Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerable part of DCIS lesions may never progress into IDC. Lower grade lesions have a lower progression speed and risk, possibly allowing treatment de-escalation. However, studies show significant inter-observer variation in DCIS grading. Automated image analysis may provide an objective solution to address high subjectivity of DCIS grading by pathologists. In this study, we developed a deep learning-based DCIS grading system. It was developed using the consensus DCIS grade of three expert observers on a dataset of 1186 DCIS lesions from 59 patients. The inter-observer agreement, measured by quadratic weighted Cohen's kappa, was used to evaluate the system and compare its performance to that of expert observers. We present an analysis of the lesion-level and patient-level inter-observer agreement on an independent test set of 1001 lesions from 50 patients. The deep learning system (dl) achieved on average slightly higher inter-observer agreement to the observers (o1, o2 and o3) ($\kappa_{o1,dl}=0.81, \kappa_{o2,dl}=0.53, \kappa_{o3,dl}=0.40$) than the observers amongst each other ($\kappa_{o1,o2}=0.58, \kappa_{o1,o3}=0.50, \kappa_{o2,o3}=0.42$) at the lesion-level. At the patient-level, the deep learning system achieved similar agreement to the observers ($\kappa_{o1,dl}=0.77, \kappa_{o2,dl}=0.75, \kappa_{o3,dl}=0.70$) as the observers amongst each other ($\kappa_{o1,o2}=0.77, \kappa_{o1,o3}=0.75, \kappa_{o2,o3}=0.72$). In conclusion, we developed a deep learning-based DCIS grading system that achieved a performance similar to expert observers. We believe this is the first automated system that could assist pathologists by providing robust and reproducible second opinions on DCIS grade

Glutathione S-transferase M1-null genotype as risk factor for SOS in oxaliplatin-treated patients with metastatic colorectal cancer

Background: Oxaliplatin is used as a neo-adjuvant therapy in hepatic colorectal carcinoma metastasis. This treatment has significant side effects, as oxaliplatin is toxic to the sinusoidal endothelial cells and can induce sinusoidal obstruction syndrome (SOS), which is related to decreased overall survival. Glutathione has an important role in the defence system, catalysed by glutathione S-transferase (GST), including two non-enzyme producing polymorphisms (GSTM1-null and GSTT1-null). We hypothesise that patients with a non-enzyme producing polymorphism have a higher risk of developing toxic injury owing to oxaliplatin. Methods: In the nontumour-bearing liver, the presence of SOS was studied histopathologically. The genotype was determined by a semi-nested PCR. Results: Thirty-two of the 55 (58%) patients showed SOS lesions, consisting of 27% mild, 22% moderate and 9% severe lesions. The GSTM1-null genotype was present in 25 of the 55 (46%). Multivariate analysis showed that the GSTM1-null genotype significantly correlated with the presence of (moderate-severe) SOS (P=0.026). Conclusion: The GSTM1-null genotype is an independent risk factor for SOS. This finding allows us, in association with other risk factors, to conceive a potential risk profile predicting whether the patient is at risk of developing SOS, before starting oxaliplatin, and subsequently might result in adjustment of treatment

Morphological segmentation analysis and texture-based support vector machines classification on mice liver fibrosis microscopic images

Background To reduce the intensity of the work of doctors, pre-classification work needs to be issued. In this paper, a novel and related liver microscopic image classification analysis method is proposed. Objective For quantitative analysis, segmentation is carried out to extract the quantitative information of special organisms in the image for further diagnosis, lesion localization, learning and treating anatomical abnormalities and computer-guided surgery. Methods in the current work, entropy based features of microscopic fibrosis mice’ liver images were analyzed using fuzzy c-cluster, k-means and watershed algorithms based on distance transformations and gradient. A morphological segmentation based on a local threshold was deployed to determine the fibrosis areas of images. Results the segmented target region using the proposed method achieved high effective microscopy fibrosis images segmenting of mice liver in terms of the running time, dice ratio and precision. The image classification experiments were conducted using Gray Level Co-occurrence Matrix (GLCM). The best classification model derived from the established characteristics was GLCM which performed the highest accuracy of classification using a developed Support Vector Machine (SVM). The training model using 11 features was found to be as accurate when only trained by 8 GLCMs. Conclusion The research illustrated the proposed method is a new feasible research approach for microscopy mice liver image segmentation and classification using intelligent image analysis techniques. It is also reported that the average computational time of the proposed approach was only 2.335 seconds, which outperformed other segmentation algorithms with 0.8125 dice ratio and 0.5253 precision

Prognostic Value of Stromal Tumor-Infiltrating Lymphocytes in Young, Node-Negative, Triple-Negative Breast Cancer Patients Who Did Not Receive (neo)Adjuvant Systemic Therapy

PURPOSE: Triple-negative breast cancer (TNBC) is considered aggressive, and therefore, virtually all young patients with TNBC receive (neo)adjuvant chemotherapy. Increased stromal tumor-infiltrating lymphocytes (sTILs) have been associated with a favorable prognosis in TNBC. However, whether this association holds for patients who are node-negative (N0), young (< 40 years), and chemotherapy-naïve, and thus can be used for chemotherapy de-escalation strategies, is unknown. METHODS: We selected all patients with N0 TNBC diagnosed between 1989 and 2000 from a Dutch population-based registry. Patients were age < 40 years at diagnosis and had not received (neo)adjuvant systemic therapy, as was standard practice at the time. Formalin-fixed paraffin-embedded blocks were retrieved (PALGA: Dutch Pathology Registry), and a pathology review including sTILs was performed. Patients were categorized according to sTILs (< 30%, 30%-75%, and ≥ 75%). Multivariable Cox regression was performed for overall survival, with or without sTILs as a covariate. Cumulative incidence of distant metastasis or death was analyzed in a competing risk model, with second primary tumors as competing risk. RESULTS: sTILs were scored for 441 patients. High sTILs (≥ 75%; 21%) translated into an excellent prognosis with a 15-year cumulative incidence of a distant metastasis or death of only 2.1% (95% CI, 0 to 5.0), whereas low sTILs (< 30%; 52%) had an unfavorable prognosis with a 15-year cumulative incidence of a distant metastasis or death of 38.4% (32.1 to 44.6). In addition, every 10% increment of sTILs decreased the risk of death by 19% (adjusted hazard ratio: 0.81; 95% CI, 0.76 to 0.87), which are an independent predictor adding prognostic information to standard clinicopathologic variables (χ2 = 46.7, P < .001). CONCLUSION: Chemotherapy-naïve, young patients with N0 TNBC with high sTILs (≥ 75%) have an excellent long-term prognosis. Therefore, sTILs should be considered for prospective clinical trials investigating (neo)adjuvant chemotherapy de-escalation strategies

Interobserver Agreement of PD-L1/SP142 Immunohistochemistry and Tumor-Infiltrating Lymphocytes (TILs) in Distant Metastases of Triple-Negative Breast Cancer: A Proof-of-Concept Study. A Report on Behalf of the International Immuno-Oncology Biomarker Working Group

Patients with advanced triple-negative breast cancer (TNBC) benefit from treatment with atezolizumab, provided that the tumor contains 651% of PD-L1/SP142-positive immune cells. Numbers of tumor-infiltrating lymphocytes (TILs) vary strongly according to the anatomic localization of TNBC metastases. We investigated inter-pathologist agreement in the assessment of PD-L1/SP142 immunohistochemistry and TILs. Ten pathologists evaluated PD-L1/SP142 expression in a proficiency test comprising 28 primary TNBCs, as well as PD-L1/SP142 expression and levels of TILs in 49 distant TNBC metastases with various localizations. Interobserver agreement for PD-L1 status (positive versus negative) was high in the proficiency test: the corresponding scores as percentages showed good agreement with the consensus diagnosis. In TNBC metastases, there was substantial variability in PD-L1 status at the individual patient level. For one in five patients, the chance of treatment was essentially random, with half of the pathologists designating them as positive and half negative. Assessment of PD-L1/SP142 and TILs as percentages in TNBC metastases showed poor and moderate agreement, respectively. Additional training for metastatic TNBC is required to enhance interobserver agreement. Such training, focusing on metastatic specimens, seems worthwhile, since the same pathologists obtained high percentages of concordance (ranging from 93% to 100%) on the PD-L1 status of primary TNBCs

Prognostic value of histopathologic traits independent of stromal tumor-infiltrating lymphocyte levels in chemotherapy-naïve patients with triple-negative breast cancer

Background: In the absence of prognostic biomarkers, most patients with early-stage triple-negative breast cancer (eTNBC) are treated with combination chemotherapy. The identification of biomarkers to select patients for whom treatment de-escalation or escalation could be considered remains an unmet need. We evaluated the prognostic value of histopathologic traits in a unique cohort of young, (neo)adjuvant chemotherapy-naïve patients with early-stage (stage I or II), node-negative TNBC and long-term follow-up, in relation to stromal tumor-infiltrating lymphocytes (sTILs) for which the prognostic value was recently reported. Materials and methods: We studied all 485 patients with node-negative eTNBC from the population-based PARADIGM cohort which selected women aged &lt;40 years diagnosed between 1989 and 2000. None of the patients had received (neo)adjuvant chemotherapy according to standard practice at the time. Associations between histopathologic traits and breast cancer-specific survival (BCSS) were analyzed with Cox proportional hazard models. Results: With a median follow-up of 20.0 years, an independent prognostic value for BCSS was observed for lymphovascular invasion (LVI) [adjusted (adj.) hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.49-3.69], fibrotic focus (adj. HR 1.61, 95% CI 1.09-2.37) and sTILs (per 10% increment adj. HR 0.75, 95% CI 0.69-0.82). In the sTILs &lt;30% subgroup, the presence of LVI resulted in a higher cumulative incidence of breast cancer death (at 20 years, 58%; 95% CI 41% to 72%) compared with when LVI was absent (at 20 years, 32%; 95% CI 26% to 39%). In the ≥75% sTILs subgroup, the presence of LVI might be associated with poor survival (HR 11.45, 95% CI 0.71-182.36, two deaths). We confirm the lack of prognostic value of androgen receptor expression and human epidermal growth factor receptor 2 -low status. Conclusions: sTILs, LVI and fibrotic focus provide independent prognostic information in young women with node-negative eTNBC. Our results are of importance for the selection of patients for de-escalation and escalation trials.</p

A Peptidoglycan Fragment Triggers β-lactam Resistance in Bacillus licheniformis

To resist to β-lactam antibiotics Eubacteria either constitutively synthesize a β-lactamase or a low affinity penicillin-binding protein target, or induce its synthesis in response to the presence of antibiotic outside the cell. In Bacillus licheniformis and Staphylococcus aureus, a membrane-bound penicillin receptor (BlaR/MecR) detects the presence of β-lactam and launches a cytoplasmic signal leading to the inactivation of BlaI/MecI repressor, and the synthesis of a β-lactamase or a low affinity target. We identified a dipeptide, resulting from the peptidoglycan turnover and present in bacterial cytoplasm, which is able to directly bind to the BlaI/MecI repressor and to destabilize the BlaI/MecI-DNA complex. We propose a general model, in which the acylation of BlaR/MecR receptor and the cellular stress induced by the antibiotic, are both necessary to generate a cell wall-derived coactivator responsible for the expression of an inducible β-lactam-resistance factor. The new model proposed confirms and emphasizes the role of peptidoglycan degradation fragments in bacterial cell regulation

Development and optimization of a system for comprehensive two-dimensional liquid chromatography with UV and mass spectrometric detection for the separation of complex samples by multi-step gradient elution

Comprehensive two-dimensional liquid chromatography (LC × LC) is a powerful tool for the separation of complex biological samples. This technique offers the advantage of simplified automation and greater reproducibility in a shorter analysis time than off-line two-dimensional separation systems. In the present study, an LC × LC system is developed enabling simultaneous UV and MS detection, and which can be easily converted to a conventional reversed-phase LC-UV/MS system. In LC × LC, a 60-min reversed-phase LC separation with a linear solvent gradient in the first dimension is coupled to a second-dimension separation on a mixed-mode cation-exchange/reversed-phase column with a modulation time of 60 s. The isocratic separation in the second-dimension column is optimized by the use of a multi-step gradient where the organic and the ionic modifier are varied independently. Intraday (n = 3) and interday (n = 4) variability of the retention times were evaluated with the complete system and found to be 0.5% and 0.7%, respectively. Good linearity was observed in calibration curves for three different compounds varying in polarity. © 2008 Elsevier B.V. All rights reserved