Evidence map›Paper›PMID 36158348›Full record

ArticleCureus2022

Next-Generation Sequencing Highlights of Diffuse Large B-cell Lymphoma in a Tertiary Care Hospital in North India.

Garima Mamgain, Manisha Naithani, Priyanka Patra, Mukesh Mamgain, Sikha Morang, Jhasketan Nayak, Karthik Kumar, Shashikant Singh, Anamika Bakliwal, Ashok Rajoreya and 7 more

Abstract read
In one paragraph

Article in Cureus, 2022. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Potential Effect of Extracellular Vesicles in Clinical Settings of Lymphoma.Indian journal of clinical biochemistry : IJCB · 2025
    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

17 authors.

Garima MamgainDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Manisha NaithaniDepartment of Biochemistry, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Priyanka PatraDepartment of Biochemistry, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Mukesh MamgainDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Sikha MorangDepartment of Pharmacology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Jhasketan NayakDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Karthik KumarDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Shashikant SinghDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Anamika BakliwalDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Ashok RajoreyaDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Sudeep VaniyathDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Debranjani ChattopadhyayDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Rituparna ChetiaDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Arvind GuptaDepartment of Pathology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Gaurav DhingraDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Deepak SundriyalDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.
Uttam Kumar NathDepartment of Medical Oncology/Haematology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNext-generation sequencing (NGS) elucidates the diffuse large B-cell lymphoma (DLBCL) genetic characteristics by finding recurrent and novel somatic mutations. This observational study attempted to create an NGS panel with a focus on identifying novel somatic mutations which could have potential clinical and therapeutic implications. This panel was created to look for mutations in 133 genes chosen on basis of a literature review and it was used to sequence the tumor DNA of 20 DLBCL patients after a centralized histopathologic review.

methodsThe study included 20 patients having DLBCL. The quality and quantity of tumor cells were accessed by H&E staining and correlated with histopathology and Immunohistochemistry (IHC) status. Patients were grouped as ABC (activated B-cell), PMBL (primary mediastinal large B-cell lymphoma), and other or unclassified subtypes. The lymphoma panel of 133 was designed on targeted sequencing of multiple genes for the coding regions through NGS. The libraries were prepared and sequenced using the Illumina platform. The alignment of obtained sequences was performed using Burrows-Wheeler Aligner and identification of somatic mutations was done using LoFreq (version 2) variant caller. The mutations were annotated using an annotation pipeline (VariMAT). Previously published literature and databases were used for the annotation of clinically relevant mutations. The common variants were filtered for reporting based on the presence in various population databases (1000G, ExAC, EVS, 1000Japanese, dbSNP, UK10K, MedVarDb). A custom read-depth-based algorithm was used to determine CNV (Copy Number Variants) from targeted sequencing experiments. Rare CNVs were detected using a comparison of the test data read-depths with the matched reference dataset. Reportable mutations were prioritized and prepared based on AMP-ASCO-CAP (Association for Molecular Pathology-American Society of Clinical Oncology-College of American Pathologists), WHO guidelines, and also based on annotation metrics from OncoMD (a knowledge base of genomic alterations).

resultsThe informativity of the panel was 95 percent.

conclusionsThis study demonstrates the high yield of information in DLBCL using the NGS Lymphoma panel. Results also highlight the molecular heterogeneity of DLBCL subtypes which indicates the need for further studies to make the results of the NGS more clinically relevant.

Indexed as

diffuse large b cell lymphomagenetic mutationinformativitylymphoma panelnext-generation sequencing

Identifiers

PMID36158348
PMCPMC9489829

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Registered trials

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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.