work was to quantify the uptake of ¹⁸F-BMS-986192, a programmed cell death ligand 1 (PD-L1) adnectin PET tracer, in patients with non-small cell lung cancer. To this end, plasma input kinetic modeling of dynamic tumor uptake data with online arterial blood sampling was performed. In addition, the accuracy of simplified uptake metrics such as SUV was investigated. Methods: Data from a study with ¹⁸F-BMS-986192 in patients with advanced-stage non-small cell lung cancer eligible for nivolumab treatment were used if a dynamic scan was available and lesions were present in the field of view of the dynamic scan. After injection of ¹⁸F-BMS-986192, a 60-min dynamic PET/CT scan was started, followed by a 30-min whole-body PET/CT scan. Continuous arterial and discrete arterial and venous blood sampling were performed to determine a plasma input function. Tumor time-activity curves were fitted by several plasma input kinetic models. Simplified uptake parameters included tumor-to-blood ratio as well as several SUV measures. Results: Twenty-two tumors in 9 patients were analyzed. The arterial plasma input single-tissue reversible compartment model with fitted blood volume fraction seems to be the most preferred model as it best fitted 11 of 18 tumor time-activity curves. The distribution volume (V _T ) ranged from 0.4 to 4.8 mL⋅cm^-3 Similar values were obtained with an image-derived input function. From the simplified measures, SUV normalized for body weight at 50 and 67 min after injection correlated best with V _T , with an R ² of more than 0.9. Conclusion: A single-tissue reversible model can be used to quantify tumor uptake of the PD-L1 PET tracer ¹⁸F-BMS-986192. SUV at 60 min after injection, normalized for body weight, is an accurate simplified parameter for uptake assessment of baseline studies. To assess its predictive value for response evaluation during programmed cell death protein 1 or PD-L1 immune checkpoint inhibition, further validation of SUV against V _T based on an image-derived input function is recommended.

External quality assessment demonstrates that PD-L1 22C3 and SP263 assays are systematically different

PD‐L1 inhibitors are part of first line treatment options for patients with advanced non‐small cell lung cancer. PD‐L1 immunohistochemistry (IHC) assays act as either a companion or a complementary diagnostic. The purpose of this study is to describe the experience of external quality assurance (EQA) provider UK NEQAS ICC and ISH with the comparison of different PD‐L1 assays used in daily practice. Three EQA rounds (pilot, run A and run B) were carried out using formalin fixed paraffin embedded samples with sample sets covering a range of epitope concentrations, including ‘critical samples’ near to clinical threshold cut‐offs. An expert panel (n = 4) evaluated all returned slides simultaneously and independently on a multi‐header microscope together with the participants own in‐house control material. The tonsil sample was evaluated as ‘acceptable’ or ‘unacceptable’, and for the other samples the percentage of PD‐L1 stained tumour cells were estimated in predetermined categories (<1%, 1 to <5%, 5 to <10%, 10 to <25%, 25 to <50%, 50 to <80%, 80 to 100%). In the pilot and the two subsequent runs the number of participating laboratories was 43, 69 and 76, respectively. The pass rate for the pilot run was 67%; this increased to 81% at run A and 82% at run B. For two ‘critical samples’, in runs A and B, 22C3 IHC had significantly higher PD‐L1 expression than SP263 IHC (p < 0.001), whilst the PD‐L1 scores for the other six samples were similar for all assays. In run A the laboratory developed tests (LDTs) using 22C3 scored lower than the commercial 22C3 tests (p = 0.01). After the initial testing, improvement in performance of PD‐L1 IHC is shown for approved and LDT PD‐L1 assays. Equivalency of approved PD‐L1 22C3 and SP263 assays cannot be assumed as the scores cross the clinically relevant thresholds of 1% and 50% PD‐L1 expression.

Multicentre study on the consistency of PD-L1 immunohistochemistry as predictive test for immunotherapy in non-small cell lung cancer

AIMS

Investigate the impact of interlaboratory- and interobserver variability of immunohistochemistry on the assessment of programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC).

METHODS

Two tissue microarrays (TMAs) were constructed from 50 (TMA-A) and 51 (TMA-B) resected NSCLC cases, and distributed among eight centres. Immunostaining for PD-L1 was performed using Agilent's 22C3 pharmDx Assay (pharmDx) and/or a 22C3 laboratory developed test (LDT). The interlaboratory variability of staining- and interobserver variability of scoring for PD-L1 were assessed in selected critical samples (samples at the cut-off of positivity) and non-critical samples. Also, PD-L1 epitope deterioration in time in stored unstained slides was analysed. Krippendorff's alpha values (0=maximal, 1=no variability) were calculated as measure for variability.

RESULTS

For interlaboratory variability of immunostaining, the percentage of PD-L1 positive cases among centres ranged 40%-51% (1% cut-off) and 23%-30% (50% cut-off). Alpha values at 1% cut-off were 0.88 (pharmDx) and 0.87 (LDT) and at 50% cut-off 0.82 (pharmDx) and 0.95 (LDT). Interobserver variability of scoring resulted in PD-L1 positive cases ranging 29%-55% (1% cut-off) and 14%-30% (50% cut-off) among pathologists. Alpha values were at 1% cut-off 0.83 (TMA-A) and 0.66 (TMA-B), and at 50% cut-off 0.77 (TMA-A) and 0.78 (TMA-B). Interlaboratory variability of staining was higher (p<0.001) in critical samples than in non-critical samples at 50% cut-off. Furthermore, PD-L1 epitope deterioration in unstained slides was observed after 12 weeks.

CONCLUSIONS

The results provide insight in factors contributing to variability of immunohistochemical assessment of PD-L1, and contribute to more reliable predictive testing for PD-L1.

Programmed Death Ligand 1 (PD-L1) as a Predictive Biomarker for Pembrolizumab Therapy in Patients with Advanced Non-Small-Cell Lung Cancer (NSCLC)

Recently, immunotherapy has been shown to be an effective and helpful therapeutic option for the treatment of advanced non-small-cell lung cancer (NSCLC). The activity of antitumor T cells may be restored through the checkpoint blockade using anti-programmed death 1 or anti-programmed death ligand 1 (PD-L1) antibodies, showing, in several cancer patients, an increased progression-free survival and overall survival compared with classical chemotherapy. As recently shown by several studies, the PD-L1 expression levels in tumors may offer a selection criterion for patients to predict their immunotherapy response. In particular, NSCLC patients with high tumor PD-L1 levels (proportional score ≥ 50% for first-line therapy and ≥ 1% for second-line treatment, respectively) showed better response rates to immunotherapy and longer survival in first-line therapy compared with conventional chemotherapy. PD-L1, whose expression is evaluated by using immunohistochemistry analysis, is currently the only biomarker approved for clinical use in the first- and second-line monotherapy setting and therefore plays a central role in treatment decision-making for patients with advanced NSCLC. In this review we will discuss the key role of PD-L1 as a predictive biomarker of response to pembrolizumab therapy in NSCLC patients by describing the appropriate techniques and methodologies for immunohistochemical evaluation of PD-L1 expression and providing an overview of the clinical studies supporting its predictive significance.

Impact of delayed and prolonged fixation on the evaluation of immunohistochemical staining on lung carcinoma resection specimen

Pre-analytical factors, such as fixation time, influence morphology of diagnostic and predictive immunohistochemical staining, which are increasingly used in the evaluation of lung cancer. Our aim was to investigate if variations in fixation time influence the outcome of immunohistochemical staining in lung cancer. From lung resections, specimen with tumor size bigger than 4 cm, 10 samples were obtained: 2 were put through the standard fixation protocol, 5 through the delayed, and 3 through the prolonged fixation protocol. After paraffin embedding, tissue microarrays (TMAs) were made. They were stained with 20 antibodies and scored for quality and intensity of staining. Samples with delay in fixation showed loss of TMA cores on glass slides and deterioration of tissue quality leading to reduction in the expression of CK 7, Keratin MNF116, CAM 5.2, CK 5/6, TTF-1, C-MET, Napsin A, D2-40, and PD-L1. Prolonged fixation had no influence on the performance of immunohistochemical stains. Delay of fixation negatively affects the expression of different immunohistochemical markers, influencing diagnostic (cytokeratins) and predictive (PD-L1) testing. These results emphasize the need for adequate fixation of resection specimen.

Next-generation protein analysis in the pathology department

Traditionally, immunohistochemistry (IHC) is used by pathologists to localise specific proteins or peptides in tissue slides. In the era of personalised medicine, however, molecular tissue analysis becomes indispensable for correct diagnosis, prognosis and therapeutic decision, not only on the DNA or mRNA level but also on the protein level. Combining molecular information with imaging presents many advantages. Therefore, matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) is a promising technique to be added to the armamentarium of the pathologist. Here, we focus on the workflow, advantages and drawbacks of both MALDI IMS and IHC. We also briefly discuss a few other protein imaging modalities and give examples of applications.

Positive PD-L1 expression is predictive for patients with advanced EGFR wild-type non-small cell lung cancer treated with gemcitabine and cisplatin

This retrospective study aimed to investigate the association between programmed death ligand-1 (PD-L1) expression and the clinicopathological characteristics of patients with advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC). The predictive role and cut-off value of PD-L1 expression was subsequently investigated. A total of 172 patients with advanced EGFR wild-type NSCLC were enrolled. All patients received platinum-based doublet chemotherapy (gemcitabine plus cisplatin). PD-L1 expression in lung tissues was assessed using immunohistochemical methods. The χ² test was used to analyze the association between PD-L1 expression and clinicopathological characteristics. Survival time analysis was performed using the Kaplan-Meier method. The two groups, positive PD-L1 expression and negative PD-L1 expression, were compared using the log-rank test. Multivariate analysis using the Cox proportional hazard regression model was conducted to determine prognostic factors for overall survival (OS) and progression-free survival (PFS) times. Positive PD-L1 expression was observed in 48.3% (84/172), 40.7% (70/172), 21.5% (37/172) and 8.1% (14/172) of patients when using cut-off values of 1, 5, 10 and 50%, respectively. The χ² test revealed that elevated pretreatment C-reactive protein (CRP) level and cancer stage IV were significantly associated with positive PD-L1 expression. The OS and PFS of positive PD-L1 (1, 5, 10 and 50% cut-off) expression group were shorter compared with the negative PD-L1 (1, 5, 10 and 50% cut-off) expression group. Multivariate survival analysis revealed that PD-L1 expression ≥50% was significantly associated with decreased OS and PFS [OS time, P=0.001; hazard ratio (HR), 2.768; 95% confidence interval (CI), 1.551–4.940; PFS time, P=0.002; HR, 2.537; 95% CI, 1.423–4.524]. These results indicated that positive PD-L1 (50% cut-off) expression was an independent predictor of poor prognosis for patients with advanced NSCLC treated with gemcitabine plus cisplatin. PD-L1 expression was associated with CRP level and cancer stage. The results obtained in the present study suggest that positive PD-L1 expression serves a prognostic role in advanced NSCLC and that the optimal cut-off value may be 50%.

Gr-MDSC-linked asset as a potential immune biomarker in pretreated NSCLC receiving nivolumab as second-line therapy

PURPOSE

Immunotherapy is a new standard first-line treatment for non-small cell lung cancers (NSCLC) with high programmed cell death-ligand 1 (PD-L1) expression (≥ 50%) and second-line treatment regardless of PD-L1 status, though not all patients benefit from this approach. Much effort is ongoing to identify robust prognostic and predictive biomarkers of response to immune checkpoint inhibitors, overcoming PD-L1 that appears limited in its ability to discriminate patient candidates to this new class of anticancer agents. The purpose of this research study is to identify potential new biomarkers for immunotherapy in lung cancer.

METHODS

Fifty-three consecutive patients with advanced NSCLC treated with nivolumab were enrolled in the study. All the patients received a blood analysis looking for the relationship between different populations of baseline white blood cells and granulocytic myeloid-derived suppressor cells (Gr-MDSC) detected by flow cytometry, to identify and characterize patients with poor likelihood of benefit from nivolumab in NSCLC second-line setting, regardless of clinical feature and PDL1 expression.

RESULTS

Univariate analysis showed that high baseline levels of Gr-MDSC and low baseline CD8/Gr-MDSC ratio are associated with significantly better (P = 0.02) response to immunotherapy treatment. Log-rank tests suggested a significant improvement in OS and PFS with high baseline levels of Gr-MDSC levels (≥ 6 cell/μl), low absolute neutrophil count (< 5840/μl), high eosinophil count (> 90 /μl), and NLR < 3. The multivariate analysis showed a statistically significant improvement for PFS (P = 0.003) and OS (P = 0.05) in favour of the identified good prognostic Gr-MDSC-linked asset group, compared with the poor prognosis group.

CONCLUSION

The role of Gr-MDSC appears interesting as a potential biomarker in NSCLC patients receiving immune-checkpoint inhibitors. Further analyses are needed to confirmed and study in deep the role of these particular cells and their role in cancer response and progression during ICI therapy.

Targeting Immune Checkpoints in Lung Cancer: Current Landscape and Future Prospects

Lung cancer is the most prevalent and deadly cancer worldwide. Immune checkpoint therapy, which targets regulatory pathways in T cells to boost anti-tumor immune response, has revolutionized lung cancer treatment paradigms. Inhibitors of the most established immune checkpoints such as programmed death-1 (PD-1)/PD-ligand 1 (PD-L1) have been approved by the US Food and Drug Administration in the management of lung cancer. Despite the pronounced survival benefits that have been seen with immune checkpoint inhibitors, not all lung cancer patients respond to single-agent immunotherapy due to the complexity of the immune microenvironment and tumor resistance. Alternative immune checkpoints beyond PD-1/PD-L1 must be sought so that more patients can benefit from immune checkpoint therapy. Additionally, novel combination strategies of immunotherapy and conventional treatments (e.g., chemotherapy, radiotherapy, and targeted therapy) have shown promise in some clinical trials. Meanwhile, identification of predictive biomarkers is pivotal in selecting eligible patients for immunotherapy and to guide individualized clinical decision-making. The future of immune checkpoint therapy in lung cancer is not devoid of challenges, and more prospective clinical studies are awaited to translate our understanding from bench to bedside.

Programmed cell death ligand 1 expression in cytologic and surgical non-small cell lung carcinoma specimens from a single institution: Association with clinicopathologic features and molecular alterations

BACKGROUND

Programmed cell death ligand 1 (PD-L1) expression by the 22C3 pharmDx companion assay has been validated in surgical specimens to support pembrolizumab treatment decisions for patients with non-small cell lung carcinoma (NSCLC). The aims of this study were 1) to assess the adequacy of cytologic specimens for PD-L1 evaluation and 2) to explore correlations of PD-L1 expression with clinicopathologic and molecular features.

METHODS

The study cohort included 100 cytology specimens (fluid [n = 28] and fine-needle aspiration [n = 72]) and 165 surgical specimens (biopsy [n = 138] and resection [n = 27]). The PD-L1 immunohistochemistry 22C3 assay and staining assessment were performed according to the manufacturer's instructions. PD-L1 expression was correlated with patients' demographics, pathologic characteristics, and molecular alterations.

RESULTS

One hundred forty-two specimens (53.6%) were positive for PD-L1 expression (≥1%). No statistically significant difference in PD-L1 expression was identified between cytologic (56.0%) and surgical specimens (52.1%). Seventy-four of 190 tested cases (38.9%) had genetic alterations. PD-L1 positivity was significantly more prevalent in cases with genetic alterations than in cases without genetic alterations. Furthermore, both PD-L1 positivity and high PD-L1 expression (≥50%) had statistically significant associations with Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations. PD-L1 expression had no significant association with histologic phenotypes or other clinicopathologic features.

CONCLUSIONS

The data indicate that cytologic specimens are comparable to surgical specimens for PD-L1 evaluation. The association of PD-L1 expression with KRAS mutations may have clinical relevance in selecting patients with NSCLC for immunotherapy.

The frequency of high PD-L1 expression is low in lung adenocarcinoma patients from Northeast Brazil

Background

As Immune checkpoint inhibitors (ICPIs) are changing the standard-care in lung cancer with good clinical activities and durable responses, its indication must be based on the appropriate patient selection once only a fraction of patients has a response to these costly drugs. In larger cohorts the expression of programmed cell death–ligand 1 (PD-L1) has been associated with good clinical response of ICPIs in lung adenocarcinoma where the rate of high PD-L1 expression (defined as PD-L1tumor proportion score ≥ 50%) is ~ 30%, but once rare studies are available addressing the frequency of PD-L1 in populations outside those cohorts, we aimed to report the prevalence of PD-L1 and the frequency of patients with high PD-L1 expression utilizing data from a major pathology laboratory in Northeastern Brazil.

Methods

We retrospectively evaluated the PD-L1 expression in 158 surgically resected primary lung adenocarcinoma including 158 with anaplastic lymphoma kinase (ALK) expression. PD-L1 and ALK expression were evaluated by immunohistochemical analysis with the SP263 and D5F3 assays, respectively.

Results

Of the 158 samples analyzed, 94 (59.5%) had a PD-L1 tumor proportion score (TPS) < 1%, 38 (24.0%) had a PD-L1 TPS of 1–49% and 26 (16.5%) had a PD-L1 TPS of ≥50%. ALK expression was detected in 21 (13.3%) of the 158 tumor samples and 5 (3.2%) of them had a PD-L1 TPS of ≥50%.

Conclusion

The frequency of strong PD-L1 expression was lower than that previously reported in the trials where PD-L1 expression was used as a biomarker for patient selection. Also, considering that a subset of patients with ALK positivity had a strong PD-L1 expression, further studies will be required to examine the efficacy of PD-1/PD-L1 inhibitors in such patients.

Whole body PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer

PD-L1 immunohistochemistry correlates only moderately with patient survival and response to PD-(L)1 treatment. Heterogeneity of tumor PD-L1 expression might limit the predictive value of small biopsies. Here we show that tumor PD-L1 and PD-1 expression can be quantified non-invasively using PET-CT in patients with non-small-cell lung cancer. Whole body PD-(L)1 PET-CT reveals significant tumor tracer uptake heterogeneity both between patients, as well as within patients between different tumor lesions.

Assessment of PD-1 and PD-L1 expression can be predictive of immunotherapy response in lung cancer. Here the authors assess the clinical toxicity, safety and quality of non-invasive imaging of PD-1 and PD-L1 expression in 13 patients with advanced lung cancer prior to treatment with immunotherapy and show it correlates with response.

Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients

Pembrolizumab monotherapy has been approved for the first- and second-line treatment of patients with PD-L1-expressing advanced non-small cell lung cancer (NSCLC). Testing for PD-L1 expression with the PD-L1 immunohistochemistry (IHC) 22C3 companion diagnostic assay, which gives a tumor proportion score (TPS), has been validated on tumor tissue. We developed an optimized laboratory-developed test (LDT) that uses the 22C3 antibody (Ab) concentrate on a widely available IHC autostainer for biopsy and cytology specimens. The PD-L1 TPS was evaluated with 120 paired whole-tumor tissue sections and biopsy samples and with 70 paired biopsy and cytology samples (bronchial washes, n = 40; pleural effusions, n = 30). The 22C3 Ab concentrate-based LDT showed a high concordance rate between biopsy (~100%) and cytology (~95%) specimens when compared to PD-L1 IHC expression determined using the PD-L1 IHC 22C3 companion assay at both TPS cut points (≥1%, ≥50%). The optimized LDT presented here, using the 22C3 Ab concentrate to determine the PD-L1 expression in both tumor tissue and in cytology specimens, will expand the ability of laboratories worldwide to assess the eligibility of patients with NSCLC for treatment with pembrolizumab monotherapy in a reliable and reproducible manner.

Predictive potential and need for standardization of PD-L1 immunohistochemistry

Checkpoint inhibitors targeting the PD-1/PD-L1 axis are a promising treatment option in several tumor types. PD-L1 expression detected by immunohistochemistry is the first clinically validated predictive biomarker for response to PD-1/PD-L1 inhibitors, though its predictive value varies significantly between tumor types. With the approval of pembrolizumab monotherapy for treatment-naïve, advanced non-small cell lung cancer, PD-L1 testing has to become broadly available in pathology laboratories. When PD-L1 testing started to be introduced in routine pathology practice, there were several open issues, which needed to be addressed in order to provide accurate results. This review will discuss the complex biological background of PD-L1 as predictive biomarker, summarize relevant clinical trials in NSCLC illustrating the origin of different PD-L1 expression cutoffs and scorings, and address issues important for PD-L1 testing including the analytical comparability of the different clinical trial-validated PD-L1 immunohistochemistry assays, the potential of laboratory-developed tests, and an overview of the different scoring algorithms.

Importance of choice of materials and methods in PD-L1 and TIL assessment in oropharyngeal squamous cell carcinoma

AIMS

A great deal of research is being conducted into PD-L1 immunohistochemistry (IHC) and tumour-infiltrating lymphocytes (TILs) as predictive or prognostic biomarkers for immunotherapy, although several practical issues exist concerning their assessment. The aim of this research was therefore to assess the importance of choice of materials and methods in PD-L1 and TILs scoring in oropharyngeal squamous cell carcinoma (OSCC).

METHODS AND RESULTS

IHC for PD-L1 (SP142 and 22C3 clone) and TILs subtyping was performed on formalin-fixed paraffin-embedded tissue slides (biopsy, resection and/or lymph nodes specimens) of 99 patients with OSCC. A comparative analysis of PD-L1 and TILs scoring was made between different types of tissue specimens, between different PD-L1 clones, between TILs and different subsets of TILs and between the quantitative and semiquantitative assessments. PD-L1 scoring resulted in fair to moderate agreement for 22C3 and SP142 between various tissue specimens, with higher agreement at higher cut-off values, and in moderate agreement for 22C3 versus SP142. Evaluation by four independent observers proved substantial inter-rater agreement for both clones with high consistency in their ratings. Moderate agreement was observed for TILs and TILs subsets for the comparison between biopsy and resection. Lastly, strong correlations were found between quantitative and semiquantitative assessment for all PD-L1 and TILs scores.

CONCLUSIONS

Our results highlight the challenges associated with the evaluation of PD-L1 and TILs in OSCC. Further research is warranted to evaluate the use of these biomarkers in order to allow implementation of PD-L1 and TILs infiltrate as biomarkers in daily clinical practice.

Any Place for Immunohistochemistry within the Predictive Biomarkers of Treatment in Lung Cancer Patients?

The identification of certain genomic alterations (EGFR, ALK, ROS1, BRAF) or immunological markers (PD-L1) in tissues or cells has led to targeted treatment for patients presenting with late stage or metastatic lung cancer. These biomarkers can be detected by immunohistochemistry (IHC) and/or by molecular biology (MB) techniques. These approaches are often complementary but depending on, the quantity and quality of the biological material, the urgency to get the results, the access to technological platforms, the financial resources and the expertise of the team, the choice of the approach can be questioned. The possibility of detecting simultaneously several molecular targets, and of analyzing the degree of tumor mutation burden and of the micro-satellite instability, as well as the recent requirement to quantify the expression of PD-L1 in tumor cells, has led to case by case development of algorithms and international recommendations, which depend on the quality and quantity of biological samples. This review will highlight the different predictive biomarkers detected by IHC for treatment of lung cancer as well as the present advantages and limitations of this approach. A number of perspectives will be considered.