Evidence map›Paper›PMID 38260351›Full record

ArticlebioRxiv : the preprint server for biology2024

Charting Single Cell Lineage Dynamics and Mutation Networks via Homing CRISPR.

Lin Wang, Wenjuan Dong, Zheng Yin, Jianting Sheng, Chika F Ezeana, Li Yang, Xiaohui Yu, Solomon Sy Wong, Zhihao Wan, Rebecca L Danforth and 3 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Lin WangDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.ORCID 0000-0002-6042-2366
Wenjuan DongDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Zheng YinDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Jianting ShengDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Chika F EzeanaDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Li YangT.T. and W. F. Chao Center for BRAIN, Houston Methodist Research Institute, Houston, Texas 77030.
Xiaohui YuDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Solomon Sy WongParnassus Medical Systems, Houston, Texas 77098.
Zhihao WanDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Rebecca L DanforthDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Kun HanDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Dingcheng GaoDepartment of Cell & Development Biology, Weill Cornell Medical College, New York, NY 10065.
Stephen T C WongDepartment of System Medicine and Bioengineering, Houston Methodist Neal Cancer Center, Houston, Texas 77030.
Houston Methodist · USCornell University · US

Funding

Spatiotemporal modeling of cancer-niche interactions in breast cancer bone metastasisU01CA253553 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI WONG, STEPHEN TC, ZHANG, XIANG · 2020 to 2024
$3.0M
Convergent AI for Precise Breast Cancer Risk AssessmentR01CA251710 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI WONG, STEPHEN TC · 2020 to 2024
$2.5M
To study the EMT contributions in tumor metastasis and chemoresistance by using lineage tracing modelsR01CA244413 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GAO, DINGCHENG · 2020 to 2024
$2.4M
A phase II multi-center trial evaluating dual targeting of the PI3K/AKT and NOS pathways for treating metaplastic breast cancer (MpBC)U01CA268813 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI JENNY C-N CHANG, FUNDA MERIC-BERNSTAM · 2022 to 2026
$2.0M
NCI NIH HHS R01 CA244413NCI NIH HHS R01 CA251710NCI NIH HHS U01 CA253553NCI NIH HHS U01 CA268813
6 · The paper itself

Abstract

Single cell lineage tracing, essential for unraveling cellular dynamics in disease evolution is critical for developing targeted therapies. CRISPR-Cas9, known for inducing permanent and cumulative mutations, is a cornerstone in lineage tracing. The novel homing guide RNA (hgRNA) technology enhances this by enabling dynamic retargeting and facilitating ongoing genetic modifications. Charting these mutations, especially through successive hgRNA edits, poses a significant challenge. Our solution, LINEMAP, is a computational framework designed to trace and map these mutations with precision. LINEMAP meticulously discerns mutation alleles at single-cell resolution and maps their complex interrelationships through a mutation evolution network. By utilizing a Markov Process model, we can predict mutation transition probabilities, revealing potential mutational routes and pathways. Our reconstruction algorithm, anchored in the Markov model's attributes, reconstructs cellular lineage pathways, shedding light on the cell's evolutionary journey to the minutiae of single-cell division. Our findings reveal an intricate network of mutation evolution paired with a predictive Markov model, advancing our capability to reconstruct single-cell lineage via hgRNA. This has substantial implications for advancing our understanding of biological mechanisms and propelling medical research forward.

Identifiers

PMID38260351
PMCPMC10802354
OpenAlexW4390660656

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.