Unknown

Dataset Information

0

Predicting cancer prognosis and drug response from the tumor microbiome.


ABSTRACT: Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-seq and whole genome sequencing data contain not only reads from host tumor and normal tissue, but also reads from the tumor microbiome, which can be used to infer the microbial abundances in each tumor. Here, we show that tumor microbial abundances, alone or in combination with tumor gene expression, can predict cancer prognosis and drug response to some extent-microbial abundances are significantly less predictive of prognosis than gene expression, although similarly as predictive of drug response, but in mostly different cancer-drug combinations. Thus, it appears possible to leverage existing sequencing technology, or develop new protocols, to obtain more non-redundant information about prognosis and drug response from RNA-seq and whole genome sequencing experiments than could be obtained from tumor gene expression or genomic data alone.

SUBMITTER: Hermida LC 

PROVIDER: S-EPMC9130323 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

Predicting cancer prognosis and drug response from the tumor microbiome.

Hermida Leandro C LC   Gertz E Michael EM   Ruppin Eytan E  

Nature communications 20220524 1


Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-seq and whole genome sequencing data contain not only reads from host tumor and normal tissue, but also reads from the tumor microbiome, which can be used to infer the microbial abundances in each tumor. Here, we show that tumor microbial abundances, alone or in combination with tumor gene expression, can predict cancer prognosis and drug response to some extent-microbial abundances are significantly less pred  ...[more]

Similar Datasets

| S-EPMC5528725 | biostudies-other
2013-06-15 | E-GEOD-43919 | biostudies-arrayexpress
| S-EPMC10041757 | biostudies-literature
2013-06-15 | GSE43919 | GEO
| S-EPMC10912776 | biostudies-literature
| S-EPMC9479109 | biostudies-literature
| S-EPMC9485450 | biostudies-literature
| S-EPMC11544644 | biostudies-literature
| S-EPMC9489948 | biostudies-literature
| S-EPMC11233133 | biostudies-literature