Integrated analysis of colorectal cancer metastasis identifies characteristics of tumor cell during metastasis.

Background: Metastasis is the main cause of death in colorectal cancer (CRC). Metastasis is a sequential and dynamic process, but the development of tumor cells during this process is unclear. In this study, we aimed to reveal characteristics of tumor cell subset during CRC metastasis. Methods: Single-cell RNA sequence CRC data of normal epithelium, non-metastatic primary tumor, metastatic primary tumor, and liver metastases from gene expression omnibus (GEO) dataset were analyzed to reveal characteristics of CRC metastasis. Primary tumor tissues of three non-metastatic CRC and three metastatic CRC patients from Union Hospital of Tongji Medical College (Wuhan, China) were used to verify the characteristics of CRC metastasis. Results: We identified a metastasis-related cancer cell subset EP1, which was characterized with a high expression of KRT17, LAMC2, EMP1, and PLAC8. EP1 had an enhanced cell-cell interaction, which interacted with SPP+ macrophages and drove them toward anti-inflammatory and immunosuppressive phenotype. Dynamic changes in genes and TF regulons during the metastasis were also revealed. Conclusions: This study advanced our understanding of the development of tumor cells during CRC metastasis and further identified metastasis-related subset and potential therapeutic targets for the treatment and prevention of CRC metastasis.

A Graphene Composite Film Based Wearable Far-Infrared Therapy Apparatus (GRAFT) for Effective Prevention of Postoperative Peritoneal Adhesion.

Postoperative peritoneal adhesion (PPA) is the most frequent complication after abdominal surgery. Current anti-adhesion strategies largely rely on the use of physical separating barriers creating an interface blocking peritoneal adhesion, which cannot reduce inflammation and suffers from limited anti-adhesion efficacy with unwanted side effects. Here, by exploiting the alternative activated macrophages to alleviate inflammation in adhesion development, a flexible graphene-composite-film (F-GCF) generating far-infrared (FIR) irradiation that effectively modulates the macrophage phenotype toward the anti-inflammatory M2 type, resulting in reduced PPA formation, is designed. The anti-adhesion effect of the FIR generated by F-GCF is determined in the rat abdominal wall abrasion-cecum defect models, which exhibit reduced incidence and area of PPA by 67.0% and 92.1% after FIR treatment without skin damage, significantly superior to the clinically used chitosan hydrogel. Notably, within peritoneal macrophages, FIR reduces inflammation reaction and promotes tissue plasminogen activator (t-PA) level via the polarization of peritoneal macrophages through upregulating Nr4a2 expression. To facilitate clinical use, a wirelessly controlled, wearable, F-GCF-based FIR therapy apparatus (GRAFT) is further developed and its remarkable anti-adhesion ability in the porcine PPA model is revealed. Collectively, the physical, biochemical, and in vivo preclinical data provide compelling evidence demonstrating the clinical-translational value of FIR in PPA prevention.

Minimally invasive bioprinting for in situ liver regeneration.

In situ bioprinting is promising for developing scaffolds directly on defect models in operating rooms, which provides a new strategy for in situ tissue regeneration. However, due to the limitation of existing in situ biofabrication technologies including printing depth and suitable bioinks, bioprinting scaffolds in deep dermal or extremity injuries remains a grand challenge. Here, we present an in vivo scaffold fabrication approach by minimally invasive bioprinting electroactive hydrogel scaffolds to promote in situ tissue regeneration. The minimally invasive bioprinting system consists of a ferromagnetic soft catheter robot for extrusion, a digital laparoscope for in situ monitoring, and a Veress needle for establishing a pneumoperitoneum. After 3D reconstruction of the defects with computed tomography, electroactive hydrogel scaffolds are printed within partial liver resection of live rats, and in situ tissue regeneration is achieved by promoting the proliferation, migration, and differentiation of cells and maintaining liver function in vivo.

Long-read sequencing identifies novel structural variations in colorectal cancer.

Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.

Identification of TGF-ß signaling-related molecular patterns, construction of a prognostic model, and prediction of immunotherapy response in gastric cancer.

Background: TGF-ß signaling pathway plays an essential role in tumor progression and immune responses. However, the link between TGF-ß signaling pathway-related genes (TSRGs) and clinical prognosis, tumor microenvironment (TME), and immunotherapy in gastric cancer is unclear. Methods: Transcriptome data and related clinical data of gastric cancer were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and 54 TSRGs were obtained from the Molecular Signatures Database (MSigDB). We systematically analyzed the expression profile characteristics of 54 TSRGs in 804 gastric cancer samples and examined the differences in prognosis, clinicopathological features, and TME among different molecular subtypes. Subsequently, TGF-ß-related prognostic models were constructed using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to quantify the degree of risk in each patient. Patients were divided into two high- and low-risk groups based on the median risk score. Finally, sensitivity to immune checkpoint inhibitors (ICIs) and anti-tumor agents was assessed in patients in high- and low-risk groups. Results: We identified two distinct TGF-ß subgroups. Compared to TGF-ß cluster B, TGF-ß cluster A exhibits an immunosuppressive microenvironment with a shorter overall survival (OS). Then, a novel TGF-ß-associated prognostic model, including SRPX2, SGCE, DES, MMP7, and KRT17, was constructed, and the risk score was demonstrated as an independent prognostic factor for gastric cancer patients. Further studies showed that gastric cancer patients in the low-risk group, characterized by higher tumor mutation burden (TMB), the proportion of high microsatellite instability (MSI-H), immunophenoscore (IPS), and lower tumor immune dysfunction and exclusion (TIDE) score, had a better prognosis, and linked to higher response rate to immunotherapy. In addition, the risk score and anti-tumor drug sensitivity were strongly correlated. Conclusion: These findings highlight the importance of TSRGs, deepen the understanding of tumor immune microenvironment, and guide individualized immunotherapy for gastric cancer patients.

Identification and validation of a novel cellular senescence-related lncRNA prognostic signature for predicting immunotherapy response in stomach adenocarcinoma.

Background: Cellular senescence is a novel hallmark of cancer associated with patient outcomes and tumor immunotherapy. However, the value of cellular senescence-related long non-coding RNAs (lncRNAs) in predicting prognosis and immunotherapy response for stomach adenocarcinoma (STAD) patients needs further investigation. Methods: The transcriptome and corresponding clinical information of STAD and cellular senescence-related genes were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and CellAge databases. Differential expression analysis and coexpression analysis were performed to obtain cellular senescence-related lncRNAs. Univariate regression analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were conducted to establish the cellular senescence-related lncRNA prognostic signature (CSLPS). Next, the survival curve, ROC curve, and nomogram were developed to assess the capacity of predictive models. Moreover, principal component analysis (PCA), gene set enrichment analysis (GSEA), tumor microenvironment (TME), tumor mutation burden (TMB), microsatellite instability (MSI), and tumor immune dysfunction and exclusion (TIDE) score analysis were performed between high- and low-risk groups. Results: A novel CSLPS involving fifteen lncRNAs (REPIN1-AS1, AL355574.1, AC104695.3, AL033527.2, AC083902.1, TYMSOS, LINC00460, AC005165.1, AL136115.1, AC007405.2, AL391152.1, SCAT1, AC129507.1, AL121748.1, and ADAMTS9-AS1) was developed. According to the nomogram, the risk model based on the CSLPS was an independent prognostic factor and could predict 1-, 3-, and 5-year overall survival for STAD patients. GSEA suggested that the high-risk group was mainly associated with Toll-like receptor, JAK/STAT, NOD-like receptor, and chemokine signaling pathways. Further analysis revealed that STAD patients in the low-risk group with better clinical outcomes had a higher TMB, higher proportion of high microsatellite instability (MSI-H), better immune infiltration, and lower TIDE scores. Conclusion: A fifteen-CSlncRNA prognostic signature could predict survival outcomes, and patients in the low-risk group may be more sensitive to immunotherapy.

RecQ mediated genome instability 2 (RMI2): a potential prognostic and immunological biomarker for pan-cancers.

BACKGROUND: RecQ mediated genome instability 2 (RMI2) is an essential component of the BLM-TopoIIIa-RMI1-RMI2 (BTR) complex. However, the mysterious veil of the potential immunological relationship of RMI2 in tumorigenesis and development has not been revealed. METHODS: We conducted the differential expression (DE) analysis of the RMI2 in pan-cancer using data onto Oncomine, TIMER, and GEPIA databases. Afterward, survival analysis and clinical-stage correlation analysis were performed via the TCGA database. Subsequently, we used R software to further explore the relationship between the expression level of RMI2 and tumor mutation burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), tumor immune-infiltrated cells (TILs), immune checkpoints (ICP), mismatch repairs (MMRs) -related genes, m6A-related genes, DNA methylation-related genes. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional networks were also performed for annotation via gene set enrichment analysis (GSEA). RESULTS: The RMI2 expressed remarkably high in most cancer types compared to cancer adjacent normal tissues (P < 0.05). High expression of RMI2 was linked to unfavorable prognosis and advanced stage of disease, especially in LIHC and PAAD. RMI2 expression was related to TMB in 16 cancer types and MSI in 8 cancer types. Furthermore, it is significant positive correlations between RMI2 and stromal and immune cells, ICP-related genes, MMRs-related genes, m6A-related genes, and DNA methylation-related genes. Finally, GSEA analysis revealed that RMI2 was engaged in a variety of signaling pathways in pan-cancers. CONCLUSIONS: RMI2 may serve as a potential biological target and probably assume a crucial part in tumorigenesis and progression.

PltDB: a blood platelets-based gene expression database for disease investigation.

MOTIVATION: Molecular profiling of blood-based liquid biopsies is a promising disease detection method, which overcomes the limitations of invasive diagnostic strategies. Recently, gene expression profiling of platelets reportedly provides valuable resource for developing new biomarkers for the detection of diseases, including cancer. However, there is no database containing RNAs in platelets. RESULTS: In this study, we constructed PltDB (http://www.pltdb-hust.com), a blood platelets-based gene expression database featuring integration and visualization of RNA expression profiles based on RNA-seq and microarray data spanning both normal individuals and patients with different diseases. PltDB currently contains the expression landscape of mRNAs, lncRNAs, circRNAs and miRNAs in platelets from patients with different disease types and healthy controls. Moreover, PltDB provides users with the tools for visualizing results of comparison and correlation analysis and for downloading expression profiles and analysis results. A submission interface for the scientific community is also embraced for uploading novel RNA expression profiles derived from platelet samples. PltDB will offer a comprehensive review of the clinical use of platelets, overcome technical problems when analyzing data from diverse studies and serve as a powerful platform for developing new blood biomarkers. AVAILABILITY AND IMPLEMENTATION: PltDB is accessible at http://www.pltdb-hust.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptome Analysis of Solute Carrier-Associated Genes in Hepatocellular Carcinoma: Friend or Foe?

Hepatocellular carcinoma (HCC) is one of the most common types of cancer, and its treatment remains difficult. Since the early symptoms of HCC are not obvious, many HCC patients are already at an advanced stage of the disease at the time of diagnosis. Although current targeted therapy and immunotherapy have been initially effective in HCC patients, several patients have shown low response rates or developed drug resistance, which leads to tumor progression and even death. Hence, there is an urgent need for new biomarkers to guide the prognosis and treatment of HCC. In our study, a prognostic signature consisting of nine SLC genes was constructed in HCC by comprehensive analysis. By calculating risk scores, HCC patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly poorer prognosis. In addition, we found a hub gene, SLC7A11, which is a robust prognostic marker of HCC. In conclusion, our study can serve as a reference for the prognostic evaluation and treatment of HCC.

RNA profiling of blood platelets noninvasively differentiates colorectal cancer from healthy donors and noncancerous intestinal diseases: a retrospective cohort study.

BACKGROUND: The RNA profiles of tumor-educated platelets (TEPs) possess pathological features that could be used for early cancer detection. However, the utility of TEP RNA profiling in detecting early colorectal cancer (CRC) versus noncancerous colorectal diseases has not yet been investigated. This study assesses the diagnostic capacity of TEP RNA profiles in a cohort of patients with CRC and noncancerous diseases. METHODS: Transcriptome sequencing for platelets isolated from 132 patients with CRC at early and late stages and 190 controls consisting of healthy donors and patients with ulcerative disease, Crohn's disease, polyps, and adenomas was performed and analyzed using binary particle swarm optimization coupled with support vector machine to identify genes that contributed to the classification of CRC patients versus controls. The area under the receiver operating curves (AUROCs) and the accuracy of TEP RNA profiles in CRC diagnosis were assessed. RESULTS: TEP RNA profiling achieved high performance in distinguishing and staging CRC patients from the controls. Using the swarm intelligence algorithm, the 921 most contributive genes that classified CRC patients from the controls were identified. AUROCs of 0.928 for the training set via leave-one-out cross-validation and 0.92 for the validation set were achieved, both of which were significantly higher than the clinically utilized serum biomarkers: carcinoembryonic antigen and cancer antigen 19-9. Notably, an AUROC of 0.915 in an external validation set was achieved. For predicting different CRC stages, an AUROC of 0.984 was achieved in the training set and 1.000 in the internal validation set. CONCLUSIONS: RNA profiles of TEPs are of potential diagnostic value for identifying early CRC from noncancerous diseases. Prospective studies are needed to validate its clinical relevance.

The Expression Pattern of Hypoxia-Related Genes Predicts the Prognosis and Mediates Drug Resistance in Colorectal Cancer.

Background: Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. However, due to the heterogeneity of CRC, the clinical therapy outcomes differ among patients. There is a need to identify predictive biomarkers to efficiently facilitate CRC treatment and prognosis. Methods: The expression profiles from Gene Expression Omnibus (GEO) database were used to identify cancer hallmarks associated with CRC outcomes. An accurate gene signature based on the prognosis related cancer hallmarks was further constructed. Results: Hypoxia was identified to be the primary factor that could influence CRC outcomes. Sixteen hypoxia-related genes were selected to construct a risk gene signature (HGS) associated with individuals' prognosis, which was validated in three independent cohorts. Further, stromal and immune cells in tumor microenvironment (TME) were found to be associated with hypoxia. Finally, among the 16 hypoxia-related genes, six genes (DCBLD2, PLEC, S100A11, PLAT, PPAP2B and LAMC2) were identified as the most attributable ones to drug resistance. Conclusion: HGS can accurately predict CRC prognosis. The expression of the drug resistance-related genes is critical in CRC treatment decision-making.

Improving regorafenib's organ target precision via nano-assembly to change its delivery mode abolishes chemoresistance and liver metastasis of colorectal cancer.

Distant metastases and chemotherapy repellency are the key causes of colorectal cancer (CRC)-related mortality. Regorafenib, an oral multi-kinase inhibitor approved for treating advanced CRC with distant metastases and/or chemo-resistance, however only improves median overall survival by 1.4 months. Such limited therapeutic effect is likely due to the low bioavailability of orally administered hydrophobic regorafenib. A regorafenib nanodrug is fabricated by one-step self-assembly with a clinically often-used fluorescent agent (indocyanine green) for overcoming regorafenib's limitations, towards improving regorafenib's therapeutic efficacy in advanced CRC. This nanodrug (nanoRF) was characterized, and its antitumor effects were assessed in three preclinical CRC models. NanoRF converts regorafenib's delivery approach from oral to intravenous with a significantly high encapsulation efficacy of regorafenib (96%) and a long-time colloidal stability. Nanodrug (nanoRF) markedly prolongs regorafenib's blood circulation by halving clearance rate, and enhances regorafenib's tumor accumulation. Across three preclinical CRC models (xenografted tumor, chemodrug-resistant xenografted tumor, and liver metastasis), nanoRF drastically enhances regorafenib's tumor inhibiting efficacy by 0.5-4 folds and effectively extends survival by 0.5-5 folds. This regorafenib nanodrug is a simple, safe, and efficient therapeutic nanodrug for treating advanced CRC with a ready-to-be-clinically-translated potential.