Back

DTCFinder: a bench-to-bits toolkit for label-free, whole-spectrum analysis of disseminated and circulating tumor cells in liquid biopsies

Yan, X.; Wang, Z.; Li, Z.; Zhao, Y.; Lu, S.; Shi, Q.; Wei, W.

2025-12-01 cancer biology
10.1101/2025.11.27.690914 bioRxiv
Show abstract

Disseminated (DTCs) and circulating tumor cells (CTCs) are rare but pivotal in understanding cancer metastasis and advancing liquid biopsy-based diagnostics. Traditional detection approaches, hindered by their dependency on epithelial markers or morphological features, impair the accurate identification of varied DTC/CTC phenotypes within liquid biopsies. We describe DTCFinder, a bench-to-bits, label-free method integrating high-throughput single-cell RNA sequencing and machine learning, enabling unbiased detection, in-depth molecular characterization, and precise tissue-of-origin tracing of DTCs/CTCs across various types of liquid biopsies, even with ultra-scarce DTC/CTC presence in peripheral blood and low sequencing depth. DTCFinder offers a robust and versatile toolkit for liquid biopsy-based cancer diagnostics, enhancing our understanding of cancer metastasis.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 6%
22.2%
Similar papers in this journal
2
Nature
○ 645 papers in training set
Top 1%
11.8%
Similar papers in this journal
3
Cancer Discovery
● 66 papers in training set
Top 0.3%
7.2%
Similar papers in this journal
4
Nature Genetics
○ 286 papers in training set
Top 1%
5.4%
Similar papers in this journal
5
Nature Cancer
○ 39 papers in training set
Top 0.3%
5.4%
Similar papers in this journal
50% of probability mass above
6
Nature Methods
○ 385 papers in training set
Top 3%
3.4%
7
Science Advances
● 1243 papers in training set
Top 13%
2.8%
8
Genome Biology
○ 637 papers in training set
Top 4%
2.6%
9
Communications Biology
○ 993 papers in training set
Top 9%
2.4%
10
Nature Medicine
○ 125 papers in training set
Top 1%
2.1%
11
eLife
● 5828 papers in training set
Top 46%
2.1%
12
Genome Medicine
○ 183 papers in training set
Top 2%
2.1%
13
Nature Cell Biology
○ 118 papers in training set
Top 2%
1.9%
14
Cell Reports
○ 1498 papers in training set
Top 19%
1.7%
15
Nature Biotechnology
○ 172 papers in training set
Top 2%
1.7%
16
Cancer Research
● 130 papers in training set
Top 2%
1.5%
17
Cancer Cell
○ 42 papers in training set
Top 0.9%
1.4%
18
Cell
○ 431 papers in training set
Top 7%
1.3%
19
Cell Reports Medicine
○ 153 papers in training set
Top 3%
1.3%
20
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 35%
1.1%
21
npj Precision Oncology
○ 53 papers in training set
Top 1%
1.1%
22
Nature Biomedical Engineering
○ 47 papers in training set
Top 1%
1.1%
23
Blood
● 74 papers in training set
Top 1.0%
1.1%
24
Cell Genomics
○ 172 papers in training set
Top 4%
1.0%
25
Nucleic Acids Research
◐ 1281 papers in training set
Top 13%
0.8%
26
Cell Research
○ 51 papers in training set
Top 2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.