Application of multicolour flow cytometry in the detection of metastatic carcinoma in serous effusions: Special emphasis in atypical cytology

Quantum measurement enables single biomarker sensitivity in flow cytometry

We present the first unambiguous experimental method enabling single-fluorophore sensitivity in a flow cytometer using quantum properties of single-photon emitters. We use a quantum measurement based on the second-order coherence function to prove that the optical signal is produced by individual biomarkers traversing the interrogation volume of the flow cytometer from the first principles. This observation enables the use of the quantum toolbox for rapid detection, enumeration, and sorting of single fluorophores in large cell populations as well as a 'photons-to-moles' calibration of this measurement modality.

High sensitivity flow cytometry immunophenotyping increases the diagnostic yield of malignant pleural effusions

Diagnosing malignant pleural effusions (MPE) is challenging when patients lack a history of cancer and cytopathology does not detect malignant cells in pleural effusions (PE). We investigated whether a systematic analysis of PE by flow cytometry immunophenotyping (FCI) had any impact on the diagnostic yield of MPE. Over 7 years, 570 samples from patients with clinical suspicion of MPE were submitted for the FCI study. To screen for epithelial malignancies, a 3-color FCI high sensitivity assay was used. The FCI results, qualified as "malignant" (FCI+) or "non-malignant" (FCI-), were compared to integrated definitive diagnosis established by clinicians based on all available information. MPE was finally diagnosed in 182 samples and FCI detected 141/182 (77.5%). Morphology further confirmed FCI findings by cytopathology detection of malignant cells in PE (n = 91) or histopathology (n = 29). Imaging tests and clinical history supported the diagnosis in the remaining samples. The median percentage of malignant cells was 6.5% for lymphoma and 0.23% for MPE secondary to epithelial cell malignancies. FCI identified a significantly lower percentage of EpCAM+ cells in cytopathology-negative MPE than in cytopathology-positive cases (0.02% vs. 1%; p < 0.0001). Interestingly, 29/52 MPE (55.8%) where FCI alerted of the presence of malignant cells were new diagnosis of cancer. Overall, FCI correctly diagnosed 456/522 samples (87.4%) suitable for comparison with cytopathology. These findings show that high sensitivity FCI significantly increases the diagnostic yield of MPE. Early detection of FCI + cases accelerates the diagnostic pathway of unsuspected MPE, thus supporting its implementation in clinical diagnostic work-up as a diagnostic tool.

Diagnostic accuracy of flow cytometry in detecting malignant epithelial cells in serous effusions

INTRODUCTION

This study aims to evaluate diagnostic accuracy of flow cytometry (FCM) in detecting malignant epithelial cells in serous effusions.

MATERIALS AND METHODS

Flow cytometric assessment of 96 serous fluids (86 ascitic, 10 pleural) was performed by using epithelial cell adhesion molecule (EpCAM) (in all 96 fluids) and MUC-1 (in a subgroup of 40 fluids) as epithelial markers and CD45 and CD14 as leucocyte markers. The percentage of EpCAM positivity and MUC-1 positivity was calculated in the CD14 and CD45 dual negative population by selective gating. The findings were then correlated with the defined gold standard criteria.

RESULTS

The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for EpCAM was found to be 92.06%, 96.96%, 98.31%, 86.48%, and 93.75%, respectively, while that for MUC-1 was 79.16%, 93.75%, 95%, 71.4%, and 85%, respectively. The sensitivity, specificity, PPV, NPV, and diagnostic accuracy for dual positivity for EpCAM and MUC-1 was found to be 83.3%, 100%, 100%, 80%, and 90% respectively. On combining FCM with cytomorphology the sensitivity, specificity, PPV, NPV, and diagnostic accuracy all increased greatly to 95.3%, 100%, 100%, 91.4%, and 96.8%, respectively.

CONCLUSIONS

This study highlights the importance of multicolored flow cytometric analysis in detecting epithelial malignancies in effusions specially in cases belonging to the atypia of undetermined significance and suspicious for malignancy categories and in cases with strong clinical suspicion of malignancy with negative fluid cytology. We recommend the combined use of FCM and cytology for this specific subgroup of patients in routine clinical practice for fast and accurate reporting.

Using a deep learning neural network for the identification of malignant cells in effusion cytology material

AIM

To evaluate the application of an artificial neural network in the detection of malignant cells in effusion samples.

MATERIALS AND METHODS

In this retrospective study, we selected 90 cases of effusion cytology samples over 2 years. There were 52 cases of metastatic adenocarcinoma and 38 benign effusion samples. In each case, an average of five microphotographs from the representative areas were taken at 40× magnification from Papanicolaou-stained samples. A total of 492 images were obtained from these 90 cases. We applied a deep convolutional neural network (DCNN) model to identify malignant cells in the cytology images of effusion cytology smears. The training was performed for 15 epochs. The model consisted of 783 layers with 188 convolution-max pool layers in between.

RESULTS

In the test set, the DCNN model correctly identified 54 of 56 images of benign samples and 49 out of 56 images of malignant samples. It showed 88% sensitivity, 96% specificity and 96% positive predictive value in the screening of malignant cases in effusion. The area under the receiver operating curve was 0.92.

CONCLUSION

DCNN is a unique technology that can detect malignant cells from cytological images. The model works rapidly and there is no bias in cell selection or feature extraction. The present DCNN model is promising and can have a significant impact on the diagnosis of malignancy in cytology.

Multicoloured flow cytometry to detect metastatic carcinoma in lymph node by epithelial cell adhesion molecule

BACKGROUND

The metastatic carcinoma in the lymph node may be missed in routine fine needle aspiration cytology (FNAC). There are limited studies on the role of epithelial cell adhesion molecule (EpCAM) in detecting metastatic carcinoma in the FNAC of lymph nodes by flow cytometry (FCM).

AIMS

To evaluate the role of EpCAM in flow cytometry detecting metastatic carcinoma in the fine needle aspiration cytology (FNAC) of the lymph node.

MATERIALS AND METHODS

In this prospective study, successive 42 cases of lymph nodes were subjected to FNAC followed by flow cytometry to detect the EpCAM positive cell population. The sample was used for cytology and FCM (CD45, CD14, and EpCAM antibodies tagged with fluorochromes). The percentage of EpCAM positive cell population in each case was calculated and compared in the metastatic carcinomas and reactive lymphoid hyperplasia (RLH) cases.

RESULT

There were 29 cases of metastatic carcinoma and 13 non-neoplastic cases (12 RLH and one granulomatous inflammation). The average percentages of EpCAM in metastatic carcinoma and reactive lymphoid cells were 11.37 and 1.24, respectively. The independent sample t-test showed a significant difference (0.001) in the percentage of EpCAM in the two groups. The cut of value of 3% EpCAM in FCM showed 97% sensitivity and 92% specificity to detect metastatic carcinoma in FNAC of the lymph node.

CONCLUSION

The percentage of EpCAM in FCM may be helpful in detecting metastatic carcinoma in the lymph node. The FCM is a rapid and quantitative test with high sensitivity and specificity.

Multicolor flow cytometry on pericardial effusion for a prompt diagnosis and treatment of hematological malignancies with heart involvement

Background

Malignancies represent 15–50% of total causes of pericardial effusions (PE). Routine analyses recommended to be performed on pericardial fluid include general chemistry, cytology, polymerase chain reaction, and microbiological cultures. Multicolor flow cytometry (FC) is a laboratory test that already proved to be useful in the detection of lymphoproliferative and metastatic malignancies in pleural and peritoneal effusions, but current guidelines do not mention its use on PE to reach a diagnosis.

Methods

Our institutional protocol foresees to routinely perform a multicolor FC analysis on pericardial fluid samples obtained by pericardiocentesis, in addition to other guidelines-recommended analyses. A sample of 15–30 ml is analyzed using a lyse and wash staining method using combination panels of antibodies, allowing to detect specific cellular subpopulations, analyzing tens to hundreds of thousands of cells in few seconds. The present manuscript aims to report our single-center experience with this diagnostic tool in patients presenting with PE requiring pericardiocentesis.

Results

Routine use of multicolor FC on pericardial fluid samples in our institution allowed to reach a definite diagnosis of cardiac lymphomas in two patients presenting with otherwise unexplained severe PE. This resulted in immediate start of combined immunotherapy, with patients’ clinical improvement. At 6 months follow-up both patients are alive and presented a complete disease regression.

Conclusion

Preliminary evidence from routine use of multicolor FC on PE support that this is a promising tool to reach a rapid diagnosis of hematological malignancies with heart involvement, leading to a prompt initiation of targeted therapies.

Routine flow cytometry approach for the evaluation of solid tumor neoplasms and immune cells in minimally invasive samples

BACKGROUND

Multidimensional flow cytometry (MFC) is routinely used for the diagnosis and follow-up of hematolymphoid neoplasms but its contribution to the identification of non-hematolymphoid malignant tumors is limited.

METHODS

The presence of non-hematolymphoid cells in clinical samples obtained via minimally invasive methods was ascertained by using a panel of monoclonal antibodies previously developed in our laboratory comprising a mixture of antibodies: CD9-PacB/CD45-OC515/CD57-FITC/CD56-PE/CD3-PerCP-Cy5.5/CD117-PE-Cy7/CD326-APC/CD81-APC-C750. Histopathological studies were performed using standard techniques.

RESULTS

164 specimens of different origins were included. Malignancy was finally confirmed in 142 (86.5%), while 22 non neoplastic samples were identified. The most frequent diagnosis was small cell lung carcinoma (SCLC) (50%). High sensitivity (S = 98.6%) was reached combining MFC and conventional pathology. Individual markers differed according to the cellular origin of the neoplasm, with neuroendocrine tumors showing a unique immunophenotypic profile (CD56+ CD326+ CD117-/+ and variable tetraspanins expression). Principal component analysis efficiently distinguished SCLC from other tumor samples. In immune cell populations, differences between reactive and malignant biopsies were found in different cell compartments, especially in B cells and Plasma cells. Differences also emerged in the percentage of CD4+ CD8- T cells, CD4-CD8+ T cells and NK cells and these were dependent on the origin of the tumor cells.

CONCLUSIONS

These results support the use of MFC as a rapid and valuable technique to detect non-hematolymphoid tumoral cells in clinical specimens, providing an initial orientation to complement hystopathological studies and allow a more precise diagnosis, especially in neuroendocrine neoplasms. The impact of different immune cell patterns warrants further research.