Breast Cancer Research : BCR最新文献

Many factors, including reproductive hormones, have been linked to a woman's risk of developing breast cancer (BC). We reviewed the literature regarding the relationship between ovulatory menstrual cycles (MCs) and BC risk. Physiological variations in the frequency of MCs and interference with MCs through genetic variations, pathological conditions and or pharmaceutical interventions revealed a strong link between BC risk and the lifetime number of MCs. A substantial reduction in BC risk is observed in situations without MCs. In genetic or transgender situations with normal female breasts and estrogens, but no progesterone (P4), the incidence of BC is very low, suggesting an essential role of P4. During the MC, P4 has a strong proliferative effect on normal breast epithelium, whereas estradiol (E2) has only a minimal effect. The origin of BC has been strongly linked to proliferation associated DNA replication errors, and the repeated stimulation of the breast epithelium by P4 with each MC is likely to impact the epithelial mutational burden. Long-lived cells, such as stem cells, present in the breast epithelium, can carry mutations forward for an extended period of time, and studies show that breast tumors tend to take decades to develop before detection. We therefore postulate that P4 is an important factor in a woman's lifetime risk of developing BC, and that breast tumors arising during hormonal contraception or after menopause, with or without menopausal hormone therapy, are the consequence of the outgrowth of pre-existing neoplastic lesions, eventually stimulated by estrogens and some progestins.

Background: Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways.

Methods: De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression.

Results: After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P < 0.05) and the overall cohort (AA = 28% vs. EA = 37%, P = 2.08e-05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P < 0.05) and HR+/HER2- (24% vs. 15%, P = 3e-03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e-162), HSPA1A (logFC = - 2.73, P = 2.43e-49), ATRX (logFC = - 1.93, P = 5.89e-83), and NUTM2F (logFC = 2.28, P = 3.22e-196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e-06), LTE2_UP.V1_UP (P = 2.90e-05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074).

Conclusions: We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

Background: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). The response to NAC is prognostic, with reductions in overall survival and disease-free survival rates in those patients who do not achieve a pathological complete response (pCR). Based on this premise, we hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence.

Methods and results: We investigated 24 samples from 12 non-LAR TNBC patients with paired pre- and post-NAC data, including four patients with recurrence shortly after surgery (< 24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and nonrecurrent TNBC tumors; however, post-NAC samples demonstrated significant alterations in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the 9 paired non-LAR samples available in the NAC I-SPY1 trial confirmed 56 gene sets. Within these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n = 392) breast cancer dataset with relapse-free survival (RFS) data was used to refine our gene list to a 17-gene signature. A threefold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine-learning models. Due to the limited number of studies with pre- and post-NAC TNBC tumor data, further validation of the signature is needed.

Conclusion: Analysis of multiomics data from post-NAC TNBC chemoresistant tumors showed down regulation of mismatch repair and tubulin pathways. Additionally, we identified a 17-gene signature in TNBC associated with post-NAC recurrence enriched with down-regulated immune genes.

Background: Response assessment of targeted cancer therapies is becoming increasingly challenging, as it is not adequately assessable with conventional morphological and volumetric analyses of tumor lesions. The tumor microenvironment is particularly constituted by tumor vasculature which is altered by various targeted therapies. The aim of this study was to noninvasively assess changes in tumor perfusion and vessel permeability after targeted therapy in murine models of breast cancer with divergent degrees of malignancy.

Methods: Low malignant 67NR or highly malignant 4T1 tumor-bearing mice were treated with either the multi-kinase inhibitor sorafenib or immune checkpoint inhibitors (ICI, combination of anti-PD1 and anti-CTLA4). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with i.v. injection of albumin-binding gadofosveset was conducted on a 9.4 T small animal MRI. Ex vivo validation of MRI results was achieved by transmission electron microscopy, immunohistochemistry and laser ablation-inductively coupled plasma-mass spectrometry.

Results: Therapy-induced changes in tumor vasculature differed between low and highly malignant tumors. Sorafenib treatment led to decreased tumor perfusion and endothelial permeability in low malignant 67NR tumors. In contrast, highly malignant 4T1 tumors demonstrated characteristics of a transient window of vascular normalization with an increase in tumor perfusion and permeability early after therapy initiation, followed by decreased perfusion and permeability parameters. In the low malignant 67NR model, ICI treatment also mediated vessel-stabilizing effects with decreased tumor perfusion and permeability, while ICI-treated 4T1 tumors exhibited increasing tumor perfusion with excessive vascular leakage.

Conclusion: DCE-MRI enables noninvasive assessment of early changes in tumor vasculature after targeted therapies, revealing different response patterns between tumors with divergent degrees of malignancy. DCE-derived tumor perfusion and permeability parameters may serve as vascular biomarkers that allow for repetitive examination of response to antiangiogenic treatment or immunotherapy.

Background: S100A6 and murine double minute 2 (MDM2) are important cancer-related molecules. A previous study identified an interaction between S100A6 and MDM2 by size exclusion chromatography and surface plasmon resonance experiments. The present study investigated whether S100A6 could bind to MDM2 in vivo and further explored its functional implication.

Methods: Co-immunoprecipitation, glutathione-S-transferase pull-down assay, and immunofluorescence were performed to determine the in vivo interaction between S100A6 and MDM2. Cycloheximide pulse-chase assay and ubiquitination assay were performed to clarify the mechanism by which S100A6 downregulated MDM2. In addition, clonogenic assay, WST-1 assay, and flow cytometry of apoptosis and the cell cycle were performed and a xenograft model was established to evaluate the effects of the S100A6/MDM2 interaction on growth and paclitaxel-induced chemosensitivity of breast cancer. The expressions of S100A6 and MDM2 in patients with invasive breast cancer were analyzed by immunohistochemistry. In addition, the correlation between the expression of S100A6 and the response to neoadjuvant chemotherapy was statistically analyzed.

Results: S100A6 promoted the MDM2 translocation from nucleus to cytoplasm, in which the S100A6 bound to the binding site of the herpesvirus-associated ubiquitin-specific protease (HAUSP) in MDM2, disrupted the MDM2-HAUSP-DAXX interactions, and induced the MDM2 self-ubiquitination and degradation. Furthermore, the S100A6-mediated MDM2 degradation suppressed the growth of breast cancer and enhanced its sensitivity to paclitaxel both in vitro and in vivo. For patients with invasive breast cancer who received epirubicin and cyclophosphamide followed by docetaxel (EC-T), expressions of S100A6 and MDM2 were negatively correlated, and high expression of S100A6 suggested a higher rate of pathologic complete response (pCR). Univariate and multivariate analyses showed that the high expression of S100A6 was an independent predictor of pCR.

Conclusion: These results reveal a novel function for S100A6 in downregulating MDM2, which directly enhances sensitivity to chemotherapy.

Background: Generalizable population-based studies are unable to account for individual tumor heterogeneity that contributes to variability in a patient's response to physician-chosen therapy. Although molecular characterization of tumors has advanced precision medicine, in early-stage and locally advanced breast cancer patients, predicting a patient's response to neoadjuvant therapy (NAT) remains a gap in current clinical practice. Here, we perform a study in an independent cohort of early-stage and locally advanced breast cancer patients to forecast tumor response to NAT and assess the stability of a previously validated biophysical simulation platform.

Methods: A single-blinded study was performed using a retrospective database from a single institution (9/2014-12/2020). Patients included: ≥ 18 years with breast cancer who completed NAT, with pre-treatment dynamic contrast enhanced magnetic resonance imaging. Demographics, chemotherapy, baseline (pre-treatment) MRI and pathologic data were input into the TumorScope Predict (TS) biophysical simulation platform to generate predictions. Primary outcomes included predictions of pathological complete response (pCR) versus residual disease (RD) and final volume for each tumor. For validation, post-NAT predicted pCR and tumor volumes were compared to actual pathological assessment and MRI-assessed volumes. Predicted pCR was pre-defined as residual tumor volume ≤ 0.01 cm³ (≥ 99.9% reduction).

Results: The cohort consisted of eighty patients; 36 Caucasian and 40 African American. Most tumors were high-grade (54.4% grade 3) invasive ductal carcinomas (90.0%). Receptor subtypes included hormone receptor positive (HR+)/human epidermal growth factor receptor 2 positive (HER2+, 30%), HR+/HER2- (35%), HR-/HER2+ (12.5%) and triple negative breast cancer (TNBC, 22.5%). Simulated tumor volume was significantly correlated with post-treatment radiographic MRI calculated volumes (r = 0.53, p = 1.3 × 10^-7, mean absolute error of 6.57%). TS prediction of pCR compared favorably to pathological assessment (pCR: TS n = 28; Path n = 27; RD: TS n = 52; Path n = 53), for an overall accuracy of 91.2% (95% CI: 82.8% - 96.4%; Clopper-Pearson interval). Five-year risk of recurrence demonstrated similar prognostic performance between TS predictions (Hazard ratio (HR): - 1.99; 95% CI [- 3.96, - 0.02]; p = 0.043) and clinically assessed pCR (HR: - 1.76; 95% CI [- 3.75, 0.23]; p = 0.054).

Conclusion: We demonstrated TS ability to simulate and model tumor in vivo conditions in silico and forecast volume response to NAT across breast tumor subtypes.

Background: CHEK2 c.1100delC was the first moderate-risk breast cancer (BC) susceptibility allele discovered. Despite several genomic, transcriptomic and functional studies, however, it is still unclear how exactly CHEK2 c.1100delC promotes tumorigenesis. Since the mutational landscape of a tumor reflects the processes that have operated on its development, the aim of this study was to uncover the somatic genomic landscape of CHEK2-associated BC.

Methods: We sequenced primary BC (pBC) and normal genomes of 20 CHEK2 c.1100delC mutation carriers as well as their pBC transcriptomes. Including pre-existing cohorts, we exhaustively compared CHEK2 pBC genomes to those from BRCA1/2 mutation carriers, those that displayed homologous recombination deficiency (HRD) and ER- and ER+ pBCs, totaling to 574 pBC genomes. Findings were validated in 517 metastatic BC genomes subdivided into the same subgroups. Transcriptome data from 168 ER+ pBCs were used to derive a TP53-mutant gene expression signature and perform cluster analysis with CHEK2 BC transcriptomes. Finally, clinical outcome of CHEK2 c.1100delC carriers was compared with BC patients displaying somatic TP53 mutations in two well-described retrospective cohorts totaling to 942 independent pBC cases.

Results: BC genomes from CHEK2 mutation carriers were most similar to ER+ BC genomes and least similar to those of BRCA1/2 mutation carriers in terms of tumor mutational burden as well as mutational signatures. Moreover, CHEK2 BC genomes did not show any evidence of HRD. Somatic TP53 mutation frequency and the size distribution of structural variants (SVs), however, were different compared to ER+ BC. Interestingly, BC genomes with bi-allelic CHEK2 inactivation lacked somatic TP53 mutations and transcriptomic analysis indicated a shared biology with TP53 mutant BC. Moreover, CHEK2 BC genomes had an increased frequency of > 1 Mb deletions, inversions and tandem duplications with peaks at specific sizes. The high chromothripsis frequency among CHEK2 BC genomes appeared, however, not associated with this unique SV size distribution profile.

Conclusions: CHEK2 BC genomes are most similar to ER+ BC genomes, but display unique features that may further unravel CHEK2-driven tumorigenesis. Increased insight into this mechanism could explain the shorter survival of CHEK2 mutation carriers that is likely driven by intrinsic tumor aggressiveness rather than endocrine resistance.

Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with limited treatment options and poor clinical prognosis. Inhibitors of transcriptional CDKs are currently under thorough investigation for application in the treatment of multiple cancer types, including breast cancer. These studies have raised interest in combining these inhibitors, including CDK12/13 inhibitor THZ531, with a variety of other anti-cancer agents. However, the full scope of these potential synergistic interactions of transcriptional CDK inhibitors with kinase inhibitors has not been systematically investigated. Moreover, the mechanisms behind these previously described synergistic interactions remain largely elusive.

Methods: Kinase inhibitor combination screenings were performed to identify kinase inhibitors that synergize with CDK7 inhibitor THZ1 and CDK12/13 inhibitor THZ531 in TNBC cell lines. CRISPR-Cas9 knockout screening and transcriptomic evaluation of resistant versus sensitive cell lines were performed to identify genes critical for THZ531 resistance. RNA sequencing analysis after treatment with individual and combined synergistic treatments was performed to gain further insights into the mechanism of this synergy. Kinase inhibitor screening in combination with visualization of ABCG2-substrate pheophorbide A was used to identify kinase inhibitors that inhibit ABCG2. Multiple transcriptional CDK inhibitors were evaluated to extend the significance of the found mechanism to other transcriptional CDK inhibitors.

Results: We show that a very high number of tyrosine kinase inhibitors synergize with the CDK12/13 inhibitor THZ531. Yet, we identified the multidrug transporter ABCG2 as key determinant of THZ531 resistance in TNBC cells. Mechanistically, we demonstrate that most synergistic kinase inhibitors block ABCG2 function, thereby sensitizing cells to transcriptional CDK inhibitors, including THZ531. Accordingly, these kinase inhibitors potentiate the effects of THZ531, disrupting gene expression and increasing intronic polyadenylation.

Conclusion: Overall, this study demonstrates the critical role of ABCG2 in limiting the efficacy of transcriptional CDK inhibitors and identifies multiple kinase inhibitors that disrupt ABCG2 transporter function and thereby synergize with these CDK inhibitors. These findings therefore further facilitate the development of new (combination) therapies targeting transcriptional CDKs and highlight the importance of evaluating the role of ABC transporters in synergistic drug-drug interactions in general.

Background: In light of the growing appreciation for the role of collective cell motility in metastasis, a deeper understanding of the underlying signaling pathways will be critical to translating these observations to the treatment of advanced cancers. Here, we examine the contribution of Wnt/planar cell polarity (Wnt/PCP), one of the non-canonical Wnt signaling pathways and defined by the involvement of the tetraspanin-like proteins Vangl1 and Vangl2, to breast tumor cell motility, collective cell invasiveness and mammary tumor metastasis.

Methods: Vangl1 and Vangl2 knockdown and overexpression and Wnt5a stimulation were employed to manipulate Wnt/PCP signaling in a battery of breast cancer cell lines representing all breast cancer subtypes, and in tumor organoids from MMTV-PyMT mice. Cell migration was assessed by scratch and organoid invasion assays, Vangl protein subcellular localization was assessed by confocal fluorescence microscopy, and RhoA activation was assessed in real time by fluorescence imaging with an advanced FRET biosensor. The impact of Wnt/PCP suppression on mammary tumor growth and metastasis was assessed by determining the effect of conditional Vangl2 knockout on the MMTV-NDL mouse mammary tumor model.

Results: We observed that Vangl2 knockdown suppresses the motility of all breast cancer cell lines examined, and overexpression drives the invasiveness of collectively migrating MMTV-PyMT organoids. Vangl2-dependent RhoA activity is localized in real time to a subpopulation of motile leader cells displaying a hyper-protrusive leading edge, Vangl protein is localized to leader cell protrusions within leader cells, and actin cytoskeletal regulator RhoA is preferentially activated in the leader cells of a migrating collective. Mammary gland-specific knockout of Vangl2 results in a striking decrease in lung metastases in MMTV-NDL mice, but does not impact primary tumor growth characteristics.

Conclusions: We conclude that Vangl-dependent Wnt/PCP signaling promotes breast cancer collective cell migration independent of breast tumor subtype and facilitates distant metastasis in a genetically engineered mouse model of breast cancer. Our observations are consistent with a model whereby Vangl proteins localized at the leading edge of leader cells in a migrating collective act through RhoA to mediate the cytoskeletal rearrangements required for pro-migratory protrusion formation.

Background: Breast cancer survivors are living longer due to early detection and advances in treatment and are at increased risk for second primary cancers. Comprehensive evaluation of second cancer risk among patients treated in recent decades is lacking.

Methods: We identified 16,004 females diagnosed with a first primary stage I-III breast cancer between 1990 and 2016 (followed through 2017) and survived ≥ 1 year at Kaiser Permanente (KP) Colorado, Northwest, and Washington. Second cancer was defined as an invasive primary cancer diagnosed ≥ 12 months after the first primary breast cancer. Second cancer risk was evaluated for all cancers (excluding ipsilateral breast cancer) using standardized incidence ratios (SIRs), and a competing risk approach for cumulative incidence and hazard ratios (HRs) adjusted for KP center, treatment, age, and year of first cancer diagnosis.

Results: Over a median follow-up of 6.2 years, 1,562 women developed second cancer. Breast cancer survivors had a 70% higher risk of any cancer (95%CI = 1.62-1.79) and 45% higher risk of non-breast cancer (95%CI = 1.37-1.54) compared with the general population. SIRs were highest for malignancies of the peritoneum (SIR = 3.44, 95%CI = 1.65-6.33), soft tissue (SIR = 3.32, 95%CI = 2.51-4.30), contralateral breast (SIR = 3.10, 95%CI = 2.82-3.40), and acute myeloid leukemia (SIR = 2.11, 95%CI = 1.18-3.48)/myelodysplastic syndrome (SIR = 3.25, 95%CI = 1.89-5.20). Women also had elevated risks for oral, colon, pancreas, lung, and uterine corpus cancer, melanoma, and non-Hodgkin lymphoma (SIR range = 1.31-1.97). Radiotherapy was associated with increased risk for all second cancers (HR = 1.13, 95%CI = 1.01-1.25) and soft tissue sarcoma (HR = 2.36, 95%CI = 1.17-4.78), chemotherapy with decreased risk for all second cancers (HR = 0.87, 95%CI = 0.78-0.98) and increased myelodysplastic syndrome risk (HR = 3.01, 95%CI = 1.01-8.94), and endocrine therapy with lower contralateral breast cancer risk (HR = 0.48, 95%CI = 0.38-0.60). Approximately 1 in 9 women who survived ≥ 1 year developed second cancer, 1 in 13 developed second non-breast cancer, and 1 in 30 developed contralateral breast cancer by 10 years. Trends in cumulative incidence declined for contralateral breast cancer but not for second non-breast cancers.

Conclusions: Elevated risks of second cancer among breast cancer survivors treated in recent decades suggests that heightened surveillance is warranted and continued efforts to reduce second cancers are needed.