A Composite Gene Expression Signature Optimizes Prediction of Colorectal Cancer Metastasis and Outcome

Identification of CD147-positive extracellular vesicles as novel non-invasive biomarkers for the diagnosis and prognosis of colorectal cancer

BACKGROUND

The mortality rate of colorectal cancer (CRC) can be decreased with effective screening and early diagnosis. Exosomes are released from cancer cells into the bloodstream, and circulating exosomes may serve as novel biomarkers. This study aimed to identify a sensitive and rapid method of exosome collection and measurement using specific antibodies.

METHODS

ExoCounter, a high-sensitive exosome-counting system, allows the identification of exosomes without enrichment or purification, based on the identification of the transmembrane protein-CD147-on serum exosomes that are associated with CRC.

RESULTS

Receiver operating characteristic curves between healthy donors and CRC patients were described and assessed by CD147-specific exosomes (exo-CD147), CEA, and CA19-9. And area under curves for exo-CD147, CEA, and CA19-9 were 0.827 (95%CI: 0.764-0.891), 0.630 (95%CI: 0.536-0.724), and 0.659 (95%CI: 0.559-0.759), respectively. Drawing a clinical decision curve of exo-CD147 for the diagnosis of CRC metastases showed that when the threshold probability of exo-CD147 was between 20% and 92%, the net clinical utilization rate was higher than for all patients with or without metastases. A nomogram was constructed using multivariate COX regression analysis to select significant variables such as the high CD147 group (>34 × 105 particles). Calibration curves for 1-, 3-, and 5-year survival rates of CRC patients showed that the actual 1-, 3-, and 5-year survival rates were in excellent agreement with the survival rates predicted by the nomogram.

CONCLUSIONS

The increased CD147 expression in exosomes could serve as a diagnostic and prognostic biomarker for CRC.

High Expression of PDLIM2 Predicts a Poor Prognosis in Prostate Cancer and Is Correlated with Epithelial-Mesenchymal Transition and Immune Cell Infiltration

Purpose

To elucidate the clinical and prognostic role of PDZ and LIM domain protein (PDLIM) genes and the association to epithelial-mesenchymal transition (EMT) and immune cell infiltration in patients with prostate cancer (PRAD).

Methods

The data of RNA-seq, DNA methylation, and clinical features of PRAD patients were collected from The Cancer Genome Atlas (TCGA) database to define the prognostic value of PDLIM gene expression and the association with EMT and immune cell infiltration. A tissue microarray including 134 radical prostatectomy specimens was served as validation by immunohistochemistry (IHC) staining analysis.

Results

The mRNA levels of PDLIM1/2/3/4/6/7 were significantly downregulated, while PDLIM5 was upregulated in PRAD (P < 0.05). High expression of PDLIM2 mRNA suggests poor progression free interval in PRAD patients. DNA methylation of PDLIM2 was correlated with its mRNA expression level, and that the cg22973076 methylation site in PDLIM2 was associated with shorter PFI (P < 0.05) in PRAD. Single-sample gene-set enrichment and gene functional enrichment results showed that PDLIM2 was correlated with EMT and immune processes. Spearman's test showed a significant correlation with six reported EMT signatures and several EMT signature-related genes. Tumor microenvironment analysis revealed that the PDLIM2 mRNA expression was positively correlated with the immune score, stromal score, and various tumor infiltrating immune cells. Additionally, the results showed that patients in the high-PDLIM2 mRNA expression group may be more sensitive to immune checkpoint blockade therapy. Finally, IHC analysis further implicated the protein level of PDLIM2 was upregulated in PRAD and acts as a novel potential biomarker in predicting tumor progression.

Conclusion

Our study suggests that PDLIM family genes might be significantly correlated with oncogenesis and the progression of PRAD. PDLIM2 correlated with EMT and immune cell infiltration by acting as an oncogene in PRAD, which may serve as a potential prognostic biomarker for PRAD patients.

A Three-Genes Signature Predicting Colorectal Cancer Relapse Reveals LEMD1 Promoting CRC Cells Migration by RhoA/ROCK1 Signaling Pathway

Objective

Colorectal cancer (CRC) patients that experience early relapse consistently exhibit poor survival. However, no effective approach has been developed for the diagnosis and prognosis prediction of postoperative relapsed CRC.

Methods

Multiple datasets from the GEO database and TCGA database were utilized for bioinformatics analysis. WGCNA analyses and RRA analysis were performed to identify key genes. The COX/Lasso regression model was used to construct the recurrence model. Subsequent in vitro experiments further validated the potential role of the hub genes in CRC.

Results

A comprehensive analysis was performed on multiple CRC datasets and a CRC recurrence model was constructed containing LEMD1, SERPINE1, and SIAE. After further validation in two independent databases, we selected LEMD1 for in vitro experiments and found that LEMD1 could regulate CRC cell proliferation, migration, invasion, and promote EMT transition. The Rho-GTPase pulldown experiments further indicated that LEMD1 could affect RhoA activity and regulate cytoskeletal dynamics. Finally, we demonstrated that LEMD1 promoted CRC cell migration through the RhoA/ROCK1 signaling pathway.

Conclusions

In this study, a CRC relapse model consisting of LEMD1, SERPINE1, and SIAE was constructed by comprehensive analysis of multiple CRC datasets. LEMD1 could promote CRC cell migration through the RhoA/ROCK signaling pathway.

PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning

Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable. The under-diagnosis of metastasis events results in biased classification labels, and classification tools using biased labels may lead to inaccurate estimations of metastasis potential. This issue is further complicated by the unknown metastasis prevalence at the population level, the small number of confirmed metastasis cases, and the high dimensionality of the candidate molecular features. Our proposed algorithm, called Positive and unlabeled Learning from Unbalanced cases and Sparse structures (PLUS), is the first to use a positive and unlabeled learning framework to account for the under-detection of metastasis events in building a classifier. PLUS is specifically tailored for studying metastasis that deals with the unbalanced instance allocation as well as unknown metastasis prevalence, which are not considered by other methods. PLUS achieves superior performance on synthetic datasets compared with other state-of-the-art methods. Application of PLUS to The Cancer Genome Atlas Pan-Cancer gene expression data generated metastasis potential predictions that show good agreement with the clinical follow-up data, in addition to predictive genes that have been validated by independent single-cell RNA-sequencing datasets.

Metastasis is the major cause of cancer-related deaths, and evaluations of metastasis risk are essential for tailored treatment of cancer patients. Existing methods often build a classifier using the clinical metastasis diagnoses as binary responses or detect genomic features significantly associated with metastasis-related survival outcomes. However, these methods tend to identify genomic predictors that have little consistency across different cancer types. Thus, there is an urgent need for a powerful tool to characterize the cancer metastasis potential applicable across a wide span of cancer types. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable, which results in biased estimations of metastasis potential. Our proposed algorithm, called PLUS, considers patients with metastasis diagnosis as positive instances and the remainder as unlabeled instances, meaning they are either metastatic or non-metastatic. Such a classifier given by PLUS rendered concordance between the predicted cancer metastasis and observed metastasis survival outcomes in the follow-up data for almost all cancer types considered. The selected genes were found to perform functions consistent with experimental research findings and are capable of clustering the single cells based on their levels of metastasis potential.

Interaction of lncRNA MIR100HG with hnRNPA2B1 facilitates m6A-dependent stabilization of TCF7L2 mRNA and colorectal cancer progression

BACKGROUND

Epithelial-to-mesenchymal transition (EMT) is a process linked to metastasis and drug resistance with non-coding RNAs (ncRNAs) playing pivotal roles. We previously showed that miR-100 and miR-125b, embedded within the third intron of the ncRNA host gene MIR100HG, confer resistance to cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal antibody, in colorectal cancer (CRC). However, whether the MIR100HG transcript itself has a role in cetuximab resistance or EMT is unknown.

METHODS

The correlation between MIR100HG and EMT was analyzed by curating public CRC data repositories. The biological roles of MIR100HG in EMT, metastasis and cetuximab resistance in CRC were determined both in vitro and in vivo. The expression patterns of MIR100HG, hnRNPA2B1 and TCF7L2 in CRC specimens from patients who progressed on cetuximab and patients with metastatic disease were analyzed by RNAscope and immunohistochemical staining.

RESULTS

The expression of MIR100HG was strongly correlated with EMT markers and acted as a positive regulator of EMT. MIR100HG sustained cetuximab resistance and facilitated invasion and metastasis in CRC cells both in vitro and in vivo. hnRNPA2B1 was identified as a binding partner of MIR100HG. Mechanistically, MIR100HG maintained mRNA stability of TCF7L2, a major transcriptional coactivator of the Wnt/β-catenin signaling, by interacting with hnRNPA2B1. hnRNPA2B1 recognized the N6-methyladenosine (m⁶A) site of TCF7L2 mRNA in the presence of MIR100HG. TCF7L2, in turn, activated MIR100HG transcription, forming a feed forward regulatory loop. The MIR100HG/hnRNPA2B1/TCF7L2 axis was augmented in specimens from CRC patients who either developed local or distant metastasis or had disease progression that was associated with cetuximab resistance.

CONCLUSIONS

MIR100HG and hnRNPA2B1 interact to control the transcriptional activity of Wnt signaling in CRC via regulation of TCF7L2 mRNA stability. Our findings identified MIR100HG as a potent EMT inducer in CRC that may contribute to cetuximab resistance and metastasis by activation of a MIR100HG/hnRNPA2B1/TCF7L2 feedback loop.

Ras Pathway Activation and MEKi Resistance Scores Predict the Efficiency of MEKi and SRCi Combination to Induce Apoptosis in Colorectal Cancer

Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. The RAS pathway is activated in more than 55% of CRC and has been targeted for therapeutic intervention with MEK inhibitors. Unfortunately, many patients have de novo resistance, or can develop resistance to this new class of drugs. We have hypothesized that much of this resistance may pass through SRC as a common signal transduction node, and that inhibition of SRC may suppress MEK inhibition resistance mechanisms. CRC tumors of the Consensus Molecular Subtype (CMS) 4, enriched in stem cells, are difficult to successfully treat and have been suggested to evade traditional chemotherapy agents through resistance mechanisms. Here, we evaluate targeting two pathways simultaneously to produce an effective treatment by overcoming resistance. We show that combining Trametinib (MEKi) with Dasatinib (SRCi) provides enhanced cell death in 8 of the 16 tested CRC cell lines compared to treatment with either agent alone. To be able to select sensitive cells, we simultaneously evaluated a validated 18-gene RAS pathway activation signature score along with a 13-gene MEKi resistance signature score, which we hypothesize predict tumor sensitivity to this dual targeted therapy. We found the cell lines that were sensitive to the dual treatment were predominantly CMS4 and had both a high 18-gene and a high 13-gene score, suggesting these cell lines had potential for de novo MEKi sensitivity but were subject to the rapid development of MEKi resistance. The 13-gene score is highly correlated to a score for SRC activation, suggesting resistance is dependent on SRC. Our data show that gene expression signature scores for RAS pathway activation and for MEKi resistance may be useful in determining which CRC tumors will respond to the novel drug combination of MEKi and SRCi.

An integrative gene expression signature analysis identifies CMS4 KRAS-mutated colorectal cancers sensitive to combined MEK and SRC targeted therapy

BACKGROUND

Over half of colorectal cancers (CRCs) are hard-wired to RAS/RAF/MEK/ERK pathway oncogenic signaling. However, the promise of targeted therapeutic inhibitors, has been tempered by disappointing clinical activity, likely due to complex resistance mechanisms that are not well understood. This study aims to investigate MEK inhibitor-associated resistance signaling and identify subpopulation(s) of CRC patients who may be sensitive to biomarker-driven drug combination(s).

METHODS

We classified 2250 primary and metastatic human CRC tumors by consensus molecular subtypes (CMS). For each tumor, we generated multiple gene expression signature scores measuring MEK pathway activation, MEKi "bypass" resistance, SRC activation, dasatinib sensitivity, EMT, PC1, Hu-Lgr5-ISC, Hu-EphB2-ISC, Hu-Late TA, Hu-Proliferation, and WNT activity. We carried out correlation, survival and other bioinformatic analyses. Validation analyses were performed in two independent publicly available CRC tumor datasets (n = 585 and n = 677) and a CRC cell line dataset (n = 154).

RESULTS

Here we report a central role of SRC in mediating "bypass"-resistance to MEK inhibition (MEKi), primarily in cancer stem cells (CSCs). Our integrated and comprehensive gene expression signature analyses in 2250 CRC tumors reveal that MEKi-resistance is strikingly-correlated with SRC activation (Spearman P < 10-320), which is similarly associated with EMT (epithelial to mesenchymal transition), regional metastasis and disease recurrence with poor prognosis. Deeper analysis shows that both MEKi-resistance and SRC activation are preferentially associated with a mesenchymal CSC phenotype. This association is validated in additional independent CRC tumor and cell lines datasets. The CMS classification analysis demonstrates the strikingly-distinct associations of CMS1-4 subtypes with the MEKi-resistance and SRC activation. Importantly, MEKi + SRCi sensitivities are predicted to occur predominantly in the KRAS mutant, mesenchymal CSC-like CMS4 CRCs.

CONCLUSIONS

Large human tumor gene expression datasets representing CRC heterogeneity can provide deep biological insights heretofore not possible with cell line models, suggesting novel repurposed drug combinations. We identified SRC as a common targetable node--an Achilles' heel--in MEKi-targeted therapy-associated resistance in mesenchymal stem-like CRCs, which may help development of a biomarker-driven drug combination (MEKi + SRCi) to treat problematic subpopulations of CRC.

APC and TP53 Mutations Predict Cetuximab Sensitivity across Consensus Molecular Subtypes

Simple Summary

Colorectal cancer (CRC) is a major cause of cancer deaths. Cetuximab is an FDA-approved, underutilized therapeutic targeting the epidermal growth factor receptor (EGFR) in metastatic CRC. To date, despite selection of patients with wild-type RAS, it is still difficult to identify patients who may benefit from EGFR inhibitor (e.g., cetuximab) therapy. Our aim is to molecularly classify CRC patients to better identify subpopulations sensitive to EGFR targeted therapy. APC and TP53 are two major tumor suppressor genes in CRC whose mutations contribute to tumor initiation and progression and may identify cetuximab-sensitive tumors. Recently, it has been suggested that the consensus molecular subtype (CMS) classification may be used to help identify cetuximab-sensitive patients. Here, we report an analysis of multiple CRC tumor/PDX/cell line datasets using combined APC and TP53 mutations to refine the CMS classification to better predict responses to cetuximab to improve patient outcomes.

Abstract

Recently, it was suggested that consensus molecular subtyping (CMS) may aide in predicting response to EGFR inhibitor (cetuximab) therapies. We recently identified that APC and TP53 as two tumor suppressor genes, when mutated, may enhance cetuximab sensitivity and may represent easily measured biomarkers in tumors or blood. Our study aimed to use APC and TP53 mutations (AP) to refine the CMS classification to better predict responses to cetuximab. In total, 433 CRC tumors were classified into CMS1-4 subtypes. The cetuximab sensitivity (CTX-S) signature scores of AP vs. non-AP tumors were determined across each of the CMS classes. Tumors harboring combined AP mutations were predominantly enriched in the CMS2 class, and to a lesser degree, in the CMS4 class. On the other hand, AP mutated CRCs had significantly higher CTX-S scores compared to non-AP CRCs across all CMS classes. Similar results were also obtained in independent TCGA tumor collections (n = 531) and in PDMR PDX/PDO/PDC models (n = 477). In addition, the in vitro cetuximab growth inhibition was preferentially associated with the CMS2 cell lines harboring A/P genotypes. In conclusion, the AP mutation signature represents a convenient biomarker that refines the CMS classification to identify CRC subpopulations predicted to be sensitive to EGFR targeted therapies.

Increased Expression of VANGL1 is Predictive of Lymph Node Metastasis in Colorectal Cancer: Results from a 20-Gene Expression Signature

This study aimed at building a prognostic signature based on a candidate gene panel whose expression may be associated with lymph node metastasis (LNM), thus potentially able to predict colorectal cancer (CRC) progression and patient survival. The mRNA expression levels of 20 candidate genes were evaluated by RT-qPCR in cancer and normal mucosa formalin-fixed paraffin-embedded (FFPE) tissues of CRC patients. Receiver operating characteristic curves were used to evaluate the prognosis performance of our model by calculating the area under the curve (AUC) values corresponding to stage and metastasis. A total of 100 FFPE primary tumor tissues from stage I-IV CRC patients were collected and analyzed. Among the 20 candidate genes we studied, only the expression levels of VANGL1 significantly varied between patients with and without LNMs (p = 0.02). Additionally, the AUC value of the 20-gene panel was found to have the highest predictive performance (i.e., AUC = 79.84%) for LNMs compared with that of two subpanels including 5 and 10 genes. According to our results, VANGL1 gene expression levels are able to estimate LNMs in different stages of CRC. After a proper validation in a wider case series, the evaluation of VANGL1 gene expression and that of the 20-gene panel signature could help in the future in the prediction of CRC progression.

CCMAlnc Promotes the Malignance of Colorectal Cancer by Modulating the Interaction Between miR-5001-5p and Its Target mRNA

Objective

Colorectal cancer (CRC) is highly malignant and cancer metastasis remains the predominant cause of CRC death. The potential molecular mechanism of long non-coding RNA (lncRNAs) in CRC malignance is still poorly elucidated.

Methods

CCMAlnc expression was analyzed by using the Sequence ReadArchive (SRA) database. Target gene expression was examined by real-time PCR and Western blotting. The biological function of CCMAlnc and miR-5001-5p was detected by cell invasion, CCK8 proliferation, and colony formation assays in loss of function and gain of function experiments in vitro. A luciferase assay was performed to validate the target site of miR-5001-5p on the 3′-UTR of HES6 mRNA.

Results

CCMAlnc was identified as a novel functional lncRNA in CRC. Elevated CCMAlnc was detected in CRC cells as well as in clinical CRC tissue samples, and the expression of this lncRNA positively correlated with the poor prognosis of CRC patients. Functional validation assays revealed that downregulation of CCMAlnc impaired CRC cell proliferation and invasion in vitro, but upregulation of CCMAlnc reversed this effect. Moreover, CCMAlnc was validated to act as a competing endogenous RNA (ceRNA) that stabilizes the expression of HES6 by downregulating miR-5001-5p.

Conclusion

CCMAlnc/miR-5001-5p/HES6 signaling is strongly activated to promote CRC malignance. CCMAlnc is defined as a potential candidate biomarker for metastasis prediction in CRC patients and as a potential therapeutic target for CRC treatment.

Development of a 15-gene signature for predicting prognosis in advanced colorectal cancer

Advanced colorectal cancer (CRC) is a significant cause of cancer mortality, with a poor prognosis. Here, we identified a novel prognostic signature for predicting survival of advanced CRC. Advanced CRC data were used (training set: n = 267 and validation set: n = 264). The survival analyses were investigated. The functional analysis of the prognostic signature was examined. In this study, our 15-gene signature was established and was an independent prognostic factor of advanced CRC. Stratification analyses also showed that this signature was still powerful for survival prediction in each stratum of age, gender, stage, and metastasis status. In mechanism, our signature involved in DNA replication, DNA damage, and cell cycle. Therefore, our findings suggested that this 15-gene signature has prognostic and predictive value in advanced CRC, which could be further used in personalized therapy for advanced CRC.

A 12-immune cell signature to predict relapse and guide chemotherapy for stage II colorectal cancer

The management of stage II colorectal cancer is still difficult. We aimed to construct a new immune cell-associated signature for prognostic evaluation and guiding chemotherapy in stage II colorectal cancer. We used the "Cell Type Identification by Estimating Relative Subsets of RNA Transcripts" (CIBERSORT) method to estimate the fraction of 22 immune cells by analyzing bulk tumor transcriptomes and a LASSO Cox regression model to select the prognostic immune cells. A 12-immune cell prognostic classifier, ISCRC, was built, which could successfully discriminate the high-risk patients in the training cohort (GSE39582: HR = 3.16, 95% CI: 1.85-5.40, P < 0.0001) and another independent cohorts (GSE14333: HR = 3.47, 95% CI: 1.18-10.15, P =0.0167). The receiver operating characteristic analysis revealed that the AUC of the ISCRC model was significantly greater than that of oncotypeDX model (0.7111 versus 0.5647, p=0.0152). We introduced the propensity score matching analysis to eliminate the selection bias; survival analysis showed relatively poor prognosis after chemotherapy in stage II CRC patients. Furthermore, a nomogram was built for clinicians and did well in the calibration plots. In conclusion, this immune cell-based signature could improve prognostic prediction and may help guide chemotherapy in stage II colorectal cancer patients.

MLH1 Deficiency Induces Cetuximab Resistance in Colon Cancer via Her-2/PI3K/AKT Signaling

The rapid onset of resistance to cetuximab (CTX) limits its clinical utility in colorectal cancer (CRC) patients. This study aims to understand a potential role of mismatch repair gene mutL homolog 1 (MLH1) in CTX response. Functional analysis of MLH1 in Her-2/phosphoinositide 3-kinases (PI3K)/PKB protein kinase (AKT)-regulated CTX sensitivity is performed using human CRC specimens, CRC cell lines with different MLH1 expression levels, and a subcutaneous xenograft model. Overexpression, knockdown, small interfering RNA, and inhibitors are used to examine the role of MLH1 and HER-2 downstream signaling and apoptotic targets in CTX sensitivity. Reduced MLH1 expression is correlated with unfavorable prognosis in cetuximab-treated patients. MLH1 loss decreases CTX sensitivity through Her-2/PI3K/AKT signaling and apoptosis resistance in culture and in xenografts, while MLH1 overexpression increases CTX sensitivity. Blocking Her-2 signaling increases CTX sensitivity of microsatellite instability CRC in vitro and in vivo. MLH1 loss induces activation of Her-2/PI3K/AKT signaling and leads to cetuximab resistance in colon cancer.

Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks

Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the prediction of proteins involved in this disease is a trending topic in drug design. This work is proposing accurate prediction classifier for BC proteins using six sets of protein sequence descriptors and 13 machine-learning methods. After using a univariate feature selection for the mix of five descriptor families, the best classifier was obtained using multilayer perceptron method (artificial neural network) and 300 features. The performance of the model is demonstrated by the area under the receiver operating characteristics (AUROC) of 0.980 ± 0.0037, and accuracy of 0.936 ± 0.0056 (3-fold cross-validation). Regarding the prediction of 4,504 cancer-associated proteins using this model, the best ranked cancer immunotherapy proteins related to BC were RPS27, SUPT4H1, CLPSL2, POLR2K, RPL38, AKT3, CDK3, RPS20, RASL11A and UBTD1; the best ranked metastasis driver proteins related to BC were S100A9, DDA1, TXN, PRNP, RPS27, S100A14, S100A7, MAPK1, AGR3 and NDUFA13; and the best ranked RNA-binding proteins related to BC were S100A9, TXN, RPS27L, RPS27, RPS27A, RPL38, MRPL54, PPAN, RPS20 and CSRP1. This powerful model predicts several BC-related proteins that should be deeply studied to find new biomarkers and better therapeutic targets. Scripts can be downloaded at https://github.com/muntisa/neural-networks-for-breast-cancer-proteins.

Prediction of tumor metastasis from sequencing data in the era of genome sequencing

Tumor metastasis is the key reason for the high mortality rate of tumor. Growing number of scholars have begun to pay attention to the research on tumor metastasis and have achieved satisfactory results in this field. The advent of the era of sequencing has enabled us to study cancer metastasis at the molecular level, which is essential for understanding the molecular mechanism of metastasis, identifying diagnostic markers and therapeutic targets and guiding clinical decision-making. We reviewed the metastasis-related studies using sequencing data, covering detection of metastasis origin sites, determination of metastasis potential and identification of distal metastasis sites. These findings include the discovery of relevant markers and the presentation of prediction tools. Finally, we discussed the challenge of studying metastasis considering the difficulty of obtaining metastatic cancer data, the complexity of tumor heterogeneity and the uncertainty of sample labels.

PAICS, a Purine Nucleotide Metabolic Enzyme, is Involved in Tumor Growth and the Metastasis of Colorectal Cancer

The identification of colorectal cancer (CRC) molecular targets is needed for the development of drugs that improve patient survival. We investigated the functional role of phosphoribosylaminoimidazole carboxylase, phosphoribosylaminoimidazole succinocarboxamide synthetase (PAICS), a de novo purine biosynthetic enzyme involved in DNA synthesis, in CRC progression and metastasis by using cell and animal models. Its clinical utility was assessed in human CRC samples. The expression of PAICS was regulated by miR-128 and transcriptionally activated by Myc in CRC cells. Increased expression of PAICS was involved in proliferation, migration, growth, and invasion of CRC cells irrespective of the p53 and microsatellite status. In mice, the depletion of PAICS in CRC cells led to reduced tumor growth and metastatic cell dissemination to the liver, lungs, and bone. Positron emission tomography imaging showed significantly reduced metastatic lesions in stable PAICS knockdown CRC cells. In cells with PAICS knockdown, there was upregulation of the epithelial mesenchymal transition marker, E-cadherin, and bromodomain inhibitor, JQ1, can target its increased expression by blocking Myc. PAICS was overexpressed in 70% of CRCs, and was associated with poor 5-year survival independent of the pathologic stage, patient’s race, gender, and age. Overall, the findings point to the usefulness of PAICS targeting in the treatment of aggressive colorectal cancer.

Block of proliferation 1 promotes cell migration and invasion in human colorectal cancer cells via the JNK pathway

Metastasis is one of the most common causes of death in patients with colorectal cancer (CRC). Block of proliferation 1 (BOP1) regulates tumorigenesis, epithelial‐to‐mesenchymal transition, migration, metastasis, and drug resistance in several tumor types. However, the role of BOP1 in the regulation of colorectal cancer cell migration and invasion is still largely unclear. In this study, the results of immunohistochemistry showed that BOP1 was upregulated in our cohort of CRC patients. BOP1 knockdown inhibited the migration and invasion of CRC cells, confirmed by the downregulation of the mRNA levels of MMP‐2 and MMP‐9. The overexpression of BOP1 in CRC cells exerted the opposite effect. SP600125, an inhibitor of JNK signaling, partially abolished the BOP1 overexpression‐mediated increase in the migratory and invasive ability of CRC cells. Our results indicated that BOP1 is an important regulator of CRC cell invasion and migration, predominantly through the JNK signaling pathway.

PTPRS drives adaptive resistance to MEK/ERK inhibitors through SRC

PTPRS is the most commonly mutated receptor tyrosine phosphatase in colorectal cancer (CRC). PTPRS has been shown to directly affect ERK and regulate its activation and nuclear localization. Here we identify that PTPRS may play a significant role in developing adaptive resistance to MEK/ERK inhibitors (MEKi/ERKi) through SRC activation. Moreover, we demonstrate a new clinical approach to averting adaptive resistance through the use of the SRC inhibitor, dasatinib. Our data suggest the potential for dasatinib to enhance the efficacy of MEKi and ERKi by preventing adaptive resistance pathways operating through SRC.

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.

Repurposing EGFR Inhibitor Utility in Colorectal Cancer in Mutant APC and TP53 Subpopulations

BACKGROUND

EGFR is a major therapeutic target for colorectal cancer. Currently, extended RAS/RAF testing identifies only nonresponders to EGFR inhibitors (EGFRi). We aimed to develop a mutation signature that further refines drug-sensitive subpopulations to improve EGFRi outcomes.

METHODS

A prespecified, 203-gene expression signature score measuring cetuximab sensitivity (CTX-S) was validated with two independent clinical trial datasets of cetuximab-treated patients with colorectal cancer (n = 44 and n = 80) as well as an in vitro dataset of 147 cell lines. The CTX-S score was then used to decipher mutated genes that predict EGFRi sensitivity. The predictive value of the identified mutation signature was further validated by additional independent datasets.

RESULTS

Here, we report the discovery of a 2-gene (APC+TP53) mutation signature that was useful in identifying EGFRi-sensitive colorectal cancer subpopulations. Mutant APC+TP53 tumors were more predominant in left- versus right-sided colorectal cancers (52% vs. 21%, P = 0.0004), in microsatellite stable (MSS) versus microsatellite instable (MSI) cases (47% vs. 2%, P < 0.0001), and in the consensus molecular subtype 2 versus others (75% vs. 37%, P < 0.0001). Moreover, mutant APC+TP53 tumors had favorable outcomes in two cetuximab-treated patient-derived tumor xenograft (PDX) datasets (P = 0.0277, n = 52; P = 0.0008, n = 98).

CONCLUSIONS

Our findings suggest that the APC and TP53 combination mutation may account for the laterality of EGFRi sensitivity and provide a rationale for refining treated populations. The results also suggest addition of APC+TP53 sequencing to extended RAS/RAF testing that may directly increase the response rates of EGFRi therapy in selected patients.

IMPACT

These findings, if further validated through clinical trials, could also expand the utility of EGFRi therapies that are currently underutilized.

PTPRS Regulates Colorectal Cancer RAS Pathway Activity by Inactivating Erk and Preventing Its Nuclear Translocation

Colorectal cancer (CRC) growth and progression is frequently driven by RAS pathway activation through upstream growth factor receptor activation or through mutational activation of KRAS or BRAF. Here we describe an additional mechanism by which the RAS pathway may be modulated in CRC. PTPRS, a receptor-type protein tyrosine phosphatase, appears to regulate RAS pathway activation through ERK. PTPRS modulates ERK phosphorylation and subsequent translocation to the nucleus. Native mutations in PTPRS, present in ~10% of CRC, may reduce its phosphatase activity while increasing ERK activation and downstream transcriptional signaling.

Role of TXNDC5 in tumorigenesis of colorectal cancer cells: In vivo and in vitro evidence

Thioredoxin domain‑containing 5 (TXNDC5) is reportedly overexpressed in colorectal cancer (CRC) and is therefore considered an oncogene. However, the role of TXNDC5 in CRC tumorigenesis remains unclear. The present study aimed to explore the role of TXNDC5 in CRC tumorigenesis in vitro and in vivo under hypoxic and normoxic conditions. Analyses of patient tissue samples revealed a positive association between the expression of hypoxia‑inducible factor‑1α (HIF‑1α) or TXNDC5 and the TNM stage of CRC. In addition, a positive correlation between the expression levels of HIF‑1α and TXNDC5 was observed in CRC tissues. Furthermore, culturing RKO and HCT‑116 human CRC cell lines under hypoxic conditions significantly increased the expression levels of HIF‑1α and TXNDC5, whereas knockdown of HIF‑1α abolished the hypoxia‑induced expression of TXNDC5. Knockdown of TXNDC5 significantly decreased cell proliferation and colony formation, and incre-ased apoptosis of both cell lines. Furthermore, knockdown of TXNDC5 markedly increased hypoxia‑induced reactive oxygen species (ROS) generation, and the expression of hypoxia‑induced endoplasmic reticulum stress (ER) markers (CCAAT‑enhancer‑binding protein homologous protein, glucose‑regulated protein 78 and activating transcription factor 4) and apoptotic markers (B‑cell lymphoma 2‑associated X protein and cleaved caspase‑8). In addition, the expression levels of TXNDC5 were significantly increased in tumor tissues compared with in adenoma and normal tissues in a mouse model of CRC tumorigenesis. In conclusion, the in vivo data demonstrated that TXNDC5 is overexpressed in CRC tissues, and this overexpression may be associated with unfavorable clinicopathological features. The in vitro data indicated that hypoxia may induce TXNDC5 expression via upregulating HIF‑1α; this effect promoted CRC cell proliferation and survival under hypoxic conditions, likely via inhibiting hypoxia‑induced ROS/ER stress signaling. These findings suggested that TXNDC5 functions as an important stress survival factor to maintain tumorigenesis of CRC cells under hypoxia by regulating hypoxia‑induced ROS/ER stress signaling. The present study provided novel insights into the role of TXNDC5 in the tumorigenesis of CRC.

lncRNA MIR100HG-derived miR-100 and miR-125b mediate cetuximab resistance via Wnt/β-catenin signaling

De novo and acquired resistance, which are largely attributed to genetic alterations, are barriers to effective anti-epidermal-growth-factor-receptor (EGFR) therapy. To generate cetuximab-resistant cells, we exposed cetuximab-sensitive colorectal cancer cells to cetuximab in three-dimensional culture. Using whole-exome sequencing and transcriptional profiling, we found that the long non-coding RNA MIR100HG and two embedded microRNAs, miR-100 and miR-125b, were overexpressed in the absence of known genetic events linked to cetuximab resistance. MIR100HG, miR-100 and miR-125b overexpression was also observed in cetuximab-resistant colorectal cancer and head and neck squamous cell cancer cell lines and in tumors from colorectal cancer patients that progressed on cetuximab. miR-100 and miR-125b coordinately repressed five Wnt/β-catenin negative regulators, resulting in increased Wnt signaling, and Wnt inhibition in cetuximab-resistant cells restored cetuximab responsiveness. Our results describe a double-negative feedback loop between MIR100HG and the transcription factor GATA6, whereby GATA6 represses MIR100HG, but this repression is relieved by miR-125b targeting of GATA6. These findings identify a clinically actionable, epigenetic cause of cetuximab resistance.

Recurrence-associated gene signature optimizes recurrence-free survival prediction of colorectal cancer

High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis‐related mRNAs may potentially enrich genes with the ability to predict cancer recurrence, therefore we attempted to build a recurrence‐associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model (least absolute shrinkage and selection operator method) was employed. Using this method, a 13‐mRNA signature was identified and then validated in two independent Gene Expression Omnibus cohorts. This classifier could successfully discriminate the high‐risk patients in discovery cohort [hazard ratio (HR) = 5.27, 95% confidence interval (CI) 2.30–12.08, P < 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR = 4.55, 95% CI 2.18–9.508, P < 0.0001; GSE33113: HR = 3.26, 95% CI 2.16–9.16, P = 0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under ROC curve of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, and did well in the calibration plots. Furthermore, this 13‐mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single‐sample gene‐set enrichment analysis revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high‐risk patients. In conclusion, this 13‐mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.

Interrogating Patient-level Genomics and Mouse Phenomics towards Understanding Cytokines in Colorectal Cancer Metastasis

Background: Colorectal cancer is the second leading cancer-related death worldwide and a majority of patients die from metastasis. Chronic intestinal inflammation plays an important role in tumor progression of colorectal cancer. However, few study works on systematically predicting colorectal cancer metastasis using inflammatory cytokine genes. Results: We developed a supervised machine learning approach to predict colorectal cancer tumor progression using patient level genomic features. To better understand the role of cytokines, we integrated the metastatic-related genes from mouse phenotypic data. In addition, pathway analysis and network visualization were also applied to top significant genes ranked by feature weights of the final prediction model. The combined model of cytokines and mouse phenotypes achieved a predictive accuracy of 75.54%, higher than the model based on mouse phenotypes independently (70.42%, p-value<0.05). In additional, the combined model outperformed the model based on the existing metastatic-related epithelial-to-mesenchymal transition (EMT) genes (75.54% vs. 71.61%, p-value<0.05). We also observed that the most important cytokine gene features of the our model interact with the cancer driver genes and are highly associated with the colorectal cancer metastasis signaling pathway. Conclusion: We developed a combined model using both cytokine and mouse phenotype information to predict colorectal cancer metastasis. The results suggested that the inflammatory cytokines increase the power of predicting metastasis. We also systematically demonstrated the critical role of cytokines in progression of colorectal tumor.

Quantitative imaging outperforms molecular markers when predicting response to chemoradiotherapy for rectal cancer

BACKGROUND AND PURPOSE

To explore the integration of imaging and molecular data for response prediction to chemoradiotherapy (CRT) for rectal cancer.

MATERIAL AND METHODS

Eighty-five rectal cancer patients underwent preoperative CRT. ¹⁸F-FDG PET/CT and diffusion-weighted imaging (DWI) were acquired before (TP1) and during CRT (TP2) and prior to surgery (TP3). Inflammatory cytokines and gene expression were analysed. Tumour response was defined as ypT0-1N0. Multivariate models were built combining the obtained parameters. Final models were calculated on the data combination with the highest AUC.

RESULTS

Twenty-two patients (26%) achieved ypT0-1N0 response. ¹⁸F-FDG PET/CT had worse predictive performance than DWI and T2-volumetry (AUC 0.61±0.04, 0.72±0.03, and 0.72±0.02, respectively). Combining all imaging parameters increased the AUC to 0.81±0.03. Adding cytokines or gene expression did not improve the AUC (AUC of 0.72±0.06 and 0.79±0.04 respectively). Final models combining ¹⁸F-FDG PET/CT, DWI, and T2-weighted volumetry at all TPs and using only TP1 and TP3, allowed ypT0-1N0 prediction with a 75% sensitivity, 94% specificity and PPV of 80%.

CONCLUSIONS

Combining ¹⁸F-FDG PET/CT, DWI, and T2-weighted MRI volumetry obtained before CRT and prior to surgery may help physicians in selecting rectal cancer patients for organ-preservation.

Three-dimensional culture system identifies a new mode of cetuximab resistance and disease-relevant genes in colorectal cancer

We previously reported that single cells from a human colorectal cancer (CRC) cell line (HCA-7) formed either hollow single-layered polarized cysts or solid spiky masses when plated in 3D in type-I collagen. To begin in-depth analyses into whether clonal cysts and spiky masses possessed divergent properties, individual colonies of each morphology were isolated and expanded. The lines thus derived faithfully retained their parental cystic and spiky morphologies and were termed CC (cystic) and SC (spiky), respectively. Although both CC and SC expressed EGF receptor (EGFR), the EGFR-neutralizing monoclonal antibody, cetuximab, strongly inhibited growth of CC, whereas SC was resistant to growth inhibition, and this was coupled to increased tyrosine phosphorylation of MET and RON. Addition of the dual MET/RON tyrosine kinase inhibitor, crizotinib, restored cetuximab sensitivity in SC. To further characterize these two lines, we performed comprehensive genomic and transcriptomic analysis of CC and SC in 3D. One of the most up-regulated genes in CC was the tumor suppressor 15-PGDH/HPGD, and the most up-regulated gene in SC was versican (VCAN) in 3D and xenografts. Analysis of a CRC tissue microarray showed that epithelial, but not stromal, VCAN staining strongly correlated with reduced survival, and combined epithelial VCAN and absent HPGD staining portended a poorer prognosis. Thus, with this 3D system, we have identified a mode of cetuximab resistance and a potential prognostic marker in CRC. As such, this represents a potentially powerful system to identify additional therapeutic strategies and disease-relevant genes in CRC and possibly other solid tumors.

Adaptation of a RAS pathway activation signature from FF to FFPE tissues in colorectal cancer

BACKGROUND

The KRAS gene is mutated in about 40 % of colorectal cancer (CRC) cases, which has been clinically validated as a predictive mutational marker of intrinsic resistance to anti-EGFR inhibitor (EGFRi) therapy. Since nearly 60 % of patients with a wild type KRAS fail to respond to EGFRi combination therapies, there is a need to develop more reliable molecular signatures to better predict response. Here we address the challenge of adapting a gene expression signature predictive of RAS pathway activation, created using fresh frozen (FF) tissues, for use with more widely available formalin fixed paraffin-embedded (FFPE) tissues.

METHODS

In this study, we evaluated the translation of an 18-gene RAS pathway signature score from FF to FFPE in 54 CRC cases, using a head-to-head comparison of five technology platforms. FFPE-based technologies included the Affymetrix GeneChip (Affy), NanoString nCounter™ (NanoS), Illumina whole genome RNASeq (RNA-Acc), Illumina targeted RNASeq (t-RNA), and Illumina stranded Total RNA-rRNA-depletion (rRNA).

RESULTS

Using Affy_FF as the "gold" standard, initial analysis of the 18-gene RAS scores on all 54 samples shows varying pairwise Spearman correlations, with (1) Affy_FFPE (r = 0.233, p = 0.090); (2) NanoS_FFPE (r = 0.608, p < 0.0001); (3) RNA-Acc_FFPE (r = 0.175, p = 0.21); (4) t-RNA_FFPE (r = -0.237, p = 0.085); (5) and t-RNA (r = -0.012, p = 0.93). These results suggest that only NanoString has successful FF to FFPE translation. The subsequent removal of identified "problematic" samples (n = 15) and genes (n = 2) further improves the correlations of Affy_FF with three of the five technologies: Affy_FFPE (r = 0.672, p < 0.0001); NanoS_FFPE (r = 0.738, p < 0.0001); and RNA-Acc_FFPE (r = 0.483, p = 0.002).

CONCLUSIONS

Of the five technology platforms tested, NanoString technology provides a more faithful translation of the RAS pathway gene expression signature from FF to FFPE than the Affymetrix GeneChip and multiple RNASeq technologies. Moreover, NanoString was the most forgiving technology in the analysis of samples with presumably poor RNA quality. Using this approach, the RAS signature score may now be reasonably applied to FFPE clinical samples.

The prognostic potential of alternative transcript isoforms across human tumors

BACKGROUND

Phenotypic changes during cancer progression are associated with alterations in gene expression, which can be exploited to build molecular signatures for tumor stage identification and prognosis. However, it is not yet known whether the relative abundance of transcript isoforms may be informative for clinical stage and survival.

METHODS

Using information theory and machine learning methods, we integrated RNA sequencing and clinical data from The Cancer Genome Atlas project to perform the first systematic analysis of the prognostic potential of transcript isoforms in 12 solid tumors to build new signatures for stage and prognosis. This study was also performed in breast tumors according to estrogen receptor (ER) status and melanoma tumors with proliferative and invasive phenotypes.

RESULTS

Transcript isoform signatures accurately separate early from late-stage groups and metastatic from non-metastatic tumors, and are predictive of the survival of patients with undetermined lymph node invasion or metastatic status. These signatures show similar, and sometimes better, accuracies compared with known gene expression signatures in retrospective data and are largely independent of gene expression changes. Furthermore, we show frequent transcript isoform changes in breast tumors according to ER status, and in melanoma tumors according to the invasive or proliferative phenotype, and derive accurate predictive models of stage and survival within each patient subgroup.

CONCLUSIONS

Our analyses reveal new signatures based on transcript isoform abundances that characterize tumor phenotypes and their progression independently of gene expression. Transcript isoform signatures appear especially relevant to determine lymph node invasion and metastasis and may potentially contribute towards current strategies of precision cancer medicine.

A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC

Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.