PD-L1 expression on tumour cells can guide the use of anti-PD-1/PD-L1 immune modulators to treat patients with non-small cell lung cancer (NSCLC). Heterogeneity of PD-L1 expression both within and between tumour sites is a well-documented phenomenon that compromises its predictive power. Our aim was to better characterise the pattern and extent of PD-L1 heterogeneity with a view to optimising tumour sampling and improve its accuracy as a biomarker. Expression of PD-L1 was assessed by immunochemistry using the SP263 clone in 107 resected primary NSCLCs and their nodal metastases. Intra-tumoural heterogeneity, defined as 'small-scale' (mm²), 'medium-scale' (cm²) and 'large-scale' (between tumour blocks), was assessed by digital imaging using a novel 'squares method'. Inter-tumoural heterogeneity between the primary tumours and their nodal metastases and between N1 and N2 nodal stages was also assessed. The majority of tumours demonstrated intra-tumoural heterogeneity (small-scale 78%, medium-scale 50%, large-scale 46%). Inter-tumoural heterogeneity between the primary and nodal metastases was present in 53% of cases and, in 17%, between N1 and N2 disease. These differences were occasionally sufficient to lead to discrepancy across the ≥1%, ≥25% and ≥50% cut-offs used to guide therapy. Heterogeneity of PD-L1 expression is common, variable in scale and extent, and carries significant implications for its accuracy as a predictive biomarker. Extensive sampling reduces, but cannot eliminate, this inaccuracy.

Context .—Adenocarcinoma of the breast is the most frequent cancer affecting women in both developed and developing regions of the world. From the moment of clinical presentation until the time of pathologic diagnosis, patients affected by this disease will face daunting questions related to prognosis and treatment options. While improvements in targeted therapies have led to increased patient survival, these same advances have created the imperative to accurately stratify patients to achieve maximum therapeutic efficacy while minimizing side effects. In this evolving era of personalized medicine, there is an ever-increasing need to overcome the limitations of traditional diagnostic practice. Objective .—To summarize the molecular diagnostics traditionally used to guide prognostication and treatment of breast carcinomas, to highlight published data on the molecular classification of these tumors, and to showcase molecular assays that will supplement traditional methods of categorizing the disease. Data Sources .—A review of the literature covering the molecular diagnostics of breast carcinomas with a focus on the gene expression and array studies used to characterize the molecular signatures of the disease. Special emphasis is placed on summarizing evolving technologies useful in the diagnosis and characterization of breast carcinoma. Conclusions .—Available and emerging molecular resources will allow pathologists to provide superior diagnostic, prognostic, and predictive information about individual breast carcinomas. These advances should translate into earlier identification and tailored therapy and should ultimately improve outcome for patients affected by this disease.

Immunohistochemistry (IHC) using formalin-fixed, paraffin embedded (FFPE) tissue is limited by epitope masking, posttranslational modification and immunoreactivity loss that occurs in stored tissue by poorly characterized mechanisms. Conformational epitopes recognized by many programmed-death-ligand-1 (PD-L1) IHC assays are particularly susceptible to degradation and provide an ideal model for understanding signal loss in stored FFPE tissue. Here we assessed 1206 tissue sections to evaluate environmental factors impacting immunoreactivity loss. PD-L1 IHC using four antibodies (22C3, 28-8, E1L3N, and SP142), raised against intracellular and extracellular epitopes, was assessed in stored FFPE tissue alongside quantitative mass spectrometry (MS). Global proteome analyses were used to assess proteome-wide oxidation across an inventory of 3041 protein groups (24,737 distinct peptides). PD-L1 quantitation correlated well with IHC expression on unaged sections (R² = 0.744; P < 0.001), with MS demonstrating no loss of PD-L1 protein, even in sections with significant signal loss by IHC impacting diagnostic category. Clones 22C3 and 28-8 were most susceptible to signal loss, with E1L3N demonstrating the most robust signal (56%, 58%, and 33% reduction respectively; p < 0.05). Increased humidity and temperature resulted in significant acceleration of immunoreactivity loss, which was mitigated by storage with desiccant. MS demonstrated only modest oxidation of 274 methionine-containing peptides and aligned with IHC results suggesting peptide oxidation is not a major factor. These data imply immunoreactivity loss driven by humidity and temperature results in structural distortion of epitopes rendering them unsuitable for antibody binding following epitope retrieval. Limitations of IHC biomarker analysis from stored tissue sections may be mitigated by cost-effective use of desiccant when appropriate. In some scenarios, complementary MS is a preferred approach for retrospective analyses of archival FFPE tissue collections.

New therapeutics targeting immune checkpoint proteins have significantly advanced treatment of non-small cell lung cancer (NSCLC), but protein level quantitation of drug targets presents a critical problem. We used multiplexed, targeted mass spectrometry (MS) to quantify immunotherapy target proteins PD-1, PD-L1, PD-L2, IDO1, LAG3, TIM3, ICOSLG, VISTA, GITR, and CD40 in formalin-fixed, paraffin-embedded (FFPE) NSCLC specimens. Immunohistochemistry (IHC) and MS measurements for PD-L1 were weakly correlated, but IHC did not distinguish protein abundance differences detected by MS. PD-L2 abundance exceeded PD-L1 in over half the specimens and the drug target proteins all displayed different abundance patterns. mRNA correlated with protein abundance only for PD-1, PD-L1, and IDO1 and tumor mutation burden did not predict abundance of any protein targets. Global proteome analyses identified distinct proteotypes associated with high PD-L1-expressing and high IDO1-expressing NSCLC. MS quantification of multiple drug targets and tissue proteotypes can improve clinical evaluation of immunotherapies for NSCLC.

The objectives were to develop a standardized Ki-67 immunohistochemistry (IHC) method for precise, robust, and reproducible assessment of patients with early breast cancer, and utilize this assay to evaluate patients participating in the monarchE study (NCT03155997). The Ki-67 assay was developed and validated for sensitivity, specificity, repeatability, precision, and robustness using a predefined ≥20% cutoff. Reproducibility studies (intersite and intrasite, interobserver and intraobserver) were conducted at 3 external laboratories using detailed scoring instructions designed for monarchE. Using the assay, patient tumors were classified as displaying high (≥20%) or low (90% for negative, positive, and overall percent agreement. Intersite reproducibility produced point estimate values of 94.7%, 100.0%, and 97.3%. External interobserver reproducibility produced point estimate values of 98.9%, 97.8%, and 98.3%. Among 1954 patients receiving ET alone, 986 (50.5%) had high and 968 (49.5%) had low Ki-67 expression. Patients with high Ki-67 had a clinically meaningful increased risk of developing invasive disease within 2 years compared with those with low Ki-67 [2-y invasive disease-free survival rate: 86.1% (95% confidence interval: 83.1%-88.7%) vs. 92.0% (95% confidence interval: 89.7%-93.9%), respectively]. This standardized Ki-67 methodology resulted in high concordance across multiple laboratories, and its use in the monarchE study prospectively demonstrated the prognostic value of Ki-67 IHC in HR+, HER2− early breast cancer with high-risk clinicopathologic features.

CD200/CD200R is an immune checkpoint with broad expression patterns and a potential target for immune therapy. In this study, we assess both CD200 and CD200R expression in solid tumors, with a focus on lung cancer, and evaluate their association with clinicopathologic characteristics, mutation status, outcome, and programmed death-ligand 1 (PD-L1) expression. We used multiplexed quantitative immunofluorescence (QIF) to measure the expression of CD200 and CD200R in a total of 455 patients from three lung cancer cohorts. Using carefully validated antibodies, we performed target measurement with tyramide-based QIF panels and analyzed the data using the PM2000 microscope and AQUA software. CD200 tumor positivity was found in 29.7% of non-small cell lung cancer (NSCLC) patients and 33.3% of lung large cell neuroendocrine carcinoma (LCNEC) patients. CD200 demonstrated notable intratumoral heterogeneity. CD200R was expressed in immune cells in 25% of NSCLC and 41.3% of LCNEC patients. While CD200R is predominantly expressed in immune cells, rare tumor cell staining was seen in a highly heterogeneous pattern. CD200R expression in the stromal compartment was significantly higher in patients with squamous differentiation (p < 0.0001). Neither CD200 nor CD200R were associated with other clinicopathologic characteristics or mutation status. Both biomarkers were not prognostic for disease-free or overall survival in NSCLC. CD200 showed moderate correlation with PD-L1. CD200/CD200R pathway is frequently expressed in lung cancer patients. Differential expression patterns of CD200 and CD200R with PD-L1 suggest a potential role for targeting this pathway alone in patients with NSCLC.