A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma : A 16-year prospective multicentric study
Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved..
Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:585 |
|---|---|
| Enthalten in: |
Cancer letters - 585(2024) vom: 31. März, Seite 216663 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Liu, Chuan [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Journal Article |
|---|
| Anmerkungen: |
Date Completed 05.03.2024 Date Revised 05.03.2024 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.canlet.2024.216663 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM36736719X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM36736719X | ||
| 003 | DE-627 | ||
| 005 | 20240305232227.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240122s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.canlet.2024.216663 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1317.xml |
| 035 | |a (DE-627)NLM36736719X | ||
| 035 | |a (NLM)38246221 | ||
| 035 | |a (PII)S0304-3835(24)00057-0 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Liu, Chuan |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma |b A 16-year prospective multicentric study |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 05.03.2024 | ||
| 500 | |a Date Revised 05.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved. | ||
| 520 | |a Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments | ||
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Molecular subtype | |
| 650 | 4 | |a Multicenter | |
| 650 | 4 | |a Primary colorectal melanoma | |
| 650 | 4 | |a Proteomics | |
| 700 | 1 | |a Cheng, Xiaofei |e verfasserin |4 aut | |
| 700 | 1 | |a Han, Kai |e verfasserin |4 aut | |
| 700 | 1 | |a Hong, Libing |e verfasserin |4 aut | |
| 700 | 1 | |a Hao, Shuqiang |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Xuqi |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Jingfeng |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Benfeng |e verfasserin |4 aut | |
| 700 | 1 | |a Jin, Dongqing |e verfasserin |4 aut | |
| 700 | 1 | |a Tian, Weihong |e verfasserin |4 aut | |
| 700 | 1 | |a Jin, Yuzhi |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yanli |e verfasserin |4 aut | |
| 700 | 1 | |a Fang, Weijia |e verfasserin |4 aut | |
| 700 | 1 | |a Bao, Xuanwen |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Peng |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Dong |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Cancer letters |d 1976 |g 585(2024) vom: 31. März, Seite 216663 |w (DE-627)NLM000147273 |x 1872-7980 |7 nnns |
| 773 | 1 | 8 | |g volume:585 |g year:2024 |g day:31 |g month:03 |g pages:216663 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.canlet.2024.216663 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 585 |j 2024 |b 31 |c 03 |h 216663 | ||