scholarly journals Uncovering the landscape of somatic mutations in Malaysian colorectal cancer patients via whole genome sequencing

2018 ◽  
Vol 9 ◽  
Author(s):  
Ryia Illani Mohd Yunos ◽  
Nurul-Syakima Ab Mutalib ◽  
Jia-Shiun Khoo ◽  
Sazuita Saidin ◽  
Muhiddin Ishak ◽  
...  
2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Agata Stodolna ◽  
Miao He ◽  
Mahesh Vasipalli ◽  
Zoya Kingsbury ◽  
Jennifer Becq ◽  
...  

Abstract Background Clinical-grade whole-genome sequencing (cWGS) has the potential to become the standard of care within the clinic because of its breadth of coverage and lack of bias towards certain regions of the genome. Colorectal cancer presents a difficult treatment paradigm, with over 40% of patients presenting at diagnosis with metastatic disease. We hypothesised that cWGS coupled with 3′ transcriptome analysis would give new insights into colorectal cancer. Methods Patients underwent PCR-free whole-genome sequencing and alignment and variant calling using a standardised pipeline to output SNVs, indels, SVs and CNAs. Additional insights into the mutational signatures and tumour biology were gained by the use of 3′ RNA-seq. Results Fifty-four patients were studied in total. Driver analysis identified the Wnt pathway gene APC as the only consistently mutated driver in colorectal cancer. Alterations in the PI3K/mTOR pathways were seen as previously observed in CRC. Multiple private CNAs, SVs and gene fusions were unique to individual tumours. Approximately 30% of patients had a tumour mutational burden of > 10 mutations/Mb of DNA, suggesting suitability for immunotherapy. Conclusions Clinical whole-genome sequencing offers a potential avenue for the identification of private genomic variation that may confer sensitivity to targeted agents and offer patients new options for targeted therapies.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lydia Y. Liu ◽  
Vinayak Bhandari ◽  
Adriana Salcedo ◽  
Shadrielle M. G. Espiritu ◽  
Quaid D. Morris ◽  
...  

AbstractWhole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumoural heterogeneity is linked to clinical outcomes. Many algorithms have been developed for subclonal reconstruction, but their variabilities and consistencies are largely unknown. We evaluate sixteen pipelines for reconstructing the evolutionary histories of 293 localized prostate cancers from single samples, and eighteen pipelines for the reconstruction of 10 tumours with multi-region sampling. We show that predictions of subclonal architecture and timing of somatic mutations vary extensively across pipelines. Pipelines show consistent types of biases, with those incorporating SomaticSniper and Battenberg preferentially predicting homogenous cancer cell populations and those using MuTect tending to predict multiple populations of cancer cells. Subclonal reconstructions using multi-region sampling confirm that single-sample reconstructions systematically underestimate intra-tumoural heterogeneity, predicting on average fewer than half of the cancer cell populations identified by multi-region sequencing. Overall, these biases suggest caution in interpreting specific architectures and subclonal variants.


2019 ◽  
Vol 7 (2) ◽  
pp. 136-143 ◽  
Author(s):  
Alison May Berner ◽  
George J. Morrissey ◽  
Nirupa Murugaesu

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Nathan Wan ◽  
David Weinberg ◽  
Tzu-Yu Liu ◽  
Katherine Niehaus ◽  
Eric A. Ariazi ◽  
...  

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