Prospective validation of immunological infiltrate for prediction of response to neoadjuvant chemotherapy in HER2-negative breast cancer--a substudy of the neoadjuvant GeparQuinto trial

Clinical and radiomics integrated nomogram for preoperative prediction of tumor-infiltrating lymphocytes in patients with triple-negative breast cancer

Objectives

The present study aimed to develop a radiomics nomogram based on conventional ultrasound (CUS) to preoperatively distinguish high tumor-infiltrating lymphocytes (TILs) and low TILs in triple-negative breast cancer (TNBC) patients.

Methods

In the present study, 145 TNBC patients were retrospectively included. Pathological evaluation of TILs in the hematoxylin and eosin sections was set as the gold standard. The patients were randomly allocated into training dataset and validation dataset with a ratio of 7:3. Clinical features (age and CUS features) and radiomics features were collected. Then, the Rad-score model was constructed after the radiomics feature selection. The clinical features model and clinical features plus Rad-score (Clin+RS) model were built using logistic regression analysis. Furthermore, the performance of the models was evaluated by analyzing the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

Results

Univariate analysis and LASSO regression were employed to identify a subset of 25 radiomics features from a pool of 837 radiomics features, followed by the calculation of Rad-score. The Clin+RS integrated model, which combined posterior echo and Rad-score, demonstrated better predictive performance compared to both the Rad-score model and clinical model, achieving AUC values of 0.848 in the training dataset and 0.847 in the validation dataset.

Conclusion

The Clin+RS integrated model, incorporating posterior echo and Rad-score, demonstrated an acceptable preoperative evaluation of the TIL level. The Clin+RS integrated nomogram holds tremendous potential for preoperative individualized prediction of the TIL level in TNBC.

Cellular interactions in tumor microenvironment during breast cancer progression: new frontiers and implications for novel therapeutics

The breast cancer tumor microenvironment (TME) is dynamic, with various immune and non-immune cells interacting to regulate tumor progression and anti-tumor immunity. It is now evident that the cells within the TME significantly contribute to breast cancer progression and resistance to various conventional and newly developed anti-tumor therapies. Both immune and non-immune cells in the TME play critical roles in tumor onset, uncontrolled proliferation, metastasis, immune evasion, and resistance to anti-tumor therapies. Consequently, molecular and cellular components of breast TME have emerged as promising therapeutic targets for developing novel treatments. The breast TME primarily comprises cancer cells, stromal cells, vasculature, and infiltrating immune cells. Currently, numerous clinical trials targeting specific TME components of breast cancer are underway. However, the complexity of the TME and its impact on the evasion of anti-tumor immunity necessitate further research to develop novel and improved breast cancer therapies. The multifaceted nature of breast TME cells arises from their phenotypic and functional plasticity, which endows them with both pro and anti-tumor roles during tumor progression. In this review, we discuss current understanding and recent advances in the pro and anti-tumoral functions of TME cells and their implications for developing safe and effective therapies to control breast cancer progress.

Clinical Relevance of Tumour-Infiltrating Immune Cells in HER2-Negative Breast Cancer Treated with Neoadjuvant Therapy

Currently, therapy response cannot be accurately predicted in HER2-negative breast cancer (BC). Measuring stromal tumour-infiltrating lymphocytes (sTILs) and mediators of the tumour microenvironment and characterizing tumour-infiltrating immune cells (TIICs) may improve treatment response in the neoadjuvant setting. Tumour tissue and peripheral blood samples were retrospectively collected from 118 patients, and sTILs were evaluated. Circulating exosomes and myeloid-derived suppressor cells were determined by flow cytometry. TIICs markers (CD4, CD8, CD20, CD1a, and CD68) were assessed immunohistochemically. High sTILs were significantly associated with pathological complete response (pCR; p = 0.048) and event-free survival (EFS; p = 0.027). High-CD68 cells were significantly associated with pCR in triple-negative (TN, p = 0.027) and high-CD1a cells with EFS in luminal-B (p = 0.012) BC. Cluster analyses of TIICs revealed two groups of tumours (C1 and C2) that had different immune patterns and clinical outcomes. An immunoscore based on clinicopathological variables was developed to identify high risk (C1) or low-risk (C2) patients. Additionally, cluster analyses revealed two groups of tumours for both luminal-B and TNBC. Our findings support the association of sTILs with pCR and show an immunological component in a subset of patients with HER2-negative BC. Our immunoscore may be useful for future escalation or de-escalation treatments.

Initial interactions with the FDA on developing a validation dataset as a medical device development tool

Quantifying tumor-infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment. To reduce this burden, we are preparing a dataset for developers to validate their models and a proposal to the Medical Device Development Tool (MDDT) program in the Center for Devices and Radiological Health of the U.S. Food and Drug Administration (FDA). If the FDA qualifies the dataset for its submitted context of use, model developers can use it in a regulatory submission within the qualified context of use without additional documentation. Our dataset aims at reducing the regulatory burden placed on developers of models that estimate the density of TILs and will allow head-to-head comparison of multiple computational models on the same data. In this paper, we discuss the MDDT preparation and submission process, including the feedback we received from our initial interactions with the FDA and propose how a qualified MDDT validation dataset could be a mechanism for open, fair, and consistent measures of computational model performance. Our experiences will help the community understand what the FDA considers relevant and appropriate (from the perspective of the submitter), at the early stages of the MDDT submission process, for validating stromal TIL density estimation models and other potential computational models. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Artificial intelligence in breast imaging: potentials and challenges

Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, including neoadjuvant chemotherapy, surgery, postoperative chemotherapy, targeted therapy, endocrine therapy, and radiotherapy, are tailored for individual patients. Such personalized therapies have tremendously reduced the threat of breast cancer in females. Furthermore, early imaging screening plays an important role in reducing the treatment cycle and improving breast cancer prognosis. The recent innovative revolution in artificial intelligence (AI) has aided radiologists in the early and accurate diagnosis of breast cancer. In this review, we introduce the necessity of incorporating AI into breast imaging and the applications of AI in mammography, ultrasonography, magnetic resonance imaging, and positron emission tomography/computed tomography based on published articles since 1994. Moreover, the challenges of AI in breast imaging are discussed.

Targeting the Tumor Microenvironment in Breast Cancer: Prognostic and Predictive Significance and Therapeutic Opportunities

Breast cancer is one of the most prevalent tumors among women. Its prognosis and treatment outcomes depend on factors related to tumor cell biology. However, recent studies have revealed the critical role of the tumor microenvironment (TME) in the development, progression, and treatment response of breast cancer. In this review, we explore the different components of the TME and their relevance as prognostic and predictive biomarkers in breast cancer. In addition, techniques for assessing the tumor microenvironment, such as immunohistochemistry or gene expression profiling, and their clinical utility in therapeutic decision-making are examined. Finally, therapeutic strategies targeting the TME are reviewed, highlighting their potential clinical benefits. Overall, this review emphasizes the importance of the TME in breast cancer and its potential as a clinical tool for better patient stratification and the design of personalized therapies.

The Value of Tumor Infiltrating Lymphocytes (TIL) for Predicting the Response to Neoadjuvant Chemotherapy (NAC) in Breast Cancer according to the Molecular Subtypes

INTRODUCTION

The antitumor host immune response is an important factor in breast cancer, but its role is not fully established. The role of tumor infiltrating lymphocytes (TIL) as an immunological biomarker in breast cancer has been significantly explored in recent years. The number of patients treated with neoadjuvant chemotherapy (NAC) has increased and the identification of a biomarker to predict the probability of pCR (pathological complete response) is a high priority.

MATERIALS AND METHODS

We evaluated 334 cases of BC treated with NAC followed by surgical resection from 2020-2022 at the Ist Clinic of Oncological Surgery, Oncological Institute "Prof Dr I Chiricuta" Cluj Napoca. Of the above, 122 cases were available for histological evaluation both in pre-NAC biopsy and post-NAC resection tissue. Evaluation of biopsy fragments and resection parts were performed using hematoxylin eosin (H&E). The TIL evaluation took place according to the recommendations of the International TIL Working Group (ITILWG).

RESULTS

There was a strong association between elevated levels of pre-NAC TIL. At the same time, there is a statistically significant correlation between stromal TIL and tumor grade, the number of lymph node metastases, the molecular subtype and the number of mitoses (p < 0.005). Intratumoral TIL showed a significant correlation with tumor size, distant metastasis, molecular subtype, number of mitosis, stage and lymph node metastasis (p < 0.005). We also demonstrated that high pre-NAC STIL represents a strong predictive marker for pCR.

CONCLUSION

This study reveals the role of TIL as a predictive biomarker in breast cancer not only for the well-established TNBC (triple negative breast cancer) and HER2+ (Her2 overexpressed) subtypes but also in Luminal A and B molecular subtypes. In this scenario, the evaluation of sTIL as a novel predictive and therapy-predicting factor should become a routinely performed analysis that could guide clinicians when choosing the most appropriate therapy.

Relationship between the change in tumour-infiltrating lymphocyte level and residual tumour after neoadjuvant chemotherapy in patients with locally advanced breast cancer

To evaluate the tumour-infiltrating lymphocyte (TIL) rates in breast tissue before and after neoadjuvant chemotherapy (NAC) and their impact on survival, eighty-four patients with locally advanced breast cancer (LABC) were assessed. Pre- and post-NAC TIL levels were determined using biopsy and surgical specimens, respectively. The median TIL rate was significantly different before (17.5%) and after (5%) NAC. Pre- and postoperative Ki-67 index, molecular subtype, pre- and post-NAC TIL concentration, and preoperative residual-cancer-burden TIL were significantly associated with pathological complete response (pCR). Specifically, higher pre-NAC TIL levels were associated with higher pCR rates. Postoperative Ki-67 index and pCR, and postoperative Ki-67 index were significant predictors of disease-free (DFS) and overall survival, respectively. The independent prognostic factors for DFS were postoperative Ki-67 score (hazard ratio [HR]: 6.16; p = 0.012), post-NAC TIL score (HR: 0.42; P = 0.041), and pCR (HR: 0.10; P = 0.038). Our study confirms that higher pre-NAC and lower postoperative TIL levels may be surrogate factors for longer DFS, and postoperative TIL rate may predict post-NAC pCR in patients with LABC.

The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy

The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer

BACKGROUND AND OBJECTIVE

In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artificial intelligence (AI) and immunohistochemistry (IHC)-stained whole-slide images (WSIs) of colorectal cancer (CRC) patients to quantitatively assess the spatial associations between tumor cells and immune cells. To achieve this, we employ the Morisita-Horn ecological index (Mor-index), which allows for a comprehensive analysis of the spatial distribution patterns between tumor cells and immune cells within the TME.

MATERIALS AND METHODS

In this study, we employed a combination of deep learning technology and traditional computer segmentation methods to accurately segment the tumor nuclei, immune nuclei, and stroma nuclei within the tumor regions of IHC-stained WSIs. The Mor-index was used to assess the spatial association between tumor cells and immune cells in TME of CRC patients by obtaining the results of cell nuclei segmentation. A discovery cohort (N = 432) and validation cohort (N = 137) were used to evaluate the prognostic value of the Mor-index for overall survival (OS).

RESULTS

The efficacy of our method was demonstrated through experiments conducted on two datasets comprising a total of 569 patients. Compared to other studies, our method is not only superior to the QuPath tool but also produces better segmentation results with an accuracy of 0.85. Mor-index was quantified automatically by our method. Survival analysis indicated that the higher Mor-index correlated with better OS in the discovery cohorts (HR for high vs. low 0.49, 95% CI 0.27-0.77, P = 0.0014) and validation cohort (0.21, 0.10-0.46, < 0.0001).

CONCLUSION

This study provided a novel AI-based approach to segmenting various nuclei in the TME. The Mor-index can reflect the immune status of CRC patients and is associated with favorable survival. Thus, Mor-index can potentially make a significant role in aiding clinical prognosis and decision-making.

Effect of tumor-infiltrating lymphocytes depending on the presence of postmastectomy radiotherapy on the prognosis in pT1-2N1M0 breast cancer

Background

Currently, it remains unclear regarding the association between tumor-infiltrating lymphocytes (TILs) and the efficacy of postoperative radiotherapy in primary tumors. Here we attempted to investigate the effect of TILs depending on the presence of postmastectomy radiotherapy (PMRT) on the prognosis in pT1-2N1M0 breast cancer.

Methods

The clinical data of pT1-2N1M0 breast cancer patients undergoing mastectomy and axillary lymph node dissection were retrospectively analyzed. The effect of TILs on the prognosis was assessed based on the infiltration degree (low: TILs ≤10%, high: TILs >10%), and then the prognosis of patients with low and high infiltration of TILs was analyzed based on presence or absence of PMRT.

Results

Totally 213 patients were eligible for the study, including 162 cases of low infiltration and 51 of high infiltration. High-infiltration patients tended to be ER/PR-negative, HER2-positive, and have high histological grade. The infiltration in triple-negative and HER2-positive subtypes was higher compared with Luminal A subtype. Regarding local-regional recurrence-free survival, recurrence-free survival, and overall survival (OS) rates, the differences were all inapparent whether in high- and low-infiltration patients or in high-infiltration patients with/without PMRT. Compared with those without PMRT, low-infiltration patients with PMRT showed a significantly increased OS rate (92.8% vs. 80.0%, p=0.023). Multivariate analysis further confirmed PMRT as an independent predicator of OS in low-infiltration patients (HR: 0.228, 95%CI: 0.081-0.644, p=0.005).

Conclusion

High infiltration of TILs in pT1-2N1M0 breast cancer may be associated with clinicopathological factors. Low-infiltration patients, but not high-infiltration patients, may derive survival benefits from PMRT.

Stromal Tumor-Infiltrating Lymphocytes Associated with Immunohistopathology and Molecular Subtypes of Breast Cancer in Vietnam

OBJECTIVE

Breast cancer is a heterogeneous disease with varied symptoms and pathogenesis, as well as variable prognosis and therapeutic outcomes. Stromal tumor-infiltrating lymphocytes, one of the tumor microenvironment factors, has been recognized as an important immunological biomarker that reflected the antitumor immune response in breast cancer.

METHODS

We analyzed 207 invasive breast cancer patients who had lumpectomy or mastectomy and have not received any pre-operative treatment. Clinicopathological characteristics, immunohistochemistry characteristics, molecular subtypes classification and stromal TILs evaluation were investigated.

RESULT

Stromal TILs correlated with well-established prognostic markers. Tumor grade showed significantly higher sTILs percentages in high-grade tumors than in low-grade tumors (p<0.001). There was a statistically significant association between intermediate and high levels of sTILs and a high Ki-67 index (p< 0.001). ER/PR negative was significantly related to high sTILs. Mean sTILs score was significantly higher in TNBC (40.1±31.6%) compared to others, statistically significant (p<0.001). In HER2-negative breast cancer, sTILs were significantly associated with histologic grade, ER status, PR status, and Ki67 index.

CONCLUSION

sTILs played an important role, associated with unfavorable factors in breast cancer. Our findings support the use of stromal sTILs to identify a more aggressive phenotype of tumors.

The prognostic value of tumour-infiltrating lymphocytes, programmed cell death protein-1 and programmed cell death ligand-1 in Stage I-III triple-negative breast cancer

BACKGROUND

Tumour-infiltrating lymphocytes (TILs) represent a robust biological prognostic biomarker in triple-negative breast cancer (TNBC); however, the contribution of different subsets of immune cells is unclear. We investigated the prognostic value of immune markers, including stromal TILs (sTILs), CD8+T and FOPX3+T cells, PD-1 and PD-L1 in non-metastatic TNBC.

METHODS

In total, 259 patients with Stage I-III TNBC were reviewed. The density of sTILs along with the presence of total (t), stromal (s), and intratumoral (i) CD8+T cells and FOPX3+T cells were evaluated by haematoxylin and eosin and immunohistochemical staining. Immunohistochemical staining of PD-1, PD-L1 was also conducted.

RESULTS

All immune markers were positively correlated with each other (P < 0.05). In the multivariate analysis, sTILs (P = 0.046), tCD8+T cells (P = 0.024), iCD8+T cells (P = 0.050) and PD-1 (P = 0.039) were identified as independent prognostic factors for disease-free survival (DFS). Further analysis showed that tCD8+T cells (P = 0.026), iCD8+T cells (P = 0.017) and PD-1 (P = 0.037) increased the prognostic value for DFS beyond that of the classic clinicopathological factors and sTILs.

CONCLUSIONS

In addition to sTILs, inclusion of tCD8+T, iCD8+T cells, or PD-1 may further refine the prognostic model for non-metastatic TNBC beyond that including classical factors alone.

Comprehensive analysis of 33 human cancers reveals clinical implications and immunotherapeutic value of the solute carrier family 35 member A2

Background

Solute carrier family 35 member A2 (SLC35A2), which belongs to the SLC35 solute carrier family of human nucleoside sugar transporters, has shown regulatory roles in various tumors and neoplasms. However, the function of SLC35A2 across human cancers remains to be systematically assessed. Insights into the prediction ability of SLC35A2 in clinical practice and immunotherapy response remains limited.

Materials and methods

We obtained the gene expression and protein levels of SLC35A2 in a variety of tumors from Molecular Taxonomy of Breast Cancer International Consortium, The Cancer Genome Atlas, Gene Expression Omnibus, Chinese Glioma Genome Atlas, and Human Protein Atlas databases. The SLC35A2 level was validated by immunohistochemistry. The predictive value for prognosis was evaluated by Kaplan-Meier survival and Cox regression analyses. Correlations between SLC35A2 expression and DNA methylation, genetic alterations, tumor mutation burden (TMB), microsatellite instability (MSI), and tumor microenvironment were performed using Spearman's correlation analysis. The possible downstream pathways of SLC35A2 in different human cancers were explored using gene set variation analysis. The potential role of SLC35A2 in the tumor immune microenvironment was evaluated via EPIC, CIBERSORT, MCP-counter, CIBERSORT-ABS, quanTIseq, TIMER, and xCell algorithms. The difference in the immunotherapeutic response of SLC35A2 under different expression conditions was evaluated by the tumor immune dysfunction and exclusion (TIDE) score as well as four independent immunotherapy cohorts, which includes patients with bladder urothelial carcinoma (BLCA, N = 299), non-small cell lung cancer (NSCLC, N = 72 and N = 36) and skin cutaneous melanoma (SKCM, N = 25). Potential drugs were identified using the CellMiner database and molecular docking.

Results

SLC35A2 exhibited abnormally high or low expression in 23 cancers and was significantly associated with the prognosis. In various cancers, SLC35A2 expression and mammalian target of rapamycin complex 1 signaling were positively correlated. Multiple algorithmic immune infiltration analyses suggested an inverse relation between SLC35A2 expression and infiltrating immune cells, which includes CD4+T cells, CD8+T cells, B cells, and natural killer cells (NK) in various tumors. Furthermore, SLC35A2 expression was significantly correlated with pan-cancer immune checkpoints, TMB, MSI, and TIDE genes. SLC35A2 showed significant predictive value for the immunotherapy response of patients with diverse cancers. Two drugs, vismodegib and abiraterone, were identified, and the free binding energy of cytochrome P17 with abiraterone was higher than that of SLC35A2 with abiraterone.

Conclusion

Our study revealed that SLC35A2 is upregulated in 20 types of cancer, including lung adenocarcinoma (LUAD), breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), and lung squamous cell carcinoma (LUSC). The upregulated SLC35A2 in five cancer types indicates a poor prognosis. Furthermore, there was a positive correlation between the overexpression of SLC35A2 and reduced lymphocyte infiltration in 13 cancer types, including BRCA and COAD. Based on data from several clinical trials, patients with LUAD, LUSC, SKCM, and BLCA who exhibited high SLC35A2 expression may experience improved immunotherapy response. Therefore, SLC35A2 could be considered a potential predictive biomarker for the prognosis and immunotherapy efficacy of various tumors. Our study provides a theoretical basis for further investigating its prognostic and therapeutic potentials.

Targeting breast cancer stem cells directly to treat refractory breast cancer

For patients with refractory breast cancer (BC), integrative immunotherapies are emerging as a critical component of treatment. However, many patients remain unresponsive to treatment or relapse after a period. Different cells and mediators in the tumor microenvironment (TME) play important roles in the progression of BC, and cancer stem cells (CSCs) are deemed the main cause of relapse. Their characteristics depend on their interactions with their microenvironment as well as on the inducing factors and elements in this environment. Strategies to modulate the immune system in the TME of BC that are aimed at reversing the suppressive networks within it and eradicating residual CSCs are, thus, essential for improving the current therapeutic efficacy of BC. This review focuses on the development of immunoresistance in BCs and discusses the strategies that can modulate the immune system and target breast CSCs directly to treat BC including immunotherapy with immune checkpoint blockades.

Evaluation of triple negative breast cancer with heterogeneous immune infiltration

Introduction

Tumor infiltrating lymphocytes (TILs) are known to be a prognostic and predictive biomarker in breast cancer, particularly in triple negative breast cancer (TNBC) patients. International guidelines have been proposed to evaluate them in the clinical setting as a continuous variable, without a clear defined cut-off. However, there are scenarios where the immune infiltration is heterogeneous that some areas of the patient's tumour have high numbers of TILs while other areas completely lack them. This spontaneous presentation of a heterogeneous immune infiltration could be a great opportunity to study why some tumours present TILs at diagnosis but others do not, while eliminating inter patient's differences.

Methods

In this study, we have identified five TNBC patients that showed great TIL heterogeneity, with areas of low (≤5%) and high (≥50%) numbers of TILs in their surgical specimens. To evaluate immune infiltration heterogeneity, we performed and analyzed bulk RNA-sequencing in three independent triplicates from the high and low TIL areas of each patient.

Results

Gene expression was homogeneous within the triplicates in each area but was remarkable different between TILs regions. These differences were not only due to the presence of TILs as there were other non-inflammatory genes and pathways differentially expressed between the two areas.

Discussion

This highlights the importance of intratumour heterogeneity driving the immune infiltration, and not patient's characteristics like the HLA phenotype, germline DNA or immune repertoire.

Cancer-Associated Fibroblasts and Extracellular Matrix: Therapeutical Strategies for Modulating the Cholangiocarcinoma Microenvironment

During the last decade, immunotherapy has radically changed perspectives on anti-tumor treatments. However, solid tumor treatment by immunotherapy has not met expectations. Indeed, poor clinical response to treatment has highlighted the need to understand and avoid immunotherapy resistance. Cholangiocarcinoma (CCA) is the second cause of hepatic cancer-related deaths because of drug inefficacy and chemo-resistance in a majority of patients. Thus, intense research is ongoing to better understand the mechanisms involved in the chemo-resistance processes. The tumor microenvironment (TME) may be involved in tumor therapy resistance by limiting drug access. Indeed, cells such as cancer-associated fibroblasts (CAFs) alter TME by producing in excess an aberrant extracellular matrix (ECM). Interestingly, CAFs are the dominant stromal component in CCA that secrete large amounts of stiff ECM. Stiff ECM could contribute to immune exclusion by limiting anti-tumor T-cells drop-in. Herein, we summarize features, functions, and interactions among CAFs, tumor-associated ECM, and immune cells in TME. Moreover, we discuss the strategies targeting CAFs and the remodeling of the ECM to improve immunotherapy and drug therapies.

Clinical Significance of Tumour-Infiltrating B Lymphocytes (TIL-Bs) in Breast Cancer: A Systematic Literature Review

Although T lymphocytes have been considered the major players in the tumour microenvironment to induce tumour regression and contribute to anti-tumour immunity, much less is known about the role of tumour-infiltrating B lymphocytes (TIL-Bs) in solid malignancies, particularly in breast cancer, which has been regarded as heterogeneous and much less immunogenic compared to other common tumours like melanoma, colorectal cancer and non-small cell lung cancer. Such paucity of research could translate to limited opportunities for this most common type of cancer in the UK to join the immunotherapy efforts in this era of precision medicine. Here, we provide a systematic literature review assessing the clinical significance of TIL-Bs in breast cancer. Articles published between January 2000 and April 2022 were retrieved via an electronic search of two databases (PubMed and Embase) and screened against pre-specified eligibility criteria. The majority of studies reported favourable prognostic and predictive roles of TIL-Bs, indicating that they could have a profound impact on the clinical outcome of breast cancer. Further studies are, however, needed to better define the functional role of B cell subpopulations and to discover ways to harness this intrinsic mechanism in the fight against breast cancer.

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

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Artificial intelligence reveals features associated with breast cancer neoadjuvant chemotherapy responses from multi-stain histopathologic images

Advances in computational algorithms and tools have made the prediction of cancer patient outcomes using computational pathology feasible. However, predicting clinical outcomes from pre-treatment histopathologic images remains a challenging task, limited by the poor understanding of tumor immune micro-environments. In this study, an automatic, accurate, comprehensive, interpretable, and reproducible whole slide image (WSI) feature extraction pipeline known as, IMage-based Pathological REgistration and Segmentation Statistics (IMPRESS), is described. We used both H&E and multiplex IHC (PD-L1, CD8+, and CD163+) images, investigated whether artificial intelligence (AI)-based algorithms using automatic feature extraction methods can predict neoadjuvant chemotherapy (NAC) outcomes in HER2-positive (HER2+) and triple-negative breast cancer (TNBC) patients. Features are derived from tumor immune micro-environment and clinical data and used to train machine learning models to accurately predict the response to NAC in breast cancer patients (HER2+ AUC = 0.8975; TNBC AUC = 0.7674). The results demonstrate that this method outperforms the results trained from features that were manually generated by pathologists. The developed image features and algorithms were further externally validated by independent cohorts, yielding encouraging results, especially for the HER2+ subtype.

Elevated ADAM-like Decysin-1 (ADAMDEC1) expression is associated with increased chemo-sensitivity and improved prognosis in breast cancer patients

Background

Chemoresistance is problematic and its mechanisms are unclear in breast cancer. More predictive markers are urgently required.

Methods

GSE32646, GSE34138, and GSE20271 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between chemosensitive and chemoresistant tumors. LinkedOmics was used to analyze ADAM-like Decysin-1 (ADAMDEC1) expression among patients with different clinical characteristics and detect co-expression genes for functional analysis. Tumor Immune Estimation Resource (TIMER) and an integrated repository portal for tumor-immune system interactions (TISIDB) were used to investigate the association between the target gene and the immune response. Gene Set Cancer Analysis (GSCA) was utilized to explore the related pathways of ADAMDEC1 and evaluate the correlation between the expression of ADAMDEC1 and drug sensitivity. RNA22, miRWalk, and miRmap were used to predict the upstream micro ribonucleic acids (miRNAs) regulating ADAMDEC1 expression, while DIANA-LncBase v2 was applied to predict the upstream long non-coding ribonucleic acids (lncRNAs). Kaplan-Meier curve analysis was applied to determine the survival time.

Results

We identified that ADAMDEC1 was upregulated among chemosensitive triple-negative breast cancer (TNBC) tissues in GSE32646, GSE34138, and GSE20271. Higher expression of ADAMDEC1 indicated longer survival in breast cancer. Next, we found that ADAMDEC1 was significantly related to the immune response in breast cancer through functional enrichment analysis and further meta-data validation. Moreover, we recognized that hsa-miR-4534 was the potential upstream miRNA regulating ADAMDEC1 expression and Taurine Up-Regulated 1 (TUG1) was the most likely upstream lncRNA of ADAMDEC1 and hsa-miR-4534. Finally, the correlation between ADAMDEC1 and chemosensitivity was confirmed through drug database analysis.

Conclusions

Elevated ADAMDEC1 expression is associated with increased chemosensitivity and better prognosis in breast cancer patients.

Radiomics features for assessing tumor-infiltrating lymphocytes correlate with molecular traits of triple-negative breast cancer

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) have become a promising biomarker for assessing tumor immune microenvironment and predicting immunotherapy response. However, the assessment of TILs relies on invasive pathological slides.

METHODS

We retrospectively extracted radiomics features from magnetic resonance imaging (MRI) to develop a radiomic cohort of triple-negative breast cancer (TNBC) (n = 139), among which 116 patients underwent transcriptomic sequencing. This radiomic cohort was randomly divided into the training cohort (n = 98) and validation cohort (n = 41) to develop radiomic signatures to predict the level of TILs through a non-invasive method. Pathologically evaluated TILs in the H&E sections were set as the gold standard. Elastic net and logistic regression were utilized to perform radiomics feature selection and model training, respectively. Transcriptomics was utilized to infer the detailed composition of the tumor microenvironment and to validate the radiomic signatures.

RESULTS

We selected three radiomics features to develop a TILs-predicting radiomics model, which performed well in the validation cohort (AUC 0.790, 95% confidence interval (CI) 0.638-0.943). Further investigation with transcriptomics verified that tumors with high TILs predicted by radiomics (Rad-TILs) presented activated immune-related pathways, such as antigen processing and presentation, and immune checkpoints pathways. In addition, a hot immune microenvironment, including upregulated T cell infiltration gene signatures, cytokines, costimulators and major histocompatibility complexes (MHCs), as well as more CD8⁺ T cells, follicular helper T cells and memory B cells, was found in high Rad-TILs tumors.

CONCLUSIONS

Our study demonstrated the feasibility of radiomics model in predicting TILs status and provided a method to make the features interpretable, which will pave the way toward precision medicine for TNBC.

Predictive and prognostic values of tumor infiltrating lymphocytes in breast cancers treated with neoadjuvant chemotherapy: A meta-analysis

BACKGROUND

This meta-analysis assessed the predictive and prognostic value of tumor infiltrating lymphocytes (TILs) in neoadjuvant chemotherapy (NACT) treated breast cancer and an optimal threshold for predicting pathologic complete response (pCR).

METHODS

A systematic search of PubMed, EMBASE and Web of Science electronic databases was conducted to identify eligible studies published before April 2022. Either a fixed or random effects model was applied to estimate the pooled hazard ratio (HR) and odds ratio (OR) for prognosis and predictive values of TILs in breast cancer patients treated with NACT. The study is registered with PROSPERO (CRD42020221521).

RESULTS

A total of 29 published studies were eligible. Increased levels of TILs predicted response to NACT in HER2 positive breast cancer (OR = 2.54 95%CI, 1.50-4.29) and triple negative breast cancer (TNBC) (OR = 3.67, 95%CI, 1.93-6.97), but not for hormone receptor (HR) positive breast cancer (OR = 1.68, 95 %CI, 0.67-4.25). A threshold of 20% of H & E-stained TILs was associated with prediction of pCR in both HER2 positive breast cancer (P = 0.035) and TNBC (P = 0.001). Moreover, increased levels of TILs (either iTILs or sTILs) were associated with survival benefit in HER2-positive breast cancer and TNBC. However, an increased level of TILs was not a prognostic factor for survival in HR positive breast cancer (pooled HR = 0.64, 95%CI: 0.03-14.1, P = 0.78).

CONCLUSIONS

Increased levels of TILs were associated with increased rates of response to NACT and improved prognosis for the molecular subtypes of TNBC and HER2-positive breast cancer, but not for patients with HR positive breast cancer. A threshold of 20% TILs was the most powerful outcome prognosticator of pCR.

The tumor-infiltrating lymphocyte ultrasonography score can provide a diagnostic prediction of lymphocyte-predominant breast cancer preoperatively

PURPOSE

Tumor-infiltrating lymphocytes (TILs) are known to predict the therapeutic effect in breast cancer. Although a preoperative tissue biopsy can be used to evaluate TILs, TILs that are heterogeneously distributed might require examination of all preoperative tissue biopsy samples. We have recently reported that the TIL ultrasonography (US) score, as determined by characteristic US findings, provides excellent predictive performance for lymphocyte predominant breast cancer (LPBC). We herein aimed to determine whether the preoperative TIL-US score can more accurately predict LPBC than preoperative tissue biopsy.

METHODS

We assessed 161 patients with invasive breast cancer that were treated with curative surgery between January 2014 and December 2017. Stromal lymphocytes were examined on preoperative tissue biopsy tissues and surgical pathological specimens. Breast cancer samples with ≥ 50% stromal TILs were defined as pre-LPBC (preoperative tissue biopsy) and LPBC (surgical pathological specimens). Useful factors for predicting LPBC were searched among clinicopathological factors.

RESULTS

The TIL-US score cutoff value for predicting LPBC was 4 points based on the receiver operating characteristic curves (area under the curve: 0.88). Several significant predictors for LPBC were revealed by the undertaken multivariate logistic regression analysis (odds ratios: TIL-US score, 26.8; pre-LPBC, 18.6; HER2, 9.2; all, p < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.74, 0.89, 0.85, 0.67, and 0.92 for the TIL-US score, respectively, and 0.51, 0.98, 0.87, 0.91, and 0.86 for the pre-LPBC, respectively.

CONCLUSION

TIL-US scores can predict LPBC preoperatively and are characterized by a significantly high sensitivity and negative predictive value.

Breast cancer vaccines: New insights into immunomodulatory and nano-therapeutic approaches

Breast cancer (BC) is known to be a highly heterogeneous disease that is clinically subdivided into four primary molecular subtypes, each having distinct morphology and clinical implications. These subtypes are principally defined by hormone receptors and other proteins involved (or not involved) in BC development. BC therapeutic vaccines [including peptide-based vaccines, protein-based vaccines, nucleic acid-based vaccines (DNA/RNA vaccines), bacterial/viral-based vaccines, and different immune cell-based vaccines] have emerged as an appealing class of cancer immunotherapeutics when used alone or combined with other immunotherapies. Employing the immune system to eliminate BC cells is a novel therapeutic modality. The benefit of active immunotherapies is that they develop protection against neoplastic tissue and readjust the immune system to an anti-tumor monitoring state. Such immunovaccines have not yet shown effectiveness for BC treatment in clinical trials. In recent years, nanomedicines have opened new windows to increase the effectiveness of vaccinations to treat BC. In this context, some nanoplatforms have been designed to efficiently deliver molecular, cellular, or subcellular vaccines to BC cells, increasing the efficacy and persistence of anti-tumor immunity while minimizing undesirable side effects. Immunostimulatory nano-adjuvants, liposomal-based vaccines, polymeric vaccines, virus-like particles, lipid/calcium/phosphate nanoparticles, chitosan-derived nanostructures, porous silicon microparticles, and selenium nanoparticles are among the newly designed nanostructures that have been used to facilitate antigen internalization and presentation by antigen-presenting cells, increase antigen stability, enhance vaccine antigenicity and remedial effectivity, promote antigen escape from the endosome, improve cytotoxic T lymphocyte responses, and produce humoral immune responses in BC cells. Here, we summarized the existing subtypes of BC and shed light on immunomodulatory and nano-therapeutic strategies for BC vaccination. Finally, we reviewed ongoing clinical trials on BC vaccination and highlighted near-term opportunities for moving forward.

Machine learning models based on immunological genes to predict the response to neoadjuvant therapy in breast cancer patients

Breast cancer (BC) is the most common malignancy worldwide and neoadjuvant therapy (NAT) plays an important role in the treatment of patients with early BC. However, only a subset of BC patients can achieve pathological complete response (pCR) and benefit from NAT. It is therefore necessary to predict the responses to NAT. Although many models to predict the response to NAT based on gene expression determined by the microarray platform have been proposed, their applications in clinical practice are limited due to the data normalization methods during model building and the disadvantages of the microarray platform compared with the RNA-seq platform. In this study, we first reconfirmed the correlation between immune profiles and pCR in an RNA-seq dataset. Then, we employed multiple machine learning algorithms and a model stacking strategy to build an immunological gene based model (Ipredictor model) and an immunological gene and receptor status based model (ICpredictor model) in the RNA-seq dataset. The areas under the receiver operator characteristic curves for the Ipredictor model and ICpredictor models were 0.745 and 0.769 in an independent external test set based on the RNA-seq platform, and were 0.716 and 0.752 in another independent external test set based on the microarray platform. Furthermore, we found that the predictive score of the Ipredictor model was correlated with immune microenvironment and genomic aberration markers. These results demonstrated that the models can accurately predict the response to NAT for BC patients and will contribute to individualized therapy.

Immune Checkpoint Blockade in Hormone Receptor-Positive Breast Cancer: Resistance Mechanisms and Future Perspectives

Anti-programmed cell death protein 1 immunotherapy has been incorporated in the treatment algorithm of triple-negative breast cancer (TNBC). However, clinical trial results for patients with hormone receptor (HR)-positive disease appear less compelling. HR-positive tumors exhibit lower levels of programmed death-ligand 1 expression in comparison with their triple-negative counterparts. Moreover, signaling through estrogen receptor alters the immune microenvironment, rendering such tumors immunologically "cold." To explain differential responses to immune checkpoint blockade, this review interrogates differences between HR-positive and TNBC. Starting from distinct genomic features, we further present disparities concerning the tumor microenvironment and finally, we summarize early-phase clinical trial results on promising novel immunotherapy combinations.

Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update

PURPOSE

To update recommendations on appropriate use of breast cancer biomarker assay results to guide adjuvant endocrine and chemotherapy decisions in early-stage breast cancer.

METHODS

An updated literature search identified randomized clinical trials and prospective-retrospective studies published from January 2016 to October 2021. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert Panel members used informal consensus to develop evidence-based recommendations.

RESULTS

The search identified 24 studies informing the evidence base.

RECOMMENDATIONS

Clinicians may use Oncotype DX, MammaPrint, Breast Cancer Index (BCI), and EndoPredict to guide adjuvant endocrine and chemotherapy in patients who are postmenopausal or age > 50 years with early-stage estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative (ER+ and HER2-) breast cancer that is node-negative or with 1-3 positive nodes. Prosigna and BCI may be used in postmenopausal patients with node-negative ER+ and HER2- breast cancer. In premenopausal patients, clinicians may use Oncotype in patients with node-negative ER+ and HER2- breast cancer. Current data suggest that premenopausal patients with 1-3 positive nodes benefit from chemotherapy regardless of genomic assay result. There are no data on use of genomic tests to guide adjuvant chemotherapy in patients with ≥ 4 positive nodes. Ki67 combined with other parameters or immunohistochemistry 4 score may be used in postmenopausal patients without access to genomic tests to guide adjuvant therapy decisions. BCI may be offered to patients with 0-3 positive nodes who received 5 years of endocrine therapy without evidence of recurrence to guide decisions about extended endocrine therapy. None of the assays are recommended for treatment guidance in individuals with HER2-positive or triple-negative breast cancer. Treatment decisions should also consider disease stage, comorbidities, and patient preferences.Additional information is available at www.asco.org/breast-cancer-guidelines.

A Novel Signature Integrated of Immunoglobulin, Glycosylation and Anti-Viral Genes to Predict Prognosis for Breast Cancer

Background: Aberrant glycosylation is significantly related to the occurrence, progression, metastasis, and drug resistance of tumors. It is essential to identify glycosylation and related genes with prognostic value for breast cancer.

Objective: We aimed to construct and validate a prognostic model based on glycosylation and related genes, and further investigate its prognosis values in validation set and external independent cohorts.

Materials and Methods: The transcriptome and clinical data of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, n = 1072), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1451), and GSE2741 (n = 120). Glycosylation-related genes were downloaded from the Genecards website. Differentially expressed glycosylation-related geneswere identified by comparing the tumor tissues with the adjacent tissues. The TCGA data were randomly divided into training set and validation set in a 1:1 ratio for further analysis. The glycosylation risk-scoring prognosis model was constructed by univariate and multivariate Cox regression analysis, followed by confirmation in TCGA validation, METABRIC, and GEO datasets. Gene set enrichment analysis (GSEA) and Gene ontology analysis for identifying the affected pathways in the high- and low-risk groups were performed.

Results: We attained 1072 breast cancer samples from the TCGA database and 786 glycosylation genes from the Genecards website. A signature contains immunoglobulin, glycosylation and anti-viral related genes was constructed to separate BRCA patients into two risk groups. Low-risk patients had better overall survival than high-risk patients (p < 0.001). A nomogram was constructed with risk scores and clinical characteristics. The area under time-dependent ROC curve reached 0.764 at 1 year, 0.744 at 3 years, and 0.765 at 5 years in the training set. Subgroup analysis showed differences in OS between the high- and low-risk patients in different subgroups. Moreover, the risk score was confirmed as an independent prognostic indicator of BRCA patients and was potentially correlated with immunotherapy response and drug sensitivity.

Conclusion: We identified a novel signature integrated of immunoglobulin (IGHA2), glycosylation-related (SLC35A2) and anti-viral gene (BST2) that was an independent prognostic indicator for BRCA patients. The risk-scoring model could be used for predicting prognosis and immunotherapy in BRCA, thus providing a powerful instrument for combating BRCA.

Prognostic Impact of High Baseline Stromal Tumor-Infiltrating Lymphocytes in the Absence of Pathologic Complete Response in Early-Stage Triple-Negative Breast Cancer

Simple Summary

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with an improved pathologic complete response (pCR) and survival in triple-negative breast cancer (TNBC). We hypothesized that high baseline sTILs would have a favorable prognostic impact in TNBC patients without a pCR. In this study of 318 early-stage TNBC patients in a prospective clinical trial, event-free survival (EFS) in patients without a pCR was not significantly different between those with high sTILs and those with low sTILs (p = 0.7). Therefore, high baseline sTILs do not confer a benefit in EFS in the absence of a pCR. RNA-seq analysis predicted more CD8+ T cells in the high-sTIL group with favorable EFS compared with the high-sTIL group with unfavorable EFS, suggesting the type of lymphocytes within the TIL fraction may be an important parameter to consider for de-escalation strategies. The implications of our findings in the setting of immune checkpoint inhibitor therapy remain to be investigated.

Abstract

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with an improved pathologic complete response (pCR) and survival in triple-negative breast cancer (TNBC). We hypothesized that high baseline sTILs would have a favorable prognostic impact in TNBC patients without a pCR after neoadjuvant chemotherapy (NACT). In this prospective NACT study, pretreatment biopsies from 318 patients with early-stage TNBC were evaluated for sTILs. Recursive partitioning analysis (RPA) was applied to search for the sTIL cutoff best associated with a pCR. With ≥20% sTILs identified as the optimal cutoff, 33% patients had high sTILs (pCR rate 64%) and 67% had low sTILs (pCR rate 29%). Patients were stratified according to the sTIL cutoff (low vs. high) and response to NACT (pCR vs. residual disease (RD)). The primary endpoint was event-free survival (EFS), with hazard ratios calculated using the Cox proportional hazards regression model and the 3-year restricted mean survival time (RMST) as primary measures. Within the high-sTIL group, EFS was better in patients with a pCR compared with those with RD (HR 0.05; 95% CI 0.01–0.39; p = 0.004). The difference in the 3-year RMST for EFS between the two groups was 5.6 months (95% CI 2.3–8.8; p = 0.001). However, among patients with RD, EFS was not significantly different between those with high sTILs and those with low sTILs (p = 0.7). RNA-seq analysis predicted more CD8+ T cells in the high-sTIL group with favorable EFS compared with the high-sTIL group with unfavorable EFS. This study did not demonstrate that high baseline sTILs confer a benefit in EFS in the absence of a pCR.

Differential Survival and Therapy Benefit of Patients with Breast Cancer Are Characterized by Distinct Epithelial and Immune Cell Microenvironments

PURPOSE

Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.

EXPERIMENTAL DESIGN

Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.

RESULTS

This large data set enables us to identify and subsequently validate the cellular composition of microenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.

CONCLUSIONS

From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.

Assessing Tumor-Infiltrating Lymphocytes in Breast Cancer: A Proposal for Combining Immunohistochemistry and Gene Expression Analysis to Refine Scoring

Scoring of tumor-infiltrating lymphocytes (TILs) in breast cancer specimens has gained increasing attention, as TILs have prognostic and predictive value in HER2+ and triple-negative breast cancer. We evaluated the intra- and interrater variability when scoring TILs by visual inspection of hematoxylin and eosin-stained tissue sections. We further addressed whether immunohistochemical staining of these sections for immune cell surface markers CD45, CD3, CD4, and CD8 and combination with nanoString nCounter® gene expression analysis could refine TIL scoring. Formalin-fixed paraffin-embedded and fresh-frozen core needle biopsies of 12 female and treatment-naive breast cancer patients were included. Scoring of TILs was performed twice by three independent pathologists with a washout period of 3 days. Increasing intra- and interrater variability was observed with higher TIL numbers. The highest reproducibility was observed on tissue sections stained for CD3 and CD8. The latter TIL scores correlated well with the TIL scores obtained through nanoString nCounter® gene expression analysis. Gene expression analysis also revealed 104 and 62 genes that are positively and negatively related to both TIL scores. In conclusion, integration of immunohistochemistry and gene expression analysis is a valuable strategy to refine TIL scoring in breast tumors.

Therapeutic vaccines for breast cancer: Has the time finally come?

The ability to exploit the immune system as a weapon against cancer has revolutionised the treatment of cancer patients, especially through immune checkpoint inhibitors (ICIs). However, ICIs demonstrated a modest benefit in treating breast cancer (BC), with the exception of certain subsets of triple-negative BCs. An immune-suppressive tumour microenvironment (TME), typically present in BC, is an important factor in the poor response to immunotherapy.

After almost two decades of poor clinical trial results, cancer vaccines (CVs), an active immunotherapy, have come back in the spotlight because of some technological advancements, ultimately boosted by coronavirus disease 2019 pandemic. In particular, neoantigens are emerging as the preferred targets for CVs, with gene-based and viral vector–based platforms in development. Moreover, lipid nanoparticles proved to be immunogenic and efficient delivery vehicles.

Past clinical trials investigating CVs focused especially on the metastatic disease, where the TME is more likely compromised by inhibitory mechanisms. In this sense, favouring the use of CVs as monotherapy in premalignant or in the adjuvant setting and establishing combination treatments (i.e. CV plus ICI) in late-stage disease are promising strategies. This review provides a full overview of the past and current breast cancer vaccine landscape.

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.

Tumor-Infiltrating Lymphocyctes in Triple-Negative Breast Cancer: Update for 2020

ABSTRACT

Triple-negative breast cancer (TNBC) continues to represent an unmet need because of its significantly poorer outcomes, including higher relapse rates following early-stage disease and dismal survival times in the advanced setting, when compared with other breast cancer subtypes (Cancer 2012;118:5463-5472). Furthermore, there remains a lack of established systemic treatment options beyond conventional cytotoxic chemotherapy, with the exception of PARP inhibitors in the small subset of patients who harbor a BRCA mutation (N Engl J Med 2018;379:753; Lancet Oncol 2020;21:1269-1282; Ann Oncol 2019;30:558-566) and recently the use of immunotherapy in the first-line metastatic setting in those who are programmed death ligand 1-positive (Lancet Oncol 2020;21(1):44-59; N Engl J Med 2018;379(22):2108-2121). Suitable biomarkers for improving prognostication and directing therapy in both the early and advanced TNBC settings are required in order for improvements in survival outcomes to be continued to be attained. Tumor-infiltrating lymphocytes are gaining increasing relevance as an immunological biomarker in this arena.

Intra-Tumour Heterogeneity Is One of the Main Sources of Inter-Observer Variation in Scoring Stromal Tumour Infiltrating Lymphocytes in Triple Negative Breast Cancer

Stromal tumour infiltrating lymphocytes (sTILs) are a strong prognostic marker in triple negative breast cancer (TNBC). Consistency scoring sTILs is good and was excellent when an internet-based scoring aid developed by the TIL-WG was used to score cases in a reproducibility study. This study aimed to evaluate the reproducibility of sTILs assessment using this scoring aid in cases from routine practice and to explore the potential of the tool to overcome variability in scoring. Twenty-three breast pathologists scored sTILs in digitized slides of 49 TNBC biopsies using the scoring aid. Subsequently, fields of view (FOV) from each case were selected by one pathologist and scored by the group using the tool. Inter-observer agreement was good for absolute sTILs (ICC 0.634, 95% CI 0.539-0.735, p < 0.001) but was poor to fair using binary cutpoints. sTILs heterogeneity was the main contributor to disagreement. When pathologists scored the same FOV from each case, inter-observer agreement was excellent for absolute sTILs (ICC 0.798, 95% CI 0.727-0.864, p < 0.001) and good for the 20% (ICC 0.657, 95% CI 0.561-0.756, p < 0.001) and 40% (ICC 0.644, 95% CI 0.546-0.745, p < 0.001) cutpoints. However, there was a wide range of scores for many cases. Reproducibility scoring sTILs is good when the scoring aid is used. Heterogeneity is the main contributor to variance and will need to be overcome for analytic validity to be achieved.

Circulating immune biomarkers in peripheral blood correlate with clinical outcomes in advanced breast cancer

Identification of the different elements intervening at the tumor microenvironment seems key to explain clinical evolution in several tumor types. In this study, a set of immune biomarkers (myeloid derived suppressor cells, regulatory T cells, and OX40 + and PD-1 + T lymphocytes counts) in peripheral blood of patients diagnosed with advanced breast cancer were analyzed along of first line antineoplastic therapy. Subsequently, a comparison between groups with clinical benefit versus progression of disease and with a healthy women cohort was executed. Results reflected that patients showed higher basal levels of myeloid derived suppressor cells (35.43, IR = 180.73 vs 17.53, IR = 16.96 cells/μl; p = 0.001) and regulatory T cells (32.05, IR = 29.84 vs 22.61, IR = 13.57 cells/μl; p = 0.001) in comparison with healthy women. Furthermore, an increase in the number of activated T lymphocytes (expressing OX40), a decrease of immune inhibitory cells (MDSCs and Tregs) and inhibited T lymphocytes (expressing PD-1) were observed along the treatment in patients with clinical benefit (p ≤ 0.001). The opposite trend was observed in the case of disease progression. These findings suggest that some critical immune elements can be easily detected and measured in peripheral blood, which open a new opportunity for translational research, as they seem to be correlated with clinical evolution, at least in ABC.

Tumor-Infiltrating Lymphocytes in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Receiving Neoadjuvant Docetaxel, Carboplatin, Trastuzumab, and Pertuzumab

PURPOSE

The tumor-infiltrating lymphocytes (TILs) expression in breast cancer is a positive prognostic marker for certain breast cancer subtypes. We evaluated the efficacy of dual anti-human epidermal growth factor receptor 2 (HER2) blockade in HER2-positive breast cancer and hypothesized that high TILs tumors are associated with better outcomes.

METHODS

A total of 176 patients who were treated with neoadjuvant docetaxel, carboplatin, trastuzumab, and pertuzumab (TCHP) between December 2015 and December 2018 were reviewed. They were grouped based on a cut-off value of the stromal TILs grade (≤ 20% TILs, > 20% TILs).

RESULTS

In total, 107 patients (60.8%) achieved pathological complete response (pCR). Hormone receptor (HR)-negativity (p = 0.001) and a high TILs grade (p = 0.022) were independent predictors of pCR. Among the HR-negative patients, high TILs tumors were significantly associated with pCR (p = 0.035).

CONCLUSION

HR status and the TILs grade are significantly correlated with pCR in dual anti-HER2 neoadjuvant therapy. The evaluation of the TILs at baseline may be beneficial for predicting pCR in HER2-positive breast cancer.

M2 tumor-associated macrophages play important role in predicting response to neoadjuvant chemotherapy in triple-negative breast carcinoma

PURPOSE

Two types of macrophages are present in tumor microenvironment. M1 macrophages exhibit potent anti-tumor properties, while M2 macrophages play the pro-tumoral roles. The presence of M2 macrophages is associated with worsened overall survival in triple-negative breast carcinoma (TNBC) patients. However, the relationship between M2 macrophages and response to neoadjuvant chemotherapy (NAC) is unknown.

METHODS

M2 macrophages were investigated on biopsy whole sections from 66 TNBCs treated with NAC by CD163 together with other immune checkpoint markers (PD1, PD-L1 and CD8) using a multi-color immunohistochemical multiplex assay.

RESULTS

Incomplete response was significantly associated with older age, lower PD-L1 expression (tumor and stroma), lower levels of CD8-positive TILs in stroma, but higher level of CD163-positive macrophages, with the level of CD163-positive M2 macrophages in peritumoral area as the strongest factor.

CONCLUSIONS

Our data have demonstrated that the level of CD163-positive M2 macrophages was significantly higher in TNBC patients with incomplete response than patients with complete response, suggesting M2 macrophages' important role in predicting TNBC patients' response to NAC.

The Immunology of Hormone Receptor Positive Breast Cancer

Immune checkpoint blockade (ICB) has revolutionized the treatment of cancer patients. The main focus of ICB has been on reinvigorating the adaptive immune response, namely, activating cytotoxic T cells. ICB has demonstrated only modest benefit against advanced breast cancer, as breast tumors typically establish an immune suppressive tumor microenvironment (TME). Triple-negative breast cancer (TNBC) is associated with infiltration of tumor infiltrating lymphocytes (TILs) and patients with TNBC have shown clinical responses to ICB. In contrast, hormone receptor positive (HR+) breast cancer is characterized by low TIL infiltration and minimal response to ICB. Here we review how HR+ breast tumors establish a TME devoid of TILs, have low HLA class I expression, and recruit immune cells, other than T cells, which impact response to therapy. In addition, we review emerging technologies that have been employed to characterize components of the TME to reveal that tumor associated macrophages (TAMs) are abundant in HR+ cancer, are highly immune-suppressive, associated with tumor progression, chemotherapy and ICB-resistance, metastasis and poor survival. We reveal novel therapeutic targets and possible combinations with ICB to enhance anti-tumor immune responses, which may have great potential in HR+ breast cancer.

Progesterone promotes immunomodulation and tumor development in the murine mammary gland

BACKGROUND

Clinical studies have linked usage of progestins (synthetic progesterone [P4]) to breast cancer risk. However, little is understood regarding the role of native P4, signaling through the progesterone receptor (PR), in breast tumor formation. Recently, we reported a link between PR and immune signaling pathways, showing that P4/PR can repress type I interferon signaling pathways. Given these findings, we sought to investigate whether P4/PR drive immunomodulation in the mammary gland and promote tumor formation.

METHODS

To determine the effect of P4 on immune cell populations in the murine mammary gland, mice were treated with P4 or placebo pellets for 21 days. Immune cell populations in the mammary gland, spleen, and inguinal lymph nodes were subsequently analyzed by flow cytometry. To assess the effect of PR overexpression on mammary gland tumor development as well as immune cell populations in the mammary gland, a transgenic mouse model was used in which PR was overexpressed throughout the entire mouse. Immune cell populations were assessed in the mammary glands, spleens, and inguinal lymph nodes of 6-month-old transgenic and control mice by flow cytometry. Transgenic mice were also monitored for mammary gland tumor development over a 2-year time span. Following development of mammary gland tumors, immune cell populations in the tumors and spleens of transgenic and control mice were analyzed by flow cytometry.

RESULTS

We found that mice treated with P4 exhibited changes in the mammary gland indicative of an inhibited immune response compared with placebo-treated mice. Furthermore, transgenic mice with PR overexpression demonstrated decreased numbers of immune cell populations in their mammary glands, lymph nodes, and spleens. On long-term monitoring, we determined that multiparous PR-overexpressing mice developed significantly more mammary gland tumors than control mice. Additionally, tumors from PR-overexpressing mice contained fewer infiltrating immune cells. Finally, RNA sequencing analysis of tumor samples revealed that immune-related gene signatures were lower in tumors from PR-overexpressing mice as compared with control mice.

CONCLUSION

Together, these findings offer a novel mechanism of P4-driven mammary gland tumor development and provide rationale in investigating the usage of antiprogestin therapies to promote immune-mediated elimination of mammary gland tumors.

Is immunotherapy in the future of therapeutic management of sarcomas?

Sarcomas are rare, ubiquitous and heterogeneous tumors usually treated with surgery, chemotherapy, target therapy, and radiotherapy. However, 25-50% of patients experience local relapses and/or distant metastases after chemotherapy with an overall survival about 12-18 months. Recently, immuno-therapy has revolutionized the cancer treatments with initial indications for non-small cell lung cancer (NSCLC) and melanoma (immune-checkpoint inhibitors).Here, we provide a narrative review on the topic as well as a critical description of the currently available trials on immunotherapy treatments in patients with sarcoma. Given the promising results obtained with anti-PD-1 monoclonal antibodies (pembrolizumab and nivolumab) and CAR-T cells, we strongly believe that these new immunotherapeutic approaches, along with an innovative characterization of tumor genetics, will provide an exciting opportunity to ameliorate the therapeutic management of sarcomas.

Immune analysis of lymph nodes in relation to the presence or absence of tumor infiltrating lymphocytes in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with unmet medical needs. Several studies have proved that high levels of tumor infiltrating lymphocytes (TILs) at diagnosis of TNBC confer better prognosis and patients respond better to specific chemotherapies. Nonetheless, current evidence suggests that only 15% of TNBC patients have very high levels of TILs, and another 15% lacks TILs. One possible reason to explain why patients have low TILs at diagnosis is that lymphocytes might be deactivated by an immune checkpoint in local lymph nodes, provoking their retention in there as they are unresponsive to other immune stimuli. We have identified 15 high TILs (≥50%) and 20 low TILs (≤5%) TNBC patients with localised tumour (T1c-T2N0M0) and compared the protein expression of five immune checkpoints in lymph nodes. We have also performed a customised 50-immune gene NanoString expression panel, the NanoString 360 Breast Cancer panel, and whole exome sequencing for mutation and neoantigen load analyses. In low TILs, we observed higher expression of CTLA-4 in local lymph nodes, which could explain why lymphocytes get retained in there and do not migrate to tumour. These patients have also higher neoantigen load and higher expression of B7.H3 and B7.H4 in the tumour. In high TILs, we observed more PD-L1+ tumour cells and more expanded humoral response. These results could provide a strategy to revert low tumour immune infiltration at diagnosis of TNBC, improving their prognosis.

Tumour-infiltrating lymphocytes as a prognostic and tamoxifen predictive marker in premenopausal breast cancer: data from a randomised trial with long-term follow-up

BACKGROUND

Tumour-infiltrating lymphocytes (TILs) are of important prognostic and predictive value in human epidermal growth factor receptor 2-positive (HER2+) breast cancer (BC) and triple-negative breast cancer (TNBC), but their clinical relevance in oestrogen receptor-positive/HER2-negative (ER+/HER2-) remains unknown. The primary study aim was to analyse the prognostic effect of TILs on the BC-free interval (BCFi) in premenopausal patients stratified by BC subtypes. The secondary aim was to investigate if TILs are predictive of tamoxifen (TAM) benefit.

METHODS

Archival tissues from primary breast tumours were collected from patients from the SBII:2pre trial, in which 564 premenopausal women were randomised to 2 years of adjuvant TAM or no systemic treatment, regardless of hormone receptor status. TILs were scored on whole tissue sections from 447 patients with available ER status. Tumours were divided into ER+/HER2-, HER2+ and TNBC subtypes by immunohistochemistry and in situ hybridisation. The prognostic value of TILs was analysed in systemically untreated patients (n = 221); the predictive information was investigated in the ER+ subgroup (n = 321) by cumulative incidence curves and Cox regression analyses. The median follow-up was 28 years.

RESULTS

High (≥ 50%) infiltration of TILs was a favourable prognostic factor in terms of BCFi (univariable analysis: hazard ratioBCFi (HRBCFi) 0.40; 95% confidence interval (CI) 0.22-0.71; P = 0.002). Similar effects were observed across all BC subtypes. The effect of adjuvant TAM was stronger in patients with ER+ tumours and TILs < 50% (HRBCFi 0.63; 95% CI 0.47-0.84; P = 0.002) than in patients with high immune infiltration (≥ 50%) (HRBCFi 0.84; 95% CI (0.24-2.86); P = 0.77). However, evidence for differential effects of TAM in categories of TILs, i.e. interaction, was weak.

CONCLUSIONS

We demonstrate a long-term favourable prognostic value of high infiltration of TILs in a cohort of premenopausal BC patients and the positive prognostic effect was extended to the ER+/HER2- subgroup. A beneficial effect of TAM in ER+ patients was observed in patients with tumours of low TIL infiltration, but evidence for a treatment predictive effect was weak.

TRIAL REGISTRATION

This trial is registered in the ISRCTN database, trial ID: ISRCTN12474687 .

Predictive and prognostic role of tumour-infiltrating lymphocytes in breast cancer patients with different molecular subtypes: a meta-analysis

BACKGROUND

Whether tumour-infiltrating lymphocytes (TILs) play different roles in different molecular subtypes of breast cancer remains unknown. Additionally, their prognostic and predictive value in different molecular subtypes of breast cancer is still controversial. The aim of our meta-analysis was to assess the prognostic and predictive value of TILs in different molecular subtypes of breast cancer by summarizing all relevant studies performing multivariate analysis.

METHODS

PubMed, Embase, EBSCO, ScienceDirect, the Cochrane Database and Web of Science were comprehensively searched (until March 2020). Hazard ratios (HRs), odds ratios (ORs) and their 95% confidence intervals (CIs) were used as effect measures to perform our meta-analysis. A random effect model was used. Stata software, version 15 (2017) (StataCorp, College Station, TX, USA) was used to perform the statistical analysis.

RESULTS

Thirty-three studies including 18,170 eligible breast cancer patients were analysed. The meta-analysis showed that high TIL expression was significantly associated with increased pathological complete response (pCR) rates after neoadjuvant chemotherapy in patients with the HER2-enriched molecular subtype (OR = 1.137, 95% CI [1.061 ~ 1.218], p < 0.001) and triple-negative breast cancer (TNBC) subtype (OR = 1.120, 95% CI [1.061 ~ 1.182], p < 0.001). However, high TIL expression was not significantly associated with high pCR rates after neoadjuvant chemotherapy in patients with the luminal molecular subtype of breast cancer (OR = 1.154, 95% CI [0.789 ~ 1.690], p = 0.460). We carried out a meta-analysis on the HRs of overall survival (OS) and disease-free survival (DFS) to assess the prognostic value of TILs in breast cancer with different molecular subtypes more deeply. Our meta-analysis confirmed that high TILs were associated with significantly improved DFS in patients with the HER2-enriched molecular subtype [HR = 0.940, 95% CI (0.903 ~ 0.979), p = 0.003] and TNBC molecular subtype [HR = 0.907, 95% CI (0.862 ~ 0.954), p < 0.001]. However, high TILs were not associated with significantly better DFS in patients with the luminal molecular subtype of breast cancer [HR = 0.998, 95% CI (0.977 ~ 1.019), p = 0.840]. Furthermore, the results confirmed that high TILs were significantly related to better OS in patients with the HER2-enriched molecular subtype [HR = 0.910, 95% CI (0.866 ~ 0.957), p < 0.001] and TNBC molecular subtype [HR = 0.869, 95% CI (0.836 ~ 0.904), p < 0.001]. Conversely, the summarized results indicated that high TILs were significantly associated with poor OS in patients with the luminal molecular subtype of breast cancer [HR = 1.077, 95% CI (1.016 ~ 1.141), p = 0.012].

CONCLUSIONS

Our meta-analysis confirms that high TILs are associated with favourable survival and predicts pCR in breast cancer patients with the TNBC and HER2-enriched molecular subtypes.

Insights for the application of TILs and AR in the treatment of TNBC in routine clinical practice

Triple negative breast cancer (TNBC), usually presenting with a very aggressive phenotype, is a heterogeneous entity. We aim to discuss new biomarkers, suitable for prognostic and predictive purposes. We retrospectively collected clinical variables and immunohistochemical characteristics of early TNBCs, specifically focusing on the prognostic and predictive significance of tumor infiltrating lymphocytes (TILs) and androgen receptor (AR) expression, assessing their correlation with clinical variables. Among 159 patients, TILs were significantly higher in younger patients and with lower BMI, and in tumors with higher ki-67 and greater nodal involvement; conversely, AR was significantly higher in older patients and in tumors with lower ki-67. Interestingly and in line with literature, both TILs level and ARs expression were lower within metastatic sites, in patients who developed distant metastases, compared to those found in the primary site. Small (pT1) and node negative tumors were highly represented and no correlation of either TILs or AR with prognosis could be observed. Our findings support the use of stromal TILs to identify a more aggressive, but chemo-sensitive phenotype, mostly represented in younger women, while AR may identify a less aggressive, slow-growing luminal TNBC subtype, more common among older patients. TILs and AR are worth implementing in routine clinical practice to refine prognosis even if, in our case series, we couldn't identify a significant correlation of the two variables with either disease-free and overall survival.

Biology of the Triple-Negative Breast Cancer: Immunohistochemical, RNA, and DNA Features

Background

The triple-negative breast cancer (TNBC) constitutes a heterogeneous disease with an aggressive behavior and a poor prognosis. A better understanding of its biology is required to identify new biomarkers and improve clinical outcomes.

Summary

To date, the definition and classification of TNBC depends on a multiomic approach including immunohistochemistry (IHC), genomic, and transcriptomic features, and the tumor immune landscape. The development of new technologies has allowed us to sequence the whole cancer genome. The Cancer Genome Atlas (TCGA) and next-generation sequencing have led to a greater knowledge of DNA alterations such as TP53 or BRCA mutations, copy number variations, and DNA methylations. In addition, gene expression profiling has allowed to define a molecular intrinsic classification of TNBC based on mRNA. IHC and genomic profiling are also necessary to identify new immune biomarkers such as the presence of tumor-infiltrating lymphocytes and the expression of immune checkpoint molecules.

Key Messages

This review aimed to provide recent knowledge of TNBC biology and classification focused on IHC, transcriptomics, genomic features, and the new immune biomarkers.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

TBCRC 031: Randomized Phase II Study of Neoadjuvant Cisplatin Versus Doxorubicin-Cyclophosphamide in Germline BRCA Carriers With HER2-Negative Breast Cancer (the INFORM trial)

PURPOSE

Platinum compounds have activity in triple-negative breast cancer (TNBC) in germline BRCA mutation carriers (BRCA carriers). Limited data exist for estrogen receptor (ER)-positive (+) breast cancer among BRCA carriers. INFORM is a randomized, multicenter, phase II trial comparing pathologic complete response (pCR) rates (ypT0/is, N0) after neoadjuvant single-agent cisplatin (CDDP) versus doxorubicin-cyclophosphamide (AC) in BRCA carriers with stage I-III human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Secondary objectives included residual cancer burden scores (RCB) of 0 or 1 (combined) and toxicity. The goal was to determine whether pCR was ≥ 20% higher with CDDP than AC.

PATIENTS AND METHODS

BRCA carriers with cT1-3 (≥ 1.5 cm), cN0-3 HER2-negative breast cancer were randomly assigned to preoperative CDDP (75 mg/m² every 3 weeks × 4 doses) or AC (doxorubicin 60 mg/m²; cyclophosphamide 600 mg/m² every 2-3 weeks × 4 doses) followed by surgery. Pathologic responses were confirmed by central review.

RESULTS

A total of 118 patients were randomly assigned; 117 were included in outcome analyses. Mean age was 42 years (range, 24-73 years); 69% were BRCA1+, 30% were BRCA2+, and 2% had both mutations. Clinical stage was I for 19%, II for 63%, and III for 18%; 45% had nodal involvement at baseline. Seventy percent had TNBC. Clinical and tumor characteristics were well matched between treatment arms. The pCR rate was 18% with CDDP and 26% with AC, yielding a risk ratio (RR) of 0.70 (90% CI, 0.39 to 1.2). The risk of RCB 0 or 1 (RCB 0/1) was 33% with CDDP and 46% with AC (RR, 0.73; 90% CI, 0.50 to 1.1). Both regimens were generally well tolerated without unexpected toxicities.

CONCLUSION

pCR or RCB 0/1 is not significantly higher with CDDP than with AC in BRCA carriers with stage I-III HER2-negative breast cancer for both TNBC and ER+/HER2-negative disease.