Periodic Reporting for period 1 - EPICUP (Development of a ncRNA DNA Methylation Kit for the Diagnosis of Cancer of Unknown Primary)
Okres sprawozdawczy: 2015-02-01 do 2016-01-31
Cancer of Unknown Primary (CUP) is a heterogeneous disease that comprises approximately 2-8% of all cancer cases in the world. It is defined by the presence of metastatic disease with no identified primary tumor at presentation using established diagnostic tools. Hence, in these patients the outcome is extremely poor, in part for lack of knowledge of which is the most suitable treatment. Indeed, it has been reported an improving in survival in those patients whose primary tumor was finally identified. Unfortunately, these patients nowadays represent less than 50% of CUP cases, in spite of improving in diagnostic strategies. This scenario makes clear the need to progress in the understanding of the formation of CUP and increase the likelihood of the development of effective prediction tools and therapies, with the ultimate aim of improving survival. Indeed, a higher diagnostic accuracy allows an optimization of prognosis and a properly treatment selection, avoiding unnecessary toxicities derived from administration of drugs for which tumor is refractory, increasing hence the quality of life of patients.
Personalized oncology is one of the major goals of the current strategies based in high-throughput techniques for molecular characterization, giving rise to biomarkers signatures that will permit a more accurate individualized managing of the patient. It is important to highlight the demonstrated evidences of the involvement of epigenetic alterations in cancer development. Despite genetic aberrations are crucial, they are not enough to explain carcinogenic processes. Epigenetics is a mechanism of genomic regulation for which no changes in genetic code are contemplated. It is defined with a flexible and reversible event with a high impact in tumorogenesis. Indeed, it has been reported the capacity of these molecular signatures of classifying human tissues, both healthy and tumoral, from different locations, using high-throughput and system biology approaches. In this context, by means of using computational biology, in the present PoC it has been generated a bioinformatic tool which permits to identify the origin of CUP cases according to their own epigenetic characteristics. A scientific breakthrough in the understanding of tumor type biology is the acceptance that every malignancy originated from distinct tissue has its own particular DNA methylation profile. However, coding zones includes an extremely high percentage of "house-keeping" genes where DNA methylation profiles are not able to easily distinguish tumor types. This is different for non-coding RNAs (ncRNAs), where a tissue-type expression, many times linked to DNA methylation tissue-type profile, is a common hallmark of these transcripts. As part of the ERC Advanced Grant “Epigenetic Disruption on Non-Coding RNAs in Human Cancer” (EPINORC), aimed at determining the contribution of DNA methylation alterations to the aberrant activity of ncRNA loci in human cancer, it has been used an advanced DNA methylation microarray technology, InfiniuHumanMethylation450 BeadChip from Illumina, to detect CpG methylation changes in a wide variety of ncRNAs (microRNAs, lincRNAs, T-UCRs, snoRNAs, piRNAs...) to increase the tumor-type prediction accuracy comparing with the accuracy reached when it is only considered CpGs sites in coding regions. Moreover, EPICUP prediction assay has also been optimized as a user-friendly and cost effective approach using little amount of DNA extracted from paraffin sections (that it is the clinical scenario encountered in the diagnosis of CUPs), fact that has made it interesting commercially.
With the aim to generate a bioinformatic predictor for indentifying the origin of primary tumor that CUP metastases come from, a discovery set of 2,790 samples from different known tumor types were analyzed, using DNA methylation technology, to establish methylation differences that allowed discriminating between different types. These results were validated in an independent cohort formed by 7,691 known tumor samples, being the algorithm capable to distinguish among 38 tumor types. Interestingly, the quantity of tumor types included in our bioinformatic test is higher than any of the commercialized platforms for CUP origin prediction. From 485,577 CpG sites from 450K strategy, 820 were included in the resulting bioinformatic algorithm, named EPICUP. Interestingly, 6.7% (55 of 820) of them corresponded to CpG sites located in ncRNA genome regions and, these allowed improving the accuracy of the tool increasing sensitivity and specificity to 97.7% and 99.6% respectively. Further for clinical validation, EPICUP tool was retrospectively applied in prediction of the origin of 216 well-characterized CUP samples, being informative in 87% of cases. The accuracy of the predictor in this set was around 85-95%.
The EPICUP project aims to solve the existing biodiagnostic gap in the analysis of CUPs within the personal cancer genomics field. The existing image and pathological diagnostic tests has proven short of expectations to determine the tumor site or origin for more than half of the currently diagnosed CUPs. This explains why, to date, this group of patients has an extremely poor overall survival. In particular, one of the main innovations of the technique to be develop is the selection of those particular CpG sites in ncRNA genomic loci that derived from our current work within the ERC Advanced EPINORC project have shown important tumor-type specific differences, which allows to interrogate the CUP DNA in an unbiased manner using genetic material from paraffin embedded sections. This PoC project has led this technology closer to the market by helping us to create a fully develop kit to determine many of methylation changes that characterizes every tumor type of the human body. In this sense, it will provide oncologist and pathologists with a unique tool that can be used to achieve a match-up between the epigenomic profile and the tumor site of origin of the CUP, allowing a more accurate diagnostic and a personalized medicine.
Regarding socioeconomic impact, EPICUP is a new potential diagnostic tool that, together with histopathological and clinical strategies currently used, supposes to be advancement in the finding of originally tumor in cases firstly diagnosed as CUP. In this sense, the physician could optimize managing of disease administering the most suitable therapy and leading to better longevity and quality of life for patients. Moreover, the administration of suitable treatment would reduce unnecessary toxicities and associated hospitalization costs, optimizing the economic impact in Health System.
Personalized oncology is one of the major goals of the current strategies based in high-throughput techniques for molecular characterization, giving rise to biomarkers signatures that will permit a more accurate individualized managing of the patient. It is important to highlight the demonstrated evidences of the involvement of epigenetic alterations in cancer development. Despite genetic aberrations are crucial, they are not enough to explain carcinogenic processes. Epigenetics is a mechanism of genomic regulation for which no changes in genetic code are contemplated. It is defined with a flexible and reversible event with a high impact in tumorogenesis. Indeed, it has been reported the capacity of these molecular signatures of classifying human tissues, both healthy and tumoral, from different locations, using high-throughput and system biology approaches. In this context, by means of using computational biology, in the present PoC it has been generated a bioinformatic tool which permits to identify the origin of CUP cases according to their own epigenetic characteristics. A scientific breakthrough in the understanding of tumor type biology is the acceptance that every malignancy originated from distinct tissue has its own particular DNA methylation profile. However, coding zones includes an extremely high percentage of "house-keeping" genes where DNA methylation profiles are not able to easily distinguish tumor types. This is different for non-coding RNAs (ncRNAs), where a tissue-type expression, many times linked to DNA methylation tissue-type profile, is a common hallmark of these transcripts. As part of the ERC Advanced Grant “Epigenetic Disruption on Non-Coding RNAs in Human Cancer” (EPINORC), aimed at determining the contribution of DNA methylation alterations to the aberrant activity of ncRNA loci in human cancer, it has been used an advanced DNA methylation microarray technology, InfiniuHumanMethylation450 BeadChip from Illumina, to detect CpG methylation changes in a wide variety of ncRNAs (microRNAs, lincRNAs, T-UCRs, snoRNAs, piRNAs...) to increase the tumor-type prediction accuracy comparing with the accuracy reached when it is only considered CpGs sites in coding regions. Moreover, EPICUP prediction assay has also been optimized as a user-friendly and cost effective approach using little amount of DNA extracted from paraffin sections (that it is the clinical scenario encountered in the diagnosis of CUPs), fact that has made it interesting commercially.
With the aim to generate a bioinformatic predictor for indentifying the origin of primary tumor that CUP metastases come from, a discovery set of 2,790 samples from different known tumor types were analyzed, using DNA methylation technology, to establish methylation differences that allowed discriminating between different types. These results were validated in an independent cohort formed by 7,691 known tumor samples, being the algorithm capable to distinguish among 38 tumor types. Interestingly, the quantity of tumor types included in our bioinformatic test is higher than any of the commercialized platforms for CUP origin prediction. From 485,577 CpG sites from 450K strategy, 820 were included in the resulting bioinformatic algorithm, named EPICUP. Interestingly, 6.7% (55 of 820) of them corresponded to CpG sites located in ncRNA genome regions and, these allowed improving the accuracy of the tool increasing sensitivity and specificity to 97.7% and 99.6% respectively. Further for clinical validation, EPICUP tool was retrospectively applied in prediction of the origin of 216 well-characterized CUP samples, being informative in 87% of cases. The accuracy of the predictor in this set was around 85-95%.
The EPICUP project aims to solve the existing biodiagnostic gap in the analysis of CUPs within the personal cancer genomics field. The existing image and pathological diagnostic tests has proven short of expectations to determine the tumor site or origin for more than half of the currently diagnosed CUPs. This explains why, to date, this group of patients has an extremely poor overall survival. In particular, one of the main innovations of the technique to be develop is the selection of those particular CpG sites in ncRNA genomic loci that derived from our current work within the ERC Advanced EPINORC project have shown important tumor-type specific differences, which allows to interrogate the CUP DNA in an unbiased manner using genetic material from paraffin embedded sections. This PoC project has led this technology closer to the market by helping us to create a fully develop kit to determine many of methylation changes that characterizes every tumor type of the human body. In this sense, it will provide oncologist and pathologists with a unique tool that can be used to achieve a match-up between the epigenomic profile and the tumor site of origin of the CUP, allowing a more accurate diagnostic and a personalized medicine.
Regarding socioeconomic impact, EPICUP is a new potential diagnostic tool that, together with histopathological and clinical strategies currently used, supposes to be advancement in the finding of originally tumor in cases firstly diagnosed as CUP. In this sense, the physician could optimize managing of disease administering the most suitable therapy and leading to better longevity and quality of life for patients. Moreover, the administration of suitable treatment would reduce unnecessary toxicities and associated hospitalization costs, optimizing the economic impact in Health System.