Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer

Navigating practical challenges in immunotherapy for metastatic triple negative breast cancer

Immunotherapy has revolutionized cancer therapy and now represents a standard of care for many tumor types, including triple-negative breast cancer. Despite the positive results that have led to the approval of immunotherapy in both early- and advanced-stage triple-negative breast cancer, pivotal clinical trials cannot address the myriad questions arising in everyday clinical practice, often falling short in delivering all the information that clinicians require. In this manuscript, we aim to address some of these practical questions, with the purpose of providing clinicians with a guide for optimizing the use of immune checkpoint inhibitors in the management of breast cancer patients and identifying opportunities for future research to clarify unresolved questions.

Divergent Cellular Expression Patterns of PD-L1 and PD-L2 Proteins in Breast Cancer

PD-L1 immunohistochemistry (IHC) has become an established method for predicting cancer response to targeted anti-PD1 immunotherapies, including breast cancer (BC). The alternative PD-1 ligand, PD-L2, remains understudied but may be a complementary predictive marker. Prospective analysis of 32 breast cancers revealed divergent expression patterns of PD-L1 and PD-L2. PD-L1-positivity was higher in immune cells than in cancer cells (median = 5.0% vs. 0.0%; p = 0.001), whereas PD-L2-positivity was higher in cancer cells than immune cells (median = 30% vs. 5.0%; p = 0.001). Percent positivity of PD-L1 and PD-L2 were not correlated, neither in cancer cells nor immune cells. Based on a cut-point of ≥1% positivity, ER+ tumors (n = 23) were frequently PD-L2-positive (73.9%), whereas only 40.9% were PD-L1-positive. These data suggest differential control of cellular PD-L1 and PD-L2 expression in BC and a potential role for PD-L2 IHC as a complementary marker to PD-L1 to improve selection of aggressive ER+ BC that may benefit from anti-PD-1 therapy.

Histological Patterns and Mammographic Presentation of Invasive Lobular Carcinoma Show No Obvious Associations

Invasive lobular carcinoma of the breast has different mammographic appearances, including spiculated or lobulated masses, architectural distortion, increased breast density, and the possibility of also being occult. Histologically, the morphology is also variable, as several patterns have been described beside the classical one, including the solid, the alveolar, the trabecular, the one with tubular elements, and others. Of 146 ILC cases, 141 were reviewed for mammographic appearance and 136 for histological patterns by two radiologist and two pathologists, respectively; 132 common cases were analyzed for possible associations between mammographic presentation and the histological patterns. Interobserver agreement on the presence or absence of a given mammographic morphology ranged from 45% (increased density) to 95% (occult lesion); the most common radiomorphology was that of a spiculated mass. Interobserver agreement on the presence or absence of a given histological pattern ranged between 79% (solid) and 99% (classical) but was worse when semi-quantification was also included. The mammography-pathology correlation was less than optimal. Multifocality was more commonly detected by histology. The identification of a mammographic mass lesion often coincided with a mass-like lesion on the histological slides and vice versa, but nearly half of the mammographically occult lesions were felt to have masses on histological slides assessed grossly. Histological patterns showed no obvious associations with one or the other mammographic appearance.

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments

Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial interobserver variability has been reported using these immunoassays. Artificial intelligence (AI) has the potential to accurately measure biomarker expression in tissue samples, but its reliability and comparability to standard manual scoring remain to be evaluated. This multinational study sought to compare the %TC scoring of PD-L1 expression in advanced urothelial carcinoma, assessed by either an AI Measurement Model (AIM-PD-L1) or expert pathologists. The concordance among pathologists and between pathologists and AIM-PD-L1 was determined. The positivity rate of ≥ 1%TC PD-L1 was between 20-30% for 8/10 pathologists, and the degree of agreement and scoring distribution for among pathologists and between pathologists and AIM-PD-L1 was similar both scored as a continuous variable or using the pre-defined cutoff. Numerically higher score variation was observed with the 22C3 assay than with the 28-8 assay. A 2-h training module on the 28-8 assay did not significantly impact manual assessment. Cases exhibiting significantly higher variability in the assessment of PD-L1 expression (mean absolute deviation > 10) were found to have patterns of PD-L1 staining that were more challenging to interpret. An improved understanding of sources of manual scoring variability can be applied to PD-L1 expression analysis in the clinical setting. In the future, the application of AI algorithms could serve as a valuable reference guide for pathologists while scoring PD-L1.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Concordance of assessments of four PD-L1 immunohistochemical assays in esophageal squamous cell carcinoma (ESCC)

OBJECTIVE

Given real-world limitations in programmed death-ligand 1 (PD-L1) testing, concordance studies between PD-L1 assays are needed. We undertook comparisons of PD-L1 assays (DAKO22C3, Ventana SP263, Ventana SP142, E1L3N) among observers in esophageal squamous cell carcinoma (ESCC) to provide information on the analytical and clinical comparability of four PD-L1 IHC assays.

METHODS

Paraffin embedded samples of 50 cases of esophageal squamous cell carcinoma were obtained, satined with all four PD-L1 assays. PD-L1 was evaluated by 68 pathologists from 19 different hospitals. PD-L1 expression was assessed for combined positive score (CPS).

RESULTS

The expression sensitivity of SP263 was the highest in ESCC, followed by 22C3, E1L3N and SP142. Taking CPS 10 as the critical value, inter-observer concordance for CPS scores among 68 physicians was assessed for the 22C3, SP263, SP142, and E1L3N assays, yielding values of 0.777, 0.790, 0.758, and 0.782, respectively. In the comparison between assays, the overall CPS scores concordance rates between 22C3 and SP263, SP142, and E1L3N were 0.896, 0.833, and 0.853, respectively. 22C3 and SP263 have high concordance, with OPA of 0.896, while E1L3N and SP142 have the highest concordance, with OPA of 0.908.

CONCLUSION

In ESCC, the concordance of PD-L1 evaluation among observers is good, and the immune cell score is still an important factor affecting the concordance of interpretation among observers. Cases near the specific threshold are still the difficult problem of interpretation. SP263 had the highest CPS score of the four assays. SP263 cannot identify all 22C3 positive cases, but had good concordance with 22C3.E1L3N and SP142 showed high concordance.

Ki67 assessment protocol as an integral biomarker for avoiding radiotherapy in the LUMINA breast cancer trial

AIMS

The LUMINA trial demonstrated a very low local recurrence rate in women ≥55 years with low-risk luminal A breast cancer (defined as grade I-II, T1N0, hormone receptor positive, HER2 negative and Ki67 index ≤13.25%) treated with breast-conserving surgery and endocrine therapy (but no other systemic therapy), supporting the safe omission of radiation in these women. Here we describe the protocol for Ki67 assessment, the companion diagnostic used to guide omission of adjuvant radiotherapy.

METHODS

Ki67 immunohistochemistry was performed on full-face sections at one of three regional labs. Pathologists trained in the International Ki67 in Breast Cancer Working Group (IKWG) method demarcated tumour areas on scanned slides and scored 100 nuclei from each of at least five randomly selected 1-mm fields. For cases with high Ki67 heterogeneity, further virtual cores were selected and scored in order to confidently assign a case as luminal A (≤13.25%) or B (>13.25%). Interlaboratory variability was assessed through an annual quality assurance programme during the study period.

RESULTS

From the quality assurance programme, the mean Ki67 index across all cases/labs was 13%. The observed intraclass correlation coefficient (ICC) and kappa statistics were ≥0.9 and ≥0.7, respectively, indicating a substantial level of agreement. Median scoring time was 4 min per case. The IKWG-recommended scoring method, performed directly from slides, requiring up to four scored fields, is concordant with the LUMINA scoring method (ICC ≥ 0.9).

CONCLUSION

Ki67 is a practical, reproducible, and inexpensive biomarker that can identify low-risk luminal A breast cancers as potential candidates for radiation de-escalation.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov number, NCT01791829.

Neoadjuvant Immunotherapy in Early, Triple-Negative Breast Cancers: Catching Up with the Rest

Despite breast cancer being long thought to be "immunologically cold," within early, triple-negative breast cancer (TNBC), there has been exciting advances with the use of immune checkpoint modulation combined with neoadjuvant chemotherapy. We review the major trials that have investigated combination immunochemotherapy in the neoadjuvant setting, reviewing both the pathological complete response rates and the maturing data regarding event-free and overall survival. Strategies to deescalate adjuvant therapy in patients with preserving excellent clinical outcome, as well as exploration of combinatorial adjuvant therapies to improve outcome in those with extensive residual are the next-generation challenges. In addition to refinement of existing biomarkers, such as PD-L1, TILs, and tumor mutational burden (TMB), exploration of topics like the microbiome as both a biomarker and a therapeutic has shown promise in other cancer types, which motivates investigating these in breast cancer.

Enhancing personalized immune checkpoint therapy by immune archetyping and pharmacological targeting

Immune checkpoint inhibitors (ICIs) are an expanding class of immunotherapeutic agents with the potential to cure cancer. Despite the outstanding clinical response in patient subsets, most individuals become refractory or develop resistance. Patient stratification and personalized immunotherapies are limited by the absence of predictive response markers. Recent findings show that dominant patterns of immune cell composition, T-cell status and heterogeneity, and spatiotemporal distribution of immune cells within the tumor microenvironment (TME) are becoming essential determinants of prognosis and therapeutic response. In this context, ICIs also function as investigational tools and proof of concept, allowing the validation of the identified mechanisms. After reviewing the current state of ICIs, this article will explore new comprehensive predictive markers for ICIs based on recent discoveries. We will discuss the recent establishment of a classification of TMEs into immune archetypes as a tool for personalized immune profiling, allowing patient stratification before ICI treatment. We will discuss the developing comprehension of T-cell diversity and its role in shaping the immune profile of patients. We describe the potential of strategies that score the mutual spatiotemporal modulation between T-cells and other cellular components of the TME. Additionally, we will provide an overview of a range of synthetic and naturally occurring or derived small molecules. We will compare compounds that were recently identified by in silico prediction to wet lab-validated drug candidates with the potential to function as ICIs and/or modulators of the cellular components of the TME.

An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment

We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Specifically, the same tumor sections were stained with the expensive multiplex immunofluorescence (mIF) assay first and then restained with cheaper multiplex immunohistochemistry (mIHC). This is a first public dataset that demonstrates the equivalence of these two staining methods which in turn allows several use cases; due to the equivalence, our cheaper mIHC staining protocol can offset the need for expensive mIF staining/scanning which requires highly-skilled lab technicians. As opposed to subjective and error-prone immune cell annotations from individual pathologists (disagreement > 50%) to drive SOTA deep learning approaches, this dataset provides objective immune and tumor cell annotations via mIF/mIHC restaining for more reproducible and accurate characterization of tumor immune microenvironment (e.g. for immunotherapy). We demonstrate the effectiveness of this dataset in three use cases: (1) IHC quantification of CD3/CD8 tumor-infiltrating lymphocytes via style transfer, (2) virtual translation of cheap mIHC stains to more expensive mIF stains, and (3) virtual tumor/immune cellular phenotyping on standard hematoxylin images. The dataset is available at https://github.com/nadeemlab/DeepLIIF.

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.

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.

Multi-Institutional Evaluation of Pathologists' Assessment Compared to Immunoscore

BACKGROUND

The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification.

METHODS

An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS.

RESULTS

Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12).

CONCLUSIONS

The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.

ESMO expert consensus statements (ECS) on the definition, diagnosis, and management of HER2-low breast cancer

Human epidermal growth factor receptor 2 (HER2)-low breast cancer has recently emerged as a targetable subset of breast tumors, based on the evidence from clinical trials of novel anti-HER2 antibody-drug conjugates. This evolution has raised several biological and clinical questions, warranting the establishment of consensus to optimally treat patients with HER2-low breast tumors. Between 2022 and 2023, the European Society for Medical Oncology (ESMO) held a virtual consensus-building process focused on HER2-low breast cancer. The consensus included a multidisciplinary panel of 32 leading experts in the management of breast cancer from nine different countries. The aim of the consensus was to develop statements on topics that are not covered in detail in the current ESMO Clinical Practice Guideline. The main topics identified for discussion were (i) biology of HER2-low breast cancer; (ii) pathologic diagnosis of HER2-low breast cancer; (iii) clinical management of HER2-low metastatic breast cancer; and (iv) clinical trial design for HER2-low breast cancer. The expert panel was divided into four working groups to address questions relating to one of the four topics outlined above. A review of the relevant scientific literature was conducted in advance. Consensus statements were developed by the working groups and then presented to the entire panel for further discussion and amendment before voting. This article presents the developed statements, including findings from the expert panel discussions, expert opinion, and a summary of evidence supporting each statement.

Unleashing the potential of AI for pathology: challenges and recommendations

Computational pathology is currently witnessing a surge in the development of AI techniques, offering promise for achieving breakthroughs and significantly impacting the practices of pathology and oncology. These AI methods bring with them the potential to revolutionize diagnostic pipelines as well as treatment planning and overall patient care. Numerous peer-reviewed studies reporting remarkable performance across diverse tasks serve as a testimony to the potential of AI in the field. However, widespread adoption of these methods in clinical and pre-clinical settings still remains a challenge. In this review article, we present a detailed analysis of the major obstacles encountered during the development of effective models and their deployment in practice. We aim to provide readers with an overview of the latest developments, assist them with insights into identifying some specific challenges that may require resolution, and suggest recommendations and potential future research directions. © 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.

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.

Multi-Institutional Study of Pathologist Reading of the Programmed Cell Death Ligand-1 Combined Positive Score Immunohistochemistry Assay for Gastric or Gastroesophageal Junction Cancer

The assessment of the expression of programmed cell death ligand-1 (PD-L1) using immunohistochemistry (IHC) has been controversial since its introduction. The methods of assessment and the range of assays and platforms contribute to confusion. Perhaps the most challenging aspect of PD-L1 IHC is the combined positive score (CPS) method of interpretation of IHC results. Although the CPS method is prescribed for more indications than any other PD-L1 scoring system, its reproducibility has never been rigorously assessed. In this study, we collected a series of 108 gastric or gastroesophageal junction cancer cases, stained them using the Food and Drug Administration-approved 22C3 assay, scanned them, and then circulated them to 14 pathologists at 13 institutions for the assessment of interpretative concordance for the CPS system. We found that higher cut points (10 or 20) performed better than a CPS of <1 or >1. We used the Observers Needed to Evaluate Subjective Tests algorithm to assess how the CPS system might perform in the real-world setting and found that the cut points of <1 or >1 showed an overall percent agreement of only 30% among the pathologist raters, with a plateau occurring at 8 raters. The raters performed better at higher cut points. However, the best cut point of <20 versus that of >20 was still disappointing, with a plateau at an overall percent agreement of 70% (at 7 raters). Although there is no ground truth for CPS, we compared the score with quantitative messenger RNA measurement and showed no relationship between the score (at any cut point) and messenger RNA amount. In summary, we showed that CPS shows high subjective variability among pathologist readers and is likely to perform poorly in the real-world setting. This system may be the root cause of the poor specificity and relatively low predictive value of IHC companion diagnostic tests for PD-1 axis therapies that use the CPS system.

TRPS1 expression in cytokeratin 5 expressing triple negative breast cancers, its value as a marker of breast origin

The lack of oestrogen receptor, progesterone receptor and human epidermal growth factor receptor-2 expression in breast cancer (BC) is the basis for the categorization of the tumour as triple negative breast carcinoma (TNBC). The majority of TNBCs are aggressive tumours with common metastases and decreased expression of markers that could help in identifying the metastatic lesion as of mammary origin. Breast markers, such as gross cystic disease fluid protein-15 (GCDPF-15), GATA binding protein 3 (GATA3), mammaglobin (MGB) and SOX10, are not uniquely specific to BC. Our aim was to evaluate trichorhinophalangeal syndrome type 1 (TRPS1) protein as a breast marker in a series of cytokeratin-5-expressing TNBC, mostly corresponding to basal-like TNBCs, previously characterized for the expression of other breast markers. One hundred seventeen TNBCs in tissue microarrays were immunostained for TRPS1. The cut-off for positivity was ≥ 10%. The reproducibility of this classification was also assessed. TRPS1 positivity was detected in 92/117 (79%) cases, and this exceeded the expression of previously tested markers like SOX10 82 (70%), GATA3 11 (9%), MGB 10 (9%) and GCDFP-15 7 (6%). Of the 25 TRPS1-negative cases, 11 were positive with SOX10, whereas 5 to 6 dual negatives displayed positivity for the other makers. The evaluation showed substantial agreement. Of the five markers compared, TRPS1 seems the most sensitive marker for the mammary origin of CK5-expressing TNBCs. Cases that are negative are most often labelled with SOX10, and the remainder may still demonstrate positivity for any of the 3 other markers. TRPS1 has a place in breast marker panels.

High Interobserver Variability among Pathologists Using Combined Positive Score to Evaluate PD-L1 Expression in Gastric, Gastroesophageal Junction and Esophageal Adenocarcinoma

Reliable, reproducible methods to interpret programmed death ligand-1 (PD-L1) expression on tumor cells (TC) and immune cells (IC) are needed for pathologists to inform decisions associated with checkpoint inhibitor therapies. Our international study compared interpathologist agreement of PD-L1 expression using combined positive score (CPS) under standardized conditions on samples from patients with gastric/gastroesophageal junction/esophageal adenocarcinoma. Tissue sections from 100 adenocarcinoma pre-treatment biopsies were stained in a single laboratory using the PD-L1 IHC 28-8 and 22C3(Agilent) pharmDx immunohistochemical assays. PD-L1 CPS was evaluated by 12 pathologists on scanned whole slide images of these biopsies before and after a 2-hour CPS training session by Agilent. Additionally, pathologists determined PD-L1 positive TC, IC, and total viable TC on a single tissue fragment from 35 of 100 biopsy samples. Scoring agreement among pathologists was assessed using the intraclass correlation coefficient (ICC). Interobserver variability for CPS for 100 biopsies was high with only fair agreement among pathologists both pre- (range 0.45 to 0.55) and post-training (range 0.56 to 0.57) for both assays. For the 35 single biopsy samples, poor/fair agreement was also observed for the total number viable TC (ICC 0.09), number of PD-L1 positive IC (ICC 0.19), number of PD-L1 positive TC (ICC 0.54), and calculated CPS (ICC 0.14), while calculated TC score (positive TC/Total TC) showed excellent agreement (ICC 0.82). Retrospective histologic review of samples with the poorest interpathologist agreement revealed (1) ambiguous identification of positively staining stromal cells, (2) faint or variable intensity of staining, (3) difficulty in distinguishing membranous from cytoplasmic tumor staining, and (4) cautery and crush artifact, as possible confounding factors. These results emphasize the need for objective techniques to standardize the interpretation of PD-L1 expression when using the CPS methodology on gastric/gastroesophageal junction cancer biopsies to accurately identify patients most likely to benefit from immune checkpoint inhibitor therapy.

Inter- and Intra-Observer Agreement of PD-L1 SP142 Scoring in Breast Carcinoma-A Large Multi-Institutional International Study

The assessment of PD-L1 expression in TNBC is a prerequisite for selecting patients for immunotherapy. The accurate assessment of PD-L1 is pivotal, but the data suggest poor reproducibility. A total of 100 core biopsies were stained using the VENTANA Roche SP142 assay, scanned and scored by 12 pathologists. Absolute agreement, consensus scoring, Cohen's Kappa and intraclass correlation coefficient (ICC) were assessed. A second scoring round after a washout period to assess intra-observer agreement was carried out. Absolute agreement occurred in 52% and 60% of cases in the first and second round, respectively. Overall agreement was substantial (Kappa 0.654-0.655) and higher for expert pathologists, particularly on scoring TNBC (6.00 vs. 0.568 in the second round). The intra-observer agreement was substantial to almost perfect (Kappa: 0.667-0.956), regardless of PD-L1 scoring experience. The expert scorers were more concordant in evaluating staining percentage compared with the non-experienced scorers (R² = 0.920 vs. 0.890). Discordance predominantly occurred in low-expressing cases around the 1% value. Some technical reasons contributed to the discordance. The study shows reassuringly strong inter- and intra-observer concordance among pathologists in PD-L1 scoring. A proportion of low-expressors remain challenging to assess, and these would benefit from addressing the technical issues, testing a different sample and/or referring for expert opinions.

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.

Immunotherapy in breast cancer: an overview of current strategies and perspectives

Recent progress in immunobiology has led the way to successful host immunity enhancement against breast cancer. In triple-negative breast cancer, the combination of cancer immunotherapy based on PD-1/PD-L1 immune checkpoint inhibitors with chemotherapy was effective both in advanced and early setting phase 3 clinical trials. These encouraging results lead to the first approvals of immune checkpoint inhibitors in triple-negative breast cancer and thus offer new therapeutic possibilities in aggressive tumors and hard-to-treat populations. Furthermore, several ongoing trials are investigating combining immunotherapies involving immune checkpoint inhibitors with conventional therapies and as well as with other immunotherapeutic strategies such as cancer vaccines, CAR-T cells, bispecific antibodies, and oncolytic viruses in all breast cancer subtypes. This review provides an overview of immunotherapies currently under clinical development and updated key results from clinical trials. Finally, we discuss the challenges to the successful implementation of immune treatment in managing breast cancer and their implications for the design of future clinical trials.

Breast Cancer Pathology in the Era of Genomics

The era of genomic medicine provides an opportunity for pathologists to offer greater detail about the molecular underpinnings of a patient's cancer and thereby more targeted therapeutic options. In this review article, the role of genomics in breast cancer pathology is discussed, as it pertains to risk management, classification of special tumor types, predictive and prognostic testing, identification of actionable therapeutic targets, and monitoring for disease progression or development of treatment resistance.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Triple negative breast cancer: Immunogenicity, tumor microenvironment, and immunotherapy

Triple negative breast cancer (TNBC) is a biologically diverse subtype of breast cancer characterized by genomic and transcriptional heterogeneity and exhibiting aggressive clinical behaviour and poor prognosis. In recent years, emphasis has been placed on the identification of mechanisms underlying the complex genomic and biological profile of TNBC, aiming to tailor treatment strategies. High immunogenicity, specific immune activation signatures, higher expression of immunosuppressive genes and higher levels of stromal Tumor Infiltrating Lymphocytes, constitute some of the key elements of the immune driven landscape associated with TNBC. The unprecedented response of TNBC to immunotherapy has undoubtedly changed the standard of care in this disease both in the early and the metastatic setting. However, the extent of interplay between immune infiltration and mutational signatures in TNBC is yet to be fully unravelled. In the present review, we present clinical evidence on the immunogenicity and tumour microenvironment influence on TNBC progression and the current treatment paradigms in TNBC based on immunotherapy.

Immunotherapy for Triple-Negative Breast Cancer: Combination Strategies to Improve Outcome

Due to the absence of hormone receptor (both estrogen receptors and progesterone receptors) along with human epidermal growth factor receptor 2 (HER-2) amplification, the treatment of triple-negative breast cancer (TNBC) cannot benefit from endocrine or anti-HER-2 therapy. For a long time, chemotherapy was the only systemic treatment for TNBC. Due to the lack of effective treatment options, the prognosis for TNBC is extremely poor. The successful application of immune checkpoint inhibitors (ICIs) launched the era of immunotherapy in TNBC. However, the current findings show modest efficacy of programmed cell death- (ligand) 1 (PD-(L)1) inhibitors monotherapy and only a small proportion of patients can benefit from this approach. Based on the basic principles of immunotherapy and the characteristics of the tumor immune microenvironment (TIME) in TNBC, immune combination therapy is expected to further enhance the efficacy and expand the beneficiary population of patients. Given the diversity of drugs that can be combined, it is important to select effective biomarkers to identify the target population. Moreover, the side effects associated with the combination of multiple drugs should also be considered.

Multi-institutional Assessment of Pathologist Scoring HER2 Immunohistochemistry

The HercepTest was approved 20+ years ago as the companion diagnostic test for trastuzumab in human epidermal growth factor 2 (HER2) or ERBB2 gene-amplified/overexpressing breast cancers. Subsequent HER2 immunohistochemistry (IHC) assays followed, including the now most common Ventana 4B5 assay. Although this IHC assay has become the clinical standard, its reliability, reproducibility, and accuracy have largely been approved and accepted on the basis of concordance among small numbers of pathologists without validation in a real-world setting. In this study, we evaluated the concordance and interrater reliability of scoring HER2 IHC in 170 breast cancer biopsies by 18 breast cancer-specialized pathologists from 15 institutions. We used the Observers Needed to Evaluate Subjective Tests method to determine the plateau of concordance and the minimum number of pathologists needed to estimate interrater agreement values for large numbers of raters, as seen in the real-world setting. We report substantial discordance within the intermediate categories (<1% agreement for 1+ and 3.6% agreement for 2+) in the 4-category HER2 IHC scoring system. The discordance within the IHC 0 cases is also substantial with an overall percent agreement (OPA) of only 25% and poor interrater reliability metrics (0.49 Fleiss' kappa, 0.55 intraclass correlation coefficient). This discordance can be partially reduced by using a 3-category system (28.8% vs 46.5% OPA for 4-category and 3-category scoring systems, respectively). Observers Needed to Evaluate Subjective Tests plots suggest that the OPA for the task of determining a HER2 IHC score 0 from not 0 plateaus statistically around 59.4% at 10 raters. Conversely, at the task of scoring HER2 IHC as 3+ or not 3+ pathologists' concordance was much higher with an OPA that plateaus at 87.1% with 6 raters. This suggests that legacy HER2 IHC remains valuable for finding the patients in whom the ERBB2 gene is amplified but unacceptably discordant in assigning HER2-low or HER2-negative status for the emerging HER2-low therapies.

Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer

Programmed death ligand-1 (PD-L1) has been recently adopted for breast cancer as a predictive biomarker for immunotherapies. The cost, time, and variability of PD-L1 quantification by immunohistochemistry (IHC) are a challenge. In contrast, hematoxylin and eosin (H&E) is a robust staining used routinely for cancer diagnosis. Here, we show that PD-L1 expression can be predicted from H&E-stained images by employing state-of-the-art deep learning techniques. With the help of two expert pathologists and a designed annotation software, we construct a dataset to assess the feasibility of PD-L1 prediction from H&E in breast cancer. In a cohort of 3,376 patients, our system predicts the PD-L1 status in a high area under the curve (AUC) of 0.91 - 0.93. Our system is validated on two external datasets, including an independent clinical trial cohort, showing consistent prediction performance. Furthermore, the proposed system predicts which cases are prone to pathologists miss-interpretation, showing it can serve as a decision support and quality assurance system in clinical practice.

PD-L1 Expression in Triple-negative Breast Cancer-a Comparative Study of 3 Different Antibodies

BACKGROUND

Assessment of programmed death protein-ligand 1 (PD-L1) in triple-negative breast cancer (TNBC) has entered daily practice to identify patients eligible for treatment with immune checkpoint inhibitors. However, different antibodies and different cut-offs for PD-L1 positivity are used, and the interchangeability of these methods is not clear. The aim of our study was to analyze whether different PD-L1 antibodies can be used interchangeably to identify TNBC patients as PD-L1 positive.

METHODS

A tissue microarray encompassing 147 TNBC cases was immunohistochemically analyzed using 3 different antibodies against PD-L1: SP142, SP263, and E1L3N. PD-L1 positivity was determined as ≥1% of positive tumor-associated immune cells. The staining patterns of the 3 antibodies were compared and correlated with clinicopathological data.

RESULTS

A total of 84 cases were evaluable for PD-L1 analysis with all 3 antibodies. PD-L1 was positive in 50/84 patients (59.5%) with SP263, in 44/84 (52.4%) with E1L3N, and in 29/84 (34.5%) with SP142. There was no statistical difference between the performance of SP263 and E1L3N, but both antibodies stained significantly more cases than the SP142 antibody.

CONCLUSIONS

Our results show that the 3 PD-L1 antibodies identify different TNBC patient subgroups as PD-L1 positive and, therefore cannot be used interchangeably. Additional studies are needed to further investigate the use and impact of different PD-L1 antibody clones for predictive selection of TNBC patients for treatment with immune checkpoint inhibitors.

Proceedings From the ASCO/College of American Pathologists Immune Checkpoint Inhibitor Predictive Biomarker Summit

PURPOSE

Immune checkpoint inhibition (ICI) therapy represents one of the great advances in the field of oncology, highlighted by the Nobel Prize in 2018. Multiple predictive biomarkers for ICI benefit have been proposed. These include assessment of programmed death ligand-1 expression by immunohistochemistry, and determination of mutational genotype (microsatellite instability or mismatch repair deficiency or tumor mutational burden) as a reflection of neoantigen expression. However, deployment of these assays has been challenging for oncologists and pathologists alike.

METHODS

To address these issues, ASCO and the College of American Pathologists convened a virtual Predictive Factor Summit from September 14 to 15, 2021. Representatives from the academic community, US Food and Drug Administration, Centers for Medicare and Medicaid Services, National Institutes of Health, health insurance organizations, pharmaceutical companies, in vitro diagnostics manufacturers, and patient advocate organizations presented state-of-the-art predictive factors for ICI, associated problems, and possible solutions.

RESULTS

The Summit provided an overview of the challenges and opportunities for improvement in assay execution, interpretation, and clinical applications of programmed death ligand-1, microsatellite instability-high or mismatch repair deficient, and tumor mutational burden-high for ICI therapies, as well as issues related to regulation, reimbursement, and next-generation ICI biomarker development.

CONCLUSION

The Summit concluded with a plan to generate a joint ASCO/College of American Pathologists strategy for consideration of future research in each of these areas to improve tumor biomarker tests for ICI therapy.

Concordance of PD-L1 expression in triple-negative breast cancers in Chinese patients: A retrospective and pathologist-based study

OBJECTIVE

To compare the expression of programmed cell death ligand 1 (PD-L1) in different paraffin blocks from the same triple-negative breast cancers (TNBC) specimen and between matched primary tumors and lymph node metastases (LNMets). We also aim to determine the interobserver agreement between pathologists trained on PD-L1 (SP142) assay in assessing TNBC.

METHODS

426 histologically confirmed TNBC cases, in which 85 have LNMets, were included in this study. A PD-L1 (SP142) assay was used to identify PD-L1 expression on tumor infiltrating immune cells (IC) and also on tumor cells (TC) in primary tumors and LNMets of TNBC by two trained pathologists. PD-L1 scoring and assessment were based on criteria in IMpassion 130 trial criteria. Concordance of PD-L1 expression in TNBC were analyzed using Kappa-test and assessed by the Kappa value.

RESULTS

Prevalence of positive PD-L1 expression (PD-L1 +) on tumor-infiltrating immune cells (PD-L1 IC+) (IC≥1%) in LNMets (49.4%) was higher than in the matched primary tumors (38.9%). Concordance of PD-L1 expression on IC between the two paraffin blocks from the same primary tumor specimen was substantial (P < 0.000, Kappa = 0.627) and was identified in 83.1% (108/130) of the selected cases. For TNBC cases with matched primary and LNMets blocks, the concordance of PD-L1IC scoring between the two blocks was moderate (P < 0.000, Kappa = 0.434). Interobserver agreement of PD-L1 assessment was 78.2% (P < 0.000, Kappa = 0.567) in primary tumors and 61.4% (P < 0.000, Kappa = 0.253) in the matched LNets.

CONCLUSION

Substantial intratumor concordance of PD-L1 scoring of the primary tumors in TNBC patients was determined, implying that immunohistochemically detection using one representative block of the primary tumor should be enough to assign the expression status of PD-L1 in clinical practice. The prevalence of PD-L1 + in lymph node metastases (LNMets) was higher than in the matched primary tumors, implying that PD-L1 detection in LNMets may provide additional PD-L1 expression information, especially in TNBC cases with PD-L1- in the matched primary breast tumors. Interobserver agreement of PD-L1 scoring in primary tumors was moderate while only fair in LNMets, implying that the additional training for PD-L1 assessment of TNBC LNMets specimens is recommended to enhance interobserver agreement.

DATA AVAILABILITY

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

PD-L1-Positive High-Grade Triple-Negative Breast Cancer Patients Respond Better to Standard Neoadjuvant Treatment-A Retrospective Study of PD-L1 Expression in Relation to Different Clinicopathological Parameters

Triple negative breast cancer (TNBC) is typically a high-grade breast cancer with poorest clinical outcome despite available treatment modalities with chemo-, immuno- and radiotherapy. The status of tumor-infiltrating lymphocytes (TILs) is a prognostic factor closely related to programmed death ligand 1 (PD-L1) expressed on T lymphocytes modulating antitumor immunity. Immune-checkpoint inhibitors (ICI) are showing promising results in a subset of breast cancer patients in both neo- and adjuvant settings. Pathologic complete response (pCR) after neoadjuvant treatment was found to be associated with better prognosis. We analyzed the prognostic and predictive significance of PD-L1 (SP142 assay) immunohistochemical expression on TNBC patients' samples as illustrated by pCR with regard to its relation to treatment regimen, stage, BRCA mutational status and outcome. Furthermore, we analyzed a few other clinicopathological parameters such as age, TILs and proliferation index. The study highlighted a positive role of PD-L1 evaluation for personalized pCR probability assessment. Although considerable research was made on comparison of PD-L1 level in TNBC with different patient parameters, to our best knowledge, the relation of PD-L1 status to pCR while taking treatment regimen and stage into consideration was so far not investigated.

Consistent expression of PD-L1 in tumor microenvironment with peripheral PD-1/PD-L1 in circulating T lymphocytes of operable breast cancer: a diagnostic test

Background

The expression of PD-L1 in the immune microenvironment can guide the application of immunosuppressants. In order to monitor the immune status of the body, repeated biopsies have to be taken. Our research aims to find new and convenient means to evaluate this indicator.

Methods

Eighty-three cases of newly diagnosed operable breast cancer without receiving preoperative treatment, were recruited from Beijing Shijitan Hospital between November 2018 and November 2019. The expression of PD-1/PD-L1 on circulating T lymphocytes was detected by flow cytometry and the expression of PD-L1 on immune cells in tumor microenvironment was detected by immunohistochemistry.

Results

The median percentage of positive PD-1 and PD-L1 expression on circulating T lymphocytes was 15.2% and 0.7%, respectively. The peripheral PD-1 had no relationship with clinicopathological characteristics, but the peripheral PD-L1 expression had a correlation with lymph node metastasis (p = 0.005) and Her-2 expression (p = 0.034) (p < 0.05). The positive rate of PD-L1 expression was 32.9% in tumor microenvironment. PD-L1 expression in tumor microenvironment had a significant correlation with PD-1/PD-L1 expression on circulating T lymphocytes, the correlation coefficients being 0.24 (p < 0.05) and 0.26 (p < 0.05), respectively. To predict the PD-L1 expression in tumor microenvironment, the area under the receiver operating characteristic curve was 0.65 and 0.66 for peripheral PD-1 and PD-L1, respectively. High level of peripheral PD-1/PD-L1 expression was associated with the odds ratios of 5.42 and 4.76 for positive PD-L1 expression in tumor microenvironment.

Conclusion

Peripheral PD-1/PD-L1 expression had a significant consistency with PD-L1 expression in tumor microenvironment and could act as an alternative choice of tissue detection, for the patients intolerable of biopsy.

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.

PD-L1 protein expression in relation to recurrence score values in early-stage ER + breast cancer

PURPOSE

We assessed associations between PD-L1 protein expression, RS, tumor grade, and stromal tumor-infiltrating lymphocyte (TIL) count in early-stage ER + cancers.

METHODS

FFPE tissue blocks of 213 patients with RS in 2012-2017 were identified. PD-L1 immunohistochemistry was performed with SP142 assay, cases with ≥ 1% tumor-infiltrating immune cell positivity in the tumor area were considered PD-L1 + . TIL scores were determined following the international TIL counting guidelines. PD-L1 expression positivity rates were compared across RS (< 11, 11-25, > 25) and TIL categories (< 10%, 10-29%, > 30%), and tumor grade using Wilcoxon and Chi-square tests. Multivariate analysis was performed using logistic regression.

RESULTS

PD-L1 and TIL results were available for 201 and 203 patients. Overall, 53% of cases were PD-L1 +. PD-L1 expression was higher among cases with RS > 25, versus RS < 11 (p = 0.00019) and RS 11-25 (p = 0.0017). PD-L1 positivity also correlated with TIL score, tumor grade, and tumor size. Among cancers with TIL > 30%, 92% were PD-L1 + versus 44% PD-L1 + among TIL < 10% (p = 2.8 × 10^-6). Grade 3 cancers had higher PD-L1 positivity (79% PD-L1 +) versus grade 2 (49% PD-L1 +) or 1 tumors (48% PD-L1 +) (p = 0.00047). T2 and T3 tumors had more frequent PD-L1 positivity (67% and 83%, respectively) versus T1 cancers (46%) (p = 0.008). In multivariate analysis, only TIL and RS remained as independent predictors of PD-L1 positivity.

CONCLUSION

PD-L1 expression is significantly more frequent and higher in larger tumors (T2, T3), grade 3 cancers, and in cancers with RS > 25. PD-L1 expression also correlates with TIL score.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer

Differences in the tumor immune microenvironment may result in differences in prognosis and response to treatment in cancer patients. We hypothesized that differences in the tumor immune microenvironment may exist between African American (AA) and NonAA patients, due to ancestry-related or socioeconomic factors, that may partially explain differences in clinical outcomes. We analyzed clinically matched triple-negative breast cancer (TNBC) tissues from self-identified AA and NonAA patients and found that stromal TILs, PD-L1 IHC-positivity, mRNA expression of immune-related pathways, and immunotherapy response predictive signatures were significantly higher in AA samples (p < 0.05; Fisher's Exact Test, Mann-Whitney Test, Permutation Test). Cancer biology and metabolism pathways, TAM-M2, and Immune Exclusion were significantly higher in NonAA samples (p < 0.05; Permutation Test, Mann-Whitney Test). There were no differences in somatic tumor mutation burden. Overall, there is greater immune infiltration and inflammation in AA TNBC and these differences may impact response to immune checkpoint inhibitors and other therapeutic agents that modulate the immune microenvironment.

Development of an immunohistochemical assay for Siglec-15

Siglec-15, a member of sialic-acid binding immunoglobulin type lectins, is normally expressed by myeloid cells and upregulated in some human cancers and represents a promising new target for immunotherapy. While PD-L1 blockade is an important strategy for immunotherapy, its effectiveness is limited. The expression of Siglec-15 has been demonstrated to be predominantly mutually exclusive to PD-L1 in certain cancer histologies. Thus, there is significant opportunity for Siglec-15 as an immunotherapeutic target for patients that do not respond to PD-1/PD-L1 inhibition. The aim of this study was to prospectively develop an immunohistochemical (IHC) assay for Siglec-15 to be used as a companion diagnostic for future clinical trials. Here, we create and validate an IHC assay with a novel recombinant antibody to the cytoplasmic domain of Siglec-15. To find an enriched target, this antibody was first used in a quantitative fluorescence (QIF) assay to screen a broad range of tumor histologies to determine tumor types where Siglec-15 demonstrated high expression. Based on this and previous data, we focused on development of a chromogenic IHC assay for lung cancer. Then we developed a scoring system for this assay that has high concordance amongst pathologist readers. We then use this chromogenic IHC assay to test the expression of Siglec-15 in two cohorts of NSCLC. We found that this assay shows a higher level of staining in both tumor and immune cells compared to previous QIF assays utilizing a polyclonal antibody. However, similar to that study, only a small percentage of positive Siglec-15 cases showed high expression for PD-L1. This validated assay for Siglec-15 expression may support development of a companion diagnostic assay to enrich for patients expressing the Siglec-15 target for therapy.

Significance of the effects of chemotherapy on programmed death-ligand 1 expression in triple-negative breast cancer

BACKGROUND

Atezolizumab has been approved as an antibody against programmed death-ligand 1 (PD-L1)-positive immune cells in patients with advanced or recurrent triple-negative breast cancer. However, the optimal timing to examine PD-L1 expression remains controversial. We retrospectively researched PD-L1 positivity rates in biopsy, surgical and recurrent specimens from patients with triple-negative breast cancer treated with neoadjuvant chemotherapy. We also examined alterations in PD-L1 and their meaning.

METHODS

In total, 35 triple-negative breast cancer biopsy specimens obtained before neoadjuvant chemotherapy, 20 corresponding specimens obtained after neoadjuvant chemotherapy and 5 corresponding recurrent specimens were obtained. We examined PD-L1 immunohistochemistry on tumor cells and tumor-infiltrating immune cells using SP142 antibody.

RESULTS

In comparison with specimens obtained before neoadjuvant chemotherapy, PD-L1 expression randomly changed in immune cells after neoadjuvant chemotherapy, but PD-L1 expression was significantly reduced in tumor cells. Pre-neoadjuvant chemotherapy specimens with low PD-L1 expression (PD-L1 scores of ≤1 for both immune cells and tumor cells) were linked to better disease-free survival (P < 0.001) and overall survival (P < 0.001) than the other specimens.

CONCLUSION

This is the first study to evaluate PD-L1 expression both before and after chemotherapy in breast cancer and examine its relationship with prognosis. The results suggest that the PD-L1 level may be useful for predicting the prognosis of patients with triple-negative breast cancer who do not have pathological complete responses to neoadjuvant chemotherapy.

Update on prognostic and predictive biomarkers of breast cancer

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

Predictive Markers of Response to Neoadjuvant Durvalumab with Nab-Paclitaxel and Dose-Dense Doxorubicin/Cyclophosphamide in Basal-Like Triple-Negative Breast Cancer

PURPOSE

We examined gene expression, germline variant, and somatic mutation features associated with pathologic response to neoadjuvant durvalumab plus chemotherapy in basal-like triple-negative breast cancer (bTNBC).

EXPERIMENTAL DESIGN

Germline and somatic whole-exome DNA and RNA sequencing, programmed death ligand 1 (PD-L1) IHC, and stromal tumor-infiltrating lymphocyte scoring were performed on 57 patients. We validated our results using 162 patients from the GeparNuevo randomized trial.

RESULTS

Gene set enrichment analysis showed that pathways involved in immunity (adaptive, humoral, innate), JAK-STAT signaling, cancer drivers, cell cycle, apoptosis, and DNA repair were enriched in cases with pathologic complete response (pCR), whereas epithelial-mesenchymal transition, extracellular matrix, and TGFβ pathways were enriched in cases with residual disease (RD). Immune-rich bTNBC with RD was enriched in CCL-3, -4, -5, -8, -23, CXCL-1, -3, -6, -10, and IL1, -23, -27, -34, and had higher expression of macrophage markers compared with immune-rich cancers with pCR that were enriched in IFNγ, IL2, -12, -21, chemokines CXCL-9, -13, CXCR5, and activated T- and B-cell markers (GZMB, CD79A). In the validation cohort, an immune-rich five-gene signature showed higher expression in pCR cases in the durvalumab arm (P = 0.040) but not in the placebo arm (P = 0.923) or in immune-poor cancers. Independent of immune markers, tumor mutation burden was higher, and PI3K, DNA damage repair, MAPK, and WNT/β-catenin signaling pathways were enriched in germline and somatic mutations in cases with pCR.

CONCLUSIONS

The TGFβ pathway is associated with immune-poor phenotype and RD in bTNBC. Among immune-rich bTNBC RD, macrophage/neutrophil chemoattractants dominate the cytokine milieu, and IFNγ and activated B cells and T cells dominate immune-rich cancers with pCR.

Protein Profiling of Breast Cancer for Treatment Decision-Making

The increasing use of neoadjuvant therapy has resulted in therapeutic decisions being made on the basis of diagnostic needle core biopsy. For many patients, this method might yield the only fragment of tumor available for biomarker analysis, necessitating judicious use. Many multiplex protein analytic methods have been developed that employ fluorescence or other tags to overcome the limitations of immunohistochemistry while still retaining the spatial annotation. Interpretation of the data can be difficult because of the limitations of the human eye. Computational deconvolution of the signals may be necessary for some of these methods to enable identification of cell-specific localization and coexpression of biomarkers. Herein, we present the different methods that are coming of age and their application in cancer research, with a focus on breast cancer. We also discuss the limitations, which include high costs and long turnaround times. The methods are also based on the premise that preanalytical factors will have identical impact on all proteins analyzed. There is a need to establish standards to normalize the data and enable cross-sample comparisons. In spite of these limitations, the multiplex technologies are extremely valuable discovery tools and can provide novel insights into the biology of cancer and mechanisms of drug resistance.

Immune Checkpoint Blockades in Triple-Negative Breast Cancer: Current State and Molecular Mechanisms of Resistance

Immune checkpoint blockades (ICBs) have revolutionized cancer treatment. Recent studies have revealed a subset of triple-negative breast cancer (TNBC) to be considered as an immunogenic breast cancer subtype. Characteristics of TNBC, such as higher mutation rates and number of tumor-infiltrating immune cells, render the immunogenic phenotypes. Consequently, TNBCs have shown durable responses to ICBs such as atezolizumab and pembrolizumab in clinic. However, a significant number of TNBC patients do not benefit from these therapies, and mechanisms of resistance are poorly understood. Here, we review biomarkers that predict the responsiveness of TNBCs to ICB and recent advances in delineating molecular mechanisms of resistance to ICBs.

Characterization of Pyroptosis-Related Subtypes via RNA-Seq and ScRNA-Seq to Predict Chemo-Immunotherapy Response in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. There is an urgent need to screen for reliable indices, especially immunotherapy-associated biomarkers that can predict patient outcomes. Pyroptosis, as an inflammation-induced type of programmed cell death, is shown to create a tumor-suppressive environment and improve the chemotherapeutic response in multiple tumors. However, the specific therapeutic effect of pyroptosis in TNBC remains unclear. In this study, we present a consensus clustering by pyroptosis-related signatures of 119 patients with TNBC into two subtypes (clusterA and clusterB) with distinct immunological and prognostic characteristics. First, clusterB, associated with better outcomes, was characterized by a significantly higher pyroptosis-related signature expression, tumor microenvironment prognostic score, and upregulation of immunotherapy checkpoints. A total of 262 differentially expressed genes between the subtypes were further identified and the Ps-score was built using LASSO and COX regression analyses. The external GEO data set demonstrated that cohorts with low Ps-scores consistently had higher expression of pyroptosis-related signatures, immunocyte infiltration levels, and better prognosis. In addition, external immunotherapy and chemotherapy cohorts validated that patients with lower Ps-scores exhibited significant therapeutic response and clinical benefit. Combined with other clinical characteristics, we successfully constructed a nomogram to effectively predict the survival rate of patients with TNBC. Finally, using the scRNA-seq data sets, we validated the landscape of cellular subtypes of TNBC and successfully constructed an miRNA-Ps-score gene interaction network. These findings indicated that the systematic assessment of tumor pyroptosis and identification of Ps-scores has potential clinical implications and facilitates tailoring optimal immunotherapeutic strategies for TNBC.

Heterogeneity derived from 18 F-FDG PET/CT predicts immunotherapy outcome for metastatic triple-negative breast cancer patients

Background

Recently, immunotherapy has been used to treat metastatic triple‐negative breast cancer (mTNBC). Basic research has indicated a relation between tumor heterogeneity and the immune response. Tumor heterogeneity derived from ¹⁸F‐FDG PET/CT is a potential predictor of chemotherapy results; however, few studies have focused on immunotherapy. This study aims to develop a convenient and efficient measurement of tumor heterogeneity for the prediction of immunotherapy in mTNBC patients.

Methods

We enrolled mTNBC patients who received immunotherapy (PD‐1/PD‐L1 antibody) plus chemotherapy as first‐line treatment and underwent ¹⁸F‐FDG PET/CT scans before treatment. We defined a novel index representing tumor heterogeneity calculated from the standard uptake value (SUV) as IATH and IETH. Optimal cutoffs were determined using time‐dependent receiver operator characteristics (ROC) analysis.

Results

A total of 32 patients were enrolled and analyzed in this trial. A significantly longer median PFS was observed in the low SUVmax group than in the high SUVmax group (9.4 vs. 5.8 months, HR = 0.3, 95% CI 0.1–0.9, p = 0.025). The median PFS of low‐IATH patients was significantly longer than that of high‐IATH patients (HR = 0.3, 95% CI 0.1–0.8, p = 0.022). Similarly, patients with low IETH had significantly longer PFS than patients with high IETH (9.4 vs. 4.9 months, HR = 0.3, 95% CI 0.1–0.7, p = 0.01). Multivariate analysis demonstrated IETH as an independent predictor of PFS.

Conclusions

This study proposed a novel method to assess intratumor and intertumor heterogeneity among metastatic breast cancer patients and determined that baseline IETH derived from ¹⁸F‐FDG PET/CT could represent a simple and promising predictor for first‐line immunotherapy among mTNBC patients.

Incorporation of TILs in daily breast cancer care: how much evidence can we bear?

One of the most important developments in the breast cancer field has been an improved understanding of prognostic and predictive biomarkers, of which TILs are increasingly gaining importance. The evaluation of TILs by light microscopy on a H&E-stained section is workable in a daily practice setting. Reproducibility of reporting TILs is good, but heterogeneity is a cause of variation. TILs provide clinicians with important prognostic information for patients with TNBC, as early-stage TNBC with high TILs have > 98% 5-year survival and TILs predict benefit to immunotherapy. Importantly, while TILs do not have level of evidence IA, TILs should be used as a prognostic factor with caution and with other accepted prognostic variables, such as tumour size and lymph node status, to inform clinicians and patients on their treatment options. A framework on how to use the TILs in daily practice is proposed, including a co-assessment with PD-L1 for its predictive role to immunotherapy.