Programmed death ligand 1 immunohistochemistry in non-small cell lung carcinoma

Revisiting the impact of clinicopathologic characteristics in PD-L1 profile in a large cohort of non-small cell lung cancer

Background

Immunotherapies using anti-programmed cell death ligand-1 (PD-L1) agents have recently shown remarkable outcomes in patients with non-small cell lung cancer (NSCLC). However, there was a poor correlation between PD-L1 expression and treatment response. Many researchers have focused on the clinicopathological factors associated with prognosis, but the results are conflicting. In the present study, we investigated the clinicopathological significance of PD-L1 overexpression in NSCLC cells.

Methods

In total, 344 NSCLC cases with PD-L1 assays were retrospectively analyzed. PD-L1 expression was evaluated via immunohistochemical staining using antibodies against SP263 and SP142. The correlation between clinicopathological factors and PD-L1 expression was analyzed for various clinicopathological features.

Results

PD-L1 expression significantly correlated with several poor clinicopathological factors, including the solid component of adenocarcinoma, lymphatic invasion, and recurrence. Squamous cell carcinoma, older age, and male sex were also associated with PD-L1 expression. However, we could not observe correlation between PD-L1 expression and disease-free survival (DFS). A novel finding was that lower metastasis was associated with high PD-L1 expression of SP142 in tumor-infiltrating immune cells (ICs).

Conclusions

PD-L1 expression in NSCLC is associated with adverse clinicopathological features and recurrence; therefore, it could be utilized to predict poor prognosis. Furthermore, the high PD-L1 expression of SP142 in tumor-infiltrating ICs could be a potential marker for low metastasis.

PD-1/PD-L1 pathway: Current research in breast cancer

INTRODUCTION

Immunotherapy has shown encouraging outcomes in breast cancer (BC) treatment in recent years. The programmed cell death ligand 1 (PD-L1) transmembrane protein is suggested to function as a co-inhibitory factor in the immune response, where it collaborates with programmed cell death protein 1 (PD-1) to stimulate apoptosis, suppress cytokine release from PD-1 positive cells, and limit the growth of PD-1 positive cells. Furthermore, in many malignancies, PD-L1 reduces the immune system's response to neoplastic cells. These observations suggest that the PD-1/PD-L1 axis plays a vital role in cancer therapy and the regulation of cancer immune escape mechanisms. This review aimed to provide an overview of the functions of PD-1 and PD-L1 in BC cancer therapy.

METHODS

This research design is a literature review. The style is a traditional review on topics or variables relating to the PD-1/PD-L1 pathway. A literature search was carried out using three online databases.

RESULTS

The search using the keywords yielded a total of 248 studies. Each result was filtered again according to the inclusion and exclusion criteria, resulting in a final total of 4 studies to be included in the literature review.

CONCLUSIONS

The combination of PD-1/PD-L1 is essential for many malignancies. According to the evidence presented, this combination presents both an opportunity and a challenge in cancer treatment. Since many solid cancers, especially BC, express high levels of PD-1/PD-L1, cancer treatment mainly involves targeted therapies.

Deep Learning for Lung Cancer Diagnosis, Prognosis and Prediction Using Histological and Cytological Images: A Systematic Review

Lung cancer is one of the deadliest cancers worldwide, with a high incidence rate, especially in tobacco smokers. Lung cancer accurate diagnosis is based on distinct histological patterns combined with molecular data for personalized treatment. Precise lung cancer classification from a single H&E slide can be challenging for a pathologist, requiring most of the time additional histochemical and special immunohistochemical stains for the final pathology report. According to WHO, small biopsy and cytology specimens are the available materials for about 70% of lung cancer patients with advanced-stage unresectable disease. Thus, the limited available diagnostic material necessitates its optimal management and processing for the completion of diagnosis and predictive testing according to the published guidelines. During the new era of Digital Pathology, Deep Learning offers the potential for lung cancer interpretation to assist pathologists' routine practice. Herein, we systematically review the current Artificial Intelligence-based approaches using histological and cytological images of lung cancer. Most of the published literature centered on the distinction between lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung carcinoma, reflecting the realistic pathologist's routine. Furthermore, several studies developed algorithms for lung adenocarcinoma predominant architectural pattern determination, prognosis prediction, mutational status characterization, and PD-L1 expression status estimation.

Cell adhesion molecules and immunotherapy in advanced non-small cell lung cancer: Current process and potential application

Advanced non-small cell lung cancer (NSCLC) is a severe disease and still has high mortality rate after conventional treatment (e.g., surgical resection, chemotherapy, radiotherapy and targeted therapy). In NSCLC patients, cancer cells can induce immunosuppression, growth and metastasis by modulating cell adhesion molecules of both cancer cells and immune cells. Therefore, immunotherapy is increasingly concerned due to its promising anti-tumor effect and broader indication, which targets cell adhesion molecules to reverse the process. Among these therapies, immune checkpoint inhibitors (mainly anti-PD-(L)1 and anti-CTLA-4) are most successful and have been adapted as first or second line therapy in advanced NSCLC. However, drug resistance and immune-related adverse reactions restrict its further application. Further understanding of mechanism, adequate biomarkers and novel therapies are necessary to improve therapeutic effect and alleviate adverse effect.

Flausino L, Iyer G, Balkrishnan R. Effectiveness of immunological agents in non-small cell lung cancer

BACKGROUND AND AIM

Non-small cell lung cancer (NSCLC) continues to claim millions of lives worldwide. Although its poor prognosis is largely attributed to the lack of adequate and precise detection technologies, cancer cells' suppression of the immune system adds on to the difficulty of identifying abnormal NSCLC tumors in their early stages. Therefore, cancer immunotherapy, which activates the immune system and helps it fight tumors, has recently become the most sought-after technique, especially in the advanced stages of NSCLC, where surgery or chemotherapy may or may not bring about the desired survival benefits in patients.

METHODS

This review focuses on the various immunotherapeutic interventions and their efficacy in advanced NSCLC clinical trials. Monoclonal antibodies like anti-PD-1/PD-L1 agents and anti-CTLA-4 antibodies, cancer vaccines, oncolytic viruses and adoptive T cell therapy have been discussed in brief. Furthermore, the effects of gender, age, and race on the efficacy of immune checkpoint inhibitors and suggest plausible future approaches in the realm of immuno-oncology.

RESULTS

Immunotherapy is used alone or in combination either with other immunological agents or with chemotherapy. However, the efficacy of these strategies depends extensively on various demographic variables, as some patients respond perfectly well to immunotherapy, while others do not benefit at all or experience disease progression. By targeting a "hallmark" of cancer (immune evasion), immunotherapy has transformed NSCLC management, though several barriers prevent its complete effectiveness.

CONCLUSIONS

All these immunological strategies should be interpreted in the current setting of synergistic treatment, in which these agents can be combined with chemotherapy, radiotherapy, and, or surgery following patient and tumor characteristics to proportionate the best-individualized treatment and achieve superior results. To better pursue this goal, further investigations on cost-effectiveness and sex-gender, race, and age differences in immunotherapy are needed.

Prognostic value of soluble programmed cell death ligand-1 in patients with non-small-cell lung cancer: a meta-analysis

Background: Previously published data was collected and a meta-analysis was conducted to precisely identify the prognostic and clinicopathological significance of soluble programmed cell death ligand-1 (sPD-L1) in patients with non-small-cell lung cancer (NSCLC). Materials & methods: Combined hazard ratios (HRs), odds ratios and 95% confidence intervals were used to assess the correlation between sPD-L1 expression and prognosis in patients with NSCLC. Results: A total of 11 studies with 976 patients were included in this meta-analysis. High levels of sPD-L1 were associated with poor overall and progression-free survival (HR: 2.65, 95% CI: 2.32-3.02; p < 0.001 vs HR: 2.02, 95% CI: 1.24-3.29; p = 0.005). sPD-L1 level was not significantly correlated with sex, smoking status, age, Eastern Cooperative Oncology Group performance status, subtype or EGFR mutation. Conclusion: High levels of sPD-L1 are a prognostic marker for poor survival in patients with NSCLC.

Atlas of PD-L1 for Pathologists: Indications, Scores, Diagnostic Platforms and Reporting Systems

Background. Innovative drugs targeting the PD1/PD-L1 axis have opened promising scenarios in modern cancer therapy. Plenty of assays and scoring systems have been developed for the evaluation of PD-L1 immunohistochemical expression, so far considered the most reliable therapeutic predictive marker. Methods. By gathering the opinion of acknowledged experts in dedicated fields of pathology, we sought to update the currently available evidence on PD-L1 assessment in various types of tumors. Results. Robust data were progressively collected for several anatomic districts and leading international agencies to approve specific protocols: among these, TPS with 22C3, SP142 and SP263 clones in lung cancer; IC with SP142 antibody in breast, lung and urothelial tumors; and CPS with 22C3/SP263 assays in head and neck and urothelial carcinomas. On the other hand, for other malignancies, such as gastroenteric neoplasms, immunotherapy has been only recently introduced, often for particular histotypes, so specific guidelines are still lacking. Conclusions. PD-L1 immunohistochemical scoring is currently the basis for allowing many cancer patients to receive properly targeted therapies. While protocols supported by proven data are already available for many tumors, dedicated studies and clinical trials focusing on harmonization of the topic in other still only partially explored fields are surely yet advisable.

A new AI-assisted scoring system for PD-L1 expression in NSCLC

BACKGROUND

Artificial intelligence (AI) analysis may serve as a scoring tool for programmed cell death ligand-1 (PD-L1) expression. In this study, a new AI-assisted scoring system for pathologists was tested for PD-L1 expression assessment in non-small cell lung cancer (NSCLC).

METHODS

PD-L1 expression was evaluated using the tumor proportion score (TPS) categorized into three levels: negative (TPS < 1%), low expression (TPS 1-49%), and high expression (TPS ≥ 50%). In order to train, validate, and test the Aitrox AI segmentation model at the whole slide image (WSI) level, 54, 53, and 115 cases were used as training, validation, and test datasets, respectively. TPS reading results from five experienced pathologists, six inexperienced and the Aitrox AI model were analyzed on 115 PD-L1 stained WSIs. The Gold Standard for TPS was derived from the review of three expert pathologists. Spearman's correlation coefficient was calculated and compared between the results.

RESULTS

Aitrox AI Model correlated strongly with the TPS Gold Standard and was comparable with the results of three of the five experienced pathologists. In contrast, the results of four of the six inexperienced pathologists correlated only moderately with the TPS Gold Standard. Aitrox AI Model performed better than the inexperienced pathologists and was comparable to experienced pathologists in both negative and low TPS groups. Despite the fact that the low TPS group showed 5.09% of cases with large fluctuations, the Aitrox AI Model still showed a higher correlation than the inexperienced pathologists. However, the AI model showed unsatisfactory performance in the high TPS groups, especially lower values than the Gold Standard in images with large regions of false-positive cells.

CONCLUSION

The Aitrox AI Model demonstrates potential in assisting routine diagnosis of NSCLC by pathologists through scoring of PD-L1 expression.

Multi-Omics Approaches for the Prediction of Clinical Endpoints after Immunotherapy in Non-Small Cell Lung Cancer: A Comprehensive Review

Immune checkpoint inhibitors (ICI) have revolutionized the management of locally advanced and advanced non-small lung cancer (NSCLC). With an improvement in the overall survival (OS) as both first- and second-line treatments, ICIs, and especially programmed-death 1 (PD-1) and programmed-death ligands 1 (PD-L1), changed the landscape of thoracic oncology. The PD-L1 level of expression is commonly accepted as the most used biomarker, with both prognostic and predictive values. However, even in a low expression level of PD-L1, response rates remain significant while a significant number of patients will experience hyperprogression or adverse events. The dentification of such subtypes is thus of paramount importance. While several studies focused mainly on the prediction of the PD-L1 expression status, others aimed directly at the development of prediction/prognostic models. The response to ICIs depends on a complex physiopathological cascade, intricating multiple mechanisms from the molecular to the macroscopic level. With the high-throughput extraction of features, omics approaches aim for the most comprehensive assessment of each patient. In this article, we will review the place of the different biomarkers (clinical, biological, genomics, transcriptomics, proteomics and radiomics), their clinical implementation and discuss the most recent trends projecting on the future steps in prediction modeling in NSCLC patients treated with ICI.

p40/PD-L1 and TTF1/PD-L1 Immunohistochemical Double Staining Contributes to Intraindividual Variability Associated With PD-L1 Staining Interpretation in Lung Cancer Samples

The important developments achieved in recent years with a consequent paradigm shift in the treatment of non-small cell lung cancer (NSCLC), including the latest immune checkpoint inhibitors, have led to an increasing need to optimize the scarce material usually available in the diagnosis of these tumors. In this sense, this study intends to evaluate the performance of double immunohistochemistry (IHC) in comparison to simple IHC for programmed death-ligand 1 (PD-L1) evaluation with 22C3 clone for selection to therapy with pembrolizumab. For that, 38 histologic samples of NSCLC small biopsies sent to our laboratory were selected. Double IHC were performed with the doublets TTF1/PD-L1 and p40/PD-L1, after all the usual diagnostic routine and molecular study was performed. The slides were interpreted by 2 independent pathologists and the results obtained were compared with each other and with the results obtained at diagnosis. A perfect agreement was observed when comparing the immunoexpression of TTF1 and p40 in double IHC in relation to single IHC. Although the agreement was substantial in the analysis of the positive/negative PD-L1 IHC (81.6% to 92.1%; κ=0.610 to 0.829) and in the analysis of the 50% cut-off (86.8% to 89.5%; κ=0.704 to 0.759), it fell short of the expected and desirable agreement for a biomarker such as PD-L1, since this result will have a major role in the institution of a treatment. In conclusion, this small series does not allow us to recommend this methodology for the evaluation of the PD-L1 biomarker in double staining IHC with the 22C3 clone for therapy selection.

PD-L1 expression and Tumor mutation burden as Pathological response biomarkers of Neoadjuvant immunotherapy for Early-stage Non-small cell lung cancer: A systematic review and meta-analysis

To date, there is no approved biomarker for predicting pathological response in neoadjuvant programmed cell death (ligand) 1 (PD-(L)1) blockades treated early-stage non-small cell lung cancer (NSCLC). Databases including PubMed, Embase, ClinicalTrials.gov, and Conference abstracts were searched for clinical trials of neoadjuvant PD-1/PD-L1 blockades for resectable NSCLC. Data regarding major pathological response (MPR), pathological complete response (pCR) in patients with high/low pretreatment PD-L1 expression, and tumor mutation burden (TMB) were synthesized using fixed-model meta-analysis and evaluated by odds ratio with 95% confidence interval. This analysis included 10 studies involving 461 NSCLC patients. Compared with PD-L1 expression <1%, PD-L1 expression ≥1% is associated with a higher rate of MPR and pCR. High-TMB associated with MPR and pCR. Similar findings were observed in subgroup analyses despite mono-PD-1/PD-L1 blockade or their combination with chemotherapy. Notably, 50% as the cutoff value for PD-L1 expression demonstrated better prediction efficacy for MPR than that of 1%.

The ubiquitin E3 ligase FBXO22 degrades PD-L1 and sensitizes cancer cells to DNA damage

High expression of programmed death-ligand 1 (PD-L1) in cancer cells drives immune-independent, cell-intrinsic functions, leading to resistance to DNA-damaging therapies. We find that high expression of the ubiquitin E3 ligase FBXO22 sensitizes nonsmall cell lung cancer (NSCLC) cells to ionizing radiation (IR) and cisplatin, and that activation of FBXO22 by phosphorylation is necessary for this function. Importantly, FBXO22 activates PD-L1 ubiquitination and degradation, which in turn increases the sensitivity of NSCLC cells to DNA damage. Cyclin-dependent kinase 5 (CDK5), aberrantly active in cancer cells, plays a crucial role in increasing the expression of PD-L1 in medulloblastoma [R. D. Dorand et al, Science 353, 399-403 (2016)]. We show in NSCLC cells that inhibiting CDK5 or reducing its expression increases the level of FBXO22, decreases that of PD-L1, and increases the sensitivity of the cells to DNA damage. We conclude that FBXO22 is a substrate of CDK5, and that inhibiting CDK5 reduces PD-L1 indirectly by increasing FBXO22. Pairing inhibitors of CDK5 with immune checkpoint inhibitors may increase the efficacy of immune checkpoint blockade alone or in combination with DNA-damaging therapies.

The prevalence of tumour markers in malignant pleural effusions associated with primary pulmonary adenocarcinoma: a retrospective study

Background

Oncological treatment of primary pulmonary adenocarcinoma (AC) includes drugs targeting the pathways involving programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK). The aim of the study was to report the prevalence of these tumour markers in pleural fluid with cytology positive for pulmonary AC and the potential influence of volume pleural fluid tested.

Methods

We retrospectively reviewed all thoracenteses performed in a two-year period at our interventional unit at Department of Respiratory Medicine at Zealand University Hospital Naestved, Denmark. ALK and PD-L1 testing was done using immunohistochemistry and EGFR testing using next-generation sequencing. We included pleural fluid specimens containing malignant cells originating from primary pulmonary AC and with at least one tumour marker requested by the clinicians.

Results

When screening 927 pleural fluid specimens, we identified 57 in accordance with the inclusion criteria. PD-L1, ALK and EGFR were obtained in 35/55 (64%), 38/57 (67%) and 26/47 (55%), respectively. The prevalence did not increase when analysing volumes > 50 mL (p = 0.21–0.58)

Conclusion

Tumour markers in pleural fluid specimens containing cells from pulmonary AC can be demonstrated in more than half of the cases. Therefore, supplementary invasive procedures than thoracentesis could potentially await these analyses.

PD-L1 Testing in Cytological Non-Small Cell Lung Cancer Specimens: A Comparison with Biopsies and Review of the Literature

INTRODUCTION

Programmed death-ligand 1 (PD-L1) expression is used for treatment prediction in non-small cell lung cancer (NSCLC). While cytology may be the only available material in the routine clinical setting, testing in clinical trials has mainly been based on biopsies.

METHODS

We included 2 retrospective cohorts of paired, concurrently sampled, cytological specimens and biopsies. Also, the literature on PD-L1 in paired cytological/histological samples was reviewed. Focus was on the cutoff levels ≥1 and ≥50% positive tumor cells.

RESULTS

Using a 3-tier scale, PD-L1 was concordant in 40/47 (85%) and 66/97 (68%) of the paired NSCLC cases in the 2 cohorts, with kappa 0.77 and 0.49, respectively. In the former cohort, all discordant cases had lower score in cytology. In both cohorts, concordance was lower in samples from different sites (e.g., biopsy from primary tumor and cytology from pleural effusion). Based on 25 published studies including about 1,700 paired cytology/histology cases, the median (range) concordance was 81-85% (62-100%) at cutoff 1% for a positive PD-L1 staining and 89% (67-100%) at cutoff 50%.

CONCLUSIONS

The overall concordance of PD-L1 between cytology and biopsies is rather good but with significant variation between laboratories, which calls for local quality assurance.

Emerging Biomarkers for the Selection of Advanced NSCLC-Affected Immunotherapy Patients

Immunotherapy in the form of ICIs has revolutionized advanced NSCLC treatment algorithms, with ICI-containing combination treatments being the latest addition to approved regimens. However, PD-L1 still represents the only routinely assessed and validated biomarker apart from genetic drivers testing, impairing our capacity to personalize and guide treatment. Therefore, this paper aims to analyze the most promising emerging predictive biomarkers that could help us in the near future to select patients more effectively.

Automated tumor proportion scoring for PD-L1 expression based on multistage ensemble strategy in non-small cell lung cancer

Introduction

Programmed cell death ligand-1 (PD-L1) expression is a promising biomarker for identifying treatment related to non-small cell lung cancer (NSCLC). Automated image analysis served as an aided PD-L1 scoring tool for pathologists to reduce inter- and intrareader variability. We developed a novel automated tumor proportion scoring (TPS) algorithm, and evaluated the concordance of this image analysis algorithm with pathologist scores.

Methods

We included 230 NSCLC samples prepared and stained using the PD-L1(SP263) and PD-L1(22C3) antibodies separately. The scoring algorithm was based on regional segmentation and cellular detection. We used 30 PD-L1(SP263) slides for algorithm training and validation.

Results

Overall, 192 SP263 samples and 117 22C3 samples were amenable to image analysis scoring. Automated image analysis and pathologist scores were highly concordant [intraclass correlation coefficient (ICC) = 0.873 and 0.737]. Concordances at moderate and high cutoff values were better than at low cutoff values significantly. For SP263 and 22C3, the concordances in squamous cell carcinomas were better than adenocarcinomas (SP263 ICC = 0.884 vs 0.783; 22C3 ICC = 0.782 vs 0.500). In addition, our automated immune cell proportion scoring (IPS) scores achieved high positive correlation with the pathologists TPS scores.

Conclusions

The novel automated image analysis scoring algorithm permitted quantitative comparison with existing PD-L1 diagnostic assays and demonstrated effectiveness by combining cellular and regional information for image algorithm training. Meanwhile, the fact that concordances vary in different subtypes of NSCLC samples, which should be considered in algorithm development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02898-z.

Precision medicine: Opportunities for health-system pharmacists

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PD-L1 and beyond: Immuno-oncology in cytopathology

Over the past decade, immunotherapy has emerged as one of the most promising cancer treatments. Several monoclonal antibodies targeting the programmed death 1 (PD-1)/ programmed death ligand-1 (PD-L1) pathway have been integrated into standard-of-care treatments for a wide range of cancer types. Although all the available PD-L1 immunohistochemistry (IHC) assays have been developed on formalin-fixed histological specimens, a growing body of research has recently suggested the feasibility of PD-L1 testing on cytological samples. Although promising results have been reported, several important issues still need to be addressed. Among these are pre-analytical issues, cyto-hystological correlation, and inter-observer agreement. This review will briefly summarise the knowledge gaps and future directions of cytopathology in the immuno-oncology scenario.

Fatal Adverse Events Associated With Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background: Immune checkpoint inhibitors (ICIs) have previously been reported to have a promising potential in terms of the improvement of outcomes in non–small cell lung cancer (NSCLC). Fatal adverse events (FAEs) of ICIs are relatively uncommon, and the incidence and risk in NSCLC remain unclear. In the present study, we conducted a systematic review and meta-analysis to evaluate the risk of FAEs in NSCLC patients administered with ICIs.

Methods: Potentially relevant studies were identified in PubMed, EMBASE, and Cochrane library database from inception to September 16, 2020. The systematic review and meta-analysis included randomized controlled trials that reported treatment-related FAEs in NSCLC. The pooled incidence and risk ratios (RRs) were calculated to evaluate prospective risk.

Results: Twenty clinical trials that included a total of 13,483 patients were selected for the meta-analysis. The overall incidence of FAEs was 0.65% [95% confidence interval (CI) = 0.31–1.07, I² = 50.2%] in ICI monotherapy, 1.17% (95% CI = 0.74–1.69, I² = 56.3%) in chemotherapy, and 2.01% (95% CI = 1.42–2.69, I² = 5.9%) in the combination therapy (ICI and chemotherapy). ICI monotherapy was associated with lower incidence of FAEs caused by blood system disorders (RR = 0.23, 95% CI = 0.07–0.73, P = 0.013, I² = 0%) and infectious diseases (RR = 0.29, 95% CI = 0.13–0.63, P = 0.002, I² = 0%). The incidence of pneumonitis significantly increased in immunotherapy (RR = 5.72, 95% CI = 1.14–28.80, P = 0.03, I² = 0%).

Conclusions: The results of the present study demonstrate that ICI monotherapy decreases the risk of FAEs, whereas the combined regimens with chemotherapy have the opposite tendency as compared to conventional chemotherapy. While the patients who received chemotherapy suffered the risks of death mainly from myelosuppression and infection, those who received immunotherapy were mainly threatened by immune-related pneumonitis.

Relevance of PD-L1 Non-Coding Polymorphisms on the Prognosis of a Genetically Admixed NSCLC Cohort

Purpose

Although non-small cell lung cancer (NSCLC) remains a deadly disease, new predictive biomarkers have emerged to assist in managing the disease, of which one of the most promising is the programmed death‐ligand 1 (PD-L1). Each, PD-L1 variant seem to modulate the function of immune checkpoints differently and affect response to adjuvant treatment and outcome in NSCLC patients. We thus investigated the influence of these PD-L1 genetic variations in genetically admixed NSCLC tissue samples, and correlated these values with clinicopathological characteristics, including prognosis.

Materials and Methods

We evaluated PD-L1 non-coding genetic variants and protein expression in lung adenocarcinomas (ADC), squamous cell carcinomas (SqCC), and large cell carcinomas (LCC) in silico. Microarray paraffin blocks from 70 samples of ADC (N=33), SqCC (N=24), and LCC (N=13) were used to create PD-L1 multiplex immunofluorescence assays with a Cell Signaling E1L3N clone. Fifteen polymorphisms of the PD-L1 gene were investigated by targeted sequencing and evaluated in silico using dedicated tools.

Results

Although PD-L1 polymorphisms seemed not to interfere with protein expression, PD-L1 expression varied among different histological subtypes, as did clinical outcomes, with the rs4742098A>G, rs4143815G>C, and rs7041009G>A variants being associated with relapse (P=0.01; P=0.05; P=0.02, respectively). The rs7041009 GG genotype showed a significant correlation with younger and alive patients compared to carriers of the A allele (P=0.02 and P<0.01, respectively). The Cox regression model showed that the rs7041009 GG genotype may influence OS (P<0.01) as a co-dependent factor associated with radiotherapy and recurrence in NSCLC patients. Furthermore, the Kaplan–Meier survival curves showed that rs7041009 and rs4742098 might impact PPS in relapsed patients. In silico approaches identified the variants as benign.

Conclusion

PD-L1 non-coding variants play an important role in modulating immune checkpoint function and may be explored as immunotherapy biomarkers. We highlight the rs7041009 variant, which impacts OS and PPS in NSCLC patients.

Tissue MicroRNA Expression as a Predictor of Response to Immunotherapy in NSCLC Patients

Introduction

Expression of PD-L1 protein on tumor cells, which is so far the only validated predictive factor for immunotherapy, is regulated by epigenetic and genetic factors. Among the most important ones that regulate gene expression are microRNAs.

Materials and Methods

The study included 60 patients with NSCLC who underwent first or second line immunotherapy with pembrolizumab or nivolumab. FFPE materials were collected before the start of immunotherapy. We examined relative expression of microRNAs (miR-141, miR-200a, miR-200b, miR-200c, miR-429, miR-508-3p, miR-1184, miR-1255a) and PD-L1 mRNA expression. Copy number variation (CNV) of PD-L1 gene by qPCR and FISH methods were assessed. Two single nucleotide polymorphisms (SNPs) in promoter region of PD-L1 gene (rs822335 and rs822336) were examined. Expression of PD-L1 protein on tumor cells was assessed by immunohistochemistry (IHC). The response rate to immunotherapy and progression free survival (PFS) measured in weeks and overall survival (OS) measured in months from the start of immunotherapy were evaluated.

Results

Response to immunotherapy was observed in nine patients (15%, including one complete response), disease stabilization in 22 patients (36.7%), and progression in 29 patients (48.3%). Significantly higher (p=0.015) expression of miR-200b and significantly lower (p=0.043) expression of miR-429 were observed in responders compared to patients who did not respond to immunotherapy. The median PFS in the whole group of patients was 16 weeks, and the median OS was 10.5 month. In univariate analysis, the median PFS was significantly higher in patients with high miR-200b expression (HR=0.4253, 95%CI: 0.1737–1.0417, p=0.05) and high miR-508 expression (HR=0.4401, 95%CI: 0.1903–1.0178, p=0.05) and with low expression of miR-429 (HR=0.1288, 95%CI: 0.01727–0.9606, p=0.0456) compared to patients with low and high expression of these molecules, respectively. The median OS was higher in patients with low expression of miR-429 (HR=0,6288, 95%CI: 0,3053–1,2949, p=0.06) compared with patients with high expression of this microRNA. In multivariate analysis, we found that patients with PD-L1 expression on ≥1% of tumor cells compared to patients without PD-L1 expression on cancer cells had a significantly lower risk of progression (HR=0.3857, 95%CI: 0.1612–0.9226, p=0.0323) and death (HR=0.377, 95%CI: 0.1636–0.8688, p=0.022).

Conclusion

The miR-200b and miR-429 molecules in tumor cells seem to have greatest impact on the effectiveness of immunotherapy in NSCLC patients.

Survival Impact of Aggressive Treatment and PD-L1 Expression in Oligometastatic NSCLC

Background: Studies have shown that aggressive treatment of non-small cell lung cancer (NSCLC) with oligometastatic disease improves the overall survival (OS) compared to a palliative approach and some immunotherapy checkpoint inhibitors, such as anti-programmed cell death ligand 1 (PD-L1), anti-programmed cell death protein 1 (PD-1), and T-Lymphocyte-associated antigen 4 (CTLA-4) inhibitors are now part of the standard of care for advanced NSCLC. However, the prognostic impact of PD-L1 expression in the oligometastatic setting remains unknown. Methods: Patients with oligometastatic NSCLC were identified from the patient database of the Centre hospitalier de l’Université de Montréal (CHUM). “Oligometastatic disease” definition chosen is one synchronous metastasis based on the M1b staging of the eight IASLC (The International Association for the Study of Lung Cancer) Classification (within sixth months of diagnosis) or up to three cerebral metastasis based on the methodology of the previous major phase II randomized study of Gomez et al. We compared the OS between patients receiving aggressive treatment at both metastatic and primary sites (Group A) and patients receiving non-aggressive treatment (Group B). Subgroup analysis was performed using tumor PD-L1 expression. Results: Among 643 metastatic NSCLC patients, we identified 67 patients with oligometastasis (10%). Median follow-up was 13.3 months. Twenty-nine patients (43%) received radical treatment at metastatic and primary sites (Group A), and 38 patients (57%) received non-aggressive treatment (Group B). The median OS (mOS) of Group A was significantly longer than for Group B (26 months vs. 5 months, p = 0.0001). Median progression-free survival (mPFS) of Group A was superior than Group B (17.5 months vs. 3.4 months, p = 0.0001). This difference was still significant when controlled for primary tumor staging: stage I (p = 0.316), stage II (p = 0.024), and stage III (p = 0.001). In the cohort of patients who were not treated with PD-L1 inhibitors, PD-L1 expression negatively correlated with mOS. Conclusions: Aggressive treatments of oligometastatic NSCLC significantly improve mOS and mPFS compared to a more palliative approach. PD-L1 expression is a negative prognostic factor which suggests a possible role for immunotherapy in this setting.

Clinical evaluation of a laboratory-developed test using clone E1L3N for the detection of PD-L1 expression status in non-small cell lung cancer

Background

Programmed death ligand 1 (PD‐L1) has been used as a diagnostic marker to identify patients that will benefit from immune checkpoint inhibitors in non‐small cell lung cancer (NSCLC). Immunohistochemistry with E1L3N clone is one of the most widely used and inexpensive laboratory‐developed tests for PD‐L1, but still need to be compared and validated with standard methods for clinical application.

Methods

We investigated the performance of E1L3N clone for PD‐L1 testing in 299 tumor tissues of NSCLC patients and its comparability with FDA‐approved 22C3 clone.

Results

The results show that the negative coincidence rate, weak positive coincidence rate, and positive coincidence rate were 97.4%, 92.2%, and 97.6% using the E1L3N assay relative to the 22C3 assay, respectively. An overall agreement of 96.3% was achieved between these two assays. We also found that the overall concordances were 97.8% and 93.9% for PD‐L1 detection in large and small specimens, respectively, and no significant difference was obtained between these two assays (p = 0.076). In addition, the expression of PD‐L1 was not detected in tumor tissues of benign lung disease using both the E1L3N and 22C3 assays.

Conclusion

E1L3N can be used as a reliable alternative antibody clone to evaluate PD‐L1 expression status for NSCLC patients.

Molecular testing and targeted therapy for non-small cell lung cancer: Current status and perspectives

Molecular testing has become a mandatory component of the non-small cell lung cancer (NSCLC) management. The detection of EGFR, BRAF and MET mutations as well as the analysis of ALK, ROS1, RET and NTRK translocations have already been incorporated in the NSCLC diagnostic standards, and the inhibitors of these kinases are in routine clinical use. There are emerging biomarkers, e.g., KRAS G12C substitutions and HER2 activating alterations, which are likely to enter NSCLC guidelines upon the approval of the corresponding drugs. In addition to genetic examination, NSCLCs are usually subjected to the analysis of PD-L1 protein expression in order to direct the use of immune checkpoint inhibitors. Comprehensive NSCLC testing for multiple predictive markers requires the analysis of distinct biological molecules (DNA, RNA, proteins) and, therefore, the involvement of different analytical platforms (PCR, DNA sequencing, immunohistochemistry, FISH). There are ongoing efforts aimed at the integration of multiple NSCLC molecular assays into a single diagnostic pipeline.

PD-L1 immunohistochemistry in non-small-cell lung cancer: unraveling differences in staining concordance and interpretation

Programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) is accepted as a predictive biomarker for the selection of immune checkpoint inhibitors. We evaluated the staining quality and estimation of the tumor proportion score (TPS) in non-small-cell lung cancer during two external quality assessment (EQA) schemes by the European Society of Pathology. Participants received two tissue micro-arrays with three (2017) and four (2018) cases for PD-L1 IHC and a positive tonsil control, for staining by their routine protocol. After the participants returned stained slides to the EQA coordination center, three pathologists assessed each slide and awarded an expert staining score from 1 to 5 points based on the staining concordance. Expert scores significantly (p < 0.01) improved between EQA schemes from 3.8 (n = 67) to 4.3 (n = 74) on 5 points. Participants used 32 different protocols: the majority applied the 22C3 (56.7%) (Dako), SP263 (19.1%) (Ventana), and E1L3N (Cell Signaling) (7.1%) clones. Staining artifacts consisted mainly of very weak or weak antigen demonstration (63.0%) or excessive background staining (19.8%). Participants using CE-IVD kits reached a higher score compared with those using laboratory-developed tests (LDTs) (p < 0.05), mainly attributed to a better concordance of SP263. The TPS was under- and over-estimated in 20/423 (4.7%) and 24/423 (5.7%) cases, respectively, correlating to a lower expert score. Additional research is needed on the concordance of less common protocols, and on reasons for lower LDT concordance. Laboratories should carefully validate all test methods and regularly verify their performance. EQA participation should focus on both staining concordance and interpretation of PD-L1 IHC.

Biomarkers for precision immunotherapy in the metastatic setting: hope or reality?

Precision immunotherapy is a crucial approach to improve the efficacy of anti-cancer treatments, particularly in the metastatic setting. In this respect, accurate patient selection takes advantage of the multidimensional integration of patients' clinical information and tumour-specific biomarkers status. Among these biomarkers, programmed death-ligand 1, tumour-infiltrating lymphocytes, microsatellite instability, mismatch repair and tumour mutational burden have been widely investigated. However, novel tumour-specific biomarkers and testing methods will further improve patients' outcomes. Here, we discuss the currently available strategies for the implementation of a precision immunotherapy approach in the clinical management of metastatic solid tumours and highlight future perspectives.

Gray E. Tumour PD-L1 Expression in Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis

Antibodies against programmed death-1 (PD-1), and its ligand, (PD-L1) have been approved recently for the treatment of small-cell lung cancer (SCLC). Although there are previous reports that addressed PD-L1 detection on tumour cells in SCLC, there is no comprehensive meta-analysis on the prevalence of PD-L1 expression in SCLC. We performed a systematic search of the PubMed, Cochrane Library and EMBASE databases to assess reports on the prevalence of PD-L1 expression and the association between PD-L1 expression and overall survival (OS). This meta-analysis included 27 studies enrolling a total of 2792 patients. The pooled estimate of PD-L1 expression was 26.0% (95% CI 17.0–37.0), (22.0% after removing outlying studies). The effect size was significantly heterogeneous (I² = 97.4, 95% CI: 95.5–98.5, p < 0.0001).Positive PD-L1 expression was a favourable prognostic factor for SCLC but not statistically significant (HR = 0.86 (95% CI (0.49–1.50), p = 0.5880; I² = 88.7%, p < 0.0001). Begg’s funnel plots and Egger’s tests indicated no publication bias across included studies (p > 0.05). Overall, there is heterogeneity in the prevalence of PD-L1 expression in SCLC tumour cells across studies. This is significantly moderated by factors such as immunohistochemistry (IHC) evaluation cut-off values, and assessment of PD-L1 staining patterns as membranous and/or cytoplasmic. There is the need for large size, prospective and multicentre studies with well-defined protocols and endpoints to advance the clinical value of PD-L1 expression in SCLC.

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.

PD-L1 in Systemic Immunity: Unraveling Its Contribution to PD-1/PD-L1 Blockade Immunotherapy

The use of monoclonal antibodies targeting PD-1/PD-L1 axis completely changed anticancer treatment strategies. However, despite the significant improvement in overall survival and progression-free survival of patients undergoing these immunotherapy treatments, the only clinically accepted biomarker with some prediction capabilities for the outcome of the treatment is PD-L1 expression in tumor biopsies. Nevertheless, even when having PD-L1-positive tumors, numerous patients do not respond to these treatments. Considering the high cost of these therapies and the risk of immune-related adverse events during therapy, it is necessary to identify additional biomarkers that would facilitate stratifying patients in potential responders and non-responders before the start of immunotherapies. Here, we review the utility of PD-L1 expression not only in tumor cells but in immune system cells and their influence on the antitumor activity of immune cell subsets.

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.

Analysis of real-world PD-L1 IHC 28-8 and 22C3 pharmDx assay utilisation, turnaround times and analytical concordance across multiple tumour types

Aims

Programmed death-1/programmed death ligand 1 (PD-1/PD-L1) inhibitor therapy is accompanied by companion or complementary PD-L1 testing in some tumour types. We investigated utilisation of the Dako PD-L1 IHC 28-8 and 22C3 pharmDx assays and the Ventana PD-L1 (SP142) assay and evaluated concordance between the 28-8 and 22C3 assays in a real-world cohort of patients tested at a single US national reference laboratory.

Methods

NeoGenomics Laboratories performed PD-L1 testing on tumour samples between October 2015 and March 2018. PD-L1 test results were matched with patient characteristics using unique identifiers. Concordance between the 28-8 and 22C3 assays was evaluated in matched tumour samples. Data were evaluated across multiple tumour types and in subgroups of patients with lung cancer, melanoma, squamous cell carcinoma of the head and neck, and urothelial carcinoma.

Results

62 180 individual PD-L1 tests were conducted on samples from 55 652 patients. PD-L1 test volume increased ~10-fold over the period evaluated. Test failure rates were typically low, and test turnaround time (TAT) ranged between 2 and 4 days. Concordance between the 28-8 and 22C3 assays was strong in the overall population and across tumour type subgroups (Kendall’s tau correlations of 0.94 and 0.92–0.98, respectively).

Conclusions

Test failure rates for PD-L1 tests were low and TAT remained reasonable despite marked increases in test volume. Concordance was high between the 28-8 and 22C3 assays across a range of tumour types and biopsy locations. These findings add to the literature showing high concordance between the 28-8 and 22C3 assays.

Comprehensive assessment of PD-L1 immunohistochemistry on paired tissue and cytology specimens from non-small cell lung cancer

OBJECTIVES

PD-L1 staining assessed by immunohistochemistry (IHC) is a predictive biomarker used to select advanced stage non-small cell lung carcinoma (NSCLC) patients who are likely to respond to PD-1/PD-L1 inhibitors. Cytology specimens represent a significant percentage of the diagnostic samples and additional data are required to show that they provide reliable PD-L1 results when compared to tissue specimens. We aimed to compare PD-L1 staining obtained from patient-matched tissue and cytology specimens. We also want to assess the feasibility of PD-L1 testing on cell blocks with two assays by evaluating the intra- and inter-observer agreement and the level of difficulty for determining the percentage of stained tumor cells (TPS).

MATERIALS AND METHODS

Forty-six patients with NSCLC were selected. Each patient provided a surgical specimen and a cytology sample (cell block) and/or a biopsy at diagnosis. PD-L1 staining using Agilent PD-L1 IHC 28-8 pharmDx and VENTANA PD-L1 (SP263) assays was evaluated by four pathologists using the TPS. Sixty slides were rescored to document intra-observer agreement. Pathologists were asked to score the level of difficulty for evaluating PD-L1 TPS for each slide. Fleiss's and Cohen's kappas (k) were used to assess the agreement between paired specimens as well as intra- and inter-observer agreement.

RESULTS

The concordance in PD-L1 TPS between cell blocks and surgical specimens (k varying from 0.56 to 0.82) or biopsies (k from 0.43 to 0.81) was moderate to substantial, depending on the cut-off. On cell blocks, inter-observer agreement was substantial (k from 0.74 to 0.82) and intra-observer agreement was almost perfect (k from 0.85 to 0.93). The perceived difficulty of PD-L1 evaluation of cell blocks was not different from surgical specimens but more difficult than biopsy samples.

CONCLUSION

PD-L1 TPS was concordant between cell blocks and tissue specimens, mainly at 10, 25 and 50 % cut-offs. PD-L1 evaluation on cell blocks was feasible and reproducible between different observers and assays.

Selected highlights of the 2019 Pulmonary Pathology Society Biennial Meeting: PD-L1 test harmonization studies

Immune checkpoint inhibitors (ICI) including programmed death 1 (PD-1) inhibitors, such as nivolumab and pembrolizumab, or programmed death ligand 1 (PD-L1) inhibitors, such as atezolizumab and durvalumab, have recently emerged in advanced stage lung cancer as new standards of care. They are now indicated in first- line and second- or later-line treatment of metastatic or locally-advanced stage III non-small cell lung cancer (NSCLC), as well as for metastatic small cell lung cancer (SCLC), as single agent immunotherapy or in combination with chemotherapy. Four PD-L1 immunohistochemistry (IHC) assays have been established and validated in randomized trials, each for a specific ICI. They use different primary monoclonal antibodies, platforms and detection systems, as well as different scoring systems to assess PD-L1 expression either by tumor cells (TCs) and/or by infiltrating immune cells (ICs). Most studies have shown a close analytical performance of three of these clinically-validated standardized assays, but their use restricted to dedicated platforms, which are not all available in most laboratories, questions their applicability. In addition, the relative high costs of the assays have led to the development of in-house protocols in many pathology laboratories. Their use in clinical practice to assess the predictive value of PD-L1 expression for prescription of ICI raises the issue of their reliability and their validation as compared to standardized assays. This article discusses the main comparative studies available between LDT and assays, with clear evidence that LDT can reach a performance equivalent to the trial-validated assays. The requirements are an adequate validation as compared to an appropriate standard, and the participation to external quality assurance programs and training programs for PD-L1 IHC assessment for pathologists.

Improving the Diagnostic Accuracy of the PD-L1 Test with Image Analysis and Multiplex Hybridization

Targeting of the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis with checkpoint inhibitors has changed clinical practice in non-small cell lung cancer (NSCLC). However, clinical assessment remains complex and ambiguous. We aim to assess whether digital image analysis (DIA) and multiplex immunofluorescence can improve the accuracy of PD-L1 diagnostic testing. A clinical cohort of routine NSCLC patients reflex tested for PD-L1 (SP263) immunohistochemistry (IHC), was assessed using DIA. Samples of varying assessment difficulty were assessed by multiplex immunofluorescence. Sensitivity, specificity, and concordance was evaluated between manual diagnostic evaluation and DIA for chromogenic and multiplex IHC. PD-L1 expression by DIA showed significant concordance (R² = 0.8248) to manual assessment. Sensitivity and specificity was 86.8% and 91.4%, respectively. Evaluation of DIA scores revealed 96.8% concordance to manual assessment. Multiplexing enabled PD-L1+/CD68+ macrophages to be readily identified within PD-L1+/cytokeratin+ or PD-L1-/cytokeratin+ tumor nests. Assessment of multiplex vs. chromogenic IHC had a sensitivity and specificity of 97.8% and 91.8%, respectively. Deployment of DIA for PD-L1 diagnostic assessment is an accurate process of case triage. Multiplex immunofluorescence provided higher confidence in PD-L1 assessment and could be offered for challenging cases by centers with appropriate expertise and specialist equipment.

Evaluation of an online training tool for scoring programmed cell death ligand-1 (PD-L1) diagnostic tests for lung cancer

BACKGROUND

Numerous studies indicate that higher tumour programmed cell death ligand-1 (PD-L1) expression is associated with greater response to anti-programmed cell death-1 (PD-1)/PD-L1 immunotherapy in non-small cell lung cancer (NSCLC). In the era of precision medicine, there is a need to provide reliable, standardised training for pathologists to improve their accuracy of interpretation and scoring, as the results are used directly to inform clinical decisions. Here we present findings regarding reader reproducibility of PD-L1 tumour cell (TC) staining scoring for NSCLC using a PD-L1 e-trainer tool as part of a PD-L1 immunohistochemistry reader training course.

METHODS

The PD-L1 training course was developed based on the use of VENTANA PD-L1 (SP263) and Dako PD-L1 IHC PharmDx 22C3 stained NSCLC samples in combination with a PD-L1 e-trainer tool. Five-hundred formalin-fixed, paraffin-embedded archival samples were obtained from commercial sources and stained for PD-L1. Slides were scored by two expert pathologists, then scanned to produce digital images and re-scored. Thirty-three cases were selected and sorted into three sets: a training set and two self-assessment tests (pre-test and 'competence' test). Participants (all selected board-certified pathologists) received face-to-face training including use of an e-trainer tool. Statistical analyses were performed using the competence test set. Overall percentage agreement (OPA) was assessed between the participant pathologists' registered scores and the reference scores assigned by expert pathologists at clinically relevant PD-L1 cut-offs (≥1%, ≥25% and ≥ 50%).

RESULTS

Seven sessions were held and 69 participant pathologists completed the training. Inter-reader concordance indicated high OPA (85-95%) for PD-L1 TC scoring at clinically relevant cut-offs, with Fleiss' Kappa > 0.5.

CONCLUSIONS

Use of this web-based training tool incorporated into classroom-style training was associated with an overall moderately good level of inter-reader reproducibility at key cut-offs for TC PD-L1 expression testing in NSCLC. Overall, the online training tool offers a means of standardised training for practising pathologists in a clinical setting.

Cachexia - sarcopenia as a determinant of disease control rate and survival in non-small lung cancer patients receiving immune-checkpoint inhibitors

PURPOSE

The metabolic changes associated with cachexia - sarcopenia syndrome might down-regulate antitumor immunity. We hypothesized that this syndrome reduces efficiency of immune checkpoint inhibitors (ICPI) in non-small cell lung cancer (NSCLC).

METHODS

The records of 142 consecutive NSCLC patients receiving first- or second-line anti-Programmed cell death protein 1) ICPI were reviewed. Response evaluation according to Response Evaluation Criteria in Solid Tumors 1.1 was performed at the eighth week of immunotherapy. Pretreatment cachexia was defined as a body-weight loss of 5% or more in the previous 6 months. Sarcopenia was estimated with the third lumbar skeletal muscle mass index (mSMI) and was evaluated before immunotherapy and at the eighth week. A decrease by 5% or more of the mSMI was considered as an evolving sarcopenia. The endpoints were disease control rate (DCR), progression-free (PFS) and overall survival (OS).Logistic regression model and Cox model took into account others covariables known to influence ICPI efficiency, particularly Programmed Death -Ligand 1 tumor cell score, Eastern Cooperative Oncology Group performance status and common somatic mutational status.

RESULTS

In multivariate analysis, cachexia - sarcopenia syndrome reduced the probability of achieving a disease control and were associated with a shorter survival. Patients without cachexia had a better probability to achieve disease control in comparison with those who did not experience cachexia (59.9 % and 41.1 %, respectively; odds ratio 95 % (confidence interval [95 %CI]): 2.60 (1.03-6.58)). Patients with cachexia had a shorter OS when compared with those without cachexia (hazard ratios [HR] (95 %CI): 6.26 (2.23-17.57)). Patients with an evolving sarcopenia had a shorter PFS and OS, with HR (95 %CI): 2.45 (1.09-5.53) and 3.87 (1.60-9.34) respectively.

CONCLUSION

Cachexia - sarcopenia syndrome negatively influences patients' outcome during anti-PD-1 ICPI therapy.

PD-1/PD-L1 pathway: current researches in cancer

Cancer immunotherapy has been accompanied by promising results over the past few years. Programmed Cell Death Protein 1 (PD-1) plays a vital role in inhibiting immune responses and promoting self-tolerance through modulating the activity of T-cells, activating apoptosis of antigen-specific T cells and inhibiting apoptosis of regulatory T cells. Programmed Cell Death Ligand 1 (PD-L1) is a trans-membrane protein that is considered to be a co-inhibitory factor of the immune response, it can combine with PD-1 to reduce the proliferation of PD-1 positive cells, inhibit their cytokine secretion and induce apoptosis. PD-L1 also plays an important role in various malignancies where it can attenuate the host immune response to tumor cells. Based on these perspectives, PD-1/PD-L1 axis is responsible for cancer immune escape and makes a huge effect on cancer therapy. This review is aimed to summarize the role of PD-1 and PD-L1 in cancer, looking forward to improve the therapy of cancer.

The emerging development of tumor mutational burden in patients with NSCLC

Immunocheckpoint inhibitors (ICIs) which target PD-1 and CTLA-4 have dramatically changed the history of non-small-cell lung cancer treatment. Multiple biomarkers especially tumor mutational burden (TMB) have been raised to be potential predictors of response to ICIs. However, great value of TMB has been observed in patients who receive ICIs monotherapy instead of ICIs combination therapy from latest exploratory studies. Thus, the innovative concept of TMB needs to be identified. This study uncovers specific aspects of TMB including signatures of TMB, factors related with variation, racial differences, heterogeneity between tissue TMB and blood-based TMB. Additionally, more and more factors are found valuable in clinical trials, suggesting that more markers should be further investigated as interesting candidates for response prediction beyond TMB.

Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

Background

To achieve optimal outcomes, an individual approach is needed in the treatment and care of patients. The potential value of tumor mutational burden (TMB) status and/or programmed cell death ligand 1 (PD-L1) expression as biomarkers to predict which patients are most likely to respond to checkpoint inhibitors has been explored in many studies. The goal of this targeted literature review is to identify data available for TMB status and/or PD-L1 expression that predict response to checkpoint inhibitors and/or anti–cytotoxic T-lymphocyte–associated protein 4 (CTLA-4) antibodies.

Methods

Targeted literature searches were performed using electronic medical databases (MEDLINE, Embase, and BIOSIS) and internet searches of specified sites. Bibliographies of key systematic literature reviews and meta-analyses also were reviewed for studies of interest.

Results

The review identified 27 studies of non-small cell lung cancer (NSCLC), 40 studies of melanoma, 10 studies of urothelial cancer, and 5 studies of renal cell cancer indications. Studies also were identified in other cancer types, e.g., colorectal, breast, gastric, and Merkel cell cancer and squamous-cell carcinoma of the head and neck.

Twelve trials, including six in NSCLC and four in melanoma, evaluated TMB as a predictor of outcomes. A TMB of ≥10 mutations per megabase was shown to be an effective biomarker in the CheckMate 227 study. PD-L1 expression was included in the majority of identified studies and was found to predict response in in melanoma and in all types of NSCLC. Prediction of response was not a prespecified analysis in some studies; others had small sample sizes and wide confidence intervals. A clear predictive trend for PD-L1 expression was not identified in renal, breast, gastric, or Merkel cell cancer.

Conclusion

Based on data contained in this review, assessment of TMB status and PD-L1 expression may help enhance the prediction of response to checkpoint inhibition in some tumors, such as NSCLC and melanoma. In this rapidly growing area of research, further exploratory biomarkers are being investigated including tumor-infiltrating lymphocytes, immune profiling (e.g., effector T cells or regulatory T cells), epigenetic signatures, T-cell receptor repertoire, proteomics, microbiome, and metabolomics.

Predictive effect of PD-L1 expression for immune checkpoint inhibitor (PD-1/PD-L1 inhibitors) treatment for non-small cell lung cancer: A meta-analysis

BACKGROUND

Programmed death-ligand-1 (PD-L1) is a well-known predictive biomarker in non-small cell lung cancer (NSCLC) patients, however, its accuracy remains controversial. Here, we investigated the correlation between PD-L1 expression level and efficacy of its inhibitors, and hence assessed the predictive effect of PD-L1 expression.

METHODS

Studies that evaluated the efficacy of programmed death-1 (PD-1)/ PD-L1 inhibitors in advanced NSCLC patients according to tumor PD-L1 expression levels were searched for on Medline, Cochrane Library, and Embase. The pooled risk ratio (RR) and 95% confidence intervals (95% CIs) were calculated for the objective response rate (ORR) with overall survival (OS) and progression-free survival (PFS) were measured in terms of hazard ratio (HR) and the corresponding 95% CIs.

RESULTS

1432 NSCLC patients from six randomized controlled trials (RCTs) were included and three PD-1/PD-L1 inhibitors (atezolizumab, nivolumab, and pembrolizumab) were used to treat the patients. A significantly higher ORR was observed in the high PD-L1 expression group compared to the low expression group (0.35 [95% CI, 0.30-0.40] vs 0.11 [95% CI, 0.09-0.14]). The results of the subgroup analysis, grouped by the type of drugs and antibodies which assess immune checkpoint inhibitors were identical with the pooled result. However, our study showed that PD-L1 expression was neither prognostic nor predictive of overall survival (OS) or progression-free survival (PFS) in patients treated with PD-1/PD-L1 inhibitors compared to chemotherapy.

CONCLUSIONS

PD-L1 can be a predictive biomarker for ORR. Nevertheless, PD-L1 expression is not a good predictive tool for OS and PFS.

Approaches to Tumor Classification in Pulmonary Sarcomatoid Carcinoma

Pulmonary sarcomatoid carcinoma (PSC) is a heterogeneous category of primary lung cancer accounting from 0.3% to 3% of all primary lung malignancies. According to the most recent 2015 World Health Organization (WHO) classification, PSC includes several different variants of malignant epithelial tumors (carcinomas) histologically mimicking sarcomas showing or entirely lacking a conventional component of non-small cell lung cancer (NSCLC). Thus, this rare subheading of lung neoplasms includes pleomorphic carcinoma, spindle cell carcinoma, giant cell carcinoma, pulmonary blastoma, and carcinosarcoma. A diagnosis of PSC may be suspected on small biopsy or cytology, but commonly requires a surgical resection to reach a conclusive definition. The majority of patients with PSC consists of elderly, smoking men with a large, peripheral mass characterized by well-defined margins. However, presentation with a central, polypoid endobronchial lesion is well-documented, particularly in pleomorphic carcinoma and carcinosarcoma showing a squamous cell carcinoma component. As expected, PSC may pose diagnostic problems and immunohistochemistry is largely used when pathologists deal these tumors in routine practice. Indeed, PSC tends to overexpress molecules associated with the epithelial-to-mesenchymal transition, such as vimentin, but the panel of immunostains also includes epithelial markers (cytokeratins, EMA), TTF-1, p40 and negative markers (e.g., melanocytic, mesothelial and sarcoma-related primary antibodies). Although rare, PSC has increased their interest among oncologist community for different reasons: a. identification of the epithelial-to-mesenchymal phenomenon as a major mechanism of secondary resistance to tyrosine kinase inhibitors; b. over-expression of PD-L1 and effective treatment with immunotherapy; c. identification of c-MET exon 14 skipping mutation representing an effective target to crizotinib and other specific inhibitors. In this review, the feasibility of the diagnosis of PSC, its differential diagnosis and novel molecular findings characterizing this group of lung tumor are discussed.

Expression and clinical significance of PD-L1 and BRAF expression in nasopharyngeal carcinoma

Background

The prognostic value of programmed death-ligand 1 (PD-L1) and BRAF expression in nasopharyngeal carcinoma (NPC) is not well-defined. In this study we investigated alterations in PD-L1, BRAF and EGFR by using immunohistochemistry analysis in a cohort of consecutively enrolled NPC patients.

Methods

A retrospective review of 154 NPC patients form our previous study (BMC Cancer. 2013; 13:226) were conducted. Survival and prognostic impacts were analyzed based on PD-L1, BRAF and EGFR expression levels.

Results

One hundred fifty four patients were included in this study. PD-L1 expression was detected in 87.7% of patients; 14.3% had 1–5% PD-L1 expression, 47.4% had 5–49% expression while 26% had ≥50% expression Higher PD-L1 expression was significantly associated with shorter PFS and OS. The median PFS was 25 months (95% CI 15.7–34.3 months) and OS was 35 months (95% CI 22.60–47.4 months) for patients with PD-L1 expression ≥50%; both median PFS and OS were not yet reached for patients with PD-L1 expression < 50%. PFS was significantly higher in BRAF mutation positive patients (5-year PFS: 55.1% vs. 30.8%, P = 0.044).

Conclusion

Tumor PD-L1 expression and BRAF mutation are associated with poor outcomes in patients with NPC. This study was retrospectively registered in ClinicalTrials.gov (NCT03989297) on 2019-6-18.

PD1/PD-L1 Expression in Blastic Plasmacytoid Dendritic Cell Neoplasm

Patients with blastic plasmacytoid dendritic cell neoplasm (BPDCN) have poor outcomes despite intensive chemotherapy, underscoring the need for novel therapeutic approaches. The expression status of PD1/PD-L1 in BPDCN remains unknown. We evaluated PD1/PD-L1 by immunohistochemistry and RNAseq expression profiling in a cohort of BPDCN patients. The study group included 28 patients with a median age of 66.8 years (range, 22.8–86.7), 22 men and 6 women. PD-L1 expression was detected by immunohistochemistry in 10/21 (47.6%) cases. PD-L1 expression had a median H-score of 157. The H-score was ≥60 in 7 patients. PD-L1 protein levels (H-score) were proportional to normalized PD-L1 mRNA transcript levels (CD274 mRNA). In addition, high-level PD-L1 expression correlated with higher numbers of PD1-positive cells within BPDCN tumors. There was no correlation between clinicopathologic characteristics and PD-L1 expression status. Similarly, there was no significant difference in overall survival between patients with PD-L1-positive and PD-L1-negative BPDCN (median 12 vs. 23 month, respectively; p = 0.743). In conclusion, PD-L1 expression by tumor cells is detectable in a sizeable subset of patients with BPDCN, suggesting that exploration of the effectiveness of therapeutic inhibition of the PD1/PD-L1 axis in patients with refractory or progressive BPDCN is warranted.