Evidence map›Paper›PMID 34458041›Full record

ReviewCureus2021

Untangling Triple-Negative Breast Cancer Molecular Peculiarity and Chemo-Resistance: Trailing Towards Marker-Based Targeted Therapies.

Bushra Kanwal

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. PARP-1 Expression andCancers · 2022
    Article
  3. 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

1 author at 1 institution in 1 country.

Bushra KanwalInternal Medicine, Brookdale University Hospital Medical Center, Brooklyn, USA.
Brookdale University Hospital and Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC), characterized by the absence of estrogen receptor, progesterone receptor, or human epidermal growth factor receptor-2, affects nearly 15% of women with breast cancer. To date, the mainstay of treatment remains chemotherapy, with all the associated consequences, such as the significant toxicity and the suboptimal effect on the five-year survival rates. RNA-expression profiling showed that TNBC is biologically a heterogeneous malignancy. Therefore, predictive biomarkers matched with the diverse subtypes of TNBC could classify patients that would most benefit from a certain targeted treatment. Three biomarker-driven therapies are currently available: poly-adenosine diphosphate (ADP) ribose polymerase inhibitors for patients with germline BReast CAncer gene (BRCA) mutations, atezolizumab combined with nab-paclitaxel for patients expressing programmed death-ligand 1 (PD-L1) on tumor-infiltrating immune cells, and sacituzumab govitecan, an antibody-drug conjugate targeting human trophoblast cell-surface antigen 2 (TROP-2). Identifying predictive biomarkers is crucial for the optimum generation and implementation of targeted agents for TNBC, while further relevant treatments are in the pipeline given the promising results in clinical trials. Finally, newly developed immunotherapies and other targeted agents should also be investigated in earlier stages of the disease, especially in the neoadjuvant setting, broadening the therapeutic application of such regimens.

Indexed as

biomarkerbrca1breast cancerestrogen receptorhuman epidermal growth factor receptor-2immune checkpoint inhibitorsparp inhibitorsprogesterone receptorrna-expression profilingtriple-negative breast cancer

Identifiers

PMID34458041
PMCPMC8384383
OpenAlexW3184692827

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.