Geometric characteristics of stromal collagen fibres in breast cancer using differential interference contrast microscopy.

Breast cancer (BC) is characterised by a high level of heterogeneity, which is influenced by the interaction of neoplastic cells with the tumour microenvironment. The diagnostic and prognostic role of the tumour stroma in BC remains to be defined. Differential interference contrast (DIC) microscopy is a label-free imaging technique well suited to visualise weak optical phase objects such as cells and tissue. This study aims to compare stromal collagen fibre characteristics between in situ and invasive breast tumours using DIC microscopy and investigate the prognostic value of collagen parameters in BC. A tissue microarray was generated from 200 cases, comprising ductal carcinoma in situ (DCIS; n = 100) and invasive tumours (n = 100) with an extra 50 (25 invasive BC and 25 DCIS) cases for validation was utilised. Two sections per case were used: one stained with haematoxylin and eosin (H&E) stain for histological review and one unstained for examination using DIC microscopy. Collagen fibre parameters including orientation angle, fibre alignment, fibre density, fibre width, fibre length and fibre straightness were measured. Collagen fibre density was higher in the stroma of invasive BC (161.68 ± 11.2 fibre/µm2) compared to DCIS (p < 0.0001). The collagen fibres were thinner (13.78 ± 1.08 µm), straighter (0.96 ± 0.006, on a scale of 0-1), more disorganised (95.07° ± 11.39°) and less aligned (0.20 ± 0.09, on a 0-1 scale) in the invasive BC compared to DCIS (all p < 0.0001). A model considering these features was developed that could distinguish between DCIS and invasive tumours with 94% accuracy. There were strong correlations between fibre characteristics and clinicopathological parameters in both groups. A statistically significant association between fibre characteristics and patients' outcomes (breast cancer specific survival, and recurrence free survival) was observed in the invasive group but not in DCIS. Although invasive BC and DCIS were both associated with stromal reaction, the structural features of collagen fibres were significantly different in the two disease stages. Analysis of the stroma fibre characteristics in the preoperative core biopsy specimen may help to differentiate pure DCIS from those associated with invasion.

Temporal gene signature of myofibroblast transformation in Peyronie's disease: first insights into the molecular mechanisms of irreversibility.

BACKGROUND: Transformation of resident fibroblasts to profibrotic myofibroblasts in the tunica albuginea is a critical step in the pathophysiology of Peyronie's disease (PD). We have previously shown that myofibroblasts do not revert to the fibroblast phenotype and we suggested that there is a point of no return at 36 hours after induction of the transformation. However, the molecular mechanisms that drive this proposed irreversibility are not known. AIM: Identify molecular pathways that drive the irreversibility of myofibroblast transformation by analyzing the expression of the genes involved in the process in a temporal fashion. METHODS: Human primary fibroblasts obtained from tunica albuginea of patients with Peyronie's disease were transformed to myofibroblasts using transforming growth factor beta 1 (TGF-ß1). The mRNA of the cells was collected at 0, 24, 36, 48, and 72 hours after stimulation with TGF-ß1 and then analyzed using a Nanostring nCounter Fibrosis panel. The gene expression results were analyzed using Reactome pathway analysis database and ANNi, a deep learning-based inference algorithm based on a swarm approach. OUTCOMES: The study outcome was the time course of changes in gene expression during transformation of PD-derived fibroblasts to myofibroblasts. RESULTS: The temporal analysis of the gene expression revealed that the majority of the changes at the gene expression level happened within the first 24 hours and remained so throughout the 72-hour period. At 36 hours, significant changes were observed in genes involved in MAPK-Hedgehog signaling pathways. CLINICAL TRANSLATION: This study highlights the importance of early intervention in clinical management of PD and the future potential of new drugs targeting the point of no return. STRENGTHS AND LIMITATIONS: The use of human primary cells and confirmation of results with further RNA analysis are the strengths of this study. The study was limited to 760 genes rather than the whole transcriptome. CONCLUSION: This study is to our knowledge the first analysis of temporal gene expression associated with the regulation of the transformation of resident fibroblasts to profibrotic myofibroblasts in PD. Further research is warranted to investigate the role of the MAPK-Hedgehog signaling pathways in reversibility of PD.

Research on biomarkers using innovative artificial intelligence systems in breast cancer.

Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings.

Prognostic significance of microinvasion with ductal carcinoma in situ of the breast: a meta-analysis.

PURPOSE: Ductal carcinoma in situ (DCIS) associated with invasive carcinoma ≤ 1 mm in size is defined as DCIS with microinvasion (DCIS/microinvasion) rather than as invasive breast carcinoma. The number of patients with microinvasion accounts for < 1% of all breast cancer in published studies. As the numbers are limited, the prognostic significance of DCIS/microinvasion has not been clearly elucidated. This meta-analysis aimed to investigate the survival differences between patients with DCIS/microinvasion and those with pure DCIS. METHODS: A meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was performed. We searched three electronic databases (MEDLINE, Cochrane Library, and EMBASE) and included observational studies published in English that contained survival details of patients with either DCIS or DCIS/microinvasion. RESULTS: This study identified 26 studies that described the clinicopathological characteristics of patients in both the DCIS and DCIS/microinvasion groups. Survival differences were evaluated in 10 of 26 studies. Disease-free survival and loco-regional recurrence-free survival were significantly shorter in patients with DCIS/microinvasion than in those with DCIS (Hazard ratio, 1.52; 95% confidence interval, 1.11-2.08; p = 0.01 and hazard ratio, 2.53; 95% confidence interval, 1.45-4.41; p = 0.001, respectively). Both overall survival and distant metastasis-free survival tended to be shorter in patients with DCIS/microinvasion than in patients with DCIS (Hazard ratio, 1.63; 95% CI, 0.63-4.23; p = 0.31 and hazard ratio, 1.85; 95% confidence interval, 0.74-4.66; p = 0.19, respectively) but the difference was not statistically significant. CONCLUSION: Our meta-analysis suggests that DCIS/microinvasion may display more aggressive biological and clinical behavior than pure DCIS, highlighting the potential need for closer follow-up and consideration of adjuvant treatment strategies in DCIS patients with microinvasive disease.

The impact of metabolic endotoxaemia on the browning process in human adipocytes.

BACKGROUND: Dysfunctional adipose tissue (AT) is known to contribute to the pathophysiology of metabolic disease, including type 2 diabetes mellitus (T2DM). This dysfunction may occur, in part, as a consequence of gut-derived endotoxaemia inducing changes in adipocyte mitochondrial function and reducing the proportion of BRITE (brown-in-white) adipocytes. Therefore, the present study investigated whether endotoxin (lipopolysaccharide; LPS) directly contributes to impaired human adipocyte mitochondrial function and browning in human adipocytes, and the relevant impact of obesity status pre and post bariatric surgery. METHODS: Human differentiated abdominal subcutaneous (AbdSc) adipocytes from participants with obesity and normal-weight participants were treated with endotoxin to assess in vitro changes in mitochondrial function and BRITE phenotype. Ex vivo human AbdSc AT from different groups of participants (normal-weight, obesity, pre- and 6 months post-bariatric surgery) were assessed for similar analyses including circulating endotoxin levels. RESULTS: Ex vivo AT analysis (lean & obese, weight loss post-bariatric surgery) identified that systemic endotoxin negatively correlated with BAT gene expression (p < 0.05). In vitro endotoxin treatment of AbdSc adipocytes (lean & obese) reduced mitochondrial dynamics (74.6% reduction; p < 0.0001), biogenesis (81.2% reduction; p < 0.0001) and the BRITE phenotype (93.8% reduction; p < 0.0001). Lean AbdSc adipocytes were more responsive to adrenergic signalling than obese AbdSc adipocytes; although endotoxin mitigated this response (92.6% reduction; p < 0.0001). CONCLUSIONS: Taken together, these data suggest that systemic gut-derived endotoxaemia contributes to both individual adipocyte dysfunction and reduced browning capacity of the adipocyte cell population, exacerbating metabolic consequences. As bariatric surgery reduces endotoxin levels and is associated with improving adipocyte functionality, this may provide further evidence regarding the metabolic benefits of such surgical interventions.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.

BACKGROUND: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. METHODS: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. RESULTS: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. CONCLUSIONS: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Ruthenium(II) Complexes of a Xanthene-Spanned Dicarbene Ligand.

Octahedral ruthenium(II) complexes of a xanthene-di(N-heterocyclic carbene) ancillary ligand (XdC) have been prepared and structurally characterized. Examples catalyze the transfer hydrogenation of ketones {[Ru(CO)I2(C,O,C'-XdC)] (1) and [Ru(CO)(MeCN)2(C,O,C'-XdC)]2+ (22+)} and the selective electrochemical reduction of CO2 to CO {[Ru(N,N'-bpy)(CO)(C,O,C'-XdC)]2+ (32+) at 0.40 V overpotential in MeCN-H2O (1 M)}. The reaction of 1 with KBEt3H afforded isomers of [(C,C'-XdC)Ru(µ-H)(H)]2 dimers, which are stable to reductive elimination of the XdC ligand, thereby suggesting similar (XdC)Rh(coligand)(H)x species may be viable intermediates in catalyses. The electrochemical reduction of CO2 involves a double reduction of 32+ to 3••, which has been characterized by IR-SEC and DFT calculations. The DFT calculations suggest the Ru-Oxanth bond breaks in 3••, opening a metal site for CO2 binding with selectivity over protons enabled by the diffuse nature of the HOMO delocalized over the metal and the bipyridine and carbonyl coligands. The results point to the promise of metal complexes of flexible and hemilabile xanthene-(NHC)2 ancillary ligands in catalysis.

[Fp(CH4)]+, [η5-CpRu(CO)2(CH4)]+, and [η5-CpOs(CO)2(CH4)]+: A Complete Set of Group 8 Metal-Methane Complexes.

Here, we report the NMR spectroscopic analysis of the group 8 transition metal methane σ-complexes [η5-CpM(CO)2(CH4)][Al(OC(CF3)3)4] (M = Fe, Ru) at -90 °C in the weakly coordinating solvent 1,1,1,3,3,3-hexafluoropropane. The iron(II)-methane complex has a 1H resonance at δ -4.27, a 13C resonance at δ -53.0, and 1JC-H = 126 Hz for the bound methane fragment. The ruthenium(II)-methane complex has a 1H resonance at δ -2.10, a 13C resonance at δ -48.8, and a 1JC-H = 126 Hz for the bound methane fragment. DFT and ab initio calculations support these experimental observations and provide further detail on the structures of the [η5-CpM(CO)2(CH4)]+ (M = Fe, Ru) complexes of the Group 8 metals. Both the iron centered methane complex, [η5-CpFe(CO)2(CH4)][Al(OC(CF3)3)4], and the ruthenium centered methane complex, [η5-CpRu(CO)2(CH4)][Al(OC(CF3)3)4], are significantly less stable than the previously reported osmium-methane complex [η5-CpOs(CO)2(CH4)][Al(OC(CF3)3)4].

Prognostic significance of receptor expression discordance between primary and recurrent breast cancers: a meta-analysis.

PURPOSE: This meta-analysis aimed to investigate whether receptor (estrogen receptor [ER], progesterone receptor [PR], and human epidermal growth factor receptor 2 [HER2]) discordances between primary and recurrent breast cancers affect patients' survival. METHODS: Search terms contained ER, PR, and HER2 status details in both primary and recurrent tumors (local recurrence or distant metastasis) in addition to survival outcome data (overall survival [OS] or post-recurrence survival [PRS]). RESULTS: Loss of ER or PR in recurrent tumors was significantly associated with shorter OS as compared with receptor-positive concordance (hazard ratio [HR], 1.67; 95% confidence interval [% CI] 1.37-2.04; p < 0.00001 and HR, 1.45; 95% CI 1.21-1.75; p < 0.0001, respectively). Similar trends were observed in groups with only distant metastasis. Gain of ER was a significant predictor of longer PRS as compared with receptor-negative concordance (HR, 0.76; 95% CI 0.59-0.97; p = 0.03). Gain of PR was not a significant predictor of longer survival compared with receptor-negative concordance, but it could be related to better OS at distant metastasis. Both HER2 of loss and gain could be related to poor outcomes. CONCLUSION: This meta-analysis showed that receptor conversion in recurrent tumors may affect patient survival as compared with receptor concordance.

Defining the area of mitoses counting in invasive breast cancer using whole slide image.

Although counting mitoses is part of breast cancer grading, concordance studies showed low agreement. Refining the criteria for mitotic counting can improve concordance, particularly when using whole slide images (WSIs). This study aims to refine the methodology for optimal mitoses counting on WSI. Digital images of 595 hematoxylin and eosin stained sections were evaluated. Several morphological criteria were investigated and applied to define mitotic hotspots. Reproducibility, representativeness, time, and association with outcome were the criteria used to evaluate the best area size for mitoses counting. Three approaches for scoring mitoses on WSIs (single and multiple annotated rectangles and multiple digital high-power (×40) screen fields (HPSFs)) were evaluated. The relative increase in tumor cell density was the most significant and easiest parameter for identifying hotspots. Counting mitoses in 3 mm2 area was the most representative regarding saturation and concordance levels. Counting in area <2 mm2 resulted in a significant reduction in mitotic count (P = 0.02), whereas counting in area ≥4 mm2 was time-consuming and did not add a significant rise in overall mitotic count (P = 0.08). Using multiple HPSF, following calibration, provided the most reliable, timesaving, and practical method for mitoses counting on WSI. This study provides evidence-based methodology for defining the area and methodology of visual mitoses counting using WSI. Visual mitoses scoring on WSI can be performed reliably by adjusting the number of monitor screens.