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.

Diagnostic gastrointestinal markers in primary lung cancer and pulmonary metastases.

Histopathological diagnosis of pulmonary tumors is essential for treatment decisions. The distinction between primary lung adenocarcinoma and pulmonary metastasis from the gastrointestinal (GI) tract may be difficult. Therefore, we compared the diagnostic value of several immunohistochemical markers in pulmonary tumors. Tissue microarrays from 629 resected primary lung cancers and 422 resected pulmonary epithelial metastases from various sites (whereof 275 colorectal cancer) were investigated for the immunohistochemical expression of CDH17, GPA33, MUC2, MUC6, SATB2, and SMAD4, for comparison with CDX2, CK20, CK7, and TTF-1. The most sensitive markers for GI origin were GPA33 (positive in 98%, 60%, and 100% of pulmonary metastases from colorectal cancer, pancreatic cancer, and other GI adenocarcinomas, respectively), CDX2 (99/40/100%), and CDH17 (99/0/100%). In comparison, SATB2 and CK20 showed higher specificity, with expression in 5% and 10% of mucinous primary lung adenocarcinomas and both in 0% of TTF-1-negative non-mucinous primary lung adenocarcinomas (25-50% and 5-16%, respectively, for GPA33/CDX2/CDH17). MUC2 was negative in all primary lung cancers, but positive only in less than half of pulmonary metastases from mucinous adenocarcinomas from other organs. Combining six GI markers did not perfectly separate primary lung cancers from pulmonary metastases including subgroups such as mucinous adenocarcinomas or CK7-positive GI tract metastases. This comprehensive comparison suggests that CDH17, GPA33, and SATB2 may be used as equivalent alternatives to CDX2 and CK20. However, no single or combination of markers can categorically distinguish primary lung cancers from metastatic GI tract cancer.

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.

Highly elevated systemic inflammation is a strong independent predictor of early mortality in advanced non-small cell lung cancer.

BACKGROUND: Ample evidence support inflammation as a marker of outcome in non-small cell lung cancer (NSCLC). Here we explore the outcome for a subgroup of patients with advanced disease and substantially elevated systemic inflammatory activity. METHODS: The source cohort included consecutive patients diagnosed with NSCLC between January 2016 - May 2017 (n = 155). Patients with active infection were excluded. Blood parameters were examined individually, and cut-offs (ESR > 60 mm, CRP > 20 mg/L, WBC > 10 × 109, PLT > 400 × 109) were set to define the group of hyperinflamed patients. A score was developed by assigning one point for each parameter above cut-off (0-4 points). RESULTS: High systemic inflammation was associated with advanced stage and was seldom present in limited NSCLC. However, the one year survival of patients in stage IIIB-IV (n = 93) with an inflammation score of ≥2 was 0% compared to 33% and 50% among patients with a score of 1 and 0 respectively. The effect of a high inflammation score on overall survival remained significant in multi-variate analysis adjusted for confounding factors. The independent hazard ratio of an inflammation score ≥ 2 in multi-variate analysis (HR 3.43, CI 1.76-6.71) was comparable to a change in ECOG PS from 0 to 2 (HR 2.42, CI 1.13-5.18). CONCLUSION: Our results show that high level systemic inflammation is a strong independent predictor of poor survival in advanced stage NSCLC. This observation may indicate a need to use hyperinflammation as an additional clinical parameter for stratification of patients in clinical studies and warrants further research on underlying mechanisms linked to tumor progression.

Comparison of ROS1-rearrangement detection methods in a cohort of surgically resected non-small cell lung carcinomas.

Background: Patients with non-small cell lung cancer (NSCLC) harboring a ROS proto-oncogene 1 (ROS1)-rearrangement respond to treatment with ROS1 inhibitors. To distinguish these rare cases, screening with immunohistochemistry (IHC) for ROS1 protein expression has been suggested. However, the reliability of such an assay and the comparability of the antibody clones has been debated. Therefore we evaluated the diagnostic performance of current detection strategies for ROS1-rearrangement in two NSCLC-patient cohorts. Methods: Resected tissue samples, retrospectively collected from consecutive NSCLC-patients surgically treated at Uppsala University Hospital were incorporated into tissue microarrays [all n=676, adenocarcinomas (AC) n=401, squamous cell carcinomas (SCC) n=213, other NSCLC n=62]. ROS1-rearrangements were detected using fluorescence in situ hybridization (FISH) (Abbott Molecular; ZytoVision). In parallel, ROS1 protein expression was detected using IHC with three antibody clones (D4D6, SP384, EPMGHR2) and accuracy, sensitivity, and specificity were determined. Gene expression microarray data (Affymetrix) and RNA-sequencing data were available for a subset of patients. NanoString analyses were performed for samples with positive or ambiguous results (n=21). Results: Using FISH, 2/630 (0.3% all NSCLC; 0.5% non-squamous NSCLC) cases were positive for ROS1 fusion. Additionally, nine cases demonstrated ambiguous FISH results. Using IHC, ROS1 protein expression was detected in 24/665 (3.6% all NSCLC; 5.1% non-squamous NSCLC) cases with clone D4D6, in 18/639 (2.8% all NSCLC; 3.9% non-squamous NSCLC) cases with clone SP384, and in 1/593 (0.2% all NSCLC; 0.3% non-squamous NSCLC) case with clone EPMGHR2. Elevated RNA-levels were seen in 19/369 (5.1%) cases (Affymetrix and RNA-sequencing combined). The overlap of positive results between the assays was poor. Only one of the FISH-positive cases was positive with all antibodies and demonstrated high RNA-expression. This rearrangement was confirmed in the NanoString-assay and also in the RNA-sequencing data. Other cases with high protein/RNA-expression or ambiguous FISH were negative in the NanoString-assay. Conclusions: The occurrence of ROS1 fusions is low in our cohorts. The IHC assays detected the fusions, but the accuracy varied depending on the clone. The presumably false-positive and uncertain FISH results questions this method for detection of ROS1-rearrangements. Thus, when IHC is used for screening, transcript-based assays are preferable for validation in clinical diagnostics.

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.

Plasma Proteomic Analysis in Non-Small Cell Lung Cancer Patients Treated with PD-1/PD-L1 Blockade.

Checkpoint inhibitors have been approved for the treatment of non-small cell lung cancer (NSCLC). However, only a minority of patients demonstrate a durable clinical response. PD-L1 scoring is currently the only biomarker measure routinely used to select patients for immunotherapy, but its predictive accuracy is modest. The aim of our study was to evaluate a proteomic assay for the analysis of patient plasma in the context of immunotherapy. Pretreatment plasma samples from 43 NSCLC patients who received anti-PD-(L)1 therapy were analyzed using a proximity extension assay (PEA) to quantify 92 different immune oncology-related proteins. The plasma protein levels were associated with clinical and histopathological parameters, as well as therapy response and survival. Unsupervised hierarchical cluster analysis revealed two patient groups with distinct protein profiles associated with high and low immune protein levels, designated as "hot" and "cold". Further supervised cluster analysis based on T-cell activation markers showed that higher levels of T-cell activation markers were associated with longer progression-free survival (PFS) (p < 0.01). The analysis of single proteins revealed that high plasma levels of CXCL9 and CXCL10 and low ADA levels were associated with better response and prolonged PFS (p < 0.05). Moreover, in an explorative response prediction model, the combination of protein markers (CXCL9, CXCL10, IL-15, CASP8, and ADA) resulted in higher accuracy in predicting response than tumor PD-L1 expression or each protein assayed individually. Our findings demonstrate a proof of concept for the use of multiplex plasma protein levels as a tool for anti-PD-(L)1 response prediction in NSCLC. Additionally, we identified protein signatures that could predict the response to anti-PD-(L)1 therapy.

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.

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.

Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene.

Infrequent and rare genetic variants in the human population vastly outnumber common ones. Although they may contribute significantly to the genetic basis of a disease, these seldom-encountered variants may also be miss-identified as pathogenic if no correct references are available. Somatic and germline TP53 variants are associated with multiple neoplastic diseases, and thus have come to serve as a paradigm for genetic analyses in this setting. We searched 14 independent, globally distributed datasets and recovered TP53 SNPs from 202,767 cancer-free individuals. In our analyses, 19 new missense TP53 SNPs, including five novel variants specific to the Asian population, were recurrently identified in multiple datasets. Using a combination of in silico, functional, structural, and genetic approaches, we showed that none of these variants displayed loss of function compared to the normal TP53 gene. In addition, classification using ACMG criteria suggested that they are all benign. Considered together, our data reveal that the TP53 coding region shows far more polymorphism than previously thought and present high ethnic diversity. They furthermore underline the importance of correctly assessing novel variants in all variant-calling pipelines associated with genetic diagnoses for cancer.

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.

Comprehensive analysis of RNA binding motif protein 3 (RBM3) in non-small cell lung cancer.

AIMS: High expression of the RNA-binding motif protein 3 (RBM3) correlates with improved prognosis in several major types of cancer. The aim of the present study was to examine the prognostic value of RBM3 protein and mRNA expression in non-small cell lung cancer (NSCLC). METHODS AND RESULTS: Immunohistochemical expression of RBM3 was evaluated in surgically treated NSCLC from two independent patient populations (n = 213 and n = 306). Staining patterns were correlated with clinicopathological parameters, overall survival (OS), and recurrence-free interval (RFI). Cases with high nuclear RBM3 protein expression had a prolonged 5-year OS in both cohorts when analyzing adenocarcinomas separately (P = .02 and P = .01). RBM3 remained an independent prognostic factor for OS in multivariable analysis of cohort I (HR 0.44, 95% CI 0.21-0.90) and for RFI in cohort II (HR 0.38, 95% CI 0.22-0.74). In squamous cell carcinoma, there was instead an insignificant association to poor prognosis. Also, the expression levels of RBM3 mRNA were investigated in 2087 lung adenocarcinomas and 899 squamous cell carcinomas assembled from 13 and 8 public gene expression microarray datasets, respectively. The RBM3 mRNA levels were not clearly associated with patient outcome in either adenocarcinomas or squamous cell carcinomas. CONCLUSIONS: The results from this study support that high protein expression of RBM3 is linked to improved outcome in lung adenocarcinoma.

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

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Diagnostic Value of Insulinoma-Associated Protein 1 (INSM1) and Comparison With Established Neuroendocrine Markers in Pulmonary Cancers.

CONTEXT.­: The diagnostic distinction of pulmonary neuroendocrine (NE) tumors from non-small cell lung carcinomas (NSCLCs) is clinically relevant for prognostication and treatment. Diagnosis is based on morphology and immunohistochemical staining. OBJECTIVE.­: To determine the diagnostic value of insulinoma-associated protein 1 (INSM1), in comparison with established NE markers, in pulmonary tumors. DESIGN.­: Fifty-four pulmonary NE tumors and 632 NSCLCs were stained for INSM1, CD56, chromogranin A, and synaptophysin. In a subset, gene expression data were available for analysis. Also, 419 metastases to the lungs were stained for INSM1. A literature search identified 39 additional studies with data on NE markers in lung cancers from the last 15 years. Seven of these included data on INSM1. RESULTS.­: A positive INSM1 staining was seen in 39 of 54 NE tumors (72%) and 6 of 623 NSCLCs (1%). The corresponding numbers were 47 of 54 (87%) and 14 of 626 (2%) for CD56, 30 of 54 (56%) and 6 of 629 (1%) for chromogranin A, and 46 of 54 (85%) and 49 of 630 (8%) for synaptophysin, respectively. Analysis of literature data revealed that CD56 and INSM1 were the best markers for identification of high-grade NE pulmonary tumors when considering both sensitivity and specificity, while synaptophysin also showed good sensitivity. INSM1 gene expression was clearly associated with NE histology. CONCLUSIONS.­: The solid data of both our and previous studies confirm the diagnostic value of INSM1 as a NE marker in pulmonary pathology. The combination of CD56 with INSM1 and/or synaptophysin should be the first-hand choice to confirm pulmonary high-grade NE tumors. INSM1 gene expression could be used to predict NE tumor histology.

c-MET as a biomarker in patients with surgically resected non-small cell lung cancer.

BACKGROUND: c-MET protein overexpression has been proposed as a biomarker in non-small cell lung cancer (NSCLC), albeit its role in the clinical setting has not been firmly established yet. PATIENTS AND METHODS: We designed a retrospective cohort study, consisting of 725 patients with surgically removed NSCLC. Immunohistochemistry (IHC) was conducted in tissue microarrays (TMA) from lung tumors and healthy tissue. IHC staining was quantified using H-scores (range 0-300). Association between c-MET H-score and overall survival (OS) as well as progression-free survival (PFS) was explored. RESULTS: c-MET H-score ≥20 had a significant positive impact on OS in the multivariate analysis in the whole study population, HR = 0.79 (95%CI: 0.64-0.97). The prognostic effect of c-MET H-score ≥20 was even stronger in patients who received adjuvant treatment with a HR = 0.61 (95% CI: 0.40-0.93). In the subgroup of adenocarcinoma and squamous cell carcinoma patients with stage IIA-IIIB disease, the prognostic impact of c-MET was significant in the univariate analysis (HR = 0.60, 95% CI: 0.43-0.83). CONCLUSION: c-MET H-score ≥20 is a positive prognostic biomarker for OS in early stage NSCLC. This benefit seems to be strongly correlated to adjuvant chemotherapy, therefore rendering c-MET H-score ≥20 a possible predictive biomarker for platinum-based adjuvant chemotherapy in early stage NSCLC.

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.

Mutation patterns in a population-based non-small cell lung cancer cohort and prognostic impact of concomitant mutations in KRAS and TP53 or STK11.

OBJECTIVES: Non-small cell lung cancer (NSCLC) is a heterogeneous disease with unique combinations of somatic molecular alterations in individual patients, as well as significant differences in populations across the world with regard to mutation spectra and mutation frequencies. Here we aim to describe mutational patterns and linked clinical parameters in a population-based NSCLC cohort. MATERIALS AND METHODS: Using targeted resequencing the mutational status of 82 genes was evaluated in a consecutive Swedish surgical NSCLC cohort, consisting of 352 patient samples from either fresh frozen or formalin fixed paraffin embedded (FFPE) tissues. The panel covers all exons of the 82 genes and utilizes reduced target fragment length and two-strand capture making it compatible with degraded FFPE samples. RESULTS: We obtained a uniform sequencing coverage and mutation load across the fresh frozen and FFPE samples by adaption of sequencing depth and bioinformatic pipeline, thereby avoiding a technical bias between these two sample types. At large, the mutation frequencies resembled the frequencies seen in other western populations, except for a high frequency of KRAS hotspot mutations (43%) in adenocarcinoma patients. Worse overall survival was observed for adenocarcinoma patients with a mutation in either TP53, STK11 or SMARCA4. In the adenocarcinoma KRAS-mutated group poor survival appeared to be linked to concomitant TP53 or STK11 mutations, and not to KRAS mutation as a single aberration. Similar results were seen in the analysis of publicly available data from the cBioPortal. In squamous cell carcinoma a worse prognosis could be observed for patients with MLL2 mutations, while CSMD3 mutations were linked to a better prognosis. CONCLUSION: Here we have evaluated the mutational status of a NSCLC cohort. We could not confirm any survival impact of isolated driver mutations. Instead, concurrent mutations in TP53 and STK11 were shown to confer poor survival in the KRAS-positive adenocarcinoma subgroup.