Microarray-based response prediction in esophageal adenocarcinoma

Circulating Biomarkers in Predicting Pathological Response to Neoadjuvant Therapy for Colorectal Cancer

Circulating biomarkers show promise in the management of many cancers. They have become the novel non-invasive approach to complement the current strategies in colorectal cancer (CRC) management. Their ability in guiding diagnosis, evaluating response to treatment, screening and prognosis is phenomenal, especially when it comes to their minimally invasive nature. These “liquid biopsies,” which show potential for replacing invasive surgical biopsies, provide useful information on the primary and metastatic disease by providing an insight into cancer biology. Analysis of blood and body fluids for circulating tumour DNA (ctDNA), carcinoembryonic antigen (CEA), circulating tumour cells (CTC), or circulating micro RNA (miRNA) shows potential for improving CRC management. Recognizing a predictive model to assess response to neoadjuvant chemotherapy would help in better patient selection. This review was conducted with the aim of outlining the use of circulatory biomarkers in current practice and their effectiveness in the management of patients having CRC with a focus on response to neoadjuvant therapy.

Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma

(1) Background: Oesophageal cancers are often late-presenting and have a poor 5-year survival rate. The standard treatment of oesophageal adenocarcinomas involves neoadjuvant chemotherapy with or without radiotherapy followed by surgery. However, less than one third of patients respond to neoadjuvant therapy, thereby unnecessarily exposing patients to toxicity and deconditioning. Hence, there is an urgent need for biomarkers to predict response to neoadjuvant therapy. This review explores the current biomarker landscape. (2) Methods: MEDLINE, EMBASE and ClinicalTrial databases were searched with key words relating to “predictive biomarker”, “neoadjuvant therapy” and “oesophageal adenocarcinoma” and screened as per the inclusion and exclusion criteria. All peer-reviewed full-text articles and conference abstracts were included. (3) Results: The search yielded 548 results of which 71 full-texts, conference abstracts and clinical trials were eligible for review. A total of 242 duplicates were removed, 191 articles were screened out, and 44 articles were excluded. (4) Discussion: Biomarkers were discussed in seven categories including imaging, epigenetic, genetic, protein, immunologic, blood and serum-based with remaining studies grouped in a miscellaneous category. (5) Conclusion: Although promising markers and novel methods have emerged, current biomarkers lack sufficient evidence to support clinical application. Novel approaches have been recommended to assess predictive potential more efficiently.

Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas

Tumor progression involves an intricate interplay between malignant cells and their surrounding tumor microenvironment (TME) at specific sites. The TME is dynamic and is composed of stromal, parenchymal, and immune cells, which mediate cancer progression and therapy resistance. Evidence from preclinical and clinical studies revealed that TME targeting and reprogramming can be a promising approach to achieve anti-tumor effects in several cancers, including in GEA. Thus, it is of great interest to use modern technology to understand the relevant components of programming the TME. Here, we discuss the approach of machine learning, which recently gained increasing interest recently because of its ability to measure tumor parameters at the cellular level, reveal global features of relevance, and generate prognostic models. In this review, we discuss the relevant stromal composition of the TME in GEAs and discuss how they could be integrated. We also review the current progress in the application of machine learning in different medical disciplines that are relevant for the management and study of GEA.

Transcriptomic biomarkers for predicting response to neoadjuvant treatment in oesophageal cancer

Oesophageal cancer is a devastating disease with poor outcomes and is the sixth leading cause of cancer death worldwide. In the setting of resectable disease, there is clear evidence that neoadjuvant chemotherapy and chemoradiotherapy result in improved survival. Disappointingly, only 15%-30% of patients obtain a histopathological response to neoadjuvant therapy, often at the expense of significant toxicity. There are no predictive biomarkers in routine clinical use in this setting and the ability to stratify patients for treatment could dramatically improve outcomes. In this review, we aim to outline current progress in evaluating predictive transcriptomic biomarkers for neoadjuvant therapy in oesophageal cancer and discuss the challenges facing biomarker development in this setting. We place these issues in the wider context of recommendations for biomarker development and reporting. The majority of studies focus on messenger RNA (mRNA) and microRNA (miRNA) biomarkers. These studies report a range of different genes involved in a wide variety of pathways and biological processes, and this is explained to a large extent by the different platforms and analysis methods used. Many studies are also vastly underpowered so are not suitable for identifying a candidate biomarker. Multiple molecular subtypes of oesophageal cancer have been proposed, although little is known about how these relate to clinical outcomes. We anticipate that the accumulating wealth of genomic and transcriptomic data and clinical trial collaborations in the coming years will provide unique opportunities to stratify patients in this poor-prognosis disease and recommend that future biomarker development incorporates well-designed retrospective and prospective analyses.

An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma

No clinically available biomarkers can predict pathological complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) with neoadjuvant chemoradiotherapy (nCRT). Considering that antitumor immunity status is an important determinant for nCRT, we performed an integrative analysis of immune-related gene profiles from pretreatment biopsies and constructed the first individualized immune signature for pCR and outcome prediction of ESCCs through a multicenter analysis. During the discovery phase, 14 differentially expressed immune-related genes (DEIGs) with greater than a twofold change between pCRs and less than pCRs (<pCRs) were revealed from 28 pretreatment tumors in a Guangzhou cohort using microarray data. Ten DEIGs were verified by qPCR from 30 cases in a Beijing discovery cohort. Then, a four-gene-based immune signature (SERPINE1, MMP12, PLAUR, and EPS8) was built based on the verified DEIGs from 71 cases in a Beijing training cohort, and achieved a high accuracy with an area under the receiver operating characteristic curve (AUC) of 0.970. The signature was further validated in an internal validation cohort and an integrated external cohort (Zhengzhou and Anyang cohorts) with AUCs of 0.890 and 0.859, respectively. Importantly, a multivariate analysis showed that the signature was the only independent predictor for pCR. In addition, patients with high predictive scores showed significantly longer overall and relapse-free survival across multiple centers (P < 0.05). This is the first, validated, and clinically applicable individualized immune signature of pCR and outcome prediction for ESCCs with nCRT. Further prospective validation may facilitate the combination of nCRT and immunotherapy.

Patients with Non-response to Neoadjuvant Chemoradiation for Esophageal Cancer Have No Survival Advantage over Patients Undergoing Primary Esophagectomy

BACKGROUND

Survival for patients with locally advanced esophageal cancer remains dismal. Non-response to neoadjuvant chemoradiation (nCRT) portends worse survival. We hypothesized that patients undergoing up-front esophagectomy may have better survival than those who do not respond to nCRT.

METHODS

We identified all patients undergoing esophagectomy with a pathologic stage of II or greater at our institution between 1994 and 2015 and separated them into two groups: those who received nCRT and those undergoing up-front esophagectomy. The neoadjuvant group was further separated into patients downstaged to pathologic stage 0 or I (responders) and patients with either the same or higher pathologic stage after nCRT, or with pathologic stage II disease or greater (non-responders). Overall survival was compared between groups using Kaplan-Meier statistics. Covariate-adjusted Cox modeling was used to estimate hazard ratios (HR) for mortality associated with non-response.

RESULTS

Overall, 287 patients met inclusion criteria. Fifty-nine percent of the responders had pathologic complete response (pCR). The majority of non-responders and primary esophagectomy patients had stage II or III disease (94%). Median survival was 58.3 months in responders, 23.9 months in non-responders, and 29.1 months in primary esophagectomy patients (p < 0.01). The HR for mortality associated with non-response was 1.82 compared to response to nCRT (p < 0.01) and 1.09 compared to primary esophagectomy (p = 0.71).

CONCLUSIONS

In patients with esophageal cancer who do not respond to nCRT, neoadjuvant therapy may represent a toxic and costly treatment modality that does not improve survival and may delay potentially curative resection. Further research is needed to identify potential non-responders with advanced resectable disease and allow individual tailoring of pre-surgical decision-making.

Immune activation by DNA damage predicts response to chemotherapy and survival in oesophageal adenocarcinoma

OBJECTIVE

Current strategies to guide selection of neoadjuvant therapy in oesophageal adenocarcinoma (OAC) are inadequate. We assessed the ability of a DNA damage immune response (DDIR) assay to predict response following neoadjuvant chemotherapy in OAC.

DESIGN

Transcriptional profiling of 273 formalin-fixed paraffin-embedded prechemotherapy endoscopic OAC biopsies was performed. All patients were treated with platinum-based neoadjuvant chemotherapy and resection between 2003 and 2014 at four centres in the Oesophageal Cancer Clinical and Molecular Stratification consortium. CD8 and programmed death ligand 1 (PD-L1) immunohistochemical staining was assessed in matched resection specimens from 126 cases. Kaplan-Meier and Cox proportional hazards regression analysis were applied according to DDIR status for recurrence-free survival (RFS) and overall survival (OS).

RESULTS

A total of 66 OAC samples (24%) were DDIR positive with the remaining 207 samples (76%) being DDIR negative. DDIR assay positivity was associated with improved RFS (HR: 0.61; 95% CI 0.38 to 0.98; p=0.042) and OS (HR: 0.52; 95% CI 0.31 to 0.88; p=0.015) following multivariate analysis. DDIR-positive patients had a higher pathological response rate (p=0.033), lower nodal burden (p=0.026) and reduced circumferential margin involvement (p=0.007). No difference in OS was observed according to DDIR status in an independent surgery-alone dataset.DDIR-positive OAC tumours were also associated with the presence of CD8+ lymphocytes (intratumoural: p<0.001; stromal: p=0.026) as well as PD-L1 expression (intratumoural: p=0.047; stromal: p=0.025).

CONCLUSION

The DDIR assay is strongly predictive of benefit from DNA-damaging neoadjuvant chemotherapy followed by surgical resection and is associated with a proinflammatory microenvironment in OAC.

Epigenomic profiling of non-small cell lung cancer xenografts uncover LRP12 DNA methylation as predictive biomarker for carboplatin resistance

Background

Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide and is primarily treated with radiation, surgery, and platinum-based drugs like cisplatin and carboplatin. The major challenge in the treatment of NSCLC patients is intrinsic or acquired resistance to chemotherapy. Molecular markers predicting the outcome of the patients are urgently needed.

Methods

Here, we employed patient-derived xenografts (PDXs) to detect predictive methylation biomarkers for platin-based therapies. We used MeDIP-Seq to generate genome-wide DNA methylation profiles of 22 PDXs, their parental primary NSCLC, and their corresponding normal tissues and complemented the data with gene expression analyses of the same tissues. Candidate biomarkers were validated with quantitative methylation-specific PCRs (qMSP) in an independent cohort.

Results

Comprehensive analyses revealed that differential methylation patterns are highly similar, enriched in PDXs and lung tumor-specific when comparing differences in methylation between PDXs versus primary NSCLC. We identified a set of 40 candidate regions with methylation correlated to carboplatin response and corresponding inverse gene expression pattern even before therapy. This analysis led to the identification of a promoter CpG island methylation of LDL receptor-related protein 12 (LRP12) associated with increased resistance to carboplatin. Validation in an independent patient cohort (n = 35) confirmed that LRP12 methylation status is predictive for therapeutic response of NSCLC patients to platin therapy with a sensitivity of 80% and a specificity of 84% (p < 0.01). Similarly, we find a shorter survival time for patients with LRP12 hypermethylation in the TCGA data set for NSCLC (lung adenocarcinoma).

Conclusions

Using an epigenome-wide sequencing approach, we find differential methylation patterns from primary lung cancer and PDX-derived cancers to be very similar, albeit with a lower degree of differential methylation in primary tumors. We identify LRP12 DNA methylation as a powerful predictive marker for carboplatin resistance. These findings outline a platform for the identification of epigenetic therapy resistance biomarkers based on PDX NSCLC models.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0562-1) contains supplementary material, which is available to authorized users.

Predictive biomarkers for the treatment of resectable esophageal and esophago-gastric junction adenocarcinoma: from hypothesis generation to clinical validation

INTRODUCTION

Esophageal and esophago-gastric junction (EGJ) adenocarcinomas remain a major health problem worldwide with a worryingly increasing incidence. Recent trials indicate survivals benefit for preoperative or perioperative chemoradiotherapy compared to surgery alone. Beside standard chemoradiotherapy regimens, new therapeutic approaches with targeted therapies have been proposed for the treatment of resectable disease. However, clinical outcomes remain extremely poor due to drug resistance phenomena. The failure of these approaches could be partially ascribed to their incorrect application in patients. Therefore, the identification of strong biomarkers for optimal patient management is urgently needed. Areas covered: This review aims to summarize and critically discuss the most relevant findings regarding predictive biomarker development for neoadjuvant treatment of resectable esophageal and esophago-gastric junction adenocarcinoma patients. Expert commentary: Optimizing the currently available therapeutic modalities through a more accurate selection of patients may avoid the use of ineffective and potentially toxic treatments. During the last decade, the advent of high-throughput '-omics' technologies has set the basis for a new biomarker discovery approach from 'molecule by molecule' screening towards a large-scale systematic screening process with exponential increases in putative biomarkers, which often failed to provide adequate clinical validation.

Overcoming multiple myeloma drug resistance in the era of cancer 'omics'

Multiple myeloma (MM) is among the most compelling examples of cancer in which research has markedly improved the length and quality of lives of those afflicted. Research efforts have led to 18 newly approved treatments over the last 12 years, including seven in 2015. However, despite significant improvement in overall survival, MM remains incurable as most patients inevitably, yet unpredictably, develop refractory disease. Recent advances in high-throughput 'omics' techniques afford us an unprecedented opportunity to (1) understand drug resistance at the genomic, transcriptomic, and proteomic level; (2) discover novel diagnostic, prognostic, and therapeutic biomarkers; (3) develop novel therapeutic targets and rational drug combinations; and (4) optimize risk-adapted strategies to circumvent drug resistance, thus bringing us closer to a cure for MM. In this review, we provide an overview of 'omics' technologies in MM biomarker and drug discovery, highlighting recent insights into MM drug resistance gleaned from the use of 'omics' techniques. Moving from the bench to bedside, we also highlight future trends in MM, with a focus on the potential use of 'omics' technologies as diagnostic, prognostic, or response/relapse monitoring tools to guide therapeutic decisions anchored upon highly individualized, targeted, durable, and rationally informed combination therapies with curative potential.

Prognostic gene expression profiling in esophageal cancer: a systematic review

Background

Individual variability in prognosis of esophageal cancer highlights the need for advances in personalized therapy. This systematic review aimed at elucidating the prognostic role of gene expression profiles and at identifying gene signatures to predict clinical outcome.

Methods

A systematic search of the Medline, Embase and the Cochrane library databases (2000-2015) was performed. Articles associating gene expression profiles in patients with esophageal adenocarcinoma or squamous cell carcinoma to survival, response to chemo(radio)therapy and/or lymph node metastasis were identified. Differentially expressed genes and gene signatures were extracted from each study and combined to construct a list of prognostic genes per outcome and histological tumor type.

Results

This review includes a total of 22 studies. Gene expression profiles were related to survival in 9 studies, to response to chemo(radio)therapy in 7 studies, and to lymph node metastasis in 9 studies. The studies proposed many differentially expressed genes. However, the findings were heterogeneous and only 12 (ALDH1A3, ATR, BIN1, CSPG2, DOK1, IFIT1, IFIT3, MAL, PCP4, PHB, SPP1) of the 1.112 reported genes were identified in more than 1 study. Overall, 16 studies reported a prognostic gene signature, which was externally validated in 10 studies.

Conclusion

This systematic review shows heterogeneous findings in associating gene expression with clinical outcome in esophageal cancer. Larger validated studies employing RNA next-generation sequencing are required to establish gene expression profiles to predict clinical outcome and to select optimal personalized therapy.

PET/Computed Tomography Scanning and Precision Medicine: Esophageal Cancer

Esophageal cancer commonly has a poor prognosis, which requires an accurate diagnosis and early treatment to improve outcome. Other modalities for staging, such as endoscopic ultrasound imaging and computed tomography (CT) scans, have a role in diagnosis and staging. However, PET with fluorine-18 fluoro-2-deoxy-d-glucose/CT (FDG PET/CT) scanning allows for improved detection of distant metastatic disease and can help to prevent unnecessary interventions that would increase morbidity. FDG PET/CT scanning is valuable in the neoadjuvant chemotherapy assessment and predicting survival outcomes subsequent to surgery. FDG PET/CT scanning detects recurrent disease and metastases in follow-up.

Development of a nomogram for the prediction of pathological complete response after neoadjuvant chemoradiotherapy in patients with esophageal squamous cell carcinoma

Nomograms incorporating multiple prognostic factors are useful for individualized estimation of survival in cancer patients. However, nomograms for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in patients with esophageal cancer are scarce. Here, we describe the development of a nomogram for predicting pCR after nCRT in patients with esophageal squamous cell carcinoma (ESCC). We retrospectively reviewed the records of 392 ESCC patients who underwent nCRT followed by esophagectomy. Seventy percent of the participants (n = 274) were randomly assigned to a training cohort, whereas the remaining 30% were included in a validation cohort (n = 118). Data from the training cohort were subjected to multivariate logistic regression analyses for selecting variables to be included in the nomogram. The performance of the resulting nomogram was internally and externally validated by calculating the bias-corrected concordance statistic (c-statistic) and the area under the receiver operating characteristics curve (AUROC) in the training and validation cohorts, respectively. After surgery, 25.77% of the study patients achieved pCR. The following variables were included in the nomogram: (i) age, (ii) pretreatment tumor length, (iii) history of head and neck cancer, (iv) post-nCRT albumin levels, and (v) post-nCRT endoscopic findings coupled with endoscopic biopsy results. The bias-corrected c-statistic and AUROC of the internal and external validation sets were 0.77 and 0.747, respectively. Our nomogram showed a good performance for predicting pCR after nCRT in ESCC patients.

Biobanking of fresh-frozen endoscopic biopsy specimens from esophageal adenocarcinoma

The process of preparing endoscopic esophageal adenocarcinoma samples for next-generation DNA/RNA sequencing is poorly described. Therefore, we assessed the feasibility and pitfalls of preparing esophageal adenocarcinoma endoscopic biopsies toward DNA/RNA samples suitable for next-generation sequencing. In this prospective study, four tumor biopsy samples were collected from consecutive esophageal cancer patients during esophagogastroduodenoscopy and fresh-frozen in liquid nitrogen. DNA and RNA were isolated from samples with a tumor percentage of at least 50%. For next-generation sequencing, double-stranded DNA (dsDNA) is required and high-quality RNA preferred. The quantity dsDNA and RNA quantity and quality were assessed with the Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). Biopsy samples of 69 consecutive patients with esophageal adenocarcinoma were included. In five patients (7%), the tumor percentage was less than 50% in all four biopsies. Using a protocol allowing simultaneous DNA and RNA isolation, the median dsDNA yield was 2.4 μg (range 0.1-12.0 μg) and the median RNA yield was 0.5 μg (range 0.01-2.05 μg). The median RNA integrity number of samples that were fresh-frozen within 30 minutes after sampling was 6.7 (range 4.2-8.9) compared with 2.5 (1.8-4.5) for samples that were fresh-frozen after 2 hours. The results from this study show that obtaining dsDNA and RNA for next-generation sequencing from endoscopic esophageal adenocarcinoma samples is feasible. Tumor percentage and dsDNA/RNA yield and quality emphasize the need for sampling multiple biopsies and minimizing the delay before fresh-freezing.

Possible prediction of the response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy based on gene expression profiling

Background

Heterogeneous efficacy of neoadjuvant chemotherapy has led to controversies that have limited its application in clinical practice. Thus, we aimed to identify potential biomarkers predicting esophageal squamous cell carcinoma (ESCC) chemo-responsiveness by gene expression profiling.

Methods

CCK8 assay was used to evaluate the growth inhibitory effect of different concentrations of cisplatin and paclitaxel on the ESCC cell lines EC109, KYSE450, KYSE410, KYSE510, and KYSE150 to differentiate between chemosensitive and chemoresistant cell lines. Gene expression profiling and Real-time PCR were applied to analyze and validate the gene expression differences between chemosensitive and chemoresistant cell lines. IHC was conducted to examine the expression of selected target markers MUC4, MUC13, and MUC20 in 186 ESCC resection samples and the relationships between their expression and tumor regression grade was analyzed. Moreover, RNAi was conducted to instantly block the expression of MUC4, MUC13, and MUC20 to observe their influences on chemo-responsiveness.

Results

EC109 was found to be relatively sensitive to both cisplatin and paclitaxel, while KYSE410 was relatively resistant to cisplatin, KYSE510 was relatively resistant to paclitaxel. Gene expression profiling analysis showed that 2018 genes were differentially expressed in sensitive cell line compared to resistant cell lines. The expression patterns of MUC4, MUC13, MUC20 were validated. Low expression of MUC4 and MUC20 in resection samples was significantly correlated with better TRG. Blockage of MUC20 and MUC13 decreased the drug-resistance capacity and chemosensitivity, respectively.

Conclusions

MUC4 and MUC20 were identified as potential biomarkers for predicting the efficacy of neoadjuvant chemotherapy in ESCC patients.

Anticancer effect of cucurbitacin B on MKN-45 cells via inhibition of the JAK2/STAT3 signaling pathway

The aim of the present study was to investigate the effect of cucurbitacin B on MKN-45 gastric carcinoma cells. Cell proliferation was determined using a cell counting kit-8 assay, and commercial cell cycle and apoptosis analysis kits were used to determine the cell cycle by flow cytometry. The mRNA expression of genes which mediate cell cycle checkpoints and apoptosis was detected using reverse transcription-quantitative polymerase chain reaction, and a terminal deoxynucleotidyl transferase dUTP nick end labeling assay was used to determine apoptosis rate. Western blot analysis was used to detect the protein expression levels of JAK2/STAT3 signaling pathway-associated proteins. The presented data show that cucurbitacin B significantly inhibited the proliferation of MKN-45 cells in a dose- and time-dependent manner. In accordance with these findings, cucurbitacin B blocked the progression of the cell cycle from G0/G1 to S phase, which was confirmed by the mRNA expression analysis. Cucurbitacin B treatment significantly suppressed the expression of cyclin D1, cyclin E, cyclin-dependent kinase 4 (CDK4) and CDK2, while increasing the expression of p27. Cucurbitacin B also promoted cell apoptosis, as was determined by TUNEL assay and evaluation of mRNA expression. Further experiments suggested that the beneficial effect of cucurbitacin B on blocking the proliferation and inducing the apoptosis of MKN-45 cells may have been associated with suppression of the JAK2/STAT3 signaling pathway. Thus, the present results indicate that cucurbitacin B suppresses proliferation and promoted apoptosis of MKN-45 cells, which may be mediated by inhibition of the JAK2/STAT3 signaling pathway. Cucurbitacin B therefore may warrant further investigation as a feasible therapy for gastric carcinoma.

MiRNA Expression Analysis of Pretreatment Biopsies Predicts the Pathological Response of Esophageal Squamous Cell Carcinomas to Neoadjuvant Chemoradiotherapy

OBJECTIVE

To identify miRNA markers useful for esophageal squamous cell carcinoma (ESCC) neoadjuvant chemoradiotherapy (neo-CRT) response prediction.

SUMMARY

Neo-CRT followed by surgery improves ESCC patients' survival compared with surgery alone. However, CRT outcomes are heterogeneous, and no current methods can predict CRT responses.

METHODS

Differentially expressed miRNAs between ESCC pathological responders and nonresponders after neo-CRT were identified by miRNA profiling and verified by real-time quantitative polymerase chain reaction (qPCR) of 27 ESCCs in the training set. Several class prediction algorithms were used to build the response-classifying models with the qPCR data. Predictive powers of the models were further assessed with a second set of 79 ESCCs.

RESULTS

Ten miRNAs with greater than a 1.5-fold change between pathological responders and nonresponders were identified and verified, respectively. A support vector machine (SVM) prediction model, composed of 4 miRNAs (miR-145-5p, miR-152, miR-193b-3p, and miR-376a-3p), were developed. It provided overall accuracies of 100% and 87.3% for discriminating pathological responders and nonresponders in the training and external validation sets, respectively. In multivariate analysis, the subgroup determined by the SVM model was the only independent factor significantly associated with neo-CRT response in the external validation sets.

CONCLUSIONS

Combined qPCR of the 4 miRNAs provides the possibility of ESCC neo-CRT response prediction, which may facilitate individualized ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

Potential biomarkers for esophageal cancer

Esophageal cancer, which consist of esophageal adenocarcinoma and esophageal squamous cell carcinoma, is one of the most common malignant tumors in the world, especially in the south of Iran and China. To find and investigate the biomarkers in the initiation, development and progression of esophageal cancer will help us predict the prognosis of esophageal cancer patients and improve the curative effect and survival rate. Here, we reviewed the potential biomarkers of esophageal cancer in three aspects: Immunohistochemical markers, blood-based markers, miRNA markers and Gene expression profiling. All these biomarkers provided promising therapeutic targets for the diagnosis, treatment, and prognosis of esophageal cancer.

Differential protein expression and oncogenic gene network link tyrosine kinase ephrin B4 receptor to aggressive gastric and gastroesophageal junction cancers

Transmembrane tyrosine-kinase Ephrin receptors promote tumor progression and/or metastasis of several malignancies including leukemia, follicular lymphoma, glioma, malignant pleural mesothelioma, papillary thyroid carcinoma, sarcomas and ovarian, breast, bladder and non-small cell lung cancers. They also drive intestinal stem cell proliferation and positioning, control intestinal tissue boundaries and are involved in liver, pancreatic and colorectal cancers, indicating involvement in additional digestive system malignancies. We investigated the role of Ephrin-B4 receptor (EPHB4), and its ligand EFNB2, in gastric and gastroesophageal junction cancers in patient cohorts through computational, mathematical, molecular and immunohistochemical analyses. We show that EPHB4 is upregulated in preneoplastic gastroesophageal lesions and its expression further increased in gastroesophageal cancers in several independent cohorts. The closely related EPHB6 receptor, which also binds EFNB2, was downregulated in all tested cohorts, consistent with its tumor-suppressive properties in other cancers. EFNB2 expression is induced in esophageal cells by acidity, suggesting that gastroesophageal reflux disease (GERD) may constitute an early triggering event in activating EFNB2-EPHB4 signaling. Association of EPHB4 to both Barrett's esophagus and to advanced tumor stages, and its overexpression at the tumor invasion front and vascular endothelial cells intimate the notion that EPHB4 may be associated with multiple steps of gastroesophageal tumorigenesis. Analysis of oncogenomic signatures uncovered the first EPHB4-associated gene network (false discovery rate: 7 × 10(-90) ) composed of a five-transcription factor interconnected gene network that drives proliferation, angiogenesis and invasiveness. The EPHB4 oncogenomic network provides a molecular basis for its role in tumor progression and points to EPHB4 as a potential tumor aggressiveness biomarker and drug target in gastroesophageal cancers.

Predictors of Disease Recurrence and Survival in Esophageal Adenocarcinomas With Complete Response to Neoadjuvant Therapy

Complete response to neoadjuvant therapy, determined by pathologic examination of the resection specimen (pCR), is associated with a favorable outcome in esophageal adenocarcinomas (EAC), but there is significant heterogeneity in survival reported within this group. Our aim was to determine predictors of disease recurrence (DR) and survival in EAC patients with pCR to neoadjuvant therapy. A total of 93 EAC patients with pCR to neoadjuvant therapy were identified, and a predetermined set of clinicopathologic variables was examined, including patient age, sex, tumor location, pretreatment tumor size, endoscopic ultrasound T and N stage, histologic tumor type, and grade in pretreatment biopsies. The esophagectomy specimens were evaluated for the extent of sampling of the tumor bed, depth of treatment-related changes, presence of treatment effect in lymph nodes, and the total number of lymph nodes examined. Complete histologic examination of the tumor bed was the most significant predictor of favorable outcome for both DR (hazard ratio [HR]=0.42; 95% confidence interval [CI]: 0.21-0.82; P=0.011) and disease-specific mortality (HR=0.40; 95% CI: 0.22-0.70; P<0.01). The presence of a high-grade adenocarcinoma component in pretreatment biopsies (HR=2.19; 95% CI: 1.22-3.94; P<0.01) was associated with a higher disease-specific mortality, and involvement of the gastroesophageal junction (HR=2.37; 95% CI: 1.11-5.06; P=0.026) was associated with a higher rate of DR. Heterogeneity in outcomes for EAC patients with pCR to therapy can be explained by adequacy of histologic examination of the tumor bed, high tumor grade, and involvement of the gastroesophageal junction.

Predicting the Response of Neoadjuvant Therapy for Patients with Esophageal Carcinoma: an In-depth Literature Review

Currently, the most promising strategy to improve the prognosis of advanced esophageal cancer is neoadjuvant chemoradiation (CRT) followed by surgery. However, patients who achieved pathological complete response can experience more survival benefit. Therefore, it is critical to identify the responders early in the course of treatment. Published data demonstrate that clinic-histopathological factors, molecular biomarkers, and functional imaging are predictive of neoadjuvant therapy. The existing biomarkers, including epidermal growth factor receptors, angiogenetic factors, transcription factors, tumor suppressor genes, cell cycle regulators, nucleotide excision repair pathway, cytokines, and chemotherapy associated genes, need to be validated and novel biomarkers warrant further exploration. Positron emission tomography (PET) is useful for differentiating the responders of neoadjuvant CRT. The most valuable parameters and the time point of performing PET in the course of treatment remains to be elucidated. Furthermore, predictive models incorporating the multiple categories of factors need to be established with a large, prospective, and homogeneous patient cohort in the future. Standardization of staging, biomarker detection method, and image acquisition protocol will be critical for the generalization of this model. Prospective, multi-center controlled trials, which stratified patients according to these predictive factors, will help guide individualized treatment strategies for patients with esophageal cancer.

Neoadjuvant treatment for advanced esophageal cancer: response assessment before surgery and how to predict response to chemoradiation before starting treatment

Patients with advanced esophageal cancer (T3-4, N) have a poor prognosis. Chemoradiation or chemotherapy before esophagectomy with adequate lymphadenectomy is the standard treatment for patients with resectable advanced esophageal carcinoma. However, only patients with major histopathologic response (regression to less than 10% of the primary tumor) after preoperative treatment will have a prognostic benefit of preoperative chemoradiation. Using current therapy regimens about 40% to 50% of the patients show major histopathological response. The remaining cohort does not benefit from this neoadjuvant approach but might benefit from earlier surgical resection. Therefore, it is an aim to develop tools for response prediction before starting the treatment and for early response assessment identifying responders. The current review discusses the different imaging techniques and the most recent studies about molecular markers for early response prediction. The results show that [(18)F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) has a good sensitivity but the specificity is not robust enough for routine clinical use. Newer positron emission tomography detector technology, the combination of FDG-PET with computed tomography, additional evaluation criteria and standardization of evaluation may improve the predictive value. There exist a great number of retrospective studies using molecular markers for prediction of response. Until now the clinical use is missing. But the results of first prospective studies are promising. A future perspective may be the combination of imaging technics and special molecular markers for individualized therapy. Another aspect is the response assessment after finishing neoadjuvant treatment protocol. The different clinical methods are discussed. The results show that until now no non-invasive method is valid enough to assess complete histopathological response.

P, Anderson KC, Li C, Avet-Loiseau H, Munshi NC. Gene expression profile alone is inadequate in predicting complete response in multiple myeloma

With advent of several treatment options in multiple myeloma (MM), a selection of effective regimen has become an important issue. Use of gene expression profile (GEP) is considered an important tool in predicting outcome; however, it is unclear whether such genomic analysis alone can adequately predict therapeutic response. We evaluated the ability of GEP to predict complete response (CR) in MM. GEP from pretreatment MM cells from 136 uniformly treated MM patients with response data on an IFM, France led study were analyzed. To evaluate variability in predictive power due to microarray platform or treatment types, additional data sets from three different studies (n=511) were analyzed using same methods. We used several machine learning methods to derive a prediction model using training and test subsets of the original four data sets. Among all methods employed for GEP-based CR predictive capability, we got accuracy range of 56-78% in test data sets and no significant difference with regard to GEP platforms, treatment regimens or in newly diagnosed or relapsed patients. Importantly, permuted P-value showed no statistically significant CR predictive information in GEP data. This analysis suggests that GEP-based signature has limited power to predict CR in MM, highlighting the need to develop comprehensive predictive model using integrated genomics approach.

Gene expression analysis of pretreatment biopsies predicts the pathological response of esophageal squamous cell carcinomas to neo-chemoradiotherapy

BACKGROUND

Neoadjuvant chemoradiotherapy (neo-CRT) followed by surgery has been shown to improve esophageal squamous cell carcinoma (ESCC) patients' survival compared with surgery alone. However, the outcomes of CRT are heterogeneous, and no clinical or pathological method can currently predict CRT response. In this study, we aim to identify mRNA markers useful for ESCC CRT-response prediction.

PATIENTS AND METHODS

Gene expression analyses were carried out on pretreated cancer biopsies from 28 ESCCs who received neo-CRT and surgery. Surgical specimens were assessed for pathological response to CRT. The differentially expressed genes identified by expression profiling were validated by real-time quantitative polymerase chain reaction (qPCR), and a classifying model was built from qPCR data using Fisher's linear discriminant analysis. The predictive power of this model was further assessed in a second set of 32 ESCCs.

RESULTS

The profiling of the 28 ESCCs identified 10 differentially expressed genes with more than a twofold change between patients with pathological complete response (pCR) and less than pCR (

CONCLUSION

The expression levels of three genes determined by qPCR provide a possible model for ESCC CRT prediction, which will facilitate the individualization of ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

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Key Words

• esophageal squamous cell carcinoma
• gene expression
• neoadjuvant chemoradiotherapy
• response prediction

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MESH Headings

• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• Biopsy
• Carcinoma, Squamous Cell/genetics
• Carcinoma, Squamous Cell/mortality
• Carcinoma, Squamous Cell/therapy
• Chemoradiotherapy
• Cisplatin/therapeutic use
• Esophageal Neoplasms/genetics
• Esophageal Neoplasms/mortality
• Esophageal Neoplasms/therapy
• Esophageal Squamous Cell Carcinoma
• Female
• Gene Expression
• Gene Expression Profiling
• Humans
• Male
• Middle Aged
• Neoadjuvant Therapy
• RNA, Messenger/genetics
• Treatment Outcome
• Vinblastine/analogs & derivatives
• Vinblastine/therapeutic use
• Vinorelbine

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Affiliation(s)

J Wen State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou
H Yang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology
M Z Liu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Radiotherapy
K J Luo State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology
H Liu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Radiotherapy
Y Hu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology
X Zhang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology
R C Lai State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China
T Lin Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology
H Y Wang State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou
J H Fu State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou; Guangdong Esophageal Cancer Institute, Guangzhou; Department of Thoracic Oncology.

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Current status of predictive biomarkers for neoadjuvant therapy in esophageal cancer

Neoadjuvant therapy has been proven to be extremely valuable and is widely used for advanced esophageal cancer. However, a significant proportion of treated patients (60%-70%) does not respond well to neoadjuvant treatments and develop severe adverse effects. Therefore, predictive markers for individualization of multimodality treatments are urgently needed in esophageal cancer. Recently, molecular biomarkers that predict the response to neoadjuvant therapy have been explored in multimodal approaches in esophageal cancer and successful examples of biomarker identification have been reported. In this review, promising candidates for predictive molecular biomarkers developed by using multiple molecular approaches are reviewed. Moreover, treatment strategies based on the status of predicted biomarkers are discussed, while considering the international differences in the clinical background. However, in the absence of adequate treatment options related to the results of the biomarker test, the usefulness of these diagnostic tools is limited and new effective therapies for biomarker-identified nonresponders to cancer treatment should be concurrent with the progress of predictive technologies. Further improvement in the prognosis of esophageal cancer patients can be achieved through the introduction of novel therapeutic approaches in clinical practice.

TPX2 expression is associated with cell proliferation and patient outcome in esophageal squamous cell carcinoma

BACKGROUND

The molecular and genetic changes underlying esophageal squamous cell carcinoma (ESCC) tumor formation and rapid progression are poorly understood. Using high-throughput data analysis, we examined molecular changes involved in ESCC pathogenesis and investigated their clinical relevance.

METHODS

Five independent microarray datasets were examined for differentially expressed genes and pathways. For validation, mRNA expression in tumor and matched normal tissues from 16 ESCC cases was examined by cDNA microarray, and protein expression in 97 ESCC specimens was investigated using immunohistochemical stains. The association between clinicopathological parameters and the expression of Aurora kinase A (Aurora-A) and TPX2 was analyzed. The impact of TPX2 expression was also assessed in ESCC cancer cells.

RESULTS

AURKA and TPX2, members of the "Role of Ran in mitotic spindle regulation" pathway, were selected for further investigation. Verification by cDNA microarray showed that both genes were overexpressed in tumor tissues, and immunohistochemical staining showed Aurora-A and TPX2 expression in 88.4 and 90.6 % of ESCC specimens, respectively. High TPX2 expression was a significant prognosticator for overall and disease-free survival in univariate analysis and remained an independent prognostic factor in multivariate analysis (HR 1.802, p = 0.037). TPX2 knockdown clones showed inhibited cellular proliferation in growth curve studies and formed fewer colonies in the clonogenic assay.

CONCLUSIONS

Using bioinformatics resources, which were validated by microarray analysis and immunohistochemistry stains, and manipulation of TPX2 expression in ESCC cell lines, we demonstrated that TPX2 expression is associated with cell proliferation and poor prognosis among patients with resected ESCC.

The current status of neoadjuvant therapy for esophageal cancer

Through the contribution of a very large number of single-arm phase II trials and many less randomized phase III trials, the standard of care for locally advanced esophageal cancer has evolved to either combination chemotherapy plus radiation or combination chemotherapy. In this review, we focus on the key findings of these studies and selected meta-analyses that have led to this evolution. We note differences in outcomes for adenocarcinomas of the esophagus when compared to squamous cell esophageal cancers. Despite progress in developing a consensus for therapy, the outcome for patients with locally advanced remains poor. We complete the review by noting newer areas of investigation seeking to provide targeted and more personalized therapy to patients with esophageal cancer.

Predictors of pathological complete response to neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma

BACKGROUNDS

In this study, we evaluated the factors associated with a pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for esophageal squamous cell carcinoma (ESCC).

METHODS

Pre-nCRT parameters in ESCC patients treated between 1999 and 2006 were analyzed to identify predictors of pCR. All patients received 5-fluorouracil/cisplatin-based chemotherapy and external beam radiation followed by scheduled esophagectomy. Variables were analyzed using univariate and multivariate analyses with pCR as the dependent variable. Estimated pCR rate was calculated with a regression model.

RESULTS

Fifty-nine (20.9%) of 282 patients achieved pCR. Univariate analysis identified four patient factors (age, smoking status, drinking history and hypertension), one pre-nCRT parameter (tumor length) as significant predictors of pCR (all P <0.05). On multivariate analysis, tumor length ≤3 cm (favorable, odds ratio (OR): 4.85, P = 0.001), patient age >55 years (favorable, OR: 1.95, P = 0.035), and being a non-smoker (favorable, OR: 3.6, P = 0.003) were independent predictors of pCR. The estimated pCR rates based on a logistic regression including those three predictors were 71%, 35 to approximately 58%, 19 to approximately 38%, and 12% for patients with 3, 2, 1 and 0 predictors, respectively.

CONCLUSION

Age, smoking habit and tumor length were important pCR predictors. These factors may be used to predict outcomes for ESCC patients receiving nCRT, to develop risk-adapted treatment strategies, and to select patients who could participate in trials on new therapies.

The '-omics' revolution and oesophageal adenocarcinoma

Oesophageal adenocarcinoma (OAC) is the eighth most common cancer type worldwide with a dismal 5-year survival. Barrett oesophagus, the replacement of the normal squamous epithelia with glandular cells, is the first step in the pathway towards OAC. Although most patients with OAC present de novo, the presence of the easily detectable OAC precursor lesion, Barrett oesophagus, enables the possibility of early detection of high-risk patients who are more likely to progress. Currently, identification of high-risk patients depends on histopathological assessment of dysplasia with no regards to molecular pathogenesis. In the future, screening and risk stratification initiatives for Barrett oesophagus that incorporate molecular profiles might permit improved early diagnosis and intervention strategies with the possibility of preventing OAC. For the majority of patients presenting de novo at an advanced stage, combining so-called -omics datasets with current clinical staging algorithms might enable OACs to be better classified according to distinct molecular programmes, thereby leading to better targeted treatment strategies as well as cancer monitoring regimes. This Review discusses how the latest advances in -omics technologies have improved our understanding of the development and biology of OAC, and how this development might alter patient management in the future.

A Predictive Genetic Signature for Response to Fluoropyrimidine-Based Neoadjuvant Chemoradiation in Clinical Stage II and III Rectal Cancer

PURPOSE

Pre-operative chemoradiation (CRT) is currently the standard of care for patients with clinical stage II and III rectal cancer but only about 45% of patients achieve tumor downstaging and <20% of patients achieve a pathologic complete response. Better methods to stratify patients according to potential neoadjuvant treatment response are needed. We used microarray analysis to identify a genetic signature that correlates with a pathological complete response (pCR) to neoadjuvant CRT. We performed a gene network analysis to identify potential signaling pathways involved in determining response to neoadjuvant treatment.

PATIENTS AND METHODS

We identified 31 T3-4 N0-1 rectal cancer patients who were treated with neoadjuvant fluorouracil-based CRT. Eight patients were identified to have achieved a pCR to treatment while 23 patients did not. mRNA expression was analyzed using cDNA microarrays. The correlation between mRNA expression and pCR from pre-treatment tumor biopsies was determined. Gene network analysis was performed for the genes represented by the predictive signature.

RESULTS

A genetic signature represented by expression levels of the three genes EHBP1, STAT1, and GAPDH was found to correlate with a pCR to neoadjuvant treatment. The difference in expression levels between patients who achieved a pCR and those who did not was greatest for EHBP1. Gene network analysis showed that the three genes can be connected by the gene ubiquitin C (UBC).

CONCLUSION

This study identifies a 3-gene signature expressed in pre-treatment tumor biopsies that correlates with a pCR to neoadjuvant CRT in patients with clinical stage II and III rectal cancer. These three genes can be connected by the gene UBC, suggesting that ubiquitination is a molecular mechanism involved in determining response to treatment. Validating this genetic signature in a larger number of patients is proposed.

Present status and progress of neoadjuvant chemoradiotherapy for esophageal cancer

Trimodality based on neoadjuvant chemoradiotherapy (nCRT) followed by surgery is gaining popularity as a treatment strategy for locally advanced esophageal cancer. In this review, we summarize the role of nCRT and the recommended nCRT regimens based on clinical trials and meta-analyses. We analyze the relationship of nCRT with pathologic complete response (pCR) and then identify potential predictive markers of response. Compared with surgery alone and neoadjuvant chemotherapy followed by surgery, trimodality provides longer survival and has the advantage of local control compared with definitive chemoradiotherapy. The standard regimen is a platinum-based regimen with a radiation dose range of 41.4-50.4 Gy by conventional fractionation. Evidence shows that patients with pCR tend to live longer than non-responders, indicating that pCR is a significant prognostic factor for patients with esophageal cancer. Individualized medicine requires predictive markers of individual patients based on their own genes. Currently, no definite marker is proved to be sufficiently sensitive and specific for use in clinical practice, although 18-fluorodeoxyglucose positron emission tomography shows promise in predicting response to nCRT.

Early diagnostic biomarkers for esophageal adenocarcinoma--the current state of play

Esophageal adenocarcinoma (EAC) is one of the two most common types of esophageal cancer with alarming increase in incidence and very poor prognosis. Aiming to detect EAC early, currently high-risk patients are monitored using an endoscopic-biopsy approach. However, this approach is prone to sampling error and interobserver variability. Diagnostic tissue biomarkers related to genomic and cell-cycle abnormalities have shown promising results, although with current technology these tests are difficult to implement in the screening of high-risk patients for early neoplastic changes. Differential miRNA profiles and aberrant protein glycosylation in tissue samples have been reported to improve performance of existing tissue-based diagnostic biomarkers. In contrast to tissue biomarkers, circulating biomarkers are more amenable to population-screening strategies, due to the ease and low cost of testing. Studies have already shown altered circulating glycans and DNA methylation in BE/EAC, whereas disease-associated changes in circulating miRNA remain to be determined. Future research should focus on identification and validation of these circulating biomarkers in large-scale trials to develop in vitro diagnostic tools to screen population at risk for EAC development.

GERD-Barrett-Adenocarcinoma: Do We Have Suitable Prognostic and Predictive Molecular Markers?

Due to unfavorable lifestyle habits (unhealthy diet and tobacco abuse) the incidence of gastroesophageal reflux disease (GERD) in western countries is increasing. The GERD-Barrett-Adenocarcinoma sequence currently lacks well-defined diagnostic, progressive, predictive, and prognostic biomarkers (i) providing an appropriate screening method identifying the presence of the disease, (ii) estimating the risk of evolving cancer, that is, the progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC), (iii) predicting the response to therapy, and (iv) indicating an overall survival—prognosis for EAC patients. Based on histomorphological findings, detailed screening and therapeutic guidelines have been elaborated, although epidemiological studies could not support the postulated increasing progression rates of GERD to BE and EAC. Additionally, proposed predictive and prognostic markers are rather heterogeneous by nature, lack substantial proofs, and currently do not allow stratification of GERD patients for progression, outcome, and therapeutic effectiveness in clinical practice. The aim of this paper is to discuss the current knowledge regarding the GERD-BE-EAC sequence mainly focusing on the disputable and ambiguous status of proposed biomarkers to identify promising and reliable markers in order to provide more detailed insights into pathophysiological mechanisms and thus to improve prognostic and predictive therapeutic approaches.

Gene expression profiles in esophageal adenocarcinoma predict survival after resection

OBJECTIVE

The incidence of esophageal adenocarcinoma is rapidly increasing in the western population. Despite aggressive treatment, survival after esophagectomy is suboptimal. The main objective of the present study was to evaluate the gene expression profiles in esophageal adenocarcinoma and determine their association with survival after resection.

METHODS

We conducted a prospective National Institutes of Health/National Cancer Institute funded study to evaluate the prognostic significance of gene expression in patients with esophageal adenocarcinoma undergoing esophagectomy. Gene expression in tumor tissue was analyzed using high-throughput oligonucleotide arrays. The association of gene expression and overall survival was analyzed using the tail-strength statistic and Cox regression analysis. Gene signatures were constructed with semisupervised methods using principal components. A cross-validated risk score was devised by conducting 10-fold cross-validation, 100 times.

RESULTS

We evaluated the gene expression in 64 patients with esophageal adenocarcinoma who underwent esophagectomy. The median overall survival was 27 months (95% confidence interval 22 to not reached). After filtering, 10,214 probe sets were used for survival analysis. The tail-strength statistic for these probe sets (0.318) indicated a significant association with overall survival. Patients were classified into high- and low-risk groups, according to the gene signature. High-risk patients had a predicted median survival of 19 months, but the median was not reached for the low-risk group (P < .05). On multivariate analysis, the gene signature was independently associated with survival (hazard ratio, 2.22; P = .04).

CONCLUSIONS

Global gene expression levels were significantly associated with overall survival after esophagectomy. Furthermore, individual genes could be successfully combined into a strongly predictive, internally cross-validated gene signature. If validated further, these results could help direct additional clinical trials of neoadjuvant and adjuvant therapies for esophageal adenocarcinoma.

Clinical issues in oesophageal adenocarcinoma: could DNA copy number hold the key?

While not being considered a common cancer, since 1975 oesophageal adenocarcinoma (OAC) has had the fastest-rising incidence of any malignancy in Caucasian Western populations. In the absence of major improvements in treatment since this rise began, the number of deaths has also increased rapidly. In contrast, there have been significant advances in basic science in this period. One such advance is the discovery of DNA copy number aberrations (CNAs), and their potential role in carcinogenesis. The study of CNAs offers the potential to answer fundamental clinical questions in OAC, which in turn may lead to improved diagnosis, staging and treatment. This review outlines current clinical dilemmas in OAC, discusses the role that CNAs have been shown to play to date and highlights potential future applications.

Esophageal carcinoma advances in treatment results for locally advanced disease: review

The treatment results of patients with locally advanced esophageal carcinomas have evolved since the publication of the first trial of concurrent mitomycin C and 5-fluorouracil with radiotherapy (RT) in 1983. Subsequent studies refined and improved on the concurrent chemotherapy (chemo) with administration of cisplatin and 5-fluorouracil infusion (PF). Chemo (PF) before surgery improved overall survival (OS) in those patients in most of the randomized trials and in meta-analyses. Two courses of PF concurrent with irradiation followed by additional two courses of PF were superior to RT alone without surgery for both groups. Concurrent chemoradiotherapy followed by surgery was found to have statistically improved OS as compared with surgery only in randomized trials and meta-analyses. In most of these studies, it was found that those patients with pathologic complete response to the initial treatment(s) did better than those who had no improvement at all. Current treatment outcome for these diseases is disappointing; newer strategies including induction chemo with the optimal combination, proper dosage of each drug, and proper number of courses before concurrent chemoradiotherapy; improvement in RT; and immunotherapy with or without subsequent surgery are exciting and definitely need to be investigated in prospective randomized trial(s).

5-Fluorouracil induced intestinal mucositis via nuclear factor-κB activation by transcriptomic analysis and in vivo bioluminescence imaging

5-Fluorouracil (5-FU) is a commonly used drug for the treatment of malignant cancers. However, approximately 80% of patients undergoing 5-FU treatment suffer from gastrointestinal mucositis. The aim of this report was to identify the drug target for the 5-FU-induced intestinal mucositis. 5-FU-induced intestinal mucositis was established by intraperitoneally administering mice with 100 mg/kg 5-FU. Network analysis of gene expression profile and bioluminescent imaging were applied to identify the critical molecule associated with 5-FU-induced mucositis. Our data showed that 5-FU induced inflammation in the small intestine, characterized by the increased intestinal wall thickness and crypt length, the decreased villus height, and the increased myeloperoxidase activity in tissues and proinflammatory cytokine production in sera. Network analysis of 5-FU-affected genes by transcriptomic tool showed that the expression of genes was regulated by nuclear factor-κB (NF-κB), and NF-κB was the central molecule in the 5-FU-regulated biological network. NF-κB activity was activated by 5-FU in the intestine, which was judged by in vivo bioluminescence imaging and immunohistochemical staining. However, 5-aminosalicylic acid (5-ASA) inhibited 5-FU-induced NF-κB activation and proinflammatory cytokine production. Moreover, 5-FU-induced histological changes were improved by 5-ASA. In conclusion, our findings suggested that NF-κB was the critical molecule associated with the pathogenesis of 5-FU-induced mucositis, and inhibition of NF-κB activity ameliorated the mucosal damage caused by 5-FU.

Pathologic nonresponders after neoadjuvant chemoradiation for esophageal cancer demonstrate no survival benefit compared with patients treated with primary esophagectomy

BACKGROUND

Neoadjuvant chemoradiation (NCRT) has become the preferred treatment for patients with locally advanced esophageal cancer. Survival often is correlated to degree of pathologic response; however, outcomes in patients who are found to be pathologic nonresponders (pNR) remain uninvestigated. This study was designed to evaluate survival in pNR to NCRT compared with patients treated with primary esophagectomy (PE).

METHODS

Using our comprehensive esophageal cancer database, we identified patients treated with NCRT and deemed pNR along with patients who proceeded to PE. Clinical and pathologic data were compared using Fisher's exact and χ(2), whereas Kaplan-Meier estimates were used for survival analysis.

RESULTS

We identified 63 patients treated with NCRT and were found to have a pNR, and 81 patients who underwent PE. Disease-free (DFS) and overall survival (OS) were significantly decreased in the pNR group compared with those treated with PE (10 vs. 50 months (0-152), P < 0.001 and 13 vs. 50 months (0-152), P < 0.001, respectively). For patients with stage II disease, DFS and OS were similarly decreased in pathologic nonresponders (13 vs. 62 months (0-120), P < 0.001 and 31 vs. 62 months (0-120), P = 0.024, respectively). There were no differences in DFS or OS for patients with stage III disease (10 vs. 14 months (0-152), P = 0.29 and 10 vs. 19 months (0-152), P = 0.16, respectively).

CONCLUSIONS

Pathologic nonresponders to NCRT for esophageal cancer receive no benefit in DFS or OS compared with patients treated with PE. For patients with stage II disease, DFS and OS are, in fact, significantly decreased in the pNR.

Pretreatment transcriptional profiling for predicting response to neoadjuvant chemoradiotherapy in rectal adenocarcinoma

PURPOSE

Patients presenting with locally advanced rectal cancer currently receive preoperative radiotherapy with or without chemotherapy. Although pathologic complete response is achieved for approximately 10% to 30% of patients, a proportion of patients derive no benefit from this therapy while being exposed to toxic side effects of treatment. Therefore, there is a strong need to identify patients who are unlikely to benefit from neoadjuvant therapy to help direct them toward alternate and ultimately more successful treatment options.

EXPERIMENTAL DESIGN

In this study, we obtained expression profiles from pretreatment biopsies for 51 rectal cancer patients. All patients underwent preoperative chemoradiotherapy, followed by resection of the tumor 6 to 8 weeks posttreatment. Gene expression and response to treatment were correlated, and a supervised learning algorithm was used to generate an original predictive classifier and validate previously published classifiers.

RESULTS

Novel predictive classifiers based on Mandard's tumor regression grade, metabolic response, TNM (tumor node metastasis) downstaging, and normal tissue expression profiles were generated. Because there were only 7 patients who had minimal treatment response (>80% residual tumor), expression profiles were used to predict good tumor response and outcome. These classifiers peaked at 82% sensitivity and 89% specificity; however, classifiers with the highest sensitivity had poor specificity, and vice versa. Validation of predictive classifiers from previously published reports was attempted using this cohort; however, sensitivity and specificity ranged from 21% to 70%.

CONCLUSIONS

These results show that the clinical utility of microarrays in predictive medicine is not yet within reach for rectal cancer and alternatives to microarrays should be considered for predictive studies in rectal adenocarcinoma.

Biomarkers in Barrett’s esophagus and esophageal adenocarcinoma: Predictors of progression and prognosis

Barrett’s esophagus is a well-known premalignant lesion of the lower esophagus that is characterized by intestinal metaplasia of the squamous epithelium. It is clinically important due to the increased risk (0.5% per annum) of progression to esophageal adenocarcinoma (EA), which has a poor outcome unless diagnosed early. The current clinical management of Barrett’s esophagus is hampered by the lack of accurate predictors of progression. In addition, when patients develop EA, the current staging modalities are limited in stratifying patients into different prognostic groups in order to guide the optimal therapy for an individual patient. Biomarkers have the potential to improve radically the clinical management of patients with Barrett’s esophagus and EA but have not yet entered mainstream clinical practice. This is in contrast to other cancers like breast and prostate for which biomarkers are utilized routinely to inform clinical decisions. This review aims to highlight the most promising predictive and prognostic biomarkers in Barrett’s esophagus and EA and to discuss what is required to move the field forward towards clinical application.

A 4-gene signature predicts survival of patients with resected adenocarcinoma of the esophagus, junction, and gastric cardia

BACKGROUND & AIMS

The incidence of esophageal and junctional adenocarcinoma has increased 6-fold in the past 30 years and 5-year survival remains approximately 20%. Current staging is limited in its ability to predict survival which has ramifications for treatment choices. The aim of this study was to generate and validate a molecular prognostic signature for esophageal adenocarcinoma.

METHODS

Gene expression profiling was performed and the resulting 42,000 gene signatures correlated with clinical and pathologic features for 75 snap-frozen esophageal and junctional resection specimens. External validation of selected targets was performed on 371 independent cases using immunohistochemistry to maximize clinical applicability.

RESULTS

A total of 119 genes were associated significantly with survival and 270 genes with the number of involved lymph nodes. Filtering of these lists resulted in a shortlist of 10 genes taken forward to validation. Four genes proved to be prognostic at the protein level (deoxycytidine kinase [DCK], 3'-phosphoadenosine 5'-phosphosulfate synthase 2 [PAPSS2], sirtuin 2 [SIRT2], and tripartite motif-containing 44 [TRIM44]) and were combined to create a molecular prognostic signature. This 4-gene signature was highly predictive of survival in the independent external validation cohort (0/4 genes dysregulated 5-year survival, 58%; 95% confidence interval [CI], 36%-80%; 1-2/4 genes dysregulated 5-year survival, 26%; 95% CI, 20%-32%; and 3-4/4 genes dysregulated 5-year survival, 14%; 95% CI, 4%-24% (P = .001). Furthermore, this 4-gene signature was independently prognostic in a multivariable model together with the existing clinical TNM staging system (P = .013).

CONCLUSIONS

This study has generated a clinically applicable prognostic gene signature that independently predicts survival in an external validation cohort and may inform management decisions.

Using gene expression profiling to predict response and prognosis in gastrointestinal cancers-the promise and the perils

Cancer treatment is now moving toward a personalized approach, promising improved rates of response and survival. A number of studies have employed the use of microarrays to investigate the predictive potential of expression profiling in gastrointestinal (GI) cancer patients. However while many robust predictive classifiers relating to response and prognosis have been generated for GI cancer patients, these have yet to make the transition to the clinic. The main obstacle is the limited cross validation between predictive gene lists identified for the same tumor type and outcome. Differences in the experimental design, analysis, and interpretation of results all contribute to this variation, with numerous factors influencing which genes are highlighted as predictive. While predictive genomics shows immense potential, it is still a relatively new field and the validation of predictive gene lists derived from microarray data remains a challenge. Future studies must carefully consider all aspects of experimental design to ensure a clinically applicable predictive test can be developed. With this in mind, more extensive and collaborative research must be undertaken before microarray-based platforms can be used routinely in tailoring GI cancer treatment and change clinical practice. Larger cohorts and consistency in methodology will enable the findings from this research to make the transition to the clinic.

Early response evaluation and prediction in neoadjuvant-treated patients with esophageal cancer

Since the introduction of multimodal therapy regimens, the prognosis of esophageal cancer has improved. There is undoubtedly true for patients with surgically resected tumors in the case of a response to neoadjuvant chemotherapy or chemoradiation. Important conclusions can be drawn from this regarding the indication for perioperative therapies, the radicality of surgery, or the surgical indications. Thus, most of the current research in this field is aimed at the early identification of this subset of patients, at the beginning of, or even before, neoadjuvant treatment. Conventional staging tools have failed to predict responses to neoadjuvant therapy. However, molecular imaging methods, e.g. positron emission tomography (PET)-scans, have shown promising results in the early selection of responders and non-responders during the course of neoadjuvant therapy, allowing physicians to alter the treatment plan accordingly. Even more desirable is the identification of potential responders before the start of neoadjuvant therapy. Preliminary molecular data on biopsy specimens demonstrate the possibility of early response prediction in these patients. We present the current knowledge on response evaluation and prediction in esophageal cancer and draw conclusions for future clinical practice and studies in this review.