Early Adaptation of Colorectal Cancer Cells to the Peritoneal Cavity Is Associated with Activation of "Stemness" Programs and Local Inflammation

Genomic landscape defines peritoneal metastatic pattern and related target of peritoneal metastasis in colorectal cancer

The primary objective of this study is to develop a prediction model for peritoneal metastasis (PM) in colorectal cancer by integrating the genomic features of primary colorectal cancer, along with clinicopathological features. Concurrently, we aim to identify potential target implicated in the peritoneal dissemination of colorectal cancer through bioinformatics exploration and experimental validation. By analyzing the genomic landscape of primary colorectal cancer and clinicopathological features from 363 metastatic colorectal cancer patients, we identified 22 differently distributed variables, which were used for subsequent LASSO regression to construct a PM prediction model. The integrated model established by LASSO regression, which incorporated two clinicopathological variables and seven genomic variables, precisely discriminated PM cases (AUC 0.899; 95% CI 0.860-0.937) with good calibration (Hosmer-Lemeshow test p = .147). Model validation yielded AUCs of 0.898 (95% CI 0.896-0.899) and 0.704 (95% CI 0.622-0.787) internally and externally, respectively. Additionally, the peritoneal metastasis-related genomic signature (PGS), which was composed of the seven genes in the integrated model, has prognostic stratification capability for colorectal cancer. The divergent genomic landscape drives the driver genes of PM. Bioinformatic analysis concerning these driver genes indicated SERINC1 may be associated with PM. Subsequent experiments indicate that knocking down of SERINC1 functionally suppresses peritoneal dissemination, emphasizing its importance in CRCPM. In summary, the genomic landscape of primary cancer in colorectal cancer defines peritoneal metastatic pattern and reveals the potential target of SERINC1 for PM in colorectal cancer.

Adipose-derived stem cells promote glycolysis and peritoneal metastasis via TGF-β1/SMAD3/ANGPTL4 axis in colorectal cancer

Peritoneal metastasis, the third most common metastasis in colorectal cancer (CRC), has a poor prognosis for the rapid progression and limited therapeutic strategy. However, the molecular characteristics and pathogenesis of CRC peritoneal metastasis are poorly understood. Here, we aimed to elucidate the action and mechanism of adipose-derived stem cells (ADSCs), a prominent component of the peritoneal microenvironment, in CRC peritoneal metastasis formation. Database analysis indicated that ADSCs infiltration was increased in CRC peritoneal metastases, and high expression levels of ADSCs marker genes predicted a poor prognosis. Then we investigated the effect of ADSCs on CRC cells in vitro and in vivo. The results revealed that CRC cells co-cultured with ADSCs exhibited stronger metastatic property and anoikis resistance, and ADSCs boosted the intraperitoneal seeding of CRC cells. Furthermore, RNA sequencing was carried out to identify the key target gene, angiopoietin like 4 (ANGPTL4), which was upregulated in CRC specimens, especially in peritoneal metastases. Mechanistically, TGF-β1 secreted by ADSCs activated SMAD3 in CRC cells, and chromatin immunoprecipitation assay showed that SMAD3 facilitated ANGPTL4 transcription by directly binding to ANGPTL4 promoter. The ANGPTL4 upregulation was essential for ADSCs to promote glycolysis and anoikis resistance in CRC. Importantly, simultaneously targeting TGF-β signaling and ANGPTL4 efficiently reduced intraperitoneal seeding in vivo. In conclusion, this study indicates that tumor-infiltrating ADSCs promote glycolysis and anoikis resistance in CRC cells and ultimately facilitate peritoneal metastasis via the TGF-β1/SMAD3/ANGPTL4 axis. The dual-targeting of TGF-β signaling and ANGPTL4 may be a feasible therapeutic strategy for CRC peritoneal metastasis.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Primary Colorectal Tumor Displays Differential Genomic Expression Profiles Associated with Hepatic and Peritoneal Metastases

BACKGROUND

Despite improvements in characterization of CRC heterogeneity, appropriate risk stratification tools are still lacking in clinical practice. This study aimed to elucidate the primary tumor transcriptomic signatures associated with distinct metastatic routes.

METHODS

Primary tumor specimens obtained from CRC patients with either isolated LM (CRC-Liver) or PM (CRC-Peritoneum) were analyzed by transcriptomic mRNA sequencing, gene set enrichment analyses (GSEA) and immunohistochemistry. We further assessed the clinico-pathological associations and prognostic value of our signature in the COAD-TCGA independent cohort.

RESULTS

We identified a significantly different distribution of Consensus Molecular Subtypes between CRC-Liver and CRC-peritoneum groups. A transcriptomic signature based on 61 genes discriminated between liver and peritoneal metastatic routes. GSEA showed a higher expression of immune response and epithelial invasion pathways in CRC-Peritoneum samples and activation of proliferation and metabolic pathways in CRC-Liver samples. The biological relevance of RNA-Seq results was validated by the immunohistochemical expression of three significantly differentially expressed genes (ACE2, CLDN18 and DUSP4) in our signature. In silico analysis of the COAD-TCGA showed that the CRC-Peritoneum signature was associated with negative prognostic factors and poor overall and disease-free survivals.

CONCLUSIONS

CRC primary tumors spreading to the liver and peritoneum display significantly different transcriptomic profiles. The implementation of this signature in clinical practice could contribute to identify new therapeutic targets for stage IV CRC and to define individualized follow-up programs in stage II-III CRC.

The molecular biology of peritoneal metastatic disease

Peritoneal metastases are a common form of tumor cell dissemination in gastrointestinal malignancies. Peritoneal metastatic disease (PMD) is associated with severe morbidity and resistance to currently employed therapies. Given the distinct route of dissemination compared with distant organ metastases, and the unique microenvironment of the peritoneal cavity, specific tumor cell characteristics are needed for the development of PMD. In this review, we provide an overview of the known histopathological, genomic, and transcriptomic features of PMD. We find that cancers representing the mesenchymal subtype are strongly associated with PMD in various malignancies. Furthermore, we discuss the peritoneal niche in which the metastatic cancer cells reside, including the critical role of the peritoneal immune system. Altogether, we show that PMD should be regarded as a distinct disease entity, that requires tailored treatment strategies.

A Prediction Model Intended for Exploratory Laparoscopy Risk Stratification in Colorectal Cancer Patients With Potential Occult Peritoneal Metastasis

Background

The early diagnosis of occult peritoneal metastasis (PM) remains a challenge due to the low sensitivity on computed tomography (CT) images. Exploratory laparoscopy is the gold standard to confirm PM but should only be proposed in selected patients due to its invasiveness, high cost, and port-site metastasis risk. In this study, we aimed to develop an individualized prediction model to identify occult PM status and determine optimal candidates for exploratory laparoscopy.

Method

A total of 622 colorectal cancer (CRC) patients from 2 centers were divided into training and external validation cohorts. All patients’ PM status was first detected as negative on CT imaging but later confirmed by exploratory laparoscopy. Multivariate analysis was used to identify independent predictors, which were used to build a prediction model for identifying occult PM in CRC. The concordance index (C-index), calibration plot and decision curve analysis were used to evaluate its predictive accuracy and clinical utility.

Results

The C-indices of the model in the development and validation groups were 0.850 (95% CI 0.815-0.885) and 0.794 (95% CI, 0.690-0.899), respectively. The calibration curve showed consistency between the observed and predicted probabilities. The decision curve analysis indicated that the prediction model has a great clinical value between thresholds of 0.10 and 0.72. At a risk threshold of 30%, a total of 40% of exploratory laparoscopies could have been prevented, while still identifying 76.7% of clinically occult PM cases. A dynamic online platform was also developed to facilitate the usage of the proposed model.

Conclusions

Our individualized risk model could reduce the number of unnecessary exploratory laparoscopies while maintaining a high rate of diagnosis of clinically occult PM. These results warrant further validation in prospective studies.

Clinical Trial Registration

https://www.isrctn.com, identifier ISRCTN76852032

Consensus molecular subtype differences linking colon adenocarcinoma and obesity revealed by a cohort transcriptomic analysis

Colorectal cancer (CRC) is the third-leading cause of cancer-related deaths in the United States and worldwide. Obesity—a worldwide public health concern—is a known risk factor for cancer including CRC. However, the mechanisms underlying the link between CRC and obesity have yet to be fully elucidated in part because of the molecular heterogeneity of CRC. We hypothesized that obesity modulates CRC in a consensus molecular subtype (CMS)-dependent manner. RNA-seq data and associated tumor and patient characteristics including body weight and height data for 232 patients were obtained from The Cancer Genomic Atlas–Colon Adenocarcinoma (TCGA-COAD) database. Tumor samples were classified into the four CMSs with the CMScaller R package; body mass index (BMI) was calculated and categorized as normal, overweight, and obese. We observed a significant difference in CMS categorization between BMI categories. Differentially expressed genes (DEGs) between obese and overweight samples and normal samples differed across the CMSs, and associated prognostic analyses indicated that the DEGs had differing associations on survival. Using Gene Set Enrichment Analysis, we found differences in Hallmark gene set enrichment between obese and overweight samples and normal samples across the CMSs. We constructed Protein-Protein Interaction networks and observed differences in obesity-regulated hub genes for each CMS. Finally, we analyzed and found differences in predicted drug sensitivity between obese and overweight samples and normal samples across the CMSs. Our findings support that obesity impacts the CRC tumor transcriptome in a CMS-specific manner. The possible associations reported here are preliminary and will require validation using in vitro and animal models to examine the CMS-dependence of the genes and pathways. Once validated the obesity-linked genes and pathways may represent new therapeutic targets to treat colon cancer in a CMS-dependent manner.