Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies.

CONTEXT.­: The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics. OBJECTIVE.­: To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer. DESIGN.­: A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available. RESULTS.­: The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores. CONCLUSIONS.­: Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Expression of cancer-testis antigens in the immune microenvironment of non-small cell lung cancer.

The antigenic repertoire of tumors is critical for successful anti-cancer immune response and the efficacy of immunotherapy. Cancer-testis antigens (CTAs) are targets of humoral and cellular immune reactions. We aimed to characterize CTA expression in non-small cell lung cancer (NSCLC) in the context of the immune microenvironment. Of 90 CTAs validated by RNA sequencing, eight CTAs (DPEP3, EZHIP, MAGEA4, MAGEB2, MAGEC2, PAGE1, PRAME, and TKTL1) were selected for immunohistochemical profiling in cancer tissues from 328 NSCLC patients. CTA expression was compared with immune cell densities in the tumor environment and with genomic, transcriptomic, and clinical data. Most NSCLC cases (79%) expressed at least one of the analyzed CTAs, and CTA protein expression correlated generally with RNA expression. CTA profiles were associated with immune profiles: high MAGEA4 expression was related to M2 macrophages (CD163) and regulatory T cells (FOXP3), low MAGEA4 was associated with T cells (CD3), and high EZHIP was associated with plasma cell infiltration (adj. P-value < 0.05). None of the CTAs correlated with clinical outcomes. The current study provides a comprehensive evaluation of CTAs and suggests that their association with immune cells may indicate in situ immunogenic effects. The findings support the rationale to harness CTAs as targets for immunotherapy.

Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer.

INTRODUCTION: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial immune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC). METHODS: We established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs). RESULTS: CD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg-B-cells, CD8-Eff-cancer cells and B-cells-CD4-Treg) demonstrated positive prognostic impact, whereas short M2-M1 distances were prognostically unfavourable. CONCLUSION: We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.

An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers.

BACKGROUND: Cancer immunity is based on the interaction of a multitude of cells in the spatial context of the tumour tissue. Clinically relevant immune signatures are therefore anticipated to fundamentally improve the accuracy in predicting disease progression. METHODS: Through a multiplex in situ analysis we evaluated 15 immune cell classes in 1481 tumour samples. Single-cell and bulk RNAseq data sets were used for functional analysis and validation of prognostic and predictive associations. FINDINGS: By combining the prognostic information of anti-tumoural CD8+ lymphocytes and tumour supportive CD68+CD163+ macrophages in colorectal cancer we generated a signature of immune activation (SIA). The prognostic impact of SIA was independent of conventional parameters and comparable with the state-of-art immune score. The SIA was also associated with patient survival in oesophageal adenocarcinoma, bladder cancer, lung adenocarcinoma and melanoma, but not in endometrial, ovarian and squamous cell lung carcinoma. We identified CD68+CD163+ macrophages as the major producers of complement C1q, which could serve as a surrogate marker of this macrophage subset. Consequently, the RNA-based version of SIA (ratio of CD8A to C1QA) was predictive for survival in independent RNAseq data sets from these six cancer types. Finally, the CD8A/C1QA mRNA ratio was also predictive for the response to checkpoint inhibitor therapy. INTERPRETATION: Our findings extend current concepts to procure prognostic information from the tumour immune microenvironment and provide an immune activation signature with high clinical potential in common human cancer types. FUNDING: Swedish Cancer Society, Lions Cancer Foundation, Selanders Foundation, P.O. Zetterling Foundation, U-CAN supported by SRA CancerUU, Uppsala University and Region Uppsala.

Fibroblast subsets in non-small cell lung cancer: Associations with survival, mutations, and immune features.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are molecularly heterogeneous mesenchymal cells that interact with malignant cells and immune cells and confer anti- and protumorigenic functions. Prior in situ profiling studies of human CAFs have largely relied on scoring single markers, thus presenting a limited view of their molecular complexity. Our objective was to study the complex spatial tumor microenvironment of non-small cell lung cancer (NSCLC) with multiple CAF biomarkers, identify novel CAF subsets, and explore their associations with patient outcome. METHODS: Multiplex fluorescence immunohistochemistry was employed to spatially profile the CAF landscape in 2 population-based NSCLC cohorts (n = 636) using antibodies against 4 fibroblast markers: platelet-derived growth factor receptor-alpha (PDGFRA) and -beta (PDGFRB), fibroblast activation protein (FAP), and alpha-smooth muscle actin (αSMA). The CAF subsets were analyzed for their correlations with mutations, immune characteristics, and clinical variables as well as overall survival. RESULTS: Two CAF subsets, CAF7 (PDGFRA-/PDGFRB+/FAP+/αSMA+) and CAF13 (PDGFRA+/PDGFRB+/FAP-/αSMA+), showed statistically significant but opposite associations with tumor histology, driver mutations (tumor protein p53 [TP53] and epidermal growth factor receptor [EGFR]), immune features (programmed death-ligand 1 and CD163), and prognosis. In patients with early stage tumors (pathological tumor-node-metastasis IA-IB), CAF7 and CAF13 acted as independent prognostic factors. CONCLUSIONS: Multimarker-defined CAF subsets were identified through high-content spatial profiling. The robust associations of CAFs with driver mutations, immune features, and outcome suggest CAFs as essential factors in NSCLC progression and warrant further studies to explore their potential as biomarkers or therapeutic targets. This study also highlights multiplex fluorescence immunohistochemistry-based CAF profiling as a powerful tool for the discovery of clinically relevant CAF subsets.

The Immune Landscape of Colorectal Cancer.

While the clinical importance of CD8+ and CD3+ cells in colorectal cancer (CRC) is well established, the impact of other immune cell subsets is less well described. We sought to provide a detailed overview of the immune landscape of CRC in the largest study to date in terms of patient numbers and in situ analyzed immune cell types. Tissue microarrays from 536 patients were stained using multiplexed immunofluorescence panels, and fifteen immune cell subclasses, representing adaptive and innate immunity, were analyzed. Overall, therapy-naïve CRC patients clustered into an 'inflamed' and a 'desert' group. Most T cell subsets and M2 macrophages were enriched in the right colon (p-values 0.046-0.004), while pDC cells were in the rectum (p = 0.008). Elderly patients had higher infiltration of M2 macrophages (p = 0.024). CD8+ cells were linked to improved survival in colon cancer stages I-III (q = 0.014), while CD4+ cells had the strongest impact on overall survival in metastatic CRC (q = 0.031). Finally, we demonstrated repopulation of the immune infiltrate in rectal tumors post radiation, following an initial radiation-induced depletion. This study provides a detailed analysis of the in situ immune landscape of CRC paving the way for better diagnostics and providing hints to better target the immune microenvironment.

Infiltration of NK and plasma cells is associated with a distinct immune subset in non-small cell lung cancer.

Immune cells of the tumor microenvironment are central but erratic targets for immunotherapy. The aim of this study was to characterize novel patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to its molecular and clinicopathologic characteristics. Lymphocytes (CD3+, CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+), PD1+, and PD-L1+ were annotated on a tissue microarray including 357 NSCLC cases. Somatic mutations were analyzed by targeted sequencing for 82 genes and a tumor mutational load score was estimated. Transcriptomic immune patterns were established in 197 patients based on RNA sequencing data. The immune cell infiltration was variable and showed only poor association with specific mutations. The previously defined immune phenotypic patterns, desert, inflamed, and immune excluded, comprised 30, 13, and 57% of cases, respectively. Notably, mRNA immune activation and high estimated tumor mutational load were unique only for the inflamed pattern. However, in the unsupervised cluster analysis, including all immune cell markers, these conceptual patterns were only weakly reproduced. Instead, four immune classes were identified: (1) high immune cell infiltration, (2) high immune cell infiltration with abundance of CD20+ B cells, (3) low immune cell infiltration, and (4) a phenotype with an imprint of plasma cells and NK cells. This latter class was linked to better survival despite exhibiting low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, CTLA4). This compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC reveals two previously unrecognized immune classes. A refined immune classification, including traits of the humoral and innate immune response, is important to define the immunogenic potency of NSCLC in the era of immunotherapy. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

FGFR1 overexpression in non-small cell lung cancer is mediated by genetic and epigenetic mechanisms and is a determinant of FGFR1 inhibitor response.

Amplification of fibroblast growth factor receptor 1 (FGFR1) in non-small cell lung cancer (NSCLC) has been considered as an actionable drug target. However, pan-FGFR tyrosine kinase inhibitors did not demonstrate convincing clinical efficacy in FGFR1-amplified NSCLC patients. This study aimed to characterise the molecular context of FGFR1 expression and to define biomarkers predictive of FGFR1 inhibitor response. In this study, 635 NSCLC samples were characterised for FGFR1 protein expression by immunohistochemistry and copy number gain (CNG) by in situ hybridisation (n = 298) or DNA microarray (n = 189). FGFR1 gene expression (n = 369) and immune cell profiles (n = 309) were also examined. Furthermore, gene expression, methylation and microRNA data from The Cancer Genome Atlas (TCGA) were compared. A panel of FGFR1-amplified NSCLC patient-derived xenograft (PDX) models were tested for response to the selective FGFR1 antagonist M6123. A minority of patients demonstrated FGFR1 CNG (10.5%) or increased FGFR1 mRNA (8.7%) and protein expression (4.4%). FGFR1 CNG correlated weakly with FGFR1 gene and protein expression. Tumours overexpressing FGFR1 protein were typically devoid of driver alterations (e.g. EGFR, KRAS) and showed reduced infiltration of T-lymphocytes and lower PD-L1 expression. Promoter methylation and microRNA were identified as regulators of FGFR1 expression in NSCLC and other cancers. Finally, NSCLC PDX models demonstrating FGFR1 amplification and FGFR1 protein overexpression were sensitive to M6123. The unique molecular and immune features of tumours with high FGFR1 expression provide a rationale to stratify patients in future clinical trials of FGFR1 pathway-targeting agents.

Stromal FAP is an independent poor prognosis marker in non-small cell lung adenocarcinoma and associated with p53 mutation.

OBJECTIVES: Fibroblasts regulate tumor growth and immune surveillance. Here, we study FAP, PDGFßR and α-SMA fibroblast markers in a well-annotated clinical cohort of non-small-cell lung cancer (NSCLC) for analyses of associations with immune cell infiltration, mutation status and survival. MATERIALS AND METHODS: A well-annotated NSCLC cohort was subjected to IHC analyses of stromal expression of FAP, PDGFßR and α-SMA and of stromal CD8 density. Fibroblast markers-related measurements were analyzed with regard to potential associations with CD8 density, cancer genetic driver mutations, survival and PD-L1 expression in the whole NSCLC cohort and in subsets of patients. RESULTS: High stromal FAP expression was identified as an independent poor prognostic marker in the whole study population (HR 1.481; 95 % CI, 1.012-2.167, p = 0.023) and in the histological subset of adenocarcinoma (HR 1.720; 95 % CI, 1.126-2.627, p = 0.012). Among patients with adenocarcinoma, a particularly strong association of FAP with poor survival was detected in patients with low stromal CD8 infiltration, and in other subpopulations identified by specific clinical characteristics; elderly patients, females, non-smokers and patients with normal ECOG performance status. α-SMA expression was negatively associated with CD8 infiltration in non-smokers, but none of the fibroblast markers expression was associated with CD8 density in the whole study population. Significant associations were detected between presence of p53 mutations and high α-SMA (p = 0.003) and FAP expression (p < 0.001). CONCLUSION: The study identifies FAP intensity as a candidate independent NSCLC prognostic biomarker. The study also suggests continued analyses of the relationships between genetic driver mutations and the composition of tumor stroma, as well as continued probing of marker-defined fibroblasts as NSCLC subset-specific modifiers of immune surveillance and outcome.

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types.

BACKGROUND: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed. METHODS: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns. FINDINGS: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR(95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59(1.49-8.62)) associations of the tumour stroma fraction with survival. INTERPRETATION: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance. FUNDING: The Swedish Cancer Society, The Lions Cancer Foundation Uppsala, The Swedish Government Grant for Clinical Research, The Mrs Berta Kamprad Foundation, Sweden, Sellanders foundation, P.O.Zetterling Foundation, and The Sjöberg Foundation, Sweden.

PD-L1 amplification is associated with an immune cell rich phenotype in squamous cell cancer of the lung.

Gene amplification is considered to be one responsible cause for upregulation of Programmed Death Ligand-1 (PD-L1) in non-small cell lung cancer (NSCLC) and to represent a specific molecular subgroup possibly associated with immunotherapy response. Our aim was to analyze the frequency of PD-L1 amplification, its relation to PD-L1 mRNA and protein expression, and to characterize the immune microenvironment of amplified cases. The study was based on two independent NSCLC cohorts, including 354 and 349 cases, respectively. Tissue microarrays were used to evaluate PD-L1 amplification by FISH and PD-L1 protein by immunohistochemistry. Immune infiltrates were characterized immunohistochemically by a panel of immune markers (CD3, CD4, CD8, PD-1, Foxp3, CD20, CD138, CD168, CD45RO, NKp46). Mutational status was determined by targeted sequencing. RNAseq data was available for 197 patients. PD-L1 amplification was detected in 4.5% of all evaluable cases. PD-L1 amplification correlated only weakly with mRNA and protein expression. About  37% of amplified cases were negative for PD-L1 protein. PD-L1 amplification did not show any association with the mutational status. In squamous cell cancer, PD-L1 amplified cases were enriched among patients with high tumoral immune cell infiltration and showed gene expression profiles related to immune exhaustion. In conclusion, PD-L1 amplification correlates with PD-L1 expression in squamous cell cancer and was associated with an immune cell rich tumor phenotype. The correlative findings help to understand the role of PD-L1 amplification as an important immune escape mechanism in NSCLC and suggest the need to further evaluate PD-L1 amplification as predictive biomarker for checkpoint inhibitor therapy.

Quantitative Evaluation of Single-Use Particle Filtering Half Masks for SARS-CoV-2 Protection.

Background: The SARS-CoV-2 pandemic put the entire healthcare sector under severe strain due to shortages of personal protection equipment. A large number of new filtering mask models were introduced on the market, claiming effectiveness that had undergone little or no objective and reliable verifications. Methods and Materials: Filter materials were tested against sodium chloride particles according to the EN149 §7.9.2 standard for particle penetration. Particle counters were used to measure the particle penetration of the filtering mask models, resolved over sizes in the range of 27-1000 nm. Results: We report on the results for 86 different filtering mask models. The majority of the tested models showed <3% penetration, whereas almost one third (i.e., 27 of 86) of the models performed poorly. Discussion: Interestingly, the poorest performing masks showed a tendency to have worse filtering effectiveness for larger particles than for smaller sized particles, following the opposite tendency of the best filtering masks. Conclusion: Almost one third of the filtering mask models tested failed the specified pass criteria as specified in the temporary EU COVID-19 standard. This fact, and the high health risks of COVID-19, highlights the need for independent testing.

Evaluation of NTRK immunohistochemistry as a screening method for NTRK gene fusion detection in non-small cell lung cancer.

PURPOSE: The small molecule inhibitors larotrectinib and entrectinib have recently been approved as cancer agnostic drugs in patients with tumours harbouring a rearrangement of the neurotrophic tropomyosin receptor kinase (NTRK). These oncogenic fusions are estimated to occur in 0.1-3 % of non-small cell lung cancers (NSCLC). Although molecular techniques are most reliable for fusion detection, immunohistochemical analysis is considered valuable for screening. Therefore, we evaluated the newly introduced diagnostic immunohistochemical assay (clone EPR17341) on a representative NSCLC cohort. METHODS: Cancer tissue from 688 clinically and molecularly extensively annotated NSCLC patients were comprised on tissue microarrays and stained with the pan-TRK antibody clone EPR17341. Positive cases were further analysed with the TruSight Tumor 170 RNA assay (Illumina). Selected cases were also tested with a NanoString NTRK fusion assay. For 199 cases, NTRK RNA expression data were available from previous RNA sequencing analysis. RESULTS: Altogether, staining patterns for 617 NSCLC cases were evaluable. Of these, four cases (0.6 %) demonstrated a strong diffuse cytoplasmic and membranous staining, and seven cases a moderate staining (1.1 %). NanoString or TST170-analysis could not confirm an NTRK fusion in any of the IHC positive cases, or any of the cases with high mRNA levels. In the four cases with strong staining intensity in the tissue microarray, whole section staining revealed marked heterogeneity of NTRK protein expression. CONCLUSION: The presence of NTRK fusion genes in non-small cell lung cancer is exceedingly rare. The use of the immunohistochemical NTRK assay will result in a small number of false positive cases. This should be considered when the assay is applied as a screening tool in clinical diagnostics.

Proximity Ligation Assay as a Tool for Antibody Validation in Human Tissues.

Immunohistochemistry (IHC) is the accepted standard for spatial analysis of protein expression in tissues. IHC is widely used for cancer diagnostics and in basic research. The development of new antibodies to proteins with unknown expression patterns has created a demand for thorough validation. We have applied resources from the Human Protein Atlas project and the Antibody Portal at National Cancer Institute to generate protein expression data for 12 proteins across 39 cancer cell lines and 37 normal human tissue types. The outcome of IHC on consecutive sections from both cell and tissue microarrays using two independent antibodies for each protein was compared with in situ proximity ligation (isPLA), where binding by both antibodies is required to generate detection signals. Semi-quantitative scores from IHC and isPLA were compared with expression of the corresponding 12 transcripts across all cell lines and tissue types. Our results show a more consistent correlation between mRNA levels and isPLA as compared to IHC. The main benefits of isPLA include increased detection specificity and decreased unspecific staining compared to IHC. We conclude that implementing isPLA as a complement to IHC for analysis of protein expression and in antibody validation pipelines can lead to more accurate localization of proteins in tissue.

ASCL1 promotes tumor progression through cell-autonomous signaling and immune modulation in a subset of lung adenocarcinoma.

The master regulator of neuroendocrine differentiation, achaete-scute complex homolog 1 (ASCL1) defines a subgroup of lung adenocarcinoma. However, the mechanistic role of ASCL1 in lung tumorigenesis and its relation to the immune microenvironment is principally unknown. Here, the immune landscape of ASCL1-positive lung adenocarcinomas was characterized by immunohistochemistry. Furthermore, ASCL1 was transduced in mouse lung adenocarcinoma cell lines and comparative RNA-sequencing and secretome analyses were performed. The effects of ASCL1 on tumorigenesis were explored in an orthotopic syngeneic transplantation model. ASCL1-positive lung adenocarcinomas revealed lower infiltration of CD8+, CD4+, CD20+, and FOXP3+ lymphocytes and CD163+ macrophages indicating an immune desert phenotype. Ectopic ASCL1 upregulated cyclin transcript levels, stimulated cell proliferation, and enhanced tumor growth in mice. ASCL1 suppressed secretion of chemokines, including CCL20, CXCL2, CXCL10, and CXCL16, indicating effects on immune cell trafficking. In accordance with lower lymphocytes infiltration, ASCL1-positive lung adenocarcinomas demonstrated lower abundance of CXCR3-and CCR6-expressing cells. In conclusion, ASCL1 mediates its tumor-promoting effect not only through cell-autonomous signaling but also by modulating chemokine production and immune responses. These findings suggest that ASCL1-positive tumors represent a clinically relevant lung cancer entity.

WITHDRAWN: Characterization of Patterns of Immune Cell Infiltration in NSCLC.

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Programmed Cell Death Ligand 1 Immunohistochemistry: A Concordance Study Between Surgical Specimen, Biopsy, and Tissue Microarray.

BACKGROUND: The immunohistochemical analysis of programmed cell death ligand 1 (PD-L1) expression in tumor tissue of non-small-cell lung cancer patients has now been integrated in the diagnostic workup. Analysis is commonly done on small tissue biopsy samples representing a minimal fraction of the whole tumor. The aim of the study was to evaluate the correlation of PD-L1 expression on biopsy specimens with corresponding resection specimens. MATERIALS AND METHODS: In total, 58 consecutive cases with preoperative biopsy and resected tumor specimens were selected. From each resection specimen 2 tumor cores were compiled into a tissue microarray (TMA). Immunohistochemical staining with the antibody SP263 was performed on biopsy specimens, resection specimens (whole sections), as well as on the TMA. RESULTS: The proportion of PD-L1-positive stainings were comparable between the resection specimens (48% and 19%), the biopsies (43% and 17%), and the TMAs (47% and 14%), using cutoffs of 1% and 50%, respectively (P > .39 all comparisons). When the resection specimens were considered as reference, PD-L1 status differed in 16%/5% for biopsies and in 9%/9% for TMAs (1%/50% cutoff). The sensitivity of the biopsy analysis was 79%/82% and the specificity was 90%/98% at the 1%/50% cutoff. The Cohens κ value for the agreement between biopsy and tumor. was 0.70 at the 1% cutoff and 0.83 at the 50% cutoff. CONCLUSION: The results indicate a moderate concordance between the analysis of biopsy and whole tumor tissue, resulting in misclassification of samples in particular when the lower 1% cutoff was used. Clinicians should be aware of this uncertainty when interpreting PD-L1 reports for treatment decisions.

Multispectral imaging for quantitative and compartment-specific immune infiltrates reveals distinct immune profiles that classify lung cancer patients.

Semiquantitative assessment of immune markers by immunohistochemistry (IHC) has significant limitations for describing the diversity of the immune response in cancer. Therefore, we evaluated a fluorescence-based multiplexed immunohistochemical method in combination with a multispectral imaging system to quantify immune infiltrates in situ in the environment of non-small-cell lung cancer (NSCLC). A tissue microarray including 57 NSCLC cases was stained with antibodies against CD8, CD20, CD4, FOXP3, CD45RO, and pan-cytokeratin, and immune cells were quantified in epithelial and stromal compartments. The results were compared with those of conventional IHC, and related to corresponding RNA-sequencing (RNAseq) expression values. We found a strong correlation between the visual and digital quantification of lymphocytes for CD45RO (correlation coefficient: r = 0.52), FOXP3 (r = 0.87), CD4 (r = 0.79), CD20 (r = 0.81) and CD8 (r = 0.90) cells. The correlation with RNAseq data for digital quantification (0.35-0.65) was comparable to or better than that for visual quantification (0.38-0.58). Combination of the signals of the five immune markers enabled further subpopulations of lymphocytes to be identified and localized. The specific pattern of immune cell infiltration based either on the spatial distribution (distance between regulatory CD8+ T and cancer cells) or the relationships of lymphocyte subclasses with each other (e.g. cytotoxic/regulatory cell ratio) were associated with patient prognosis. In conclusion, the fluorescence multiplexed immunohistochemical method, based on only one tissue section, provided reliable quantification and localization of immune cells in cancer tissue. The application of this technique to clinical biopsies can provide a basic characterization of immune infiltrates to guide clinical decisions in the era of immunotherapy. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

PD-L1 immunohistochemistry in clinical diagnostics of lung cancer: inter-pathologist variability is higher than assay variability.

Assessment of programmed cell death ligand 1 (PD-L1) immunohistochemical staining is used for decision on treatment with programmed cell death 1 and PD-L1 checkpoint inhibitors in lung adenocarcinomas and squamous cell carcinomas. This study aimed to compare the staining properties of tumor cells between the antibody clones 28-8, 22C3, SP142, and SP263 and investigate interrater variation between pathologists to see if these stainings can be safely evaluated in the clinical setting. Using consecutive sections from a tissue microarray with tumor tissue from 55 resected lung cancer cases, staining with five PD-L1 assays (28-8 from two different vendors, 22C3, SP142, and SP263) was performed. Seven pathologists individually evaluated the percentage of positive tumor cells, scoring each sample applying cutoff levels used in clinical studies: <1% positive tumor cells (score 0), 1-4% (score 1), 5-9% (score 2), 10-24% (score 3), 25-49% (score 4), and >50% positive tumor cells (score 5). Pairwise analysis of antibody clones showed weighted kappa values in the range of 0.45-0.91 with the highest values for comparisons with 22C3 and 28-8 and the lowest involving SP142. Excluding SP142 resulted in kappa 0.75-0.91. Weighted kappa for interobserver variation between pathologists was 0.71-0.96. Up to 20% of the cases were differently classified as positive or negative by any pathologist compared with consensus score using ≥1% positive tumor cells as cutoff. A significantly better agreement between pathologists was seen using ≥50% as cutoff (0-5% of cases). In conclusion, the concordance between the PD-L1 antibodies 22C3, 28-8 and SP263 is relatively good when evaluating lung cancers and suggests that any one of these assays may be sufficient as basis for decision on treatment with nivolumab, pembrolizumab, and durvalumab. The scoring of the pathologist presents an intrinsic source of error that should be considered especially at low PD-L1 scores.