Detection of early-stage lung cancer in sputum using automated flow cytometry and machine learning.

BACKGROUND: Low-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases. METHODS: Single cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer. RESULTS: Automated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83-0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were < 20 mm (AUC of 0.94; 95% CI 0.89-0.99). Testing of the model on an independent second set of samples showed an AUC of 0.85 (95% CI 0.71-0.98) with an 83% sensitivity, 77% specificity, 95% negative predictive value and 45% positive predictive value. The model is robust to differences in sample processing and disease state. CONCLUSION: CyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules < 20 mm in diameter. This test is intended for use after lung cancer screening to improve early-stage lung cancer diagnosis. Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018.

Sputum analysis by flow cytometry; an effective platform to analyze the lung environment.

Low dose computed tomography (LDCT) is the standard of care for lung cancer screening in the United States (US). LDCT has a sensitivity of 93.8% but its specificity of 73.4% leads to potentially harmful follow-up procedures in patients without lung cancer. Thus, there is a need for additional assays with high accuracy that can be used as an adjunct to LDCT to diagnose lung cancer. Sputum is a biological fluid that can be obtained non-invasively and can be dissociated to release its cellular contents, providing a snapshot of the lung environment. We obtained sputum from current and former smokers with a 30+ pack-year smoking history and who were either confirmed to have lung cancer or at high risk of developing the disease. Dissociated sputum cells were counted, viability determined, and labeled with a panel of markers to separate leukocytes from non-leukocytes. After excluding debris and dead cells, including squamous epithelial cells, we identified reproducible population signatures and confirmed the samples' lung origin. In addition to leukocyte and epithelial-specific fluorescent antibodies, we used the highly fluorescent meso-tetra(4-carboxyphenyl) porphyrin (TCPP), known to preferentially stain cancer (associated) cells. We looked for differences in cell characteristics, population size and fluorescence intensity that could be useful in distinguishing cancer samples from high-risk samples. We present our data demonstrating the feasibility of a flow cytometry platform to analyze sputum in a high-throughput and standardized matter for the diagnosis of lung cancer.

Quality-Controlled Sputum Analysis by Flow Cytometry.

Sputum, widely used to study the cellular content and other microenvironmental features to understand the health of the lung, is traditionally analyzed using cytology-based methodologies. Its utility is limited because reading the slides is time-consuming and requires highly specialized personnel. Moreover, extensive debris and the presence of too many squamous epithelial cells (SECs), or cheek cells, often renders a sample inadequate for diagnosis. In contrast, flow cytometry allows for high-throughput phenotyping of cellular populations while simultaneously excluding debris and SECs. The protocol presented here describes an efficient method to dissociate sputum into a single cell suspension, antibody stain and fix cellular populations, and acquire samples on a flow cytometric platform. A gating strategy that describes the exclusion of debris, dead cells (including SECs) and cell doublets is presented here. Further, this work also explains how to analyze viable, single sputum cells based on a cluster of differentiation (CD)45 positive and negative populations to characterize hematopoietic and epithelial lineage subsets. A quality control measure is also provided by identifying lung-specific macrophages as evidence that a sample is derived from the lung and is not saliva. Finally, it has been demonstrated that this method can be applied to different cytometric platforms by providing sputum profiles from the same patient analyzed on three flow cytometers; Navios EX, LSR II, and Lyric. Furthermore, this protocol can be modified to include additional cellular markers of interest. A method to analyze an entire sputum sample on a flow cytometric platform is presented here that makes sputum amenable for developing high-throughput diagnostics of lung disease.

Arenavirus stable signal peptide is the keystone subunit for glycoprotein complex organization.

UNLABELLED: The rodent arenavirus glycoprotein complex encodes a stable signal peptide (SSP) that is an essential structural component of mature virions. The SSP, GP1, and GP2 subunits of the trimeric glycoprotein complex noncovalently interact to stud the surface of virions and initiate arenavirus infectivity. Nascent glycoprotein production undergoes two proteolytic cleavage events: first within the endoplasmic reticulum (ER) to cleave SSP from the remaining precursor GP1/2 (glycoprotein complex [GPC]) glycoprotein and second within the Golgi stacks by the cellular SKI-1/S1P for GP1/2 processing to yield GP1 and GP2 subunits. Cleaved SSP is not degraded but retained as an essential glycoprotein subunit. Here, we defined functions of the 58-amino-acid lymphocytic choriomeningitis virus (LCMV) SSP in regard to glycoprotein complex processing and maturation. Using molecular biology techniques, confocal microscopy, and flow cytometry, we detected SSP at the plasma membrane of transfected cells. Further, we identified a sorting signal (FLLL) near the carboxyl terminus of SSP that is required for glycoprotein maturation and trafficking. In the absence of SSP, the glycoprotein accumulated within the ER and was unable to undergo processing by SKI-1/S1P. Mutation of this highly conserved FLLL motif showed impaired glycoprotein processing and secretory pathway trafficking, as well as defective surface expression and pH-dependent membrane fusion. Immunoprecipitation of SSP confirmed an interaction between the signal peptide and the GP2 subunit; however, mutations within this FLLL motif disrupted the association of the GP1 subunit with the remaining glycoprotein complex. IMPORTANCE: Several members of the Arenaviridae family are neglected human pathogens capable of causing illness ranging from a nondescript flu-like syndrome to fulminant hemorrhagic fever. Infections by arenaviruses are mediated by attachment of the virus glycoprotein to receptors on host cells and virion internalization by fusion within an acidified endosome. SSP plays a critical role in the fusion of the virus with the host cell membrane. Within infected cells, the retained glycoprotein SSP plays a neglected yet essential role in glycoprotein biosynthesis. Without this 6-kDa polypeptide, the glycoprotein precursor is retained within the endoplasmic reticulum, and trafficking to the plasma membrane where SSP, GP1, and GP2 localize for glycoprotein assembly into infectious virions is inhibited. To investigate SSP contributions to glycoprotein maturation and function, we created an SSP-tagged glycoprotein to directly detect and manipulate this subunit. This resource will aid future studies to identify host factors that mediate glycoprotein maturation.

LCMV glycosylation modulates viral fitness and cell tropism.

The glycoprotein (GP) of arenaviruses is glycosylated at 11 conserved N-glycosylation sites. We constructed recombinant lymphocytic choriomeningitis virus (rLCMV) featuring either additions or deletions of these N-glycans to investigate their role in the viral life cycle. N-glycosylation at two sites, T87 and S97, were found to be necessary to rescue rLCMV. Three of nine successfully rescued mutants, S116A, T234A, and S373A, under selective pressures in either epithelial, neuronal, or macrophage cells reverted to WT sequence. Of the seven stable N-glycan deletion mutants, five of these led to altered viral fitness and cell tropism, assessed as growth in either mouse primary cortical neurons or bone marrow derived macrophages. These results demonstrate that the deletion of N-glycans in LCMV GP may confer an advantage to the virus for infection of neurons but a disadvantage in macrophages.

Development of peptide-conjugated morpholino oligomers as pan-arenavirus inhibitors.

Members of the Arenaviridae family are a threat to public health and can cause meningitis and hemorrhagic fever, and yet treatment options remain limited by a lack of effective antivirals. In this study, we found that peptide-conjugated phosphorodiamidate morpholino oligomers (PPMO) complementary to viral genomic RNA were effective in reducing arenavirus replication in cell cultures and in vivo. PPMO complementary to the Junín virus genome were designed to interfere with viral RNA synthesis or translation or both. However, only PPMO designed to potentially interfere with translation were effective in reducing virus replication. PPMO complementary to sequences that are highly conserved across the arenaviruses and located at the 5' termini of both genomic segments were effective against Junín virus, Tacaribe virus, Pichinde virus, and lymphocytic choriomeningitis virus (LCMV)-infected cell cultures and suppressed viral titers in the livers of LCMV-infected mice. These results suggest that arenavirus 5' genomic termini represent promising targets for pan-arenavirus antiviral therapeutic development.

Glycosylation modulates arenavirus glycoprotein expression and function.

The glycoprotein of lymphocytic choriomeningitis virus (LCMV) contains nine potential N-linked glycosylation sites. We investigated the function of these N-glycosylations by using alanine-scanning mutagenesis. All the available sites were occupied on GP1 and two of three on GP2. N-linked glycan mutations at positions 87 and 97 on GP1 resulted in reduction of expression and absence of cleavage and were necessary for downstream functions, as confirmed by the loss of GP-mediated fusion activity with T87A and S97A mutants. In contrast, T234A and E379N/A381T mutants impaired GP-mediated cell fusion without altered expression or processing. Infectivity via virus-like particles required glycans and a cleaved glycoprotein. Glycosylation at the first site within GP2, not normally utilized by LCMV, exhibited increased VLP infectivity. We also confirmed the role of the N-linked glycan at position 173 in the masking of the neutralizing epitope GP-1D. Taken together, our results indicated a strong relationship between fusion and infectivity.