A better understanding of the features that define the interplay between cancer cells and immune cells is key to identify new cancer therapies 1 . Yet, focus is often given to those interactions that occur within the primary tumor and its microenvironment, while the role of immune cells during cancer dissemination in patients remains largely uncharacterized 2,3 . Circulating tumor cells (CTCs) are precursors of metastasis in several cancer types [4][5][6] , and are occasionally found within the bloodstream in association with non-malignant cells such as white blood cells (WBCs) 7,8 . The identity and function of these CTC-associated WBCs, as well as the molecular features that define the interaction between WBCs and CTCs are unknown. Here, we achieve the isolation and interrogation of individual CTC-associated WBCs, alongside with corresponding cancer cells within each CTC-WBC cluster, from multiple breast cancer patients and mouse models. Single-cell RNA sequencing reveals a specific pattern of WBCs attached to CTCs, with neutrophils representing the majority of the cases. When comparing the transcriptome profiles of CTCs that were associated to neutrophils with that of CTCs alone, we detect a number of differentially expressed genes that outline cell cycle progression, leading to a higher ability to efficiently seed metastasis. Additionally, we identify cell-cell junction and cytokine-receptor pairs that define CTC-neutrophil clusters, representing key vulnerabilities of the metastatic process. Thus, the association between neutrophils and CTCs fuels cell cycle progression within the bloodstream and expands the metastatic potential of CTCs, providing a rationale for targeting this interaction in breast cancer. 3/28 Main TextCirculating tumor cells (CTCs) are precursors of metastasis in various solid cancers including breast cancer 6 , and are occasionally found in association to white blood cells (WBCs) 7 . The role of CTC-WBC clusters in metastasis development as well as the principles that govern the interplay between CTCs and WBCs during blood-borne metastasis are largely uncharacterized.We first sought to determine the number and composition of CTC-WBC clusters in breast cancer patients and mouse models. We obtained blood samples from 70 patients with invasive breast cancer that discontinued their treatment due to progressive disease, as well as from five different breast cancer mouse models, and we enriched for CTCs using the Parsortix microfluidic device 9 (Extended Data Fig. 1a-e). Live CTCs were stained for cancer-associated cell surface markers EpCAM, HER2, and EGFR or imaged directly for the expression of GFP, as well as labeled for CD45 to identify WBCs (Fig. 1a and Extended Data Fig. 1f). Among 70 patients, 34 (48.6%) had detectable CTCs, with a mean number of 22 CTCs per 7.5ml of blood (Supplementary Tables 1 and 2). While the majority of CTCs were single (88.0%), we also detected CTC clusters (8.6%) and CTC-WBC clusters (3.4%) (Fig. 1b and Extended Data Fig. 1g,h). Similarly, we observed that CTC-...

Single-cell analyses have revealed extensive intra-and inter-patient cancer heterogeneity 1 , but complex single-cell phenotypes and their spatial context are not yet reflected in the histologic stratification that is the foundation of many clinical decisions. Here, we used imaging mass cytometry 2 to simultaneously quantify 35 biomarkers resulting in 720 highdimension immunohistochemistry pathology images of tumor tissue from 352 breast cancer patients for whom long-term survival data were available. Spatial, single-cell analysis identified tumor and stromal single-cell phenotypes, their organization and heterogeneity, and enabled categorization of breast cancer cellular architecture based on cellular composition and tissue organization. Our analysis revealed multi-cellular features of the tumor microenvironment and novel breast cancer subgroups associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intra-tumor phenotypic heterogeneity in a disease-relevant manner with the potential to inform patient-specific diagnosis. MainHistologic and phenotypic differences between tumors guide cancer diagnosis, prognosis, and selection of treatment. Currently, breast cancer patients are graded based on tumor structure and cellular morphology, and subcategorized when more than 1% of tumor cells contain hormone receptors or more than 10% express high levels of HER2 or have amplified HER2 [3][4][5] . This leaves a large portion of cells uncharacterized even though additional molecular subclasses and morphologic features have been identified as prognostic [6][7][8][9] . It is clear that clonal evolution and spatially distinct tumor microenvironments drive inter-and intra-patient cellular

SummaryThe ability of circulating tumor cells (CTCs) to form clusters has been linked to increased metastatic potential. Yet biological features and vulnerabilities of CTC clusters remain largely unknown. Here, we profile the DNA methylation landscape of single CTCs and CTC clusters from breast cancer patients and mouse models on a genome-wide scale. We find that binding sites for stemness- and proliferation-associated transcription factors are specifically hypomethylated in CTC clusters, including binding sites for OCT4, NANOG, SOX2, and SIN3A, paralleling embryonic stem cell biology. Among 2,486 FDA-approved compounds, we identify Na+/K+ ATPase inhibitors that enable the dissociation of CTC clusters into single cells, leading to DNA methylation remodeling at critical sites and metastasis suppression. Thus, our results link CTC clustering to specific changes in DNA methylation that promote stemness and metastasis and point to cluster-targeting compounds to suppress the spread of cancer.

Summary Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1 + tumor-associated macrophages and exhausted T cells were found in high-grade ER + and ER − tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment.

Recent studies in multiple epithelial cancers have shown that the inhibitory receptor programmed cell death 1 (PD-1) is expressed on tumor-infiltrating lymphocytes and/or programmed death ligand 1 (PD-L1) is expressed on tumor cells, suggesting that antitumor immunity may be modulated by the PD-1/PD-L1 signaling pathway. In addition, phase 1 clinical trials with monoclonal antibodies targeting PD-1 or PD-L1 have shown promising results in several human cancers. The purpose of this study was to investigate the impact of PD-L1 expression in human breast cancer specimens. We conducted an immunohistochemistry study using a tissue microarray encompassing 650 evaluable formalin-fixed breast cancer cases with detailed clinical annotation and outcomes data. PD-L1 was expressed in 152 (23.4 %) of the 650 breast cancer specimens. Expression was significantly associated with age, tumor size, AJCC primary tumor classification, tumor grade, lymph node status, absence of ER expression, and high Ki-67 expression. In univariate analysis, PD-L1 expression was associated with a significantly worse OS. In multivariate analysis, PD-L1 expression remained an independent negative prognostic factor for OS. In subset analyses, expression of PD-L1 was associated with significantly worse OS in the luminal B HER2− subtype, the luminal B HER2+ subtype, the HER2 subtype, and the basal-like subtype. This is the first study to demonstrate that PD-L1 expression is an independent negative prognostic factor in human breast cancer. This finding has important implications for the application of antibody therapies targeting the PD-1/PD-L1 signaling pathway in this disease.

was held virtually, owing to the global COVID-19 pandemic. More than 3300 participants took part in this important bi-annual critical review of the 'state of the art' in the multidisciplinary care of early-stage breast cancer. Seventy-four expert panelists (see Appendix 1) from all continents discussed and commented on the previously elaborated consensus questions, as well as many key questions on early breast cancer diagnosis and treatment asked by the audience. The theme of this year's conference was 'Customizing local and systemic therapies.' A well-organized program of pre-recorded symposia, live panel discussions and real-time panel voting results drew a worldwide audience of thousands, reflecting the farreaching impact of breast cancer on every continent. The interactive technology platform allowed, for the first time, audience members to ask direct questions to panelists, and to weigh in with their own vote on several key panel questions. A hallmark of this meeting was to focus on customized recommendations for treatment of early-stage breast cancer. There is increasing recognition that the care of a breast cancer patient depends on highly individualized clinical features, including the stage at presentation, the biological subset of breast cancer, the genetic factors that may underlie breast cancer risk, the genomic signatures that inform treatment recommendations, the extent of response before surgery in patients who receive neoadjuvant therapy, and patient preferences. This customized approach to treatment requires integration of clinical care between patients and radiology, pathology, genetics, and surgical, medical and radiation oncology providers. It also requires a dynamic response from clinicians as they encounter accumulating clinical information at the time of diagnosis and then serially with each step in the treatment plan and follow-up, reflecting patient experiences and treatment response.

Testicular germ cell tumor (TGCT) is the most common cancer in young men. Despite a considerable familial component to TGCT risk, no genetic change that confers increased risk has been substantiated to date. The human Y chromosome carries a number of genes specifically involved in male germ cell development, and deletion of the AZFc region at Yq11 is the most common known genetic cause of infertility. Recently, a 1.6-Mb deletion of the Y chromosome that removes part of the AZFc region--known as the "gr/gr" deletion--has been associated with infertility. In epidemiological studies, male infertility has shown an association with TGCT that is out of proportion with what can be explained by tumor effects. Thus, we hypothesized that the gr/gr deletion may be associated with TGCT. Using logistic modeling, we analyzed this deletion in a large series of TGCT cases with and without a family history of TGCT. The gr/gr deletion was present in 3.0% (13/431) of TGCT cases with a family history, 2% (28/1,376) of TGCT cases without a family history, and 1.3% (33/2,599) of unaffected males. Presence of the gr/gr deletion was associated with a twofold increased risk of TGCT (adjusted odds ratio [aOR] 2.1; 95% confidence interval [CI] 1.3-3.6; P = .005) and a threefold increased risk of TGCT among patients with a positive family history (aOR 3.2; 95% CI 1.5-6.7; P = .0027). The gr/gr deletion was more strongly associated with seminoma (aOR 3.0; 95% CI 1.6-5.4; P = .0004) than with nonseminoma TGCT (aOR 1.5; 95% CI 0.72-3.0; P = .29). These data indicate that the Y microdeletion gr/gr is a rare, low-penetrance allele that confers susceptibility to TGCT.

When cefuroxime is used as a prophylactic antibiotic, administration 59 to 30 minutes before incision is more effective than administration during the last half hour.