In response to Park, et al van Diessen, Judi N.A.; Kwint, Margriet H.; Sonke, Jan-Jakob ...
Radiotherapy and oncology,
June 2020, 2020-06-00, 20200601, Letnik:
147
Journal Article
Metastatic disease remains the primary cause of death for patients with breast cancer. The different steps of the metastatic cascade rely on reciprocal interactions between cancer cells and their ...microenvironment. Within this local microenvironment and in distant organs, immune cells and their mediators are known to facilitate metastasis formation. However, the precise contribution of tumour-induced systemic inflammation to metastasis and the mechanisms regulating systemic inflammation are poorly understood. Here we show that tumours maximize their chance of metastasizing by evoking a systemic inflammatory cascade in mouse models of spontaneous breast cancer metastasis. We mechanistically demonstrate that interleukin (IL)-1β elicits IL-17 expression from gamma delta (γδ) T cells, resulting in systemic, granulocyte colony-stimulating factor (G-CSF)-dependent expansion and polarization of neutrophils in mice bearing mammary tumours. Tumour-induced neutrophils acquire the ability to suppress cytotoxic T lymphocytes carrying the CD8 antigen, which limit the establishment of metastases. Neutralization of IL-17 or G-CSF and absence of γδ T cells prevents neutrophil accumulation and downregulates the T-cell-suppressive phenotype of neutrophils. Moreover, the absence of γδ T cells or neutrophils profoundly reduces pulmonary and lymph node metastases without influencing primary tumour progression. Our data indicate that targeting this novel cancer-cell-initiated domino effect within the immune system--the γδ T cell/IL-17/neutrophil axis--represents a new strategy to inhibit metastatic disease.
Summary Background If treatment of the axilla is indicated in patients with breast cancer who have a positive sentinel node, axillary lymph node dissection is the present standard. Although axillary ...lymph node dissection provides excellent regional control, it is associated with harmful side-effects. We aimed to assess whether axillary radiotherapy provides comparable regional control with fewer side-effects. Methods Patients with T1–2 primary breast cancer and no palpable lymphadenopathy were enrolled in the randomised, multicentre, open-label, phase 3 non-inferiority EORTC 10981-22023 AMAROS trial. Patients were randomly assigned (1:1) by a computer-generated allocation schedule to receive either axillary lymph node dissection or axillary radiotherapy in case of a positive sentinel node, stratified by institution. The primary endpoint was non-inferiority of 5-year axillary recurrence, considered to be not more than 4% for the axillary radiotherapy group compared with an expected 2% in the axillary lymph node dissection group. Analyses were by intention to treat and per protocol. The AMAROS trial is registered with ClinicalTrials.gov , number NCT00014612. Findings Between Feb 19, 2001, and April 29, 2010, 4823 patients were enrolled at 34 centres from nine European countries, of whom 4806 were eligible for randomisation. 2402 patients were randomly assigned to receive axillary lymph node dissection and 2404 to receive axillary radiotherapy. Of the 1425 patients with a positive sentinel node, 744 had been randomly assigned to axillary lymph node dissection and 681 to axillary radiotherapy; these patients constituted the intention-to-treat population. Median follow-up was 6·1 years (IQR 4·1–8·0) for the patients with positive sentinel lymph nodes. In the axillary lymph node dissection group, 220 (33%) of 672 patients who underwent axillary lymph node dissection had additional positive nodes. Axillary recurrence occurred in four of 744 patients in the axillary lymph node dissection group and seven of 681 in the axillary radiotherapy group. 5-year axillary recurrence was 0·43% (95% CI 0·00–0·92) after axillary lymph node dissection versus 1·19% (0·31–2·08) after axillary radiotherapy. The planned non-inferiority test was underpowered because of the low number of events. The one-sided 95% CI for the underpowered non-inferiority test on the hazard ratio was 0·00–5·27, with a non-inferiority margin of 2. Lymphoedema in the ipsilateral arm was noted significantly more often after axillary lymph node dissection than after axillary radiotherapy at 1 year, 3 years, and 5 years. Interpretation Axillary lymph node dissection and axillary radiotherapy after a positive sentinel node provide excellent and comparable axillary control for patients with T1–2 primary breast cancer and no palpable lymphadenopathy. Axillary radiotherapy results in significantly less morbidity. Funding EORTC Charitable Trust.
Automated detection of cancer metastases in lymph nodes has the potential to improve the assessment of prognosis for patients. To enable fair comparison between the algorithms for this purpose, we ...set up the CAMELYON17 challenge in conjunction with the IEEE International Symposium on Biomedical Imaging 2017 Conference in Melbourne. Over 300 participants registered on the challenge website, of which 23 teams submitted a total of 37 algorithms before the initial deadline. Participants were provided with 899 whole-slide images (WSIs) for developing their algorithms. The developed algorithms were evaluated based on the test set encompassing 100 patients and 500 WSIs. The evaluation metric used was a quadratic weighted Cohen's kappa. We discuss the algorithmic details of the 10 best pre-conference and two post-conference submissions. All these participants used convolutional neural networks in combination with pre- and postprocessing steps. Algorithms differed mostly in neural network architecture, training strategy, and pre- and postprocessing methodology. Overall, the kappa metric ranged from 0.89 to −0.13 across all submissions. The best results were obtained with pre-trained architectures such as ResNet. Confusion matrix analysis revealed that all participants struggled with reliably identifying isolated tumor cells, the smallest type of metastasis, with detection rates below 40%. Qualitative inspection of the results of the top participants showed categories of false positives, such as nerves or contamination, which could be targeted for further optimization. Last, we show that simple combinations of the top algorithms result in higher kappa metric values than any algorithm individually, with 0.93 for the best combination.
Increased lymphangiogenesis and lymph node metastasis, the important prognostic indicators of aggressive hepatobiliary malignancies such as hepatocellular cancer and cholangiocarcinoma, are ...associated with poor patient outcome. The liver produces 25% to 50% of total lymphatic fluid in the body and has a dense network of lymphatic vessels. The lymphatic system plays critical roles in fluid homeostasis and inflammation and immune response. Yet, lymphatic vessel alterations and function are grossly understudied in the context of liver pathology. Expansion of the lymphatic network has been documented in clinical samples of liver cancer; and although largely overlooked in the liver, tumor-induced lymphangiogenesis is an important player, increasing tumor metastasis in several cancers. This review aims to provide a detailed perspective on the current knowledge of alterations in the hepatic lymphatic system during liver malignancies, as well as various molecular signaling mechanisms and growth factors that may provide future targets for therapeutic intervention. In addition, the review also addresses current mechanisms and bottlenecks for effective therapeutic targeting of tumor-associated lymphangiogenesis.
Pathologists face a substantial increase in workload and complexity of histopathologic cancer diagnosis due to the advent of personalized medicine. Therefore, diagnostic protocols have to focus ...equally on efficiency and accuracy. In this paper we introduce 'deep learning' as a technique to improve the objectivity and efficiency of histopathologic slide analysis. Through two examples, prostate cancer identification in biopsy specimens and breast cancer metastasis detection in sentinel lymph nodes, we show the potential of this new methodology to reduce the workload for pathologists, while at the same time increasing objectivity of diagnoses. We found that all slides containing prostate cancer and micro- and macro-metastases of breast cancer could be identified automatically while 30-40% of the slides containing benign and normal tissue could be excluded without the use of any additional immunohistochemical markers or human intervention. We conclude that 'deep learning' holds great promise to improve the efficacy of prostate cancer diagnosis and breast cancer staging.
During the growth of various cancers, primary tumors can escape antitumor immune responses of their host and eventually disseminate into distant organs. Peritumoral lymphatic vessels connect the ...primary tumor to lymph nodes, facilitating tumor entry into lymph nodes, systemic circulation, and metastasis. Lymph node metastases that occur frequently provide sites of tumor cell spread, whereas tumor antigen transfer into and presentation in tumor-draining lymph nodes induce activation of tumor-specific T-lymphocyte responses that can result in cytolytic targeting of the tumor. Here, we discuss the recently emerged controversial role of the lymphatic vessels in tumor dissemination and cancer immunotherapy.
Purpose
To develop a deep learning–based computer-aided diagnosis (CAD) system for use in the CT diagnosis of cervical lymph node metastasis (LNM) in patients with thyroid cancer.
Methods
A total of ...995 axial CT images that included benign (
n
= 647) and malignant (
n
= 348) lymph nodes were collected from 202 patients with thyroid cancer who underwent CT for surgical planning between July 2017 and January 2018. The datasets were randomly split into training (79.0%), validation (10.5%), and test (10.5%) datasets. Eight deep convolutional neural network (CNN) models were used to classify the images into metastatic or benign lymph nodes. Pretrained networks were used on the ImageNet and the best-performing algorithm was selected. Class-specific discriminative regions were visualized with attention heatmap using a global average pooling method.
Results
The area under the ROC curve (AUROC) for the tested algorithms ranged from 0.909 to 0.953. The sensitivity, specificity, and accuracy of the best-performing algorithm were all 90.4%, respectively. Attention heatmap highlighted important subregions for further clinical review.
Conclusion
A deep learning–based CAD system could accurately classify cervical LNM in patients with thyroid cancer on preoperative CT with an AUROC of 0.953. Whether this approach has clinical utility will require evaluation in a clinical setting.
Key Points
• A deep learning–based CAD system could accurately classify cervical lymph node metastasis. The AUROC for the eight tested algorithms ranged from 0.909 to 0.953.
• Of the eight models, the ResNet50 algorithm was the best-performing model for the validation dataset with 0.953 AUROC. The sensitivity, specificity, and accuracy of the ResNet50 model were all 90.4%, respectively, in the test dataset.
• Based on its high accuracy of 90.4%, we consider that this model may be useful in a clinical setting to detect LNM on preoperative CT in patients with thyroid cancer.
Sentinel lymph node biopsy (SLNB) is the gold-standard procedure for evaluating axillary lymph node (ALN) status in patients with breast cancer. However, the morbidity of SLNB is not negligible, and ...the procedure is invasive for patients without ALN metastasis. Here, we developed a diagnostic model for evaluating ALN status using a combination of serum miRNAs and clinicopathologic factors as a novel less-invasive biomarker.
Preoperative serum samples were collected from patients who underwent surgery for primary breast cancer or breast benign diseases between 2008 and 2014. A total of 958 serum samples (921 cases of primary breast cancer, including 630 cases in the no ALN metastasis group and 291 cases in the ALN metastasis group, and 37 patients with benign breast diseases) were analyzed by miRNA microarray. Samples were randomly divided into training and test sets. Logistic LASSO regression analysis was used to construct diagnostic models in the training set, which were validated in the test set.
An optimal diagnostic model was identified using a combination of two miRNAs (miR-629-3p and miR-4710) and three clinicopathologic factors (T stage, lymphovascular invasion, and ultrasound findings), which showed a sensitivity of 0.88 (0.84-0.92), a specificity of 0.69 (0.61-0.76), an accuracy of 0.818, and an area under the receiver operating characteristic curve of 0.86 in the test set.
Serum miRNA profiles may be useful for the diagnosis of ALN metastasis before surgery in a less-invasive manner than SLNB.
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