scholarly journals Contribution of Genetic Variants of ATP Transporters (ABCC1 and ABCG2) genes with the Pathogenesis of Colorectal Cancer

2018 ◽  
Vol 15 (3) ◽  
pp. 555-559
Author(s):  
Huda A. Al Doghaither ◽  
Ayat B. Al-Ghafari

Colorectal cancer (CRC) is one of the major cancers that is characterized with high percentage of morbidity worldwide due to the advanced metastatic cancer that developed via acquired drug resistance mechanisms. Therefore, there is an urgent need to identify genetic variants in major genes that could contribute to the poor overall survival rate and drug-resistance. ATP-binding cassette (ABC) transporters are among the most studied genes that are related to the development of many cancers including CRC. In this study, three variants namely (G2168A and G3173A) in ABCC1 and (C421A) in ABCG2 were examined to evaluate their contribution to CRC in Saudi Arabia. DNA was extracted from the whole blood of 62 CRC patients and 100 controls. PCR-RFLP technique was used to identify the different genotypes among Saudi population. All statistical data were obtained by chi-square test and P values ˂0.05 were considered statistically significant. Interestingly, neither of the tested variants showed heterozygous nor homozygous distribution among the 162 samples. Therefore, those variants are rare in Saudi population and are not suspected to be involved in CRC pathogenesis. In conclusion, those variants cannot be used as diagnostic or prognostic markers for CRC in Saudi Arabia. However, more experiments need to be performed to confirm our findings.

2017 ◽  
Vol 77 (12) ◽  
pp. 3364-3375 ◽  
Author(s):  
Federica Eduati ◽  
Victoria Doldàn-Martelli ◽  
Bertram Klinger ◽  
Thomas Cokelaer ◽  
Anja Sieber ◽  
...  

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Zuan-Fu Lim ◽  
Patrick C. Ma

AbstractThe biggest hurdle to targeted cancer therapy is the inevitable emergence of drug resistance. Tumor cells employ different mechanisms to resist the targeting agent. Most commonly in EGFR-mutant non-small cell lung cancer, secondary resistance mutations on the target kinase domain emerge to diminish the binding affinity of first- and second-generation inhibitors. Other alternative resistance mechanisms include activating complementary bypass pathways and phenotypic transformation. Sequential monotherapies promise to temporarily address the problem of acquired drug resistance, but evidently are limited by the tumor cells’ ability to adapt and evolve new resistance mechanisms to persist in the drug environment. Recent studies have nominated a model of drug resistance and tumor progression under targeted therapy as a result of a small subpopulation of cells being able to endure the drug (minimal residual disease cells) and eventually develop further mutations that allow them to regrow and become the dominant population in the therapy-resistant tumor. This subpopulation of cells appears to have developed through a subclonal event, resulting in driver mutations different from the driver mutation that is tumor-initiating in the most common ancestor. As such, an understanding of intratumoral heterogeneity—the driving force behind minimal residual disease—is vital for the identification of resistance drivers that results from branching evolution. Currently available methods allow for a more comprehensive and holistic analysis of tumor heterogeneity in that issues associated with spatial and temporal heterogeneity can now be properly addressed. This review provides some background regarding intratumoral heterogeneity and how it leads to incomplete molecular response to targeted therapies, and proposes the use of single-cell methods, sequential liquid biopsy, and multiregion sequencing to discover the link between intratumoral heterogeneity and early adaptive drug resistance. In summary, minimal residual disease as a result of intratumoral heterogeneity is the earliest form of acquired drug resistance. Emerging technologies such as liquid biopsy and single-cell methods allow for studying targetable drivers of minimal residual disease and contribute to preemptive combinatorial targeting of both drivers of the tumor and its minimal residual disease cells.


2017 ◽  
Vol 8 ◽  
Author(s):  
Mohammad J. Nasiri ◽  
Mehri Haeili ◽  
Mona Ghazi ◽  
Hossein Goudarzi ◽  
Ali Pormohammad ◽  
...  

2021 ◽  
Vol 5 (1 (January)) ◽  
pp. 88-93
Author(s):  
Hasan KURTER ◽  
Janberk YEŞİL ◽  
Ezgi DASKIN ◽  
Gizem ÇALIBAŞI KOÇAL ◽  
Hülya ELLİDOKUZ ◽  
...  

2018 ◽  
Author(s):  
Sha Cao ◽  
Wennan Chang ◽  
Changlin Wan ◽  
Yong Zhang ◽  
Jing Zhao ◽  
...  

In light of the marked differences in the intrinsic biological underpinnings and prognostic outcomes among different subtypes, Consensus Molecular Subtype (CMS) classification provides a new taxonomy of colorectal cancer (CRC) solely based on transcriptomics data and has been accepted as a standard rule for CRC stratification. Even though CMS was built on highly cancer relevant features, it suffers from limitations in capturing the promiscuous mechanisms in a clinical setting. There are at least two facts about using transcriptomic data for prognosis prediction: the engagement of genes or pathways that execute the clinical response pathway are highly dynamic and interactive with others; and a predefined patient stratification not only largely decrease the statistical analysis power, but also excludes the fact that clusters of patients that confer similar clinical outcomes may or may not overlap with a pre-defined subgrouping. To enable a flexible and prospective stratified exploration, we here present a novel computational framework based on bi-clustering aiming to identify gene regulatory mechanisms associated with various biological, clinical and drug-resistance features, with full recognition of the transiency of transcriptional regulation and complicacies of patients subgrouping with regards to different biological and clinical settings. Our analysis on multiple large scale CRC transcriptomics data sets using a bi-clustering based formulation suggests that the detected local low rank modules can not only generate new biological understanding coherent to CMS stratification, but also identify predictive markers for prognosis that are general to CRC or CMS dependent, as well as novel alternative drug resistance mechanisms. Our key results include: (1) a comprehensive annotation of the local low rank module landscape of CRC; (2) a mechanistic relationship between different clinical subtypes and outcomes, as well as their characteristic biological underpinnings, visible through a novel consensus map; and (3) a few (novel) resistance mechanisms of Oxaliplatin, 5-Fluorouracil, and the FOLFOX therapy are revealed, some of which are validated on independent datasets.


2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 595-595
Author(s):  
Junjie Gu ◽  
Zhao Sun ◽  
Chunmei Bai ◽  
Fei Luo

595 Background: Colorectal cancer(CRC) is the fourth most prevalent cancer and the leading cause of cancer mortality worldwide. Drug resistance remains the main obstacle to the success of cytotoxic therapies. It is reported that soluble factors released by carcinoma-associated fibroblasts(CAFs) can induce the translocation of AKT, Survivin, P38 to the nucleus of tumor cells, which might be the mechanism of microenvironment-mediated drug resistance to nonspecific conventional chemotherapeutic agents, such as platinum compounds or 5-FU. Methods: Clinicopathological data of colorectal cancer patients who underwent chemotherapy (XELOX or FOLFOX) were collected, followed up and evaluated. p-AKT and survivin expression were assessed by immunohistochemical (IHC) staining. The relationships between p-AKT and survivin expression and patients’ resistance to chemotherapy were analyzed by Chi square respectively. The expression between p-AKT and survivin expression and progression-free survival(PFS) of patients were analyzed by Kaplan-Meier. Results: 51 CRC patients were enrolled in our research. Among them, 21 patients were resistant to chemotherapy(PD), and 30 patients were sensitive to chemotherapy(PR). P-AKT and survivin were assessed by IHC in 47 patients. Among them, 17 patients were p-AKT positive, and 29 patients were survivin positive. Patients of progressive disease(resistant to chemotherapy) were significantly associated with p-AKT positive and survivin positive(p = 0.009, 0.000). Poorer progression-free survival(PFS) was observed in patients with survivin positive compared to those with survivin negative(6.323±0.9m, 13.857±2.664m, Breslow chi square = 4.885, p value = 0.027). There is no significant difference between p-AKT expression and PFS(Breslow chi square = 2.403, p value = 0.121). Conclusions: CRC patients with p-AKT positive or survivin positive were more likely to be resistant to chemotherapeutic agents. CRC patients with survivin positive had a shorter DFS.


2014 ◽  
Vol 59 (2) ◽  
pp. 1152-1161 ◽  
Author(s):  
Yongfei Hu ◽  
Yuying Zhu ◽  
Yanan Ma ◽  
Fei Liu ◽  
Na Lu ◽  
...  

ABSTRACTAchromobacter xylosoxidansis an opportunistic pathogen known to be resistant to a wide range of antibiotics; however, the knowledge about the drug resistance mechanisms is limited. We used a high-throughput sequencing approach to sequence the genomes of theA. xylosoxidanstype strain ATCC 27061 and a clinical isolate,A. xylosoxidansX02736, and then we used different bioinformatics tools to analyze the drug resistance genes in these bacteria. We obtained the complete genome sequence forA. xylosoxidansATCC 27061 and the draft sequence for X02736. We predicted a total of 50 drug resistance-associated genes in the type strain, including 5 genes for β-lactamases and 17 genes for efflux pump systems; these genes are also conserved among otherA. xylosoxidansgenomes. In the clinical isolate, except for the conserved resistance genes, we also identified several acquired resistance genes carried by a new transposon embedded in a novel integrative and conjugative element. Our study provides new insights into the intrinsic and acquired drug resistance mechanisms inA. xylosoxidans, which will be helpful for better understanding the physiology ofA. xylosoxidansand the evolution of antibiotic resistance in this bacterium.


2017 ◽  
Vol 38 (3) ◽  
pp. 1420-1430 ◽  
Author(s):  
Jian Sun ◽  
Ke Xu ◽  
Yanyan Qiu ◽  
Hong Gao ◽  
Jianhua Xu ◽  
...  

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