Litcius/Paper detail

Single-cell low-pass whole genome sequencing accurately detects circulating tumor cells for liquid biopsy-based multi-cancer diagnosis

Xiaohan Shen, Jiao Dai, Lingchuan Guo, Zhigang Liu, Yang Liu, Dongmei Gu, Yinghong Xie, Zhuo Wang, Ziming Li, Haimiao Xu, Qihui Shi

2024npj Precision Oncology17 citationsDOIOpen Access PDF

Abstract

Accurate detection of circulating tumor cells (CTCs) in blood and non-blood body fluids enables generation of deterministic cancer diagnosis and represent a less invasive and safer liquid biopsy approach. Although genomic alternations have been widely used in circulating tumor DNA (ctDNA) analysis, studies on cell-based genomic alternations profiling for CTC detection are rare due to major technical limitations in single-cell whole genome sequencing (WGS) including low throughput, low accuracy and high cost. We report a single-cell low-pass WGS-based protocol (scMet-Seq) for sensitive and accurate CTC detection by combining a metabolic function-associated marker Hexokinase 2 (HK2) and a Tn5 transposome-based WGS method with improved cell fixation strategy. To explore the clinical use, scMet-Seq has been investigated with blood and non-blood body fluids in diagnosing metastatic diseases, including ascites-based diagnosis of malignant ascites (MA) and blood-based diagnosis of metastatic small-cell lung cancer (SCLC). ScMet-Seq shows high diagnostic sensitivity (MA: 79% in >10 cancer types; metastatic SCLC: 90%) and ~100% of diagnostic specificity and positive predictive value, superior to clinical cytology that exhibits diagnostic sensitivity of 52% in MA diagnosis and could not generate blood-based diagnosis. ScMet-Seq represents a liquid biopsy approach for deterministic cancer diagnosis in different types of cancers and body fluids.

Topics & Concepts

Liquid biopsyCirculating tumor cellCell-free fetal DNACancerMedicineBiopsyLung cancerPathologyComputational biologyOncologyCancer researchInternal medicineBiologyMetastasisGeneticsPregnancyFetusPrenatal diagnosisCancer Genomics and DiagnosticsCancer Cells and MetastasisSingle-cell and spatial transcriptomics