Quantitative Diagnosis of Malignant Pleural Effusions by Single-Cell Mechanophenotyping

Single-cell biophysical properties were used for diagnosing malignant pleural effusions from patients. Cytometry Device Helps (De)form a Diagnosis Is it benign, or malignant? That is the main concern of cytopathologists as they screen cells in pleural effusions, taken from the lungs of patients suspected of having infections or cancer. This process is subjective and time-intensive and requires an expert’s eye. So, to quickly “prescreen” samples for malignancy (and follow-up), Tse et al. describe deformability cytometry (DC)—an approach that relies on microfluidic forces to diagnose pleural effusion samples as malignant, or not. The authors’ device accelerates effusion samples through two opposing microfluidic channels. At the channels’ four-way intersection, the cells are rapidly decelerated as they encounter the opposing flow, and then exit out the side channels. This leads to cell deformation, changing them from sphere-like shapes to pancakes. High-speed video of this intersection allowed Tse et al. to quantify cellular squishing: the more deformable the cell, the more malignant it is. The authors took 119 pleural effusion samples from patients with known clinical outcomes—negative for malignant cells (benign), acute inflammation, chronic/mixed inflammation, atypical cells, and malignant pleural effusions (MPEs)—to develop a diagnostic scoring system on a scale of 1 to 10, with 1 being benign. DC showed the best predictive abilities in two high-confidence regimes: 1 to 6 and 9 to 10. Scores of 7 and 8 were more difficult to diagnose, so these may be the types of samples where a cytopathologist’s initial input would be necessary. Importantly, the authors looked at samples from patients that were cytology-negative with concurrent malignancy, such as a tumor, but 6 months later were diagnosed with disseminated disease. Five of 10 patients with high-grade cancers that were cytology-negative at sample collection scored high using DC. This suggests that the DC tool could be used to screen early for MPE. Using deformability as a marker of disease will require additional validation in pleural effusion samples from patients with many different types of cancer. Nevertheless, owing to the ease of use and objective readout, with further clinical testing, DC should be useful as a quick screening tool to form an early diagnosis of MPEs. Biophysical characteristics of cells are attractive as potential diagnostic markers for cancer. Transformation of cell state or phenotype and the accompanying epigenetic, nuclear, and cytoplasmic modifications lead to measureable changes in cellular architecture. We recently introduced a technique called deformability cytometry (DC) that enables rapid mechanophenotyping of single cells in suspension at rates of 1000 cells/s—a throughput that is comparable to traditional flow cytometry. We applied this technique to diagnose malignant pleural effusions, in which disseminated tumor cells can be difficult to accurately identify by traditional cytology. An algorithmic diagnostic scoring system was developed on the basis of quantitative features of two-dimensional distributions of single-cell mechanophenotypes from 119 samples. The DC scoring system classified 63% of the samples into two high-confidence regimes with 100% positive predictive value or 100% negative predictive value, and achieved an area under the curve of 0.86. This performance is suitable for a prescreening role to focus cytopathologist analysis time on a smaller fraction of difficult samples. Diagnosis of samples that present a challenge to cytology was also improved. Samples labeled as “atypical cells,” which require additional time and follow-up, were classified in high-confidence regimes in 8 of 15 cases. Further, 10 of 17 cytology-negative samples corresponding to patients with concurrent cancer were correctly classified as malignant or negative, in agreement with 6-month outcomes. This study lays the groundwork for broader validation of label-free quantitative biophysical markers for clinical diagnoses of cancer and inflammation, which could help to reduce laboratory workload and improve clinical decision-making.