The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes

Integrative modeling uncovers p21-driven drug resistance and prioritizes therapies for PIK3CA-mutant breast cancer

Utility of PI3Kα inhibitors like BYL719 is limited by the acquisition of genetic and non-genetic mechanisms of resistance which cause disease recurrence. Several combination therapies based on PI3K inhibition have been proposed, but a way to systematically prioritize them for breast cancer treatment is still missing. By integrating published and in-house studies, we have developed in silico models that quantitatively capture dynamics of PI3K signaling at the network-level under a BYL719-sensitive versus BYL719 resistant-cell state. Computational predictions show that signal rewiring to alternative components of the PI3K pathway promote resistance to BYL719 and identify PDK1 as the most effective co-target with PI3Kα rescuing sensitivity of resistant cells to BYL719. To explore whether PI3K pathway-independent mechanisms further contribute to BYL719 resistance, we performed phosphoproteomics and found that selection of high levels of the cell cycle regulator p21 unexpectedly promoted drug resistance in T47D cells. Functionally, high p21 levels favored repair of BYL719-induced DNA damage and bypass of the associated cellular senescence. Importantly, targeted inhibition of the check-point inhibitor CHK1 with MK-8776 effectively caused death of p21-high T47D cells, thus establishing a new vulnerability of BYL719-resistant breast cancer cells. Together, our integrated studies uncover hidden molecular mediators causing resistance to PI3Kα inhibition and provide a framework to prioritize combination therapies for PI3K-mutant breast cancer.

Differential Expression of NOTCH-1 and Its Molecular Targets in Response to Metronomic Followed by Conventional Therapy in a Patient with Advanced Triple-Negative Breast Cancer

A group of 27 patients diagnosed with metastatic triple-negative breast cancer (mTNBC) was randomly distributed into two groups and underwent different lines of metronomic treatment (mCHT). The former group (N 14) received first-line mCHT and showed a higher overall survival rate than the second group (N 13), which underwent second-line mCHT. Analysis of one patient still alive from the first group, diagnosed with mTNBC in 2019, showed a complete metabolic response (CMR) after a composite approach implicating first-line mCHT followed by second-line epirubicin and third-line nab-paclitaxel, and was chosen for subsequent molecular characterization. We found altered expression in the cancer stemness-associated gene NOTCH-1 and its corresponding protein. Additionally, we found changes in the expression of oncogenes, such as MYC and AKT, along with their respective proteins. Overall, our data suggest that a first-line treatment with mCHT followed by MTD might be effective by negatively regulating stemness traits usually associated with the emergence of drug resistance.

Prognostic Markers in Tyrosine Kinases Specific to Basal-like 2 Subtype of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC), a heterogeneous and therapeutically challenging subtype, comprises over 50% of patients categorized into basal-like 1 (BL1) and basal-like 2 (BL2) intrinsic molecular subtypes. Despite their shared basal-like classification, BL2 is associated with a poor response to neoadjuvant chemotherapy and reduced relapse-free survival compared to BL1. Here, the study focused on identifying subtype-specific markers for BL2 through transcriptomic analysis of TNBC patients using RNA-seq and clinical integration. Six receptor tyrosine kinase (TK) genes, including EGFR, EPHA4, EPHB2, PDGFRA, PDGFRB, and ROR1, were identified as potential differentiators for BL2. Correlations between TK mRNA expression and TNBC prognosis, particularly EGFR, PDGFRA, and PDGFRB, revealed potential synergistic interactions in pathways related to cell survival and proliferation. Our findings also suggest promising dual markers for predicting disease prognosis. Furthermore, RT-qPCR validation demonstrated that identified BL2-specific TKs were expressed at a higher level in BL2 than in BL1 cell lines, providing insights into unique characteristics. This study advances the understanding of TNBC heterogeneity within the basal-like subtypes, which could lead to novel clinical treatment approaches and the development of targeted therapies.

Comprehensive genomic evaluation of advanced and recurrent breast cancer patients for tailored precision treatments

AIM

The aim of this study was to investigate genetic alterations within breast cancer in the setting of recurrent or de novo stage IV disease.

PATIENTS AND METHODS

This study included 22 patients with recurrent breast cancer (n = 19) and inoperable de novo stage IV breast cancer (n = 3). For next generation sequencing, FoundationOneCDx (F1CDx) (Foundation Medicine Inc., Cambridge, MA, USA) was performed in 21 patients and FoundationOneLiquid CDx was performed in 1 patient.

RESULTS

Median age was 62.9 years (range, 33.4-82.1). Pathological diagnoses of specimens included invasive ductal carcinoma (n = 19), invasive lobular carcinoma (n = 2), and invasive micropapillary carcinoma (n = 1). F1CDx detected a median of 4.5 variants (range, 1-11). The most commonly altered gene were PIK3CA (n = 9), followed by TP53 (n = 7), MYC (n = 4), PTEN (n = 3), and CDH1 (n = 3). For hormone receptor-positive patients with PIK3CA mutations, hormonal treatment plus a phosphoinositide 3-kinase inhibitor was recommended as the treatment of choice. Patients in the hormone receptor-negative and no human epidermal growth factor receptor 2 expression group had significantly higher tumor mutational burden than patients in the hormone receptor-positive group. A BRCA2 reversion mutation was revealed by F1CDx in a patient with a deleterious germline BRCA2 mutation during poly ADP ribose polymerase inhibitor treatment.

CONCLUSION

Guidance on tailored precision therapy with consideration of genomic mutations was possible for some patients with information provided by F1CDx. Clinicians should consider using F1CDx at turning points in the course of the disease.

Circulating tumour mutation detection in triple-negative breast cancer as an adjunct to tissue response assessment

Circulating tumour DNA (ctDNA) detection via liquid biopsy is an emerging alternative to tissue biopsy, but its potential in treatment response monitoring and prognosis in triple negative breast cancer (TNBC) is not yet well understood. Here we determined the prevalence of actionable mutations detectable in ctDNA using a clinically validated cancer gene panel assay in patients with TNBC, without recurrence at the time of study entry. Sequencing of plasma DNA and validation of variants from 130 TNBC patients collected within 7 months of primary treatment completion revealed that 7.7% had detectable residual disease with a hotspot panel. Among neoadjuvant treated patients, we observed a trend where patients with incomplete pathologic response and positive ctDNA within 7 months of treatment completion were at much higher risk of reduced progression free survival. We propose that a high risk subset of early TNBC patients treated in neoadjuvant therapy protocols may be identifiable by combining tissue response and sensitive ctDNA detection.

Identification of a Notch transcriptomic signature for breast cancer

BACKGROUND

Dysregulated Notch signalling contributes to breast cancer development and progression, but validated tools to measure the level of Notch signalling in breast cancer subtypes and in response to systemic therapy are largely lacking. A transcriptomic signature of Notch signalling would be warranted, for example to monitor the effects of future Notch-targeting therapies and to learn whether altered Notch signalling is an off-target effect of current breast cancer therapies. In this report, we have established such a classifier.

METHODS

To generate the signature, we first identified Notch-regulated genes from six basal-like breast cancer cell lines subjected to elevated or reduced Notch signalling by culturing on immobilized Notch ligand Jagged1 or blockade of Notch by γ-secretase inhibitors, respectively. From this cadre of Notch-regulated genes, we developed candidate transcriptomic signatures that were trained on a breast cancer patient dataset (the TCGA-BRCA cohort) and a broader breast cancer cell line cohort and sought to validate in independent datasets.

RESULTS

An optimal 20-gene transcriptomic signature was selected. We validated the signature on two independent patient datasets (METABRIC and Oslo2), and it showed an improved coherence score and tumour specificity compared with previously published signatures. Furthermore, the signature score was particularly high for basal-like breast cancer, indicating an enhanced level of Notch signalling in this subtype. The signature score was increased after neoadjuvant treatment in the PROMIX and BEAUTY patient cohorts, and a lower signature score generally correlated with better clinical outcome.

CONCLUSIONS

The 20-gene transcriptional signature will be a valuable tool to evaluate the response of future Notch-targeting therapies for breast cancer, to learn about potential effects on Notch signalling from conventional breast cancer therapies and to better stratify patients for therapy considerations.

Metabolic switch regulates lineage plasticity and induces synthetic lethality in triple-negative breast cancer

Metabolic reprogramming is key for cancer development, yet the mechanism that sustains triple-negative breast cancer (TNBC) cell growth despite deficient pyruvate kinase M2 (PKM2) and tumor glycolysis remains to be determined. Here, we find that deficiency in tumor glycolysis activates a metabolic switch from glycolysis to fatty acid β-oxidation (FAO) to fuel TNBC growth. We show that, in TNBC cells, PKM2 directly interacts with histone methyltransferase EZH2 to coordinately mediate epigenetic silencing of a carnitine transporter, SLC16A9. Inhibition of PKM2 leads to impaired EZH2 recruitment to SLC16A9, and in turn de-represses SLC16A9 expression to increase intracellular carnitine influx, programming TNBC cells to an FAO-dependent and luminal-like cell state. Together, these findings reveal a new metabolic switch that drives TNBC from a metabolically heterogeneous-lineage plastic cell state to an FAO-dependent-lineage committed cell state, where dual targeting of EZH2 and FAO induces potent synthetic lethality in TNBC.

MRCK as a Potential Target for Claudin-Low Subtype of Breast Cancer

To find new molecular targets for triple negative breast cancer (TNBC), we analyzed a large-scale drug screening dataset based on breast cancer subtypes. We discovered that BDP-9066, a specific MRCK inhibitor (MRCKi), may be an effective drug against TNBC. After confirming the efficacy and specificity of BDP-9066 against TNBC in vitro and in vivo, we further analyzed the underlying mechanism of specific activity of BDP-9066 against TNBC. Comparing the transcriptome of BDP-9066-sensitive and -resistant cells, the activation of the focal adhesion and YAP/TAZ pathway were found to play an important role in the sensitive cells. Furthermore, YAP/TAZ is indeed repressed by BDP-9066 in the sensitive cells, and active form of YAP suppresses the effects of BDP-9066. YAP/TAZ expression and activity are high in TNBC, especially the Claudin-low subtype, consistent with the expression of focal adhesion-related genes. Interestingly, NF-κB functions downstream of YAP/TAZ in TNBC cells and is suppressed by BDP-9066. Furthermore, the PI3 kinase pathway adversely affected the effects of BDP-9066 and that alpelisib, a PI3 kinase inhibitor, synergistically increased the effects of BDP-9066, in PIK3CA mutant TNBC cells. Taken together, we have shown for the first time that MRCKi can be new drugs against TNBC, particularly the Claudin-low subtype.

Selective inhibition of CDK9 in triple negative breast cancer

Targeted therapy for triple-negative breast cancers (TNBC) remains a clinical challenge due to tumour heterogeneity. Since TNBC have key features of transcriptionally addicted cancers, targeting transcription via regulators such as cyclin-dependent kinase 9 (CDK9) has potential as a therapeutic strategy. Herein, we preclinically tested a new selective CDK9 inhibitor (CDDD11-8) in TNBC using cell line, patient-derived organoid, and patient-derived explant models. In vitro, CDDD11-8 dose-dependently inhibited proliferation (IC50 range: 281-734 nM), induced cell cycle arrest, and increased apoptosis of cell lines, which encompassed the three major molecular subtypes of TNBC. On target inhibition of CDK9 activity was demonstrated by reduced RNAPII phosphorylation at a CDK9 target peptide and down-regulation of the MYC and MCL1 oncogenes at the mRNA and protein levels in all cell line models. Drug induced RNAPII pausing was evident at gene promoters, with strongest pausing at MYC target genes. Growth of five distinct patient-derived organoid models was dose-dependently inhibited by CDDD11-8 (IC50 range: 272-771 nM), including three derived from MYC amplified, chemo-resistant TNBC metastatic lesions. Orally administered CDDD11-8 also inhibited growth of mammary intraductal TNBC xenograft tumours with no overt toxicity in vivo (mice) or ex vivo (human breast tissues). In conclusion, our studies indicate that CDK9 is a viable therapeutic target in TNBC and that CDDD11-8, a novel selective CDK9 inhibitor, has efficacy in TNBC without apparent toxicity to normal tissues.

HTRA1 expression is associated with immune-cell infiltration and survival in breast cancer

Background

High temperature requirement A1 (HTRA1), a member of the HTRA family, is a serine peptidase involved in many crucial bioprocesses such as proliferation, mitochondrial homeostasis, apoptosis, and protein quality control. It also plays an important role in the development of various tumors. However, the potential role and mechanisms of action of HTRA1 in breast cancer (BRCA) remain unclear. We conducted a bioinformatics-based study to investigate HTRA1 expression in BRCA alongside its associations with immune-cell infiltrates and survival outcomes.

Methods

The expression of HTRA1 in BRCA samples was analyzed using RNAseq datasets from The Cancer Genome Atlas and Gene Expression Omnibus. R software was employed to assess the relationship between HTRA1 expression and clinicopathological characteristics, tumor-infiltrating immune cells, and immunity-associated biomarkers in BRCA. MethSurv and cBioPortal database were utilized to evaluate DNA methylation and genovariation within the HTRA1 DNA. Receiver operating characteristic curves, Kaplan-Meier analysis, and Cox regression were performed to estimate the impact of HTRA1 on diagnosis, prognosis, and response to chemotherapy in BRCA.

Results

HTRA1 expression was significantly downregulated in BRCA tissues compared to adjacent normal breast tissue controls. Differentially expressed genes associated with HTRA1 expression primarily enriched in cell proliferation pathways. Furthermore, altered HTRA1 expression significantly correlated with patient age, tumor histological type, T stage, progesterone receptor/estrogen receptor status, and PAM50 subtype of BRCA. Both positive and negative associations were observed between HTRA1 levels and the abundance of different types of immune cells, as well as immune biomarkers, including resting mast cells, follicular helper T cells, PD-L1, p53, and Ki67. Low HTRA1 expression was related with pathological complete response in luminal B BRCA patients undergoing chemotherapy. Additionally, lower HTRA1 expression in BRCA was associated with inferior overall survival and relapse-free survival.

Conclusions

HTRA1 expression is associated with immune-cell infiltration, response to chemotherapy, and survival outcomes in BRCA. HTRA1 has the potential to serve as a promising biomarker and therapeutic target moving forward.

Ferroptosis Inducers Upregulate PD-L1 in Recurrent Triple-Negative Breast Cancer

(1) Background: Triple-negative breast cancer (TNBC) is a distinct subgroup of breast cancer presenting a high level of recurrence, and neo-adjuvant chemotherapy is beneficial in its therapy management. Anti-PD-L1 immunotherapy improves the effect of neo-adjuvant therapy in TNBC. (2) Methods: Immune-modulation and ferroptosis-related R-packages were developed for integrative omics analyses under ferroptosis-inducer treatments: TNBC cells stimulated with ferroptosis inducers (GSE173905, GSE154425), single cell data (GSE191246) and mass spectrometry on breast cancer stem cells. Clinical association analyses were carried out with breast tumors (TCGA and METABRIC cohorts). Protein-level validation was investigated through protein atlas proteome experiments. (3) Results: Erastin/RSL3 ferroptosis inducers upregulate CD274 in TNBC cells (MDA-MB-231 and HCC38). In breast cancer, CD274 expression is associated with overall survival. Breast tumors presenting high expression of CD274 upregulated some ferroptosis drivers associated with prognosis: IDO1, IFNG and TNFAIP3. At the protein level, the induction of Cd274 and Tnfaip3 was confirmed in breast cancer stem cells under salinomycin treatment. In a 4T1 tumor treated with cyclophosphamide, the single cell expression of Cd274 was found to increase both in myeloid- and lymphoid-infiltrated cells, independently of its receptor Pdcd1. The CD274 ferroptosis-driver score computed on a breast tumor transcriptome stratified patients on their prognosis: low score was observed in the basal subgroup, with a higher level of recurrent risk scores (oncotypeDx, ggi and gene70 scores). In the METABRIC cohort, CD274, IDO1, IFNG and TNFAIP3 were found to be overexpressed in the TNBC subgroup. The CD274 ferroptosis-driver score was found to be associated with overall survival, independently of TNM classification and age diagnosis. The tumor expression of CD274, TNFAIP3, IFNG and IDO1, in a biopsy of breast ductal carcinoma, was confirmed at the protein level (4) Conclusions: Ferroptosis inducers upregulate PD-L1 in TNBC cells, known to be an effective target of immunotherapy in high-risk early TNBC patients who received neo-adjuvant therapy. Basal and TNBC tumors highly expressed CD274 and ferroptosis drivers: IFNG, TNFAIP3 and IDO1. The CD274 ferroptosis-driver score is associated with prognosis and to the risk of recurrence in breast cancer. A potential synergy of ferroptosis inducers with anti-PD-L1 immunotherapy is suggested for recurrent TNBC.

Chronic chromosome instability induced by Plk1 results in immune suppression in breast cancer

Chromosome instability (CIN) contributes to resistance to therapies and tumor evolution. Although natural killer (NK) cells can eliminate cells with complex karyotypes, high-CIN human tumors have an immunosuppressive phenotype. To understand which CIN-associated molecular features alter immune recognition during tumor evolution, we overexpress Polo-like kinase 1 (Plk1) in a Her2+ breast cancer model. These high-CIN tumors activate a senescence-associated secretory phenotype (SASP), upregulate PD-L1 and CD206, and induce non-cell-autonomous nuclear factor κB (NF-κβ) signaling, facilitating immune evasion. Single-cell RNA sequencing from pre-neoplastic mammary glands unveiled the presence of Arg1+ macrophages, NK cells with reduced effector functions, and increased resting regulatory T cell infiltration. We further show that high PLK1-expressing human breast tumors display gene expression patterns associated with SASP, NF-κβ signaling, and immune suppression. These findings underscore the need to understand the immune landscape in CIN tumors to identify more effective therapies, potentially combining immune checkpoint or NF-κβ inhibitors with current treatments.

Low CDKN1B Expression Associated with Reduced CD8+ T Lymphocytes Predicts Poor Outcome in Breast Cancer in a Machine Learning Analysis

The cyclin-dependent kinase inhibitor 1B (CDKN1B) gene, which encodes the p27Kip1 protein, is important in regulating the cell cycle process and cell proliferation. Its role in breast cancer prognosis is controversial. We evaluated the significance and predictive role of CDKN1B expression in breast cancer prognosis. We investigated the clinicopathologic factors, survival rates, immune cells, gene sets, and prognostic models according to CDKN1B expression in 3794 breast cancer patients. We performed gene set enrichment analysis (GSEA), in silico cytometry, pathway network analyses, gradient boosting machine (GBM) learning, and in vitro drug screening. High CDKN1B expression levels in breast cancer correlated with high lymphocyte infiltration signature scores and increased CD8+ T cells, both of which were associated with improved prognosis in breast cancer. which were associated with a better prognosis. CDKN1B expression was associated with gene sets for the upregulation of T-cell receptor signaling pathways and downregulation of CD8+ T cells. Pathway network analysis revealed a direct link between CDKN1B and the pathway involved in the positive regulation of the protein catabolic process pathway. In addition, an indirect link was identified between CDKN1B and the T-cell receptor signaling pathway. In in vitro drug screening, BMS-345541 demonstrated efficacy as a therapeutic targeting of CDKN1B, effectively impeding the growth of breast cancer cells characterized by low CDKN1B expression. The inclusion of CDKN1B expression in GBM models increased the accuracy of survival predictions. CDKN1B expression plays a significant role in breast cancer progression, implying that targeting CDKN1B might be a promising strategy for treating breast cancer.

Heterozygous Knockout of ARID4B Using CRISPR/Cas9 Attenuates Some Aggressive Phenotypes in a Breast Cancer Cell Line

Breast cancer is one of the leading causes of death in women around the world. Over time, many genes and mutations that are associated with the development of this disease have been identified. However, the specific role of many genes has not yet been fully elucidated. Higher ARID4B expression has been identified as a risk factor for diverse cancer types. Silencing experiments also showed that ARID4B is associated with developing cancer-associated characteristics. However, no transcriptomic studies have shown the overall cellular effect of loss of function in breast cancer in humans. This study addresses the impact of loss-of-function mutations in breast cancer MCF-7 cells. Using the CRISPR/Cas9 system, we generated mutations that caused heterozygous truncated proteins, isolating three monoclonal lines carrying insertions and deletions in ARID4B. We observed reduced proliferation and migration in in vitro experiments. In addition, from RNA-seq assays, a differential expression analysis shows known and novel deregulated cancer-associate pathways in mutated cells supporting the impact of ARID4B. For example, we found the AKT-PI3K pathway to be altered at the transcript level but through different genes than those reported for ARID4B. Our transcriptomic results also suggest new insights into the role of ARID4B in aggressiveness by the epithelial-to-mesenchymal transition and TGF-β pathways and in metabolism through cholesterol and mevalonate pathways. We also performed exome sequencing to show that no off-target effects were apparent. In conclusion, the ARID4B gene is associated with some aggressive phenotypes in breast cancer cells.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Breast cancers with high proliferation and low ER-related signalling have poor prognosis and unique molecular features with implications for therapy

BACKGROUND

Luminal breast cancers with high proliferation (MKShi) and low ER-related signalling (ERSlo) have a poor prognosis. We investigated treatment responses and molecular features of MKShi/ERSlo tumours to inform potential therapies.

METHODS

Gene expression data from patients who received neoadjuvant chemotherapy (NAC) without (MDACC, N = 199) or with pembrolizumab (I-SPY2, N = 40), or endocrine therapy (NET) without (POETIC, N = 172) or with palbociclib (NeoPalAna, N = 32) were analyzed to assess treatment response by MKS/ERS-subgroups. TCGA was used to assess the mutational landscape and biomarkers associated with palbociclib-resistance (Cyclin-E, RBsig, IRPR) and immunotherapy-response (TMB, TILs, T-cell inflamed) by MKS/ERS-subgroups.

RESULTS

Compared to MKShi/ERShi tumours, MKShi/ERSlo tumours had higher pathological response rates to NAC (22% vs 8%, p = 0.06) but a higher recurrence risk (4-year metastasis-free survival 70% vs 94%, p = 0.01). MKShi/ERSlo tumours frequently harboured TP53 (34%) and PIK3CA (33%) mutations, and showed high expression of Cyclin-E, RBsig and IRPR, high TMB and elevated TIL and T-cell inflamed metagene expression. MKShi/ERSlo tumours retained high proliferation after NET with or without palbociclib but had higher pathological complete response rates when pembrolizumab was added to NAC (42% vs 21%, p = 0.07).

CONCLUSIONS

MKShi/ERSlo tumours have dismal outcomes and are enriched in chemotherapy-sensitive but ET- and palbociclib-resistant tumours. Biomarker analysis and clinical data suggest a potential role for immunotherapy in this group.

HS-10352 in hormone receptor-positive, HER2-negative advanced breast cancer: A phase 1 dose-escalation trial

BACKGROUND

Approximately 40% of patients with hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer (ABC) exhibit PIK3CA mutations.

AIMS

This study aims to evaluate the safety, tolerability, pharmacokinetics, and preliminary antitumor activity of HS-10352, a selective PI3Kα inhibitor, in this patient population.

MATERIALS AND METHODS

Conducted as a phase 1 dose-escalation trial, HS-10352 was administered orally once-daily (QD) at dose levels of 2, 4, 6, and 8 mg. The primary endpoints were dose-limiting toxicity (DLT) and the maximum tolerated dose (MTD). This study is registered at ClinicalTrials.gov (NCT04631835).

RESULTS

Between August 2020 and March 2022, a total of 18 female patients were enrolled. DLT, manifested as hyperglycemia, occurred in two patients in the 8 mg QD group, establishing an MTD of 6 mg QD. The most common treatment-related adverse events were hyperglycemia (88.9%) and weight loss (61.3%). In the 6 mg QD group, four patients (66.7%) had a partial response (PR), and one (16.7%) had stable disease (SD). Among the four patients with PIK3CA mutated tumors in this dosage group, three (75.0%) had PR and one (25.0%) had SD. The median progression-free survival was not reached (95% confidence interval, 11.1-NA).

DISCUSSION AND CONCLUSION

HS-10352 at 6 mg QD was well-tolerated in patients with HR-positive, HER2-negative ABC, and showed preliminary antitumor activity in patients with PIK3CA mutated tumors. These findings support the further clinical development of HS-10352.

MAF amplification licenses ERα through epigenetic remodelling to drive breast cancer metastasis

MAF amplification increases the risk of breast cancer (BCa) metastasis through mechanisms that are still poorly understood yet have important clinical implications. Oestrogen-receptor-positive (ER+) BCa requires oestrogen for both growth and metastasis, albeit by ill-known mechanisms. Here we integrate proteomics, transcriptomics, epigenomics, chromatin accessibility and functional assays from human and syngeneic mouse BCa models to show that MAF directly interacts with oestrogen receptor alpha (ERα), thereby promoting a unique chromatin landscape that favours metastatic spread. We identify metastasis-promoting genes that are de novo licensed following oestrogen exposure in a MAF-dependent manner. The histone demethylase KDM1A is key to the epigenomic remodelling that facilitates the expression of the pro-metastatic MAF/oestrogen-driven gene expression program, and loss of KDM1A activity prevents this metastasis. We have thus determined that the molecular basis underlying MAF/oestrogen-mediated metastasis requires genetic, epigenetic and hormone signals from the systemic environment, which influence the ability of BCa cells to metastasize.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

Molecular targets and therapeutic strategies for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is known for its heterogeneous complexity and is often difficult to treat. TNBC lacks the expression of major hormonal receptors like estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 and is further subdivided into androgen receptor (AR) positive and AR negative. In contrast, AR negative is also known as quadruple-negative breast cancer (QNBC). Compared to AR-positive TNBC, QNBC has a great scarcity of prognostic biomarkers and therapeutic targets. QNBC shows excessive cellular growth and proliferation of tumor cells due to increased expression of growth factors like EGF and various surface proteins. This study briefly reviews the limited data available as protein biomarkers that can be used as molecular targets in treating TNBC as well as QNBC. Targeted therapy and immune checkpoint inhibitors have recently changed cancer treatment. Many studies in medicinal chemistry continue to focus on the synthesis of novel compounds to discover new antiproliferative medicines capable of treating TNBC despite the abundance of treatments currently on the market. Drug repurposing is one of the therapeutic methods for TNBC that has been examined. Moreover, some additional micronutrients, nutraceuticals, and functional foods may be able to lower cancer risk or slow the spread of malignant diseases that have already been diagnosed with cancer. Finally, nanomedicines, or applications of nanotechnology in medicine, introduce nanoparticles with variable chemistry and architecture for the treatment of cancer. This review emphasizes the most recent research on nutraceuticals, medication repositioning, and novel therapeutic strategies for the treatment of TNBC.

Correlation of an immune-related 8-gene panel with pathologic response to neoadjuvant chemotherapy in patients with primary breast cancers

Neoadjuvant chemotherapy (NACT)-induced pathologic complete response (pCR) is associated with a favorable prognosis for breast cancer. Prior research links tumor-infiltrating lymphocytes with breast cancer chemotherapy response, suggesting the tumor-immune microenvironment's role. The aim of this study was to evaluate the immune-related genes that exhibit associations with the response to NACT. In this study, we analyzed a total of 37 patients (aged 27-67) who received NACT as the first-line treatment for primary breast cancer, followed by surgery. This group consisted of nine patients (24.3 %) with estrogen receptor (ER)-positive/HER2-negative status, ten patients (27.0 %) with ER-positive/HER2-positive status, five patients (13.5 %) with ER-negative/HER2-positive status, and thirteen patients (35.1 %) with triple-negative breast cancer (TNBC). Among these patients, twelve (32.4 %) achieved a pCR, with eight (66.6 %) having HER2-positive tumors, and the remaining four having TNBC. To identify immune-related genes linked with pCR in subjects with breast cancer prior to NACT, we collected fresh tissues for next-generation sequencing. Patients with pCR had higher expressions of eight genes, KLRK1, IGJ, CD69, CD40LG, MS4A1, CD1C, KLRB1, and CA4, compared to non-pCR patients. The 8-gene signature was associated with good prognosis and linked to better relapse-free survival in patients receiving chemotherapy. The expression of these genes was involved in better drug response, displaying a positive correlation with the infiltration of immune cells. In conclusion, we have identified eight immune-related genes that are associated with a favorable prognosis and positive responses to drugs. This 8-gene signature could potentially provide prognostic insights for breast cancer patients undergoing NACT.

Coexistent ARID1A-PIK3CA mutations are associated with immune-related pathways in luminal breast cancer

Up to 40% of luminal breast cancer patients carry activating mutations in the PIK3CA gene. PIK3CA mutations commonly co-occur with other mutations, but the implication of this co-occurrence may vary according to the specific genes involved. Here, we characterized a subgroup of luminal breast cancer expressing co-mutations in ARID1A and PIK3CA genes and identified their effect on important signaling pathways. Our study included 2609 primary breast cancer samples from the TCGA and METABRIC datasets that were classified based on tumor subtype and the existence of mutations in PIK3CA and ARID1A genes. Differential expression and WGCNA analyses were performed to detect molecular modules affected by the existence of the mutations. Our results reveal various evidence for the involvement of immune-related pathways in luminal tumors harboring ARID1A and PIK3CA mutations, as well as a unique Tumor-infiltrated immune cells composition. We also identified seven key hub genes in the ARID1A-PIK3CA mutated tumors associated with immune-related pathways: CTLA4, PRF1, LCK, CD3E, CD247, ZAP70, and LCP2. Collectively, these results indicate an immune system function that may contribute to tumor survival. Our data induced a hypothesis that ARID1A and PIK3CA mutations' co-occurrence might predict responses to immunotherapy in luminal BC and, if validated, could guide immunotherapy development.

Genomic profiling and pre-clinical modelling of breast cancer leptomeningeal metastasis reveals acquisition of a lobular-like phenotype

Breast cancer leptomeningeal metastasis (BCLM), where tumour cells grow along the lining of the brain and spinal cord, is a devastating development for patients. Investigating this metastatic site is hampered by difficulty in accessing tumour material. Here, we utilise cerebrospinal fluid (CSF) cell-free DNA (cfDNA) and CSF disseminated tumour cells (DTCs) to explore the clonal evolution of BCLM and heterogeneity between leptomeningeal and extracranial metastatic sites. Somatic alterations with potential therapeutic actionability were detected in 81% (17/21) of BCLM cases, with 19% detectable in CSF cfDNA only. BCLM was enriched in genomic aberrations in adherens junction and cytoskeletal genes, revealing a lobular-like breast cancer phenotype. CSF DTCs were cultured in 3D to establish BCLM patient-derived organoids, and used for the successful generation of BCLM in vivo models. These data reveal that BCLM possess a unique genomic aberration profile and highlight potential cellular dependencies in this hard-to-treat form of metastatic disease.

Machine learning-based cluster analysis of immune cell subtypes and breast cancer survival

Host immunity involves various immune cells working in concert to achieve balanced immune response. Host immunity interacts with tumorigenic process impacting disease outcome. Clusters of different immune cells may reveal unique host immunity in relation to breast cancer progression. CIBERSORT algorithm was used to estimate relative abundances of 22 immune cell types in 3 datasets, METABRIC, TCGA, and our study. The cell type data in METABRIC were analyzed for cluster using unsupervised hierarchical clustering (UHC). The UHC results were employed to train machine learning models. Kaplan-Meier and Cox regression survival analyses were performed to assess cell clusters in association with relapse-free and overall survival. Differentially expressed genes by clusters were interrogated with IPA for molecular signatures. UHC analysis identified two distinct immune cell clusters, clusters A (83.2%) and B (16.8%). Memory B cells, plasma cells, CD8 positive T cells, resting memory CD4 T cells, activated NK cells, monocytes, M1 macrophages, and resting mast cells were more abundant in clusters A than B, whereas regulatory T cells and M0 and M2 macrophages were more in clusters B than A. Patients in cluster A had favorable survival. Similar survival associations were also observed in other independent studies. IPA analysis showed that pathogen-induced cytokine storm signaling pathway, phagosome formation, and T cell receptor signaling were related to the cell type clusters. Our finding suggests that different immune cell clusters may indicate distinct immune responses to tumor growth, suggesting their potential for disease management.

A novel coiled-coil domain containing-related gene signature for predicting prognosis and treatment effect of breast cancer

PURPOSE

Breast cancer (BRCA) is a prevalent tumor worldwide. The association between the coiled-coil domain-containing (CCDC) protein family and different tumors has been established. However, the prognostic significance of this protein family in breast cancer remains uncertain.

METHODS

Gene expression and clinical data were obtained from the TCGA, METABRIC, and GEO databases. Prognosis genes were identified using univariate Cox and LASSO Cox regression, leading to the establishment of a prognostic signature. Subsequently, the risk model was conducted based on survival and clinical feature analyses, and a nomogram for prognosis prediction was developed. Furthermore, analyses of biological function, immune characteristics, and drug sensitivity were performed. Finally, single-cell sequencing data were utilized to uncover the expression patterns of genes in the risk model.

RESULTS

Five genes were identified and utilized for risk modeling. The model demonstrated excellent prognostic value as indicated by ROC and Kaplan-Meier analysis. The high-risk group exhibited shorter survival time and higher likelihood of recurrence. Functional annotation indicated a correlation between the risk score and immune pathways. Conversely, the low-risk group displayed a greater enrichment in immune pathways and exhibited more active immune microenvironment characteristics. Additionally, drug sensitivity analysis using both public and our sequencing data revealed that the risk model possessed a broad range of predictive values.

CONCLUSIONS

We have developed a gene signature and have verified that patients with low-risk are more likely to have better prognosis and respond positively to therapy. This finding offers a valuable point of reference for BRCA individualized treatment.

Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture

Prediction of the stage of cancer plays an important role in planning the course of treatment and has been largely reliant on imaging tools which do not capture molecular events that cause cancer progression. Gene-expression data-based analyses are able to identify these events, allowing RNA-sequence and microarray cancer data to be used for cancer analyses. Breast cancer is the most common cancer worldwide, and is classified into four stages - stages 1, 2, 3, and 4 [2]. While machine learning models have previously been explored to perform stage classification with limited success, multi-class stage classification has not had significant progress. There is a need for improved multi-class classification models, such as by investigating deep learning models. Gene-expression-based cancer data is characterised by the small size of available datasets, class imbalance, and high dimensionality. Class balancing methods must be applied to the dataset. Since all the genes are not necessary for stage prediction, retaining only the necessary genes can improve classification accuracy. The breast cancer samples are to be classified into 4 classes of stages 1 to 4. Invasive ductal carcinoma breast cancer samples are obtained from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets and combined. Two class balancing techniques are explored, synthetic minority oversampling technique (SMOTE) and SMOTE followed by random undersampling. A hybrid feature selection pipeline is proposed, with three pipelines explored involving combinations of filter and embedded feature selection methods: Pipeline 1 - minimum-redundancy maximum-relevancy (mRMR) and correlation feature selection (CFS), Pipeline 2 - mRMR, mutual information (MI) and CFS, and Pipeline 3 - mRMR and support vector machine-recursive feature elimination (SVM-RFE). The classification is done using deep learning models, namely deep neural network, convolutional neural network, recurrent neural network, a modified deep neural network, and an AutoKeras generated model. Classification performance post class-balancing and various feature selection techniques show marked improvement over classification prior to feature selection. The best multiclass classification was found to be by a deep neural network post SMOTE and random undersampling, and feature selection using mRMR and recursive feature elimination, with a Cohen-Kappa score of 0.303 and a classification accuracy of 53.1%. For binary classification into early and late-stage cancer, the best performance is obtained by a modified deep neural network (DNN) post SMOTE and random undersampling, and feature selection using mRMR and recursive feature elimination, with an accuracy of 81.0% and a Cohen-Kappa score (CKS) of 0.280. This pipeline also showed improved multiclass classification performance on neuroblastoma cancer data, with a best area under the receiver operating characteristic (auROC) curve score of 0.872, as compared to 0.71 obtained in previous work, an improvement of 22.81%. The results and analysis reveal that feature selection techniques play a vital role in gene-expression data-based classification, and the proposed hybrid feature selection pipeline improves classification performance. Multi-class classification is possible using deep learning models, though further improvement particularly in late-stage classification is necessary and should be explored further.

Genomic Characterization of Aggressive Breast Cancer in Younger Women

PURPOSE

Although breast cancer (BC) risk increases with age, BC in younger women is more aggressive with higher mortality compared with older women. We characterize the genomic landscape of BCs in younger women.

METHODS

Clinicopathologic, molecular, and genomic differences across age groups (< 40 years, 40-60 years, > 60 years) in female BC patients were investigated in two large cohorts [AACR-GENIE8.1 (n = 11,594) and METABRIC (n = 2509)]. Cox-proportional regression analyzed the prognostic impact of age groups for disease-specific survival (DSS) and recurrence-free survival (RFS) in METABRIC and progression-free survival (PFS) in GENIE cohorts. Chi-squared test was used to assess statistical associations between genomic alterations and age groups.

RESULTS

Survival analysis showed that women < 40 years had shorter DSS [hazard ratio (HR): 1.52, p = 0.005], RFS (HR: 1.4, p = 0.006), and PFS (HR: 1.82, p = 0.0003) compared with women 40-60 years, and shorter RFS (HR: 1.5, p = 0.001) and PFS (HR: 2.95, p < 0.0001) compared with women > 60 years. Molecular subtypes in the METABRIC cohort showed women < 40 years were enriched with basal, and HER2+ subtypes, and less enriched with luminal A and B subtype (p < 0.0001). Characterization of genomic alterations in both cohorts demonstrated that BCs in women < 40 years were more enriched with TP53 mutations (FDR < 0.0001), BRCA1 mutations (FDR = 0.01), ERBB2 amplifications (FDR < 0.001), CDK12 amplifications (FDR < 0.001), and PPM1D amplifications (FDR < 0.001). In contrast, BCs in older women (> 60 years) were more enriched with PIK3CA, KMT2C, and CDH1 mutations (FDR < 0.0001).

CONCLUSIONS

BCs in young women are associated with shorter survival and more aggressive genomic features, including mutations in TP53 and BRCA1, and amplifications in ERBB2 and CDK12. These findings have the potential to impact clinical trial design and treatment.

Molecular Characteristics and Therapeutic Vulnerabilities of Claudin-low Breast Cancers Derived from Cell Line Models

BACKGROUND/AIM

Breast cancers constitute heterogeneous tumor groups and their categorization in subtypes based on the expression of the estrogen (ER), progesterone (PR) and HER2 receptors has advanced therapeutics. Claudin-low breast cancer has been proposed as an additional subtype which is mostly ER, PR and HER2 negative, but its identification has not led to corresponding specific treatments yet.

MATERIALS AND METHODS

Breast cancer cell lines from the Cancer Cell Line Encyclopedia (CCLE) were assessed for mRNA suppression of claudins and mRNA expression of ER and ERBB2 (the gene encoding HER2). The set of identified claudin-low cell lines were compared with representative ER-/ERBB2- cell lines for associated molecular alterations, gene dependencies through CRISPR and microRNA arrays and in vitro drug sensitivities using the Genomics of Drug Sensitivity in Cancer (GDSC) project.

RESULTS

Claudin-low cell lines display up-regulation of mRNA expression of epithelial to mesenchymal transition (EMT) regulators. Methylation sensitive genes are down-regulated in claudin-low lines compared with other cell lines, without associated up-regulation of DNA methyltransferases. Dependency screen microarrays reveal dependencies of claudin-low cell lines on components of the cytoskeleton but no consistent dependencies in known oncogenes or tumor suppressors. Potential drug sensitivities revealed in the drug screens included sensitivities to WNT pathway modulators, tyrosine kinase cascade inhibitors and BET inhibitors. On the other hand, claudin-low cell lines showed resistance to deacetylase inhibitors.

CONCLUSION

Claudin-low cell line models duplicate features of claudin-low breast cancers and may serve as guides for identification of drugs worth exploring for further development.

Targeted inhibition of Wnt signaling with a Clostridioides difficile toxin B fragment suppresses breast cancer tumor growth

Wnt signaling pathways are transmitted via 10 homologous frizzled receptors (FZD1-10) in humans. Reagents broadly inhibiting Wnt signaling pathways reduce growth and metastasis of many tumors, but their therapeutic development has been hampered by the side effect. Inhibitors targeting specific Wnt-FZD pair(s) enriched in cancer cells may reduce side effect, but the therapeutic effect of narrow-spectrum Wnt-FZD inhibitors remains to be established in vivo. Here, we developed a fragment of C. difficile toxin B (TcdBFBD), which recognizes and inhibits a subclass of FZDs, FZD1/2/7, and examined whether targeting this FZD subgroup may offer therapeutic benefits for treating breast cancer models in mice. Utilizing 2 basal-like and 1 luminal-like breast cancer models, we found that TcdBFBD reduces tumor-initiating cells and attenuates growth of basal-like mammary tumor organoids and xenografted tumors, without damaging Wnt-sensitive tissues such as bones in vivo. Furthermore, FZD1/2/7-positive cells are enriched in chemotherapy-resistant cells in both basal-like and luminal mammary tumors treated with cisplatin, and TcdBFBD synergizes strongly with cisplatin in inhibiting both tumor types. These data demonstrate the therapeutic value of narrow-spectrum Wnt signaling inhibitor in treating breast cancers.

Metabolic stratification of human breast tumors reveal subtypes of clinical and therapeutic relevance

Extensive metabolic heterogeneity in breast cancers has limited the deployment of metabolic therapies. To enable patient stratification, we studied the metabolic landscape in breast cancers (∼3000 patients combined) and identified three subtypes with increasing degrees of metabolic deregulation. Subtype M1 was found to be dependent on bile-acid biosynthesis, whereas M2 showed reliance on methionine pathway, and M3 engaged fatty-acid, nucleotide, and glucose metabolism. The extent of metabolic alterations correlated strongly with tumor aggressiveness and patient outcome. This pattern was reproducible in independent datasets and using in vivo tumor metabolite data. Using machine-learning, we identified robust and generalizable signatures of metabolic subtypes in tumors and cell lines. Experimental inhibition of metabolic pathways in cell lines representing metabolic subtypes revealed subtype-specific sensitivity, therapeutically relevant drugs, and promising combination therapies. Taken together, metabolic stratification of breast cancers can thus aid in predicting patient outcome and designing precision therapies.

Hormone Receptor Signaling and Breast Cancer Resistance to Anti-Tumor Immunity

Breast cancers regroup many heterogeneous diseases unevenly responding to currently available therapies. Approximately 70-80% of breast cancers express hormone (estrogen or progesterone) receptors. Patients with these hormone-dependent breast malignancies benefit from therapies targeting endocrine pathways. Nevertheless, metastatic disease remains a major challenge despite available treatments, and relapses frequently ensue. By improving patient survival and quality of life, cancer immunotherapies have sparked considerable enthusiasm and hope in the last decade but have led to only limited success in breast cancers. In addition, only patients with hormone-independent breast cancers seem to benefit from these immune-based approaches. The present review examines and discusses the current literature related to the role of hormone receptor signaling (specifically, an estrogen receptor) and the impact of its modulation on the sensitivity of breast cancer cells to the effector mechanisms of anti-tumor immune responses and on the capability of breast cancers to escape from protective anti-cancer immunity. Future research prospects related to the possibility of promoting the efficacy of immune-based interventions using hormone therapy agents are considered.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BACKGROUND

Breast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.

METHODS

Tumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.

RESULTS

Herein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.

CONCLUSIONS

We conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

Early-Stage Breast Cancer Detection in Breast Milk

Breast cancer occurring during pregnancy (PrBC) and postpartum (PPBC) is usually diagnosed at more advanced stages compared with other breast cancer, worsening its prognosis. PPBC is particularly aggressive, with increased metastatic risk and mortality. Thus, effective screening methods to detect early PrBC and PPBC are needed. We report for the first time that cell-free tumor DNA (ctDNA) is present in breast milk (BM) collected from patients with breast cancer. Analysis of ctDNA from BM detects tumor variants in 87% of the cases by droplet digital PCR, while variants remain undetected in 92% of matched plasma samples. Retrospective next-generation sequencing analysis in BM ctDNA recapitulates tumor variants, with an overall clinical sensitivity of 71.4% and specificity of 100%. In two cases, ctDNA was detectable in BM collected 18 and 6 months prior to standard diagnosis. Our results open up the potential use of BM as a new source for liquid biopsy for PPBC detection.

SIGNIFICANCE

For the first time, we show that BM obtained from patients with breast cancer carries ctDNA, surpassing plasma-based liquid biopsy for detection and molecular profiling of early-stage breast cancer, even prior to diagnosis by image. See related commentary by Cunningham and Turner, p. 2125. This article is featured in Selected Articles from This Issue, p. 2109.

Human basal-like breast cancer is represented by one of the two mammary tumor subtypes in dogs

BACKGROUND

About 20% of breast cancers in humans are basal-like, a subtype that is often triple-negative and difficult to treat. An effective translational model for basal-like breast cancer is currently lacking and urgently needed. To determine whether spontaneous mammary tumors in pet dogs could meet this need, we subtyped canine mammary tumors and evaluated the dog-human molecular homology at the subtype level.

METHODS

We subtyped 236 canine mammary tumors from 3 studies by applying various subtyping strategies on their RNA-seq data. We then performed PAM50 classification with canine tumors alone, as well as with canine tumors combined with human breast tumors. We identified feature genes for human BLBC and luminal A subtypes via machine learning and used these genes to repeat canine-alone and cross-species tumor classifications. We investigated differential gene expression, signature gene set enrichment, expression association, mutational landscape, and other features for dog-human subtype comparison.

RESULTS

Our independent genome-wide subtyping consistently identified two molecularly distinct subtypes among the canine tumors. One subtype is mostly basal-like and clusters with human BLBC in cross-species PAM50 and feature gene classifications, while the other subtype does not cluster with any human breast cancer subtype. Furthermore, the canine basal-like subtype recaptures key molecular features (e.g., cell cycle gene upregulation, TP53 mutation) and gene expression patterns that characterize human BLBC. It is enriched in histological subtypes that match human breast cancer, unlike the other canine subtype. However, about 33% of canine basal-like tumors are estrogen receptor negative (ER-) and progesterone receptor positive (PR+), which is rare in human breast cancer. Further analysis reveals that these ER-PR+ canine tumors harbor additional basal-like features, including upregulation of genes of interferon-γ response and of the Wnt-pluripotency pathway. Interestingly, we observed an association of PGR expression with gene silencing in all canine tumors and with the expression of T cell exhaustion markers (e.g., PDCD1) in ER-PR+ canine tumors.

CONCLUSIONS

We identify a canine mammary tumor subtype that molecularly resembles human BLBC overall and thus could serve as a vital translational model of this devastating breast cancer subtype. Our study also sheds light on the dog-human difference in the mammary tumor histology and the hormonal cycle.

Disruption of lineage integrity as a precursor to breast tumor initiation

Increase in lineage infidelity and/or imbalance is frequently observed around the earliest stage of breast tumor initiation. In response to disruption of homeostasis, differentiated cells can partially lose their identity and gain cellular plasticity, a process involving epigenome landscape remodeling. This increase of cellular plasticity may promote the malignant transformation of breast tumors and fuel their heterogeneity. Here, we review recent studies that have yield insights into important regulators of lineage integrity and mechanisms that trigger mammary epithelial lineage derail, and evaluate their impacts on breast tumor development.

Molecular classification of hormone receptor-positive HER2-negative breast cancer

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most prevalent type of breast cancer, in which endocrine therapy resistance and distant relapse remain unmet challenges. Accurate molecular classification is urgently required for guiding precision treatment. We established a large-scale multi-omics cohort of 579 patients with HR+/HER2- breast cancer and identified the following four molecular subtypes: canonical luminal, immunogenic, proliferative and receptor tyrosine kinase (RTK)-driven. Tumors of these four subtypes showed distinct biological and clinical features, suggesting subtype-specific therapeutic strategies. The RTK-driven subtype was characterized by the activation of the RTK pathways and associated with poor outcomes. The immunogenic subtype had enriched immune cells and could benefit from immune checkpoint therapy. In addition, we developed convolutional neural network models to discriminate these subtypes based on digital pathology for potential clinical translation. The molecular classification provides insights into molecular heterogeneity and highlights the potential for precision treatment of HR+/HER2- breast cancer.

Promyelocytic leukemia protein regulates angiogenesis and epithelial-mesenchymal transition to limit metastasis in MDA-MB-231 breast cancer cells

Promyelocytic leukemia protein (PML) modulates diverse cell functions that contribute to both tumor suppressor and pro-oncogenic effects, depending on the cellular context. We show here that PML knockdown (KD) in MDA-MB-231, but not MCF7, breast cancer cells, prolonged stem-cell-like survival, and increased cell proliferation and migration, which is in line with gene-enrichment results from their RNA sequencing analysis. Of note, increased migration was accompanied by higher levels of the epithelial-mesenchymal transition (EMT) regulator Twist-related protein 2 (TWIST2). We showed here that PML binds to TWIST2 via its basic helix-loop-helix (bHLH) region and functionally interferes with the suppression of the epithelial target of TWIST2, CD24. In addition, PML ablation in MDA-MB-231 cells led to higher protein levels of hypoxia-inducible factor 1-alpha (HIF1a), resulting in a higher cell hypoxic response. Functionally, PML directly suppressed the induction of the HIF1a target gene vascular endothelial growth factor A (VEGFa). In line with these results, tumor xenografts of MDA-MB-231 PML-KD cells had enhanced aggressive properties, including higher microvessel density, faster local growth, and higher metastatic ability, with a preference for lung. Collectively, PML suppresses the cancer aggressive behavior by multiple mechanisms that impede both the HIF-hypoxia-angiogenic and EMT pathways.

TCL1A+ B cells predict prognosis in triple-negative breast cancer through integrative analysis of single-cell and bulk transcriptomic data

Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options and high mortality rates. It remains a prevailing clinical need to distinguish whether the patient can benefit from therapy, such as chemotherapy. By integrating single-cell and global transcriptome data, we have for the first time identified TCL1A+ B cell functions that are prognostically relevant in TNBC. This finding broadens the perspective of traditional tumor-infiltrating lymphocytes in predicting survival, especially the potential value of B cells in TNBC. Single-cell RNA-seq data from five TNBC patients were collected to identify the association between immune cell populations and clinical outcomes. Functional analysis was according to gene set enrichment analysis using pathways from MsigDB. Subsequently, the gene signature of TCL1A+ B cells based on differential expression genes of TCL1A+ B cells versus other immune cells was used to explore the correlation with tumor microenvironment (TME) and construct a prognostic signature using a non-parametric and unsupervised method. We identified TCL1A+ B cells as a cluster of B cells associated with clinical outcomes in TNBC. Functional analysis demonstrated its function in B cell activation and regulation of immune response. The highly enriched TCL1A+ B cell population was found to be associated with a thermal TME with anti-tumor effects. A high abundance of TCL1A+ B cell population is positively correlated with a favorable therapeutic outcome, as indicated by longer overall survival. The present study suggests that TCL1A+ B cells play a key role in the treatment and prognostic prediction of TNBC, although further studies are needed to validate our findings. Moreover, the integration of transcriptome data at various resolutions provides a viable approach for the discovery of novel prognostic markers.

S100A8/A9 predicts triple-negative breast cancer response to PIM kinase and PD-1/PD-L1 inhibition

It remains elusive why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well. Our retrospective analysis of historical gene expression datasets reveals that increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors is robustly associated with subsequent disease progression in TNBC. Although it has recently gained recognition as a potential anticancer target, S100A8/A9 has not been integrated into clinical study designs evaluating molecularly targeted therapies. Our small molecule screen has identified PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Furthermore, combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Importantly, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC. Thus, our data suggest that S100A8/A9 could be a predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC and encourage the development of S100A8/A9-based liquid biopsy tests.

Prognostic significance of TP53 and PIK3CA mutations analyzed by next-generation sequencing in breast cancer

Breast cancer is one of the most prevalent malignant tumors affecting women globally. It is a heterogeneous disease characterized by mutations in several genes. Several gene panels have been applied to assess the risk of breast cancer and determine the appropriate treatment. As a powerful tool, Next-generation sequencing (NGS) has been widely utilized in cancer research due to its advantages, including high speed, high throughput, and high accuracy. In this study, we aim to analyze the correlation between somatic mutations in breast cancer, analyzed using NGS, and the prognosis of patients. Between May 2018 and May 2019, a total of 313 patients with breast cancer underwent surgical treatment, which included total mastectomy and breast-conserving surgery. Among these patients, 265 were diagnosed with invasive ductal carcinoma. In this study, we analyzed the NGS results, clinicopathological characteristics, and their correlation with prognosis. Using a gene panel, we examined 143 somatic mutations in solid cancers. Notably, the study population included patients who had received neoadjuvant chemotherapy. The mean age of the patients was 53.1 (±10.28) years, and the median follow-up time was 48 months (range, 8-54). Among the 265 patients, 68 had received prior systemic therapy. Of these, 203 underwent breast-conserving surgery, and 62 underwent a mastectomy. Various somatic mutations were observed in NGS, with the most frequent mutation being PIK3CA mutations, which accounted for 44% of all mutations. TP53 mutations were the second most frequent, and ERBB2 mutations were the third most frequent. TP53 mutations were associated with poor disease-free survival (P = .027), while PIK3CA mutations were associated with better disease-free survival (P = .035) than PIK3CA wild-type. In our study, we identified various somatic mutations in breast cancer. Particularly, we found that TP53 and PIK3CA mutations are potentially associated with the prognosis of breast cancer. These findings suggest that the presence of specific mutations may have implications for predicting the prognosis of breast cancer. Further research and validation are needed to gain a deeper understanding of the role of these mutations and their mechanisms in prognosis prediction.

Adaptive MCMC for Bayesian Variable Selection in Generalised Linear Models and Survival Models

Developing an efficient computational scheme for high-dimensional Bayesian variable selection in generalised linear models and survival models has always been a challenging problem due to the absence of closed-form solutions to the marginal likelihood. The Reversible Jump Markov Chain Monte Carlo (RJMCMC) approach can be employed to jointly sample models and coefficients, but the effective design of the trans-dimensional jumps of RJMCMC can be challenging, making it hard to implement. Alternatively, the marginal likelihood can be derived conditional on latent variables using a data-augmentation scheme (e.g., Pólya-gamma data augmentation for logistic regression) or using other estimation methods. However, suitable data-augmentation schemes are not available for every generalised linear model and survival model, and estimating the marginal likelihood using a Laplace approximation or a correlated pseudo-marginal method can be computationally expensive. In this paper, three main contributions are presented. Firstly, we present an extended Point-wise implementation of Adaptive Random Neighbourhood Informed proposal (PARNI) to efficiently sample models directly from the marginal posterior distributions of generalised linear models and survival models. Secondly, in light of the recently proposed approximate Laplace approximation, we describe an efficient and accurate estimation method for marginal likelihood that involves adaptive parameters. Additionally, we describe a new method to adapt the algorithmic tuning parameters of the PARNI proposal by replacing Rao-Blackwellised estimates with the combination of a warm-start estimate and the ergodic average. We present numerous numerical results from simulated data and eight high-dimensional genetic mapping data-sets to showcase the efficiency of the novel PARNI proposal compared with the baseline add-delete-swap proposal.

Use of cutting-edge RNA-sequencing technology to identify biomarkers and potential therapeutic targets in canine and feline cancers and other diseases

With the growing interest in companion animals and the rapidly expanding animal healthcare and pharmaceuticals market worldwide. With the advancements in RNA-sequencing (RNA-seq) technology, it has become a valuable tool for understanding biological processes in companion animals and has multiple applications in animal healthcare. Historically, veterinary diagnoses and treatments relied solely on clinical symptoms and drugs used in human diseases. However, RNA-seq has emerged as an effective technology for studying companion animals, providing insights into their genetic information. The sequencing technology has revealed that not only messenger RNAs (mRNAs) but also non-coding RNAs (ncRNAs) such as long ncRNAs and microRNAs can serve as biomarkers. Based on the examination of RNA-seq applications in veterinary medicine, particularly in dogs and cats, this review concludes that RNA-seq has significant potential as a diagnostic and research tool. It has enabled the identification of potential biomarkers for cancer and other diseases in companion animals. Further research and development are required to maximize the utilization of RNA-seq for improved disease diagnosis and therapeutic targeting in companion animals.

Commonalities and differences in the mutational signature and somatic driver mutation landscape across solid and hollow viscus organs

Advances in sequencing have revealed a highly variegated landscape of mutational signatures and somatic driver mutations in a range of normal tissues. Normal tissues accumulate mutations at varying rates ranging from 11 per cell per year in the liver, to 1879 per cell per year in the bladder. In addition, some normal tissues are also comprised of a large proportion of cells which possess driver mutations while appearing phenotypically normal, as in the oesophagus where a majority of cells harbour driver mutations. Individual tissue proliferation and mutation rate, unique mutagenic stimuli, and local tissue architecture contribute to this highly variegated landscape which confounds the functional characterization of driver mutations found in normal tissue. In particular, our understanding of the relationship between normal tissue somatic mutations and tumour initiation or future cancer risk remains poor. Here, we describe the mutational signatures and somatic driver mutations in solid and hollow viscus organs, highlighting unique characteristics in a tissue-specific manner, while simultaneously seeking to describe commonalities which can bring forward a basic unified theory on the role of these driver mutations in tumour initiation. We discuss novel findings which can be used to inform future research in this field.

P110α inhibitor alpelisib exhibits a synergistic effect with pyrotinib and reverses pyrotinib resistant in HER2+ breast cancer

Human epidermal growth factor receptor 2 (HER2) plays a critical role in breast cancer progression in patients with HER2 overexpression, thereby driving the development of targeted drugs and advancing therapy strategies targeting this gene. Pyrotinib is a novel irreversible pan-ErbB kinase inhibitor, primarily suppresses the downstream MAPK and PI3K/AKT pathways. Alpelisib, a selective PI3K p110α inhibitor, has been approved for clinical application in HR+, HER2-, PIK3CA mutated breast cancers and is also being developed for use in other breast cancer subtypes. In this study, we hypothesised that combining pyrotinib with alpelisib would yield superior results compared to single-drug treatment. Our data demonstrated that the combination of alpelisib and pyrotinib exhibited a synergistic effect in HER2+ breast cancer both in vitro and in vivo. This combination led to decreased cell proliferation and migration, G0-G1 cell cycle arrest, and increased apoptosis rates. Additionally, the deactivation of ErbB receptors and sustained activation of PI3K/AKT pathway by upstream compensatory pathways induced acquired pyrotinib resistant cells resistant to pyrotinib treatment, thus alpelisib combined with pyrotinib showed a tremendous synergistic effect and reverse pyrotinib resistance in acquired pyrotinib resistant cells by suppressing the activated PI3K/AKT pathway. Our results revealed a combination of pyrotinib and alpelisib as an effective therapeutic strategy in treating HER2+ breast cancer, whether sensitive or resistant to pyrotinib treatment.

Adverse Crosstalk between Extracellular Matrix Remodeling and Ferroptosis in Basal Breast Cancer

(1) Background: Breast cancer is a frequent heterogeneous disorder diagnosed in women and causes a high number of mortality among this population due to rapid metastasis and disease recurrence. Ferroptosis can inhibit breast cancer cell growth, improve the sensitivity of chemotherapy and radiotherapy, and inhibit distant metastases, potentially impacting the tumor microenvironment. (2) Methods: Through data mining, the ferroptosis/extracellular matrix remodeling literature text-mining results were integrated into the breast cancer transcriptome cohort, taking into account patients with distant relapse-free survival (DRFS) under adjuvant therapy (anthracyclin + taxanes) with validation in an independent METABRIC cohort, along with the MDA-MB-231 and HCC338 transcriptome functional experiments with ferroptosis activations (GSE173905). (3) Results: Ferroptosis/extracellular matrix remodeling text-mining identified 910 associated genes. Univariate Cox analyses focused on breast cancer (GSE25066) selected 252 individual significant genes, of which 170 were found to have an adverse expression. Functional enrichment of these 170 adverse genes predicted basal breast cancer signatures. Through text-mining, some ferroptosis-significant adverse-selected genes shared citations in the domain of ECM remodeling, such as TNF, IL6, SET, CDKN2A, EGFR, HMGB1, KRAS, MET, LCN2, HIF1A, and TLR4. A molecular score based on the expression of the eleven genes was found predictive of the worst prognosis breast cancer at the univariate level: basal subtype, short DRFS, high-grade values 3 and 4, and estrogen and progesterone receptor negative and nodal stages 2 and 3. This eleven-gene signature was validated as regulated by ferroptosis inductors (erastin and RSL3) in the triple-negative breast cancer cellular model MDA-MB-231. (4) Conclusions: The crosstalk between ECM remodeling-ferroptosis functionalities allowed for defining a molecular score, which has been characterized as an independent adverse parameter in the prognosis of breast cancer patients. The gene signature of this molecular score has been validated to be regulated by erastin/RSL3 ferroptosis activators. This molecular score could be promising to evaluate the ECM-related impact of ferroptosis target therapies in breast cancer.

NFIB facilitates replication licensing by acting as a genome organizer

The chromatin-based rule governing the selection and activation of replication origins in metazoans remains to be investigated. Here we report that NFIB, a member of Nuclear Factor I (NFI) family that was initially purified in host cells to promote adenoviral DNA replication but has since mainly been investigated in transcription regulation, is physically associated with the pre-replication complex (pre-RC) in mammalian cells. Genomic analyses reveal that NFIB facilitates the assembly of the pre-RC by increasing chromatin accessibility. Nucleosome binding and single-molecule magnetic tweezers shows that NFIB binds to and opens up nucleosomes. Transmission electron microscopy indicates that NFIB promotes nucleosome eviction on parental chromatin. NFIB deficiency leads to alterations of chromosome contacts/compartments in both G1 and S phase and affects the firing of a subset of origins at early-replication domains. Significantly, cancer-associated NFIB overexpression provokes gene duplication and genomic alterations recapitulating the genetic aberrance in clinical breast cancer and empowering cancer cells to dynamically evolve growth advantage and drug resistance. Together, these results point a role for NFIB in facilitating replication licensing by acting as a genome organizer, shedding new lights on the biological function of NFIB and on the replication origin selection in eukaryotes.

Concurrent predictors of an immune responsive tumor microenvironment within tumor mutational burden-high breast cancer

Background

Data supporting high tumor mutational burden (TMB-H) as a lone biomarker for an immune-responsive tumor microenvironment (TME) in metastatic breast cancer (MBC) are weak, yet tumor agnostic approval in TMB-H advanced tumors provides immune checkpoint inhibition (ICI) as a clinical option. We evaluated concurrent predictors of immune-responsive and non-responsive TME within MBC.

Methods

Tumor samples from patients with MBC (N=5621) were analyzed by next-generation sequencing of DNA (592-gene panel or whole exome) and RNA (whole transcriptome) at Caris Life Sciences (Phoenix, AZ). TMB-H threshold was set to ≥ 10 muts/Mb. PDL-1 was evaluated using SP142 antibody. Gene expression profiling and RNA deconvolution were used to estimate immune and stromal cell population abundance in the TME, and transcriptomic signature of immunotherapy response (T cell-inflamed score).

Results

461 (8.2%) TMB-H MBC samples were identified. Consistent with prior studies, TMB-H tumors exhibited significant dMMR/MSI-H enrichment (7 vs. 0%, p<0.0001) and PD-L1+ expression (36 vs. 28%, p<0.05) compared to TMB-L. Across all samples, T cell-inflamed scores were weakly correlated with TMB. TMB-H was not associated with significantly increased immune responsive cell types (CD8+ T-cells, NK cells, or B cells) or immune response gene signatures (e.g. antigen presentation), yet positive trends were observed, while immunosuppressive fibroblasts were significantly decreased in TMB-H tumors (0.84-fold change compared to TMB-L, P<0.05). HR+/HER2- breast cancer was the only subtype in which TMB-H tumors exhibited increased T cell-inflamed scores vs. TMB-L. Concurrent PD-L1+ or dMMR/MSI-H with TMB-H was associated with high T cell-inflamed scores in both HR+/HER2- and TNBC. Among several associated biomarkers, B2M mutations and CD274 amplifications were positively associated with T-cell inflamed scores in TMB-H tumors; CDH1 and ERBB2 mutations were negatively associated.

Conclusion

High TMB alone does not strongly correlate with immune infiltrate or immune-related gene signatures in MBC. TMB-H predicts T-cell inflamed signature compared to TMB-L in HR+/HER2- tumors only. Along with MSI-H and PD-L1+, several biomarkers, including B2M mutation and CD274 amplification, may help predict ICI benefit amongst TMB-H tumors. Co-occurring biomarkers within TMB-H breast cancer warrant evaluation in larger cohorts for response or resistance to ICI to develop composite predictive biomarkers in MBC.

Structural basis of histone H2A lysine 119 deubiquitination by Polycomb repressive deubiquitinase BAP1/ASXL1

Histone H2A lysine 119 (H2AK119Ub) is monoubiquitinated by Polycomb repressive complex 1 and deubiquitinated by Polycomb repressive deubiquitinase complex (PR-DUB). PR-DUB cleaves H2AK119Ub to restrict focal H2AK119Ub at Polycomb target sites and to protect active genes from aberrant silencing. The PR-DUB subunits (BAP1 and ASXL1) are among the most frequently mutated epigenetic factors in human cancers. How PR-DUB establishes specificity for H2AK119Ub over other nucleosomal ubiquitination sites and how disease-associated mutations of the enzyme affect activity are unclear. Here, we determine a cryo-EM structure of human BAP1 and the ASXL1 DEUBAD in complex with a H2AK119Ub nucleosome. Our structural, biochemical, and cellular data reveal the molecular interactions of BAP1 and ASXL1 with histones and DNA that are critical for restructuring the nucleosome and thus establishing specificity for H2AK119Ub. These results further provide a molecular explanation for how >50 mutations in BAP1 and ASXL1 found in cancer can dysregulate H2AK119Ub deubiquitination, providing insight into understanding cancer etiology.

Advances in the Management of Early-Stage Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with both inter- and intratumor heterogeneity, thought to result in a more aggressive course and worse outcomes. Neoadjuvant therapy (NAT) has become the preferred treatment modality of early-stage TNBC as it allows for the downstaging of tumors in the breast and axilla, monitoring early treatment response, and most importantly, provides important prognostic information that is essential to determining post-surgical therapies to improve outcomes. It focuses on combinations of systemic drugs to optimize pathologic complete response (pCR). Excellent response to NAT has allowed surgical de-escalation in ideal candidates. Further, treatment algorithms guide the systemic management of patients based on their pCR status following surgery. The expanding knowledge of molecular pathways, genomic sequencing, and the immunological profile of TNBC has led to the use of immune checkpoint inhibitors and targeted agents, including PARP inhibitors, further revolutionizing the therapeutic landscape of this clinical entity. However, subgroups most likely to benefit from these novel approaches in TNBC remain elusive and are being extensively studied. In this review, we describe current practices and promising therapeutic options on the horizon for TNBC, surgical advances, and future trends in molecular determinants of response to therapy in early-stage TNBC.