To develop markers predictive of 5-FU response, we selected four colorectal adenocarcinoma cell lines representing extremes of sensitivity or resistance to 5-FU and chose a set of candidate genes including thymidylate synthase and genes that correlated highly with 5-FU response in a microarray study (12
). provides an overview of the strategy. For each of the 12 candidate genes, we examined active transcription sites in individual cells using FISH (). Our results showed differential transcription of several genes in 5-FU–sensitive or 5-FU–resistant colorectal tumor cell lines (). We examined various combinations of these genes to identify expression signatures that correlated with either resistance or sensitivity to 5-FU.
Figure 1 Defining markers of 5-FU response in human colorectal tumor cell lines using single-cell profiling of transcription site activation. A, flowchart of the strategy used to define a predictive model for response to 5-FU–based chemotherapy. Candidate (more ...)
To evaluate the predictive value of each combination of genes, we used logistic regression to build a model that predicted response of a cell line to 5-FU based on the active transcription site profile of those genes. Exhaustive combinations of the 12 potential markers for 5-FU response were used to build various models, each of which was evaluated for predictive accuracy using a training set of 4 cell lines with documented responses to 5-FU (12
Due to the small sample size of the training set, we used leave-one-out crossvalidation to assess the accuracy of the predictive models. The transcriptional profile and the outcome of k−1 of the k training samples was used to produce a linear decision boundary as outlined in the statistical methods section. The model was then used to predict the outcome of the kth training sample. The process was repeated k times, excluding a different training sample for validation each time.
If a set of genes was not a good predictor of response to 5-FU, then the decision boundary was sensitive to each of the k training samples that were excluded. The result was a large variation between calculated decision boundaries, leading to poor sensitivity and specificity of the predictive model (). Alternatively, shows a set of genes whose expression levels yielded a model with high predictive accuracy and robustness. The variance between k decision boundaries calculated for each of the k subsets was small. A gene expression signature consisting of four genes, TYMS, MRGX, BAK and ATP7B, correctly classified the training set of cell lines as either sensitive or resistant to 5-FU ().
Figure 2 Chemotherapy indicator plot. A, two genes that are poor predictive markers of response to 5-FU treatment. Filled squares, cell lines known to be sensitive. Filled cirlces, cell lines known to be resistant. The decision line is an average of 12 decision (more ...)
This model was then used to predict the response of independent test cell lines to 5-FU. Four additional colorectal adenocarcinoma cell lines, HCT15, SW620, RKO, and HCT116, were used to test the predictive model. Analysis of these test cell lines was blinded to eliminate bias in scoring of transcription sites. Cells were scored for number of transcription sites for MRGX, TYMS, BAK, and ATP7B. Our model, consisting of these four genes, correctly predicted the response of all four test cell lines to 5-FU (): SW620 (P = 0.023) was classified as 5-FU resistant, whereas RKO (P = 0.051) and HCT116 (P = 0.0005) were classified as 5-FU sensitive. The fourth cell line, HCT15, was classified as 5-FU resistant with somewhat lower significance (P = 0.099).
To investigate the potential of using transcription site profiling in tumors, we examined active transcription sites in tissue samples from 15 anonymous colon cancer patients on a TMA hybridized with probes for either TYMS and MRGX () or BAK and ATP7B (). Although colon tumor tissues were all from patients with grade 2 colon adenocarcinomas, single-cell transcription site profiles of individual tumors revealed a large variability in the expression of marker genes (). A majority of these tumor samples had high expression of the proapoptotic gene BAK, suggesting that these early-grade tumors would be sensitive to apoptosis induced by chemotherapeutic drugs such as 5-FU. Our predictive model classified 11 of the 15 samples as relatively sensitive (). Two of the 15 tumors were classified as more resistant, whereas the remaining two tumors showed mixed characteristics.
Figure 3 Detection of active transcription sites for 5-FU marker genes in paraffin-embedded human colon tumor TMA. A, merge of DAPI, Cy3, and Cy5 channels. Image shows DAPI-stained nuclei containing transcription sites (arrows) for MRGX and TYMS. Scale bar, 5 (more ...)
To provide proof of principle that these transcription site profiles are associated with outcomes to therapy, we tested colon tumor samples from a small number of patients with known outcomes. Tissue samples were obtained from surgically resected tumors of patients undergoing treatment for colon cancer. Three patients, designated 1F, 4F, and 6F, received 5-FU–based chemotherapy before and after surgery, whereas four patients, designated 1N, 4N, 5N, and 6N, received 5-FU–based therapy only after surgery. Tissues were hybridized with probes for TYMS, MRGX, BAK, and ATP7B (). Analysis was blinded to eliminate bias in the scoring of transcription sites. Tumors from patients 1F, 4F, and 6F had relatively higher expression of TYMS and MRGX and lower expression of ATP7B and BAK, classifying these patients as relatively less sensitive to 5-FU–based chemotherapy (). Among these three patients, 1F had tumor recurrence after previous surgery and 5-FU–based chemotherapy, although presently has no evidence of another reccurence, whereas patients 4F and 6F both later developed metastatic disease after 5-FU–based chemotherapy. In contrast, patients 1N, 4N, 5N, and 6N had tumors with higher expression of ATP7B and BAK than TYMS and MRGX, classifying them as more sensitive to 5-FU–based chemotherapy (). These four patients have not had a recurrence of their tumors or evidence of metastasis after surgery and 5-FU therapy, consistent with their classification as more sensitive to the drug treatment they received. On the basis of our predictive model, tumors from patients 1F, 4F, and 6F were classified as relatively resistant and tumors from patients 1N, 4N, 5N, and 6N as relatively sensitive ().
Figure 4 Prediction of response to 5-FU–based chemotherapy in colon cancer patients. A, active transcription sites for 5-FU marker genes in paraffin-embedded human colon tumor tissues. Image shows DAPI-stained nuclei containing transcription sites for (more ...)