Evidence map›Paper›PMID 33691026›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2021

A multi-scale integrated analysis identifies KRT8 as a pan-cancer early biomarker.

Madeleine K D Scott, Maneesha Limaye, Steven Schaffert, Robert West, Michael G Ozawa, Pauline Chu, Viswam S Nair, Albert C Koong, Purvesh Khatri

Open access · greenAbstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

17 citing papers in PubMed, 15 citations in OpenAlex.

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  15. Modification of STIM2 by mAnnals of translational medicine · 2022
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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

9 authors at 3 institutions in 1 country.

Madeleine K D ScottBiophysics Program, Department of Medicine, Stanford University, Stanford, CA, USA, scottmk@stanford.edu.
Maneesha Limaye
Steven Schaffert
Robert West
Michael G Ozawa
Pauline Chu
Viswam S Nair
Albert C Koong
Purvesh Khatri
Stanford University · USChildren's Hospital of Orange County · USFred Hutch Cancer Center · US

Funding

Using a tonsil organoid system to probe conditions for the induction of protective antibody and T cell responses to influenza.U19AI057229 · NIAID · STANFORD UNIVERSITY · PI Mark Morris Davis · 2003 to 2026
$88.5M
Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Giant MagnetoResistive (GMR) Sensors for Measuring Influenza VaccineR01AI125197 · NIAID · STANFORD UNIVERSITY · PI UTZ, PAUL JOSEPH, WANG, SHAN X. · 2016 to 2021
$5.0M
Role of cleaved H3 as a key epigenetic regulator of macrophages in idiopathic pulmonary fibrosisF30HL149252 · NHLBI · STANFORD UNIVERSITY · PI SCOTT, MADELEINE · 2020 to 2021
$76k
NHLBI NIH HHS F30 HL149252NIAID NIH HHS R01 AI125197NIAID NIH HHS U19 AI057229NIAID NIH HHS U19 AI109662
6 · The paper itself

Abstract

An early biomarker would transform our ability to screen and treat patients with cancer. The large amount of multi-scale molecular data in public repositories from various cancers provide unprecedented opportunities to find such a biomarker. However, despite identification of numerous molecular biomarkers using these public data, fewer than 1% have proven robust enough to translate into clinical practice. One of the most important factors affecting the successful translation to clinical practice is lack of real-world patient population heterogeneity in the discovery process. Almost all biomarker studies analyze only a single cohort of patients with the same cancer using a single modality. Recent studies in other diseases have demonstrated the advantage of leveraging biological and technical heterogeneity across multiple independent cohorts to identify robust disease biomarkers. Here we analyzed 17149 samples from patients with one of 23 cancers that were profiled using either DNA methylation, bulk and single-cell gene expression, or protein expression in tumor and serum. First, we analyzed DNA methylation profiles of 9855 samples across 23 cancers from The Cancer Genome Atlas (TCGA). We then examined the gene expression profile of the most significantly hypomethylated gene, KRT8, in 6781 samples from 57 independent microarray datasets from NCBI GEO. KRT8 was significantly over-expressed across cancers except colon cancer (summary effect size=1.05; p < 0.0001). Further, single-cell RNAseq analysis of 7447 single cells from lung tumors showed that genes that significantly correlated with KRT8 (p < 0.05) were involved in p53-related pathways. Immunohistochemistry in tumor biopsies from 294 patients with lung cancer showed that high protein expression of KRT8 is a prognostic marker of poor survival (HR = 1.73, p = 0.01). Finally, detectable KRT8 in serum as measured by ELISA distinguished patients with pancreatic cancer from healthy controls with an AUROC=0.94. In summary, our analysis demonstrates that KRT8 is (1) differentially expressed in several cancers across all molecular modalities and (2) may be useful as a biomarker to identify patients that should be further tested for cancer.

Indexed as

Biomarkers, TumorLung NeoplasmsCohort StudiesComputational BiologyDNA MethylationHumansKeratin-8Survival AnalysisBiomarkers, TumorKeratin-8KRT8 protein, human

Identifiers

PMID33691026
PMCPMC7958996
OpenAlexW3108236520

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.