Circulating tumor cell detection and single‐cell analysis using an integrated workflow based on ChimeraX®‐i120 Platform: A prospective study |
| |
| Authors: | Peng‐ Xiang Wang,Yun‐ Fan Sun,Wei‐ Xiang Jin,Jian‐ Wen Cheng,Hai‐ Xiang Peng,Yang Xu,Kai‐ Qian Zhou,Li‐ Meng Chen,Kai Huang,Sui‐ Yi Wu,Bo Hu,Ze‐ Fan Zhang,Wei Guo,Ya Cao,Jian Zhou,Jia Fan,Xin‐ Rong Yang |
| |
| Abstract: | Circulating tumor cell (CTC) analysis holds great potential to be a noninvasive solution for clinical cancer management. A complete workflow that combined CTC detection and single‐cell molecular analysis is required. We developed the ChimeraX®‐i120 platform to facilitate negative enrichment, immunofluorescent labeling, and machine learning‐based identification of CTCs. Analytical performances were evaluated, and a total of 477 participants were enrolled to validate the clinical feasibility of ChimeraX®‐i120 CTC detection. We analyzed copy number alteration profiles of isolated single cells. The ChimeraX®‐i120 platform had high sensitivity, accuracy, and reproducibility for CTC detection. In clinical samples, an average value of > 60% CTC‐positive rate was found for five cancer types (i.e., liver, biliary duct, breast, colorectal, and lung), while CTCs were rarely identified in blood from healthy donors. In hepatocellular carcinoma patients treated with curative resection, CTC status was significantly associated with tumor characteristics, prognosis, and treatment response (all P < 0.05). Single‐cell sequencing analysis revealed that heterogeneous genomic alteration patterns resided in different cells, patients, and cancers. Our results suggest that the use of this ChimeraX®‐i120 platform and the integrated workflow has validity as a tool for CTC detection and downstream genomic profiling in the clinical setting.Abbreviations- ADABOOST
- AdaBoost classification trees
- AFP
- alpha‐fetoprotein
- AUC
- areas under the curve
- BC
- breast cancer
- BCLC
- barcelona clinic liver cancer
- BHL
- benign hepatic lesion
- CCD
- charge‐coupled device
- CHB
- chronic hepatitis B
- CK
- cytokeratin
- CNA
- copy number alteration
- CNLC
- Chinese staging for liver cancer
- CRC
- colorectal cancer
- CTC
- circulating tumor cell
- CTM
- circulating tumor microemboli
- CV
- coefficient of variation
- DAPI
- 4’,6‐diamidine‐2’‐phenylindole dihydrochloride
- EpCAM
- epithelial cell adhesion molecule
- FPR
- false‐positive rate
- GBM
- stochastic gradient boosting
- HCC
- hepatocellular carcinoma
- HD
- healthy donor
- ICC
- intrahepatic cholangiocarcinoma
- LC
- liver cirrhosis
- LCA
- lung cancer
- LOD
- limit of detection
- PBS
- phosphate‐buffered saline
- PCR
- polymerase chain reaction
- RF
- random forest
- ROC
- receiver operating characteristic
- SVM
- support vector machines
- TCGA
- The Cancer Genome Atlas
- TPR
- true‐positive rate
- TTR
- time to recurrence
- WBC
- white blood cell
- WGA
- whole‐genome amplification
- WGS
- whole‐genome sequencing
- XGB
- extreme gradient boosting
|
| |
| Keywords: | circulating tumor cell, enumeration, integrated platform, liquid biopsy, machine learning‐ based image recognition, single‐ cell sequencing |
|
|
