Integration of tumour infiltrating lymphocytes, programmed cell-death ligand-1, CD8 and FOXP3 in prognostic models for triple-negative breast cancer: Analysis of 244 stage I-III patients treated with standard therapy

A review concerning the breast cancer-related tumour microenvironment

Breast cancer (BC) is currently the most common malignant tumour in women and one of the leading causes of their death around the world. New and increasingly personalised diagnostic and therapeutic tools have been introduced over the last few decades, along with significant advances regarding the study and knowledge related to BC. The tumour microenvironment (TME) refers to the tumour cell-associated cellular and molecular environment which can influence conditions affecting tumour development and progression. The TME is composed of immune cells, stromal cells, extracellular matrix (ECM) and signalling molecules secreted by these different cell types. Ever deeper understanding of TME composition changes during tumour development and progression will enable new and more innovative therapeutic strategies to become developed for targeting tumours during specific stages of its evolution. This review summarises the role of BC-related TME components and their influence on tumour progression and the development of resistance to therapy. In addition, an account on the modifications in BC-related TME components associated with therapy is given, and the completed or ongoing clinical trials related to this topic are presented.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Pathologic and immunohistochemical prognostic markers in residual triple-negative breast cancer after neoadjuvant chemotherapy

Background

The persistence of residual tumour after neoadjuvant chemotherapy (NAC) in localised triple-negative breast cancer (TNBC) is known to have a negative prognostic value. However, different degrees of expression of some immunohistochemical markers may correlate with different prognoses.

Methods

The expression of biomarkers with a known prognostic value, i.e., cytokeratin 5/6 (CK5/6), androgen receptor (AR), epidermal growth factor receptor (EGFR) proliferation-related nuclear antigen Ki-67, human epidermal growth factor receptor 2 (HER2), protein 53 (p53), forkhead box protein 3 (FOXP3), and cluster differentiation 8 (CD8), was analysed by immunohistochemistry in 111 samples after NAC in non-metastatic TNBC patients addressed to Georges-François Leclerc Cancer Centre Dijon, France. Clinical and pathological variables were retrospectively collected. Cox regression was used to identify immunohistochemical (IHC) and clinicopathological predictors of event-free survival (EFS) (relapse or death).

Results

Median age was 50.4 years (range 25.6-88.3), 55.9% (n = 62) were non-menopausal, 70 (63.1%) had stage IIA-IIB disease. NAC was mostly sequential anthracycline-taxanes (72.1%), and surgical intervention was principally conservative (51.3%). We found 65.7% ypT1, 47.2% lymph node involvement (ypN+), and 29.4% lymphovascular invasion (LVI). Most residual tumours were EGFR >110 (H-score) (60.5%, n = 66), AR ≥4% (53.2%, n = 58), p53-positive mutated (52.7%, n = 58), CD8 ≥26 (58.1%, n = 61), FOXP3 ≥7 (51.4%, n = 54), more than half in the stroma, and 52.3% (n = 58) HER2 score 0. After a median follow-up of 80.8 months, 48.6% had relapsed. Median EFS was 62.3 months (95% CI, 37.2-not reached (NR)). Factors independently associated with poor EFS were AR-low (p = 0.002), ypN+ (p < 0.001), and LVI (p = 0.001). Factors associated with lower overall survival (OS) were EGFR-low (p = 0.041), Ki-67 high (p = 0.024), and ypN+ (p < 0.001).

Conclusion

Post-NAC residual disease in TNBC showed biomarkers specific to a basal-like subtype and markers of lymphocyte infiltration mostly present in the stroma. Prognostic markers for EFS were AR, LVI, and ypN and warrant further validation in a prognostic model.

Massage on the prevention of breast cancer through stress reduction and enhancing immune system

INTRODUCTION

Housewives are a population at high risk of breast cancer due to repeated or chronic exposure to stress. Prevention in a simple yet evidence-based manner is needed.

METHODS

This study is a narrative review of the potential of massage as breast cancer prevention through stress and immune system mechanisms.

RESULTS

Massage is able to prevent chronic stress through improved sleep and fatigue and lower stress levels. Prevention of chronic stress will maximize the function of cells that eliminate cancer cells, such as B cells, T cells, and natural killer (NK) cells, and improve the balance of Foxp3 Tregulator cells. Partnered delivery massage will bring effective benefits for stress reduction.

CONCLUSIONS

Massage can provide indirect prevention of breast cancer, and partnered delivery massage can be a good choice to reduce stress.

Prognostic Value of Immunohistochemistry-based Subtyping Before and After Neoadjuvant Chemotherapy in Patients with Triple-negative Breast Cancer

To assess the predictive and prognostic value of a subtyping method based on immunohistochemistry in patients with triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC). This study included patients with TNBC treated with anthracycline- and taxane-based NAC and curative surgery. Immunohistochemical (IHC) subtyping was performed using core needle biopsy specimens before NAC (pre-NAC) and residual tumors after NAC (post-NAC). Logistic regression was performed to identify predictive biomarkers of pathological complete response (pCR). Invasive disease-free survival (iDFS), distant disease-free survival (DDFS), and overall survival (OS) were assessed using the log-rank test and Cox proportional hazards regression. A total of 230 patients were followed up for a median of 59 months. Clinical lymph node status and the pre-NAC subtype were independent predictors of pCR (P=0.006 and 0.005, respectively). The pre-NAC subtype was an independent prognostic factor for long-term survival (iDFS: P < 0.001, DDFS: P=0.010, and OS: P=0.044). Among patients with residual disease (RD) after NAC, approximately 45% of tumors changed their IHC subtype. Furthermore, the post-NAC subtype, but not the pre-NAC subtype, was strongly associated with the survival of patients with RD (iDFS: P < 0.001, DDFS: P=0.005, and OS: P=0.006). The IHC subtype predicted response to NAC and long-term survival in patients with early TNBC. In patients with RD, almost 45% of the tumors changed subtype after NAC. The IHC subtype should be considered when planning additional therapies pre- and post-NAC.

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.

The prognostic value of a combined immune score in tumor and immune cells assessed by immunohistochemistry in triple-negative breast cancer

BACKGROUND

This study aimed to develop a novel combined immune score (CIS)-based model assessing prognosis in triple-negative breast cancer (TNBC).

METHODS

The expression of eight immune markers (PD-1, PD-L1, PD-L2, IDO, TIM3, OX40, OX40L, and H7-H2) was assessed with immunohistochemistry on the tumor cells (TCs) and immune cells (ICs) of 227 TNBC cases, respectively, and subsequently associated with selected clinicopathological parameters and survival. Data retrieved from The Cancer Genome Atlas (TCGA) were further examined to validate our findings.

RESULTS

All immune markers were often expressed in TCs and ICs, except for PD-1 which was not expressed in TCs. In ICs, the expression of all immune markers was positively correlated between one another, except between PD-L1 and OX40, also TIM3 and OX40. In ICs, PD-1, PD-L1, and OX40L positive expression was associated with a longer progression-free survival (PFS; p = 0.040, p = 0.020, and p = 0.020, respectively). In TCs, OX40 positive expression was associated with a shorter PFS (p = 0.025). Subsequently, the TNBC patients were classified into high and low combined immune score groups (CIS-H and CIS-L), based on the expression levels of a selection of biomarkers in TCs (TCIS-H or TCIS-L) and ICs (ICIS-H or ICIS-L). The TCIS-H group was significantly associated with a longer PFS (p < 0.001). Furthermore, the ICIS-H group was additionally associated with a longer PFS (p < 0.001) and overall survival (OS; p = 0.001), at significant levels. In the multivariate analysis, both TCIS-H and ICIS-H groups were identified as independent predictors of favorable PFS (p = 0.012 and p = 0.001, respectively). ICIS-H was also shown to be an independent predictor of favorable OS (p = 0.003). The analysis of the mRNA expression data from TCGA also validated our findings regarding TNBC.

CONCLUSION

Our novel TCIS and ICIS exhibited a significant prognostic value in TNBC. Additional research would be needed to strengthen our findings and identify the most efficient prognostic and predictive biomarkers for TNBC patients.

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.

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

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

Prognostic Implications of the Residual Tumor Microenvironment after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Patients without Pathological Complete Response

With a high risk of relapse and death, and a poor or absent response to therapeutics, the triple-negative breast cancer (TNBC) subtype is particularly challenging, especially in patients who cannot achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Although the tumor microenvironment (TME) is known to influence disease progression and the effectiveness of therapeutics, its predictive and prognostic potential remains uncertain. This work aimed to define the residual TME profile after NAC of a retrospective cohort with 96 TNBC patients by immunohistochemical staining (cell markers) and chromogenic in situ hybridization (genetic markers). Kaplan-Meier curves were used to estimate the influence of the selected TME markers on five-year overall survival (OS) and relapse-free survival (RFS) probabilities. The risks of each variable being associated with relapse and death were determined through univariate and multivariate Cox analyses. We describe a unique tumor-infiltrating immune profile with high levels of lymphocytes (CD4, FOXP3) and dendritic cells (CD21, CD1a and CD83) that are valuable prognostic factors in post-NAC TNBC patients. Our study also demonstrates the value of considering not only cellular but also genetic TME markers such as MUC-1 and CXCL13 in routine clinical diagnosis to refine prognosis modelling.

Tumor immune microenvironment components and the other markers can predict the efficacy of neoadjuvant chemotherapy for breast cancer

Breast cancer is an epithelial malignant tumor that occurs in the terminal ducts of the breast. Neoadjuvant chemotherapy (NACT) is an important part of breast cancer treatment. Its purpose is to use systemic treatment for some locally advanced breast cancer patients, to decrease the tumor size and clinical stage so that non-operable breast cancer patients can have a chance to access surgical treatment, or patients who are not suitable for breast-conserving surgery can get the opportunity of breast-conserving. However, some patients who do not respond to NACT will lead deterioration in their condition. Therefore, prediction of NACT efficacy in breast cancer is vital for precision therapy. The tumor microenvironment (TME) has a crucial role in the carcinogenesis and therapeutic response of breast cancer. In this review, we summarized the immune cells, immune checkpoints, and other biomarkers in the TME that can evaluate the efficacy of NACT in treating breast cancer. We believe that the detection and evaluation of the TME components in breast cancer are helpful to predict the efficacy of NACT, and the prediction methods are in the prospect. In addition, we also summarized other predictive factors of NACT, such as imaging examination, biochemical markers, and multigene/multiprotein profiling.

Integrative prognostic analysis of tumor-infiltrating lymphocytes, CD8, CD20, programmed cell death-ligand 1, and tertiary lymphoid structures in patients with early-stage triple-negative breast cancer who did not receive adjuvant chemotherapy

PURPOSE

Stromal tumor-infiltrating lymphocytes (TILs) are independent prognostic factors in systemically untreated early-stage triple-negative breast cancer (TNBC). Other immune biomarkers including CD8, CD20, programmed cell death-ligand 1 (PD-L1), and tertiary lymphoid structures (TLS) are also reported to be associated with prognosis. However, whether combining other immune biomarkers with TILs would allow for further prognostic stratification is unknown.

METHODS

We retrospectively analyzed 125 patients with early-stage TNBC not receiving perioperative chemotherapy. Stromal TILs and TLS were evaluated on hematoxylin-eosin slides. PD-L1 expression was evaluated using the SP142 assay. CD8 and CD20 were assessed by immunohistochemistry and counted by digital pathology.

RESULTS

Immune biomarker levels were positively correlated (p < 0.001). Adding CD8 and PD-L1 to multivariable analysis including clinicopathological factors (stage and histological grade) and TILs significantly improved the prognostic model (likelihood ratio χ² = 9.24, p = 0.01). In Cox regression analysis, high CD8 was significantly associated with better prognosis [hazard ratio (HR) 0.69, 95% confidence interval (CI) 0.48-0.98, p = 0.04], and PD-L1 positivity was significantly associated with worse prognosis (HR 4.33, 95%CI 1.57-11.99, p = 0.005). Patients with high CD8/PD-L1 (-) tumors had the most favorable prognosis [5 year invasive disease-free survival (iDFS), 100%], while patients with low CD8/PD-L1( +) tumors had the worst prognosis (5 year iDFS, 33.3%).

CONCLUSION

CD8 and PD-L1 levels add prognostic information beyond TILs for early-stage TNBC not receiving perioperative chemotherapy. CD8-positive T cells and PD-L1 may be useful for prognostic stratification and in designing future clinical trials of TNBC.

Radiomic models based on magnetic resonance imaging predict the spatial distribution of CD8+ tumor-infiltrating lymphocytes in breast cancer

Infiltration of CD8⁺ T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8⁺ T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-whole_FC) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-peri_FC) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-whole_FC and RM-peri_FC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-whole_FC and lower scores from RM-peri_FC. Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8⁺ T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment.

Association of tumor immune microenvironment profiling and 21-gene recurrence assay in early breast cancer patients

INTRODUCTION

Tumor immune microenvironment (TIME) plays a vital role in breast cancer development, treatment resistance, and prognosis. This study evaluates the association of TIME profiling and 21-gene recurrence score (RS) in early Luminal breast cancer patients.

METHODS

ER+ /HER2-, pN0 breast cancer patients with available RS results who received surgery between January 2009 and December 2013 were enrolled. TIME markers, including stromal tumor infiltrating lymphocytes (TILs), CD3, CD4, CD8, and tumor PD-L1 expression, were comprehensively analyzed. Association of TIME markers with RS, as well as their correlation with breast cancer-specific survival (BCSS) were tested.

RESULTS

Overall, 385 patients were included, of whom 341 (88.6%) had TILs ≤10%. TIME markers were positively but moderately correlated with each other (Spearman r 0.28-0.53, all P < 0.05). Continuous RS showed a weak correlation with continuous TILs, CD3, CD8, and PD-L1. Regarding single gene mRNA level in the 21-gene RS panel, higher expression of TIME markers was related to lower ER group genes expression, but higher proliferation and invasion group genes level. After a median follow-up of 91.67 (range 5.03-134.03) months, TILs (P = 0.049) and PD-L1 (P = 0.034) were inversely associated with BCSS.

CONCLUSIONS

Breast cancer TIME markers, including TILs, CD3, CD4, CD8, and PD-L1, were correlated with 21-gene RS score. Lower expression of ER group genes, as well as higher expression of proliferation and invasion group genes were associated with a higher level of these TIME markers, warranting further exploration.

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

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

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.

A comprehensive profiling of the immune microenvironment of breast cancer brain metastases

BACKGROUND

Despite potential clinical implications, the complexity of breast cancer (BC) brain metastases (BM) immune microenvironment is poorly understood. Through multiplex immunofluorescence, we here describe the main features of BCBM immune microenvironment (density and spatial distribution) and evaluate its prognostic impact.

METHODS

Sixty BCBM from patients undergoing neurosurgery at three institutions (2003-2018) were comprehensively assessed using two multiplex immunofluorescence panels (CD4, CD8, Granzyme B, FoxP3, CD68, pan-cytokeratin, DAPI; CD3, PD-1, PD-L1, LAG-3, TIM-3, CD163, pan-cytokeratin, DAPI). The prognostic impact of immune subpopulations and cell-to-cell spatial interactions was evaluated.

RESULTS

Subtype-related differences in BCBM immune microenvironment and its prognostic impact were observed. While in HR-/HER2- BM and HER2+ BM, higher densities of intra-tumoral CD8+ lymphocytes were associated with significantly longer OS (HR 0.16 and 0.20, respectively), in HR+/HER2- BCBMs a higher CD4+FoxP3+/CD8+ cell ratio in the stroma was associated with worse OS (HR 5.4). Moreover, a higher density of intra-tumoral CD163+ M2-polarized microglia/macrophages in BCBMs was significantly associated with worse OS in HR-/HER2- and HR+/HER2- BCBMs (HR 6.56 and 4.68, respectively), but not in HER2+ BCBMs. In HER2+ BCBMs, multiplex immunofluorescence highlighted a negative prognostic role of PD-1/PD-L1 interaction: patients with a higher percentage of PD-L1+ cells spatially interacting with (within a 20 µm radius) PD-1+ cells presented a significantly worse OS (HR 4.60).

CONCLUSIONS

Our results highlight subtype-related differences in BCBM immune microenvironment and identify two potential therapeutic targets, M2 microglia/macrophage polarization in HER2- and PD-1/PD-L1 interaction in HER2+ BCBMs, which warrant future exploration in clinical trials.

Prognostic Role of PD-L1 Expression in Invasive Breast Cancer: A Systematic Review and Meta-Analysis

Simple Summary

The role of PD-L1 expression in breast cancer remains controversial. Therefore, we performed a systematic review and meta-analysis to assess the association of PD-L1 expression with clinicopathological variables, overall survival (OS), and disease-free survival (DFS) in invasive breast cancer. PD-L1 expression was associated with age ≥ 50 years, lymph node status-negative, progesterone receptor-negative, Ki67 ≥ 20%, and human epidermal growth factor receptor 2 (HER2)-negative. PD-L1 positivity was associated with worse OS; however, there was no significant improvement in DFS. PD-L1 positivity was significantly associated with the clinicopathological characteristics of favorable and unfavorable prognoses. However, the final clinical outcome was associated with lower OS and had no significant association with DFS.

Abstract

Programmed death ligand 1 (PD-L1) has been investigated in various types of cancer; however, the role of PD-L1 expression in breast cancer remains controversial. We performed a systematic review and meta-analysis to assess the association of PD-L1 expression with clinicopathological variables, overall survival (OS), and disease-free survival (DFS) in invasive breast cancer. A total of 965 articles were included from CINAHL, Embase, PubMed, and Scopus databases. Of these, 22 studies encompassing 6468 cases of invasive breast cancer were included in the systematic review, and 15 articles were included in the meta-analysis. PD-L1 expression was associated with age ≥ 50 years, lymph node status-negative, progesterone receptor-negative, Ki67 ≥ 20%, and human epidermal growth factor receptor 2 (HER2)-negative. PD-L1 positivity was associated with worse OS (hazard ratio, HR, 2.39; 95% confidence interval, CI, 1.26–3.52; p =< 0.000); however, there was no significant improvement in DFS (HR 0.17; 95% CI −0.12–0.46; p =< 0.252). PD-L1 positivity was significantly associated with the clinicopathological characteristics of favorable and unfavorable prognoses. However, the final clinical outcome was associated with lower OS and had no significant association with DFS.

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

High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland-Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from -0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the 'ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.

Tumour-infiltrating CD4-, CD8- and FOXP3-positive immune cells as predictive markers of mortality in BRCA1- and BRCA2-associated breast cancer

BACKGROUND

The prognostic value of tumour-infiltrating lymphocytes (TILs) in breast cancer is well-established. However, the investigation of specific T-cell subsets exclusively in BRCA-associated breast cancer is sparse.

METHODS

Tumour tissues from 414 BRCA-mutated breast cancer patients were analysed by immunohistochemistry and digital image analysis for expression of CD4, CD8 and FOXP3 immune markers. Distribution of CD4-, CD8- and FOXP3-positive cells and clinicopathological characteristics were assessed according to groups of low or high expression. The prognostic value was evaluated as continuous variables in univariate and multivariate analyses of overall survival and disease-free survival.

RESULTS

Both CD4 and CD8 expression are associated with histological diagnosis, tumour grade and oestrogen and progesterone receptor expression status. CD4 expression is associated with BRCA gene status. A high percentage of tumour-infiltrating CD4-, CD8- or FOXP3-positive cells is significantly associated with lower mortality in BRCA1- and BRCA2-associated breast cancer and CD8-positive cells are associated with disease-free survival. No heterogeneity according to BRCA gene status was found for the prognostic value of the immune markers.

CONCLUSIONS

The results support a prognostic role of specific T-cell subsets in BRCA-associated breast cancer and the promising potential of targeting the immune system in the treatment of these patients.

How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction

Differences between computer-assisted image analysis (CAI) algorithms may cause discrepancies in the identification of immunohistochemically stained immune biomarkers in biopsies of breast cancer patients. These discrepancies have implications for their association with disease outcome. This study aims to compare three CAI procedures (A, B and C) to measure positive marker areas in post-neoadjuvant chemotherapy biopsies of patients with triple-negative breast cancer (TNBC) and to explore the differences in their performance in determining the potential association with relapse in these patients. A total of 3304 digital images of biopsy tissue obtained from 118 TNBC patients were stained for seven immune markers using immunohistochemistry (CD4, CD8, FOXP3, CD21, CD1a, CD83, HLA-DR) and were analyzed with procedures A, B and C. The three methods measure the positive pixel markers in the total tissue areas. The extent of agreement between paired CAI procedures, a principal component analysis (PCA) and Cox multivariate analysis was assessed. Comparisons of paired procedures showed close agreement for most of the immune markers at low concentration. The probability of differences between the paired procedures B/C and B/A was generally higher than those observed in C/A. The principal component analysis, largely based on data from CD8, CD1a and HLA-DR, identified two groups of patients with a significantly lower probability of relapse than the others. The multivariate regression models showed similarities in the factors associated with relapse for procedures A and C, as opposed to those obtained with procedure B. General agreement among the results of CAI procedures would not guarantee that the same predictive breast cancer markers were consistently identified. These results highlight the importance of developing additional strategies to improve the sensitivity of CAI procedures.

Platelet-to-Lymphocyte Ratio Is Associated With Favorable Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer: A Study on 120 Patients

Introduction

Triple negative breast cancer (TNBC) is highly heterogeneous, but still most of the patients are treated by the anthracycline/taxane-based neoadjuvant therapy (NACT). Tumor-infiltrating lymphocytes (TILs) are a strong predictive and prognostic biomarker in TNBC, however are not always available. Peripheral blood counts, which reflect the systemic inflammatory/immune status, are easier to obtain than TILs. We investigated whether baseline white cell or platelet counts, as well as, Neutrophil-to-Lymphocyte Ratio (NLR) or Platelet-to-Lymphocyte Ratio (PLR) could replace baseline TILs as predictive or prognostic biomarkers in a series of TNBC treated by standard NACT.

Patients and Methods

One hundred twenty patients uniformly treated by FEC/taxane NACT in a tertiary cancer care center were retrospectively analyzed. The presence of pathological complete response (pCR: ypT0/Tis, ypN0) or the presence of pCR and/small residual disease (ypT0/Tis/T1ab, ypN0) were considered as good responses in data analysis. Baseline/pre-NACT blood count, NLR, PLR and TILs were evaluated as predictors of response, distant recurrence rate and distant recurrence-free survival (DRFS).

Results

TILs ≥30% and ≥1.5% were best predictors of pCR and distant recurrence risk, respectively (p = 0.007, p = 0.012). However, in this cohort, pCR status was not significantly associated with recurrence. Only the ensemble of patients with pCR and small residual disease had lower recurrence risk and longer survival DRFS (p = 0.042, p = 0.024, respectively) than the rest of the cohort (larger residual disease). The only parameter which could predict the pCR/small residual disease status was PLR: patients with values lower than 133.25 had significantly higher chance of reaching that status after NACT (p = 0.045). However, no direct correlation could be established between baseline PLR and metastatic recurrence. No correlation either was found between TIL and individual blood counts, or between TILs and NLR or PLR.

Conclusion

In this cohort, TILs retained their pCR predictive value; however PLR was a better predictor of the ensemble of responses which had good outcome in terms of less distant recurrences or longer DRFS (pCR or small residual disease). Thus, baseline PLR is worth further, prospective investigation together with baseline TILs, as it might indicate a good TNBC response to NACT when TILs are unavailable.

Multiplexed imaging analysis of the tumor-immune microenvironment reveals predictors of outcome in triple-negative breast cancer

Triple-negative breast cancer, the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification and treatment management. Prior literature has shown that interrogation of the tumor-immune microenvironment may be a promising approach to fill these gaps. Recently developed high-dimensional tissue imaging technology, such as multiplexed ion beam imaging, provide spatial context to protein expression in the microenvironment, allowing in-depth characterization of cellular processes. We demonstrate that profiling the functional proteins involved in cell-to-cell interactions in the microenvironment can predict recurrence and overall survival. We highlight the immunological relevance of the immunoregulatory proteins PD-1, PD-L1, IDO, and Lag3 by tying interactions involving them to recurrence and survival. Multivariate analysis reveals that our methods provide additional prognostic information compared to clinical variables. In this work, we present a computational pipeline for the examination of the tumor-immune microenvironment using multiplexed ion beam imaging that produces interpretable results, and is generalizable to other cancer types.

Immune microenvironment changes induced by neoadjuvant chemotherapy in triple-negative breast cancers: the MIMOSA-1 study

Background

The immune microenvironment (IME) of triple-negative breast cancers (TNBCs) and its modulation by neoadjuvant chemotherapy (NACT) remain to be fully characterized. Our current study aims to evaluate NACT-induced IME changes and assess the prognostic value of specific immune biomarkers.

Methods

Tumor-infiltrating lymphocytes (TILs) were identified from hematoxylin-eosin-stained sections of paired pre- and post-NACT tumor samples from a TNBC cohort (n = 66) and expression of PD-L1, TIM-3, and LAG-3 evaluated by immunohistochemistry.

Results

Overall TIL counts and PD-L1 expression did not differ pre- and post-NACT, but there was a response-specific statistically significant difference. TIL counts decreased in 65.5% of patients who achieved a pathological complete response (pCR) and increased in 56.8% of no-pCR patients (p = 0.0092). PD-L1 expression was significantly more frequently lost after NACT in pCR than in no-pCR patients (41.4% vs 16.2%, p = 0.0020). TIM-3 positivity (≥ 1%) was significantly more frequent after NACT (p < 0.0001) with increases in expression levels occurring more frequently in no-pCR than in pCR patients (51.4% vs 31%). LAG-3 expression significantly decreased after NACT, but there was no difference between response groups. Before NACT, a high TIL count (> 10%) was significantly associated with better overall survival (OS), p = 0.0112. After NACT, PD-L1 positivity and strong TIM-3 positivity (≥ 5%) were both associated with significantly worse OS (p = 0.0055 and p = 0.0274, respectively). Patients positive for both PD-L1 and TIM-3 had the worst prognosis (p = 0.0020), even when only considering patients who failed to achieve a pCR, p = 0.0479.

Conclusions

NACT induces significant IME changes in TNBCs. PD-L1 and TIM-3 expression post-NACT may yield important prognostic information for TNBC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01437-4.

Neoadjuvant approach as a platform for treatment personalization: focus on HER2-positive and triple-negative breast cancer

The neoadjuvant setting provides unquestionable clinical benefits for high-risk breast cancer (BC) patients, mainly in terms of expansion of locoregional treatment options and prognostic stratification. Additionally, it is also emerging as a strategical tool in the research field. In the present review, by focusing on HER2-positive and triple-negative subtypes, we examined the role of the neoadjuvant setting as a research platform to facilitate and rationalize the placement of escalation strategies, promote the adoption of biomarker-driven approaches for the investigation of de-escalated treatments, and foster the conduction of comprehensive translational analyses, thus ultimately aiming at pursuing treatment personalization. The solid prognostic role of pathologic complete response after neoadjuvant therapy, and its use as a surrogate endpoint to accelerate the drug approval process were discussed. In this context, available data on escalated treatment strategies capable of enhancing pathologic complete response (pCR) rate or improving prognosis of patients with residual disease (RD) after neoadjuvant treatment, were comprehensively reviewed. We also summarized evidence regarding the possibility of obtaining pCR with de-escalated strategies, with particular emphasis on the role of biomarker-driven approaches for patient selection. Pitfalls of the dichotomy of pCR/RD were also deepened, and data on alternative/complementary biomarkers with a possible clinical relevance in this regard were reviewed.

PD-L1 testing based on the SP142 antibody in metastatic triple-negative breast cancer: summary of an expert round-table discussion

Triple-negative breast cancer (TNBC) is more aggressive than other breast cancer subtypes. TNBC is characterized by increased expression of Programmed Death-ligand 1 (PD-L1), a signal used by many tumors to escape the immune response. Expression of PD-L1 is a positive predictor of response to immunotherapy; therefore, it should be investigated in TNBC in order to select patients who may benefit from anti-PD-L1 therapies. While many PD-L1 assays are available, only the VENTANA platform with the anti-PD-L1 (SP142) antibody is licensed as a companion diagnostic device for selecting patients with metastatic/advanced TNBC who are candidates for treatment with atezolizumab. In this article, we provide a summary of an expert round-table discussion about PD-L1 testing, using the SP142 antibody in metastatic TNBC.

Prognostic Value of Natural Killer Cells Besides Tumor-Infiltrating Lymphocytes in Breast Cancer Tissues

BACKGROUND

Each subgroup of immune cells has a different prognostic role in breast cancer; however, the prognostic impact of tumor-infiltrating natural killer cells (TINKs) is still not well established. Our aim was to assess the prognostic impact of natural killer (NK) cells in breast carcinomas.

MATERIALS AND METHODS

NK cells infiltration were assessed by immunohistochemistry (IHC). Statistical analyses were performed to evaluate the correlation of NK cells with clinical-pathological features and outcome.

RESULTS

CD56 IHC was realized in 126 patients. NK cells infiltration showed significant and positive association with tumor high Scarff-Bloom-Richardson (SBR) grade. NK cells were significantly associated with HER2-positive breast cancer and triple-negative breast cancer subtypes. Analyses showed significant and inverse correlation with progesterone and estrogen receptors expression status. High NK cells were significantly related to high Ki-67 labeling index. Our data showed that high NK cells infiltrate was significantly associated with tumor-infiltrating lymphocytes in breast cancer tissues. At a median follow-up of 5.5 years, high CD56 expression (≥ 5 cells/10 high power field) was associated significantly with a good overall survival and with good disease-free survival.

CONCLUSION

In this study, we assessed the important prognostic role of TINKs in breast carcinomas, which seems to be evident despite its association with aggressive pathological features. Thus evaluation of NK cells can be standardized and integrated in daily routine.

Clinicopathological Correlates of γδ T Cell Infiltration in Triple-Negative Breast Cancer

Simple Summary

The prognostic impact of the different tumor-infiltrating lymphocyte (TIL) subpopulations remains debated in solid cancers. We investigated the clinicopathological correlates and prognostic impact of TILs, particularly of γδ T cells, in 162 triple-negative breast cancer (TNBC) patients. A high γδ T cell density was significantly associated with younger age, higher tumor histological grade, adjuvant chemotherapy, BRCA1 promoter methylation, TIL density, and PD-L1 and PD-1 expression. In multivariate analyses, γδ T cell infiltration was an independent prognostic factor. However, this prognostic impact varied according to the tumor PIK3CA mutational status. High γδ T cell infiltration was associated with better survival in patients with PIK3CA wild-type tumors, without significant difference in the PIK3CA-mutated tumor subgroup. Altogether, these data suggest that high γδ T cell infiltrate is correlated with immune infiltration and might represent a prognostic tool in TNBC patients.

Abstract

The prognostic impact of the different tumor-infiltrating lymphocyte (TIL) subpopulations in solid cancers is still debated. Here, we investigated the clinicopathological correlates and prognostic impact of TILs, particularly of γδ T cells, in 162 patients with triple-negative breast cancer (TNBC). A high γδ T cell density (>6.625 γδ T cells/mm²) was associated with younger age (p = 0.008), higher tumor histological grade (p = 0.002), adjuvant chemotherapy (p = 0.010), BRCA1 promoter methylation (p = 0.010), TIL density (p < 0.001), and PD-L1 (p < 0.001) and PD-1 expression (p = 0.040). In multivariate analyses, γδ T cell infiltration (cutoff = 6.625 γδ T cells/mm²) was an independent prognostic factor (5-year relapse-free survival: 63.3% vs. 89.8%, p = 0.027; 5-year overall survival: 73.8% vs. 89.9%, p = 0.031, for low vs. high infiltration). This prognostic impact varied according to the tumor PIK3CA mutational status. High γδ T cell infiltration was associated with better survival in patients with PIK3CA wild-type tumors, but the difference was not significant in the subgroup with PIK3CA-mutated tumors. Altogether, these data suggest that high γδ T cell infiltrate is correlated with immune infiltration and might represent a candidate prognostic tool in patients with TNBC.

A Novel Immune and Stroma Related Prognostic Marker for Invasive Breast Cancer in Tumor Microenvironment: A TCGA Based Study

BACKGROUND

Breast cancer (BC) is the most frequent cancer in women. The tumor microenvironment (TME), consisting of blood vessels, immune cells, fibroblasts, and extracellular matrix, plays a pivotal role in tumorigenesis and progression. Increasing evidence has emphasized the importance of TME, especially the immune components, in patients with BC. Nevertheless, we still lack a deep understanding of the correlation between tumor invasion and TME status.

METHODS

Transcriptome and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was applied for quantifying stromal and immune scores. Then we screened out the differentially expressed genes (DEGs) through the intersection analysis. Furthermore, the establishment of protein-protein interaction (PPI) network and univariate COX regression analysis were utilized to determine the core genes in DEGs. In addition, we also performed Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis to distinguish the function of crucial gene expression and the proportion of tumor-infiltrating immune cells (TICs), respectively.

RESULTS

A total of 1178 samples (112 normal samples and 1066 tumor samples) were extracted from TCGA for calculation, and 226 DEGs were obtained from this assessment. Further intersection analysis revealed eight key genes, including ITK, CD3E, CCL19, CD2, SH2D1A, CD5, SLAMF6, SPN, which were proven to correlate with BC status. Moreover, ITK was picked out for further study. The results illustrated that high expression of BC patients had a more prolonged overall survival (OS) time than ITK low expression BC patients (p = 0.009), and ITK expression also presented the statistical significance in age, TNM staging, tumor size classification, and metastasis classification. Additionally, GSEA and CIBERSORT analysis indicated that ITK expression had an association with immune activity in TME.

CONCLUSION

ITK may be a potential indicator for prognosis prediction in patients with BC, and its biological behavior may promote our understanding of the molecular mechanism of tumor progression and targeted therapy.

The Tumor Microenvironment of Primitive and Metastatic Breast Cancer: Implications for Novel Therapeutic Strategies

Breast cancer evolves thanks to a dense and close interaction with the surrounding tumor microenvironment (TME). Fibroblasts, leukocytes, blood and lymphatic endothelial cells and extracellular matrix are the constituents of this entity, and they synergistically play a pivotal role in all of the stages of breast cancer development, from its onset to its metastatic spread. Moreover, it has been widely demonstrated that variations to the TME can correspond to prognosis variations. Breast cancer not only modulates the transformation of the environment within the mammary gland, but the same process is observed in metastases as well. In this minireview, we describe the features of TME within the primitive breast cancer, throughout its evolution and spread into the main metastatic sites.