Multiplexed immunofluorescence identifies high stromal CD68+PD-L1+ macrophages as a predictor of improved survival in triple negative breast cancer

Stromal B Lymphocytes Affecting Prognosis in Triple-Negative Breast Cancer by Opal/TSA Multiplexed Immunofluorescence

Objective

Immune cells play a key role in tumor microenvironment. The purpose of this study was to investigate the infiltration and clinical indication of immune cells including their combined prognostic value in microenvironment of triple negative breast cancer.

Methods

We investigated 100 patients with triple negative breast cancer by Opal/Tyramide Signal Amplification multispectral immunofluorescence between 2003 and 2017 at Zhejiang Provincial people's Hospital. Intratumoral and stromal immune cells of triple negative breast cancer were classified and quantitatively analyzed. Survival outcomes were compared using the Kaplan-Meier method and further analyzed with multivariate analysis.

Results

Infiltration level of stromal B lymphocytes, stromal and intratumoral CD8+ T cells, stromal CD4+ T cells, stromal PD-L1 and intratumoral tumor associated macrophages 2 cells were shown as independent factors affecting disease-free survival and overall survival in univariate analysis. Stromal B lymphocytes, T stage, N stage and pathological type were independent predictive factors for both DFS and OS in multivariate analysis. We firstly found that patients with B lymphocytes-enriched subtypes have a better prognosis than those with T lymphocytes-enriched subtypes and tumor-associated macrophage-enriched subtypes.

Conclusion

The present study identified a bunch of immune targets and subtypes, which could be exploited in future combined immunotherapy/chemotherapy strategies for triple negative breast cancer patients.

Multiplex Digital Spatial Profiling in Breast Cancer Research: State-of-the-Art Technologies and Applications across the Translational Science Spectrum

While RNA sequencing and multi-omic approaches have significantly advanced cancer diagnosis and treatment, their limitation in preserving critical spatial information has been a notable drawback. This spatial context is essential for understanding cellular interactions and tissue dynamics. Multiplex digital spatial profiling (MDSP) technologies overcome this limitation by enabling the simultaneous analysis of transcriptome and proteome data within the intact spatial architecture of tissues. In breast cancer research, MDSP has emerged as a promising tool, revealing complex biological questions related to disease evolution, identifying biomarkers, and discovering drug targets. This review highlights the potential of MDSP to revolutionize clinical applications, ranging from risk assessment and diagnostics to prognostics, patient monitoring, and the customization of treatment strategies, including clinical trial guidance. We discuss the major MDSP techniques, their applications in breast cancer research, and their integration in clinical practice, addressing both their potential and current limitations. Emphasizing the strategic use of MDSP in risk stratification for women with benign breast disease, we also highlight its transformative potential in reshaping the landscape of breast cancer research and treatment.

A perspective on FAIR quality control in multiplexed imaging data processing

Multiplexed imaging approaches are getting increasingly adopted for imaging of large tissue areas, yielding big imaging datasets both in terms of the number of samples and the size of image data per sample. The processing and analysis of these datasets is complex owing to frequent technical artifacts and heterogeneous profiles from a high number of stained targets To streamline the analysis of multiplexed images, automated pipelines making use of state-of-the-art algorithms have been developed. In these pipelines, the output quality of one processing step is typically dependent on the output of the previous step and errors from each step, even when they appear minor, can propagate and confound the results. Thus, rigorous quality control (QC) at each of these different steps of the image processing pipeline is of paramount importance both for the proper analysis and interpretation of the analysis results and for ensuring the reusability of the data. Ideally, QC should become an integral and easily retrievable part of the imaging datasets and the analysis process. Yet, limitations of the currently available frameworks make integration of interactive QC difficult for large multiplexed imaging data. Given the increasing size and complexity of multiplexed imaging datasets, we present the different challenges for integrating QC in image analysis pipelines as well as suggest possible solutions that build on top of recent advances in bioimage analysis.

Molecular profiles of different PD-L1 expression in patients with esophageal squamous cell carcinoma

BACKGROUND

PD-1/PD-L1 inhibitors are approved treatments for patients with esophageal squamous cell carcinoma (ESCC). The present investigation aspired to explore the interrelation between molecular phenotype and PD-L1 expression in ESCC.

METHODS

PD-L1 testing and targeted next-generation sequencing (NGS) were performed on tumoral tissues from 139 ESCC patients. Tumor-infiltrating lymphocytes (TILs) were scrutinized using a tyramide signal amplification system combined with immunohistochemistry.

RESULTS

Among enrolled patients, 36.7% displayed high PD-L1 expression (combined positive score [CPS] ≥10). BRCA1 and NF1 gene mutations were significantly associated with high PD-L1 expression (p < .05) while TGFβ pathway alterations were linked to low PD-L1 expression (p = .02). High copy number instability (CNI) and copy number alterations (CNA) were correlated with low PD-L1 expression. Patients with CDKN2A deletion exhibited higher PD-L1 expression. Varying types of TILs were observed across different PD-L1 expression groups. The ratio of CD8+PD-L1+ T cells and CD8+PD-1+ T cells to CD8+ T cells remained comparable in both tumoral and stromal regions, but the ratio of CD68+PD-L1+ macrophages to CD68+ macrophages was higher than the ratio of CD68+PD-1+ macrophages to CD68+ macrophages. CPS was significantly correlated with PD-L1+ lymphocytes and CD68+ macrophages in the tumoral region. CD8+ T cell infiltration was positively correlated with PD-1+ cells in both tumoral and stromal regions.

CONCLUSION

In this study, we presented the prevalence rates of PD-L1 expression in Chinese ESCC patients. The association of genetic profiles with PD-L1 expression levels also provide the clue that genomic phenotype may interact with the immunologic phenotype in ESCC.

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.

Changes in the immune landscape of TNBC after neoadjuvant chemotherapy: correlation with relapse

Introduction

Patients with high-risk, triple negative breast cancer (TNBC) often receive neoadjuvant chemotherapy (NAC) alone or with immunotherapy. Various single-cell and spatially resolved techniques have demonstrated heterogeneity in the phenotype and distribution of macrophages and T cells in this form of breast cancer. Furthermore, recent studies in mice have implicated immune cells in perivascular (PV) areas of tumors in the regulation of metastasis and anti-tumor immunity. However, little is known of how the latter change during NAC in human TNBC or their impact on subsequent relapse, or the likely efficacy of immunotherapy given with or after NAC.

Methods

We have used multiplex immunofluorescence and AI-based image analysis to compare the immune landscape in untreated and NAC-treated human TNBCs. We quantified changes in the phenotype, distribution and intercellular contacts of subsets of tumor-associated macrophages (TAMs), CD4+ and CD8+ T cells, and regulatory T cells (Tregs) in PV and non-PV various areas of the stroma and tumor cell islands. These were compared in tumors from patients who had either developed metastases or were disease-free (DF) after a three-year follow up period.

Results

In tumors from patients who remained DF after NAC, there was a marked increase in stromal CD163+ TAMs, especially those expressing the negative checkpoint regulator, T-cell immunoglobulin and mucin domain 3 (TIM-3). Whereas CD4+ T cells preferentially located to PV areas in the stroma of both untreated and NAC-treated tumors, specific subsets of TAMs and Tregs only did so only after NAC. Distinct subsets of CD4+ and CD8+ T cells formed PV clusters with CD163+ TAMs and Tregs. These were retained after NAC.

Discussion

Quantification of stromal TIM-3+CD163+ TAMs in tumor residues after NAC may represent a new way of identifying patients at high risk of relapse. PV clustering of immune cells is highly likely to regulate the activation and function of T cells, and thus the efficacy of T cell-based immunotherapies administered with or after NAC.

CSPG4 as a target for the specific killing of triple-negative breast cancer cells by a recombinant SNAP-tag-based antibody-auristatin F drug conjugate

PURPOSE

Triple-negative breast cancer (TNBC) is phenotypic of breast tumors lacking expression of the estrogen receptor (ER), the progesterone receptor (PgR), and the human epidermal growth factor receptor 2 (HER2). The paucity of well-defined molecular targets in TNBC, coupled with the increasing burden of breast cancer-related mortality, emphasizes the need to develop targeted diagnostics and therapeutics. While antibody-drug conjugates (ADCs) have emerged as revolutionary tools in the selective delivery of drugs to malignant cells, their widespread clinical use has been hampered by traditional strategies which often give rise to heterogeneous mixtures of ADC products.

METHODS

Utilizing SNAP-tag technology as a cutting-edge site-specific conjugation method, a chondroitin sulfate proteoglycan 4 (CSPG4)-targeting ADC was engineered, encompassing a single-chain antibody fragment (scFv) conjugated to auristatin F (AURIF) via a click chemistry strategy.

RESULTS

After showcasing the self-labeling potential of the SNAP-tag component, surface binding and internalization of the fluorescently labeled product were demonstrated on CSPG4-positive TNBC cell lines through confocal microscopy and flow cytometry. The cell-killing ability of the novel AURIF-based recombinant ADC was illustrated by the induction of a 50% reduction in cell viability at nanomolar to micromolar concentrations on target cell lines.

CONCLUSION

This research underscores the applicability of SNAP-tag in the unambiguous generation of homogeneous and pharmaceutically relevant immunoconjugates that could potentially be instrumental in the management of a daunting disease like TNBC.

Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma

To understand the clinical significance of the tumor microenvironment (TME), it is essential to study the interactions between malignant and non-malignant cells in clinical specimens. Here, we established a computational framework for a multiplex imaging system to comprehensively characterize spatial contexts of the TME at multiple scales, including close and long-distance spatial interactions between cell type pairs. We applied this framework to a total of 1,393 multiplex imaging data newly generated from 88 primary central nervous system lymphomas with complete follow-up data and identified significant prognostic subgroups mainly shaped by the spatial context. A supervised analysis confirmed a significant contribution of spatial context in predicting patient survival. In particular, we found an opposite prognostic value of macrophage infiltration depending on its proximity to specific cell types. Altogether, we provide a comprehensive framework to analyze spatial cellular interaction that can be broadly applied to other technologies and tumor contexts.

Targeting molecular cross-talk between tumor cells and tumor associated macrophage as therapeutic strategy in triple negative breast cancer

Triple-negative Breast cancer (TNBC) is a subtype of breast cancer (BC) that lacks expression for ER/PR/Her2 receptors and is associated with aggressive disease pathogenesis and the worst prognosis among other subtypes of BC. Accumulating evidence-based studies indicate the high immunogenic ability of TNBC tumors and the applicability of immunotherapeutic strategies to overcome therapy resistance and tumor recurrence in TNBC patients. However, not all TNBC patients respond equally well to current immunotherapies that mainly target the adaptive immune system for tumor rejection. Recent studies are contemplating the efficacy of tumor-associated macrophage (TAM) targeted therapies since these subpopulations of cells comprise one of the major components of tumor-infiltrating immune cells (TIIs) in the TNBC tumor microenvironment (TME) and play an essential role in priming the adaptive immune response mediators towards both antitumorigenic and pro-tumorigenic response facilitated by intercellular cross-talk between tumor cells and TAM populations present within TNBC-TME. The present review discusses these molecular mechanisms and their consequence on the progression of TNBC tumors. Also, the therapeutic strategies targeting candidate genes/pathways involved in molecular cross-talk between TAM-TNBC cells and their impact on the development and progression of TNBC tumors are also discussed.

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.

Spatially variant immune infiltration scoring in human cancer tissues

The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.

The Landscape of Tumor-Infiltrating Immune Cells in Feline Mammary Carcinoma: Pathological and Clinical Implications

Feline mammary carcinoma (FMC) shares key molecular and clinicopathological features with human breast cancer. We have herein studied the inflammatory infiltrate of FMC in order to uncover potential therapeutic targets and prognostic markers. To this end, the expression of different markers (CD3, CD4, CD8, CD20, CD56, FoxP3, CD68 and CD163) was analyzed in total, stromal (s) and intratumoral (i) tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs), in 73 feline mammary carcinomas. The results revealed that higher percentages of sCD8⁺ TILs were associated with longer disease-free survival (p = 0.05) and overall survival (p = 0.021). Additionally, higher percentages of iCD4⁺ TILs correlated with positive lymph node status (p = 0.003), whereas CD163⁺ TAMs were associated with undifferentiated tumors (p = 0.013). In addition, sCD3⁺ (p = 0.033), sCD8⁺ (p = 0.044) and sCD68⁺ (p = 0.023) immune cells were enriched in triple negative normal-like carcinomas compared to other subtypes. Altogether, our results suggest that specific subsets of immune cells may play a major role in clinical outcome of cats with mammary carcinoma, resembling what has been reported in human breast cancer. These data further support the relevance of the feline model in breast cancer studies.

GM-CSF derived from the inflammatory microenvironment potentially enhanced PD-L1 expression on tumor-associated macrophages in human breast cancer

Ever since immune checkpoint inhibitors have been approved for anti-cancer therapy in several cancers, including triple-negative breast cancer, the significance of programmed death-1 ligand 1 (PD-L1) expression in the tumor immune microenvironment has been a topic of interest. In the present study, we investigated the detailed mechanisms of PD-L1 overexpression on tumor-associated macrophages (TAMs) in breast cancer. In in vitro culture studies using human monocyte-derived macrophages, lymphocytes, and breast cancer cell lines, PD-L1 overexpression on macrophages was induced by the conditioned medium (CM) of activated lymphocytes, but not that of cancer cells. Granulocyte–macrophage colony-stimulating factor (GM-CSF) derived from activated lymphocytes was found to be involved in PD-L1 overexpression, in addition to interferon (IFN)-γ, via STAT3 pathway activation. Macrophages suppressed lymphocyte activation, and this inhibition was impaired by PD-1 blocking. The CM of activated lymphocytes also induced the overexpression of PD-L2, but GM-CSF did not affect PD-L2 expression. In the murine E0771 breast cancer model, anti-GM-CSF therapy did not affect PD-L1 expression on TAMs, and the mechanisms of PD-L1 expression on TAMs might differ between humans and mice. However, not only PD-L1, but also PD-L2 was overexpressed on TAMs in the E0771 tumor model, and their expression levels were significantly lower in the tumors in nude mice than in wild-type mice. Anti-PD-L1 antibody and anti-PD-L2 antibody synergistically inhibited E0771 tumor development. In conclusion, PD-L1 and PD-L2 were overexpressed on TAMs, and they potentially contributed to immunosuppression. The GM-CSF-STAT3 pathway is thought to represent a new mechanism of PD-L1 overexpression on TAMs in human breast cancer microenvironment.

Challenges and the Evolving Landscape of Assessing Blood-Based PD-L1 Expression as a Biomarker for Anti-PD-(L)1 Immunotherapy

While promising, PD-L1 expression on tumor tissues as assessed by immunohistochemistry has been shown to be an imperfect biomarker that only applies to a limited number of cancers, whereas many patients with PD-L1-negative tumors still respond to anti-PD-(L)1 immunotherapy. Recent studies using patient blood samples to assess immunotherapeutic responsiveness suggests a promising approach to the identification of novel and/or improved biomarkers for anti-PD-(L)1 immunotherapy. In this review, we discuss the advances in our evolving understanding of the regulation and function of PD-L1 expression, which is the foundation for developing blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy. We further discuss current knowledge and clinical study results for biomarker identification using PD-L1 expression on tumor and immune cells, exosomes, and soluble forms of PD-L1 in the peripheral blood. Finally, we discuss key challenges for the successful development of the potential use of blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy.

Case Report: Favorable Response and Manageable Toxicity to the Combination of Camrelizumab, Oxaliplatin, and Oral S-1 in a Patient With Advanced Epstein-Barr Virus-Associated Gastric Cancer

Some pertinent studies have demonstrated that Epstein-Barr virus-associated gastric cancer (EBVaGC) patients showed a favorable clinical outcome to immunotherapy and Epstein-Barr virus (EBV)-positive status might be a potential biomarker for immunotherapy in gastric cancer (GC). However, knowledge of given exposure to EBVaGC to the first-line immunotherapy is largely inadequate. Moreover, whether camrelizumab can be as effective as other PD-1 inhibitors in the treatment of advanced EBVaGC has not been reported. We report a case of advanced EBVaGC patient with a positive expression of PD-L1, enriched PD-L1+CD68+macrophages, and high TMB who had a long-term partial response and manageable toxicity to the combined approach of camrelizumab (a novel PD-1 inhibitor) and oxaliplatin plus oral S-1 (SOX). As the first-line treatment of advanced EBVaGC patients, camrelizumab combined with SOX regimen may provide a novel combined approach with favorable response and manageable safety. Combination of multiple biomarkers could have a higher effective predictive capacity to immunotherapy. Integrated treatment (chemo-immunotherapy and radiotherapy) might be the optimal strategy for patients with oligometastasis. It deserves prospective research to further validate the efficacy.