Bridging Histopathology and Radiomics Toward Prognosis of Metastasis in Early Breast Cancer.

Tumor histomorphology is crucial for the prognostication of breast cancer outcomes because it contains histological, cellular, and molecular tumor heterogeneity related to metastatic potential. To enhance breast cancer prognosis, we aimed to apply radiomics analysis-traditionally used in 3D scans-to 2D histopathology slides. This study tested radiomics analysis in a cohort of 92 breast tumor specimens for outcome prognosis, addressing -omics dimensionality by comparing models with moderate and high feature counts, using least absolute shrinkage and selection operator for feature selection and machine learning for prognostic modeling. In the test folds, models with radiomics features [area under the curves (AUCs) range 0.799-0.823] significantly outperformed the benchmark model, which only included clinicopathological (CP) parameters (AUC = 0.584). The moderate-dimensionality model with 11 CP + 93 radiomics features matched the performance of the highly dimensional models with 1,208 radiomics or 11 CP + 1,208 radiomics features, showing average AUCs of 0.823, 0.799, and 0.807 and accuracies of 79.8, 79.3, and 76.6%, respectively. In conclusion, our application of deep texture radiomics analysis to 2D histopathology showed strong prognostic performance with a moderate-dimensionality model, surpassing a benchmark based on standard CP parameters, indicating that this deep texture histomics approach could potentially become a valuable prognostic tool.

Directionally Sensitive Fractal Radiomics Compatible With Irregularly Shaped Magnetic Resonance Tumor Regions of Interest: Association With Osteosarcoma Chemoresistance.

BACKGROUND: Computational analysis of routinely acquired MRI has potential to improve the tumor chemoresistance prediction and to provide decision support in precision medicine, which may extend patient survival. Most radiomic analytical methods are compatible only with rectangular regions of interest (ROIs) and irregular tumor shape is therefore an important limitation. Furthermore, the currently used analytical methods are not directionally sensitive. PURPOSE: To implement a tumor analysis that is directionally sensitive and compatible with irregularly shaped ROIs. STUDY TYPE: Retrospective. SUBJECTS: A total of 54 patients with histopathologic diagnosis of primary osteosarcoma on tubular long bones and with prechemotherapy MRI. FIELD STRENGTH/SEQUENCE: A 1.5 T, T2-weighted-short-tau-inversion-recovery-fast-spin-echo. ASSESSMENT: A model to explore associations with osteosarcoma chemo-responsiveness included MRI data obtained before OsteoSa MAP neoadjuvant cytotoxic chemotherapy. Osteosarcoma morphology was analyzed in the MRI data by calculation of the nondirectional two-dimensional (2D) and directional and nondirectional one-dimensional (1D) Higuchi dimensions (Dh). MAP chemotherapy response was assessed by histopathological necrosis. STATISTICAL TESTS: The area under the receiver operating characteristic (ROC) curve (AUC) evaluated the association of the calculated features with the actual chemoresponsiveness, using tumor histopathological necrosis (95%) as the endpoint. Least absolute shrinkage and selection operator (LASSO) machine learning and multivariable regression were used for feature selection. Significance was set at <0.05. RESULTS: The nondirectional 1D Dh reached an AUC of 0.88 in association with the 95% tumor necrosis, while the directional 1D analysis along 180 radial lines significantly improved this association according to the Hanley/McNeil test, reaching an AUC of 0.95. The model defined by variable selection using LASSO reached an AUC of 0.98. The directional analysis showed an optimal predictive range between 90° and 97° and revealed structural osteosarcoma anisotropy manifested by its directionally dependent textural properties. DATA CONCLUSION: Directionally sensitive radiomics had superior predictive performance in comparison to the standard nondirectional image analysis algorithms with AUCs reaching 0.95 and full compatibility with irregularly shaped ROIs. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

The prognostic significance of serum interferon-gamma (IFN-γ) in hormonally dependent breast cancer.

BACKGROUND: Interferon-γ (IFN-γ) is a pleiotropic immunomodulatory cytokine. Because of its contradictory and even dualistic roles in malignancies, its potential as a biomarker remains to be unraveled. AIM: To evaluate the prognostic significance of serum IFN-γ in hormonally treated breast cancer patients. MATERIAL AND METHODS: The study included 72 premenopausal breast cancer patients with known clinicopathological characteristics. All patients received adjuvant hormonal therapy based on hormone receptor-positivity. The median follow-up period was 93 months. IFN-γ serum protein levels were determined by quantitative ELISA. Prognostic performance was evaluated by the receiver operating characteristic (ROC), Cox proportional hazards regression and Kaplan-Meier analyses. Classification of patients into IFN-γlow and IFN-γhigh subgroups was performed by the use of the outcome-oriented cut-off point categorization approach. RESULTS: The best prognostic performance was achieved by IFN-γ (AUC = 0.24 and p = 0.01 for distant events, AUC = 0.29 and p = 0.01 for local and distant events combined). Age and IFN-γ were prognostically significant in instances of all types of outcomes and IFN-γ was the independent prognostic parameter (Cox regression). There was a significant difference between IFN-γ values of patients without any events and those with distant metastases (Mann-Whitney test, p = 0.007). IFN-γ levels correlated significantly with nodal status and tumor stage (Spearman's rank order, r = -0.283 and r = -0.238, respectively). Distant recurrence incidence was 4% for the IFN-γhigh subgroup and 33% for the IFN-γlow subgroup (Kaplan-Meier analysis). CONCLUSIONS: Raised serum IFN-γ levels associate independently with favorable disease outcome in hormonally dependent breast cancer.

MRI radiomics in the prediction of the volumetric response in meningiomas after gamma knife radiosurgery.

PURPOSE: This report presents the first investigation of the radiomics value in predicting the meningioma volumetric response to gamma knife radiosurgery (GKRS). METHODS: The retrospective study included 93 meningioma patients imaged by three Tesla MRI. Tumor morphology was quantified by calculating 337 shape, first- and second-order radiomic features from MRI obtained before GKRS. Analysis was performed on original 3D MR images and after their laplacian of gaussian (LoG), logarithm and exponential filtering. The prediction performance was evaluated by Pearson correlation, linear regression and ROC analysis, with meningioma volume change per month as the outcome. RESULTS: Sixty calculated features significantly correlated with the outcome. The feature selection based on LASSO and multivariate regression started from all available 337 radiomic and 12 non-radiomic features. It selected LoG-sigma-1-0-mm-3D_firstorder_InterquartileRange and logarithm_ngtdm_Busyness as the predictively most robust and non-redundant features. The radiomic score based on these two features produced an AUC = 0.81. Adding the non-radiomic karnofsky performance status (KPS) to the score has increased the AUC to 0.88. Low values of the radiomic score defined a homogeneous subgroup of 50 patients with consistent absence (0%) of tumor progression. CONCLUSION: This is the first report of a strong association between MRI radiomic features and volumetric meningioma response to radiosurgery. The clinical importance of the early and reliable prediction of meningioma responsiveness to radiosurgery is based on its potential to aid individualized therapy decision making.

The Magnetic Resonance Imaging Pattern of the Lesions Caused by Knee Overuse in the Pediatric Population.

Background and Objectives: Excessive use of the knee in patients with immature locomotor systems leads to a whole spectrum of morphological changes with possible consequences in adulthood. This study aimed to examine the morphological pattern in magnetic resonance imaging (MRI) that is associated with recurrent pain due to increased physical activity in children. Materials and Methods: This was a retrospective study conducted among pediatric patients treated at the University Children's Hospital in Belgrade in 2018 and 2019. MRI findings of patients who reported recurrent pain in the knee joint during physical activity and who were without any pathological findings on both clinical examination and knee radiographs were included in the study. Results: MRI findings of 168 patients (73 boys and 95 girls, mean age 14.07 ± 3.34 years) were assessed. Meniscus and cartilage lesions were the most commonly detected morphological findings: meniscus lesions in 49.4%, cartilage ruptures in 44.6%, and cartilage edema in 26.2% of patients. The medial meniscus was more often injured in girls (p = 0.030), while boys were more prone to other joint injuries (p = 0.016), re-injury of the same joint (p = 0.036), bone bruises (p < 0.001), and ligament injuries (p = 0.001). In children older than 15 years, tibial plateau cartilage edema (p = 0.016), chondromalacia patellae (p = 0.005), and retropatellar effusion (p = 0.011) were detected more frequently compared to younger children. Conclusions: Children reporting recurrent knee pain due to increased physical activity, without any detected pathological findings on clinical examination and knee radiography, may have morphological changes that can be detected on MRI. Timely diagnosis of joint lesions should play a significant role in preventing permanent joint dysfunction in the pediatric population as well as in preventing the development of musculoskeletal diseases in adulthood.

Analysis of Spatial Distribution and Prognostic Value of Different Pan Cytokeratin Immunostaining Intensities in Breast Tumor Tissue Sections.

Cancer risk prognosis could improve patient survival through early personalized treatment decisions. This is the first systematic analysis of the spatial and prognostic distribution of different pan cytokeratin immunostaining intensities in breast tumors. The prognostic model included 102 breast carcinoma patients, with distant metastasis occurrence as the endpoint. We segmented the full intensity range (0-255) of pan cytokeratin digitized immunostaining into seven discrete narrow grey level ranges: 0-130, 130-160, 160-180, 180-200, 200-220, 220-240, and 240-255. These images were subsequently examined by 33 major (GLCM), fractal and first-order statistics computational analysis features. Interestingly, while moderate intensities were strongly associated with metastasis outcome, high intensities of pan cytokeratin immunostaining provided no prognostic value even after an exhaustive computational analysis. The intense pan cytokeratin immunostaining was also relatively rare, suggesting the low differentiation state of epithelial cells. The observed variability in immunostaining intensities highlighted the intratumoral heterogeneity of the malignant cells and its association with a poor disease outcome. The prognostic importance of the moderate intensity range established by complex computational morphology analyses was supported by simple measurements of its immunostaining area which was associated with favorable disease outcome. This study reveals intratumoral heterogeneity of the pan cytokeratin immunostaining together with the prognostic evaluation and spatial distribution of its discrete intensities.

Spatial perspectives in the redox code-Mass spectrometric proteomics studies of moonlighting proteins.

The Redox Code involves specific, reversible oxidative changes in proteins that modulate protein tertiary structure, interactions, trafficking, and activity, and hence couple the proteome to the metabolic/oxidative state of cells. It is currently a major focus of study in cell biology. Recent studies of dynamic cellular spatial reorganization with MS-based subcellular-spatial-razor proteomics reveal that protein constituents of many subcellular structures, including mitochondria, the endoplasmic reticulum, the plasma membrane, and the extracellular matrix, undergo changes in their subcellular abundance/distribution in response to oxidative stress. These proteins are components of a diverse variety of functional processes spatially distributed across cells. Many of the same proteins are involved in response to suppression of DNA replication indicate that oxidative stress is strongly intertwined with DNA replication/proliferation. Both are replete with networks of moonlighting proteins that show coordinated changes in subcellular location and that include primary protein actuators of the redox code involved in the processing of NAD+ /NADH, NADP+ /NADPH, Cys/CySS, and GSH/GSSG redox couples. Small groups of key proteins such as {KPNA2, KPNB1, PCNA, PTMA, SET} constitute "spatial switches" that modulate many nuclear processes. Much of the functional response involves subcellular protein trafficking, including nuclear import/export processes, vesicle-mediated trafficking, the endoplasmic reticulum/Golgi pathway, chaperone-assisted processes, and other transport systems. This is not visible to measurements of total protein abundance by transcriptomics or proteomics. Comprehensive pictures of cellular function will require collection of data on the subcellular transport and local functions of many moonlighting proteins, especially of those with critical roles in spatial coordination across cells. The proteome-wide analysis of coordinated changes in abundance and trafficking of proteins offered by MS-based proteomics has a unique, crucial role to play in deciphering the complex adaptive systems that underlie cellular function. © 2016 Wiley Periodicals, Inc. Mass Spec Rev.

Interleukin-6 and interleukin-8 serum levels in prognosis of hormone-dependent breast cancer.

BACKGROUND: Increasing amount of evidence points to the importance of immunity in breast cancer. The prognostic value of cytokines and their effect on tumorigenesis remains inconsistent. AIM: To investigate the prognostic significance of IL6 and IL8 and their association with ER and HER2 in estrogen-dependent (ER+) breast cancer. MATERIAL AND METHODS: The study included 79 premenopausal women with early and locally advanced ER+ breast cancer. All patients received adjuvant hormonal therapy: tamoxifen alone (56/79) or combination with LHRH agonist goserelin (23/79). IL6 and IL8 serum protein levels were measured by ELISA. Cox proportional hazards regression analysis was implemented for prognostic evaluation of the data categorized based on metastasis outcome. RESULTS: IL6 associated with good (P = 0.001, HR = 0.05) and IL8 with poor disease outcome (P = 0.03, HR = 2.5) in the whole group of patients. Multivariate analyses highlighted IL6 as the independent prognostic factor (P = 0.001, HR = 0.0007). When patients were classified according to ER or HER2 status, IL6 did not have prognostic significance in ERlow and ERhigh subgroups, while IL8 retained prognostic significance only in the ERhigh subgroup (P = 0.04, HR = 2.8). IL6 was significant in both HER2- (P = 0.001, HR = 0.05) and HER2+ subgroups (P = 0.002, HR = 0.04), while IL8 retained its prognostic significance only in the HER2+ subgroup (P = 0.001, HR = 77.8). CONCLUSIONS: This study contributes to the clarification of the prognostic performance of IL6 and IL8 by providing their first prognostic evaluation in the homogenized ER+ breast cancer patient group. IL6 was indicated as a marker of favorable, whereas IL8 was a marker of unfavorable disease outcome.

The time-dependent prognostic value of intratumoral cytokine expression profiles in a natural course of primary breast cancer with a long-term follow-up.

Despite the increasing evidence for the importance of immunity in breast cancer, the contradictory role of inflammation has not been thoroughly researched. In this study, we investigate the prognostic value of intratumoral inflammation as evaluated by cytokine mRNA levels. Intratumoral mRNA was measured for IL1ß, IL6, IL8, IL10 and IL17A, using Taqman quantitative PCR. By the AUC criteria, none of the cytokines associated with metastasis outcome over the entire follow-up period. However, separation of the follow-up period has revealed a time-dependent and robust prognostic association of IL ß. It discriminated between patients with and without metastasis relapse by AUCs of 0.21 and 0.82 during the early and late follow-up of 0-7 and 7-14 years, respectively. Interestingly, the prognostic effect by IL1ß shifted during follow-up from good prognosis in the first seven years to bad prognosis thereafter. By the less stringent criteria of Cox regression analysis, other cytokines also significantly associated positively or negatively with metastasis outcome. IL17A associated with good prognosis in the first 7 years of follow up while IL6 associated with poor and IL10 with good prognosis from 7 to 14 years. The revealed time-dependent prognostic effects of cytokine mRNA levels are intriguing and may reflect valuable biological information which should be considered in breast cancer immunotherapy research.

Atypical localization of intraosseous angioleiomyoma in the rib of a pediatric patient: a case report.

BACKGROUND: This is the first reported case of a primary intraosseous angioleiomyoma and the second case of a primary leiomyoma of the rib, irrespective of age. Angioleiomyomas mostly occur in patients of advanced age, in any part of the body, particularly the lower extremities and present as painful, slow-growing nodules in the dermis, subcutaneous fat or deep fascia. Other localizations, especially bone, are considered extremely rare, as well as their occurrence in paediatric patients. CASE PRESENTATION: A 10-year-old girl was admitted to the orthopaedic surgery department for further assessment of a pain localized in the posterior part of the right hemithorax. After magnetic resonance imaging (MRI) and surgical biopsy, intraosseus angioleiomyoma of the fourth rib was diagnosed by histopathology examination. Atypical costal localization of this type of a benign tumour presents diagnostic difficulty, especially in children. The differential diagnoses included cartilaginous tumours, Ewing sarcoma, fibrous dysplasia, Langerhans cell histiocytosis, intraosseous haemangioma and metastatic tumours. We report a detailed diagnostic procedure including MRI, selective angiography and histopathologic examination. CONCLUSION: Diagnosis of intraosseous angioleiomyoma is difficult due to the extreme rarity of this tumour and absence of pathognomonic radiological signs. Although very rarely identified in bones and young age group, radiographers and reporting doctors should be aware of this possible angioleiomyoma presentation and supported by the provided detailed diagnostic information.

Spatial Cross-Talk between Oxidative Stress and DNA Replication in Human Fibroblasts.

MS-based proteomics has been applied to a differential network analysis of the nuclear-cytoplasmic subcellular distribution of proteins between cell-cycle arrest: (a) at the origin activation checkpoint for DNA replication, or (b) in response to oxidative stress. Significant changes were identified for 401 proteins. Cellular response combines changes in trafficking and in total abundance to vary the local compartmental abundances that are the basis of cellular response. Appreciable changes for both perturbations were observed for 245 proteins, but cross-talk between oxidative stress and DNA replication is dominated by 49 proteins that show strong changes for both. Many nuclear processes are influenced by a spatial switch involving the proteins {KPNA2, KPNB1, PCNA, PTMA, SET} and heme/iron proteins HMOX1 and FTH1. Dynamic spatial distribution data are presented for proteins involved in caveolae, extracellular matrix remodelling, TGFß signaling, IGF pathways, emerin complexes, mitochondrial protein import complexes, spliceosomes, proteasomes, and so on. The data indicate that for spatially heterogeneous cells cross-compartmental communication is integral to their system biology, that coordinated spatial redistribution for crucial protein networks underlies many functional changes, and that information on dynamic spatial redistribution of proteins is essential to obtain comprehensive pictures of cellular function. We describe how spatial data of the type presented here can provide priorities for further investigation of crucial features of high-level spatial coordination across cells. We suggest that the present data are related to increasing indications that much of subcellular protein transport is constitutive and that perturbation of these constitutive transport processes may be related to cancer and other diseases. A quantitative, spatially resolved nucleus-cytoplasm interaction network is provided for further investigations.

Comparison of Monofractal, Multifractal and gray level Co-occurrence matrix algorithms in analysis of Breast tumor microscopic images for prognosis of distant metastasis risk.

Breast cancer prognosis is a subject undergoing intense study due to its high clinical relevance for effective therapeutic management and a great patient interest in disease progression. Prognostic value of fractal and gray level co-occurrence matrix texture analysis algorithms has been previously established on tumour histology images, but without any direct performance comparison. Therefore, this study was designed to compare the prognostic power of the monofractal, multifractal and co-occurrence algorithms on the same set of images. The investigation was retrospective, with 51 patients selected on account of non-metastatic IBC diagnosis, stage IIIB. Image analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Bootstrap-corrected Cox proportional hazards regression P-values indicated a significant association with metastasis outcome of at least one of the features within each group. AUC values were far better for co-occurrence (0.66-0.77) then for fractal features (0.60-0.64). Correction by the split-sample cross-validation likewise indicated the generalizability only for the co-occurrence features, with their classification accuracies ranging between 67 and 72 %, while accuracies of monofractal and multifractal features were reduced to nearly random 52-55 %. These findings indicate for the first time that the prognostic value of texture analysis of tumour histology is less dependent on the morphological complexity of the image as measured by fractal analysis, but predominantly on the spatial distribution of the gray pixel intensities as calculated by the co-occurrence features.

Early prognosis of metastasis risk in inflammatory breast cancer by texture analysis of tumour microscopic images.

Inflammatory breast cancer (IBC) is a rare and aggressive type of locally advanced breast cancer. The purpose of this study was to determine the value of microscopic tumour histomorphology texture for prognosis of local and systemic recurrence at the time of initial IBC diagnosis. This retrospective study included a group of 52 patients selected on the basis of non-metastatic IBC diagnosis, stage IIIB. Gray-Level-Co-Occurrence-Matrix (GLCM) texture analysis was performed on digital images of primary tumour tissue sections stained with haematoxylin/eosin. Obtained values were categorized by use of both data- and outcome-based methods. All five acquired GLCM texture features significantly associated with metastasis outcome. By accuracies of 69-81% and AUCs of 0.71-0.81, prognostic performance of GLCM parameters exceeded that of standard major IBC clinical prognosticators such as tumour grade and response to induction chemotherapy. Furthermore, a composite score consisting of tumour grade, contrast and correlation as independent features resulted in further enhancement of prognostic performance by accuracy of 89%, discrimination efficiency by AUC of 0.93 and an outstanding hazard ratio of 71.6 (95%CI, 41.7-148.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the model is generalizable. This study indicates for the first time the potential use of primary breast tumour histology texture as a highly accurate, simple and cost-effective prognostic indicator of metastasis risk in IBC. Clinical relevance of the obtained results rests on the role of prognosis in decisions on induction chemotherapy and the resulting impact on quality of life and survival.

Multifractal analysis of tumour microscopic images in the prediction of breast cancer chemotherapy response.

Due to the individual heterogeneity, highly accurate predictors of chemotherapy response in invasive breast cancer are needed for effective chemotherapeutic management. However, predictive molecular determinants for conventional chemotherapy are only emerging and still incorporate a high degree of predictive variability. Based on such pressing need for predictive performance improvement, we explored the value of pre-therapy tumour histology image analysis to predict chemotherapy response. Fractal analysis was applied to hematoxylin/eosin stained archival tissue of diagnostic biopsies derived from 106 patients diagnosed with invasive breast cancer. The tissue was obtained prior to neoadjuvant anthracycline-based chemotherapy and patients were subsequently divided into three groups according to their actual chemotherapy response: partial pathological response (pPR), pathological complete response (pCR) and progressive/stable disease (PD/SD). It was shown that multifractal analysis of breast tumour tissue prior to chemotherapy indeed has the capacity to distinguish between histological images of the different chemotherapy responder groups with accuracies of 91.4% for pPR, 82.9% for pCR and 82.1% for PD/SD. F(α)max was identified as the most important predictive parameter. It represents the maximum of multifractal spectrum f(α), where α is the Hölder's exponent. This is the first study investigating the predictive value of multifractal analysis as a simple and cost-effective tool to predict the chemotherapy response. Improvements in chemotherapy prediction provide clinical benefit by enabling more optimal chemotherapy decisions, thus directly affecting the quality of life and survival.

Gray-Level Co-Occurrence Matrix Texture Analysis of Breast Tumor Images in Prognosis of Distant Metastasis Risk.

Owing to exceptional heterogeneity in the outcome of invasive breast cancer it is essential to develop highly accurate prognostic tools for effective therapeutic management. Based on this pressing need, we aimed to improve breast cancer prognosis by exploring the prognostic value of tumor histology image analysis. Patient group (n=78) selection was based on invasive breast cancer diagnosis without systemic treatment with a median follow-up of 147 months. Gray-level co-occurrence matrix texture analysis was performed retrospectively on primary tumor tissue section digital images stained either nonspecifically with hematoxylin and eosin or specifically with a pan-cytokeratin antibody cocktail for epithelial malignant cells. Univariate analysis revealed stronger association with metastasis risk by texture analysis when compared with clinicopathological parameters. The combination of individual clinicopathological and texture variables into composite scores resulted in further powerful enhancement of prognostic performance, with an accuracy of up to 90%, discrimination efficiency by the area under the curve [95% confidence interval (CI)] of 0.94 (0.87-0.99) and hazard ratio (95% CI) of 20.1 (7.5-109.4). Internal validation was successfully performed by bootstrap and split-sample cross-validation, suggesting that the models are generalizable. Whereas further validation is needed on an external set of patients, this preliminary study indicates the potential use of primary breast tumor histology texture as a highly accurate, simple, and cost-effective prognostic indicator of distant metastasis risk.

Nuclear cytoplasmic trafficking of proteins is a major response of human fibroblasts to oxidative stress.

We have used a subcellular spatial razor approach based on LC-MS/MS-based proteomics with SILAC isotope labeling to determine changes in protein abundances in the nuclear and cytoplasmic compartments of human IMR90 fibroblasts subjected to mild oxidative stress. We show that response to mild tert-butyl hydrogen peroxide treatment includes redistribution between the nucleus and cytoplasm of numerous proteins not previously associated with oxidative stress. The 121 proteins with the most significant changes encompass proteins with known functions in a wide variety of subcellular locations and of cellular functional processes (transcription, signal transduction, autophagy, iron metabolism, TCA cycle, ATP synthesis) and are consistent with functional networks that are spatially dispersed across the cell. Both nuclear respiratory factor 2 and the proline regulatory axis appear to contribute to the cellular metabolic response. Proteins involved in iron metabolism or with iron/heme as a cofactor as well as mitochondrial proteins are prominent in the response. Evidence suggesting that nuclear import/export and vesicle-mediated protein transport contribute to the cellular response was obtained. We suggest that measurements of global changes in total cellular protein abundances need to be complemented with measurements of the dynamic subcellular spatial redistribution of proteins to obtain comprehensive pictures of cellular function.

Systematic nucleo-cytoplasmic trafficking of proteins following exposure of MCF7 breast cancer cells to estradiol.

We have used a proteomics subcellular spatial razor approach to look at changes in total protein abundance and in protein distribution between the nucleus and cytoplasm following exposure of MCF7 breast cancer cells to estradiol. The dominant response of MCF7 cells to estrogen stimulation involves dynamic changes in protein subcellular spatial distribution rather than changes in total protein abundance. Of the 3604 quantitatively monitored proteins, only about 2% show substantial changes in total abundance (>2-fold), whereas about 20% of the proteins show substantial changes in local abundance and/or redistribution of their subcellular location, with up to 16-fold changes in their local concentration in the nucleus or the cytoplasm. We propose that dynamic redistribution of the subcellular location of multiple proteins in response to stimuli is a fundamental characteristic of cells and suggest that perturbation of cellular spatial control may be an important feature of cancer.

Fractals in the Neurosciences: A Translational Geographical Approach.

The chapter presents three new fractal indices (fractal fragmentation index, fractal tentacularity index, and fractal anisotropy index) and normalized Kolmogorov complexity with proven applicability in geographic research, developed by the authors, and the possibility of their future use in neuroscience. The research demonstrates the relevance of fractal analysis in different fields and the basic concepts and principles of fractal geometry being sufficient for the development of models relevant to the studied reality. Also, the research highlighted the need to continue interdisciplinary research based on known fractal indicators, as well as the development of new analysis methods with the translational potential between fields.

Performance and Dimensionality of Pretreatment MRI Radiomics in Rectal Carcinoma Chemoradiotherapy Prediction.

(1) Background: This study aimed to develop a machine learning model based on radiomics of pretreatment magnetic resonance imaging (MRI) 3D T2W contrast sequence scans combined with clinical parameters (CP) to predict neoadjuvant chemoradiotherapy (nCRT) response in patients with locally advanced rectal carcinoma (LARC). The study also assessed the impact of radiomics dimensionality on predictive performance. (2) Methods: Seventy-five patients were prospectively enrolled with clinicopathologically confirmed LARC and nCRT before surgery. Tumor properties were assessed by calculating 2141 radiomics features. Least absolute shrinkage selection operator (LASSO) and multivariate regression were used for feature selection. (3) Results: Two predictive models were constructed, one starting from 72 CP and 107 radiomics features, and the other from 72 CP and 1862 radiomics features. The models revealed moderately advantageous impact of increased dimensionality, with their predictive respective AUCs of 0.86 and 0.90 in the entire cohort and 0.84 within validation folds. Both models outperformed the CP-only model (AUC = 0.80) which served as the benchmark for predictive performance without radiomics. (4) Conclusions: Predictive models developed in this study combining pretreatment MRI radiomics and clinicopathological features may potentially provide a routine clinical predictor of chemoradiotherapy responders, enabling clinicians to personalize treatment strategies for rectal carcinoma.

Vascular endothelial growth factor (VEGF) -A, -C and VE-cadherin as potential biomarkers in early breast cancer patients.

BACKGROUND: Vascular endothelial growth factor (VEGF) -A and -C act as multifunctional molecules and growth factors, while VE-cadherin (cadherin 5, CDH5) is the endothelial junction protein. AIM: To assess the relationship between intratumoral VEGF -A, -C and CDH5 levels and clinical outcome, in primary, early-stage, breast cancer patients. PATIENTS AND METHODS: The study included 69 node-negative (N0) breast cancer patients, all of whom had not received any prior hormonal or chemotherapeutic systemic therapy that would affect the course of disease. The median follow-up period was 144 months. Intratumoral mRNA levels of VEGF -A, -C and CDH5 were determined by RT-qPCR. Prognostic performance was evaluated by Cox proportional hazards regression, Kaplan-Meier analysis, as well as by the multivariable approach based on the least absolute shrinkage and selection operator (LASSO) logit regression. Classification of patients into the low and high subgroups was performed using the outcome-oriented cut-off point categorization approach. RESULTS: Of the measured mRNAs, only CDH5 mRNA (t = -2.17; p = 0.04) and VEGF-C mRNA (t = -2.41; p = 0.03) showed significant differences between values in patient subgroups with distant metastasis and those without recurrences, respectively. These t-test results were in agreement with the Cox regression by which CDH5 mRNA reached the most pronounced hazard ratio (HR=2.07; p = 0.05), followed by VEGF-C mRNA (HR=1.59; p = 0.005). HR values above 1.0 indicate that high levels of either CDH5 or VEGF-C mRNAs associated with a higher risk of poor clinical outcome. Distant recurrence incidence was 26% for the CDH5high and 3% for the CDH5low subgroup (Kaplan-Meier analysis). Distant recurrence incidence was 23% for the VEGF-Chigh and 0% for VEGF-Clow subgroup. The independent prognostic value of VEGF-C mRNA was confirmed by LASSO regression. CONCLUSION: Intratumoral VEGF-A levels did not associate with disease outcome in primary, early-stage, breast cancer patients, whilst raised levels of either CDH5 or VEGF-C prognosticated a high risk of distant metastasis.