ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67

Edible mushroom (Pleurotus cornucopiae) extract vs. glibenclamide on alloxan induced diabetes: sub-acute in vivo study of Nrf2 expression and renal toxicity

The study aims to compare the action of Pleurotus cornucopiae and glibenclamide on alloxan-induced diabetes and ascertain how an aqueous extract of the edible mushroom regulates the expression of nuclear factor erythroid 2-related factor 2 (Nrf2), oxidative stress biomarkers and renal toxicity in a diabetic male Wistar rat model. Twenty-five adult male Wistar rats were randomly grouped into five groups with five rats per. Group 1 and those in the treatment groups received normal feed and water ad libitum. Group 2 received intraperitoneal administration of alloxan monohydrate (150 mg/kg body weight). Group 3 received alloxan monohydrate and glibenclamide (5 mg/kg body weight bwt), group 4 received alloxan monohydrate plus the extract (250 mg/kg bwt) and group 5 received alloxan monohydrate plus the extract (500 mg/kg bwt). The administration of glibenclamide plus the extract was oral for 14 days. Glibenclamide and the extract lowered blood glucose level, catalase, and glutathione peroxidase activities, increased the superoxide dismutase (SOD) activity in rats with alloxan induced diabetes. The extract at 500 mg/kg bwt reduced the plasma urea and sodium concentration in the treated rats. The extract and glibenclamide could detoxify alloxan and restore its induced renal degeneration and glomeruli atrophy, intra renal hemorrhage and inflammation and oxidative biomarkers through activation of Nrf2 expression. The drug glibenclamide and P. cornucopiae have appreciable hypoglycemic activity and potential to restore the normal renal architecture in the rats, hence they offer similar curative effects. Additionally, the extract at 500 mg/kg bwt activated SOD and Nrf2 expression more than glibenclamide in rats with alloxan-induced diabetes.

Histopathologic Differential Diagnosis and Estrogen Receptor/Progesterone Receptor Immunohistochemical Evaluation of Breast Carcinoma Using a Deep Learning-Based Artificial Intelligence Architecture

In breast carcinoma, invasive ductal carcinoma (IDC) is the most common histopathologic subtype, and ductal carcinoma in situ (DCIS) is a precursor of IDC. They are often concomitant. The immunohistochemical staining of estrogen receptor (ER)/progesterone receptor (PR) in IDC/DCIS on whole slide histopathologic images (WSIs) can predict the prognosis of patients. However, the interobserver variability among pathologists in reading WSIs is inevitable. Thus, artificial intelligence (AI) technology is crucial. Herein, IDC/DCIS detection was conducted by a deep learning approach, including faster region-based convolutional neural network (Faster R-CNN), RetinaNet, single-shot multibox detector 300 (SSD300), you only look once (YOLO) v3, YOLOv5, YOLOv7, YOLOv8, and Swin transformer. Their performance was estimated by mean average precision (mAP) values. Cell recognition and counting were performed using AI technology to evaluate the intensity and proportion of ER/PR-immunostained cancer cells in IDC/DCIS. A three-round ring study (RS) was conducted to assess WSIs. A database for modelling the underlying probability distribution of a data set with labels was established. YOLOv8 exhibits the highest detection performance with an mAP at 0.5 of 0.944 and an mAP at 0.5 to 0.95 of 0.790. With the assistance of YOLOv8, the scoring concordance across all pathologists was boosted to excellent in RS3 (0.970) from moderate in RS1 (0.724) and good in RS2 (0.812). Deep learning detection can be applied in the clinicopathologic field. To facilitate the histopathologic diagnosis of IDC/DCIS and immunostaining scoring of ER/PR, a novel AI architecture and well-organized data set were developed.

The REMAR (Rhein-Main-Registry) real-world study: prospective evaluation of the 21-gene breast recurrence score® assay in addition to Ki-67 for adjuvant treatment decisions in early-stage breast cancer

PURPOSE

Ki-67 is recommended by international/national guidelines for risk stratification in early breast cancer (EBC), particularly for defining "intermediate risk," despite inter-laboratory/inter-observer variability and cutoff uncertainty. We investigated Ki-67 (> 10%- < 40%, determined locally) as a prognostic marker for intermediate/high risk in EBC, pN0-1 patients.

METHODS

This prospective, non-interventional, real-world study included females ≥ 18 years, with pN0/pN1mi/pN1, HR+ , HER2-negative EBC, and locally determined Ki-67 ranging 10%-40%. The primary outcome was changes in treatment recommendations after disclosing the Oncotype DX Breast Recurrence Score®(RS) assay result.

RESULTS

The analysis included 567 patients (median age, 57 [range, 29-83] years; 70%/1%/29%/ with pN0/pN1mi/pN1 disease; 81% and 19% with RS results 0-25 and 26-100, respectively). The correlations between local and central Ki-67, local Ki-67, and the RS, and central Ki-67 and the RS results were weak (r = 0.35, r = 0.3, and r = 0.46, respectively), and discrepancies were noted in both directions (e.g., local Ki-67 was lower or higher than central Ki-67). After disclosing the RS, treatment recommendations changed for 190 patients (34%). Changes were observed in pN0 and pN1mi/pN1 patients and in patients with centrally determined Ki-67 ≤ 10% and > 10%. Treatment changes were aligned with RS results (adding chemotherapy for patients with higher RS results, omitting it for lower RS results), and their net result was 8% reduction in adjuvant chemotherapy use (from 32% pre-RS results to 24% post-RS results).

CONCLUSION

The Oncotype DX® assay is a tool for individualizing treatments that adds to classic treatment decision factors. The RS result and Ki-67 are not interchangeable, and Ki-67, as well as nodal status, should not be used as gatekeepers for testing eligibility, to avoid under and overtreatment.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study

BACKGROUND AND AIMS

Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable.

METHODS

We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method.

RESULTS

In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall.

CONCLUSION

With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

NFκB dynamics-dependent epigenetic changes modulate inflammatory gene expression and induce cellular senescence

Upregulation of nuclear factor κB (NFκB) signaling is a hallmark of aging and a major cause of age-related chronic inflammation. However, its effect on cellular senescence remains unclear. Here, we show that alteration of NFκB nuclear dynamics from oscillatory to sustained by depleting a negative feedback regulator of NFκB pathway, NFκB inhibitor alpha (IκBα), in the presence of tumor necrosis factor α (TNFα) promotes cellular senescence. Sustained NFκB activity enhanced inflammatory gene expression through increased NFκB-DNA binding and slowed the cell cycle. IκBα protein was decreased under replicative or oxidative stress in vitro. Furthermore, a decrease in IκBα protein and an increase in DNA-NFκB binding at the transcription start sites of age-associated genes in aged mouse hearts suggested that nuclear NFκB dynamics may play a critical role in the progression of aging. Our study suggests that nuclear NFκB dynamics-dependent epigenetic changes regulated over time in a living system, possibly through a decrease in IκBα, enhance the expression of inflammatory genes to advance the cells to a senescent state.

Histopathological evaluation of infertility: Lessons from laboratory rodents

Infertility is a growing challenge globally with emerging risk factors. There are effective laboratory tests to evaluate infertility in humans, nevertheless, some measures, especially histopathological evaluations, are invasive due to the pain inflicted when accessing the reproductive organs and obtaining samples; hence, their relevance may be limited in humans. However, these histopathological evaluations provide essential information on the etiopathogenesis of infertility and the likely mechanisms of action of potential therapeutic candidates. Also, non-invasive methods are available, such as the assay of testosterone in the blood and semen analysis, both of which are predictors of testicular functions. This review provides detailed information on the available histopathological investigations of infertility, such as qualitative and quantitative histopathological assessments of gonadal tissues, specific cell counts, and sperm morphology characterization, with a focus on the procedures, interpretation, and pathophysiological basis. Data from the literature revealed that histopathological examinations of the reproductive organs, as well as spermatozoa, are useful in understanding the pathogenesis of incident infertility. Histopathological evaluation may range from basic hematoxylin and eosin stains to some special stains. Also, histopathological findings (such as spermatogenic cells and planimetric variables, like seminiferous tubule diameter and theca cell and corpus luteum thickness) may be quantified and analyzed for comparison. Some skill is required for these investigations, which may be a limiting factor; however, they are important tools in translational medicine.

Methyl-CpG binding domain protein 2 (Mbd2) drives breast cancer progression through the modulation of epithelial-to-mesenchymal transition

Methyl-CpG-binding domain protein 2 (Mbd2), a reader of DNA methylation, has been implicated in different types of malignancies, including breast cancer. However, the exact role of Mbd2 in various stages of breast cancer growth and progression in vivo has not been determined. To test whether Mbd2 plays a causal role in mammary tumor growth and metastasis, we performed genetic knockout (KO) of Mbd2 in MMTV-PyMT transgenic mice and compared mammary tumor progression kinetics between the wild-type (PyMT-Mbd2+/+) and KO (PyMT-Mbd2-/-) groups. Our results demonstrated that deletion of Mbd2 in PyMT mice impedes primary tumor growth and lung metastasis at the experimental endpoint (postnatal week 20). Transcriptomic and proteomic analyses of primary tumors revealed that Mbd2 deletion abrogates the expression of several key determinants involved in epithelial-to-mesenchymal transition, such as neural cadherin (N-cadherin) and osteopontin. Importantly, loss of the Mbd2 gene impairs the activation of the PI3K/AKT pathway, which is required for PyMT-mediated oncogenic transformation, growth, and survival of breast tumor cells. Taken together, the results of this study provide a rationale for further development of epigenetic therapies targeting Mbd2 to inhibit the progression of breast cancer.

Curcumin abrogates cobalt-induced neuroinflammation by suppressing proinflammatory cytokines release, inhibiting microgliosis and modulation of ERK/MAPK signaling pathway

Curcumin, a bioactive polyphenol derived from turmeric, has been reported to have anti-inflammatory properties. The current study investigated the anti-inflammatory effect of curcumin in the hippocampal subfields (CA1 and CA3) after exposure to cobalt (Co) and the impact of ERK protein. Twenty-eight albino Wistar rats were divided into four groups, each with seven randomly selected rats as follows: Control (distilled water), Cobalt (Co) only (40 mg/kg), 120 mg/kg or 240 mg/kg curcumin + Co (40 mg/kg). Treatment was via oral gavage for 28 days. We performed a biochemical investigation to determine the levels of proinflammatory cytokines (TNFα and IL-1β). Furthermore, we conducted an immunohistochemical evaluation to assess the expression of IBA1 by microglial cells and the immunoexpression of ERK protein in the hippocampus. Results revealed a significant (p<0.05) elevation in the tissue level of TNFα and IL-1β, an increase in the number of IBA1-positive microglia, and upregulation of ERK protein in the hippocampal subfields of the rats after exposure to cobalt-only. Nevertheless, pretreatment with curcumin restored these parameters to levels comparable to control. In conclusion, our results showed that curcumin abrogated the Co-induced neuroinflammation by suppressing the release of proinflammatory biomarkers, reducing microgliosis, and modulating the ERK/MAPK pathway.

Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Deregulation of lipid composition in adipose tissue adjacent to breast tumour is observed in ex vivo and animal models. Novel non-invasive magnetic resonance imaging (MRI) allows rapid lipid mapping of the human whole breast. We set out to elucidate the spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive (ER +) breast cancer. Thirteen participants (mean age, 62 ± [SD] 6 years) with ER + breast cancer and 13 age-matched postmenopausal healthy controls were scanned on MRI. The number of double bonds in triglycerides was computed from MRI images to derive lipid composition maps of monounsaturated, polyunsaturated, and saturated fatty acids (MUFA, PUFA, SFA). The spatial heterogeneity measures (mean, median, skewness, entropy and kurtosis) of lipid composition in the peri-tumoural region and the whole breast of participants and in the whole breast of controls were computed. The Ki-67 proliferative activity marker and CD163 antibody on tumour-associated macrophages were assessed histologically. Mann Whitney U or Wilcoxon tests and Spearman's coefficients were used to assess group differences and correlations, respectively. For comparison against the whole breast in participants, peri-tumoural MUFA had a lower mean (median (IQR), 0.40 (0.02), p < .001), lower median (0.42 (0.02), p < .001), a negative skewness with lower magnitude (- 1.65 (0.77), p = .001), higher entropy (4.35 (0.64), p = .007) and lower kurtosis (5.13 (3.99), p = .001). Peri-tumoural PUFA had a lower mean (p < .001), lower median (p < .001), a positive skewness with higher magnitude (p = .005) and lower entropy (p = .002). Peri-tumoural SFA had a higher mean (p < .001), higher median (p < .001), a positive skewness with lower magnitude (p < .001) and lower entropy (p = .012). For comparison against the whole breast in controls, peri-tumoural MUFA had a negative skewness with lower magnitude (p = .01) and lower kurtosis (p = .009), however there was no difference in PUFA or SFA. CD163 moderately correlated with peri-tumoural MUFA skewness (rs = - .64), PUFA entropy (rs = .63) and SFA skewness (rs = .59). There was a lower MUFA and PUFA while a higher SFA, and a higher heterogeneity of MUFA while a lower heterogeneity of PUFA and SFA, in the peri-tumoural region in comparison with the whole breast tissue. The degree of lipid deregulation was associated with inflammation as indicated by CD163 antibody on macrophages, serving as potential marker for early diagnosis and response to therapy.

Histopathological Images Analysis and Predictive Modeling Implemented in Digital Pathology-Current Affairs and Perspectives

In modern clinical practice, digital pathology has an essential role, being a technological necessity for the activity in the pathological anatomy laboratories. The development of information technology has majorly facilitated the management of digital images and their sharing for clinical use; the methods to analyze digital histopathological images, based on artificial intelligence techniques and specific models, quantify the required information with significantly higher consistency and precision compared to that provided by optical microscopy. In parallel, the unprecedented advances in machine learning facilitate, through the synergy of artificial intelligence and digital pathology, the possibility of diagnosis based on image analysis, previously limited only to certain specialties. Therefore, the integration of digital images into the study of pathology, combined with advanced algorithms and computer-assisted diagnostic techniques, extends the boundaries of the pathologist's vision beyond the microscopic image and allows the specialist to use and integrate his knowledge and experience adequately. We conducted a search in PubMed on the topic of digital pathology and its applications, to quantify the current state of knowledge. We found that computer-aided image analysis has a superior potential to identify, extract and quantify features in more detail compared to the human pathologist's evaluating possibilities; it performs tasks that exceed its manual capacity, and can produce new diagnostic algorithms and prediction models applicable in translational research that are able to identify new characteristics of diseases based on changes at the cellular and molecular level.

Identifying TOPK and Hypoxia Hallmarks in Esophageal Tumors for Photodynamic/Chemo/Immunotherapy and Liver Metastasis Inhibition with Nanocarriers

Although esophageal squamous cell carcinoma (ESCC) is one of the most lethal cancers, there are major bottlenecks in its therapeutic approaches, primarily the identification of clinically relevant targets and the lack of effective targeted therapeutics. Herein, we identified the hallmarks of ESCC, namely, high T-lymphokine-activated killer cell-originated protein kinase (TOPK) expression in human ESCC tumors and its correlation with poor patient prognosis and hypoxia in the tumor microenvironment. We developed hypoxia-sensitive nanoparticles encapsulating TOPK inhibitor OTS964 and photosensitizer chlorin e6 for the imaging-directed precision therapy of ESCC tumors. The sub-100 nm monodisperse nanoparticles efficiently delivered drugs into the human ESCC KYSE 150 cancer cells to kill the cells. The nanoparticles were selectively accumulated in the ESCC tumors after intravenous (i.v.) injection, thereby enabling the diagnosis and photoacoustic imaging-guided local laser irradiation of tumors. The combination of chemotherapy and photodynamic therapy effectively eradicated human ESCC KYSE 150 tumors and inhibited liver metastasis and recurrence by suppressing TOPK and inducing ESCC cell apoptosis. The nanoparticle-based therapies further stimulated high rates of natural killer cells in ESCC tumors, thereby exhibiting the potential of immunotherapy. This study identified important therapeutic targets of ESCC tumors and delineated an effective nanocarrier-based approach for tumor microenvironment and molecular targeted therapy.

Bacterial protease alleviate chronic liver fibrosis induced by thioacetamide through suppression of hepatic stellate cells consequently decrease its proliferative index

In chronic liver diseases, liver fibrosis occurs due to excessive extracellular matrix (ECM) protein accumulation. Approximately 2 million deaths occur yearly due to liver disease, while cirrhosis is the 11th most common cause of death. Therefore, newer compounds or biomolecules must be synthesized to treat chronic liver diseases. In this aspect, the present study focuses on the assessment of the anti-inflammatory and antioxidant impact of Bacterial Protease (BP) produced by a new mutant strain of bacteria (Bacillus cereus S6-3/UM90) and 4,4'-(2,5-dimethoxy-1,4-phenylene) bis (1-(3-ethoxy phenyl)-1H-1,2,3-triazole) (DPET) in the treatment of early stage of liver fibrosis induced by thioacetamide (TAA). Sixty male rats were divided into six groups, ten rats each as follows: (1) Control group, (2) BP group, (3) TAA group, (4) TAA-Silymarin (S) group, (5) TAA-BP group, and (6) TAA-DPET group. Liver fibrosis significantly elevated liver function ALT, AST, and ALP, as well as anti-inflammatory interleukin 6 (IL-6) and VEGF. The oxidative stress parameters (MDA, SOD, and NO) were significantly increased with a marked reduction in GSH. Expression of MAPK and MCP-1 was unregulated in the TAA group, with downregulation of Nrf₂ was observed. TAA caused histopathological alterations associated with hepatic vacuolation and fibrosis, increasing collagen fibers and high immuno-expression of VEGF. On the other hand, treatment with BP successfully improved the severe effects of TAA on the liver and restored histological architecture. Our study concluded the protective potentials of BP for attenuating liver fibrosis and could be used as adjuvant therapy for treating hepatic fibrosis.

Mitigating Effect of Dietary Dioclea reflexa (Hook F) Seed Inclusion in Experimental Colon Carcinogenesis

Rats exposed to 72-hour intrarectal instillations of N-methyl-N-nitrosourea (MNU) were fed with Dioclea reflexa seed-included diets (0, 2.5, 5.0, and 10%). Following sacrifice, organs and blood were collected and analyzed for indices of oxidative stress and carcinogenesis using spectrophotometric, ELISA, histological, and immunohistochemical techniques. Dioclea reflexa seed-included diets significantly ( $p<0.05$ ) prevented MNU-induced elevation of carcinoembryonic antigen (CEA), malondialdehyde, and neutrophil-to-lymphocyte ratio (NLR) and boosted the activities of glutathione s-transferase, superoxide dismutase, and catalase. It also prevented MNU-induced colonic mucosal ulceration/interglandular inflammations and protected the mismatch repair gene, Mutl homolog1, against MNU-induced damage. There was a strong negative relationship between CEA, NLR, and the antioxidant enzyme activities, as well as total polyphenols, total flavonoids, and crude fiber, while CEA correlated positively with malondialdehyde levels. These results suggest that Dioclea reflexa seed is endowed with constituents possessing a potent capacity to mitigate oxidative stress, as well as the initiation and promotion of chemically induced colon carcinogenesis.

Modulatory Role of Curcumin on Cobalt-Induced Memory Deficit, Hippocampal Oxidative Damage, Astrocytosis, and Nrf2 Expression

Chemical overexposure is a growing environmental risk factor for many medical issues. Cobalt toxicity from environmental, industrial, and medical exposure has previously been linked to neurological impairment. Hence, the current study looked into the neuroprotective potential of curcumin, a natural polyphenol contained in the spice turmeric, against cobalt-induced neurotoxicity. Adult rats were randomly divided into six groups as follows: control, 40 mg/kg cobalt chloride (CoCl₂) only, 240 mg/kg curcumin only, 120 mg/kg or 240 mg/kg curcumin, or 100 mg/kg vitamin C co-administered with CoCl₂. The administration was via oral route daily for 4 weeks. After that, neurobehavioral tests were undertaken to evaluate short-term spatial memory. Biochemical investigation was performed to determine the hippocampal levels of status via measures of SOD, CAT, GST, and LPO. Furthermore, immunohistochemical assessment of the expression of GFAP and Nrf2 in the hippocampus was carried out. In the CoCl₂ group, the results showed altered behavioral responses, a decrease in antioxidant activities, increased expression of GFAP and the number of activated astrocytes, and decreased immunoexpression of Nrf2. These effects were mitigated in the curcumin- and vitamin C-treated groups. These results collectively imply that curcumin enhances memory functions in rats exposed to cobalt possibly by attenuating oxidative responses, mitigating astrocytosis, and modulating Nrf2 signaling.

Artificial intelligence in breast cancer histopathology

This is a review on the use of artificial intelligence for digital breast pathology. A systematic search on PubMed was conducted, identifying 17,324 research papers related to breast cancer pathology. Following a semimanual screening, 664 papers were retrieved and pursued. The papers are grouped into six major tasks performed by pathologists-namely, molecular and hormonal analysis, grading, mitotic figure counting, ki-67 indexing, tumour-infiltrating lymphocyte assessment, and lymph node metastases identification. Under each task, open-source datasets for research to build artificial intelligence (AI) tools are also listed. Many AI tools showed promise and demonstrated feasibility in the automation of routine pathology investigations. We expect continued growth of AI in this field as new algorithms mature.

Effect of chlorogenic acid plus donepezil on critical neurocortical enzyme activities, inflammatory markers, and synaptophysin immunoreactivity in scopolamine-assaulted rats, supported by multiple ligand simultaneous docking

The effect of chlorogenic acid (a natural phenolic acid ubiquitous in plant foods) on selected therapeutic properties of donepezil (DON) in a scopolamine (SCOP)-induced rat model of amnesia was the focus of this study. Adult albino (Wister strain) rats were allocated into five groups (n = 11) consisting of control, SCOP, SCOP + chlorogenic acid (CGA), SCOP + DON, and SCOP + CGA + DON for 7 days. Post-treatment, the rat brain cerebral cortex homogenate was assayed for cholinesterase and monoamine oxidase activities. Also, the reactive oxygen species, total thiol and nitric oxide contents, alongside catalase, and superoxide dismutase activities were determined. Routine histology for neuronal and glial cells as well as synaptophysin immunoreactivity was also carried out on the cerebral cortex. Thereafter, multiple ligand simultaneous docking was carried out for DON and CGA at the active sites of AChE and BChE. The results revealed that the biochemical parameters, glial cells, and synaptophysin immunoreactivity were significantly impaired in the cerebral cortex of scopolamine-treated rats. However, impaired butyrylcholinesterase and monoamine oxidase activity, together with antioxidant, glial cells, and synaptophysin levels were significantly ameliorated in scopolamine-treated rats administered DON + CGA compared to donepezil alone. The docking of both DON and CGA at the active sites of AChE or BChE showed higher binding energy to both enzymes compared to individual interactions of either DON or CGA. Hence, this study has been able to show that CGA could improve some of the therapeutic effects of DON, which could broaden the therapeutic spectrum of this drug. PRACTICAL APPLICATIONS: This study showed that chlorogenic acid (a major phenolic acid found in plant foods such as coffee) modulated some of the therapeutic properties of donepezil (an anticholinesterase drug used in the treatment of mild-to-moderate Alzheimer's disease). The combinations elicited better anti-butyrylcholinesterase, antimonoamine oxidase, and antioxidant properties, thus presenting this food-drug interaction as potentially able to offer better therapeutic properties.

Validation of a color deconvolution method to quantify MSC tri-lineage differentiation across species

Mesenchymal stem cells (MSCs) are a promising candidate for both human and veterinary regenerative medicine applications because of their abundance and ability to differentiate into several lineages. Mesenchymal stem cells are however a heterogeneous cell population and as such, it is imperative that they are unequivocally characterized to acquire reproducible results in clinical trials. Although the tri-lineage differentiation potential of MSCs is reported in most veterinary studies, a qualitative evaluation of representative histological images does not always unambiguously confirm tri-lineage differentiation. Moreover, potential differences in differentiation capacity are not identified. Therefore, quantification of tri-lineage differentiation would greatly enhance proper characterization of MSCs. In this study, a method to quantify the tri-lineage differentiation potential of MSCs is described using digital image analysis, based on the color deconvolution plug-in (ImageJ). Mesenchymal stem cells from three species, i.e., bovine, equine, and porcine, were differentiated toward adipocytes, chondrocytes, and osteocytes. Subsequently, differentiated MSCs were stained with Oil Red O, Alcian Blue, and Alizarin Red S, respectively. Next, a differentiation ratio (DR) was obtained by dividing the area % of the differentiation signal by the area % of the nuclear signal. Although MSCs isolated from all donors in all species were capable of tri-lineage differentiation, differences were demonstrated between donors using this quantitative DR. Our straightforward, simple but robust method represents an elegant approach to determine the degree of MSC tri-lineage differentiation across species. As such, differences in differentiation potential within the heterogeneous MSC population and between different MSC sources can easily be identified, which will support further optimization of regenerative therapies.

The IL-4/IL-13 signaling axis promotes prostatic fibrosis

Background

Lower urinary tract symptoms (LUTS) are a costly and pervasive medical problem for millions of aging men. Recent studies have showed that peri-urethral tissue fibrosis is an untreated pathobiology contributing to LUTS. Fibrosis results from excessive extracellular matrix deposition which increases transition zone and peri-urethral tissue stiffness and compromises prostatic urethral flexibility and compliance, producing urinary obstructive symptoms. Inflammatory cells, including neutrophils, macrophages, and T-lymphocytes, secrete a medley of pro-fibrotic proteins into the prostatic microenvironment, including IFNγ, TNFα, CXC-type chemokines, and interleukins, all of which have been implicated in inflammation-mediated fibrosis. Among these, IL-4 and IL-13 are of particular interest because they share a common signaling axis that, as shown here for the first time, promotes the expression and maintenance of IL-4, IL-13, their cognate receptors, and ECM components by prostate fibroblasts, even in the absence of immune cells. Based on studies presented here, we hypothesize that the IL-4/IL-13 axis promotes prostate fibroblast activation to ECM-secreting cells.

Methods

N1 or SFT1 immortalized prostate stromal fibroblasts were cultured and treated, short- or long-term, with pro-fibrotic proteins including IL-4, IL-13, TGF-β, TNF-α, IFNγ, with or without prior pre-treatment with antagonists or inhibitors. Protein expression was assessed by immunohistochemistry, immunofluorescence, ELISA, immunoblot, or Sircoll assays. Transcript expression levels were determined by qRT-PCR. Intact cells were counted using WST assays.

Results

IL-4Rα, IL-13Rα1, and collagen are concurrently up-regulated in human peri-urethral prostate tissues from men with LUTS. IL-4 and IL-13 induce their own expression as well as that of their cognate receptors, IL-4Rα and IL-13Rα1. Low concentrations of IL-4 or IL-13 act as cytokines to promote prostate fibroblast proliferation, but higher (>40ng/ml) concentrations repress cellular proliferation. Both IL-4 and IL-13 robustly and specifically promote collagen transcript and protein expression by prostate stromal fibroblasts in a JAK/STAT-dependent manner. Moreover, IL-4 and IL-13-mediated JAK/STAT signaling is coupled to activation of the IL-4Rα receptor.

Conclusions

Taken together, these studies show that IL-4 and IL-13 signal through the IL-4Rα receptor to activate JAK/STAT signaling, thereby promoting their own expression, that of their cognate receptors, and collagens. These finding suggest that the IL-4/IL-13 signaling axis is a powerful, but therapeutically targetable, pro-fibrotic mechanism in the lower urinary tract.

Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic Review

Breast cancer is the most common disease among women, with over 2.1 million new diagnoses each year worldwide. About 30% of patients initially presenting with early stage disease have a recurrence of cancer within 10 years. Predicting who will have a recurrence and who will not remains challenging, with consequent implications for associated treatment. Artificial intelligence strategies that can predict the risk of recurrence of breast cancer could help breast cancer clinicians avoid ineffective overtreatment. Despite its significance, most breast cancer recurrence datasets are insufficiently large, not publicly available, or imbalanced, making these studies more difficult. This systematic review investigates the role of artificial intelligence in the prediction of breast cancer recurrence. We summarise common techniques, features, training and testing methodologies, metrics, and discuss current challenges relating to implementation in clinical practice. We systematically reviewed works published between 1 January 2011 and 1 November 2021 using the methodology of Kitchenham and Charter. We leveraged Springer, Google Scholar, PubMed, and IEEE search engines. This review found three areas that require further work. First, there is no agreement on artificial intelligence methodologies, feature predictors, or assessment metrics. Second, issues such as sampling strategies, missing data, and class imbalance problems are rarely addressed or discussed. Third, representative datasets for breast cancer recurrence are scarce, which hinders model validation and deployment. We conclude that predicting breast cancer recurrence remains an open problem despite the use of artificial intelligence.

DAB-quant: An open-source digital system for quantifying immunohistochemical staining with 3,3'-diaminobenzidine (DAB)

Here, we describe DAB-quant, a novel, open-source program designed to facilitate objective quantitation of immunohistochemical (IHC) signal in large numbers of tissue slides stained with 3,3'-diaminobenzidine (DAB). Scanned slides are arranged into separate folders for negative controls and test slides, respectively. Otsu's method is applied to the negative control slides to define a threshold distinguishing tissue from empty space, and all pixels deemed tissue are scored for normalized red minus blue (NRMB) color intensity. Next, a user-defined tolerance for error is applied to the negative control slides to set a NRMB threshold distinguishing stained from unstained tissue and this threshold is applied to calculate the fraction of stained tissue pixels on each test slide. Results are recorded in a spreadsheet and pseudocolor images are presented to document how each pixel was categorized. Slides can be analyzed in full, or sampled using small boxes scattered randomly and automatically across the tissue area. Quantitation of sampling boxes enables faster processing, reveals the degree of heterogeneity of signal, and enables exclusion of problem areas on a slide, if needed. This system should prove useful for a broad range of applications. The code, usage instructions, and sample data are freely and publicly available on GitHub (https://github.com/sarafridov/DAB-quant) and at protocols.io (dx.doi.org/10.17504/protocols.io.dm6gpb578lzp/v1).

Impact of artificial intelligence on pathologists' decisions: an experiment

OBJECTIVE

The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this paper is to determine the reliance of pathologists on AI and to investigate whether providing information on AI impacts this reliance.

MATERIALS AND METHODS

The experiment using an online survey design. Under 3 conditions, 116 pathologists and pathology students were tasked with assessing the Gleason grade for a series of 12 prostate biopsies: (1) without AI recommendations, (2) with AI recommendations, and (3) with AI recommendations accompanied by information about the algorithm itself, specifically algorithm accuracy rate and algorithm decision-making process.

RESULTS

Participant responses were significantly more accurate with the AI decision aids than without (92% vs 87%, odds ratio 13.30, P < .01). Unexpectedly, the provision of information on the algorithm made no significant difference compared to AI without information. The reliance on AI correlated with general beliefs on AI's usefulness but not with particular assessments of the AI tool offered. Decisions were made faster when AI was provided.

DISCUSSION

These results suggest that pathologists are willing to rely on AI regardless of accuracy or explanations. Generalization beyond the specific tasks and explanations provided will require further studies.

CONCLUSION

This study suggests that the factors that influence the reliance on AI differ in practice from beliefs expressed by clinicians in surveys. Implementation of AI in prospective settings should take individual behaviors into account.

A conserved YAP/Notch/REST network controls the neuroendocrine cell fate in the lungs

The Notch pathway is a conserved cell-cell communication pathway that controls cell fate decisions. Here we sought to determine how Notch pathway activation inhibits the neuroendocrine cell fate in the lungs, an archetypal process for cell fate decisions orchestrated by Notch signaling that has remained poorly understood at the molecular level. Using intratumoral heterogeneity in small-cell lung cancer as a tractable model system, we uncovered a role for the transcriptional regulators REST and YAP as promoters of the neuroendocrine to non-neuroendocrine transition. We further identified the specific neuroendocrine gene programs repressed by REST downstream of Notch in this process. Importantly, we validated the importance of REST and YAP in neuroendocrine to non-neuroendocrine cell fate switches in both developmental and tissue repair processes in the lungs. Altogether, these experiments identify conserved roles for REST and YAP in Notch-driven inhibition of the neuroendocrine cell fate in embryonic lungs, adult lungs, and lung cancer.

Developing image analysis methods for digital pathology

The potential to use quantitative image analysis and artificial intelligence is one of the driving forces behind digital pathology. However, despite novel image analysis methods for pathology being described across many publications, few become widely adopted and many are not applied in more than a single study. The explanation is often straightforward: software implementing the method is simply not available, or is too complex, incomplete, or dataset‐dependent for others to use. The result is a disconnect between what seems already possible in digital pathology based upon the literature, and what actually is possible for anyone wishing to apply it using currently available software. This review begins by introducing the main approaches and techniques involved in analysing pathology images. I then examine the practical challenges inherent in taking algorithms beyond proof‐of‐concept, from both a user and developer perspective. I describe the need for a collaborative and multidisciplinary approach to developing and validating meaningful new algorithms, and argue that openness, implementation, and usability deserve more attention among digital pathology researchers. The review ends with a discussion about how digital pathology could benefit from interacting with and learning from the wider bioimage analysis community, particularly with regard to sharing data, software, and ideas. © 2022 The Author. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

AI Model for Prostate Biopsies Predicts Cancer Survival

An artificial intelligence (AI) algorithm for prostate cancer detection and grading was developed for clinical diagnostics on biopsies. The study cohort included 4221 scanned slides from 872 biopsy sessions at the HUS Helsinki University Hospital during 2016–2017 and a subcohort of 126 patients treated by robot-assisted radical prostatectomy (RALP) during 2016–2019. In the validation cohort (n = 391), the model detected cancer with a sensitivity of 98% and specificity of 98% (weighted kappa 0.96 compared with the pathologist’s diagnosis). Algorithm-based detection of the grade area recapitulated the pathologist’s grade group. The area of AI-detected cancer was associated with extra-prostatic extension (G5 OR: 48.52; 95% CI 1.11–8.33), seminal vesicle invasion (cribriform G4 OR: 2.46; 95% CI 0.15–1.7; G5 OR: 5.58; 95% CI 0.45–3.42), and lymph node involvement (cribriform G4 OR: 2.66; 95% CI 0.2–1.8; G5 OR: 4.09; 95% CI 0.22–3). Algorithm-detected grade group 3–5 prostate cancer depicted increased risk for biochemical recurrence compared with grade groups 1–2 (HR: 5.91; 95% CI 1.96–17.83). This study showed that a deep learning model not only can find and grade prostate cancer on biopsies comparably with pathologists but also can predict adverse staging and probability for recurrence after surgical treatment.

UV-induced local immunosuppression in the tumour microenvironment of eccrine porocarcinoma and poroma

Eccrine porocarcinoma (EPC) is a rare malignant adnexal tumour of the skin. Part of EPCs develop from their benign counterpart, poroma (EP), with chronic light exposure and immunosuppression hypothesized to play a role in the malignant transformation. However, the impact of chronic light exposure on the microenvironment of EPCs and EPs has not been investigated yet. Although the clinical relevance of tumour infiltrating lymphocytes (TILs) and tertiary lymphoid structures (TLSs) has been established in various tumours, their distribution and significance in EPCs and EPs is still poorly understood. We characterized the distribution of TILs and TLSs using CD3, CD4, CD8, CD20 immunohistochemistry in a cohort of 10 EPCs and 49 EPs. We then classified our samples using solar-elastosis grading, analyzing the influence of ultraviolet (UV) damage on TIL density. A negative correlation between UV damage and TIL density was observed (CD4 r = −0.286, p = 0.04. CD8 r = −0.305, p = 0.033). No significant difference in TIL density was found between EPCs and EPs. TLS was scarse with the presence rate 10% in EPCs and 8.3% in EPs. The results suggest that UV has an immunosuppressive effect on the microenvironment of EPCs and EPs.

Artificial intelligence to identify genetic alterations in conventional histopathology

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues. In many tumor types, a limited set of molecular tests is currently part of standard diagnostic workflows. However, universal testing for all targetable alterations, especially rare ones, is limited by the cost and availability of molecular assays. From 2017 to 2021, multiple studies have shown that artificial intelligence (AI) methods can predict the probability of specific genetic alterations directly from conventional hematoxylin and eosin (H&E) tissue slides. Although these methods are currently less accurate than gold-standard testing (e.g. immunohistochemistry, polymerase chain reaction or next-generation sequencing), they could be used as pre-screening tools to reduce the workload of genetic analyses. In this systematic literature review, we summarize the state of the art in predicting molecular alterations from H&E using AI. We found that AI methods perform reasonably well across multiple tumor types, although few algorithms have been broadly validated. In addition, we found that genetic alterations in FGFR, IDH, PIK3CA, BRAF, TP53 and DNA repair pathways are predictable from H&E in multiple tumor types, while many other genetic alterations have rarely been investigated or were only poorly predictable. Finally, we discuss the next steps for the implementation of AI-based surrogate tests in diagnostic workflows. This article is protected by copyright. All rights reserved.

Peri-tumoural spatial distribution of lipid composition and tubule formation in breast cancer

BACKGROUND

Response guided treatment in breast cancer is highly desirable, but the effectiveness is only established based on residual cellularity from histopathological analysis after surgery. Tubule formation, a key component of grading score, is directly associated with cellularity, with significant implications on prognosis. Peri-tumoural lipid composition, a potential marker, can be rapidly mapped across the entire breast using novel method of chemical shift-encoded imaging, enabling the quantification of spatial distribution. We hypothesise that peri-tumoural spatial distribution of lipid composition is sensitive to tumour cellular differentiation and proliferative activity.

METHODS

Twenty whole tumour specimens freshly excised from patients with invasive ductal carcinoma (9 Score 2 and 11 Score 3 in tubule formation) were scanned on a 3 T clinical scanner (Achieva TX, Philips Healthcare). Quantitative lipid composition maps were acquired for polyunsaturated, monounsaturated, and saturated fatty acids (PUFA, MUFA, SFA). The peri-tumoural spatial distribution (mean, skewness, entropy and kurtosis) of each lipid constituent were then computed. The proliferative activity marker Ki-67 and tumour-infiltrating lymphocytes (TILs) were assessed histologically.

RESULTS

For MUFA, there were significant differences between groups in mean (p = 0.0119), skewness (p = 0.0116), entropy (p = 0.0223), kurtosis (p = 0.0381), and correlations against Ki-67 in mean (ρ = -0.5414), skewness (ρ = 0.6045) and entropy (ρ = 0.6677), and TILs in mean (ρ = -0.4621). For SFA, there were significant differences between groups in mean (p = 0.0329) and skewness (p = 0.0111), and correlation against Ki-67 in mean (ρ = 0.5910). For PUFA, there was no significant difference in mean, skewness, entropy or kurtosis between the groups.

CONCLUSIONS

There was an association between peri-tumoural spatial distribution of lipid composition with tumour cellular differentiation and proliferation. Peri-tumoural lipid composition imaging might have potential in non-invasive quantitative assessment of patients with breast cancer for treatment planning and monitoring.

The clinical impacts of molecular subtyping by multigene assay on hormone receptor-positive breast cancers

BACKGROUND

Multigene assays, such as MammaPrint and BluePrint, provide additional information other than conventional immunohistochemistry (IHC) to help making decision of treatment. This study aims to compare the clinical correlation between molecular subtyping (MS) versus surrogate pathological subtyping (PS).

METHODS

A database from patients receiving MS evaluation in Taipei Veterans General Hospital from 2013 to 2018 was reviewed retrospectively. Patients were categorized as luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) and basal type from MS results and also centrally assessed according to PS (estrogen receptor [ER], progesterone receptor [PgR], HER2, and Ki-67). The clinical correlation between two different subtyping methodologies was analyzed, and the application of chemotherapy was compared.

RESULTS

From 2013 to 2018, a total of 130 patients received MS testing in our institute, and 132 tumor samples were sent for analysis. From MammaPrint, 64 (48.5%) and 55 (41.7%) samples were defined as low and high risks, respectively. The other 13 (9.8%) tumor samples were identified as late recurrence low risk. MS restratified 44 tumors as subtype shifting including 20 tumors from A to B in intrinsic subtypes and 24 tumors from B to A after MS evaluation. Chemotherapy was conducted in only one (1.3%) patient with MS-luminal A but in 87.8% (n = 43) of MS-luminal B subtypes.

CONCLUSION

The MS results restratify the subtypes of hormone receptor positive breast cancer and dominate decision-making of adjuvant therapy. The role of surrogate biomarkers as an alternative tool needs further elucidation. The treatment outcome in different subtypes categorized by MS or PS will be the interesting focus of research.

Assessment of Ki-67 proliferation index with deep learning in DCIS (ductal carcinoma in situ)

The proliferation index (PI) is crucial in histopathologic diagnostics, in particular tumors. It is calculated based on Ki-67 protein expression by immunohistochemistry. PI is routinely evaluated by a visual assessment of the sample by a pathologist. However, this approach is far from ideal due to its poor intra- and interobserver variability and time-consuming. These factors force the community to seek out more precise solutions. Virtual pathology as being increasingly popular in diagnostics, armed with artificial intelligence, may potentially address this issue. The proposed solution calculates the Ki-67 proliferation index by utilizing a deep learning model and fuzzy-set interpretations for hot-spots detection. The obtained region-of-interest is then used to segment relevant cells via classical methods of image processing. The index value is approximated by relating the total surface area occupied by immunopositive cells to the total surface area of relevant cells. The achieved results are compared to the manual calculation of the Ki-67 index made by a domain expert. To increase results reliability, we trained several models in a threefold manner and compared the impact of different hyper-parameters. Our best-proposed method estimates PI with 0.024 mean absolute error, which gives a significant advantage over the current state-of-the-art solution.

Healthy and pro-inflammatory gut ecology plays a crucial role in the digestion and tolerance of a novel Gluten Friendly™ bread in celiac subjects: a randomized, double blind, placebo control in vivo study

Gluten Friendly™ (GF) is a new gluten achieved through a physicochemical process applied to wheat kernels. The goal of this research was to assess the in vivo effects of Gluten Friendly™ bread on celiac gut mucosa and microbiota. In a double-blind placebo-controlled intervention study, 48 celiac disease (CD) patients were randomized into 3 groups to eat 100 g of bread daily, containing different doses (0; 3 g; 6 g) of GF for 12 weeks. The small-bowel morphology (VH/CrD), intraepithelial densities of CD3+, celiac serology, MUC2, CB1, gut permeability, proinflammatory cytokines, gluten in stools, symptoms, and gut microbial composition were assessed. All 48 CD subjects experienced no symptoms. K-means analysis evidenced celiac subjects clustering around unknown parameters independent of GF dosage: K1 35%; K2 30%; K3 35%. VH/CrD significantly decreased in K1 and K2. VH/CrD did not correlate with IEL increase in K2. 33-mer was not detected in 47% and 73% of patients in both K1 and K2, respectively. VH/CrD and IEL did not change significantly and strongly correlated with the absence of 33-mer in K3. Inflammation and VH/CrD decrease are strongly related with the presence of proinflammatory species at the baseline. A boost in probiotic, butyrate-producing genera, is strongly related with GF tolerance at the end of the trial. Our research suggests that a healthy and proinflammatory ecology could play a crucial role in the digestion and tolerance of the new gluten molecule in celiac subjects. However, GF can be completely digested by gut microbiota of CD subjects and shapes it toward gut homeostasis by boosting healthy butyrate-producing populations. The clinical trial registry number is NCT03137862 (https://clinicaltrials.gov).

Signaling by the tyrosine kinase Yes promotes liver cancer development

Most patients with hepatocellular carcinoma (HCC) are diagnosed at a late stage and have few therapeutic options and a poor prognosis. This is due to the lack of clearly defined underlying mechanisms or a dominant oncogene that can be targeted pharmacologically, unlike in other cancer types. Here, we report the identification of a previously uncharacterized oncogenic signaling pathway in HCC that is mediated by the tyrosine kinase Yes. Using genetic and pharmacological interventions in cellular and mouse models of HCC, we showed that Yes activity was necessary for HCC cell proliferation. Transgenic expression of activated Yes in mouse hepatocytes was sufficient to induce liver tumorigenesis. Yes phosphorylated the transcriptional coactivators YAP and TAZ (YAP/TAZ), promoting their nuclear accumulation and transcriptional activity in HCC cells and liver tumors. We also showed that YAP/TAZ were effectors of the Yes-dependent oncogenic transformation of hepatocytes. Src family kinase activation correlated with the tyrosine phosphorylation and nuclear localization of YAP in human HCC and was associated with increased tumor burden in mice. Specifically, high Yes activity predicted shorter overall survival in patients with HCC. Thus, our findings identify Yes as a potential therapeutic target in HCC.

Spatial analysis of histology in 3D: quantification and visualization of organ and tumor level tissue environment

Histological changes in tissue are of primary importance in pathological research and diagnosis. Automated histological analysis requires ability to computationally separate pathological alterations from normal tissue. Conventional histopathological assessments are performed from individual tissue sections, leading to the loss of three-dimensional context of the tissue. Yet, the tissue context and spatial determinants are critical in several pathologies, such as in understanding growth patterns of cancer in its local environment. Here, we develop computational methods for visualization and quantitative assessment of histopathological alterations in three dimensions. First, we reconstruct the 3D representation of the whole organ from serial sectioned tissue. Then, we proceed to analyze the histological characteristics and regions of interest in 3D. As our example cases, we use whole slide images representing hematoxylin-eosin stained whole mouse prostates in a Pten+/- mouse prostate tumor model. We show that quantitative assessment of tumor sizes, shapes, and separation between spatial locations within the organ enable characterizing and grouping tumors. Further, we show that 3D visualization of tissue with computationally quantified features provides an intuitive way to observe tissue pathology. Our results underline the heterogeneity in composition and cellular organization within individual tumors. As an example, we show how prostate tumors have nuclear density gradients indicating areas of tumor growth directions and reflecting varying pressure from the surrounding tissue. The methods presented here are applicable to any tissue and different types of pathologies. This work provides a proof-of-principle for gaining a comprehensive view from histology by studying it quantitatively in 3D.

Varying outcomes of triple-negative breast cancer in different age groups-prognostic value of clinical features and proliferation

PURPOSE

Triple-negative breast cancer (TNBC) is an aggressive disease lacking specific biomarkers to guide treatment decisions. We evaluated the combined prognostic impact of clinical features and novel biomarkers of cell cycle-progression in age-dependent subgroups of TNBC patients.

METHODS

One hundred forty seven TNBC patients with complete clinical data and up to 18 year follow-up were collected from Turku University Hospital, Finland. Eight biomarkers for cell division were immunohistochemically detected to evaluate their clinical applicability in relation to patient and tumor characteristics.

RESULTS

Age at diagnosis was the decisive factor predicting disease-specific mortality in TNBC (p = 0.002). The established prognostic features, nodal status and Ki-67, predicted survival only when combined with age. The outcome and prognostic features differed significantly between age groups, middle-aged patients showing the most favorable outcome. Among young patients, only lack of basal differentiation predicted disease outcome, indicating 4.5-fold mortality risk (p = 0.03). Among patients aged > 57, the established prognostic features predicted disease outcome with up to 3.0-fold mortality risk for tumor size ≥ 2 cm (p = 0.001). Concerning cell proliferation, Ki-67 alone was a significant prognosticator among patients aged > 57 years (p = 0.009). Among the studied cell cycle-specific biomarkers, only geminin predicted disease outcome, indicating up to 6.2-fold increased risk of mortality for tumor size < 2 cm (p = 0.03).

CONCLUSION

Traditional clinical features do not provide optimal prognostic characterization for all TNBC patients. Young age should be considered as an additional adverse prognostic feature in therapeutic considerations. Increased proliferation, as evaluated using Ki-67 or geminin immunohistochemistry, showed potential in detecting survival differences in subgroups of TNBC.

Comparing the Expressions of Vitamin D Receptor, Cell Proliferation, and Apoptosis in Gastric Mucosa With Gastritis, Intestinal Metaplasia, or Adenocarcinoma Change

Background: This study aimed to compare the expression of vitamin D receptor (VDR), cell proliferation, and apoptosis in the gastric mucosa of patients with gastritis, intestinal metaplasia (IM), and adenocarcinoma using artificial intelligence.

Material and Methods: This study retrospectively enrolled patients at the Keelung Chang Gung Memorial Hospital from November of 2016 to June, 2017, who were diagnosed with gastric adenocarcinoma. The inclusion criteria were patients' pathologic reports that revealed all compartments of Helicobacter pylori infection, gastritis, IM, and adenocarcinoma simultaneously in the same gastric sample. Tissue slides after immunohistochemical (IHC) staining were transformed into digital images using a scanner and counted using computer software (QuPath and ImageJ). IHC staining included PA1-711 antibody for VDR, Ki67 antigen for proliferation, and M30 antibody CK18 for apoptosis.

Results: Twenty-nine patients were included in the IHC staining quantitative analysis. The mean age was 69.1 ± 11.3 y/o. Most (25/29, 86.2%) patients had poorly differentiated adenocarcinoma. The mean expression of Ki67 and CK18 increased progressively from gastritis and IM to adenocarcinoma, with statistical significance (P < 0.05). VDR expression did not correlate with Ki67 or CK18 expression. Survival time was only correlated with tumor stage (correlation coefficient = −0.423, P value < 0.05), but was not correlated with the expression of VDR, Ki67, and CK18.

Conclusion: Ki67 expression and CK18 expression progressively increased in the areas of gastritis, IM, and adenocarcinoma. No correlation between VDR expression and Ki67 or CK18 expression was found in this study.

The additional value of ONEST (Observers Needed to Evaluate Subjective Tests) in assessing reproducibility of oestrogen receptor, progesterone receptor, and Ki67 classification in breast cancer

The reproducibility of assessing potential biomarkers is crucial for their implementation. ONEST (Observers Needed to Evaluate Subjective Tests) has been recently introduced as a new additive evaluation method for the assessment of reliability, by demonstrating how the number of observers impact on interobserver agreement. Oestrogen receptor (ER), progesterone receptor (PR), and Ki67 proliferation marker immunohistochemical stainings were assessed on 50 core needle biopsy and 50 excision samples from breast cancers by 9 pathologists according to daily practice. ER and PR statuses based on the percentages of stained nuclei were the most consistently assessed parameters (intraclass correlation coefficients, ICC 0.918-0.996), whereas Ki67 with 5 different theoretical or St Gallen Consensus Conference-proposed cut-off values demonstrated moderate to good reproducibility (ICC: 0.625-0.760). ONEST highlighted that consistent tests like ER and PR assessment needed only 2 or 3 observers for optimal evaluation of reproducibility, and the width between plots of the best and worst overall percent agreement values for 100 randomly selected permutations of observers was narrow. In contrast, with less consistently evaluated tests of Ki67 categorization, ONEST suggested at least 5 observers required for more trustful assessment of reliability, and the bandwidth of the best and worst plots was wider (up to 34% difference between two observers). ONEST has additional value to traditional calculations of the interobserver agreement by not only highlighting the number of observers needed to trustfully evaluate reproducibility but also by highlighting the rate of agreement with an increasing number of observers and disagreement between the better and worse ratings.

Progestin Significantly Inhibits Carcinogenesis in the Mogp-TAg Transgenic Mouse Model of Fallopian Tube Cancer

Recent studies suggest that the fallopian tube epithelium (FTE) harbors the precursor for high grade ovarian cancer, creating opportunities for targeting the FTE for ovarian cancer prevention. Preclinical evidence supports progestins as ovarian cancer preventives, but the effect of progestins on the FTE is not well characterized. The murine oviduct-specific glycoprotein promotor-driven simian virus 40 large T-Antigen (mogp-TAg) transgenic mouse model develops neoplastic lesions in the fallopian tube (FT) in a manner similar to that described in human fallopian and ovarian cancer. In this study, we investigated the inhibitory effects of the progestin Depo-medroxyprogesterone acetate (DMPA) on FT carcinogenesis following treatment for 3 and 7 weeks in 5-week-old mogp-TAg mice. Overall, compared to vehicle-treated mice, the FT of DMPA-treated mice was significantly smaller (p<0.0005), accumulated fewer p53-positive cells, had normal distribution of ciliated cells, less nuclear pleomorphism and epithelial tufting, and had a significantly lower proliferative index (p=0.001). Accumulation of p53 signatures and serous tubal intraepithelial carcinomas (STICs) in the FT was significantly reduced in the DMPA (p<0.0005) treatment group. Moreover, the FT of the DMPA-treated mice developed significantly less adenocarcinoma compared to vehicle (p<0.005) at both treatment time points. DMPA treatment significantly induced cleaved caspase-3 (p<0.0005) in the FTE compared to vehicle suggesting that apoptosis is involved in DMPA-related clearance of abnormal cells from the FT. These data demonstrate that DMPA targets early events in FT carcinogenesis by clearing genetically damaged cells, leading to marked reduction in adenocarcinoma, supporting progestins as chemopreventives for FT and ovarian cancer.

Artificial intelligence applied to breast pathology

The convergence of digital pathology and computer vision is increasingly enabling computers to perform tasks performed by humans. As a result, artificial intelligence (AI) is having an astoundingly positive effect on the field of pathology, including breast pathology. Research using machine learning and the development of algorithms that learn patterns from labeled digital data based on "deep learning" neural networks and feature-engineered approaches to analyze histology images have recently provided promising results. Thus far, image analysis and more complex AI-based tools have demonstrated excellent success performing tasks such as the quantification of breast biomarkers and Ki67, mitosis detection, lymph node metastasis recognition, tissue segmentation for diagnosing breast carcinoma, prognostication, computational assessment of tumor-infiltrating lymphocytes, and prediction of molecular expression as well as treatment response and benefit of therapy from routine H&E images. This review critically examines the literature regarding these applications of AI in the area of breast pathology.

Biomimetic cellulose-based superabsorbent hydrogels for treating obesity

In the treatment of obesity, nutritional and behavioral modifications are difficult to implement and maintain. Since vegetable consumption is a fundamental part of many dietary interventions and daily nutrient requirements, we developed a novel cellulose-based superabsorbent hydrogel (CB-SAH) platform, inspired by the composition and mechanical properties of raw vegetables, as a mechanobiological therapy. The CB-SAHs properties were studied in a simulated gastrointestinal environment, while their impact on gut tissue was investigated by an ex vivo organ culture (EVOC) model. Functional fibers and raw vegetables were used as reference. CB-SAHs demonstrated orders of magnitude higher elasticity in comparison to the tested functional fibers, however performed similar to the tested raw vegetables. Notably, the biomimetic CB-SAHs with elasticity levels similar to raw vegetables showed benefits in preserving and regulating the gut tissue in the EVOC model. Non-systemic oral mechanotherapeutics based on this technology were advanced through clinical studies, with a first product cleared as an aid for weight management in the US and Europe.

Canine mammary cancer in overweight or obese female dogs is associated with intratumoral microvessel density and macrophage counts

Obesity is a major health condition owing to its effects on chronic diseases and cancers in humans, but little information is available regarding the role of obesity in canine mammary cancer (CMC). In the present study, we performed immunohistochemistry to investigate the effect of obesity on CMC by analyzing the number of tumor-associated macrophages, intratumoral microvessel density (iMVD), and the expression of prognostic factors including epidermal growth factor receptor (EGFR), cyclooxygenase 2 (COX-2), and Ki67 in CMC specimens. These data were compared in CMC specimens from lean or ideal body weight (Group 1) versus overweight or obese (Group 2) female dogs (n = 60 for each group). Associations between obesity status and histologic characteristics, such as histologic subtype, grading, and lymphatic invasion, were also investigated. Compared with lean or ideal body weight dogs, TAM (tumor-associated macrophage) counts (P < .005) and iMVD (P < .001) were significantly higher in overweight or obese dogs. CMC specimens of dogs in the overweight or obese group also showed higher histologic grade (P < .001). In addition, although no association was found between obesity status and either COX-2 or EGFR expression, Ki67 expression was greater in CMC specimens of overweight or obese dogs (P < .005). The results of this study suggest that obesity may influence CMC development and progression, being associated with higher histologic grade, greater infiltration of TAMs, and increased tumor angiogenesis.

Autochthonous male urothelial carcinoma immune competent model: from induction to BCG transurethral treatment

To describe a new animal model of autochthonous urothelial cancer (UC) accessible by transurethral catheter in males, from induction to treatment. Seven-week-old male Fischer 344 rats were used. The first 10 animals were used to overcome and standardize the technical challenges of safe transurethral catheterization of male rats. The remaining 14 animals underwent intravesical N-Methyl-Nitrosourea (MNU) instillation for UC induction, of which six were randomized to undergo intravesical BCG treatment. The stretched male rat urethra travels 35 mm in a tortuous "S" shaped trajectory with a 180° angle behind the pubic bone, safely traversed by a 20G 36" 0.8 mm epidural catheter in a stretched, straightened urethra inserted after anterior dilation of the penile urethra with a 24G IV catheter. Histopathologic analysis of the urinary bladder demonstrated Stage pT1, pTa, and pTis lesions in the 8 controls, all with increased cell proliferation by Ki-67 expression and no pT1 or pTis in the animals 6 treated with BCG. This pioneering study describes an autochthonous, effective, and accessible transurethral animal model of immune-competent UC in males, and may help with understanding of the biology, immunology, and treatment of UC, which predominates in males.

Development of Dl1.72, a Novel Anti-DLL1 Antibody with Anti-Tumor Efficacy against Estrogen Receptor-Positive Breast Cancer

Simple Summary

Over 70% of breast cancers (BCs) are estrogen receptor-positive (ER⁺). The development of endocrine therapy has considerably improved patient outcomes. However, there is a clinical need for novel effective therapies against ER⁺ BCs, since many of these do not respond to standard therapy, and more than one-third of responders acquire resistance, experience relapse and metastasize. The Notch ligand Delta-like 1 (DLL1) is a key player in ER⁺ BC development and aggressiveness. Contrary to complete Notch pharmacological inhibitors, antibody-targeting of individual Notch components is expected to have superior therapeutic efficacy and be better tolerated. In this study, we developed and characterized a novel specific anti-DLL1 antibody with efficacy in inhibiting BC cell proliferation, mammosphere formation and angiogenesis, as well as anti-tumor and anti-metastatic efficacy in an ER⁺ BC mouse model without side effects. Thus, our data suggest that this anti-DLL1 antibody is a promising candidate for ER⁺ BC treatment.

Abstract

The Notch-signaling ligand DLL1 has emerged as an important player and promising therapeutic target in breast cancer (BC). DLL1-induced Notch activation promotes tumor cell proliferation, survival, migration, angiogenesis and BC stem cell maintenance. In BC, DLL1 overexpression is associated with poor prognosis, particularly in estrogen receptor-positive (ER⁺) subtypes. Directed therapy in early and advanced BC has dramatically changed the natural course of ER⁺ BC; however, relapse is a major clinical issue, and new therapeutic strategies are needed. Here, we report the development and characterization of a novel monoclonal antibody specific to DLL1. Using phage display technology, we selected an anti-DLL1 antibody fragment, which was converted into a full human IgG1 (Dl1.72). The Dl1.72 antibody exhibited DLL1 specificity and affinity in the low nanomolar range and significantly impaired DLL1-Notch signaling and expression of Notch target genes in ER⁺ BC cells. Functionally, in vitro treatment with Dl1.72 reduced MCF-7 cell proliferation, migration, mammosphere formation and endothelial tube formation. In vivo, Dl1.72 significantly inhibited tumor growth, reducing both tumor cell proliferation and liver metastases in a xenograft mouse model, without apparent toxicity. These findings suggest that anti-DLL1 Dl1.72 could be an attractive agent against ER⁺ BC, warranting further preclinical investigation.

Correlation of manual semi-quantitative and automated quantitative Ki-67 proliferative index with OncotypeDXTM recurrence score in invasive breast carcinoma

BACKGROUND

Ki-67 immunohistochemistry (IHC) staining is a widely used cancer proliferation assay; however, its limitations could be improved with automated scoring. The OncotypeDXTM Recurrence Score (ORS), which primarily evaluates cancer proliferation genes, is a prognostic indicator for breast cancer chemotherapy response; however, it is more expensive and slower than Ki-67.

OBJECTIVE

To compare manual Ki-67 (mKi-67) with automated Ki-67 (aKi-67) algorithm results based on manually selected Ki-67 "hot spots" in breast cancer, and correlate both with ORS.

METHODS

105 invasive breast carcinoma cases from 100 patients at our institution (2011-2013) with available ORS were evaluated. Concordance was assessed via Cohen's Kappa (κ).

RESULTS

57/105 cases showed agreement between mKi-67 and aKi-67 (κ 0.31, 95% CI 0.18-0.45), with 41 cases overestimated by aKi-67. Concordance was higher when estimated on the same image (κ 0.53, 95% CI 0.37-0.69). Concordance between mKi-67 score and ORS was fair (κ 0.27, 95% CI 0.11-0.42), and concordance between aKi-67 and ORS was poor (κ 0.10, 95% CI -0.03-0.23).

CONCLUSIONS

These results highlight the limits of Ki-67 algorithms that use manual "hot spot" selection. Due to suboptimal concordance, Ki-67 is likely most useful as a complement to, rather than a surrogate for ORS, regardless of scoring method.

Antifungal agent Terbinafine restrains tumor growth in preclinical models of hepatocellular carcinoma via AMPK-mTOR axis

The prognosis of hepatocellular carcinoma (HCC) remains unsatisfactory due to limited effective treatment options. In this work, we investigated the therapeutic efficacy of Terbinafine for HCC and the underlying mechanism. The influence of Terbinafine on cell growth, 3D spheroid formation, clonogenic survival, and protein synthesis was investigated in human HCC cell lines. Co-immunoprecipitation, immunofluorescence, and other techniques were employed to explore how Terbinafine exerts its anticancer effect. Subcutaneous tumorigenicity assay, orthotopic and patient-derived xenograft (PDX) HCC models were used to evaluate the anticancer effect of Terbinafine monotherapy and the combinatorial treatment with Terbinafine and sorafenib against HCC. The anticancer activity of Terbinafine was Squalene epoxidase (SQLE)-independent. Instead, Terbinafine robustly suppressed the proliferation of HCC cells by inhibiting mTORC1 signaling via activation of AMPK. Terbinafine alone or in combination with sorafenib delayed tumor progression and markedly prolonged the survival of tumor-bearing mice. The synergy between Terbinafine and sorafenib was due to concomitant inhibition of mTORC1 and induction of severe persistent DNA double-strand breaks (DSBs), which led to the delayed proliferation and accelerated cell death. Terbinafine showed promising anticancer efficacy in preclinical models of HCC and may serve as a potential therapeutic strategy for HCC.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Radiological and pathological assessment of response to neoadjuvant CDK4/6 inhibitor and endocrine treatments in a real-life setting-initial results

BACKGROUND

Neoadjuvant endocrine therapy is an alternative to neoadjuvant chemotherapy in women with inoperable luminal-like breast cancers. Neoadjuvant cyclin-dependent kinase 4/6 inhibitor treatment combined with endocrine treatment (CDK4/6I + E) is interesting given the combination's utility in the treatment of metastatic breast cancer. Currently, the literature on the radiological response evaluation of patients treated with neoadjuvant CDK4/6I + E in a real-life setting is scarce.

PURPOSE

To conduct a radiological response evaluation of patients treated with neoadjuvant CDK4/6I + E in a real-life setting.

MATERIAL AND METHODS

We retrospectively reviewed clinical, pathological, and radiological findings of six patients with luminal-like breast cancers treated with neoadjuvant CDK4/6I + E treatment. The radiological neoadjuvant CDK4/6I + E response was evaluated with the RECIST 1.1 criteria and the pathological residual disease was assessed using the Residual Cancer Burden (RBC) criteria.

RESULTS

None of the patients achieved a complete radiological magnetic resonance imaging (MRI)-determined response or a complete pathological response; three (50%) patients had a partial radiological response; in the three others, the disease remained stable radiologically. All of the tumors were rendered susceptible to surgical treatment. Two out of six (33.3%) patients had a moderate response (RBC-II); four (66.7%) had an extensive residual disease (RBC-III) in the final surgical sample.

CONCLUSION

Although none of the patients achieved a pathologically complete response, neoadjuvant CDK4/6I + E treatment rendered all tumors operable. MRI appears to be reliable in the assessment of the neoadjuvant CDK4/6I + E treatment response in a real-life setting. Larger studies are warranted to confirm these results.

Expression of Transcription Factor CREM in Human Tissues

Cyclic AMP element modulator (CREM) is a transcription factor best known for its intricate involvement in spermatogenesis. The CREM gene encodes for multiple protein isoforms, which can enhance or repress transcription of target genes. Recent studies have identified fusion genes, with CREM as a partner gene in many neoplastic diseases. EWSR1-CREM fusion genes have been found in several mesenchymal tumors and in salivary gland carcinoma. These genes encode fusion proteins that include the C-terminal DNA-binding domain of CREM. We used a transcriptomic approach and immunohistochemistry to study the expression of CREM isoforms that include DNA-binding domains across human tissues. We found that CREM protein is widely expressed in almost all normal human tissues. A transcriptomic analysis of normal tissues and cancer showed that transcription of CREM can be altered in tumors, suggesting that also wild-type CREM may be involved in cancer biology. The wide expression of CREM protein in normal human tissues and cancer may limit the utility of immunohistochemistry for identification of tumors with CREM fusions:

Efficacy of a Three Drug-Based Therapy for Neuroblastoma in Mice

High-risk neuroblastoma (HR-NB) still remains the most dangerous tumor in early childhood. For this reason, the identification of new therapeutic approaches is of fundamental importance. Recently, we combined the conventional pharmacological approach to NB, represented by cisplatin, with fendiline hydrochloride, an inhibitor of several transporters involved in multidrug resistance of cancer cells, which demonstrated an enhancement of the ability of cisplatin to induce apoptosis. In this work, we co-administrated acetazolamide, a carbonic anhydrase isoform IX (CAIX) inhibitor which was reported to increase chemotherapy efficacy in various cancer types, to the cisplatin/fendiline approach in SKNBE2 xenografts in NOD-SCID mice with the aim of identifying a novel and more effective treatment. We observed that the combination of the three drugs increases more than twelvefold the differences in the cytotoxic activity of cisplatin alone, leading to a remarkable decrease of the expression of malignancy markers. Our conclusion is that this approach, based on three FDA-approved drugs, may constitute an appropriate improvement of the pharmacological approach to HR-NB.

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy

OBJECTIVES

Despite improved survival due to new treatments, the 10-year survival rate in patients with breast cancer is approximately 75%. Lymphovascular invasion (LVI), a prognostic marker independent from histological grade and stage, can only be fully determined at final histological examination. Lipid composition is deregulated in tumour via de novo lipogenesis, with alteration in lipogenic genes in LVI. We hypothesise alteration in lipid composition derived from novel non-invasive spectroscopy method is associated with LVI positivity.

METHODS

Thirty female patients (age 39-78) with invasive ductal carcinoma were enrolled, with 13 LVI negative and 17 LVI positive. Saturated, monounsaturated, polyunsaturated fatty acids and triglycerides (SFA, MUFA, PUFA and TRG) were quantified from ex vivo breast tumours freshly excised from patients on a 3 T clinical MRI scanner, and proliferative activity marker Ki-67 and serotonin derived histologically.

RESULTS

There were significantly lower MUFA (p = 0.0189) in LVI positive (median: 0.37, interquartile range (IQR): 0.25-0.64) than negative (0.63, 0.49-0.96). There were significantly lower TRG (p = 0.0226) in LVI positive (1.32, 0.95-2.43) than negative (2.5, 1.92-4.15). There was no significant difference in SFA (p = 0.6009) or PUFA (p = 0.1641). There was no significant correlation between lipid composition against Ki-67 or serotonin, apart from a borderline negative correlation between PUFA and serotonin (r = - 0.3616, p = 0.0496).

CONCLUSION

Lipid composition might provide a biomarker to study lymphovascular invasion in breast cancer.

KEY POINTS

• Monounsaturated fatty acids in lymphovascular invasion (LVI) positive invasive breast carcinoma were significantly lower than that in LVI negative. • Triglycerides in LVI positive invasive breast carcinoma were significantly lower than that in LVI negative. • Lipid composition from MR spectroscopy reflects the rate of de novo lipogenesis and provides a potential biomarker independent from histological grade and stage.

In vivo genome-wide CRISPR screen reveals breast cancer vulnerabilities and synergistic mTOR/Hippo targeted combination therapy

Triple negative breast cancer (TNBC) patients exhibit poor survival outcomes and lack effective targeted therapies. Using unbiased in vivo genome-wide CRISPR screening, we interrogated cancer vulnerabilities in TNBC and identified an interplay between oncogenic and tumor suppressor pathways. This study reveals tumor regulatory functions for essential components of the mTOR and Hippo pathways in TNBC. Using in vitro drug matrix synergy models and in vivo patient-derived xenografts, we further establish the therapeutic relevance of our findings and show that pharmacological inhibition of mTORC1/2 and oncoprotein YAP efficiently reduces tumorigenesis in TNBC. At the molecular level, we find that while verteporfin-induced YAP inhibition leads to apoptosis, torin1-mediated mTORC1/2 inhibition promotes macropinocytosis. Torin1-induced macropinocytosis further facilitates verteporfin uptake, thereby greatly enhancing its pro-apoptotic effects in cancer cells. Overall, our study underscores the power and robustness of in vivo CRISPR genome-wide screens in identifying clinically relevant and innovative therapeutic modalities in cancer.

Triple negative breast cancer (TNBC) lack effective therapies. Here, through an in vivo genome-wide CRISPR screen in TNBCs, the authors identify tumorigenic functions for components of the mTORC1/2 complex and of the YAP/Hippo pathway, and demonstrate that pharmacological inhibition of mTOR and YAP reduces tumour growth in vivo.