Genes involved in the transition from normal epithelium to intraepithelial neoplasia are associated with colorectal cancer patient survival

Integrating spatial and single-cell transcriptomics reveals tumor heterogeneity and intercellular networks in colorectal cancer

Single cell RNA sequencing (scRNA-seq), a powerful tool for studying the tumor microenvironment (TME), does not preserve/provide spatial information on tissue morphology and cellular interactions. To understand the crosstalk between diverse cellular components in proximity in the TME, we performed scRNA-seq coupled with spatial transcriptomic (ST) assay to profile 41,700 cells from three colorectal cancer (CRC) tumor-normal-blood pairs. Standalone scRNA-seq analyses revealed eight major cell populations, including B cells, T cells, Monocytes, NK cells, Epithelial cells, Fibroblasts, Mast cells, Endothelial cells. After the identification of malignant cells from epithelial cells, we observed seven subtypes of malignant cells that reflect heterogeneous status in tumor, including tumor_CAV1, tumor_ATF3_JUN | FOS, tumor_ZEB2, tumor_VIM, tumor_WSB1, tumor_LXN, and tumor_PGM1. By transferring the cellular annotations obtained by scRNA-seq to ST spots, we annotated four regions in a cryosection from CRC patients, including tumor, stroma, immune infiltration, and colon epithelium regions. Furthermore, we observed intensive intercellular interactions between stroma and tumor regions which were extremely proximal in the cryosection. In particular, one pair of ligands and receptors (C5AR1 and RPS19) was inferred to play key roles in the crosstalk of stroma and tumor regions. For the tumor region, a typical feature of TMSB4X-high expression was identified, which could be a potential marker of CRC. The stroma region was found to be characterized by VIM-high expression, suggesting it fostered a stromal niche in the TME. Collectively, single cell and spatial analysis in our study reveal the tumor heterogeneity and molecular interactions in CRC TME, which provides insights into the mechanisms underlying CRC progression and may contribute to the development of anticancer therapies targeting on non-tumor components, such as the extracellular matrix (ECM) in CRC. The typical genes we identified may facilitate to new molecular subtypes of CRC.

B7-H3 is spliced by SRSF3 in colorectal cancer

B7-H3, an important co-inhibitor, is abnormally highly expressed in a variety of malignancies. The antibodies targeting B7-H3 have exhibited beneficial therapeutic effects in clinical trials. Therefore, discovery of the regulatory factors in B7-H3 expression may provide new strategies for tumor therapy. Here, we investigated the splicing factors involved in the splicing of B7-H3. By individual knockdown of the splicing factors in colorectal cancer (CRC) cells, we found that B7-H3 expression was markedly inhibited by SRSF3 and SRSF8, especially SRSF3. Then we found that both SRSF3 and B7-H3 were highly expressed in CRC tissues. Moreover, high-expression of either SRSF3 or B7-H3 was significantly correlated with poor prognosis of patients. The expression of B7-H3 mRNA and protein were evidently reduced by SRSF3 silence, but were enhanced by overexpression of SRSF3 in both HCT-116 and HCT-8 cells. The results from the RNA immunoprecipitation (RIP) assays demonstrated that SRSF3 protein directly binds to B7-H3 mRNA. In addition, we constructed a minigene recombinant plasmid for expressing B7-H3 exons 3-6. We found that SRSF3 contributed to the retention of B7-H3 exon 4. These findings demonstrate that SRSF3 involves in the splicing of B7-H3 by directly binding to its exon 4 and/or 6. It may provide novel insights into the regulatory mechanisms of B7-H3 expression and potential strategies for the treatment of CRC.

Identification of prognostic genes in colorectal cancer through transcription profiling of multi-stage carcinogenesis

Colorectal cancer is a complex multistage process following the adenoma-carcinoma sequence. Additional research on the basis of molecular dysregulations, particularly in the precancerous stage, may provide insight into the realization of potential biomarkers and therapeutic targets for the disease. In the present study, the expression profile of human multistage colorectal mucosa tissues, including healthy, adenoma and adenocarcinoma samples, was downloaded. Genes that were consistently differentially expressed in precancerous tissues and cancer samples were collected. Based on a merged biological network, the biggest connected component composed of these identified genes and their one-step neighbors were retrieved to conduct random walk with restart algorithm, in order to identify genes significantly affected during carcinogenesis. Therefore, 35 genes significantly affected by carcinogenic dysregulation were successfully identified. Survival and Cox analysis indicated that the expression of these genes was an independent prognostic factor confirmed by six cohorts. In summary, based on the transcription profile of multi-stage carcinogenesis and bioinformatics analysis, 35 genes significantly associated with patient survival were successfully identified, which may serve as promising therapeutic targets for the disease.

mRNA-miRNA bipartite network reconstruction to predict prognostic module biomarkers in colorectal cancer stage differentiation

Biomarker detection is one of the most important and challenging problems in cancer studies. Recently, non-coding RNA based biomarkers such as miRNA expression levels have been used for early diagnosis of many cancer types. In this study, a systems biology approach was used to detect novel miRNA based biomarkers for CRC diagnosis in early stages. The mRNA expression data from three CRC stages (Low-grade Intraepithelial Neoplasia (LIN), High-grade Intraepithelial Neoplasia (HIN) and Adenocarcinoma) were used to reconstruct co-expression networks. The networks were clustered to extract co-expression modules and detected low preserved modules among CRC stages. Then, the experimentally validated mRNA-miRNA interaction data were applied to reconstruct three mRNA-miRNA bipartite networks. Twenty miRNAs with the highest degree (hub miRNAs) were selected in each bipartite network to reconstruct three bipartite subnetworks for further analysis. The analysis of these hub miRNAs in the bipartite subnetworks revealed 30 distinct important miRNAs as prognostic markers in CRC stages. There are two novel CRC related miRNAs (hsa-miR-190a-3p and hsa-miR-1277-5p) in these 30 hub miRNAs that have not been previously reported in CRC. Furthermore, a drug-gene interaction network was reconstructed to detect potential candidate drugs for CRC treatment. Our analysis shows that the hub miRNAs in the mRNA-miRNA bipartite network are very essential in CRC progression and should be investigated precisely in future studies. In addition, there are many important target genes in the results that may be critical in CRC progression and can be analyzed as therapeutic targets in future research.

Prognostic impact of a novel gene expression profile classifier for the discrimination between metastatic and non-metastatic primary colorectal cancer tumors

Despite significant advances have been achieved in the genetic characterization of sporadic colorectal cancer (sCRC), the precise genetic events leading to the development of distant metastasis remain poorly understood. Thus, accurate prediction of metastatic disease in newly-diagnosed sCRC patients remains a challenge. Here, we evaluated the specific genes and molecular pathways associated with the invasive potential of colorectal tumor cells, through the assessment of the gene expression profile (GEP) of coding and non-coding genes in metastatic (MTX) vs. non-metastatic (non-MTX) primary sCRC tumors followed for >5 years. Overall, MTX tumors showed up-regulation of genes associated with tumor progression and metastatic potential while non-MTX cases displayed GEP associated with higher cell proliferation, activation of DNA repair and anti-tumoral immune/inflammatory responses. Based on only 19 genes a specific GEP that classifies sCRC tumors into two MTX-like and non-MTX-like molecular subgroups was defined which shows an independent prognostic impact on patient overall survival, particularly when it is combined with the lymph node status at diagnosis. In summary, we show an association between the global GEP of primary sCRC cells and their metastatic potential and defined a GEP-based classifier that provides the basis for further prognostic stratification of sCRC patients who are at risk of distant metastases.

Feasibility of Unbiased RNA Profiling of Colorectal Tumors: A Proof of Principle

Despite recent advances in molecular profiling of colorectal cancer (CRC), as of yet this has not translated into an unbiased molecular liquid biopsy profile which can accurately screen for early CRC. In this study we depict the profile of early stage CRC as well as for advanced adenomas (AA) by combination of current molecular knowledge with microarray technology, using efficient circulating free plasma RNA purification from blood and RNA amplification technologies. We joined literature search with Affymetrix gene chip experimental procedure to draw the circulating free plasma RNA profile of colorectal cancer disease reflected in blood. The RNA panel was tested by two datasets comparing patients with CRC with healthy subjects and patients with AA to healthy subjects. For the CRC patient cohort (28 CRC cases vs. 41 healthy controls), the ROC analysis of the selected biomarker panel generated a sensitivity of 75% and a specificity of 93% for the detection of CRC using 8-gene classification model. For the AA patient cohort (28 subjects vs. 46 healthy controls), a sensitivity of 60% and a specificity of 87% were calculated using a 2-gene classification model. We have identified a panel of 8 plasma RNA markers as a preliminary panel for CRC detection and subset markers suitable for AA detection. Subjected to extensive clinical validation we suggest that this panel represents a feasible approach and a potential strategy for noninvasive early diagnosis, as a first-line screening test for asymptomatic, average-risk population before colonoscopy.

A network-based method for identifying prognostic gene modules in lung squamous carcinoma

Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients.

Serum miR-21, miR-29a, and miR-125b Are Promising Biomarkers for the Early Detection of Colorectal Neoplasia

PURPOSE

Circulating microRNAs (miRNA) are emerging as promising diagnostic biomarkers for colorectal cancer, but their usefulness for detecting early colorectal neoplasms remains unclear. This study aimed to identify serum miRNA biomarkers for the identification of patients with early colorectal neoplasms.

EXPERIMENTAL DESIGN

A cohort of 237 serum samples from 160 patients with early colorectal neoplasms (148 precancerous lesions and 12 cancers) and 77 healthy subjects was analyzed in a three-step approach that included a comprehensive literature review for published biomarkers, a screening phase, and a validation phase. RNA was extracted from sera, and levels of miRNAs were examined by real-time RT-PCR.

RESULTS

Nine miRNAs (miR-18a, miR-19a, miR-19b, miR-20a, miR-21, miR-24, miR-29a, miR-92, and miR-125b) were selected as candidate biomarkers for initial analysis. In the screening phase, serum levels of miR-21, miR-29a, and miR-125b were significantly higher in patients with early colorectal neoplasm than in healthy controls. Elevated levels of miR-21, miR-29a, and miR-125b were confirmed in the validation phase using an independent set of subjects. Area under the curve (AUC) values for serum miR-21, miR-29a, miR-125b, and their combined score in discriminating patients with early colorectal neoplasm from healthy controls were 0.706, 0.741, 0.806, and 0.827, respectively. Serum levels of miR-29a and miR-125b were significantly higher in patients who had only small colorectal neoplasms (≤5 mm) than in healthy subjects.

CONCLUSIONS

Because serum levels of miR-21, miR-29a, and miR-125b discriminated patients with early colorectal neoplasm from healthy controls, our data highlight the potential clinical use of these molecular signatures for noninvasive screening of patients with colorectal neoplasia.