Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study

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.

Predictive markers for pathological complete response (pCR) after neo-adjuvant chemotherapy in HER2-positive breast carcinoma

OBJECTIVES

Patients with HER2-positive invasive breast cancer that is node-positive and/or larger than 3 cm are generally treated with neoadjuvant chemotherapy (NAC). We aimed to identify predictive markers for pathological complete response (pCR) after NAC in HER2-positive breast carcinoma.

METHODS

Hematoxylin/eosin-stained slides of 43 HER2-positive breast carcinoma biopsies were histopathologically reviewed. Immunohistochemistry (IHC) was performed on pre-NAC biopsies, comprising HER2, estrogen receptor (ER), progesterone receptor (PR), Ki-67, epidermal growth factor receptor (EGFR), mucin-4 (MUC4), p53 and p63. Dual-probe HER2 in situ hybridization (ISH) was performed to study the mean HER2 and CEP17 copy numbers. ISH and IHC data were retrospectively collected for a validation cohort, comprising 33 patients.

RESULTS

Younger age at diagnosis, 3+ HER2 IHC scores, high mean HER2 copy numbers and high mean HER2/CEP17 ratios were significantly associated with an increased chance of achieving a pCR, and the latter two associations were confirmed in the validation cohort. No other immunohistochemical or histopathological markers were associated with pCR.

CONCLUSIONS

This retrospective study of two community-based NAC-treated HER2-positive breast cancer patient cohorts identified high mean HER2 copy numbers as a strong predictor for pCR. Further studies on larger cohorts are required to determine a precise cut-point for this predictive marker.

Circulating blood biomarkers correlated with the prognosis of advanced triple negative breast cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) can improve survivals of metastatic triple negative breast cancer (mTNBC); however, we still seek circulating blood biomarkers to predict the efficacy of ICIs.

MATERIALS AND METHODS

In this study, we analyzed the data of ICIs treated mTNBC collected in Anhui Medical University affiliated hospitals from 2018 to 2023. The counts of lymphocytes, monocytes, platelets, and ratio indexes (NLR, MLR, PLR) in peripheral blood were investigated via the Kaplan-Meier curves and the Cox proportional-hazards model.

RESULTS

The total of 50 mTNBC patients were treated with ICIs. High level of peripheral lymphocytes and low level of NLR and MLR at baseline and post the first cycle of ICIs play the predictable role of immunotherapies. Lymphocytes counts (HR = 0.280; 95% CI: 0.095-0.823; p = 0.021) and NLR (HR = 1.150; 95% CI: 1.052-1.257; p = 0.002) are significantly correlated with overall survival. High NLR also increases the risk of disease progression (HR = 2.189; 95% CI:1.085-4.414; p = 0.029). When NLR at baseline ≥ 2.75, the hazard of death (HR = 2.575; 95% CI:1.217-5.447; p = 0.013) and disease progression (HR = 2.189; 95% CI: 1.085-4.414; p = 0.029) significantly rise. HER-2 expression and anti-tumor therapy lines are statistically correlated with survivals.

CONCLUSIONS

Before the initiation of ICIs, enriched peripheral lymphocytes and poor neutrophils and NLR contribute to the prediction of survivals.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a biomarker in locally advanced unresectable thymic epithelial neoplasm: A single-center, retrospective, longitudinal cohort study

BACKGROUND

Thymic epithelial tumors (TET) are rare malignancies and lack well-defined biomarkers for neoadjuvant therapy. This study aimed to evaluate the clinical utility of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in TET.

METHODS

Patients initially diagnosed with unresectable thymoma or thymic carcinoma who underwent neoadjuvant therapy between January 2004 and December 2021 formed our study population. Hematoxylin and eosin-stained sections from the initial biopsy and surgery were analyzed using an AI-powered spatial TIL analyzer. Intratumoral TIL (iTIL) and stromal TIL (sTIL) were quantified and their immune phenotype (IP) was identified.

RESULTS

Thirty-five patients were included in this study. The proportion of patients with partial response to neoadjuvant therapy was higher in the group with nondesert IP in preneoadjuvant biopsy (63.6% vs. 17.6%, p = 0.038). A significant increase in both iTIL (median 22.18/mm2 vs. 340.69/mm2 , p < 0.001) and sTIL (median 175.19/mm2 vs. 531.02/mm2 , p = 0.004) was observed after neoadjuvant therapy. Patients with higher iTIL (>147/mm2 ) exhibited longer disease-free survival (median, 29 months vs. 12 months, p = 0.009) and overall survival (OS) (median, 62 months vs. 45 months, p = 0.002). Patients with higher sTIL (>232.1/mm2 ) exhibited longer OS (median 62 months vs. 30 months, p = 0.021).

CONCLUSIONS

Nondesert IP in initial biopsy was associated with a better response to neoadjuvant therapy. Increased infiltration of both iTIL and sTIL in surgical specimens were associated with longer OS in patients with TET who underwent resection followed by neoadjuvant therapy.

Assessment of the Tumor-Stroma Ratio and Tumor-Infiltrating Lymphocytes in Colorectal Cancer: Inter-Observer Agreement Evaluation

BACKGROUND

To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers' estimations.

METHODS

Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen's kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. To investigate the association between biomarkers and patient data, Pearson's correlation analysis was applied.

RESULTS

For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35-0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32-0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35-0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032-0.51), p-value = 0.03).

CONCLUSIONS

The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements.

Multiomics technologies for comprehensive tumor microenvironment analysis in triple-negative breast cancer under neoadjuvant chemotherapy

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes and is characterized by abundant infiltrating immune cells within the microenvironment. As standard care, chemotherapy remains the fundamental neoadjuvant treatment in TNBC, and there is increasing evidence that supplementation with immune checkpoint inhibitors may potentiate the therapeutic efficiency of neoadjuvant chemotherapy (NAC). However, 20-60% of TNBC patients still have residual tumor burden after NAC and require additional chemotherapy; therefore, it is critical to understand the dynamic change in the tumor microenvironment (TME) during treatment to help improve the rate of complete pathological response and long-term prognosis. Traditional methods, including immunohistochemistry, bulk tumor sequencing, and flow cytometry, have been applied to elucidate the TME of breast cancer, but the low resolution and throughput may overlook key information. With the development of diverse high-throughput technologies, recent reports have provided new insights into TME alterations during NAC in four fields, including tissue imaging, cytometry, next-generation sequencing, and spatial omics. In this review, we discuss the traditional methods and the latest advances in high-throughput techniques to decipher the TME of TNBC and the prospect of translating these techniques to clinical practice.

ONEST (Observers Needed to Evaluate Subjective Tests) Analysis of Stromal Tumour-Infiltrating Lymphocytes (sTILs) in Breast Cancer and Its Limitations

Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the reliable estimation of inter-observer agreement of TIL categorisation. This has not been explored previously in relation to TILs. ONEST analyses, using an open-source software developed by the first author, were performed on TIL quantification in breast cancers taken from two previous studies. These were one reproducibility study involving 49 breast cancers, 23 in the first circulation and 14 pathologists in the second circulation, and one study involving 100 cases and 9 pathologists. In addition to the estimates of the number of observers required, other factors influencing the results of ONEST were examined. The analyses reveal that between six and nine observers (range 2-11) are most commonly needed to give a robust estimate of reproducibility. In addition, the number and experience of observers, the distribution of values around or away from the extremes, and outliers in the classification also influence the results. Due to the simplicity and the potentially relevant information it may give, we propose ONEST to be a part of new reproducibility analyses.

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.

Recent Advances in Combination of Immunotherapy and Chemoradiotherapy for Locally Advanced Esophageal Squamous Cell Carcinoma

Simple Summary

Neoadjuvant chemoradiotherapy (CRT), followed by surgery or definitive CRT, is the standard treatment for locally advanced esophageal squamous cell carcinoma (ESCC); however, the clinical outcomes remain unsatisfactory. Immunotherapy combined with CRT is currently being investigated as a novel treatment option for locally advanced ESCC. In this review, we discuss the theoretical background and status of immunotherapy for locally advanced ESCC and potential biomarkers for predicting tumor response and prognosis.

Abstract

Esophageal cancer has a high mortality rate and a poor prognosis, with more than one-third of patients receiving a diagnosis of locally advanced cancer. Esophageal squamous cell carcinoma (ESCC) is the dominant histological subtype of esophageal cancer in Asia and Eastern Europe. Although neoadjuvant or definitive chemoradiotherapy (CRT) has been the standard treatment for locally advanced ESCC, patient outcomes remain unsatisfactory, with recurrence rates as high as 30–50%. The combination of immune checkpoint inhibitors (ICIs) and CRT has emerged as a novel strategy to treat esophageal cancer, and it may have a synergistic action and provide greater efficacy. In the phase III CheckMate-577 trial, one year of adjuvant nivolumab after neoadjuvant CRT improved disease-free survival in patients with residual disease on pathology. Moreover, several phase I and II studies have shown that ICIs combined with concurrent CRT may increase the rate of pathologic complete response for resectable ESCC, but they lack long-term follow-up results. In unresectable cases, the combination of camrelizumab and definitive CRT showed promising results against ESCC in a phase Ib trial. Phase III randomized trials are currently ongoing to investigate the survival benefits of ICIs combined with neoadjuvant or definitive CRT, and they will clarify the role of immunotherapy in locally advanced ESCC. Additionally, valid biomarkers to predict tumor response and survival outcomes need to be further explored.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

HER2-low breast cancer shows a lower immune response compared to HER2-negative cases

Currently, the human epidermal growth factor receptor 2 (HER2) status of breast cancer is classified dichotomously as negative or positive to select patients for HER2-targeted therapy. However, with the introduction of novel treatment options, it is important to get more insight in the biology of cancers with low HER2 expression. Therefore, we studied several clinicopathologic characteristics in relation to the level of HER2 expression (HER2- versus HER2low). We used a well-documented cohort of breast cancer patients (n = 529), with available tissue microarrays and Affymetrix mRNA expression data. HER2 status was scored as negative (immunohistochemistry 0) or low (immunohistochemistry 1 + or 2 + without amplification). We associated HER2 status with several clinicopathologic characteristics, gene-expression data and survival, stratified for estrogen receptor (ER) status. Overall, breast cancers were scored as HER2- (n = 429) or HER2low (n = 100). Within the ER+ cohort (n = 305), no significant associations were found between the HER2 groups and clinicopathologic features. However, HER2low tumors showed several differentially expressed genes compared to HER2- cases, including genes that are associated with worse outcome and depletion of immunity. In ER- cases (n = 224), HER2low status was significantly associated with increased regional nodal positivity, lower density of tumor infiltrating lymphocyte and a lower protein expression of Ki-67 and EGFR compared to HER2- cases. After multivariate analysis, only density of tumor infiltrating lymphocytes remained significantly associated with HER2low status (P = 0.035). No difference in survival was observed between HER2low and HER2- patients, neither in the ER+ nor ER- cohort. In conclusion, our data suggests that HER2low breast cancer is associated with a lower immune response compared to HER2- breast cancer.

Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms

Purpose: Validation of artificial intelligence (AI) algorithms in digital pathology with a reference standard is necessary before widespread clinical use, but few examples focus on creating a reference standard based on pathologist annotations. This work assesses the results of a pilot study that collects density estimates of stromal tumor-infiltrating lymphocytes (sTILs) in breast cancer biopsy specimens. This work will inform the creation of a validation dataset for the evaluation of AI algorithms fit for a regulatory purpose. Approach: Collaborators and crowdsourced pathologists contributed glass slides, digital images, and annotations. Here, "annotations" refer to any marks, segmentations, measurements, or labels a pathologist adds to a report, image, region of interest (ROI), or biological feature. Pathologists estimated sTILs density in 640 ROIs from hematoxylin and eosin stained slides of 64 patients via two modalities: an optical light microscope and two digital image viewing platforms. Results: The pilot study generated 7373 sTILs density estimates from 29 pathologists. Analysis of annotations found the variability of density estimates per ROI increases with the mean; the root mean square differences were 4.46, 14.25, and 26.25 as the mean density ranged from 0% to 10%, 11% to 40%, and 41% to 100%, respectively. The pilot study informs three areas of improvement for future work: technical workflows, annotation platforms, and agreement analysis methods. Upgrades to the workflows and platforms will improve operability and increase annotation speed and consistency. Conclusions: Exploratory data analysis demonstrates the need to develop new statistical approaches for agreement. The pilot study dataset and analysis methods are publicly available to allow community feedback. The development and results of the validation dataset will be publicly available to serve as an instructive tool that can be replicated by developers and researchers.

Immunotherapy for triple negative breast cancer: How can pathologic responses to experimental drugs in early-stage disease be enhanced?

INTRODUCTION

: The treatment landscape of early triple negative breast cancer (TNBC) has recently expanded after the Food and Drug Administration (FDA) approval of pembrolizumab in combination with neoadjuvant chemotherapy. The addition of this immune checkpoint inhibitor (ICI) has shown to significantly increased pathological complete response (pCR) rate and event free survival (EFS) in the KEYNOTE-522 phase 3 trial. Several additional studies are ongoing with the goal of further improving outcomes and achieving an optimal integration of ICIs in the treatment of TNBC.

AREAS COVERED

: The article examines pCR and survival rates in TNBC. It appraises clinical trials investigating neoadjuvant ICIs for TNBC and the improvement of pCR rates (biomarker-driven escalation of treatment, optimization of chemotherapy backbone and addition of locoregional treatments or innovative agents). Insights on the role of pCR as surrogate endpoint and the possibility of enhancing pCR rates for women affected by early TNBC are offered.

EXPERT OPINION

: The pharmacopoeia of early TNBC is growing and becoming more heterogeneous with the advent of ICIs; to enhance the clinical benefit of patients, it is necessary to develop response endpoints that consider the mechanism of action of experimental drugs, to optimize patient selection through validated biomarkers, and to compare the most promising treatment strategies in randomized clinical trials.

Interobserver Agreement of PD-L1/SP142 Immunohistochemistry and Tumor-Infiltrating Lymphocytes (TILs) in Distant Metastases of Triple-Negative Breast Cancer: A Proof-of-Concept Study. A Report on Behalf of the International Immuno-Oncology Biomarker Working Group

Patients with advanced triple-negative breast cancer (TNBC) benefit from treatment with atezolizumab, provided that the tumor contains ≥1% of PD-L1/SP142-positive immune cells. Numbers of tumor-infiltrating lymphocytes (TILs) vary strongly according to the anatomic localization of TNBC metastases. We investigated inter-pathologist agreement in the assessment of PD-L1/SP142 immunohistochemistry and TILs. Ten pathologists evaluated PD-L1/SP142 expression in a proficiency test comprising 28 primary TNBCs, as well as PD-L1/SP142 expression and levels of TILs in 49 distant TNBC metastases with various localizations. Interobserver agreement for PD-L1 status (positive vs. negative) was high in the proficiency test: the corresponding scores as percentages showed good agreement with the consensus diagnosis. In TNBC metastases, there was substantial variability in PD-L1 status at the individual patient level. For one in five patients, the chance of treatment was essentially random, with half of the pathologists designating them as positive and half negative. Assessment of PD-L1/SP142 and TILs as percentages in TNBC metastases showed poor and moderate agreement, respectively. Additional training for metastatic TNBC is required to enhance interobserver agreement. Such training, focusing on metastatic specimens, seems worthwhile, since the same pathologists obtained high percentages of concordance (ranging from 93% to 100%) on the PD-L1 status of primary TNBCs.