Characterization and spatial distribution of infiltrating lymphocytes in medullary, and lymphocyte-predominant triple negative breast cancers.

Medullary carcinoma of the breast (MedBC) is a rare histological type that accounts for less than 5% of all invasive breast cancers. Here, we performed an exploratory study aimed to determine whether imaging mass cytometry (IMC) can be used to characterize the immune infiltration and the spatial distribution heterogeneity in the rare subtype of MedBC compared to atypical MedBC and TNBC-TILS tumors. In both MedBC and TNBC-TILs, there was a notable enrichment of immune cells in the peripheral regions of the tumors, whereas in atypical MedBC, the immune cells exhibited a central enrichment pattern.

Copy number alterations in metastatic and early breast tumours: prognostic and acquired biomarkers of resistance to CDK4/6 inhibitors.

Background: Copy number alterations (CNA) are acquired during the evolution of cancers from their early stage to metastatic stage. This study aims at analysing the clinical value of the identified metastasis-associated CNAs both in metastatic breast cancers (mBCs) and early breast cancers (eBCs).

Methods: Single-nucleotide polymorphism (SNP)-array was performed on 926 biopsies from mBC patients, enrolled in SAFIR02-BREAST prospective trial.

Development of a deep-learning model tailored for HER2 detection in breast cancer to aid pathologists in interpreting HER2-low cases.

Aims: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti-HER2 antibody-drug conjugates (ADCs) for treating HER2-low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2-low breast cancer. In this study we evaluated the performance of a deep-learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2-Null between a pathologist and the DL model.

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer.

New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer.

Association between endocrine adjuvant therapy intake timing and disease-free survival in patients with high-risk early breast cancer: results of a sub-study of the UCBG- UNIRAD trial.

Background: Circadian rhythms regulate cellular physiology and could influence the efficacy of endocrine therapy (ET) in breast cancer (BC). We prospectively tested this hypothesis within the UNIRAD adjuvant phase III trial (NCT01805271).

Methods: 1278 patients with high-risk hormonal receptor positive (HR+)/HER2 negative (HER2-) primary BC were randomly assigned to adjuvant ET with placebo or everolimus.

Prognostic value of EndoPredict test in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative primary breast cancer screened for the randomized, double-blind, phase III UNIRAD trial.

Background: The purpose of this study was to evaluate the prognostic value of the multigene EndoPredict test in prospectively collected data of patients screened for the randomized, double-blind, phase III UNIRAD trial, which evaluated the addition of everolimus to adjuvant endocrine therapy in high-risk, hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer.

Patients And Methods: Patients were classified into low or high risk according to the EPclin score, consisting of a 12-gene molecular score combined with tumor size and nodal status. Association of the EPclin score with disease-free survival (DFS) and distant metastasis-free survival (DMFS) was evaluated using Kaplan-Meier estimates.

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.

Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial.

The mechanisms of action of and resistance to trastuzumab deruxtecan (T-DXd), an anti-HER2-drug conjugate for breast cancer treatment, remain unclear. The phase 2 DAISY trial evaluated the efficacy of T-DXd in patients with HER2-overexpressing (n = 72, cohort 1), HER2-low (n = 74, cohort 2) and HER2 non-expressing (n = 40, cohort 3) metastatic breast cancer. In the full analysis set population (n = 177), the confirmed objective response rate (primary endpoint) was 70.

Pattern and risk factors of isolated local relapse among women with hormone receptor-positive and HER2-negative breast cancer and lymph node involvement: 10-year follow-up analysis of the PACS 01 and PACS 04 trials.

Purpose: We aimed to determine the pattern of isolated local recurrences (ILR) in women with stage II-III hormone receptor-positive and human epidermal growth factor receptor 2 breast cancer (HR + /HER2-BC) after 10-year follow-up.

Methods: UNICANCER-PACS 01 and PACS 04 trials included 5,008 women with T1-T3 and N1-N3 to evaluate the efficacy of different anthracycline ± taxanes-containing regimens after modified mastectomy or lumpectomy plus axillary lymph node dissection. We analyzed the data from 2,932 women with HR + /HER2- BC to evaluate the cumulative incidence of ILR and describe the factors associated with ILR.

Uncommon invasive lobular carcinoma with papillary architecture-clinicopathologic and molecular characterization with review of the literature.

Breast cancer is the most common malignancy in woman, and its associated mortality is still rising worldwide. Among all the different subtypes of breast cancer, invasive lobular carcinoma (ILC) is the second most frequent. Several histological variants of ILC currently exist such as solid, alveolar, pleomorphic, tubulo-lobular, and mixed types.

Comparative Genomic Profiling of Second Breast Cancers following First Ipsilateral Hormone Receptor-Positive Breast Cancers.

Purpose: We compared the mutational profile of second breast cancers (SBC) following first ipislateral hormone receptor-positive breast cancers of patient-matched tumors to distinguish new primaries from true recurrences.

Experimental Design: Targeted next-generation sequencing using the Oncomine Tumor Mutation Load Assay. Variants were filtered according to their allele frequency ≥ 5%, read count ≥ 5X, and genomic effect and annotation.

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.

Tissue Selection for PD-L1 Testing in Triple Negative Breast Cancer (TNBC).

Atezolizumab in combination with nab-paclitaxel has been introduced for the treatment of locally advanced or recurrent triple negative breast cancer (TNBC). Patient selection relies on the use of immunohistochemistry using a specific monoclonal PD-L1 antibody (clone SP142) in a tightly controlled companion diagnostic test (CDx) with a defined interpretative algorithm. Currently there are no standardized recommendations for selecting the optimal tissue to be tested and there is limited data to support decision making, raising the possibility that tissue selection may bias test results.

Tumor infiltrating lymphocyte stratification of prognostic staging of early-stage triple negative breast cancer.

The importance of integrating biomarkers into the TNM staging has been emphasized in the 8 Edition of the American Joint Committee on Cancer (AJCC) Staging system. In a pooled analysis of 2148 TNBC-patients in the adjuvant setting, TILs are found to strongly up and downstage traditional pathological-staging in the Pathological and Clinical Prognostic Stage Groups from the AJJC 8 edition Cancer Staging System. This suggest that clinical and research studies on TNBC should take TILs into account in addition to stage, as for example patients with stage II TNBC and high TILs have a better outcome than patients with stage I and low TILs.

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HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negative categories is well implemented and reproducible, the introduction of a new "HER2-low" category could raise some concerns about its scoring and reproducibility.

[2021 update of the GEFPICS' recommendations for HER2 status assessment in invasive breast cancer in 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.

Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study.

High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR.

Evolution of overall survival and receipt of new therapies by subtype among 20 446 metastatic breast cancer patients in the 2008-2017 ESME cohort.

Background: Treatment strategies for metastatic breast cancer (MBC) have made great strides over the past 10 years. Real-world data allow us to evaluate the actual benefit of new treatments. ESME (Epidemio-Strategy-Medico-Economical)-MBC, a nationwide observational cohort (NCT03275311), gathers data of all consecutive MBC patients who initiated their treatment in 18 French Cancer Centres since 2008.

Phenotypic discordance between primary and metastatic breast cancer in the large-scale real-life multicenter French ESME cohort.

Expression of hormone receptor (HR) for estrogens (ER) and progesterone (PR) and HER2 remains the cornerstone to define the therapeutic strategy for breast cancer patients. We aimed to compare phenotypic profiles between matched primary and metastatic breast cancer (MBC) in the ESME database, a National real-life multicenter cohort of MBC patients. Patients with results available on both primary tumour and metastatic disease within 6 months of MBC diagnosis and before any tumour progression were eligible for the main analysis.