Cuong Duong

Gene expression profiling of esophageal cancer: comparative analysis of Barrett's esophagus, adenocarcinoma, and squamous cell carcinoma.

Esophageal cancer is a particularly aggressive tumor with poor prognosis, however, our current knowledge of the genes and pathways involved in tumorigenesis of the esophagus are limited. To obtain insight into the molecular processes underlying tumorigenesis of the esophagus, we have used cDNA microarrays to compare the gene expression profiles of 128 tissue samples representing the major histological subtypes of esophageal cancer (squamous cell carcinoma and adenocarcinoma (ADC)) as well as Barretts esophagus (BE), the precursor lesion to ADC, and normal esophageal epithelium. Linear discriminant analysis and unsupervised hierarchical clustering show the separation of samples into 4 distinct groups consistent with their histological subtype. Differentially expressed genes were identified between each of the tissue types. Comparison of gene ontologies and gene expression profiles identified gene profiles specific to esophageal cancer, as well as BE. “Esophageal cancer clusters,” representing proliferation, immune response, and extracellular matrix genes were identified, as well as digestion, hydrolase, and transcription factor clusters specific to the columnar phenotype observed during BE and esophageal ADC. These clusters provide valuable insight into the molecular and functional differences between normal esophageal epithelium, BE, and the 2 histologically distinct forms of esophageal cancers. Our thorough, unbiased analysis provides a rich source of data for further studies into the molecular basis of tumorigenesis of the esophagus, as well as identification of potential biomarkers for early detection of progression.

18F-FDG PET/CT Has a High Impact on Patient Management and Provides Powerful Prognostic Stratification in the Primary Staging of Esophageal Cancer: A Prospective Study with Mature Survival Data

The aim of this study is to evaluate the incremental staging information, management impact, and prognostic stratification of PET/CT in the primary staging of esophageal cancer in a cohort of patients with mature survival data. Methods: Between July 2002 and June 2005, 139 consecutive patients with newly diagnosed esophageal cancer underwent conventional staging investigations (CSI), followed by PET/CT. Disease stage was classified according to the American Joint Committee on Cancer staging system (6th edition) and grouped as stage I–IIA, stage IIB–III, and stage IV reflecting broad groupings that determine therapeutic choice. Validation of results was performed when PET/CT and CSI stage groups were discordant and in those patients where PET/CT changed management. Management impact was determined by comparing prospectively recorded pre-PET/CT management plans with post-PET/CT management plans. Survival after follow-up of at least 5 y in patients was analyzed using the Kaplan–Meier product limit method and the Cox proportional hazards regression model. Results: PET/CT changed the stage group in 56 of 139 (40%) patients and changed management in 47 of 139 (34%) patients. In 22 patients, therapy was changed from curative to palliative and in 3 from palliative to curative; in 11, treatment modality was changed without a change in treatment intent, and in 11 the delivery of therapy or diagnostic procedure was changed. Of the 47 patients with management change, imaging results could be validated in 31 patients, and PET/CT correctly changed management in 26 (84%) of these. Of the remaining 5 patients, CSI stage was also incorrect in 4 and correct in 1. Median survival was 23 mo. PET/CT stages I–IIA, IIB–III, and IV had a 5-y survival of 40%, 38%, and 6%, respectively. Post-PET/CT stage group and treatment intent were both strongly associated with survival (P < 0.001). Conclusion: PET/CT provides incremental staging information compared with CSI, changes management in one third of patients, and has powerful prognostic stratification in the primary staging of esophageal cancer.

FDG-PET status following chemoradiotherapy provides high management impact and powerful prognostic stratification in oesophageal cancer

PurposeThe purpose of this study was to evaluate the impact of FDG-PET following chemoradiotherapy (CRT) on treatment planning and survival in patients with oesophageal cancer (OC).MethodsFifty-three consecutive OC patients had a post-treatment PET scan to evaluate tumour response to CRT prior to possible surgery. Baseline pre-CRT PET was performed in 33 patients. Prospectively recorded post-CRT management plans were compared with post-PET treatment. High impact was defined as a change in treatment intent or modality. Survival was analysed using the Kaplan-Meier product limit method and Cox proportional hazards regression model.ResultsAfter completion of CRT, 23/53 patients (43%) achieved complete metabolic response (CMR), as compared with only four (8%) with complete response on computed tomography. High PET impact was observed in 19 patients (36%). CMR was strongly predictive of survival (p<0.008) on multivariate analysis. CMR patients in whom resection was not performed had comparable survival to those (CMR and non-CMR) who underwent resection.ConclusionThe use of post-treatment FDG-PET for assessment of tumour response after CRT changed the clinical management of more than one-third of OC patients. CMR status as assessed by PET powerfully stratified prognosis. Even in the absence of a baseline study, normalisation of uptake at all sites of known tumoral involvement carries a good medium-term prognosis.

Pretreatment Gene Expression Profiles Can Be Used to Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

BackgroundThe use of neoadjuvant therapy, in particular chemoradiotherapy (CRT), in the treatment of esophageal cancer (EC) remains controversial. The ability to predict treatment response in an individual EC patient would greatly aid therapeutic planning. Gene expression profiles of EC were measured and relationship to therapeutic response assessed.MethodsTumor biopsy samples taken from 46 EC patients before neoadjuvant CRT were analyzed on 10.5K cDNA microarrays. Response to treatment was assessed and correlated to gene expression patterns by using a support vector machine learning algorithm.ResultsComplete clinical response at conclusion of CRT was achieved in 6 of 21 squamous cell carcinoma (SCC) and 11 of 25 adenocarcinoma (AC) patients. CRT response was an independent prognostic factor for survival (P < .001). A range of support vector machine models incorporating 10 to 1000 genes produced a predictive performance of tumor response to CRT peaking at 87% in SCC, but a distinct positive prediction profile was unobtainable for AC. A 32-gene classifier was produced, and by means of this classifier, 10 of 21 SCC patients could be accurately identified as having disease with an incomplete response to therapy, and thus unlikely to benefit from neoadjuvant CRT.ConclusionsOur study identifies a 32-gene classifier that can be used to predict response to neoadjuvant CRT in SCC. However, because of the molecular diversity between the two histological subtypes of EC, when considering the AC and SCC samples as a single cohort, a predictive profile could not be resolved, and a negative predictive profile was observed for AC.

Significant clinical impact and prognostic stratification provided by FDG-PET in the staging of oesophageal cancer

PurposeTo evaluate the clinical impact of FDG-PET in staging oesophageal cancer and whether this information improves prognostic stratification.MethodsImpact was based on comparison of a prospectively recorded pre-PET plan with post-PET treatment in 68 consecutive patients undergoing primary staging. Survival was analysed using the Kaplan-Meier product limit method and the Cox proportional hazards regression model.ResultsFDG-PET findings impacted on the management of 27/68 patients (40%): in 12 therapy was changed from curative to palliative and in three from palliative to curative, while in 12 other patients there was a change in the treatment modality or delivery but not in the treatment intent. The median survival was 21 months, with post-PET stage and treatment intent both strongly associated with survival (p<0.001). Conventional stage was not able to clearly stratify this population.ConclusionThe use of FDG-PET for primary staging of oesophageal cancer changed the clinical management of more than one-third of patients and provided superior prognostic stratification compared with conventional investigations.

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 Mandards 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. Clin Cancer Res; 17(9); 3039–47. ©2011 AACR.

Surgical and ablative therapies for the management of adrenal 'oligometastases' - A systematic review

BACKGROUND We systematically reviewed the literature on the use of surgery, stereotactic ablative body radiotherapy (SABR) and percutaneous catheter ablation (PCA) techniques for the treatment of adrenal metastases to develop evidence-based recommendations. METHODS A systematic review of the MEDLINE database was performed using structured search terms following PRISMA guidelines. Eligible publications were those published from 1990 to 2012, written in English, had at least five patients treated for adrenal metastasis and reported on patient clinical outcomes (local control, survival and treatment related complications/toxicity). Where possible, pooled 2-year local control and overall survival outcomes were analysed. RESULTS Our search strategy produced a total of 45 papers addressing the three modalities - 30 adrenalectomy, nine SABR and six PCA (818, 178 and 51 patients, respectively). There was marked heterogeneity in outcome reporting, patient selection and follow-up periods between studies. The weighted 2-year local control and overall survival for adrenalectomy were 84% and 46%, respectively, compared with 63% and 19%, respectively for the SABR cohort. Only one study of PCA with five patients analysed clinical outcomes, reporting an actuarial local control of 80% at 1 year. Treatment related complications/toxicities were inconsistently reported. CONCLUSION There is insufficient evidence to determine the best local treatment modality for isolated or limited adrenal metastases from any primary tumour. Published data suggests adrenalectomy to be a reasonable treatment approach for isolated adrenal metastasis in suitable patients. SABR is a valid alternative in cases when surgery is not feasible or the operative risk is unacceptable. PCA cannot be recommended until there are more robust studies which include long-term oncological outcomes.

Inhibiting the system xC(-)/glutathione axis selectively targets cancers with mutant-p53 accumulation.

TP53, a critical tumour suppressor gene, is mutated in over half of all cancers resulting in mutant-p53 protein accumulation and poor patient survival. Therapeutic strategies to target mutant-p53 cancers are urgently needed. We show that accumulated mutant-p53 protein suppresses the expression of SLC7A11, a component of the cystine/glutamate antiporter, system xC−, through binding to the master antioxidant transcription factor NRF2. This diminishes glutathione synthesis, rendering mutant-p53 tumours susceptible to oxidative damage. System xC− inhibitors specifically exploit this vulnerability to preferentially kill cancer cells with stabilized mutant-p53 protein. Moreover, we demonstrate that SLC7A11 expression is a novel and robust predictive biomarker for APR-246, a first-in-class mutant-p53 reactivator that also binds and depletes glutathione in tumours, triggering lipid peroxidative cell death. Importantly, system xC− antagonism strongly synergizes with APR-246 to induce apoptosis in mutant-p53 tumours. We propose a new paradigm for targeting cancers that accumulate mutant-p53 protein by inhibiting the SLC7A11–glutathione axis.

APR-246 potently inhibits tumour growth and overcomes chemoresistance in preclinical models of oesophageal adenocarcinoma

Objectives p53 is a critical tumour suppressor and is mutated in 70% of oesophageal adenocarcinomas (OACs), resulting in chemoresistance and poor survival. APR-246 is a first-in-class reactivator of mutant p53 and is currently in clinical trials. In this study, we characterised the activity of APR-246 and its effect on p53 signalling in a large panel of cell line xenograft (CLX) and patient-derived xenograft (PDX) models of OAC. Design In vitro response to APR-246 was assessed using clonogenic survival, cell cycle and apoptosis assays. Ectopic expression, gene knockdown and CRISPR/Cas9-mediated knockout studies of mutant p53 were performed to investigate p53-dependent drug effects. p53 signalling was examined using quantitative RT-PCR and western blot. Synergistic interactions between APR-246 and conventional chemotherapies were evaluated in vitro and in vivo using CLX and PDX models. Results APR-246 upregulated p53 target genes, inhibited clonogenic survival and induced cell cycle arrest as well as apoptosis in OAC cells harbouring p53 mutations. Sensitivity to APR-246 correlated with cellular levels of mutant p53 protein. Ectopic expression of mutant p53 sensitised p53-null cells to APR-246, while p53 gene knockdown and knockout diminished drug activity. Importantly, APR-246 synergistically enhanced the inhibitory effects of cisplatin and 5-fluorouracil through p53 accumulation. Finally, APR-246 demonstrated potent antitumour activity in CLX and PDX models, and restored chemosensitivity to a cisplatin/5-fluorouracil-resistant xenograft model. Conclusions APR-246 has significant antitumour activity in OAC. Given that APR-246 is safe at therapeutic levels our study strongly suggests that APR-246 can be translated into improving the clinical outcomes for OAC patients.

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.