Evidence map›Paper›PMID 36841736›Full record

ReviewTrends in microbiology2023

Computational methods and challenges in analyzing intratumoral microbiome data.

Qi Wang, Zhaoqian Liu, Anjun Ma, Zihai Li, Bingqiang Liu, Qin Ma

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Trends in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 5% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 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

6 authors at 2 institutions in 2 countries.

Qi WangSchool of Mathematics, Shandong University, Jinan, Shandong, 250100, China.
Zhaoqian LiuSchool of Mathematics, Shandong University, Jinan, Shandong, 250100, China.
Anjun MaDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.
Zihai LiPelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA.
Bingqiang LiuSchool of Mathematics, Shandong University, Jinan, Shandong, 250100, China; Shandong National Center for Applied Mathematics, Jinan, Shandong, 250100, China. Electronic address: bingqiang@sdu.edu.cn.
Qin MaDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA. Electronic address: qin.ma@osumc.edu.
Shandong University · CNThe Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute · US

Funding

Construction of cell specific gene co-regulations signatures based on single cell transcriptomics analysisR01GM131399 · NIGMS · SOUTH DAKOTA STATE UNIVERSITY · PI MA, QIN · 2018 to 2021
$1.3M
NIGMS NIH HHS R01 GM131399
6 · The paper itself

Abstract

The human microbiome is intimately related to cancer biology and plays a vital role in the efficacy of cancer treatments, including immunotherapy. Extraordinary evidence has revealed that several microbes influence tumor development through interaction with the host immune system, that is, immuno-oncology-microbiome (IOM). This review focuses on the intratumoral microbiome in IOM and describes the available data and computational methods for discovering biological insights of microbial profiling from host bulk, single-cell, and spatial sequencing data. Critical challenges in data analysis and integration are discussed. Specifically, the microorganisms associated with cancer and cancer treatment in the context of IOM are collected and integrated from the literature. Lastly, we provide our perspectives for future directions in IOM research.

Indexed as

MicrobiotaNeoplasmsComputational BiologyForecastingHumansImmunotherapycancer treatment and diagnosiscomputational methodsimmuno-oncology-microbiomeimmunotherapyintratumoral microbiome

Identifiers

PMID36841736
PMCPMC10272078
OpenAlexW4321606471

What OpenQuestion holds

Textmetadata
LicenceTDM
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.