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Abstract As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Abstract Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model’s biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.

Abstract Background The global BOLERO-2 trial established the efficacy and safety of combination everolimus (EVE) and exemestane (EXE) in the treatment of estrogen receptor positive (ER +), HER2-, advanced breast cancer (ABC). BOLERO-5 investigated this combination in a Chinese population (NCT03312738). Methods BOLERO-5 is a randomized, double-blind, multicenter, placebo controlled, phase II trial comparing EVE (10 mg/day) or placebo (PBO) in combination with EXE (25 mg/day). The primary endpoint was progression-free survival (PFS) per investigator assessment. Secondary endpoints included PFS per blinded independent review committee (BIRC), overall survival (OS), overall response rate (ORR), clinical benefit rate (CBR), pharmacokinetics, and safety. Results A total of 159 patients were randomized to EVE + EXE (n = 80) or PBO + EXE (n = 79). By investigator assessment, treatment with EVE + EXE prolonged median PFS by 5.4 months (HR 0.52; 90% CI 0.38, 0.71), from 2.0 months (PBO + EXE; 90% CI 1.9, 3.6) to 7.4 months (EVE + EXE; 90% CI 5.5, 9.0). Similar results were observed following assessment by BIRC, with median PFS prolonged by 4.3 months. Treatment with EVE + EXE was also associated with improvements in ORR and CBR. No new safety signals were identified in BOLERO-5, with the incidence of adverse events in Chinese patients consistent with the safety profile of both drugs. Conclusion The efficacy and safety results of BOLERO-5 validate the findings from BOLERO-2, and further support the use of EVE + EXE in Chinese post-menopausal women with ER + , HER2- ABC. NCT03312738, registered 18 October 2017.

Summary: Breast cancer is a common disease that causes great health concerns to women worldwide. During the diagnosis and treatment of breast cancer, medical imaging plays an essential role, but its interpretation relies on radiologists or clinical doctors. Radiomics can extract high-throughput quantitative imaging features from images of various modalities via traditional machine learning or deep learning methods following a series of standard processes. Hopefully, radiomic models may aid various processes in clinical practice. In this review, we summarize the current utilization of radiomics for predicting clinicopathological indices and clinical outcomes. We also focus on radio-multi-omics studies that bridge the gap between phenotypic and microscopic scale information. Acknowledging the deficiencies that currently hinder the clinical adoption of radiomic models, we discuss the underlying causes of this situation and propose future directions for advancing radiomics in breast cancer research.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

Abstract Extensive exploration of the molecular subtypes of triple-negative breast cancer (TNBC) is critical for advancing precision medicine. Notably, the luminal androgen receptor (LAR) subtype has attracted attention for targeted treatment combining androgen receptor antagonists and CDK4/6 inhibitors. Unfortunately, this strategy has proven to be of limited efficacy, highlighting the need for further optimization. Using our center’s comprehensive multiomics dataset (n = 465), we identified novel therapeutic targets and evaluated their efficacy through multiple models, including in vitro LAR cell lines, in vivo cell-derived allograft models and ex vivo patient-derived organoids. Moreover, we conducted flow cytometry and RNA-seq analysis to unveil potential mechanisms underlying the regulation of tumor progression by these therapeutic strategies. LAR breast cancer cells exhibited sensitivity to chidamide and enzalutamide individually, with a drug combination assay revealing their synergistic effect. Crucially, this synergistic effect was verified through in vivo allograft models and patient-derived organoids. Furthermore, transcriptomic analysis demonstrated that the combination therapeutic strategy could inhibit tumor progression by regulating metabolism and autophagy. This study confirmed that the combination of histone deacetylase (HDAC) inhibitors and androgen receptor (AR) antagonists possessed greater therapeutic efficacy than monotherapy in LAR TNBC. This finding significantly bolsters the theoretical basis for the clinical translation of this combination therapy and provides an innovative strategy for the targeted treatment of LAR TNBC.

Abstract Diet, serving as a vital source of nutrients, exerts a profound influence on human health and disease progression. Recently, dietary interventions have emerged as promising adjunctive treatment strategies not only for cancer but also for neurodegenerative diseases, autoimmune diseases, cardiovascular diseases, and metabolic disorders. These interventions have demonstrated substantial potential in modulating metabolism, disease trajectory, and therapeutic responses. Metabolic reprogramming is a hallmark of malignant progression, and a deeper understanding of this phenomenon in tumors and its effects on immune regulation is a significant challenge that impedes cancer eradication. Dietary intake, as a key environmental factor, can influence tumor metabolism. Emerging evidence indicates that dietary interventions might affect the nutrient availability in tumors, thereby increasing the efficacy of cancer treatments. However, the intricate interplay between dietary interventions and the pathogenesis of cancer and other diseases is complex. Despite encouraging results, the mechanisms underlying diet-based therapeutic strategies remain largely unexplored, often resulting in underutilization in disease management. In this review, we aim to illuminate the potential effects of various dietary interventions, including calorie restriction, fasting-mimicking diet, ketogenic diet, protein restriction diet, high-salt diet, high-fat diet, and high-fiber diet, on cancer and the aforementioned diseases. We explore the multifaceted impacts of these dietary interventions, encompassing their immunomodulatory effects, other biological impacts, and underlying molecular mechanisms. This review offers valuable insights into the potential application of these dietary interventions as adjunctive therapies in disease management.

Abstract Breast tumor‐initiating cells (BTICs) of triple‐negative breast cancer (TNBC) tissues actively repair DNA and are resistant to treatments including chemotherapy, radiotherapy, and targeted therapy. Herein, it is found that a previously reported secreted protein, sclerostin domain containing 1 (SOSTDC1), is abundantly expressed in BTICs of TNBC cells and positively correlated with a poor patient prognosis. SOSTDC1 knockdown impairs homologous recombination (HR) repair, BTIC maintenance, and sensitized bulk cells and BTICs to Olaparib. Mechanistically, following Olaparib treatment, SOSTDC1 translocates to the nucleus in an importin‐α dependent manner. Nuclear SOSTDC1 interacts with the N‐terminus of the nucleoprotein, chromatin helicase DNA‐binding factor (CHD1), to promote HR repair and BTIC maintenance. Furthermore, nuclear SOSTDC1 bound to β‐transducin repeat‐containing protein (β‐TrCP) binding motifs of CHD1 is found, thereby blocking the β‐TrCP‐CHD1 interaction and inhibiting β‐TrCP‐mediated CHD1 ubiquitination and degradation. Collectively, these findings identify a novel nuclear SOSTDC1 pathway in regulating HR repair and BTIC maintenance, providing insight into the TNBC therapeutic strategies.

Background: Breast cancer (BC) poses a global threat, with HER2-positive BC being a particularly hazardous subtype. Despite the promise shown by neoadjuvant therapy (NAT) in improving prognosis, resistance in HER2-positive BC persists despite emerging targeted therapies. The objective of this study is to identify markers that promote therapeutic sensitivity and unravel the underlying mechanisms. Methods: We conducted an analysis of 86 HER2-positive BC biopsy samples pre-NAT using RNA-seq. Validation was carried out using TCGA, Kaplan‒Meier Plotter, and Oncomine databases. Phenotype verification utilized IC50 assays, and prognostic validation involved IHC on tissue microarrays. RNA-seq was performed on wild-type/DUSP4-KO cells, while RT‒qPCR assessed ROS pathway regulation. Mechanistic insights were obtained through IP and MS assays. Results: Our findings reveal that DUSP4 enhances therapeutic efficacy in HER2-positive BC by inhibiting the ROS pathway. Elevated DUSP4 levels correlate with increased sensitivity to HER2-targeted therapies and improved clinical outcomes. DUSP4 independently predicts disease-free survival (DFS) and overall survival (OS) in HER2-positive BC. Moreover, DUSP4 hinders G6PD activity via ALDOB dephosphorylation, with a noteworthy association with heightened ROS levels. Conclusions: In summary, our study unveils a metabolic reprogramming paradigm in BC, highlighting DUSP4′s role in enhancing therapeutic sensitivity in HER2-positive BC cells. DUSP4 interacts with ALDOB, inhibiting G6PD activity and the ROS pathway, establishing it as an independent prognostic predictor for HER2-positive BC patients.

Abstract Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

Immunotherapy has rejuvenated cancer therapy, especially after anti-PD-(L)1 came onto the scene. Among the many therapeutic options, therapeutic cancer vaccines are one of the most essential players. Although great progress has been made in research on tumor antigen vaccines, few phase III trials have shown clinical benefits. One of the reasons lies in obstruction from the tumor microenvironment (TME). Meanwhile, the therapeutic cancer vaccine reshapes the TME in an ambivalent way, leading to immune stimulation or immune escape. In this review, we summarize recent progress on the interaction between therapeutic cancer vaccines and the TME. With respect to vaccine resistance, innate immunosuppressive TME components and acquired resistance caused by vaccination are both involved. Understanding the underlying mechanism of this crosstalk provides insight into the treatment of cancer by directly targeting the TME or synergizing with other therapeutics.

Abstract Digital pathology allows computerized analysis of tumor ecosystem using whole slide images (WSIs). Here, we present single-cell morphological and topological profiling (sc-MTOP) to characterize tumor ecosystem by extracting the features of nuclear morphology and intercellular spatial relationship for individual cells. We construct a single-cell atlas comprising 410 million cells from 637 breast cancer WSIs and dissect the phenotypic diversity within tumor, inflammatory and stroma cells respectively. Spatially-resolved analysis identifies recurrent micro-ecological modules representing locoregional multicellular structures and reveals four breast cancer ecotypes correlating with distinct molecular features and patient prognosis. Further analysis with multiomics data uncovers clinically relevant ecosystem features. High abundance of locally-aggregated inflammatory cells indicates immune-activated tumor microenvironment and favorable immunotherapy response in triple-negative breast cancers. Morphological intratumor heterogeneity of tumor nuclei correlates with cell cycle pathway activation and CDK inhibitors responsiveness in hormone receptor-positive cases. sc-MTOP enables using WSIs to characterize tumor ecosystems at the single-cell level.

Abstract Background Immune checkpoint inhibitors (ICIs) shed new light on triple‐negative breast cancer (TNBC), but only a minority of patients demonstrate response. Therefore, adaptive immune resistance (AIR) needs to be further defined to guide the development of ICI regimens. Methods Databases, including The Cancer Genome Atlas, Gene Ontology Resource, University of California Santa Cruz Genome Browser, and Pubmed, were used to screen epigenetic modulators, regulators for CD8+ T cells, and transcriptional regulators of programmed cell death‐ligand 1 (PD‐L1). Human peripheral blood mononuclear cell (Hu‐PBMC) reconstruction mice were adopted for xenograft transplantation. Tumor specimens from a TNBC cohort and the clinical trial CTR20191353 were retrospectively analyzed. RNA‐sequencing, Western blotting, qPCR and immunohistochemistry were used to assess gene expression. Coculture assays were performed to evaluate the regulation of TNBC cells on T cells. Chromatin immunoprecipitation and transposase‐accessible chromatin sequencing were used to determine chromatin‐binding and accessibility. Results The epigenetic modulator AT‐rich interaction domain 1A (ARID1A) gene demonstrated the highest expression association with AIR relative to other epigenetic modulators in TNBC patients. Low ARID1A expression in TNBC, causing an immunosuppressive microenvironment, promoted AIR and inhibited CD8+ T cell infiltration and activity through upregulating PD‐L1. However, ARID1A did not directly regulate PD‐L1 expression. We found that ARID1A directly bound the promoter of nucleophosmin 1 (NPM1) and that low ARID1A expression increased NPM1 chromatin accessibility as well as gene expression, further activating PD‐L1 transcription. In Hu‐PBMC mice, atezolizumab demonstrated the potential to reverse ARID1A deficiency‐induced AIR in TNBC by reducing tumor malignancy and activating anti‐tumor immunity. In CTR20191353, ARID1A‐low patients derived more benefit from pucotenlimab compared to ARID1A‐high patients. Conclusions In AIR epigenetics, low ARID1A expression in TNBC contributed to AIR via the ARID1A/NPM1/PD‐L1 axis, leading to poor outcome but sensitivity to ICI treatment.

Abstract The molecular heterogeneity and distinct features of HER2-low breast cancers, particularly in the Chinese population, are not well understood, limiting its precise management in the era of antibody‒drug conjugates. To address this issue, we established a cohort of 434 Chinese patients with HER2-low breast cancer (433 female and one male) and integrated genomic, transcriptomic, proteomic, and metabolomic profiling data. In this cohort, HER2-low tumors are more distinguished from HER2-0 tumors in the hormone receptor–negative subgroup. Within HER2-low tumors, significant interpatient heterogeneity also exists in the hormone receptor–negative subgroup: basal-like tumors resemble HER2-0 disease, and non-basal-like HER2-low tumors mimic HER2-positive disease. These non-basal-like HER2-low tumors are enriched in the HER2-enriched subtype and the luminal androgen receptor subtype and feature PIK3CA mutation, FGFR4/PTK6/ERBB4 overexpression and lipid metabolism activation. Among hormone receptor–positive tumors, HER2-low tumors show less loss/deletion in 17q peaks than HER2-0 tumors. In this work, we reveal the heterogeneity of HER2-low breast cancers and emphasize the need for more precise stratification regarding hormone receptor status and molecular subtype.

Background: With our growing insight into the molecular heterogeneity and biological characteristics of breast cancer, individualized treatment is the future of cancer treatment. In this prospective Fudan University Shanghai Cancer Center Breast Cancer Precision Platform Series study – neoadjuvant therapy (FASCINATE-N) trial, we classify breast cancer patients using multiomic characteristics into different subtypes to evaluate the efficacy of precision-based targeted therapies compared to standard neoadjuvant chemotherapy. Methods and design: The FASCINATE-N trial is a prospective, randomized, precision-based umbrella trial that plans to enroll 716 women with early breast cancer. After enrollment, patients will first be divided into three groups: hormone receptor (HR)+/human epidermal growth factor receptor 2 (HER2)−, HER2+, and HR−/HER2−. The HR+/HER2− patients are further stratified using fusion and clustering of similarity network fusion (SNF) algorithm into four subtypes; HER2+ patients are divided into HR+/HER2+ and HR−/HER2+ subtypes; and HR−/HER2− patients are stratified using the Fudan University Shanghai Cancer Center classification. For the assignment of drugs to patients, Bayesian methods of adaptive randomization will be used. The primary endpoint is pathological complete response rate; secondary endpoints include 3-year invasive disease-free survival, overall response rate, and toxicities according to common terminology criteria for adverse events (CTCAE) scale version 4.0 and the ratio of patients with complete cell cycle arrest (Ki67 < 2.7%) in HR+/HER2+ breast cancer. Discussion: The goal of our trial is to test the efficacy of our subtyping-based treatment in a neoadjuvant setting and to conduct a pilot study into the efficacy of targeted therapies within each precision-based subtype. The precision-based treatment arm can be updated with the refinement of our subtyping method, the discovery of new targets, and the development of novel targeted drugs. Our trial offers a unique opportunity to provide patients with individualized neoadjuvant therapy and test promising novel treatments that may further benefit patients. Trial registration: ClinicalTrials.gov identifier: NCT05582499 ( https://classic.clinicaltrials.gov/ct2/show/NCT05582499 ).

Abstract Despite the high prevalence of mammographic calcifications, our understanding remains limited regarding the clinical and molecular features of calcifications within triple-negative breast cancer (TNBC). To investigate the clinical relevance and biological basis of TNBC with calcifications of high suspicion for malignancy, we established a study cohort (N = 312) by integrating mammographic records with clinical data and genomic, transcriptomic, and metabolomic profiling. Despite similar clinicopathological features, patients with highly suspicious calcifications exhibited a worse overall survival than those without. In addition, TNBC with highly suspicious calcifications was characterized by a higher frequency of PIK3CA mutation, lower infiltration of immune cells, and increased abnormality of lipid metabolism. Overall, our study systematically revealed clinical and molecular heterogeneity between TNBC with or without calcifications of high suspicion for malignancy. These data might help to understand the clinical relevance and biological basis of mammographic calcifications.

Abstract Introduction We have previously reported that Toll-like receptor 3 (TLR3) acts as a suppressor gene for breast cancer initiation and progression. In this study, we evaluated the role of TLR3 in breast cancer using our original Fudan University Shanghai Cancer Center (FUSCC) datasets and breast cancer tissue microarrays. Methods Using FUSCC multiomics datasets on triple- negative breast cancer (TNBC), we compared the mRNA expression of TLR3 in TNBC tissue and the adjacent normal tissue. A Kaplan–Meier plotter was performed to investigate the expression of TLR3 on prognosis in the FUSCC TNBC cohort. We performed immunohistochemical staining to analyze TLR3 protein expression in the TNBC tissue microarrays. Furthermore, bioinformatics analysis was performed using the Cancer Genome Atlas (TCGA) data to verify the results of our FUSCC study. The relationship between TLR3 and clinicopathological features was analyzed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in TCGA patients was assessed using the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways that are differentially activated in breast cancer. Results The mRNA expression of TLR3 was lower in TNBC tissue than in the adjacent normal tissue in the FUSCC datasets. The TLR3 had high expression in immunomodulatory (IM) and mesenchymal-like (MES) subtypes and low expression in luminal androgen receptor (LAR) and basal-like immune-suppressed (BLIS) subtypes. High expression of TLR3 in TNBC predicted better prognosis in the FUSCC TNBC cohort. Immunohistochemical staining of the tissue microarrays showed that TLR3 had lower expression in breast cancer tissues than in the adject normal tissues. Furthermore, the TLR3 expression was positively associated with B cell, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells. Bioinformatic analysis using high-throughput RNA-sequencing data from the TCGA demonstrated that the reduced expression of TLR3 in breast cancer was associated with advanced clinicopathological characteristics, survival time, and poor prognosis. Conclusions TLR3 has low expression in TNBC tissue. High expression of TLR3 in triple-negative breast cancer predicts better prognosis. TLR3 expression may be a potential prognostic molecular marker of poor survival in breast cancer.

Abstract Antibody‐drug conjugates (ADCs) are a rapidly developing therapeutic approach in cancer treatment that has shown remarkable activity in breast cancer. Currently, there are two ADCs approved for the treatment of human epidermal growth factor receptor 2‐positive breast cancer, one for triple‐negative breast cancer, and multiple investigational ADCs in clinical trials. However, drug resistance has been noticed in clinical use, especially in trastuzumab emtansine. Here, the mechanisms of ADC resistance are summarized into four categories: antibody‐mediated resistance, impaired drug trafficking, disrupted lysosomal function, and payload‐related resistance. To overcome or prevent resistance to ADCs, innovative development strategies and combination therapy options are being investigated. Analyzing predictive biomarkers for optimal therapy selection may also help to prevent drug resistance.

To provide complementary information and reveal the molecular characteristics and therapeutic insights of HER2-low breast cancer, we performed this multiomics study of hormone receptor–negative (HR–) and HER2-low breast cancer, also known as HER2-low triple-negative breast cancer (TNBC), and identified 3 subgroups: basal-like, receptor tyrosine kinase–relevant (TKR), and mesenchymal stem–like. These 3 subgroups had distinct features and potential therapeutic targets and were validated in external data sets. Interestingly, the TKR subgroup (which exists in both HR+ and HR– breast cancer) had activated HER2 and downstream MAPK signaling. In vitro and in vivo patient-derived xenograft experiments revealed that pretreatment of the TKR subgroup with a tyrosine kinase inhibitor (lapatinib or tucatinib) could inhibit HER2 signaling and induce accumulated expression of nonfunctional HER2, resulting in increased sensitivity to the sequential HER2-targeting, Ab–drug conjugate DS-8201. Our findings identify clinically relevant subgroups and provide potential therapeutic strategies for HER2-low TNBC subtypes.

Abstract Background Tumor-infiltrating lymphocytes (TILs) have become a promising biomarker for assessing tumor immune microenvironment and predicting immunotherapy response. However, the assessment of TILs relies on invasive pathological slides. Methods We retrospectively extracted radiomics features from magnetic resonance imaging (MRI) to develop a radiomic cohort of triple-negative breast cancer (TNBC) (n = 139), among which 116 patients underwent transcriptomic sequencing. This radiomic cohort was randomly divided into the training cohort (n = 98) and validation cohort (n = 41) to develop radiomic signatures to predict the level of TILs through a non-invasive method. Pathologically evaluated TILs in the H&E sections were set as the gold standard. Elastic net and logistic regression were utilized to perform radiomics feature selection and model training, respectively. Transcriptomics was utilized to infer the detailed composition of the tumor microenvironment and to validate the radiomic signatures. Results We selected three radiomics features to develop a TILs-predicting radiomics model, which performed well in the validation cohort (AUC 0.790, 95% confidence interval (CI) 0.638–0.943). Further investigation with transcriptomics verified that tumors with high TILs predicted by radiomics (Rad-TILs) presented activated immune-related pathways, such as antigen processing and presentation, and immune checkpoints pathways. In addition, a hot immune microenvironment, including upregulated T cell infiltration gene signatures, cytokines, costimulators and major histocompatibility complexes (MHCs), as well as more CD8+ T cells, follicular helper T cells and memory B cells, was found in high Rad-TILs tumors. Conclusions Our study demonstrated the feasibility of radiomics model in predicting TILs status and provided a method to make the features interpretable, which will pave the way toward precision medicine for TNBC.

Measurement(s) RNA expression profiling • whole-exome sequencing (WES) • somatic mutations • copy number alterations (CNAs) Technology Type(s) RNA sequencing • DNA sequencing • OncoScan CNV assay Factor Type(s) Intervention or procedure Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location China

Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer. High fibrosis, marked by increased collagen fibers, is widespread in TNBC and correlated with tumor progression. However, the molecular features of fibrosis and why it results in a poor prognosis remain poorly understood. Based on multiomics datasets of TNBC, we evaluated the pathological fibrosis grade of 344 samples for further analysis. Genomic, transcriptomic, and immune changes were analyzed among different subgroups of fibrosis. High fibrosis was an independent adverse prognosis predictor and had interactions with low stromal tumor-infiltrating lymphocytes. Genomic analysis identified copy number gains of 6p22.2–6p22.1 (TRIM27) and 20q13.33 (CDH4) as genomic hallmarks of tumors with high fibrosis. Transcriptome analysis revealed the transforming growth factor-beta pathway and hypoxia pathway were key pro-oncogenic pathways in tumors with high fibrosis. Moreover, we systematically evaluate the relationship between fibrosis and different kinds of immune and stromal cells. Tumors with high fibrosis were characterized by an immunosuppressive tumor microenvironment with limited immune cell infiltration and increased fibroblasts. This study proposes new insight into the genomic and transcriptomic alterations potentially driving fibrosis. Moreover, fibrosis is related to an immunosuppressive tumor microenvironment that contributes to the poor prognosis.

Abstract Background Immune checkpoint inhibitors had a great effect in triple-negative breast cancer (TNBC); however, they benefited only a subset of patients, underscoring the need to co-target alternative pathways and select optimal patients. Herein, we investigated patient subpopulations more likely to benefit from immunotherapy and inform more effective combination regimens for TNBC patients. Methods We conducted exploratory analyses in the FUSCC cohort to characterize a novel patient selection method and actionable targets for TNBC immunotherapy. We investigated this in vivo and launched a phase 2 trial to assess the clinical value of such criteria and combination regimen. Furthermore, we collected clinicopathological and next-generation sequencing data to illustrate biomarkers for patient outcomes. Results CD8-positivity could identify an immunomodulatory subpopulation of TNBCs with higher possibilities to benefit from immunotherapy, and angiogenesis was an actionable target to facilitate checkpoint blockade. We conducted the phase II FUTURE-C-Plus trial to assess the feasibility of combining famitinib (an angiogenesis inhibitor), camrelizumab (a PD-1 monoclonal antibody) and chemotherapy in advanced immunomodulatory TNBC patients. Within 48 enrolled patients, the objective response rate was 81.3% (95% CI, 70.2–92.3), and the median progression-free survival was 13.6 months (95% CI, 8.4–18.8). No treatment-related deaths were reported. Patients with CD8- and/or PD-L1- positive tumors benefit more from this regimen. PKD1 somatic mutation indicates worse progression-free and overall survival. Conclusion This study confirms the efficacy and safety of the triplet regimen in immunomodulatory TNBC and reveals the potential of combining CD8, PD-L1 and somatic mutations to guide clinical decision-making and treatments. Trial registration ClinicalTrials.gov: NCT04129996 . Registered 11 October 2019.

Copy number alterations are pivotal genetic events in triple-negative breast cancer. Here the authors show the amplification of ENSA at the 1q21.3 region promotes the progression of TNBC via up-regulation of cholesterol biosynthesis.

Abstract Breast cancer is now the most frequently diagnosed malignancy, and metastasis remains the leading cause of death in breast cancer. However, little is known about the dynamic changes during the evolvement of dissemination. In this study, 65 968 cells from four patients with breast cancer and paired metastatic axillary lymph nodes are profiled using single‐cell RNA sequencing (scRNA‐seq) and spatial transcriptomics. A disseminated cancer cell cluster with high levels of oxidative phosphorylation (OXPHOS), including the upregulation of cytochrome C oxidase subunit 6C and dehydrogenase/reductase 2, is identified. The transition between glycolysis and OXPHOS when dissemination initiates is noticed. Furthermore, this distinct cell cluster is distributed along the tumor's leading edge. The findings here are verified in three different cohorts of breast cancer patients and an external scRNA‐seq dataset, which includes eight patients with breast cancer and paired metastatic axillary lymph nodes. This work describes the dynamic metabolic evolvement of early disseminated breast cancer and reveals a switch between glycolysis and OXPHOS in breast cancer cells as the early event during lymph node metastasis.

Abstract Hormone receptor testing mainly serves the purpose of guiding treatment choices for breast cancer patients. Patients with estrogen receptor (ER)‐positive breast cancers show significant response to endocrine therapy. However, the methods to define ER status and eligibility for treatment remain controversial. Despite recent guidelines considering staining ≥1% of tumor nuclei by immunohistology as ER‐positive, it has raised concerns on the benefit of endocrine therapy for tumors with ER 1%‐10% expression, termed “ER‐low positive”. This subgroup accounts for 3% to 9% of all patients and is likely to have unique molecular features, and therefore distinct therapeutic response to endocrine therapy compared with ER‐high positive tumors. The latest guidelines did not provide detailed descriptions for those patients, resulting in inconsistent treatment strategies. Consequently, we aimed to resolve this dilemma comprehensively. This review discusses molecular traits and recent ER‐low positive breast cancer innovations, highlighting molecular‐targeted treatment rather than traditional unified endocrine therapy for future basic and clinical research.

BackgroundIn this study, we investigated the prediction and prognostic value of SDF-1 for triple-negative breast cancer (TNBC) patients who underwent neoadjuvant chemotherapy (NAC) following standard radical surgery.MethodsA total of 303 TNBC patients were included in this study. The NAC regimen was weekly paclitaxel plus carboplatin (PC) for all patients. SDF-1 and CXCR4 expression were measured at baseline and surgery via enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC), respectively. Correlations between variables and treatment response were studied, and Cox proportional hazards regression analysis was implemented for prognostic evaluation.ResultsOf the 303 patients, 103 (34.0%) experienced pathological complete response (pCR) after completion of NAC. Serum SDF-1 expression before NAC was significantly correlated with the abundance of TILs. A higher pCR rate was more likely to be observed in patients with lower serum SDF-1 levels before NAC (P=0.001, OR=0.997, 95% CI: 0.996-0.999) and higher levels of TILs (P=0.005). In the multivariate survival model for nonpCR patients, serum SDF-1 expression at surgery served as an independent prognostic value for survival (high level, HR=1.980, 95% CI: 1.170-3.350, low level was used as a reference; P=0.011). Additionally, the predictive and prognostic value of serum SDF-1 expression was significant in patients with high abundance of TILs but not in patients with low abundance of TILs.ConclusionsThis study contributes to the clarification of the value of serum SDF-1 to predict pCR and survival for TNBC patients who underwent NAC. This new serum marker, together with TILs, might help identify clinical subtypes of TNBC with different treatment responses and survival and play an important role in tailoring and modifying the NAC strategy for advanced TNBCs in the future.

Background Despite the success of HER2-targeted therapy in achieving prolonged survival in approximately 50% of treated individuals, treatment resistance is still an important challenge for HER2+ breast cancer (BC) patients. The influence of both adaptive and innate immune responses on the therapeutic outcomes of HER2+BC patients has been extensively demonstrated.Methods Long non-coding RNAs expressed in non-pathological complete response (pCR) HER2 positive BC were screened and validated by RNA-seq. Survival analysis were made by Kaplan-Meier method. Cell death assay and proliferation assay were performed to confirm the phenotype of LINC00624. RT-qPCR and western blot were used to assay the IFN response. Xenograft mouse model were used for in vivo confirmation of anti-neu treatment resistance. RNA pull-down and immunoblot were used to confirm the interaction of ADAR1 and LINC00624. ADAR1 recombinant protein were purified from baculovirus expression system. B16-OVA cells were used to study antigen presentation both in vitro and in vivo. Flow cytometry was used to determine the tumor infiltrated immune cells of xenograft model. Antisense oligonucleotides (ASOs) were used for in vivo treatment.Results In this study, we found that LINC00624 blocked the antitumor effect of HER2- targeted therapy both in vitro and in vivo by inhibiting type I interferon (IFN) pathway activation. The double-stranded RNA-like structure of LINC00624 can bind and be edited by the adenosine (A) to inosine (I) RNA-editing enzyme adenosine deaminase RNA specific 1 (ADAR1), and this editing has been shown to release the growth inhibition and attenuate the innate immune response caused by the IFN response. Notably, LINC00624 promoted the stabilization of ADAR1 by inhibiting its ubiquitination-induced degradation triggered by β-TrCP. In contrast, LINC00624 inhibited major histocompatibility complex (MHC) class I antigen presentation and limited CD8+T cell infiltration in the cancer microenvironment, resulting in immune checkpoint blockade inhibition and anti-HER2 treatment resistance mediated through ADAR1.Conclusions In summary, these results suggest that LINC00624 is a cancer immunosuppressive lncRNA and targeting LINC00624 through ASOs in tumors expressing high levels of LINC00624 has great therapeutic potential in future clinical applications.

Abstract Immunotherapies play critical roles in cancer treatment. However, given that only a few patients respond to immune checkpoint blockades and other immunotherapeutic strategies, more novel technologies are needed to decipher the complicated interplay between tumor cells and the components of the tumor immune microenvironment (TIME). Tumor immunomics refers to the integrated study of the TIME using immunogenomics, immunoproteomics, immune-bioinformatics, and other multi-omics data reflecting the immune states of tumors, which has relied on the rapid development of next-generation sequencing. High-throughput genomic and transcriptomic data may be utilized for calculating the abundance of immune cells and predicting tumor antigens, referring to immunogenomics. However, as bulk sequencing represents the average characteristics of a heterogeneous cell population, it fails to distinguish distinct cell subtypes. Single-cell-based technologies enable better dissection of the TIME through precise immune cell subpopulation and spatial architecture investigations. In addition, radiomics and digital pathology-based deep learning models largely contribute to research on cancer immunity. These artificial intelligence technologies have performed well in predicting response to immunotherapy, with profound significance in cancer therapy. In this review, we briefly summarize conventional and state-of-the-art technologies in the field of immunogenomics, single-cell and artificial intelligence, and present prospects for future research.

Abstract Tumors are not only aggregates of malignant cells but also well-organized complex ecosystems. The immunological components within tumors, termed the tumor immune microenvironment (TIME), have long been shown to be strongly related to tumor development, recurrence and metastasis. However, conventional studies that underestimate the potential value of the spatial architecture of the TIME are unable to completely elucidate its complexity. As innovative high-flux and high-dimensional technologies emerge, researchers can more feasibly and accurately detect and depict the spatial architecture of the TIME. These findings have improved our understanding of the complexity and role of the TIME in tumor biology. In this review, we first epitomized some representative emerging technologies in the study of the spatial architecture of the TIME and categorized the description methods used to characterize these structures. Then, we determined the functions of the spatial architecture of the TIME in tumor biology and the effects of the gradient of extracellular nonspecific chemicals (ENSCs) on the TIME. We also discussed the potential clinical value of our understanding of the spatial architectures of the TIME, as well as current limitations and future prospects in this novel field. This review will bring spatial architectures of the TIME, an emerging dimension of tumor ecosystem research, to the attention of more researchers and promote its application in tumor research and clinical practice.

BackgroundBreast cancer is one of the leading causes of cancer-related death among women, and the pathological status of axillary lymph nodes is an important predictor of prognosis. However, the mechanism involved in this early stage of metastasis remains largely unknown.MethodsMicroarray analysis was used to carry out differential genomics analyses between matched pairs of metastatic sentinel lymph node tissues and breast primary tumors. The CRISPR/Cas9 gene editing system was used for in vivo screening by transplanting a loss-of-function cell pool into immunocompromised mice. MAGeCK was used to analyze the screening results. Survival analysis was performed via the Kaplan–Meier method. Cell proliferation, wound healing, migration and invasion assays were performed to confirm the phenotype. A tail vein model and subcutaneous xenotransplanted tumor model were used for the in vivo study. The relationship between coiled-coil domain containing 102B (CCDC102B) and receptor for activated C kinase 1 (RACK1) was examined using coimmunoprecipitation, mass spectrometry, nuclear protein extraction and immunofluorescence assays. The primary biological functions and pathways related to CCDC102B were enriched by RNA sequencing.ResultsWe identified CCDC102B through screening and found that it was significantly upregulated in metastatic lesions in lymph nodes compared to matched primary tumors. Increased expression of CCDC102B promoted breast cancer metastasis in vitro and in vivo. Additionally, high expression of CCDC102B was correlated with poor clinical outcomes in breast cancer patients. We further identified that CCDC102B was stabilized by the loss of RACK1, a protein negatively correlated with breast cancer metastasis. Mechanistically, we found that RACK1 promoted CCDC102B lysosomal degradation by mediating chaperone-mediated autophagy (CMA). The aggressive behavior of CCDC102B in breast cancer cells could be reversed by the expression of RACK1. Moreover, CCDC102B was correlated with the significant enrichment of NF-κB pathway components. Overexpressing CCDC102B led to less interaction between RACK1 and IKKa. Thus, CCDC102B positively regulates the NF−κB pathway by interacting with RACK1.ConclusionTaken together, our findings uncover a novel role of CCDC102B in breast cancer metastasis. CCDC102B serves as a potential metastasis promoter by regulating the activation of the NF-κB pathway and can be degraded by RACK1 via CMA.

BackgroundThe optimal (neo)adjuvant regimen for human epidermal growth factor receptor-2 (HER2)-positive breast cancer regarding survival outcomes remains unclear.MethodsWe searched Web of Science, PubMed, and the Cochrane Central Register of Controlled Trials systematically to find out randomized controlled studies, up to January 2022, that compared different anti-HER2 regimens in the (neo)adjuvant setting. The primary endpoint was disease-free survival (DFS). We used a Bayesian statistical model to combine direct and indirect comparisons and used odds ratios (ORs) to pool effect sizes and performed the surface under the cumulative ranking area (SUCRA) curves to estimate the ranking probabilities of various regimens. For survival outcomes, we performed two parallel analyses, one based on data from both neoadjuvant and adjuvant studies and the other specific to adjuvant studies. All statistics were two-sided.ResultsFifteen studies were finally enrolled. Regarding DFS, the overall analysis indicated that the top two regimens for HER2-positive breast cancer were chemotherapy plus trastuzumab with lapatinib, and chemotherapy plus trastuzumab with pertuzumab (SUCAR of 81% and 79%, respectively), with the OR of 0.99 [95% confidence interval (CI), 0.59 to 1.54]; the parallel analysis specific to adjuvant trials indicated that the top two regimens were chemotherapy plus trastuzumab with sequential neratinib, and chemotherapy plus trastuzumab with pertuzumab (SUCRA of 80% and 76%, respectively), with the OR of 1.04 (95% CI, 0.63 to 1.73). The dual-target therapy that combines trastuzumab and pertuzumab showed the highest risk of inducing cardiac events, with an SUCRA of 92%.ConclusionsChemotherapy plus trastuzumab and pertuzumab might be the optimal regimen for HER2-positive breast cancer in improving the survival rate. However, the cardiotoxicity of this dual-target therapy should be taken care of.

Abstract Background Triple-negative breast cancer (TNBC) is a heterogeneous disease and we have previously shown that rapid relapse of TNBC is associated with distinct sociodemographic features. We hypothesized that rapid versus late relapse in TNBC is also defined by distinct clinical and genomic features of primary tumors. Methods Using three publicly-available datasets, we identified 453 patients diagnosed with primary TNBC with adequate follow-up to be characterized as ‘rapid relapse’ (rrTNBC; distant relapse or death ≤2 years of diagnosis), ‘late relapse’ (lrTNBC; > 2 years) or ‘no relapse’ (nrTNBC: > 5 years no relapse/death). We explored basic clinical and primary tumor multi-omic data, including whole transcriptome (n = 453), and whole genome copy number and mutation data for 171 cancer-related genes (n = 317). Association of rapid relapse with clinical and genomic features were assessed using Pearson chi-squared tests, t-tests, ANOVA, and Fisher exact tests. We evaluated logistic regression models of clinical features with subtype versus two models that integrated significant genomic features. Results Relative to nrTNBC, both rrTNBC and lrTNBC had significantly lower immune signatures and immune signatures were highly correlated to anti-tumor CD8 T-cell, M1 macrophage, and gamma-delta T-cell CIBERSORT inferred immune subsets. Intriguingly, lrTNBCs were enriched for luminal signatures. There was no difference in tumor mutation burden or percent genome altered across groups. Logistic regression mModels that incorporate genomic features significantly outperformed standard clinical/subtype models in training (n = 63 patients), testing (n = 63) and independent validation (n = 34) cohorts, although performance of all models were overall modest. Conclusions We identify clinical and genomic features associated with rapid relapse TNBC for further study of this aggressive TNBC subset.

Summary: Immune checkpoint inhibitor (ICI) therapy is generating remarkable responses in individuals with cancer, but only a small portion of individuals with breast cancer respond well. Here we report that tumor-derived Jagged1 is a key regulator of the tumor immune microenvironment. Jagged1 promotes tumorigenesis in multiple spontaneous mammary tumor models. Through Jagged1-induced Notch activation, tumor cells increase expression and secretion of multiple cytokines to help recruit macrophages into the tumor microenvironment. Educated macrophages crosstalk with tumor-infiltrating T cells to inhibit T cell proliferation and tumoricidal activity. In individuals with triple-negative breast cancer, a high expression level of Jagged1 correlates with increased macrophage infiltration and decreased T cell activity. Co-administration of an ICI PD-1 antibody with a Notch inhibitor significantly inhibits tumor growth in breast cancer models. Our findings establish a distinct signaling cascade by which Jagged1 promotes adaptive immune evasion of tumor cells and provide several possible therapeutic targets.

Background: For estrogen receptor–positive (ER+)/human epidermal growth factor receptor 2–negative (HER2–) advanced breast cancer (ABC), the current standard first-line treatment includes an aromatase inhibitor in combination with a cyclin-dependent kinase 4/6 inhibitor. When resistance occurs, often related to the occurrence of ESR1 mutations, selective estrogen receptor modulators or degraders (SERDs) may be used, alone or in combination regimens. Amcenestrant (SAR439859), an optimized oral SERD, has shown clinical antitumor activity in combination with palbociclib in patients with ER+/HER2– ABC and, as monotherapy, in patients with and without ESR1 mutations. Here, we describe the study design of AMEERA-5, an ongoing, prospective, phase 3, randomized, double-blind, multinational study comparing the efficacy and safety of amcenestrant plus palbociclib versus letrozole plus palbociclib in patients with advanced (locoregional recurrent or metastatic) ER+/HER2– breast cancer. Methods: Patients are pre-/postmenopausal women and men with no prior systemic therapy for ABC. The planned enrollment is 1066 patients. Patients are randomized 1:1 to either amcenestrant 200 mg plus palbociclib 125 mg or letrozole 2.5 mg plus palbociclib 125 mg. Amcenestrant, letrozole, and their matching placebos are taken once daily continuously; palbociclib is taken once daily for 21 days, followed by 7 days off-treatment for a 28-day cycle. Treatment continues until disease progression, unacceptable toxicity, or decision to stop treatment. Pre-/perimenopausal women and men receive goserelin subcutaneously. Randomization is stratified by de novo metastatic disease, menopausal status, and visceral metastases. The primary endpoint is progression-free survival. The key secondary endpoint is overall survival; others are safety, pharmacokinetics, and quality of life. Conclusions: AMEERA-5 is evaluating the efficacy and safety of amcenestrant in combination with palbociclib as first-line therapy in pre-/postmenopausal women and men with ER+/HER2– ABC. ClinicalTrials Identifier: NCT04478266.

Chinese breast cancer patients have not been well represented in clinical sequencing studies. Here the authors analyse the mutational landscape of 1,134 Chinese breast cancer patients, finding actionable targets and a higher prevalence of p53 and Hippo pathway mutations compared to Western cohorts.

Abstract The tumor microenvironment is highly complex, and immune escape is currently considered an important hallmark of cancer, largely contributing to tumor progression and metastasis. Named for their capability of killing target cells autonomously, natural killer (NK) cells serve as the main effector cells toward cancer in innate immunity and are highly heterogeneous in the microenvironment. Most current treatment options harnessing the tumor microenvironment focus on T cell-immunity, either by promoting activating signals or suppressing inhibitory ones. The limited success achieved by T cell immunotherapy highlights the importance of developing new-generation immunotherapeutics, for example utilizing previously ignored NK cells. Although tumors also evolve to resist NK cell-induced cytotoxicity, cytokine supplement, blockade of suppressive molecules and genetic engineering of NK cells may overcome such resistance with great promise in both solid and hematological malignancies. In this review, we summarized the fundamental characteristics and recent advances of NK cells within tumor immunometabolic microenvironment, and discussed potential application and limitations of emerging NK cell-based therapeutic strategies in the era of presicion medicine.

Abstract Background Estrogen receptor-positive (ER+) breast cancers represent approximately two-thirds of all breast cancers and have a sustained risk of late disease recurrence. Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors have shown significant efficacy in ER+ breast cancer. However, their effects are still limited by drug resistance. In this study, we aim to explore the role of long noncoding RNA TROJAN in ER+ breast cancer. Methods The expression level of TROJAN in breast cancer tissue and cell lines was determined by quantitative real-time PCR. In vitro and in vivo assays as well as patient derived organoid were preformed to explore the phenotype of TROJAN in ER+ breast cancer. The TROJAN-NKRF-CDK2 axis were screened and validated by RNA pull-down, mass spectrometry, RNA immunoprecipitation, microarray, dual-luciferase reporter and chromatin immunoprecipitation assays. Results Herein, we showed that TROJAN was highly expressed in ER+ breast cancer. TROJAN promoted cell proliferation and resistance to a CDK4/6 inhibitor and was associated with poor survival in ER+ breast cancer. TROJAN can bind to NKRF and inhibit its interaction with RELA, upregulating the expression of CDK2. The inhibition of TROJAN abolished the activity of CDK2, reversing the resistance to CDK4/6 inhibitor. A TROJAN antisense oligonucleotide sensitized breast cancer cells and organoid to the CDK4/6 inhibitor palbociclib both in vitro and in vivo. Conclusions TROJAN promotes ER+ breast cancer proliferation and is a potential target for reversing CDK4/6 inhibitor resistance.

Abstract Background The associations between socioeconomic statuses and survival outcomes of breast cancer remain unclear. No model has included both histological and socioeconomic factors to predict the survival of breast cancer. This study was designed to develop nomograms to predict breast cancer–specific survival (BCSS) and overall survival (OS) with consideration of socioeconomic factors for breast cancer patients. Materials and methods We included a total of 207 749 female patients, diagnosed with malignant breast cancer between 2007 and 2012 from the Surveillance, Epidemiology, and End Results database. BCSS and OS were evaluated with Gray's test and log‐rank tests, respectively. Marital statuses, insurance statuses, residence, median household income, poverty rate, unemployment rate, and education level were included as socioeconomic factors in univariate and multivariate Cox regression analyses. Clinicopathological factors and socioeconomic factors were integrated to construct nomograms. Calibration plots and concordance indexes (C‐indexes) were used to evaluate the accuracy and discrimination of the models. Results Four and three socioeconomic factors were involved in constructing the nomograms for 3‐, 5‐, and 7‐year BCSS and OS, respectively. The C‐indexes of the final nomograms were higher than those of the TNM staging system for predicting BCSS (0.835 vs 0.782; P

Background: Metastatic regional lymph nodes (LN) is a strong predictor of worse long-term outcome. Therefore, different LN staging systems have been proposed in recent years. In this study, we proposed a modified lymph node ratio (mLNR) as a new lymph node staging system and then compared the prognostic performance of mLNR with American Joint Committee on Cancer N stage, lymph node ratio (LNR) and log odds of metastatic lymph nodes in breast cancer patients. Methods: Breast cancer patients who underwent surgery between 2004 and 2012 were identified from the Surveillance, Epidemiology, and End Results database. Restricted cubic spline functions were calculated to characterize the association between variables and the risk of death. The Cox proportional hazards models were constructed to assess the predictive ability of different lymph node staging systems using the Akaike’s Information Criterion (AIC) and Harrell’s concordance index (C-index). Results: A total of 264,096 breast cancer patients were enrolled and 187,785 (71.1%) patients had a limited number of LNs harvested. In the limited LN harvest cohort, the prognostic performance of LNR decreased and mLNR could greatly solve this problem. In addition, among the entire cohort, mLNR modeled as a continuous value had the best predictive ability (AIC: 922021.9 and C-index: 0.727) than other lymph node staging systems. Conclusions: The predictive ability of LNR is restricted by a limited LN harvest. However, mLNR shows superiority to LNR and other lymph node staging systems especially in a limited LN harvest cohort, making mLNR the most powerful lymph node staging systems.

Abstract Decondesation of the highly compacted chromatin architecture is essential for efficient DNA repair, but how this is achieved remains largely unknown. Here, we report that microrchidia family CW-type zinc finger protein 2 (MORC2), a newly identified ATPase-dependent chromatin remodeling enzyme, is required for nucleosome destabilization after DNA damage through loosening the histone-DNA interaction. Depletion of MORC2 attenuates phosphorylated histone H2AX (γH2AX) focal formation, compromises the recruitment of DNA repair proteins, BRCA1, 53BP1, and Rad51, to sites of DNA damage, and consequently reduces cell survival following treatment with DNA-damaging chemotherapeutic drug camptothecin (CPT). Furthermore, we demonstrate that MORC2 can form a homodimer through its C-terminal coiled-coil (CC) domain, a process that is enhanced in response to CPT-induced DNA damage. Deletion of the C-terminal CC domain in MORC2 disrupts its homodimer formation and impairs its ability to destabilize histone-DNA interaction after DNA damage. Consistently, expression of dimerization-defective MORC2 mutant results in impaired the recruitment of DNA repair proteins to damaged chromatin and decreased cell survival after CPT treatment. Together, these findings uncover a new mechanism for MORC2 in modulating chromatin dynamics and DDR signaling through its c-terminal dimerization.

Abstract Background The majority of breast cancer patients die of metastasis rather than primary tumors, whereas the molecular mechanisms orchestrating cancer metastasis remains poorly understood. Long noncoding RNAs (lncRNA) have been shown to regulate cancer occurrence and progression. However, the lncRNAs that drive metastasis in cancer patients and their underlying mechanisms are still largely unknown. Methods lncRNAs highly expressed in metastatic lymph nodes were identified by microarray. Survival analysis were made by Kaplan-Meier method. Cell proliferation, migration, and invasion assay was performed to confirm the phenotype of LINC02273. Tail vein model and mammary fat pad model were used for in vivo study. RNA pull-down and RIP assay were used to confirm the interaction of hnRNPL and LINC02273. Chromatin isolation by RNA purification followed by sequencing (ChIRP-seq), RNA-seq, ChIP-seq, and luciferase reporter assay reveal hnRNPL-LINC02273 regulates AGR2. Antisense oligonucleotides were used for in vivo treatment. Results We identified a novel long noncoding RNA LINC02273, whose expression was significantly elevated in metastatic lesions compared to the primary tumors, by genetic screen of matched tumor samples. Increased LINC02273 promoted breast cancer metastasis in vitro and in vivo. We further showed that LINC02273 was stabilized by hnRNPL, a protein increased in metastatic lesions, in breast cancer cells. Mechanistically, hnRNPL-LINC02273 formed a complex which activated AGR2 transcription and promoted cancer metastasis. The recruitment of hnRNPL-LINC02273 complex to AGR2 promoter region epigenetically upregulated AGR2 by augmenting local H3K4me3 and H3K27ac levels. Combination of AGR2 and LINC02273 was an independent prognostic factor for predicting breast cancer patient survival. Moreover, our data revealed that LINC02273-targeting antisense oligonucleotides (ASO) substantially inhibited breast cancer metastasis in vivo. Conclusions Our findings uncover a key role of LINC02273-hnRNPL-AGR2 axis in breast cancer metastasis and provide potential novel therapeutic targets for metastatic breast cancer intervention.

Abstract Background Few studies have discussed the contradictory roles of mutated‐PI3Kα in HER2‐positive (HER2+) breast cancer. Thus, we characterised the adaptive roles of PI3Kα mutations among HER2+ tumour progression. Methods We conducted prospective clinical sequencing of 1923 Chinese breast cancer patients and illustrated the clinical significance of PIK3CA mutations in locally advanced and advanced HER2+ cohort. A high‐throughput PIK3CA mutations‐barcoding screen was performed to reveal impactful mutation sites in tumour growth and drug responses. Results PIK3CA mutations acted as a protective factor in treatment‐naïve patients; however, advanced/locally advanced patients harbouring mutated‐PI3Kα exhibited a higher progressive disease rate (100% vs. 15%, p = .000053) and a lower objective response rate (81.7% vs. 95.4%, p = .0008) in response to trastuzumab‐based therapy. Meanwhile, patients exhibiting anti‐HER2 resistance had a relatively high variant allele fraction (VAF) of PIK3CA mutations; we defined the VAF > 12.23% as a predictor of poor anti‐HER2 neoadjuvant treatment efficacy. Pooled mutations screen revealed that specific PI3Kα mutation alleles mediated own biological effects. PIK3CA functional mutations suppressed the growth of HER2+ cells, but conferred anti‐HER2 resistance, which can be reversed by the PI3Kα‐specific inhibitor BYL719. Conclusions We proposed adaptive treatment strategies that the mutated PIK3CA and amplified ERBB2 should be concomitantly inhibited when exposing to continuous anti‐HER2 therapy, while the combination of anti‐HER2 and anti‐PI3Kα treatment was not essential for anti‐HER2 treatment‐naïve patients. These findings improve the understanding of genomics‐guided treatment in the different progressions of HER2+ breast cancer.

Background: The microenvironment of triple-negative breast cancer (TNBC) can be divided into three clusters based on bioinformatics-based immunogenomic analysis: the “immune-desert” cluster, the “innate immune-inactivated” cluster, and the “immune-inflamed” cluster. The immune-inflamed cluster is considered as “hot tumor” while the other two are considered as “cold tumor”.Methods: To investigate the prognostic effect of microenvironment phenotypes on TNBC, we compared relapse-free survival (RFS) of different phenotypes in 100 patients with RNA sequencing-based expression data from the PATTERN trial (NCT01216111, published in JAMA Oncol 2020), which indicated a superior efficacy of adjuvant paclitaxel-plus-carboplatin regimen compared to the regimen of cyclophosphamide/epirubicin/fluorouracil followed by docetaxel for TNBC. We also analyzed the efficacy of the two regimens for different immune phenotypes to explore potential treatment strategies.Results: No significant difference in RFS was observed between the “hot tumor” and the “cold tumor” (hazard ratio [HR] = 0.68, 95% confidence interval [CI] 0.28–1.66, P = 0.40). However, the “hot tumor” subtype was associated with significantly longer RFS in node-positive patients (HR = 0.27, 95%CI 0.07–0.97, P = 0.03). Consistently, a similar trend to improved RFS of the “hot tumor” phenotype was detected in patients with stage pT2-3 tumors (HR = 0.29, 95%CI 0.06–1.30, P = 0.08). Furthermore, no significant difference in RFS between the two treatment arms was observed in patients with “hot tumor” (HR = 0.39, 95% CI 0.08–2.01, P = 0.24) or “cold tumor” (HR = 1.05, 95% CI 0.39–2.82, P = 0.92).Conclusion: The microenvironment phenotype in TNBC might have prognostic significance to patients with a high risk of recurrence. The association of the microenvironment phenotypes with the efficacy of adjuvant chemotherapy for TNBC remains to be further studied.