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

Tumor Infiltrating Lymphocytes (TILS) and PD-L1 Expression in Breast Cancer: A Review of Current Evidence and Prognostic Implications from Pathologist's Perspective

With the rise of novel immunotherapies able to stimulate the antitumor immune response, increasing literature concerning the immunogenicity of breast cancer has been published in recent years. Numerous clinical studies have been conducted in order to identify novel biomarkers that could reflect the immunogenicity of BC and predict response to immunotherapy. In this regard, TILs have emerged as an important immunological biomarker related to the antitumor immune response in BC. TILs are more frequently observed in triple-negative breast cancer and HER2+ subtypes, where increased TIL levels have been linked to a better response to neoadjuvant chemotherapy and improved survival. PD-L1 is a type 1 transmembrane protein ligand expressed on T lymphocytes, B lymphocytes, and antigen-presenting cells and is considered a key inhibitory checkpoint involved in cancer immune regulation. PD-L1 immunohistochemical expression in breast cancer is observed in about 10-30% of cases and is extremely variable based on tumor stage and molecular subtypes. Briefly, TNBC shows the highest percentage of PD-L1 positivity, followed by HER2+ tumors. On the other hand, PD-L1 is rarely expressed (0-10% of cases) in hormone-receptor-positive BC. The prognostic role of PD-L1 expression in BC is still controversial since different immunohistochemistry (IHC) clones, cut-off points, and scoring systems have been utilized across published studies. In the present paper, an extensive review of the current knowledge of the immune landscape of BC is provided. TILS and PD-L1 expression across different BC subtypes are discussed, providing a guide for their pathological assessment and reporting.

Computational pathology to improve biomarker testing in breast cancer: how close are we?

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided.

Impact of Tumor-Infiltrating Lymphocytes on Disease Progression in Human Papillomavirus-Related Oropharyngeal Carcinoma

OBJECTIVE

We aim to explore the prognostic value of tumor-infiltrating lymphocytes (TILs) in the primary tumor and metastatic lymph nodes of patients with HPV(+)OPSCC. We hypothesize that TILS density at both sites is associated with disease-free survival in HPV(+)OPSCC.

STUDY DESIGN

Matched case-control study among HPV(+)OPSCC patients who underwent intent-to-cure surgery. Cases developed locoregional or distant recurrence. Controls were matched based on age, sex, pathologic T, N, and overall stage, year of surgery, type of adjuvant treatment received, and the Adult Comorbidity Evaluation-27 (ACE-27) score.

SETTING

Single tertiary care center, May 2007 to December 2016.

METHODS

Tumoral TILs (tTILs) density was defined as % TILs; stromal TILs (sTILs) density was defined as absent/sparse or moderate/dense crowding. Associations between TILs and time to disease progression were assessed using Cox regression models.

RESULTS

Forty-four case-control pairs (N = 88) were included: 42 (48%) AJCC pStage I, 39 (44%) pStage II, and 7 (8%) pStage III. tTILs density ≥10% (hazard ratio [HR] 0.41, 95% confidence interval [CI] 0.17-0.99, p = .048) and a moderate/dense sTILs density (HR 0.21, 95% CI 0.06-0.75, p = .016) in the primary tumor were significantly associated with decreased risk of progression. TILs density in the lymph node was associated with decreased risk of progression but did not reach statistical significance. The tTILs and sTILs density correlated strongly between the primary tumor and lymph node. Concordance between the pathologists' was moderate (60%-70%).

CONCLUSIONS

In HPV(+)OPSCC, a higher density of tumoral and stromal TILs in the primary tumor and possibly the lymph node may predict a lower risk of disease progression.

Tumor-Infiltrating Lymphocytes and Tumor-Stroma Ratio on Early-Stage Cervix Carcinoma: Prognostic Value of Two Distinct Morphological Patterns of Microenvironment

Background Tumor progression is influenced by the complex network of different cellular elements that make up its microenvironment. Tumor-infiltrating lymphocytes (TILs) and stroma characteristics reflect two faces of the intricate mechanisms involved in the tumor-host interaction and can be easily evaluated by routine histological examination. Their prognostic value could be demonstrated in different tumor tumor types, but they are poorly explored in cervical cancer. Methodology In this retrospective study, we analyzed the association of TILs, tumor-stroma ratio (TSR), and pattern of stromal fibroblasts with prognosis and classical clinicopathological variables. We studied 61 patients with early-stage cervical cancer. We reviewed histological type, tumor grade, Silva pattern of invasion for adenocarcinomas, tumor thickness, depth of stromal invasion, lymph vascular space invasion, and lymph node status. The median follow-up was 37.77 months (range 4.77 to 112.37 months). Results The TSR did not correlate with any clinicopathological features or disease-free and overall survival. On the other hand, the reactive pattern of stroma composed of larger fibroblasts and less collagenization was associated with the FIGO IB2 stage (p=0.04), larger tumor (p=0.03), and deeper infiltration (p=0.005). There were more recurrences in the group of reactive stroma (33.13% vs. 11.5%), although the difference did not reach statistical significance. Reactive stroma was associated with lower survival free of recurrence (p=0.05) and overall survival (p=0.009). High TILs were associated with squamous cell type (p=0.003), higher tumor grade (p=0.02), and more LVSI (p=0.02). Tumors with higher TILs presented higher free recurrence interval (p=0.06) and overall survival (p=0.03). No association was observed between stroma characteristics and TILs. Conclusions Our study suggested that although immune activation and stromal changes are important features of microenvironment remodeling during tumoral progression, they are independent, following distinct carcinogenetic pathways. Pathological assessment of stroma characteristics and TILs adds significant prognostic information and demonstrates how a simple routine laboratory assessment can generate a better understanding of biological phenomena.

Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer

Tumor-infiltrating lymphocytes (TILs) have been recognized as key players in the tumor microenvironment of breast cancer, but substantial interobserver variability among pathologists has impeded its utility as a biomarker. We developed a deep learning (DL)-based TIL analyzer to evaluate stromal TILs (sTILs) in breast cancer. Three pathologists evaluated 402 whole slide images of breast cancer and interpreted the sTIL scores. A standalone performance of the DL model was evaluated in the 210 cases (52.2%) exhibiting sTIL score differences of less than 10 percentage points, yielding a concordance correlation coefficient of 0.755 (95% confidence interval [CI], 0.693-0.805) in comparison to the pathologists' scores. For the 226 slides (56.2%) showing a 10 percentage points or greater variance between pathologists and the DL model, revisions were made. The number of discordant cases was reduced to 116 (28.9%) with the DL assistance (p < 0.001). The DL assistance also increased the concordance correlation coefficient of the sTIL score among every two pathologists. In triple-negative and human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients who underwent the neoadjuvant chemotherapy, the DL-assisted revision notably accentuated higher sTIL scores in responders (26.8 ± 19.6 vs. 19.0 ± 16.4, p = 0.003). Furthermore, the DL-assistant revision disclosed the correlation of sTIL-high tumors (sTIL ≥ 50) with the chemotherapeutic response (odd ratio 1.28 [95% confidence interval, 1.01-1.63], p = 0.039). Through enhancing inter-pathologist concordance in sTIL interpretation and predicting neoadjuvant chemotherapy response, here we report the utility of the DL-based tool as a reference for sTIL scoring in breast cancer assessment.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

Computational pathology in cancer diagnosis, prognosis, and prediction - present day and prospects

Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging from the prospect of automation of routine diagnostic tasks to the discovery of new prognostic and predictive biomarkers from tissue morphology. Despite the promising potential of computational pathology, its integration in clinical settings has been limited by a range of obstacles including operational, technical, regulatory, ethical, financial, and cultural challenges. Here, we focus on the pathologists' perspective of computational pathology: we map its current translational research landscape, evaluate its clinical utility, and address the more common challenges slowing clinical adoption and implementation. We conclude by describing contemporary approaches to drive forward these techniques. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Bridging Pyroptosis and Immunity: A Comprehensive Study of the Pyroptosis-Related Long Non-Coding RNA Signature in Breast Cancer

Breast cancer continuously poses serious clinical challenges to human health due to its intrinsic heterogenicity and evolving drug resistance. Recently, increasing evidence has shown that pyroptosis, known as a programmed and inflammatory form of cell death, participates in tumorigenesis, progression, and remodeling of the tumor immune microenvironment (TIME). However, a comprehensive insight into pyroptosis-related signatures for breast cancer remains elusive. The current study established a pyroptosis-related lncRNA signature using transcriptome data and corresponding clinical information from The Cancer Genome Atlas (TCGA). Pyroptosis-related gene clusters, the associated differential expression in breast cancer patients' subtypes, and the potential mechanisms were all discussed. This integrative analysis revealed a unique signature underpinning the dichotomy of breast cancer progression and survival outcomes. Interestingly, the pyroptosis-related lncRNA signature was revealed as closely intertwined with the TIME. A correlation was established between the pyroptosis-related LncRNA signature and the TIME, underlying the mutual effect between pyroptosis and the immune responses implicated in breast cancer. The findings in this work underline the critical role exerted by pyroptosis in breast cancer, providing new insights into disease progression, prognosis, and therapeutic potential. This work has been poised to provide new avenues for personalized, immune-based cancer therapeutics by enhancing our understanding of pyroptosis in breast cancer.

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases

BACKGROUND

Recent advances in digital pathology have enabled accurate and standardised enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a percentage electronic TIL score (eTILs) and investigate its prognostic and predictive relevance in cutaneous melanoma.

METHODS

We included stage I to IV cutaneous melanoma patients and used hematoxylin-eosin-stained slides for TIL analysis. We assessed eTILs as a continuous and categorical variable using the published cut-off of 16.6% and applied Cox regression models to evaluate associations of eTILs with relapse-free, distant metastasis-free, and overall survival. We compared eTILs of the primaries with matched metastasis. Moreover, we assessed the predictive relevance of eTILs in therapy-naïve metastases according to the first-line therapy.

FINDINGS

We analysed 321 primary cutaneous melanomas and 191 metastatic samples. In simple Cox regression, tumour thickness (p < 0.0001), presence of ulceration (p = 0.0001) and eTILs ≤16.6% (p = 0.0012) were found to be significant unfavourable prognostic factors for RFS. In multiple Cox regression, eTILs ≤16.6% (p = 0.0161) remained significant and downgraded the current staging. Lower eTILs in the primary tissue was associated with unfavourable relapse-free (p = 0.0014) and distant metastasis-free survival (p = 0.0056). In multiple Cox regression adjusted for tumour thickness and ulceration, eTILs as continuous remained significant (p = 0.019). When comparing TILs in primary tissue and corresponding metastasis of the same patient, eTILs in metastases was lower than in primary melanomas (p < 0.0001). In therapy-naïve metastases, an eTILs >12.2% was associated with longer progression-free survival (p = 0.037) and melanoma-specific survival (p = 0.0038) in patients treated with anti-PD-1-based immunotherapy. In multiple Cox regression, lactate dehydrogenase (p < 0.0001) and eTILs ≤12.2% (p = 0.0130) were significantly associated with unfavourable melanoma-specific survival.

INTERPRETATION

Assessment of TILs is prognostic in primary melanoma samples, and the eTILs complements staging. In therapy-naïve metastases, eTILs ≤12.2% is predictive of unfavourable survival outcomes in patients receiving anti-PD-1-based therapy.

FUNDING

See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

A scoping review of statistical methods in studies of biomarker-related treatment heterogeneity for breast cancer

BACKGROUND

Many scientific papers are published each year and substantial resources are spent to develop biomarker-based tests for precision oncology. However, only a handful of tests is currently used in daily clinical practice, since development is challenging. In this situation, the application of adequate statistical methods is essential, but little is known about the scope of methods used.

METHODS

A PubMed search identified clinical studies among women with breast cancer comparing at least two different treatment groups, one of which chemotherapy or endocrine treatment, by levels of at least one biomarker. Studies presenting original data published in 2019 in one of 15 selected journals were eligible for this review. Clinical and statistical characteristics were extracted by three reviewers and a selection of characteristics for each study was reported.

RESULTS

Of 164 studies identified by the query, 31 were eligible. Over 70 different biomarkers were evaluated. Twenty-two studies (71%) evaluated multiplicative interaction between treatment and biomarker. Twenty-eight studies (90%) evaluated either the treatment effect in biomarker subgroups or the biomarker effect in treatment subgroups. Eight studies (26%) reported results for one predictive biomarker analysis, while the majority performed multiple evaluations, either for several biomarkers, outcomes and/or subpopulations. Twenty-one studies (68%) claimed to have found significant differences in treatment effects by biomarker level. Fourteen studies (45%) mentioned that the study was not designed to evaluate treatment effect heterogeneity.

CONCLUSIONS

Most studies evaluated treatment heterogeneity via separate analyses of biomarker-specific treatment effects and/or multiplicative interaction analysis. There is a need for the application of more efficient statistical methods to evaluate treatment heterogeneity in clinical studies.

Characterization of the immune environment in pregnancy-associated breast cancer

Pregnancy-associated breast cancer (PrBC) is a rare and clinically challenging condition. Specific immune mechanisms and pathways are involved in maternal-fetal tolerance and tumor-host immunoediting. The comprehension of the molecular processes underpinning this immune synergy in PrBC is needed to improve patients' clinical management. Only a few studies focused on the immune biology of PrBC and attempted to identify bona fide biomarkers. Therefore, clinically actionable information remains extremely puzzling for these patients. In this review article, we discuss the current knowledge on the immune environment of PrBC, in comparison with pregnancy-unrelated breast cancer and in the context of maternal immune changes during pregnancy. A particular emphasis is given to the actual role of potential immune-related biomarkers for PrBC clinical management.

Intratumor spatial heterogeneity in programmed death-ligand 1 (PD-L1) protein expression in early-stage breast cancer

PURPOSE

Programmed death-ligand 1 (PD-L1) expression is required for benefit from immune checkpoint inhibitors in metastatic triple negative breast cancer (TNBC). In contrast, in the neoadjuvant setting patients benefited regardless of PD-L1 expression. We hypothesized that, in stages II-III breast cancers, low levels of PD-L1 expression may be sufficient to confer sensitivity to therapy and focal expression could be missed by a biopsy.

METHODS

In this study, we examined intratumor spatial heterogeneity of PD-L1 protein expression in multiple biopsies from different regions of breast cancers in 57 primary breast tumors (n = 33 TNBC, n = 19 estrogen receptor-positive [ER-positive], n = 5 human epidermal receptor 2-positive [HER2 +]). E1L3N antibody was used to assess PD-L1 status and staining was scored using the combined positivity score (CPS) with PD-L1 positive defined as CPS ≥ 10.

RESULTS

Overall, 19% (11/57) of tumors were PD-L1 positive based on positivity in at least 1 biopsy. Among TNBC, PD-L1 positivity was 27% (9/33). The discordance rate, defined as the same tumor yielding PD-L1 positive and negative samples in different regions, was 16% (n = 9) in the whole study population and 23% (n = 7) in TNBC. Cohen's kappa coefficient of agreement was 0.214 for the whole study and 0.239 for TNBC, both of which falling into a non-statistically significant fair agreement range. Among all PD-L1 positive cases, 82% (n = 9/11) had positivity in only one of the tissue assessments.

CONCLUSION

These results indicate that the overall 84% concordance is driven by concordant negative results. In PD-L1 positive cancers, within-tumor heterogeneity in PD-L1 expression exists.

Clinical Meaning of Stromal Tumor Infiltrating Lymphocytes (sTIL) in Early Luminal B Breast Cancer

Luminal breast cancer (BC) is associated with less immune activation, and the significance of stromal lymphocytic infiltration (sTIL) is more uncertain than in other BC subtypes. The aim of this study was to investigate the predictive and prognostic value of sTIL in early luminal BC. The study was performed with an observational design in a prospective cohort of 345 patients with predominantly high-risk luminal (hormone receptor positive, HER2 negative) BC and with luminal B features (n = 286), in which the presence of sTIL was analyzed with validated methods. Median sTIL infiltration was 5% (Q1-Q3 range (IQR), 0-10). We found that sTIL were associated with characteristics of higher biological and clinical aggressiveness (tumor and lymph node proliferation and stage, among others) and that the percentage of sTIL was predictive of pathologic complete response in patients treated with neoadjuvant chemotherapy (OR: 1.05, 95%CI 1.02-1.09, p < 0.001). The inclusion of sTIL (any level of lymphocytic infiltration: sTIL > 0%) in Cox regression multivariable prognostic models was associated with a shorter relapse-free interval (HR: 4.85, 95%CI 1.33-17.65, p = 0.016) and significantly improved its performance. The prognostic impact of sTIL was independent of other clinical and pathological variables and was mainly driven by its relevance in luminal B BC.

Immune cells in residual disease and recurrence

Tumor recurrence following potentially curative therapy constitutes a major obstacle to achieving cures in patients with cancer. Recurrent tumors frequently arise from a population of residual cancer cells - also referred to as minimal residual disease (RD) or persister cells - that survive therapy and persist for prolonged periods prior to tumor relapse. While there has been significant recent progress in deciphering tumor-cell-intrinsic pathways that regulate residual cancer cell survival and recurrence, much less is known about how the tumor microenvironment (TME) of residual tumors impacts persister cancer cells or tumor recurrence. In this review, we highlight recent studies exploring the regulation and function of immune cells in RD and discuss therapeutic opportunities to target immune cells in residual tumors.

Combining histological grade, TILs, and the PD-1/PD-L1 pathway to identify immunogenic tumors and de-escalate radiotherapy in early breast cancer: a secondary analysis of a randomized clinical trial

BACKGROUND

The implementation of immunological biomarkers for radiotherapy (RT) individualization in breast cancer requires consideration of tumor-intrinsic factors. This study aimed to investigate whether the integration of histological grade, tumor-infiltrating lymphocytes (TILs), programmed cell death protein-1 (PD-1), and programmed death ligand-1 (PD-L1) can identify tumors with aggressive characteristics that can be downgraded regarding the need for RT.

METHODS

The SweBCG91RT trial included 1178 patients with stage I-IIA breast cancer, randomized to breast-conserving surgery with or without adjuvant RT, and followed for a median time of 15.2 years. Immunohistochemical analyses of TILs, PD-1, and PD-L1 were performed. An activated immune response was defined as stromal TILs ≥10% and PD-1 and/or PD-L1 expression in ≥1% of lymphocytes. Tumors were categorized as high-risk or low-risk using assessments of histological grade and proliferation as measured by gene expression. The risk of ipsilateral breast tumor recurrence (IBTR) and benefit of RT were then analyzed with 10 years follow-up based on the integration of immune activation and tumor-intrinsic risk group.

RESULTS

Among high-risk tumors, an activated immune infiltrate was associated with a reduced risk of IBTR (HR 0.34, 95% CI 0.16 to 0.73, p=0.006). The incidence of IBTR in this group was 12.1% (5.6-25.0) without RT and 4.4% (1.1-16.3) with RT. In contrast, the incidence of IBTR in the high-risk group without an activated immune infiltrate was 29.6% (21.4-40.2) without RT and 12.8% (6.6-23.9) with RT. Among low-risk tumors, no evidence of a favorable prognostic effect of an activated immune infiltrate was seen (HR 2.0, 95% CI 0.87 to 4.6, p=0.100).

CONCLUSIONS

Integrating histological grade and immunological biomarkers can identify tumors with aggressive characteristics but a low risk of IBTR despite a lack of RT boost and systemic therapy. Among high-risk tumors, the risk reduction of IBTR conferred by an activated immune infiltrate is comparable to treatment with RT. These findings may apply to cohorts dominated by estrogen receptor-positive tumors.

Enhancement of immune surveillance in breast cancer by targeting hypoxic tumor endothelium: Can it be an immunological switch point?

Breast cancer ranks second among the causes of cancer-related deaths in women. In spite of the recent advances achieved in the diagnosis and treatment of breast cancer, further study is required to overcome the risk of cancer resistance to treatment and thereby improve the prognosis of individuals with advanced-stage breast cancer. The existence of a hypoxic microenvironment is a well-known event in the development of mutagenesis and rapid proliferation of cancer cells. Tumor cells, purposefully cause local hypoxia in order to induce angiogenesis and growth factors that promote tumor growth and metastatic characteristics, while healthy tissue surrounding the tumor suffers damage or mutate. It has been found that these settings with low oxygen levels cause immunosuppression and a lack of immune surveillance by reducing the activation and recruitment of tumor infiltrating leukocytes (TILs). The immune system is further suppressed by hypoxic tumor endothelium through a variety of ways, which creates an immunosuppressive milieu in the tumor microenvironment. Non responsiveness of tumor endothelium to inflammatory signals or endothelial anergy exclude effector T cells from the tumor milieu. Expression of endothelial specific antigens and immunoinhibitory molecules like Programmed death ligand 1,2 (PDL-1, 2) and T cell immunoglobulin and mucin-domain containing-3 (TIM-3) by tumor endothelium adds fuel to the fire by inhibiting T lymphocytes while promoting regulatory T cells. The hypoxic microenvironment in turn recruits Myeloid Derived Suppressor Cells (MDSCs), Tumor Associated Macrophages (TAMs) and T regulatory cells (Treg). The structure and function of newly generated blood vessels within tumors, on the other hand, are aberrant, lacking the specific organization of normal tissue vasculature. Vascular normalisation may work for a variety of tumour types and show to be an advantageous complement to immunotherapy for improving tumour access. By enhancing immune response in the hypoxic tumor microenvironment, via immune-herbal therapeutic and immune-nutraceuticals based approaches that leverage immunological evasion of tumor, will be briefly reviewed in this article. Whether these tactics may be the game changer for emerging immunological switch point to attenuate the breast cancer growth and prevent metastatic cell division, is the key concern of the current study.

A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images

Background and objectives

The detection of tumor-infiltrating lymphocytes (TILs) could aid in the development of objective measures of the infiltration grade and can support decision-making in breast cancer (BC). However, manual quantification of TILs in BC histopathological whole slide images (WSI) is currently based on a visual assessment, thus resulting not standardized, not reproducible, and time-consuming for pathologists. In this work, a novel pathomic approach, aimed to apply high-throughput image feature extraction techniques to analyze the microscopic patterns in WSI, is proposed. In fact, pathomic features provide additional information concerning the underlying biological processes compared to the WSI visual interpretation, thus providing more easily interpretable and explainable results than the most frequently investigated Deep Learning based methods in the literature.

Methods

A dataset containing 1037 regions of interest with tissue compartments and TILs annotated on 195 TNBC and HER2+ BC hematoxylin and eosin (H&E)-stained WSI was used. After segmenting nuclei within tumor-associated stroma using a watershed-based approach, 71 pathomic features were extracted from each nucleus and reduced using a Spearman's correlation filter followed by a nonparametric Wilcoxon rank-sum test and least absolute shrinkage and selection operator. The relevant features were used to classify each candidate nucleus as either TILs or non-TILs using 5 multivariable machine learning classification models trained using 5-fold cross-validation (1) without resampling, (2) with the synthetic minority over-sampling technique and (3) with downsampling. The prediction performance of the models was assessed using ROC curves.

Results

21 features were selected, with most of them related to the well-known TILs properties of having regular shape, clearer margins, high peak intensity, more homogeneous enhancement and different textural pattern than other cells. The best performance was obtained by Random-Forest with ROC AUC of 0.86, regardless of resampling technique.

Conclusions

The presented approach holds promise for the classification of TILs in BC H&E-stained WSI and could provide support to pathologists for a reliable, rapid and interpretable clinical assessment of TILs in BC.

Recent Advances in Optimizing Radiation Therapy Decisions in Early Invasive Breast Cancer

Adjuvant whole breast irradiation after breast-conserving surgery is a well-established treatment standard for early invasive breast cancer. Screening, early diagnosis, refinement in surgical techniques, the knowledge of new and specific molecular prognostic factors, and now the standard use of more effective neo/adjuvant systemic therapies have proven instrumental in reducing the rates of locoregional relapses. This underscores the need for reliably identifying women with such low-risk disease burdens in whom elimination of radiation from the treatment plan would not compromise oncological safety. This review summarizes the current evidence for radiation de-intensification strategies and details ongoing prospective clinical trials investigating the omission of adjuvant whole breast irradiation in molecularly defined low-risk breast cancers and related evidence supporting the potential for radiation de-escalation in HER2+ and triple-negative clinical subtypes. Furthermore, we discuss the current evidence for the de-escalation of regional nodal irradiation after neoadjuvant chemotherapy. Finally, we also detail the current knowledge of the clinical value of stromal tumor-infiltrating lymphocytes and liquid-based biomarkers as prognostic factors for locoregional relapse.

ONEST (Observers Needed to Evaluate Subjective Tests) Analysis of Stromal Tumour-Infiltrating Lymphocytes (sTILs) in Breast Cancer and Its Limitations

Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the reliable estimation of inter-observer agreement of TIL categorisation. This has not been explored previously in relation to TILs. ONEST analyses, using an open-source software developed by the first author, were performed on TIL quantification in breast cancers taken from two previous studies. These were one reproducibility study involving 49 breast cancers, 23 in the first circulation and 14 pathologists in the second circulation, and one study involving 100 cases and 9 pathologists. In addition to the estimates of the number of observers required, other factors influencing the results of ONEST were examined. The analyses reveal that between six and nine observers (range 2-11) are most commonly needed to give a robust estimate of reproducibility. In addition, the number and experience of observers, the distribution of values around or away from the extremes, and outliers in the classification also influence the results. Due to the simplicity and the potentially relevant information it may give, we propose ONEST to be a part of new reproducibility analyses.

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

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

Triple-Negative Breast Cancer and Predictive Markers of Response to Neoadjuvant Chemotherapy: A Systematic Review

Around 40-50% of all triple-negative breast cancer (TNBC) patients achieve a pathological complete response (pCR) after treatment with neoadjuvant chemotherapy (NAC). The identification of biomarkers predicting the response to NAC could be helpful for personalized treatment. This systematic review provides an overview of putative biomarkers at baseline that are predictive for a pCR following NAC. Embase, Medline and Web of Science were searched for articles published between January 2010 and August 2022. The articles had to meet the following criteria: patients with primary invasive TNBC without distant metastases and patients must have received NAC. In total, 2045 articles were screened by two reviewers resulting in the inclusion of 92 articles. Overall, the most frequently reported biomarkers associated with a pCR were a high expression of Ki-67, an expression of PD-L1 and the abundance of tumor-infiltrating lymphocytes, particularly CD8+ T cells, and corresponding immune gene signatures. In addition, our review reveals proteomic, genomic and transcriptomic markers that relate to cancer cells, the tumor microenvironment and the peripheral blood, which also affect chemo-sensitivity. We conclude that a prediction model based on a combination of tumor and immune markers is likely to better stratify TNBC patients with respect to NAC response.

Landscape of costimulatory molecule signature in breast cancer and its prognostic significance

Background

Breast cancer (BRCA) is the most common malignant tumor in the world. Because of its substantial heterogeneity, its clinical treatment is faced with various problems. Only a small number of patients can benefit from the treatment of immune checkpoint inhibitor (ICI). Costimulatory molecule signature (CMS) plays an essential role in T cell activation and antitumor immune response. Previous studies found that CMS is associated with prognosis-related immune response markers, suggesting that CMS may be a potential therapeutic target. However, the research on their function in BRCA subtype is still inadequate. Our study aims to analyze CMS in BRCA and establish an effective prognostic model.

Methods

We extracted 1,222 messenger RNA (mRNA) samples of 1,110 patients registered in the BRCA cohort of The Cancer Genome Atlas (TCGA), including 1,109 tumor tissue mRNA samples and 113 standard tissue samples for model construction and verification. The prognostic significance was determined by least absolute shrinkage and selection operator (LASSO)-Cox proportional hazard regression, which showed that the overall survival (OS) of the high-risk group was shorter than that of the low group (P<0.01).

Results

Although the CMS prognostic model can predict the prognosis well, the receiver operating characteristic (ROC) prediction results were unsatisfactory. The reason for this may be the heteromorphism of BRCA, so we divided the cases into four subtypes according to the PAM50 (PAM50Call_RNAseq) in clinical information. The same method was used to construct the model in the four subtypes and verify the effect of each subtype prognostic model.

Conclusions

The results showed that the submodels constructed in this study can be used to evaluate the prognosis of each subtype.

Tumor Infiltrating Lymphocytes across Breast Cancer Subtypes: Current Issues for Biomarker Assessment

Tumor-infiltrating lymphocytes (TILs) represent a surrogate biomarker of anti-tumor, lymphocyte-mediated immunity. In early, triple-negative breast cancer, TILs have level 1B of evidence to predict clinical outcomes. TILs represent a promising biomarker to select patients who can experience a better prognosis with de-intensified cancer treatments and derive larger benefits from immune checkpoint inhibitors. However, the assessment and the validation of TILs as a biomarker require a prospective and rigorous demonstration of its clinical validity and utility, provided reproducible analytical performance. With pending data about the prospective validation of TILs' clinical validity to modulate treatments in early breast cancer, this review summarizes the most important current issues and future challenges related to the implementation of TILs assessments across all breast cancer subtypes and their potential integration into clinical practice.

Current State and Future Challenges for PI3K Inhibitors in Cancer Therapy

The phosphoinositide 3 kinase (PI3K)-protein kinase B (PKB/AKT)-mammalian target of the rapamycin (mTOR) axis is a key signal transduction system that links oncogenes and multiple receptor classes which are involved in many essential cellular functions. Aberrant PI3K signalling is one of the most commonly mutated pathways in cancer. Consequently, more than 40 compounds targeting key components of this signalling network have been tested in clinical trials among various types of cancer. As the oncogenic activation of the PI3K/AKT/mTOR pathway often occurs alongside mutations in other signalling networks, combination therapy should be considered. In this review, we highlight recent advances in the knowledge of the PI3K pathway and discuss the current state and future challenges of targeting this pathway in clinical practice.

Incorporating weekly carboplatin in anthracycline and paclitaxel-containing neoadjuvant chemotherapy for triple-negative breast cancer: propensity-score matching analysis and TIL evaluation

BACKGROUND

The generation of data capturing the risk-benefit ratio of incorporating carboplatin (Cb) to neoadjuvant chemotherapy (NACT) for triple-negative breast cancer (TNBC) in a clinical practice setting is urgently needed. Tumour-infiltrating lymphocytes (TILs) have an established role in TNBC receiving NACT, however, the role of TIL dynamics under NACT exposure in patients receiving the current standard of care is largely uncharted.

METHODS

Consecutive TNBC patients receiving anthracycline-taxane [A-T] +/- Cb NACT at three Institutions were enrolled. Stromal-TILs were evaluated on pre-NACT and residual disease (RD) specimens. In the clinical cohort, propensity-score-matching was used to control selection bias.

RESULTS

In total, 247 patients were included (A-T = 40.5%, A-TCb = 59.5%). After propensity-score-matching, pCR was significantly higher for A-TCb vs A-T (51.9% vs 34.2%, multivariate: OR = 2.40, P = 0.01). No differences in grade ≥3 haematological toxicities were observed. TILs increased from baseline to RD in the overall population and across A-T/A-TCb subgroups. TIL increase from baseline to RD was positively and independently associated with distant disease-free survival (multivariate: HR = 0.43, P = 0.05).

CONCLUSIONS

We confirmed in a clinical practice setting of TNBC patients receiving A-T NACT that the incorporation of weekly Cb significantly improved pCR. In addition, A-T +/- Cb enhanced immune infiltration from baseline to RD. Finally, we reported a positive independent prognostic role of TIL increase after NACT exposure.

The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes

Breast cancer, the most common type of cancer affecting women, encompasses a collection of histologic (mainly ductal and lobular) and molecular subtypes exhibiting diverse clinical presentation, disease trajectories, treatment options, and outcomes. Immunotherapy has revolutionized treatment for some solid tumors but has shown limited promise for breast cancers. In this review, we summarize recent advances in our understanding of the complex interactions between tumor and immune cells in subtypes of breast cancer at the cellular and microenvironmental levels. We aim to provide a perspective on opportunities for future immunotherapy agents tailored to specific features of each subtype of breast cancer.

SIGNIFICANCE

Although there are currently over 200 ongoing clinical trials testing immunotherapeutics, such as immune-checkpoint blockade agents, these are largely restricted to the triple-negative and HER2+ subtypes and primarily focus on T cells. With the rapid expansion of new in vitro, in vivo, and clinical data, it is critical to identify and highlight the challenges and opportunities unique for each breast cancer subtype to drive the next generation of treatments that harness the immune system.

Radiomic Models Predict Tumor Microenvironment Using Artificial Intelligence-the Novel Biomarkers in Breast Cancer Immune Microenvironment

Breast cancer is the most common malignancy in women, and some subtypes are associated with a poor prognosis with a lack of efficacious therapy. Moreover, immunotherapy and the use of other novel antibody‒drug conjugates have been rapidly incorporated into the standard management of advanced breast cancer. To extract more benefit from these therapies, clarifying and monitoring the tumor microenvironment (TME) status is critical, but this is difficult to accomplish based on conventional approaches. Radiomics is a method wherein radiological image features are comprehensively collected and assessed to build connections with disease diagnosis, prognosis, therapy efficacy, the TME, etc In recent years, studies focused on predicting the TME using radiomics have increasingly emerged, most of which demonstrate meaningful results and show better capability than conventional methods in some aspects. Beyond predicting tumor-infiltrating lymphocytes, immunophenotypes, cytokines, infiltrating inflammatory factors, and other stromal components, radiomic models have the potential to provide a completely new approach to deciphering the TME and facilitating tumor management by physicians.

Immune-Checkpoint Inhibitors: A New Line of Attack in Triple-Negative Breast Cancer

Poor prognosis is a distinctive feature of triple-negative breast cancer (TNBC). Chemotherapy has long represented the main and unique treatment for patients with TNBC. Recently, immune checkpoint inhibitors (ICIs) were investigated in several clinical trials and were approved for clinical use in TNBC patients that express programmed cell death protein-1 (PD-1) in combination with chemotherapy in the first-line setting. ICIs are also being investigated in the neoadjuvant and adjuvant settings for TNBC. This chapter aims to discuss different ICIs used to treat all TNBC stages to date.

Activation of cancer immunotherapy by nanomedicine

Cancer is one of the most difficult diseases to be treated in the world. Immunotherapy has made great strides in cancer treatment in recent years, and several tumor immunotherapy drugs have been approved by the U.S. Food and Drug Administration. Currently, immunotherapy faces many challenges, such as lacking specificity, cytotoxicity, drug resistance, etc. Nanoparticles have the characteristics of small particle size and stable surface function, playing a miraculous effect in anti-tumor treatment. Nanocarriers such as polymeric micelles, liposomes, nanoemulsions, dendrimers, and inorganic nanoparticles have been widely used to overcome deficits in cancer treatments including toxicity, insufficient specificity, and low bioavailability. Although nanomedicine research is extensive, only a few nanomedicines are approved to be used. Either Bottlenecks or solutions of nanomedicine in immunotherapy need to be further explored to cope with challenges. In this review, a brief overview of several types of cancer immunotherapy approaches and their advantages and disadvantages will be provided. Then, the types of nanomedicines, drug delivery strategies, and the progress of applications are introduced. Finally, the application and prospect of nanomedicines in immunotherapy and Chimeric antigen receptor T-cell therapy (CAR-T) are highlighted and summarized to address the problems of immunotherapy the overall goal of this article is to provide insights into the potential use of nanomedicines and to improve the efficacy and safety of immunotherapy.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

Anti-TGF-β/PD-L1 bispecific antibody promotes T cell infiltration and exhibits enhanced antitumor activity in triple-negative breast cancer

BACKGROUND

Agents blocking programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have been approved for triple-negative breast cancer (TNBC). However, the response rate of anti-PD-1/PD-L1 is still unsatisfactory, partly due to immunosuppressive factors such as transforming growth factor-beta (TGF-β). In our previous pilot study, the bispecific antibody targeting TGF-β and murine PD-L1 (termed YM101) showed potent antitumor effect. In this work, we constructed a bispecific antibody targeting TGF-β and human PD-L1 (termed BiTP) and explored the antitumor effect of BiTP in TNBC.

METHODS

BiTP was developed using Check-BODY^TM bispecific platform. The binding affinity of BiTP was measured by surface plasmon resonance, ELISA, and flow cytometry. The bioactivity was assessed by Smad and NFAT luciferase reporter assays, immunofluorescence, western blotting, and superantigen stimulation assays. The antitumor activity of BiTP was explored in humanized epithelial-mesenchymal transition-6-hPDL1 and 4T1-hPDL1 murine TNBC models. Immunohistochemical staining, flow cytometry, and bulk RNA-seq were used to investigate the effect of BiTP on immune cell infiltration.

RESULTS

BiTP exhibited high binding affinity to dual targets. In vitro experiments verified that BiTP effectively counteracted TGF-β-Smad and PD-L1-PD-1-NFAT signaling. In vivo animal experiments demonstrated that BiTP had superior antitumor activity relative to anti-PD-L1 and anti-TGF-β monotherapy. Mechanistically, BiTP decreased collagen deposition, enhanced CD8⁺ T cell penetration, and increased tumor-infiltrating lymphocytes. This improved tumor microenvironment contributed to the potent antitumor activity of BiTP.

CONCLUSION

BiTP retains parent antibodies' binding affinity and bioactivity, with superior antitumor activity to parent antibodies in TNBC. Our data suggest that BiTP might be a promising agent for TNBC treatment.

The tumor microenvironment and triple-negative breast cancer aggressiveness: shedding light on mechanisms and targeting

INTRODUCTION

In contrast to other breast cancer subtypes, there are currently limited options of targeted therapies for triple-negative breast cancer (TNBC). Immense research has demonstrated that not only cancer cells but also stromal cells and immune cells in the tumor microenvironment (TME) play significant roles in the progression of TNBC. It is thus critical to understand the components of the TME of TNBC and the interactions between the various cell populations.

AREAS COVERED

The components of the TME of TNBC identified by single-cell technologies are reviewed. Furthermore, the molecular interactions between the cells and the potential therapeutic targets contributing to the progression of TNBC are discussed.

EXPERT OPINION

Single-cell omics studies have contributed to the classification of cells in the TME and the identification of important cell types involved in the progression and the treatment of the tumor. The interactions between cancer cells and stromal cells/immune cells in the TME have led to the discovery of potential therapeutic targets. Experimental data with spatial and temporal resolution will further boost the understanding of the TME of TNBC.

One Step Nucleic Acid Amplification (OSNA) Lysate Samples Are Suitable to Establish a Transcriptional Metastatic Signature in Patients with Early Stage Hormone Receptors-Positive Breast Cancer

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7, VTCN1, CD44, GATA3, ALOX15B, RORC, NECTIN2, LRG1, CD276, FOXM1 and IGF1R. Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.

Immune-Related Gene Signatures to Predict the Effectiveness of Chemoimmunotherapy in Triple-Negative Breast Cancer Using Exploratory Subgroup Discovery

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. Although immunotherapy has shown potential in TNBC patients, clinical studies have only demonstrated a modest response. Therefore, the exploration of immunotherapy in combination with chemotherapy is warranted. In this project we identified immune-related gene signatures for TNBC patients that may explain differences in patients' outcomes after anti-PD-L1+chemotherapy treatment. First, we ran the exploratory subgroup discovery algorithm on the TNBC dataset comprised of 422 patients across 24 studies. Secondly, we narrowed down the search to twelve homogenous subgroups based on tumor mutational burden (TMB, low or high), relapse status (disease-free or recurred), tumor cellularity (high, low and moderate), menopausal status (pre- or post) and tumor stage (I, II and III). For each subgroup we identified a union of the top 10% of genotypic patterns. Furthermore, we employed a multinomial regression model to predict significant genotypic patterns that would be linked to partial remission after anti-PD-L1+chemotherapy treatment. Finally, we uncovered distinct immune cell populations (T-cells, B-cells, Myeloid, NK-cells) for TNBC patients with various treatment outcomes. CD4-Tn-LEF1 and CD4-CXCL13 T-cells were linked to partial remission on anti-PD-L1+chemotherapy treatment. Our informatics pipeline may help to select better responders to chemoimmunotherapy, as well as pinpoint the underlying mechanisms of drug resistance in TNBC patients at single-cell resolution.

Triple-negative breast cancer: new options for systemic targeted therapy. A review

Background. In 15-20% of patients, breast cancer is characterized by the absence or negligible expression in malignant cells of molecular therapeutic receptor targets of three key types: estrogen receptors, progesterone receptors, human epidermal growth factor receptor-2 (triple negative breast cancer TNBC). At the 2021 conferences of the American and European Societies of Clinical Oncology (ASCO and ESMO) and the San Antonio Breast Cancer Symposium (SABCS), held from December 7 to 10, important advances in new approaches to the treatment of heterogeneous TNBC cohort were announced. Aim. To find and summarize the most striking results of clinical studies on new treatment options for TNBC patients based on the SABCS 2021. Materials and methods. We searched the databases of the digital medical education platform MEDtalks (Hilversum, The Netherlands) and the PubMed/Medline database and analyzed the results published in 2021-2022. Results. We systematized some results of clinical studies on drug therapy in patients with TNBC, discussed at SABCS 2021 (December 7-10, San Antonio, USA). There are now promising results from innovative clinical studies worldwide to identify the optimal approach to the selection of differentiated targeted and immunotherapies for the treatment of TNBC patients: OlympiA, KEYNOTE-522, cTRAK TN Phase II, KEYNOTE-355, NIMBUS, TROPION Phase I study. Conclusion. Considering the molecular and histological heterogeneity of TNBC, it is reasonable to identify subgroups of patients with some quantitative and qualitative clinical characteristics for further identification of effective personalized treatment regimens. Additional clinical studies and multivariate analysis of data in the subgroups of patients with TNBC, as well as individualized treatment cases, using current methodological tools will contribute to solving the issues in the management of this category of patients.

Evaluation of tumor-infiltrating lymphocytes (TILs) in molecular subtypes of an Indian cohort of breast cancer patients

OBJECTIVES

Evaluation of tumor-infiltrating lymphocytes (TILs) distribution in an Indian cohort of breast cancer patients for its prognostic significance.

METHODS

A retrospective cohort of breast cancer patients from a single onco-surgeon's breast cancer clinic with a uniform treatment strategy was evaluated for TILs. Tumor sections were H&E stained and scored for the spatial distribution and percent stromal TILs infiltration by a certified pathologist. The scores were analysed for association with treatment response and survival outcomes across molecular subtypes.

RESULTS

Total 229 breast cancer tumors were evaluated. Within spatial distribution categories, intra-tumoral TILs were observed to be associated with complete pathological response and lower recurrence frequency for the entire cohort. Subtype-wise analysis of stromal TILs (sTILs) re-enforced significantly higher infiltration in TNBC compared to HER2-positive and ER-positive tumors. A favourable association of higher stromal infiltration was observed with treatment response and disease outcomes, specifically in TNBC.

CONCLUSION

Intra-tumoral TILs showed a higher proportion with favourable association with better patient outcomes in an Indian cohort, unlike western cohorts where both stromal and intra-tumoral TILs show similar association with prognosis. With further validation, TILs can be developed as a cost-effective surrogate marker for treatment response, especially in a low-resource setting such as India.

Breast Cancer Sera Changes in Alu Element Methylation Predict Metastatic Disease Progression

BACKGROUND/AIM

During metastatic disease development, the cancer-immune system crosstalk induces epigenetic modifications to immune cells, impairing their functions. Recently, Alu elements methylation changes were widely studied in terms of early cancer detection. This study aimed to demonstrate in vitro Alu element methylation changes in peripheral immune cells in a metastatic setting and examine their prognostic values in metastatic breast cancer.

MATERIALS AND METHODS

Sera from sixteen metastatic cancer patients and sixteen healthy participants were obtained and used to culture normal peripheral immune cells. After 48 h of incubation, the percentage and pattern of Alu element methylation were examined for clinical relevance.

RESULTS

We found that the Alu element hypomethylation was affected by age in the cancer group. Intriguingly, a decrease in Alu element methylation was found in patients with early progressive disease. Moreover, an increase in unmethylated cytosine (mCuC) loci was related to the poorer prognosis group. Accordingly, the decrease in Alu element methylation and the increase in mCuC loci pattern in peripheral immune cells correlated with poorer prognosis and early progression in metastatic breast cancer.

CONCLUSION

Alu element hypomethylation in immune cells and their increased mCuC foci were related to the early progression of breast cancer. These warrant the use of Alu element methylation changes for diagnostic and therapeutic purposes in breast cancer.

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.

The Immune Landscape of Papillary Thyroid Cancer in the Context of Autoimmune Thyroiditis

Simple Summary

The association between papillary thyroid cancer and Hashimoto’s thyroiditis went through a long-standing human debate recently elucidated by the establishment of a novel mouse model. Papillary thyroid carcinoma is an excellent model for studying the tumor immune microenvironment because it is naturally accompanied by immune cells, making it a good candidate for the treatment with immune checkpoint inhibitors.

Abstract

Papillary thyroid cancer (PTC) often co-occurs with Hashimoto’s thyroiditis, an association that has long been reported in clinical studies, remaining controversial. Experimental evidence has recently shown that pre-existing thyroiditis has a beneficial effect on PTC growth and progression by a distinctive expansion of effector memory CD8 T cells. Although the link between inflammation and PTC might involve different components of the immune system, a deep characterization of them which includes T cells, B cells and tertiary lymphoid structures, Mye-loid cells, Neutrophils, NK cells and dendritic cells will be desirable. The present review article considers the role of the adaptive and innate immune response surrounding PTC in the context of Hashimoto’s thyroiditis. This review will focus on the current knowledge by in vivo and in vitro studies specifically performed on animals’ models; thyroid cancer cells and human samples including (i) the dual role of tumor-infiltrating lymphocytes; (ii) the emerging role of B cells and tertiary lymphoid structures; (iii) the role of myeloid cells, dendritic cells, and natural killer cells; (iv) the current knowledge of the molecular biomarkers implicated in the complex link between thyroiditis and PTC and the potential implication of cancer immunotherapy in PTC patients in the context of thyroiditis.

Prognostic Capability of TNBC 3-Gene Score among Triple-Negative Breast Cancer Subtypes

Background: Triple-negative breast cancer (TNBC) is a complex and molecularly heterogeneous entity, with the poorest outcome compared with other breast cancer subtypes. Previously, we developed a TNBC 3-gene score with a significant prognostic capability. This study aims to test the 3-gene score in the different TNBC subtypes. Methods: Data from 204 TNBC patients treated with neoadjuvant chemotherapy were retrieved from public datasets and pooled (GSE25066, GSE58812, and GSE16446). After removing batch effects, cases were classified into Lehman’s TNBC subtypes and then the TNBC 3-gene score was used to evaluate the risk of distant recurrence in each subgroup. In addition, the association with tumor-infiltrating lymphocyte (TILs) levels was evaluated in a retrospective group of 72 TNBC cases. Results: The TNBC 3-gene score was able to discriminate patients with different risks within the pooled cohort (HR = 2.41 for high vs. low risk; 95%CI: 1.50−3.86). The score showed predictive capability in the immunomodulatory subtype (HR = 4.16; 95%CI: 1.63−10.60) and in the mesenchymal stem-like subtype (HR = 18.76; 95%CI: 1.68−208.97). In the basal-like 1, basal-like-2, and mesenchymal subtypes, the observed differential risk patterns showed no statistical significance. The score had poor predictive capability in the luminal androgen receptor subtype (p = 0.765). In addition, a low TNBC 3-gene score was related to a high level of TIL infiltration (p < 0.001). Conclusions: The TNBC 3-gene score is able to predict the risk of distant recurrence in TNBC patients, specifically in the immunomodulatory and mesenchymal stem-like subtype. Despite a small sample size in each subgroup, an improved prognostic capability was seen in TNBC subtypes with tumor-infiltrating components.

Biomarkers and immunotherapy: where are we?

PURPOSE OF REVIEW

Here, we reviewed the recent breakthroughs in the understanding of predictive biomarkers for immune checkpoint inhibitors (ICI) treatment.

RECENT FINDINGS

ICI have revolutionized cancer therapy enabling novel therapeutic indications in multiple tumor types and increasing the probability of survival in patients with metastatic disease. However, in every considered tumor types only a minority of patients exhibits clear and lasting benefice from ICI treatment, and due to their unique mechanism of action treatment with ICI is also associated with acute clinical toxicities called immune related adverse events (irAEs) that can be life threatening. The approval of the first ICI drug has prompted many exploratory strategies for a variety of biomarkers and have shown that several factors might affect the response to ICI treatment, including tumors intrinsic factors, tumor microenvironment and tumor extrinsic or systemic factor. Currently, only three biomarkers programmed death-ligand 1 (PD-L1), tumor microenvironment and microsatellite instability had the US Food and Drug Administration-approbation with some limitations.

SUMMARY

The establishment of valid predictive biomarkers of ICI sensitivity has become a priority to guide patient treatment to maximize the chance of benefit and prevent unnecessary toxicity.

Immune Modulatory Effects of Molecularly Targeted Therapy and Its Repurposed Usage in Cancer Immunotherapy

The fast evolution of anti-tumor agents embodies a deeper understanding of cancer pathogenesis. To date, chemotherapy, targeted therapy, and immunotherapy are three pillars of the paradigm for cancer treatment. The success of immune checkpoint inhibitors (ICIs) implies that reinstatement of immunity can efficiently control tumor growth, invasion, and metastasis. However, only a fraction of patients benefit from ICI therapy, which turns the spotlight on developing safe therapeutic strategies to overcome the problem of an unsatisfactory response. Molecular-targeted agents were designed to eliminate cancer cells with oncogenic mutations or transcriptional targets. Intriguingly, accumulating shreds of evidence demonstrate the immunostimulatory or immunosuppressive capacity of targeted agents. By virtue of the high attrition rate and cost of new immunotherapy exploration, drug repurposing may be a promising approach to discovering combination strategies to improve response to immunotherapy. Indeed, many clinical trials investigating the safety and efficacy of the combination of targeted agents and immunotherapy have been completed. Here, we review and discuss the effects of targeted anticancer agents on the tumor immune microenvironment and explore their potential repurposed usage in cancer immunotherapy.

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.

Identification of Immune Cell Components in Breast Tissues by a Multiparametric Flow Cytometry Approach

Simple Summary

The tumor microenvironment in breast cancer plays important roles in tumor development and treatment response, giving important information critical for disease management. Today, an analysis of the tumor microenvironment is included in routine histopathologic reporting for practical clinical application. This manuscript aimed to deepen the study of the tumor microenvironment, analyzing the immune cells in breast tumoral and benign pathologies. Indeed, using a deep immunophenotyping approach by flow cytometry, we have studied the immune cells at the level of breast tissues, identifying different immunophenotyping that could be useful in the diagnosis and follow up of breast pathologies. As possible targets are continually being discovered in the tumor microenvironment, a future approach to breast cancer diagnosis and therapy could likely combine cancer cell elimination and tumor microenvironment modulation.

Abstract

Immune cell components are able to infiltrate tumor tissues, and different reports described the presence of infiltrating immune cells (TILs) in several types of solid tumors, including breast cancer. The primary immune cell component cells are reported as a lymphocyte population mainly comprising the cytotoxic (CD8+) T cells, with varying proportions of helper (CD4+) T cells and CD19+ B cells, and rarely NK cells. In clinical practice, an expert pathologist commonly detects TILs areas in hematoxylin and eosin (H&E)-stained histological slides via light microscopy. Moreover, other more in-depth approaches could be used to better define the immunological component associated with tumor tissues. Using a multiparametric flow cytometry approach, we have studied the immune cells obtained from breast tumor tissues compared to benign breast pathologies. A detailed evaluation of immune cell components was performed on 15 and 14 biopsies obtained from breast cancer and fibroadenoma subjects, respectively. The percentage of tumor-infiltrating T lymphocytes was significantly higher in breast cancer patients compared to patients with fibroadenoma. Infiltrating helper T lymphocytes were increased in the case of malignant breast lesions, while cytotoxic T lymphocytes disclosed an opposite trend. In addition, our data suggest that the synergistic effect of the presence/activation of NK cells and NKT cells, in line with the data in the literature, determines the dampening of the immune response. Moreover, the lymphocyte-to-monocyte ratio was calculated and was completely altered in patients with breast cancer. Our approach could be a potent prognostic factor to be used in diagnostic/therapeutic purposes for the improvement of breast cancer patients’ management.

Neither Tumor-Infiltrating Lymphocytes nor Cytotoxic T Cells Predict Enhanced Benefit from Chemotherapy in the DBCG77B Phase III Clinical Trial

Simple Summary

Apart from the direct killing of cancer cells, cyclophosphamide-based chemotherapy has been shown to induce an antitumor immune response, and is being used in combination with immunotherapies in cancer care. We assessed the interaction of chemotherapy with immune biomarkers expressed on primary tumor tissue from a randomized phase III clinical trial, and confirmed that the presence of tumor-infiltrating lymphocytes is linked to improved survival in premenopausal women with high-risk breast cancer, regardless of their treatment allocation. However, immune biomarkers including tumor-infiltrating lymphocytes do not predict extra benefit from cyclophosphamide chemotherapy. This finding applies across the major molecular subgroups, including non-luminal and basal breast cancers that tend to be more immunogenic, and are often considered the most suitable subsets for receiving immunotherapy.

Abstract

Recent studies have shown that immune infiltrates in the tumor microenvironment play a role in response to therapy, with some suggesting that patients with immunogenic tumors may receive increased benefit from chemotherapies. We evaluated this hypothesis in early breast cancer by testing the interaction between immune biomarkers and chemotherapy using materials from DBCG77B, a phase III clinical trial where high-risk premenopausal women were randomized to receive chemotherapy or no chemotherapy. Tissue microarrays were evaluated for tumor-infiltrating lymphocytes (TILs) assessed morphologically on hematoxylin and eosin-stained slides, and by immunohistochemistry for CD8, FOXP3, LAG-3, PD-1 and PD-L1. Following REMARK reporting guidelines, data analyses were performed according to a prespecified statistical plan, using 10-year invasive disease-free survival as the endpoint. Differences in survival probabilities between biomarker groups were evaluated by Kaplan–Meier and Cox proportional hazard ratio analyses and prediction for treatment benefit by an interaction test. Our results showed that stromal TILs were associated with an improved prognosis (HR = 0.93; p-value = 0.03), consistent with previous studies. However, none of the immune biomarkers predicted benefit from chemotherapy in the full study set nor within major breast cancer subtypes. Our study indicates that primary tumors with higher immune infiltration do not derive extra benefit from cyclophosphamide-based cytotoxic chemotherapy.

Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer

Background

The clinical outcomes of breast cancer (BC) are unpredictable due to the high level of heterogeneity and complex immune status of the tumor microenvironment (TME). When set up, multiple long non-coding RNA (lncRNA) signatures tended to be employed to appraise the prognosis of BC. Nevertheless, predicting immunotherapy responses in BC is still essential. LncRNAs play pivotal roles in cancer development through diverse oncogenic signal pathways. Hence, we attempted to construct an oncogenic signal pathway–based lncRNA signature for forecasting prognosis and immunotherapy response by providing reliable signatures.

Methods

We preliminarily retrieved RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and extracted lncRNA profiles by matching them with GENCODE. Following this, Gene Set Variation Analysis (GSVA) was used to identify the lncRNAs closely associated with 10 oncogenic signaling pathways from the TCGA-BRCA (breast-invasive carcinoma) cohort and was further screened by the least absolute shrinkage and selection operator Cox regression model. Next, an lncRNA signature (OncoSig) was established through the expression level of the final 29 selected lncRNAs. To examine survival differences in the stratification described by the OncoSig, the Kaplan–Meier (KM) survival curve with the log-rank test was operated on four independent cohorts (n = 936). Subsequently, multiple Cox regression was used to investigate the independence of the OncoSig as a prognostic factor. With the concordance index (C-index), the time-dependent receiver operating characteristic was employed to assess the performance of the OncoSig compared to other publicly available lncRNA signatures for BC. In addition, biological differences between the high- and low-risk groups, as portrayed by the OncoSig, were analyzed on the basis of statistical tests. Immune cell infiltration was investigated using gene set enrichment analysis (GSEA) and deconvolution tools (including CIBERSORT and ESTIMATE). The combined effect of the Oncosig and immune checkpoint genes on prognosis and immunotherapy was elucidated through the KM survival curve. Ultimately, a pan-cancer analysis was conducted to attest to the prevalence of the OncoSig.

Results

The OncoSig score stratified BC patients into high- and low-risk groups, where the latter manifested a significantly higher survival rate and immune cell infiltration when compared to the former. A multivariate analysis suggested that OncoSig is an independent prognosis predictor for BC patients. In addition, compared to the other four publicly available lncRNA signatures, OncoSig exhibited superior predictive performance (AUC = 0.787, mean C-index = 0.714). The analyses of the OncoSig and immune checkpoint genes clarified that a lower OncoSig score meant significantly longer survival and improved response to immunotherapy. In addition to BC, a high OncoSig score in several other cancers was negatively correlated with survival and immune cell infiltration.

Conclusions

Our study established a trustworthy and discriminable prognostic signature for BC patients with similar clinical profiles, thus providing a new perspective in the evaluation of immunotherapy responses. More importantly, this finding can be generalized to be applicable to the vast majority of human cancers.

Addiction of Cancer Stem Cells to MUC1-C in Triple-Negative Breast Cancer Progression

Triple-negative breast cancer (TNBC) is an aggressive malignancy with limited treatment options. TNBC progression is associated with expansion of cancer stem cells (CSCs). Few insights are available regarding druggable targets that drive the TNBC CSC state. This review summarizes the literature on TNBC CSCs and the compelling evidence that they are addicted to the MUC1-C transmembrane protein. In normal epithelia, MUC1-C is activated by loss of homeostasis and induces reversible wound-healing responses of inflammation and repair. However, in settings of chronic inflammation, MUC1-C promotes carcinogenesis. MUC1-C induces EMT, epigenetic reprogramming and chromatin remodeling in TNBC CSCs, which are dependent on MUC1-C for self-renewal and tumorigenicity. MUC1-C-induced lineage plasticity in TNBC CSCs confers DNA damage resistance and immune evasion by chronic activation of inflammatory pathways and global changes in chromatin architecture. Of therapeutic significance, an antibody generated against the MUC1-C extracellular domain has been advanced in a clinical trial of anti-MUC1-C CAR T cells and in IND-enabling studies for development as an antibody–drug conjugate (ADC). Agents targeting the MUC1-C cytoplasmic domain have also entered the clinic and are undergoing further development as candidates for advancing TNBC treatment. Eliminating TNBC CSCs will be necessary for curing this recalcitrant cancer and MUC1-C represents a promising druggable target for achieving that goal.

Tumor-Associated Macrophages in Canine Oral and Cutaneous Melanomas and Melanocytomas: Phenotypic and Prognostic Assessment

The tumor microenvironment is a complex system, where neoplastic cells interact with immune and stromal cells. Tumor-associated macrophages (TAMs) are considered among the most numerically and biologically noteworthy cellular components in tumors and the attention on this cellular population has been growing during the last decade, both for its prognostic role and as a potential future therapeutic target. Melanoma, particularly the oral form, despite being one of the most immunogenic tumors, bears a poor prognosis in dogs and humans, due to its highly aggressive biological behavior and limited therapeutic options. The aims of this study are to characterize and quantify TAMs (using CD163, CD204, Iba1, and MAC387) in canine melanocytic tumors and to evaluate the association of these markers with diagnosis, histologic prognostic features, presence of metastases, and outcome, and to provide preliminary data for possible future therapies targeting TAMs. Seventy-two melanocytic tumors (27 oral melanomas, 25 cutaneous melanomas, 14 cutaneous melanocytomas, and 6 oral melanocytomas) were retrospectively selected and submitted to immunohistochemistry and double immunofluorescence. Double immunolabeling revealed that most CD163⁺ and CD204⁺cells co-expressed Iba1, which labeled also dendritic cells. Iba1 was instead rarely co-expressed with MAC387. Nevertheless, the expression of macrophagic markers showed a mild to moderate association among the four markers, except for CD204 and MAC387. The number of CD163⁺, CD204⁺, and MAC387⁺ cells was significantly higher in oral melanomas compared to oral melanocytomas (p < 0.001; p < 0.05 and p < 0.01, respectively), whereas Iba1 was differentially expressed in cutaneous melanomas and melanocytomas (p < 0.05). Moreover, CD163, IBA1 and MAC387 expression was associated with nuclear atypia and mitotic count. The number of CD163⁺cells was associated with the presence of metastases and tumor-related death in oral melanocytic tumors (p < 0.05 and p = 0.001, respectively).