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Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer

Published in Nature Communications (2022-02-10)
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TL

TL;DR

A machine learning-based integrative procedure to construct a consensus immune-related lncRNA signature to predict prognosis, recurrence and treatment benefits in colorectal cancer and could serve as a robust and promising tool to improve clinical outcomes for individual CRC patients.

Abstract

Authors

Zaoqu Liu

1 Paper

Long Liu

1 Paper

Siyuan Weng

1 Paper

C-C Guo

1 Paper

Q. Dang

1 Paper

Hui-Xian Xu

1 Paper

Libo Wang

1 Paper

Taoyuan Lu

1 Paper

Yuyuan Zhang

1 Paper

Zhenqiang Sun

1 Paper

Xinwei Han

1 Paper

References48 items

1

Bevacizumab in Combination With Oxaliplatin-Based Chemotherapy As First-Line Therapy in Metastatic Colorectal Cancer: A Randomized Phase III Study

2

Development and clinical validation of a novel six-gene signature for accurately predicting the recurrence risk of patients with stage II/III colorectal cancer

3

Establishment and experimental validation of an immune miRNA signature for assessing prognosis and immune landscape of patients with colorectal cancer

4

Prognostic Cancer Gene Expression Signatures: Current Status and Challenges

5

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

Research Impact

313

Citations

48

References

0

Datasets

11

6

Identification of LncRNAs Associated With FOLFOX Chemoresistance in mCRC and Construction of a Predictive Model

7

The clinical relevance of gene expression based prognostic signatures in colorectal cancer.

8

Pembrolizumab in MSI-H-dMMR Advanced Colorectal Cancer - A New Standard of Care.

9

Emerging Role and Therapeutic Potential of lncRNAs in Colorectal Cancer

10

Genomic Alteration Characterization in Colorectal Cancer Identifies a Prognostic and Metastasis Biomarker: FAM83A|IDO1

11

Long noncoding RNA: a dazzling dancer in tumor immune microenvironment

12

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients

13

Bevacizumab (Avastin®) in cancer treatment: A review of 15 years of clinical experience and future outlook.

14

Pan-cancer characterization of immune-related lncRNAs identifies potential oncogenic biomarkers

15

Prognostic and Predictive Molecular Biomarkers for Colorectal Cancer: Updates and Challenges

16

Hypoxia induced LUCAT1/PTBP1 axis modulates cancer cell viability and chemotherapy response

17

The combination of bevacizumab/Avastin and erlotinib/Tarceva is relevant for the treatment of metastatic renal cell carcinoma: the role of a synonymous mutation of the EGFR receptor

18

5-fluorouracil and other fluoropyrimidines in colorectal cancer: Past, present and future.

19

Relative contribution of clinicopathological variables, genomic markers, transcriptomic subtyping and microenvironment features for outcome prediction in stage II/III colorectal cancer

20

Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.

21

Immunotherapy in colorectal cancer: rationale, challenges and potential

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Durable Clinical Benefit With Nivolumab Plus Ipilimumab in DNA Mismatch Repair-Deficient/Microsatellite Instability-High Metastatic Colorectal Cancer.

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Immunobiology of Long Noncoding RNAs.

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Predictive biomarkers for checkpoint inhibitor-based immunotherapy.

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Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models

29

A molecular portrait of microsatellite instability across multiple cancers

30

Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade

31

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade

32

The Consensus Molecular Subtypes of Colorectal Cancer

33

Combination cancer immunotherapy and new immunomodulatory targets

34

Critical limitations of consensus clustering in class discovery

35

New Approaches but the Same Flaws in the Search for Prognostic Signatures

36

Gene Expression Classification of Colon Cancer into Molecular Subtypes: Characterization, Validation, and Prognostic Value

37

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38

Prognostic and predictive markers in stage II colon cancer: is there a role for gene expression profiling?

39

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40

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41

Bevacizumab plus irinotecan, fluorouracil, and leucovorin for metastatic colorectal cancer.

42

Identi cation of an immune-related gene signature to improve prognosis prediction of colorectal cancer patients

43

New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

44

Identi cation of LncRNAs associated With FOLFOX and Y.Y.

45

Competing interests The authors declare no competing interests

46

Author contributions

47

Reprints and permission information is available at Publisher ’ s note Springer Nature remains neutral with published maps and institutional af fi liations.

48

Project (YXKC2020037); and Henan Provincial Health Commission Joint Youth (SB201902014). The human fi gure outline was sourced from the free website

Authors

Field of Study

Medicine

Journal Information

Name

Nature Communications

Volume

13

Venue Information

Name

Nature Communications

Type

journal

URL

https://www.nature.com/ncomms/

Alternate Names

  • Nat Commun