Evidence map›Paper›PMID 26568682›Full record

ReviewBreast cancer : basic and clinical research2015

A Perspective of Immunotherapy for Breast Cancer: Lessons Learned and Forward Directions for All Cancers.

George R Nahas, Nykia D Walker, Margarette Bryan, Pranela Rameshwar

Open access · goldAbstract readReview
In one paragraph

Review in Breast cancer : basic and clinical research, 2015. 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
0.3field-weighted citation impact, top 39% 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, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

4 authors at 2 institutions in 1 country.

George R NahasRutgers New Jersey Medical School, Newark, NJ, USA.
Nykia D WalkerRutgers New Jersey Medical School, Newark, NJ, USA. ; Rutgers Graduate School of Biomedical Sciences, Newark, NJ, USA.
Margarette BryanRutgers New Jersey Medical School, Newark, NJ, USA.
Pranela RameshwarRutgers New Jersey Medical School, Newark, NJ, USA. ; Rutgers Graduate School of Biomedical Sciences, Newark, NJ, USA.
Rutgers New Jersey Medical SchoolRutgers, The State University of New Jersey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapy for cancer has been a focus 50 years ago. At the time, this treatment was developed prior to cloning of the cytokines, no knowledge of regulatory T-cells, and very little information that mesenchymal stem cells (MSCs) (originally colony forming unit-fibroblasts [CFU-F]) could be licensed by the inflammatory microenvironment to suppress an immune response. Given the information available at that time, mononuclear cells from the peripheral blood were activated ex vivo and then replaced in the patients with tumor. The intent was to harness these activated immune cells to target the cancer cells. These studies did not lead to long-term responses because the activated cells when reinfused into the patients were an advantage to the resident MSCs, which can home the tumor and then become suppressive in the presence of the immune cells. The immune suppression caused by MSCs would also expand regulatory T-cells, resulting instead in tumor protection. As time progressed, these different fields converged into a new approach to use immunotherapy for cancer. This article discusses these approaches and also reviews chimeric antigen receptor in the context of future treatments for solid tumors, including breast cancer.

Indexed as

cancer stem cellsCAR T-cellmesenchymal stem cellT-cells

Identifiers

PMID26568682
PMCPMC4631157
OpenAlexW1920845532

What OpenQuestion holds

Textmetadata
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.