Using plasma cell‐free DNA to monitor the chemoradiotherapy course of cervical cancer

Tian, Jichao; Geng, Yan; Lv, Dekang; Li, Peiying; Córdova, Miguel; Liao, Yuwei; Tian, Xiaoyuan; Zhang, Xiaolong; Zhang, Qingzheng; Zou, Kun; Zhang, Yu; Zhang, Xia; Li, Yulong; Zhang, Jian; Ma, Zhaokui; Shao, Yanyan; Song, Limei; Owen, Gareth I.; Li, Tingting; Liu, Ruimei; Liu, Quentin; Zou, Lijuan; Zhang, Zhuo; Li, Chi Kong

doi:10.1002/ijc.32295

Cited by 28 publications

(25 citation statements)

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“…Recent liquid biopsy studies showed that cell-free DNA (cfDNA), which originates from the apoptosis and necrosis of normal and tumor cells may be valuable for monitoring tumor behaviors and treatment responses [ 6 – 8 ]. The detection of HPV16 and HPV18 DNA or alterations in the cfDNA of patients with CC patients is used as biomarkers for recurrence monitoring [ 9 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

Efficient mutation screening for cervical cancers from circulating tumor DNA in blood

Lee

Chae²,

Lee³

et al. 2020

BMC Cancer

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Background Early diagnosis and continuous monitoring are necessary for an efficient management of cervical cancers (CC). Liquid biopsy, such as detecting circulating tumor DNA (ctDNA) from blood, is a simple, non-invasive method for testing and monitoring cancer markers. However, tumor-specific alterations in ctDNA have not been extensively investigated or compared to other circulating biomarkers in the diagnosis and monitoring of the CC. Therfore, Next-generation sequencing (NGS) analysis with blood samples can be a new approach for highly accurate diagnosis and monitoring of the CC. Method Using a bioinformatics approach, we designed a panel of 24 genes associated with CC to detect and characterize patterns of somatic single-nucleotide variations, indels, and copy number variations. Our NGS CC panel covers most of the genes in The Cancer Genome Atlas (TCGA) as well as additional cancer driver and tumor suppressor genes. We profiled the variants in ctDNA from 24 CC patients who were being treated with systemic chemotherapy and local radiotherapy at the Jeonbuk National University Hospital, Korea. Result Eighteen out of 24 genes in our NGS CC panel had mutations across the 24 CC patients, including somatic alterations of mutated genes ( ZFHX3– 83%, KMT2C- 79% , KMT2D- 79%, NSD1–67%, ATM- 38% and RNF213 –27%). We demonstrated that the RNF213 mutation could be used potentially used as a monitoring marker for response to chemo- and radiotherapy. Conclusion We developed our NGS CC panel and demostrated that our NGS panel can be useful for the diagnosis and monitoring of the CC, since the panel detected the common somatic variations in CC patients and we observed how these genetic variations change according to the treatment pattern of the patient.

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Section: Introductionmentioning

confidence: 99%

Efficient mutation screening for cervical cancers from circulating tumor DNA in blood

Lee

Chae²,

Lee³

et al. 2020

BMC Cancer

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“…A number of studies have reported that tumor size is a prognostic factor used to predict patient progression and outcomes [51]. A Previous study related to AFD demonstrated the effectiveness of AFD in predicting the benefit and response of cervical cancer patients to treatment and the predicted evidence of metastases was better than tumor size [27]. AFD performed in our study was independent of the tumor size, patients with high AFD had worse progression compared to patients with low AFD values.…”

Section: Discussionmentioning

confidence: 44%

“…In addition, dVAF has also been identified as a predictor of clinical outcomes at NSCLC and UC [23], Moreover, several studies bagan to identify gene biomarkers related to NSCLC prognosis [24][25][26]. Another study on AFD involved cervical cancer patients revealed that AFD is positively correlated with therapy response and helps in expecting the progression-free survival 27 .…”

Section: Introductionmentioning

confidence: 99%

“…This approach has helped us to recognize a novel 7-gene signature which can be used for successfully prediction of prognostic risk in NSCLC patients (secondary aim). Kemer content and over-represented sequences [27]. Sequencing readings were aligned with the human reference genome (hg38) using the Burrows-Wheeler Aligner (BWA) software package with the default parameters [28], and we removed the reads that were mapped in multiple genome positions.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Overall Survival for Early-stage Non-small Cell Lung Cancer via a Novel 7-gene Prognostic Signature and Allele Frequency Deviation (AFD)

Al-Dherasi

Liao

Huang

et al. 2020

Preprint

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Background Due to the late and poor prognosis of non-small lung cancer(NSCLC), the mortality of patients is high, underlines the need to identify a credible prognostic marker for NSCLC patients. The aim of our study is to examine the association of allele frequency deviation (AFD) with the patient's survival, as well as identification and validation of a new prognostic signature to predict NSCLC overall survival(OS).Methods First, we developed a new algorithm to calculate AFD from whole-exome sequencing(WES) data, then we compared the predictability of the patient's survival between AFD, tumor mutation burden (TMB) and change of variants allele frequency (dVAF). Second, we overlapped the differentially expressed genes (DEGs) from our data with the genes associated with the survival of The Cancer Genome Atlas (TCGA) database to confirm all genes significantly related to the survival of lung cancer. We identified 149 genes, 31 of which are new genes and have not been reported for lung cancer, that was used to develop a new prognostic model. Lung cancer adenocarcinoma (LUAD) data from the TCGA database was used to validate the gene-signature model. The prognostic model relating to the genes was established and validated in training and LUAD validation groups.Results There was a significant association found between the high AFD value and poor survival among non-small cell lung cancer (NSCLC) patients. A novel seven genes (UCN2, RIMS2, CAVIN2, GRIA1, PKHD1L1, PGM5, CLIC6) were obtained through multivariate Cox regression analysis and significantly associated with NSCLC patients survival. Cox regression analysis confirmed that AFD and 7-gene signature are an independent prognostic marker in NSCLC patients. The AUC for 5-year survival in AFD and the AUC for 3-year survival in both training and validation groups were greater than 0.7.Conclusion As a result, AFD and 7-gene signatures were identified as new independent predictive factors used for predicting the survival among NSCLC patients.

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“…In-house pipelines were used to process the sequencing of 54 WES data. Tumor and normal samples quality data were evaluated using FastQC (http:/www.bioinformatics.babraham.ac.uk/projects/fastqc/), including sequence length distribution, GC content, aspect of per-base quality, sequence duplicate levels, Kemer content and over-represented sequences [27]. Sequencing readings were aligned with the human reference genome (hg38) using the Burrows-Wheeler Aligner (BWA) software package with the default parameters [28], and we removed the reads that were mapped in multiple genome positions.…”

Section: Alignment and Quality Controlmentioning

confidence: 99%

Prediction of Overall Survival for Early-stage Non-small Cell Lung Cancer via a Novel 7-gene Prognostic Signature and Allele Frequency Deviation (AFD)

Al-Dherasi

Liao

Huang

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Due to the late and poor prognosis of non-small lung cancer(NSCLC), the mortality of patients is high, underlines the need to identify a credible prognostic marker for NSCLC patients. The aim of our study is to examine the association of allele frequency deviation (AFD) with the patient's survival, as well as identification and validation of a new prognostic signature to predict NSCLC overall survival(OS).Methods: First, we developed a new algorithm to calculate AFD from whole-exome sequencing(WES) data, then we compared the predictability of the patient's survival between AFD, tumor mutation burden (TMB) and change of variants allele frequency (dVAF). Second, we overlapped the differentially expressed genes (DEGs) from our data with the genes associated with the survival of The Cancer Genome Atlas (TCGA) database to confirm all genes significantly related to the survival of lung cancer. We identified 149 genes, 31 of which are new genes and have not been reported for lung cancer, that was used to develop a new prognostic model. Lung cancer adenocarcinoma (LUAD) data from the TCGA database was used to validate the gene-signature model. The prognostic model relating to the genes was established and validated in training and LUAD validation groups. Results: There was a significant association found between the high AFD value and poor survival among non-small cell lung cancer (NSCLC) patients. A novel seven genes (UCN2, RIMS2, CAVIN2, GRIA1, PKHD1L1, PGM5, CLIC6) were obtained through multivariate Cox regression analysis and significantly associated with NSCLC patients survival. Cox regression analysis confirmed that AFD and 7-gene signature are an independent prognostic marker in NSCLC patients. The AUC for 5-year survival in AFD and the AUC for 3-year survival in both training and validation groups were greater than 0.7.Conclusion: As a result, AFD and 7-gene signatures were identified as new independent predictive factors used for predicting the survival among NSCLC patients.

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Using plasma cell‐free DNA to monitor the chemoradiotherapy course of cervical cancer

Cited by 28 publications

References 55 publications

Efficient mutation screening for cervical cancers from circulating tumor DNA in blood

Efficient mutation screening for cervical cancers from circulating tumor DNA in blood

Prediction of Overall Survival for Early-stage Non-small Cell Lung Cancer via a Novel 7-gene Prognostic Signature and Allele Frequency Deviation (AFD)

Prediction of Overall Survival for Early-stage Non-small Cell Lung Cancer via a Novel 7-gene Prognostic Signature and Allele Frequency Deviation (AFD)

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