This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
The tumor environment immune phenotype of LUSC by genome-wide analysis
Cheng Zhan
Fudan University
Corresponding Author
ORCiD: https://orcid.org/0000-0001-8745-9276
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
To compare the landscape of tumor microenvironment (TME) of lung squamous carcinoma (LUSC) in different immune pattern and explore potential factors on immune therapy and prognosis
Method and Materials:
We have obtained the LUSC data from TCGA, GEO, and our department and classified them into 2 TME clusters by random forest model based on the infiltration pattern of 24 immune cell populations. Then we systemically compared the genomic significance, clinical characteristic and immune infiltration pattern in 2 TME clusters.
Results
Samples were divided into 2 TME clusters based on the relative abundance of 24 immune cells and a random forest classifier model was constructed. TME cluster B was a higher immune infiltration group with lower mutation load, richer co-infiltrate immune cells, up-regulated immune-related cytokines including immune checkpoint molecules, and higher active immune cells. TME cluster was also an independent predictor in prognosis (B vs A, p < 0.05) in patients from TCGA, GEO and our department.
Conclusions
Our study has described the microenvironment landscape of LUSC in different immune infiltration patterns and systemically analyzed genomic and clinical characteristics with distinct immunophenotypes, thus partly revealed the interaction between tumors and immune microenvironment, which may guide a more precise and personalized immune therapeutic strategy for LUSC patients.
Keywords
Immune infiltration, Lung squamous carcinoma, Genome-wide, Tumor environment, Immune therapy, Random forest
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 20 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Translational Medicine
Learn more about our company.
This is a preprint. It has not completed peer review.
Research
The tumor environment immune phenotype of LUSC by genome-wide analysis
Cheng Zhan
Fudan University
Corresponding Author
ORCiD: https://orcid.org/0000-0001-8745-9276
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 20 May, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Translational Medicine
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
To compare the landscape of tumor microenvironment (TME) of lung squamous carcinoma (LUSC) in different immune pattern and explore potential factors on immune therapy and prognosis
Method and Materials:
We have obtained the LUSC data from TCGA, GEO, and our department and classified them into 2 TME clusters by random forest model based on the infiltration pattern of 24 immune cell populations. Then we systemically compared the genomic significance, clinical characteristic and immune infiltration pattern in 2 TME clusters.
Results
Samples were divided into 2 TME clusters based on the relative abundance of 24 immune cells and a random forest classifier model was constructed. TME cluster B was a higher immune infiltration group with lower mutation load, richer co-infiltrate immune cells, up-regulated immune-related cytokines including immune checkpoint molecules, and higher active immune cells. TME cluster was also an independent predictor in prognosis (B vs A, p < 0.05) in patients from TCGA, GEO and our department.
Conclusions
Our study has described the microenvironment landscape of LUSC in different immune infiltration patterns and systemically analyzed genomic and clinical characteristics with distinct immunophenotypes, thus partly revealed the interaction between tumors and immune microenvironment, which may guide a more precise and personalized immune therapeutic strategy for LUSC patients.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5