2.1.

Instrumentation and Data Analysis

The home assembled HPLC-LIF system consists of the following components. The HPLC unit consists of an HP 1100 gradient HPLC system with G1322A degasser, G1311A pump, and a manual injector (model number 7725, Rheodyne, Idex Health and Science, Oak Harbor, Washington) coupled to a Vydac 219TP52 biphenyl reversed phase narrow bore column (diphenyl, 2.1 × 250 mm, 5 μm, 300 Å). The effluent from the column was sent into a capillary flow cell made of a quartz capillary (75 μm i.d. 300 μm O.D. Hewlett Packard, G1600–64311). The 257-nm laser emission from a frequency-doubled Ar⁺ laser (Innova 90C FreD, Coherent, Santa Clara, California) with 15-mW power was used to excite the sample. Fluorescence at 340 nm was detected by a photomultiplier tube (PMT operated at –850 V), coupled through a preamplifier to a lock-in amplifier. The fluorescence was chopped with an EG&G model 651 (Signal Recovery, Oak Ridge, Tennessee) chopper at the entrance slit at 20 Hz for lock-in detection.^{14, 24}

Blood was collected from healthy, malignant and premalignant subjects at Manipal College of Dental Sciences (MCODS), Manipal University, India. Soon after its collection, the sample was then subjected to centrifugation at 5000 rpm for 10 min, following which the supernatant was collected and centrifuged again for 10 min at 5000 rpm. Filtered supernatant, if not immediately used for analysis, were stored at –80°C in the deep freezer. The supernatant of serum was diluted 1:1000 times with HPLC grade water (Merck, Whitehouse Station, New Jersey) and injected into HPLC for the protein profile. The conditions for the liquid chromatography run were optimized to get a suitable chromatogram that successfully separates out the proteins present in the sample. We used water with 0.1% and acetonitrile with 0.1% TFA (HPLC grade) for the gradient runs. Each time, a blank was run before the gradient to confirm the stability and to ensure that no residual contamination was present in the column. 20 μl of sample was injected into the narrow bore biphenyl column and then eluted with the water-acetonitrile gradient. The gradient started with 70% water +30% acetonitrile and changed to 40% water +60% acetonitrile in 60 min. Fluorescence intensity verses the time of elution of proteins gives rise to a protein profile.

The HPLC technique coupled with an ultrasensitive laser-induced fluorescence (LIF) detection system assembled and standardized in our laboratory is highly efficient and capable of detecting trace amounts of proteins (of the order of femtomoles) in microliter volumes of sample. The system is also highly reproducible and can be operated for several months (even years) without any noticeable change in the performance, as we have verified from protein profiles of normal serum samples run over periods of 1 to 2 years. Typical protein profiles of normal, premalignant, and malignant serum samples are shown in Fig. 1. We have shown that intensities and retention times of the component proteins in normal serum are highly reproducible.²³ Even small changes observed in the protein profiles from normal to other types can thus be considered as significant for diagnostic applications. To illustrate the importance of this point, in Fig. 2 we show sections of the protein profile expanded 50 times. It is clear that the serum protein profile is very complex, with about eight to ten proteins present in large concentrations (albumin, globulins, transferrin, IgG, IgA, etc.), while many other proteins are present only in very small quantities. The concentrations of the proteins present in small amounts change noticeably from normal to premalignant and malignant conditions. Also several new peaks are observed on induction of malignancy. For example, while peaks at 360, 445, and 1360 (transferrin) become very weak or disappear, new peaks come at 555, 585, 850, 1250, etc., shown in Fig. 2. This is expected, since induction of malignancy is accompanied by expression of several new proteins by the activation of the oncogenes and loss of others by inactivation of tumor suppressor genes.²⁸

Fig. 1

(a) Typical baseline corrected and normalized (with respect the marked peak) serum protein profiles of normal, premalignant, and malignant samples. (b) Protein profiles for the region 1650 to 3000 s.

Fig. 2

(a) Typical protein profiles of normal, premalignant, and malignant serum samples with expanded scale (50 times), and (b) expanded region 0 to 1400 s.

For the validation of the HPLC-LIF protein profiling method for diagnostic applications, the principal component analysis (PCA) was used for the discrimination of protein profiles. Details of our method of PCA have been given earlier.²³ Sample details are given in Table 1. Normal and premalignant samples were clinically confirmed as “true” normal and premalignant, respectively. Malignant samples were diagnosed as “true” malignant by histopathology. In our method, standard sets of a given class, say normal, are formed by random selection from clinically/pathologically certified samples of that class. All of the normal, premalignant, and malignant samples are tested against a standard set (say, normal samples) for match/no-match criterion.¹⁵ In this test, PCA of the standard set is carried out first to decide the required factors that will express the protein profiles of the standard set with the desired accuracy. With this set of factors, the protein profile of the sample to be tested is then added to the standard set, and the scores of factors from PCA are derived for the test sample. The scores are used to simulate the observed protein profiles of the test sample. The scores, squared residuals, i.e., observed protein profile – simulated protein profile)² and Mahalanobis distance (M-distance) are used for match/no-match of test samples with respect to the same parameters for the members of the standard set. The M-distance (D ²) for any sample is defined by the equation:

Table 1

Sample information.

Here, S is the vector of scores of factors and squared residual for a standard/sample, and N is the number of protein profiles in the standard set. It can be seen that the M-distance is expressed in units of standard deviation.¹⁵ Any sample that has an M-distance of two or more can be considered to be out of the standard group, with only a very small probability (<0.1%) of belonging to that group. Results from these match/no-match tests are used to estimate the sensitivity and specificity pairs, receiver operating characteristic (ROC) analysis, and Youden's index.

2.2.

Diagnostic Evaluation

To reduce the arbitrariness and subjective nature of diagnostic decision-making statistical parameters like specificity, sensitivity, positive predictive value, and negative predictive value can be used for performance evaluation. Before understanding these measures, one should have a clear idea about the terms true positive (TP), false negative (FN), true negative (TN), and false positive (FP), since, they are required for calculation of specificity and sensitivity.³⁰ Generally, positive refers to the disease state and negative refers to the nondisease state. A subject is said to be true positive (TP) if a disease subject is diagnosed correctly, otherwise it will be called false negative (FN). Similarly, if a nondisease subject is diagnosed correctly, then it is considered as true negative (TN), otherwise as false positive (FP). In the present studies, decision making involves not disease states, but premalignant conditions. Hence “true positive” here means “true positive decision,” meaning premalignant. Similarly “true negative” means “not premalignant.” In the latter situation, the subject can be normal or also malignant. It is shown that the present method can discriminate between these two situations as well (see Table 2). Sensitivity and specificity, as applied to the premalignant condition, is:

Table 2

Decision matrix.

3.1.

Data Analysis

Intercomparison of protein profiles recorded over several months requires a rigorous data analysis protocol. For this, all protein profiles were preprocessed as follows. Since the background fluorescence varied across the 60-min gradient run, possibly from the varying TFA-acetonitrile gradient, a background correction was carried out using a polynomial fit to the background. Small day-to-day changes in experimental conditions lead to minor shifts in peak positions from run to run. These were corrected by a standard of all the protein profiles along the time scale, using mean values of protein peaks common to all samples. All the protein profiles were then normalized with respect to the serum peak at 1666 s, which remained more or less unchanged in intensity and retention time in all runs.

A highly objective approach was used for data analysis. We used the principal component analysis (PCA) full region of the protein profiles to cover all the observed peaks, and the match/no-match tests were performed by comparing the test samples with standard sets (say normal, malignant, and premalignant).²³ In practice, not only the test sample but each member of the standard set also is tested against the standard set by rotating them out one at a time and matching them against the rest of the set.

As mentioned before, PCA was done with the whole protein profiles. In this case, the protein profiles in the region 400 to 2800 s was used, as there was not much information in the regions below 400 s and above 2800 s. The trial runs showed that about five to six factors contribute to more than 95% of the variations of any sample in a class from the mean of that class. This indicates that about the first five factors are sufficient to fully represent that class. We used 15 samples for a normal standard set and for making premalignant and malignant standard sets; the number of samples used are 10 and 12 samples, respectively. For all three standard sets, five factors have been used. Plots of squared residuals against M-distance for normal standard, malignant standard, and premalignant standard sets are shown in Figs. 3, 3, 3. The results are shown in Tables 3, 4, 5. It is seen that the PCA of complete protein profiles gives better classification for normal compared to premalignant and malignant groups, and better sensitivity and specificity.

Fig. 3

M-distance versus squared residual plot for the region 400 to 2800 s tested for (a) normal, (b) malignant, and (c) premalignant standard sets.

Table 3

Match/no-match test results for the region 400 to 2800 s when tested with normal standard set.

Table 4

Match/no-match test results for the region 400 to 2800 s when tested with a malignant standard set.

Table 5

Match/no-match test results for the region 400 to 2800 s when tested with a premalignant standard set.

In Table 3, it can be seen that with a normal standard set, the normal validation test samples (as well as the members of the standard set) lie close to the origin having small values of M-distance and spectral residual, while all other test samples (premalignant and malignant) show large values, indicating that they do not belong to the normal class. Except for some suspicious cases, almost similar results are obtained when all the test samples are subjected to the match/no-match test with the premalignant standard set.

Similarly, from Tables 4, 5, Figs. 3 and 3, one can see that for malignant and premalignant standard sets, the samples of respective class lie very close to the origin, whereas samples from other classes are scattered away. This has been done for the cross validation of respective classes.

3.2.

Diagnostic Accuracy

Using the results for a full protein profile, ROC curves, Youden's indices, and area under the ROC curves were obtained for all the serum samples. The ROC curves were plotted using specificity and sensitivity values corresponding to selected cutoff thresholds for M-distance. ROC and Youden's index curve for normal, malignant, and premalignant standard sets are shown in Figs. 4 and 4. ROC area under the curve for normal, malignant, and premalignant standard sets were found to be 0.907, 0.829, and 0.787, respectively. As mentioned earlier, Youden's index plays an important role in deciding threshold, since it gives an idea about combined measures (i.e., specificity and sensitivity). A Youden's index plot in Fig. 4 shows the plot of Youden's index value for each threshold and cutoff (threshold). The figures give a clear idea about the optimum threshold that has to be used for the screening. In this case, the ideal M-distance threshold observed is 2 for all normal, malignant, and premalignant standard sets. The nonlinear fit to Youden's index plots were found to be significant with regression value screening tests at 0.984, 0.948, and 0.973 for normal, malignant, and premalignant tests, respectively. The specificities and sensitivities at an ideal threshold (M-distance = 2) for normal, malignant, and premalignant standard sets are found to be 100, 69.5, and 61.5%, and 86.5, 87.5, and 87.5%, respectively.

Fig. 4

(a) Receiver operating characteristic (ROC) curve, (b) Youden's index plots for normal, premalignant, and malignant standard sets.

It is to be noted that the premalignant set included leukoplakia, OSMF, and Lichenplanus samples. The serum protein profiling method can classify normal, all premalignant, and malignant conditions separately. This is highly advantageous in deciding whether a subject with a premalignant condition is going over to malignancy, by periodic screening, without the need for repeated biopsies. Moreover, biopsy and histopathology examine heterogeneous sample (tissue) and can give results that do not represent the true condition.¹² Serum samples, on the other hand, are homogeneous and will reflect the true state of the disease condition. Serum protein profiles are thus highly suitable for monitoring premalignant conditions to decide whether they are crossing over to malignancy. Decision making involves only a simple blood test, which can be done in any clinical chemistry laboratory by a trained technician. Efforts are to collect unknown peaks to find out their identity.