Gene expression signature and response to the use of leucovorin, fluorouracil and oxaliplatin in colorectal cancer patients

A flexible approach for predictive biomarker discovery

An endeavor central to precision medicine is predictive biomarker discovery; they define patient subpopulations which stand to benefit most, or least, from a given treatment. The identification of these biomarkers is often the byproduct of the related but fundamentally different task of treatment rule estimation. Using treatment rule estimation methods to identify predictive biomarkers in clinical trials where the number of covariates exceeds the number of participants often results in high false discovery rates. The higher than expected number of false positives translates to wasted resources when conducting follow-up experiments for drug target identification and diagnostic assay development. Patient outcomes are in turn negatively affected. We propose a variable importance parameter for directly assessing the importance of potentially predictive biomarkers and develop a flexible nonparametric inference procedure for this estimand. We prove that our estimator is double robust and asymptotically linear under loose conditions in the data-generating process, permitting valid inference about the importance metric. The statistical guarantees of the method are verified in a thorough simulation study representative of randomized control trials with moderate and high-dimensional covariate vectors. Our procedure is then used to discover predictive biomarkers from among the tumor gene expression data of metastatic renal cell carcinoma patients enrolled in recently completed clinical trials. We find that our approach more readily discerns predictive from nonpredictive biomarkers than procedures whose primary purpose is treatment rule estimation. An open-source software implementation of the methodology, the uniCATE R package, is briefly introduced.

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome

BACKGROUND

Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers.

METHODS

We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient's response to a variety of therapies in multiple cancer types without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: personalized oncology (PO), aimed at prioritizing treatments for a single patient, and clinical trial design (CTD), selecting the most likely responders in a patient cohort.

FINDINGS

Evaluating ENLIGHT's performance on 21 blinded clinical trial datasets in the PO setting, we show that it can effectively predict a patient's treatment response across multiple therapies and cancer types. Its prediction accuracy is better than previously published transcriptomics-based signatures and is comparable with that of supervised predictors developed for specific indications and drugs. In combination with the interferon-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, ENLIGHT can potentially enhance clinical trial success for immunotherapies and other monoclonal antibodies by excluding non-responders while overall achieving more than 90% of the response rate attainable under an optimal exclusion strategy.

CONCLUSIONS

ENLIGHT demonstrably enhances the ability to predict therapeutic response across multiple cancer types from the bulk tumor transcriptome.

FUNDING

This research was supported in part by the Intramural Research Program, NIH and by the Israeli Innovation Authority.

A new natural killer cell-specific gene signature predicting recurrence in colorectal cancer patients

The protective role of Natural Killer (NK) cell tumour immunosurveillance has long been recognised in colorectal cancer (CRC). However, as most patients show limited intra-tumoral NK cell infiltration, improving our ability to identify those with high NK cell activity might aid in dissecting the molecular features which underlie NK cell sensitivity. Here, a novel CRC-specific NK cell gene signature that infers NK cell load in primary tissue samples was derived and validated in multiple patient CRC cohorts. In contrast with other NK cell gene signatures that have several overlapping genes across different immune cell types, our NK cell signature has been extensively refined to be specific for CRC-infiltrating NK cells. The specificity of the signature is substantiated in tumour-infiltrating NK cells from primary CRC tumours at the single cell level, and the signature includes genes representative of NK cells of different maturation states, activation status and anatomical origin. Our signature also accurately discriminates murine NK cells, demonstrating the applicability of this geneset when mining datasets generated from preclinical studies. Differential gene expression analysis revealed tumour-intrinsic features associated with NK cell inclusion versus exclusion in CRC patients, with those tumours with predicted high NK activity showing strong evidence of enhanced chemotactic and cytotoxic transcriptional programs. Furthermore, survival modelling indicated that NK signature expression is associated with improved survival outcomes in CRC patients. Thus, scoring CRC samples with this refined NK cell signature might aid in identifying patients with high NK cell activity who could be prime candidates for NK cell directed immunotherapies.

Comprehensive analysis of m6A circRNAs identified in colorectal cancer by MeRIP sequencing

Purpose

To characterize the entire profile of m6A modifications and differential expression patterns for circRNAs in colorectal cancer (CRC).

Methods

First, High-throughput MeRIP-sequencing and RNA-sequencing was used to determine the difference in m6A methylome and expression of circRNA between CRC tissues and tumor-adjacent normal control (NC) tissues. Then, GO and KEGG analysis detected pathways involved in differentially methylated and differentially expressed circRNAs (DEGs). The correlations between m6A status and expression level were calculated using a Pearson correlation analysis. Next, the networks of circRNA-miRNA-mRNA were visualized using the Target Scan and miRanda software. Finally, We describe the relationship of distance between the m6A peak and internal ribosome entry site (IRES) and protein coding potential of circRNAs.

Results

A total of 4340 m6A peaks of circRNAs in CRC tissue and 3216 m6A peaks of circRNAs in NC tissues were detected. A total of 2561 m6A circRNAs in CRC tissues and 2129 m6A circRNAs in NC tissues were detected. Pathway analysis detected that differentially methylated and expressed circRNAs were closely related to cancer. The conjoint analysis of MeRIP-seq and RNA-seq data discovered 30 circRNAs with differentially m6A methylated and synchronously differential expression. RT-qPCR showned circRNAs (has_circ_0032821, has_circ_0019079, has_circ_0093688) were upregulated and circRNAs (hsa_circ_0026782, hsa_circ_0108457) were downregulated in CRC. In the ceRNA network, the 10 hyper-up circRNAs were shown to be associated with 19 miRNAs and regulate 16 mRNAs, 14 hypo-down circRNAs were associated with 30 miRNAs and regulated 27 mRNAs. There was no significant correlation between the level of m6A and the expression of circRNAs. The distance between the m6A peak and IRES was not significantly related to the protein coding potential of circRNAs.

Conclusion

Our study found that there were significant differences in the m6A methylation patterns of circRNAs between CRC and NC tissues. M6A methylation may affect circRNA-miRNA-mRNA co-expression in CRC and further affect the regulation of cancer-related target genes.

Involvement of Serotonergic System in Oxaliplatin-Induced Neuropathic Pain

Oxaliplatin is a chemotherapeutic agent widely used against colorectal and breast cancers; however, it can also induce peripheral neuropathy that can rapidly occur even after a single infusion in up to 80–90% of treated patients. Numerous efforts have been made to understand the underlying mechanism and find an effective therapeutic agent that could diminish pain without damaging its anti-tumor effect. However, its mechanism is not yet clearly understood. The serotonergic system, as part of the descending pain inhibitory system, has been reported to be involved in different types of pain. The malfunction of serotonin (5-hydroxytryptamine; 5-HT) or its receptors has been associated with the development and maintenance of pain. However, its role in oxaliplatin-induced neuropathy has not been clearly elucidated. In this review, 16 in vivo studies focused on the role of the serotonergic system in oxaliplatin-induced neuropathic pain were analyzed. Five studies analyzed the involvement of 5-HT, while fourteen studies observed the role of its receptors in oxaliplatin-induced allodynia. The results show that 5-HT is not involved in the development of oxaliplatin-induced allodynia, but increasing the activity of the 5-HT_1A, 5-HT_2A, and 5-HT₃ receptors and decreasing the action of 5-HT_2C and 5-HT₆ receptors may help inhibit pain.

5-Fluorouracil efficacy requires anti-tumor immunity triggered by cancer-cell-intrinsic STING

5-Fluorouracil (5-FU) is a widely used chemotherapeutic drug, but the mechanisms underlying 5-FU efficacy in immunocompetent hosts in vivo remain largely elusive. Through modeling 5-FU response of murine colon and melanoma tumors, we report that effective reduction of tumor burden by 5-FU is dependent on anti-tumor immunity triggered by the activation of cancer-cell-intrinsic STING. While the loss of STING does not induce 5-FU resistance in vitro, effective 5-FU responsiveness in vivo requires cancer-cell-intrinsic cGAS, STING, and subsequent type I interferon (IFN) production, as well as IFN-sensing by bone-marrow-derived cells. In the absence of cancer-cell-intrinsic STING, a much higher dose of 5-FU is needed to reduce tumor burden. 5-FU treatment leads to increased intratumoral T cells, and T-cell depletion significantly reduces the efficacy of 5-FU in vivo. In human colorectal specimens, higher STING expression is associated with better survival and responsiveness to chemotherapy. Our results support a model in which 5-FU triggers cancer-cell-initiated anti-tumor immunity to reduce tumor burden, and our findings could be harnessed to improve therapeutic effectiveness and toxicity for colon and other cancers.

Identification of Two Subgroups of FOLFOX Resistance Patterns and Prediction of FOLFOX Response in Colorectal Cancer Patients

To dissect gene expression subgroups of FOLFOX resistance colorectal cancer(CRC) and predict FOLFOX response, gene expression data of 83 stage IV CRC tumor samples (FOLFOX responder n = 42, non-responder n = 41) are used to develop a novel iterative supervised learning method IML. IML identified two mutually exclusive subgroups of CRC patients that rely on different DNA damage repair proteins and resist FOLFOX. IML was validated in two validation sets (HR = 2.6, p Value = 0.02; HR = 2.36, p value = 0.02). A subgroup of mesenchymal subtype patients benefit from FOLFOX. Different subgroups of FOLFOX nonresponders may need to be treated differently.

PDXGEM: patient-derived tumor xenograft-based gene expression model for predicting clinical response to anticancer therapy in cancer patients

Background

Cancer is a highly heterogeneous disease with varying responses to anti-cancer drugs. Although several attempts have been made to predict the anti-cancer therapeutic responses, there remains a great need to develop highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward a personalized medicine. Patient derived xenografts (PDXs) are preclinical cancer models in which the tissue or cells from a patient’s tumor are implanted into an immunodeficient or humanized mouse. In the present study, we develop a bioinformatics analysis pipeline to build a predictive gene expression model (GEM) for cancer patients’ drug responses based on gene expression and drug activity data from PDX models.

Results

Drug sensitivity biomarkers were identified by performing an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. We built a drug response prediction model (called PDXGEM) in a random-forest algorithm by using a subset of the drug sensitvity biomarkers with concordant co-expression patterns between the PDXs and pretreatment cancer patient tumors. We applied the PDXGEM to several cytotoxic chemotherapies as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological response or survival outcomes were observed in extensive independent validations on multiple cancer patient datasets obtained from retrospective observational studies and prospective clinical trials.

Conclusion

Our results demonstrated the strong potential of using molecular profiles and drug activity data of PDX tumors in developing a clinically translatable predictive cancer biomarkers for cancer patients. The PDXGEM web application is publicly available at http://pdxgem.moffitt.org.

FBXW4 Acts as a Protector of FOLFOX-Based Chemotherapy in Metastatic Colorectal Cancer Identified by Co-Expression Network Analysis

Background

FOLFOX chemotherapy is one of the most commonly used treatments for colorectal cancer (CRC) patients. However, the efficacy and tolerance of FOLFOX therapy varies between patients. The purpose of this study was to explore hub genes associated with primary chemotherapy-resistance and to explore the possible mechanisms involved from non-European patients.

Method

A weighted gene co-expression network was constructed to identify gene modules associated with chemotherapy resistance in mCRC from China.

Results

A Gene Array Chip was used to detect mRNA expression in 11 mCRC patients receiving preoperative FOLFOX chemotherapy. The immune response was associated with chemotherapy-resistance in microarray data. Through the use of WGCNA, we demonstrated that the crucial functions enriched in chemotherapy-resistance modules were cell proliferation, MAPK signaling pathways, and PI3K signaling pathways. Additionally, we identified and validated FBXW4 as a new effective predictor for chemotherapy sensitivity and a prognostic factor for survival of CRC patients by using our own data and GSE69657. Furthermore, a meta-analysis of 15 Gene Expression Omnibus–sourced datasets showed that FBXW4 messenger RNA levels were significantly lower in CRC tissues than in normal colon tissues. An analysis of the data from the R2: Genomics Analysis and Visualization Platform showed that low FBXW4 expression was correlated with a significantly worse event- and relapse-free survival. Gene set enrichment analysis showed that the mechanism of FBXW4-mediated chemotherapy resistance may involve the DNA replication signal pathway and the cell cycle.

Conclusion

FBXW4 is associated with chemotherapy resistance and prognosis of CRC probably by regulating DNA replication signaling pathways and the cell cycle.

Overexpressed CES2 has prognostic value in CRC and knockdown CES2 reverses L-OHP-resistance in CRC cells by inhibition of the PI3K signaling pathway

CES-2 (carboxylesterase-2) belongs to the carboxylesterase gene family, which plays crucial roles in lipid mobilization and chemosensitivity to irinotecan. However, its role in chemosensitivity to oxaliplatin (L-OHP) remains unclear. Herein, L-OHP-resistant cells (HCT-116L and RKOL) were established by increasing the concentration of L-OHP. The results showed that CES2 expression was upregulated in L-OHP-resistant tissues and cells lines (both P < 0.01). Low expression of CES2 correlated with a better survival, and the results were further confirmed in the R2 platform: a biologist friendly web-based genomics analysis and visualization application. Downregulation of CES2 suppressed cell proliferation, induced apoptosis and reversed L-OHP resistance by medicating the PI3K signaling pathway in L-OHP-resistant cells. However, both PI3K inhibitor (LY294002) and activator (IGF-1) could not medicate CES2 expression. These findings indicated that CES2 may be utilized as a novel biomarker and therapeutic target for L-OHP resistance in CRC treatment.

FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms

Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5-FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta-analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy.

Qualitative transcriptional signature for predicting pathological response of colorectal cancer to FOLFOX therapy

FOLFOX (5‐fluorouracil, leucovorin and oxaliplatin) is one of the main chemotherapy regimens for colorectal cancer (CRC), but only half of CRC patients respond to this regimen. Using gene expression profiles of 96 metastatic CRC patients treated with FOLFOX, we first selected gene pairs whose within‐sample relative expression orderings (REO) were significantly associated with the response to FOLFOX using the exact binomial test. Then, from these gene pairs, we applied an optimization procedure to obtain a subset that achieved the largest F‐score in predicting pathological response of CRC to FOLFOX. The REO‐based qualitative transcriptional signature, consisting of five gene pairs, was developed in the training dataset consisting of 96 samples with an F‐score of 0.90. In an independent test dataset consisting of 25 samples with the response information, an F‐score of 0.82 was obtained. In three other independent survival datasets, the predicted responders showed significantly better progression‐free survival than the predicted non‐responders. In addition, the signature showed a better predictive performance than two published FOLFOX signatures across different datasets and is more suitable for CRC patients treated with FOLFOX than 5‐fluorouracil‐based signatures. In conclusion, the REO‐based qualitative transcriptional signature can accurately identify metastatic CRC patients who may benefit from the FOLFOX regimen.

Prospective validation in epithelial tumors of a gene expression predictor of liver metastasis derived from uveal melanoma

Predicting the risk of liver metastasis can have important prognostic and therapeutic implications, given the availability of liver-directed therapy. Uveal melanoma has a striking predisposition for liver metastasis despite the absence of anatomical proximity. Understanding its biology may uncover factors promoting liver metastasis in other malignancies. We quantified gene expression by RNAseq in 76 uveal melanomas and combined with public data in a meta-analysis of 196 patients. The meta-analysis of uveal melanoma gene expression identified 63 genes which remained prognostic after adjustment for chromosome 3 status. Two genes, PTP4A3 and JPH1, were selected by L1-penalized regression and combined in a prognostic score. The score predicted liver-specific relapse in a public pan-cancer dataset and in two public colorectal cancer datasets. The score varied between colorectal consensus molecular subtypes (CMS), as did the risk of liver relapse, which was lowest in CMS1. Additional prospective validation was done by real-time PCR in 463 breast cancer patients. The score was significantly correlated with liver relapse in hormone receptor positive tumors. In conclusion, the expression of PTP4A3 and JPH1 correlates with risk of liver metastasis in colorectal cancer and breast cancer. The underlying biological mechanism is an interesting area for further research.

HCMDB: the human cancer metastasis database

Metastasis is the main event leading to death in cancer patients. Over the past decade, high-throughput technologies have provided genome-wide view of transcriptomic changes associated with cancer metastases. Many microarray and RNA sequencing studies have addressed metastases-related expression patterns in various types of cancer, and the number of relevant works continues to increase rapidly. These works have characterized genes that orchestrate the metastatic phenotype of cancer cells. However, these expression data have been deposited in various repositories, and efficiently analyzing these data is still difficult because of the lack of an integrated data mining platform. To facilitate the in-depth analyses of transcriptome data on metastasis, it is quite important to make a comprehensive integration of these metastases-related expression data. Here, we presented a database, HCMDB (the human cancer metastasis database, http://hcmdb.i-sanger.com/index), which is freely accessible to the research community query cross-platform transcriptome data on metastases. HCMDB is developed and maintained as a useful resource for building the systems-biology understanding of metastasis.

Identification of differentially expressed circular RNAs in chemoresistant colorectal cancer

Aim: Chemoresistance in colorectal cancer (CRC) has become a burden in treating the disease effectively. Circular RNAs (circRNAs) are a type of noncoding RNA that were found to be important in cellular homeostasis. The involvement of circRNAs in relation to chemoresistance in other types of cancers has also been reported. This study aims to identify the differentially expressed circRNAs between chemoresistant and chemosensitive CRC cells. Materials & methods: We developed a chemoresistant cell line model and profiled the circRNAs via microarray. We further validated the expression of two circRNAs in 25 formalin-fixed paraffin-embedded (FFPE) tissue specimens (13 nonresponders and 12 responders) via quantitative polymerase chain reaction (qPCR).  Results & conclusion: We found that there were 773 upregulated and 732 downregulated circRNAs between the chemoresistant and chemosensitive HCT-116 cells. We found that hsa_circ_32883 could be a promising biotarget.

YAP1-induced MALAT1 promotes epithelial-mesenchymal transition and angiogenesis by sponging miR-126-5p in colorectal cancer

Yes-associated protein 1 (YAP1) exerts significant effects in various malignancies. However, the oncogenic role of YAP1 remains controversial, and the mechanism by which YAP1 regulates non-coding RNAs is still largely unknown. The present study aimed to assess the effect of YAP1 on the malignant behaviors of colorectal carcinoma (CRC) and explore the underlying regulatory mechanism of the YAP1-MALAT1-miR-126-5p axis. YAP1 was highly expressed in CRC tissues as assessed by GSE20916 and its expression was negatively correlated with overall survival in 83 CRC cases. Meanwhile, YAP1 promoted proliferation, invasion, and migration in colon cancer cells, in vitro and in vivo. MALAT1 was obviously expressed, with differential expression of 11 lncRNAs in HCT116 cells after transfection with siYAP1 or si-Ctl. Based on bioinformatics prediction, immunoprecipitation (IP), and chromatin immunoprecipitation (ChIP), the interaction of YAP1 with TCF4/β-catenin was regulated by MALAT1. Bioinformatics prediction, dual luciferase assay, RNA-IP, and RNA pull-down assay demonstrated that YAP1-induced MALAT1 promoted the expression of metastasis-associated molecules such as VEGFA, SLUG, and TWIST, by sponging miR-126-5p in CRC. These findings indicated that the YAP1-MALAT1-miR-126-5p axis could control angiogenesis and epithelial-mesenchymal transition in CRC, providing potential biomarkers and therapeutic targets for CRC.

Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis

BACKGROUND

Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts.

RESULTS

We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and > 3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication.

CONCLUSIONS

We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes.

Identification of the predictive genes for the response of colorectal cancer patients to FOLFOX therapy

Background

Colorectal cancer is a malignant tumor with high death rate. Chemotherapy, radiotherapy and surgery are the three common treatments of colorectal cancer. For early colorectal cancer patients, postoperative adjuvant chemotherapy can reduce the risk of recurrence. For advanced colorectal cancer patients, palliative chemotherapy can significantly improve the life quality of patients and prolong survival. FOLFOX is one of the mainstream chemotherapies in colorectal cancer, however, its response rate is only about 50%.

Methods

To systematically investigate why some of the colorectal cancer patients have response to FOLFOX therapy while others do not, we searched all publicly available database and combined three gene expression datasets of colorectal cancer patients with FOLFOX therapy. With advanced minimal redundancy maximal relevance and incremental feature selection method, we identified the biomarker genes.

Results

A Support Vector Machine-based classifier was constructed to predict the response of colorectal cancer patients to FOLFOX therapy. Its accuracy, sensitivity and specificity were 0.854, 0.845 and 0.863, respectively.

Conclusion

The biological analysis of representative biomarker genes suggested that apoptosis and inflammation signaling pathways were essential for the response of colorectal cancer patients to FOLFOX chemotherapy.

Relationship Between Expression of Proteins ERCC1, ERCC2, and XRCC1 and Clinical Outcomes in Patients with Rectal Cancer Treated with FOLFOX-Based Preoperative Chemoradiotherapy

BACKGROUND

Platinum resistance enhances DNA damage repair through nucleotide excision repair mechanisms involving the excision repair cross-complementing group 1 (ERCC1), X-ray cross-complementing group 1 (XRCC1), and excision repair cross-complementing group 2 (ERCC2). We evaluated the correlation between the expression of these three DNA repair genes and clinical outcomes in patients with rectal cancer receiving FOLFOX-based preoperative chemoradiotherapy (CRT).

METHODS

Using immunohistochemistry, we examined the expression of ERCC1, ERCC2, and XRCC1 in pre-CRT cancer tissues from 86 patients with rectal cancer who had undergone curative resection and preoperative CRT with FOLFOX-4 to identify potential predictors of clinical outcomes.

RESULTS

Following CRT, 57 and 29 patients were classified as responders (pathological tumor regression grade TRG 0 and TRG 1) and poor responders (TRG 2 and TRG 3), respectively. The multivariate analysis revealed that ERCC1 overexpression was correlated with a poor CRT response [p < 0.0001; odds ratio (OR), 9.397; 95% confidence interval (CI) 2.721-32.457]. Furthermore, a poor response to CRT (pathological TRG of 2-3) (p = 0.18; OR 5.685; 95% CI 1.349-23.954) and abnormal pre-CRT serum carcinoembryonic antigen levels (>5 ng/mL) (p = 0.03; OR 6.288; 95% CI 1.198-33.006) were independent predictors of postoperative relapse. By contrast, ERCC2 and XRCC1 expression did not play predictive roles in the analyzed patients.

CONCLUSIONS

ERCC1 overexpression is associated with a poor preoperative CRT response in patients with rectal cancer receiving FOLFOX-based preoperative CRT. ERCC1 is a potential biomarker for identifying patients who can benefit from customized treatment programs.

Nucleotide excision repair and response and survival to chemotherapy in colorectal cancer patients

Several new chemotherapeutic agents have become available for the treatment of colorectal cancer, which has led to increased complexity in treatment planning. Treatment decision making for individual patients could be facilitated if guided by predictive and prognostic markers. As most cytotoxic drugs induce DNA damage, the DNA damage repair pathways hold potential for yielding such biomarkers. Here, we review the current evidence of a possible involvement of the nucleotide excision repair pathway in the efficacy of chemotherapeutic agents used in the treatment of colorectal cancer. Although a large number of studies have been conducted, they are generally of moderate size and heterogeneous in design. Up to date no firm conclusions can be drawn to translate these results into the clinic. We recommend further comprehensive investigations of the nucleotide excision repair pathway in large patient studies that include both discovery and validation cohorts.

An 80-gene set to predict response to preoperative chemoradiotherapy for rectal cancer by principle component analysis

Preoperative chemoradiotherapy (CRT) for locally advanced rectal cancer not only improves the postoperative local control rate, but also induces downstaging. However, it has not been established how to individually select patients who receive effective preoperative CRT. The aim of this study was to identify a predictor of response to preoperative CRT for locally advanced rectal cancer. This study is additional to our multicenter phase II study evaluating the safety and efficacy of preoperative CRT using oral fluorouracil (UMIN ID: 03396). From April, 2009 to August, 2011, 26 biopsy specimens obtained prior to CRT were analyzed by cyclopedic microarray analysis. Response to CRT was evaluated according to a histological grading system using surgically resected specimens. To decide on the number of genes for dividing into responder and non-responder groups, we statistically analyzed the data using a dimension reduction method, a principle component analysis. Of the 26 cases, 11 were responders and 15 non-responders. No significant difference was found in clinical background data between the two groups. We determined that the optimal number of genes for the prediction of response was 80 of 40,000 and the functions of these genes were analyzed. When comparing non-responders with responders, genes expressed at a high level functioned in alternative splicing, whereas those expressed at a low level functioned in the septin complex. Thus, an 80-gene expression set that predicts response to preoperative CRT for locally advanced rectal cancer was identified using a novel statistical method.

Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer

Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip^® HG-U133 Plus 2.0) were performed in fresh frozen tumor samples of 37 mCRC patients (training cohort). Differential gene expression profiles among the two study conditions (responders versus non-responders) were assessed using supervised class prediction algorithms. A set of 161 differentially expressed genes in responders (23 patients; 62%) versus non-responders (14 patients; 38%) was selected for further assessment and validation by RT-qPCR (TaqMan^®Low Density Arrays (TLDA) 7900 HT Micro Fluidic Cards) in an independent multi-institutional cohort (53 mCRC patients). Seven of these genes were confirmed as significant predictors of response. Patients with a favorable predictive signature had significantly greater response rate (58% vs 13%, p = 0.024), progression-free survival (61% vs 13% at 1 year, HR = 0.32, p = 0.009) and overall survival (32 vs 16 months, HR = 0.21, p = 0.003) than patients with an unfavorable gene signature. This is the first study to validate a gene-expression profile predictive of response to CT in mCRC patients. Larger and prospective confirmatory studies are required, however, in order to successfully provide oncologists with adequate tools to optimize treatment selection in routine clinical practice.

Precision Medicine and Non-Colorectal Cancer Liver Metastases: Fiction or Reality?

BACKGROUND

Non-colorectal liver metastases (nCRLM) constitute a variety of heterogeneous diseases and a considerable therapeutic challenge. Management is based on the primary tumor and the clinical course. In the era of precision medicine (PM) we know that cancer is heterogeneous within the tumor and across different sites.

METHODS

We give an overview of the path to PM through 'omics' beyond genomics. We refer to the experience gained to date from models such as colorectal cancer and we discuss the opportunity offered by PM for the management of nCRLM.

RESULTS

In order to best characterize and track tumor biological behaviors as well as to understand mechanisms of response to therapy and survival we suggest the application of novel clinical trial designs, a dynamic approach with serial monitoring involving evaluation of primary and metastatic sites. Quality and standardization of tissue acquisition and biobanking is a precondition for the reliability of this approach.

CONCLUSION

The application of PM is increasingly becoming a reality. Elucidating the mysteries of tumors in complex settings can only be achieved with the approach PM offers. nCRLM may serve as a model for the application of PM principles and techniques in understanding individual diseases and also cancer as an entity and therapeutic challenge.

PKLR promotes colorectal cancer liver colonization through induction of glutathione synthesis

Colorectal cancer metastasis to the liver is a major cause of cancer-related death; however, the genes and pathways that govern this metastatic colonization event remain poorly characterized. Here, using a large-scale in vivo RNAi screen, we identified liver and red blood cell pyruvate kinase (PKLR) as a driver of metastatic liver colonization. PKLR expression was increased in liver metastases as well as in primary colorectal tumors of patients with metastatic disease. Evaluation of a murine liver colonization model revealed that PKLR promotes cell survival in the tumor core during conditions of high cell density and oxygen deprivation by increasing glutathione, the primary endogenous antioxidant. PKLR negatively regulated the glycolytic activity of PKM2, the major pyruvate kinase isoenzyme known to regulate cellular glutathione levels. Glutathione is critical for metastasis, and we determined that the rate-limiting enzyme of glutathione synthesis, GCLC, becomes overexpressed in patient liver metastases, promotes cell survival under hypoxic and cell-dense conditions, and mediates metastatic liver colonization. RNAi-mediated inhibition of glutathione synthesis impaired survival of multiple colon cancer cell lines, and pharmacological targeting of this metabolic pathway reduced colonization in a primary patient-derived xenograft model. Our findings highlight the impact of metabolic reprogramming within the niche as metastases progress and suggest clinical potential for targeting this pathway in colorectal cancer.

Reactive oxygen species mediate oxaliplatin-induced epithelial-mesenchymal transition and invasive potential in colon cancer

Therapeutic benefits offered by common chemotherapy drugs, such as oxaliplatin, are limited due to the development of resistance, which contributes to treatment failure and metastasis. The epithelial-mesenchymal transition (EMT) is a key event contributing to the development of resistance to chemotherapeutics. Although the relationship between oxaliplatin and chemotherapy resistance has been described for decades, the molecular mechanisms have remained elusive. The aim of the present study was to investigate the underlying mechanisms of oxaliplatin-mediated metastasis. Here, we identify reactive oxygen species (ROS) as mediators that promote the oxaliplatin-induced EMT. Following oxaliplatin treatment, the messenger RNA (mRNA) levels of most peroxiredoxin family genes, except for peroxiredoxin 1 (prdx1) gene, were constant or even decreased, resulting in ROS abundance. And the antioxidant guardian Nrf2 was unconspicuously raised both transcriptionally and translationally with oxaliplatin treatment as compared to those induced by topotecan treatment, which has been proved with no induced metastasis. In addition, the study evaluated high levels of ROS leading to EMT via activation of the known oncogenes Akt and Snail. Using the Akt inhibitor LY294002 or knocking down Snail expression via RNA interference (RNAi) reversed the effects of oxaliplatin on the EMT and metastasis. Our studies establish a role for the ROS-Akt-Snail axis as a mechanism by which chemotherapeutics induce EMT and cancer metastasis.

AngioMatrix, a signature of the tumor angiogenic switch-specific matrisome, correlates with poor prognosis for glioma and colorectal cancer patients

Angiogenesis represents a rate-limiting step during tumor progression. Targeting angiogenesis is already applied in cancer treatment, yet limits of anti-angiogenic therapies have emerged, notably because tumors adapt and recur after treatment. Therefore, there is a strong need to better understand the molecular and cellular mechanisms underlying tumor angiogenesis. Using the RIP1-Tag2 transgenic murine model, we identified 298 genes that are deregulated during the angiogenic switch, revealing an ingression/expansion of specific stromal cell types including endothelial cells and pericytes, but also macrophages and perivascular mesenchymal cells. Canonical TGF-β signaling is up-regulated during the angiogenic switch, especially in tumor-associated macrophages and fibroblasts. The matrisome, comprising extracellular matrix (ECM) and ECM-associated molecules, is significantly enriched, which allowed us to define the AngioMatrix signature as the 110 matrisomal genes induced during the RIP1-Tag2 angiogenic switch. Several AngioMatrix molecules were validated at expression level. Ablation of tenascin-C, one of the most highly induced ECM molecules during the switch, resulted in reduced angiogenesis confirming its important role. In human glioma and colorectal samples, the AngioMatrix signature correlates with the expression of endothelial cell markers, is increased with tumor progression and finally correlates with poor prognosis demonstrating its diagnostic and therapeutic potential.

Predictive value of ERCC1, ERCC2, and XRCC1 overexpression for stage III colorectal cancer patients receiving FOLFOX-4 adjuvant chemotherapy

OBJECTIVES

To determine the correlation between expression of three DNA repair genes and early failure/clinical outcome of stage III colorectal cancer (CRC) patients administrated with FOLFOX-4, including the excision repair cross-complementation group 1 (ERCC1), the excision repair cross-complementing 2 (ERCC2), and X-ray repair cross-complementing protein 1 (XRCC1).

MATERIALS AND METHODS

We retrospectively analyzed clinicopathological features and ERCC1, ERCC2, XRCC1 expressions by immunohistochemical staining in 180 stage III CRC patients undergoing curative resection and treated with FOLFOX-4 chemotherapy to identify predictors of postoperative early failure.

RESULTS

Among 180 CRC patients, 44 patients were classified into early failure group, and 136 patients were categorized into non-early failure group. A multivariate logistic regression analysis showed that ERCC1 overexpression (P = 0.005), and high postoperative carcinoembryonic antigen (CEA) levels (P = 0.001) were independent predictors of early failure. Additionally, ERCC1 overexpression was not only a predictor of early failure but also for disease-free survival (P < 0.001) and overall survival (P < 0.001). However, no predictive roles of ERCC2 and XRCC1 expression among these analyzed patients.

CONCLUSIONS

ERCC1 overexpression is an important predictor of early failure in patients with stage III CRC administrating FOLFOX-4 adjuvant chemotherapy and this marker may help identify patients who would benefit from intensive follow-up and enhance therapeutic programs.

Targeted therapy in metastatic colorectal cancer -- an example of personalised medicine in action

In metastatic colorectal cancer (mCRC), an improved understanding of the underlying pathology and molecular biology has successfully merged with advances in diagnostic techniques and local/systemic therapies as well as improvements in the functioning of multidisciplinary teams, to enable tailored treatment regimens and optimized outcomes. Indeed, as a result of these advancements, median survival for patients with mCRC is now in the range of 20-24months, having approximately tripled in the last 20years. The identification of KRAS as a negative predictive marker for activity of epidermal growth factor receptor (EGFR)-targeted monoclonal antibodies (mAbs), such as panitumumab (Amgen, Thousand Oaks, USA) and cetuximab (ImClone, Branchburg, USA), has perhaps had the greatest impact on patient management. This meant that, for the first time, mCRC patients unlikely to respond to a targeted therapy could be defined ahead of treatment. Ongoing controversies such as whether patients with KRAS G13D- (or BRAF V600-) mutated tumours can still respond to EGFR-targeted mAbs and the potential impact of inter- and intra-tumour heterogeneity on tumour sampling show that the usefulness of KRAS as a biomarker has not yet been exhausted, and that other downstream biomarkers should be considered. Conversely, a predictive biomarker for anti-angiogenic agents such as bevacizumab (Genentech, San Francisco, USA) in the mCRC setting is still lacking. In this review we will discuss the discovery and ongoing investigation into predictive biomarkers for mCRC as well as how recent advances have impacted on clinical practice and ultimately the overall cost of treatment for these patients.

Gene expression signature predicting high-grade prostate cancer responses to oxaliplatin

Prostate cancer is one of the leading causes of cancer-related deaths among men. Several prognostic factors allow differentiation of low-grade tumors from high-grade tumors with high metastatic potential. High-grade tumors are currently treated with hormone therapy, to which taxanes are added when the tumors become resistant to castration. Clinical trials with other anticancer agents did not take into account the genetic backgrounds of the tumors, and most trials demonstrated low response rates. Here we used an in silico approach to screen for drug candidates that might be used as alternatives to taxanes, on the basis of a published expression signature involving 86 genes that could distinguish high-grade and low-grade tumors (Proc Natl Acad Sci USA 103:10991-10996, 2006). We explored the National Cancer Institute databases, which include data on the gene expression profiles of 60 human tumor cell lines and the in vitro sensitivities of the cell lines to anticancer drugs, and we identified several genes in the signature for which expression levels were correlated with chemosensitivity. As an example of the validation of this in silico approach, we identified a set of six genes for which expression levels could predict cell sensitivity to oxaliplatin but not cisplatin. This signature was validated in vitro through silencing of the genes in DU145, LNCaP, and C4-2B prostate cancer cells, which was accompanied by changes in oxaliplatin but not cisplatin cytotoxicity. These results demonstrate the relevance of our approach for the identification of both alternative treatments for high-grade prostate cancers and new biomarkers to predict clinical tumor responses.

Absence of transcriptomic signature of response to chemotherapy in metastatic colorectal carcinoma patients

Aim: Tumor gene-expression profiling may define signatures capable of discriminating between responders and nonresponders to chemotherapy. Patients & methods: Fifty seven metastatic colorectal cancer patients were prospectively included and 40 tumors were analyzed. Patients were treated in first line with 5-fluorouracil associated with irinotecan or oxaliplatin. Response was evaluated using WHO criteria every 2 months after chemotherapy. Gene-expression profiling was performed using Applied Biosystems microarrays (Human Genome Survey Microarray v2.0; Paris, France). Data were analyzed using Bioconductor packages. Differential-expression analysis was performed by fitting a linear model. Moderated t-statistics were computed and p-values were adjusted for false-discovery rate. Pearson correlations tests were evaluated between gene expression and progression-free and overall survival. Results: Nonsupervised analysis did not show any clustering of expression levels according to treatment response. Supervised analysis compared expression levels between responders and nonresponders, within each treatment group and independently from treatment. No genes were identified as differentially expressed at a p-value of 10-3 and false-discovery rate of 30%. No correlation between expression levels and survival data was found. Conclusion: These negative results show that the determinants of response to chemotherapy should be sought not only in the tumor characteristics, but also among the processes leading to drug availability to the tumor.

Original submitted 7 July 2011; Revision submitted 17 October 2011