Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil‐based adjuvant chemotherapy benefit

Abstract

The current study suggests that the identification of predictive signatures of fluorouracil (5-FU) response for stage II and III colorectal cancer (CRC) could be confounded by chemotherapy-irrelevant low relapse risk. Using the samples of patients with stage II and III CRC who were treated with curative surgery only, we identified a signature with which to predict chemotherapy-irrelevant relapse risk for patients after curative surgery. By applying this signature to the samples of patients with stage II and III CRC who were treated with 5-FU-based adjuvant chemotherapy (ACT) after surgery, we predicted the relapse risk if treated with surgery only. From high-risk samples, we further identified another signature with which to predict therapeutic benefit from 5-FU-based ACT. On the basis of the relative expression orderings of gene pairs, a postsurgery relapse risk signature that consisted of 44 gene pairs was developed and verified in 3 independent data sets. A 5-FU therapeutic benefit signature that consisted of 4 gene pairs was then developed to predict the response of 5-FU-based ACT for those patients with high relapse risk after curative surgery. The signature was verified in 4 independent datasets. For patients with stage II and III CRC, the coupled signatures can first identify patients with high relapse risk after curative surgery, then predict therapeutic benefit from 5-FU-based ACT.-Song, K., Guo, Y., Wang, X., Cai, H., Zheng, W., Li, N., Song, X., Ao, L., Guo, Z., Zhao, W. Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

A Qualitative Transcriptional Signature for the Histological Reclassification of Lung Squamous Cell carcinomas and Adenocarcinomas

“…Fortunately, the within-sample relative expression orderings (REOs) of genes, which are the qualitative transcriptional characteristics of samples, are robust against to experimental batch effects and disease signatures based on REOs can be directly applied to samples at the individualized level [21][22][23][24][25][26]. Besides, we have reported that the within-sample REOs of genes are highly robust against to partial RNA degradation during specimen storage and preparation [ 18], varied proportions of the tumor cells in tumor tissues [ 19], and low-input RNA specimens [ 20].…”

A Qualitative Transcriptional Signature for Predicting CpG Island Methylator Phenotype Status of the Right-Sided Colon Cancer

“…Our laboratory proposes the concept of "a sequence for all, " which is composed by a series of qualitative transcriptional signatures for the prognostic and predictive biomarkers of CRC, including identifying micro-metastasis after surgery, 5-FU-based ACT benefit of high relapse risk patients, MSI status for CRC patients and so on (Zhao et al, 2016;Song et al, 2019). The qualitative transcriptional signature for predicting CIMP status in this study could combine with the other panels to predict the prognosis and guide the optimal therapy for CRC patients in clinical application.…”

“…In addition, the quantitative signatures would also be greatly affected by varied proportions of tumor epithelial cell in tumor tissues sampled from different tumor locations of the same patient (Cheng et al, 2017), partial RNA degradation during specimen storage and preparation (Chen et al, 2017), and amplification bias for minimum specimens even with about 15-25 cancer cells (Liu et al, 2017), which are common factors that can lead to failures in clinical applications. In contrast, the qualitative signatures based on relative expression orderings (REOs) of gene pairs within a sample are robust against the batch effects, different tumor locations, partial RNA degradation, and amplification bias (Zhao et al, 2016;Song et al, 2019), which could be directly applied to the sample at the individual level in clinical applications (Qi et al, 2016;Chen et al, 2017;Cheng et al, 2017;Liu et al, 2017;.…”

A Qualitative Transcriptional Signature for Predicting Recurrence Risk of Stage I–III Bladder Cancer Patients After Surgical Resection

“…For the establishment of predictive signatures for stage I-III bladder cancer patients who would be treated with curative surgery, we need to firstly identify the patients with adjuvant therapy-irrelevant low recurrence risk after surgery and exclude them from the analysis for predictive signatures because they would confound the identification of predictive signatures of response to a specific adjuvant therapy (34, 36). Therefore, the identification of prognostic signature for stage I-III bladder cancer patients treated with curative surgery only should be a basis for the establishment of predictive signatures of response to a specific adjuvant therapy.…”