Collagen fiber orientation disorder from H&E images is prognostic for early stage breast cancer: clinical trial validation.
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ABSTRACT:
SUBMITTER: Li H
PROVIDER: S-EPMC8346522 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States. One critical question with these tumors is identifying which patients will receive added benefit from adjuvant chemotherapy. Nuclear pleomorphism (variance in nuclear shape and morphology) is an important constituent of breast grading schemes, and in ER+ cases, the grade is highly correlated with disease outcome. This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative (LN-), ER+ BCa could help stratify patients into discrete (<10 years short-term vs. >10 years long-term survival) outcome groups independent of standard clinical and pathological parameters. We considered a tissue microarray (TMA) cohort of 276 ER+, LN- patients comprising 150 patients with long-term and 126 patients with short-term overall survival, wherein 177 randomly chosen cases formed the modeling set, and 99 remaining cases the test set. Segmentation of individual nuclei was performed using multiresolution watershed; subsequently, 615 features relating to nuclear shape/texture and orientation disorder were extracted from each TMA spot. The Wilcoxon's rank-sum test identified the 15 most prognostic quantitative histomorphometric features within the modeling set. These features were then subsequently combined via a linear discriminant analysis classifier and evaluated on the test set to assign a probability of long-term vs. short-term disease-specific survival. In univariate survival analysis, patients identified by the image classifier as high risk had significantly poorer survival outcome: hazard ratio (95% confident interval)?=?2.91(1.23-6.92), p?=?0.02786. Multivariate analysis controlling for T-stage, histology grade, and nuclear grade showed the classifier to be independently predictive of poorer survival: hazard ratio (95% confident interval)?=?3.17(0.33-30.46), p?=?0.01039. Our results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN- BCa.
| S-EPMC6214731 | biostudies-literature
Project description:Diffusion magnetic resonance imaging (dMRI) is widely used to probe tissue microstructure, and is currently the only non-invasive way to measure the brain's fiber architecture. While a large number of approaches to recover the intra-voxel fiber structure have been utilized in the scientific community, a direct, 3D, quantitative validation of these methods against relevant histological fiber geometries is lacking. In this study, we investigate how well different high angular resolution diffusion imaging (HARDI) models and reconstruction methods predict the ground-truth histologically defined fiber orientation distribution (FOD), as well as investigate their behavior over a range of physical and experimental conditions. The dMRI methods tested include constrained spherical deconvolution (CSD), Q-ball imaging (QBI), diffusion orientation transform (DOT), persistent angular structure (PAS), and neurite orientation dispersion and density imaging (NODDI) methods. Evaluation criteria focus on overall agreement in FOD shape, correct assessment of the number of fiber populations, and angular accuracy in orientation. In addition, we make comparisons of the histological orientation dispersion with the fiber spread determined from the dMRI methods. As a general result, no HARDI method outperformed others in all quality criteria, with many showing tradeoffs in reconstruction accuracy. All reconstruction techniques describe the overall continuous angular structure of the histological FOD quite well, with good to moderate correlation (median angular correlation coefficient > 0.70) in both single- and multiple-fiber voxels. However, no method is consistently successful at extracting discrete measures of the number and orientations of FOD peaks. The major inaccuracies of all techniques tend to be in extracting local maxima of the FOD, resulting in either false positive or false negative peaks. Median angular errors are ?10° for the primary fiber direction and ?20° for the secondary fiber, if present. For most methods, these results did not vary strongly over a wide range of acquisition parameters (number of diffusion weighting directions and b value). Regardless of acquisition parameters, all methods show improved successes at resolving multiple fiber compartments in a voxel when fiber populations cross at near-orthogonal angles, with no method adequately capturing low to moderate angle (<60°) crossing fibers. Finally, most methods are limited in their ability to capture orientation dispersion, resulting in low to moderate, yet statistically significant, correlation with histologically-derived dispersion with both HARDI and NODDI methodologies. Together, these results provide quantitative measures of the reliability and limitations of dMRI reconstruction methods and can be used to identify relative advantages of competing approaches as well as potential strategies for improving accuracy.
| S-EPMC5732036 | biostudies-literature
Project description:Background: Altered copper levels have been observed in several cancers, but studies on the relationship between serum copper and early-stage triple-negative breast cancer (TNBC) remain scare. We sought to establish a predictive model incorporating serum copper levels for individualized survival predictions. Methods: We retrospectively analyzed clinicopathological information and baseline peripheric blood samples of patients diagnosed with early-stage TNBC between September 2005 and October 2016 at Sun Yat-sen University Cancer Center. The optimal cut-off point of serum copper level was determined using maximally selected log-rank statistics. Kaplan-Meier curves were used to estimate survival probabilities. Independent prognostic indicators associated with survival were identified using multivariate Cox regression analysis, and subsequently, prognostic nomograms were established to predict individualized disease-free survival (DFS) and overall survival (OS). The nomograms were validated in a separate cohort of 86 patients from the original randomized clinical trial SYSUCC-001 (SYSUCC-001 cohort). Results: 350 patients were eligible in this study, including 264 in the training cohort and 86 in the SYSUCC-001 cohort. An optimal cut-off value of 21.3 μmol/L of serum copper was determined to maximally divide patients into low- and high-copper groups. After a median follow-up of 87.1 months, patients with high copper levels had significantly worse DFS (p = 0.002) and OS (p < 0.001) than those with low copper levels in the training cohort. Multivariate Cox regression analysis revealed that serum copper level was an independent factor for DFS and OS. Further, prognostic models based on serum copper were established for individualized predictions. These models showed excellent discrimination [C-index for DFS: 0.689, 95% confidence interval (CI): 0.621-0.757; C-index for OS: 0.728, 95% CI: 0.654-0.802] and predictive calibration, and were validated in the SYSUCC-001 cohort. Conclusion: Serum copper level is a potential predictive biomarker for patients with early-stage TNBC. Predictive nomograms based on serum copper might be served as a practical tool for individualized prognostication.
| S-EPMC8657150 | biostudies-literature
Project description:The interstitial matrix is comprised of cross-linked collagen fibers, generally arranged in nonisotropic orientations. Spatial alignment of matrix components within the tissue can affect diffusion patterns of drugs. In this study, we developed a methodology for the calculation of diffusion coefficients of macromolecules and nanoparticles in collagenous tissues. The tissues are modeled as three-dimensional, stochastic, fiber networks with varying degrees of alignment. We employed a random walk approach to simulate diffusion and a Stokesian dynamics method to account for hydrodynamic hindrance. We performed our analysis for four different structures ranging from nearly isotropic to perfectly aligned. We showed that the overall diffusion coefficient is not affected by the orientation of the network. However, structural anisotropy results in diffusion anisotropy, which becomes more significant with increase in the degree of alignment, the size of the diffusing particle, and the fiber volume fraction. To test our model predictions we performed diffusion measurements in reconstituted collagen gels and tumor xenografts. We measured fiber alignment and diffusion with second harmonic generation and multiphoton fluorescent recovery after photobleaching techniques, respectively. The results showed for the first time in tumors that the structure and orientation of collagen fibers in the extracellular space leads to diffusion anisotropy.
| S-EPMC2980743 | biostudies-literature
Project description:A novel method for semiautomated assessment of directions of collagen fibers in soft tissues using histological image analysis is presented. It is based on multiple rotated images obtained via polarized light microscopy without any additional components, i.e., with just two polarizers being either perpendicular or nonperpendicular (rotated). This arrangement breaks the limitation of 90° periodicity of polarized light intensity and evaluates the in-plane fiber orientation over the whole 180° range accurately and quickly. After having verified the method, we used histological specimens of porcine Achilles tendon and aorta to validate the proposed algorithm and to lower the number of rotated images needed for evaluation. Our algorithm is capable to analyze 5·105 pixels in one micrograph in a few seconds and is thus a powerful and cheap tool promising a broad application in detection of collagen fiber distribution in soft tissues.
| S-EPMC8645375 | biostudies-literature
Project description:PurposeThe posterior sclera has a major biomechanical influence on the optic nerve head, and may therefore be important in glaucoma. Scleral material properties are influenced significantly by collagen fiber architecture. Here we quantitatively map fiber orientation in non-glaucoma and glaucoma posterior human sclerae.MethodsWide-angle x-ray scattering quantified fiber orientation at 0.5-mm intervals across seven non-glaucoma post-mortem human sclerae, and five sclerae with glaucoma history and confirmed axon loss. Multiphoton microscopy provided semiquantitative depth-profiling in the peripapillary sclera.ResultsMidposterior fiber orientation was either uniaxial (one preferred direction) or biaxial (two directions). The peripapillary sclera was characterized by a ring of fibers located mainly in the mid-/outer stromal depth and encompassing ?50% of the total tissue thickness. Fiber anisotropy was 37% higher in the peripapillary sclera compared with midposterior, varied up to 4-fold with position around the scleral canal, and was consistently lowest in the superior-nasal quadrant. Mean fiber anisotropy was significantly lower in the superior-temporal (P < 0.01) and inferior-nasal (P < 0.05) peripapillary scleral quadrants in glaucoma compared with non-glaucoma eyes.ConclusionsThe collagen fiber architecture of the posterior human sclera is highly anisotropic and inhomogeneous. Regional differences in peripapillary fiber anisotropy between non-glaucoma and glaucoma eyes may represent adaptive changes in response to elevated IOP and/or glaucoma, or baseline structural properties that associate with predisposition to glaucomatous axon damage. Quantitative fiber orientation data will benefit numerical eye models aimed at predicting the sclera's influence on nerve head biomechanics, and thereby its possible role in glaucoma.
| S-EPMC3416032 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-08-28 | GSE157011 | GEO
Project description:Background: Patients with early stage non-small cell lung carcinoma (NSCLC) may benefit from treatments based on more accurate prognosis. A 15-gene prognostic classifier for NSCLC was identified from mRNA expression profiling of tumor samples from the NCIC CTG JBR.10 trial. Here, we assessed its value in an independent set of cases. Methods: Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 Stage I and II NSCLC cases collected at University Health Network (UHN181). Kaplan-Meier methodology was used to estimate three year overall survival probabilities and the prognostic effect of the classifier was assessed using log-rank testing. Cox proportional hazards model evaluated the signature's effect adjusting for clinical prognostic factors. Results: Expression data of the 15-gene classifier stratified UHN181 cases into high and low-risk subgroups with significantly different overall survival (HR=1.92, 95% CI: 1.15-3.23, p=0.012). Its strength as a prognostic classifier was superior to stage alone (HR=1.52, 95% CI: 0.90-2.55, p-value=0.11). In subgroup analysis, this classifier predicted survival in 127 Stage I patients (HR=2.17, 95% CI: 1.12-4.20, p=0.018) and the smaller subgroup of 48 Stage IA patients (HR=5.61, 95% CI: 1.19-26.45, p=0.014. The signature was prognostic for both adenocarcinoma and squamous cell carcinoma cases (HR= 1.76, p-value=0.058; HR= 4.19, p-value=0.045, respectively). Conclusions: The prognostic accuracy of a 15-gene classifier was validated in an independent cohort of 181 early stage NSCLC samples including Stage IA cases and in different NSCLC histologic subtypes. Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 Stage I and II NSCLC cases collected at University Health Network (UHN181). !Series_contributor = Sandy,D,Der
| S-ECPF-GEOD-50081 | biostudies-other
Project description:Cell structure depends on both matrix strain and stiffness, but their interactive effects are poorly understood. We investigated the interactive roles of matrix properties and stretching patterns on cell structure by uniaxially stretching U2OS cells expressing GFP-actin on silicone rubber sheets supporting either a surface-adsorbed coating or thick hydrogel of type-I collagen. Cells and their actin stress fibers oriented perpendicular to the direction of cyclic stretch on collagen-coated sheets, but oriented parallel to the stretch direction on collagen gels. There was significant alignment parallel to the direction of a steady increase in stretch for cells on collagen gels, while cells on collagen-coated sheets did not align in any direction. The extent of alignment was dependent on both strain rate and duration. Stretch-induced alignment on collagen gels was blocked by the myosin light-chain kinase inhibitor ML7, but not by the Rho-kinase inhibitor Y27632. We propose that active orientation of the actin cytoskeleton perpendicular and parallel to direction of stretch on stiff and soft substrates, respectively, are responses that tend to maintain intracellular tension at an optimal level. Further, our results indicate that cells can align along directions of matrix stress without collagen fibril alignment, indicating that matrix stress can directly regulate cell morphology.
| S-EPMC3933569 | biostudies-literature
Project description:Breast cancer is the most common malignancy among women, with the highest incidence rate worldwide. Dysregulation of long noncoding RNAs during the preliminary stages of breast carcinogenesis is poorly understood. In this study, we performed RNA sequencing to identify long noncoding RNA expression profiles associated with early-stage breast cancer. RNA sequencing was performed on six invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, seven ductal carcinoma in situ tissues, and five apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (~ 58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was performed in n = 52 IDC and paired normal tissue by qRT-PCR for the identified targets (ADAMTS9-AS2, EPB41L4A-AS1, WDFY3-AS2, RP11-295M3.4, RP11-161M6.2, RP11-490M8.1, CTB-92J24.3, and FAM83H-AS1). We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and report that overexpression of FAM83H-AS1 was associated with patient poor survival. We confirmed that the downregulation of ADAMTS9-AS2 in breast cancer was due to promoter hypermethylation through in vitro silencing experiments and pyrosequencing.
| S-EPMC6547626 | biostudies-literature