Evidence map›Paper›PMID 29296697›Full record

ArticleBlood advances2016

Targetable subsets of non-Hodgkin lymphoma in Malawi define therapeutic opportunities.

Elizabeth A Morgan, M Patrick Sweeney, Tamiwe Tomoka, Nadja Kopp, Daniel Gusenleitner, Robert A Redd, Christopher D Carey, Leo Masamba, Steve Kamiza, Geraldine S Pinkus and 4 more

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Identifying transcriptional profiles and evaluating prognostic biomarkers of HIV-associated diffuse large B-cell lymphoma from Malawi.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2020
    Observational
  8. Review
  9. 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

14 authors at 5 institutions in 3 countries.

Elizabeth A MorganDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.ORCID 0000-0001-5880-9337
M Patrick SweeneyTulane University School of Medicine, New Orleans, LA.
Tamiwe TomokaDepartment of Histopathology, University of Malawi College of Medicine, Blantyre, Malawi.
Nadja KoppDepartment of Medical Oncology.
Daniel GusenleitnerCenter for Immuno-Oncology, and.
Robert A ReddDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA.
Christopher D CareyDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Leo MasambaDepartment of Medicine, University of Malawi College of Medicine, Blantyre, Malawi; and.
Steve KamizaDepartment of Histopathology, University of Malawi College of Medicine, Blantyre, Malawi.
Geraldine S PinkusDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Donna S NeubergDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA.ORCID 0000-0003-2566-3145
Scott J RodigDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Danny A MilnerDepartment of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
David M WeinstockDepartment of Medical Oncology.
Brigham and Women's Hospital · USUniversity of Malawi · MWDana-Farber Cancer Institute · USBroad Institute · USTulane University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diagnostics and supportive care for patients with non-Hodgkin lymphoma (NHL) in lower- and middle-income countries (LMICs) are lacking. We hypothesized that high-throughput transcription-based diagnostics could classify NHL specimens from Malawi amenable to targeted therapeutics. We established tissue microarrays and classified 328 cases diagnosed by hematoxylin and eosin as NHL at University of Malawi College of Medicine using immunohistochemistry (IHC) for conventional markers and therapeutic targets. A subset was analyzed using NanoString-based expression profiling with parsimonious transcriptional classifiers. Overall, 72% of lymphomas were high-grade B-cell tumors, subsets of which were enriched for expression of MYC, BCL2, and/or PD-L1. A 21-gene transcriptional classifier, previously validated in Western cohorts, divided 96% of diffuse large B-cell lymphomas (DLBCLs) with 100% of B-cell lymphomas, unclassifiable, into 1 cluster and 88% of Burkitt lymphomas into a separate cluster. Cell-of-origin categorization of 36 DLBCLs by NanoString lymphoma subtyping test (LST) revealed 69% concordance with IHC. All discordant cases were classified as germinal center B cell-like (GCB) by LST but non-GCB by IHC. In summary, utilization of advanced diagnostics facilitates objective assessment and segregation of biologically defined subsets of NHL from an LMIC without expert review, thereby establishing a basis for the implementation of effective and less toxic targeted agents.

Identifiers

PMID29296697
PMCPMC5744047
OpenAlexW2558937528

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.