Evidence map›Paper›PMID 33442444›Full record

ReviewWorld journal of hepatology2020

Molecular heterogeneity in intrahepatic cholangiocarcinoma.

Keun Soo Ahn, Koo Jeong Kang

Abstract readReview
In one paragraph

Review in World journal of hepatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Meeting report of the editorial board meeting forWorld journal of hepatology · 2021
    Article
  11. 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

2 authors.

Keun Soo AhnDepartment of Surgery, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu 42601, South Korea. ahnksmd@gmail.com.
Koo Jeong KangDepartment of Surgery, Keimyung University Dongsan Hospital, Keimyung University School of Medicine, Daegu 42601, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intrahepatic cholangiocarcinoma (iCCA) is a heterogeneous primary liver cancer, and currently there exist only a few options of targeted therapy. Histopathologically, iCCA is sub-classified according to morphology (mass forming type, periductal infiltrating type, and intraductal growing type) and histology (small duct type and large duct type). According to different histopathological types, clinical features such as risk factors and prognosis vary. Recent developments in genomic profiling have revealed several molecular markers for poor prognosis and activation of oncogenic pathways. Exploration of molecular characteristics of iCCA in each patient is a major challenge in a clinical setting, and there is no effective molecular-based targeted therapy. However, several recent studies suggested molecular-based subtypes with corresponding clinical and pathological features. Even though the subtypes have not yet been validated, it is possible that molecular features can be predicted based on clinicopathological characteristics and that this could be used for a more rational approach to integrative clinical and molecular subclassification and targeted therapy. In this review, we explored the genomic landscape of iCCA and attempted to find relevance between clinicopathologic and molecular features in molecular subtypes in several published studies. The results reveal future directions that may lead to a rational approach to the targeted therapy.

Indexed as

CholangiocarcinomaGene expressionMolecularMutationPathwayTarget therapy

Identifiers

PMID33442444
PMCPMC7772740

What OpenQuestion holds

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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.