Evidence map›Paper›PMID 32404198›Full record

ArticleBMC cancer2020

Dynamic alterations of genome and transcriptome in KRAS G13D mutant CRC PDX model treated with cetuximab.

Hangyu Zhang, Liyun Yuan, Lulu Liu, Cong Yan, Jinming Cheng, Qihan Fu, Zhou Tong, Weiqin Jiang, Yi Zheng, Peng Zhao and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Hangyu ZhangDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Liyun YuanNational Genomics Data Center, Bio-Med Big Data Center, CAS-MPG Partner Institute for Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai, 200031, People's Republic of China.
Lulu LiuDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Cong YanDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Jinming ChengNational Genomics Data Center, Bio-Med Big Data Center, CAS-MPG Partner Institute for Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai, 200031, People's Republic of China.
Qihan FuDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Zhou TongDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Weiqin JiangDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Yi ZhengDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Peng ZhaoDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China.
Guoqing ZhangNational Genomics Data Center, Bio-Med Big Data Center, CAS-MPG Partner Institute for Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai, 200031, People's Republic of China. gqzhang@picb.ac.cn.
Weijia FangDepartment of Medical Oncology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People's Republic of China. weijiafang@zju.edu.cn.
Zhejiang University · CNShanghai Institute of Nutrition and Health · CNChinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 81472210Science and Technology Service Network Initiative of Chinese Academy of Sciences Y919C11011Young Scientists Fund 81602128
6 · The paper itself

Abstract

backgroundKRAS mutations have been characterized as the major predictive biomarkers for resistance to cetuximab treatment. However, studies indicate that not all KRAS mutations are associated with equivalent treatment outcomes. KRAS G13D mutations were observed to account for approximately 16% of all KRAS mutations in advanced colorectal cancer patients, and whether these patients can benefit from cetuximab has not been determined.

methodsAn established KRAS G13D mutant colorectal cancer (CRC) patient-derived xenograft (PDX) model was treated with cetuximab. After repeated use of cetuximab, treatment-resistant PDX models were established. Tissue samples were collected before and during treatment, and multiomics data were subsequently sequenced and processed, including whole-exome, mRNA and miRNA data, to explore potential dynamic changes.

resultsCetuximab treatment initially slowed tumor growth, but resistance developed not long after treatment. WES (whole-exome sequencing) and RNA sequencing found that 145 genes had low P values (< 0.01) when analyzed between the locus genotype and its related gene expression level. Among these genes, SWAP70 was believed to be a probable cause of acquired resistance. JAK2, PRKAA1, FGFR2 and RALBP1, as well as 10 filtered immune-related genes, also exhibited dynamic changes during the treatment.

conclusionsCetuximab may be effective in KRAS G13D mutation patients. Dynamic changes in transcription, as determined by WES and RNA sequencing, occurred after repeated drug exposure, and these changes were believed to be the most likely cause of drug resistance.

Indexed as

Drug Resistance, NeoplasmGenome, HumanMutationAnimalsAntineoplastic Agents, ImmunologicalApoptosisCell ProliferationCetuximabColorectal NeoplasmsFemaleHumansMiceMice, NudeProto-Oncogene Proteins p21(ras)TranscriptomeTumor Cells, CulturedAntineoplastic Agents, ImmunologicalCetuximabKRAS protein, humanProto-Oncogene Proteins p21(ras)Cetuximab resistanceColorectal cancerRNA sequencingWhole-exome sequencing

Identifiers

PMID32404198
PMCPMC7222508
OpenAlexW3027890341

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.