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Computer-assisted quantification of motile and invasive capabilities of cancer cells.

ABSTRACT: High-throughput analysis of cancer cell dissemination and its control by extrinsic and intrinsic cellular factors is hampered by the lack of adequate and efficient analytical tools for quantifying cell motility. Oncology research would greatly benefit from such a methodology that allows to rapidly determine the motile behaviour of cancer cells under different environmental conditions, including inside three-dimensional matrices. We combined automated microscopy imaging of two- and three-dimensional cell cultures with computational image analysis into a single assay platform for studying cell dissemination in high-throughput. We have validated this new approach for medulloblastoma, a metastatic paediatric brain tumour, in combination with the activation of growth factor signalling pathways with established pro-migratory functions. The platform enabled the detection of primary tumour and patient-derived xenograft cell sensitivity to growth factor-dependent motility and dissemination and identified tumour subgroup-specific responses to selected growth factors of excellent diagnostic value.

SUBMITTER: Kumar KS

PROVIDER: S-EPMC4614254 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Computer-assisted quantification of motile and invasive capabilities of cancer cells.

Kumar Karthiga Santhana KS Pillong Max M Kunze Jens J Burghardt Isabel I Weller Michael M Grotzer Michael A MA Schneider Gisbert G Baumgartner Martin M

Scientific reports 20151021

High-throughput analysis of cancer cell dissemination and its control by extrinsic and intrinsic cellular factors is hampered by the lack of adequate and efficient analytical tools for quantifying cell motility. Oncology research would greatly benefit from such a methodology that allows to rapidly determine the motile behaviour of cancer cells under different environmental conditions, including inside three-dimensional matrices. We combined automated microscopy imaging of two- and three-dimensio ...[more]

PMID: 26486848

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Project description:BackgroundCollagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.MethodsIn this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS).ResultsTCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts).ConclusionThese results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

Project description:PURPOSE:Bladder cancer recurrence following cystectomy remains a significant cause of bladder cancer specific mortality. Residual cancer cells contribute to cancer recurrence due to tumor spillage or undetectable preexisting micrometastatic tumor clones. We detected and quantified residual cancer cells in pelvic washing using ultradeep targeted sequencing. We compared the levels of residual cancer cells with clinical variables and cancer recurrence. MATERIALS AND METHODS:The primary tumor specimen was available in 17 patients who underwent robot-assisted radical cystectomy. All tumors had negative surgical margins. Pelvic washes and blood were collected intraoperatively before and after robot-assisted radical cystectomy, after pelvic lymph node dissection and in the suction fluid collected during the procedure. Two-step sequencing, including whole exome sequencing followed by ultradeep targeted sequencing (× greater than 50,000), was done to quantify residual cancer cells in each sample. Eight patients were excluded from study due to sample quality issues. The final analysis cohort comprised 9 patients. The residual cancer cell level was quantified for each sample as the relative cancer cell fraction and compared between time points. The peak relative cancer cell fraction of each patient was correlated with clinical and pathological variables. RESULTS:Residual cancer cells were detected in approximately half of the pelvic washing specimens during or after but not before robot-assisted radical cystectomy. Higher residual cancer cell levels were associated with aggressive variant histology and cancer recurrence. Verifying the feasibility of using residual cancer cells as a novel biomarker for recurrence requires larger cohorts. CONCLUSIONS:Detection of residual cancer cells in intraoperative peritoneal washes of patients with bladder cancer who undergo radical cystectomy may represent a robust biomarker of tumor aggressiveness and metastatic potential.

Project description:ObjectivesSuccessful lung cancer screening delivery requires sensitive, timely reporting of low-dose computed tomography (LDCT) scans, placing a demand on radiology resources. Trained non-radiologist readers and computer-assisted detection (CADe) software may offer strategies to optimise the use of radiology resources without loss of sensitivity. This report examines the accuracy of trained reporting radiographers using CADe support to report LDCT scans performed as part of the Lung Screen Uptake Trial (LSUT).MethodsIn this observational cohort study, two radiographers independently read all LDCT performed within LSUT and reported on the presence of clinically significant nodules and common incidental findings (IFs), including recommendations for management. Reports were compared against a 'reference standard' (RS) derived from nodules identified by study radiologists without CADe, plus consensus radiologist review of any additional nodules identified by the radiographers.ResultsA total of 716 scans were included, 158 of which had one or more clinically significant pulmonary nodules as per our RS. Radiographer sensitivity against the RS was 68-73.7%, with specificity of 92.1-92.7%. Sensitivity for detection of proven cancers diagnosed from the baseline scan was 83.3-100%. The spectrum of IFs exceeded what could reasonably be covered in radiographer training.ConclusionOur findings highlight the complexity of LDCT reporting requirements, including the limitations of CADe and the breadth of IFs. We are unable to recommend CADe-supported radiographers as a sole reader of LDCT scans, but propose potential avenues for further research including initial triage of abnormal LDCT or reporting of follow-up surveillance scans.Key points• Successful roll-out of mass screening programmes for lung cancer depends on timely, accurate CT scan reporting, placing a demand on existing radiology resources. • This observational cohort study examines the accuracy of trained radiographers using computer-assisted detection (CADe) software to report lung cancer screening CT scans, as a potential means of supporting reporting workflows in LCS programmes. • CADe-supported radiographers were less sensitive than radiologists at identifying clinically significant pulmonary nodules, but had a low false-positive rate and good sensitivity for detection of confirmed cancers.

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Computer-assisted quantification of motile and invasive capabilities of cancer cells.

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Computer-assisted quantification of motile and invasive capabilities of cancer cells.

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