Evidence map›Paper›PMID 38568057›Full record

ArticleJournal of cellular and molecular medicine2024

Development, synthesis and validation of improved c-Myc/Max inhibitors.

Sümbül Yıldırım, Fatih Kocabaş, Arif Mermer

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Development, synthesis and validation of improved c-Myc/Max inhibitors.Journal of cellular and molecular medicine · 2024
    Article
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.

Sümbül YıldırımDepartment of Genetics and Bioengineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey.
Fatih KocabaşDepartment of Genetics and Bioengineering, Faculty of Engineering, Yeditepe University, Istanbul, Turkey.
Arif MermerDepartment of Biotechnology, University of Health Sciences, Istanbul, Turkey.ORCID 0000-0002-4789-7180

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathophysiological foundations of various diseases are often subject to alteration through the utilization of small compounds, rendering them invaluable tools for the exploration and advancement of novel therapeutic strategies. Within the scope of this study, we meticulously curated a diverse library of novel small compounds meticulously designed to specifically target the c-Myc/Max complex. We conducted in vitro examinations of novel c-Myc inhibitors across a spectrum of cancer cell lines, including PANC1 (pancreatic adenocarcinoma), MCF7 (breast carcinoma), DU-145 (prostate carcinoma), and A549 (lung cancer). The initial analysis involved a 25 μM dose, which enabled the identification of potent anticancer compounds effective against a variety of tumour types. We identified c-Myc inhibitors with remarkable potency, featuring IC50 values as low as 1.6 μM and up to 40 times more effective than the reference molecule in diminishing cancer cell viability. Notably, c-Myc-i7 exhibited exceptional selectivity, displaying 37-fold and 59-fold preference for targeting prostate and breast cancers, respectively, over healthy cells. Additionally, we constructed drug-likeness models. This study underscores the potential for in vitro investigations of various tumour types using novel c-Myc inhibitors to yield ground-breaking and efficacious anticancer compounds.

Indexed as

AdenocarcinomaPancreatic NeoplasmsCell LineCell NucleusCell SurvivalHumansMaleanti‐cancerc‐MycMaxrhodanineultrasonication

Identifiers

PMID38568057
PMCPMC10989597

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.