Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

Interobserver Variation in the Assessment of Immunohistochemistry Expression Levels in HER2-Negative Breast Cancer: Can We Improve the Identification of Low Levels of HER2 Expression by Adjusting the Criteria? An International Interobserver Study.

The classification of human epidermal growth factor receptor 2 (HER2) expression is optimized to detect HER2-amplified breast cancer (BC). However, novel HER2-targeting agents are also effective for BCs with low levels of HER2. This raises the question whether the current guidelines for HER2 testing are sufficiently reproducible to identify HER2-low BC. The aim of this multicenter international study was to assess the interobserver agreement of specific HER2 immunohistochemistry scores in cases with negative HER2 results (0, 1+, or 2+/in situ hybridization negative) according to the current American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) guidelines. Furthermore, we evaluated whether the agreement improved by redefining immunohistochemistry (IHC) scoring criteria or by adding fluorescent in situ hybridization (FISH). We conducted a 2-round study of 105 nonamplified BCs. During the first assessment, 16 pathologists used the latest version of the ASCO/CAP guidelines. After a consensus meeting, the same pathologists scored the same digital slides using modified IHC scoring criteria based on the 2007 ASCO/CAP guidelines, and an extra "ultralow" category was added. Overall, the interobserver agreement was limited (4.7% of cases with 100% agreement) in the first round, but this was improved by clustering IHC categories. In the second round, the highest reproducibility was observed when comparing IHC 0 with the ultralow/1+/2+ grouped cluster (74.3% of cases with 100% agreement). The FISH results were not statistically different between HER2-0 and HER2-low cases, regardless of the IHC criteria used. In conclusion, our study suggests that the modified 2007 ASCO/CAP criteria were more reproducible in distinguishing HER2-0 from HER2-low cases than the 2018 ASCO/CAP criteria. However, the reproducibility was still moderate, which was not improved by adding FISH. This could lead to a suboptimal selection of patients eligible for novel HER2-targeting agents. If the threshold between HER2 IHC 0 and 1+ is to be clinically actionable, there is a need for clearer, more reproducible IHC definitions, training, and/or development of more accurate methods to detect this subtle difference in protein expression levels.

Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms.

Purpose: Validation of artificial intelligence (AI) algorithms in digital pathology with a reference standard is necessary before widespread clinical use, but few examples focus on creating a reference standard based on pathologist annotations. This work assesses the results of a pilot study that collects density estimates of stromal tumor-infiltrating lymphocytes (sTILs) in breast cancer biopsy specimens. This work will inform the creation of a validation dataset for the evaluation of AI algorithms fit for a regulatory purpose. Approach: Collaborators and crowdsourced pathologists contributed glass slides, digital images, and annotations. Here, "annotations" refer to any marks, segmentations, measurements, or labels a pathologist adds to a report, image, region of interest (ROI), or biological feature. Pathologists estimated sTILs density in 640 ROIs from hematoxylin and eosin stained slides of 64 patients via two modalities: an optical light microscope and two digital image viewing platforms. Results: The pilot study generated 7373 sTILs density estimates from 29 pathologists. Analysis of annotations found the variability of density estimates per ROI increases with the mean; the root mean square differences were 4.46, 14.25, and 26.25 as the mean density ranged from 0% to 10%, 11% to 40%, and 41% to 100%, respectively. The pilot study informs three areas of improvement for future work: technical workflows, annotation platforms, and agreement analysis methods. Upgrades to the workflows and platforms will improve operability and increase annotation speed and consistency. Conclusions: Exploratory data analysis demonstrates the need to develop new statistical approaches for agreement. The pilot study dataset and analysis methods are publicly available to allow community feedback. The development and results of the validation dataset will be publicly available to serve as an instructive tool that can be replicated by developers and researchers.

External Quality Assessment 2.0: The Importance of a Standardized Implementation of TILs for Daily and Trial Practices.

Increasing data suggests that an intact immune system is required for improvedoutcomes in patients with Human Epidermal Growth Factor Receptor 2 (HER2+) and Triple Negative Breast Cancer (TNBC) [...].

Interrogating breast cancer heterogeneity using single and pooled circulating tumor cell analysis.

Single cell technologies allow the interrogation of tumor heterogeneity, providing insights into tumor evolution and treatment resistance. To better understand whether circulating tumor cells (CTCs) could complement metastatic biopsies for tumor genomic profiling, we characterized 11 single CTCs and 10 pooled CTC samples at the mutational and copy number aberration (CNA) levels, and compared these results with matched synchronous tumor biopsies from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive and estrogen receptor-positive (ER+) tumors. Similar CNA profiles and the same patient-specific driver mutations were found in bulk tissue and CTCs for the HER2-positive and TNBC tumors, whereas different CNA profiles and driver mutations were identified for the ER+ tumor, which presented two distinct clones in CTCs defined by mutations in ESR1 Y537N and TP53, respectively. Furthermore, de novo mutational signatures derived from CTCs described patient-specific biological processes. These data suggest that tumor tissue and CTCs provide complementary clinically relevant information to map tumor heterogeneity and tumor evolution.

Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer.

The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer biopsy specimens. After completing the pilot study, we found notable variability in the sTILs estimates as well as inconsistencies and gaps in the provided training to pathologists. Using the pilot study data and an expert panel, we created custom training materials to improve pathologist annotation quality for the pivotal study. We categorized regions of interest (ROIs) based on their mean sTILs density and selected ROIs with the highest and lowest sTILs variability. In a series of eight one-hour sessions, the expert panel reviewed each ROI and provided verbal density estimates and comments on features that confounded the sTILs evaluation. We aggregated and shaped the comments to identify pitfalls and instructions to improve our training materials. From these selected ROIs, we created a training set and proficiency test set to improve pathologist training with the goal to improve data collection for the pivotal study. We are not exploring AI/ML performance in this paper. Instead, we are creating materials that will train crowd-sourced pathologists to be the reference standard in a pivotal study to create an AI/ML model validation dataset. The issues discussed here are also important for clinicians to understand about the evaluation of sTILs in clinical practice and can provide insight to developers of AI/ML models.

Circulating tumor cell detection: A prospective comparison between CellSearch® and RareCyte® platforms in patients with progressive metastatic breast cancer.

PURPOSE: Circulating tumor cells (CTCs) are prognostic in patients with breast cancer. Several technical platforms exist for their enumeration and characterization. Comparative studies between these platforms are scarce. The RareCyte CTC detection is theoretically more sensitive than the established CellSearch platform, which identifies only CTCs that express EpCAM and cytokeratin. This study prospectively compares CTC enumeration in patients with breast cancer in a paired analysis using these two platforms. It investigates survival outcomes in groups defined by a CTC count threshold. DESIGN: CTC enumeration was performed on 100 samples obtained from 86 patients with progressive metastatic breast cancer (MBC) in two independent laboratories each blinded to the clinical data and the results from the other platform. RESULTS: One hundred paired samples were collected and CTC counts were determined using the CellSearch and RareCyte CTC platforms. In total, 65% and 75% of samples had at least one detectable CTC in 7.5 mL blood with the CellSearch and the RareCyte systems, respectively. CTC counts with the CellSearch system ranged from 0 to 2289 with a median of 3 CTCs, the RareCyte CTC counts ranged from 0 to 1676 with a median of 3 CTCs. The number of samples with 5 or more CTCs in 7.5 mL of blood (the poor prognosis cut-off validated with the CellSearch system) blood was 45% with the CellSearch test and 48% with the RareCyte test. CTC counts quantified with the CellSearch and the RareCyte systems were strongly correlated (Spearman's r = 0.8235 (0.7450-0.8795) p < 0.001). 86 patients were included for Kaplan-Meier survival analysis. An increased mortality risk in patients with CellSearch of 5 CTCs or more per 7.5 mL blood, with a log-rank hazard ratio of 5.164 (2.579-10.34) (p < 0.001) was confirmed. The survival analysis with RareCyte CTC counts with the identical cut-off showed a significantly impaired survival with a hazard ratio of 4.213 (2.153-8.244) (p < 0.001). CONCLUSION: Our data demonstrate the analytical and prognostic equivalence of CellSearch and RareCyte CTC enumeration platforms in patients with MBC using the CellSearch cut-off. This is the first demonstration of prognostic significance using the RareCyte platform.

Interobserver Agreement of PD-L1/SP142 Immunohistochemistry and Tumor-Infiltrating Lymphocytes (TILs) in Distant Metastases of Triple-Negative Breast Cancer: A Proof-of-Concept Study. A Report on Behalf of the International Immuno-Oncology Biomarker Working Group.

Patients with advanced triple-negative breast cancer (TNBC) benefit from treatment with atezolizumab, provided that the tumor contains ≥1% of PD-L1/SP142-positive immune cells. Numbers of tumor-infiltrating lymphocytes (TILs) vary strongly according to the anatomic localization of TNBC metastases. We investigated inter-pathologist agreement in the assessment of PD-L1/SP142 immunohistochemistry and TILs. Ten pathologists evaluated PD-L1/SP142 expression in a proficiency test comprising 28 primary TNBCs, as well as PD-L1/SP142 expression and levels of TILs in 49 distant TNBC metastases with various localizations. Interobserver agreement for PD-L1 status (positive vs. negative) was high in the proficiency test: the corresponding scores as percentages showed good agreement with the consensus diagnosis. In TNBC metastases, there was substantial variability in PD-L1 status at the individual patient level. For one in five patients, the chance of treatment was essentially random, with half of the pathologists designating them as positive and half negative. Assessment of PD-L1/SP142 and TILs as percentages in TNBC metastases showed poor and moderate agreement, respectively. Additional training for metastatic TNBC is required to enhance interobserver agreement. Such training, focusing on metastatic specimens, seems worthwhile, since the same pathologists obtained high percentages of concordance (ranging from 93% to 100%) on the PD-L1 status of primary TNBCs.

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. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland-Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from -0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the 'ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.

PD-L1 Immunohistochemistry Assay Comparison in Atezolizumab Plus nab-Paclitaxel-Treated Advanced Triple-Negative Breast Cancer.

BACKGROUND: In the phase III IMpassion130 study, atezolizumab plus nab-paclitaxel (A+nP) showed clinical benefit in advanced or metastatic triple-negative breast cancer patients who were programmed death-ligand 1 (PD-L1)+ (tumor-infiltrating immune cells [IC] ≥1%) using the SP142 immunohistochemistry assay. Here we evaluate 2 other PD-L1 assays for analytical concordance with SP142 and patient-associated clinical outcomes. METHODS: Samples from 614 patients (68.1% of intention-to-treat population) were centrally evaluated by immunohistochemistry for PD-L1 status on IC (VENTANA SP142, SP263, Dako 22C3) or as a combined positive score (CPS; 22C3). RESULTS: Using SP142, SP263, and 22C3 assays, PD-L1 IC ≥1% prevalence was 46.4% (95% confidence interval [CI] = 42.5% to 50.4%), 74.9% (95% CI = 71.5% to 78.3%), and 73.1% (95% CI = 69.6% to 76.6%), respectively; 80.9% were 22C3 CPS ≥1. At IC ≥1% (+), the analytical concordance between SP142 and SP263 and 22C3 was 69.2% and 68.7%, respectively. Almost all SP142+ cases were captured by other assays (double positive), but several SP263+ (29.6%) or 22C3+ (29.0%) cases were SP142- (single positive). A+nP clinical activity vs placebo+nP in SP263+ and 22C3+ patients (progression-free survival [PFS] hazard ratios [HRs] = 0.64 to 0.68; overall survival [OS] HRs = 0.75 to 0.79) was driven by double-positive cases (PFS HRs = 0.60 to 0.61; OS HRs = 0.71 to 0.75) rather than single-positive cases (PFS HRs = 0.68 to 0.81; OS HRs = 0.87 to 0.95). Concordance for harmonized cutoffs for SP263 (IC ≥4%) and 22C3 (CPS ≥10) to SP142 (IC ≥1%) was subpar (approximately 75%). CONCLUSIONS: 22C3 and SP263 assays identified more patients as PD-L1+ (IC ≥1%) than SP142. No inter-assay analytical equivalency was observed. Consistent improved A+nP efficacy was captured by the SP142 PD-L1 IC ≥1% subgroup nested within 22C3 and SP263 PD-L1+ (IC ≥1%) populations.

PDX1 DNA Methylation Distinguishes Two Subtypes of Pancreatic Neuroendocrine Neoplasms with a Different Prognosis.

DNA methylation is a crucial epigenetic mechanism for gene expression regulation and cell differentiation. Furthermore, it was found to play a major role in multiple pathological processes, including cancer. In pancreatic neuroendocrine neoplasms (PNENs), epigenetic deregulation is also considered to be of significance, as the most frequently mutated genes have an important function in epigenetic regulation. However, the exact changes in DNA methylation between PNENs and the endocrine cells of the pancreas, their likely cell-of-origin, remain largely unknown. Recently, two subtypes of PNENs have been described which were linked to cell-of-origin and have a different prognosis. A difference in the expression of the transcription factor PDX1 was one of the key molecular differences. In this study, we performed an exploratory genome-wide DNA methylation analysis using Infinium Methylation EPIC arrays (Illumina) on 26 PNENs and pancreatic islets of five healthy donors. In addition, the methylation profile of the PDX1 region was used to perform subtyping in a global cohort of 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples. In our exploratory analysis, we identified 26,759 differentially methylated CpGs and 79 differentially methylated regions. The gene set enrichment analysis highlighted several interesting pathways targeted by altered DNA methylation, including MAPK, platelet-related and immune system-related pathways. Using the PDX1 methylation in 83 PNEN, 2 healthy alpha cell and 3 healthy beta cell samples, two subtypes were identified, subtypes A and B, which were similar to alpha and beta cells, respectively. These subtypes had different clinicopathological characteristics, a different pattern of chromosomal alterations and a different prognosis, with subtype A having a significantly worse prognosis compared with subtype B (HR 0.22 [95% CI: 0.051-0.95], p = 0.043). Hence, this study demonstrates that several cancer-related pathways are differently methylated between PNENs and normal islet cells. In addition, we validated the use of the PDX1 methylation status for the subtyping of PNENs and its prognostic importance.

The path to a better biomarker: application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice.

Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying ≥1% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin-stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Interobserver variability in upfront dichotomous histopathological assessment of ductal carcinoma in situ of the breast: the DCISion study.

Histopathological assessment of ductal carcinoma in situ, a nonobligate precursor of invasive breast cancer, is characterized by considerable interobserver variability. Previously, post hoc dichotomization of multicategorical variables was used to determine the "ideal" cutoffs for dichotomous assessment. The present international multicenter study evaluated interobserver variability among 39 pathologists who performed upfront dichotomous evaluation of 149 consecutive ductal carcinomas in situ. All pathologists independently assessed nuclear atypia, necrosis, solid ductal carcinoma in situ architecture, calcifications, stromal architecture, and lobular cancerization in one digital slide per lesion. Stromal inflammation was assessed semiquantitatively. Tumor-infiltrating lymphocytes were quantified as percentages and dichotomously assessed with a cutoff at 50%. Krippendorff's alpha (KA), Cohen's kappa and intraclass correlation coefficient were calculated for the appropriate variables. Lobular cancerization (KA = 0.396), nuclear atypia (KA = 0.422), and stromal architecture (KA = 0.450) showed the highest interobserver variability. Stromal inflammation (KA = 0.564), dichotomously assessed tumor-infiltrating lymphocytes (KA = 0.520), and comedonecrosis (KA = 0.539) showed slightly lower interobserver disagreement. Solid ductal carcinoma in situ architecture (KA = 0.602) and calcifications (KA = 0.676) presented with the lowest interobserver variability. Semiquantitative assessment of stromal inflammation resulted in a slightly higher interobserver concordance than upfront dichotomous tumor-infiltrating lymphocytes assessment (KA = 0.564 versus KA = 0.520). High stromal inflammation corresponded best with dichotomously assessed tumor-infiltrating lymphocytes when the cutoff was set at 10% (kappa = 0.881). Nevertheless, a post hoc tumor-infiltrating lymphocytes cutoff set at 20% resulted in the highest interobserver agreement (KA = 0.669). Despite upfront dichotomous evaluation, the interobserver variability remains considerable and is at most acceptable, although it varies among the different histopathological features. Future studies should investigate its impact on ductal carcinoma in situ prognostication. Forthcoming machine learning algorithms may be useful to tackle this substantial diagnostic challenge.

HER-2 status of circulating tumor cells in a metastatic breast cancer cohort: A comparative study on characterization techniques.

BACKGROUND: Personalized targeted treatment in metastatic breast cancer relies on accurate assessment of molecular aberrations, e.g. overexpression of Human Epidermal growth factor Receptor 2 (HER-2). Molecular interrogation of circulating tumor cells (CTCs) can provide an attractive alternative for real-time biomarker assessment. However, implementation of CellSearch-based HER-2 analysis has been limited. Immunofluorescent (IF) image interpretation is crucial, as different HER-2 categories have been described. Major questions in CTC research are how these IF categories reflect gene expression and amplification, and if we should consider 'medium' HER-2 expressing CTCs for patient selection. METHODS: Tumor cells from spiked cell lines (n = 8) and CTCs (n = 116 samples) of 85 metastatic breast cancer patients were enriched using CellSearch. Comparative analysis of HER-2 expression by IF imaging (ACCEPT, DEPArray, and visual scoring) with qRT-PCR and HER-2/neu FISH was performed. RESULTS: Automated IF HER-2-profiling by DEPArray and ACCEPT delivered comparable results. There was a 98% agreement between 17 trained observers (visual scoring) and ACCEPT considering HER-2neg and HER-2high expressing CTCs. However, 89% of HER-2med expressing CTCs by ACCEPT were scored negative by observers. HER-2high expressing tumor cells demonstrated HER-2/neu gene amplification, whereas HER-2neg and HER-2med expressing tumor cells and CTCs by ACCEPT were copy-number neutral. All patients with HER-2-positive archival tumors had ≥1 HER-2high expressing CTCs, while 80% of HER-2-negative patients did not. High relative gene expression of HER-2 measured on enriched CTC lysates correlated with having ≥1 HER-2high expressing CTCs. CONCLUSION: Automated images analysis has enormous potential for clinical implementation. HER-2 characterization and clinical trial design should be focused on HER-2high expressing CTCs.

The clinical use of circulating tumor cells (CTCs) enumeration for staging of metastatic breast cancer (MBC): International expert consensus paper.

BACKGROUND: The heterogeneity of metastatic breast cancer (MBC) necessitates novel biomarkers allowing stratification of patients for treatment selection and drug development. We propose to use the prognostic utility of circulating tumor cells (CTCs) for stratification of patients with stage IV disease. METHODS: In a retrospective, pooled analysis of individual patient data from 18 cohorts, including 2436 MBC patients, a CTC threshold of 5 cells per 7.5 ml was used for stratification based on molecular subtypes, disease location, and prior treatments. Patients with ≥ 5 CTCs were classified as Stage IVaggressive, those with < 5 CTCs as Stage IVindolent. Survival was analyzed using Kaplan-Meier curves and the log rank test. RESULTS: For all patients, Stage IVindolent patients had longer median overall survival than those with Stage IVaggressive (36.3 months vs. 16.0 months, P < 0.0001) and similarly for de novo MBC patients (41.4 months Stage IVindolent vs. 18.7 months Stage IVaggressive, p < 0.0001). Moreover, patients with Stage IVindolent disease had significantly longer overall survival across all disease subtypes compared to the aggressive cohort: hormone receptor-positive (44 months vs. 17.3 months, P < 0.0001), HER2-positive (36.7 months vs. 20.4 months, P < 0.0001), and triple negative (23.8 months vs. 9.0 months, P < 0.0001). Similar results were obtained regardless of prior treatment or disease location. CONCLUSIONS: We confirm the identification of two subgroups of MBC, Stage IVindolent and Stage IVaggressive, independent of clinical and molecular variables. Thus, CTC count should be considered an important tool for staging of advanced disease and for disease stratification in prospective clinical trials.

Dichotomous histopathological assessment of ductal carcinoma in situ of the breast results in substantial interobserver concordance.

AIMS: Robust prognostic markers for ductal carcinoma in situ (DCIS) of the breast require high reproducibility and thus low interobserver variability. The aim of this study was to compare interobserver variability among 13 pathologists, in order to enable the identification of robust histopathological characteristics. METHODS AND RESULTS: One representative haematoxylin and eosin-stained slide was selected for 153 DCIS cases. All pathologists independently assessed nuclear grade, intraductal calcifications, necrosis, solid growth, stromal changes, stromal inflammation, and apocrine differentiation. All characteristics were assessed categorically. Krippendorff's alpha was calculated to assess overall interobserver concordance. Cohen's kappa was calculated for every observer duo to further explore interobserver variability. The highest concordance was observed for necrosis, calcifications, and stromal inflammation. Assessment of solid growth, nuclear grade and stromal changes resulted in lower concordance. Poor concordance was observed for apocrine differentiation. Kappa values for each observer duo identified the 'ideal' cut-off for dichotomisation of multicategory variables. For instance, concordance was higher for 'non-high versus high' nuclear grade than for 'low versus non-low' nuclear grade. 'Absent/mild' versus 'moderate/extensive' stromal inflammation resulted in substantially higher concordance than other dichotomous cut-offs. CONCLUSIONS: Dichotomous assessment of the histopathological features of DCIS resulted in moderate to substantial agreement among pathologists. Future studies on prognostic markers in DCIS should take into account this degree of interobserver variability to define cut-offs for categorically assessed histopathological features, as reproducibility is paramount for robust prognostic markers in daily clinical practice. A new prognostic index for DCIS might be considered, based on two-tier grading of histopathological features. Future research should explore the prognostic potential of such two-tier assessment.

Adult suprapatellar pleiomorphic rhabdomyosarcoma with jejunal metastasis causing intussusception: a case report.

Jejuno-jejunal intussusception is rarely encountered in adults. Management depends on the viability of the involved bowel. Exploration is favored because in adults generally an underlying 'lead point' is found to be present. Pleimorphic rhabdomyosarcoma (pRMS) arises from striated muscle cells. They are usually diagnosed during childhood and can occur virtually all over the body, controversially in places were few striated cells are found. In adults, these tumors are rare and are mostly encountered in the head-and-neck region. We present the case of a 48-year-old woman with a jejunal metastasis from a suprapatellar pRMS diagnosed 2.5 years earlier resulting in a jejuno-jejunal intussusception.