Evidence map›Paper›PMID 28523942›Full record

ArticleDrug development and industrial pharmacy2017

Combinatorial therapeutic approaches with RNAi and anticancer drugs using nanodrug delivery systems.

Anish Babu, Anupama Munshi, Rajagopal Ramesh

Open access · hybridAbstract read
In one paragraph

Article in Drug development and industrial pharmacy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

29 citing papers in PubMed, 61 citations in OpenAlex.

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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 at 1 institution in 1 country.

Anish Babua Department of Pathology , University of Oklahoma Health Sciences Center , Oklahoma City , OK , USA.
Anupama Munshib Stephenson Cancer Center, University of Oklahoma Health Sciences Center , Oklahoma City , OK , USA.
Rajagopal Ramesha Department of Pathology , University of Oklahoma Health Sciences Center , Oklahoma City , OK , USA.
University of Oklahoma Health Sciences Center · US

Funding

HuR Targeted Nanotherapy for Lung CancerR01CA167516 · NCI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI RAMESH, RAJAGOPAL · 2013 to 2017
$1.9M
NCI NIH HHS R01 CA167516
6 · The paper itself

Abstract

RNA interference (RNAi) is emerging as a powerful approach in cancer treatment. siRNA is an important RNAi tool that can be designed to specifically silence the expression of genes involved in drug resistance and chemotherapeutic inactivity. Combining siRNA and other therapeutic agents can overcome the multidrug resistance (MDR) phenomenon by simultaneously silencing genes and enhancing chemotherapeutic activity. Moreover, the therapeutic efficiency of anticancer drugs can be significantly improved by additive or synergistic effects induced by siRNA and combined therapies. Co-delivery of these diverse anticancer agents, however, requires specially designed nanocarriers. This review highlights the recent trends in siRNA/anticancer drug co-delivery systems under the major categories of liposomes/lipid, polymeric and inorganic nanoplatforms. The objective is to discuss the strategies for nanocarrier-based co-delivery systems using siRNA/anticancer drug combinations, emphasizing various siRNA targets that help overcome MDR and enhance therapeutic efficiency.

Indexed as

Antineoplastic AgentsDrug Delivery SystemsDrug Resistance, MultipleGene SilencingHumansLipidsLiposomesNanoparticlesRNA InterferenceRNA, Small InterferingAntineoplastic AgentsLipidsLiposomesRNA, Small InterferingCancer therapychemotherapeuticco-deliveryliposomenanoparticlesiRNA

Identifiers

PMID28523942
PMCPMC6101010
OpenAlexW2615538013

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.