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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.

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 &a

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage(1). Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types(2-6). Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types.

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.

Tumor-associated macrophages (TAMs) are attractive targets for immunotherapy. Recently, studies in animal models showed that treatment with an anti-TAM antibody directed against the scavenger receptor MARCO resulted in suppression of tumor growth and metastatic dissemination. Here we investigated the expression of MARCO in relation to other macrophage markers and immune pathways in a non-small cell lung cancer (NSCLC) cohort (n=352). MARCO, CD68, CD163, MSR1 and programmed death ligand-1 (PD-L1) were analyzed by immunohistochemistry and immunofluorescence, and associations to other immune cells and regulatory pathways were studied in a subset of cases (n=199) with available RNA-seq data. We observed a large variation in macrophage density between cases and a strong correlation between CD68 and CD163, suggesting that the majority of TAMs present in NSCLC exhibit a protumor phenotype. Correlation to clinical data only showed a weak trend toward worse survival for patients with high macrophage infiltration. Interestingly, MARCO was expressed on a distinct subpopulation of TAMs, which tended to aggregate in close proximity to tumor cell nests. On the transcriptomic level, we found a positive association between MARCO gene expression and general immune response pathways including strong links to immunosuppressive TAMs, T-cell infiltration and immune checkpoint molecules. Indeed, a higher macrophage infiltration was seen in tumors expressing PD-L1, and macrophages residing within tumor cell nests co-expressed MARCO and PD-L1. Thus, MARCO is a potential new immune target for anti-TAM treatment in a subset of NSCLC patients, possibly in combination with available immune checkpoint inhibitors.

Despite recent treatment advancements, the survival outcome remains poor for the majority of patients with non-small cell lung cancer (NSCLC). The aim of this thesis was to evaluate protein expression to predict prognosis and identify biomarkers that can be used as targets for immunotherapy or for early detection of NSCLC. In Paper I an optimized immunohistochemistry (IHC)-based prognostic model was developed for NSCLC. The prognostic performance of the model was compared to the clinicopathological parameters that are used in the clinical setting to predict outcome. The protein model failed to outperform clinicopathological parameters in predicting survival outcome questioning the potential of IHC-based assessment of prognostic markers in NSCLC. In Paper II the human testis-specific proteome was profiled using RNA-sequencing (RNA-seq) data from testis and 26 other organs. More than 1000 genes demonstrated a testis-enriched expression pattern which makes testis the tissue with the most tissue-specific genes. The majority of the testis-enriched genes were previously poorly described and were further profiled by IHC. This analysis provides a starting point to increase the molecular understanding of testicular biology. In Paper III the profiling of cancer-testis antigens (CTAs) was performed in NSCLC by using RNA-seq data from 32 normal organs and NSCLC. Ninety genes showed CTA expression profiles. The transcriptomic data were validated by IHC for several CTAs. The comprehensive analysis of CTAs can guide biomarker studies or help to identify targets for immunotherapeutic strategies. In Paper IV the reactivity of CTAs was evaluated by measuring the abundance of autoantibodies in plasma from patients with NSCLC and benign lung diseases. Twenty-nine CTAs demonstrated exclusive reactivity in NSCLC and six of them were reactive in an independent NSCLC cohort. These findings suggest that some CTAs are immunogenic and could be utilized in immunotherapy. In Paper V an immunoas

Background: There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). Methods: Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray (n = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts (n = 181; n = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. Results: CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203-0.719, P = 0.003). Conclusions: CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC., QC 20170210