Results of a worldwide survey on the currently used histopathological diagnostic criteria for invasive lobular breast cancer.

Invasive lobular carcinoma (ILC) represents the second most common subtype of breast cancer (BC), accounting for up to 15% of all invasive BC. Loss of cell adhesion due to functional inactivation of E-cadherin is the hallmark of ILC. Although the current world health organization (WHO) classification for diagnosing ILC requires the recognition of the dispersed or linear non-cohesive growth pattern, it is not mandatory to demonstrate E-cadherin loss by immunohistochemistry (IHC). Recent results of central pathology review of two large randomized clinical trials have demonstrated relative overdiagnosis of ILC, as only ~60% of the locally diagnosed ILCs were confirmed by central pathology. To understand the possible underlying reasons of this discrepancy, we undertook a worldwide survey on the current practice of diagnosing BC as ILC. A survey was drafted by a panel of pathologists and researchers from the European lobular breast cancer consortium (ELBCC) using the online tool SurveyMonkey®. Various parameters such as indications for IHC staining, IHC clones, and IHC staining procedures were questioned. Finally, systematic reporting of non-classical ILC variants were also interrogated. This survey was sent out to pathologists worldwide and circulated from December 14, 2020 until July, 1 2021. The results demonstrate that approximately half of the institutions use E-cadherin expression loss by IHC as an ancillary test to diagnose ILC and that there is a great variability in immunostaining protocols. This might cause different staining results and discordant interpretations. As ILC-specific therapeutic and diagnostic avenues are currently explored in the context of clinical trials, it is of importance to improve standardization of histopathologic diagnosis of ILC diagnosis.

Harmonization of programmed death-ligand 1 immunohistochemistry and mRNA expression scoring in metastatic melanoma: a multicentre analysis.

AIMS: The aim of this multicentre study was to harmonize programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) and melanoma scoring. To provide a reference for PD-L1 expression independently of the IHC protocol, PD-L1 mRNA expression was compared with IHC. METHODS AND RESULTS: Standardized PD-L1 assays (22C3, 28-8, SP142, SP263) and laboratory-developed tests (QR1, 22C3) were evaluated on three IHC platforms with a training set (seven cases). mRNA expression was determined by RNAscope (CD274/PD-L1 probe) and analysed with image analysis. PD-L1 IHC findings were scored by seven blinded pathologists using the tumour proportion score (TPS), the combined positive score (CPS), and the MELscore. This method was validated by three blinded pathologists on 40 metastatic melanomas. Concordances among various antibody/platforms were high across antibodies [intraclass correlation coefficient (ICC) >0.80 for the CPS], except for SP142. Two levels of immunostaining intensity were observed: high (QR1 and SP263) and low (28-8, 22C3, and SP142). Reproducibilities across pathologists were higher for QR1 and SP263 (ICC ≥0.87 and ICC ≥0.85 for the TPS and the CPS, respectively). QR1, SP263 and 28-8 showed the highest concordance with mRNA expression. We developed a standardized method for PD-L1 immunodetection and scoring, tested on 40 metastatic melanomas. Concordances among antibodies were excellent for all criteria, and concordances among pathologists were better for the MELscore than for other scores. CONCLUSION: Harmonization of PD-L1 staining and scoring in melanomas with good concordance is achievable with the PD-L1 IHC protocols applied to other cancers; this reproducible approach can simplify daily practice.

Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training-The Case of Cancer Detection.

The class distribution of a training dataset is an important factor which influences the performance of a deep learning-based system. Understanding the optimal class distribution is therefore crucial when building a new training set which may be costly to annotate. This is the case for histological images used in cancer diagnosis where image annotation requires domain experts. In this paper, we tackle the problem of finding the optimal class distribution of a training set to be able to train an optimal model that detects cancer in histological images. We formulate several hypotheses which are then tested in scores of experiments with hundreds of trials. The experiments have been designed to account for both segmentation and classification frameworks with various class distributions in the training set, such as natural, balanced, over-represented cancer, and over-represented non-cancer. In the case of cancer detection, the experiments show several important results: (a) the natural class distribution produces more accurate results than the artificially generated balanced distribution; (b) the over-representation of non-cancer/negative classes (healthy tissue and/or background classes) compared to cancer/positive classes reduces the number of samples which are falsely predicted as cancer (false positive); (c) the least expensive to annotate non-ROI (non-region-of-interest) data can be useful in compensating for the performance loss in the system due to a shortage of expensive to annotate ROI data; (d) the multi-label examples are more useful than the single-label ones to train a segmentation model; and (e) when the classification model is tuned with a balanced validation set, it is less affected than the segmentation model by the class distribution of the training set.

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

BACKGROUND: The immune microenvironment (IME) of triple-negative breast cancers (TNBCs) and its modulation by neoadjuvant chemotherapy (NACT) remain to be fully characterized. Our current study aims to evaluate NACT-induced IME changes and assess the prognostic value of specific immune biomarkers. METHODS: Tumor-infiltrating lymphocytes (TILs) were identified from hematoxylin-eosin-stained sections of paired pre- and post-NACT tumor samples from a TNBC cohort (n = 66) and expression of PD-L1, TIM-3, and LAG-3 evaluated by immunohistochemistry. RESULTS: Overall TIL counts and PD-L1 expression did not differ pre- and post-NACT, but there was a response-specific statistically significant difference. TIL counts decreased in 65.5% of patients who achieved a pathological complete response (pCR) and increased in 56.8% of no-pCR patients (p = 0.0092). PD-L1 expression was significantly more frequently lost after NACT in pCR than in no-pCR patients (41.4% vs 16.2%, p = 0.0020). TIM-3 positivity (≥ 1%) was significantly more frequent after NACT (p < 0.0001) with increases in expression levels occurring more frequently in no-pCR than in pCR patients (51.4% vs 31%). LAG-3 expression significantly decreased after NACT, but there was no difference between response groups. Before NACT, a high TIL count (> 10%) was significantly associated with better overall survival (OS), p = 0.0112. After NACT, PD-L1 positivity and strong TIM-3 positivity (≥ 5%) were both associated with significantly worse OS (p = 0.0055 and p = 0.0274, respectively). Patients positive for both PD-L1 and TIM-3 had the worst prognosis (p = 0.0020), even when only considering patients who failed to achieve a pCR, p = 0.0479. CONCLUSIONS: NACT induces significant IME changes in TNBCs. PD-L1 and TIM-3 expression post-NACT may yield important prognostic information for TNBC patients.

Translesion Synthesis or Repair by Specialized DNA Polymerases Limits Excessive Genomic Instability upon Replication Stress.

DNA can experience "replication stress", an important source of genome instability, induced by various external or endogenous impediments that slow down or stall DNA synthesis. While genome instability is largely documented to favor both tumor formation and heterogeneity, as well as drug resistance, conversely, excessive instability appears to suppress tumorigenesis and is associated with improved prognosis. These findings support the view that karyotypic diversity, necessary to adapt to selective pressures, may be limited in tumors so as to reduce the risk of excessive instability. This review aims to highlight the contribution of specialized DNA polymerases in limiting extreme genetic instability by allowing DNA replication to occur even in the presence of DNA damage, to either avoid broken forks or favor their repair after collapse. These mechanisms and their key regulators Rad18 and Polθ not only offer diversity and evolutionary advantage by increasing mutagenic events, but also provide cancer cells with a way to escape anti-cancer therapies that target replication forks.

[2021 update of the GEFPICS' recommendations for HER2 status assessment in invasive breast cancer in France]. / Mise à jour 2021 des recommandations du GEFPICS pour l'évaluation du statut HER2 dans les cancers infiltrants du sein en France.

The last international guidelines on HER2 determination in breast cancer have been updated in 2018 by the American Society of Clinical Oncology and College of American Pathologists, on the basis of a twenty-year practice and results of numerous clinical trials. Moreover, the emerging HER2-low concept for 1+ and 2+ non amplified breast cancers lead to refine French practices for HER2 status assessment. The GEFPICS group, composed of expert pathologists, herein presents the latest French recommendations for HER2 status evaluation in breast cancer, taking into account the ASCO/CAP guidelines and introducing the HER2-low concept. In the era of personalized medicine, HER2 status assessment remains one of the most important biomarkers in breast cancer and its quality guaranties the optimal patients' care. French pathologists' commitment in theranostic biomarker quality is more than ever required to provide the most efficient cares in oncology.

Exclusive B-cell phenotype of primary prostatic lymphomas: a potential role of chronic prostatitis.

AIMS: Primary prostatic lymphomas (PPL) is exceedingly rare. The aim of this study was to investigate the largest series of PPL obtained from a nationwide expert pathologist network, and thus try to understand the pathophysiology of these tumours. METHODS AND RESULTS: Up to 66 000 lymphoma cases have been collected and submitted for central expert review by the French Lymphopath network. We confirm the low frequency of PPL (n = 77; 0.12%), all cases being of B-cell origin. Diffuse large B-cell lymphoma and small lymphocytic lymphoma were the most frequent subtypes, comprising 31% and 26% of cases respectively, followed by mucosa-associated lymphoid tissue (MALT)/lymphoplasmacytic lymphoma (19%), follicular lymphoma (12%), mantle cell lymphoma (6%), Burkitt lymphoma (4%), and unclassified lymphoma (1%). Clinical data obtained in 25 cases suggests that PPLs are rather indolent tumours. Our hypothesis for B-cell recruitment in the prostatic tissue was derived from the observation in chronic inflammation (prostatitis) of frequent heterotopic proliferation of high endothelial venules (HEVs). The latter are dedicated to lymphocyte entry into secondary lymphoid organs, here putatively driving circulating clonal B-lymphocytes from the blood into the inflamed prostate. This may account for the relatively high incidence of small lymphocytic lymphoma consistently reported in series of primary or secondary prostatic lymphoma. As in other organs or glands, chronic inflammation may promote antigen-dependent intraprostatic MALT lymphoma and diffuse large B-cell lymphoma development. CONCLUSIONS: PPLs are exclusively of B-cell origin, and chronic inflammation resulting from the proliferation of high endothelial venules could play some role in their development.

Bifascicular nature of the flexor digitorum profundus and flexor pollicis longus tendons: forgotten anatomical characteristics rediscovered with US imaging.

OBJECTIVES: To demonstrate the bifid configuration of the flexor digitorum profundus (FDP) and flexor pollicis longus (FPL). METHODS: In the first part of this study, 20 digits from 4 cadaver hands were dissected and analyzed using anatomical and histological slices. The second part of the study was carried out over a 12-month period starting in August 2018. It was a prospective US imaging study of 300 digits from 30 healthy participants performed by two radiologists in a double-blinded manner. This study focused on two items: tendon shape and whether a central septum separated the two hemitendons. Descriptive statistics were calculated along with the inter-rater reliability. RESULTS: In 100% (300/300) of fingers and thumbs, the FDP and FPL tendons were made up of two parallel bundles arranged side by side, with a central vertical septum between these two hemitendons, starting at the head of the proximal phalanx (PP) and continuing distally. This central septum was always present starting at the proximal third of PP for the FDP of the index, middle, and ring fingers. The septum was more difficult to identify in the thumb and little finger. Cohen's kappa indicated near perfect agreement when all digits were considered together (≥ 0.9), and substantial agreement for the thumb (0.71) and for the little finger (0.82). CONCLUSIONS: With US imaging, the bifascicular nature of the FDP and FPL tendons is easy to see, as these tendons have a double-barreled configuration starting at the head of the proximal phalanx. KEY POINTS: •Analysis of anatomical slices of the hand tendons found a bifascicular appearance of the flexor digitorum profundus and flexor pollicis longus tendons starting at the head of the proximal phalanx. •This distinct feature of two hemitendons arranged side by side was seen in 100% of tendons we examined with US. It is associated with a vertical central septum that causes anisotropy. •Awareness of this "forgotten" anatomical detail has practical implications when interpreting images generated by latest-generation US systems and during surgery on hand flexor tendons.

Identification of a tumor-promoter cholesterol metabolite in human breast cancers acting through the glucocorticoid receptor.

Breast cancer (BC) remains the primary cause of death from cancer among women worldwide. Cholesterol-5,6-epoxide (5,6-EC) metabolism is deregulated in BC but the molecular origin of this is unknown. Here, we have identified an oncometabolism downstream of 5,6-EC that promotes BC progression independently of estrogen receptor α expression. We show that cholesterol epoxide hydrolase (ChEH) metabolizes 5,6-EC into cholestane-3ß,5α,6ß-triol, which is transformed into the oncometabolite 6-oxo-cholestan-3ß,5α-diol (OCDO) by 11ß-hydroxysteroid-dehydrogenase-type-2 (11ßHSD2). 11ßHSD2 is known to regulate glucocorticoid metabolism by converting active cortisol into inactive cortisone. ChEH inhibition and 11ßHSD2 silencing inhibited OCDO production and tumor growth. Patient BC samples showed significant increased OCDO levels and greater ChEH and 11ßHSD2 protein expression compared with normal tissues. The analysis of several human BC mRNA databases indicated that 11ßHSD2 and ChEH overexpression correlated with a higher risk of patient death, highlighting that the biosynthetic pathway producing OCDO is of major importance to BC pathology. OCDO stimulates BC cell growth by binding to the glucocorticoid receptor (GR), the nuclear receptor of endogenous cortisol. Interestingly, high GR expression or activation correlates with poor therapeutic response or prognosis in many solid tumors, including BC. Targeting the enzymes involved in cholesterol epoxide and glucocorticoid metabolism or GR may be novel strategies to prevent and treat BC.

Adipocytes promote breast cancer resistance to chemotherapy, a process amplified by obesity: role of the major vault protein (MVP).

INTRODUCTION: Clinical studies suggest that obesity, in addition to promoting breast cancer aggressiveness, is associated with a decrease in chemotherapy efficacy, although the mechanisms involved remain elusive. As chemotherapy is one of the main treatments for aggressive or metastatic breast cancer, we investigated whether adipocytes can mediate resistance to doxorubicin (DOX), one of the main drugs used to treat breast cancer, and the mechanisms associated. METHODS: We used a coculture system to grow breast cancer cells with in vitro differentiated adipocytes as well as primary mammary adipocytes isolated from lean and obese patients. Drug cellular accumulation, distribution, and efflux were studied by immunofluorescence, flow cytometry, and analysis of extracellular vesicles. Results were validated by immunohistochemistry in a series of lean and obese patients with cancer. RESULTS: Adipocytes differentiated in vitro promote DOX resistance (with cross-resistance to paclitaxel and 5-fluorouracil) in a large panel of human and murine breast cancer cell lines independently of their subtype. Subcellular distribution of DOX was altered in cocultivated cells with decreased nuclear accumulation of the drug associated with a localized accumulation in cytoplasmic vesicles, which then are expelled into the extracellular medium. The transport-associated major vault protein (MVP), whose expression was upregulated by adipocytes, mediated both processes. Coculture with human mammary adipocytes also induced chemoresistance in breast cancer cells (as well as the related MVP-induced DOX efflux) and their effect was amplified by obesity. Finally, in a series of human breast tumors, we observed a gradient of MVP expression, which was higher at the invasive front, where tumor cells are at close proximity to adipocytes, than in the tumor center, highlighting the clinical relevance of our results. High expression of MVP in these tumor cells is of particular interest since they are more likely to disseminate to give rise to chemoresistant metastases. CONCLUSIONS: Collectively, our study shows that adipocytes induce an MVP-related multidrug-resistant phenotype in breast cancer cells, which could contribute to obesity-related chemoresistance.

[GEFPICS' guidelines for management of breast cancer tissue samples in the neoadjuvant setting]. / Recommandations du GEFPICS pour la prise en charge des prélèvements dans le cadre du traitement néoadjuvant du cancer du sein.

Neoadjuvant therapy is an increasing treatment option in the management of breast cancer. The tumor response to neoadjuvant therapy, especially the pathological complete response, is a validated endpoint frequently used in clinical trials. However, there is still a lack of standardization for the surgical specimen management in the neoadjuvant setting. This leads to heterogeneity in the specimen handling and might lead to significant bias for the prognostic assessment of patients or in clinical trials. The GEFPICS group, composed of expert breast cancer pathologists, herein presents guidelines for the management of breast and axillary specimen before treatment (management of biopsy, items of the pathological report) and after neoadjuvant therapy (specimen handling, histological assessment of response, items of the pathological report and response grading systems).

[Sudden death of a young man as late sequelae complicating a pediatric disease: About a case]. / Mort subite d'un homme jeune dans le cadre de séquelles tardives d'une pathologie pédiatrique : à propos d'un cas.

In France, sudden death is responsible every year for 40,000 deaths. The most frequent etiology is cardiac disease. Atheromatous-related pathology is the most common etiology beyond 35, but cardiomyopathies and channelopathies are responsible for a significant number of deaths in young adults. Some acquired disorders can also cause sudden cardiac death. We report the case of a 17-year-old man who died suddenly after sport. Autopsy and pathological study found multiple giant coronary aneurysms. Thrombosis and fibrous scar of myocardial ischemic events were observed. These lesions were in favor of late sequelae of Kawasaki disease. Kawasaki disease is a rare but not exceptional cause of sudden cardiac death in young adults. In the lack of known clinical history, some aspects, even not specific, should evoke this diagnosis. Even in front of apparent good clinical tolerance, these sequelae require appropriate follow-up because of a significant risk of sudden death.

Instant-quality fluorescence in-situ hybridization as a new tool for HER2 testing in breast cancer: a comparative study.

AIMS: HER2 instant-quality fluorescence in-situ hybridization (IQFISH) is a new fluorescence in-situ hybridization (FISH) assay developed with a non-toxic buffer that reduces the hybridization time to 1-2 h, enabling a turnaround time of 3 h 30 min from dewax to counting. The aim of this study was to compare assessment of HER2 status using IQFISH and assessment using standard FISH. METHODS AND RESULTS: We selected 160 breast cancer samples according to their HER2 status as determined by immunohistochemistry (IHC) in a retrospective multicentre cohort (40 cases in each scoring category, i.e. 0/1+/2+/3+). Each participating site (n = 5) constructed its tissue microarray (TMA) of 32 archival cases and sent it to the central site (site 1). HER2 IHC, HER2 FISH and HER2 IQFISH were performed blindly at site 1. IQFISH provided excellent quality signals without any background staining, thus allowing excellent reading conditions even on TMA. Statistical analysis showed almost perfect agreement between IQFISH and FISH (99.3%, κ = 0.98). The only discordant case was an equivocal one with an HER2/CEP17 ratio near the ASCO/CAP cut-off. CONCLUSIONS: The highly concordant data support IQFISH as a useful alternative to FISH, allowing reliable assessment of HER2 status. Use of this method could lead to reporting of HER status to the oncologist within a day.

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images.

Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus weakening pathologists' trust in these tools. Technically, it is well known that microscopic images are altered by tissue processing and staining procedures, being one of the main sources of bias in machine learning for digital pathology. So as to deal with it, many teams have written about color normalization and augmentation methods. However, only a few of them have monitored their effects on bias reduction and model generalizability. In our study, two methods for stain augmentation (AugmentHE) and fast normalization (HEnorm) have been created and their effect on bias reduction has been monitored. Actually, they have also been compared to previously described strategies. To that end, a multicenter dataset created for breast cancer histological grading has been used. Thanks to it, classification models have been trained in a single center before assessing its performance in other centers images. This setting led to extensively monitor bias reduction while providing accurate insight of both augmentation and normalization methods. AugmentHE provided an 81% increase in color dispersion compared to geometric augmentations only. In addition, every classification model that involved AugmentHE presented a significant increase in the area under receiving operator characteristic curve (AUC) over the widely used RGB shift. More precisely, AugmentHE-based models showed at least 0.14 AUC increase over RGB shift-based models. Regarding normalization, HEnorm appeared to be up to 78x faster than conventional methods. It also provided satisfying results in terms of bias reduction. Altogether, our pipeline composed of AugmentHE and HEnorm improved AUC on biased data by up to 21.7% compared to usual augmentations. Conventional normalization methods coupled with AugmentHE yielded similar results while being much slower. In conclusion, we have validated an open-source tool that can be used in any deep learning-based digital pathology project on H&E whole slide images (WSI) that efficiently reduces stain-induced bias and later on might help increase pathologists' confidence when using AI-based products.

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic potential and poor prognosis, and has limited treatment options. The current standard of care in nonmetastatic settings is neoadjuvant chemotherapy (NACT), but treatment efficacy varies substantially across patients. This heterogeneity is still poorly understood, partly due to the paucity of curated TNBC data. Here we investigate the use of machine learning (ML) leveraging whole-slide images and clinical information to predict, at diagnosis, the histological response to NACT for early TNBC women patients. To overcome the biases of small-scale studies while respecting data privacy, we conducted a multicentric TNBC study using federated learning, in which patient data remain secured behind hospitals' firewalls. We show that local ML models relying on whole-slide images can predict response to NACT but that collaborative training of ML models further improves performance, on par with the best current approaches in which ML models are trained using time-consuming expert annotations. Our ML model is interpretable and is sensitive to specific histological patterns. This proof of concept study, in which federated learning is applied to real-world datasets, paves the way for future biomarker discovery using unprecedentedly large datasets.

PKCθ-mediated serine/threonine phosphorylations of FAK govern adhesion and protrusion dynamics within the lamellipodia of migrating breast cancer cells.

The cytoskeleton and cell-matrix adhesions constitute a dynamic network that controls cellular behavior during development and cancer. The Focal Adhesion Kinase (FAK) is a central actor of these cell dynamics, promoting cell-matrix adhesion turnover and active membrane fluctuations. However, the initial steps leading to FAK activation and subsequent promotion of cell dynamics remain elusive. Here, we report that the serine/threonine kinase PKCθ participates in the initial steps of FAK activation. PKCθ, which is strongly expressed in aggressive human breast cancers, controls the dynamics of cell-matrix adhesions and active protrusions through direct FAK activation, thereby promoting cell invasion and lung metastases. Using various tools for in vitro and live cell studies, we precisely decipher the molecular mechanisms of FAK activation. PKCθ directly interacts with the FAK FERM domain to open FAK conformation through PKCθ's specific V3 domain, while phosphorylating FAK at newly identified serine/threonine residues within nascent adhesions, inducing cell dynamics and aggressive behavior. This study thus places PKCθ-directed FAK opening and phosphorylations as an original mechanism controlling dynamic, migratory, and invasive abilities of aggressive breast cancer cells, further strengthening the emerging oncogenic function of PKCθ.

Recent Advances in Enhancing the Therapeutic Index of PARP Inhibitors in Breast Cancer.

As poly-(ADP)-ribose polymerase (PARP) inhibition is synthetic lethal with the deficiency of DNA double-strand (DSB) break repair by homologous recombination (HR), PARP inhibitors (PARPi) are currently used to treat breast cancers with mutated BRCA1/2 HR factors. Unfortunately, the increasingly high rate of PARPi resistance in clinical practice has dented initial hopes. Multiple resistance mechanisms and acquired vulnerabilities revealed in vitro might explain this setback. We describe the mechanisms and vulnerabilities involved, including newly identified modes of regulation of DSB repair that are now being tested in large cohorts of patients and discuss how they could lead to novel treatment strategies to improve the therapeutic index of PARPi.