Biology subjects

Lewensohn, R.

Publications and source records attributed to Lewensohn, R..

4 recordsLinked to original sources

bioRxiv2022

Analyses of single extracellular vesicles from non-small lung cancer cells to reveal effects by Epidermal growth factor inhibitor treatments

Precision cancer medicine have changed the treatment landscape of non-small cell lung cancer (NSCLC) as illustrated by tyrosine kinase inhibitors (TKIs) towards mutated Epidermal growth factor receptor (EGFR). Yet, responses to such TKIs e.g., erlotinib and osimertinib among patients are heterogenous and there is a need for non-invasive blood-based analytics to follow treatment response and reveal resistance to improve patients treatment outcome. Recently, extracellular vesicles (EVs) have been identified as an important source of tumor biomarkers promising to revolutionize liquid biopsy-based diagnosis of cancer. However, high heterogeneity has been a major bottleneck. The pathological signature is often hidden in the differential expression of membrane proteins in a subset of EVs which are difficult to identify with bulk techniques. Using a fluorescence-based approach, we for the first time demonstrate that the single-EV technique can be used to monitor the treatment response of targeted cancer therapies such as TKIs towards EGFR. To test the hypothesis, we analyzed the membrane proteins of native EVs extracted from EGFR-mutant NSCLC cell line, both prior and post treatment with EGFR-TKIs erlotinib or osimertinib. The selected cell line being refractory to erlotinib and responsive to osimertinib makes it a suitable model system. The expression level of five surface proteins; two common tetraspanins (CD9, CD81) and three markers of specific interest in lung cancer (EGFR, PD-L1, HER2) were studied. The data suggest that in contrast to erlotinib, the osimertinib treatment increases the population of PD-L1, EGFR and HER2 positive EVs while the expression level per EV decreases for all the three markers. The PD-L1 and HER2 expressing EV population seems to increase by several fold because of osimertinib treatment. The observations agree with the previous reports performed on cellular level indicating the biomarker potential of EVs for liquid-biopsy based monitoring of targeted cancer treatments. HighlightsO_LIMembrane protein analyses of single EVs may reveal distinct differences when lung cancer cells are refractory vs responsive under different EGFR-TKI treatments. C_LIO_LIComparison of 1st generation erlotinib and 3rd generation osimertinib shows clear signature on the expression of PD-L1, EGFR, HER2 on single EVs C_LIO_LIColocalization showed a change in common marker combinations before after treatment. C_LIO_LIPD-L1 expression per vesicle decreases while the number of PD-L1 positive EVs increases as a result of osimertinib treatment, indicating that such signature may not be detectable under bulk analysis C_LI

bioengineering↗

bioRxiv2021

SRF-CLICAL: an approach for patient risk stratification using random forest models

An important part of good clinical care is identifying which patients have a high likelihood of experiencing adverse outcomes. Similarly, due to the significant impact cancer treatment can have on a patients quality of life, it is also important to properly identify which patients are likely to benefit from more aggressive treatment options. As such, models for predictive risk stratification can be extremely useful in clinical decision making. In this paper, we present, Survival Random Forest-Clinical Categorization Algorithm (SRF-CLICAL), a new method for patient risk stratification using random forests for survival, regression and classification. As a proof of concept, we demonstrate this method on two different cohorts of cancer patients.

bioinformatics↗

bioRxiv2021

Multiplexed electrokinetic sensor for detection and therapy monitoring of extracellular vesicles from liquid biopsies of non-small-cell lung cancer patients

Liquid biopsies based on extracellular vesicle (EV) protein profiles represent a promising tool for treatment monitoring of tumors, including non-small-cell lung cancers (NSCLC). In this study, we present the development of an electrokinetic sensor for multiplexed surface protein profiling of EVs and analysis of clinical samples. The method detects the difference in the streaming current obtained as a result of EV binding to the inner surface of a functionalized microcapillary, thereby estimating the expression level of a surface marker. Using multiple microchannels functionalized with different antibodies in a parallel fluidic connection, we first demonstrate the capacity for simultaneous detection of multiple surface markers in small EVs (sEVs) from NSCLC cells. To investigate the prospects of liquid biopsies based on EVs, we then apply the method to profile sEVs isolated from the pleural effusion (PE) fluids of three NSCLC adenocarcinoma patients with different genomic alterations (ALK-fusion, KRAS and EGFR) and applied treatments (chemotherapy, EGFR or ALK tyrosine kinase inhibitors). These vesicles were targeted against CD9 tetraspanin, as well as EGFR and PD-L1, two markers of interest in NSCLC. The electrokinetic signals showed detection of these markers on sEVs yet highlighting distinct interpatient differences, e.g., increased EGFR levels in sEVs from a patient with EGFR mutation as compared to an ALK-mutant one. The sensors also detected differences in PD-L1 expressions, in line with those measured by complementary methods. The analysis of sEVs from a patient prior and post crizotinib treatment also revealed a significant increase in the expression of some markers, e.g. EGFR and PD-L1. The obtained results hold promise for the application of the method for tumor treatment monitoring based on sEVs from liquid biopsies.

bioengineering↗

bioRxiv2021

High throughput imaging of nanoscale extracellular vesicles by scanning electron microscopy for accurate size-based profiling and morphological analysis.

Nanoscale extracellular vesicle (EVs) have been found to play a key role in intercellular communication, offering opportunities for both diagnostics and therapeutics. However, lying below the diffraction limit and also being highly heterogeneous in their size, morphology and abundance, these vesicles pose significant challenges for their physical characterization. Here, we present a direct visual approach for their accurate morphological and size-based profiling by using scanning electron microscopy (SEM). To achieve that, we methodically examined various process steps and developed a protocol to improve the throughput, conformity and image quality while preserving the shape of EVs. The investigation was performed with small EVs (sEVs) isolated from a non-small cell lung cancer (NSCLC) cell line H1975 as well as from a human serum, and the results were compared with those obtained from nanoparticle tracking analysis (NTA). While the comparison of the sEV size distributions showed good agreement between the two methods for large sEVs (diameter >70 nm), the microscopy based approach showed a better capacity for analyses on smaller vesicles, with higher sEV counts compared to NTA. In addition, we demonstrated the possibility of identifying non-EV particles based on size and morphological features. The study also showed process steps that can generate artifacts bearing resemblance with sEVs. The results therefore present a simple way to use a widely available microscopy tool for accurate and high throughput physical characterization of EVs.

bioengineering↗