Literature DB >> 26452385

Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

Joan Maurel1, Antonio Postigo.   

Abstract

Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients.

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Year:  2015        PMID: 26452385     DOI: 10.2174/156800961508151001102822

Source DB:  PubMed          Journal:  Curr Cancer Drug Targets        ISSN: 1568-0096            Impact factor:   3.428


  7 in total

1.  Optimal detection of clinically relevant mutations in colorectal carcinoma: sample pooling overcomes intra-tumoral heterogeneity.

Authors:  Andrew C Nelson; Jamie Boone; David Cartwright; Bharat Thyagarajan; Robyn Kincaid; Aaron P Lambert; Kylene Karnuth; Christine Henzler; Sophia Yohe
Journal:  Mod Pathol       Date:  2017-10-13       Impact factor: 7.842

Review 2.  High microsatellite instability (MSI-H) colorectal carcinoma: a brief review of predictive biomarkers in the era of personalized medicine.

Authors:  Zoran Gatalica; Semir Vranic; Joanne Xiu; Jeffrey Swensen; Sandeep Reddy
Journal:  Fam Cancer       Date:  2016-07       Impact factor: 2.375

3.  Prediction of novel target genes and pathways involved in irinotecan-resistant colorectal cancer.

Authors:  Precious Takondwa Makondi; Chi-Ming Chu; Po-Li Wei; Yu-Jia Chang
Journal:  PLoS One       Date:  2017-07-27       Impact factor: 3.240

Review 4.  Implementing liquid biopsies into clinical decision making for cancer immunotherapy.

Authors:  Dagmar Quandt; Hans Dieter Zucht; Arno Amann; Anne Wulf-Goldenberg; Carl Borrebaeck; Michael Cannarile; Diether Lambrechts; Herbert Oberacher; James Garrett; Tapan Nayak; Michael Kazinski; Charles Massie; Heidi Schwarzenbach; Michele Maio; Robert Prins; Björn Wendik; Richard Hockett; Daniel Enderle; Mikkel Noerholm; Hans Hendriks; Heinz Zwierzina; Barbara Seliger
Journal:  Oncotarget       Date:  2017-07-18

5.  Dual inhibition of MET and SRC kinase activity as a combined targeting strategy for colon cancer.

Authors:  Na Song; Xiujuan Qu; Shizhou Liu; Simeng Zhang; Jing Liu; Jinglei Qu; Huachuan Zheng; Yunpeng Liu; Xiaofang Che
Journal:  Exp Ther Med       Date:  2017-06-27       Impact factor: 2.447

6.  The prognostic value of abnormally expressed lncRNAs in colorectal cancer: A meta-analysis.

Authors:  June Wang; Shenlin Du; Jiamin Wang; Wei Fan; Ping Wang; Zheng Zhang; Peipei Xu; Shihui Tang; Qiaoling Deng; Weiqing Yang; Mingxia Yu
Journal:  PLoS One       Date:  2017-06-28       Impact factor: 3.240

7.  Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer.

Authors:  Precious Takondwa Makondi; Chia-Hwa Lee; Chien-Yu Huang; Chi-Ming Chu; Yu-Jia Chang; Po-Li Wei
Journal:  PLoS One       Date:  2018-01-17       Impact factor: 3.240

  7 in total

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