Serum immunoinflammation-related protein complexes discriminate between inflammatory bowel disease and colorectal cancer

Yacon (Smallanthus sonchifolius) Flour Reduces Inflammation and Had No Effects on Oxidative Stress and Endotoxemia in Wistar Rats with Induced Colorectal Carcinogenesis

Colorectal cancer has a high worldwide incidence. The aim of this study was to determine the effect of yacon flour (YF) on oxidative stress, inflammation, and endotoxemia in rats with induced colorectal cancer (CRC). The Wistar male rats were divided and kept for 8 weeks in four groups: S (basal diet, n = 10), Y (YF flour + basal diet, n = 10), C (CRC-induced control + basal diet, n = 12), CY (CRC-induced animals + YF, n = 12). CRC was induced by intraperitoneal injections of 1,2-dimethylhydrazine (25 mg/kg body weight). Groups Y and CY received 7.5% of the prebiotic FOS from YF. The treatment with YF increased fecal secretory immunoglobulin A levels and decreased lipopolysaccharides, tumor necrosis factor alpha and interleukin-12. However, no effect was observed on the oxidative stress by the total antioxidant capacity of plasma, anion superoxide, and nitric oxide analysis of the animals (p < 0.05). The short-chain fatty acids acetate, propionate, and butyrate showed interactions with NF-κB, TLR4, iNOS, and NADPH oxidase by in silico analysis and had a correlation (by the Person analysis) with CRC markers. The yacon flour treatment reduced the inflammation in rats with induced CRC, and could be a promising food to reduce the damages caused by colorectal cancer.

Case Report: Exploration of changes in serum immunoinflammation-related protein complexes of patients with metastatic breast cancer

Patients with advanced breast cancer are difficult to treat and have poor prognosis. At present, the commonly used methods to monitor the disease progression of breast cancer are imaging examinations such as breast ultrasound, mammography and peripheral blood tumor markers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA15-3). However, none of them can detect tumor progression at an early stage. Serum immunoinflammation-related protein complexes (IIRPCs) showed potential to indicate cancer progression. Therefore, we attempted to monitor the level of IIRPCs in peripheral blood of patients with metastatic breast cancer and compare it with patients' treatment and disease progression, and here we performed case reports of two of them.

Serum disease-specific IgG Fc glycosylation as potential biomarkers for nonproliferative diabetic retinopathy using mass spectrometry

OBJECTIVE

To explore the potential of serum disease-specific immunoglobulin G (DSIgG) glycosylation as a biomarker for the diagnosis of nonproliferative diabetic retinopathy (NPDR).

METHODS

A total of 387 consecutive diabetic patients presenting in an eye clinic without proliferative diabetic retinopathy (DR) were included and divided into those with nondiabetic retinopathy (NDR) (n = 181) and NPDR (n = 206) groups. Serum was collected from all patients for DSIgG separation. The enriched glycopeptides of the tryptic digests of DSIgG were detected using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Patients were randomly divided into discovery and validation sets (1:1). The differences in glycopeptide ratios between the groups were compared by using Student's t-test or the Mann-Whitney U test. The predictive ability of the model was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

DSIgG1 G1FN/G0FN, G2N/G2, G2FN/G2N and DSIgG2 G1F/G0F, G1FN/G0FN, G2N/G1N, G2S/G2 were significantly different between NDR and NPDR patients (p < 0.05) in both the discovery and validation sets. The prediction model that was built comprising the seven glycopeptide ratios showed good NPDR prediction performance with an AUC of 0.85 in the discovery set and 0.87 in the validation set.

CONCLUSION

DSIgG Fc N-glycosylation ratios were associated with NPDR and can be used as potential biomarkers for the early diagnosis of DR.

Construction and Validation of a Protein-associated Prognostic Model for Gastrointestinal Cancer

Background Gastrointestinal cancer (GIC) is a prevalent and lethal malignant tumor. It is obligatory to investigate innovative biomarkers for the diagnosis and prognosis. Proteins play a crucial role in regulating the occurrence and progression of GIC. However, the prognostic value of proteins is unclear in GIC.

OBJECTIVE

This paper aims to identify the hub prognosis-related proteins (PAPs) and construct a prognosis model for GIC patients for clinical application.

METHODS

Protein expression data of GIC was obtained from The Cancer Proteome Atlas (TCPA) and downloaded the clinicopathological data from The Cancer Genome Atlas database (TCGA). Besides, hub proteins were filtrated via univariate and multivariate Cox regression analysis. Moreover, survival analysis and nomogram were used to predict overall survival (OS). We used the calibration curves to assess the consistency of predictive and actual survival rates. The consistency index (C-index) was used to evaluate the prognostic ability of the predictive model. Furthermore, functional enrichment analysis and protein co-expression of PAPs were used to explore their roles in GIC.

RESULTS

Finally, a prognosis model was conducted based on ten PAPs (CYCLIND1, DVL3, NCADHERIN, SYK, ANNEXIN VII, CD20, CMET, RB, TFRC, and PREX1). The risk score calculated by the model was an independent prognostic predictor. Compared with the high-risk subgroup, the low-risk subgroup had better OS. In the TCGA cohort, the area under the curve value of the receiver operating characteristic curve of the prognostic model was 0.692. The expression of proteins and risk score had a significant association with the clinicopathological characteristics of GIC. Besides, a nomogram based on GIC clinicopathological features and risk scores could properly predict the OS of individual GIC patients. The C-index is 0.71 in the TCGA cohort and 0.73 in the GEO cohort.

CONCLUSION

The results indicate that the risk score is an independent prognostic biomarker and is related to the malignant clinical features of GIC patients. Besides, several PAPs associated with the survival and clinicopathological characteristics of GIC might be potential biomarkers for GIC diagnosis and treatment.

Serum immunoinflammatory-related protein complexes as personalized biomarkers for monitoring disease progression and response to treatment in lung cancer patients

BACKGROUND

Although routine surveillance to detect lung cancer recurrence with clinical imaging is recommended, early detection of disease progression has a major role in avoiding over-treatment.

METHODS

Here, serum immunoinflammatory-related protein complexes (IIRPCs) of a series of 1331 serum samples collected from 119 patients during the follow-up period were isolated using native-PAGE and then their levels were quantified. The associations of representative IIRPCs levels at their beginning, maximum, and minimum and the ratios of the maximum or minimum to the beginning IIRPCs levels with clinical characteristics were statistically analyzed.

RESULTS

The statistical results indicate that patients with these ratios below the first quantiles of the minimum ratios had shorter progressive-free survival (PFS) and the follow-up time points for 108 of 113 patients with over 1.5-fold change in IIRPCs level relative to the beginning level as the beginning time point of humoral immune response has a median lead time of 61.9 weeks (IQR, 30.9-105.3) relative to progressive disease(PD) detected using clinical imaging.

CONCLUSIONS

These findings suggest that changes in IIRPCs levels may be early-warning signals of disease progression and response to treatment for lung cancer patients.

Clinical Management of Gastrointestinal Disease in the Common Marmoset (Callithrix jacchus)

Gastrointestinal disease is a frequently encountered problem among captive common marmoset (Callithrix jacchus) colonies. Management can be challenging due to the number of etiologies responsible for gastrointestinal disease in this species, limitations on diagnostic capabilities, and lack of effective treatments. Understanding commonly described GI diseases in the captive marmoset can provide insight on the impact these diseases have on research studies and aid in the development of appropriate management strategies. A review of commonly encountered GI disease processes as well as routinely implicated causes of GI disease in the common marmoset are provided. Current strategies in clinical management of GI disease in the common marmoset, including approaches to colony health, diagnostic testing, and commonly employed treatments are discussed.

The long non-coding RNA TSLC8 inhibits colorectal cancer by stabilizing puma

The colorectal cancer (CRC) dictates a common malignancy with high recurrence rate. Long non-coding RNAs (lncRNAs) belong to a class of regulatory factors involved in multiple cancers. In current work, we have uncovered a novel lncRNA named TSLC8. TSLC8 was dramatically downregulated in CRC samples and cell lines. Reintroduction of TSLC8 inhibited tumor sphere formation and viability in CRC cells. In vivo experiments further confirmed the tumor suppressive function of TSLC8. Ectopic TSLC8 expression elevates puma abundance whereas this effect is mediated by TSLC8-puma binding and stabilization. FOXO1 can transcriptionally induce TSLC8 expression. Epigenetic investigation suggested that TSLC8 locus was hypermethylated in CRC leading to diminished TSLC8 expression. Our current work has identified a novel tumor suppressive function of TSLC8, whose reduced expression may facilitate malignant phenotypes during CRC progression.

Identification of prognosis-associated immune genes and exploration of immune cell infiltration in colorectal cancer

Aim: To identify prognosis-related immune genes (PRIGs) and construct a prognosis model of colorectal cancer (CRC) patients for clinical use. Materials & methods: Expression profiles were obtained from The Cancer Genome Atlas database and identified differentially expressed PRIGs of CRC. Results: A prognostic model was conducted based on nine PRIGs. The risk score, based on prognosis model, was an independent prognostic predictor. Five PRIGs and risk score were significantly associated with the clinical stage of CRC and five immune cells related to the risk score. Conclusion: The risk score was an independent prognostic biomarker for CRC patients. The research excavated immune genes that were associated with survival and that could be potential biomarkers for prognosis and treatment for CRC patients.

Prognostic implications of metabolism-associated gene signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most common and deadly malignancies. Novel biomarkers for the diagnosis and prognosis of this disease must be identified. Besides, metabolism plays an essential role in the occurrence and development of CRC. This article aims to identify some critical prognosis-related metabolic genes (PRMGs) and construct a prognosis model of CRC patients for clinical use. We obtained the expression profiles of CRC from The Cancer Genome Atlas database (TCGA), then identified differentially expressed PRMGs by R and Perl software. Hub genes were filtered out by univariate Cox analysis and least absolute shrinkage and selection operator Cox analysis. We used functional enrichment analysis methods, such as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, to identify involved signaling pathways of PRMGs. The nomogram predicted overall survival (OS). Calibration traces were used to evaluate the consistency between the actual and the predicted survival rate. Finally, a prognostic model was constructed based on six metabolic genes (NAT2, XDH, GPX3, AKR1C4, SPHK1, and ADCY5), and the risk score was an independent prognostic prognosticator. Genetic expression and risk score were significantly correlated with clinicopathologic characteristics of CRC. A nomogram based on the clinicopathological feature of CRC and risk score accurately predicted the OS of individual CRC cancer patients. We also validated the results in the independent colorectal cancer cohorts GSE39582 and GSE87211. Our study demonstrates that the risk score is an independent prognostic biomarker and is closely correlated with the malignant clinicopathological characteristics of CRC patients. We also determined some metabolic genes associated with the survival and clinical stage of CRC as potential biomarkers for CRC diagnosis and treatment.