Evaluating the Radiation Sensitivity Index and 12-Chemokine Gene Expression Signature for Clinical Use in a CLIA Laboratory

Abstract

Abstract: The radiation sensitivity index (RSI) and 12-chemokine gene expression signature (12CK GES) are two gene expression signatures (GES) that were previously developed to predict tumor radiation sensitivity or identify the presence of tertiary lymphoid structures in tumors, respectively. To advance the use of these GESs into clinical trial evaluation, their assays must be assessed within the context of the Clinical Laboratory Improvement Amendments (CLIA) process. Using HG-U133Plus2.0 arrays, we first established CLIA laboratory proficiency. Then the accuracy (limit of detection and macrodissection impact), precision (variability by time and operator), sample type (surgery vs. biopsy), and concordance with a reference laboratory were evaluated. RSI and 12CK GES were reproducible (RSI: 0.01 mean difference, 12CK GES: 0.17 mean difference) and precise with respect to time and operator. Taken together, the reproducibility analysis of the scores indicated a median RSI difference of 0.06 (6.47% of range) across samples and a median 12CK GES difference of 0.92 (12.29% of range). Experiments indicated that the lower limit of input RNA is 5 ng. Reproducibility with a second CLIA laboratory demonstrated reliability with the median RSI score difference of 0.065 (6% of full range) and 12CK GES difference of 0.93 (12% of observed range). Overall, under CLIA, RSI and 12CK GES were demonstrated by the Moffitt Cancer Center Advanced Diagnostic Laboratory to be reproducible GESs for clinical usage.

Significance: The RSI and 12CK GES are two GESs that predict tumor radiation sensitivity or the presence of tertiary lymphoid structures in tumors, respectively. These GESs were assessed within the CLIA process for future clinical use. We established proficiency, reproducibility, and reliability characteristics for both signatures in a controlled setting, indicating these GESs are suitable for validation within future clinical trials.

Figure 1

Proficiency and repeatability of the CLIA laboratory in generating 12CK GES and RSI. A, Proficiency of the CLIA laboratory compared with an established research-grade molecular genomics shared resource facility. Four samples were previously processed by the MCC Molecular Genomics Core (MGC) and available for CLIA laboratory processing. GESs were derived from both experimental conditions. The experiment was performed to determine that the CLIA laboratory was proficient in generating the expression data for the HG-U133Plus platform. Left, 12CK GES scores in MGC vs. CLIA laboratory (r = 0.991) indicating high correlation, although signature calibration was needed. Right, RSI signature scores in MGC vs. CLIA laboratory indicating compressed RSI signal from the CLIA experiments. B, Repeatability of GES from quadruplicate samples in the CLIA laboratory. Four samples were processed in quadruplicate and arrayed in the CLIA laboratory from the same operator. GES scores were derived from each experiment. Left, 12CK GES scores had a low variability in each of the four samples. Right, RSI was identical in two samples and had low level of variability in two samples.

Figure 2

Replicability and precision analysis through measuring operator-to-operator and repeated run experiments. A, Operator variability: Three samples were run in duplicate by two different operators to assess both the variability in operator handling and repeatability from the same operator. The 12CK GES showed low variability across operator, whereas a larger difference in RSI score was obtained between operators. B, Repeated run over time: Four samples were repeated 1 week apart and assessed. The variability in the 12CK GES was low for all samples. RSI showed variability (less than 0.1) in two of the four samples.

Figure 3

A, Impact of the amount of input RNA on GES scores. Three samples were profiled using different amounts of input RNA (100, 25, 10, 5, and 2.5 ng). Lower 12CK GES scores were observed at 2.5 ng, suggesting a lower limit on input RNA. RSI demonstrated more variability overall but did not seem to have a systematic difference at 2.5 ng. B, Impact of macrodissection on signature scores. Three samples were profiled across three different sample conditions: T, N and non-macrodissected tissue (PM). As expected, normal tissue can result in large changes to the signature score, which can be seen in PM as well. For instance, the 12CK GES score for normal tissue from sample 1 is much higher; however, there is elevated signal in the PM sample as well. By contrast, the differences in sample 3 (N, T, and PM) are small.

Figure 4

Impact of surgery vs. biopsy sample on signature scores. A, Breast cancer specimens from tissue resection (surgery) and punch biopsy (biopsy) were compared. B, Head and neck cancer specimens from tissue resection (surgery) and punch biopsy (biopsy) were compared.

Figure 5

Concordance of signature scores across MCC CLIA laboratory and external vendor. Thirty samples were profiled in the MCC CLIA laboratory and external vendor. After excluding low-quality samples, the linearity of the 12CK GES (left) and RSI (right) scores for 14 samples across sites was assessed. COV, CLIA Outside Validation.