Blood serum is a source of cancer biomarkers. Tumour development is accompanied by a metabolic malfunction may result in altered serum composition, including proteins that are upregulated or downregulated and low molecular weight metabolites undergoing changes in concentration.

Researchers analyse blood serum through multifactorial techniques profiling to transform the current scenario in cancer therapy by determining patient prognosis, monitoring tumour recurrence and therapeutic responses in real-time, identifying new therapeutic targets, elucidating drug resistance mechanisms, and improving their current understanding of tumour progression and metastatic disease.

One of the main advantages of using plasma samples is that only a minimally invasive assay such as a routine blood test analysis is required.

In this context, differential scanning calorimetry (DSC) has revealed its potential as a technique for a global analysis of serum samples.

Traditionally, DSC has been employed for determining the partial heat capacity of a macromolecule as a function of temperature, from which the thermodynamic parameters associated with the structural stability of the macromolecule by thermal denaturation can be estimated.

Due to its high sensitivity, the precise determination of the thermally-induced conformational transitions of biomolecules that are present in plasma can be readily performed using DSC.

Ten of the most abundant proteins in blood serum, including albumin, IgG, fibrinogen and haptoglobin, account for 90% weight-by-weight (w/w) of serum. Another twelve proteins represent the next 9% and 3,000 proteins account for the final 1%.

Interestingly, the normal serum thermogram can be reasonably reproduced with just the most abundant proteins. Therefore, serum thermograms do not provide direct information about the remaining, low-concentration serum proteins. However, the ability of those proteins, as well as disease-associated metabolites, to bind to and alter the unfolding temperatures of the most abundant proteins is responsible for the changes observed in the thermograms from disease states.

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