The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group

Optimizing Postneoadjuvant Treatment in Patients With Early Breast Cancer Achieving Pathologic Complete Response

pCR should be integrated with other prognostic factors to optimize postneoadjuvant treatments in BC.

Combining Molecular and Traditional Prognostic Factors: A Holistic Approach to Breast Cancer Prognostication

Breast cancer is a heterogeneous disease with various morphologies and molecular features, and it is the second leading cause of cancer death in women in developed countries. According to the literature, we currently lack both prognostic biomarkers and therapeutic targets. The most important prognostic factors are disease stage and Nottingham grade. We conducted a retrospective analysis involving 273 patients with BC who underwent neoadjuvant therapy before proceeding to curative surgical treatment between 1 January 2014 and 31 December 2023. Pathological procedures were conducted at the Department of Pathology, Emergency County Hospital of Targu Mureș, Romania. A statistical analysis was performed. Regarding the relationship between Nottingham grade and Ki67, grade I was associated with a Ki67 of less than 14. The relationship between tumor grade and luminal was similar (p = 0.0001): Grade I was associated with luminal A. Regarding TNM stage, it was statistically significantly correlated with TILs (p = 0.01) and RCB (p = 0.0001). Stages III and IV were associated with a high RCB and poor prognosis. Regarding the prognostic value, Nottingham grade 3 and TNM stages III and IV were correlated with low overall survival and disease-free survival, with poor prognosis, and, among the molecular variables, RCB played the most important prognostic role.

Tumor immune microenvironment permissive to metastatic progression of ING4-deficient breast cancer

Deficiencies in the ING4 tumor suppressor are associated with advanced stage tumors and poor patient survival in cancer. ING4 was shown to inhibit NF-kB in several cancers. As NF-kB is a key mediator of immune response, the ING4/NF-kB axis is likely to manifest in tumor-immune modulation but has not been investigated. To characterize the tumor immune microenvironment associated with ING4-deficient tumors, three approaches were employed in this study: First, tissue microarrays composed of 246 primary breast tumors including 97 ING4-deficient tumors were evaluated for the presence of selective immune markers, CD68, CD4, CD8, and PD-1, using immunohistochemical staining. Second, an immune-competent mouse model of ING4-deficient breast cancer was devised utilizing CRISPR-mediated deletion of Ing4 in a Tp53 deletion-derived mammary tumor cell line; mammary tumors were evaluated for immune markers using flow cytometry. Lastly, the METABRIC gene expression dataset was evaluated for patient survival related to the immune markers associated with Ing4-deleted tumors. The results showed that CD68, CD4, CD8, or PD-1, was not significantly associated with ING4-deficient breast tumors, indicating no enrichment of macrophages, T cells, or exhausted T cell types. In mice, Ing4-deleted mammary tumors had a growth rate comparable to Ing4-intact tumors but showed increased tumor penetrance and metastasis. Immune marker analyses of Ing4-deleted tumors revealed a significant increase in tumor-associated macrophages (Gr-1loCD11b+F4/80+) and a decrease in granzyme B-positive (GzmB+) CD4+ T cells, indicating a suppressive and/or less tumoricidal immune microenvironment. The METABRIC data analyses showed that low expression of GZMB was significantly associated with poor patient survival, as was ING4-low expression, in the basal subtype of breast cancer. Patients with GZMB-low/ING4-low tumors had the worst survival outcomes (HR = 2.80, 95% CI 1.36-5.75, p = 0.0004), supportive of the idea that the GZMB-low immune environment contributes to ING4-deficient tumor progression. Collectively, the study results demonstrate that ING4-deficient tumors harbor a microenvironment that contributes to immune evasion and metastasis.

Breast Cancer Immune Landscape: Interplay Between Systemic and Local Immunity

Breast cancer (BC) is one of the most common malignancies in women worldwide. Numerous studies in immuno-oncology and successful trials of immunotherapy have demonstrated the causal role of the immune system in cancer pathogenesis. The interaction between the tumor and the immune system is known to have a dual nature. Despite cytotoxic lymphocyte activity against transformed cells, a tumor can escape immune surveillance and leverage chronic inflammation to maintain its own development. Research on antitumor immunity primarily focuses on the role of the tumor microenvironment, whereas the systemic immune response beyond the tumor site is described less thoroughly. Here, a comprehensive review of the formation of the immune profile in breast cancer patients is offered. The interplay between systemic and local immune reactions as self-sustaining mechanism of tumor progression is described and the functional activity of the main cell populations related to innate and adaptive immunity is discussed. Additionally, the interaction between different functional levels of the immune system and their contribution to the development of the pro- or anti-tumor immune response in BC is highlighted. The presented data can potentially inform the development of new immunotherapy strategies in the treatment of patients with BC.

Coordinated inflammation and immune response transcriptional regulation in breast cancer molecular subtypes

Breast cancer, characterized by its complexity and diversity, presents significant challenges in understanding its underlying biology. In this study, we employed gene co-expression network analysis to investigate the gene composition and functional patterns in breast cancer subtypes and normal breast tissue. Our objective was to elucidate the detailed immunological features distinguishing these tumors at the transcriptional level and to explore their implications for diagnosis and treatment. The analysis identified nine distinct gene module clusters, each representing unique transcriptional signatures within breast cancer subtypes and normal tissue. Interestingly, while some clusters exhibited high similarity in gene composition between normal tissue and certain subtypes, others showed lower similarity and shared traits. These clusters provided insights into the immune responses within breast cancer subtypes, revealing diverse immunological functions, including innate and adaptive immune responses. Our findings contribute to a deeper understanding of the molecular mechanisms underlying breast cancer subtypes and highlight their unique characteristics. The immunological signatures identified in this study hold potential implications for diagnostic and therapeutic strategies. Additionally, the network-based approach introduced herein presents a valuable framework for understanding the complexities of other diseases and elucidating their underlying biology.

PatchSorter: a high throughput deep learning digital pathology tool for object labeling

The discovery of patterns associated with diagnosis, prognosis, and therapy response in digital pathology images often requires intractable labeling of large quantities of histological objects. Here we release an open-source labeling tool, PatchSorter, which integrates deep learning with an intuitive web interface. Using >100,000 objects, we demonstrate a >7x improvement in labels per second over unaided labeling, with minimal impact on labeling accuracy, thus enabling high-throughput labeling of large datasets.

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

Deconstructing neutrophil to lymphocyte ratio (NLR) in early breast cancer: lack of prognostic utility and biological correlates across tumor subtypes

PURPOSE

The prognostic utility and biological correlates of neutrophil to lymphocyte ratio (NLR), a potential biomarker of the balance between immune response and the inflammatory status, are still uncertain in breast cancer (BC).

METHODS

We analysed a cohort of 959 women with early breast cancer, mostly treated with neoadjuvant or adjuvant chemotherapy. Clinical and pathological data, survival, NLR (continuous and categorical) and stromal tumor infiltrating lymphocytes (sTIL) were evaluated.

RESULTS

NLR was only weakly associated with Ki67, while no association was found for grade, histology, immunohistochemical subtype or stage. Lymphocyte infiltration of the tumor did not correlate with NLR (Rho: 0.05, p = 0.30). These results were similar in the whole group and across the different BC subtypes, with no differences in triple negative BC. Relapse free interval (RFI), breast cancer specific survival (BCSS) and overall survival (OS) changed according to pre-treatment NLR neither in the univariate nor in the multivariate Cox models (RFI: HR 0.948, p = 0.61; BCSS: HR 0.920, p = 0.57; OS: HR 0.96, p = 0.59).

CONCLUSION

These results question the utility of NLR as a prognostic biomarker in early breast cancer and suggest the lack of correlation of NLR with tumor microenvironment immune response.

The anti-cancer immune response in breast cancer: current and emerging biomarkers and treatments

Triple-negative breast cancers (TNBCs) exhibit heightened T cell infiltration, contributing to an enhanced response to immune checkpoint blockade (ICB) compared with other subtypes. An immune-rich immune microenvironment correlates with improved prognosis in early and advanced TNBC. Combination chemotherapy and ICB is now the standard of care in early- and late-stage TNBC. Although programmed death ligand-1 (PD-L1) positivity predicts ICB response in advanced stages, its role in early-stage disease remains uncertain. Despite neoadjuvant ICB becoming common in early-stage TNBC, the necessity of adjuvant ICB after surgery remains unclear. Understanding the molecular basis of the immune response in breast cancer is vital for precise biomarkers for ICB and effective combination therapy strategies.

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

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

Dynamic changes in B cell subpopulations in response to triple-negative breast cancer development

Despite presenting a worse prognosis and being associated with highly aggressive tumors, triple-negative breast cancer (TNBC) is characterized by the higher frequency of tumor-infiltrating lymphocytes, which have been implicated in better overall survival and response to therapy. Though recent studies have reported the capacity of B lymphocytes to recognize overly-expressed normal proteins, and tumor-associated antigens, how tumor development potentially modifies B cell response is yet to be elucidated. Our findings reveal distinct effects of 4T1 and E0771 murine tumor development on B cells in secondary lymphoid organs. Notably, we observe a significant expansion of total B cells and plasma cells in the tumor-draining lymph nodes (tDLNs) as early as 7 days after tumor challenge in both murine models, whereas changes in the spleen are less pronounced. Surprisingly, within the tumor microenvironment (TME) of both models, we detect distinct B cell subpopulations, but tumor development does not appear to cause major alterations in their frequency over time. Furthermore, our investigation into B cell regulatory phenotypes highlights that the B10 Breg phenotype remains unaffected in the evaluated tissues. Most importantly, we identified an increase in CD19 + LAG-3 + cells in tDLNs of both murine models. Interestingly, although CD19 + LAG-3 + cells represent a minor subset of total B cells (< 3%) in all evaluated tissues, most of these cells exhibit elevated expression of IgD, suggesting that LAG-3 may serve as an activation marker for B cells. Corroborating with these findings, we detected distinct cell cycle and proliferation genes alongside LAG-3 analyzing scRNA-Seq data from a cohort of TNBC patients. More importantly, our study suggests that the presence of LAG-3 B cells in breast tumors could be associated with a good prognosis, as patients with higher levels of LAG-3 B cell transcripts had a longer progression-free interval (PFI). This novel insight could pave the way for targeted therapies that harness the unique properties of LAG-3 + B cells, potentially offering new avenues for improving patient outcomes in TNBC. Further research is warranted to unravel the mechanistic pathways of these cells and to validate their prognostic value in larger, diverse patient cohorts.

A comprehensive single-cell breast tumor atlas defines epithelial and immune heterogeneity and interactions predicting anti-PD-1 therapy response

We present an integrated single-cell RNA sequencing atlas of the primary breast tumor microenvironment (TME) containing 236,363 cells from 119 biopsy samples across eight datasets. In this study, we leverage this resource for multiple analyses of immune and cancer epithelial cell heterogeneity. We define natural killer (NK) cell heterogeneity through six subsets in the breast TME. Because NK cell heterogeneity correlates with epithelial cell heterogeneity, we characterize epithelial cells at the level of single-gene expression, molecular subtype, and 10 categories reflecting intratumoral transcriptional heterogeneity. We develop InteractPrint, which considers how cancer epithelial cell heterogeneity influences cancer-immune interactions. We use T cell InteractPrint to predict response to immune checkpoint inhibition (ICI) in two breast cancer clinical trials testing neoadjuvant anti-PD-1 therapy. T cell InteractPrint was predictive of response in both trials versus PD-L1 (AUC = 0.82, 0.83 vs. 0.50, 0.72). This resource enables additional high-resolution investigations of the breast TME.

High tumour-infiltrating lymphocytes correlate with distinct gene expression profile and favourable survival in single hormone receptor-positive breast cancer

Introduction

This study aimed to evaluate the impact of tumour-infiltrating lymphocytes (TILs) on the expression of immune-related genes and prognosis in single hormone receptor-positive breast cancer. Material and methods: Tumour-infiltrating lymphocytes were analysed according to the guidelines of the International TILs Working Group in a cohort of 206 patients with single hormone receptor-positive breast cancer. Of these, 44.7% were classified as ER+/PgR-/HER2-, 18.4% as ER+/PgR-/HER2+, 26.2% as ER-/PgR+/HER2-, and 10.7% as ER-/PgR+/HER2+. Moreover, in 52 samples the analysis of gene expression profiling was performed using nCounter technology.

Results

Most cases (74.3%) showed at least 1% of stromal TILs, with a median of 4%, mean of 16.3%, and interquartile range of 0-20%. ER-/PgR+ tumours displayed significantly higher TILs density than ER+/PgR- cases (p < 0.001, Wilcoxon test), regardless of HER2 status. The abundance of TILs was positively associated with ER-/PgR+ phenotype, higher Ki-67, and higher grade, but not with age, tumour size, or regional and distant metastases at diagnosis. Additionally, in ER+/PgR- subgroup higher TILs were associated with HER2-positive status. Stromal TILs > 5% were associated with better survival in the whole group, but this effect was less prominent in ER-/PgR+ patients. We identified 50 differentially expressed genes (DEGs) between single hormone receptor-positive breast tumours with high and low TILs, including 39 up-regulated and 11 down-regulated genes in the high TILs group.

Conclusions

The up-regulated expression of immune-related genes was consistent also among separately analysed single hormone receptor-positive groups (ER+/PgR- and ER-/PgR+).

High tumor infiltrating lymphocytes are significantly associated with pathological complete response in triple negative breast cancer treated with neoadjuvant KEYNOTE-522 chemoimmunotherapy

INTRODUCTION

For patients with locally advanced triple negative breast cancer (TNBC), the standard of care is to administer the KEYNOTE-522 (K522) regimen, including chemotherapy and immunotherapy (pembrolizumab) given in the neoadjuvant setting. Pathological complete response (pCR) is more likely in patients who receive the K522 regimen than in patients who receive standard chemotherapy. Studies have shown that pCR is a strong predictor of long-term disease-free survival. However, factors predicting pCR to K522 are not well understood and require further study in real-world populations.

METHODS

We evaluated 76 patients who were treated with the K522 regimen at our institution. Twenty-nine pre-treatment biopsy slides were available for pathology review. Nuclear grade, Nottingham histologic grade, Ki-67, lymphovascular invasion, and tumor infiltrating lymphocytes (TIL) were evaluated in these 29 cases. For the cases that did not have available slides for review from pre-treatment biopsies, these variables were retrieved from available pathology reports. In addition, clinical staging, race, and BMI at the time of biopsy were retrieved from all 76 patients' charts. Binary logistic regression models were used to correlate these variables with pCR.

RESULTS

At the current time, 64 of 76 patients have undergone surgery at our institution following completion of K522 and 31 (48.4%) of these achieved pCR. In univariate analysis, only TIL was significantly associated with pCR (p = 0.014) and this finding was also confirmed in multivariate analysis, whereas other variables including age, race, nuclear grade, Nottingham grade, Ki-67, lymphovascular invasion, BMI, pre-treatment tumor size, and lymph node status were not associated with pCR (p > 0.1).

CONCLUSION

Our real-world data demonstrates high TIL is significantly associated with pCR rate in the K522 regimen and may potentially serve as a biomarker to select optimal treatment. The pCR rate of 48.4% in our study is lower than that reported in K522, potentially due to the smaller size of our study; however, this may also indicate differences between real-world data and clinical trial results. Larger studies are warranted to further investigate the role of immune cells in TNBC response to K522 and other treatment regimens.

Adoptive cell immunotherapy for breast cancer: harnessing the power of immune cells

Breast cancer is the most prevalent malignant neoplasm worldwide, necessitating the development of novel therapeutic strategies owing to the limitations posed by conventional treatment modalities. Immunotherapy is an innovative approach that has demonstrated significant efficacy in modulating a patient's innate immune system to combat tumor cells. In the era of precision medicine, adoptive immunotherapy for breast cancer has garnered widespread attention as an emerging treatment strategy, primarily encompassing cellular therapies such as tumor-infiltrating lymphocyte therapy, chimeric antigen receptor T/natural killer/M cell therapy, T cell receptor gene-engineered T cell therapy, lymphokine-activated killer cell therapy, cytokine-induced killer cell therapy, natural killer cell therapy, and γδ T cell therapy, among others. This treatment paradigm is based on the principles of immune memory and antigen specificity, involving the collection, processing, and expansion of the patient's immune cells, followed by their reintroduction into the patient's body to activate the immune system and prevent tumor recurrence and metastasis. Currently, multiple clinical trials are assessing the feasibility, effectiveness, and safety of adoptive immunotherapy in breast cancer. However, this therapeutic approach faces challenges associated with tumor heterogeneity, immune evasion, and treatment safety. This review comprehensively summarizes the latest advancements in adoptive immunotherapy for breast cancer and discusses future research directions and prospects, offering valuable guidance and insights into breast cancer immunotherapy.

Longitudinal Assessment of Tumor-Infiltrating Lymphocytes in Primary Breast Cancer Following Neoadjuvant Radiation Therapy

PURPOSE

Tumor-infiltrating lymphocytes (TILs) have prognostic significance in several cancers, including breast cancer. Despite interest in combining radiation therapy with immunotherapy, little is known about the effect of radiation therapy itself on the tumor-immune microenvironment, including TILs. Here, we interrogated longitudinal dynamics of TILs and systemic lymphocytes in patient samples taken before, during, and after neoadjuvant radiation therapy (NART) from PRADA and Neo-RT breast clinical trials.

METHODS AND MATERIALS

We manually scored stromal TILs (sTILs) from longitudinal tumor samples using standardized guidelines as well as deep learning-based scores at cell-level (cTIL) and cell- and tissue-level combination analyses (SuperTIL). In parallel, we interrogated absolute lymphocyte counts from routine blood tests at corresponding time points during treatment. Exploratory analyses studied the relationship between TILs and pathologic complete response (pCR) and long-term outcomes.

RESULTS

Patients receiving NART experienced a significant and uniform decrease in sTILs that did not recover at the time of surgery (P < .0001). This lymphodepletive effect was also mirrored in peripheral blood. Our SuperTIL deep learning score showed good concordance with manual sTILs and importantly performed comparably to manual scores in predicting pCR from diagnostic biopsies. The analysis suggested an association between baseline sTILs and pCR, as well as sTILs at surgery and relapse, in patients receiving NART.

CONCLUSIONS

This study provides novel insights into TIL dynamics in the context of NART in breast cancer and demonstrates the potential for artificial intelligence to assist routine pathology. We have identified trends that warrant further interrogation and have a bearing on future radioimmunotherapy trials.

Prognostic value and distribution pattern of tumor infiltrating lymphocytes and their subsets in distant metastases of advanced breast cancer

BACKGROUND

There are significant correlations between the levels of tumor infiltrating lymphocytes (TILs) and the prognosis of primary breast cancer. While little is known about immunological mechanisms in the distant metastasis of advanced breast cancer.

PATIENTS AND METHODS

A total of 106 patients with advanced metastatic breast cancer were enrolled in this study between 2016 and 2022. Hematoxylin and eosin staining and immunohistochemistry were used to assess the densities of stromal TILs (sTILs), intratumoral TILs (iTILs) and invasive marginal TILs (imTILs) and CD4+, CD8+, CD20+, FOXP3+ TILs in the primary tumor and metastasis (bone, lung, liver, and distant lymph node) of advanced breast cancer.

RESULTS

Higher levels of sTILs at metastatic sites were associated with better progression-free survival (PFS), postmetastasis survival (PMS) and overall survival (OS) (p = .026, .001 and .005, respectively). The levels of iTILs were significantly lower than those of sTILs and imTILs in both primary tumor (p< .001, both) and metastasis (p< .001, both). The level of CD4+ T cells was higher than those of CD8+ T cells and CD20+ B cells in both primary tumor (p < .001) and metastasis (p < .001). The levels of sTILs (p=0. 001) and imTILs (p< .001) in the primary tumor were generally higher than those in the metastasis.

CONCLUSION

The levels of TILs and their subsets can predict the survival and prognosis of patients with advanced breast cancer. The distributions of TILs and their subsets are similar between the primary tumor and metastasis. The metastases have a lower degree of lymphocytes infiltration than its corresponding primary tumor.

Adjuvant nivolumab, capecitabine or the combination in patients with residual triple-negative breast cancer: the OXEL randomized phase II study

Chemotherapy and immune checkpoint inhibitors have a role in the post-neoadjuvant setting in patients with triple-negative breast cancer (TNBC). However, the effects of nivolumab, a checkpoint inhibitor, capecitabine, or the combination in changing peripheral immunoscore (PIS) remains unclear. This open-label randomized phase II OXEL study (NCT03487666) aimed to assess the immunologic effects of nivolumab, capecitabine, or the combination in terms of the change in PIS (primary endpoint). Secondary endpoints included the presence of ctDNA, toxicity, clinical outcomes at 2-years and association of ctDNA and PIS with clinical outcomes. Forty-five women with TNBC and residual invasive disease after standard neoadjuvant chemotherapy were randomized to nivolumab, capecitabine, or the combination. Here we show that a combination of nivolumab plus capecitabine leads to a greater increase in PIS from baseline to week 6 (91%) compared with nivolumab (47%) or capecitabine (53%) alone (log-rank p = 0.08), meeting the pre-specified primary endpoint. In addition, the presence of circulating tumor DNA (ctDNA) is associated with disease recurrence, with no new safety signals in the combination arm. Our results provide efficacy and safety data on this combination in TNBC and support further development of PIS and ctDNA analyses to identify patients at high risk of recurrence.

Comparison of assessment of programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer biopsies and surgical specimens

AIMS

Programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer (TNBC) is important for immune checkpoint inhibitor therapies but may vary between different immunohistochemical assays, scorings and the type of specimen used for analysis.

METHODS

We compared the analytical concordance of three clinically relevant PD-L1 assays (VENTANA SP142, VENTANA SP263 and DAKO 22C3 pharmDx) assessing immune cell score (IC), tumour proportion score and combined positive score (CPS) in preoperative biopsies and resection specimens of primary TNBC. PD-L1 expression was scored on virtual whole slide images and compared with expression data from corresponding surgical specimens.

RESULTS

The mean PD-L1 positivity in TNBC biopsies defined as IC ≥1% and CPS ≥1 ranged between 11% and 61% with the lowest positivity for SP142 and highest for SP263. The corresponding surgical specimens showed overall higher positivity rates (53%-75%). When comparing biopsies with surgical specimens, the agreement for PD-L1 positivity with SP263 and 22C3 at IC score ≥1% and CPS ≥1 was fair (kappa 0.47-0.52) and poor for SP142 (kappa 0.15-0.19). Using CPS ≥10 cut-off, the agreement for SP263 was excellent (kappa 0.751) but poor for 22C3 (kappa 0.261). Spearman correlation coefficients ranged between 0.489 and 0.75 indicating a generally moderate to strong correlation between biopsies and surgical specimens for all assays and scores.

CONCLUSIONS

We demonstrate high accordance between biopsies and surgical specimens for SP263 and 22C3 scoring but less for SP142. Generally, biopsies are suitable for PD-L1 testing in TNBC but the appropriate assay, scoring and cut-off must be considered.

The assessment of tumor-infiltrating lymphocytes in invasive apocrine carcinoma of the breast in relation to the HER2 status

In the current study, we assessed the prevalence and molecular features of HER2-low phenotype in the apocrine carcinomas of the breast (ApoCa) and its relationship with tumor-infiltrating lymphocytes (TILs). A cohort of 64 well-characterized therapy-naïve ApoCa was used. The TIL distribution was assessed using the hematoxylin and eosin whole slide/scanned images following the international TILs working group recommendations. Next-generation sequencing (NGS) was performed in a subset of HER2-low ApoCa. All patients were women, with a mean age of 62 years. Forty-three carcinomas were pure apocrine carcinoma (PAC; ER-/AR+), and the remaining 21 were classified as apocrine-like carcinomas (ALCs; ER+/-, AR+/-). HER2/neu was positive (score 3+ by IHC and/or amplified by FISH) in 20/43 (47%) PAC and 4/21 (19%) ALC. The prevalence of HER2-low expression (scores 1+ or 2+ without HER2 amplification) in ApoCa was 39% without significant differences between PAC and ALC (P = 0.14); however, the HER2-low phenotype was more prevalent in triple-negative PAC than in ALC (P < 0.001). Levels of TILs were low (≤10%) in 74% of ApoCa (median 5%, range 0%-50%). TIL levels were significantly higher in ALC than in PAC (P = 0.02). HER2 status had no impact on TIL distribution (P = 0.45). The genomic profile of HER2-low ApoCa was similar to other subtypes of ApoCa. ApoCa has predominantly low TIL, particularly PAC. The prevalence of the HER2-low phenotype in ApoCa is high, which should have therapeutic and clinical implications given the recently approved therapies with antibody-drug conjugates (ADCs) for HER2-low breast cancers.

HER2-low and tumor infiltrating lymphocytes in triple-negative breast cancer: Are they connected?

Most patients with triple-negative breast cancer (TNBC) are not candidates for targeted therapy, leaving chemotherapy as the primary treatment option. Recently, immunotherapy has demonstrated promising results in TNBC, due to its immunogenicity. In addition, a novel antibody-drug conjugate, namely, trastuzumab-deruxtecan, has shown effectiveness in TNBC patients with low-HER2 expression (HER2-low). These novel treatment options raise the question about the potential association between the density of stromal tumor-infiltrating lymphocytes (sTILs) and the level of HER2 expression. We aimed to evaluate the association between the level of HER2 expression (HER2-low versus HER2-0) and density of sTILs in TNBC patients, and how they impact the response to neoadjuvant chemotherapy (NAC). This was a retrospective multicenter study including all TNBC patients diagnosed between 2018 and 2022. Central pathology review included sTILs percentages and level of HER2 expression. Tumors were reclassified as either HER2-0 (HER2 IHC 0) or HER2-low (IHC 1 + or 2 + with negative reflex test). Various clinicopathologic characteristics, including sTILs density, and response to NAC were compared between HER2-0 and HER2-low cases. In total, 753 TNBC patients were included in this study, of which 292 patients received NAC. Interobserver agreement between the original pathology report and central review was moderate (77% had the same IHC status after reclassification in either HER2-0 or HER2-low; k = 0.45). HER2-low TNBC represented about one third (36%) of the tumors. No significant difference in sTILs density or complete pathologic response rate was found between HER2-0 and HER2-low cases (p = 0.476 and p = 0.339, respectively). The density of sTILs (≥ 10% sTILs vs. < 10%) was independently associated with achieving a pCR (p = 0.011). In conclusion, no significant association was found between HER2-low status and density of sTILs nor response to NAC. Nonetheless, sTILs could be an independent biomarker for predicting NAC response in TNBC patients.

Spatial Distribution and Densities of CD103+ and FoxP3+ Tumor Infiltrating Lymphocytes by Digital Analysis for Outcome Prediction in Breast Cancer

BACKGROUND

The evaluation of tumor-infiltrating lymphocytes (TILs) for breast cancer prognosis is now established. However, the clinical value for their spatial distributions of specific immune subsets, namely CD103+ tissue-resident memory T cells FoxP3+ regulatory T ells, have not been thoroughly examined.

METHOD

Representative whole sections of breast cancers were subjected to CD103 and FoxP3 double staining. Their density, ratio, and spatial features were analyzed in tumor area and tumor-stromal interface. Their associations with clinicopathological parameters and patient's prognosis were analyzed.

RESULTS

CD103 TILs were closer to tumor nests than FoxP3 TILs in the tumor-stromal interface. Their densities were associated with high-grade disease, TNBC, and stromal TILs. High stromal FoxP3 (sFoxP3) TILs and close proximity of sCD103 TILs to tumor were independently associated with better survival at multivariate analysis. Subgroup analysis showed the high FoxP3 TILs density associated better survival was seen in HER2-OE and TNBC subtypes while the proximity of CD103 TILs to tumor nests associated better survival was seen in luminal cancers.

CONCLUSION

The prognostic impact of CD103 and FoxP3 TILs in breast cancer depends on their spatial localization. High sFoxP3 TIL density and the lower distance of CD103 TILs from the tumor nests had independent favorable prognostic values.

Exploring histological predictive biomarkers for immune checkpoint inhibitor therapy response in non-small cell lung cancer

Treatment challenges persist in advanced lung cancer despite the development of therapies beyond the traditional platinum-based chemotherapy. The early 2000s marked a shift to tyrosine kinase inhibitors targeting epidermal growth factor receptor, ushering in personalized genetic-based treatment. A further significant advance was the development of immune checkpoint inhibitors (ICIs), especially for non-small cell lung cancer. These target programmed death-ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4, which enhanced the immune response against tumor cells. However, not all patients respond, and immune-related toxicities arise. This review emphasizes identifying biomarkers for ICI response prediction. While PD-L1 is a widely used, validated biomarker, its predictive accuracy is imperfect. Investigating tumor-infiltrating lymphocytes, tertiary lymphoid structure, and emerging biomarkers such as high endothelial venule, Human leukocyte antigen class I, T-cell immunoreceptors with Ig and ITIM domains, and lymphocyte activation gene-3 counts is promising. Understanding and exploring additional predictive biomarkers for ICI response are crucial for enhancing patient stratification and overall care in lung cancer treatment.

The NDV-MLS as an Immunotherapeutic Strategy for Breast Cancer: Proof of Concept in Female Companion Dogs with Spontaneous Mammary Cancer

The absence of tumor-infiltrating lymphocytes negatively impacts the response to chemotherapy and prognosis in all subtypes of breast cancer. Therapies that stimulate a proinflammatory environment may help improve the response to standard treatments and also to immunotherapies such as checkpoint inhibitors. Newcastle disease virus (NDV) shows oncolytic activity, as well as immune modulating potential, in the treatment of breast cancer in vitro and in vivo; however, its potential to enhance tumor-infiltrating immune cells in breast cancer has yet to be evaluated. Since spontaneous canine mammary tumors represent a translational model of human breast cancer, we conducted this proof-of-concept study, which could provide a rationale for further investigating NDV-MLS as immunotherapy for mammary cancer. Six female companion dogs with spontaneous mammary cancer received a single intravenous and intratumoral injection of oncolytic NDV-MLS. Immune cell infiltrates were evaluated by histology and immunohistochemistry in the stromal, intratumoral, and peritumoral compartments on day 6 after viral administration. Increasing numbers of immune cells were documented post-viral treatment, mainly in the peritumoral compartment, where plasma cells and CD3+ and CD3-/CD79- lymphocytes predominated. Viral administration was well tolerated, with no significant adverse events. These findings support additional research on the use of NDV-MLS immunotherapy for mammary cancer.

miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine

Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.

S100A8/A9 predicts response to PIM kinase and PD-1/PD-L1 inhibition in triple-negative breast cancer mouse models

BACKGROUND

Understanding why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well remains a challenge. This study aims to understand the potential underlying mechanisms distinguishing early-stage TNBC tumors that respond to clinical intervention from non-responders, as well as to identify clinically viable therapeutic strategies, specifically for TNBC patients who may not benefit from existing therapies.

METHODS

We conducted retrospective bioinformatics analysis of historical gene expression datasets to identify a group of genes whose expression levels in early-stage tumors predict poor clinical outcomes in TNBC. In vitro small-molecule screening, genetic manipulation, and drug treatment in syngeneic mouse models of TNBC were utilized to investigate potential therapeutic strategies and elucidate mechanisms of drug action.

RESULTS

Our bioinformatics analysis reveals a robust association between increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors and subsequent disease progression in TNBC. A targeted small-molecule screen identifies PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Notably, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC.

CONCLUSIONS

Our data propose S100A8/A9 as a potential predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC. This work encourages the development of S100A8/A9-based liquid biopsy tests for treatment guidance.

Distinct profiles of proliferating CD8+/TCF1+ T cells and CD163+/PD-L1+ macrophages predict risk of relapse differently among treatment-naïve breast cancer subtypes

Immunophenotypic analysis of breast cancer microenvironment is gaining attraction as a clinical tool improving breast cancer patient stratification. The aim of this study is to evaluate proliferating CD8 + including CD8 + TCF1 + Τ cells along with PD-L1 expressing tissue-associated macrophages among different breast cancer subtypes. A well-characterized cohort of 791 treatment-naïve breast cancer patients was included. The analysis demonstrated a distinct expression pattern among breast cancer subtypes characterized by increased CD8 + , CD163 + and CD163 + PD-L1 + cells along with high PD-L1 status and decreased fraction of CD8 + Ki67 + T cells in triple negative (TNBC) and HER2 + compared to luminal tumors. Kaplan-Meier and Cox univariate survival analysis revealed that breast cancer patients with high CD8 + , CD8 + Ki67 + , CD8 + TCF1 + cells, PD-L1 score and CD163 + PD-L1 + cells are likely to have a prolonged relapse free survival, while patients with high CD163 + cells have a worse prognosis. A differential impact of high CD8 + , CD8 + Ki67 + , CD8 + TCF1 + T cells, CD163 + PD-L1 + macrophages and PD-L1 status on prognosis was identified among the various breast cancer subtypes since only TNBC patients experience an improved prognosis compared to patients with luminal A tumors. Conversely, high infiltration by CD163 + cells is associated with worse prognosis only in patients with luminal A but not in TNBC tumors. Multivariate Cox regression analysis in TNBC patients revealed that increased CD8 + [hazard ratio (HR) = 0.542; 95% confidence interval (CI) 0.309-0.950; p = 0.032), CD8 + TCF1 + (HR = 0.280; 95% CI 0.101-0.779; p = 0.015), CD163 + PD-L1 + (HR: 0.312; 95% CI 0.112-0.870; p = 0.026) cells along with PD-L1 status employing two different scoring methods (HR: 0.362; 95% CI 0.162-0.812; p = 0.014 and HR: 0.395; 95% CI 0.176-0.884; p = 0.024) were independently linked with a lower relapse rate. Multivariate analysis in Luminal type A patients revealed that increased CD163 + was independently associated with a higher relapse rate (HR = 2.360; 95% CI 1.077-5.170; p = 0.032). This study demonstrates that the evaluation of the functional status of CD8 + T cells in combination with the analysis of immunosuppressive elements could provide clinically relevant information in different breast cancer subtypes.

High Numbers of CD163+ Tumor-Associated Macrophages Predict Poor Prognosis in HER2+ Breast Cancer

Tumor-associated macrophages (TAMs) are associated with a poor outcome in breast cancer (BC), but their prognostic value in different BC subtypes has remained somewhat unclear. Here, we investigated the prognostic value of M2-like TAMs (CD163+) and all TAMs (CD68+) in a patient cohort of 278 non-metastatic BC patients, half of whom were HER2+ (n = 139). The survival endpoints investigated were overall survival (OS), breast cancer-specific survival (BCSS) and disease-free survival (DFS). In the whole patient cohort (n = 278), a high CD163+ TAM count and a high CD68+ TAM count were associated with a worse outcome (p ≤ 0.023). In HER2+ BC, a high CD163+ TAM count was an independent factor for a poor prognosis across all the investigated survival endpoints (p < 0.001). The prognostic effect was evident in both the HER2+/hormone receptor-positive (p < 0.001) and HER2+/hormone receptor-negative (p ≤ 0.012) subgroups and regardless of the provision of adjuvant trastuzumab (p ≤ 0.002). In HER2-negative BC, the CD163+ TAM count was not significantly associated with survival. These results suggest that a high CD163+ TAM count predicts an inferior outcome, especially in HER2+ BC patients, and as adjuvant trastuzumab did not overcome the poor prognostic effect, combination treatments including therapies targeting the macrophage function could represent an effective therapeutic approach in HER2+ BC.

Ten-year clinical outcome, toxicity and compliance of dose-dense sequential adjuvant administration of cyclophosphamide & epirubicin followed by docetaxel in patients with early breast cancer: A hellenic cooperative oncology group observational study (HE 10/10) with concurrent investigation of significance of tumor infiltrating lymphocytes

BACKGROUND

Dose-dense sequential (dds) chemotherapy has changed the clinical outcome of patients with early breast cancer (BC). To investigate the impact of dose intensity (DI) in the adjuvant setting of BC, this observational trial (HE 10/10) was conducted assessing the long-term survival outcome, safety and toxicity of a currently widely used chemotherapeutic regimen. In addition, the prognostic significance of tumor infiltrating lymphocytes (TILs) and infiltrating CD8+ lymphocytes were also evaluated in the same cohort.

PATIENTS AND METHODS

Totally, 1054 patients were prospectively enrolled in the current study with 1024 patients being eligible, while adequate tissue was available for 596 of them. TILs, CD8+ lymphocytes in intratumoral areas in contact with malignant cells (iCD8), CD8+ lymphocytes in tumor stroma (sCD8) as well as the total number of CD8+ lymphocytes within the tumor area (total CD8) were assessed by immunohistochemistry.

RESULTS

Within a median follow-up of 125.18 months, a total of 200 disease-free survival (DFS) events (19.5%) were reported. Importantly, the 10-year DFS and OS rates were 78.4% (95% CI 75.0-81.5) and 81.7% (95% CI 79.0-84.1), respectively. Interestingly, higher CD8+ T cells as well as TILs in the tumor microenvironment were associated with an improved long-term survival outcome.

CONCLUSIONS

In conclusion, this study confirms the significance of dds adjuvant chemotherapeutic regimen in terms of long-term survival outcome, safety and toxicity as well as the prognostic significance of TILs and infiltrating CD8+ lymphocytes in BC patients with early-stage disease.

Breast Cancer Immunity: It is TIME for the Next Chapter

Our ability to interrogate the tumor immune microenvironment (TIME) at an ever-increasing granularity has uncovered critical determinants of disease progression. Not only do we now have a better understanding of the immune response in breast cancer, but it is becoming possible to leverage key mechanisms to effectively combat this disease. Almost every component of the immune system plays a role in enabling or inhibiting breast tumor growth. Building on early seminal work showing the involvement of T cells and macrophages in controlling breast cancer progression and metastasis, single-cell genomics and spatial proteomics approaches have recently expanded our view of the TIME. In this article, we provide a detailed description of the immune response against breast cancer and examine its heterogeneity in disease subtypes. We discuss preclinical models that enable dissecting the mechanisms responsible for tumor clearance or immune evasion and draw parallels and distinctions between human disease and murine counterparts. Last, as the cancer immunology field is moving toward the analysis of the TIME at the cellular and spatial levels, we highlight key studies that revealed previously unappreciated complexity in breast cancer using these technologies. Taken together, this article summarizes what is known in breast cancer immunology through the lens of translational research and identifies future directions to improve clinical outcomes.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Spatial Distribution of Immune Cells Drives Resistance to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) alone or combined with target therapies represents the standard of care for localized triple-negative breast cancer (TNBC). However, only a fraction of patients have a response, necessitating better understanding of the complex elements in the TNBC ecosystem that establish continuous and multidimensional interactions. Resolving such complexity requires new spatially-defined approaches. Here, we used spatial transcriptomics to investigate the multidimensional organization of TNBC at diagnosis and explore the contribution of each cell component to response to NAC. Starting from a consecutive retrospective series of TNBC cases, we designed a case-control study including 24 patients with TNBC of which 12 experienced a pathologic complete response (pCR) and 12 no-response or progression (pNR) after NAC. Over 200 regions of interest (ROI) were profiled. Our computational approaches described a model that recapitulates clinical response to therapy. The data were validated in an independent cohort of patients. Differences in the transcriptional program were detected in the tumor, stroma, and immune infiltrate comparing patients with a pCR with those with pNR. In pCR, spatial contamination between the tumor mass and the infiltrating lymphocytes was observed, sustained by a massive activation of IFN-signaling. Conversely, pNR lesions displayed increased pro-angiogenetic signaling and oxygen-based metabolism. Only modest differences were observed in the stroma, revealing a topology-based functional heterogeneity of the immune infiltrate. Thus, spatial transcriptomics provides fundamental information on the multidimensionality of TNBC and allows an effective prediction of tumor behavior. These results open new perspectives for the improvement and personalization of therapeutic approaches to TNBCs.

Breast cancer immunopeptidomes contain numerous shared tumor antigens

Hormone receptor-positive breast cancer (HR+) is immunologically cold and has not benefited from advances in immunotherapy. In contrast, subsets of triple-negative breast cancer (TNBC) display high leukocytic infiltration and respond to checkpoint blockade. CD8+ T cells, the main effectors of anticancer responses, recognize MHC I-associated peptides (MAPs). Our work aimed to characterize the repertoire of MAPs presented by HR+ and TNBC tumors. Using mass spectrometry, we identified 57,094 unique MAPs in 26 primary breast cancer samples. MAP source genes highly overlapped between both subtypes. We identified 25 tumor-specific antigens (TSAs) mainly deriving from aberrantly expressed regions. TSAs were most frequently identified in TNBC samples and were more shared among The Cancer Genome Atlas (TCGA) database TNBC than HR+ samples. In the TNBC cohort, the predicted number of TSAs positively correlated with leukocytic infiltration and overall survival, supporting their immunogenicity in vivo. We detected 49 tumor-associated antigens (TAAs), some of which derived from cancer-associated fibroblasts. Functional expansion of specific T cell assays confirmed the in vitro immunogenicity of several TSAs and TAAs. Our study identified attractive targets for cancer immunotherapy in both breast cancer subtypes. The higher prevalence of TSAs in TNBC tumors provides a rationale for their responsiveness to checkpoint blockade.

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features

Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastases. In this pilot study, we hypothesized that computer extracted handcrafted (HC) histomorphometric features can be utilized to identify the PSO of liver metastases. Cellular features, including tumor nuclei morphological and graph features as well as cytoplasm texture features, were extracted by computer algorithms from 175 slides (114 patients). The study comprised three experiments: (1) comparing and (2) fusing a machine learning (ML) model trained with HC pathomic features and deep learning (DL)-based classifiers to predict site of origin; (3) identifying the section of the primary tumor from which metastases were derived. For experiment 1, we divided the cohort into training sets composed of primary and matched liver metastases [60 patients, 121 whole slide images (WSIs)], and a hold-out validation set (54 patients, 54 WSIs) composed solely of liver metastases of known site of origin. Using the extracted HC features of the training set, a combination of supervised machine classifiers and unsupervised clustering was applied to identify the PSO. A random forest classifier achieved areas under the curve (AUCs) of 0.83, 0.64, 0.82, and 0.64 in classifying the metastatic tumor from colon, esophagus, breast, and pancreas on the validation set. The top features related to nuclear and peri-nuclear shape and textural attributes. We also trained a DL network to serve as a direct comparison to our method. The DL model achieved AUCs for colon: 0.94, esophagus: 0.66, breast: 0.79, and pancreas: 0.67 in identifying PSO. A decision fusion-based strategy was deployed to fuse the trained ML and DL classifiers and achieved slightly better results than ML or DL classifier alone (colon: 0.93, esophagus: 0.68, breast: 0.81, and pancreas: 0.69). For the third experiment, WSI-level attention maps were also generated using a trained DL network to generate a composite feature similarity heat map between paired primaries and their associated metastases. Our experiments revealed that epithelium-rich and moderately differentiated tumor regions of primary tumors were quantitatively similar to paired metastatic tumors. Our findings suggest that a combination of HC and DL features could potentially help identify the PSO for liver metastases while at the same time also potentially identify the spatial sites of origin for the metastases within primary tumors.

PD-L1 and PD-1 Expression in Early Stage Uterine Endometrioid Carcinoma

BACKGROUND/AIM

Immune checkpoint inhibitors (ICI) and tumor-infiltrating lymphocytes (TILs) for cancer treatment in clinical oncology have revolutionized patient care. However, no gold standard exists for the criteria of analytical validity of TILs of different types of cancer.

MATERIALS AND METHODS

Clinicopathological data from 60 patients with endometrioid carcinoma (EC) who had undergone surgical treatment at the Gyeongsang National University Hospital between January 2002 and December 2009, were investigated. The programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PDL1) expression levels were characterized by immunohistochemical staining patterns, and the interpretations derived from machine learning morphometric analysis (Genie) and the pathologists' assessments were compared. In solid tumors, pathologists assessed the proportion of positive cells in each core of the tissue microarray. For Genie, the proportion of positive cells in the entire core and the number of positive cells per 1 mm2 were used.

RESULTS

Both the pathologists and Genie identified the same trend in association with tumor size, with significant differences (p=0.026, p=0.033). Genie expression showed a significant association with PD1 expression, and pathologists identified a significant association with PDL1 expression in immune cells.

CONCLUSION

The PD1 expression levels identified in immune cells of EC specimens were similar between the pathologists and Genie, suggesting that there is little resistance to the introduction of morphometric analysis. To our knowledge, this is the first study to introduce and validate machine learning as an integrated method for predicting prognosis and treatment based on PD1 expression in EC tumor microenvironments.

Adjuvant nivolumab, capecitabine or the combination in patients with residual triple-negative breast cancer: the OXEL randomized phase II study

Chemotherapy and immune checkpoint inhibitors have a role in the post-neoadjuvant setting in patients with triple-negative breast cancer (TNBC). However, the effects of nivolumab, a checkpoint inhibitor, capecitabine, or the combination in changing peripheral immunoscore (PIS) remains unclear. This open-label randomized phase II OXEL study (NCT03487666) aimed to assess the immunologic effects of nivolumab, capecitabine, or the combination in terms of the change in PIS (primary endpoint). Secondary endpoints include the presence of ctDNA, toxicity, clinical outcomes at 2-years and association of ctDNA and PIS with clinical outcomes. Forty-five women with TNBC and residual invasive disease after standard neoadjuvant chemotherapy were randomized to nivolumab, capecitabine, or the combination. Here we show that a combination of nivolumab plus capecitabine leads to a greater increase in PIS from baseline to week 6 (91%) compared with nivolumab (47%) or capecitabine (53%) alone (log-rank p = 0.08), meeting the pre-specified primary endpoint. In addition, the presence of circulating tumor DNA (ctDNA) was associated with disease recurrence, with no new safety signals in the combination arm. Our results provide efficacy and safety data on this combination in TNBC and support further development of PIS and ctDNA analyses to identify patients at high risk of recurrence.

Evaluation of tumor-infiltrating lymphocytes, PD-L1, and PIK3CA mutations and association with prognosis in HER2-positive early stage breast cancer

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) have predictive and prognostic potential in HER2-positive breast cancer (HER2+ BC). Programmed death-ligand 1 (PD-L1) is an immune checkpoint protein, with important roles in the tumor microenvironment, possibly in both tumor and immune cells (ICs), providing rationale for targeting with immune-checkpoint therapy. PIK3CA mutations are oncogenic, activating mutations, which are also of relevance in breast cancer. Herein, we investigate the frequency of TILs, PD-L1 and PIK3CA mutations, and whether these factors influence outcome, in early HER2+ BC.

MATERIALS AND METHODS

Stromal TILs (sTILs) and PD-L1 expressions were assessed using full tumor-sections and TMA, respectively, from 236 patients with HER2+ BC. TILs were assessed, according to a standardized method, as continuous measurement and according to three predefined categories: low (0-10%), intermediate (11-59%), and high (60-100%). PD-L1 immunohistochemistry (Ventana SP263) was evaluated and positivity defined as ≥1% expression in tumor and ICs. PIK3CA mutations (exons 9 and 20) were determined by pyrosequencing.

RESULTS

Fourteen percent of patients had high sTILs and 25% had a PIK3CA mutation. PD-L1 expression was more frequent in ICs (68%) than tumor cells (24%). Patients with low sTILs had a significantly worse overall survival (multivariate: HR 2.80; 95% CI 1.36-5.78; p = .02).

DISCUSSION

Patients with low sTILs had a significantly poorer survival, despite adequate treatment with adjuvant therapy.

A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives

Breast cancer is one of the most common and deadly cancers worldwide. Approximately, 20% of all breast cancers are characterized as triple negative (TNBC). TNBC typically is associated with a poorer prognosis relative to other breast cancer subtypes. Due to its aggressiveness and lack of response to hormonal therapy, conventional cytotoxic chemotherapy is the usual treatment; however, this treatment is not always effective, and an important percentage of patients develop recurrence. More recently, immunotherapy has started to be used on some populations with TNBC showing promising results. Unfortunately, immunotherapy is only applicable to a minority of patients and responses in metastatic TNBC have overall been modest in comparison to other cancer types. This situation evidences the need for developing effective biomarkers that help to stratify and personalize patient management. Thanks to recent advances in artificial intelligence (AI), there has been an increasing interest in its use for medical applications aiming at supporting clinical decision making. Several works have used AI in combination with diagnostic medical imaging, more specifically radiology and digitized histopathological tissue samples, aiming to extract disease-specific information that is difficult to quantify by the human eye. These works have demonstrated that analysis of such images in the context of TNBC has great potential for (1) risk-stratifying patients to identify those patients who are more likely to experience disease recurrence or die from the disease and (2) predicting pathologic complete response. In this manuscript, we present an overview on AI and its integration with radiology and histopathological images for developing prognostic and predictive approaches for TNBC. We present state of the art approaches in the literature and discuss the opportunities and challenges with developing AI algorithms regarding further development and clinical deployment, including identifying those patients who may benefit from certain treatments (e.g., adjuvant chemotherapy) from those who may not and thereby should be directed toward other therapies, discovering potential differences between populations, and identifying disease subtypes.

Semi-reference based cell type deconvolution with application to human metastatic cancers

Bulk RNA-seq experiments, commonly used to discern gene expression changes across conditions, often neglect critical cell type-specific information due to their focus on average transcript abundance. Recognizing cell type contribution is crucial to understanding phenotype and disease variations. The advent of single-cell RNA sequencing has allowed detailed examination of cellular heterogeneity; however, the cost and analytic caveat prohibits such sequencing for a large number of samples. We introduce a novel deconvolution approach, SECRET, that employs cell type-specific gene expression profiles from single-cell RNA-seq to accurately estimate cell type proportions from bulk RNA-seq data. Notably, SECRET can adapt to scenarios where the cell type present in the bulk data is unrepresented in the reference, thereby offering increased flexibility in reference selection. SECRET has demonstrated superior accuracy compared to existing methods using synthetic data and has identified unknown tissue-specific cell types in real human metastatic cancers. Its versatility makes it broadly applicable across various human cancer studies.

Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics

OBJECTIVE

To generate an image-driven biomarker (Rad_score) to predict tumor-infiltrating regulatory T lymphocytes (Treg) in breast cancer (BC).

METHODS

Overall, 928 BC patients were enrolled from the Cancer Genome Atlas (TCGA) for survival analysis; MRI (n = 71 and n = 30 in the training and validation sets, respectively) from the Cancer Imaging Archive (TCIA) were retrieved and subjected to repeat least absolute shrinkage and selection operator for feature reduction. The radiomic scores (rad_score) for Treg infiltration estimation were calculated via support vector machine (SVM) and logistic regression (LR) algorithms, and validated on the remaining patients.

RESULTS

Landmark analysis indicated Treg infiltration was a risk factor for BC patients in the first 5 years and after 10 years of diagnosis (p = 0.007 and 0.018, respectively). Altogether, 108 radiomic features were extracted from MRI images, 4 of which remained for model construction. Areas under curves (AUCs) of the SVM model were 0.744 (95% CI 0.622-0.867) and 0.733 (95% CI 0.535-0.931) for training and validation sets, respectively, while for the LR model, AUCs were 0.771 (95% CI 0.657-0.885) and 0.724 (95% CI 0.522-0.926). The calibration curves indicated good agreement between prediction and true value (p > 0.05), and DCA shows the high clinical utility of the radiomic model. Rad_score was significantly correlated with immune inhibitory genes like CTLA4 and PDCD1.

CONCLUSIONS

High Treg infiltration is a risk factor for patients with BC. The Rad_score formulated on radiomic features is a novel tool to predict Treg abundance in the tumor microenvironment.

Immune checkpoint inhibitors in breast cancer: development, mechanisms of resistance and potential management strategies

The use of immune checkpoint inhibitors (ICIs) has increased exponentially in the past decade, although its progress specifically for breast cancer has been modest. The first U.S. Food and Drug Administration approval for ICI in breast cancer came in 2019, eight years after the first-ever approval of an ICI. At present, current indications for ICIs are relevant only to a subset of patients with triple-negative breast cancer, or those displaying high microsatellite instability or deficiency in the mismatch repair protein pathway. With an increasing understanding of the limitations of using ICIs, which stem from breast cancer being innately poorly immunogenic, as well as the presence of various intrinsic and acquired resistance pathways, ongoing trials are evaluating different combination therapies to overcome these barriers. In this review, we aim to describe the development timeline of ICIs and resistance mechanisms limiting their utility, and summarise the available approaches and ongoing trials relevant to overcoming each resistance mechanism.

Advances in Early Breast Cancer Risk Profiling: From Histopathology to Molecular Technologies

Early breast cancer (BC) is the definition applied to breast-confined tumors with or without limited involvement of locoregional lymph nodes. While risk stratification is essential for guiding clinical decisions, it can be a complex endeavor in these patients due to the absence of comprehensive guidelines. Histopathological analysis and biomarker assessment play a pivotal role in defining patient outcomes. Traditional histological criteria such as tumor size, lymph node involvement, histological type and grade, lymphovascular invasion, and immune cell infiltration are significant prognostic indicators. In addition to the hormone receptor, HER2, and-in specific scenarios-BRCA1/2 testing, molecular subtyping through gene expression profiling provides valuable insights to tailor clinical decision-making. The emergence of "omics" technologies, applicable to both tissue and liquid biopsy samples, has broadened our arsenal for evaluating the risk of early BC. However, a pressing need remains for standardized methodologies and integrated pathological models that encompass multiple analytical dimensions. In this study, we provide a detailed examination of the existing strategies for early BC risk stratification, intending to serve as a practical guide for histopathologists and molecular pathologists.

Immunohistological analysis of B7-H4, IDO1, and PD-L1 expression and tumor immune microenvironment based on triple-negative breast cancer subtypes

BACKGROUND

B7 homolog 4 (B7-H4) and indoleamine 2,3-dioxygenase (IDO1) are factors involved in the inhibition of antitumor activity and are new therapeutic targets for immune checkpoint therapy. Our study aimed to simultaneously investigate the interrelationship among B7-H4, IDO1 and programmed cell death ligand 1 (PD-L1) expression in triple-negative breast cancer (TNBC), including tumor immune microenvironment (TIME) and TNBC subtypes.

METHODS

Immunostaining for PD-L1, B7-H4, and IDO1 was performed on whole-slide sections of 119 cases of TNBC. The TIME was evaluated based on stromal tumor infiltrating lymphocytes (sTILs; %), pattern classification of TILs, tumor-stroma ratio (TSR), and tertiary lymphoid structure (TLS). TNBC subtypes were also determined by immunohistochemistry analysis of cytokeratin 5/6 and androgen receptor (AR) expression.

RESULTS

B7-H4 expression was significantly higher in cases with a combined positive score cutoff of 5 for PD-L1 (clone 28-8; p = 0.021), inflamed TIL pattern (p = 0.007), and TLS ≥ 4 (p = 0.006). B7-H4 expression was higher in case of CK5/6 ≥ 10 (p = 0.035). The H-scores of AR and B7-H4 were inversely correlated (ρ = - 0.509, p < 0.001). B7-H4 and IDO1 expression levels were inversely correlated in cases with AR < 10 (ρ = - 0.354, p < 0.001).

CONCLUSIONS

These results suggest that considering the TIL pattern and TLS and identifying the expression of PD-L1 and the basal-like type are useful for estimating B7-H4 expression. In addition, luminal androgen receptor (LAR)-type is frequently deficient in B7-H4 expression. In non-LAR types, B7-H4 and IDO1 expression are exclusive.

Evaluation of tumour infiltrating lymphocytes in luminal breast cancer using artificial intelligence

BACKGROUND

Tumour infiltrating lymphocytes (TILs) are a prognostic parameter in triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). However, their role in luminal (oestrogen receptor positive and HER2 negative (ER + /HER2-)) BC remains unclear. In this study, we used artificial intelligence (AI) to assess the prognostic significance of TILs in a large well-characterised cohort of luminal BC.

METHODS

Supervised deep learning model analysis of Haematoxylin and Eosin (H&E)-stained whole slide images (WSI) was applied to a cohort of 2231 luminal early-stage BC patients with long-term follow-up. Stromal TILs (sTILs) and intratumoural TILs (tTILs) were quantified and their spatial distribution within tumour tissue, as well as the proportion of stroma involved by sTILs were assessed. The association of TILs with clinicopathological parameters and patient outcome was determined.

RESULTS

A strong positive linear correlation was observed between sTILs and tTILs. High sTILs and tTILs counts, as well as their proximity to stromal and tumour cells (co-occurrence) were associated with poor clinical outcomes and unfavourable clinicopathological parameters including high tumour grade, lymph node metastasis, large tumour size, and young age. AI-based assessment of the proportion of stroma composed of sTILs (as assessed visually in routine practice) was not predictive of patient outcome. tTILs was an independent predictor of worse patient outcome in multivariate Cox Regression analysis.

CONCLUSION

AI-based detection of TILs counts, and their spatial distribution provides prognostic value in luminal early-stage BC patients. The utilisation of AI algorithms could provide a comprehensive assessment of TILs as a morphological variable in WSIs beyond eyeballing assessment.

Implications of tumor-infiltrating lymphocytes in early-stage triple-negative breast cancer: clinical oncologist perspectives

Breast cancer (BC) is the most common neoplasm in women worldwide and one of the leading causes of female death. The triple-negative subtype, characterized by the absence of hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2), tends to occur in younger patients, be more aggressive and less differentiated. Furthermore, this subtype is considered the most immunogenic and associated with higher levels of tumor cell infiltration, mainly lymphocytes. Tumor-infiltrating lymphocytes (TILs) play a crucial role in the interaction of the host's immune system and cancer cells. The microenvironment is critical in tumor development and progression. Assessment of infiltrating lymphocytes can provide valuable information about the immune response and, given the lack of biomarkers to guide treatment decisions and predict outcomes in triple-negative tumors and can be considered as a potential biomarker. Some evidence suggests that higher levels of these lymphocytes are associated with better responses to systemic treatment, longer progression-free survival and overall survival (OS). However, treatment escalation or de-escalation strategies for triple-negative BC (TNBC) currently do not consider the presence or density of TILs for therapeutic decisions. TILs appear to be useful predictive and prognostic indicators. Further clinical studies are needed to confirm these relationships and integrate TILs as a biomarker consistently into clinical practice. This article summarizes key concepts relating to the role of the immune infiltrate in BC, along with the current status and future prospects regarding TILs as a predictive and prognostic biomarker.

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.

Intratumoral Tumor Infiltrating Lymphocytes (TILs) are Associated With Cell Proliferation and Better Survival But Not Always With Chemotherapy Response in Breast Cancer

OBJECTIVE

To investigate the clinical relevance of intratumoral tumor infiltrating lymphocytes (TILs) in breast cancer as measured by computational deconvolution of bulk tumor transcriptomes.

SUMMARY BACKGROUND DATA

Commonly assessed TILs, located in tumor stroma without direct contact with cancer cells (stromal TILs), correlate with breast cancer treatment response and survival. The clinical relevance of intratumoral TILs has been less studied partly due to their rarity; however, they may have nonnegligible effects given their direct contact with cancer cells.

METHODS

In all, 5870 breast cancer patients from TCGA, METABRIC, GSE96058, GSE25066, GSE163882, GSE123845, and GSE20271 cohorts were analyzed and validated.

RESULTS

The intratumoral TIL score was established by the sum of all types of lymphocytes using the xCell algorithm. This score was the highest in triple-negative breast cancer (TNBC) and the lowest in the ER-positive/HER2-negative subtype. It correlated with cytolytic activity and infiltrations of dendritic cells, macrophages, and monocytes, and uniformly enriched immune-related gene sets regardless of subtype. Intratumoral TIL-high tumors correlated with higher mutation rates and significant cell proliferation on biological, pathological, and molecular analyses only in the ER-positive/HER2-negative subtype. It was significantly associated with pathological complete response after anthracycline- and taxane-based neoadjuvant chemotherapy in about half of the cohorts, regardless of the subtype. Intratumoral TIL-high tumors correlated with better overall survival in HER2-positive and TNBC subtypes consistently in 3 cohorts.

CONCLUSIONS

Intratumoral TILs estimated by transcriptome computation were associated with increased immune response and cell proliferation in ER-positive/HER2-negative and better survival in HER2-positive and TNBC subtypes, but not always with pathological complete response after neoadjuvant chemotherapy.

Individualising radiation therapy decisions in breast cancer patients based on tumour infiltrating lymphocytes and genomic biomarkers

Radiation therapy (RT) has long been fundamental for the curative treatment of breast cancer. While substantial progress has been made in the anatomical and technological precision of RT delivery, and some approaches to de-escalate or omit RT based on clinicopathologic features have been successful, there remain substantial opportunities to refine individualised RT based on tumour biology. A major area of clinical and research interest is to ascertain the individualised risk of loco-regional recurrence to direct treatment decisions regarding escalation and de-escalation of RT. Patient-tailored treatment with RT is considerably lagging behind compared with the massive progress made in the field of personalised medicine that currently mainly applies to decisions on the use of systemic therapy or targeted agents. Herein we review select literature surrounding the use of tumour genomic biomarkers and biomarkers of the immune system, including tumour infiltrating lymphocytes (TILs), within the management of breast cancer, specifically as they relate to progress in moving toward analytically validated and clinically tested biomarkers utilized in RT.

S100A8/A9 predicts triple-negative breast cancer response to PIM kinase and PD-1/PD-L1 inhibition

It remains elusive why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well. Our retrospective analysis of historical gene expression datasets reveals that increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors is robustly associated with subsequent disease progression in TNBC. Although it has recently gained recognition as a potential anticancer target, S100A8/A9 has not been integrated into clinical study designs evaluating molecularly targeted therapies. Our small molecule screen has identified PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Furthermore, combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Importantly, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC. Thus, our data suggest that S100A8/A9 could be a predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC and encourage the development of S100A8/A9-based liquid biopsy tests.

Emerging systemic therapy options beyond CDK4/6 inhibitors for hormone receptor-positive HER2-negative advanced breast cancer

Endocrine therapy (ET) with cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) is currently the standard first-line treatment for most patients with hormone receptor (HR) positive, human epidermal growth factor receptor (HER2) negative advanced breast cancer. However, resistance to ET and CDK4/6i inevitably ensues. The optimal post-progression treatment regimens and their sequencing continue to evolve in the rapidly changing treatment landscape. In this review, we summarize the mechanisms of resistance to ET and CDK4/6i, which can be broadly classified as alterations affecting cell cycle mediators and activation of alternative signaling pathways. Recent clinical trials have been directed at the targets and pathways implicated, including estrogen and androgen receptors, PI3K/AKT/mTOR and MAPK pathways, tyrosine kinase receptors such as FGFR and HER2, homologous recombination repair pathway, other components of the cell cycle and cell death. We describe the findings from these clinical trials using small molecule inhibitors, antibody-drug conjugates and immunotherapy, providing insights into how these novel strategies may circumvent treatment resistance, and discuss how some have not translated into clinical benefit. The challenges posed by tumor heterogeneity, adaptive rewiring of signaling pathways and dose-limiting toxicities underscore the need to elucidate the latest tumor biology in each patient, and develop treatments with improved therapeutic index in the era of precision medicine.