Evaluation of tumor-infiltrating lymphocytes using routine H&E slides predicts patient survival in resected non–small cell lung cancer

Spatial distance between tumor and lymphocyte can predict the survival of patients with resectable lung adenocarcinoma

Background and objective

Spatial interaction between tumor-infiltrating lymphocytes (TILs) and tumor cells is valuable in predicting the effectiveness of immune response and prognosis amongst patients with lung adenocarcinoma (LUAD). Recent evidence suggests that the spatial distance between tumor cells and lymphocytes also influences the immune responses, but the distance analysis based on Hematoxylin and Eosin (H&E) -stained whole-slide images (WSIs) remains insufficient. To address this issue, we aim to explore the relationship between distance and prognosis prediction of patients with LUAD in this study.

Methods

We recruited patients with resectable LUAD from three independent cohorts in this multi-center study. We proposed a simple but effective deep learning-driven workflow to automatically segment different cell types in the tumor region using the HoVer-Net model, and quantified the spatial distance (DIST) between tumor cells and lymphocytes based on H&E-stained WSIs. The association of DIST with disease-free survival (DFS) was explored in the discovery set (D1, n = 276) and the two validation sets (V1, n = 139; V2, n = 115).

Results

In multivariable analysis, the low DIST group was associated with significantly better DFS in the discovery set (D1, HR, 0.61; 95 % CI, 0.40-0.94; p = 0.027) and the two validation sets (V1, HR, 0.54; 95 % CI, 0.32-0.91; p = 0.022; V2, HR, 0.44; 95 % CI, 0.24-0.81; p = 0.009). By integrating the DIST with clinicopathological factors, the integrated model (full model) had better discrimination for DFS in the discovery set (C-index, D1, 0.745 vs. 0.723) and the two validation sets (V1, 0.621 vs. 0.596; V2, 0.671 vs. 0.650). Furthermore, the computerized DIST was associated with immune phenotypes such as immune-desert and inflamed phenotypes.

Conclusions

The integration of DIST with clinicopathological factors could improve the stratification performance of patients with resectable LUAD, was beneficial for the prognosis prediction of LUAD patients, and was also expected to assist physicians in individualized treatment.

Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets

The field of immunology is fundamental to our understanding of the intricate dynamics of the tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment emerges as essential aspect in breast cancer cases. To gain comprehensive insights, the quantification of TILs through computer-assisted pathology (CAP) tools has become a prominent approach, employing advanced artificial intelligence models based on deep learning techniques. The successful recognition of TILs requires the models to be trained, a process that demands access to annotated datasets. Unfortunately, this task is hampered not only by the scarcity of such datasets, but also by the time-consuming nature of the annotation phase required to create them. Our review endeavors to examine publicly accessible datasets pertaining to the TIL domain and thereby become a valuable resource for the TIL community. The overall aim of the present review is thus to make it easier to train and validate current and upcoming CAP tools for TIL assessment by inspecting and evaluating existing publicly available online datasets.

Gastric cancer immune microenvironment score predicts neoadjuvant chemotherapy efficacy and prognosis

The efficacy of neoadjuvant chemotherapy (NACT) in patients with advanced gastric cancer (GC) varies greatly. Thus, we aimed to verify the predictive value of tumor-infiltrating immune cells (TIICs) on the treatment response to NACT and the prognosis of patients with advanced GC, and to explore the impact of NACT on the tumor immune microenvironment (TIME). Paired tumor tissues (pre- and post-NACT) from patients with advanced GC were collected for this study. TIICs were assessed using immunohistochemistry staining and analyzed using logistic regression to establish an immune microenvironment score for GC (ISGC score) and predict NACT efficacy. Kaplan-Meier curves were used to evaluate the survival outcome of patients. The results showed that TIME was dramatically heterogeneous between NACT response and nonresponse patients. In the validation cohort, the ISGC score demonstrated good predictive performance for treatment response to NACT. Moreover, high ISGC indicated better long-term survival in patients with advanced GC. Furthermore, tumor-infiltrated T cells (CD3+ and CD8+) and CD11c+ macrophages were significantly increased in the response group, while CD163+ macrophages and FOXP3+ Treg cells were decreased after NACT. However, opposite results were exhibited in the nonresponse group. Finally, we found that the percentage of programmed cell death ligand 1 (PD-L1)-positive tumors was 31% (32/104) pre-NACT and 49% (51/104) post-NACT, and almost all patients with elevated PD-L1 were in the NACT response group. The ISGC model accurately predicted NACT efficacy and classified patients with GC into different survival groups. NACT regulates the TIME in GC, which may provide strategies for personalized immunotherapy.

Prognostic Impact of Tumor-Associated Macrophage-Related Markers in Patients with Adenocarcinoma of the Lung

BACKGROUND

Macrophage polarization is an important pathogenetic factor in neoplastic diseases. Phosphorylated signal transducer and activator of transcription 1 (phospho-STAT1) regulates the M1 phenotype, and c-Maf regulates the M2 phenotype. However, the role of macrophage phenotype in lung adenocarcinoma (LAD) remains unclear.

PATIENTS AND METHODS

We examined whether the density of M1 and M2 macrophages was associated with prognosis in patients with LAD using double-labeling immunohistochemistry. In addition, programmed death ligand 1 (PD-L1) expression was investigated. Immune cells coexpressing CD68 and phospho-STAT1 were considered M1 macrophages, whereas those coexpressing CD68 and c-Maf were recognized as M2 macrophages. Patients with LAD (N = 307) were divided into two cohorts (n = 100 and n = 207) to evaluate the associations of M1 and M2 phenotypes with prognosis in patients with LAD. We determined the cut-off values of CD68/phospho-STAT1-positive cells and CD68/c-Maf-positive cells to assess correlations with overall survival (OS) using receiver operating characteristic curve analysis in the first cohort.

RESULTS

According to the cut-off values of 5 or less CD68/phospho-STAT1-positive cells and more than 11 CD68/c-Maf-positive cells, high expression of CD68/c-Maf and low expression of CD68/Phospho-STAT1 were identified as independent prognostic markers for OS and disease-free survival (DFS). Moreover, the M1/M2 ratio (0.19 or less) was a poor prognostic factor for OS and DFS. However, PD-L1 expression did not correlate with patient outcomes.

CONCLUSIONS

Overall, these findings suggest that double immunostaining of markers of phospho-STAT1 (M1) and c-Maf (M2) can be used as prognostic indicators for patients with LAD.

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases

BACKGROUND

Recent advances in digital pathology have enabled accurate and standardised enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a percentage electronic TIL score (eTILs) and investigate its prognostic and predictive relevance in cutaneous melanoma.

METHODS

We included stage I to IV cutaneous melanoma patients and used hematoxylin-eosin-stained slides for TIL analysis. We assessed eTILs as a continuous and categorical variable using the published cut-off of 16.6% and applied Cox regression models to evaluate associations of eTILs with relapse-free, distant metastasis-free, and overall survival. We compared eTILs of the primaries with matched metastasis. Moreover, we assessed the predictive relevance of eTILs in therapy-naïve metastases according to the first-line therapy.

FINDINGS

We analysed 321 primary cutaneous melanomas and 191 metastatic samples. In simple Cox regression, tumour thickness (p < 0.0001), presence of ulceration (p = 0.0001) and eTILs ≤16.6% (p = 0.0012) were found to be significant unfavourable prognostic factors for RFS. In multiple Cox regression, eTILs ≤16.6% (p = 0.0161) remained significant and downgraded the current staging. Lower eTILs in the primary tissue was associated with unfavourable relapse-free (p = 0.0014) and distant metastasis-free survival (p = 0.0056). In multiple Cox regression adjusted for tumour thickness and ulceration, eTILs as continuous remained significant (p = 0.019). When comparing TILs in primary tissue and corresponding metastasis of the same patient, eTILs in metastases was lower than in primary melanomas (p < 0.0001). In therapy-naïve metastases, an eTILs >12.2% was associated with longer progression-free survival (p = 0.037) and melanoma-specific survival (p = 0.0038) in patients treated with anti-PD-1-based immunotherapy. In multiple Cox regression, lactate dehydrogenase (p < 0.0001) and eTILs ≤12.2% (p = 0.0130) were significantly associated with unfavourable melanoma-specific survival.

INTERPRETATION

Assessment of TILs is prognostic in primary melanoma samples, and the eTILs complements staging. In therapy-naïve metastases, eTILs ≤12.2% is predictive of unfavourable survival outcomes in patients receiving anti-PD-1-based therapy.

FUNDING

See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Prognostic impact of LILRB4 expression on tumor-infiltrating cells in resected non-small cell lung cancer

BACKGROUND

Leukocyte immunoglobulin-like receptor subfamily B member 4 (LILRB4/ILT3) is an up-and-coming molecule that promotes immune evasion. We have previously reported that LILRB4 facilitates myeloid-derived suppressor cells (MDSCs)-mediated tumor metastasis in mice. This study aimed to investigate the impact of the LILRB4 expression levels on tumor-infiltrating cells on the prognosis of non-small cell lung cancer (NSCLC) patients.

METHODS

We immunohistochemically evaluated the LILRB4 expression levels of completely resected 239 NSCLC specimens. Whether the blocking of LILRB4 on human PBMC-derived CD33⁺ MDSCs inhibited the migration ability of lung cancer cells was also examined using transwell migration assay.

RESULTS

The LILRB4 ^high group, in which patients with a high LILRB4 expression level on tumor-infiltrating cells, showed a shorter overall survival (OS) (p = 0.013) and relapse-free survival (RFS) (p = 0.0017) compared to the LILRB4 ^low group. Multivariate analyses revealed that a high LILRB4 expression was an independent factor for postoperative recurrence, poor OS and RFS. Even in the cohort background aligned by propensity score matching, OS (p = 0.023) and RFS (p = 0.0046) in the LILRB4 ^high group were shorter than in the LILRB4 ^low group. Some of the LILRB4 positive cells were positive for MDSC markers, CD33 and CD14. Transwell migration assay demonstrated that blocking LILRB4 significantly inhibited the migration of human lung cancer cells cocultured with CD33⁺ MDSCs.

CONCLUSION

Together, signals through LILRB4 on tumor-infiltrating cells, including MDSCs, play an essential role in promoting tumor evasion and cancer progression, impacting the recurrence and poor prognosis of patients with resected NSCLC.

Functional binding of PD1 ligands predicts response to anti-PD1 treatment in patients with cancer

Accurate predictive biomarkers of response to immune checkpoint inhibitors (ICIs) are required for better stratifying patients with cancer to ICI treatments. Here, we present a new concept for a bioassay to predict the response to anti-PD1 therapies, which is based on measuring the binding functionality of PDL1 and PDL2 to their receptor, PD1. In detail, we developed a cell-based reporting system, called the immuno-checkpoint artificial reporter with overexpression of PD1 (IcAR-PD1) and evaluated the functionality of PDL1 and PDL2 binding in tumor cell lines, patient-derived xenografts, and fixed-tissue tumor samples obtained from patients with cancer. In a retrospective clinical study, we found that the functionality of PDL1 and PDL2 predicts response to anti-PD1 and that the functionality of PDL1 binding is a more effective predictor than PDL1 protein expression alone. Our findings suggest that assessing the functionality of ligand binding is superior to staining of protein expression for predicting response to ICIs.

Impact of microvessel patterns and immune status in NSCLC: a non-angiogenic vasculature is an independent negative prognostic factor in lung adenocarcinoma

Introduction

Non-small cell lung carcinomas (NSCLC) exhibit different microvessel patterns (MVPs). Basal (BA), diffuse (DA) and papillary (PA) patterns show signs of angiogenesis (new blood vessels), while an alveolar pattern indicates that tumors are co-opting existing normal vessels (non-angiogenic alveolar, NAA). NAA tumor growth is known to exist in NSCLC, but little is known about its prognostic impact in different histological subgroups, and about associations between MVPs and immune cell infiltration.

Methods

Detailed patterns of angiogenic and non-angiogenic tumor growth were evaluated by CD34 immunohistochemistry in whole tissue slides from 553 surgically treated patients with NSCLC stage I-IIIB disease. Associations with clinicopathological variables and markers related to tumor immunology-, angiogenesis- and hypoxia/metabolism were explored, and disease-specific survival (DSS) was analyzed according to histological subtypes.

Results

The predominant MVP was angiogenic in 82% of tumors: BA 40%, DA 34%, PA 8%, while a NAA pattern dominated in 18%. A contribution of the NAA pattern >5% (NAA+), i.e., either dominant or minority, was observed in 40.1% of tumors and was associated with poor disease-specific survival (DSS) (p=0.015). When stratified by histology, a significantly decreased DSS for NAA+ was found for adenocarcinomas (LUAD) only (p< 0.003). In multivariate analyses, LUAD NAA+ pattern was a significant independent prognostic factor; HR 2.37 (CI 95%, 1.50-3.73, p< 0.001). The immune cell density (CD3, CD4, CD8, CD45RO, CD204, PD1) added prognostic value in squamous cell carcinoma (LUSC) and LUAD with 0-5% NAA (NAA-), but not in LUAD NAA+. In correlation analyses, there were several significant associations between markers related to tumor metabolism (MCT1, MCT4, GLUT1) and different MVPs.

Conclusion

The NAA+ pattern is an independent poor prognostic factor in LUAD. In NAA+ tumors, several immunological markers add prognostic impact in LUSC but not in LUAD.

Clinical significance of overall assessment of tumor-infiltrating lymphocytes in oropharyngeal cancer: A meta-analysis

BACKGROUND

The overall assessment of tumor-infiltrating lymphocytes (TILs) evaluated using hematoxylin and eosin (HE) staining has been recently studied in oropharyngeal squamous cell carcinoma (OPSCC).

METHODS

We conducted a systematic review of Scopus, Ovid Medline, PubMed, Web of Science, and Cochrane Library to retrieve studies assessing TILs in HE-stained sections of OPSCC. We used fixed-effect models and random-effect models to estimate the pooled hazard ratios (HRs) and confidence intervals (CIs) for disease-free survival (DFS), overall survival (OS) and disease-specific survival (DSS).

RESULTS

Eleven studies were identified that had analyzed the prognostic significance of TILs in OPSCC using HE-stained specimens. Our meta-analyses showed that a high infiltration of TILs was significantly associated with improved DFS (HR 0.39, 95%CI 0.24-0.65, P = 0.0003), OS (HR 0.38, 95%CI 0.29-0.50, P < 0.0001), and DSS (HR 0.32, 95%CI 0.19-0.53, P < 0.0001).

CONCLUSION

Findings of our meta-analysis support a growing body of evidence indicating that assessment of TILs in OPSCC using HE-stained sections has reliable prognostic value. The clinical significance of such assessment of TILs has been reported repeatedly in many studies on OPSCC. The assessment is cost-effective, feasible, easy to transfer from lab to clinic, and therefore can be incorporated in daily practice.

Virotherapy combined with anti-PD-1 transiently reshapes the tumor immune environment and induces anti-tumor immunity in a preclinical PDAC model

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is largely refractory to cancer immunotherapy with PD-1 immune checkpoint blockade (ICB). Oncolytic virotherapy has been shown to synergize with ICB. In this work, we investigated the combination of anti-PD-1 and oncolytic measles vaccine in an immunocompetent transplantable PDAC mouse model.

Methods

We characterized tumor-infiltrating T cells by immunohistochemistry, flow cytometry and T cell receptor sequencing. Further, we performed gene expression profiling of tumor samples at baseline, after treatment, and when tumors progressed. Moreover, we analyzed systemic anti-tumor and anti-viral immunity.

Results

Combination treatment significantly prolonged survival compared to monotherapies. Tumor-infiltrating immune cells were increased after virotherapy. Gene expression profiling revealed a unique, but transient signature of immune activation after combination treatment. However, systemic anti-tumor immunity was induced by virotherapy and remained detectable even when tumors progressed. Anti-PD-1 treatment did not impact anti-viral immunity.

Discussion

Our results indicate that combined virotherapy and ICB induces anti-tumor immunity and reshapes the tumor immune environment. However, further refinement of this approach may be required to develop its full potential and achieve durable efficacy.

Prognostic impact of tumor microenvironment-related markers in patients with adenocarcinoma of the lung

Cancer-associated fibroblasts (CAFs) are a prominent component in the tumor microenvironment (TME), which plays an important role in lung carcinogenesis. Here, we investigated microenvironmental markers expressed by CAFs, including α-smooth muscle actin, CD10, podoplanin, fibroblast-specific protein 1, platelet-derived growth factor α and β, fibroblast-associated protein, tenascin-C, zinc finger E-box binding homeobox 1 (ZEB1), and twist-related protein 1 expression levels. We evaluated samples from 257 patients with lung adenocarcinoma (LAD) to assess the associations of CAF-related protein expression patterns with prognosis. LAD cases were stratified using cluster analysis. To determine the utility of prognostic markers in LAD, univariate and multivariate analyses were performed. LAD cases were classified into subgroups 1 and 2. Subgroup 2 was shown to be significantly correlated with disease-free and overall survival using univariate and multivariate analyses in this group. Upregulation of podoplanin was identified as a single prognostic marker in this study by univariate and multivariate analyses. In addition, ZEB1 overexpression was correlated with disease-free survival. Our current results suggested that the specific CAF phenotype (e.g., the expression pattern of CAF-related proteins) could predict outcomes in patients with LAD. In addition, podoplanin upregulation may predict outcomes in these patients.

Association of Machine Learning-Based Assessment of Tumor-Infiltrating Lymphocytes on Standard Histologic Images With Outcomes of Immunotherapy in Patients With NSCLC

Importance

Currently, predictive biomarkers for response to immune checkpoint inhibitor (ICI) therapy in lung cancer are limited. Identifying such biomarkers would be useful to refine patient selection and guide precision therapy.

Objective

To develop a machine-learning (ML)-based tumor-infiltrating lymphocytes (TILs) scoring approach, and to evaluate TIL association with clinical outcomes in patients with advanced non-small cell lung cancer (NSCLC).

Design, Setting, and Participants

This multicenter retrospective discovery-validation cohort study included 685 ICI-treated patients with NSCLC with median follow-up of 38.1 and 43.3 months for the discovery (n = 446) and validation (n = 239) cohorts, respectively. Patients were treated between February 2014 and September 2021. We developed an ML automated method to count tumor, stroma, and TIL cells in whole-slide hematoxylin-eosin-stained images of NSCLC tumors. Tumor mutational burden (TMB) and programmed death ligand-1 (PD-L1) expression were assessed separately, and clinical response to ICI therapy was determined by medical record review. Data analysis was performed from June 2021 to April 2022.

Exposures

All patients received anti-PD-(L)1 monotherapy.

Main Outcomes and Measures

Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were determined by blinded medical record review. The area under curve (AUC) of TIL levels, TMB, and PD-L1 in predicting ICI response were calculated using ORR.

Results

Overall, there were 248 (56%) women in the discovery cohort and 97 (41%) in the validation cohort. In a multivariable analysis, high TIL level (≥250 cells/mm2) was independently associated with ICI response in both the discovery (PFS: HR, 0.71; P = .006; OS: HR, 0.74; P = .03) and validation (PFS: HR = 0.80; P = .01; OS: HR = 0.75; P = .001) cohorts. Survival benefit was seen in both first- and subsequent-line ICI treatments in patients with NSCLC. In the discovery cohort, the combined models of TILs/PD-L1 or TMB/PD-L1 had additional specificity in differentiating ICI responders compared with PD-L1 alone. In the PD-L1 negative (<1%) subgroup, TIL levels had superior classification accuracy for ICI response (AUC = 0.77) compared with TMB (AUC = 0.65).

Conclusions and Relevance

In these cohorts, TIL levels were robustly and independently associated with response to ICI treatment. Patient TIL assessment is relatively easily incorporated into the workflow of pathology laboratories at minimal additional cost, and may enhance precision therapy.

Computerized tumor-infiltrating lymphocytes density score predicts survival of patients with resectable lung adenocarcinoma

A high abundance of tumor-infiltrating lymphocytes (TILs) has a positive impact on the prognosis of patients with lung adenocarcinoma (LUAD). We aimed to develop and validate an artificial intelligence-driven pathological scoring system for assessing TILs on H&E-stained whole-slide images of LUAD. Deep learning-based methods were applied to calculate the densities of lymphocytes in cancer epithelium (DLCE) and cancer stroma (DLCS), and a risk score (WELL score) was built through linear weighting of DLCE and DLCS. Association between WELL score and patient outcome was explored in 793 patients with stage I-III LUAD in four cohorts. WELL score was an independent prognostic factor for overall survival and disease-free survival in the discovery cohort and validation cohorts. The prognostic prediction model-integrated WELL score demonstrated better discrimination performance than the clinicopathologic model in the four cohorts. This artificial intelligence-based workflow and scoring system could promote risk stratification for patients with resectable LUAD.

Immune profile analysis of peripheral blood and tumors of lung cancer patients treated with immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become central to lung cancer drug therapy, and establishing biomarkers that can predict effects and adverse events (AEs) is awaited. We prospectively analyzed the association between the immune-related molecular expression in peripheral blood mononuclear cells (PBMCs) and lung cancer tissues, and the effects of ICI monotherapy.

METHODS

Twenty-one patients with advanced non-small cell lung cancer (NSCLC) who received ICI monotherapy were included. Changes in the expression of immune-related molecules in PBMCs before and after the administration of ICI were analyzed by flow cytometry. The major histocompatibility complex (MHC) class I and programmed cell death-ligand 1 (PD-L1) expression of cancer cells, and the PD-L1, CD8 and CD103 expression of tumor infiltrating immune cells in lung cancer tissue before the administration of ICI were confirmed by immunohistochemistry (IHC).

RESULTS

Twenty-one patients were investigated, including 11 adenocarcinoma and 10 squamous cell carcinoma cases. Anti-programmed cell death protein-1 (PD-1) antibody (n=18) and anti-PD-L1 antibody (n=3) were administered. The clinical responses were graded as follows: complete response (CR) (n=1), partial response (PR) (n=7), stable disease (SD) (n=10) and progressive disease (PD) (n=3). Among immune-related molecules expressed in PBMCs, the CD103+ CD39+ CD8+ T cell change after administration closely correlated with the clinical response. In the univariate analyses of the factors associated with progression-free survival (PFS), CD103+ CD39+ CD8+ cell change after administration was identified as a significant prognostic factor, while the CD103+ CD39+ CD8+ cell change after administration and Brinkman index were independent prognostic factors in a multivariate analysis of the factors associated with PFS.

CONCLUSIONS

The CD103+ CD39+ CD8+ cell change after administration may predict the efficacy of ICIs.

Prognostic Value of Selected Histologic Features for Lung Squamous Cell Carcinoma

The recent histologic subtyping of lung adenocarcinoma has demonstrated the prognostic values of histologic patterns in this malignancy. However, the histological features of lung squamous cell carcinoma (SCC) are much less established. This short review discusses several promising histological prognostic markers for SCC, including tumor budding, tumor cell nesting, and the spreading of tumors through air spaces. Wherever appropriate, the biological significance of these morphological features was also discussed. The investigators consider that histological prognostic markers are highly valuable in understanding the cancer biology of SCC, and in guiding clinical treatment. However, larger clinical cohorts are needed to better establish the prognostic values of the aforementioned histological markers. The application of modern technologies, including machine-learning, would make the histological analysis accurate and reproducible.

Clinical significance of tumor-infiltrating lymphocytes investigated using routine H&E slides in small cell lung cancer

BACKGROUND

Tumor-infiltrating lymphocytes (TILs), investigated using routine hematoxylin and eosin (H&E)-stained section slides (H&E-sTILs), provide a robust prognostic biomarker in various types of solid cancer. The purpose of the present study was to investigate the prognostic significance of H&E-sTILs in patients with small cell lung cancer (SCLC).

METHODS

The clinical data of patients with SCLC who had been treated in our cancer center between January 2013 and October 2019 were collected and retrospectively reviewed. The H&E-sTILs were re-assessed by two experienced pathologists independently. H&E-sTILs that affected the overall survival (OS), progression free survival (PFS) and brain-metastasis free survival (BMFS) rates were explored using the Kaplan-Meier method, and the log-rank test was used to assess the differences. Multivariate analysis was subsequently performed using the Cox proportion hazards model.

RESULTS

A total of 159 patients with SCLC who fulfilled the inclusion criteria were enrolled in the current study. The OS rates at 1, 2 and 3 years were 59.8, 28.6 and 19.8%, respectively, for the whole group. The 3-year OS, PFS and BMFS rates for the H&E-sTILs(+) and H&E-sTILs(-) groups were 25.1% cf. 5.1% (P = 0.030), 14.0% cf. 4.0% (P = 0.013), and 66.0% cf. 11.4% (P = 0.023), respectively. Multivariate analyses subsequently revealed that H&E-sTILs, clinical M stage, the cycles of chemotherapy and short-term response to thoracic radiotherapy were independent factors affecting OS, whereas H&E-sTILs, clinical N stage, clinical M stage and short-term response to chemotherapy were factors affecting PFS. The H&E-sTILs affected OS, PFS and BMFS simultaneously.

CONCLUSIONS

The results of this retrospective study have shown that H&E-sTILs may be considered as a prognostic biomarker affecting the short-term response to treatment, and they are the one and only risk factor for BMFS. However, due to the limitations of the nature of the retrospective design and shortcomings in visually assessing the TILs based on the H&E-stained slides, further prospective studies are required to confirm these conclusions.

A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images

Simple Summary

Tumor tissues sampled from patients contain prognostic and predictive information beyond what is currently being used in clinical practice. Large-scale digitization enables new ways of exploiting this information. The most promising analysis pipelines include deep learning/artificial intelligence (AI). However, to ensure success, AI often requires a time-consuming curation of data. In our approach, we repurposed AI pipelines and training data for cell segmentation and classification to identify tissue-infiltrating lymphocytes (TILs) in lung cancer tissue. We showed that our approach is able to identify TILs and provide prognostic information in an unseen dataset from lung cancer patients. Our methods can be adapted in myriad ways and may help pave the way for the large-scale deployment of digital pathology.

Abstract

Increased levels of tumor-infiltrating lymphocytes (TILs) indicate favorable outcomes in many types of cancer. The manual quantification of immune cells is inaccurate and time-consuming for pathologists. Our aim is to leverage a computational solution to automatically quantify TILs in standard diagnostic hematoxylin and eosin-stained sections (H&E slides) from lung cancer patients. Our approach is to transfer an open-source machine learning method for the segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of the data. Our results show that the resulting TIL quantification correlates to the patient prognosis and compares favorably to the current state-of-the-art method for immune cell detection in non-small cell lung cancer (current standard CD8 cells in DAB-stained TMAs HR 0.34, 95% CI 0.17–0.68 vs. TILs in HE WSIs: HoVer-Net PanNuke Aug Model HR 0.30, 95% CI 0.15–0.60 and HoVer-Net MoNuSAC Aug model HR 0.27, 95% CI 0.14–0.53). Our approach bridges the gap between machine learning research, translational clinical research and clinical implementation. However, further validation is warranted before implementation in a clinical setting.

Development and validation of a computed tomography-based immune ecosystem diversity index as an imaging biomarker in non-small cell lung cancer

OBJECTIVES

To date, there are no data on the noninvasive surrogate of intratumoural immune status that could be prognostic of survival outcomes in non-small cell lung cancer (NSCLC). We aimed to develop and validate the immune ecosystem diversity index (iEDI), an imaging biomarker, to indicate the intratumoural immune status in NSCLC. We further investigated the clinical relevance of the biomarker for survival prediction.

METHODS

In this retrospective study, two independent NSCLC cohorts (Resec1, n = 149; Resec2, n = 97) were included to develop and validate the iEDI to classify the intratumoural immune status. Paraffin-embedded resected specimens in Resec1 and Resec2 were stained by immunohistochemistry, and the density percentiles of CD3⁺, CD4⁺, and CD8⁺ T cells to all cells were quantified to estimate intratumoural immune status. Then, EDI features were extracted using preoperative computed tomography to develop an imaging biomarker, called iEDI, to determine the immune status. The prognostic value of iEDI was investigated on NSCLC patients receiving surgical resection (Resec1; Resec2; internal cohort Resec3, n = 419; external cohort Resec4, n = 96; and TCIA cohort Resec5, n = 55).

RESULTS

iEDI successfully classified immune status in Resec1 (AUC 0.771, 95% confidence interval [CI] 0.759-0.783; and 0.770 through internal validation) and Resec2 (0.669, 0.647-0.691). Patients with higher iEDI-score had longer overall survival (OS) in Resec3 (unadjusted hazard ratio 0.335, 95%CI 0.206-0.546, p < 0.001), Resec4 (0.199, 0.040-1.000, p < 0.001), and TCIA (0.303, 0.098-0.944, p = 0.001).

CONCLUSIONS

iEDI is a non-invasive surrogate of intratumoural immune status and prognostic of OS for NSCLC patients receiving surgical resection.

KEY POINTS

• Decoding tumour immune microenvironment enables advanced biomarkers identification. • Immune ecosystem diversity index characterises intratumoural immune status noninvasively. • Immune ecosystem diversity index is prognostic for NSCLC patients.

Building Efficient CNN Architectures for Histopathology Images Analysis: A Case-Study in Tumor-Infiltrating Lymphocytes Classification

Background

Deep learning methods have demonstrated remarkable performance in pathology image analysis, but they are computationally very demanding. The aim of our study is to reduce their computational cost to enable their use with large tissue image datasets.

Methods

We propose a method called Network Auto-Reduction (NAR) that simplifies a Convolutional Neural Network (CNN) by reducing the network to minimize the computational cost of doing a prediction. NAR performs a compound scaling in which the width, depth, and resolution dimensions of the network are reduced together to maintain a balance among them in the resulting simplified network. We compare our method with a state-of-the-art solution called ResRep. The evaluation is carried out with popular CNN architectures and a real-world application that identifies distributions of tumor-infiltrating lymphocytes in tissue images.

Results

The experimental results show that both ResRep and NAR are able to generate simplified, more efficient versions of ResNet50 V2. The simplified versions by ResRep and NAR require 1.32× and 3.26× fewer floating-point operations (FLOPs), respectively, than the original network without a loss in classification power as measured by the Area under the Curve (AUC) metric. When applied to a deeper and more computationally expensive network, Inception V4, NAR is able to generate a version that requires 4× lower than the original version with the same AUC performance.

Conclusions

NAR is able to achieve substantial reductions in the execution cost of two popular CNN architectures, while resulting in small or no loss in model accuracy. Such cost savings can significantly improve the use of deep learning methods in digital pathology. They can enable studies with larger tissue image datasets and facilitate the use of less expensive and more accessible graphics processing units (GPUs), thus reducing the computing costs of a study.

Relationship between Kita-Kyushu Lung Cancer antigen-1 expression and prognosis of cases with lung squamous cell carcinoma

Background

Previously, we identified the highly immunogenic cancer testicular antigen named Kita-Kyushu Lung Cancer antigen-1 (KK-LC-1). In this study, we analyzed the effect of KK-LC-1 expression on the prognosis of patients with resected squamous cell lung cancer.

Methods

Fifty squamous cell lung cancer patients, who received complete resection, were enrolled in this study. The expressions of KK-LC-1, CD8, human leukocyte antigen (HLA) class I, and programmed cell death protein ligand-1 (PD-L1) were assessed via immunohistochemistry staining using the specimens obtained from the participants. The association between the expression of the abovementioned molecules and patient prognosis was investigated.

Results

KK-LC-1 expression was observed in 21 of 50 recruited cases (42%). However, no significant correlation was found between KK-LC-1 expression and patient prognosis. The prognosis was significantly better in lung cancer cases with KK-LC-1 expression in which CD8⁺ T cells infiltrated the tumor. Regardless of the HLA class I expression or the PD-L1 expression, the KK-LC-1 expression in squamous cell lung cancer could not be detected as a significant prognostic factor. Furthermore, considering the polarity of the cancer tissue as epithelium, staining of KK-LC-1 tended to be strong in the area corresponding to the basal side of the tumor tissue. The Ki-67 expression was frequently observed in cancer cells on the basal side, which was consistent with the KK-LC-1 expression in representative four cases with KK-LC-1-positive squamous cell lung cancer.

Conclusions

Our results indicated that lung squamous cell cancer patients with KK-LC-1 expression and the tumor infiltrating CD8⁺ T cells might exhibit better prognosis. KK-LC-1 might be highly expressed in cancer cells with high proliferative capacity. Larger cohort analysis is still required for further elucidation and validation of the results of this study.

Tumour-infiltrating lymphocytes in oropharyngeal cancer: a validation study according to the criteria of the International Immuno-Oncology Biomarker Working Group

Background

The evaluation of immune response can aid in prediction of cancer behaviour. Here, we assessed the prognostic significance of tumour-infiltrating lymphocytes (TILs) in oropharyngeal squamous cell carcinoma (OPSCC).

Methods

A total of 182 patients treated for OPSCC were included in this study. Assessment of TILs was conducted on tumour sections stained with standard haematoxylin and eosin (HE) staining. We used the scoring criteria proposed by the International Immuno-Oncology Biomarker Working Group.

Results

The multivariable analysis showed that TILs associated with disease-specific survival with a hazard ratio (HR) of 2.13 (95% CI 1.14–3.96; P = 0.017). Similarly, TILs associated significantly with overall survival with HR of 1.87 (95% CI 1.11–3.13; P = 0.018). In a sub-analysis of HPV-positive and HPV-negative cases separately, TILs showed a significant prognostic value in both groups (P < 0.05).

Conclusion

The evaluation of TILs as proposed by the International Immuno-Oncology Biomarker Working Group is a simple and promising method in prediction of survival of OPSCC. It is easily applicable and after further validation can be implemented in the routine pathological report as a basic immune parameter.

Lymphocytes and sinus histiocytosis in tumor and matched lymph nodes as predictors of survival in non-small-cell lung cancer

Aim: To analyze immune cell populations in non-small-cell lung cancer (NSCLC) tumors and matched tumor-bearing and non-tumor-bearing lymph nodes (ntbLNs) to predict prognosis. Patients & methods: 71 patients with long-term disease-free survival and 80 patients with relapse within 3 years were included in this study. We used Cox regression to identify factors associated with overall survival (OS) and progression-free survival (PFS). Results: Sinus histiocytosis and tumor-infiltrating lymphocyte density in the tumor were positively associated with PFS and OS. CD4 expression in N1 (hazard ratio = 0.72; p = 0.02) and N2 (hazard ratio = 0.91; p = 0.04) ntbLNs were positively correlated with OS and PFS, respectively. Discussion: Immunological markers in ntbLNs could be used to predict survival in NSCLC.

Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

Conventional histological stains, such as hematoxylin plus eosin (H&E), and immunohistochemistry (IHC) are mainstays of histology that provide complementary diagnostic information. H&E and IHC currently require separate slides, because the stains would otherwise obscure one another. This consumes small specimen, limiting the total amount of testing. Additionally, performing H&E and IHC on different slides does not permit comparison of staining at the single cell level, since the same cells are not present on each slide, and alignment of tissue features can be problematic due to changes in tissue landscape with sectioning. We have solved these problems by performing conventional staining and IHC on the same slide using invisible IHC chromogens, such that the chromogens are not visible when viewing the conventional stain and the conventional stain is excluded from images of the IHC. Covalently deposited chromogens provided a convenient route to invisible chromogen design and are stable to reagents used in conventional staining. A dual-camera brightfield microscope system was developed that permits simultaneous viewing of both visible conventional stains and invisible IHC chromogens. Simultaneous staining was demonstrated on several formalin-fixed paraffin-embedded tissue specimens using single and duplex IHC, with chromogens that absorb ultraviolet and near infrared light, followed by H&E staining. The concept was extended to other conventional stains, including mucicarmine special stain and Papanicoulou stain, and further extended to cytology specimens. In addition to interactive video review, images were recorded using multispectral imaging and image processing to provide flexible production of color composite images and enable quantitative analysis.

An analysis of the immunological tumor microenvironment of primary tumors and regional lymph nodes in squamous cell lung cancer

Background

Various immune cells that play a central role in antitumor immunity accumulate in primary tumors and regional lymph nodes. Such cellular accumulation and the molecular expression were analyzed to elucidate the immunological tumor microenvironment.

Methods

Fifty squamous cell lung cancer patients with complete resection were included. Resected specimens from primary lung tumors and regional lymph nodes were immunostained for immune-related molecules, such as CD8, CD103, major histocompatibility complex (MHC) class I, and programmed cell death protein ligand-1 (PD-L1), and the relationship between the prognosis and clinicopathological factors was retrospectively analyzed.

Results

Tumor-infiltrating lymphocytes and CD8+ lymphocytes, intratumoral and intrastromal CD103+ lymphocytes, tumor diameter, pathological T and N factors, and pathological stage were significant prognostic factors for the disease-specific survival (DSS) in a univariate analysis. In a multivariate analysis, intratumoral and intrastromal CD103+ lymphocytes and pathological T and N factors were independent prognostic factors of the DSS. Significant concordance was found between the PD-L1 expression of primary tumors and metastatic lymph nodes as well as among tumor-infiltrating lymphocytes, CD8+ lymphocytes and CD103+ lymphocytes. Infiltration of CD103+ lymphocytes into the tumor was significantly correlated with an increased PD-L1 expression of cancer cells in both primary tumors and reginal lymph node metastases. Both the intratumoral infiltration of CD103+ lymphocytes and PD-L1 expression of cancer cells were significantly higher in lymph node metastases than in primary tumors.

Conclusions

CD103+ lymphocyte infiltration in the primary tumor was shown to be strongly involved in the prognosis.

PD-L1 Dependent Immunogenic Landscape in Hot Lung Adenocarcinomas Identified by Transcriptome Analysis

Simple Summary

Lung cancer, with non-small-cell lung cancer as its most common form, is the leading cause of cancer-related mortality and shows a poor prognosis. Despite recent advantages in the field of immunotherapy, there is still a great need for an improved understanding of PD-1/PD-L1 checkpoint blockade-responsive biology. Since immune cell infiltration is regarded as an important parameter in this field, we aimed to identify the immunogenic landscape in primary lung adenocarcinoma on the transcriptomic level in context with tumoral PD-L1 expression (positive vs. negative) and extent of immune infiltration (“hot” vs. “cold” phenotype). Our results reveal that genes that are related to the tumor microenvironment are differentially expressed based on tumoral PD-L1 expression indicating novel aspects of PD-L1 regulation, with potential biological relevance, as well as relevance for immunotherapy response stratification.

Abstract

Background: Lung cancer is the most frequent cause of cancer-related deaths worldwide. The clinical development of immune checkpoint blockade has dramatically changed the treatment paradigm for patients with lung cancer. Yet, an improved understanding of PD-1/PD-L1 checkpoint blockade-responsive biology is warranted. Methods: We aimed to identify the landscape of immune cell infiltration in primary lung adenocarcinoma (LUAD) in the context of tumoral PD-L1 expression and the extent of immune infiltration (“hot” vs. “cold” phenotype). The study comprises LUAD cases (n = 138) with “hot” (≥150 lymphocytes/HPF) and “cold” (<150 lymphocytes/HPF) tumor immune phenotype and positive (>50%) and negative (<1%) tumor PD-L1 expression, respectively. Tumor samples were immunohistochemically analyzed for expression of PD-L1, CD4, and CD8, and further investigated by transcriptome analysis. Results: Gene set enrichment analysis defined complement, IL-JAK-STAT signaling, KRAS signaling, inflammatory response, TNF-alpha signaling, interferon-gamma response, interferon-alpha response, and allograft rejection as significantly upregulated pathways in the PD-L1-positive hot subgroup. Additionally, we demonstrated that STAT1 is upregulated in the PD-L1-positive hot subgroup and KIT in the PD-L1-negative hot subgroup. Conclusion: The presented study illustrates novel aspects of PD-L1 regulation, with potential biological relevance, as well as relevance for immunotherapy response stratification.

Digital Pathology Scoring of Immunohistochemical Staining Reliably Identifies Prognostic Markers and Anatomical Associations in a Large Cohort of Oral Cancers

Utilizing digital pathology algorithms for the objective quantification of immunohistochemical staining, this study aimed to identify robust prognostic biomarkers for oral cancer. Tissue microarrays with specimens of a large cohort of oral squamous cell carcinoma (n=222) were immunohistochemically stained to determine the expression of PD-L1, EGFR, and COX-2 and the amount of infiltrating NK cells and CD8-positive T cells. Immunoreactivity scores were assessed using both a classical manual scoring procedure and a digital semi-automatic approach using QuPath. Digital scoring was successful in quantifying the expression levels of different prognostic biomarkers (CD8: p<0.001; NK cells: p=0.002, PD-L1: p=0.026) and high levels of concordance with manual scoring results were observed. A combined score integrating EGFR expression, neck node status and immune cell signatures with a significant impact on overall and progression-free survival was identified (p<0.001). These data may contribute to the ongoing research on the identification of reliable and clinically relevant biomarkers for the individualization of primary and adjuvant treatment in oral cancer.

Prognostic Value of Tumor-Infiltrating Lymphocytes and Tertiary Lymphoid Structures in Epstein-Barr Virus-Associated and -Negative Gastric Carcinoma

Background

Tumor-infiltrating lymphocytes (TILs) are considered a manifestation of the host immune response against cancer and tertiary lymphoid structures (TLS) may contribute to lymphocytes recruitment. Both of them have been reported as potential prognostic parameters in some human malignancies. However, the roles of TILs, TLS, and their correlation in Epstein-Barr Virus-associated gastric carcinoma (EBVaGC) and EBV-negative gastric carcinoma (EBVnGC) are largely unknown.

Methods

To observe the correlation among TILs, TLS, and clinicopathological characteristics and their prognostic significance in EBVaGC and EBVnGC, respectively. TILs and TLS were assessed by morphology and/or immunohistochemistry, and accompanied by clinicopathological analysis from 846 gastric cancer patients in multiple institutions.

Results

Forty-two (5.0%) cases of EBVaGC and 804 cases of EBVnGC were identified by in situ hybridization, respectively. For EBVnGC, higher TILs grade was correlated with TLS-present. EBVnGC patients with high TILs grade and TLS-present exhibited survival benefits. TILs (P = 0.001) and TLS (P = 0.003), especially TILs & TLS (P < 0.001) were independent prognostic factors in EBVnGC. A nomogram was constructed and validated for predicting the probability of overall survival and performed well with a good calibration. No significant prognostic value was detected in EBVaGC.

Conclusion

TILs and TLS, especially TILs & TLS were promising prognostic indicators for overall survival in EBVnGC. TILs and TLS were highly overlapping in their extent and prognostic abilities, and may be considered as a coindicator of prognosis of gastric cancer. The evaluations of TILs and TLS are simple and can be assessed routinely in pathological diagnosis.

Tumour infiltrating lymphocytes in oropharyngeal carcinoma: prognostic value and evaluation of a standardised method

Tumour infiltrating lymphocytes (TILs) have been described as a biomarker for the host immune response against the tumour with prognostic properties. The International Immuno-Oncology Biomarkers Working Group (IBWG) proposed a standardised method for quantifying TILs in solid tumours to improve consistent and reproducible scoring. In this study, the methodology was tested in a retrospective population of oropharyngeal squamous cell carcinoma (OPSCC). TIL quantification was performed on 92 OPSCC samples (2004-2013) by four independent observers as described by the IBWG. Interobserver variability was assessed and results were correlated with clinicopathological variables and survival. TIL evaluation turned out to be challenging in OPSCC due to heterogeneity of TILs distribution, presence of pre-existing lymphoid tissue, surface ulceration or erosion and insufficient amount of intertumoural stroma in biopsies. Nonetheless, interobserver variability proved to be good to excellent. High stromal TILs (TILstr) and intratumoural TILs (TILtum) were both correlated to favourable overall survival and multivariate analysis showed TILstr to be the sole independent prognostic factor in OPSCC. The IBWG-proposed TIL quantification method is feasible and reproducible in OPSCC and provides valuable prognostic information regarding clinicopathological characteristics and overall survival. The use of this standardised methodology may facilitate implementation of TILs scoring as a prognostic biomarker in OPSCC.

Tertiary lymphoid structure score: a promising approach to refine the TNM staging in resected non-small cell lung cancer

BACKGROUND

We previously proposed an immune cell score (tumour node metastasis (TNM)-Immune cell score) classifier as an add-on to the existing TNM staging system for non-small cell lung cancer (NSCLC). Herein, we examined how to reliably assess a tertiary lymphoid structure (TLS) score to refine the TNM staging system.

METHODS

Using immunohistochemistry (CD8/cytokeratin), we quantified TLS in resected NSCLC whole-tumour tissue sections with three different scoring models on two independent collections (total of 553 patients). In a pilot setting, NanoString gene expression signatures were analysed for associations with TLS.

RESULTS

The number of TLSs significantly decreased in stage III patients as compared to stage II. The TLS score was an independent positive prognostic factor, regardless of the type of (semi)-quantification strategy used (four-scale semi-quantitative; absolute count of total TLS; subpopulation of mature TLS) or the endpoint (disease-specific survival; overall survival; time to recurrence). Subgroup analyses revealed a significant prognostic impact of TLS score within each pathological stage, patient cohort and main histological subtype. Targeted gene expression analysis showed that high TLS levels were associated with the expression of B cell and adaptive immunity genes/metagenes including tumour inflammation signature.

CONCLUSIONS

The TLS score increases the prognostic power in each pathological stage and hence has the potential to refine TNM staging in resected NSCLC.

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.

Characteristics of T-Cell Receptor Repertoire and Correlation With EGFR Mutations in All Stages of Lung Cancer

Lung cancer is the leading cause of cancer-related deaths worldwide, and its occurrence is related to the accumulation of gene mutations and immune escape of the tumor. Sequencing of the T-cell receptor (TCR) repertoire can reveal the immunosurveillance status of the tumor microenvironment, which is related to tumor escape and immunotherapy. This study aimed to determine the characteristics and clinical significance of the TCR repertoire in lung cancer. To comprehensively profile the TCR repertoire, results from high-throughput sequencing of samples from 93 Chinese patients with lung cancer were analyzed. We found that the TCR clonality of tissues was related to smoking, with higher clonality in patients who had quit smoking for less than 1 year. As expected, TCR clonality was correlated with stages: patients with stage IV disease showed higher clonality than others. The correlation between TCR repertoire and epidermal growth factor receptor (EGFR) status was also investigated. Patients with EGFR non-L858R mutations showed higher clonality and a lower Shannon index than other groups, including patients with EGFR L858R mutation and wild-type EGFR. Furthermore, we analyzed the TCR similarity metrics—that is, the TCR shared between postoperative peripheral blood and tissue of patients with non-distant metastasis of lung cancer. A similar trend was found, in which patients with EGFR L858R mutations had lower overlap index (OLI) and Morisita index (MOI) scores. Moreover, the OLI showed a positive correlation with several clinical characteristics, including the tumor mutational burden of tissues and the maximum somatic allele frequency of blood; OLI showed a negative correlation with the ratio of CD4+CD28+ in CD4+ cells and the ratio of CD8+CD28+ in CD8+ cells. In conclusion, TCR clonality and TCR similarity metrics correlated with clinical characteristics of patients with lung cancer. Differences in TCR clonality, Shannon index, and OLI across EGFR subtypes provide information to improve understanding about varied responses to immunotherapy in patients with different EGFR mutations.

Significantly different immunological score in lung adenocarcinoma and squamous cell carcinoma and a proposal for a new immune staging system

TNM stage is not enough to accurately predict the prognosis of patients with non-small cell lung cancer (NSCLC). This study aimed to establish the immunological score (IS) in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), separately, and propose a new staging system in NSCLC. We used the multiplex fluorescent immunohistochemistry (mIHC) technology to detect 17 immune biomarkers of 304 patients with NSCLC. The LASSO-COX regression model was used to establish the IS_NSCLC in the training cohorts. The IS_NSCLC was then validated in the validation cohort. The constructed IS_LUAD contained three immune features: CD4⁺CD73⁺ _{core of tumor (CT)}, PD-L1⁺ _CT, and IDO⁺ _{invasive margin (IM)}. IS_LUSC also contained two immune features: CD8⁺CD39^-CD73^- _CT, CD8⁺Tim-3⁺ _IM. In the training cohort, significant prognostic differences were found upon comparing low-IS_NSCLC patients with high-IS_NSCLC patients. For LUAD, the 5-y disease-free survival (DFS) rates were 54.7% vs. 8.1% and the 5-y overall survival (OS) rates were 82.4% vs. 36% (all P< .0001). For LUSC, the 5-y DFS rates were 74.0% vs. 14.7% and the 5-y OS rates were 78.2% vs. 17.6% (all P< .0001). Multivariate analyses indicated that IS_NSCLC was an independent indicator for prognosis. Finally, we combined IS_NSCLC with clinicopathological factors to establish a TN-I staging system and two nomogram models for clinical use. The TN-I stage had better prediction accuracy than TNM stage. The newly established IS_LUAD and IS_LUSC were completely different, and both were excellent indicators for the prognostic prediction. The TN-I stage could effectively improve prognostic accuracy and facilitate clinical application. Abbreviations NSCLC, non-small cell lung cancer; IS, immunological score; mIHC, multiplex fluorescent immunohistochemistry; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; CT, core of tumor; IM, invasive margin; DFS, disease-free survival; OS, overall survival; SITC, the Society for Immunotherapy of Cancer; FFPE, formalin-fixed paraffin-embedded; MWT, microwave treatment; DCA, decision curve analysis; ROC, receiver operating characteristic; AUC, area under the curve; EGFR, epidermal growth factor receptor.

High tumor mutation burden predicts favorable outcome among patients with aggressive histological subtypes of lung adenocarcinoma: A population-based single-institution study

OBJECTIVES

Tumor mutation burden (TMB) is an emerging predictive cancer biomarker. Few studies have addressed the prognostic role of TMB in non-small cell lung carcinoma, with conflicting results. Moreover, the association of TMB with different histological subtypes of lung adenocarcinoma has hitherto not been systematically evaluated. Here we studied the prognostic value of TMB and its distribution in different histological subtypes of lung adenocarcinomas in a retrospective cohort using the most recent updated classification guidelines.

MATERIALS AND METHODS

176 surgically resected stage I-IV lung adenocarcinomas were histologically reclassified according to WHO 2015 guidelines. A modified classification subdividing the acinar subtype into classic acinar, complex glandular and cribriform subtypes was further applied and potentially prognostic histopathological characteristics such as tumor-infiltrating lymphocytes were evaluated. 148 patients with stage I-III tumors and complete follow-up data were included in the survival analyses. TMB was determined by a commercial next generation sequencing panel from 131 tumors, out of which 105 had survival data available.

RESULTS

Predominant micropapillary, solid and complex glandular as well as nonpredominant cribriform histological subtypes were associated with significantly shorter survival. High TMB concentrated in micropapillary, solid and acinar predominant subtypes. Interestingly, TMB ≥ 14 mutations/MB conferred a stage- and histology-independent survival benefit compared to TMB < 14 in multivariable analysis for overall (HR 0.284, 95% CI 0.14-0.59, P=0.001) and disease-specific survival (HR 0.213, 95% CI 0.08-0.56, P=0.002).

CONCLUSION

TMB was an independent biomarker of favorable prognosis in our cohort of lung adenocarcinoma despite being associated with predominant histological subtypes considered aggressive.

Artificial intelligence as the next step towards precision pathology

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to improve both the volume and precision of histomorphological evaluation. Recently, machine learning, and particularly deep learning, has enabled rapid advances in computational pathology. The integration of machine learning into routine care will be a milestone for the healthcare sector in the next decade, and histopathology is right at the centre of this revolution. Examples of potential high-value machine learning applications include both model-based assessment of routine diagnostic features in pathology, and the ability to extract and identify novel features that provide insights into a disease. Recent groundbreaking results have demonstrated that applications of machine learning methods in pathology significantly improves metastases detection in lymph nodes, Ki67 scoring in breast cancer, Gleason grading in prostate cancer and tumour-infiltrating lymphocyte (TIL) scoring in melanoma. Furthermore, deep learning models have also been demonstrated to be able to predict status of some molecular markers in lung, prostate, gastric and colorectal cancer based on standard HE slides. Moreover, prognostic (survival outcomes) deep neural network models based on digitized HE slides have been demonstrated in several diseases, including lung cancer, melanoma and glioma. In this review, we aim to present and summarize the latest developments in digital image analysis and in the application of artificial intelligence in diagnostic pathology.

Identification of non-cancer cells from cancer transcriptomic data

Interactions between cancer cells and non-cancer cells composing the tumour microenvironment play a primary role in determining cancer progression and shaping the response to therapy. The qualitative and quantitative characterisation of the different cell populations in the tumour microenvironment is therefore crucial to understand its role in cancer. In recent years, many experimental and computational approaches have been developed to identify the cell populations composing heterogeneous tissue samples, such as cancer. In this review, we describe the state-of-the-art approaches for the quantification of non-cancer cells from bulk and single-cell cancer transcriptomic data, with a focus on immune cells. We illustrate the main features of these approaches and highlight their applications for the analysis of the tumour microenvironment in solid cancers. We also discuss techniques that are complementary and alternative to RNA sequencing, particularly focusing on approaches that can provide spatial information on the distribution of the cells within the tumour in addition to their qualitative and quantitative measurements. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Deep-Learning-Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

PURPOSE

Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs.

METHODS

We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)-positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes.

RESULTS

The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes.

CONCLUSION

Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development.

Assessment of Tumor-infiltrating Lymphocytes Predicts the Behavior of Early-stage Oral Tongue Cancer

Tumor-infiltrating lymphocytes (TILs) have shown a promising prognostic value in many epithelial cancers. We sought to assess the prognostic value of TILs in a multicenter cohort of early oral tongue squamous cell carcinoma (OTSCC). The percentage of TILs was assessed on the surgical resection slides stained with hematoxylin and eosin. The assessment of TILs was performed in the stromal compartment and in the intraepithelial compartment (at the invasive front and at the center of the tumor). We followed the method that was described recently by the International Immuno-Oncology Biomarker Working Group for the assessment of TILs. A total of 308 cases from the 5 Finnish university hospitals and from A.C. Camargo Cancer Center, São Paulo, Brazil, were included. We found a promising prognostic value for stromal TILs at the invasive front in the multivariable analysis with a hazard ratio of 2.61 (95% confidence interval [CI], 1.77-3.83; P<0.001) for overall survival, 1.99 (95% CI, 1.07-3.69; P=0.040) for disease-specific survival, and 1.94 (95% CI, 1.14-3.29; P=0.020) for disease-free survival. In conclusion, evaluation of TILs is simple and can aid in identifying the high-risk cases of early OTSCC. The method introduced by the International Immuno-Oncology Biomarker Working Group can be used for standardized determination of TILs in early OTSCC.

Overall assessment of tumor-infiltrating lymphocytes in head and neck squamous cell carcinoma: time to take notice

Background: The immune response has an important role in cancer progression. At the same time, anti-tumor effect of the immune response has been speculated to cause destruction of cancer cells. Recent studies have highlighted the significance of tumor-infiltrating lymphocytes (TILs) in different cancers. The International Immuno-Oncology Biomarkers Working Group has in 2017 published a practical review proposing a standardized method to assess TILs in the routine hematoxylin and eosin (HE) stained sections.Aims/objectives: To discuss the association between TILs and survival in head and neck squamous cell carcinoma (HNSCC).Material and methods: We review recent studies having assessed TILs in HNSCC and showing that tumors having low TILs associate significantly with worse survival.Results: These findings underline that HNSCC cases with low TILs might benefit from multimodality treatment and might be indicated to receive immunotherapy.Conclusions: The evaluation of TILs using routine HE-stained sections is practical and can be considered in assessment of antitumor activity.Significance: Here, we highlight the impact of overall assessment of TILs using the routine HE-stained specimens in HNSCC.

Advances in Diagnostic Procedures and Their Applications in the Era of Cancer Immunotherapy

Diagnostic procedures play critical roles in cancer immunotherapy. In this chapter, we briefly discuss three major diagnostic procedures widely used in immunotherapy: immunohistochemistry, next-generation sequencing, and flow cytometry. We also describe the uses of other diagnostic procedures and preclinical animal models in cancer immunotherapy translational research.

Level of tumor-infiltrating lymphocytes and density of infiltrating immune cells in different malignancies

Aim: To correlate levels of tumor-infiltrating lymphocytes (TIL) evaluated using the International Immuno-Oncology Biomarker Working Group methodology, and both density of tumor-infiltrating immune cell and clinicopathological features in different malignancies. Methods: 209 pathological samples from gastric cancer, cervical cancer (CC), non-small-lung cancer, cutaneous melanoma (CM) and glioblastoma were tested for TIL in hematoxylin eosin, and density of CD3+, CD4+, CD8+, CD20+, CD68+ and CD163+ cells by digital analysis. Results: TIL levels were higher in invasive margin compartments (IMC). TIL in IMC, intratumoral and stromal compartments predicted survival. CC and gastric cancer had higher TIL in intratumoral; CC and CM had higher TIL in stromal compartment and IMC. CM had the highest density of lymphocyte and macrophage populations. CD20 density was associated with survival in the whole series. Conclusion: Standardized evaluation of TIL levels may provide valuable prognostic information in a spectrum of different malignancies.

The prognostic significance of tumor-infiltrating lymphocytes assessment with hematoxylin and eosin sections in resected primary lung adenocarcinoma

The prognostic significance of tumor-infiltrating lymphocytes has been determined in cancers of the lung, colon and breast, though there is no standardized method for using this prognostic indicator for lung cancer. We applied a modified version of the method proposed by the International Immuno-Oncology Biomarkers Working Group to primary lung adenocarcinoma, which uses histologic findings of hematoxylin and eosin sections. The study included a total cohort of 146 lung adenocarcinoma patients who underwent lobectomy with lymph node dissection at two hospitals between 2008 and 2012. The full-face sections of hematoxylin and eosin-stained slides were reviewed, and we evaluated the level of tumor-infiltrating lymphocytes as a percentage of the area occupied out of the total intra-tumoral stromal area. Histopathologic factors include histologic grade, necrosis, extracellular mucin, lymphovascular invasion, lymph node metastasis, level of tumor infiltrating lymphocytes, tertiary lymphoid structures around the tumor, and the presence of a germinal center in tertiary lymphoid structures. The high level of tumor-infiltrating lymphocytes was found to be significantly correlated with the histologic grade (p = 0.023), necrosis (p = 0.042), abundance of tertiary lymphoid structures(p<0.001) and presence of a germinal center in tertiary lymphoid structures (p = 0.004). A high level of tumor-infiltrating lymphocytes was associated with better progression-free survival (p = 0.011) as well as overall survival (p = 0.049). On multivariable analysis, high tumor-infiltrating lymphocyte levels were a good independent prognostic factor for progression-free survival (Hazard ratio: 0.389, 95% confidence interval: 0.161–0.941, p = 0.036). Histologic evaluation of tumor-infiltrating lymphocytes level in lung adenocarcinoma with H&E sections therefore has prognostic value in routine surgical pathology.

The Cancer Immunotherapy Biomarker Testing Landscape

CONTEXT.—

Cancer immunotherapy provides unprecedented rates of durable clinical benefit to late-stage cancer patients across many tumor types, but there remains a critical need for biomarkers to accurately predict clinical response. Although some cancer immunotherapy tests are associated with approved therapies and considered validated, other biomarkers are still emerging and at various states of clinical and translational exploration.

OBJECTIVE.—

To provide pathologists with a current and practical update on the evolving field of cancer immunotherapy testing. The scientific background, clinical data, and testing methodology for the following cancer immunotherapy biomarkers are reviewed: programmed death ligand-1 (PD-L1), mismatch repair, microsatellite instability, tumor mutational burden, polymerase δ and ε mutations, cancer neoantigens, tumor-infiltrating lymphocytes, transcriptional signatures of immune responsiveness, cancer immunotherapy resistance biomarkers, and the microbiome.

DATA SOURCES.—

Selected scientific publications and clinical trial data representing the current field of cancer immunotherapy.

CONCLUSIONS.—

The cancer immunotherapy field, including the use of biomarker testing to predict patient response, is still in evolution. PD-L1, mismatch repair, and microsatellite instability testing are helping to guide the use of US Food and Drug Administration-approved therapies, but there remains a need for better predictors of response and resistance. Several categories of tumor and patient characteristics underlying immune responsiveness are emerging and may represent the next generation of cancer immunotherapy predictive biomarkers. Pathologists have important roles and responsibilities as the field of cancer immunotherapy continues to develop, including leadership of translational studies, exploration of novel biomarkers, and the accurate and timely implementation of newly approved and validated companion diagnostics.

Correlation between PD-L1 expression and clinicopathological characteristics of non-small cell lung cancer: A real-world study of a large Chinese cohort

BACKGROUND

Programmed death ligand-1 (PD-L1) is a predictive marker of anti-programmed death protein 1 (PD-1)/PD-L1 therapies for non-small cell lung cancer (NSCLC). However, little is known between PD-L1 expression and the clinicopathological characteristics of NSCLC in the Chinese population in a real-world setting.

METHODS

We analyzed PD-L1 expression by immunohistochemistry (IHC) in NSCLC patients using the 22C3 clone on the Dako Autostainer Link 48 platform. We then examined the associations of PD-L1 expression with clinicopathological characteristics, stromal tumor-infiltrating lymphocytes (TILs) and major molecular features.

RESULTS

A total of 1,156 recently NSCLC specimens including 827 sequentially resected specimens and 293 biopsy specimens were enrolled in our study. PD-L1 high expression was observed in 9.7% of 827 NSCLC patients, including 6.5% with adenocarcinoma (ADC, n=690), and 27.4% with squamous cell carcinoma (SqCC, n=117). These results showed higher expression rates than those in archived samples (>5 years old, n=329), that were previously reported by our group (4.9%, 0.5%, and 13.9% in NSCLC, ADC, and SqCC, respectively). The prevalence of PD-L1 expression was lower in surgical resection samples than in small biopsy samples. PD-L1 high expression in the lung biopsy was less likely present in the primary cancer than in metastases, and was also associated with a high level of stromal TILs (P=0.029) and PD-L1-positive immune cells (IC) (P<0.001). Both PD-L1 high and low expressions were more frequent in EGFR-wild type than in mutant type (P<0.001).

CONCLUSIONS

This study demonstrates that expression of PD-L1 is linked to the type of tumor specimens, resection versus biopsy specimens, and biopsies of primary versus metastatic cancers. These findings have substantial implications for clinical practice.

Programmed death ligand 1 (PD-L1) expression in parathyroid tumors

INTRODUCTION

PD-L1 is associated with prognosis and immunotherapeutic response in patients with malignancies. In previous studies, PD-L1 expression was detected in many endocrine tumors. However, the PD-L1 expression status in parathyroid tumors is unknown.

METHODS

We included 26 parathyroid carcinoma and 37 adenoma samples, as well as the corresponding patient information. PD-L1 was stained using the FDA-approved PD-L1 IHC 22C3 pharmDx and Ventana PD-L1 (SP263) assays, and staining was assessed by the estimated percentages of positive tumor cells and immune cells, respectively.

RESULTS

We classified the PD-L1 expression in the parathyroid tumors into four groups: (0) <1%, (1) 1-4%, (2) 5-9% and (3) ≥10% positive. With the SP263 clone, 37 (carcinoma:adenoma = 18:19) samples scored 0, 13 (carcinoma:adenoma = 4:9) scored 1, 7 (carcinoma:adenoma = 1:6) scored 2 and 6 (carcinoma:adenoma = 3:3) scored 3. However, in the series of cases using the 22C3 clone, 45 (carcinoma:adenoma = 20:25) samples scored 0, 10 (carcinoma: adenoma = 3:7) scored 1, 5 (carcinoma:adenoma = 1:4) scored 2, and 3 (carcinoma:adenoma = 2:1) scored 3. Concerning tumor-infiltrating immune cells, 57 samples were negative and six were positive with SP263, and 59 were negative and four were positive with 22C3. Moreover, PD-L1 expression was negatively correlated with the Ki-67 index and mitotic rate in parathyroid tumors depending on the different clones. However, the results indicated only moderate consistency between the SP263 and 22C3 clones in parathyroid tumors.

CONCLUSION

We found deficient PD-L1 expression in the majority of parathyroid tumors. However, the PD-L1 expression score in parathyroid tumors depended greatly on the antibody clone used.

Immunologic cellular characteristics of the tumour microenvironment of hepatocellular carcinoma drive patient outcomes

Background

Anti-tumour immune competence has an impact in hepatocarcinogenesis and success of anti-cancer therapies. Tumour-infiltrating lymphocytes (TILs) and monocytes/macrophages (TAMs) are proposed to have significance in cancer. However, there is only limited data concerning their impact on patient outcome and survival in hepatocellular carcinoma (HCC).

Methods

Frequencies of CD68⁺, CD163⁺ M2-polarized TAMs and TILs were measured in de novo HCC tumours in non-cirrhosis (n = 58) using immunohistology and correlated to patients’ clinicopathological characteristics and survival rates.

Results

Patients with tumours marked by appearance of TILs and CD68⁺ TAMs showed an improved 1-, 3- and 5-year recurrence-free survival (all p ≤ 0.05). CD68⁺ TAMs were associated with reduced incidence of recurrent and multifocal disease. Conversely, CD163⁺ TAMs were associated with multifocal HCC and lymphangiosis carcinomatosa (all p ≤ 0.05).

Conclusions

TILs and CD68⁺ TAMs are associated with multiple tumour characteristics and patient survival in HCC. However, there is only scarce data about the biology underlying their mechanistic involvement in human tumour progression. Thus, experimental data on functional links might help develop novel immunologic checkpoint inhibitor targets for liver cancer.

Oncolytic virotherapy for small-cell lung cancer induces immune infiltration and prolongs survival

Oncolytic virotherapy has been proposed as an ablative and immunostimulatory treatment strategy for solid tumors that are resistant to immunotherapy alone; however, there is a need to optimize host immune activation using preclinical immunocompetent models in previously untested common adult tumors. We studied a modified oncolytic myxoma virus (MYXV) that shows high efficiency for tumor-specific cytotoxicity in small-cell lung cancer (SCLC), a neuroendocrine carcinoma with high mortality and modest response rates to immune checkpoint inhibitors. Using an immunocompetent SCLC mouse model, we demonstrated the safety of intrapulmonary MYXV delivery with efficient tumor-specific viral replication and cytotoxicity associated with induction of immune cell infiltration. We observed increased SCLC survival following intrapulmonary MYXV that was enhanced by combined low-dose cisplatin. We also tested intratumoral MYXV delivery and observed immune cell infiltration associated with tumor necrosis and growth inhibition in syngeneic murine allograft tumors. Freshly collected primary human SCLC tumor cells were permissive to MYXV and intratumoral delivery into patient-derived xenografts resulted in extensive tumor necrosis. We confirmed MYXV cytotoxicity in classic and variant SCLC subtypes as well as cisplatin-resistant cells. Data from 26 SCLC human patients showed negligible immune cell infiltration, supporting testing MYXV as an ablative and immune-enhancing therapy.

Prognostic Value of Macrophage Phenotypes in Resectable Non-Small Cell Lung Cancer Assessed by Multiplex Immunohistochemistry

Macrophages are important inflammatory cells that regulate innate and adaptive immunity in cancer. Tumor-associated macrophages (TAMs) are thought to differentiate into two main phenotypes: proinflammatory M1 and protumorigenic M2. Currently, the prognostic impact of TAMs and their M1 and M2 phenotypes is unclear in non–small cell cancer (NSCLC). The present study was set up to evaluate an approach for identifying common M1 and M2 macrophage markers and explore their clinical significance in NSCLC. Using multiplex chromogenic immunohistochemistry, tissue microarrays of 553 primary tumors and 143 paired metastatic lymph nodes of NSCLC specimens were stained to detect various putative macrophage phenotypes: M1 (HLA-DR/CD68), M2 (CD163/CD68), M2 (CD204/CD68), and pan-macrophage (CD68/CK). Correlation analyses were performed to examine the relationship between TAMs and adaptive/innate immune infiltrates. HLA-DR⁺/CD68⁺M1 TAM level significantly decreased from pathological stage I to III. In a compartment-specific correlation analysis, moderate to strong correlations were observed between both TAM subsets (M1 and M2) with CD3-, CD8-, CD4-, and CD45RO-positive immune cells. Survival analyses, in both stromal and intratumoral compartments, revealed that high levels of HLA-DR⁺/CD68⁺M1 (stroma, hazard ratio [HR] = 0.73, P = .03; intratumor, HR = 0.7, P = .04), CD204⁺M2 (stroma, HR = 0.7, P = .02; intratumor, HR = 0.6, P = .004), and CD68 (stroma, HR = 0.69, P = .02; intratumor, HR = 0.73, P = .04) infiltration were independently associated with improved NSCLC-specific survival. In lymph nodes, the intratumoral level of HLA-DR⁺/CD68⁺M1 was an independent positive prognostic indicator (Cox model, HR = 0.38, P = .001). In conclusion, high levels of M1, CD204⁺M2, and CD68 macrophages are independent prognosticators of prolonged survival in NSCLC.

Tumor-infiltrating lymphocytes associate with outcome in nonendemic nasopharyngeal carcinoma: a multicenter study

The prognostic significance of tumor-infiltrating lymphocytes (TILs) has been studied recently in many cancers. For the first time in a nonendemic region, we have evaluated the prognostic value of TILs in a whole population-based nationwide cohort of nasopharyngeal carcinoma (NPC) in Finland. A total of 115 cases from Finnish hospitals were included. TILs were analyzed using hematoxylin and eosin-stained slides according to the criteria of the International Immuno-Oncology Biomarker Working Group. TILs were evaluated separately in stromal and tumor compartments. The log-rank test and univariable and multivariable analyses were used to compare survival in patients with tumors with low and high TILs. A significant positive correlation was observed between the occurrence of intratumoral and stromal TILs (P < .001). In multivariable analysis, NPC cases with low intratumoral TILs had poor overall survival with a hazard ratio (HR) of 2.55 and 95% confidence interval (95% CI) of 1.60 to 4.05 (P < .001). Cases with low intratumoral TILs also had poor disease-specific survival (HR, 2.02; 95% CI, 1.16-3.52; P = .015). Keratinized tumors with low intratumoral TILs were associated with an even poorer overall survival (HR, 3.94; 95% CI, 2.17-7.15; P < .001) and a poor disease-specific survival (HR, 2.97; 95% CI, 1.46-6.05; P = .009). Our study demonstrates that the evaluation of TILs is simple and can be assessed routinely in NPC.