Prognostic value of putative circulating cancer stem cells in patients undergoing hepatic resection for colorectal liver metastasis.

BACKGROUND: Although surgery is the gold standard treatment of hepatic metastasis from colorectal cancer (CRC), many patients ultimately die of their disease. We tested the hypothesis that the detection of circulating tumor cells (CTC) might identify patients at high risk of dying of disease recurrence after apparently radical liver surgery. METHODS: We considered 50 patients undergoing radical surgery for liver-confined hepatic metastasis from CRC. The expression of a panel of cancer-related genes, as assessed by quantitative real-time PCR, was used to detect CTC in the peripheral blood of these patients immediately before surgery. Survival analysis was performed by the Cox regression model. RESULTS: Univariate analysis of the expression levels of CD133 (a marker of colon cancer stem cells) and survivin (an antiapoptotic factor) resulted in statistically significant association with patient survival [hazard ratio (HR) 2.7, 95% confidence interval (CI) 1.9-3.7, P < 0.0001; and hazard ratio 2.1, 95% CI 1.4-3.2, P < 0.0001, respectively]. Remarkably, multivariate analysis found that only the transcriptional amount of CD133 resulted in statistical significance (HR 2.6, 95% CI 1.9-3.6, P < 0.0001), indicating that this biomarker can independently predict the survival of these patients. CONCLUSIONS: CD133-positive CTC may represent a suitable prognostic marker to stratify the risk of patients who undergo liver resection for CRC metastasis, which opens the avenue to identifying and potentially monitoring the patients who are most likely to benefit from adjuvant treatments

Targeted Therapy Database (TTD): a model to match patient's molecular profile with current knowledge on cancer biology.

BackgroundThe efficacy of current anticancer treatments is far from satisfactory and many patients still die of their disease. A general agreement exists on the urgency of developing molecularly targeted therapies, although their implementation in the clinical setting is in its infancy. In fact, despite the wealth of preclinical studies addressing these issues, the difficulty of testing each targeted therapy hypothesis in the clinical arena represents an intrinsic obstacle. As a consequence, we are witnessing a paradoxical situation where most hypotheses about the molecular and cellular biology of cancer remain clinically untested and therefore do not translate into a therapeutic benefit for patients.ObjectiveTo present a computational method aimed to comprehensively exploit the scientific knowledge in order to foster the development of personalized cancer treatment by matching the patient's molecular profile with the available evidence on targeted therapy.MethodsTo this aim we focused on melanoma, an increasingly diagnosed malignancy for which the need for novel therapeutic approaches is paradigmatic since no effective treatment is available in the advanced setting. Relevant data were manually extracted from peer-reviewed full-text original articles describing any type of anti-melanoma targeted therapy tested in any type of experimental or clinical model. To this purpose, Medline, Embase, Cancerlit and the Cochrane databases were searched.Results and conclusionsWe created a manually annotated database (Targeted Therapy Database, TTD) where the relevant data are gathered in a formal representation that can be computationally analyzed. Dedicated algorithms were set up for the identification of the prevalent therapeutic hypotheses based on the available evidence and for ranking treatments based on the molecular profile of individual patients. In this essay we describe the principles and computational algorithms of an original method developed to fully exploit the available knowledge on cancer biology with the ultimate goal of fruitfully driving both preclinical and clinical research on anticancer targeted therapy. In the light of its theoretical nature, the prediction performance of this model must be validated before it can be implemented in the clinical setting

Telomerase is an independent prognostic marker of overall survival in patients with colorectal cancer

Abstract: Background: Colorectal cancer (CRC) is an important cause of cancer-related death. Prediction of recurrence is an important issue in the treatment of disease, particularly for stage II patients. The level of telomere-specific reverse transcriptase (hTERT), the catalytic component of the telomerase complex, increases along with CRC progression, but its prognostic value is still unclear. Methods: One hundred and thirty-seven CRC patients were studied for hTERT expression in tumour cells by real-time PCR. hTERT level was evaluated as a prognostic factor of overall survival (OS) in all patients and of disease recurrence in a subgroup of 50 stage II patients. Results: The median hTERT level was 93.8 copies (interquartile range 48-254). Patients with high hTERT levels (above the median) showed a significantly worse survival than those with low hTERT levels (below the median; log-rank test P<0.0001; hazard ratio (HR) = 3.30 (95% confidence interval (CI) 1.98-5.52); P<0.0001). The negative prognostic value of high hTERT level is independent of the pathological stage and microsatellite instability (HR = 2.09 (95% CI 1.20-3.64), P = 0.009). Moreover, in stage II CRC, high hTERT levels identified patients with a higher risk of disease recurrence (HR = 3.06 (95% CI 1.03-9.04), P = 0.043) and death (HR = 3.24 (95% CI = 1.37-7.71), P = 0.008). Conclusion: hTERT level is an independent prognostic marker of OS in CRC patients. In addition, assessment of hTERT level could improve stratification of stage II CRC patients for the risk of disease recurrence

Circulating Cell-Free DNA: A Promising Marker of Pathologic Tumor Response in Rectal Cancer Patients Receiving Preoperative Chemoradiotherapy

PURPOSE: The circulating cell-free DNA (cfDNA) in plasma has been reported to be a marker of cancer detection. The aim of this study was to investigate whether the cfDNA has a role as response biomarker in patients receiving preoperative chemoradiotherapy (CRT) for rectal cancer. METHODS: Sixty-seven patients (median age 61 years; male/female 42/25) who underwent CRT for rectal cancer were evaluated. After tumor regression grade (TRG) classification was made, the patients were classified as having disease that responded (TRG 1-2) and that did not respond (TRG 3-5) to therapy. Plasma samples were obtained from patients before and after CRT. The cfDNA levels were analyzed by quantitative real-time polymerase chain reaction of \u3b2-globin. On the basis of the Alu repeats, the cfDNA was considered as either total (fragments of 115 bp, Alu 115) or tumoral (fragments of 247 bp, Alu 247). The association between the pre- or post-CRT levels and between variations during CRT of the Alu 247, Alu 115 repeat, and Alu 247/115 ratio (cfDNA integrity index) and the pathologic tumor response was analyzed. RESULTS: The baseline levels of cfDNA were not associated with tumor response. The post-CRT levels of the cfDNA integrity index were significantly lower in responsive compared to nonresponsive disease (P = 0.0009). Both the median value of the Alu 247 repeat and the cfDNA integrity index decreased after CRT in disease that responded to therapy (P < 0.005 and P < 0.005, respectively) compared to disease that did not respond to therapy (P = 0.83 and P = 0.726, respectively). The results of the multivariable logistic regression analysis showed that only the cfDNA integrity index was significantly and independently associated with tumor response to treatment. CONCLUSIONS: The plasma levels of the longer fragments (Alu 247) of cfDNA and the cfDNA integrity index are promising markers to predict tumor response after preoperative CRT for rectal cancer