Intratumoral heterogeneity in programmed death-ligand 1 immunoreactivity is associated with variation in non-small cell lung carcinoma histotype

PD-L1 expression in resected lung adenocarcinoma: prevalence and prognostic significance in relation to the IASLC grading system

AIMS

Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for adjuvant immunotherapy and has been linked to poor differentiation in lung adenocarcinoma. However, its prevalence and prognostic role in the context of the novel histologic grade has not been evaluated.

METHODS

We analysed a cohort of 1233 patients with resected lung adenocarcinoma where PD-L1 immunohistochemistry (22C3 assay) was reflexively tested. Tumour PD-L1 expression was correlated with the new standardized International Association for the Study of Lung Cancer (IASLC) histologic grading system (G1, G2, and G3). Clinicopathologic features including patient outcome were analysed.

RESULTS

PD-L1 was positive (≥1%) in 7.0%, 23.5%, and 63.0% of G1, G2, and G3 tumours, respectively. PD-L1 positivity was significantly associated with male sex, smoking, and less sublobar resection among patients with G2 tumours, but this association was less pronounced in those with G3 tumours. PD-L1 was an independent risk factor for recurrence (adjusted hazard ratio [HR] = 3.25, 95% confidence intervals [CI] = 1.93-5.48, P < 0.001) and death (adjusted HR = 2.69, 95% CI = 1.13-6.40, P = 0.026) in the G2 group, but not in the G3 group (adjusted HR for recurrence = 0.94, 95% CI = 0.64-1.40, P = 0.778).

CONCLUSION

PD-L1 expression differs substantially across IASLC grades and identifies aggressive tumours within the G2 subgroup. This knowledge may be used for both prognostication and designing future studies on adjuvant immunotherapy.

Expression Changes in Programmed Death Ligand 1 from Precancerous Lesions to Invasive Adenocarcinoma in Subcentimeter Pulmonary Nodules: A Large Study of 2022 Cases in China

PURPOSE

This large-scale, multicenter, retrospective observational study aimed to evaluate the clinicopathological and molecular profiles associated with programmed death-ligand 1 (PD-L1) expression in precancerous lesions and invasive adenocarcinoma in subcentimeter pulmonary nodules.

PATIENTS AND METHODS

Patients with histologically confirmed atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) were included. PD-L1 expression was evaluated at each center using a PD-L1 immunohistochemistry 22C3 pharmDx kit (Agilent, Santa Clara, CA, USA). The tumor proportion score (TPS) cutoff values were set at ≥ 1% and ≥ 50%.

RESULTS

A total of 2022 nodules from 1844 patients were analyzed. Of these, 9 (0.45%) nodules had PD-L1 TPS ≥ 50%, 187 (9.25%) had PD-L1 TPS 1-49%, and 1826 (90.30%) had PD-L1 TPS < 1%. A total of 378 (18.69%), 1016 (50.25%), and 628 (31.06%) nodules were diagnosed as AAH/AIS, MIA, and ADC, respectively, by pathology. A total of 1377 (68.10%), 591 (25.67%), and 54 (2.67%) nodules were diagnosed as pure ground-glass opacity (GGO), mixed GGO, and solid nodules, respectively, by computed tomography. There was a significant difference between PD-L1 expression and anaplastic lymphoma kinase (ALK) mutation status (P < 0.001). PD-L1 expression levels were significantly different from those determined using the International Association for the Study of Lung Cancer (IASLC) grading system (P < 0.001).

CONCLUSIONS

PD-L1 expression was significantly associated with radiological and pathological invasiveness and driver mutation status in subcentimeter pulmonary nodules. The significance of PD-L1 expression in the evolution of early-stage lung adenocarcinoma requires further investigation.

Clinical efficacy and safety of adjuvant EGFR-TKIs for resected stage IB lung adenocarcinoma: A real-world study based on propensity score matching

BACKGROUND

Adjuvant therapy for stage IB non-small cell lung cancer remains debatable. In this real-world study, we evaluate the efficacy and safety of adjuvant epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) for resected stage IB lung adenocarcinoma.

METHODS

This real-world study recruited 249 patients diagnosed with stage IB disease after surgical resection between January 2013 and September 2021. Sixty-six (26.5%) patients received adjuvant targeted therapy (TKIs group), and 183 (73.5%) were enrolled in the clinical observation (CO) group. Propensity scores were matched to minimize the observed confounder effects between the two groups, and 59 patient pairs were matched. The primary endpoint was disease-free survival (DFS).

RESULTS

In the TKI group, 38 (64.4%) patients chose to receive icotinib, 27.1% (16/59) received gefitinib, and 5 patients (8.5%) chose osimertinib. The median follow-up time was 30.8 months (range: 7-107 months). Two (3.4%) patients in the TKI group and 10 (16.9%) in the CO group experienced disease relapse. The 3-year DFS rates were 98.3% in the TKI group and 83.0% in the CO group (HR: 0.10; 95% CI: 0.01-0.78; p = 0.008). DFS differences were found in the entire cohort (p = 0.005) and the matched cohort (p = 0.024) between the two groups. Multivariate analysis showed that adjuvant EGFR-TKIs was an independent factor for DFS (HR: 0.211; 95% CI: 0.045-0.979; p = 0.047), along with poor cell differentiation (HR: 5.256; 95% CI: 1.648-16.769; p = 0.005), and spread through air spaces (HR: 5.612; 95% CI: 1.137-27.700; p = 0.034). None of the patients discontinued EGFR-TKIs owing to the low occurrence rate of treatment-related serious adverse events.

CONCLUSION

Adjuvant EGFR-TKIs could significantly improve DFS among patients with stage IB lung adenocarcinoma compared with CO, with a safe and tolerable profile.

Characteristics and Prognostic Nomogram for Primary Lung Lepidic Adenocarcinoma

Background. Lepidic adenocarcinoma (LPA) is an infrequent subtype of invasive pulmonary adenocarcinoma (ADC). However, the clinicopathological features and prognostic factors of LPA have not been elucidated. Methods. Data from the Surveillance, Epidemiology, and End Results (SEER) database of 4191 LPA patients were retrospectively analyzed and compared with non-LPA pulmonary ADC to explore the clinicopathological and prognosis features of LPA. Univariate and multivariate Cox proportional hazard models were performed to identify independent survival predictors for further nomogram development. The nomograms were validated using the concordance index, receiver operating characteristic curves, and calibration plots, as well as decision curve analysis, in both the training and validation cohorts. Results. Compared with non-LPA pulmonary ADC patients, those with LPA exhibited unique clinicopathological features, including more elderly and female patients, smaller tumor size, less pleural invasion, and lower histological grade and stage. Multivariate analyses showed that age, sex, race, tumor location, primary tumor size, pleural invasion, histological grade, stage, primary tumor surgery, and chemotherapy were independently associated with overall survival (OS) and cancer-specific survival (CSS) in patients with LPA. The nomograms showed good accuracy compared with the actual observed results and demonstrated improved prognostic capacity compared with the TNM stage. Conclusions. LPA is more frequently diagnosed in older people and women. LPA was inclined to be smaller in tumor size and lower in tumor grade and staging, which may indicate a favorable prognosis. The constructed nomograms accurately predict the long-term survival of LPA patients.

Concordance, Correlation, and Clinical Impact of Standardized PD-L1 and TIL Scoring in SCCHN

Simple Summary

In patients with relapsed or metastasized squamous cell cancer of the head and neck (R/M SCCHN), the PD-L1 Combined Positive Score (CPS) is currently the only predictive biomarker for treatment with anti-PD-1 agents. However, ambiguous results have been determined regarding the overall response rates of immunotherapeutic agents based on PD-L1 status, which may be partially attributed to spatiotemporal heterogeneity. Furthermore, tumor-infiltrating lymphocytes (TILs) have proven to be of significant prognostic value, yet lack of a standardized method for quantification impedes their integration into the current armamentarium of biomarkers in SCCHN. In this paper, concordance of PD-L1 CPS and stromal TILs was investigated in different paired samples of SCCHN subtypes. The results were then linked to well-known clinicopathological variables and prognosis.

Abstract

Background: The clinical significance of tumor-infiltrating lymphocytes (TILs) and programmed cell death-ligand 1 (PD-L1) expression has been thoroughly researched in squamous cell carcinoma of the head and neck (SCCHN). To address the impact of intra- and intertumoral heterogeneity in these biomarkers, we explored the concordance of PD-L1 combined positive score (CPS) and stromal TILs in different paired tissue sample types, while evaluating their internal relationship and prognostic impact. Methods: A total of 165 tissue blocks from 80 SCCHN patients were reviewed for TILs and PD-L1 CPS. Concordance between paired tissue samples was evaluated, and their association with several clinicopathological variables, overall survival (OS), and disease-free survival (DFS) was determined. Results: Biopsies and paired resection material were severely discordant in 39% and 34% of samples for CPS and TIL count, respectively, of which CPS was underscored in 27% of biopsies. In paired primary tumor–metastatic lesions, the disagreement was lower for CPS (19%) but not for TIL count (44%). PD-L1 CPS was correlated with prolonged OS when calculated from tissue acquirement, while extended OS and DFS were observed for high TIL density. Conclusion: Intertumoral and, especially, intratumoral heterogeneity were confounding factors when determining PD-L1 CPS and TIL count on paired tissue samples, indicating the increasing necessity of assessing both biomarkers on representative tissue material. Although TILs hold valuable prognostic information in SCCHN, the robustness of PD-L1 as a biomarker in SCCHN remains ambiguous.

Heterogeneity of PD-L1 expression between invasive and lepidic components of lung adenocarcinomas

The dynamics of PD-L1 expression are poorly understood over the development of lung adenocarcinomas from pre-invasive lesions to fully invasive carcinomas. Given the importance of PD-L1 expression for the selection of patients to receive immunotherapy in the metastatic setting and possibly in the neoadjuvant setting, we sought to evaluate the agreement of PD-L1 expression in invasive and lepidic components of resected tumor specimens. We stained 86 adenocarcinomas for PD-L1 using the SP263 clone. We assessed the agreement of PD-L1 expression by tumor cells and immune cells between lepidic and invasive components. When both lepidic and invasive components were considered, PD-L1 positive immune cells and tumor cells were observed in 50 (58.1%) and 18 (20.9%) samples, respectively, using a ≥ 1% PD-L1 expression cutoff. Using a ≥ 1% cutoff for PD-L1 expression, positively stained tumor cells were observed in 11 (13%) lepidic and 15 (17%) invasive patterns, with agreement in 76 (88%) specimens and disagreement in 10 (12%) specimens (ĸ = 0.549). At ≥ 1% PD-L1 expression cutoff, PD-L1 positive immune cells were observed in 31 (35%) lepidic and 32 (37%) invasive patterns with an agreement of PD-L1 expression in 49 (57%) specimens and disagreement in 37 (43%) specimens (ĸ = 0.073). In our study of early stage adenocarcinomas of the lung, there was poor agreement in PD-L1 expression between paired invasive and lepidic components of tumors. Our data suggest that the non-invasive tumor components may not be as immunostimulatory as the invasive components, resulting in less adaptive expression of PD-L1.

Radiomics Study for Predicting the Expression of PD-L1 and Tumor Mutation Burden in Non-Small Cell Lung Cancer Based on CT Images and Clinicopathological Features

Background

The present study compared the predictive performance of pretreatment computed tomography (CT)-based radiomics signatures and clinicopathological and CT morphological factors for ligand programmed death-ligand 1 (PD-L1) expression level and tumor mutation burden (TMB) status and further explored predictive models in patients with advanced-stage non-small cell lung cancer (NSCLC).

Methods

A total of 120 patients with advanced-stage NSCLC were enrolled in this retrospective study and randomly assigned to a training dataset or validation dataset. Here, 462 radiomics features were extracted from region-of-interest (ROI) segmentation based on pretreatment CT images. The least absolute shrinkage and selection operator (LASSO) and logistic regression were applied to select radiomics features and develop combined models with clinical and morphological factors for PD-L1 expression and TMB status prediction. Ten-fold cross-validation was used to evaluate the accuracy, and the predictive performance of these models was assessed using receiver operating characteristic (ROC) and area under the curve (AUC) analyses.

Results

The PD-L1-positive expression level correlated with differentiation degree (p = 0.005), tumor shape (p = 0.006), and vascular convergence (p = 0.007). Stage (p = 0.023), differentiation degree (p = 0.017), and vacuole sign (p = 0.016) were associated with TMB status. Radiomics signatures showed good performance for predicting PD-L1 and TMB with AUCs of 0.730 and 0.759, respectively. Predictive models that combined radiomics signatures with clinical and morphological factors dramatically improved the predictive efficacy for PD-L1 (AUC = 0.839) and TMB (p = 0.818). The results were verified in the validation datasets.

Conclusions

Quantitative CT-based radiomics features have potential value in the classification of PD-L1 expression levels and TMB status. The combined model further improved the predictive performance and provided sufficient information for the guiding of immunotherapy in clinical practice, and it deserves further analysis.

PD-L1 expression in non-small cell lung cancer: heterogeneity by pathologic types, tissue sampling and metastasis

Background

Programmed cell death ligand-1 (PD-L1) is a predictive marker of anti-PD-1/PD-L1 therapy response. Intra-tumour heterogeneity of PD-L1 expression has been reported in non-small cell lung cancer (NSCLC), but comprehensive studies regarding the determination of PD-L1 expression in different materials are still lacking. Therefore, we aimed to compare PD-L1 expression in paired tumour samples and in different specimen types.

Methods

A total of 1,002 resected NSCLC specimens, 35 biopsy specimens and 54 endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) samples were performed PD-L1 immunohistochemistry (IHC) testing using the 22C3 assay. PD-L1 expression was evaluated using the tumour proportion score (TPS) and categorized into three levels: negative (TPS <1%), low expression (TPS 1–49%) and high expression (TPS ≥50%).

Results

A total of 1,002 resected NSCLC specimens, including 852 adenocarcinomas (ADCs) and 150 squamous cell carcinomas (SCCs); 35 paired biopsy and resected samples; 54 paired cell block and biopsy samples; 53 paired blocks from the same resected tissue and 49 paired primary and metastatic lesion samples were included in this study. Interestingly, high PD-L1 expression was significantly more frequent in poorly differentiated subtypes than in well-differentiated subtypes in the ADC subgroup (P<0.001). In the SCC subgroup, high PD-L1 expression was significantly more associated with the nonkeratinizing type than the keratinizing type (P=0.001). PD-L1 expression differed between cell blocks and matched biopsy specimens (discordance rate =11.1%, 6/54) and between biopsy and matched resected specimens (discordance rate =31.4%, 11/35). PD-L1 expression differed between different paraffin blocks from the same resected specimen (discordance rate =35.8%, 19/53), and the discordance rate of PD-L1 expression between primary tumours and matched lymph node metastases was 28.6% (14/49).

Conclusions

Discordant PD-L1 expression is not uncommon in NSCLC and warrants additional studies and serious consideration when interpreting PD-L1 test results. Initial negative test results may lead to repeat PD-L1 testing in additional samples or the use of a different clone if necessary.

Integrating endobronchial ultrasound bronchoscopy with molecular testing of immunotherapy biomarkers in non-small cell lung cancer

Immunotherapy has transformed treatment of advanced non-small-cell lung cancer (NSCLC) patients leading to remarkable long-term survival benefit. However, only about 20% of advanced NSCLC patients typically respond to immune checkpoint inhibitors (ICIs) that target the PD-1/PD-L1 pathway. The only validated biomarker for ICI therapy is the PD-L1 immunohistochemistry (IHC) test, which is considered an imperfect assay due to several variables including availability and integrity of tumour tissue, variability in staining/scoring techniques and heterogeneity in PD-L1 protein expression within and across tumour biopsies. Herein, we discuss integrating minimally invasive EBUS bronchoscopy procedures with novel molecular approaches to improve accuracy and sensitivity of PD-L1 testing. EBUS guided bronchoscopy facilitates repeated sampling of tumour tissue to increase the probability of detecting PD-L1 positive tumours. Since intra-tumoural PD-L1 (CD274) copy number is reported to be less heterogeneous than PD-L1 protein detection, quantifying PD-L1 transcript levels may increase detection of PD-L1 positive tumours. PD-L1 transcript levels show excellent concordance with PD-L1 IHC scoring and multiplex digital droplet PCR (ddPCR) assays that quantify absolute PD-L1 transcript copy number have been developed. ddPCR can also be automated for high throughput detection of low abundant variants with excellent sensitivity and accuracy to improve the broader application of diagnostic cut-off values. Optimizing diagnostic workflows that integrate optimal EBUS bronchoscopy procedures with emerging molecular ICI biomarker assays may improve the selection criteria for ICI therapy benefit.

Heterogeneity of PD-L1 expression in lung adenocarcinoma metastasis is related to histopathological subtypes

OBJECTIVES

The heterogeneity of PD-L1 expression and its relationship with histopathological subtype has recently been shown on primary tumor but has not been evaluated on metastases. The aim of our work is to analyze PD-L1 expression within each histopathological pattern on resected metastases.

MATERIAL AND METHODS

136 patients were included in this retrospective study. Immunohistochemistry was performed with 22C3 laboratory-developed test. The Tumor Proportion Score was evaluated on each subtype.

RESULTS

The most frequent major histopathological subtype was solid (n = 69, 50.7 %), followed by acinar (n = 37, 27.2 %), micropapillary (n = 14, 10.3 %) and papillary (n = 10, 7.3 %). Mean percentage of PD-L1 expression for each subtype was at 28+/-4.8 % for solid subtype, 5.3+/-1.9 % for acinar subtype, 5+/-1.9 % for papillary subtype and 23.6+/-4.1 % for micropapillary subtype. Mean percentage of PD-L1 expression was different between solid pattern and acinar pattern (p < 0.001), solid pattern and papillary pattern (p = 0.007), micropapillary pattern and acinar pattern (p < 0.001) and micropapillary pattern and papillary pattern (p = 0.015).

CONCLUSION

To conclude, we have showed firstly that several patterns are present in metastases of lung adenocarcinoma, secondly that the evaluation of patterns and PD-L1 stain on different patterns is reproducible, thirdly that pattern heterogeneity is related to PD-L1 staining, fourthly that in metastatic lung adenocarcinoma with at least two patterns, solid and micropapillary subtypes have higher levels of PD-L staining, fifthly that PD-L1 heterogeneity between different patterns is not a rare event. These results might explain discrepancies of PD-L1 results between biopsies and surgical samples and the fact that some patients might respond to checkpoint inhibitors even though PD-L1 expression is low or absent.

Proteomic Analyses Identify Differentially Expressed Proteins and Pathways Between Low-Risk and High-Risk Subtypes of Early-Stage Lung Adenocarcinoma and Their Prognostic Impacts

The histopathological subtype of lung adenocarcinoma (LUAD) is closely associated with prognosis. Micropapillary or solid predominant LUAD tends to relapse after surgery at an early stage, whereas lepidic pattern shows a favorable outcome. However, the molecular mechanism underlying this phenomenon remains unknown. Here, we recruited 31 lepidic predominant LUADs (LR: low-risk subtype group) and 28 micropapillary or solid predominant LUADs (HR: high-risk subtype group). Tissues of these cases were obtained and label-free quantitative proteomic and bioinformatic analyses were performed. Additionally, prognostic impact of targeted proteins was validated using The Cancer Genome Atlas databases (n = 492) and tissue microarrays composed of early-stage LUADs (n = 228). A total of 192 differentially expressed proteins were identified between tumor tissues of LR and HR and three clusters were identified via hierarchical clustering excluding eight proteins. Cluster 1 (65 proteins) showed a sequential decrease in expression from normal tissues to tumor tissues of LR and then to HR and was predominantly enriched in pathways such as tyrosine metabolism and ECM-receptor interaction, and increased matched mRNA expression of 18 proteins from this cluster predicted favorable prognosis. Cluster 2 (70 proteins) demonstrated a sequential increase in expression from normal tissues to tumor tissues of LR and then to HR and was mainly enriched in pathways such as extracellular organization, DNA replication and cell cycle, and high matched mRNA expression of 25 proteins indicated poor prognosis. Cluster 3 (49 proteins) showed high expression only in LR, with high matched mRNA expression of 20 proteins in this cluster indicating favorable prognosis. Furthermore, high expression of ERO1A and FEN1 at protein level predicted poor prognosis in early-stage LUAD, supporting the mRNA results. In conclusion, we discovered key differentially expressed proteins and pathways between low-risk and high-risk subtypes of early-stage LUAD. Some of these proteins could serve as potential biomarkers in prognostic evaluation.

Clinicopathological and molecular characteristics associated with PD-L1 expression in non-small cell lung cancer: a large-scale, multi-center, real-world study in China

PURPOSE

The study aimed to evaluate the clinicopathological and molecular profiles associated with programmed death ligand 1 (PD-L1) expression in non-small cell lung cell (NSCLC) in a large-scale, multi-center, real-world Chinese cohort.

METHODS

A total of 6295 NSCLC specimens from six centers in China were analyzed by PD-L1 (22C3) assay. PD-L1 expression in tumor cells (TCs) was classified as negative (TPS expression in < 1% of TCs), low (TPS in 1-49% of TCs), or high (TPS in ≥ 50% of TCs). The status of EGFR mutation was determined by reverse transcription polymerase chain reaction or next-generation sequencing, and ALK and ROS1 translocation was analyzed by immunohistochemistry and fluorescence in situ hybridization. Associations of PD-L1 expression with clinicopathological features and driver mutations were analyzed.

RESULTS

Positive PD-L1 expression was more frequently seen in squamous cell carcinoma (SCC) and other histological types of NSCLC compared to adenocarcinoma (AC). In AC, PD-L1 expression was associated with gender, histological type, metastatic status, and pathological features of lymphovascular invasion and visceral pleural invasion. Solid and micropapillary subtypes of AC were more likely to have positive PD-L1 expression compared to other subtypes. PD-L1 was more highly expressed in biopsy samples than in resected samples, and in metastatic samples compared with primary tissues. PD-L1 expression was significantly associated with wild-type EGFR and ALK translocations.

CONCLUSIONS

PD-L1 expression in NSCLC is linked to histological type, pathological features, and driver mutation status, which has meaningful implications for clinical practice.

Programmed death-ligand 1 (PD-L1)/thyroid transcription factor-1 double immunohistochemical staining facilitates scoring of tumor PD-L1 expression in cytopathology specimens from lung adenocarcinoma patients

BACKGROUND

Immune checkpoint inhibitor therapy has revolutionized lung adenocarcinoma therapy. Treatment with antibodies against the immune checkpoint molecules programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) can induce a durable response in a subset of patients. Immunohistochemistry characterization of tumor PD-L1 expression using either a histopathology specimen or a cytopathology specimen has been shown to correlate with treatment response. However, the current practice relies on pathologists' visual estimation of tumor PD-L1 staining, which can be variable in certain conditions. Highlighting tumor cells via double immunostaining with PD-L1 and thyroid transcription factor-1 (TTF-1) may improve estimation accuracy.

METHODS

We performed PD-L1 single staining and PD-L1/TTF-1 double staining in 42 pairs of cytopathology and histopathology specimens from lung adenocarcinoma patients. An experienced pathologist visually estimated PD-L1 expression in each case and placed tumor PD-L1 expression into 1 of 3 categories: <1%, 1%-49%, or ≥50%. A medical technologist also performed estimations of the same cases based on a count of 200 tumor cells, and the results were compared.

RESULTS

PD-L1/TTF-1 double immunohistochemistry could better identify the PD-L1-positive tumor cells in cytopathology specimens compared with PD-L1 single staining. The concordance of PD-L1 expression categorization between the pathologist's visual estimation and the medical technologist's counting was increased by double staining in cytopathology specimens (Cohen's weighted kappa: single stain, 0.784; double stain, 0.880). Double staining reduced possible error in the pathologist's visual estimation of PD-L1 expression from 9.5% to 4.8%. The benefit was not observed in histopathology specimens.

CONCLUSION

A simple PD-L1/TTF-1 double immunohistochemistry technique can be applied successfully to cytopathology specimens in better identifying patients who can potentially benefit from immune checkpoint blockade treatment.

Spatial heterogeneity of PD-L1 expression and the risk for misclassification of PD-L1 immunohistochemistry in non-small cell lung cancer

BACKGROUND

Intra-tumor heterogeneity for PD-L1 expression in non-small cell lung cancer (NSCLC) might lead to inaccurate stratification of patients to immunotherapy. The purpose of this research was to quantitate the effect of different factors on the risk of inaccurate diagnosis of PD-L1 expression.

METHODS

MATLAB software was used to model tumor with a different fraction, distribution and clustering of PD-L1 protein expression and their effect on false positive and negative diagnosis in subsets of the modeled tumor (representing biopsies). Additionally, we evaluated the agreement between PD-L1 status in random segments and whole slides of PD-L1 stained clinical NSCLC cases.

RESULTS

Our computer-based model showed a significant increase in error rate when the fraction of PD-L1 positive cells was closer to the cut-off value (error rate of 33.33 %, 0.45 % and 0.74 % for PD-L1 positivity in 40-60%, ≤20 % and ≥80 % of tumor cells, respectively, P < 0.0001). In addition, biopsy size showed negative correlation with error rate (P < 0.0001) and larger clusters of PD-L1 positive cells were associated with higher error rate (P < 0.0001). Analysis of the clinical samples supported those of the computer-based model with higher error rate in cases with positive PD-L1 expression closer to the cutoff value. Based on our computerized model and clinical analysis, we developed a model to predict error rate based on biopsy size and the fraction of PD-L1 positive cells in the biopsy.

CONCLUSION

Analysis of small biopsies for PD-L1 expression might be associated with significant error rate. The model presented can be used to identify cases with increased risk for error in whom interpretation of the test results should be made with caution.

Correlation between PD-L1 expression and clinicopathological characteristics of non-small cell lung cancer: A real-world study of a large Chinese cohort

BACKGROUND

Programmed death ligand-1 (PD-L1) is a predictive marker of anti-programmed death protein 1 (PD-1)/PD-L1 therapies for non-small cell lung cancer (NSCLC). However, little is known between PD-L1 expression and the clinicopathological characteristics of NSCLC in the Chinese population in a real-world setting.

METHODS

We analyzed PD-L1 expression by immunohistochemistry (IHC) in NSCLC patients using the 22C3 clone on the Dako Autostainer Link 48 platform. We then examined the associations of PD-L1 expression with clinicopathological characteristics, stromal tumor-infiltrating lymphocytes (TILs) and major molecular features.

RESULTS

A total of 1,156 recently NSCLC specimens including 827 sequentially resected specimens and 293 biopsy specimens were enrolled in our study. PD-L1 high expression was observed in 9.7% of 827 NSCLC patients, including 6.5% with adenocarcinoma (ADC, n=690), and 27.4% with squamous cell carcinoma (SqCC, n=117). These results showed higher expression rates than those in archived samples (>5 years old, n=329), that were previously reported by our group (4.9%, 0.5%, and 13.9% in NSCLC, ADC, and SqCC, respectively). The prevalence of PD-L1 expression was lower in surgical resection samples than in small biopsy samples. PD-L1 high expression in the lung biopsy was less likely present in the primary cancer than in metastases, and was also associated with a high level of stromal TILs (P=0.029) and PD-L1-positive immune cells (IC) (P<0.001). Both PD-L1 high and low expressions were more frequent in EGFR-wild type than in mutant type (P<0.001).

CONCLUSIONS

This study demonstrates that expression of PD-L1 is linked to the type of tumor specimens, resection versus biopsy specimens, and biopsies of primary versus metastatic cancers. These findings have substantial implications for clinical practice.