Improved understanding of the molecular mechanisms by which small-molecule inhibitors of histone deacetylases (HDAC) induce programs, such as cellular differentiation and apoptosis, would undoubtedly ...assist their clinical development as anticancer agents. As modulators of gene transcript levels, HDAC inhibitors (HDACi) typically affect only 5% to 10% of actively transcribed genes with approximately as many mRNA transcripts being up-regulated as down-regulated. Using microRNA (miRNA) array analysis, we report rapid alteration of miRNA levels in response to the potent hydroxamic acid HDACi LAQ824 in the breast cancer cell line SKBr3. Within 5 hours of exposure to a proapoptotic dose of LAQ824, significant changes were measured in 40% of the >60 different miRNA species expressed in SKBr3 cells with 22 miRNA species down-regulated and 5 miRNAs up-regulated. To explore a potential functional link between HDACi induced mRNA up-regulation and miRNA down-regulation, antisense experiments were done against miR-27a and miR-27b, both abundantly expressed and down-regulated in SKBr3 cells by LAQ824. Correlating a set of genes previously determined by cDNA array analysis to be rapidly up-regulated by LAQ824 in SKBr3 with a database of potential 3' untranslated region miRNA binding elements, two genes containing putative miR-27 anchor elements were identified as transcriptionally up-regulated following miR-27 antisense transfection, ZBTB10/RINZF, a Sp1 repressor, and RYBP/DEDAF, an apoptotic facilitator. These findings emphasize the importance of post-transcriptional mRNA regulation by HDACi in addition to their established effects on promoter-driven gene expression.
Cancer cells often acquire a constitutively active nuclear factor-κB (NF-κB) program to promote survival, proliferation and metastatic potential by mechanisms that remain largely unknown. Extending ...observations from an immunologic setting, we demonstrate that microRNA-146a and microRNA-146b (miR-146a/b) when expressed in the highly metastatic human breast cancer cell line MDA-MB-231 function to negatively regulate NF-κB activity. Lentiviral-mediated expression of miR-146a/b significantly downregulated interleukin (IL)-1 receptor-associated kinase and TNF receptor-associated factor 6, two key adaptor/scaffold proteins in the IL-1 and Toll-like receptor signaling pathway, known to positively regulate NF-κB activity. Impaired NF-κB activity was evident from reduced phosphorylation of the NF-κB inhibitor IκBα, reduced NF-κB DNA-binding activity and suppressed expression of the NF-κB target genes IL-8, IL-6 and matrix metalloproteinase-9. Functionally, miR-146a/b-expressing MDA-MB-231 cells showed markedly impaired invasion and migration capacity relative to control cells. These findings implicate miR-146a/b as a negative regulator of constitutive NF-κB activity in a breast cancer setting and suggest that modulating miR-146a/b levels has therapeutic potential to suppress breast cancer metastases.
Abstract
Background
Previous studies have identified and validated a risk-associated
Active
transcriptome phenotype commonly expressed in the cancer-adjacent and histologically normal epithelium, ...stroma, and adipose containing peritumor microenvironment of clinically established invasive breast cancers, conferring a 2.5- to 3-fold later risk of dying from recurrent breast cancer. Expression of this
Active
transcriptome phenotype has not yet been evaluated in normal breast tissue samples unassociated with any benign or malignant lesions; however, it has been associated with increased peritumor adipocyte composition.
Methods
Detailed histologic and transcriptomic (RNAseq) analyses were performed on normal breast biopsy samples from 151 healthy, parous, non-obese (mean BMI = 29.60 ± 7.92) women, ages 27–66 who donated core breast biopsy samples to the Komen Tissue Bank, and whose average breast cancer risk estimate (Gail score) at the time of biopsy (1.27 ± 1.34) would not qualify them for endocrine prevention therapy.
Results
Full genome RNA sequencing (RNAseq) identified 52% (78/151) of these normal breast samples as expressing the
Active
breast phenotype. While
Active
signature genes were found to be most variably expressed in mammary adipocytes, donors with the
Active
phenotype had no difference in BMI but significantly higher Gail scores (1.46 vs. 1.18;
p
= 0.007).
Active
breast samples possessed 1.6-fold more (~ 80%) adipocyte nuclei, larger cross-sectional adipocyte areas (
p
< 0.01), and 0.5-fold fewer stromal and epithelial cell nuclei (
p
< 1e−6). Infrequent low-level expression of cancer gene hotspot mutations was detected but not enriched in the
Active
breast samples.
Active
samples were enriched in gene sets associated with adipogenesis and fat metabolism (FDR
q
≤ 10%), higher signature scores for cAMP-dependent lipolysis known to drive breast cancer progression, white adipose tissue browning (Wilcoxon
p
< 0.01), and genes associated with adipocyte activation (leptin, adiponectin) and remodeling (CAV1, BNIP3), adipokine growth factors (IGF-1, FGF2), and pro-inflammatory fat signaling (IKBKG, CCL13).
Conclusions
The risk-associated
Active
transcriptome phenotype first identified in cancer-adjacent breast tissues also occurs commonly in healthy women without breast disease who do not qualify for breast cancer chemoprevention, and independently of breast expressed cancer-associated mutations. The risk-associated
Active
phenotype appears driven by a pro-tumorigenic adipocyte microenvironment that can predate breast cancer development.
Breast cancer intrinsic molecular subtype (IMS) as classified by the expression-based PAM50 assay is considered a strong prognostic feature, even when controlled for by standard clinicopathological ...features such as age, grade, and nodal status, yet the molecular testing required to elucidate these subtypes is not routinely performed. Furthermore, when such bulk assays as RNA sequencing are performed, intratumoral heterogeneity that may affect prognosis and therapeutic decision-making can be missed.
As a more facile and readily available method for determining IMS in breast cancer, we developed a deep learning approach for approximating PAM50 intrinsic subtyping using only whole-slide images of H&E-stained breast biopsy tissue sections. This algorithm was trained on images from 443 tumors that had previously undergone PAM50 subtyping to classify small patches of the images into four major molecular subtypes-Basal-like, HER2-enriched, Luminal A, and Luminal B-as well as Basal vs. non-Basal. The algorithm was subsequently used for subtype classification of a held-out set of 222 tumors.
This deep learning image-based classifier correctly subtyped the majority of samples in the held-out set of tumors. However, in many cases, significant heterogeneity was observed in assigned subtypes across patches from within a single whole-slide image. We performed further analysis of heterogeneity, focusing on contrasting Luminal A and Basal-like subtypes because classifications from our deep learning algorithm-similar to PAM50-are associated with significant differences in survival between these two subtypes. Patients with tumors classified as heterogeneous were found to have survival intermediate between Luminal A and Basal patients, as well as more varied levels of hormone receptor expression patterns.
Here, we present a method for minimizing manual work required to identify cancer-rich patches among all multiscale patches in H&E-stained WSIs that can be generalized to any indication. These results suggest that advanced deep machine learning methods that use only routinely collected whole-slide images can approximate RNA-seq-based molecular tests such as PAM50 and, importantly, may increase detection of heterogeneous tumors that may require more detailed subtype analysis.
Motivation: High-throughput data is providing a comprehensive view of the molecular changes in cancer tissues. New technologies allow for the simultaneous genome-wide assay of the state of genome ...copy number variation, gene expression, DNA methylation and epigenetics of tumor samples and cancer cell lines. Analyses of current data sets find that genetic alterations between patients can differ but often involve common pathways. It is therefore critical to identify relevant pathways involved in cancer progression and detect how they are altered in different patients. Results: We present a novel method for inferring patient-specific genetic activities incorporating curated pathway interactions among genes. A gene is modeled by a factor graph as a set of interconnected variables encoding the expression and known activity of a gene and its products, allowing the incorporation of many types of omic data as evidence. The method predicts the degree to which a pathway's activities (e.g. internal gene states, interactions or high-level ‘outputs’) are altered in the patient using probabilistic inference. Compared with a competing pathway activity inference approach called SPIA, our method identifies altered activities in cancer-related pathways with fewer false-positives in both a glioblastoma multiform (GBM) and a breast cancer dataset. PARADIGM identified consistent pathway-level activities for subsets of the GBM patients that are overlooked when genes are considered in isolation. Further, grouping GBM patients based on their significant pathway perturbations divides them into clinically-relevant subgroups having significantly different survival outcomes. These findings suggest that therapeutics might be chosen that target genes at critical points in the commonly perturbed pathway(s) of a group of patients. Availability:Source code available at http://sbenz.github.com/Paradigm Contact: jstuart@soe.ucsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Perturbations in the transcriptional programs specifying epidermal differentiation cause diverse skin pathologies ranging from impaired barrier function to inflammatory skin disease. However, the ...global scope and organization of this complex cellular program remain undefined. Here we report single-cell RNA sequencing profiles of 92,889 human epidermal cells from 9 normal and 3 inflamed skin samples. Transcriptomics-derived keratinocyte subpopulations reflect classic epidermal strata but also sharply compartmentalize epithelial functions such as cell-cell communication, inflammation, and WNT pathway modulation. In keratinocytes, ∼12% of assessed transcript expression varies in coordinate patterns, revealing undescribed gene expression programs governing epidermal homeostasis. We also identify molecular fingerprints of inflammatory skin states, including S100 activation in the interfollicular epidermis of normal scalp, enrichment of a CD1C+CD301A+ myeloid dendritic cell population in psoriatic epidermis, and IL1βhiCCL3hiCD14+ monocyte-derived macrophages enriched in foreskin. This compendium of RNA profiles provides a critical step toward elucidating epidermal diseases of development, differentiation, and inflammation.
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•Stereotyped keratinocyte subpopulations modularly comprise human epidermis•Scalp keratinocytes exhibit an inherent inflammatory transcriptional program•Myeloid dendritic cells predominate APCs in psoriatic epidermis•Macrophages represent major APCs in foreskin epidermis
Cheng et al. report single-cell RNA sequencing of normal and inflamed human epidermis, revealing a discrete set of specialized keratinocytes that exhibit a distinct composition at different anatomic sites. Myeloid dendritic cells and macrophages also vary sharply with epidermal anatomic site and inflammation, indicating dynamic programming of antigen-presenting cells.
To assess the long-term (20-year) endocrine therapy benefit in premenopausal patients with breast cancer.
Secondary analysis of the Stockholm trial (STO-5, 1990-1997) randomly assigning 924 ...premenopausal patients to 2 years of goserelin (3.6 mg subcutaneously once every 28 days), tamoxifen (40 mg orally once daily), combined goserelin and tamoxifen, or no adjuvant endocrine therapy (control) is performed. Random assignment was stratified by lymph node status; lymph node-positive patients (n = 459) were allocated to standard chemotherapy (cyclophosphamide, methotrexate, and fluorouracil). Primary tumor immunohistochemistry (n = 731) and gene expression profiling (n = 586) were conducted in 2020. The 70-gene signature identified genomic low-risk and high-risk patients. Kaplan-Meier analysis, multivariable Cox proportional hazard regression, and multivariable time-varying flexible parametric modeling assessed the long-term distant recurrence-free interval (DRFI). Swedish high-quality registries allowed a complete follow-up of 20 years.
In estrogen receptor-positive patients (n = 584, median age 47 years), goserelin, tamoxifen, and the combination significantly improved long-term distant recurrence-free interval compared with control (multivariable hazard ratio HR, 0.49; 95% CI, 0.32 to 0.75, HR, 0.57; 95% CI, 0.38 to 0.87, and HR, 0.63; 95% CI, 0.42 to 0.94, respectively). Significant goserelin-tamoxifen interaction was observed (
= .016). Genomic low-risk patients (n = 305) significantly benefitted from tamoxifen (HR, 0.24; 95% CI, 0.10 to 0.60), and genomic high-risk patients (n = 158) from goserelin (HR, 0.24; 95% CI, 0.10 to 0.54). Increased risk from the addition of tamoxifen to goserelin was seen in genomic high-risk patients (HR, 3.36; 95% CI, 1.39 to 8.07). Moreover, long-lasting 20-year tamoxifen benefit was seen in genomic low-risk patients, whereas genomic high-risk patients had early goserelin benefit.
This study shows 20-year benefit from 2 years of adjuvant endocrine therapy in estrogen receptor-positive premenopausal patients and suggests differential treatment benefit on the basis of tumor genomic characteristics. Combined goserelin and tamoxifen therapy showed no benefit over single treatment. Long-term follow-up to assess treatment benefit is critical.
Advances in image reconstruction are necessary to decrease radiation exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has been shown to degrade image quality at high ...levels. Deep-learning image reconstruction (DLIR) offers unique opportunities to overcome these limitations. The present study compared the impact of DLIR and adaptive statistical iterative reconstruction-Veo (ASiR-V) on quantitative and qualitative image parameters and the diagnostic accuracy of CCTA using invasive coronary angiography (ICA) as the standard of reference.
This retrospective study includes 43 patients who underwent clinically indicated CCTA and ICA. Datasets were reconstructed with ASiR-V 70% (using standard SD and high-definition HD kernels) and with DLIR at different levels (i.e., medium M and high H). Image noise, image quality, and coronary luminal narrowing were evaluated by three blinded readers. Diagnostic accuracy was compared against ICA.
Noise did not significantly differ between ASiR-V SD and DLIR-M (37 vs. 37 HU, p = 1.000), but was significantly lower in DLIR-H (30 HU, p < 0.001) and higher in ASiR-V HD (53 HU, p < 0.001). Image quality was higher for DLIR-M and DLIR-H (3.4–3.8 and 4.2–4.6) compared to ASiR-V SD and HD (2.1–2.7 and 1.8–2.2; p < 0.001), with DLIR-H yielding the highest image quality. Consistently across readers, no significant differences in sensitivity (88% vs. 92%; p = 0.453), specificity (73% vs. 73%; p = 0.583) and diagnostic accuracy (80% vs. 82%; p = 0.366) were found between ASiR-V HD and DLIR-H.
DLIR significantly reduces noise in CCTA compared to ASiR-V, while yielding superior image quality at equal diagnostic accuracy.
The present study evaluated the impact of deep-learning image reconstruction (DLIR) on noise, image quality, and diagnostic accuracy. In 43 patients who underwent clinically indicated coronary CT angiography and invasive coronary angiography, image quality was improved by up to 62% at similar noise levels. In addition, DLIR-H yielded the highest noise reduction (up to 43%) and best image quality (improvement of up to 138%). More importantly, sensitivity (92% vs. 88%), specificity (73% vs. 73%) and diagnostic accuracy (82% vs. 80%) of DLIR were at least non-inferior to ASiR-V.
Breast cancer patients with estrogen receptor (ER)-positive disease have a continuous long-term risk for fatal breast cancer, but the biological factors influencing this risk are unknown. We aimed to ...determine whether high intratumor heterogeneity of ER predicts an increased long-term risk (25 years) of fatal breast cancer.
The STO-3 trial enrolled 1780 postmenopausal lymph node-negative breast cancer patients randomly assigned to receive adjuvant tamoxifen vs not. The fraction of cancer cells for each ER intensity level was scored by breast cancer pathologists, and intratumor heterogeneity of ER was calculated using Rao's quadratic entropy and categorized into high and low heterogeneity using a predefined cutoff at the second tertile (67%). Long-term breast cancer-specific survival analyses by intra-tumor heterogeneity of ER were performed using Kaplan-Meier and multivariable Cox proportional hazard modeling adjusting for patient and tumor characteristics.
A statistically significant difference in long-term survival by high vs low intratumor heterogeneity of ER was seen for all ER-positive patients (P < .001) and for patients with luminal A subtype tumors (P = .01). In multivariable analyses, patients with high intratumor heterogeneity of ER had a twofold increased long-term risk as compared with patients with low intratumor heterogeneity (ER-positive: hazard ratio HR = 1.98, 95% confidence interval CI = 1.31 to 3.00; luminal A subtype tumors: HR = 2.43, 95% CI = 1.18 to 4.99).
Patients with high intratumor heterogeneity of ER had an increased long-term risk of fatal breast cancer. Interestingly, a similar long-term risk increase was seen in patients with luminal A subtype tumors. Our findings suggest that intratumor heterogeneity of ER is an independent long-term prognosticator with potential to change clinical management, especially for patients with luminal A tumors.
Experienced Involvement (also called Peer Support Work, PSW) has existed in mental health care in Germany since 2005 though its implementation lags behind, compared to other countries. Due to the ...unique challenges of forensic-psychiatric settings, implementation of PSW in these settings is even less developed. We prepared the implementation of a peer support worker in our forensic hospital for addicted offenders in Germany in several steps: A survey amongst the 75 forensic hospitals in Germany was conducted to evaluate the prevalence of PSW in these settings. Individual interviews were conducted with directors and peer support workers of forensic clinics nation-wide to investigate their facilities’ experiences with PSW. Focus groups with several occupational groups of the clinic in Rostock addressed staffs opinions, expectations and reservations regarding peer support work. These were recorded and transcribed for thematic analysis.
Results:
revealed that the majority of forensic hospitals (83.6%) has no experience with peer support work. Interviews with external clinic directors revealed similar concerns and expectations among the employees as our focus groups did. Staff at the clinics expected the peer support worker to offer useful experiences and new perspectives. Concerns occurred about stability of health condition of the peer support worker, trust issues because of former criminal behavior and attitudes towards psychiatric treatment that might interfere with professional treatment negatively. Furthermore the clinic directors stressed the importance of a well prepared implementation and a good “fit” of the peer support workers background to the patients (e.g. regarding diagnosis).
Disclosure
No significant relationships.
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