This chapter deals with circulating biomarkers; however, it may be helpful to briefly examine some aspects related to the measurement of biomarkers in the tumor tissue, in order to identify the advantages and limits that the two matrices present and to better understand why the determination of bio markers in tissues or in blood can answer different clinical questions.
Tissue biomarkers are receiving prevalent interest because of the need to identify molecular targets for new anticancer drugs. The determination of biomarkers in tissues has several points of strength. First, the biomarker is measured in the target tissue. Thus, no biomarker dilution occurs (as it does in the blood), and possible nonspecific or background signals should be mainly related to analytical aspects and eventually constrained. In the case of tissue biomarkers, diagnostic sensitivity and specificity are both associated with analytical specificity and sensitivity; in other words, the ability to correctly identify the molecule of interest is mainly dependent on the characteristics of the method of determination. The problem of tissue heterogeneity can also be addressed by several approaches, such as, for example, by selecting areas or cell types of interest by laser-assisted microdissection. Interpretation of biomarker expression at the tissue level thus appears relatively straightforward.
However, the determination of biomarkers in a tissue has some significant limitations associated with biological, conceptual, and technical aspects, which must be considered in both clinical application and research design.
The biological aspects concern: (1) the intrinsic complexity of the molecular mechanisms; (2) the complex interaction of tumor cells with the microenvironment; and (3) the redundancy of the regulatory mechanisms of the tumor cell. These variables are associated with the inherent biological complexity of development and progression of cancer and explain the difficulties in identifying appropriate biomarkers as drug targets for some signaling pathways. However, it can reason ably be expected that the increase of knowledge of cancer cell biology and the progressive development of technologies will lead to an increasingly wide variety of measurable biomarkers as well as to a progressive improvement of diagnostic sensitivity and specificity of the available methods.
The conceptual limitations of the determination of a bio marker in the tissue matrix are twofold: (1) the representativeness of the sample and (2) the timing of the sampling in relation to the possible variability of biomarker expression over time. Regarding representativeness, biomarker determination is performed with a minimal amount of tissue as only a few milligrams of the tumor tissue are usually examined by immunohistochemistry under routine conditions. Thus, it is difficult to consider the immunohistochemical determination of a biomarker as a truly quantitative measure in terms of representativeness of the examined tissue specimen. This issue might be of poor relevance in homogeneous tumors, but it should be considered in the case of intrinsically heterogeneous malignancies. The second conceptual aspect concerns the one-shot feature of the measure, which shows the expression of the biomarker in a single site and at a single time point. Therefore, clinical decisions during the disease course are based on the presence/absence of the biomarker measured in a sample examined even years earlier, rather than on the current phenotype of the malignancy. This entails a risk of error in the characterization of the disease and, consequently, in therapeutic decisions. For example, HER2 expression may differ in metastases and in primary breast cancer in approximately 25% of cases; nonetheless, the therapy of patients with metastatic breast cancer is based on HER2 determination obtained in the primary tumor; a com parable degree of variability between the primary tumor and metastases has been reported for estrogen receptors.
Finally, a technical issue must be considered. Biomarkers are measured in tissues mainly by molecular biology techniques or immunohistochemistry. The latter is extensively used for routine biomarker measurements for clinical decision- making. Immunohistochemical techniques are typically qualitative, and the assumption that biomarker determination (e.g., estrogen receptors) is quantitative stems from the fact that the result is often expressed as a quantitative score or a percentage. However, it has been shown that the routine immunohistochemical method performed on fixed tissue samples does not lead to accurate quantitative results, even when performed in highly qualified laboratories.
The measurement of biomarkers in a tumor tissue is crucial for prognostic assessment and the prediction of response to anticancer agents, but it is inherently unsuitable for risk assessment, diagnosis, early recognition of recurrence, and therapy monitoring. In these situations, biomarkers can only be measured in blood. Table 1 summarizes the scenarios in which biomarkers can provide clinical information if measured in a tumor tissue or in blood.
Table1. Indications for biomarker use in different clinical scenarios according to the biological material: comparison between the tumor tissue and peripheral blood
Biomarkers in the blood can be determined at all stages of the disease, can be easily repeated over time, and their measurement is typically quantitative and expressed on a continuous scale. The categorization into positive and negative results based on a threshold value is a conventional dichotomization operation. However, different from tissue biomarkers, they are measured in a biological fluid distant from the malignancy, and, therefore, they are a surrogate measure of the actual amount of biomarkers produced and released by the tumor tissue. In fact, the amount of biomarker in the blood results from several variables in addition to the pro duction and release by the tumor tissue. Such variables include: (1) the possible production of the biomarker by nor mal tissues; (2) the possible presence in the blood of sub stances that cross-react with the measurement system; (3) the dilution in blood volume; and (4) metabolism and clearance. All of these factors may contribute to the blood con centration of a biomarker in a variable and unpredictable manner, both between different patients and in the same patient at different time points. Since the biomarker level in the blood results from different factors that add up algebraically (some factors cause an increase, others a decrease), it is necessary to use a threshold value to classify the biomarker result as positive or negative. The threshold value is usually determined from the distribution of the biomarker in a control group of healthy subjects or patients with non- oncological diseases. The classification of the biomarker results with reference to a positive/negative threshold value in subjects with the neoplasm of interest and in control subjects allows to classify patients and controls into four groups: (1) true positives (subjects with the disease and positive biomarker); (2) false negatives (subjects with the disease and negative bio marker); (3) true negatives (subjects without the disease and negative biomarker); and (4) false positives (subjects without the disease and positive biomarker).
The frequencies of patients and controls falling into the four groups enable the calculation of the diagnostic performance of the biomarker, such as sensitivity, specificity, predictive value, and likelihood ratio, as summarized in Table 2.
Table2. Measures of diagnostic accuracy
The non-specificity of a malignancy and the relatively low diagnostic sensitivity represent the commonly recognized limitations of the vast majority of, if not all, circulating biomarkers available for clinical use.
Poor specificity is an intrinsic problem of known bio markers. The so-called “tumor markers” are biochemical substances generally produced by several organs or cell types. They are therefore not specific to a given tumor but to the tissue or organ in which the tumor develops. The amount of biomarker produced and/or released by the tissue cells is low or very low in a physiological status but may increase under pathological conditions. These certainly include the development of a malignancy but also encompass several other conditions, such as, for example, the increase of the size of the organ (hyperplasia), inflammatory events, infections, autoimmune diseases, traumas, surgery, and administration of several drugs. In addition, the impairment of liver or kidney function can indirectly cause a spurious increase in circulating levels of some biomarkers by reducing their metabolism or clearance.
The poor diagnostic sensitivity is due to two major com ponents: the frequently low concentration of the biomarker in the blood and the analytical sensitivity of the method of measurement. The low amount of biomarker present in the blood in patients bearing small tumors is an objective issue, which impairs the possible use of the biomarker in early diagnosis, and limits its value for the early detection of the relapse during the follow-up. When the amount of tumor tissue is still minimal, the circulating concentration of the biomarker may remain within the normal range. The analysis of biomarker increments over time seems a promising approach to improve the diagnostic efficacy for early cancer. The progressive development of the malignancy may lead to a gradual increase of the biomarker concentration, even when it is within the normal range. The variation of biomarker levels between serial samples has been investigated in several clinical scenarios, such as early detection of ovarian and prostate cancers or early recognition of relapse in different types of malignancies, including breast, ovarian, and colon cancers. The criteria to standardize the interpretation of serial sample- based biomarker measurements have been proposed to facilitate the conduct of clinical trials, but the available results are in general still inconclusive. This is due at least in part to the relatively low analytical sensitivity of many assay methods. Indeed, most commercially available methods for measuring “tumor markers” are designed to offer linearity of dose–response interpolation over a broad concentration range, ensuring reliable results in a wide variety of clinical situations. This choice, aimed at facilitating the routine use of biomarker determination in clinical laboratories, entails the assumption that the quantitative level of the biomarker below the threshold value – classified as negative – is clinically uninformative. The assay design often implies that analytical precision is optimal for biomarker concentrations close to, or above, the threshold value, with analytical variability tending to worsen as the biomarker concentration decreases. To be clinically meaningful, differences between serial samples must be more significant than the analytical and biological variability of the biomarker. The poor reproducibility and comparability between the results reported in different studies on biomarker variations over time may be due, at least in part, to unsatisfactory assay precision at low biomarker concentrations, which negatively affects both analytical sensitivity and the calculation of biological variability. The availability of differently designed assay methods, targeted toward low biomarker concentrations and therefore characterized by higher analytical sensitivity and high precision in the low value range, would allow to better explore the clinical use of decision criteria based on serial sample variations.
In conclusion, determining biomarkers in the tumor tis sue and in blood is not an alternative but a complementary approach, presenting different advantages and limits. In both matrices, significant margins for improvement are recognizable, related to the development of knowledge, innovation of the study design, and improvement of technological aspects. Research policies in the field of bio markers should consider the value of diversities between tissue and blood biomarkers, thus avoiding unnecessary redundancies and overlaps and emphasizing the advantage of complementarities.
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