Personalized targeted therapy prescription in colorectal cancer using algorithmic analysis of RNA sequencing data.
Bioinformatics
Biomarkers detection
Colorectal cancer
Molecular diagnostics
Oncobox
Personalized medicine
RNA sequencing
Second opinion system
Targeted therapy
Transcriptomics
Journal
BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800
Informations de publication
Date de publication:
31 Oct 2022
31 Oct 2022
Historique:
received:
27
10
2021
accepted:
26
09
2022
entrez:
1
11
2022
pubmed:
2
11
2022
medline:
3
11
2022
Statut:
epublish
Résumé
Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments. We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected. Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84-0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality. Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC.
Sections du résumé
BACKGROUND
BACKGROUND
Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments.
METHODS
METHODS
We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected.
RESULTS
RESULTS
Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84-0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality.
CONCLUSION
CONCLUSIONS
Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC.
Identifiants
pubmed: 36316649
doi: 10.1186/s12885-022-10177-3
pii: 10.1186/s12885-022-10177-3
pmc: PMC9623986
doi:
Substances chimiques
Bevacizumab
2S9ZZM9Q9V
Cetuximab
PQX0D8J21J
Proto-Oncogene Proteins p21(ras)
EC 3.6.5.2
RNA
63231-63-0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1113Subventions
Organisme : Ministry of Science and Higher Education of the Russian Federation
ID : 075-15-2020-926
Organisme : Ministry of Science and Higher Education of the Russian Federation
ID : 075-15-2020-926
Organisme : Ministry of Science and Higher Education of the Russian Federation
ID : 075-15-2020-926
Organisme : National Natural Science Foundation of China
ID : 81800805
Organisme : Qingdao Key Research Project
ID : 17-3-3-10-nsh and 19-6-1-3-nsh
Informations de copyright
© 2022. The Author(s).
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