Evaluation of the Predictive Role of Tumor Immune Infiltrate in Patients with HER2-Positive Breast Cancer Treated with Neoadjuvant Anti-HER2 Therapy without Chemotherapy

A nomogram to predict the pathological complete response in patients with breast cancer based on the TILs-US score

BACKGROUND

The tumor-infiltrating lymphocytes-ultrasonography score is a calculation system for predicting lymphocyte-predominant breast cancers in surgical specimens. A nomogram based on the tumor-infiltrating lymphocytes-ultrasonography score was developed to predict the pathological complete response in breast cancer treated with neoadjuvant chemotherapy.

METHODS

A retrospective evaluation was conducted on 118 patients with breast cancer treated with neoadjuvant chemotherapy at Hiroshima University Hospital. Tumor-infiltrating lymphocytes-ultrasonography scores ≥4 were classified as high. A nomogram was developed using a stepwise logistic regression model for pathological complete response (ypT0 ypN0), based on the smallest Akaike information criterion. The predictive ability and clinical usefulness of the nomogram were also evaluated.

RESULTS

Among 118 patients, 34 (28.8%) achieved a pathological complete response, and 52 (44.1%) exhibited high tumor-infiltrating lymphocytes-ultrasonography. In multivariate logistic regression analysis, high tumor-infiltrating lymphocytes-ultrasonography (odds ratio, 6.01; P < 0.001), clinical complete response (odds ratio, 4.83; P = 0.004) and hormone receptor (odds ratio, 3.48; P = 0.038) were independent predictors of pathological complete response. A nomogram based on tumor-infiltrating lymphocytes-ultrasonography score, clinical complete response, hormone receptor and clinical N status was developed. The nomogram showed an area under the curve of 0.831 and a bias-corrected area under the curve of 0.809. The calibration plot showed a good fit between the expected and actual pathological complete response values. Decision curve analysis also showed the clinical utility of the nomogram for predicting pathological complete responses.

CONCLUSIONS

A nomogram based on the tumor-infiltrating lymphocytes-ultrasonography score exhibited a favorable predictive ability for pathological complete response in patients with breast cancer, which can be useful in predicting the residual disease status after neoadjuvant chemotherapy.

The association of PD-L1 expression and CD8-positive T cell infiltration rate with the pathological complete response after neoadjuvant treatment in HER2-positive breast cancer

PURPOSE

Achieving a pathological complete response (pCR) after neoadjuvant therapy in HER2-positive breast cancer patients is the most significant prognostic indicator, suggesting a low risk of recurrence and a survival advantage. This study aims to investigate clinicopathological parameters that can predict the response to neoadjuvant treatment in HER2 + breast cancers and to explore the roles of tumour-infiltrating lymphocytes (TILs), CD8 + T lymphocytes and PD-L1 expression.

METHODS

This single-centre retrospective study was conducted with 85 HER2-positive breast cancer patients who underwent surgery after receiving neoadjuvant therapy between January 2017 and January 2020. Paraffin blocks from these patients were selected for immunohistochemical studies.

RESULTS

A complete pathological response to neoadjuvant treatment was determined in 39 (45.9%) patients. High Ki-67 index (> 30%), moderate to high TIL infiltration, PD-L1 positivity and high CD8 cell count (≥ 25) were significantly associated with pCR in univariate analyses (p: 0.023, 0.025, 0.017 and 0.003, respectively). Multivariate regression analysis identified high Ki-67 index (> 30%) and CD8 cell infiltration as independent predictors for pCR in HER2-positive breast cancer.

CONCLUSIONS

High Ki-67 index, and high CD8 cell count are strong predictors for pCR in HER2-positive breast cancer. Tumours with high Ki-67 index, high TILs and CD8 infiltration may represent a subgroup where standard therapies are adequate. Conversely, those with low TILs and CD8 infiltration may identify a subgroup where use of novel strategies, including those that increase CD8 infiltration could be applied.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Phase II Trial Assessing the Repeatability and Tumor Uptake of [68Ga]Ga-HER2 Single-Domain Antibody PET/CT in Patients with Breast Carcinoma

Human epidermal growth factor receptor 2 (HER2) status is used for decision-making in breast carcinoma treatment. The status is obtained through immunohistochemistry or in situ hybridization. These two methods have the disadvantage of necessitating tissue sampling, which is prone to error due to tumor heterogeneity or interobserver variability. Whole-body imaging might be a solution to map HER2 expression throughout the body. Methods: Twenty patients with locally advanced or metastatic breast carcinoma (5 HER2-positive and 15 HER2-negative patients) were included in this phase II trial to assess the repeatability of uptake quantification and the extended safety of the [68Ga]Ga-NOTA-anti-HER2 single-domain antibody (sdAb). The tracer was injected, followed by a PET/CT scan at 90 min. Within 8 d, the procedure was repeated. Blood samples were taken for antidrug antibody (ADA) assessment and liquid biopsies. On available tissues, immunohistochemistry, in situ hybridization, and mass spectrometry were performed to determine the correlation of HER2 status with uptake values measured on PET. If relevant preexisting [18F]FDG PET/CT images were available (performed as standard of care), a comparison was made. Results: With a repeatability coefficient of 21.8%, this imaging technique was repeatable. No clear correlation between PET/CT uptake values and pathology could be established, as even patients with low levels of HER2 expression showed moderate to high uptake. Comparison with [18F]FDG PET/CT in 16 patients demonstrated that in 7 patients, [68Ga]Ga-NOTA-anti-HER2 shows interlesional heterogeneity within the same patient, and [18F]FDG uptake did not show the same heterogeneous uptake in all patients. In some patients, the extent of disease was clearer with the [68Ga]Ga-NOTA-anti-HER2-sdAb. Sixteen adverse events were reported but all without a clear relationship to the tracer. Three patients with preexisting ADAs did not show adverse reactions. No new ADAs developed. Conclusion: [68Ga]Ga-NOTA-anti-HER2-sdAb PET/CT imaging shows similar repeatability to [18F]FDG. It is safe for clinical use. There is tracer uptake in cancer lesions, even in patients previously determined to be HER2-low or -negative. The tracer shows potential in the assessment of interlesional heterogeneity of HER2 expression. In a subset of patients, [68Ga]Ga-NOTA-anti-HER2-sdAb uptake was seen in lesions with no or low [18F]FDG uptake. These findings support further clinical development of [68Ga]Ga-NOTA-anti-HER2-sdAb as a PET/CT tracer in breast cancer patients.

Unveiling the Immune Microenvironment's Role in Breast Cancer: A Glimpse into Promising Frontiers

Breast cancer (BC), one of the most widespread and devastating diseases affecting women worldwide, presents a significant public health challenge. This review explores the emerging frontiers of research focused on deciphering the intricate interplay between BC cells and the immune microenvironment. Understanding the role of the immune system in BC is critical as it holds promise for novel therapeutic approaches and precision medicine strategies. This review delves into the current literature regarding the immune microenvironment's contribution to BC initiation, progression, and metastasis. It examines the complex mechanisms by which BC cells interact with various immune cell populations, including tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs). Furthermore, this review highlights the impact of immune-related factors, such as cytokines and immune checkpoint molecules. Additionally, this comprehensive analysis sheds light on the potential biomarkers associated with the immune response in BC, enabling early diagnosis and prognostic assessment. The therapeutic implications of targeting the immune microenvironment are also explored, encompassing immunotherapeutic strategies and combination therapies to enhance treatment efficacy. The significance of this review lies in its potential to pave the way for novel therapeutic interventions, providing clinicians and researchers with essential knowledge to design targeted and personalized treatment regimens for BC patients.

B-cells and regulatory T-cells in the microenvironment of HER2+ breast cancer are associated with decreased survival: a real-world analysis of women with HER2+ metastatic breast cancer

BACKGROUND

Despite major improvements in treatment of HER2-positive metastatic breast cancer (MBC), only few patients achieve complete remission and remain progression free for a prolonged time. The tumor immune microenvironment plays an important role in the response to treatment in HER2-positive breast cancer and could contain valuable prognostic information. Detailed information on the cancer-immune cell interactions in HER2-positive MBC is however still lacking. By characterizing the tumor immune microenvironment in patients with HER2-positive MBC, we aimed to get a better understanding why overall survival (OS) differs so widely and which alternative treatment approaches may improve outcome.

METHODS

We included all patients with HER2-positive MBC who were treated with trastuzumab-based palliative therapy in the Netherlands Cancer Institute between 2000 and 2014 and for whom pre-treatment tissue from the primary tumor or from metastases was available. Infiltrating immune cells and their spatial relationships to one another and to tumor cells were characterized by immunohistochemistry and multiplex immunofluorescence. We also evaluated immune signatures and other key pathways using next-generation RNA-sequencing data. With nine years median follow-up from initial diagnosis of MBC, we investigated the association between tumor and immune characteristics and outcome.

RESULTS

A total of 124 patients with 147 samples were included and evaluated. The different technologies showed high correlations between each other. T-cells were less prevalent in metastases compared to primary tumors, whereas B-cells and regulatory T-cells (Tregs) were comparable between primary tumors and metastases. Stromal tumor-infiltrating lymphocytes in general were not associated with OS. The infiltration of B-cells and Tregs in the primary tumor was associated with unfavorable OS. Four signatures classifying the extracellular matrix of primary tumors showed differential survival in the population as a whole.

CONCLUSIONS

In a real-world cohort of 124 patients with HER2-positive MBC, B-cells, and Tregs in primary tumors are associated with unfavorable survival. With this paper, we provide a comprehensive insight in the tumor immune microenvironment that could guide further research into development of novel immunomodulatory strategies.

Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments

The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then generate melanoma histocytometry whole slide images and verify that CISA can detect similar interactions across data modalities. Interestingly, CISA histoctyometry analysis also reveals that T-cell:macrophage synapse formation is associated with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.

B Cells in Breast Cancer Pathology

B cells have recently become a focus in breast cancer pathology due to their influence on tumour regression, prognosis, and response to treatment, besides their contribution to antigen presentation, immunoglobulin production, and regulation of adaptive responses. As our understanding of diverse B cell subsets in eliciting both pro- and anti-inflammatory responses in breast cancer patients increases, it has become pertinent to address the molecular and clinical relevance of these immune cell populations within the tumour microenvironment (TME). At the primary tumour site, B cells are either found spatially dispersed or aggregated in so-called tertiary lymphoid structures (TLS). In axillary lymph nodes (LNs), B cell populations, amongst a plethora of activities, undergo germinal centre reactions to ensure humoral immunity. With the recent approval for the addition of immunotherapeutic drugs as a treatment option in the early and metastatic settings for triple-negative breast cancer (TNBC) patients, B cell populations or TLS may resemble valuable biomarkers for immunotherapy responses in certain breast cancer subgroups. New technologies such as spatially defined sequencing techniques, multiplex imaging, and digital technologies have further deciphered the diversity of B cells and the morphological structures in which they appear in the tumour and LNs. Thus, in this review, we comprehensively summarise the current knowledge of B cells in breast cancer. In addition, we provide a user-friendly single-cell RNA-sequencing platform, called "B singLe cEll rna-Seq browSer" (BLESS) platform, with a focus on the B cells in breast cancer patients to interrogate the latest publicly available single-cell RNA-sequencing data collected from diverse breast cancer studies. Finally, we explore their clinical relevance as biomarkers or molecular targets for future interventions.

Tumor-Infiltrating Lymphocytes and Immune Response in HER2-Positive Breast Cancer

Human epidermal growth factor receptor 2-positive (HER2-positive) breast cancer accounts for 15 to 25% of breast cancer cases. Although therapies based on the use of monoclonal anti-HER2 antibodies present clinical benefit for a subtype of patients with HER2-positive breast cancer, more than 50% of them are unresponsive to targeted therapies or they eventually relapse. In recent years, reactivation of the adaptive immune system in patients with solid tumors has emerged as a therapeutic option with great potential for clinical benefit. Since the approval of the first treatment directed against HER2 as a therapeutic target, the range of clinical options has expanded greatly, and, in this sense, cellular immunotherapy with T cells relies on the cytotoxicity generated by these cells, which ultimately leads to antitumor activity. Lymphocytic infiltration of tumors encompasses a heterogeneous population of immune cells within the tumor microenvironment that exhibits distinct patterns of immune activation and exhaustion. The prevalence and prognostic value of tumor-infiltrating lymphocyte (TIL) counts are associated with a favorable prognosis in HER2-positive breast cancers. This review discusses emerging findings that contribute to a better understanding of the role of immune infiltrates in HER2-positive breast cancer. In addition, it summarizes the most recent results in HER2-positive breast cancer immunotherapy and anticipates which therapeutic strategies could be applied in the immediate future.

Matrix stiffness-dependent STEAP3 coordinated with PD-L2 identify tumor responding to sorafenib treatment in hepatocellular carcinoma

BACKGROUND

Ferroptosis have been implicated in tumorigenesis, tumor progression, and chemo- and immuno-therapy in cirrhotic hepatocellular carcinoma (HCC), indicating its association with matrix stiffness and clinical benefit of targeting drugs or immune checkpoint inhibitor. Here, we postulated that increased matrix stiffness reduces ferroptosis and impairs tumor immunity by regulating the expression of ferroptosis- and immune-related genes in HCC, which might be a robust predictor of therapeutic efficacy.

METHODS

Using publicly available tissue microarray datasets, liver cancer rat model, and clinical specimen, ferroptosis-related differential genes in HCV-infected cirrhotic HCC and its mechanical heterogeneous pattern of expression were screened and identified. Further investigation on the underlying mechanism of matrix stiffness-regulated ferroptosis and the expression of immune mediator were performed. Finally, threshold analysis of HCC cases with sorafenib treatment revealed the value of clinical applications of these potential predictors.

RESULTS

STEAP3 was identified as the ferroptosis-related differential genes in HCV-infected cirrhotic HCC. Stiffer matrix decreased STEAP3 in the invasive front area of HCC and the liver cirrhotic tissue. Contrarily, softer matrix induced STEAP3 in the central area of HCC and the normal liver tissue. Immunological correlation of STEAP3 in cirrhotic HCC showed that STEAP3-mediated immune infiltration of CD4+ T and CD8+ T cells, macrophages, neutrophils, and dendritic cells and HCC prognosis, predicting to regulate immune infiltration. Overexpression of STEAP3 induced ferroptosis and inhibited the expression of immune mediator of PD-L2 on a stiff matrix. Especially, the ferroptosis- and immune-related gene predictive biomarker (FIGPB), including STEAP3 and PD-L2, predicts better clinical benefit of sorafenib in HCC patients.

CONCLUSIONS

This finding identifies matrix stiffness impairs ferroptosis and anti-tumor immunity by mediating STEAP3 and PD-L2. More importantly, coordinated with PD-L2, matrix stiffness-dependent STEAP3 could be applied as the independent predictors to favorable sorafenib response, and thus targeting it could be a potential diagnosis and treatment strategy for HCC.

Multiplexed In Situ Spatial Protein Profiling in the Pursuit of Precision Immuno-Oncology for Patients with Breast Cancer

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many solid tumors. In breast cancer (BC), immunotherapy is currently approved in combination with chemotherapy, albeit only in triple-negative breast cancer. Unfortunately, most patients only derive limited benefit from ICIs, progressing either upfront or after an initial response. Therapeutics must engage with a heterogeneous network of complex stromal-cancer interactions that can fail at imposing cancer immune control in multiple domains, such as in the genomic, epigenomic, transcriptomic, proteomic, and metabolomic domains. To overcome these types of heterogeneous resistance phenotypes, several combinatorial strategies are underway. Still, they can be predicted to be effective only in the subgroups of patients in which those specific resistance mechanisms are effectively in place. As single biomarker predictive performances are necessarily suboptimal at capturing the complexity of this articulate network, precision immune-oncology calls for multi-omics tumor microenvironment profiling in order to identify unique predictive patterns and to proactively tailor combinatorial treatments. Multiplexed single-cell spatially resolved tissue analysis, through precise epitope colocalization, allows one to infer cellular functional states in view of their spatial organization. In this review, we discuss-through the lens of the cancer-immunity cycle-selected, established, and emerging markers that may be evaluated in multiplexed spatial protein panels to help identify prognostic and predictive patterns in BC.

Neoadjuvant Trastuzumab and Pyrotinib for Locally Advanced HER2-Positive Breast Cancer (NeoATP): Primary Analysis of a Phase II Study

PURPOSE

Despite accumulating evidence on dual blockade of human epidermal growth factor receptor 2 (HER2) for locally advanced HER2-positive breast cancer, no robust evidence supports the addition of pyrotinib to trastuzumab in the neoadjuvant setting. The NeoATP trial aimed to evaluate the efficacy and safety of pyrotinib with neoadjuvant trastuzumab and chemotherapy.

METHODS

The phase II NeoATP trial included female patients with histologically confirmed stage IIA-IIIC and HER2-positive primary invasive breast cancer. Eligible patients received pyrotinib and trastuzumab with weekly paclitaxel-cisplatin neoadjuvant chemotherapy for four cycles. The primary endpoint was pathological complete response (pCR; ypT0 ypN0) rate. Key secondary endpoints included locoregional pCR (ypT0/is ypN0) rate, biomarker analysis and safety.

RESULTS

Among 53 enrolled patients (median age, 47 years; 73.58% stage III), 52 completed the study treatment and surgery. Overall, 37 patients (69.81%) achieved pCR. For women with hormone receptor negative and positive tumors, the pCR rates were 85.71% and 59.38% (P = 0.041), while the corresponding rates were 69.23% and 70.00% respectively for those with and without PIK3CA mutation (P = 0.958). The most frequently reported grade 3 to 4 adverse events were diarrhea (45.28%), leukopenia (39.62%) and neutropenia (32.08%). No deaths occurred, and no left ventricular ejection fraction <50% or >10 points drop from baseline to before surgery was reported.

CONCLUSIONS

The addition of pyrotinib to trastuzumab plus chemotherapy is an efficacious and safe regimen for patients with HER2-positive locally advanced breast cancer in the neoadjuvant setting. The randomized controlled clinical trial is warranted to validate our results.

Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.

Dissecting Tumor-Immune Microenvironment in Breast Cancer at a Spatial and Multiplex Resolution

The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of spatial information and histopathological evaluation of tumor infiltrating lymphocytes exhibits interobserver variability. Towards improved understanding of the complex interactions in TIME, several emerging multiplex in situ methods are being developed and gaining much attention for protein detection. They enable the simultaneous evaluation of multiple targets in situ, detection of cell densities/subpopulations as well as estimations of functional states of immune infiltrate. Furthermore, they can characterize spatial organization of TIME—by cell-to-cell interaction analyses and the evaluation of distribution within different regions of interest and tissue compartments—while digital imaging and image analysis software allow for reproducibility of the various assays. In this review, we aim to provide an overview of the different multiplex in situ methods used in cancer research with special focus on breast cancer TIME at the neoadjuvant, adjuvant and metastatic setting. Spatial heterogeneity of TIME and importance of longitudinal evaluation of TIME changes under the pressure of therapy and metastatic progression are also addressed.

Clinical trial data and emerging strategies: HER2-positive breast cancer

A deeper insight into tumor biology and HER2 signaling has led to the development of novel anti-HER2 drugs that have significantly improved the prognosis of patients with HER2-positive breast cancer. The breast cancer immune microenvironment has emerged as a potential prognostic factor. Moreover, the host immune system not only seems to play a critical role in the prognosis of HER2-positive breast cancer, but also seems to modulate treatment response to some HER2-targeted agents. Here, we review the latest evidence of the role of immunotherapy in HER2-positive breast cancer and present emerging strategies.

The Therapeutic Effectiveness of Neoadjuvant Trastuzumab Plus Chemotherapy for HER2-Positive Breast Cancer Can Be Predicted by Tumor-Infiltrating Lymphocytes and PD-L1 Expression

Introduction

Neoadjuvant trastuzumab plus chemotherapy may affect programmed death-ligand 1 (PD-L1) expression and tumor-infiltrating lymphocytes (TILs) in HER2-positive breast cancer. Discordant results were shown on the correlation between PD-L1 expression or TILs and the effectiveness of neoadjuvant therapy in HER2-positive breast cancer patients. This study aimed to clarify the predictive value of PD-L1 expression and TILs in neoadjuvant therapy in patients with HER2-positive breast cancer.

Methods

HER2-positive breast cancer cases receiving neoadjuvant treatment (NAT; n = 155) were retrospectively collected from July 2013 to November 2018. Histopathologic analysis of TILs was performed on hematoxylin and eosin (H&E)-stained sections from pre- and post-NAT specimens. The TIL score as a categorical variable can be divided into high (≥30%) and low (<30%) categories. The expression of PD-L1 was detected by immunohistochemistry, and the percentage of positive membranous staining (at least 1%) in tumor cells (PD-L1+TC) and TILs (PD-L1+TILs) was scored.

Results

In our study, 87 patients received neoadjuvant chemotherapy alone and 68 received neoadjuvant trastuzumab plus chemotherapy. Multivariate logistic regression analysis confirmed that lymph node metastasis, high TILs, and PD-L1+TILs in pre-neoadjuvant therapy specimens were independent predictors of pathological complete response (pCR) in neoadjuvant therapy (p < 0.05, for all). Among all patients, TILs were increased in breast cancer tissues post-neoadjuvant therapy (p < 0.001). Consistent results were found in the subgroup analysis of the trastuzumab plus chemotherapy group and the chemotherapy alone group (p < 0.05, for both). In 116 non-pCR patients, PD-L1+TC was decreased in breast cancer tissues post-neoadjuvant therapy (p = 0.0219). Consistent results were found in 43 non-pCR patients who received neoadjuvant trastuzumab plus chemotherapy (p = 0.0437). However, in 73 non-pCR patients who received neoadjuvant chemotherapy, there was no significant difference in PD-L1+TC expression in pre- and post-neoadjuvant therapy specimens (p = 0.1465). On the other hand, in the general population, the neoadjuvant trastuzumab plus chemotherapy group, and the neoadjuvant chemotherapy group, PD-L1+TILs decreased after treatment (p < 0.05, for both).

Conclusion

Higher TIL counts and PD-L1+TILs in pre-neoadjuvant therapy specimens and lymph node metastasis are independent predictors of pCR in patients with HER2-positive breast cancer treated with neoadjuvant therapy. TIL counts, PD-L1+TC, and PD-L1+TILs changed before and after neoadjuvant trastuzumab plus chemotherapy for HER2-positive breast cancer, which may suggest that, in HER2-positive breast cancer, neoadjuvant trastuzumab plus chemotherapy may stimulate the antitumor immune effect of the host, thereby preventing tumor immune escape.

Nomogram to Predict Tumor-Infiltrating Lymphocytes in Breast Cancer Patients

Background: Tumor-infiltrating lymphocytes (TILs) play important roles in the prediction of prognosis and neoadjuvant therapy (NAT) efficacy in breast cancer (BRCA) patients, in this study, we identified clinicopathological factors related to BRCA TILs, then to construct and validate nomogram to predict high density of TILs.

Methods: A total of 826 patients diagnosed with BRCA in Sun Yat-Sen University cancer center were enrolled in nomogram cohort. TILs were assessed using hematoxylin-eosin (H&E) staining by two pathologists. Complete clinical data were collected for analysis. Then the enrolled patients were split into a training set and validation set at a ratio of 8:2. and the backward multivariate binary logistic regression model was used to establish nomogram for predicting BRCA TILs, which were further evaluated and validated using the C-index, receiver operating characteristic (ROC) curves and calibration curves. Then another independent NAT cohort of 106 patients was established for verifying this nomogram in NAT efficacy prediction.

Results: TILs were significantly correlated with body mass index (BMI), tumor differentiation, ER, PR, HER2 expression, Ki67, blood biochemical indicators including total bilirubin (TBIL), indirect bilirubin (IBIL), total protein (TP), Globulin (GLOB), inorganic phosphorus (IP), calcium (Ca). In which ER expression level [OR = 0.987, 95%CI (0.982–0.992), p < 0.001], IP [OR = 4.462, 95%CI (1.171∼17.289), p = 0.029], IBIL [OR = 0.906, 95%CI (0.845–0.966), p = 0.004] and TP [OR = 1.053, 95%CI (1.010–1.098, p = 0.016)] were independent predictors of TILs. Then nomogram was established, for which calibration curves (C-index = 0.759) and ROC curve (AUC = 0.759, 95%CI 0.717–0.801) in training sets, calibration curves (C-index = 0.708) and ROC curve (AUC = 0.708, 95%CI 0.617–0.800) in validation sets demonstrated great evaluation efficiency. Besides, independent NAT cohort verified this nomogram can distinguish patients with greater NAT efficacy (p = 0.041).

Conclusion: The finds of clinicopathological factors associated with TILs could help clinicians to understand the tumor immunity of BRCA and improve treatment system for patients, and the established nomogram with high evaluation efficiency may be used as a complement tool for distinguishing patients with better NAT efficacy.

Comparing Biomarkers for Predicting Pathological Responses to Neoadjuvant Therapy in HER2-Positive Breast Cancer: A Systematic Review and Meta-Analysis

INTRODUCTION

The predictive strength and accuracy of some biomarkers for the pathological complete response (pCR) to neoadjuvant therapy for HER2-positive breast cancer remain unclear. This study aimed to compare the accuracy of the HER2-enriched subtype and the presence of PIK3CA mutations, namely, TILs, HRs, and Ki-67, in predicting the pCR to HER2-positive breast cancer therapy.

METHODS

We screened studies that included pCR predicted by one of the following biomarkers: the HER2-enriched subtype and the presence of PIK3CA mutations, TILs, HRs, or Ki-67. We then calculated the pooled sensitivity, specificity, positive and negative predictive values (PPVs and NPVs, respectively), and positive and negative likelihood ratios (LRs). Summary receiver operating characteristic (SROC) curves and areas under the curve (AUCs) were used to estimate the diagnostic accuracy.

RESULTS

The pooled estimates of sensitivity and specificity for the HER2-enriched subtype and the presence of PIK3CA mutations, namely, TILs, HRs, and Ki-67, were 0.66 and 0.62, 0.85 and 0.27, 0.49 and 0.61, 0.54 and 0.64, and 0.68 and 0.51, respectively. The AUC of the HER2-enriched subtype was significantly higher (0.71) than those for the presence of TILs (0.59, p = 0.003), HRs (0.65, p = 0.003), and Ki-67 (0.62, p = 0.005). The AUC of the HER2-enriched subtype had a tendency to be higher than that of the presence of PIK3CA mutations (0.58, p = 0.220). Moreover, it had relatively high PPV (0.58) and LR+ (1.77), similar NPV (0.73), and low LR- (0.54) compared with the other four biomarkers.

CONCLUSIONS

The HER2-enriched subtype has a moderate breast cancer diagnostic accuracy, which is better than those of the presence of PIK3CA mutations, TILs, HRs, and Ki-67.

Biomarkers of immunotherapy response in breast cancer beyond PD-L1

Immune checkpoint inhibitors have modified the treatment algorithm in a variety of cancer types, including breast cancer. Nevertheless, optimal selection of ideal candidates to these drugs remains an unmet need. Although PD-L1 expression by immunohistochemistry seems to be the most promising biomarker to date, its predictive ability is far from ideal. Thus, the development of new predictive biomarkers is essential for a better selection of patients. Here, we discuss potential biomarkers beyond PD-L1 that could play an important role in precision cancer immunotherapy.

Analysis Predictors of the Outcome of Adjuvant of Hormone Therapy on Estrogen Receptor-positive Breast Cancer in Indonesia

BACKGROUND: An existing study reported variation of the outcome of adjuvant hormone therapy on breast cancer. AIM: This study aimed to examine predictors of the hormone therapy to the outcome of recurrence-free survival (RFS) of estrogen receptor-positive (ER+) breast cancer. METHODS: In this cohort study, we followed up 219 eligible breast cancer patients with ER+ who had hormone therapy in 2017–2018. Age of patients, cancer stage, and various histopathology parameters were collected from the medical records, then we followed up with the patients within 2 years (2019–2020) to assess the RFS outcome. Bivariate analysis was conducted to assess the association between the clinicopathology parameters with RFS outcome. Multivariate analysis with logistic regression was also performed to see the dominant predictor. Mediation path analysis was also performed to determine the estimated effect of a predictor on the level of RFS and to see the visualization of the association of predictors with RFS. RESULTS: Breast cancer RFS was 91.3% within 2 years of hormone therapy. The recurrent rate was only 8.7%, which most of them (68.4%) were local. There was no association of age, lymphovascular invasion (LVI), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status with RFS. Based on the molecular subtype, the RFS was better in luminal A (p = 0.045), and also better gradually in the lower stage (p = 0.001). Multivariate analysis shows that the cancer stage was the dominant predictor of the RFS outcome (p = 0.001) with OR = 4.271 (Exp[B] = 1.937–9.417). Mediation analysis also found that there was a positively associated molecular subtype with RFS through cancer stage mediation (r = 16.7%, p = 0.006) but no statistically significant association of age, LVI, PR, and HER2 status (p > 0.005). CONCLUSION: Cancer stage is the main predictor of RFS of hormone therapy outcome. Luminal A is most also likely to have a better outcome of RFS, especially mediated by the lower stage.

Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy

Background

Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients.

Methods

Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR.

Results

The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER⁺PR⁺ and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR.

Conclusion

Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization.

Relationship of the standard uptake value of 18F-FDG-PET-CT with tumor-infiltrating lymphocytes in breast tumors measuring ≥ 1 cm

Evidence suggests that tumor cells and tumor-infiltrating lymphocytes (TILs) compete for glucose in the tumor microenvironment and that tumor metabolic parameters correlate with localized immune markers in several solid tumors. We investigated the relationship of the standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose positron emission tomography computed tomography (¹⁸F-FDG-PET-CT) with stromal TIL levels in breast cancer. We included 202 patients who underwent preoperative ¹⁸F-FDG-PET-CT and had a tumor measuring ≥ 1 cm. Maximum SUV (SUVmax) was determined using ¹⁸F-FDG-PET-CT. Multiple logistic regression was used to identify factors related to high TIL levels (≥ 40%). All tumors were treatment naïve. A significant and weak correlation existed between continuous SUVmax and continuous TIL levels (p = 0.002, R = 0.215). Tumors with high SUVmax (≥ 4) had higher mean TIL levels than those with low SUVmax (< 4). In multivariable analysis, continuous SUVmax was an independent factor associated with high TIL levels; each 1-unit increment in SUVmax corresponded to an odds ratio of 1.14 (95% confidence interval: 1.01–1.29) for high TIL levels. Our study implies that SUV is associated with TILs in breast cancer and provides clinical evidence that elevated glucose uptake by breast tumors can predict the immune system-activated tumor micromilieu.

Immune Infiltrates in Breast Cancer: Recent Updates and Clinical Implications

In recent decades, the increasing interest in the field of immunotherapy has fostered an intense investigation of the breast cancer (BC) immune microenvironment. In this context, tumor-infiltrating lymphocytes (TILs) have emerged as a clinically relevant and highly reproducible biomarker capable of affecting BC prognosis and response to treatment. Indeed, the evaluation of TILs on primary tumors proved to be strongly prognostic in triple-negative (TN) BC patients treated with either adjuvant or neoadjuvant chemotherapy, as well as in early TNBC patients not receiving any systemic treatment, thus gaining level-1b evidence in this setting. In addition, a strong relationship between TILs and pathologic complete response after neoadjuvant chemotherapy has been reported in all BC subtypes and the prognostic role of higher TILs in early HER2-positive breast cancer patients has also been demonstrated. The interest in BC immune infiltrates has been further fueled by the introduction of the first immune checkpoint inhibitors in the treatment armamentarium of advanced TNBC in patients with PD-L1-positive status by FDA-approved assays. However, despite these advances, a biomarker capable of reliably and exhaustively predicting immunotherapy benefit in BC is still lacking, highlighting the imperative need to further deepen this issue. Finally, more comprehensive evaluation of immune infiltrates integrating both the quantity and quality of tumor-infiltrating immune cells and incorporation of TILs in composite scores encompassing other clinically or biologically relevant biomarkers, as well as the adoption of software-based and/or machine learning platforms for a more comprehensive characterization of BC immune infiltrates, are emerging as promising strategies potentially capable of optimizing patient selection and stratification in the research field. In the present review, we summarize available evidence and recent updates on immune infiltrates in BC, focusing on current clinical applications, potential clinical implications and major unresolved issues.

Development of a predictive model utilizing the neutrophil to lymphocyte ratio to predict neoadjuvant chemotherapy efficacy in early breast cancer patients

Neutrophils and lymphocytes are key regulators of breast cancer (BC) development and progression. Neutrophil to lymphocyte ratio (NLR) values have been found to offer clear prognostic utility when evaluating BC patients. In this study, we sought to determine whether BC patient baseline NLR values are correlated with pathological complete response (pCR) following neoadjuvant chemotherapy (NCT) treatment. In total, 346 BC patients underwent NCT at our hospital from January 1, 2014 to October 31, 2019, and data pertaining to these patients were retrospectively analyzed. Correlations between clinicopathological characteristics and pCR rates were assessed via multivariate logistic regression analyses. A predictive scoring model was used to gauge the likelihood of pCR based upon regression coefficient (β) values for each significant variable identified through these analyses. NLR cut-off values suitable for identifying patients likely to achieve pCR following NCT treatment were calculated using receiver operating characteristic (ROC) curves. All patients in the present study were females with a median age of 48 years old (range 22–77). An optimal NLR cut-off value of 1.695 was identified and was associated with respective sensitivity and specificity values of 63.6% and 45.5%. We found that higher NLR values were significantly associated with younger age, premenopausal status, and non-pCR status. Logistic regression analyses indicated that NLR, tumor size, hormone receptor (HR) status, and Ki-67 expression were all independent predictors of pCR. The area under the curve (AUC) for the resultant predictive scoring model was 0.705, and this model was assessed via K-fold cross-validation (k = 10) and bootstrapping validation, yielding respective AUC values of 0.68 and 0.694. Moreover, the incorporation of NLR into this predictive model incrementally improved its overall prognostic value relative to that of a model not incorporating NLR (AUC = 0.674). BC patients with a lower baseline NLR are more likely to exhibit pCR following NCT treatment, indicating that NLR may be a valuable biomarker for BC patient prognostic evaluation and treatment planning. Overall, our results demonstrate that this NLR-based predictive model can efficiently predict NCT efficacy in early BC patients with a high degree of accuracy.

Multiplex immunofluorescence to measure dynamic changes in tumor-infiltrating lymphocytes and PD-L1 in early-stage breast cancer

BACKGROUND

The H&E stromal tumor-infiltrating lymphocyte (sTIL) score and programmed death ligand 1 (PD-L1) SP142 immunohistochemistry assay are prognostic and predictive in early-stage breast cancer, but are operator-dependent and may have insufficient precision to characterize dynamic changes in sTILs/PD-L1 in the context of clinical research. We illustrate how multiplex immunofluorescence (mIF) combined with statistical modeling can be used to precisely estimate dynamic changes in sTIL score, PD-L1 expression, and other immune variables from a single paraffin-embedded slide, thus enabling comprehensive characterization of activity of novel immunotherapy agents.

METHODS

Serial tissue was obtained from a recent clinical trial evaluating loco-regional cytokine delivery as a strategy to promote immune cell infiltration and activation in breast tumors. Pre-treatment biopsies and post-treatment tumor resections were analyzed by mIF (PerkinElmer Vectra) using an antibody panel that characterized tumor cells (cytokeratin-positive), immune cells (CD3, CD8, CD163, FoxP3), and PD-L1 expression. mIF estimates of sTIL score and PD-L1 expression were compared to the H&E/SP142 clinical assays. Hierarchical linear modeling was utilized to compare pre- and post-treatment immune cell expression, account for correlation of time-dependent measurement, variation across high-powered magnification views within each subject, and variation between subjects. Simulation methods (Monte Carlo, bootstrapping) were used to evaluate the impact of model and tissue sample size on statistical power.

RESULTS

mIF estimates of sTIL and PD-L1 expression were strongly correlated with their respective clinical assays (p < .001). Hierarchical linear modeling resulted in more precise estimates of treatment-related increases in sTIL, PD-L1, and other metrics such as CD8+ tumor nest infiltration. Statistical precision was dependent on adequate tissue sampling, with at least 15 high-powered fields recommended per specimen. Compared to conventional t-testing of means, hierarchical linear modeling was associated with substantial reductions in enrollment size required (n = 25➔n = 13) to detect the observed increases in sTIL/PD-L1.

CONCLUSION

mIF is useful for quantifying treatment-related dynamic changes in sTILs/PD-L1 and is concordant with clinical assays, but with greater precision. Hierarchical linear modeling can mitigate the effects of intratumoral heterogeneity on immune cell count estimations, allowing for more efficient detection of treatment-related pharmocodynamic effects in the context of clinical trials.

TRIAL REGISTRATION

NCT02950259 .

Biomarkers for precision immunotherapy in the metastatic setting: hope or reality?

Precision immunotherapy is a crucial approach to improve the efficacy of anti-cancer treatments, particularly in the metastatic setting. In this respect, accurate patient selection takes advantage of the multidimensional integration of patients' clinical information and tumour-specific biomarkers status. Among these biomarkers, programmed death-ligand 1, tumour-infiltrating lymphocytes, microsatellite instability, mismatch repair and tumour mutational burden have been widely investigated. However, novel tumour-specific biomarkers and testing methods will further improve patients' outcomes. Here, we discuss the currently available strategies for the implementation of a precision immunotherapy approach in the clinical management of metastatic solid tumours and highlight future perspectives.

Evaluation of PD-L1, tumor-infiltrating lymphocytes, and CD8+ and FOXP3+ immune cells in HER2-positive breast cancer treated with neoadjuvant therapies

BACKGROUND

The tumor immune microenvironment plays a critical role in the prognosis and outcome of breast cancers. This study examined the role of tumor-infiltrating lymphocytes (TILs), CD8+, FOXP3+ lymphocytes, PD-L1 expression, and other clinicopathological parameters in HER2+ breast cancer and correlate with tumor response to neoadjuvant therapy.

METHODS

We included 173 HER2+ patients treated with neoadjuvant HER2-targeted chemotherapy regimens from 2010 to 2016. 67 cases had biopsy blocks to evaluate TIL, CD8, FOXP3, and PD-L1 immunohistochemistry staining. Tumors were classified as pCR vs non-pCR group. Clinicopathological parameters, TIL, CD8+ and FOXP3+ cell count, and PD-L1 expression were correlated with pCR rate.

RESULTS

Univariate analyses showed that pCR rate was significantly correlated with low PR, low ER, high Ki-67, high FOXP3, HER2 IHC3+ , high HER2 ratio and copy number. By multivariate analysis, Ki-67 was the only variable significantly correlated with pCR. PD-L1 expression was detected in 9.2% cases. TIL hotspot has a non-significant correlation with pCR rate (p = 0.096).

CONCLUSIONS

High Ki-67 is a strong predictor for pCR in HER2+ breast cancer. TIL and FOXP3 T cells may play a role in tumor response in HER2+ cancer. PD-L1 is expressed in a subset of HER2+ breast cancer, supporting a role of immunotherapy in treating a subset of HER2+ breast cancers. The role of PD-L1, TIL, and other markers of immunogenicity as predictors of response to neoadjuvant chemotherapy in HER2+ breast cancer should be further evaluated.

Levels of different subtypes of tumour-infiltrating lymphocytes correlate with each other, with matched circulating lymphocytes, and with survival in breast cancer

Purpose

Breast cancer tumour-infiltrating lymphocytes associate with clinico-pathological factors, including survival, although the literature includes many conflicting findings. Our aim was to assess these associations for key lymphocyte subtypes and in different tumour compartments, to determine whether these provide differential correlations and could, therefore, explain published inconsistencies. Uniquely, we also examine whether infiltrating levels merely reflect systemic lymphocyte levels or whether local factors are predominant in recruitment.

Methods

Immunohistochemistry was used to detect tumour-infiltrating CD20+ (B), CD4+ (helper T), CD8+ (cytotoxic T) and FoxP3+ (regulatory T) cells in breast cancers from 62 patients, with quantification in tumour stroma, tumour cell nests, and tumour margins. Levels were analysed with respect to clinico-pathological characteristics and matched circulating levels (determined by flow-cytometry).

Results

CD4+ lymphocytes were the most prevalent subtype in tumour stroma and at tumour edge and CD8+ lymphocytes were most prevalent in tumour nests; FoxP3+ lymphocytes were rarest in all compartments. High grade or hormone receptor negative tumours generally had significantly increased lymphocytes, especially in tumour stroma. Only intra-tumoural levels of CD8+ lymphocytes correlated significantly with matched circulating levels (p < 0.03), suggesting that recruitment is mainly unrelated to systemic activity. High levels of stromal CD4+ and CD20+ cells associated with improved survival in hormone receptor negative cases (p < 0.04), while tumour nest CD8+ and FoxP3+ cells associated with poor survival in hormone receptor positives (p < 0.005).

Conclusions

Lymphocyte subtype and location define differential impacts on tumour biology, therefore, roles of tumour-infiltrating lymphocytes will only be unravelled through thorough analyses that take this into account.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05757-5) contains supplementary material, which is available to authorized users.

Infiltrating Mast Cell-Mediated Stimulation of Estrogen Receptor Activity in Breast Cancer Cells Promotes the Luminal Phenotype

Tumor growth and development is determined by both cancer cell-autonomous and microenvironmental mechanisms, including the contribution of infiltrating immune cells. Because the role of mast cells (MC) in this process is poorly characterized and even controversial, we investigated their part in breast cancer. Crossing C57BL/6 MMTV-PyMT mice, which spontaneously develop mammary carcinomas, with MC-deficient C57BL/6-Kit^W-sh/W-sh (Wsh) mice, showed that MCs promote tumor growth and prevent the development of basal CK5-positive areas in favor of a luminal gene program. When cocultured with breast cancer cells in vitro, MCs hindered activation of cMET, a master regulator of the basal program, and simultaneously promoted expression and activation of estrogen receptor (ESR1/ER) and its target genes (PGR, KRT8/CK8, BCL2), which are all luminal markers. Moreover, MCs reduced ERBB2/HER2 levels, whose inhibition further increased ESR1 expression. In vivo and in silico analysis of patients with breast cancer revealed a direct correlation between MC density and ESR1 expression. In mice engrafted with HER2-positive breast cancer tumors, coinjection of MCs increased tumor engraftment and outgrowth, supporting the link between MCs and increased risk of relapse in patients with breast cancer. Together, our findings support the notion that MCs influence the phenotype of breast cancer cells by stimulating a luminal phenotype and ultimately modifying the outcome of the disease. SIGNIFICANCE: Mast cells impact breast cancer outcome by directly affecting the phenotype of tumor cells through stimulation of the estrogen receptor pathway.