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By analyse the tissue/blood variant spectrum model using NGS, the present clinical trial aims to elucidate the genetic basis of CRC in Chinese; to establish of CRC genetic map in Chinese patients; to identification new genetic biomarkers, drug and pathways; and to subtyping for precision treatment and management for Chinese CRC patients.
Colorectal cancer (CRC), as one of the common malignant tumors with high morbidity and mortality, is a major health threat in China. Surgical resection is the conventional treatment for early and intermediate stage CRC, chemotherapy is the main treatment for late stage CRC.
Circulating tumor DNA (ctDNA) is tumor-derived fragmented DNA with an average size of 170bp, mixed with cell free DNA (cfDNA) of other sources in blood circulation. Although the mechanisms of its release have not been fully addressed, apoptosis and/or necrosis of tumor cells and serum exosome are considered as its main source, which makes it a genomic reservoir of different tumor clones. Also, as its half-life is up to hours, ctDNA is reflecting the most up-to-date status of tumor genome. Hence, it allows for noninvasive molecular characterization of tumors,which can be qualitative, quantitative and used for disease monitoring. The possibility of that ctDNA could be used to detect micrometastatic disease in patients received surgical resection was suggested in several studies. Using Next Generation Sequencing (NGS), Newman et al. have shown that the serum level of ctDNA was correlated with tumor progress and prognosis in NSCLC. Isaac et al. demonstrated the postoperative ctDNA level was associated with breast cancer progression, and it was more sensitive compared to CT scan for predicting the early relapse. Tie et al. examined the postoperative ctDNA level of 1046 plasma samples from a prospective cohort of 230 patients with resected stage II CRC by NGS, and their results demonstrated that recurrence happened in 79% of the patients with positive postoperative ctDNA at median follow-up of 27 months, versus 9.8% in the negative postoperative ctDNA group.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Retrospective cohort | Whole exome sequencing of 2500 retrospective tissue sample. | ||
| Prospective cohort | Whole exome sequencing of 500 prospectively collected tissue samples. Panel sequencing of 451 genes of prospectively collected blood samples. |
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| Measure | Description | Time Frame |
|---|---|---|
| prediction accuracy of survival rate | We will use the gene mutation data and follow-up data of the patients to construct a prediction model,the accuracy of model to anticipating the 5 year survival rate of patients is the primary endpoint | through study completion, an average of 5 years |
| prediction accuracy of recurrent rate | We will use the gene mutation data and follow-up data of the patients to construct a prediction model,the accuracy of model to anticipating the 3 year recurrent rate of patients is the primary endpoint | through study completion, an average of 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Mutation Consistency of tissue and blood sample | We do NGS sequencing of both the tissue sample and blood sample of the CRC patients. The gene mutation data will be analysis, and the percentage of same and different mutation of tissue and blood sample will be reported. | through study completion, an average of 3 years |
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Inclusion Criteria:
Retrospective cohort:
Prospective cohort:
Exclusion Criteria:
Retrospective cohort:
4. The date of treatment after surgery are not integrity, outcome data are not available
Prospective cohort:
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Patients must have baseline evaluations performed prior to the study and must meet all inclusion and exclusion criteria. In addition, the patient of the prospective cohort should be thoroughly informed about the study, including the study visit schedule and required evaluations and all regulatory requirements for informed consent. The written informed consent of the prospective cohort should be obtained from the patient prior to enrollment. The following criteria apply to all patients enrolled onto the study unless otherwise specified.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Feng Wang, MD.,PhD. | Contact | +862087343795 | wangfeng@sysucc.org.cn |
| Name | Affiliation | Role |
|---|---|---|
| Ruihua Xu, MD.,PhD | Sun Yat-sen University | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Medical Oncology,Sun Yat-sen University Cancer Center | Recruiting | Guangzhou | Guangdong | 510060 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26457759 | Background | Guinney J, Dienstmann R, Wang X, de Reynies A, Schlicker A, Soneson C, Marisa L, Roepman P, Nyamundanda G, Angelino P, Bot BM, Morris JS, Simon IM, Gerster S, Fessler E, De Sousa E Melo F, Missiaglia E, Ramay H, Barras D, Homicsko K, Maru D, Manyam GC, Broom B, Boige V, Perez-Villamil B, Laderas T, Salazar R, Gray JW, Hanahan D, Tabernero J, Bernards R, Friend SH, Laurent-Puig P, Medema JP, Sadanandam A, Wessels L, Delorenzi M, Kopetz S, Vermeulen L, Tejpar S. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015 Nov;21(11):1350-6. doi: 10.1038/nm.3967. Epub 2015 Oct 12. | |
| 25444714 |
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| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
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The fresh tumor tissues/biopsies of each patient will be collected during the surgical resection. The peripheral blood samples of each patient will be collected at the following time points: 1) prior to the surgical treatment; 2) prior to the chemotherapy/targeted therapy/immunotherapy; 3) every real efficacy evaluation, until disease progression (up to 24 months).
| Background |
| Rolfo C, Castiglia M, Hong D, Alessandro R, Mertens I, Baggerman G, Zwaenepoel K, Gil-Bazo I, Passiglia F, Carreca AP, Taverna S, Vento R, Santini D, Peeters M, Russo A, Pauwels P. Liquid biopsies in lung cancer: the new ambrosia of researchers. Biochim Biophys Acta. 2014 Dec;1846(2):539-46. doi: 10.1016/j.bbcan.2014.10.001. Epub 2014 Oct 16. |
| 23603797 | Background | Yu SC, Lee SW, Jiang P, Leung TY, Chan KC, Chiu RW, Lo YM. High-resolution profiling of fetal DNA clearance from maternal plasma by massively parallel sequencing. Clin Chem. 2013 Aug;59(8):1228-37. doi: 10.1373/clinchem.2013.203679. Epub 2013 Apr 19. |
| 24705333 | Background | Newman AM, Bratman SV, To J, Wynne JF, Eclov NC, Modlin LA, Liu CL, Neal JW, Wakelee HA, Merritt RE, Shrager JB, Loo BW Jr, Alizadeh AA, Diehn M. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med. 2014 May;20(5):548-54. doi: 10.1038/nm.3519. Epub 2014 Apr 6. |
| 26311728 | Background | Garcia-Murillas I, Schiavon G, Weigelt B, Ng C, Hrebien S, Cutts RJ, Cheang M, Osin P, Nerurkar A, Kozarewa I, Garrido JA, Dowsett M, Reis-Filho JS, Smith IE, Turner NC. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci Transl Med. 2015 Aug 26;7(302):302ra133. doi: 10.1126/scitranslmed.aab0021. |
| 27384348 | Background | Tie J, Wang Y, Tomasetti C, Li L, Springer S, Kinde I, Silliman N, Tacey M, Wong HL, Christie M, Kosmider S, Skinner I, Wong R, Steel M, Tran B, Desai J, Jones I, Haydon A, Hayes T, Price TJ, Strausberg RL, Diaz LA Jr, Papadopoulos N, Kinzler KW, Vogelstein B, Gibbs P. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci Transl Med. 2016 Jul 6;8(346):346ra92. doi: 10.1126/scitranslmed.aaf6219. |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |