Differential scanning calorimetry of blood plasma for clinical diagnosis and monitoring

Characterization of myocardial injury phenotype by thermal liquid biopsy

Background and aims

With the advent and implementation of high-sensitivity cardiac troponin assays, differentiation of patients with distinct types of myocardial injuries, including acute thrombotic myocardial infarction (TMI), acute non-thrombotic myocardial injury (nTMi), and chronic coronary atherosclerotic disease (cCAD), is of pressing clinical importance. Thermal liquid biopsy (TLB) emerges as a valuable diagnostic tool, relying on identifying thermally induced conformational changes of biomolecules in blood plasma. While TLB has proven useful in detecting and monitoring several cancers and autoimmune diseases, its application in cardiovascular diseases remains unexplored. In this proof-of-concept study, we sought to determine and characterize TLB profiles in patients with TMI, nTMi, and cCAD at multiple acute-phase time points (T 0 h, T 2 h, T 4 h, T 24 h, T 48 h) as well as a follow-up time point (Tfu) when the patient was in a stable state.

Methods

TLB profiles were collected for 115 patients (60 with TMI, 35 with nTMi, and 20 with cCAD) who underwent coronary angiography at the event presentation and had subsequent follow-up. Medical history, physical, electrocardiographic, histological, biochemical, and angiographic data were gathered through medical records, standardized patient interviews, and core laboratory measurements.

Results

Distinctive signatures were noted in the median TLB profiles across the three patient types. TLB profiles for TMI and nTMi patients exhibited gradual changes from T0 to Tfu, with significant differences during the acute and quiescent phases. During the quiescent phase, all three patient types demonstrated similar TLB signatures. An unsupervised clustering analysis revealed a unique TLB signature for the patients with TMI. TLB metrics generated from specific features of TLB profiles were tested for differences between patient groups. The first moment temperature (TFM) metric distinguished all three groups at time of presentation (T0). In addition, 13 other TLB-derived metrics were shown to have distinct distributions between patients with TMI and those with cCAD.

Conclusion

Our findings demonstrated the use of TLB as a sensitive and data-rich technique to be explored in cardiovascular diseases, thus providing valuable insight into acute myocardial injury events.

Deconvolution Analysis of the Non-Ionic Iomeprol, Iobitridol and Iodixanol Contrast Media-Treated Human Whole Blood Thermograms: A Comparative Study

To study the effect of non-ionic contrast media on anticoagulated and non-anticoagulated human whole blood samples, calorimetric measurements were performed. The anticoagulated plasma showed the greatest fall in the total ΔH after Iodixanol treatment. The plasma-free erythrocytes revealed a pronounced shift in the Tmax and a decrease in the ΔH of hemoglobin and transferrin. The total ΔH of Iodixanol treatment showed the highest decline, while Iomeprol and Iobitridol had fewer adverse effects. Similarly, the non-anticoagulated samples revealed a decrease both in the Tmax and the ΔH of albumin and immunoglobulin-specific transitions. The total ΔH showed that Iodixanol had more influence on the serum. The serum-free erythrocyte samples resulted in a significant drop in the Tmax of erythrocyte and transferrin (~5-6 °C). The ΔH of deconvolved hemoglobin and transferrin decreased considerably; however, the ΔH of albumin increased. Surprisingly, compared to Iomeprol and Iobitridol treatments, the total ΔH of Iodixanol was less pronounced in the non-anticoagulated erythrocyte samples. In sum, each non-ionic contrast medium affected the thermal stability of anticoagulated and non-anticoagulated erythrocyte proteins. Interestingly, Iodixanol treatment caused more significant effects. These findings suggest that conformational changes in blood components can occur, which can potentially lead to the increased prevalence of cardiovascular dysfunctions and blood clotting.

Plasma Thermogram Parameters Differentiate Status and Overall Survival of Melanoma Patients

Melanoma is the fifth most common cancer in the United States and the deadliest of all skin cancers. Even with recent advancements in treatment, there is still a 13% two-year recurrence rate, with approximately 30% of recurrences being distant metastases. Identifying patients at high risk for recurrence or advanced disease is critical for optimal clinical decision-making. Currently, there is substantial variability in the selection of screening tests and imaging, with most modalities characterized by relatively low accuracy. In the current study, we built upon a preliminary examination of differential scanning calorimetry (DSC) in the melanoma setting to examine its utility for diagnostic and prognostic assessment. Using regression analysis, we found that selected DSC profile (thermogram) parameters were useful for differentiation between melanoma patients and healthy controls, with more complex models distinguishing melanoma patients with no evidence of disease from patients with active disease. Thermogram features contributing to the third principal component (PC3) were useful for differentiation between controls and melanoma patients, and Cox proportional hazards regression analysis indicated that PC3 was useful for predicting the overall survival of active melanoma patients. With the further development and optimization of the classification method, DSC could complement current diagnostic strategies to improve screening, diagnosis, and prognosis of melanoma patients.

Blood Plasma Calorimetric Profiles of Women with Preeclampsia: Effect of Oxidative Stress

Preeclampsia is a pregnancy-related disease with poor placentation and presents itself through hypertension and proteinuria. The disease is also associated with the oxidative modification of proteins in maternal blood plasma. In this work, we combine differential scanning calorimetry (DSC), capillary electrophoresis, and atomic force microscopy (AFM) to evaluate the changes in the plasma denaturation profiles of patients with preeclampsia (PE) as compared with those of pregnant controls. Our results demonstrate that the last trimester of pregnancy substantially affects the main calorimetric characteristics of blood plasma from pregnant controls relative to nonpregnant women. These variations correlate well with the changes in protein levels determined by electrophoresis. DSC analysis revealed significant deviations in the plasma heat capacity profiles of preeclamptic patients from those of pregnant controls. These alterations are expressed mainly in a substantial reduction in albumin-assigned transitions and an upward shift in its denaturation temperature, lower calorimetric enthalpy changes, and a reduced ratio of heat capacity in the albumin/globulin-assigned thermal transitions, which are more pronounced in severe PE cases. The in vitro oxidation model shows that the alteration of PE thermograms is partly related to protein oxidation. AFM data detected numerous aggregate formations in the plasma of PE samples and fewer small ones in the pregnant controls, which are not found in healthy nonpregnant samples. These findings could serve as a basis for further investigations to reveal the possible relationship between albumin thermal stabilization, the increased inflammatory state and oxidative stress, and protein misfolding in preeclampsia.

Modification of the structural stability of human serum albumin in rheumatoid arthritis

Differential scanning calorimetry (DSC) can indicate changes in structure and/or concentration of the most abundant proteins in a biological sample via heat denaturation curves (HDCs). In blood serum for example, HDC changes result from either concentration changes or altered thermal stabilities for 7-10 proteins and has previously been shown capable of differentiating between sick and healthy human subjects. Here, we compare HDCs and proteomic profiles of 50 patients experiencing joint-inflammatory symptoms, 27 of which were clinically diagnosed with rheumatoid arthritis (RA). The HDC of all 50 subjects appeared significantly different from expected healthy curves, but comparison of additional differences between the RA and the non-RA subjects allowed more specific understanding of RA samples. We used mass spectrometry (MS) to investigate the reasons behind the additional HDC changes observed in RA patients. The HDC differences do not appear to be directly related to differences in the concentrations of abundant serum proteins. Rather, the differences can be attributed to modified thermal stability of some fraction of the human serum albumin (HSA) proteins in the sample. By quantifying differences in the frequency of artificially induced post translational modifications (PTMs), we found that HSA in RA subjects had a much lower surface accessibility, indicating potential ligand or protein binding partners in certain regions that could explain the shift in HSA melting temperature in the RA HDCs. Several low abundance proteins were found to have significant changes in concentration in RA subjects and could be involved in or related to binding of HSA. Certain amino acid sites clusters were found to be less accessible in RA subjects, suggesting changes in HSA structure that may be related to changes in protein-protein interactions. These results all support a change in behavior of HSA which may give insight into mechanisms of RA pathology.

Plasma nanoDSF Denaturation Profile at Baseline Is Predictive of Glioblastoma EGFR Status

Glioblastoma (GBM) is the most frequent and aggressive primary brain tumor in adults. Recently, we demonstrated that plasma denaturation profiles of glioblastoma patients obtained using Differential Scanning Fluorimetry can be automatically distinguished from healthy controls with the help of Artificial Intelligence (AI). Here, we used a set of machine-learning algorithms to automatically classify plasma denaturation profiles of glioblastoma patients according to their EGFR status. We found that Adaboost AI is able to discriminate EGFR alterations in GBM with an 81.5% accuracy. Our study shows that the use of these plasma denaturation profiles could answer the unmet neuro-oncology need for diagnostic predictive biomarker in combination with brain MRI and clinical data, in order to allow for a rapid orientation of patients for a definitive pathological diagnosis and then treatment. We complete this study by showing that discriminating another mutation, MGMT, seems harder, and that post-surgery monitoring using our approach is not conclusive in the 48 h that follow the surgery.

Thermodynamic Signatures of Blood Plasma Proteome in Neurodegenerative Pathologies

Discovery of diagnostic biomarkers for age-related neurodegenerative pathologies (NDDs) is essential for accurate diagnosis, following disease progression and drug development. Blood plasma and blood cells are important peripheral sources for NDDs' biomarkers that, although present in lower concentrations than in cerebrospinal fluid, would allow noninvasive diagnostics. To identify new biomarkers for Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS), in this work we have evaluated the modifications in the thermodynamic behavior of blood plasma proteome exploring differential scanning calorimetry. The plasma thermodynamics reflected the complexity and heterogeneity of the two pathologies. The unfolding temperature of the most abundant plasma protein albumin and the weighted average center of the calorimetric profile appeared as the two thermodynamic signatures that reflected modifications of the plasma proteome, i.e., strong thermal stabilization of albumin and plasma proteins' interaction network, related to both pathologies. Based on those two signatures, both PD and ALS patients were stratified in two sets, except several cases with thermodynamic parameters that strongly differed from those of the calorimetric sets. Along with modifications of the plasma thermodynamic behavior, we found altered globulin levels in all PD and ALS patients' plasma (higher level of α- and β-globulin fractions and lower level of γ-globulin fraction than the respective reference values) employing capillary electrophoresis. The presented results reveal the potential of calorimetry to indirectly identify NDDs' biomarkers in blood plasma.

Thermodynamic Sensitivity of Blood Plasma Components in Patients Afflicted with Skin, Breast and Pancreatic Forms of Cancer

According to the World Health Organization's 2018 Global Cancer Survey, cancer is the second leading cause of death. From this survey, the third most common is breast cancer, the fifth is melanoma malignum and pancreatic adenocarcinoma ranks twentieth. Undoubtedly, the early diagnosis and monitoring of these tumors and related research is important for aspects of patient care. The aim of our present review was to explain an impressive methodology that is deemed suitable in reference to studying blood sample deviations in the case of solid tumors. Essentially, we compared the heat denaturation responses of blood plasma components through differential scanning calorimetry (DSC). In the control, between five and seven separable components can be detected, in which the primary component was albumin, while in the case of tumorous patients, the peaks of immunoglobulins were dominant. Moreover, the shape of the plasma DSC curves changed with a shift in the higher temperature ranges; thus, their pattern can be used as a suitable marker of direct immunological responses. The further development of the analysis of DSC curves raises the possibility of the early diagnosis of a potential tumor, the monitoring of diseases, or testing the efficacy of the therapy from a single drop of blood.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Calorimetric Markers for Detection and Monitoring of Multiple Myeloma

Simple Summary

This review highlights the potential of differential scanning calorimetry for multiple myeloma diagnosis and monitoring of the treatment outcome. The thermodynamic signatures of blood sera from patients with multiple myeloma are strongly dependent on the concentration and isotype of the secreted monoclonal immunoglobulins. Mathematical methods developed to analyze the biocalorimetry data and distinguish “diseased” from “healthy” thermogram to stratify plasma calorimetric profiles and determine specific interrelations between calorimetric and biochemical/clinical data are discussed.

Abstract

This review summarizes data obtained thus far on the application of differential scanning calorimetry (DSC) for the analysis of blood sera from patients diagnosed with multiple myeloma (MM) with the secretion of the most common isotypes of monoclonal proteins (M-proteins), free light chains (FLC) and non-secretory MM, as well as Waldenström macroglobulinemia and the premalignant state monoclonal gammopathy of undetermined significance. The heterogeneous nature of MM is reflected in the thermal stability profiles of the blood serum proteome of MM patients found to depend on both the level and the isotype of the secreted M-proteins or FLC. Common calorimetric markers feature the vast majority of the different myeloma types, i.e., stabilization of the major serum proteins and decrease in the albumin/globulin heat capacity ratio. A unique calorimetric fingerprint of FLC molecules forming amorphous aggregates is the low-temperature transition centered at 57 °C for a calorimetric set of FLC MM and at 46–47 °C for a single FLC MM case for which larger aggregates were formed. The calorimetric assay proved particularly advantageous for non-secretory MM and is thus a suitable tool for monitoring such patients during treatment courses. Thus, DSC provides a promising blood-based approach as a complementary tool for MM detection and monitoring.

Altered Thermal Behavior of Blood Plasma Proteome Related to Inflammatory Cytokines in Early Pregnancy Loss

Early pregnancy loss (EPL) is a relatively common pathology of which almost 50% of cases remain idiopathic. In the search for novel biomarkers, differential scanning calorimetry (DSC) is intensively used to characterize the thermodynamic behavior of blood plasma/serum proteome in health and disease. Herein, for the first time, we investigate the DSC denaturation profiles of blood plasma derived from patients suffering EPL compared to healthy pregnant and non-pregnant women. Data analysis reveals that 58% of the EPL thermograms differ significantly from those of healthy pregnant women. Thermal stabilization of a fraction of albumin-assigned transition with concomitant suppression of the major and enhancement of the globulin-assigned transition are characteristic features of EPL calorimetric profiles that could be used as a new indicator of a risk pregnancy. The presented results suggest an altered composition or intermolecular interactions of the plasma proteome of women with EPL. In addition, the alterations of the EPL thermograms correlate with the increased blood levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and a higher prevalence of the polymorphism in the plasminogen activator inhibitor type-1 (PAI-1) gene, suggesting an expression of an overall enhanced immune response. The concomitant changes in plasma thermograms confirm the potential of the DSC approach for distinguishing changes in the pathological state of the blood plasma proteome.

Saliva profiling with differential scanning calorimetry: A feasibility study with ex vivo samples

Differential scanning calorimetry (DSC) has been used widely to study various biomarkers from blood, less is known about the protein profiles from saliva. The aim of the study was to investigate the use DSC in order to detect saliva thermal profiles and determine the most appropriate sampling procedure to collect and process saliva. Saliva was collected from 25 healthy young individuals and processed using different protocols based on centrifugation and filtering. The most effective protocol was centrifugation at 5000g for 10 min at 4°C followed by filtration through Millex 0.45 μm filter. Prepared samples were transferred to 3 mL calorimetric ampoules and then loaded into TAM48 calibrated to 30°C until analysis. DSC scans were recorded from 30°C to 90°C at a scan rate of 1°C/h with a pre-conditioning the samples to starting temperature for 1 h. The results show that the peak distribution of protein melting points was clearly bimodal, and the majority of peaks appeared between 40–50°C. Another set of peaks is visible between 65°C– 75°C. Additionally, the peak amplitude and area under the peak are less affected by the concentration of protein in the sample than by the individual differences between people. In conclusion, the study shows that with right preparation of the samples, there is a possibility to have thermograms of salivary proteins that show peaks in similar temperature regions between different healthy volunteers.

Sample Processing Considerations for Protein Stability Studies of Low Concentration Biofluid Samples using Differential Scanning Calorimetry

Background:

The analysis of biofluid samples with low protein content (e.g., urine or saliva) can be challenging for downstream analysis methods with limited sensitivity. To circumvent this problem, sample processing methods are employed to increase the protein concentration in analyzed samples. However, for some techniques, like differential scanning calorimetry (DSC) that characterizes thermally-induced unfolding of biomolecules, sample processing must not affect native protein structure and stability.

Methods:

We evaluated centrifugal concentration and stirred cell ultrafiltration, two common methods of sample concentration characterized by a low risk of protein denaturation, with the goal of establishing a protocol for DSC analysis of low concentration biospecimens.

Results:

Our studies indicate that both methods can affect protein stability assessed by DSC and, even after optimization of several parameters, the obtained DSC profile (thermogram) suggested that sample processing affects the structure or intermolecular interactions of component proteins contributing to altered thermal stability detectable by DSC. We also found a relationship between changes in thermograms and low protein concentration, indicating that diluting biospecimens to concentrations below 0.1 mg/mL can perturb the intermolecular environment and affect the structure of proteins present in the solution.

Conclusions:

Dilution of samples below 0.1 mg/mL, as well as concentration of samples with low protein content, resulted in affected thermogram shapes suggesting changes in protein stability. This should be taken into account when concentrating dilute samples or employing techniques that lower the protein concentration (e.g., fractionation), when downstream applications include techniques, such as DSC, that require the preservation of native protein forms.

The Utility of Differential Scanning Calorimetry Curves of Blood Plasma for Diagnosis, Subtype Differentiation and Predicted Survival in Lung Cancer

Early detection of lung cancer (LC) significantly increases the likelihood of successful treatment and improves LC survival rates. Currently, screening (mainly low-dose CT scans) is recommended for individuals at high risk. However, the recent increase in the number of LC cases unrelated to the well-known risk factors, and the high false-positive rate of low-dose CT, indicate a need to develop new, non-invasive methods for LC detection. Therefore, we evaluated the use of differential scanning calorimetry (DSC) for LC patients' diagnosis and predicted survival. Additionally, by applying mass spectrometry, we investigated whether changes in O- and N-glycosylation of plasma proteins could be an underlying mechanism responsible for observed differences in DSC curves of LC and control subjects. Our results indicate selected DSC curve features could be useful for differentiation of LC patients from controls with some capable of distinction between subtypes and stages of LC. DSC curve features also correlate with LC patients' overall/progression free survival. Moreover, the development of classification models combining patients' DSC curves with selected plasma protein glycosylation levels that changed in the presence of LC could improve the sensitivity and specificity of the detection of LC. With further optimization and development of the classification method, DSC could provide an accurate, non-invasive, radiation-free strategy for LC screening and diagnosis.

Red Blood Cells' Thermodynamic Behavior in Neurodegenerative Pathologies and Aging

The main trend of current research in neurodegenerative diseases (NDDs) is directed towards the discovery of novel biomarkers for disease diagnostics and progression. The pathological features of NDDs suggest that diagnostic markers can be found in peripheral fluids and cells. Herein, we investigated the thermodynamic behavior of the peripheral red blood cells (RBCs) derived from patients diagnosed with three common NDDs—Parkinson’s disease (PD), Alzheimer’s disease (AD), and amyotrophic lateral sclerosis (ALS) and compared it with that of healthy individuals, evaluating both fresh and aged RBCs. We established that NDDs can be differentiated from the normal healthy state on the basis of the variation in the thermodynamic parameters of the unfolding of major RBCs proteins—the cytoplasmic hemoglobin (Hb) and the membrane Band 3 (B3) protein. A common feature of NDDs is the higher thermal stability of both Hb and B3 proteins along the RBCs aging, while the calorimetric enthalpy can distinguish PD from ALS and AD. Our data provide insights into the RBCs thermodynamic behavior in two complex and tightly related phenomena—neurodegenerative pathologies and aging, and it suggests that the determined thermodynamic parameters are fingerprints of the altered conformation of Hb and B3 protein and modified RBCs’ aging in the studied NDDs.

Blood serum denaturation profile examined by differential scanning calorimetry reflects the effort put into ultramarathon by amateur long-distance runners

The impact of participation in the ultramarathon on the health and mental and physical condition is very complex. Undoubtedly, exercise brings many benefits but also involves health risks. Especially such an extreme effort as the one associated with finishing the ultramarathon run, can be dangerous to the health of the runner. With the variety of possible biomarkers of excessive fatigue that threaten health and life, a question arises which of them are the best and which should be considered in amateur long-distance runners showing particularly high individual variability. In this study differential scanning calorimetry (DSC) has been applied to show the overall effect of the 12-h run on blood sera of participants. Serum samples were obtained from the blood of ten male amateur long-distance runners, collected before and immediately after the run. Distinct changes in the shape of DSC curves have been observed for serum after finishing the run relative to pre-race serum. Statistically significant differences between stages "before" and "after" ultramarathon running have been found for parameters of the endothermic transition associated with denaturation of serum proteins. An increase in the temperature (from 70.9 ± 0.9 to 75.8 ± 2.9 °C) and excess heat capacity (from 0.859 ± 0.201 to 1.102 ± 0.226 Jg-1 °C-1) at peak maximum, the enthalpy of serum denaturation (from 18.55 ± 6.52 to 22.08 ± 5.61 Jg^-1) and the first moment of the thermal transition with respect to the temperature (from the value of 67.0 ± 2.1 to 72.6 ± 2.1 °C) has been observed. These results show a clear impact of running an ultramarathon on the participant's blood serum.

An AI-Powered Blood Test to Detect Cancer Using NanoDSF

Glioblastoma is the most frequent and aggressive primary brain tumor. Its diagnosis is based on resection or biopsy that could be especially difficult and dangerous in the case of deep location or patient comorbidities. Monitoring disease evolution and progression also requires repeated biopsies that are often not feasible. Therefore, there is an urgent need to develop biomarkers to diagnose and follow glioblastoma evolution in a minimally invasive way. In the present study, we described a novel cancer detection method based on plasma denaturation profiles obtained by a non-conventional use of differential scanning fluorimetry. Using blood samples from 84 glioma patients and 63 healthy controls, we showed that their denaturation profiles can be automatically distinguished with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool requiring only a simple blood test.

Insights into graphene oxide interaction with human serum albumin in isolated state and in blood plasma

The interactions of graphene oxide (GO), a 2-dimensional nanomaterial with hydrophilic edges, hydrophobic basal plane and large flat surfaces, with biological macromolecules, are of key importance for the development of novel nanomaterials for biomedical applications. To gain more insight into the interaction of GO flakes with human serum albumin (HSA), we examined GO binding to HSA in its isolated state and in blood plasma. Calorimetric data reveal that GO strongly stabilizes free isolated HSA against a thermal challenge at low ionic strength, indicating strong binding interactions, confirmed by the drop in ζ-potential of the HSA/GO assemblies compared to bare GO flakes. However, calorimetry also revealed that the HSA-GO molecular interaction is hampered in blood plasma, the ionic strength being particularly important for the interactions. Molecular modelling calculations are in full concert with these experimental findings, indicating a considerably higher binding affinity for HSA to GO in its partially unfolded state, characteristic to low-ionic-strength environment, than for the native protein conformation, observed under physiological conditions. Therefore, for the first time we demonstrate an impeded interaction between HSA and GO nanoflakes in blood plasma, and suggest that the protein is protected from the plausible toxic effects of GO under native conditions.

The effect of prolonged intense physical exercise of special forces volunteers on their plasma protein denaturation profile examined by differential scanning calorimetry

The human blood plasma proteome profile has been an area of intensive investigation and differential scanning calorimetry (DSC) has come forward as a novel tool in analyzing plasma heat capacity changes to monitor various physiological responses in health and disease. This study used DSC to assess potential alterations in the plasma heat capacity profile of albumin and globulins during extremely demanding physical exercise. We monitored the changes in denaturation profiles of those plasma proteins for five consecutive days of an extraordinary exercise training schedule in 14 young male Special Forces volunteers, as well as after a 30-day recovery period. The major effect of the prolonged intense exercise was the continuous upward shift of the albumin peak by 2°-3 °C on the initial days of exercise, with a tendency to plateau circa the 5th day of exercise. In addition, some redistribution of the denaturational enthalpy was observed upon exercise, where the globulins peak increased relative to the albumin peak. Noteworthy, the alterations in the plasma proteome denaturational profiles were not persistent, as virtually full recovery of the initial status was observed after 30 days of recovery. Our findings indicate that 5 days of exhaustive physical exercise of highly trained individuals enhanced the thermal stability of plasma albumin shifting its denaturational transition to higher temperatures. We surmise that these effects may be a result of increased blood oxygenation during the prolonged intense exercise and, consequently, of albumin oxidation as part of the overall adaptation mechanisms of the body to extreme physical and/or oxidative stress.

Thermal Liquid Biopsy (TLB) Focused on Benign and Premalignant Pancreatic Cyst Diagnosis

Background: Current efforts in the identification of new biomarkers are directed towards an accurate differentiation between benign and premalignant cysts. Thermal Liquid Biopsy (TLB) has been previously applied to inflammatory and tumor diseases and could offer an interesting point of view in this type of pathology. Methods: In this work, twenty patients (12 males and 8 females, average ages 62) diagnosed with a pancreatic cyst benign (10) and premalignant (10) cyst lesions were recruited, and biological samples were obtained during the endoscopic ultrasonography procedure. Results: Proteomic content of cyst liquid samples was studied and several common proteins in the different groups were identified. TLB cyst liquid profiles reflected protein content. Also, TLB serum score was able to discriminate between healthy and cysts patients (71% sensitivity and 98% specificity) and between benign and premalignant cysts (75% sensitivity and 67% specificity). Conclusions: TLB analysis of plasmatic serum sample, a quick, simple and non-invasive technique that can be easily implemented, reports valuable information on the observed pancreatic lesion. These preliminary results set the basis for a larger study to refine TLB serum score and move closer to the clinical application of TLB providing useful information to the gastroenterologist during patient diagnosis.

Differences in cryostimulation and sauna effects on post-exercise changes in blood serum of athletes

OBJECTIVES

There is a growing body of evidence supporting the role of whole-body cryostimulation (WBC) and sauna - bathing as treatments for relaxation, mental well-being and several health problems. Despite their polar opposite temperatures, both of these treatments come with a dose of similar health benefits. This study is designed to compare effects of WBC and sauna application on the athletes' response to exercise.

DESIGN

The blood samples were collected from 10 professional cross-country skiers at four stages: before exercise, after exercise, at 1-h recovery and after 24 h of rest in sessions before and after 10 thermal treatments. Differential scanning calorimetry (DSC) was used to examine the process of serum denaturation. The parameters of endothermic transition were compared at various stages of each exercise session.

RESULTS

Post-exercise changes in DSC profiles of athlete's blood serum are similar in character but clearly stronger in the session held after sauna treatments and slightly weaker after WBC than those in the session not preceded by treatments. These changes can be, at least in part, explained by the exercise induced increase in the concentration of oxidized albumin. A return of serum denaturation transition to pre-exercise shape has been observed within a few hours of rest. It suggests relatively quick restoration of a fraction of non-oxidized albumin molecules during the recovery period.

CONCLUSIONS

An exercise performed by athletes after a series of sauna treatments leads to temporary greater modification of the blood serum proteome than the similar exercise during the session preceded by WBC treatments.

Exothermic transitions in the heat capacity profiles of human cerebrospinal fluid

In this work, we examined by DSC protein denaturation heat capacity profiles for two body fluids, cerebrospinal fluid (CSF) and blood plasma obtained from brain tumor (mainly glioblastoma) patients and healthy volunteers. We observed large distinctions between the heat capacity profiles of CSF and blood plasma, although their protein compositions are believed to have much in common. A prominent, previously unreported CSF feature was the existence of a pre-denaturation exothermic transition peaking at ~ 50-52 °C, recorded for both control and brain tumor CSF. This appears to be the first observation of a pre-denaturation exotherm in a human body fluid. In all studied samples, the exotherms deconvoluted with high precision into a sum of two Gaussian peaks. These exotherms are apparently specific, originating from brain tissue-soluble proteins in the CSF not present in blood plasma. Malignant brain tumors (glioblastoma multiforme, Grade IV, and low-grade glioma, Grade II) reduced twofold the enthalpy of the exotherms relative to the control. These results suggest that the amount and/or conformational state of the CSF proteins (e.g., intrinsic disorder) giving rise to pre-denaturation exothermic events substantially changed upon brain tumor progression. Concomitantly, the enthalpy of the CSF endothermic peaks was partially redistributed from a lower-temperature (main) transition to a higher-temperature transition. The presented data demonstrated that the heat capacity profiles of intrinsic CSF proteins constitute a sensitive biomarker of glioblastoma and other brain malignancies.

Multi-group diagnostic classification of high-dimensional data using differential scanning calorimetry plasma thermograms

The thermoanalytical technique differential scanning calorimetry (DSC) has been applied to characterize protein denaturation patterns (thermograms) in blood plasma samples and relate these to a subject’s health status. The analysis and classification of thermograms is challenging because of the high-dimensionality of the dataset. There are various methods for group classification using high-dimensional data sets; however, the impact of using high-dimensional data sets for cancer classification has been poorly understood. In the present article, we proposed a statistical approach for data reduction and a parametric method (PM) for modeling of high-dimensional data sets for two- and three- group classification using DSC and demographic data. We compared the PM to the non-parametric classification method K-nearest neighbors (KNN) and the semi-parametric classification method KNN with dynamic time warping (DTW). We evaluated the performance of these methods for multiple two-group classifications: (i) normal versus cervical cancer, (ii) normal versus lung cancer, (iii) normal versus cancer (cervical + lung), (iv) lung cancer versus cervical cancer as well as for three-group classification: normal versus cervical cancer versus lung cancer. In general, performance for two-group classification was high whereas three-group classification was more challenging, with all three methods predicting normal samples more accurately than cancer samples. Moreover, specificity of the PM method was mostly higher or the same as KNN and DTW-KNN with lower sensitivity. The performance of KNN and DTW-KNN decreased with the inclusion of demographic data, whereas similar performance was observed for the PM which could be explained by the fact that the PM uses fewer parameters as compared to KNN and DTW-KNN methods and is thus less susceptible to the risk of overfitting. More importantly the accuracy of the PM can be increased by using a greater number of quantile data points and by the inclusion of additional demographic and clinical data, providing a substantial advantage over KNN and DTW-KNN methods.

Plasmatic Signature of Disease by Differential Scanning Calorimetry (DSC)

Differential scanning calorimetry (DSC) has been used for several decades to characterize thermal stability of macromolecules such as proteins and DNA. It allows to determine the denaturation temperature and enthalpy of individual domains of proteins, thus giving new insights into their domain organization and ligand interaction. Over the past decade, it has been shown that this technique can also be used to study biofluids such as plasma or cerebrospinal fluid to obtain denaturation profiles. An increasing number of studies demonstrated that such profiles obtained from patients were significantly different from profiles obtained using biofluids of healthy individuals. This opens interesting perspectives for new diagnostics and monitoring tools for a large number of diseases. Nevertheless, the extensive studies of plasma samples from patients with different pathologies as well as the development of standardized methods of data analysis are necessary to reach the promising diagnostic potential of this methodology. Using plasma samples from healthy individuals and glioblastoma patients, we outline the steps necessary to obtain a plasmatic calorimetric profile with VP-DSC instrument and describe a cluster analysis of obtained data.

Thermal Liquid Biopsy (TLB): A Predictive Score Derived from Serum Thermograms as a Clinical Tool for Screening Lung Cancer Patients

Risk population screening programs are instrumental for advancing cancer management and reducing economic costs of therapeutic interventions and the burden of the disease, as well as increasing the survival rate and improving the quality of life for cancer patients. Lung cancer, with high incidence and mortality rates, is not excluded from this situation. The success of screening programs relies on many factors, with some of them being the appropriate definition of the risk population and the implementation of detection techniques with an optimal discrimination power and strong patient adherence. Liquid biopsy based on serum or plasma detection of circulating tumor cells or DNA/RNA is increasingly employed nowadays, but certain limitations constrain its wide application. In this work, we present a new implementation of thermal liquid biopsy (TLB) for lung cancer patients. TLB provides a prediction score based on the ability to detect plasma/serum proteome alterations through calorimetric thermograms that strongly correlates with the presence of lung cancer disease (91% accuracy rate, 90% sensitivity, 92% specificity, diagnostic odds ratio 104). TLB is a quick, minimally-invasive, low-risk technique that can be applied in clinical practice for evidencing lung cancer, and it can be used in screening and monitoring actions.

Thermally Induced Denaturing Energetics of Human Blood Plasma Albumin by Differential Scanning Calorimetry (DSC) as an Indicator for Breast Cancer Diagnosis in Female Patients

Cancerous invasion yields unusual metabolisms providing a significant amount of peptide albuminomes that modulate albumin stability via binding. The study aimed at the investigation of the thermal stability of human plasma albumin with breast cancer of various stages by means of differential scanning calorimetry (DSC). Blood plasma was drawn from 11 female breast cancer patients and 50 healthy volunteers of homogeneous demographics. Plasma samples and their albumin-enriched fractions were subjected to DSC scanning between 37 and 90°C at 5°C/min rate. For normal blood plasma, a characteristic signature of DSC tracing was observed. And, the deconvolution of DSC thermograms revealed the recognition of thermal transition of albumin. It was found that denaturing temperature of albumin increased with increasing breast cancer staging which implied the increase in albuminome/peptide abundance produced by cancerous invasion. The analysis of albumin denaturing energetics based on rational approximation of the simple Lumry-Eyring model demonstrated that thermal transition of free albumin and albuminome-bound form attained energetic levels expressed as apparent activation energy (E_app ± s.e.) of 132.68 ± 14.21 and 46.76 ± 8.42 Kcal/mol corresponded to the schemes dominated by irreversible alteration and by reversible unfolding, respectively. Thus, E_app value may indicate the degrees of cancerous invasion. It was proposed that E_app may be used as an indicator to diagnose and assess the prognosis of breast cancer.

Coformulation of Broadly Neutralizing Antibodies 3BNC117 and PGT121: Analytical Challenges During Preformulation Characterization and Storage Stability Studies

In this study, we investigated analytical challenges associated with the formulation of 2 anti-HIV broadly neutralizing antibodies (bnAbs), 3BNC117 and PGT121, both separately at 100 mg/mL and together at 50 mg/mL each. The bnAb formulations were characterized for relative solubility and conformational stability followed by accelerated and real-time stability studies. Although the bnAbs were stable during 4°C storage, incubation at 40°C differentiated their stability profiles. Specific concentration-dependent aggregation rates at 30°C and 40°C were measured by size exclusion chromatography for the individual bnAbs with the mixture showing intermediate behavior. Interestingly, although the relative ratio of the 2 bnAbs remained constant at 4°C, the ratio of 3BNC117 to PGT121 increased in the dimer that formed during storage at 40°C. A mass spectrometry-based multiattribute method, identified and quantified differences in modifications of the Fab regions for each bnAb within the mixture including clipping, oxidation, deamidation, and isomerization sites. Each bnAb showed slight differences in the levels and sites of lysine residue glycations. Together, these data demonstrate the ability to differentiate degradation products from individual antibodies within the bnAb mixture, and that degradation rates are influenced not only by the individual bnAb concentrations but also by the mixture concentration.

Thermal liquid biopsy for monitoring melanoma patients under surveillance during treatment: A pilot study

BACKGROUND

Differential Scanning Calorimetry (DSC) is a technique traditionally used to study thermally induced macromolecular transitions, and it has recently been proposed as a novel approach for diagnosis and monitoring of several diseases. We report a pilot study applying Thermal Liquid Biopsy (TLB, DSC thermograms of plasma samples) as a new clinical approach for diagnostic assessment of melanoma patients.

METHODS

Multiparametric analysis of DSC thermograms of patient plasma samples collected during treatment and surveillance (63 samples from 10 patients) were compared with clinical and diagnostic imaging assessment to determine the utility of thermograms for diagnostic assessment in melanoma. Nine of the ten patients were stage 2 or 3 melanoma subjects receiving adjuvant therapy after surgical resection of their melanomas. The other patient had unresectable stage 4 melanoma and was treated with immunotherapy. Two reference groups were used: (A) 36 healthy subjects and (B) 13 samples from 8 melanoma patients who had completed successful surgical management of their disease and were determined by continued clinical assessment to have no evidence of disease.

RESULTS

Plasma thermogram analysis applied to melanoma patients generally agrees with clinical evaluation determined by physical assessment or diagnostic imaging (~80% agreement). No false negatives were obtained from DSC thermograms. Importantly, this methodology was able to detect changes in disease status before it was identified clinically.

CONCLUSIONS

Thermal Liquid Biopsy could be used in combination with current clinical assessment for the earlier detection of melanoma recurrence and metastasis.

GENERAL SIGNIFICANCE

TLB offers advantages over current diagnostic techniques (PET/CT imaging), limited in frequency by radiation burden and expense, in providing a minimally-invasive, low-risk, low-cost clinical test for more frequent personalized patient monitoring to assess recurrence and facilitate clinical decision-making.

Differential scanning calorimetry of plasma in glioblastoma: toward a new prognostic / monitoring tool

Glioblastoma is the most frequent and aggressive primary brain tumor in adults. Recently, a growing number of studies have shown that denaturation profile of plasma samples obtained by differential scanning calorimetry (DSC) can represent a signature of a disease. In this study, we analyzed for the first time the DSC denaturation profiles of the plasma from patients with recurrent glioblastoma (n=17). Comparison to the one of healthy individuals (n=10) and to already described profiles in others cancer showed clear differences suggesting that this DSC profile may constitute a signature of glioblastoma. Parameters extracted from these profiles were used for cluster analysis which revealed the existence of glioblastoma profile subgroups which correlated with prognostic factors. Moreover, we showed that the presence of circulating bevacizumab and carmustine did not alter this calorimetric signature of the disease, indicating that an evolution of the profile could be followed without being masked by ongoing systemic treatment. Thus, our results constitute a very promising proof of principle that a specific calorimetric profile could be detected in the plasma of glioblastoma patients. Moreover, we believe that our findings point to a potential easy-to-use non-invasive monitoring tool for glioblastoma patients.

Calorimetric markers for monitoring of multiple myeloma and Waldenström's macroglobulinemia patients

The blood proteome has been studied extensively for identification of novel reliable disease biomarkers. In recent years, differential scanning calorimetry has emerged as a new tool for characterization of the thermodynamic properties of the major serum/plasma proteins and for the establishment of calorimetric markers for a variety of diseases. Here we applied calorimetry to monitor the effect of treatment of patients diagnosed with multiple myeloma and Waldenström's macroglobulinemia on the calorimetric profiles of patients' blood sera. The parameters derived from the calorimetric profiles were compared with the primary serum biomarkers, monoclonal immunoglobulin (M protein) concentration, and κ/λ free light chain ratio. For the secretory cases, the calorimetric parameters thermogram's shape similarity and weighted average center strongly depended on the M protein level but had lower sensitivity and specificity. By contrast, for non-secretory cases, the calorimetric parameters did not depend on the κ/λ free light chains ratio and exhibited significantly higher sensitivity and specificity than M protein levels. A combination of the immunological and calorimetric tests was found to greatly improve the sensitivity and specificity of the clinical status evaluation. The pronounced differences in blood sera thermograms before and during monitoring reflected the individual patients' response to treatment received and showed maintenance of heterogeneity during the disease course.

Blood Serum Calorimetry Indicates the Chemotherapeutic Efficacy in Lung Cancer Treatment

Chemotherapy is a primary treatment for the metastatic lung cancer patients. To select the most effective combination of drugs, we need an efficient way of assessing tumor response. Here, we showed that differential scanning calorimetry (DSC) analysis of blood serum proteins could reveal the patient response to the treatment. If chemotherapy is effective, serum proteins DSC curve of non-small cellular lung cancer (NSCLC) case is similar to the those of the healthy individuals. If treatment fails, notable changes occur in the DSC profile of NSCLC patient's blood serum. Our preliminary work illustrates how thermal analysis of changes in the heat capacity of blood serum proteins can provide an insight into patient response to chemotherapy - the essential information for any successive lung cancer treatment.

Characterization and classification of lupus patients based on plasma thermograms

Objective

Plasma thermograms (thermal stability profiles of blood plasma) are being utilized as a new diagnostic approach for clinical assessment. In this study, we investigated the ability of plasma thermograms to classify systemic lupus erythematosus (SLE) patients versus non SLE controls using a sample of 300 SLE and 300 control subjects from the Lupus Family Registry and Repository. Additionally, we evaluated the heterogeneity of thermograms along age, sex, ethnicity, concurrent health conditions and SLE diagnostic criteria.

Methods

Thermograms were visualized graphically for important differences between covariates and summarized using various measures. A modified linear discriminant analysis was used to segregate SLE versus control subjects on the basis of the thermograms. Classification accuracy was measured based on multiple training/test splits of the data and compared to classification based on SLE serological markers.

Results

Median sensitivity, specificity, and overall accuracy based on classification using plasma thermograms was 86%, 83%, and 84% compared to 78%, 95%, and 86% based on a combination of five antibody tests. Combining thermogram and serology information together improved sensitivity from 78% to 86% and overall accuracy from 86% to 89% relative to serology alone. Predictive accuracy of thermograms for distinguishing SLE and osteoarthritis / rheumatoid arthritis patients was comparable. Both gender and anemia significantly interacted with disease status for plasma thermograms (p<0.001), with greater separation between SLE and control thermograms for females relative to males and for patients with anemia relative to patients without anemia.

Conclusion

Plasma thermograms constitute an additional biomarker which may help improve diagnosis of SLE patients, particularly when coupled with standard diagnostic testing. Differences in thermograms according to patient sex, ethnicity, clinical and environmental factors are important considerations for application of thermograms in a clinical setting.

Application and interpretation of functional data analysis techniques to differential scanning calorimetry data from lupus patients

Background

DSC is used to determine thermally-induced conformational changes of biomolecules within a blood plasma sample. Recent research has indicated that DSC curves (or thermograms) may have different characteristics based on disease status and, thus, may be useful as a monitoring and diagnostic tool for some diseases. Since thermograms are curves measured over a range of temperature values, they are considered functional data. In this paper we apply functional data analysis techniques to analyze differential scanning calorimetry (DSC) data from individuals from the Lupus Family Registry and Repository (LFRR). The aim was to assess the effect of lupus disease status as well as additional covariates on the thermogram profiles, and use FD analysis methods to create models for classifying lupus vs. control patients on the basis of the thermogram curves.

Methods

Thermograms were collected for 300 lupus patients and 300 controls without lupus who were matched with diseased individuals based on sex, race, and age. First, functional regression with a functional response (DSC) and categorical predictor (disease status) was used to determine how thermogram curve structure varied according to disease status and other covariates including sex, race, and year of birth. Next, functional logistic regression with disease status as the response and functional principal component analysis (FPCA) scores as the predictors was used to model the effect of thermogram structure on disease status prediction. The prediction accuracy for patients with Osteoarthritis and Rheumatoid Arthritis but without Lupus was also calculated to determine the ability of the classifier to differentiate between Lupus and other diseases. Data were divided 1000 times into separate 2/3 training and 1/3 test data for evaluation of predictions. Finally, derivatives of thermogram curves were included in the models to determine whether they aided in prediction of disease status.

Results

Functional regression with thermogram as a functional response and disease status as predictor showed a clear separation in thermogram curve structure between cases and controls. The logistic regression model with FPCA scores as the predictors gave the most accurate results with a mean 79.22% correct classification rate with a mean sensitivity = 79.70%, and specificity = 81.48%. The model correctly classified OA and RA patients without Lupus as controls at a rate of 75.92% on average with a mean sensitivity = 79.70% and specificity = 77.6%. Regression models including FPCA scores for derivative curves did not perform as well, nor did regression models including covariates.

Conclusion

Changes in thermograms observed in the disease state likely reflect covalent modifications of plasma proteins or changes in large protein-protein interacting networks resulting in the stabilization of plasma proteins towards thermal denaturation. By relating functional principal components from thermograms to disease status, our Functional Principal Component Analysis model provides results that are more easily interpretable compared to prior studies. Further, the model could also potentially be coupled with other biomarkers to improve diagnostic classification for lupus.

Fibrinogen: a journey into biotechnology

Fibrinogen has been known since the mid-nineteenth century. Although initially its interest had been within the field of physiology over time its study has spread to new disciplines such as biochemistry, colloids and interfaces or biotechnology. First, we will describe the bulk properties of the molecule as well as its supramolecular assembly with different ligands by using different techniques and theoretical models. In the next step we will analyze the interfacial properties, an important topic because fibrinogen is considered to be a major inhibitor of lung surfactants' function at the lining layer of alveoli. The final step will be devoted to its main application in biotechnology. Thus, the adsorption of fibrinogen at solid/electrolyte interfaces and at carrier particles will be discussed. The reversibility of adsorption, fibrinogen molecule orientation, and maximum coverage will be thoroughly discussed. The stability of fibrinogen monolayers formed at these surfaces with respect to pH and ionic strength cyclic changes will also be presented. Based on the physicochemical data, adsorption kinetics and colloid particle deposition measurements, probable adsorption mechanisms of fibrinogen on solid/electrolyte interfaces will be defined.

Investigation of early and advanced stages in ovarian cancer using human plasma by differential scanning calorimetry and mass spectrometry

Ovarian cancer is recognized with high mortality due to asymptomatic nature of the disease and difficulties in diagnosing early stage of the cancer. The present study evaluates the use of differential scanning calorimetry (DSC) in differentiating the severity of ovarian cancer from healthy women. 47 diseased women were subdivided into four stages with respect to clinical relevance and severity. Stages I-II were regarded as early stages and stages III-IV were regarded as advanced stages. The two average transition temperatures (T m ) increased with disease severity from 64.84 and 70.32 °C (healthy) to 68.46 and 75.24 °C (stage IV), respectively. T m were increased depending on clinical groups. In addition, the change in heat capacity was also dependent on the disease severity. To further support and investigate the nature of the proposed interactions, matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis is employed. The results suggest the differences in peptide expression between early and advanced stage of ovarian cancer, affected abundant proteins in plasma. The combined DSC and MS approach was supportive in identifying a unique signature of ovarian cancer stages, and demonstrates the potential of DSC as a complementary diagnostic tool in the evaluation of early stage ovarian cancer.

Differential scanning calorimetry as a complementary diagnostic tool for the evaluation of biological samples

BACKGROUND

Differential scanning calorimetry (DSC) is a tool for measuring the thermal stability profiles of complex molecular interactions in biological fluids. DSC profiles (thermograms) of biofluids provide specific signatures which are being utilized as a new diagnostic approach for characterizing disease but the development of these approaches is still in its infancy.

METHODS

This article evaluates several approaches for the analysis of thermograms which could increase the utility of DSC for clinical application. Thermograms were analyzed using localized thermogram features and principal components (PCs). The performance of these methods was evaluated alongside six models for the classification of a data set comprised of 300 systemic lupus erythematosus (SLE) patients and 300 control subjects obtained from the Lupus Family Registry and Repository (LFRR).

RESULTS

Classification performance was substantially higher using the penalized algorithms relative to localized features/PCs alone. The models were grouped into two sets, the first having smoother solution vectors but lower classification accuracies than the second with seemingly noisier solution vectors.

CONCLUSIONS

Coupling thermogram technology with modern classification algorithms provides a powerful diagnostic approach for analysis of biological samples. The solution vectors from the models may reflect important information from the thermogram profiles for discriminating between clinical groups.

GENERAL SIGNIFICANCE

DSC thermograms show sensitivity to changes in the bulk plasma proteome that correlate with clinical status. To move this technology towards clinical application the development of new approaches is needed to extract discriminatory parameters from DSC profiles for the comparison and diagnostic classification of patients.

Protein Assembly in Serum and the Differences from Assembly in Buffer

This chapter illustrates how analytical ultracentrifugation methods, coupled with the fluorescence detection system, are an excellent approach to characterizing and comparing protein-binding interactions in dilute solution and concentrated, crowded solutions like serum. We show that in serum, the binding and assembly states for a pair of endogenous protein ligands and an antibody inhibitor are dramatically different than those observed in dilute, simple buffers. This type of analysis approach may be helpful in research efforts intent at discerning the underpinnings to a therapeutic's activity and pharmacokinetic properties in vivo.

Characterization of monoclonal gammopathy of undetermined significance by calorimetric analysis of blood serum proteome

Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant proliferative disorder that may progress to multiple myeloma, a malignant plasma cell neoplasia. We evaluated differential scanning calorimetry (DSC) as an experimental tool for differentiating serum samples of MGUS patients from healthy individuals. DSC thermograms can be used for monitoring changes in the serum proteome associated with MGUS. MGUS patients showed great variability in serum thermogram characteristics, which depended on the IgG, IgA or IgM isotypes and/or the κ or λ light chains. Thermogram feature parameters distinguished patients with MGUS from healthy people. Serum samples, named as non-MGUS, were also collected from patients with subjacent immunological pathologies who were discarded of having MGUS through serum immunofixation. They were used to verify the sensitivity of DSC for discriminating MGUS from related blood dyscrasias. Only some DSC thermogram feature parameters differentiated, to a lesser extent, between MGUS and non-MGUS individuals. We contemplate DSC as a tool for early diagnosis and monitoring of MGUS.

Deconvolution analysis for classifying gastric adenocarcinoma patients based on differential scanning calorimetry serum thermograms

Recently, differential scanning calorimetry (DSC) has been acknowledged as a novel tool for diagnosing and monitoring several diseases. This highly sensitive technique has been traditionally used to study thermally induced protein folding/unfolding transitions. In previous research papers, DSC profiles from blood samples of patients were analyzed and they exhibited marked differences in the thermal denaturation profile. Thus, we investigated the use of this novel technology in blood serum samples from 25 healthy subjects and 30 patients with gastric adenocarcinoma (GAC) at different stages of tumor development with a new multiparametric approach. The analysis of the calorimetric profiles of blood serum from GAC patients allowed us to discriminate three stages of cancer development (I to III) from those of healthy individuals. After a multiparametric analysis, a classification of blood serum DSC parameters from patients with GAC is proposed. Certain parameters exhibited significant differences (P < 0.05) and allowed the discrimination of healthy subjects/patients from patients at different tumor stages. The results of this work validate DSC as a novel technique for GAC patient classification and staging, and offer new graphical tools and value ranges for the acquired parameters in order to discriminate healthy from diseased subjects with increased disease burden.

Calorimetric markers of Bence Jones and nonsecretory multiple myeloma serum proteome

The present work provides a thermodynamic description of blood serum from patients diagnosed with Bence Jones myeloma (BJMM) and nonsecretory myeloma (NSMM) by means of differential scanning calorimetry (DSC), serum protein electrophoresis, and free light chain assay. Specific alterations in the thermodynamic behavior of both BJMM and NSMM proteome have been revealed. On the basis of the transition temperature of the main transition in the calorimetric profiles and the shape similarity criterion, we defined BJMM and NSMM sets/subsets of thermograms with very similar thermodynamic features. We show that some of the BJMM and NSMM subsets correlate with previously defined secretory myeloma subsets (Todinova et al. Anal. Chem. 2011, 83, 7992). The established analogies strongly suggest that common molecular markers contribute to the calorimetric profiles of the different, secretory and nonsecretory, myeloma types; our data show robust evidence that these are ligands stabilizing the major serum proteins. We demonstrate that the DSC approach might be highly beneficial, especially for NSMM patients, since the characteristic modifications in the DSC profiles might serve as calorimetric markers when no monoclonal proteins can be detected in the bloodstream and the diagnosis heavily relies on invasive methods.

Clinical application of plasma thermograms. Utility, practical approaches and considerations

Differential scanning calorimetry (DSC) studies of blood plasma are part of an emerging area of the clinical application of DSC to biofluid analysis. DSC analysis of plasma from healthy individuals and patients with various diseases has revealed changes in the thermal profiles of the major plasma proteins associated with the clinical status of the patient. The sensitivity of DSC to the concentration of proteins, their interactions with other proteins or ligands, or their covalent modification underlies the potential utility of DSC analysis. A growing body of literature has demonstrated the versatility and performance of clinical DSC analysis across a range of biofluids and in a number of disease settings. The principles, practice and challenges of DSC analysis of plasma are described in this article.

The role of caprylate ligand ion on the stabilization of human serum albumin

Sodium caprylate was added to a pharmaceutical-grade human serum albumin (HSA) to stabilize the product. In this study we have aimed to establish how caprylate ligand protects HSA from thermal degradation. The fatty acid stabilizer was first removed from commercial HSA by charcoal treatment. Cleaned HSA was made to 10% w/v in pH 7.4 buffered solutions and doped with sodium caprylate in serial concentrations up to 0.16 mmol/g-protein. These solutions as well as a commercial HSA, human serum, and enriched-albumin fraction were subjected to differential scanning calorimetry (DSC) within the temperature range of 37-90°C at a 5.0°C/min scanning rate. The globular size of the cleaned HSA solutions was measured by dynamic light scattering. The denaturing temperatures for albumin with sodium caprylate and a commercial one were significantly higher than for albumin only. It was found that the protein globules of cleaned HSA were not as stable as that of the native one due to aggregation, and the caprylate ion may reduce the aggregation by enlarging the globules' electrical double layer. A rational approximation of the Lumry-Eyring protein denaturation model was used to treat DSC denaturing endotherms. The system turned from irreversible dominant Scheme: N (k3K)→ P to reversible dominant Scheme:N (k1)→ P with the increase in caprylate concentration from null to ~0.08 mmol/g-protein. It was postulated that the caprylate ligand may decrease the rate of reversible unfolding as it binds to the IIIA domain which is prone to reversible unfolding/refolding and causes further difficulty for irreversible denaturation which, in turn, HSA can be stabilized.

Detection of cervical cancer biomarker patterns in blood plasma and urine by differential scanning calorimetry and mass spectrometry

Improved methods for the accurate identification of both the presence and severity of cervical intraepithelial neoplasia (CIN) and extent of spread of invasive carcinomas of the cervix (IC) are needed. Differential scanning calorimetry (DSC) has recently been shown to detect specific changes in the thermal behavior of blood plasma proteins in several diseases. This methodology is being explored to provide a complementary approach for screening of cervical disease. The present study evaluated the utility of DSC in differentiating between healthy controls, increasing severity of CIN and early and advanced IC. Significant discrimination was apparent relative to the extent of disease with no clear effect of demographic factors such as age, ethnicity, smoking status and parity. Of most clinical relevance, there was strong differentiation of CIN from healthy controls and IC, and amongst patients with IC between FIGO Stage I and advanced cancer. The observed disease-specific changes in DSC profiles (thermograms) were hypothesized to reflect differential expression of disease biomarkers that subsequently bound to and affected the thermal behavior of the most abundant plasma proteins. The effect of interacting biomarkers can be inferred from the modulation of thermograms but cannot be directly identified by DSC. To investigate the nature of the proposed interactions, mass spectrometry (MS) analyses were employed. Quantitative assessment of the low molecular weight protein fragments of plasma and urine samples revealed a small list of peptides whose abundance was correlated with the extent of cervical disease, with the most striking plasma peptidome data supporting the interactome theory of peptide portioning to abundant plasma proteins. The combined DSC and MS approach in this study was successful in identifying unique biomarker signatures for cervical cancer and demonstrated the utility of DSC plasma profiles as a complementary diagnostic tool to evaluate cervical cancer health.

Liver exhibits thermal variations according to the stage of fibrosis progression: A novel use of modulated-differential scanning calorimetry for research in hepatology

AIM

Liver fibrosis results in a disproportion of the hepatic composition and architecture, characterized by a progressive accumulation of fibrillar proteins at the liver parenchyma. Modulated-differential scanning calorimetry (mDSC) is an experimental methodology able to determine the specific thermal signature from any biological substance, based on the variation in heat flow and heat capacity. As these physicochemical properties are directly influenced by compositional and structural changes, we decided to study the thermal behavior of the liver during fibrosis using mDSC.

METHODS

Liver fibrosis was induced in rats by bile duct ligation or carbon tetrachloride administration. Degree of liver fibrosis was determined by histological examination using the Masson-trichrome stain, accompanied by hepatic expression of α-smooth muscle actin. The thermal analysis was performed in a modulated-differential scanning calorimeter using 20 mg of fresh liver mass.

RESULTS

The liver showed a characteristic thermal signature in control animals, which progressively differed among mild (F1), moderate (F2) and advanced (F3-F4) liver fibrosis. For heat flow, the hepatic thermal signature from F3-F4 rats exhibited significant differences when compared with F1, F2 and controls. In terms of heat capacity, liver specimens provided a specific thermal signature for each stage of disease, characterized by a transition temperature onset at 95°C for controls, whereas in F1, F2 and F3-F4 animals this temperature significantly decreased to 93°C, 84°C and 75°C, respectively.

CONCLUSION

Because the liver shows a differential thermal signature according to the degree of fibrosis, mDSC could be a novel tool in the study of liver fibrosis progression.

Calorimetric analysis of the plasma proteome: identification of type 1 diabetes patients with early renal function decline

BACKGROUND

Microalbuminuria (MA) has been questioned as a predictor of progressive renal dysfunction in patients with type 1 diabetes (T1D). Consequently, new clinical end points are needed that identify or predict patients that are at risk for early renal function decline (ERFD). The potential clinical utility of differential scanning calorimetry (DSC) analysis of blood plasma and other biofluids has recently been reported. This method provides an alternate physical basis with which to study disease-associated changes in the bulk plasma proteome.

METHODS

DSC analysis of blood plasma was applied to identify unique signatures of ERFD in subjects enrolled in the 1st Joslin Study of the Natural History of Microalbuminuria in Type 1 Diabetes, a prospective cohort study of T1D patients. Recent data suggests that differences in the plasma peptidome of these patients correlate with longitudinal measures of renal function. Differences in DSC profile (thermogram) features were evaluated between T1D MA individuals exhibiting ERFD (n=15) and matched control subjects (n=14).

RESULTS

The average control group thermogram resembled a previously defined healthy thermogram. Differences were evident between ERFD and control individuals. Heat capacity values of the main two transitions were found to be significant discriminators of patient status.

CONCLUSIONS

Results from this pilot study suggest the potential utility of DSC proteome analysis to prognostic indicators of renal disease in T1D.

GENERAL SIGNIFICANCE

DSC shows sensitivity to changes in the bulk plasma proteome that correlate with clinical status in T1D providing additional support for the utility of DSC profiling in clinical diagnostics.