A Phase II Clinical Trial Comparing the Efficacy of RO7198457 Versus Watchful Waiting in Patients With ctDNA-positive, Resected Stage II (High Risk) and Stage III Colorectal Cancer
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ABSTRACT:
DISEASE(S): Colorectal Cancer (stage Ii [high Risk] And Stage Iii),Colorectal Cancer,Neoplasms Benign, Malignant And Unspecified (incl Cysts And Polyps),Colorectal Neoplasms,Cancer,Colorectal Cancer Stage Ii,Colorectal Cancer Stage Iii
PROVIDER: 2346758 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration.
2009-07-02 | GSE12032 | GEO
Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration. Of 198 samples, 129 represented the discovery phase and 69 represented the validation phase.
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Project description:Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient but combination with molecular markers may improve tumors classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors but their implementation in medical practice remains controversial. Stage-II tumors have been recognized as a heterogeneous group and high-risk morphologic features have been retained as justifying adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defect. A series of 130 colon cancer samples was retained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical then supervised analyses were successively performed applying the data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with an adjusted p-values lower than 10^-10. A subgroup of stage-II tumors aggregated this cluster in both series. No correlation was found between with the disease severity but the function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies. Further pharmacogenetic studies might document this observation. Expression profile of stage-II colon carcinomas distinguishes two patterns of tumors based on a 7-gene signature. One pattern is very similar to that of stage-III tumors and the corresponding tumors aggregate into a single cluster. Genes function suggests possible tumor determinism in drug response more than in prognosis evolution.
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