Proteomic characterization of esophageal squamous cell carcinoma response to immunotherapy reveals potential therapeutic strategy and predictive biomarkers.

Immunotherapy is the first-line therapy for esophageal squamous cell carcinoma (ESCC), yet many patients do not respond due to drug resistance and the lack of reliable predictive markers. We collected 73 ESCC patients (including discovery cohort and validation cohort) without immune thrombocytopenia and undergoing anti-PD1 immunotherapy. Proteomic and phosphoproteomic analysis of 73 ESCC treatment-naive samples by mass spectrometry-based label-free quantification were applied to explore the potential resistant and sensitive mechanisms, and identify predictive markers of ESCC immunotherapy. Comparative analysis found the pathways related to immune and mitochondrial functions were associated with ESCC immunotherapy sensitivity; while platelet activation bioprocess showed negative correlation with CD8+ T cells and related to ESCC immunotherapy non-sensitivity. Finally, we identified 10 ESCC immunotherapy predictive biomarkers with high accuracy (≥ 0.90) to predict the immunotherapeutic response, which was validated in the independent cohort.

Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer.

Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma.

Soft tissue sarcoma is a broad family of mesenchymal malignancies exhibiting remarkable histological diversity. We portray the proteomic landscape of 272 soft tissue sarcomas representing 12 major subtypes. Hierarchical classification finds the similarity of proteomic features between angiosarcoma and epithelial sarcoma, and elevated expression of SHC1 in AS and ES is correlated with poor prognosis. Moreover, proteomic clustering classifies patients of soft tissue sarcoma into 3 proteomic clusters with diverse driven pathways and clinical outcomes. In the proteomic cluster featured with the high cell proliferation rate, APEX1 and NPM1 are found to promote cell proliferation and drive the progression of cancer cells. The classification based on immune signatures defines three immune subtypes with distinctive tumor microenvironments. Further analysis illustrates the potential association between immune evasion markers (PD-L1 and CD80) and tumor metastasis in soft tissue sarcoma. Overall, this analysis uncovers sarcoma-type-specific changes in proteins, providing insights about relationships of soft tissue sarcoma.

Proteomic Characterization Identifies Clinically Relevant Subgroups of Gastrointestinal Stromal Tumors.

BACKGROUND & AIMS: Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the gastrointestinal tract, and it has high metastatic and recurrence rates. We aimed to characterize the proteomic features of GIST to understand biological processes and treatment vulnerabilities. METHODS: Quantitative proteomics and phosphoproteomics analyses were performed on 193 patients with GIST to reveal the biological characteristics of GIST. Data-driven hypotheses were tested by performing functional experiments using both GIST cell lines and xenograft mouse models. RESULTS: Proteomic analysis revealed differences in the molecular features of GISTs from different locations or with different histological grades. MAPK7 was identified and functionally proved to be associated with tumor cell proliferation in GIST. Integrative analysis revealed that increased SQSTM1 expression inhibited the patient response to imatinib mesylate. Proteomics subtyping identified 4 clusters of tumors with different clinical and molecular attributes. Functional experiments confirmed the role of SRSF3 in promoting tumor cell proliferation and leading to poor prognosis. CONCLUSIONS: Our study provides a valuable data resource and highlights potential therapeutic approaches for GIST.

Timing of Cognitive Test Score Decline Prior to Incident Dementia Diagnosis in Blacks and Whites: The Atherosclerosis Risk in Communities Neurocognitive Study.

INTRODUCTION: Commonly occurring dementias include those of Alzheimer's, vascular, and mixtures of these and other pathologies. They are believed to evolve over many years, but that time interval has been difficult to establish. Our objective was to determine how many years in advance of a dementia diagnosis cognitive scores begin to change. METHODS: 14,086 dementia-free ARIC participants underwent a cognitive exam at baseline visit 2 (1990-1992, mean age 57 ± 5.72), and 11,244 at visit 4 (1996-1998), 5,640 at visit 5 (2011-2013), and 3,574 at visit 6 (2016-2017) with surveillance for dementias of all-causes combined. Within 5-year intervals after each visit, we compared performance on the Delayed Word Recall Test (DWRT), the Digit Symbol Substitution Test (DSST), the Word Fluency Test (WFT), and the combined mean of three cognitive tests at baseline in participants who were diagnosed with dementia within each interval versus those who survived the interval without a dementia diagnosis. Z-scores were adjusted for demographics and education in separate regression models for each visit. We plotted adjusted z-score means by time interval following each visit. RESULTS: During follow-up 3,334, 2,821, 1,218, and 329 dementia cases were ascertained after visits 2, 4, 5, and 6, respectively. Adjusted DWRT z-scores were significantly lower 20-25 years before dementia than those who did not experience dementia within 25 years. DSST z-scores were significantly lower at 25-30 years and 3-test combination z-scores were significantly lower as early as 30-31 years before onset. The difference between dementia and non-dementia group in the visit 2 3-test combination z-score was -0.20 at 30-31 years prior to dementia diagnosis. As expected, differences between the dementia and non-dementia groups increased closer to the time of dementia occurrence, up to their widest point at 0-5 years prior to dementia diagnosis. The difference between dementia and non-dementia groups in the visit 2 3-test combination z-score at 0-5 years was -0.90. WFT z-score differences were smaller than for the DSST or DWRT and began later. Patterns were similar in Black and White participants. CONCLUSION: DWRT, DSST, and combined 3-test z-scores were significantly lower more than 20 years prior to diagnosis in the dementia group versus the non-dementia group. Findings contribute to our knowledge of the long prodromal period in Blacks and Whites.

Proteomic characterization of the colorectal cancer response to chemoradiation and targeted therapies reveals potential therapeutic strategies.

Chemoradiation and targeted therapies are the major treatments for colorectal cancer (CRC); however, molecular properties associated with therapy resistance are incompletely characterized. Here, we profile the proteome of 254 tumor tissues from patients with CRC undergoing chemotherapy, chemoradiation, or chemotherapy combined with targeted therapy. Proteome-based classification reveals four subtypes featured with distinct biological and therapeutic characteristics. The integrative analysis of CRC cell lines and clinical samples indicates that immune regulation is significantly associated with drug sensitivity. HSF1 can increase DNA damage repair and cell cycle, thus inducing resistance to radiation, while high expression of HDAC6 is negatively associated with response of cetuximab. Furthermore, we develop prognostic models with high accuracy to predict the therapeutic response, further validated by parallel reaction monitoring (PRM) assay in an independent validation cohort. This study provides a rich resource for investigating the mechanisms and indicators of chemoradiation and targeted therapy in CRC.

Proteolytic cleavage of amyloid precursor protein by ADAM10 promotes proliferation and migration via activating MAPKs pathway in tongue squamous cell carcinoma in vitro.

APP, well-studied in the development of Alzheimer's disease, has been recently identified as the key gene correlated with TSCC. Here, we investigate the function of APP and its proteolytic cleavage by ADAM10 in the pathogenesis of TSCC. A total of 63 TSCC patients and 30 healthy controls were included and the results of IHC assay showed high expressions of ADAM10 and APP in TSCC tissues compared to paired para-carcinoma tissues. Interestingly, APP expression in TSCC patients was correlated with ADAM10 expression and their combined expression was related to the poor patients' survival. We found that APP was ɑ-cleaved in TSCC cells to form sAPPα, and the serum level of sAPPα but not sAPPß in TSCC patients was higher than healthy controls. Both overexpression with full-length APP and sAPPα promoted TSCC cell proliferation, migration and invasion. Downregulation of APP or ADAM10 by siRNA decreased the generation of sAPPα and inhibited the activity of ERK1/2 and p38 pathways, thereby reducing TSCC cell proliferation, migration and invasion. Treatment with ERK1/2 or p38 agonist or sAPPα overexpression reversed the effects of APP or ADAM10 knockdown. In conclusion, our data demonstrated the pathogenic roles of APP cleaved by ADAM10 to activate ERK1/2 and p38 pathways in TSCC cells. Both high expressions of ADAM10 and APP were related to poor prognosis. Targeting APP cleaved by ADAM10 might be a potential strategy in TSCC treatment.

Proteogenomics of different urothelial bladder cancer stages reveals distinct molecular features for papillary cancer and carcinoma in situ.

The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

BACKGROUND: Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. RESULTS: Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics. CONCLUSION: Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Plasma proteomic profiling discovers molecular features associated with upper tract urothelial carcinoma.

Upper tract urothelial carcinoma (UTUC) is often diagnosed late and exhibits poor prognosis. Limited data are available on potential non-invasive biomarkers for disease monitoring. Here, we investigate the proteomic profile of plasma in 362 UTUC patients and 239 healthy controls. We present an integrated tissue-plasma proteomic approach to infer the signature proteins for identifying patients with muscle-invasive UTUC. We discover a protein panel that reflects lymph node metastasis, which is of interest in identifying UTUC patients with high risk and poor prognosis. We also identify a ten-protein classifier and establish a progression clock predicting progression-free survival of UTUC patients. Finally, we further validate the signature proteins by parallel reaction monitoring assay in an independent cohort. Collectively, this study portrays the plasma proteomic landscape of a UTUC cohort and provides a valuable resource for further biological and diagnostic research in UTUC.

Integrated analysis based on vesicle trafficking-related genes identifying CNIH4 as a novel therapeutic target for glioma.

BACKGROUND: Vesicle trafficking is a highly important process in numerous human diseases, especially in the central nervous system dysfunctions. However, as a key component of vesicle trafficking-related genes (VRGs), Cornichon family AMPA receptor auxiliary protein 4 (CNIH4) has not been systematically elucidated in glioma so far. METHODS: Differentially expressed VRGs were selected using molecular signatures database (MSigDB), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) mRNA expression profiles. Further exploration of CNIH4 was determined using LASSO-Cox regression algorithms. Then Kaplan-Meier (K-M) plotter, receiver operating characteristic (ROC) curves, and multivariate Cox regression analyses were utilized to assess the independent significance of CNIH4 in the CGGA validation cohort. Functional exploration was performed with Gene Set Enrichment Analysis (GSEA) and then verified using a series of functional experiments in glioma cells. Finally, the consensus clustering algorithm was applied to identify clusters in glioma samples. After that, differences in prognosis, the tumor immune microenvironment (TIME), and therapy response were evaluated between clusters. RESULTS: CNIH4 was shown to be overexpressed in malignant glioma variants and was frequently observed in GCSs and TMZ-resistant cell lines. Higher CNIH4 levels were significantly related to poor outcomes and positively correlated with adverse clinicopathological characteristics. Survival analyses revealed CNIH4 as an independent risk factor that outperformed traditional measures. Enrichment analysis indicated that overactive CNIH4 significantly gathered in stem cell processes. Furthermore, functional assays of silencing CNIH4 expression suppressed stem cell-like properties in vitro and inhibited tumorigenicity in vivo. Finally, the CNIH4-enriched subgroup negatively modulated immunotherapeutic response and reflected lower chemotherapy sensitivity for glioma patients. CONCLUSION: Our study identified CNIH4 as a potential VRG that regulates tumor stemness, microenvironment immunity, and chemotherapy sensitivity. It may serve as a novel prognostic factor and a promising target against glioma therapy.

Photodynamic therapy enhances the cytotoxicity of temozolomide against glioblastoma via reprogramming anaerobic glycolysis.

The successful application of photodynamic therapy in the treatment of glioma (CNS WHO grade 4) depends in large part to the effect of killing cells in the infiltrating area after tumor had been removed, when combined with radiotherapy, chemotherapy, and targeted drug therapy. The purpose of this study was to investigate the potential mechanism of TMZ's involvement in the glioma's glycolytic metabolic pathway during photodynamic therapy. The low dose of photodynamic therapy treatment on the cell viability of gliomas was investigated by CCK8. Alterations in reactive oxygen species were detected by flow cytometer. The differentially expressed proteins related to glucose transporter 1 (GLUT-1), matrix metalloproteinase-2 (MMP-2)/actively MMP-2 and apoptosis-associated caspase-3/cleaved caspase-3 were evaluated by Western Blot experiment. Additionally, transmission electron microscopy observed apoptosis, necrosis and the changes of the ultrastructure in U251 cells. In addition, antitumor effects in vivo were tested using orthotopic BALB/c mice with the glioma U87 model. The findings showed that low dose PDT affected mitochondrial function by inducing radical oxygen, hindered cellular glucose transport and metabolism, and induced apoptosis. The results also showed that cell viability considerably decreased and increased cell apoptosis under the PDT therapy. The HIF-1/GLUT-1 axis enhanced the cytotoxicity of temozolomide in gliomas as a result of PDT treatment, which was influenced by ROS. As a result, this study presents PDT as a potential therapeutic approach for treating malignant glioma, and enhanced antitumor effect of TMZ by inhibiting glycolytic pathway.

Multilevel proteomic analyses reveal molecular diversity between diffuse-type and intestinal-type gastric cancer.

Diffuse-type gastric cancer (DGC) and intestinal-type gastric cancer (IGC) are the major histological types of gastric cancer (GC). The molecular mechanism underlying DGC and IGC differences are poorly understood. In this research, we carry out multilevel proteomic analyses, including proteome, phospho-proteome, and transcription factor (TF) activity profiles, of 196 cases covering DGC and IGC in Chinese patients. Integrative proteogenomic analysis reveals ARIDIA mutation associated with opposite prognostic effects between DGC and IGC, via diverse influences on their corresponding proteomes. Systematical comparison and consensus clustering analysis identify three subtypes of DGC and IGC, respectively, based on distinct patterns of the cell cycle, extracellular matrix organization, and immune response-related proteins expression. TF activity-based subtypes demonstrate that the disease progressions of DGC and IGC were regulated by SWI/SNF and NFKB complexes. Furthermore, inferred immune cell infiltration and immune clustering show Th1/Th2 ratio is an indicator for immunotherapeutic effectiveness, which is validated in an independent GC anti-PD1 therapeutic patient group. Our multilevel proteomic analyses enable a more comprehensive understanding of GC and can further advance the precision medicine.

Region-resolved multi-omics of the mouse eye.

The eye is a complex organ consisting of multiple compartments with unique and specialized properties, and small disturbances in one eye region can result in impaired vision and blindness. Although there have been advancements in ocular research, the hierarchical molecular network in region-wide resolution, indicating the division of labor and crosstalk among different eye regions, is not yet comprehensively illuminated. Here, we present an atlas of region-resolved proteome and lipidome of mouse eye. Multiphoton microscopy-guided laser microdissection combined with in-depth label-free proteomics identifies 13,536 proteins across various mouse eye regions. Further integrative analysis of spectral imaging, label-free proteome, and imaging mass spectrometry of the lipidome and phosphoproteome reveals distinctive molecular features, including proteins and lipids of various anatomical mouse eye regions. These deposited datasets and our open proteome server integrating all information provide a valuable resource for future functional and mechanistic studies of mouse eye and ocular disease.

Proteogenomics of diffuse gliomas reveal molecular subtypes associated with specific therapeutic targets and immune-evasion mechanisms.

Diffuse gliomas are devastating brain tumors. Here, we perform a proteogenomic profiling of 213 retrospectively collected glioma tumors. Proteogenomic analysis reveals the downstream biological events leading by EGFR-, IDH1-, TP53-mutations. The comparative analysis illustrates the distinctive features of GBMs and LGGs, indicating CDK2 inhibitor might serve as a promising drug target for GBMs. Further proteogenomic integrative analysis combined with functional experiments highlight the cis-effect of EGFR alterations might lead to glioma tumor cell proliferation through ERK5 medicates nucleotide synthesis process. Proteome-based stratification of gliomas defines 3 proteomic subgroups (S-Ne, S-Pf, S-Im), which could serve as a complement to WHO subtypes, and would provide the essential framework for the utilization of specific targeted therapies for particular glioma subtypes. Immune clustering identifies three immune subtypes with distinctive immune cell types. Further analysis reveals higher EGFR alteration frequencies accounts for elevation of immune check point protein: PD-L1 and CD70 in T-cell infiltrated tumors.

Proteogenomic characterization of cholangiocarcinoma.

BACKGROUND AND AIMS: Cholangiocarcinoma (CCA) is a highly heterogeneous cancer with limited understanding and few effective therapeutic approaches. We aimed at providing a proteogenomic CCA characterization to inform biological processes and treatment vulnerabilities. APPROACH AND RESULTS: Integrative genomic analysis with functional validation uncovered biological perturbations downstream of driver events including DPCR1 , RBM47 mutations, SH3BGRL2 copy number alterations, and FGFR2 fusions in CCA. Proteomic clustering identified three subtypes with distinct clinical outcomes, molecular features, and potential therapeutics. Phosphoproteomics characterized targetable kinases in CCA, suggesting strategies for effective treatment with CDK and MAPK inhibitors. Patients with CCA with HBV infection showed increased antigen processing and presentation (APC) and T cell infiltration, conferring a favorable prognosis compared with those without HBV infection. The characterization of extrahepatic CCA recommended the feasible application of vascular endothelial-derived growth factor inhibitors. Multiomics profiling presented distinctive molecular characteristics of the large bile duct and the small bile duct of intrahepatic CCA. The immune landscape further revealed diverse tumor immune microenvironments, suggesting immune subtypes C1 and C5 might benefit from immune checkpoint therapy. TCN1 was identified as a potential CCA prognostic biomarker, promoting cell growth by enhancing vitamin B12 metabolism. CONCLUSIONS: We characterized the proteogenomic landscape of 217 CCAs with 197 paired normal adjacent tissues and identified their subtypes and potential therapeutic targets. The multiomics analyses with other databases and some functional validations have indicated strategies regarding the clinical, biological, and therapeutic approaches to the management of CCA.

Integrated proteomic and transcriptomic landscape of macrophages in mouse tissues.

Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server ( http://macrophage.mouseprotein.cn ) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.

Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor prognosis. Proteogenomic characterization and integrative proteomic analysis provide a functional context to annotate genomic abnormalities with prognostic value. METHODS: We performed an integrated multi-omics analysis, including whole-exome sequencing, RNA-seq, proteomic, and phosphoproteomic analysis of 217 PDAC tumors with paired non-tumor adjacent tissues. In vivo functional experiments were performed to further illustrate the biological events related to PDAC tumorigenesis and progression. RESULTS: A comprehensive proteogenomic landscape revealed that TP53 mutations upregulated the CDK4-mediated cell proliferation process and led to poor prognosis in younger patients. Integrative multi-omics analysis illustrated the proteomic and phosphoproteomic alteration led by genomic alterations such as KRAS mutations and ADAM9 amplification of PDAC tumorigenesis. Proteogenomic analysis combined with in vivo experiments revealed that the higher amplification frequency of ADAM9 (8p11.22) could drive PDAC metastasis, though downregulating adhesion junction and upregulating WNT signaling pathway. Proteome-based stratification of PDAC revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Immune clustering defined a metabolic tumor subset that harbored FH amplicons led to better prognosis. Functional experiments revealed the role of FH in altering tumor glycolysis and in impacting PDAC tumor microenvironments. Experiments utilizing both in vivo and in vitro assay proved that loss of HOGA1 promoted the tumor growth via activating LARP7-CDK1 pathway. CONCLUSIONS: This proteogenomic dataset provided a valuable resource for researchers and clinicians seeking for better understanding and treatment of PDAC.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis.

Background: Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management. Methods: Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened. Results: Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM. Conclusions: Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

Biomarkers of coordinate metabolic reprogramming and the construction of a co-expression network in colorectal cancer.

Background: Globally, the incidence and mortality of colorectal cancer (CRC) rank amongst the highest of all malignancies. Thus, research aimed at developing new screening strategies and biomarkers for the early detection of CRC is needed. At present, conventional screening methods have limitations; therefore, new testing strategies have been considered. Using metabolomics to explore the molecular changes in CRC tissue is a mainstream method for identifying potential biomarkers and key cancer factors. Methods: In the present study, 27 samples from nine CRC patients were used to analyze the metabolite differences between the tumor, paracancerous, and normal tissues. The metabolite differences in the various stages of CRC (stages IIA, IIB, and IIIC) were analyzed as well. Subsequently, principal component analysis (PCA), permutation, and trend analyses were performed. Weighted gene co-expression and metabolite-metabolite interaction networks were also constructed. Results: A total of 5,834 metabolites were identified among the included samples. Permutation analysis showed a clear separation between the different tissues and different stages. Compared with normal tissues, tumor tissues exhibited 11, 233, and 25 up-regulated metabolites as well as one, 77, and zero down-regulated metabolites in stages IIA, IIB, and IIIC, respectively. Moreover, tumor tissues in stage IIB exhibited more differential metabolites (233 up-regulated and 77 down-regulated). Weighted Gene Correlation Network Analysis (WGCNA) clustered the 5,834 metabolites into 15 different modules, of which four modules were significantly correlated with tissue specificity. Notably, glycerophospholipid metabolism, fatty acid metabolism, and other pathways were enriched in these modules. Conclusions: Fatty acids and glycerophospholipids were significantly related to the development of CRC. This result is of great significance for future targeted screening of CRC biomarkers and further clarifying the nutrient metabolism of cancer cells.