Image Analysis-based Assessment of PD-L1 and Tumor-Associated Immune Cells Density Supports Distinct Intratumoral Microenvironment Groups in Non-small Cell Lung Carcinoma Patients

Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma

Surgical resection of pulmonary adenocarcinoma is considered to be curative but progression-free survival (PFS) has remained highly variable. Antitumor immune response may be important, however, the prognostic significance of tumor-infiltrating natural killer (NK) and regulatory T (Treg) lymphocytes is uncertain. Resected pulmonary adenocarcinoma tissues (n = 115) were studied by immunohistochemical detection of NKp46 and FoxP3 positivity to identify NK and Treg cells, respectively. Association of cell densities with clinicopathological features and progression-free survival (PFS) as well as overall survival (OS) were analyzed with a follow-up time of 60 months. Both types of immune cells were accumulated predominantly in tumor stroma. NK cell density showed association with female gender, non-smoking and KRAS wild-type status. According to Kaplan-Meier analysis, PFS and OS proved to be longer in patients with high NK or Treg cell densities (p = 0.0293 and p = 0.0375 for PFS, p = 0.0310 and p = 0.0448 for OS, respectively). Evaluating the prognostic effect of the combination of NK and Treg cell density values revealed that PFS and OS were significantly longer in NKhigh/Treghigh cases compared to the other groups combined (p = 0.0223 and p = 0.0325, respectively). Multivariate Cox regression analysis indicated that high NK cell density was independent predictor of longer PFS while high NK and high Treg cell densities both proved significant predictors of longer OS. The NKhigh/Treghigh combination also proved to be an independent prognostic factor for both PFS and OS. In conclusion, NK and Treg cells can be components of the innate and adaptive immune response at action against progression of pulmonary adenocarcinoma.

Radiomics model based on intratumoral and peritumoral features for predicting major pathological response in non-small cell lung cancer receiving neoadjuvant immunochemotherapy

Objective

To establish a radiomics model based on intratumoral and peritumoral features extracted from pre-treatment CT to predict the major pathological response (MPR) in patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant immunochemotherapy.

Methods

A total of 148 NSCLC patients who underwent neoadjuvant immunochemotherapy from two centers (SRRSH and ZCH) were retrospectively included. The SRRSH dataset (n=105) was used as the training and internal validation cohort. Radiomics features of intratumoral (T) and peritumoral regions (P1 = 0-5mm, P2 = 5-10mm, and P3 = 10-15mm) were extracted from pre-treatment CT. Intra- and inter- class correlation coefficients and least absolute shrinkage and selection operator were used to feature selection. Four single ROI models mentioned above and a combined radiomics (CR: T+P1+P2+P3) model were established by using machine learning algorithms. Clinical factors were selected to construct the combined radiomics-clinical (CRC) model, which was validated in the external center ZCH (n=43). The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis.

Results

Histopathological type was the only independent clinical risk factor. The model CR with eight selected radiomics features demonstrated a good predictive performance in the internal validation (AUC=0.810) and significantly improved than the model T (AUC=0.810 vs 0.619, p<0.05). The model CRC yielded the best predictive capability (AUC=0.814) and obtained satisfactory performance in the independent external test set (AUC=0.768, 95% CI: 0.62-0.91).

Conclusion

We established a CRC model that incorporates intratumoral and peritumoral features and histopathological type, providing an effective approach for selecting NSCLC patients suitable for neoadjuvant immunochemotherapy.

Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Leveraging an immune cell signature to improve the survival and immunotherapy response of lung adenocarcinoma

Background: Immune cells play a critical role in the prognosis of cancer. However, the function of different immune cell types in lung adenocarcinoma (LUAD) and the development of a prognostic signature based on immune cell types have not been comprehensively investigated. Methods: We collected and included a total of 2499 LUAD patients and performed calculations to determine the penetration level of 24 immune cells. This examination was conducted using the macro-gene-based approach provided by ImmuCellAI. We performed a meta-analysis using Lasso-Cox analysis to establish the immune cell pair score (ICPS). We conducted a survival analysis to measure differences in survival across ICPS-risk groups. Wilcox test was used to measure the difference in expression level. Spearman correlation analysis was used for the relevance assessment. Results: We collected a total of 24 immune cell types to construct cell pairs. Utilizing 17 immune cell pairs, we constructed and validated the ICPS, which plays a critical role in stratifying survival and dynamically monitoring the effectiveness of immunotherapy. Additionally, we identified several candidate drugs that target ICPS. Conclusions: The ICPS shows promise as a valuable tool for identifying suitable candidates for immunotherapy among patients. Our comprehensive assessment of immune cell interactions in LUAD contributes to a deeper understanding of infiltration patterns and functions, thereby guiding the development of more efficacious immunotherapy strategies.

Increased co-expression of PD1 and TIM3 is associated with poor prognosis and immune microenvironment heterogeneity in gallbladder cancer

BACKGROUND

The effectiveness of immune checkpoint inhibitors in treating gallbladder cancer (GBC) remains unsatisfactory. Recently, several new immune checkpoints have been identified. However, investigations exploring these immune checkpoints in GBC are limited. In this study, we aim to investigate the expression patterns and clinical implications of various immune checkpoints, and further characterize the spatial and quantitative heterogeneity of immune components in GBC.

METHODS

We employed single and multiplex immunohistochemistry to evaluate the expression of five immune checkpoint markers and four immune cell markers in the primary tumor core, hepatic invasion margin, and liver metastasis. Subsequently, we analyzed their interrelationships and their prognostic significance.

RESULTS

We observed a robust positive correlation between PD1/TIM3 expression in GBC (R = 0.614, P < 0.001). The co-expression of PD1/TIM3 exhibited a synergistic effect in predicting poor prognosis among postoperative GBC patients. Further analysis revealed that the prognostic significance of PD1/TIM3 was prominent in the subgroup with high infiltration of CD8 + T cells (P < 0.001). Multiplex immunohistochemistry reveals that PD1 + TIM3 + FOXP3 + cells constitute a significant proportion of FOXP3 + TILs in GBC tissue. Moreover, the co-high expression of PD1 and TIM3 is positively correlated with the accumulation of CD8 + TILs at the hepatic invasion margin. Lastly, our findings indicated reduced expression levels of immune checkpoints and diminished immune cell infiltration in liver metastases compared to primary tumors.

CONCLUSIONS

Increased co-expression of PD1/TIM3 is associated with poor prognosis in GBC patients and is related to the heterogeneity of immune microenvironment between GBC primary tumor and its hepatic invasion margin or liver metastases, which may be a potential target for future immunotherapy of GBC.

Pre-existing tumor host immunity characterization in resected non-small cell lung cancer

INTRODUCTION

Neoadjuvant and adjuvant immune checkpoint blockade (ICB) have recently become standard of care in resectable non-small cell lung cancer (NSCLC). Yet, biomarkers that inform patients who benefit from this approach remain largely unknown. Here, we interrogated the tumor immune microenvironment (TIME) in early-stage NSCLC patients that underwent up-front surgery.

METHODS

A total of 185 treatment-naïve patients with early-stage NSCLC, that underwent up-front surgical treatment between 2006 and 2018 at Hospital del Mar were included. 124 lung adenocarcinomas (LUADs), and 61 squamous cell carcinoma (LUSCs) were included in a tissue microarray. Immunohistochemistry for CD3, CD4, CD8, CD68, CD80, CD103, FOXP3, PD-1, PD-L1, PD-L2 and HLA class II were evaluated by digital image analysis (QuPath software). TIME was categorized into four groups using PD-L1 expression in tumor cells (<1 % or ≥1 %) and tumor resident memory (CD103⁺) immune cells (using the median as cut-off). We explored the association between different TIME dimensions and patient's clinicopathological features and outcomes.

RESULTS

We found increased levels of T cell markers (CD3⁺, CD4⁺, CD8⁺ cells), functional immune markers (FOXP3⁺ cells) as well as, higher HLA-II tumor membrane expression in LUADs compared to LUSCs (p < 0.05 for all). In contrast, LUSCs displayed higher percentage of intratumor macrophages (CD68⁺ cells) as well as, higher PD-L1 and PD-L2 tumor membrane expression (p < 0.05 for all). Unsupervised analysis revealed three different tumor subsets characterized by membrane tumor expression of PD-L1, PD-L2 and HLA-class II. Enrichment of T cells (CD3⁺, CD8⁺ cells), regulatory T cells (FOXP3⁺ cells) and macrophages (CD68⁺ cells) was observed in the CD103⁺/PD-L1⁺ group (p < 0.05 for all). Multivariate analysis showed that infiltration by CD103⁺ immune cells was associated with improved OS (p = 0.009).

CONCLUSIONS

TIME analysis in resected NSCLC highlighted differences by histology, PD-L1 expression and molecular subgroups. Biomarker studies using IHC might aid to individually tailor adjuvant treatment in early-stage NSCLC.

Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.

PET-based radiomics visualizes tumor-infiltrating CD8 T cell exhaustion to optimize radiotherapy/immunotherapy combination in mouse models of lung cancer

BACKGROUND

Cumulative preclinical and clinical evidences showed radiotherapy might augment systemic antitumoral responses to immunotherapy for metastatic non-small cell lung cancer, but the optimal timing of combination is still unclear. The overall infiltration and exhausted subpopulations of tumor-infiltrating CD8⁺ T cells might be a potential biomarker indicating the response to immune checkpoint inhibitors (ICI), the alteration of which is previously uncharacterized during peri-irradiation period, while dynamic monitoring is unavailable via repeated biopsies in clinical practice.

METHODS

Basing on tumor-bearing mice model, we investigated the dynamics of overall infiltration and exhausted subpopulations of CD8⁺ T cells after ablative irradiation. With the understanding of distinct metabolic characteristics accompanied with T cell exhaustion, we developed a PET radiomics approach to identify and visualize T cell exhaustion status.

RESULTS

CD8⁺ T cell infiltration increased from 3 to 14 days after ablative irradiation while terminally exhausted populations significantly predominated CD8⁺ T cells during late course of this infiltrating period, indicating that 3-7 days post-irradiation might be a potential appropriate window for delivering ICI treatment. A PET radiomics approach was established to differentiate T cell exhaustion status, which fitted well in both ICI and irradiation settings. We also visualized the underlying association of more heterogeneous texture on PET images with progressed T cell exhaustion.

CONCLUSIONS

We proposed a non-invasive imaging predictor which accurately assessed heterogeneous T cell exhaustion status relevant to ICI treatment and irradiation, and might serve as a promising solution to timely estimate immune-responsiveness of tumor microenvironment and the optimal timing of combined therapy.

Visible- and near-infrared hyperspectral imaging for the quantitative analysis of PD-L1+ cells in human lymphomas: Comparison with fluorescent multiplex immunohistochemistry

INTRODUCTION

We analyzed the expression of PD-L1 in human lymphomas using hyperspectral imaging (HSI) compared to visual assessment (VA) and conventional digital image analysis (DIA) to strengthen further the value of HSI as a tool for the evaluation of brightfield-based immunohistochemistry (IHC). In addition, fluorescent multiplex immunohistochemistry (mIHC) was used as a second detection method to analyze the impact of a different detection method.

MATERIAL AND METHODS

18 cases (6 follicular lymphomas and 12 diffuse large B-cell lymphomas) were stained for PD-L1 by IHC and for PD-L1, CD3, and CD8 by fluorescent mIHC. The percentage of positively stained cells was evaluated with VA, HSI, and DIA for IHC and VA and DIA for mIHC. Results were compared between the different methods of detection and analysis.

RESULTS

An overall high concordance was found between VA, HSI, and DIA in IHC (Cohens Kappa = 0.810^VA/HSI, 0.710 ^VA/DIA, and 0.516 ^HSI/DIA) and for VA^mIHCversus DIA^mIHC (Cohens Kappa = 0.894). Comparing IHC and mIHC general agreement differed depending on the methods compared but reached at most a moderate agreement (Coheńs Kappa between 0.250 and 0.483). This is reflected by the significantly higher percentage of PD-L1+ cells found with mIHC (p^Friedman = 0.014).

CONCLUSION

Our study shows a good concordance for the different analysis methods. Compared to VA and DIA, HSI proved to be a reliable tool for assessing IHC. Understanding the regulation of PD-L1 expression will further enlighten the role of PD-L1 as a biomarker. Therefore it is necessary to develop an instrument, such as HSI, which can offer a reliable and objective evaluation of PD-L1 expression.

Functional status and spatial interaction of T cell subsets driven by specific tumor microenvironment correlate with recurrence of non-small cell lung cancer

Background

The anti-tumoral or pro-tumoral roles of CD4+ and CD8+ T cells typify the complexity of T cell subsets function in cancer. In the non-small cell lung cancer (NSCLC), the density and topology of distinct T cell phenotypes at the tumor center (TC) versus the invasive margin (IM) are largely unknown. Here, we investigated T cell subsets density and distribution within TC and IM regions in NSCLC and its impact on the prognosis.

Methods

We performed multiplex immunofluorescence using a tissue microarray of samples from 99 patients with locally advanced NSCLC to elucidate the distributions of tumor cell, T cell subpopulations (CD4/conventional CD4/regulatory CD4/CD8/cytotoxic CD8/pre-dysfunctional CD8/dysfunctional CD8), microvessel density (MVD), cancer-associated fibroblasts (CAFs) and hypoxia-inducible factor-1α (HIF-1α) in TC and IM tissues. Cell-to-cell nearest neighbor distances and interactions were analyzed using the phenoptrreports R package. Cox regression was used to evaluate the associations between T cell subsets density and proximity to tumor cells and recurrence-free survival (RFS). Correlations between different cell subsets were examined by Spearman's or Kruskal-Wallis tests.

Results

In the locally advanced NSCLC, the proportion of tumor cells and CAFs in IM is lower than in the TC, while MVD, CD4+, and CD8+ T lymphocytes were increased, and tumor cells were closer to T lymphocytes and their subsets. The density and proximity of CD4+ and CD8+ T cells in the TC and IM regions were not associated with RFS, but in the IM area, increased density of dysfunctional CD8 and closer regulatory CD4 to tumor cells were independent risk factors for recurrence (HR were 3.536 and 2.884, respectively), and were positively correlated with HIF-1α+CD8 (r = 0.41, P = 0.000) and CAFs (P = 0.017), respectively.s.

Conclusions

In locally advanced NSCLC, the functional status of T cells in the IM region is closely related to recurrence. The density of dysfunctional CD8 and the proximity of regulatory CD4 to tumor cells were independent risk factors for recurrence, and are positively correlated with the hypoxia response of CD8+ T cells and CAFs. Targeting hypoxia or CAFs is expected to further sensitize therapy.

Analysis of Immune Intratumor Heterogeneity Highlights Immunoregulatory and Coinhibitory Lymphocytes as Hallmarks of Recurrence in Stage I Non-Small Cell Lung Cancer

Our understanding of the molecular mechanisms underlying postsurgical recurrence of non-small cell lung cancer (NSCLC) is rudimentary. Molecular and T cell repertoire intratumor heterogeneity (ITH) have been reported to be associated with postsurgical relapse; however, how ITH at the cellular level impacts survival is largely unknown. Here we report the analysis of 2880 multispectral images representing 14.2% to 27% of tumor areas from 33 patients with stage I NSCLC, including 17 cases (relapsed within 3 years after surgery) and 16 controls (without recurrence ≥5 years after surgery) using multiplex immunofluorescence. Spatial analysis was conducted to quantify the minimum distance between different cell types and immune cell infiltration around malignant cells. Immune ITH was defined as the variance of immune cells from 3 intratumor regions. We found that tumors from patients having relapsed display different immune biology compared with nonrecurrent tumors, with a higher percentage of tumor cells and macrophages expressing PD-L1 (P =.031 and P =.024, respectively), along with an increase in regulatory T cells (Treg) (P =.018), antigen-experienced T cells (P =.025), and effector-memory T cells (P =.041). Spatial analysis revealed that a higher level of infiltration of PD-L1+ macrophages (CD68+PD-L1+) or antigen-experienced cytotoxic T cells (CD3+CD8+PD-1+) in the tumor was associated with poor overall survival (P =.021 and P =.006, respectively). A higher degree of Treg ITH was associated with inferior recurrence-free survival regardless of tumor mutational burden (P =.022), neoantigen burden (P =.021), genomic ITH (P =.012) and T cell repertoire ITH (P =.001). Using multiregion multiplex immunofluorescence, we characterized ITH at the immune cell level along with whole exome and T cell repertoire sequencing from the same tumor regions. This approach highlights the role of immunoregulatory and coinhibitory signals as well as their spatial distribution and ITH that define the hallmarks of tumor relapse of stage I NSCLC.

MYCBP2 expression correlated with inflammatory cell infiltration and prognosis immunotherapy in thyroid cancer patients

Introduction

Immune checkpoint inhibitors (ICIs) have shown promising results for the treatment of multiple cancers. ICIs and related therapies may also be useful for the treatment of thyroid cancer (TC). In TC, Myc binding protein 2 (MYCBP2) is correlated with inflammatory cell infiltration and cancer prognosis. However, the relationship between MYCBP2 expression and ICI efficacy in TC patients is unclear.

Methods

We downloaded data from two TC cohorts, including transcriptomic data and clinical prognosis data. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict the efficacy of ICIs in TC patients. MCPcounter, xCell, and quanTIseq were used to calculate immune cell infiltration scores. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to evaluate signaling pathway scores. Immunohistochemical (IHC) analysis and clinical follow up was used to identify the MYCBP2 protein expression status in patients and associated with clinical outcome.

Results

A higher proportion of MYCBP2-high TC patients were predicted ICI responders than MYCBP2-low patients. MYCBP2-high patients also had significantly increased infiltration of CD8+ T cells, cytotoxic lymphocytes (CTLs), B cells, natural killer (NK) cells and dendritic cells (DC)s. Compared with MYCBP2-low patients, MYCBP2-high patients had higher expression of genes associated with B cells, CD8+ T cells, macrophages, plasmacytoid dendritic cells (pDCs), antigen processing and presentation, inflammatory stimulation, and interferon (IFN) responses. GSEA and ssGSEA also showed that MYCBP2-high patients had significantly increased activity of inflammatory factors and signaling pathways associated with immune responses.In addiation, Patients in our local cohort with high MYCBP2 expression always had a better prognosis and greater sensitivity to therapy while compared to patients with low MYCBP2 expression after six months clinic follow up.

Conclusions

In this study, we found that MYCBP2 may be a predictive biomarker for ICI efficacy in TC patients. High MYCBP2 expression was associated with significantly enriched immune cell infiltration. MYCBP2 may also be involved in the regulation of signaling pathways associated with anti-tumor immune responses or the production of inflammatory factors.

Combined pembrolizumab and bevacizumab therapy effectively inhibits non-small-cell lung cancer growth and prevents postoperative recurrence and metastasis in humanized mouse model

Antibodies targeting the programmed cell death protein 1/programmed cell death ligand-1 (PD-1/PD-L1) pathway have dramatically changed the treatment landscape of advanced non-small cell lung cancer (NSCLC). However, combination approaches are required to extend this benefit beyond a subset of patients. In addition, it is of equal interest whether these combination therapy can be applied to neoadjuvant therapy of early-stage NSCLC. In this study, we hypothesized that combining immunotherapy with anti-angiogenic therapy may have a synergistic effect in local tumor control and neoadjuvant therapy. To this end, the effect of combination of bevacizumab and pembrolizumab in humanized mouse models was evaluated. Furthermore, we innovatively constructed a neoadjuvant mouse model that can simulate postoperative recurrence and metastasis of NSCLC to perform neoadjuvant study. Tumor growth and changes in the tumor vasculature, along with the frequency and phenotype of tumor-infiltrating lymphocytes, were examined. Additionally, in vivo imaging system (IVIS) was used to observe the effect of neoadjuvant therapy. Results showed that combination therapy could inhibited tumor growth by transforming tumor with low immunoreactivity into inflamed ('hot') tumor, as demonstrated by increased CD8⁺granzyme B⁺ cytotoxic T cell infiltration. Subsequent studies revealed that this process is mediated by vascular normalization and endothelial cell activation. IVIS results showed that neoadjuvant therapy can effectively prevent postoperative recurrence and metastasis. Taken together, these preclinical studies demonstrated that the combination of bevacizumab and pembrolizumab had a synergistic effect in both advanced tumor therapy and neoadjuvant setting and therefore provide a theoretical basis for translating this basic research into clinical applications.

Prediction of lung squamous cell carcinoma immune microenvironment and immunotherapy efficiency with pyroptosis-derived genes

Lung squamous cell carcinoma (LUSC) is a common subtype of lung cancer that exhibits diverse pyroptosis regulatory patterns. Studies have highlighted the significance of pyroptosis in cancer invasion and immune responses. We aimed to explore the signatures of pyroptosis-related genes and their immune relevance in LUSC. Using The Cancer Genome Atlas (TCGA)-LUSC cohort and 5 gene expression omnibus (GEO) datasets, we performed consensus clustering based on 41 pyroptosis-related genes, and single sample gene set enrichment analysis (ssGSEA) was employed to calculate the infiltration levels of distinct clusters. A pyroptosis scoring scheme using the principal component analysis (PCA) method was used to quantify pyroptosis regulation in patients with LUSC and predict their prognosis. Four pyroptosis clusters were identified among 833 LUSC samples, which were associated with different Kyoto encyclopedia of genes and genome (KEGG) signaling pathways and tumor microenvironment infiltration features, and were highly consistent with 4 reported immune phenotypes: immune-responsive, immune-non-functional, immune-exclusion, and immune-ignorance. We then divided the patients into high- and low-pyroptosis score subgroups, and patients with higher scores were characterized by prolonged survival and attenuated immune infiltration. Moreover, higher scores were correlated with male patients, higher microsatellite instability, lower immune checkpoint inhibitor expression (such as CTLA-4 and GAL-9), and high mutation rates of typical mutated genes (e.g., TP53 and TTN). In particular, patients with lower pyroptosis scores showed better immune response to immune checkpoint inhibitor treatment. Pyroptosis regulatory patterns in the immune microenvironment can predict the clinical outcomes of patients with LUSC. Accurately quantifying the pyroptosis of individual patients will strengthen the understanding of heterogeneity within the LUSC tumor microenvironment infiltration areas.

Biomarkers for Immunotherapy in Poorly Differentiated Sinonasal Tumors

The sinonasal cavities harbor a wide variety of rare cancer types. Histopathological classification can be challenging, especially for poorly differentiated tumors. Despite advances in surgery and radio-chemotherapy, the 5-year survival rate is still very low. Thus, there is an unmet clinical need for new therapeutic options. We retrospectively evaluated poorly differentiated tumors of 9 different histological subtypes from 69 patients who had received conventional treatments for the presence of CD8+ tumor-infiltrating lymphocytes (TILs), as well as the expression of PD-L1 and microsatellite instability (MSI) markers MLH1, MSH2, MSH6 and PMS2, as biomarkers for immunotherapy. CD8+ TILs were present in 23/69 (33%) cases, PD-L1 expression was observed in 23/69 (33%), and markers for MSI positivity in 5/69 (7%) cases. CD8+ TILs correlated with PD-L1 positivity, while both were mutually exclusive with MSI markers. None of the biomarkers were associated with clinical features as age, gender or tumor stage. Cases with CD8+ TILs and PD-L1 positivity showed a tendency toward worse disease-specific survival. Immune checkpoint inhibitors are emerging as new options for treatment of many tumor types. Our results indicate that also a substantial subset of patients with poorly differentiated sinonasal tumors may be a candidate to be treated with this promising new therapy.

Tobacco Use and Response to Immune Checkpoint Inhibitor Therapy in Non-Small Cell Lung Cancer

Tobacco is a known risk factor for lung cancer, and continued tobacco use is associated with poorer outcomes across multiple lung cancer treatment modalities including surgery, chemotherapy and radiation therapy. Less is known about the association of tobacco use and outcomes with immune checkpoint inhibitors (ICIs), which are becoming an important part of the treatment landscape in lung cancer, both in metastatic and curative settings. We reviewed the literature on the association of tobacco and tumor biology as it relates to immunotherapy. We also reviewed the association of tobacco use on outcomes among phase III randomized clinical trials involving ICIs in non-small cell lung cancer (NSCLC). We identified that patients with a smoking history may have a greater benefit with ICI treatment compared to never smokers in both treatment-naïve (HR 0.82, 95% CI 0.69–0.97, vs. HR 1.06, 95% CI 0.81–1.38) and pre-treated (HR 0.79, 95% CI 0.70–0.90 vs. 1.03, 95% CI 0.74–1.43) settings. In trials where smoking status was further defined, ex-smokers appear to demonstrate greater benefit with ICI therapy compared to current smokers (HR 0.78, 95% CI 0.59–1.01 vs. 0.91, 95% CI 0.72–1.14). We conclude by offering our perspective on future directions in this area of research, including implementation of standardized collection and analysis of tobacco use in clinical trials involving ICI therapy in lung cancer and other disease sites, and also evaluating how tobacco may affect toxicities related to ICI therapy. Based on our review, we believe that a patient’s history of tobacco smoking does have a role to play in guiding treatment decision making in patients with lung cancer.

Immunogenomic profiling of lung adenocarcinoma reveals poorly differentiated tumors are associated with an immunogenic tumor microenvironment

OBJECTIVES

Pathologists have routinely observed distinct histologic patterns of growth in early-stage lung adenocarcinoma (LUAD), which have been suggested to be associated with prognosis. Herein, we investigated the relationship between LUAD patterns of growth, as defined by the updated international association for the study of lung cancer (IASLC) grading criteria, and differences in the tumor immune microenvironment to identify predictors of response to immunotherapy.

METHODS

174 resected stage I-III LUAD tumors were classified by histologic pattern of growth (i.e. solid, micropapillary, acinar, papillary, and lepidic) and then grouped as well differentiated, moderately differentiated, and poorly differentiated. Comprehensive multiplatform analysis including whole exome sequencing, gene expression profiling, immunohistochemistry, CIBERSORT, and T-cell receptor sequencing was performed and groups were compared for differences in genomic drivers, immune cell infiltrate, clonality, and survival. Finally, multivariate analysis was performed adjusting for pathologic stage and smoking status.

RESULTS

Poorly differentiated tumors demonstrated a strong association with smoking relative to moderately differentiated or well differentiated tumors. However, unlike in prior reports, poorly differentiated tumors were not associated with a worse survival after curative-intent resection. Genomic analysis revealed that poorly differentiated tumors are associated with high tumor mutation burden but showed no association with oncogenic drivers. Immune analyses revealed that poorly differentiated tumors are associated with increased T-cell clonality, expression of PD-L1, and infiltration by cytotoxic CD8 T-cells, activated CD4 T-cells, and pro-inflammatory (M1) macrophages. Finally, multivariate analysis controlling for stage and smoking status confirmed independence of immune differences between IASLC grade groups.

CONCLUSIONS

Poorly differentiated tumors, as defined by the updated IASLC grading criteria, are associated with a distinct immunogenic tumor microenvironment that predicts for therapeutic response to immune agents, including checkpoint inhibitors, and should be included in the clinical trial design of immunotherapy studies in early-stage lung adenocarcinoma.

Mutational Activation of the NRF2 Pathway Upregulates Kynureninase Resulting in Tumor Immunosuppression and Poor Outcome in Lung Adenocarcinoma

Activation of the NRF2 pathway through gain-of-function mutations or loss-of-function of its suppressor KEAP1 is a frequent finding in lung cancer. NRF2 activation has been reported to alter the tumor microenvironment. Here, we demonstrated that NRF2 alters tryptophan metabolism through the kynurenine pathway that is associated with a tumor-promoting, immune suppressed microenvironment. Specifically, proteomic profiles of 47 lung adenocarcinoma (LUAD) cell lines (11 KEAP1 mutant and 36 KEAP1 wild-type) revealed the tryptophan-kynurenine enzyme kynureninase (KYNU) as a top overexpressed protein associated with activated NRF2. The siRNA-mediated knockdown of NFE2L2, the gene encoding for NRF2, or activation of the NRF2 pathway through siRNA-mediated knockdown of KEAP1 or via chemical induction with the NRF2-activator CDDO-Me confirmed that NRF2 is a regulator of KYNU expression in LUAD. Metabolomic analyses confirmed KYNU to be enzymatically functional. Analysis of multiple independent gene expression datasets of LUAD, as well as a LUAD tumor microarray demonstrated that elevated KYNU was associated with immunosuppression, including potent induction of T-regulatory cells, increased levels of PD1 and PD-L1, and resulted in poorer survival. Our findings indicate a novel mechanism of NRF2 tumoral immunosuppression through upregulation of KYNU.

Lymphocyte-activation gene 3 in non-small-cell lung carcinomas: correlations with clinicopathologic features and prognostic significance

Lymphocyte-activation gene 3 (LAG-3) modulates the tumor microenvironment through immunosuppressive effects. Its associations with clinicopathologic parameters and prognostic significance in non-small-cell lung carcinomas remain unclear. We examined LAG-3 expression in 368 resected non-small-cell lung carcinomas (including 218 adenocarcinomas and 150 squamous-cell carcinomas) using tissue microarrays, with normalization to CD8⁺ T-cell count (LAG-3/CD8 index), and correlated LAG-3, CD8, and LAG-3/CD8 index with clinicopathologic features, molecular status, and survival. LAG-3 expression in the immune cells (ranged 0.35-540.1 cells/mm²) was identified in 92% of non-small-cell lung carcinomas. In adenocarcinomas and squamous-cell carcinomas, LAG-3 expression correlated with CD8⁺ T-cell count and PD-L1 expression. In adenocarcinomas, high LAG-3 expression (defined as >median) was additionally associated with smoking history, high T stage, aggressive pathologic features (solid-predominant histologic pattern, lymphovascular invasion, and nodal metastasis), and lack of EGFR mutation. In the entire resected tumor cohort and in adenocarcinomas, high LAG-3 and LAG-3/CD8 index were each associated with worse overall survival. In squamous-cell carcinomas, high CD8 was associated with better overall survival. In an exploratory analysis of pretreatment samples from advanced non-small-cell lung carcinoma patients treated with pembrolizumab, high CD8 was predictive of improved overall and progression-free survival, while high LAG-3, but not high LAG-3/CD8 index, was associated with improved progression-free survival. In conclusion, the clinicopathologic correlations and prognostic impact of LAG-3 in non-small-cell lung carcinoma are histotype-dependent, highlighting differences in the immune microenvironment between adenocarcinomas and squamous-cell carcinomas. The predictive impact of LAG-3 warrants further investigation.

Combined Consideration of Tumor-Associated Immune Cell Density and Immune Checkpoint Expression in the Peritumoral Microenvironment for Prognostic Stratification of Non-Small-Cell Lung Cancer Patients

Given the complexity and highly heterogeneous nature of the microenvironment and its effects on antitumor immunity and cancer immune evasion, the prognostic value of a single immune marker is limited. Here, we show how the integration of immune checkpoint molecule expression and tumor-associated immune cell distribution patterns can influence prognosis prediction in non-small-cell lung cancer (NSCLC) patients. We analyzed tissue microarray (TMA) data derived from multiplex immunohistochemistry results and measured the densities of tumor-infiltrating CD8+ and FOXP3+ immune cells and tumor cells (PanCK+), as well as the densities of programmed cell death 1 (PD-1)+ and programmed cell death ligand 1 (PD-L1)+ cells in the peritumor and intratumor subregions. We found a higher density of infiltrating CD8+ and FOXP3+ immune cells in the peritumoral compartment than in the intratumoral compartment. In addition, unsupervised hierarchical clustering analysis of these markers revealed that the combination of high CD8/FOXP3 expression, low PD-1 and PD-L1 immune checkpoint expression, and lack of epidermal growth factor receptor (EGFR) mutation could be a favorable predictive marker. On the other hand, based on the clustering analysis, low CD8/FOXP3 and immune checkpoint (PD-1 and PD-L1) expression might be a marker for patients who are likely to respond to strategies targeting regulatory T (Treg) cells. Furthermore, an immune risk score model was established based on multivariate Cox regression, and the risk score was determined to be an independent prognostic factor for NSCLC patients. These results indicate that the immune context is heterogeneous because of the complex interactions of different components and that using multiple factors in combination might be promising for predicting the prognosis of and stratifying NSCLC patients.

Distinct immune gene programs associated with host tumor immunity, neoadjuvant chemotherapy and chemoimmunotherapy in resectable NSCLC

PURPOSE

Our understanding of the immunopathology of resectable NSCLC is still limited. Here, we explore immune programs that inform of tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in localized NSCLC.

EXPERIMENTAL DESIGN

Targeted immune gene sequencing using the HTG Precision Immuno-Oncology panel was performed in localized NSCLCs from three cohorts based on treatment: naïve (n=190), neoadjuvant chemotherapy (n=38) and neoadjuvant chemoimmunotherapy (n=21). Tumor immune microenvironment (TIME) phenotypes based on the location of CD8+ T cells (inflamed, cold, excluded), tumoral PD-L1 expression (&lt;1% and {greater than or equal to}1%), and tumor infiltrating lymphocytes (TILs). Immune programs and signatures were statistically analyzed based on tumoral PD-L1 expression, immune phenotypes, pathological response and were cross-compared across the three cohorts.

RESULTS

PD-L1 positive tumors exhibited increased signature scores for various lymphoid and myeloid cell subsets (p&lt;0.05). TIME phenotypes exhibited disparate frequencies by stage, PD-L1 expression, and mutational burden. Inflamed and PD-L1+/TILs+ NSCLCs displayed overall significantly heightened levels of immune signatures, with the excluded group representing an intermediate state. A cytotoxic T cell signature was associated with favorable survival in neoadjuvant chemotherapy-treated NSCLCs (p&lt;0.05). Pathological response to chemoimmunotherapy was positively associated with higher expression of genes involved in immune activation, chemotaxis, as well as T and NK cells (p&lt;0.05 for all). Among the three cohorts, chemoimmunotherapy-treated NSCLCs exhibited highest scores for various immune cell subsets including T effector and B cells (p&lt;0.05).

CONCLUSIONS

Our findings highlight immune gene programs that may underlie host tumor immunity and response to neoadjuvant chemotherapy and chemoimmunotherapy in resectable NSCLC.

Novel imaging biomarkers predict outcomes in stage III unresectable non-small cell lung cancer treated with chemoradiation and durvalumab

Background

The landmark study of durvalumab as consolidation therapy in NSCLC patients (PACIFIC trial) demonstrated significantly longer progression-free survival (PFS) in patients with locally advanced, unresectable non-small cell lung cancer (NSCLC) treated with durvalumab (immunotherapy, IO) therapy after chemoradiotherapy (CRT). In clinical practice in the USA, durvalumab continues to be used in patients across all levels of programmed cell death ligand-1 (PD-L1) expression. While immune therapies have shown promise in several cancers, some patients either do not respond to the therapy or have cancer recurrence after an initial response. It is not clear so far who will benefit of this therapy or what the mechanisms behind treatment failure are.

Methods

A total of 133 patients with unresectable stage III NSCLC who underwent durvalumab after CRT or CRT alone were included. Patients treated with durvalumab IO after CRT were randomly split into training (D1=59) and test (D2=59) sets and the remaining 15 patients treated with CRT alone were grouped in D3. Radiomic textural patterns from within and around the target nodules were extracted. A radiomic risk score (RRS) was built and was used to predict PFS and overall survival (OS). Patients were divided into high-risk and low-risk groups based on median RRS.

Results

RRS was found to be significantly associated with PFS in D1 (HR=2.67, 95% CI 1.85 to 4.13, p<0.05, C-index=0.78) and D2 (HR=2.56, 95% CI 1.63 to 4, p<0.05, C-index=0.73). Similarly, RRS was associated with OS in D1 (HR=1.89, 95% CI 1.3 to 2.75, p<0.05, C-index=0.67) and D2 (HR=2.14, 95% CI 1.28 to 3.6, p<0.05, C-index=0.69), respectively. RRS was found to be significantly associated with PFS in high PD-L1 (HR=3.01, 95% CI 1.41 to 6.45, p=0.0044) and low PD-L1 (HR=2.74, 95% CI 1.8 to 4.14, p=1.77e-06) groups. Moreover, RRS was not significantly associated with OS in the high PD-L1 group (HR=2.08, 95% CI 0.98 to 4.4, p=0.054) but was significantly associated with OS in the low PD-L1 group (HR=1.61, 95% CI 1.14 to 2.28, p=0.0062). In addition, RRS was significantly associated with PFS (HR=2.77, 95% CI 1.17 to 6.52, p=0.019, C-index=0.77) and OS (HR=2.62, 95% CI 1.25 to 5.51, p=0.01, C-index=0.77) in D3, respectively.

Conclusions

Tumor radiomics of pretreatment CT images from patients with stage III unresectable NSCLC were prognostic of PFS and OS to CRT followed by durvalumab IO and CRT alone.

Expression Profiles and Prognostic Value of Multiple Inhibitory Checkpoints in Head and Neck Lymphoepithelioma-Like Carcinoma

Background

Inhibitory checkpoints are promising antitumor targets and predictive biomarkers in a variety of cancers. We aimed to identify the expression levels and prognostic value of multiple inhibitory checkpoints supported by preclinical and clinical evidence in head and neck lymphoepithelioma-like carcinoma (HNLELC).

Methods

The expression of seven inhibitory checkpoints were evaluated in the tumor nest (TN) and tumor stroma (TS) of 102 HNLELC specimens using immunohistochemistry and digital pathology, and an inhibitory checkpoint-based signature (ICS) was subsequently constructed using the LASSO Cox regression model.

Results

PD-L1, B7H3, and IDO-1 were mostly expressed in the TN, with median H-score of TN vs TS: 63.6 vs 14.6; 8.1 vs 1.0; 61.5 vs 34.7 (all P &lt; 0.001), whereas PD-1, TIM-3, LAG-3, and VISTA were mainly observed in the TS, with median H-score of TN vs TS: 0.2 vs 12.4, 3.4 vs 7.1, 6.2 vs 11.9, 16.4 vs 47.2 (all P &lt; 0.001), respectively. The most common simultaneously expressed combinations consisted of PD-L1 + B7H3 + IDO-1 + TIM-3 + LAG-3 + VISTA and B7H3 + IDO-1 + TIM-3 + LAG-3 in the TN (both occurring in 8.8% of patients) and PD-L1 + B7H3 + IDO-1 in the TS (4.9%). In addition, high-ICS patients had shorter 5-year disease-free (40.6% vs 81.7%; P &lt; 0.001), regional recurrence-free (63.5% vs 88.2%; P = 0.003), and overall survival (73.5% vs 92.9%; P = 0.006) than low-ICS patients. Multivariate analysis revealed that ICS represented an independent predictor, which could significantly complement the predictive performance of TNM stage for 3-year (AUC 0.724 vs 0.619, P = 0.014), 5-year (AUC 0.727 vs 0.640, P = 0.056), and 10-year disease-free survival (AUC 0.815 vs 0.709, P = 0.023).

Conclusions

The expression of inhibitory checkpoints and ICS classifier may increase the prognostic value of the TNM staging system and guide the rational design of personalized inhibitory checkpoint blockade therapy in HNLELC.

Predicting programmed death-ligand 1 expression level in non-small cell lung cancer using a combination of peritumoral and intratumoral radiomic features on computed tomography

In this study, we investigated the possibility of predicting expression levels of programmed death-ligand 1 (PD-L1) using radiomic features of intratumoral and peritumoral tumors on computed tomography (CT) images. We retrospectively analyzed 161 patients with non-small cell lung cancer. We extracted radiomics features for intratumoral and peritumoral regions on CT images. The null importance, least absolute shrinkage, and selection operator model were used to select the optimized feature subset to build the prediction models for the PD-L1 expression level. LightGBM with five-fold cross-validation was used to construct the prediction model and evaluate the receiver operating characteristics. The corresponding area under the curve (AUC) was calculated for the training and testing cohorts. The proportion of ambiguously clustered pairs was calculated based on consensus clustering to evaluate the validity of the selected features. In addition, Radscore was calculated for the training and test cohorts. For expression level of PD-L1 above 1%, prediction models that included radiomic features from the intratumoral region and a combination of radiomic features from intratumoral and peritumoral regions yielded an AUC of 0.83 and 0.87 and 0.64 and 0.74 in the training and test cohorts, respectively. In contrast, the models above 50% prediction yielded an AUC of 0.80, 0.97, and 0.74, 0.83, respectively. The selected features were divided into two subgroups based on PD-L1 expression levels ≥ 50% or ≥ 1%. Radscore was statistically higher for subgroup one than subgroup two when radiomic features for intratumoral and peritumoral regions were combined. We constructed a predictive model for PD-L1 expression level using CT images. The model using a combination of intratumoral and peritumoral radiomic features had a higher accuracy than the model with only intratumoral radiomic features.

IFN-Gamma Expression in the Tumor Microenvironment and CD8-Positive Tumor-Infiltrating Lymphocytes as Prognostic Markers in Urothelial Cancer Patients Receiving Pembrolizumab

Simple Summary

Pembrolizumab, an immune checkpoint inhibitor, has shown therapeutic benefit for advanced urothelial carcinoma (aUC) patients, but only a limited population achieves a long-term response. Prediction of treatment outcomes for aUC patients receiving immune checkpoint inhibitors is a clinical challenge. We assessed the associations between the expression of multiple immune markers in the tumor microenvironment using immunohistochemistry of tumor tissues obtained from 26 aUC patients who received second-line pembrolizumab treatment. We found that high infiltration of CD8-positive lymphocytes was significantly associated with a favorable objective response and overall and progression-free survival. Furthermore, expression of interferon-gamma (IFNγ) showed a significant positive correlation with post-progression survival. Finally, we demonstrated that the coincidence of low infiltration of CD8-positive lymphocytes and low IFNγ expression was an independent prognostic factor for an unfavorable response to pembrolizumab.

Abstract

Although immune checkpoint inhibitors have shown benefit for advanced urothelial carcinoma (aUC) patients, prognostication of treatment efficacy and response duration remains a clinical challenge. We evaluated the expression of immune markers in the tumor microenvironment and assessed their associations with response to and survival after pembrolizumab treatment in 26 aUC patients. High levels of CD8⁺ tumor-infiltrating lymphocytes (TILs) were associated with favorable objective responses (23.0% vs. 15.3%, p = 0.0425), progression-free survival (median, 8.8 vs 2.1 months; hazard ratio (HR), 0.24; 95% confidence interval (CI), 0.07–0.66, p = 0.0060), and overall survival (median, >24.0 vs. 5.3 months; HR, 0.17; 95% CI, 0.04–0.56, p = 0.0034) compared with low levels. High interferon-gamma (IFNγ) expression levels were associated with longer post-progression survival (median, 4.9 vs. 1.0 months; HR, 0.18; 95% CI, 0.04–0.59, p = 0.0027) compared with low expression. Multivariate analysis incorporating clinical prognosticators demonstrated that the coincidence of low CD8⁺ T cells/IFNγ was an independent factor for unfavorable overall survival after pembrolizumab treatment (HR, 4.07; 95% CI, 1.36–12.73; p = 0.0125). The combination of low CD8⁺ TILs and IFNγ expression was an independent prognostic factor with predictive ability equivalent to previously reported clinical prognosticators.

The effect of neoadjuvant therapy on PD-L1 expression and CD8+lymphocyte density in non-small cell lung cancer

PD-L1 expression is the routine clinical biomarker for the selection of patients to receive immunotherapy in non-small cell lung cancer (NSCLC). However, the application and best timing of immunotherapy in the resectable setting is still under investigation. We aimed to study the effect of chemotherapy on PD-L1 expression and tumor infiltrating lymphocytes (TILs), which is to date still poorly understood. Our retrospective, single-centre neoadjuvant cohort comprised 96 consecutive patients with NSCLC resected 2000-2016 after neoadjuvant therapy, including paired diagnostic chemo-naïve specimens in 53 cases. A biologically matched surgical cohort of 114 primary resected cases was included. PD-L1 expression, CD8 + TILs density and tertiary lymphoid structures were assessed on whole slides and correlated with clinico-pathological characteristics and survival. Seven/53 and 12/53 cases had lower respectively higher PD-L1 expressions after neoadjuvant therapy. Most cases (n = 34) showed no changes in PD-L1 expression, the majority of these harboring PD-L1 < 1% in both samples (21/34 [61.8%]). Although CD8 + TILs density was significantly higher after chemotherapy (p = 0.031) in resections compared to diagnostic biopsies, this might be due to sampling and statistical bias. No difference in PD-L1 expression or CD8 + TILs density was detected when comparing the neoadjuvant and surgical cohort. In univariable analyses, higher CD8 + TILs density, higher numbers of tertiary lymphoid structures but not PD-L1 expression were significantly associated with longer survival. Increased PD-L1 expression after neoadjuvant chemotherapy was not significantly associated with shorter 5-year survival, but the number of cases was very low. In multivariable analysis, only pT category and age remained independent prognostic factors. In summary, PD-L1 expression was mostly unchanged after neoadjuvant chemotherapy compared to diagnostic biopsies. The sample size of cases with changed PD-L1 expression was too small to draw conclusions on any prognostic value.

Exploration of immune-related cells and ceRNA in squamous cell lung cancer

The treatment for squamous cell lung cancer (SqCLC) is limited, and the prognosis of SqCLC is poor. In this article, we aimed to analyze and identify immune-related cells and competition endogenous RNA (ceRNA) that influence the prognosis of SqCLC. SqCLC and lung adenocarcinoma data were downloaded from TCGA-GDC. A total of 22 types of immune cell fractions were estimated using CIBERSORT. R software was used to identify any significantly different transcriptome data, including mRNA, LncRNA, and miRNA. The univariate cox regression method was applied to screen for prognosis-related lncRNA, miRNA, mRNA and tumor-infiltrating immune cells. There were 504 patients included in this study. There was a higher proportion of memory activated CD4+ T cells and CD8+ T cells in younger women. Follicular helper T (Tfh) cells were predictive of a good prognosis and reflected immune activation in SqCLC. The SFTA1P/NKX2-1-AS1, hsa-mir-503, GREM2 ceRNA axes and NKX2-1-AS1, hsa-mir-96, PROK2 ceRNA axes were found to be important for the immune function, pathogenesis, and prognosis of SqCLC. Collectively, the immune-related ceRNA and tumor-infiltrating immune cells in SqCLC are likely important determinants of SqCLC pathogenesis, prognosis, and immune status.

Efficacy and safety profile of avelumab monotherapy

Avelumab can kill cancer cells through immune checkpoint inhibition and antibody-dependent cell-mediated cytotoxicity (ADCC). Here, we analyzed the clinical efficacy and adverse events (AEs) in 3935 cancer patients from 21 trials. Compared with conventional treatment, avelumab monotherapy was associated with more tumor responses and less AEs. The pooled objective response rate was 14.18 % (95 % CI, 10.68 %-18.08 %). More PD-L1 positive patients responded to avelumab monotherapy compared to PD-L1 negative patients. The overall incidence was 73.78 % for all-grade treatment-related AE (TRAE), 14.44 % for high-grade TRAE, 6.07 % for serious adverse event, 0.44 % for fatal adverse event, 17.86 % for all-grade immune-related AE (irAE), and 3.22 % for high-grade irAE. In summary, avelumab monotherapy presents an active anti-tumor activity, shows no sign of increased toxicity due to the ADCC. These characteristics provide rational for further application of avelumab in cancer treatment.

CD8+ T cells inhibit metastasis and CXCL4 regulates its function

BACKGROUND

The mechanism by which immune cells regulate metastasis is unclear. Understanding the role of immune cells in metastasis will guide the development of treatments improving patient survival.

METHODS

We used syngeneic orthotopic mouse tumour models (wild-type, NOD/scid and Nude), employed knockout (CD8 and CD4) models and administered CXCL4. Tumours and lungs were analysed for cancer cells by bioluminescence, and circulating tumour cells were isolated from blood. Immunohistochemistry on the mouse tumours was performed to confirm cell type, and on a tissue microarray with 180 TNBCs for human relevance. TCGA data from over 10,000 patients were analysed as well.

RESULTS

We reveal that intratumoral immune infiltration differs between metastatic and non-metastatic tumours. The non-metastatic tumours harbour high levels of CD8⁺ T cells and low levels of platelets, which is reverse in metastatic tumours. During tumour progression, platelets and CXCL4 induce differentiation of monocytes into myeloid-derived suppressor cells (MDSCs), which inhibit CD8⁺ T-cell function. TCGA pan-cancer data confirmed that CD8^lowPlatelet^high patients have a significantly lower survival probability compared to CD8^highPlatelet^low.

CONCLUSIONS

CD8⁺ T cells inhibit metastasis. When the balance between CD8⁺ T cells and platelets is disrupted, platelets produce CXCL4, which induces MDSCs thereby inhibiting the CD8⁺ T-cell function.

CD73 expression defines immune, molecular, and clinicopathological subgroups of lung adenocarcinoma

INTRODUCTION

CD73 is a membrane-bound enzyme crucial in adenosine generation. The adenosinergic pathway plays a critical role in immunosuppression and in anti-tumor effects of immune checkpoint inhibitors (ICI). Here, we interrogated CD73 expression in a richly annotated cohort of human lung adenocarcinoma (LUAD) and its association with clinicopathological, immune, and molecular features to better understand the role of this immune marker in LUAD pathobiology.

MATERIALS AND METHODS

Protein expression of CD73 was evaluated by immunohistochemistry in 106 archived LUADs from patients that underwent surgical treatment without neoadjuvant therapy. Total CD73 (T +) was calculated as the average of luminal (L +) and basolateral (BL +) percentage membrane expression scores for each LUAD and was used to classify tumors into three groups based on the extent of T CD73 expression (high, low, and negative).

RESULTS

CD73 expression was significantly and progressively increased across normal-appearing lung tissue, adenomatous atypical hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, and LUAD. In LUAD, BL CD73 expression was associated with an increase in PD-L1 expression in tumor cells and increase of tumor-associated immune cells. Stratification of LUADs based on T CD73 extent also revealed that tumors with high expression of this enzyme overall exhibited significantly elevated immune infiltration and PD-L1 protein expression. Immune profiling demonstrated that T-cell inflammation and adenosine signatures were significantly higher in CD73-expressing lung adenocarcinomas relative to those lacking CD73.

CONCLUSION

Our study suggests that higher CD73 expression is associated with an overall augmented host immune response, suggesting potential implications in the immune pathobiology of early stage lung adenocarcinoma. Our findings warrant further studies to explore the role of CD73 in immunotherapeutic response of LUAD.

Integrated Analysis of Genomic and Immunological Features in Lung Adenocarcinoma With Micropapillary Component

Background

Micropapillary adenocarcinoma is one of the most aggressive histologic subtypes of lung adenocarcinoma (LADC), and even a minor proportion of micropapillary component (MPC) within the LADC could contribute to poor prognosis. Comprehensive analysis of genetic and immunological features of LADC with different percentages of MPC would help better understand cancer biology of this LADC subtype and direct future treatments.

Methods

We performed next-generation sequencing (NGS) for a discovery cohort of 43 LADC patients whose tumors were micro-dissected to separate MPC and non-MPC lesions and a reference cohort of 113 LADC patients. MPC-enriched genetic alterations that were detected in the discovery cohort were then confirmed using a validation cohort of 183 LADC patients. Immunological staining was also conducted on the MPC-containing samples in the discovery cohort.

Results

Tumors with a higher percentage of MPC tended to harbor more tumor mutation burdens (TMBs) and chromosome instability (CIN). Some rare genetic events may serve as the genetic landscape to drive micropapillary tumor progression. Specifically, alterations in transcription termination factor 1 (TTF1), brain-specific angiogenesis inhibitor 3 (BAI3), mammalian target of rapamycin (MTOR), and cyclin-dependent kinase inhibitor 2A (CDKN2A) were cross-validated to be enriched in MPC-contained LADC. Additionally, tumors with a higher percentage of MPC were associated with a higher percentage of CD4+, CD8+, and PD-L1+ staining, and some genetic changes that were enriched in MPC, including MET amplification and MTOR mutation, were correlated with increased PD-L1 expression.

Conclusion

We identified multiple novel MPC-enriched genetic changes that could help us understand the nature of this aggressive cancer subtype. High MPC tumors tended to have elevated levels of TMBs, T cell infiltration, and immunosuppression than low MPC tumors, implying the potential link between MPC content and sensitivity to immunotherapy.

Methods to Determine and Analyze the Cellular Spatial Distribution Extracted From Multiplex Immunofluorescence Data to Understand the Tumor Microenvironment

Image analysis using multiplex immunofluorescence (mIF) to detect different proteins in a single tissue section has revolutionized immunohistochemical methods in recent years. With mIF, individual cell phenotypes, as well as different cell subpopulations and even rare cell populations, can be identified with extraordinary fidelity according to the expression of antibodies in an mIF panel. This technology therefore has an important role in translational oncology studies and probably will be incorporated in the clinic. The expression of different biomarkers of interest can be examined at the tissue or individual cell level using mIF, providing information about cell phenotypes, distribution of cells, and cell biological processes in tumor samples. At present, the main challenge in spatial analysis is choosing the most appropriate method for extracting meaningful information about cell distribution from mIF images for analysis. Thus, knowing how the spatial interaction between cells in the tumor encodes clinical information is important. Exploratory analysis of the location of the cell phenotypes using point patterns of distribution is used to calculate metrics summarizing the distances at which cells are processed and the interpretation of those distances. Various methods can be used to analyze cellular distribution in an mIF image, and several mathematical functions can be applied to identify the most elemental relationships between the spatial analysis of cells in the image and established patterns of cellular distribution in tumor samples. The aim of this review is to describe the characteristics of mIF image analysis at different levels, including spatial distribution of cell populations and cellular distribution patterns, that can increase understanding of the tumor microenvironment.

Immunomodulatory effects of renin-angiotensin system inhibitors on T lymphocytes in mice with colorectal liver metastases

Background

It is now recognized that many anticancer treatments positively modulate the antitumor immune response. Clinical and experimental studies have shown that inhibitors of the classical renin–angiotensin system (RAS) reduce tumor progression and are associated with better outcomes in patients with colorectal cancer. RAS components are expressed by most immune cells and adult hematopoietic cells, thus are potential targets for modulating tumor-infiltrating immune cells and can provide a mechanism of tumor control by the renin–angiotensin system inhibitors (RASi).

Aim

To investigate the effects of the RASi captopril on tumor T lymphocyte distribution in a mouse model of colorectal liver metastases.

Methods

Liver metastases were established in a mouse model using an autologous colorectal cancer cell line. RASi (captopril 750 mg/kg) or carrier (saline) was administered to the mice daily via intraperitoneal injection, from day 1 post-tumor induction to endpoint (day 15 or 21 post-tumor induction). At the endpoint, tumor growth was determined, and lymphocyte infiltration and composition in the tumor and liver tissues were analyzed by flow cytometry and immunohistochemistry (IHC).

Results

Captopril significantly decreased tumor viability and impaired metastatic growth. Analysis of infiltrating T cells into liver parenchyma and tumor tissues by IHC and flow cytometry showed that captopril significantly increased the infiltration of CD3⁺ T cells into both tissues at day 15 following tumor induction. Phenotypical analysis of CD45⁺ CD3⁺ T cells indicated that the major contributing phenotype to this influx is a CD4 and CD8 double-negative T cell (DNT) subtype, while CD4⁺ T cells decreased and CD8⁺ T cells remained unchanged. Captopril treatment also increased the expression of checkpoint receptor PD-1 on CD8⁺and DNT subsets.

Conclusion

Captopril treatment modulates the immune response by increasing the infiltration and altering the phenotypical composition of T lymphocytes and may be a contributing mechanism for tumor control.

Female Gender Predicts Augmented Immune Infiltration in Lung Adenocarcinoma

INTRODUCTION

Immune infiltration in lung adenocarcinomas (LUADs) has been associated with response to immune checkpoint inhibitors. Clinical features underlying differential responses of patients with LUADs to immunotherapy are not well understood. Here, we analyzed the association between LUAD immune infiltration and clinicopathologic variables.

MATERIALS AND METHODS

Intratumoral CD3, CD8, and CD68 cell densities (tumor-associated immune cells [TAICs]) were immunohistochemically assessed in 146 surgically resected LUADs. LUADs were classified into 2 groups, low and high TAICs, based on the median values of cell densities for CD3, CD8, and CD68. Somatic mutation burden and driver gene mutation status were analyzed in a subset of the cases (n = 92). We statistically analyzed the association between the TAIC groups and various clinicopathologic and molecular variables by using the χ²/Fisher and Wilcoxon sum tests and multivariable logistic regression models.

RESULTS

Patient gender, tumor size, and STK11 mutations were significantly associated with TAIC levels in LUAD. Female patients exhibited significantly elevated TAIC levels (P = .005) compared with male patients. Tumor size was inversely associated with TAIC levels (P = .012). STK11 mutated tumors were associated with lower TAICs (P = .008). Higher TAICs were consistently observed in female patients with LUADs after adjusting for stage, tumor size, and age. Multivariable regression models confirmed female gender as an independent variable associated with TAIC levels in LUAD (P = .0141).

CONCLUSION

Immune infiltration in LUADs was significantly higher in female patients, warranting further exploration into the association between this clinical variable and immunotherapeutic response in LUAD.

Multiplex Immunofluorescence Tyramide Signal Amplification for Immune Cell Profiling of Paraffin-Embedded Tumor Tissues

Every day, more evidence is revealed regarding the importance of the relationship between the response to cancer immunotherapy and the cancer immune microenvironment. It is well established that a profound characterization of the immune microenvironment is needed to identify prognostic and predictive immune biomarkers. To this end, we find phenotyping cells by multiplex immunofluorescence (mIF) a powerful and useful tool to identify cell types in biopsy specimens. Here, we describe the use of mIF tyramide signal amplification for labeling up to eight markers on a single slide of formalin-fixed, paraffin-embedded tumor tissue to phenotype immune cells in tumor tissues. Different panels show different markers, and the different panels can be used to characterize immune cells and relevant checkpoint proteins. The panel design depends on the research hypothesis, the cell population of interest, or the treatment under investigation. To phenotype the cells, image analysis software is used to identify individual marker expression or specific co-expression markers, which can differentiate already selected phenotypes. The individual-markers approach identifies a broad number of cell phenotypes, including rare cells, which may be helpful in a tumor microenvironment study. To accurately interpret results, it is important to recognize which receptors are expressed on different cell types and their typical location (i.e., nuclear, membrane, and/or cytoplasm). Furthermore, the amplification system of mIF may allow us to see weak marker signals, such as programmed cell death ligand 1, more easily than they are seen with single-marker immunohistochemistry (IHC) labeling. Finally, mIF technologies are promising resources for discovery of novel cancer immunotherapies and related biomarkers. In contrast with conventional IHC, which permits only the labeling of one single marker per tissue sample, mIF can detect multiple markers from a single tissue sample, and at the same time, deliver extensive information about the cell phenotypes composition and their spatial localization. In this matter, the phenotyping process is critical and must be done accurately by a highly trained personal with knowledge of immune cell protein expression and tumor pathology.

Tumor microenvironment disparity in multiple primary lung cancers: Impact of non-intrinsic factors, histological subtypes, and genetic aberrations

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Tumor microenvironment (TME) was compared among multiple primary lung cancers (MPLCs).

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Sex and smoking status concomitantly impacted PD-L1 expression in paired tumors.

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EGFR mutations were independently associated with PD-L1 expression.

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KRAS mutations altered the TMEs according to the types of co-mutations.

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The number of FOXP3-positive t cells reflected histological subtypes.

Introduction

Multiple primary lung cancers (MPLCs) occur in common carcinogenetic risks such as lifestyle, biological aging, immune responses, hormones, and metabolism. Although MPLCs harbor various genetic profiles within the same individuals, differences in the tumor microenvironment (TME) are unclear. We investigated the impact of genetic aberrations, non-intrinsic factors, and pathological subtypes on tumor immunity.

Materials and Methods

In total, 73 surgically resected specimens from 32 patients with MPLC were analyzed. PD-L1 expression in tumor cells (TCs) and immune cells (ICs), CD3-positive tumor-infiltrating lymphocytes (TILs), CD8/CD3 ratios, and FOXP3-positive TILs that compose TMEs were evaluated by immunohistochemistry and classified on a score of 0–2. 38 tumors were sequenced for somatic mutations in 409 cancer-associated genes.

Results

Females and never or light smokers had a higher incidence of PD-L1-negative tumors and a higher concordance rate. PD-L1 positivity in TCs and ICs was significantly less frequent in EGFR-mutated than in wild-type tumors. Differences in the score of TMEs were observed between the KRAS-mutated-only tumor and the KRAS and TP53-co-mutated tumors, and between the KRAS-mutated-only tumor and the KRAS and STK11-co-mutated tumors. Significantly more FOXP3-high TILs were observed in invasive pathological subtypes than in non-invasive ones.

Conclusion

Comparing TMEs among MPLCs revealed that non-smokers or light smokers and females were unlikely to express PD-L1 regardless of tumor site and confirmed that the EGFR mutations and co-occurring KRAS and STK11 or TP53 mutations were associated with TME. Pathological subtypes may impact the efficacy of immune therapy due to their potential correlations with regulatory T cells.

Immuno-profiling and cellular spatial analysis using five immune oncology multiplex immunofluorescence panels for paraffin tumor tissue

Multiplex immunofluorescence (mIF) has arisen as an important tool for immuno-profiling tumor tissues. We updated our manual protocol into an automated protocol that allows the use of up to seven markers in five mIF panels to apply to formalin-fixed paraffin-embedded tumor tissues. Using a tyramide signal amplification system, we optimized five mIF panels that included cytokeratin to characterize malignant cells (MCs), immune checkpoint markers (i.e., PD-L1, B7-H3, B7-H4, IDO-1, VISTA, LAG3, ICOS, TIM3, and OX40), tumor-infiltrating lymphocytic markers (i.e., CD3, CD8, CD45RO, granzyme B, PD-1, and FOXP3), and markers to characterize myeloid-derived suppressor cells (i.e., CD68, CD66b, CD14, CD33, Arg-1, and CD11b). To determine analytical reproducibility and the impact of those panels for immuno-profiling tumor tissues, we performed an exploratory analysis in a set of non–small cell lung cancer (NSCLC) samples. The slides were scanned, and the different cell phenotypes were quantified by simultaneous co-localizations with the markers using image analysis software. Comparison between the time points of staining showed high analytical reproducibility. The analysis of NSCLC cases showed an immunosuppressive microenvironment with PD-L1/PD-1 expression as a predominant axis. Interestingly, high density of MCs expressing B7-H4 was correlated with recurrence. Unexpectedly, MCs expressing OX40 were also detected, and those cells were a closer distance to CD3+T-cells than were MCs expressing other immune checkpoints. Two different cellular patterns of spatial distribution were determined according the CD3 distribution, and the predominant pattern was related with active immunosuppressive interaction with MCs. Our study shows that these five mIF panels can identify multiple targets in a single cell with high reproducibility. The study of different cell populations and their spatial relationship can open new ideas for therapeutic approaches.

Next-Generation Digital Histopathology of the Tumor Microenvironment

Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology-which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning.

Tumor Margin Contains Prognostic Information: Radiomic Margin Characteristics Analysis in Lung Adenocarcinoma Patients

Simple Summary

The tumor microenvironment is a dynamic area, with continuous interaction between tumor cells and their surrounding environment. We aimed to investigate the relationship between tumor radiomic margin characteristics and prognosis in patients with lung cancer. When compared to the model with clinical variables only (C-index = 0.738), the model incorporating clinical variables and radiomic margin characteristics (C-index = 0.753) demonstrated a higher C-index for predicting overall survival. In the model integrating both clinical variables and radiomic margin characteristics, convexity, Laplace of Gaussian (LoG) kurtosis 3, and roundness factor were independent predictive factors of overall survival. Our study showed that radiomic margin characteristics helped predict overall survival in patients with lung adenocarcinomas, thus implying that the tumor margin contains prognostic information.

Abstract

We aimed to investigate the relationship between tumor radiomic margin characteristics and prognosis in patients with lung cancer. We enrolled 334 patients who underwent complete resection for lung adenocarcinoma. A quantitative computed tomography analysis was performed, and 76 radiomic margin characteristics were extracted. The radiomic margin characteristics were correlated with overall survival. The selected clinical variables and radiomic margin characteristics were used to calculate a prognostic model with subsequent internal and external validation. Nearly all of the radiomic margin characteristics showed excellent reproducibility. The least absolute shrinkage and selection operator (LASSO) method was used to select eight radiomic margin characteristics. When compared to the model with clinical variables only (C-index = 0.738), the model incorporating clinical variables and radiomic margin characteristics (C-index = 0.753) demonstrated a higher C-index for predicting overall survival. In the model integrating both clinical variables and radiomic margin characteristics, convexity, a Laplace of Gaussian (LoG) kurtosis of 3, and the roundness factor were each independently predictive of overall survival. In addition, radiomic margin characteristics were also correlated with the micropapillary subtype, and the sphericity value was able to predict the presence of the micropapillary subtype. In conclusion, our study showed that radiomic margin characteristics helped predict overall survival in patients with lung adenocarcinomas, thus implying that the tumor margin contains prognostic information.

Profiles of immune cell infiltration in head and neck squamous carcinoma

Tumor immune infiltration cells (TIICs) are highly heterogeneous, not only in different cancer subtypes but also within different cancer regions. We conducted the Cell-type Identification using Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method. We assessed the relative proportions of 22 TIICs in HNSC using publicly available TCGA transcriptional datasets, analyzed the proportions of TIICs between HNSC tissues and normal tissues, along with accompanying clinicopathological data, and the impact of TIICs on clinical outcome. After the filter criteria, a total of 395 patients were included in the analysis. We found significant differences in naïve B cells, monocytes, resting mast cells, activated mast cells, CD8⁺ T cells, and M0 macrophages between HNSC tissues and adjacent non-cancer tissues. We also found that some TIIC subgroups were significantly associated with clinical parameters. Moreover, the patients with low Tregs fraction had worse OS and DFS than those with high Tregs fraction. However, low M0 macrophages fraction was associated with better OS and DFS in HNSC patients. Moreover, Tregs and M0 macrophages are likely to be important determinants of prognosis, which may serve as a potential immunotherapy target for HNSC. Then, we screened the immune-related differentially expressed genes (DEGs), performed the GO and KEGG enrichment analysis, constructed the protein–protein interaction network, and screened the prognosis-related hub genes in HNSC. However, further clinical investigation and basic experiments are needed to validate our results, and uncover the molecular mechanisms interlinking TIICs in HNSC and their roles in prognosis and therapy.

CD8+CD57+ T cells exhibit distinct features in human non-small cell lung cancer

Background

The repetitive antigen stimulation during chronic infection often leads to the accumulation of CD8⁺CD57⁺ T cells. These cells express high levels of interferon-γ, granzyme B and perforin with elevated cytolytic effect, and are considered as the most potent cells for combating chronical viral infection. The status of CD8⁺CD57⁺ T cells in non-small cell lung cancer (NSCLC) has not been well defined.

Methods

We used flow cytometry and undertook a systemic approach to examine the frequency, immunophenotyping and functional properties of CD8⁺CD57⁺ T cells in the peripheral blood, tumor tissue and the corresponding normal tissue, as well as lung draining lymph nodes, of patients with NSCLC.

Results

CD57⁺ T cells expressed high levels of programmed cell death-1 (PD-1) in all tested compartments and were predominantly CD8⁺ T cells. These cells in the peripheral blood displayed a terminally differentiated phenotype as defined by loss of CD27 and CD28 while expressing KLRG1. CD8⁺CD57⁺ T cells exhibited enhanced cytotoxic potencies and impaired proliferative capability. Unlike CD57⁺ T cells in the peripheral blood, a significant proportion of CD57⁺ T cells in the primary tumors expressed CD27 and CD28. CD8⁺CD57⁺ T cells in tumors lacked cytotoxic activity. The proliferative activity of these cells was also impaired. CD8⁺CD57⁺ T cells in the corresponding normal lung tissues shared similarities with their counterparts in peripheral blood rather than their counterparts in tumors. The vast majority of CD8⁺CD57⁺ T cells in lung draining lymph nodes were positive for CD27 and CD28. These cells were unable to produce perforin and granzyme B, but their proliferative activity was preserved. CD8⁺CD57⁺ T cells in tumors displayed an inferior response to PD-1 blockade compared with their CD8⁺CD57^- counterparts. Interleukin (IL)-15 preferentially restored the effector function of these cells. Additionally, IL-15 was able to restore the impaired proliferative activity of CD8⁺CD57⁺ T cells in tumors and peripheral blood.

Conclusions

Our data indicate that the failure of the immune system to fight cancer progression could be a result of impaired CD8⁺ T-cell functional maturation into fully differentiated effector T cells within the tumor microenvironment. Boosting IL-15 activity might promote tumor-reactive CD8⁺ T-cell functional maturation while preserving their proliferative activity.

Small cell lung cancer: a slightly less orphan disease after immunotherapy

Small cell lung cancer (SCLC) is an aggressive malignancy accounting for 15% of all diagnosed cases of lung cancer. After >15 years without any clinically relevant therapeutic advances, extensive-disease SCLC has become the second thoracic malignancy for which immune checkpoint inhibitors (ICIs) have shifted the treatment paradigm to improve overall survival. Today, atezolizumab or durvalumab in combination with platinum-etoposide chemotherapy is considered the new standard of care in the first-line setting in SCLC. However, the magnitude of benefit with this immune-chemotherapy strategy in SCLC is more modest than that observed in metastatic non-small-cell lung cancer patients. The immunosuppressive phenotype of SCLC plays an important role in hampering ICI efficacy and may explain the differences in outcomes between these two types of lung cancer. In this review, we provide a summary of recent therapeutic advances in SCLC in light of ICIs, as well as current challenges of this strategy in patients who are elderly, have poor performance status or brain metastases. We also address future perspectives of immunotherapeutic strategies currently in clinical development for these patients.

Cell-autonomous immune gene expression is repressed in pulmonary neuroendocrine cells and small cell lung cancer

Small cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed “variant” due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings may help guide the design of treatment regimens in SCLC.

Ling Cai et al. used transcriptomic profiling data of healthy lung, patient-derived small cell lung cancer cell lines, xenografts, and primary tumors to examine a link between neuroendocrine (NE) signatures and immune gene expression. Their findings suggest that cell-autonomous immune gene repression is a shared feature between healthy and tumor cells of NE lineage and may influence tumor-immune cell interaction and response to immunotherapy.

Biomarkers for Immunotherapy of Oral Squamous Cell Carcinoma: Current Status and Challenges

Oral squamous cell carcinoma (OSCC) forms a major health problem in many countries. For several decades the management of OSCC consisted of surgery with or without radiotherapy or chemoradiotherapy. Aiming to increase survival rate, recent research has underlined the significance of harnessing the immune response in treatment of many cancers. The promising finding of checkpoint inhibitors as a weapon for targeting metastatic melanoma was a key event in the development of immunotherapy. Furthermore, clinical trials have recently proven inhibitor of PD-1 for treatment of recurrent/metastatic head and neck cancer. However, some challenges (including patient selection) are presented in the era of immunotherapy. In this mini-review we discuss the emergence of immunotherapy for OSCC and the recently introduced biomarkers of this therapeutic strategy. Immune biomarkers and their prognostic perspectives for selecting patients who may benefit from immunotherapy are addressed. In addition, possible use of such biomarkers to assess the response to this new treatment modality of OSCC will also be discussed.

Identification of distinct immune landscapes using an automated nine-color multiplex immunofluorescence staining panel and image analysis in paraffin tumor tissues

Immune profiling is becoming a vital tool for identifying predictive and prognostic markers for translational studies. The study of the tumor microenvironment (TME) in paraffin tumor tissues such as malignant pleural mesothelioma (MPM) could yield insights to actionable targets to improve patient outcome. Here, we optimized and tested a new immune-profiling method to characterize immune cell phenotypes in paraffin tissues and explore the co-localization and spatial distribution between the immune cells within the TME and the stromal or tumor compartments. Tonsil tissues and tissue microarray (TMA) were used to optimize an automated nine-color multiplex immunofluorescence (mIF) panel to study the TME using eight antibodies: PD-L1, PD-1, CD3, CD8, Foxp3, CD68, KI67, and pancytokeratin. To explore the potential role of the cells into the TME with this mIF panel we applied this panel in twelve MPM cases to assess the multiple cell phenotypes obtained from the image analysis and well as their spatial distribution in this cohort. We successful optimized and applied an automated nine-color mIF panel to explore a small set of MPM cases. Image analysis showed a high degree of cell phenotype diversity with immunosuppression patterns in the TME of the MPM cases. Mapping the geographic cell phenotype distribution in the TME, we were able to identify two distinct, complex immune landscapes characterized by specific patterns of cellular distribution as well as cell phenotype interactions with malignant cells. Successful we showed the optimization and reproducibility of our mIF panel and their incorporation for comprehensive TME immune profiling into translational studies that could refine our ability to correlate immunologic phenotypes with specific patterns of cells distribution and distance analysis. Overall, this will improve our ability to understand the behavior of cells within the TME and predict new treatment strategies to improve patient outcome.

Tumor infiltrated immune cell types support distinct immune checkpoint inhibitor outcomes in patients with advanced non-small cell lung cancer

The evaluation of PD‐L1 expression alone has limitations in predicting clinical outcome in immune‐checkpoint inhibitors (ICI). This study aimed to evaluate the predictive and prognostic effects of the presence of various immune cells in pretreatment tissue samples and to identify determinants associated with response in patients with advanced non‐small cell lung cancer (NSCLC) treated with PD‐1 blockade. Immune cell distribution was heterogeneous and the most dominant immune cell type was T cells. Patients with durable clinical benefit (DCB) showed significantly higher PD‐L1 expression. The ratio of tumor/stroma region of T cell, B cell, and macrophage was significantly higher in patient with DCB. High intratumoral T‐ and B‐cell density (≥median) was associated with DCB in the low PD‐L1 expression (<50%) group. In univariate analyses, the overall survival (OS) benefit was shown according to intratumoral B‐cell density (p = 0.0337). The incidence of hyperprogressive disease (HPD) was 13.0%. The Chi‐square test revealed that HPD was significantly associated with intratumoral B‐cell density but not T‐cell or macrophage density. Our results demonstrate different predictive and prognostic values for infiltrating immune cells in tumor tissue, which may help in selecting patients for ICI.

Digital Immunophenotyping Predicts Disease Free and Overall Survival in Early Stage Melanoma Patients

Background: the prognostic significance of tumor infiltrating lymphocytes (TILs) in intermediate/thick primary cutaneous melanoma (PCM) remains controversial, partially because conventional evaluation is not reliable, due to inter-observer variability and diverse scoring methods. We aimed to assess the prognostic impact of the density and spatial distribution of immune cells in early stage intermediate/thick PCM. Materials and Methods: digital image acquisition and quantitative analysis of tissue immune biomarkers (CD3, CD4, CD8, CD68, PD-L1, CD163, FOX-P3, and PD-1) was carried out in a training cohort, which included patients with primary PCM ≥ 2 mm diagnosed, treated, and followed-up prospectively in three Italian centers. Results were validated in an independent Italian cohort. Results: in the training cohort, 100 Stage II–III melanoma patients were valuable. At multivariable analysis, a longer disease free survival (DFS) was statistically associated with higher levels of CD4⁺ intratumoral T-cells (aHR [100 cell/mm² increase] 0.98, 95%CI 0.95–1.00, p = 0.041) and CD163⁺ inner peritumoral (aHR [high vs. low] 0.56, 95%CI 0.32–0.99, p = 0.047). A statistically significant longer DFS (aHR [high-high vs. low-low] 0.52, 95%CI 0.28–0.99, p = 0.047) and overall survival (OS) (aHR [high-high vs. low-low] 0.39, 95%CI 0.18–0.85, p = 0.018) was found in patients with a high density of both intratumoral CD8⁺ T-cells and CD68⁺ macrophages as compared to those with low density of both intratumoral CD8⁺ T-cells and CD68⁺ macrophages. Consistently, in the validation cohort, patients with high density of both intratumoral CD8⁺ and CD3⁺ T-cells were associated to a statistically better DFS (aHR[high-high vs. low-low] 0.24, 95%CI 0.10–0.56, p < 0.001) and those with high density of both intratumoral CD8⁺ and CD68⁺ were associated to a statistically longer OS (aHR[high-high vs. low-low] 0.28, 95%CI 0.09–0.86, p = 0.025). Conclusion: our findings suggest that a specific preexisting profile of T cells and macrophages distribution in melanomas may predict the risk of recurrence and death with potential implications for the stratification of stage II–III melanoma patients.