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Background: Non-small cell lung cancer (NSCLC) is a heterogenous disease with challenging prognosis despite clinical improvements in the last years. The tumor-microenvironment (TME) is a major factor with many cell types involved as well as distinct spatial organization. We assessed the global immune landscape and spatial architecture of excluded immune cell types within the stroma of NSCLC tissues.

Methods: Multiplex Immunofluorescence (mIF) staining was used to detect major immune cell lineages in tissues of 674 NSCLC patients. AI-based digital image analyses were conducted to stratify NSCLC tissues into stroma and tumor compartments as well as identify and classify single cells based on mIF marker combinations into major immune cell phenotypes. Quantitative single-cell resolved immune cell phenotypes within the stroma area were used to cluster patients based on their excluded immune signature and spatial architecture and explored for impact on overall-survival.

Results: NSCLC stroma harbored distinct immune cell as well as spatial organizational patterns with varying combinations. Among these, a mixed immune landscape together with a stromal organization dominated by long distances to B cells and short distances to Helper T cells was associated with long-term overall-survival. This was successfully reduced to a two-variable signature comprising three different cell types, where short distances of Helper T cells to Regulatory T cells in conjunction with high B cell densities provided superior prognostic value.

Conclusions: The excluded immune cells within the stromal compartment are associated with strong prognostic effects based on their spatial architecture and represent a previously underappreciated cell population.

Introduction

Tertiary lymphoid structures (TLS) are lymphocyte aggregates resembling secondary lymphoid organs and are pivotal in cancer immunity. The ambiguous morphological definition of TLS makes it challenging to ascertain their clinical impact on patient survival and response to immunotherapy.

Objectives

This study aimed to characterize TLS in hematoxylin-eosin tissue sections from lung cancer patients, assessing their occurrence in relation to the local immune environment, mutational background, and patient outcome.

Methods

Two pathologists evaluated one whole tissue section from resection specimens of 680 NSCLC patients. TLS were spatially quantified within the tumor area or periphery and further categorized based on the presence of germinal centers (mature TLS). Metrics were integrated with immune cell counts, genomic and transcriptomic data, and correlated with clinical parameters.

Results

TLS were present in 86% of 536 evaluable cases, predominantly in the tumor periphery, with a median of eight TLS per case. Mature TLS were found in 24% of cases. TLS presence correlated positively with increased plasma cell (CD138+) and lymphocytic cell (CD3+, CD8+, FOXP3+) infiltration. Tumors with higher tumor mutational burden exhibited higher numbers of peripheral TLS. The overall TLS quantity was independently associated with improved patient survival, irrespective of TLS maturation status. This prognostic association held true for peripheral TLS but not for tumor TLS.

Conclusion

TLS in NSCLC is common and their correlation with a specific immune phenotype suggests biological relevance in the local immune reaction. The prognostic significance of this scoring system on routine hematoxylin-eosin sections has the potential to augment diagnostic algorithms for NSCLC patients.

Lung cancer is the leading cause of cancer-related death globally, with non-small cell lung cancer (NSCLC) constituting 85% of cases. The introduction of immunotherapies and targeted therapies have dramatically improved the prognosis and outcome for a subset of patients, and stressed the development of diagnostic tools for effective patient selection. This thesis addresses different aspects of current and future diagnostic strategies in NSCLC patients.

In Paper I, an immunohistochemical assay targeting the neurotropic tropomyosin receptor kinase (NTRK) was evaluated on tissue microarrays (TMAs) from a well-characterized NSCLC cohort. Although a few cases showed positive staining, none were positive in the reference molecular testing, highlighting the rarity of this targetable aberration and underscoring the value of cost-effective screening methods.

In Paper II, paired patient samples (biopsy, TMA, and surgical specimen) were evaluated regarding the immunohistochemical staining for PD-L1. The results indicated a strong correlation between the PD-L1 expression on biopsy and TMA compared with the tumor whole slide, suggesting that tumor heterogeneity has minor relevance for PD-L1 evaluation.

In Paper III, paired tissue samples (biopsy, TMA, and surgical specimen) were evaluated regarding infiltrating CD3+ immune cells. Only weak correlation was found between the biopsies and tumor whole slide, while the agreement between the whole slide and TMA was higher. These results question the use of biopsies for immune cell quantification, while supporting the TMA as a reliable tool in cancer research.

In Paper IV, the amount and distribution of tertiary lymphoid structures (TLS) was annotated on scanned tumor whole slides. TLS were present in most of the tumors and correlated with the abundance of specific immune cell subsets. Higher number of TLS were associated with longer survival, particularly in adenocarcinomas. High tumor mutational burden was associated with higher numbers of periphery TLS. These results provide a rationale for using TLS metrics as a diagnostic marker for NSCLC patients undergoing surgical resection.

In summary, this thesis addresses challenges in prognostic and predictive lung cancer diagnostics in the areas of targeted therapy and immunotherapy. The results provide crucial insights into tumor heterogeneity that may impact clinical decision-making and aid scientists in selecting appropriate tissue sources for translational and clinical cancer research.

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 ¼ .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.

Introduction: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial im-mune 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 thorn 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.

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.

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.

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.

Programmed cell death ligand 1 (PD-L1) expression within the same lung cancer tissue is variable. In this study we evaluated if the PD-L1 expression on small biopsy specimens represent the PD-L1 status of the corresponding resection specimen. Our results indicate a relative good agreement between biopsy and surgical specimens, with a discordance in approximately 10% of the cases. 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 kappa 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.

Introduction: A subgroup of lung adenocarcinoma shows neuroendocrine differentiation and expression of achaete-scute family bHLH transcription factor 1 (ASCL1), common to high-grade neuroendocrine tumors, small-cell lung cancer and large cell neuroendocrine carcinoma. Methods: The aim of this study was to characterize clinical and molecular features of ASCL1-positive lung adenocarcinoma by using recent transcriptome profiling in multiple patient cohorts and genome-wide epigenetic profiling including data from The Cancer Genome Atlas. Results: The ASCL1-positive subtype of lung adenocarcinoma developed preferentially in current or former smokers and usually did not harbor EGFR mutations. In transcriptome profiling, this subtype overlapped with the recently proposed proximal-proliferative molecular subtype. Gene expression profiling of ASCL1-positive cases suggested generally poor immune cell infiltration and none of the tumors were positive for programmed cell death ligand 1 protein expression. Genome-wide methylation analysis showed global DNA hypomethylation in ASCL1-positive cases. ASCL1 was associated with super-enhancers in ASCL1-positive lung adenocarcinoma cells, and ASCL1 silencing suppressed other super-enhancer-associated genes, suggesting thatASCL1 acts as a master transcriptional regulator. This was further reinforced by the essential roles of ASCL1 in cell proliferation, survival, and cell cycle control. Conclusions: These results suggest that ASCL1 defines a subgroup of lung adenocarcinoma with distinct molecular features by driving super-enhancer-mediated transcriptional programs.