Diagnostic Utility of PD-L1 Expression in Lung Adenocarcinoma: Immunohistochemistry and RNA In Situ Hybridization

Evaluation of the Suitability of RNAscope as a Technique to Measure Gene Expression in Clinical Diagnostics: A Systematic Review

Objective

To evaluate the application of RNAscope in the clinical diagnostic field compared to the current ‘gold standard’ methods employed for testing gene expression levels, including immunohistochemistry (IHC), quantitative real time PCR (qPCR), and quantitative reverse transcriptase PCR (qRT-PCR), and to detect genes, including DNA in situ hybridisation (DNA ISH).

Methods

This systematic review searched CINAHL, Medline, Embase and Web of Science databases for studies that were conducted after 2012 and that compared RNAscope with one or more of the ‘gold standard’ techniques in human samples. QUADAS-2 test was used for the evaluation of the articles’ risk of bias. The results were reviewed narratively and analysed qualitatively.

Results

A total of 27 articles (all retrospective studies) were obtained and reviewed. The 27 articles showed a range of low to middle risk of bias scores, as assessed by QUADAS-2 test. 26 articles studied RNAscope within cancer samples. RNAscope was compared to different techniques throughout the included studies (IHC, qPCR, qRT-PCR and DNA ISH). The results confirmed that RNAscope is a highly sensitive and specific method that has a high concordance rate (CR) with qPCR, qRT-PCR, and DNA ISH (81.8–100%). However, the CR with IHC was lower than expected (58.7–95.3%), which is mostly due to the different products that each technique measures (RNA vs. protein).

Discussion

This is the first systematic review to be conducted on the use of RNAscope in the clinical diagnostic field. RNAscope was found to be a reliable and robust method that could complement gold standard techniques currently used in clinical diagnostics to measure gene expression levels or for gene detection. However, there were not enough data to suggest that RNAscope could stand alone in the clinical diagnostic setting, indicating further prospective studies to validate diagnostic accuracy values, in keeping with relevant regulations, followed by cost evaluation are required.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40291-021-00570-2.

Discordance of PD-L1 Expression at the Protein and RNA Levels in Early Breast Cancer

Simple Summary

Despite the increasing use of checkpoint inhibitors for early and metastatic breast cancer, Programmed Death Ligand 1 (PD-L1) remains the only validated albeit imperfect predictive biomarker. Significant discordance in PD-L1 protein expression depending on the antibody used has been demonstrated, while the weak correlation and discordant prognostic information between protein and gene expression underscore its biologic heterogeneity. In this study, we use material from two patient cohorts of early breast cancer and multiple methodologies (immunohistochemistry, RNA fluorescent in situ hybridization, immunofluorescence, bulk gene expression, and multiplex fluorescent immunohistochemistry) to demonstrate the significant discordance in PD-L1 expression among various methods and between different areas of the same tumor, which hints toward the presence of spatial, intratumoral and biological heterogeneity.

Abstract

We aimed to assess if the discrepant prognostic information between Programmed Death Ligand 1 (PD-L1) protein versus mRNA expression in early breast cancer (BC) could be attributed to heterogeneity in its expression. PD-L1 protein and mRNA expression in BC tissue microarrays from two clinical patient cohorts were evaluated (105 patients; cohort 1: untreated; cohort 2: neoadjuvant chemotherapy-treated). Immunohistochemistry (IHC) with SP142, SP263 was performed. PD-L1 mRNA was evaluated using bulk gene expression and RNA-FISH RNAscope^®, the latter scored in a semi-quantitative manner and combined with immunofluorescence (IF) staining for the simultaneous detection of PD-L1 protein expression. PD-L1 expression was assessed in cores as a whole and in two regions of interest (ROI) from the same core. The cell origin of PD-L1 expression was evaluated using multiplex fluorescent IHC. IHC PD-L1 expression between SP142 and SP263 was concordant in 86.7% of cores (p < 0.001). PD-L1 IF/IHC was weakly correlated with spatial mRNA expression (concordance 54.6–71.2%). PD-L1 was mostly expressed by lymphocytes intra-tumorally, while its stromal expression was mostly observed in macrophages. Our results demonstrate only moderate concordance between the various methods of assessing PD-L1 expression at the protein and mRNA levels, which may be attributed to both analytical performance and spatial heterogeneity.

PD-L1 and PD-L2 Expression in Cervical Cancer: Regulation and Biomarker Potential

PD-1/PD-L1 immune checkpoint inhibitors show potential for cervical cancer treatment. However, low response rates suggest that patient selection based on PD-L1 protein expression is not optimal. Here, we evaluated different PD-L1 detection methods and studied transcriptional regulation of PD-L1/PD-L2 expression by The Cancer Genome Atlas (TCGA) mRNAseq analysis. First, we determined the copy number of the PD-L1/PD-L2 locus by fluorescence in situ hybridization (FISH), PD-L1 mRNA expression by RNA in situ hybridization (RNAish), and PD-L1/PD-L2 protein expression by immunohistochemistry (IHC) on tissue microarrays containing a cohort of 60 patients. Additionally, distribution of PD-L1/PD-L2 was visualized based on flow cytometry analysis of single-cell suspensions (n = 10). PD-L1/PD-L2 locus amplification was rare (2%). PD-L1 mRNA expression in tumor cells was detected in 56% of cases, while 41% expressed PD-L1 protein. Discordant scores for PD-L1 protein expression on tumor cells between cores from one patient were observed in 27% of cases. Interestingly, with RNAish, PD-L1 heterogeneity was observed in only 11% of the cases. PD-L2 protein expression was found in 53%. PD-L1 mRNA and protein expression on tumor cells were strongly correlated (p < 0.001). PD-L1 and PD-L2 protein expression showed no correlation on tumor cells (p = 0.837), but a strong correlation on cells in stromal fields (p < 0.001). Co-expression of PD-L1 and PD-L2 on macrophage-like populations was also observed with flow cytometry analysis. Both PD-L1 and PD-L2 TCGA transcript levels strongly correlated in the TCGA data, and both PD-L1 and PD-L2 strongly correlated with interferon gamma (IFNG) expression/transcript levels (p < 0.0001). Importantly, patients with high PD-L1/PD-L2/IFNG transcript levels had a survival advantage over patients with high PD-L1/PD-L2 and low IFNG expression. Based on these findings, we conclude that PD-L1/PD-L2 expression in cervical cancer is mainly associated with interferon induction and not gene amplification, which makes FISH unsuitable as biomarker. The heterogeneous PD-L1 and PD-L2 expression patterns suggest IHC unreliable for patient selection. RNAish, in conjunction with interferon signaling evaluation, seems a promising technique for immune checkpoint detection. These results warrant further investigation into their prognostic and predictive potential.

Transcriptional Spatial Profiling of Cancer Tissues in the Era of Immunotherapy: The Potential and Promise

Intratumoral heterogeneity poses a major challenge to making an accurate diagnosis and establishing personalized treatment strategies for cancer patients. Moreover, this heterogeneity might underlie treatment resistance, disease progression, and cancer relapse. For example, while immunotherapies can confer a high success rate, selective pressures coupled with dynamic evolution within a tumour can drive the emergence of drug-resistant clones that allow tumours to persist in certain patients. To improve immunotherapy efficacy, researchers have used transcriptional spatial profiling techniques to identify and subsequently block the source of tumour heterogeneity. In this review, we describe and assess the different technologies available for such profiling within a cancer tissue. We first outline two well-known approaches, in situ hybridization and digital spatial profiling. Then, we highlight the features of an emerging technology known as Visium Spatial Gene Expression Solution. Visium generates quantitative gene expression data and maps them to the tissue architecture. By retaining spatial information, we are well positioned to identify novel biomarkers and perform computational analyses that might inform on novel combinatorial immunotherapies.

Immune checkpoint inhibitors of the PD-1/PD-L1-axis in non-small cell lung cancer: promise, controversies and ambiguities in the novel treatment paradigm

Immune checkpoint inhibitors (ICIs) have received much attention not least for melanoma since the award of the Nobel prize in 2018. Here, we review the current state of knowledge about the use of these monoclonal antibodies (mAbs) in non-small cell lung cancer (NSCLC). These drugs have generally been conditionally approved on limited early data and there are few long-term follow-up data from randomized clinical trials. The effect observed for NSCLC thus far is, on average, moderately better than that obtained with chemotherapy. Severe side-effects are more common than might have been expected. The drugs themselves are expensive and are associated with time-consuming histopathologic testing even though the predictive value of these tests can be discussed. In addition, monitoring for side-effects involves increased workload and budgetary expense for clinical chemistry laboratories. Here, we review and summarize the current knowledge, controversies and ambiguities of ICIs for the treatment of NSCLC.

Concordance levels of PD-L1 expression by immunohistochemistry, mRNA in situ hybridization, and outcome in lung carcinomas

Targeted inhibition of programmed cell death-1 (PD-1) and its ligand (PD-L1) has emerged as first-line therapy for advanced non-small cell lung cancer. Although patients with high PD-L1 expression have improved outcomes with anti-PD-1/PD-L1-directed therapies, use as a predictive biomarker is complicated by robust responses in some patients with low-level expression. Furthermore, reported PD-L1 levels in lung cancers vary widely, and discrepancies exist with different antibodies. PD-L1 expression was thus compared by immunohistochemistry (IHC) versus RNA in situ hybridization (ISH) in 112 lung cancers by tissue microarray: 51 adenocarcinoma, 42 squamous cell carcinoma, 9 adenosquamous carcinoma, 5 carcinoid, 3 undifferentiated large cell carcinoma, 1 large cell neuroendocrine carcinoma, and 1 small cell carcinoma. At least 1% tumor cell staining was considered positive in each modality. A positive concordance of only 60% (67/112) was found between IHC and ISH. Fifty percent (56/112) were positive by IHC and 50% (56/112) by ISH; however, 20% (22/112) were ISH positive but IHC negative. Conversely, 21% (23/112) were IHC positive but ISH negative. There was no significant stratification of PD-L1 positivity by histologic subtype. A trend of more PD-L1-positive stage I cancers identified by ISH versus IHC was observed but was not statistically significant (50% [27/54] by IHC and 64% [35/55] by ISH, P = .18). No significant difference in survival was identified, with an average of 5.3 months in IHC versus 5.2 months in ISH-positive cases. The results demonstrate discordance between PD-L1 RNA levels and protein expression in non-small cell lung cancers, warranting comparison as predictive biomarkers.