Role of flow cytometry immunophenotyping in the diagnosis of leptomeningeal carcinomatosis

Subirá, Dolores; Serrano, Cristina; Castañón, Susana; Gonzalo, Raquel; Illán, Julia; Pardo, Javier; Martinez-García, Maria; Millastre, E.; Aparisi, Francisco; Navarro, Miguel; Dómine, Manuel; Gil-Bazo, Ignacio; Segura, Pedro Pérez; Gil, Miguel Ángel Cobos; Bruna, Jordi

doi:10.1093/neuonc/nor172

Cited by 49 publications

(37 citation statements)

References 36 publications

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“…Early and accurate diagnosis of LC and treatment initiation could offer the best chance of controlling symptoms and prevent the establishment of irreversible neurologic deficits that impair the patient's quality of life . However, LC diagnosis currently remains a challenge.…”

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confidence: 99%

“…Therefore, LC diagnosis often requires repeated CSF analyses that are not always easy to carry out, due to the clinical conditions of patients . Imaging techniques as well as biochemical markers, and molecular biology techniques of the CSF offer useful information for diagnosis; however, they should be considered in the right clinical context, because their use has been generally limited by poor sensitivity and specificity . Therefore, it is important to develop a new method that improves the diagnostic sensitivity of LC and, thereby, can facilitate early diagnosis.…”

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confidence: 99%

“…6,7 Early and accurate diagnosis of LC and treatment initiation could offer the best chance of controlling symptoms and prevent the establishment of irreversible neurologic deficits that impair the patient's quality of life. 1,8,9 However, LC diagnosis currently remains a challenge. CSF cytology shows higher specificity (theoretical 100%) than MRI analysis (about 77%) and a sensitivity of 75% upon repeated spinal tapping.…”

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An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

Cho

Kim

et al. 2014

Int. J. Cancer

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Leptomeningeal carcinomatosis (LC) is a metastatic cancer invading the central nervous system (CNS). We previously reported a metabolomic diagnostic approach as tested on an animal model and compared with current modalities. Here, we provide a proof of concept by applying it to human LC originating from lung cancer, the most common cause of CNS metastasis. Cerebrospinal fluid from LC (n 5 26) and normal groups (n 5 41) were obtained, and the diagnosis was established with clinical signs, cytology, MRI and biochemical tests. The cytology on the CSF, the current gold standard, exhibited 69% sensitivity (~100% specificity) from the first round of CSF tapping. In comparison, the nuclear magnetic resonance spectra on the CSF showed a clear difference in the metabolic profile between the LC and normal groups. Multivariate analysis and crossvalidation yielded the diagnostic sensitivity of 92%, the specificity of 96% and the area under the curve (AUC) of 0.991. Further spectral and statistical analysis identified myo-inositol (p < 5 3 10 214 ), creatine (p < 7 3 10 28 ), lactate (p < 9 3 10 24 ), alanine (p < 7.9 3 10 23 ) and citrate (p < 3 3 10 24 ) as the most contributory metabolites, whose combination exhibited an receiver-operating characteristic diagnostic AUC of 0.996. In addition, the metabolic profile could be correlated with the grading of radiological leptomeningeal enhancement (R 2 5 0.3881 and p 5 6.66 3 10 24), suggesting its potential utility in grading LC. Overall, we propose that the metabolomic approach might augment current diagnostic modalities for LC, the accurate diagnosis of which remains a challenge.Leptomeningeal carcinomatosis (LC) is a devastating complication of systemic cancer that occurs in 5-10% of patients with solid tumors, more frequently adenocarcinoma, and is observed most commonly in patients with breast cancer, lung cancer or melanoma.1 Especially, lung cancer is one of the most common primary cancers that cause central nervous system (CNS) metastases, and the incidence of LC is increasing as lung cancer patients survive longer with more advanced treatment modalities. [2][3][4][5] In addition, with the expansion of therapeutic options for systemic treatment of lung cancer, including targeted therapies, the landscape for treating LC is changing. Although some drugs have demonstrated activity within the CNS, they have limitation to pass the blood-brain barrier. 6,7 Early and accurate diagnosis of LC and treatment initiation could offer the best chance of controlling symptoms and prevent the establishment of irreversible neurologic deficits that impair the patient's quality of life. 1,8,9 However, LC diagnosis currently remains a challenge. CSF cytology shows higher specificity (theoretical 100%) than MRI analysis (about 77%) and a sensitivity of 75% upon repeated spinal tapping.10,11 One

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An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

Cho

Kim

et al. 2014

Int. J. Cancer

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“…FC is a sensitive technique for the detection of abnormal lymphoid populations in CSF [26,27]. Flow cytometric analysis shows a high sensitivity and specificity for the diagnosis of carcinomatous meningitis [28,29]. The utility of FC lies in the ability to immunophenotype rare cells.…”

Section: Flow Cytometric Evaluation Of Csf Samplesmentioning

confidence: 99%

Flow Cytometry of Nonhematopoietic Neoplasms

Pillai

Dorfman

2016

Acta Cytologica

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Many epithelial neoplasms can be analyzed by flow cytometry (FC), particularly from serous cavity effusion samples, using EpCAM, a cell adhesion molecule expressed on most normal epithelial cells and expressed at a higher level in most epithelial neoplasms. A simple 3-color flow cytometric panel can provide a high sensitivity and specificity compared to cytomorphology. FC provides more rapid immunophenotyping than conventional immunohistochemical staining, can identify rare malignant cells that could be missed by a cytological exam alone, and can be utilized to evaluate limited samples such as cerebrospinal fluid or fine-needle aspiration samples. Flow cytometric analysis for epithelial antigens can be combined with DNA ploidy analysis or assessment of the nucleus-to-cytoplasm ratio. Panels of flow cytometric markers are useful for the assessment of pediatric nonhematopoietic neoplasms, including neuroblastomas, primitive neuroectodermal tumors, Wilms' tumor, rhabdomyosarcomas, germ cell tumors, and hemangiopericytomas, as well as small-round-blue-cell tumors in adults, including small-cell carcinomas.

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“…However, studies regarding the role of CSF flow cytometry in solid tumors LM are still limited [24–27]. …”

Section: Introductionmentioning

confidence: 99%

Overexpression of syndecan-1, MUC-1, and putative stem cell markers in breast cancer leptomeningeal metastasis: a cerebrospinal fluid flow cytometry study

Cordone¹,

Masi²,

Summa³

et al. 2017

Breast Cancer Res

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BackgroundCancer is a mosaic of tumor cell subpopulations, where only a minority is responsible for disease recurrence and cancer invasiveness. We focused on one of the most aggressive circulating tumor cells (CTCs) which, from the primitive tumor, spreads to the central nervous system (CNS), evaluating the expression of prognostic and putative cancer stem cell markers in breast cancer (BC) leptomeningeal metastasis (LM).MethodsFlow cytometry immunophenotypic analysis of cerebrospinal fluid (CSF) samples (4.5 ml) was performed in 13 consecutive cases of BCLM. Syndecan-1 (CD138), MUC-1 (CD227) CD45, CD34, and the putative cancer stem cell markers CD15, CD24, CD44, and CD133 surface expression were evaluated on CSF floating tumor cells. The tumor-associated leukocyte population was also characterized.ResultsDespite a low absolute cell number (8 cell/μl, range 1–86), the flow cytometry characterization was successfully conducted in all the samples. Syndecan-1 and MUC-1 overexpression was documented on BC cells in all the samples analyzed; CD44, CD24, CD15, and CD133 in 77%, 75%, 70%, and 45% of cases, respectively. A strong syndecan-1 and MUC-1 expression was also documented by immunohistochemistry on primary breast cancer tissues, performed in four patients. The CSF tumor population was flanked by T lymphocytes, with a different immunophenotype between the CSF and peripheral blood samples (P ≤ 0.02).ConclusionsFlow cytometry can be successfully employed for solid tumor LM characterization even in CSF samples with low cell count. This in vivo study documents that CSF floating BC cells overexpress prognostic and putative cancer stem cell biomarkers related to tumor invasiveness, potentially representing a molecular target for circulating tumor cell detection and LM treatment monitoring, as well as a primary target for innovative treatment strategies. The T lymphocyte infiltration, documented in all CSF samples, suggests a possible involvement of the CNS lymphatic system in both lymphoid and cancer cell migration into and out of the meninges, supporting the extension of a new form of cellular immunotherapy to LM. Due to the small number of cases, validation on large cohorts of patients are warranted to confirm these findings and to evaluate the impact and value of these results for diagnosis and management of LM.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-017-0827-4) contains supplementary material, which is available to authorized users.

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Role of flow cytometry immunophenotyping in the diagnosis of leptomeningeal carcinomatosis

Cited by 49 publications

References 36 publications

An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients

Flow Cytometry of Nonhematopoietic Neoplasms

Overexpression of syndecan-1, MUC-1, and putative stem cell markers in breast cancer leptomeningeal metastasis: a cerebrospinal fluid flow cytometry study

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