PD-L1 expression on routine samples of non-small cell lung cancer: results and critical issues from a 1-year experience of a centralised laboratory

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

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

Programmed Death Ligand-1 and Tumor Mutation Burden Testing of Patients With Lung Cancer for Selection of Immune Checkpoint Inhibitor Therapies: Guideline From the College of American Pathologists, Association for Molecular Pathology, International Association for the Study of Lung Cancer, Pulmonary Pathology Society, and LUNGevity Foundation

CONTEXT.—

Rapid advancements in the understanding and manipulation of tumor-immune interactions have led to the approval of immune therapies for patients with non-small cell lung cancer. Certain immune checkpoint inhibitor therapies require the use of companion diagnostics, but methodologic variability has led to uncertainty around test selection and implementation in practice.

OBJECTIVE.—

To develop evidence-based guideline recommendations for the testing of immunotherapy/immunomodulatory biomarkers, including programmed death ligand-1 (PD-L1) and tumor mutation burden (TMB), in patients with lung cancer.

DESIGN.—

The College of American Pathologists convened a panel of experts in non-small cell lung cancer and biomarker testing to develop evidence-based recommendations in accordance with the standards for trustworthy clinical practice guidelines established by the National Academy of Medicine. A systematic literature review was conducted to address 8 key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were created from the available evidence, certainty of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

RESULTS.—

Six recommendation statements were developed.

CONCLUSIONS.—

This guideline summarizes the current understanding and hurdles associated with the use of PD-L1 expression and TMB testing for immune checkpoint inhibitor therapy selection in patients with advanced non-small cell lung cancer and presents evidence-based recommendations for PD-L1 and TMB testing in the clinical setting.

Determinants of activity and efficacy of anti-PD1/PD-L1 therapy in patients with advanced solid tumors recruited in a clinical trials unit: a longitudinal prospective biomarker-based study

Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer. However, optimal patient selection is still an unmet need. One-hundred-forty-six patients with metastatic cancer candidates to ICI at the Hospital Clinic of Barcelona Clinical Trials Unit were prospectively recruited in this observational study. Blood samples were collected at different timepoints, baseline LIPI score calculated and pre-ICI archived tissues retrieved to evaluate PD-L1, tumor-infiltrating lymphocytes (TILs) and PD1 mRNA levels. Tumor assessments were centrally reviewed by RECIST 1.1 criteria. Associations with overall response rates (ORR), durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) were performed with univariable/multivariable logistic and Cox regressions, where appropriate. At a median follow-up of 26.9 months, median PFS and OS were 2.7 and 12.9 months. Response rates were 17.8% with duration of response (DOR) of 4.4 months. LIPI score was independently associated with PFS (p = 0.025) and OS (p < 0.001). Immunotherapy-naïve status was independently associated with better PFS (p = 0.005). Time-to-best response (TTBR) and ORR (p < 0.001 both) were associated with better OS at univariate analysis. PFS and DOR were moderately correlated with OS (p < 0.001 both). A PD-L1 10% cut-off detected worse/best responders in terms of ORR (univariate p = 0.011, multivariate p = 0.028) and DCB (univariate p = 0.043). PD1 mRNA levels were strikingly associated to complete responses (p = 0.021). To resume, in our prospective observational pan-cancer study, baseline LIPI score, immunotherapy-naïve status, cancer type and RT before starting ICI were the most relevant clinical factors independently correlated with immunotherapy outcomes. Longer TTBR seemed to associate with better survival, while PD1 mRNA and PD-L1 protein levels might be tumor-agnostic predictive factors of response to ICI and should be furtherly explored.

Nationwide differences in cytology fixation and processing methods and their impact on interlaboratory variation in PD-L1 positivity

Programmed death ligand-1 (PD-L1) immunostaining, which aids clinicians in decision-making on immunotherapy for non-small cell lung cancer (NSCLC) patients, is sometimes performed on cytological specimens. In this study, differences in cytology fixation and cell block (CB) processing between pathology laboratories were assessed, and the influence of these differences on interlaboratory variation in PD-L1 positivity was investigated. Questionnaires on cytology processing were sent to all Dutch laboratories. Information gathered from the responses was added to data on all Dutch NSCLC patients with a mention of PD-L1 testing in their cytopathology report from July 2017 to December 2018, retrieved from PALGA (the nationwide network and registry of histo- and cytopathology in the Netherlands). Case mix-adjusted PD-L1 positivity rates were determined for laboratories with known fixation and CB method. The influence of differences in cytology processing on interlaboratory variation in PD-L1 positivity was assessed by comparing positivity rates adjusted for differences in the variables fixative and CB method with positivity rates not adjusted for differences in these variables. Twenty-eight laboratories responded to the survey and reported 19 different combinations of fixation and CB method. Interlaboratory variation in PD-L1 positivity was assessed in 19 laboratories. Correcting for differences in the fixative and CB method resulted in a reduction (from eight (42.1%) to five (26.3%)) in the number of laboratories that differed significantly from the mean in PD-L1 positivity. Substantial variation in cytology fixation and CB processing methods was observed between Dutch pathology laboratories, which partially explains the existing considerable interlaboratory variation in PD-L1 positivity.

Evaluation of the Molecular Landscape in PD-L1 Positive Metastatic NSCLC: Data from Campania, Italy

Background: Immune-checkpoint inhibitors (ICIs) have increased and improved the treatment options for patients with non-oncogene-addicted advanced stage non-small cell lung cancer (NSCLC). However, the role of ICIs in oncogene-addicted advanced stage NSCLC patients is still debated. In this study, in an attempt to fill in the informational gap on the effect of ICIs on other driver mutations, we set out to provide a molecular landscape of clinically relevant oncogenic drivers in programmed death-ligand 1 (PD-L1) positive NSCLC patients. Methods: We retrospectively reviewed data on 167 advanced stage NSCLC PD-L1 positive patients (≥1%) who were referred to our clinic for molecular evaluation of five driver oncogenes, namely, EGFR, KRAS, BRAF, ALK and ROS1. Results: Interestingly, n = 93 (55.7%) patients showed at least one genomic alteration within the tested genes. Furthermore, analyzing a subset of patients with PD-L1 tumor proportion score (TPS) ≥ 50% and concomitant gene alterations (n = 8), we found that n = 3 (37.5%) of these patients feature clinical benefit with ICIs administration, despite the presence of a concomitant KRAS gene alteration. Conclusions: In this study, we provide a molecular landscape of clinically relevant biomarkers in NSCLC PD-L1 positive patients, along with data evidencing the clinical benefit of ICIs in patient NSCLC PD-L1 positive alterations.

Circulating L-Arginine predicts the survival of cancer patients treated with immune checkpoint inhibitors

BACKGROUND

The discovery of immune checkpoint inhibitors (ICIs) has revolutionized the systemic approach to cancer treatment. However, most patients receiving ICIs do not derive benefits. Therefore, it is crucial to identify reliable predictive biomarkers of response to ICIs. One important pathway in regulating immune cell reactivity is L-arginine (ARG) metabolism, essential to T-cell activation. We therefore aimed to evaluate the association between baseline plasma ARG levels and the clinical benefit of ICIs.

PATIENTS AND METHODS

The correlation between ARG levels and clinical ICI activity was assessed by analyzing plasma samples obtained before treatment onset in two independent cohorts of patients with advanced cancer included in two institutional molecular profiling programs (BIP, NCT02534649, n = 77; PREMIS, NCT03984318, n = 296) and from patients in a phase 1 first-in-human study of budigalimab monotherapy (NCT03000257). Additionally, the correlation between ARG levels and ICI efficacy in preclinical settings was evaluated using a syngeneic mouse model of colorectal cancer responsive to ICIs. Using matched PBMC plasma samples, we analyzed the correlation between ARG levels and PBMC features through multiplexed flow cytometry analysis.

RESULTS

In both discovery and validation cohorts, low ARG levels at baseline (<42 μM) were significantly and independently associated with a worse clinical benefit rate, progression-free survival, and overall survival. Moreover, at the preclinical level, the tumor rejection rate was significantly higher in mice with high baseline ARG levels than in those with low ARG levels (85.7% versus 23.8%; P = 0.004). Finally, PBMC immunophenotyping showed that low ARG levels were significantly associated with increased PD-L1 expression in several immune cell subsets from the myeloid lineage.

CONCLUSION

We demonstrate that baseline ARG levels predict ICI response. Plasma ARG quantification may therefore represent an attractive biomarker to tailor novel therapeutic regimens targeting the ARG pathway in combination with ICIs.

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.

Program death ligand-1 immunocytochemistry in lung cancer cytological samples: A systematic review

In this era of personalized medicine, targeted immunotherapies like immune checkpoint inhibitors (ICI) blocking the programmed death‐1 (PD‐1)/program death ligand‐1 (PD‐L1) axis have become an integral part of treating advanced stage non‐small cell lung carcinoma (NSCLC) and many other cancer types. Multiple monoclonal antibodies are available commercially to detect PD‐L1 expression in tumor cells by immunohistochemistry (IHC). As most clinical trials initially required tumor biopsy for PD‐L1 detection by IHC, many of the currently available PD‐1/PD‐L1 assays have been developed and validated on formalin fixed tissue specimens. The majority (>50%) of lung cancer cases do not have a surgical biopsy or resection specimen available for ancillary testing and instead must rely primarily on fine needle aspiration biopsy specimens for diagnosis, staging and ancillary tests. Review of the literature shows multiple studies exploring the feasibility of PD‐L1 IHC on cytological samples. In addition, there are studies addressing various aspects of IHC validation on cytology preparations including pre‐analytical (e.g., different fixatives), analytical (e.g., antibody clone, staining platforms, inter and intra‐observer agreement, cytology‐histology concordance) and post‐analytical (e.g., clinical outcome) issues. Although promising results in this field have emerged utilizing cytology samples, many important questions still need to be addressed. This review summarizes the literature of PD‐L1 IHC in lung cytology specimens and provides practical tips for optimizing analysis.

Plasma proteomics identifies leukemia inhibitory factor (LIF) as a novel predictive biomarker of immune-checkpoint blockade resistance

BACKGROUND

Immune checkpoint blockers (ICBs) are now widely used in oncology. Most patients, however, do not derive benefit from these agents. Therefore, there is a crucial need to identify novel and reliable biomarkers of resistance to such treatments in order to prescribe potentially toxic and costly treatments only to patients with expected therapeutic benefits. In the wake of genomics, the study of proteins is now emerging as the new frontier for understanding real-time human biology.

PATIENTS AND METHODS

We analyzed the proteome of plasma samples, collected before treatment onset, from two independent prospective cohorts of cancer patients treated with ICB (discovery cohort n = 95, validation cohort n = 292). We then investigated the correlation between protein plasma levels, clinical benefit rate, progression-free survival and overall survival by Cox proportional hazards models.

RESULTS

By using an unbiased proteomics approach, we show that, in both discovery and validation cohorts, elevated baseline serum level of leukemia inhibitory factor (LIF) is associated with a poor clinical outcome in cancer patients treated with ICB, independently of other prognostic factors. We also demonstrated that the circulating level of LIF is inversely correlated with the presence of tertiary lymphoid structures in the tumor microenvironment.

CONCLUSION

This novel clinical dataset brings strong evidence for the role of LIF as a potential suppressor of antitumor immunity and suggests that targeting LIF or its pathway may represent a promising approach to improve efficacy of cancer immunotherapy in combination with ICB.

Mature tertiary lymphoid structures predict immune checkpoint inhibitor efficacy in solid tumors independently of PD-L1 expression

Only a minority of patients derive long-term clinical benefit from anti-PD1/PD-L1 monoclonal antibodies. The presence of tertiary lymphoid structures (TLS) has been associated with improved survival in several tumor types. Here, using a large-scale retrospective analysis of three independent cohorts of cancer patients treated with anti-PD1/PD-L1 antibodies, we showed that the presence of mature TLS was associated with improved objective response rate, progression-free survival, and overall survival independently of PD-L1 expression status and CD8+ T-cell density. These results pave the way for using TLS detection to select patients who are more likely to benefit from immune checkpoint blockade.

Considerable interlaboratory variation in PD-L1 positivity in a nationwide cohort of non-small cell lung cancer patients

OBJECTIVES

Immunohistochemical expression of programmed death-ligand 1 (PD-L1) is used as a predictive biomarker for prescription of immunotherapy to non-small cell lung cancer (NSCLC) patients. Accurate assessment of PD-L1 expression is therefore crucial. In this study, the extent of interlaboratory variation in PD-L1 positivity in the Netherlands was assessed, using real-world clinical pathology data.

MATERIALS AND METHODS

Data on all NSCLC patients in the Netherlands with a mention of PD-L1 testing in their pathology report from July 2017 to December 2018 were extracted from PALGA, the nationwide network and registry of histo- and cytopathology in the Netherlands. PD-L1 positivity rates were determined for each laboratory that performed PD-L1 testing, with separate analyses for histological and cytological material. Two cutoffs (1% and 50%) were used to determine PD-L1 positivity. Differences between laboratories were assessed using funnel plots with 95% confidence limits around the overall mean.

RESULTS

6,354 patients from 30 laboratories were included in the analysis of histology data. At the 1% cutoff, maximum interlaboratory variation was 39.1% (32.7%-71.8%) and ten laboratories (33.3%) differed significantly from the mean. Using the 50% cutoff, four laboratories (13.3%) differed significantly from the mean and maximum variation was 23.1% (17.2%-40.3%). In the analysis of cytology data, 1,868 patients from 23 laboratories were included. Eight laboratories (34.8%) differed significantly from the mean in the analyses of both cutoffs. Maximum variation was 41.2% (32.2%-73.4%) and 29.2% (14.7%-43.9%) using the 1% and 50% cutoffs, respectively.

CONCLUSION

Considerable interlaboratory variation in PD-L1 positivity was observed. Variation was largest using the 1% cutoff. At the 50% cutoff, analysis of cytology data demonstrated a higher degree of variation than the analysis of histology data.

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.

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.

Predictive molecular pathology in the time of COVID-19

AIMS

In the time of COVID-19, predictive molecular pathology laboratories must still timely select oncological patients for targeted treatments. However, the need to respect social distancing measures may delay results generated by laboratory-developed tests based on sequential steps a long hands-on time. Laboratory workflows should now be simplified.

METHODS

The organisation of the University of Naples Federico II predictive pathology laboratory was assessed before (March-April 2019) and during (March-April 2020) the Italian lockdown.

RESULTS

The number of patients undergoing single or multiple biomarker testing was similar in 2019 (n=43) and in 2020 (n=45). Considering adequate samples for molecular testing, before the outbreak, next-generation sequencing was mostly used (35/42, 83.3%). Testing six genes had a reagent cost of €98/patient. Conversely, in 2020, almost all cases (38/41, 92.7%) were analysed by automated testing. This latter had for any single assay/gene a significant reagent cost (€95-€136) and a faster mean turnaround time (5.3 vs 7.9 working days).

CONCLUSION

In the times of coronavirus, laboratory fully automated platforms simplify predictive molecular testing. Laboratory staff may be more safely and cost-effectively managed.

Dealing with NSCLC EGFR mutation testing and treatment: A comprehensive review with an Italian real-world perspective

Since their discovery, relevant efforts have been made to optimize the detection approaches to EGFR mutations as well as the clinical management of EGFR-mutated NSCLC. The recent shift from single gene testing to novel comprehensive detection platforms along with the development of new generation tyrosine kinase inhibitors, targeting both common and uncommon EGFR-mutations, is leading to a progressive increase in the number of patients who may benefit from targeted approaches, with subsequent impact on their long-term survival and quality of life. However, a prompt and adequate implementation of the most recent diagnostic and treatment advances in the routine practice often remains critical to be specifically addressed. In this review we provide a complete and updated overview of the different detection platforms and therapeutic options currently available for the clinical management of advanced EGFR-positive NSCLC, summarizing scientific evidence and describing molecular testing as well as treatment practice in the real-word scenario.

A pan-cancer analysis of PD-L1 immunohistochemistry and gene amplification, tumor mutation burden and microsatellite instability in 48,782 cases

PD-L1 immunohistochemistry (IHC) currently has the most Food and Drug Administration (FDA) approvals as a companion diagnostic (CDx) for immunotherapies in specific tumor types; however, multiple other immunotherapy biomarkers exist. We performed this study to examine and report the prevalence of PD-L1 expression in a wide variety of tumor types and examine its relationship to microsatellite instability (MSI), tumor mutational burden (TMB), and CD274 (PD-L1) gene amplification. We performed a retrospective analysis of all cases in which both PD-L1 IHC (using the DAKO 22C3 IHC assay with either tumor proportion score (TPS) or combined positive score (CPS); or the VENTANA SP142 assay with infiltrating immune cell score (IC)) and comprehensive genomic profiling (CGP) were tested at Foundation Medicine between January 2016 and November 2019. Of note, PD-L1 positivity is defined per the CDx indication and tumor proportion score (TPS ≥ 1) for indications without a CDx claim; and TMB positivity is defined as ≥10 mutations/Mb. A total of 48,782 cases were tested for PD-L1 IHC and CGP. Immune cell expression of PD-L1 was more frequently identified than tumor cell expression of PD-L1. We saw a high correlation between PD-L1 expression and CD274 gene amplification (p < 0.0001), MSI and TMB (p < 0.0001), and PD-L1 and TMB (p < 0.0001). In addition, the combination of PD-L1 and TMB identified four unique disease subsets PD-L1^-/TMB^-, PD-L1⁺/TMB^-, PD-L1^-/TMB⁺, and PD-L1⁺/TMB⁺ with varying prevalence dependent on tumor type. Lastly, 50.3% (24527/48782) of the overall cohort was positive for at least one of the CDx or exploratory biomarkers described above. This is the largest pan-cancer analysis of relevant biomarkers associated with response to checkpoint inhibitors to date, including more than 48,000 cases. Additional clinical trials with treatment outcome data in individual tumor types are needed to determine whether the double positive PD-L1⁺/TMB⁺ disease subset would respond best to immunotherapy.

PD-L1 expression in NSCLC: Role of cell blocks and concordance between samples

BACKGROUND

PD-L1 immunohistochemistry is currently performed in patients with advanced non-small cell lung carcinoma (NSCLC) to identify responders to immune checkpoint inhibitors. Cell blocks from fine needle aspiration of NSCLC are frequently used for diagnostic purposes. The aims of the study are to analyze: (a) the distribution of PD-L1 in cell blocks, in comparison to biopsies and surgical specimens; (b) the concordance of PD-L1 in specimens of the same patients.

METHODS

PD-L1 analyses conducted in NSCLCs were retrieved. Cell blocks were prepared with the self-clotting method. PD-L1 was performed with Dako 22C3 on the Ventana BenchMark ULTRA platform. Results were divided by tumor proportion score (TPS) in 3 categories: <1%; 1% to 49%; ≥50%.

RESULTS

A total of 483 samples from 456 patients was collected: 120 cell blocks (24.8%), 307 endoscopic or transthoracic biopsies (63.6%), 56 surgical specimens (11.6%). TPS was: <1% in 230 samples (47.8%), 1% to -49% in 136 (28.3%) and ≥ 50% in 115 (23.9%); in two samples material was insufficient. Statistics did not reveal significant differences in PD-L1 expression among the various materials (χ² = 2.905; P = .574). In 50 samples from 25 patients, PD-L1 was carried out in two samples of the same patients, with moderate agreement (concordance rate: 68.0%, k = 0.469).

CONCLUSION

(a) PD-L1 is similarly distributed in the different materials; (b) PD-L1 shows moderate concordance in different samples of the same patients. PD-L1 may be routinely tested in cell blocks, but interpreted with caution and repeated whenever possible.

The potential of 18F-FDG PET/CT in predicting PDL1 expression status in pulmonary lesions of untreated stage IIIB-IV non-small-cell lung cancer

OBJECTIVES

To investigate the potential of 2-deoxy-2(¹⁸F)fluoro-d-glucose (¹⁸F-FDG) combined positron emission tomography and computed tomography (PET/CT) in predicting programmed cell death ligand-1 (PDL1) expression status in pulmonary lesions of advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective study includes 133 untreated stage IIIB-IV NSCLC patients who underwent pulmonary lesion biopsy for PDL1 immunochemistry 1-4 weeks after ¹⁸F-FDG PET/CT scanning, randomly assigned to cohorts for modelling and validation of PDL1 expression predictors. Mean and maximum standard uptake values (pSUVmean and pSUVmax), metabolic tumour volume (pMTV), and total lesion glycolysis (pTLG) of primary lesions were determined. PDL1 expression in pulmonary lesions (pPDL1) was determined using tumour proportion score (TPS), and pPDL1 TPS < 1%, 1-49 %, and ≥ 50 % were considered as pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively.

RESULTS

pSUVmean and pSUVmax values were increased with the increase of pPDL1 levels, whereas pMTV and pTLG values were not associated with pPDL1 levels. In the modelling cohort, we found that pSUVmax rather than pSUVmean was an independent predictor for pPDL1-negative, pPDL1-moderate, and pPDL1-strong, whereas pSUVmax < 14.4, 14.4-17.5, and > 17.5 were suggested as predictors for pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively (odds ratio: 4.82, 3.92, and 4.45, respectively; P = 0.002, 0.021, and 0.020, respectively). In the validation cohort, pSUVmax < 14.4, 14.4-17.5, and > 17.5 showed significantly high probabilities of being pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively (P = 0.006). The accuracies of pSUVmax < 14.4, 14.4-17.5, and > 17.5 predicting pPDL1-negative, pPDL1-moderate, and pPDL1-strong, respectively, in validation cohort, were 66.7 %, 75.8 %, and 84.8 %, respectively.

CONCLUSION

pSUVmax on ¹⁸F-FDG PET/CT is a potential biomarker for pPDL1 TPS < 1%, 1-49 %, and ≥ 50 % in untreated stage IIIB-IV NSCLC, and therefore may be helpful for determining immunotherapeutic strategy for advanced NSCLC.

BRAF as a positive predictive biomarker: Focus on lung cancer and melanoma patients

In the era of personalized medicine, BRAF mutational assessment is mandatory in advanced-stage melanoma and non-small cell lung cancer (NSCLC) patients. The identification of actionable mutations is crucial for the adequate management of these patients. To date various drugs have been implemented in clinical practice. Similarly, various methods may be adopted for the identification of BRAF mutations. Here, we briefly review the current literature on BRAF in melanoma and NSCLC, focusing attention in particular on the different methods and drugs adopted in these patients. In addition, an overview of the real-world practice in different Italian laboratories with high expertise in molecular predictive pathology testing is provided.

Treatment of advanced non-small-cell lung cancer: The 2019 AIOM (Italian Association of Medical Oncology) clinical practice guidelines

The Italian Association of Medical Oncology (AIOM) has developed clinical practice guidelines for the treatment of patients with advanced non-small cell lung cancer (NSCLC). In the current paper a panel of AIOM experts in the field of thoracic malignancies discussed the available scientific evidences, with the final aim of providing a summary of clinical recommendations, which may guide physicians in their current practice.

LncRNA MALAT1 contributes to non-small cell lung cancer progression via modulating miR-200a-3p/programmed death-ligand 1 axis

This study was to investigate the expression correlation between long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (lncRNA MALAT1), miR-200a-3p and programmed death-ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC), and their roles in NSCLC. Real-time polymerase chain reaction (PCR) was performed to detect the expressions of MALAT1, miR-200a-3p and PD-L1 in NSCLC tissues and cells for the correlation analysis. The starBase and Targetscan databases were used to predict the binding sites between MALAT1 and miR-200a-3p, and miR-200a-3p and PD-L1, respectively. The targeting relationship between MALAT1 and miR-200a-3p, and miR-200a-3p and PD-L1 were further verified by real-time PCR and dual luciferase reporter gene assay. Cell proliferation was monitored by CCK8 and colony formation assays. The apoptosis was detected using flow cytometry. Wound healing assay and transwell assay were conducted to determine cell migration and invasion. In this study, we demonstrated that in NSCLC tissues, the expression level of MALAT1 was negatively correlated with that of miR-200a-3p, while positively correlated with PD-L1. Besides, MALAT1 promoted proliferation, mobility, migration, and invasion of NSCLC cells via sponging miR-200a-3p. PD-L1 was validated as a target of miR-200a-3p, and indirectly modulated by MALAT1. In conclusion, LncRNA MALAT1 facilitates the progression of NSCLC by modulating miR-200a-3p/PDL1 axis.

Accurate expression of PD-L1/L2 in lung adenocarcinoma cells: A retrospective study by double immunohistochemistry

The percentage of programmed death ligand 1 (PD‐L1) positivity in cancer cells, named as the tumor proportion score, is considered to be a predictive biomarker for anti‐PD‐1/PD‐L1 therapy in lung cancer. PD‐L1 is expressed on not only cancer cells but also on immune cells, including macrophages. Although previous studies related to PD‐L1/2 expression in cancer tissues have been generally based on single immunohistochemistry (IHC), in the present study, we attempted to evaluate accurate PD‐L1/2 expression in cancer cells in lung adenocarcinoma cells using double IHC to also evaluate macrophages. Of the 231 patients, PD‐L1 expression was negative in 169 patients (73.2%), 1%‐49% positive in 47 patients (20.3%), and ≥50% positive in 15 patients (6.5%). Interestingly, PD‐L1 positivity was decreased when using double IHC compared with the estimation by single IHC. High PD‐L1 expression was associated with high‐grade cancer cells and in higher stage cancer. PD‐L2 was negative in 109 patients (47.2%), 1%‐49% positive in 50 patients (21.6%), and ≥50% positive in 72 patients (31.2%). The number of PD‐L2‐positive patients was increased in cases that had an epidermal growth factor receptor (EGFR) mutation and in lower stage cancer. Thirty‐five patients (15.2%) were positive for both PD‐L1 and PD‐L2, whereas 81 patients (35.1%) were negative for both PD‐L1 and PD‐L2. Log‐rank analysis showed that progression‐free survival and overall survival were significantly the longest in the PD‐L1‐negative and PD‐L2‐positive groups (P < .0001 and P = .0120). We observed lower PD‐L1 or PD‐L2 expression in lung adenocarcinoma than previously reported. Double IHC for macrophages may help clinicians to evaluate PD‐L1 or PD‐L2 expression specifically in cancer cells.