Fractionating power in programmed field-flow fractionation: exponential sedimentation field decay

A novel immune-related prognostic index for predicting breast cancer overall survival

PURPOSE

To find immune-related genes with prognostic value in breast cancer, and construct a prognostic risk assessment model to make a more accurate assessment. Moreover, looking for potential immune markers for breast cancer immunotherapy.

METHODS

The breast cancer (BC) data were retrieved from The Cancer Genome Atlas (TCGA) database as a training set. Through the Weighted gene co-expression network analysis (WGCNA), Kaplan-Meier (KM) analysis, lasso regression analysis and stepwise backward Cox regression analysis, screening for prognosis-related immune genes, a prognostic index was built, and external validation with two data sets of Gene Expression Omnibus (GEO) database was performed. Transcription factor (TF) regulatory network was constructed to identify key transcription factors that regulate prognostic immune genes. Gene set enrichment analysis (GSEA) was used to explore the signal pathways differences between high and low-risk groups, estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment.

RESULTS

We obtained 10 prognosis-related immune genes, and the index showed accurate prognostic value. We also identified 7 prognostic transcription factors. Multiple signaling pathways that inhibit tumor progression were enriched in the low-risk group, and risk score was significantly negatively related to the degree of immune infiltration and the expression level of immune checkpoint genes.

CONCLUSION

We successfully constructed an independent prognostic index, which not only has a stronger predictive ability than the tumor pathological stage, but also can reflect the immune infiltration of breast cancer patients.

Midkine rewires the melanoma microenvironment toward a tolerogenic and immune-resistant state

An open question in aggressive cancers such as melanoma is how malignant cells can shift the immune system to pro-tumorigenic functions. Here we identify midkine (MDK) as a melanoma-secreted driver of an inflamed, but immune evasive, microenvironment that defines poor patient prognosis and resistance to immune checkpoint blockade. Mechanistically, MDK was found to control the transcriptome of melanoma cells, allowing for coordinated activation of nuclear factor-κB and downregulation of interferon-associated pathways. The resulting MDK-modulated secretome educated macrophages towards tolerant phenotypes that promoted CD8⁺ T cell dysfunction. In contrast, genetic targeting of MDK sensitized melanoma cells to anti-PD-1/anti-PD-L1 treatment. Emphasizing the translational relevance of these findings, the expression profile of MDK-depleted tumors was enriched in key indicators of a good response to immune checkpoint blockers in independent patient cohorts. Together, these data reveal that MDK acts as an internal modulator of autocrine and paracrine signals that maintain immune suppression in aggressive melanomas.

Microscaled proteogenomic methods for precision oncology

Cancer proteogenomics promises new insights into cancer biology and treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifications by mass spectrometry (MS). A critical limitation is sample input requirements that exceed many sources of clinically important material. Here we report a proteogenomics approach for core biopsies using tissue-sparing specimen processing and microscaled proteomics. As a demonstration, we analyze core needle biopsies from ERBB2 positive breast cancers before and 48–72 h after initiating neoadjuvant trastuzumab-based chemotherapy. We show greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identify potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression and an inactive immune microenvironment. The clinical utility and discovery potential of proteogenomics at biopsy-scale warrants further investigation.

Connecting genomics and proteomics allows the development of more efficient and specific treatments for cancer. Here, the authors develop proteogenomic methods to defining cancer signaling in-vivo starting from core needle biopsies and with application to a HER2 breast cancer focused clinical trial.

Asymmetrical flow field flow fractionation methods to characterize submicron particles: application to carbon-based aggregates and nanoplastics

In the last 10 years, asymmetrical flow field flow fractionation (AF4) has been one of the most promising approaches to characterize colloidal particles. Nevertheless, despite its potentialities, it is still considered a complex technique to set up, and the theory is difficult to apply for the characterization of complex samples containing submicron particles and nanoparticles. In the present work, we developed and propose a simple analytical strategy to rapidly determine the presence of several submicron populations in an unknown sample with one programmed AF4 method. To illustrate this method, we analyzed polystyrene particles and fullerene aggregates of size covering the whole colloidal size distribution. A global and fast AF4 method (method O) allowed us to screen the presence of particles with size ranging from 1 to 800 nm. By examination of the fractionating power F _d, as proposed in the literature, convenient fractionation resolution was obtained for size ranging from 10 to 400 nm. The global F _d values, as well as the steric inversion diameter, for the whole colloidal size distribution correspond to the predicted values obtained by model studies. On the basis of this method and without the channel components or mobile phase composition being changed, four isocratic subfraction methods were performed to achieve further high-resolution separation as a function of different size classes: 10-100 nm, 100-200 nm, 200-450 nm, and 450-800 nm in diameter. Finally, all the methods developed were applied in characterization of nanoplastics, which has received great attention in recent years. Graphical Absract Characterization of the nanoplastics by asymmetrical flow field flow fractionation within the colloidal size range.

Size exclusion chromatography with superficially porous particles

A comparison is made using size-exclusion chromatography (SEC) of synthetic polymers between fully porous particles (FPPs) and superficially porous particles (SPPs) with similar particle diameters, pore sizes and equal flow rates. Polystyrene molecular weight standards with a mobile phase of tetrahydrofuran are utilized for all measurements conducted with standard HPLC equipment. Although it is traditionally thought that larger pore volume is thermodynamically advantageous in SEC for better separations, SPPs have kinetic advantages and these will be shown to compensate for the loss in pore volume compared to FPPs. The comparison metrics include the elution range (smaller with SPPs), the plate count (larger for SPPs), the rate production of theoretical plates (larger for SPPs) and the specific resolution (larger with FPPs). Advantages to using SPPs for SEC are discussed such that similar separations can be conducted faster using SPPs. SEC using SPPs offers similar peak capacities to that using FPPs but with faster operation. This also suggests that SEC conducted in the second dimension of a two-dimensional liquid chromatograph may benefit with reduced run time and with equivalently reduced peak width making SPPs advantageous for sampling the first dimension by the second dimension separator. Additional advantages are discussed for biomolecules along with a discussion of optimization criteria for size-based separations.

Fractionating power and outlet stream polydispersity in asymmetrical flow field-flow fractionation. Part II: programmed operation

Asymmetrical flow field-flow fractionation (As-FlFFF) is a widely used technique for analyzing polydisperse nanoparticle and macromolecular samples. The programmed decay of cross flow rate is often employed. The interdependence of the cross flow rate through the membrane and the fluid flow along the channel length complicates the prediction of elution time and fractionating power. The theory for their calculation is presented. It is also confirmed for examples of exponential decay of cross flow rate with constant channel outlet flow rate that the residual sample polydispersity at the channel outlet is quite well approximated by the reciprocal of four times the fractionating power. Residual polydispersity is of importance when online MALS or DLS detection are used to extract quantitative information on particle size or molecular weight. The theory presented here provides a firm basis for the optimization of programmed flow conditions in As-FlFFF. Graphical abstract Channel outlet polydispersity remains significant following fractionation by As-FlFFF under conditions of programmed decay of cross flow rate.

Simulation and experimental determination of the online separation of blood components with the help of microfluidic cascading spirals

Microfluidic spirals were used to successfully separate rare solid components from unpretreated human whole blood samples. The measured separation ratio of the spirals is the factor by which the concentration of the rare component is increased due to the Dean effect present in a flow profile in a curved duct. Different rates of dilution of the blood samples with a phosphate-buffered solution were investigated. The diameters of the spherical particles to separate ranged from 2 μm to 18 μm. It was found that diluting the blood to 20% is optimal leading to a separation ratio up to 1.97. Using two spirals continuously placed in a row led to an increase in separation efficacy in samples consisting of phosphate-buffered solution only from 1.86 to 3.79. Numerical investigations were carried out to display the flow profiles of Newtonian water samples and the shear-thinning blood samples in the cross-section of the experimentally handled channels. A macroscopic difference in velocity between the two rheologically different fluids could not be found. The macroscopic Dean flow is equally present and useful to help particles migrate to certain equilibrium positions in blood as well as lower viscous Newtonian fluids. The investigations highlight the potential for using highly concentrated, very heterogeneous, and non-Newtonian fluidic systems in known microsystems for screening applications.

Characterization of magnetic nanoparticles using programmed quadrupole magnetic field-flow fractionation

Quadrupole magnetic field-flow fractionation is a relatively new technique for the separation and characterization of magnetic nanoparticles. Magnetic nanoparticles are often of composite nature having a magnetic component, which may be a very finely divided material, and a polymeric or other material coating that incorporates this magnetic material and stabilizes the particles in suspension. There may be other components such as antibodies on the surface for specific binding to biological cells, or chemotherapeutic drugs for magnetic drug delivery. Magnetic field-flow fractionation (MgFFF) has the potential for determining the distribution of the magnetic material among the particles in a given sample. MgFFF differs from most other forms of field-flow fractionation in that the magnetic field that brings about particle separation induces magnetic dipole moments in the nanoparticles, and these potentially can interact with one another and perturb the separation. This aspect is examined in the present work. Samples of magnetic nanoparticles were analysed under different experimental conditions to determine the sensitivity of the method to variation of conditions. The results are shown to be consistent and insensitive to conditions, although magnetite content appeared to be somewhat higher than expected.

Sequential CD34 cell fractionation by magnetophoresis in a magnetic dipole flow sorter

Cell separation and fractionation based on fluorescent and magnetic labeling procedures are common tools in contemporary research. These techniques rely on binding of fluorophores or magnetic particles conjugated to antibodies to target cells. Cell surface marker expression levels within cell populations vary with progression through the cell cycle. In an earlier work we showed the reproducible magnetic fractionation (single pass) of the Jurkat cell line based on the population distribution of CD45 surface marker expression. Here we present a study on magnetic fractionation of a stem and progenitor cell (SPC) population using the established acute myelogenous leukemia cell line KG-1a as a cell model. The cells express a CD34 cell surface marker associated with the hematopoietic progenitor cell activity and the progenitor cell lineage commitment. The CD34 expression level is approximately an order of magnitude lower than that of the CD45 marker, which required further improvements of the magnetic fractionation apparatus. The cells were immunomagnetically labeled using a sandwich of anti-CD34 antibody-phycoerythrin (PE) conjugate and anti-PE magnetic nanobead and fractionated into eight components using a continuous flow dipole magnetophoresis apparatus. The CD34 marker expression distribution between sorted fractions was measured by quantitative PE flow cytometry (using QuantiBRITE PE calibration beads), and it was shown to be correlated with the cell magnetophoretic mobility distribution. A flow outlet addressing scheme based on the concept of the transport lamina thickness was used to control cell distribution between the eight outlet ports. The fractional cell distributions showed good agreement with numerical simulations of the fractionation based on the cell magnetophoretic mobility distribution in the unsorted sample.

Varations of molecular weight estimation by HP-size exclusion chromatography with UVA versus online DOC detection

High performance size exclusion chromatography (HPSEC) with ultraviolet absorbance (UVA) detection has been widely utilized to estimate the molecular weight (MW) and MW distribution of natural organic matter (NOM). However, the estimation of MW with UVA detection is inherently inaccurate because UVA at 254 nm only detects limited components (mostly pi bonded molecules) of NOM, and the molar absorptivity of these different NOM constituents is not equal. In comparison, a SEC chromatogram obtained with a DOC detector showed significant differences compared to a corresponding UVA chromatogram, resulting in different MW values as well as different estimates of polydispersivity. The MWs of Suwannee River humic acid (SRHA), Suwannee River fulvic acid (SRFA), and various mixtures thereof were estimated with HPSEC coupled with UVA and DOC detectors. The results show that UVA is not an adequate detector for quantitative analysis of MW estimation but rather can be used only for limited qualitative analysis. The NOM in several natural waters (Irvine Ranch, California groundwater, and Barr Lake, Colorado surface water) were also characterized to demonstrate the different MWs obtained with the two detectors. The results of the SEC-DOC chromatograms revealed NOM constituent peaks that went undetected by UVA. Utilizing online DOC detection, a better representation of NOM MWs was suggested, with NOM displaying higher weight-averaged MW (Mw) and lower number-averaged MW (Mn) as well as higher polydispersivity. A method for estimation of the MWs of NOM fractional components and polydispersivities is presented.

Physical Characterization and Quantification of Bacteria by Sedimentation Field-Flow Fractionation

Studies in microbial ecology require accurate measures of cell number and biomass. Although epifluorescence microscopy is an accepted and dependable method for determining cell numbers, current methods of converting biovolume to biomass are error prone, tedious, and labor-intensive. This paper describes a technique with sedimentation field-flow fractionation to enumerate bacteria and determine their density, size, and mass. Using cultured cells of different shapes and sizes, we determined optimum values for separation run parameters and sample-handling procedures. The technique described can separate and detect 4′, 6-diamidino-2-phenylindole-stained cells and generate a fractogram from which cell numbers and their size or mass distribution can be calculated. A direct method for estimating bacterial biomass (dry organic matter content) which offers distinct advantages over present methods for calculating biomass has been developed.

Comparison of power and exponential field programming in field-flow fractionation

Field programming in field-flow fractionation has the purpose of expanding the molecular weight or particle diameter range subject to a single analytical run. The two most widely used field programs are those in which the field strength decays with time according to an exponential function and a power function, respectively. The performances of these two programming functions are compared by obtaining limiting equations showing how retention time tr, standard deviation in retention sigma t, and fractionating power Fd vary with particle diameter d. It is shown that uniform fractionating power (Fd independent of d) can be obtained with power programming but that in exponential programming Fd is always non-uniform, varying as d-1/2. In exponential programming a linear relationship arises between tr and log d. This particular relationship is impossible to realize in power programming but an alternative linear relationship can be obtained by plotting tr versus dt/3. These results are made more concrete by plotting and comparing field strength, relative field strength, Fd and tr for specific programming cases.