Assessment Of Tumor-infiltrating Lymphocytes Research Articles

A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images

Background and objectivesThe detection of tumor-infiltrating lymphocytes (TILs) could aid in the development of objective measures of the infiltration grade and can support decision-making in breast cancer (BC). However, manual quantification of TILs in BC histopathological whole slide images (WSI) is currently based on a visual assessment, thus resulting not standardized, not reproducible, and time-consuming for pathologists. In this work, a novel pathomic approach, aimed to apply high-throughput image feature extraction techniques to analyze the microscopic patterns in WSI, is proposed. In fact, pathomic features provide additional information concerning the underlying biological processes compared to the WSI visual interpretation, thus providing more easily interpretable and explainable results than the most frequently investigated Deep Learning based methods in the literature. MethodsA dataset containing 1037 regions of interest with tissue compartments and TILs annotated on 195 TNBC and HER2+ BC hematoxylin and eosin (H&E)-stained WSI was used. After segmenting nuclei within tumor-associated stroma using a watershed-based approach, 71 pathomic features were extracted from each nucleus and reduced using a Spearman's correlation filter followed by a nonparametric Wilcoxon rank-sum test and least absolute shrinkage and selection operator. The relevant features were used to classify each candidate nucleus as either TILs or non-TILs using 5 multivariable machine learning classification models trained using 5-fold cross-validation (1) without resampling, (2) with the synthetic minority over-sampling technique and (3) with downsampling. The prediction performance of the models was assessed using ROC curves. Results21 features were selected, with most of them related to the well-known TILs properties of having regular shape, clearer margins, high peak intensity, more homogeneous enhancement and different textural pattern than other cells. The best performance was obtained by Random-Forest with ROC AUC of 0.86, regardless of resampling technique. ConclusionsThe presented approach holds promise for the classification of TILs in BC H&E-stained WSI and could provide support to pathologists for a reliable, rapid and interpretable clinical assessment of TILs in BC.

Predictive and Prognostic Role of Tumor-Infiltrating Lymphocytes in Patients with Advanced Breast Cancer Treated with Primary Systemic Therapy.

Tumor-infiltrating lymphocytes (TILs) are gaining recognition as an important immunological biomarker with therapeutic potential in breast cancer. In this cohort study conducted on patients with advanced breast cancer treated with primary systemic therapy (PST), the TILs concentration was correlated with response to PST and survival outcomes. Patients with primary breast cancer treated with PST between 2016 and 2020 were included in this study, approved by IEC, and registered on ClinicalTrials.gov (NCT05250336). Tumor core biopsies obtained prior to starting treatment from 489 patients were assessed for the proportion of stromal TILs by standardized method and categorized into low (0-10% immune cells), intermediate (11-59%), and high (≥ 60%) TILs. TIL concentration and complete pathological response (pCR), disease-free survival (DFS), and overall survival (OS) were correlated. Of the 489 patients, 372 matched the eligibility criteria for assessment of TILs and made the final study cohort. Among these, 135 were luminal, 129 HER2-enriched, and 108 triple-negative breast cancers (TNBC). Proportions of patients with high TILs were greater in TNBC (15.7%) and HER2-enriched (9.3%), compared to luminal cancers (4.4%). High TIL concentration was correlated with higher pCR in all subtypes. A pCR was achieved in 33.3, 50, and 52.9% of high TIL patients in luminal, HER2-enriched, and TNBC subtypes, respectively (p < 0.05). High TILs were linked to longer DFS and OS in TNBC and HER2-enriched breast cancers. In this first study of its kind from a low- and middle-income country, high TILs concentration was found to be a predictor of response to PST across all breast cancer subtypes. TILs concentration was found predictive of better DFS and OS in TNBC and HER2-enriched cancers. Prognostic role of TILs in luminal cancers was not so apparent.

Deep Learning with Transformer or Convolutional Neural Network in the Assessment of Tumor-Infiltrating Lymphocytes (TILs) in Breast Cancer Based on US Images: A Dual-Center Retrospective Study.

This study aimed to explore the feasibility of using a deep-learning (DL) approach to predict TIL levels in breast cancer (BC) from ultrasound (US) images. A total of 494 breast cancer patients with pathologically confirmed invasive BC from two hospitals were retrospectively enrolled. Of these, 396 patients from hospital 1 were divided into the training cohort (n = 298) and internal validation (IV) cohort (n = 98). Patients from hospital 2 (n = 98) were in the external validation (EV) cohort. TIL levels were confirmed by pathological results. Five different DL models were trained for predicting TIL levels in BC using US images from the training cohort and validated on the IV and EV cohorts. The overall best-performing DL model, the attention-based DenseNet121, achieved an AUC of 0.873, an accuracy of 79.5%, a sensitivity of 90.7%, a specificity of 65.9%, and an F1 score of 0.830 in the EV cohort. In addition, the stratified analysis showed that the DL models had good discrimination performance of TIL levels in each of the molecular subgroups. The DL models based on US images of BC patients hold promise for non-invasively predicting TIL levels and helping with individualized treatment decision-making.

Expression patterns and prognostic implications of tumor-infiltrating lymphocytes dynamics in early breast cancer patients receiving neoadjuvant therapy: A systematic review and meta-analysis.

High levels of tumor-infiltrating lymphocytes (TILs) are associated with better outcomes in early breast cancer and higher pathological response rates to neoadjuvant chemotherapy especially in the triple-negative (TNBC) and HER2+ subtypes. However, the dynamic changes in TILs levels after neoadjuvant treatment (NAT) are less studied. This systematic review and meta-analysis aimed to investigate the patterns and role of TILs dynamics change in early breast cancer patients receiving NAT. Medline, Embase, Web of Science Core Collection and PubMed Central databases were searched for eligible studies. Data were extracted independently by two researchers and discordances were resolved by a third. Pooled TILs rates pre- & post-treatment (overall and per subtype), pooled rates of ΔTILs and direction of change after NAT as well as correlation of ΔTILs with survival outcomes were generated in the outcome analysis. Of 2116 identified entries, 34 studies fulfilled the criteria and provided adequate data for the outcomes of interest. A decreased level of TILs was observed after NAT in paired samples across all subtypes. The effect of NAT on TILs was most prominent in TNBC subtype with a substantial change, either increase or decrease, in 79.3% (95% CI 61.7-92.6%) of the patients as well as in HER2+ disease (14.4% increased vs 46.2% decreased). An increase in ΔTILs in TNBC was associated with better disease-free/relapse-free survival in pooled analysis (univariate HR = 0.59, 95% CI: 0.37-0.95, p = 0.03). This meta-analysis illustrates the TILs dynamics during NAT for breast cancer and indicates prognostic implications of ΔTILs in TNBC. The potential clinical utility of the longitudinal assessment of TILs during neoadjuvant therapy warrants further validation.

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

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

260 (PB-084) Poster - The combination of platelet-to-lymphocyte ratios with TIL assessment as prognostic factor for patients with triple negative breast cancer

Background: Tumor infiltrating lymphocytes (TILs) are a prognostic marker in breast cancer and high TIL infiltration correlates with better patient outcomes. Meanwhile, parameters involving immune cells in peripheral blood have also been established as prognostic markers. High platelet-to-lymphocyte ratios (PLRs) and neutrophil-to-lymphocyte ratios (NLRs) are related to poor outcomes in breast cancer, but their mechanisms remain unknown. To date, TILs and these parameters have been examined separately.

Validation of the Optimum Timing of Assessment of Tumor Infiltrating Lymphocytes During Preoperative Chemotherapy for Breast Cancer.

Tumor microenvironment (TME) assessment is considered to play an important role in the prediction of prognosis and therapeutic response following breast cancer treatment. No consensus has been reached regarding evaluation methods despite reports on the utilization of tumor-infiltrating lymphocytes (TILs) for immune TME (iTME) monitoring. Optimum timing of iTME assessment has not yet been established. Two hundred thirty-nine patients were treated with neoadjuvant chemotherapy (NAC). During the period from diagnostic needle biopsy to NAC initiation for breast cancer, the optimal evaluation timing was examined using a receiver operating characteristic (ROC) curve analysis. A significant correlation between TILs and pathological complete response (pCR) was only observed in the short-term group (≤35 days) (p=0.033). Prognostic analysis revealed that in the short-term group, patients with high TIL levels had a significantly better survival prognosis relative to those with low TIL levels (>35 days) [disease-free survival (DFS): p=0.001, overall survival (OS): p=0.021]. TILs were identified as an independent factor affecting DFS in a multivariate analysis (p=0.008, hazard ratio=0.130). TIL assessment during NAC for breast cancer is a prognostic predictor only when performed at ≤35 days before NAC initiation.

Inter-observer agreement of tumor infiltrating lymphocytes in primary HER2-positive breast cancer and correlation between tissue microarray and full tumor-sections.

Tumor infiltrating lymphocytes (TILs) have predictive and prognostic potential in HER2-positive breast cancer (HER2 + BC). Due to tumor heterogeneity, guidelines recommend evaluation on full tumor-sections over biopsies, but aren't clear regarding tissue microarrays (TMAs). Herein, we investigate the inter-observer agreement of TILs assessment in HER2 + BC on full-sections and TMAs using a standardized method. Two pathologists assessed TILs using HE full-sections and TMAs from 244 patients with HER2 + BC. TILs were assessed in 10% intervals; values <10% evaluated as 0%, 1% or 5%. Levels of agreement were evaluated using intraclass-coefficient (ICC), Kappa statistics and concordance analysis. For inter-observer agreement for full-sections, ICC was 0.93 (95% CI 0.89-0.95) and Kappa was 0.75, corresponding to acceptable and moderate agreement respectively. For TMAs, ICC was 0.73 (95% CI: 0.62-0.81) and Kappa 0.33, corresponding to unacceptable agreement. For association in matched TMA and full-sections, ICC was 0.64 (95% CI 0.55-0.71) and Lin's concordance correlation coefficient was 0.63 (95% CI 0.55-0.71), corresponding to unacceptable agreement. There is acceptable inter-observer agreement of TILs assessment on full-sections but not TMAs and discrepancy between full-sections and TMAs. TMA preparation must include consideration for representation of both entire tumor area and tumor-microenvironment to correctly define prognostic and predictive values of potential immuno-related biomarkers.

Abstract CT570: KISIMA-01: A first-in-human trial of the heterologous prime-boost vaccine ATP128/VSV-GP128 with ezabenlimab (BI 754091) in patients with stage IV colorectal cancer

Abstract Background: Most microsatellite stable/mismatch repair proficient (MSS/MMRp) stage IV colorectal cancers (CRC) do not respond to PD-1 inhibition. ATP128, based on the KISIMA platform, is a single chimeric fusion protein, composed of 3 elements essential to generate potent antitumoral cellular immunity: a proprietary cell-penetrating peptide (CPP) for antigen delivery, a proprietary Toll-like receptor (TLR)-peptide agonist with self-adjuvant properties and a modulable multi-antigenic domain (Mad), where the Mad for CRC includes 3 antigens: carcinoembryonic antigen (CEA), Survivin, Achaete-scute complex homolog 2 (ASCL2). VSV-GP128 is a recombinant vesicular stomatitis virus (VSV) carrying the glycoprotein (GP) of a non-neurotropic strain of lymphocytic choriomeningitis virus (LCMV) instead of the native VSV-GP. The GP of the LCMV abrogates neurotoxicity. As viral vector, VSV-GP128 expresses a Mad with identical sequence to ATP128 integrated in a linear, negative-sense, single-stranded RNA genome. Preclinical data have shown that priming with KISIMA vaccine followed by VSV-GP boost induced a large pool of polyfunctional and persistent antigen-specific cytotoxic T cells in the periphery as well as within the tumor in several tumor models. Combining heterologous vaccination with a PD-1 inhibitor further improved its therapeutic efficacy (Das et al., Nature Communication 2021). Methods: KISIMA-01 (NCT04046445) is an open-label, multi-center Phase 1b umbrella trial to investigate the safety, tolerability and immunogenicity of the heterologous prime-boost vaccine AT128/VSV-GP128 in combination with the anti-PD1 ezabenlimab in patients with stage IV MSS CRC. Two different patient cohorts are investigated: 1) maintenance setting (during a chemotherapy free period) after a minimum of 4 months of 1st line standard chemotherapy with clinical benefit (defined as PR or SD) (n=30); 2) resectable liver-limited disease (n=15). ATP128 is given subcutaneously on day 1 (prime); VSV-GP128 is administered intravenously on day 15 as the heterologous boost. ATP128 is again administered on day 29 (injection 3) and then every 4 weeks for the last 3 immunizations. Ezabenlimab is administered every 3 weeks starting with the first ATP128 administration. Blood and tissue samples are collected before, during and after ATP128/VSV-GP128 treatment to monitor the induction of a tumor associated antigen-specific immune response and immune-related changes. Immunogenicity will be analyzed in the peripheral blood using ELISpot, and in the tumor microenvironment by immunohistochemical assessment of tumor-infiltrating lymphocytes (TILs). Clearance of ctDNA is analyzed as an exploratory endpoint. The heterologous prime-boost cohorts (ATP128/VSV-GP128) of the KISIMA-01 trial are recruiting in the US, Switzerland and Belgium. Citation Format: Heinz-Josef Lenz, Thibaud Koessler, Paul Oberstein, Eric Van Cutsem, Sunnie Kim, Ralph Fritsch, Hans Prenen, Michael Morse, Delphine Gani, Madiha Derouazi, Thomas Bogenrieder, Scott Kopetz. KISIMA-01: A first-in-human trial of the heterologous prime-boost vaccine ATP128/VSV-GP128 with ezabenlimab (BI 754091) in patients with stage IV colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT570.

Combined assessment of metabolic response and tumor infiltrating lymphocytes as a predictor of outcomes following neoadjuvant therapy for HER2-positive breast cancer: Results from the randomized PREDIX HER2 trial.

593 Background: Abundance of tumor infiltrating lymphocytes (TIL) is prognostic in early HER2-positive breast cancer (BC). Response to neoadjuvant therapy (NAT) according to positron emission tomography combined with computed tomography (PET-CT) has been shown to predict pathologic complete response (pCR). There is paucity of data regarding long-term prognostication using PET-CT and the potential value of the combined assessment of both these biomarkers. Methods: PREDIX HER2 (NCT02568839) is a prospective randomized phase 2 trial that compared standard NAT (docetaxel, trastuzumab, pertuzumab) with trastuzumab emtansine, in patients with HER2-positive BC. Overall, 202 patients were included (197 evaluable) and the primary efficacy analysis showed no difference in pCR or event-free survival (EFS) between the two groups (Hatschek, JAMA Oncology 2021). Assessment with fluorine 18–labeled fluorodeoxyglucose PET-CT was performed at baseline and after 2 and 6 treatment cycles, and SUVmax was evaluated as a continuous variable. TILs were assessed at baseline biopsies according to guidelines from the International TIL Working Group (J.H.). The aim of this secondary analysis was to investigate the combined assessment of TIL and PET-CT as an early predictor of response to NAT. Results: Overall, 112 patients underwent baseline PET-CT and 109 after C2, whereas 173 had baseline TIL. In multivariable analysis, baseline SUVmax did not predict pCR (ORadj= 1.04, 95% CI 0.97-1.12, p = 0.259) or EFS (HRadj= 1.07, 95% CI 0.98-1.17, p = 0.117). In contrast, higher SUVmax at C2 predicted lower pCR (ORadj= 0.65, 95% CI 0.48-0.87, p = 0.005) and worse EFS (HRadj= 1.18, 95% CI 1.04-1.34, p = 0.01). Baseline TIL &gt; 10% (median cut-off) provided additional prognostic information to clinical parameters (stage and hormone receptor expression) and C2 SUVmax (LR-Δχ2 = 7.19, p = 0.007; ORadj= 3.52, 95% CI 1.37 – 9.06, p = 0.009). 75% of patients with high TIL and C2 SUVmax &lt; 2.49 achieved pCR, compared with 13.8% of those with low TIL and high C2 SUVmax and 39.1%-41.3% for the intermediate groups (p = 0.001). Conclusions: SUVmax after two cycles of NAT for HER2-positive BC is an independent predictor of both short- and long-term outcomes. A combined assessment with TIL may facilitate early selection of good responders for de-escalation and poor responders for alternative treatment strategies. Clinical trial information: NCT02568839.

Artificial intelligence (AI)–powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC).

595 Background: Stromal TIL are a well-recognized prognostic and predictive biomarker in breast cancer. There is a need for tools assisting visual assessment of TIL, to improve reproducibility as well as for convenience. This study aims to assess the clinical significance of AI-powered spatial TIL analysis in the prediction of pathologic complete response (pCR) after NAC in TNBC patients. Methods: H&amp;E stained slides and clinical outcomes data were obtained from stage I – III TNBC patients treated with NAC in two centers in Korea. For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&amp;E Whole-Slide Image (WSI) analyzer, which identifies and quantifies TIL within the cancer or stroma area. Lunit SCOPE IO was developed with a 13.5 x 109 micrometer2 area and 6.2 x 106 TIL from 17,849 H&amp;E WSI of multiple cancer types, annotated by 104 board-certified pathologists. iTIL score and sTIL score were defined as area occupied by TIL in the intratumoral area (%) and the surrounding stroma (%), respectively. Immune phenotype (IP) of each slide was defined from spatial TIL calculation, as inflamed (high TIL density in tumor area), immune-excluded (high TIL density in stroma), or desert (low TIL density overall). Results: A total of 954 TNBC patients treated from 2006 to 2019 were included in this analysis. pCR (ypT0N0) was confirmed in 261 (27.4%) patients. The neoadjuvant regimens used were mostly anthracycline (97.8%) and taxane (75.1%) -based, with 116 (12.1%) patients receiving additional platinum and 41 (4.3%) patients treated as part of immune checkpoint inhibitor or PARP inhibitor clinical trials. The median iTIL score and sTIL score were 4.3% (IQR 3.2 – 5.8) and 8.1% (IQR 6.3 – 13.4), respectively. The mean iTIL score was significantly higher in patients who achieved pCR after NAC (5.8% vs. 4.5%, p &lt; 0.001), and a similar difference was observed with sTIL score (12.1%.1 vs. 9.4%, p &lt; 0.001). iTIL score was found to remain as an independent predictor of pCR along with cT stage and Ki-67 in the multivariable analysis (adjusted odds ratio 1.211 (95% CI 1.125 – 1.304) per 1 point (%) change in the score, p &lt;0.001). By IP groups, 291 (30.5%) patients were classified as inflamed, 502 (52.6%) as excluded, and 161 (16.9%) as desert phenotype. The patients with inflamed phenotype were more likely to achieve pCR (44.7%) than other phenotypes (19.8%, p &lt; 0.001). Conclusions: AI-powered spatial TIL analysis could assess TIL densities in the cancer area and surrounding stroma of TNBC, and TIL density scores and IP classification could predict pCR after NAC.

DDTNet: A dense dual-task network for tumor-infiltrating lymphocyte detection and segmentation in histopathological images of breast cancer.

The morphological evaluation of tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H& E)-stained histopathological images is the key to breast cancer (BCa) diagnosis, prognosis, and therapeutic response prediction. For now, the qualitative assessment of TILs is carried out by pathologists, and computer-aided automatic lymphocyte measurement is still a great challenge because of the small size and complex distribution of lymphocytes. In this paper, we propose a novel dense dual-task network (DDTNet) to simultaneously achieve automatic TIL detection and segmentation in histopathological images. DDTNet consists of a backbone network (i.e., feature pyramid network) for extracting multi-scale morphological characteristics of TILs, a detection module for the localization of TIL centers, and a segmentation module for the delineation of TIL boundaries, where a boundary-aware branch is further used to provide a shape prior to segmentation. An effective feature fusion strategy is utilized to introduce multi-scale features with lymphocyte location information from highly correlated branches for precise segmentation. Experiments on three independent lymphocyte datasets of BCa demonstrate that DDTNet outperforms other advanced methods in detection and segmentation metrics. As part of this work, we also propose a semi-automatic method (TILAnno) to generate high-quality boundary annotations for TILs in H& E-stained histopathological images. TILAnno is used to produce a new lymphocyte dataset that contains 5029 annotated lymphocyte boundaries, which have been released to facilitate computational histopathology in the future.

Prognostic impact of tumor-infiltrating lymphocytes and neutrophils in resected non-small cell lung carcinoma

The prognostic impact of tumor-infiltrating lymphocytes (TILs) has been determined in non-small cell lung carcinoma; however, there is no standardized method for counting TILs. In this report, we applied the method proposed by the International Immuno-Oncology Biomarkers Working Group for the assessment of TILs to count the number of tumor-infiltrating neutrophils (TINs). We then analyzed the association between TIL counts, TIN counts, and clinicopathological factors in lung cancer. We retrospectively analyzed a series of 1191 Japanese patients with resected lung adenocarcinoma and squamous cell carcinoma, which were restaged according to the eighth edition of the TNM staging system. Tumors were classified according to the 2015 WHO classification of lung carcinoma. Recurrence-free probability (RFP) and overall survival (OS) were analyzed using the log-rank test and Cox proportional hazard model. Using multivariate analysis for patient outcome in patients with adenocarcinoma, high TIN counts were an independent prognostic factor for worse RFP (hazard ratio [HR]: 1.94, p<0.001) and worse OS (hazard ratio [HR]: 1.75, p=0.006). On the other hand, TIL counts were not related to patient outcome. We have demonstrated that high TINs are unfavorable prognostic markers for resected lung adenocarcinoma. In resected lung squamous cell carcinoma, TIL and TIN counts were not related to patient prognosis. It has been suggested that the immune response to cancer cells may differ depending on the histological type. An understanding of how neutrophils are programmed to perform protumor activities is necessary for the future design of targeted immunotherapies.

Magnetic Resonance Imaging of Tumor-Infiltrating Lymphocytes by Anti-CD3-Conjugated Iron Oxide Nanoparticles.

Immune checkpoint blockade, considered a revolutionary approach in cancer treatment, is only effective in patients with high tumor-infiltrating lymphocytes (TILs). This work aimed to investigate the feasibility of targeted contrast agent (CA) based on dextran-coated superparamagnetic iron oxide nanoparticles (SPIONs-DEX) for TILs detection by magnetic resonance imaging (MRI) studies. To do so, we synthesized an MRI CA by conjugating SPIONs-DEX to an anti-CD3 monoclonal antibody via cyanogen bromide as a cross-linker. In vitro assessments demonstrated the higher labeling efficiency of the developed CA to CD3+ lymphocytes compared to SPIONs-DEX. In vivo MRI of a xenograft model of CD3+ lymphocytes revealed the significant signal loss after the intravenous injection of the bioconjugate by ∼34 % and 21 % in T2 *-weighted and T2 -weighted images, respectively. The histopathological evaluation of xenograft tumors confirmed the labeling of lymphocytes by the targeted CA. This approach could open up a new horizon in the non-invasive assessment of TILs to identify patients eligible for immunotherapy.

Tumor-Infiltrating Lymphocytes in Head and Neck Cancer: Ready for Prime Time?

Simple SummaryThe immune response has been shown to be a promising indicator to predict the clinical behavior of many cancers, including head and neck cancer. Tumor-infiltrating lymphocytes (TILs) were widely introduced as an important tool to reveal the status of the immune response. This review discusses the significance of TILs in head and neck cancers.The evaluation of tumor-infiltrating lymphocytes (TILs) has received global attention as a promising prognostic cancer biomarker that can aid in clinical decision making. Proof of their significance was first shown in breast cancer, where TILs are now recommended in the classification of breast tumors. Emerging evidence indicates that the significance of TILs extends to other cancer types, including head and neck cancer. In the era of immunotherapy as a treatment choice for head and neck cancer, assessment of TILs and immune checkpoints is of high clinical relevance. The availability of the standardized method from the International Immuno-oncology Biomarker Working Group (IIBWG) is an important cornerstone toward standardized assessment. The aim of the current article is to summarize the accumulated evidence and to establish a clear premise for future research toward the implementation of TILs in the personalized management of head and neck squamous cell carcinoma patients.

Tumour-infiltrating lymphocytes add prognostic information for patients with low-risk DCIS: findings from the SweDCIS randomised radiotherapy trial

BackgroundThe immune microenvironment is an important modulator of tumour progression and treatment response. In invasive breast cancer, assessment of tumour-infiltrating lymphocytes (TILs) provides prognostic and predictive information. However, the clinical impact of TILs for ductal carcinoma in situ (DCIS) has not yet been demonstrated. Patients and methodsPost hoc analysis of the SweDCIS randomised radiotherapy trial including primary DCIS cases following breast-conserving surgery. TILs were assessed on haematoxylin-eosin sections (n = 711) according to the International Immuno-Oncology Biomarker Working Group guidelines. TILs-scores were analysed as continuous and dichotomised (≤5% versus >5%) variable regarding ipsilateral breast events (IBEs) as the predefined primary endpoint. ResultsMost women (61.9%) showed a TILs prevalence of ≤5%. High TILs-scores were associated with larger lesion size, human epidermal growth factor receptor 2 (HER2)-positivity, higher nuclear grade, and KI67-score. DCIS cases with high TILs prevalence had a significant increased cumulative IBE incidence at five years post-surgery (TILslow-versus TILshigh 9% versus 18%; p < 0.001). Among patients with HER2-negative DCIS, high TILs remained an independent poor prognosis marker for IBE risk in multivariable analysis with an adjusted hazard ratio of 2.41 [95%CI 1.17–4.95, p = 0.017]. Including TILs-status provided a refined stratification of patients with general low-risk DCIS (grade <3, size <25 mm, free margin). No interaction between TILs and radiotherapy benefits was detected. ConclusionHigh TILs are associated with higher IBE risk over 5-years post-surgery, particularly for HER2-negative DCIS. Our data indicate that TILs should be integrated into the clinical workup to define patients with low-risk DCIS who can omit adjuvant therapy or patients with potential benefits from immunotherapy.

Abstract P2-07-09: Characterization of the tumor microenvironment in patients with hormone receptor positive, HER2 negative early breast cancer

Abstract Background: Patients (pts) with early stage HER2+ breast cancer (HER2+ EBC) are often treated with neoadjuvant chemotherapy (NACT). Recent studies have demonstrated that increased densities of tumor infiltrating lymphocytes (TIL) are associated with increased rates of pathologic complete response (pCR) in HER2+ EBC. However, outside of standard TIL analysis, a more comprehensive description of the tumor microenvironment (TME) and its impact on clinical outcomes in HER+ EBC is not well defined. Using novel methods, we sought to characterize the TME of patients with hormone receptor positive (HR+), HER2+ EBC treated with NACT. In addition to standard H&amp;E based TIL analysis, we utilized quantitative multiplex immunofluorescence (qmIF), spatial analysis and analysis of RNA-based gene signatures to assess for pretreatment TME characteristics associated with pCR to NACT in HER2+/HR+ EBC. Methods: We identified 29 pts with HER2+/HR+ EBC treated with NACT between 2005 and 2015 for which pretreatment biopsy tissue was available. 13 pts (45%) were treated with an anthracycline, 26 (90%) were treated with trastuzumab in addition to chemotherapy and 14 (48%) were treated with trastuzumab and pertuzumab. At surgery, 13 pts (45%) achieved a pCR. A breast cancer pathologist performed TIL analysis according to international guidelines on pretreatment H&amp;E slides. qmIF was performed on 28 pretreatment specimens using an antibody panel targeting CD3, CD8, CD68, FOXP3, and pancytokeratin. We analyzed multispectral images using HALO software to perform tissue segmentation (tumor vs stroma) and phenotypic analysis based on antibody staining patterns. Upon spatially resolving these components, we then performed proximity analysis. We obtained mRNA-based gene signatures via the Nanostring nCounter Breast Cancer 360 Panel for 28 patients. T-tests were performed to evaluate for associations of TME features with pCR. Results: We evaluated the association of pCR with: manual H&amp;E-based TIL assessments, lymphocyte densities and interactions (assessed by spatial proximity) from qmIF, and RNA signatures assessed from the NanoString BC360 panel. Univariate analysis revealed strong associations of inflammation signatures derived from qmIF with pCR, including higher stromal densities of CD3+ (p&amp;lt;0.01), CD8+ (p=0.02) and CD3+CD8-FOXP3- (p=0.02) cells. pCR was also associated with higher ratios of CD3+:CD68+ (p&amp;lt;0.01). This finding remained significant in T-cell subsets CD8+:CD68+ (p=0.04) and was driven by CD3+CD8-FOXP3-:CD68+ (p=0.02). High numbers of lymphocyte interactions, assessed by counting pairs of cells within 30 microns of each other, were also associated with pCR, including CD3+:FOXP3+ (p&amp;lt;0.01) and CD3+CD8-FOXP3-:FOXP3+ (p&amp;lt;0.01). We found no significant associations between pCR and manual H&amp;E based TIL assessments or RNA signatures. Conclusion: In this population of HER2+/HR+ EBC treated with NACT, stromal and intratumoral TIL assessment by standard H&amp;E was not associated with pCR. Higher stromal densities of CD3+, CD8+, and CD3+CD8-FOXP3- TIL subsets were associated with pCR by qmIF and further analysis revealed the presence and proximity of lymphocyte subpopulations correlated with pCR, suggesting that spatial relationships between these populations within the TME contributes to sensitivity to NACT. The lack of association between TILs and pCR in our cohort by standard H&amp;E is likely due to small numbers; however, significance was seen by qmIF, indicating this method as a potentially more sensitive approach to this analysis. Analysis of RNA signatures by NanoString BC360 panel did not reveal signatures associated with pCR . While our study demonstrates the feasibility of this approach to TME evaluation, further studies of larger cohorts are needed to validate markers predictive of response to NACT. Citation Format: Matthew Ryan Kearney, Rami Vanguri, Qi Wang, Kathleen Fenn, Hua Guo, Douglas Marks, Hanina Hibshoosh, Kevin M Kalinsky, Eileen Connolly. Characterization of the tumor microenvironment in patients with hormone receptor positive, HER2 negative early breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-07-09.

Abstract P5-06-14: A novel combination of a 2 gene score &amp; TIL as a predictive Biomarker for responders to novel therapies in Indian TNBC - A population with greater proportion of TNBCs

Abstract Introduction: Triple-Negative Breast Cancer (TNBC) comprises approximately 30% of all breast cancers in Indian women. Given their aggressive nature, TNBCs have high rates of systemic metastasis and mortality with only chemotherapy available for treatment. Compelling evidence has demonstrated the prognostic value of tumor-infiltrating lymphocytes (TILs), in many cancers especially in Breast Cancer and play a critical role in tumour progression, response to therapeutics and prognosis. They are typically measured by H&amp;E staining and immunohistochemistry for research purpose and degree of infiltrate is also known to differ among subtypes. Nonetheless, the literature regarding the types of immune cells characterizing TILs and their prognostic utility in TNBC has been conflicting for lack of accurate “functional” TIL assessments. Herein we have used a combination signature of TILs and a 2 gene immune function expression based signature to develop an unique classifier, to identify a subgroup within TNBC that has better clinical outcome, such as survival and response to treatment. Our findings also suggest a possible use of the score as a predictive biomarker for response to immune checkpoint therapy Patients and Methods: Surgically excised TNBC tumor specimens from 44 women from a single treating hospital in Bangalore, India were accessed under IERB approved protocols and assayed on nCounter® PanCancer Immune Profiling Panel which comprised of 740 genes and characterises 14 different immune cell types. Analysis using Non-negative Matrix factorization (NMF) based unsupervised clustering was done to arrive at stable subtypes characterized by different tumor microenvironments within TNBC. SSGSEA analysis was done to identify immune cell types. TILs were characterised by a pathologist on H&amp;E sections according to guidelines from TIL working group. The Immune classifier was validated on Breast Cancer data sets from TCGA. Results: NMF followed by SAM and PAM analysis yielded 2 stable subtypes (ST1 and ST2) of proportions 59% and 41% respectively. TIL groups also were divided into Dense and Mild groups which were 52% and 48% respectively. Despite similar distributions of the groups, ST1 and ST2 had distinct survival with ST2 having poorer outcome (p=0.023) while the dense and mild TIL groups did not separate as distinct groups. On a closer examination using SSGSEA analysis with Rooney et al signature, ST1 was enriched with T-cells, Dendritic cells, MHC-class 1 and very significantly high cytolytic score (CYT), which was defined by Granzyme A and Perforin expressions, proteins secreted by cytotoxic T cells (p=0.0074). The CYT Score ranged from -35 to 170 and cutoff was based on 75th percentile. We next hypothesized that a combined score of TIL and CYT would represent a functional TIL group with high immune activity. We arrived at a CYT+TIL score based on 75th percentile cut off of CYT and 2 groups of TIL. Of the resultant four groups, TIL High-CYT high that constituted about 20% of all TNBCs indicated an elevated immune response because of their microenvironment constitution and this can be identified using our simple immune classifier. On the other hand, in the TIL-high and CYT-low group, despite lymphocyte migration, outcome was not favorable. The classifier was applied to TNBC from TCGA (n=96) and similar results seen, with ST1 and ST2 which had distinctly separate survival and had similar patterns on CYT high groups. Conclusion: We developed a simple immune classifier with 2 gene signature c and H&amp;E slide TIL assessment for identifying a group with TNBC that can be better targeted with therapies. Our signature is predictive for selecting TNBCs which are potential responders to Immune therapies and has the potential for quick clinical adoption though it requires validation on a larger set. Citation Format: Aruna Korlimarla, Hari PS, Jyothi S Prabhu, Chantirika Ragulan, Ravi B Diwakar, Sandhya Apachu, Maggie Cheang, Rekha V Kumar, BS Srinath, TS Sridhar, Savitha Rajarajan, Annie Alexander, Anguraj Sadanandam. A novel combination of a 2 gene score &amp; TIL as a predictive Biomarker for responders to novel therapies in Indian TNBC - A population with greater proportion of TNBCs [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-06-14.

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

BackgroundThe 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).MethodsA 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.ResultsThe 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).ConclusionThe 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.

Prognostic value of immune factors in the tumor microenvironment of patients with pancreatic ductal adenocarcinoma

BackgroundBoth activated tumor-infiltrating lymphocytes (TILs) and immune-suppressive cells, such as regulatory T cells (Tregs), in the tumor microenvironment (TME) play an important role in the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).MethodsThe densities of TILs, programmed death receptor 1 (PD-1) + T cells, and forkhead box P3 (Foxp3) + T cells were analyzed by immunohistochemical staining. The associations of the immunological status of the PDAC microenvironment with overall survival (OS) time and disease-free survival (DFS) time were evaluated.ResultsPDAC patients with a high density of TILs in the TME or PD-1-positive T cells in tertiary lymphoid aggregates (TLAs) demonstrated a significantly better prognosis than those with a low density of TILs or PD-1-negativity, respectively. Moreover, PDAC patients with high levels of Foxp3-expressing T cells showed a worse prognosis than those with low levels of Foxp3-expressing T cells. Importantly, even with a high density of the TILs in TME or PD-1-positive T cells in TLAs, PDAC patients with high levels of Foxp3-expressing T cells showed a worse prognosis than patients with low levels of Foxp3-expressing T cells. A PDAC TME with a high density of TILs/high PD-1 positivity/low Foxp3 expression was an independent predictive marker associated with superior prognosis.ConclusionCombined assessment of TILs, PD-1+ cells, and Foxp3+ T cells in the TME may predict the prognosis of PDAC patients following surgical resection.