Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 22 min ago
Peer-reviewedCC BY 4.0Oncology Research

Seven-Gene Signature and Immune Microenvironment as Determinants of Survival Rate in Colorectal Carcinoma

  • Vincenzo Rallo1
  • Matteo Massidda1
  • Xiaofen Wen2,3
  • Manila Deiana1
  • Andrea Maschio1
  • Jiaxin Shen2,4
  • Maria Chiara Ninniri5
  • Daniela Piras6
  • Ciriaco Carru2
  • Donatella Coradduzza2
  • Maria Rosaria Muroni5
  • Paolo Cossu-Rocca5
3 more authors
  • Antonio Mario Scanu5
  • Andrea Angius1
  • Maria Rosaria De Miglio5
6 affiliations
  1. 1Institute of Genetic and Biomedical Research (IRGB), National Research Council (CNR), Monserrato, Italy
  2. 2Department of Biomedical Sciences, University of Sassari, Sassari, Italy
  3. 3Department of Medical Oncology, Cancer Hospital of Shantou University Medical College, Shantou, China
  4. 4Department of Hematology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China
  5. 5Department of Medicine, Surgery and Pharmacy, University of Sassari, Sassari, Italy
  6. 6Complex Structure Epidemiology and Cancer Registry North Sardinia, ATS Sardinia, Sassari, Italy
Read full textPDFDOICite

Abstract

Backgrounds: Colorectal cancer (CRC) prognosis remains difficult due to molecular heterogeneity and interaction between tumor cells and the immune microenvironment. This study aimed to identify transcriptomic and immune-cell patterns associated with overall survival (OS) and to develop an integrated prognostic model to improve risk stratification. Methods: RNA-sequencing was performed on 131 primary CRC samples and matched normal tissues. Differentially expressed genes (DEGs) were identified and functionally characterized through gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction (PPI) network analysis. Immune-cell composition was estimated using CIBERSORTx deconvolution and evaluated for its association with OS. Prognostic DEGs were screened using univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk score. The model was validated in the Cancer Genome Atlas Database (TCGA)-COAD (colon cancer) and READ (rectal cancer) cohorts. A nomogram integrating molecular and clinicopathological variables were generated. Results: A total of 5589 DEGs were identified between CRC and normal tissues, enriched in pathways related to cell cycle, Tumor Protein P53 (TP53), WNT Family Member (WNT), Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT), calcium signaling, metabolism, and immune regulation. PPI analysis highlighted ten upregulated hub genes involved in mitotic spindle formation and chromosomal stability. Immune infiltration analysys indicated that higher proportions of plasma cells (p = 6.9 × 10−4), naïve B cells (p = 0.019), resting CD4+ memory T cells (p = 0.02), M0 macrophages (p = 0.0077), and activated dendritic cells (p = 1.89 × 10−5) were associated with improved OS, whereas monocytes (p = 0.012), neutrophils (p = 0.041), activated mast cells (p = 0.0066), and M2 macrophages (p = 0.014) were linked to poorer survival. A seven-gene signature including aspartate beta-hydroxylase (ASPH), bradykinin receptor B1 (BDKRB1), calcium voltage-gated channel auxiliary subunit beta 1 (CACNB1), C-C motif chemokine receptor 8 (CCR8), cyclic nucleotide gated channel subunit alpha 3 (CNGA3), microtubule associated protein 1A (MAP1A) and oxytocin receptor (OXTR) stratified patients into high- and low-risk groups with significant OS differences. The model demonstrated strong predictive performance (AUC: 0.84 at 1 year) and was validated in TCGA cohorts. Multivariate analysis confirmed the risk score as an independent prognostic factor. The integrated nomogram accurately predicted 1-, 3-, and 5-year survival (C-index = 0.757; 95% CI 0.724–0.791). Conclusions: We developed and validated a seven-gene immune-related prognostic signature that, combined with clinicopathological parameters, provides a robust tool for individualized survival prediction and may guide precision management in CRC patients.

Related

  1. Ferroptosis-related lncRNA signature predicts prognosis and immune microenvironment remodeling in laryngeal squamous cell carcinoma
    Haibo Xu, Meiling Xu, Huijie Weng +3
    Discover OncologyPeer-reviewedCC BYFull textOncologyDOAJ
  2. A mitoxyperilysis-derived spatial signature predicts immune exclusion and survival in oral squamous cell carcinoma
    J. Liu, D. Zhang, Z. Meng +1
    medRxivPreprintCC BY-NCFull textOncologymedRxiv
  3. An R-loop-related gene signature predicts prognosis and shapes the immune microenvironment in esophageal squamous cell carcinoma.
    Cui Meng, Hong Su, Ruiqing Yan +4
    BMC cancerPeer-reviewedCC BY-NC-NDFull textSurgery & anaesthesiaEurope PMCDOAJ
  4. Postbiotic-related host transcriptomic axes link tumour immune microenvironment, stage and survival in colorectal cancer.
    Soroush Akbari-Ardabili
    Journal of translational medicinePeer-reviewedCC BY-NC-NDFull textOncologyEurope PMCPMC
  5. A tumor purity-based gene signature predicts prognosis and shapes the immune microenvironment in PAAD
    Lijun Ma, Zhi Ji, Lila Zhu +7
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textOncologyCrossref

Cite

BibTeXRIS
BibTeX
@article{rallo2026sevengene,
  title = {{Seven-Gene Signature and Immune Microenvironment as Determinants of Survival Rate in Colorectal Carcinoma}},
  author = {Vincenzo Rallo and Matteo Massidda and Xiaofen Wen and Manila Deiana and Andrea Maschio and Jiaxin Shen and Maria Chiara Ninniri and Daniela Piras and Ciriaco Carru and Donatella Coradduzza and Maria Rosaria Muroni and Paolo Cossu-Rocca and Antonio Mario Scanu and Andrea Angius and Maria Rosaria De Miglio},
  journal = {Oncology Research},
  year = {2026},
  month = oct,
  doi = {10.32604/or.2026.077466},
  url = {https://doi.org/10.32604/or.2026.077466},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Seven-Gene Signature and Immune Microenvironment as Determinants of Survival Rate in Colorectal Carcinoma
AU  - Vincenzo Rallo
AU  - Matteo Massidda
AU  - Xiaofen Wen
AU  - Manila Deiana
AU  - Andrea Maschio
AU  - Jiaxin Shen
AU  - Maria Chiara Ninniri
AU  - Daniela Piras
AU  - Ciriaco Carru
AU  - Donatella Coradduzza
AU  - Maria Rosaria Muroni
AU  - Paolo Cossu-Rocca
AU  - Antonio Mario Scanu
AU  - Andrea Angius
AU  - Maria Rosaria De Miglio
PY  - 2026
DA  - 2026/10/28
JO  - Oncology Research
DO  - 10.32604/or.2026.077466
UR  - https://doi.org/10.32604/or.2026.077466
AB  - Backgrounds: Colorectal cancer (CRC) prognosis remains difficult due to molecular heterogeneity and interaction between tumor cells and the immune microenvironment. This study aimed to identify transcriptomic and immune-cell patterns associated with overall survival (OS) and to develop an integrated prognostic model to improve risk stratification. Methods: RNA-sequencing was performed on 131 primary CRC samples and matched normal tissues. Differentially expressed genes (DEGs) were identified and functionally characterized through gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction (PPI) network analysis. Immune-cell composition was estimated using CIBERSORTx deconvolution and evaluated for its association with OS. Prognostic DEGs were screened using univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk score. The model was validated in the Cancer Genome Atlas Database (TCGA)-COAD (colon cancer) and READ (rectal cancer) cohorts. A nomogram integrating molecular and clinicopathological variables were generated. Results: A total of 5589 DEGs were identified between CRC and normal tissues, enriched in pathways related to cell cycle, Tumor Protein P53 (TP53), WNT Family Member (WNT), Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT), calcium signaling, metabolism, and immune regulation. PPI analysis highlighted ten upregulated hub genes involved in mitotic spindle formation and chromosomal stability. Immune infiltration analysys indicated that higher proportions of plasma cells (p = 6.9 × 10−4), naïve B cells (p = 0.019), resting CD4+ memory T cells (p = 0.02), M0 macrophages (p = 0.0077), and activated dendritic cells (p = 1.89 × 10−5) were associated with improved OS, whereas monocytes (p = 0.012), neutrophils (p = 0.041), activated mast cells (p = 0.0066), and M2 macrophages (p = 0.014) were linked to poorer survival. A seven-gene signature including aspartate beta-hydroxylase (ASPH), bradykinin receptor B1 (BDKRB1), calcium voltage-gated channel auxiliary subunit beta 1 (CACNB1), C-C motif chemokine receptor 8 (CCR8), cyclic nucleotide gated channel subunit alpha 3 (CNGA3), microtubule associated protein 1A (MAP1A) and oxytocin receptor (OXTR) stratified patients into high- and low-risk groups with significant OS differences. The model demonstrated strong predictive performance (AUC: 0.84 at 1 year) and was validated in TCGA cohorts. Multivariate analysis confirmed the risk score as an independent prognostic factor. The integrated nomogram accurately predicted 1-, 3-, and 5-year survival (C-index = 0.757; 95% CI 0.724–0.791). Conclusions: We developed and validated a seven-gene immune-related prognostic signature that, combined with clinicopathological parameters, provides a robust tool for individualized survival prediction and may guide precision management in CRC patients.
SN  - 0965-0407
SN  - 1555-3906
ER  -