Construct prognostic models of multiple myeloma with pathway information incorporated
Multiple myeloma (MM) is a hematological disease exhibiting aberrant clonal expansion of cancerous plasma cells in the bone marrow. The effects of treatments for MM vary between patients, highlighting the importance of developing prognostic models for informed therapeutic decision-making. Most previ...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
September 10, 2024
|
| In: |
PLoS Computational Biology
Year: 2024, Jahrgang: 20, Heft: 9, Pages: 1-20 |
| ISSN: | 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1012444 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1371/journal.pcbi.1012444 Verlag, kostenfrei, Volltext: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012444 
|
| Verfasserangaben: | Shuo Wang, ShanJin Wang, Wei Pan, YuYang Yi, Junyan Lu |
MARC
| LEADER | 00000caa a2200000 c 4500 | ||
|---|---|---|---|
| 001 | 191727839X | ||
| 003 | DE-627 | ||
| 005 | 20250716231929.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 250214s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1371/journal.pcbi.1012444 |2 doi | |
| 035 | |a (DE-627)191727839X | ||
| 035 | |a (DE-599)KXP191727839X | ||
| 035 | |a (OCoLC)1528019214 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 084 | |a 32 |2 sdnb | ||
| 100 | 1 | |a Wang, Shuo |e VerfasserIn |0 (DE-588)1284496910 |0 (DE-627)1840142049 |4 aut | |
| 245 | 1 | 0 | |a Construct prognostic models of multiple myeloma with pathway information incorporated |c Shuo Wang, ShanJin Wang, Wei Pan, YuYang Yi, Junyan Lu |
| 264 | 1 | |c September 10, 2024 | |
| 300 | |b Illustrationen | ||
| 300 | |a 20 | ||
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Gesehen am 14.02.2025 | ||
| 520 | |a Multiple myeloma (MM) is a hematological disease exhibiting aberrant clonal expansion of cancerous plasma cells in the bone marrow. The effects of treatments for MM vary between patients, highlighting the importance of developing prognostic models for informed therapeutic decision-making. Most previous models were constructed at the gene level, ignoring the fact that the dysfunction of the pathway is closely associated with disease development and progression. The present study considered two strategies that construct predictive models by taking pathway information into consideration: pathway score method and group lasso using pathway information. The former simply converted gene expression to sample-wise pathway scores for model fitting. We considered three methods for pathway score calculation (ssGSEA, GSVA, and z-scores) and 14 data sources providing pathway information. We implemented these methods in microarray data for MM (GSE136324) and obtained a candidate model with the best prediction performance in interval validation. The candidate model is further compared with the gene-based model and previously published models in two external data. We also investigated the effects of missing values on prediction. The results showed that group lasso incorporating Vax pathway information (Vax(grp)) was more competitive in prediction than the gene model in both internal and external validation. Immune information, including VAX pathways, seemed to be more predictive for MM. Vax(grp) also outperformed the previously published models. Moreover, the new model was more resistant to missing values, and the presence of missing values (<5%) would not evidently deteriorate its prediction accuracy using our missing data imputation method. In a nutshell, pathway-based models (using group lasso) were competitive alternatives to gene-based models for MM. These models were documented in an R package (https://github.com/ShuoStat/MMMs), where a missing data imputation method was also integrated to facilitate future validation. | ||
| 650 | 4 | |a Cancers and neoplasms | |
| 650 | 4 | |a Decision making | |
| 650 | 4 | |a Forecasting | |
| 650 | 4 | |a Gene expression | |
| 650 | 4 | |a Gene ontologies | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Multiple myeloma | |
| 650 | 4 | |a Principal component analysis | |
| 700 | 1 | |a Wang, ShanJin |e VerfasserIn |4 aut | |
| 700 | 1 | |8 1\p |a Pan, Wei |d 1987- |e VerfasserIn |0 (DE-588)1296600629 |0 (DE-627)185305772X |4 aut | |
| 700 | 1 | |a Yi, YuYang |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lu, Junyan |e VerfasserIn |0 (DE-588)124416478X |0 (DE-627)1775109585 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |a Public Library of Science |t PLoS Computational Biology |d San Francisco, Calif. : Public Library of Science, 2005 |g 20(2024), 9, Artikel-ID e1012444, Seite 1-20 |h Online-Ressource |w (DE-627)491436017 |w (DE-600)2193340-6 |w (DE-576)273890492 |x 1553-7358 |7 nnas |
| 773 | 1 | 8 | |g volume:20 |g year:2024 |g number:9 |g elocationid:e1012444 |g pages:1-20 |g extent:20 |a Construct prognostic models of multiple myeloma with pathway information incorporated |
| 856 | 4 | 0 | |u https://doi.org/10.1371/journal.pcbi.1012444 |x Verlag |x Resolving-System |z kostenfrei |3 Volltext |
| 856 | 4 | 0 | |u https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1012444 |x Verlag |z kostenfrei |3 Volltext |
| 883 | |8 1\p |a cgwrk |d 20250301 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | ||
| 951 | |a AR | ||
| 992 | |a 20250214 | ||
| 993 | |a Article | ||
| 994 | |a 2024 | ||
| 998 | |g 124416478X |a Lu, Junyan |m 124416478X:Lu, Junyan |d 910000 |d 911700 |e 910000PL124416478X |e 911700PL124416478X |k 0/910000/ |k 1/910000/911700/ |p 5 |y j | ||
| 999 | |a KXP-PPN191727839X |e 466422480X | ||
| BIB | |a Y | ||
| SER | |a journal | ||
| JSO | |a {"relHost":[{"physDesc":[{"extent":"Online-Ressource"}],"name":{"displayForm":["publ. by the Public Library of Science (PLoS) in association with the International Society for Computational Biology (ISCB)"]},"id":{"zdb":["2193340-6"],"eki":["491436017"],"issn":["1553-7358"]},"origin":[{"publisher":"Public Library of Science","dateIssuedKey":"2005","dateIssuedDisp":"2005-","publisherPlace":"San Francisco, Calif."}],"language":["eng"],"corporate":[{"role":"aut","roleDisplay":"VerfasserIn","display":"Public Library of Science"}],"recId":"491436017","type":{"bibl":"periodical","media":"Online-Ressource"},"disp":"Public Library of SciencePLoS Computational Biology","note":["Gesehen am 23. November 2020"],"part":{"year":"2024","pages":"1-20","issue":"9","volume":"20","text":"20(2024), 9, Artikel-ID e1012444, Seite 1-20","extent":"20"},"pubHistory":["1.2005 -"],"title":[{"title_sort":"PLoS Computational Biology","subtitle":"a new community journal","title":"PLoS Computational Biology"}]}],"physDesc":[{"noteIll":"Illustrationen","extent":"20 S."}],"name":{"displayForm":["Shuo Wang, ShanJin Wang, Wei Pan, YuYang Yi, Junyan Lu"]},"id":{"doi":["10.1371/journal.pcbi.1012444"],"eki":["191727839X"]},"origin":[{"dateIssuedDisp":"September 10, 2024","dateIssuedKey":"2024"}],"language":["eng"],"recId":"191727839X","type":{"bibl":"article-journal","media":"Online-Ressource"},"note":["Gesehen am 14.02.2025"],"person":[{"family":"Wang","given":"Shuo","roleDisplay":"VerfasserIn","display":"Wang, Shuo","role":"aut"},{"given":"ShanJin","family":"Wang","role":"aut","roleDisplay":"VerfasserIn","display":"Wang, ShanJin"},{"family":"Pan","given":"Wei","roleDisplay":"VerfasserIn","display":"Pan, Wei","role":"aut"},{"given":"YuYang","family":"Yi","role":"aut","display":"Yi, YuYang","roleDisplay":"VerfasserIn"},{"given":"Junyan","family":"Lu","role":"aut","roleDisplay":"VerfasserIn","display":"Lu, Junyan"}],"title":[{"title_sort":"Construct prognostic models of multiple myeloma with pathway information incorporated","title":"Construct prognostic models of multiple myeloma with pathway information incorporated"}]} | ||
| SRT | |a WANGSHUOWACONSTRUCTP1020 | ||