ArticleCancer cell international2025
Multi-omics profiling of metastatic colorectal cancer reveals the transcriptional network of focal adhesion and immune suppression and the role of p-RPS6.
Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Identification and Integration of LRG1-Induced Differentially Expressed Gene (DEG) Hub Profiles in Breast Cancer Cells.International journal of molecular sciences · 2026Article
- Genetic insights into colorectal cancer pathogenesis: a multi-omics and immunity perspective.Translational cancer research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundColorectal cancer (CRC) is one of the deadliest malignancies worldwide characterized by rapid progression, high metastasis propensity. Our study aimed to identify the driving biological factors of metastatic CRC.
methodsWe obtained frozen tumor tissues of 8 metastatic CRC (mCRC) patients and 10 non-metastatic CRC (nmCRC) patients from Ruijin Hospital for proteome analysis. FFPE tumor and adjacent normal tissues of another 8 metastatic CRC patients and 8 non-metastatic CRC patients were collected for transcriptome and whole exome sequencing. Mutational burden and signatures were revealed and differentially expressed genes and proteins were analyzed. Molecular Complex Detection was used to build the core network. KEGG and GO pathway enrichment analysis were performed. IHC staining against p-RPS6 and subsequent quantification were performed on human samples.
resultsWe identified 53,917 SNPs by WES with a median of 1154 variants per sample and 23.08 mutations per megabase (Mb). We observed the mutation burdens were similar between mCRC tumor and nmCRC tumor tissues (p = 0.57), as well as the mutation frequencies of HRR and MMR related genes. All mCRC samples were affected by RTK-RAS, NOTCH and WNT pathway mutations. We constructed a 16-hub-gene network in mCRC which was characterized by dis-modulation of cell adhesion (SELE, SELL and SELP) and immune exhaustion (CXCR2, CCR7, CXCR1, CXCL13, CCL7, CCL19, CXCL11 and CD19) in mCRC tumor microenvironment. We detected 22 differentially expressed proteins, 54 phosphorylated proteins and 6 tyrosine-phosphorylated proteins between mCRC and nmCRC tumors. Phosphorylated RPS6 (p-RPS6) was the most differentially expressed protein between mCRC and nmCRC tumor tissues, which was found to be positively correlated with EMT proteins and poor prognosis in CRC. The IHC staining against p-RPS6 on human samples supported the strong expression in mCRC tumor samples.
conclusionsWe identified the key transcriptome network in mCRC and confirmed the important role for RPS6 phosphorylation in mCRC. Our study suggested that the features of mCRC tumors were not driven by gene mutations. We revealed the EMT feature and immune exhaustion of the mCRC tumor microenvironment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.