Evidence map›Paper›PMID 31447846›Full record

ReviewFrontiers in immunology2019

Metastatic Latency, a Veiled Threat.

Kangsan Kim, Mauricio Marquez-Palencia, Srinivas Malladi

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Review
  2. The Pro-Metastatic Roles of ROS.Antioxidants (Basel, Switzerland) · 2026
    Review
  3. Review
  4. Review
  5. Metabolic adaptations of brain metastasis.Nature reviews. Cancer · 2025
    Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
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  15. Review
  16. Article
  17. The changing role of natural killer cells in cancer metastasis.The Journal of clinical investigation · 2022
    Review
  18. Article
  19. Review
  20. Review
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

3 authors.

Kangsan KimDepartment of Pathology, UT Southwestern Medical Center, Dallas, TX, United States.
Mauricio Marquez-PalenciaDepartment of Pathology, UT Southwestern Medical Center, Dallas, TX, United States.
Srinivas MalladiDepartment of Pathology, UT Southwestern Medical Center, Dallas, TX, United States.

Funding

University of Texas Southwestern Medical Center SPORE in Kidney CancerP50CA196516 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI James Brugarolas · 2016 to 2026
$24.7M
NCI NIH HHS P50 CA196516
6 · The paper itself

Abstract

Metastatic relapse is observed in cancer patients with no clinical evidence of disease for months to decades after initial diagnosis and treatment. Disseminated cancer cells that are capable of entering reversible cell cycle arrest are believed to be responsible for these late metastatic relapses. Dynamic interactions between the latent disseminated tumor cells and their surrounding microenvironment aid cancer cell survival and facilitate escape from immune surveillance. Here, we highlight findings from preclinical models that provide a conceptual framework to define and target the latent metastatic phase of tumor progression. The hope is by identifying patients harboring latent metastatic cells and providing therapeutic options to eliminate metastatic seeds prior to their emergence will result in long lasting cures.

Indexed as

Neoplasm MetastasisEndoplasmic Reticulum StressExtracellular MatrixHumansLeukocytesNeoplasm, ResidualNeoplastic Cells, CirculatingRecurrenceTumor Microenvironmentdormancyimmune-surveillancelatencymetastasismicroenvironmentminimal residual disease

Identifiers

PMID31447846
PMCPMC6691038

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.