Evidence map›Paper›PMID 31807308›Full record

ArticleBiomarker research2019

Cancer biomarkers for targeted therapy.

Delong Liu

Open access · goldAbstract readEditorial
In one paragraph

Article in Biomarker research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 2 pooled it
6.4field-weighted citation impact, top 3% of its field
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

69 citing papers in PubMed, 2 syntheses or guidelines pooled it, 125 citations in OpenAlex.

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9 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Delong Liu1New York Medical College, Valhalla, NY 10595 USA.
New York Medical College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor-associated antigens (TAA) or cancer biomarkers are major targets for cancer therapies. Antibody- based agents targeting the cancer biomarkers include monoclonal antibodies (MoAbs), radiolabeled MoAbs, bispecific T cell engagers, and antibody-drug conjugates. Antibodies targeting CD19, CD20, CD22, CD30, CD33, CD38, CD79B and SLAMF7 are in clinical applications for hematological malignancies. CD123, CLL-1, B cell maturation antigen, and CD138 are targets for cancer immunotherapeutic agents, including the chimeric antigen receptor - engineered T cells. Immune checkpoint inhibitors (ICIs) against PD-1, PD-L1, and CTLA-4 have led to the revolution of cancer immunotherapy. More ICIs targeting IDO, LAG3, TIM-3, TIGIT, SIGLECs, VISTA and CD47 are being explored. Small molecule inhibitors (SMIs) against tyrosine kinase oncoproteins such as BCR-ABL, JAK2, Bruton tyrosine kinase, FLT3, EGFR, ALK, HER2, VEGFR, FGFR, MEK, and MET have fundamentally changed the landscape of cancer therapy. SMIs against BCL-2, IDHs, BRAF, PI3 kinase, mTOR, PARP, and CDKs have become the mainstay in the treatment of a variety of cancer types. To reduce and avoid off-tumor toxicities, cancer-specific TAAs such as CD33 are being manufactured through systems biology approach. Search for novel biomarkers and new designs as well as delivery methods of targeted agents are fueling the next wave of advances in cancer therapy.

Indexed as

Antibody-drug conjugateBiomarkerBiTECAR-TTumor-associated antigen

Identifiers

PMID31807308
PMCPMC6857213
OpenAlexW2987088121

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.