Immune Lymphocyte Infiltrate and its Prognostic Value in Triple-Negative Breast Cancer

A non-inferiority, phase III trial of gemcitabine plus capecitabine versus gemcitabine plus carboplatin as first-line therapy and tumor-infiltrating lymphocytes as a prognostic biomarker in patients with advanced triple-negative breast cancer

Background

Gemcitabine plus capecitabine (GX) shows survival benefit and manageable safety in patients with advanced triple-negative breast cancer (TNBC) but there is a paucity of phase III trial evidence. We aimed to compare the efficacy and safety of GX with gemcitabine plus carboplatin (GC) as first-line treatment for patients with advanced TNBC and validate the prognostic value of tumor-infiltrating lymphocytes (TILs).

Methods

Patients with advanced TNBC were randomly assigned 1:1 to receive gemcitabine (1000 mg/m2) on days 1 and 8 plus oral capecitabine (1000 mg/m2 twice a day) on days 1-14, or gemcitabine (1000 mg/m2) on days 1 and 8 plus carboplatin area under curve 2 on days 1 and 8. The primary endpoint was progression-free survival (PFS). TILs were analyzed by immunohistochemistry. The margin used to establish non-inferiority was 1.2.

Results

In all, 187 patients were randomly assigned, with 93 in GX and 94 in GC. Median PFS was 6.1 months in the GX arm compared with 6.3 months in the GC arm. The hazard ratio for PFS was 1.148, and a 95% CI was 0.856-1.539, exceeding the non-inferiority margin of 1.2. The median overall survival (OS) was 21.0 months in the GX arm compared with 21.5 months in the GC arm. The safety profile for the GX regimen was superior to the GC regimen, especially regarding hematological toxicity. Patients with high CD8+ TILs had significantly longer PFS and OS compared with patients with low CD8+ TILs. In the high CD8+ TIL group, the GC arm had prolonged PFS and OS compared with the GX arm.

Conclusion

The trial did not meet the prespecified criteria for the primary endpoint of PFS in patients with advanced TNBC. Moreover, the GC regimen showed better efficacy compared with the GX regimen in patients with high CD8+ TILs. However, the GX regimen should be considered in patients who cannot tolerate hematological toxicity.

Trial registration

ClinicalTrials.gov identifier: NCT02207335.

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.

Inverse correlation between the amounts of lymphocytic infiltrate and stroma in breast carcinoma

Background

Previous breast carcinoma studies focused on the evaluation of tumour-infiltrating lymphocytes (TILs) or of tumoural stroma via the tumour stroma ratio (TSR). Few studies assessed peritumoural lymphocytes and almost no studies investigated a possible relationship between lymphocytes and stroma. This prompted us to evaluate the amount of tumour cells, intra- and peritumoural lymphocytes, and stroma in breast cancer to support the hypothesis that the stroma may block the infiltration of lymphocytes inside the tumour.

Methods

We collected a retrospective series of 158 breast cancers (<25 mm). In addition to standard TILs and TSR evaluations, we assessed the percentages of tumour cells, stromal myofibroblasts, intra- and peritumoural lymphocytes on full-section tumours with haematoxylin and eosin and immunohistochemical staining.

Results

We showed significant negative correlations between the amounts of stroma and both intra- and peritumoural lymphocyte percentages. Considering the estrogen receptor positive invasive breast cancer of no special type cases, we showed that TSR had a positive prognostic value with an optimal threshold of 10 %.

Conclusions

This study is one of the first to show inverse correlations between tumoural stroma amount and intra- and peritumoural lymphocyte percentages, which supports the hypothesis that tumoural stroma can prevent the recruitment of lymphocytes around and within the tumour.

Effect modification between HLA-F and CD56 markers reveals differences in survival for triple-negative breast cancer patients

Triple-negative breast cancer (TNBC) is usually aggressive and challenging to treat. With high tumour immunogenicity TNBC patients might benefit from immunotherapy. We evaluated heterogeneous immune profiles of individual tumours in relation to clinical development to identify immune markers and their mutual expression. We assessed 122 biopsies from patients with primary TNBC tumours by automated image analysis of immunohistochemically stained tissue microarrays. Tumour-infiltrating lymphocytes (TILs), expression of HLA I molecules (HLA-ABC, HLA-G, HLA-E, HLA-F) and their mutual associations, as well as associations with other immune response markers (PD-L1, FOXP3, CD4, CD8, CD56) were investigated together with survival outcomes. Analysis of effect modification between HLA-F and CD56 showed longer disease-free survival and time-to-recurrence for tumours with low expression of both markers. TILs were significantly associated with tumour grade and with HLA-F, PD-L1, FOXP3 and CD8 expression, and were significantly associated with longer disease-free survival, also in multivariate analysis. Expression of all immune markers was positively correlated with each other, except CD56. The study highlights the complex immune regulation in TNBC stressing the importance of evaluating the immune landscape of individual tumours to identify patients that can benefit from immunotherapy. The finding of an effect modulation between HLA-F and CD56 is one aspect.

LCP1 correlates with immune infiltration: a prognostic marker for triple-negative breast cancer

OBJECTIVE

Triple-Negative Breast Cancer (TNBC) is known for its aggressiveness and treatment challenges due to the absence of ER, PR, and HER2 receptors. Our work emphasizes the prognostic value of LCP1 (Lymphocyte cytosolic protein 1), which plays a crucial role in cell processes and immune cell activity, to predict outcomes and guide treatments in TNBC.

METHODS

We explored LCP1 as a potential biomarker in TNBC and investigated the mRNA and protein expression levels of LCP1. We investigated different databases, including GTEX, TCGA, GEO, cBioPortal and Kaplan-Meier Plotter. Immunohistochemistry on TNBC and benign tumor samples was performed to examine LCP1's relationship with patient clinical characteristics and macrophage markers. We also assessed survival rates, immune cell infiltration, and drug sensitivity related to LCP1 using various bioinformatics tools.

RESULTS

The results indicated that LCP1 expression was higher in TNBC tissues compared to adjacent normal tissues. However, high expression of LCP1 was significantly associated with favorable survival outcomes in patients with TNBC. Enrichment analysis revealed that genes co-expressed with LCP1 were significantly enriched in various immune processes. LCP1 showed a positive correlation with the infiltration of resting dendritic cells, M1 macrophages, and memory CD4 T cells, and a negative correlation with M2 macrophages. Further analysis suggested a link between high levels of LCP1 and increased survival outcomes in cancer patients receiving immunotherapy.

CONCLUSION

LCP1 may serve as a potential diagnostic and prognostic biomarker for TNBC, which was closely associated with immune cell infiltration, particularly M1 and M2 macrophages. Our findings may provide valuable insights into immunotherapeutic strategies for TNBC patients.

Influence of tumor microenvironment on the different breast cancer subtypes and applied therapies

Despite the significant improvements made in breast cancer therapy during the last decades, this disease still has increasing incidence and mortality rates. Different targets involved in general processes, like cell proliferation and survival, have become alternative therapeutic options for this disease, with some of them already used in clinic, like the CDK4/6 inhibitors for luminal A tumors treatment. Nevertheless, there is a demand for novel therapeutic strategies focused not only on tumor cells, but also on their microenvironment. Tumor microenvironment (TME) is a very complex and dynamic system that, more than surrounding and supporting tumor cells, actively participates in tumor development and progression. During the last decades, it has become clear that the cellular and acellular components of TME differ between the various breast cancer subtypes and shape the differences regarding their severity and prognosis. The pivotal role of the TME in controlling tumor growth and influencing responses to therapy represents a potential source for novel targets and therapeutic strategies. In this review, we present a description of the multiple therapeutic options used for different breast cancer subtypes, as well as the influence that the TME may exert on the development of the disease and on the response to the distinct therapies, which in some cases may explain their failure by the occurrence of relapses and resistance. Furthermore, the ongoing studies focused on the use of TME components for developing potential cancer treatments are described.

Artificial intelligence learning landscape of triple-negative breast cancer uncovers new opportunities for enhancing outcomes and immunotherapy responses

Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable biomarkers to predict prognosis and precisely guide TNBC immunotherapy is still an unmet clinical need. To address this issue, we successfully constructed a novel 25 machine learning (ML) algorithms-based immune infiltrating cell (IIC) associated signature of TNBC (MLIIC), achieved by multiple transcriptome data of purified immune cells, TNBC cell lines, and TNBC entities. The TSI index was employed to determine IIC-RNAs that were accompanied by an expression pattern of upregulation in immune cells and downregulation in TNBC cells. LassoLR, Boruta, Xgboost, SVM, RF, and Pamr were utilized for further obtaining the optimal IIC-RNAs. Following univariate Cox regression analysis, LassoCox, CoxBoost, and RSF were utilized for the dimensionality reduction of IIC-RNAs from a prognostic perspective. RSF, Ranger, ObliqueRSF, Rpart, CoxPH, SurvivalSVM, CoxBoost, GlmBoost, SuperPC, StepwiseCox, Enet, LassoCox, CForest, Akritas, BlackBoost, PlsRcox, SurvReg, GBM, and CTree were used for determining the most potent MLIIC signature. Consequently, this MLIIC signature was correlated significantly with survival status validated by four independent TNBC cohorts. Also, the MLIIC signature had a superior predictive capability for TNBC prognosis, compared with 148 previously reported signatures. In addition, MLIIC signature scores developed by immunofluorescent staining of tissue arrays from TNBC patients showed a substantial prognostic value. In TNBC immunotherapy, the low MLIIC profile demonstrated significant immune-responsive efficacy in a dataset of multiple cancer types. MLIIC signature could also predict m6A epigenetic regulation which controls T cell homeostasis. Therefore, this well-established MLIIC signature is a robust predictive indicator for TNBC prognosis and the benefit of immunotherapy, thus providing an efficient tool for combating TNBC.

Immune Biomarkers in Triple-Negative Breast Cancer: Improving the Predictivity of Current Testing Methods

Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis and disease recurrence. The limited treatment options and the development of resistance to chemotherapy make it particularly difficult to manage these patients. However, recent research has been shifting its focus towards biomarker-based approaches for TNBC, with a particular emphasis on the tumor immune landscape. Immune biomarkers in TNBC are now a subject of great interest due to the presence of tumor-infiltrating lymphocytes (TILs) in these tumors. This characteristic often coincides with the presence of PD-L1 expression on both neoplastic cells and immune cells within the tumor microenvironment. Furthermore, a subset of TNBC harbor mismatch repair deficient (dMMR) TNBC, which is frequently accompanied by microsatellite instability (MSI). All of these immune biomarkers hold actionable potential for guiding patient selection in immunotherapy. To fully capitalize on these opportunities, the identification of additional or complementary biomarkers and the implementation of highly customized testing strategies are of paramount importance in TNBC. In this regard, this article aims to provide an overview of the current state of the art in immune-related biomarkers for TNBC. Specifically, it focuses on the various testing methodologies available and sheds light on the immediate future perspectives for patient selection. By delving into the advancements made in understanding the immune landscape of TNBC, this study aims to contribute to the growing body of knowledge in the field. The ultimate goal is to pave the way for the development of more personalized testing strategies, ultimately improving outcomes for TNBC patients.

Histopathological Aspects of the Prognostic Factors for Salivary Gland Cancers

Salivary gland cancers (SGCs) are diagnosed using histopathological examination, which significantly contributes to their progression, including lymph node/distant metastasis or local recurrence. In the current World Health Organization (WHO) Classification of Head and Neck Tumors: Salivary Glands (5th edition), malignant and benign epithelial tumors are classified into 21 and 15 tumor types, respectively. All malignant tumors have the potential for lymph node/distant metastasis or local recurrence. In particular, mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma (AdCC), salivary duct carcinoma, salivary carcinoma, not otherwise specified (NOS, formerly known as adenocarcinoma, NOS), myoepithelial carcinoma, epithelial-myoepithelial carcinoma, and carcinoma ex pleomorphic adenoma (PA) are relatively prevalent. High-grade transformation is an important aspect of tumor progression in SGCs. MEC, AdCC, salivary carcinoma, and NOS have a distinct grading system; however, a universal histological grading system for SGCs has not yet been recommended. Conversely, PA is considered benign; nonetheless, it should be cautiously treated to avoid the development of metastasizing/recurrent PA. The aim of this review is to describe the current histopathological aspects of the prognostic factors for SGCs and discuss the genes or molecules used as diagnostic tools that might have treatment target potential in the future.