Serum S100A6, S100A8, S100A9 and S100A11 proteins in colorectal neoplasia: results of a single centre prospective study

Screening colorectal cancer associated autoantigens through multi-omics analysis and diagnostic performance evaluation of corresponding autoantibodies

BACKGROUND

This study aims to screen, validate novel biomarkers and develop a user-friendly online tool for the detection of colorectal cancer (CRC).

METHODS

Multi-omics approach, comprising proteomic analysis and single-cell transcriptomic analysis, was utilized to discover candidate tumor-associated antigens (TAAs). The presence of tumor-associated autoantibodies (TAAbs) in serum was subsequently assessed using enzyme-linked immunosorbent assays (ELISA) in 300 CRC patients and 300 healthy controls. Ten machine learning algorithms were utilized to develop diagnostic models, with the optimal one selected and integrated into an R Shiny-based GUI to enhance usability and accessibility.

RESULTS

We identified twelve potential TAAs: HMGA1, NPM1, EIF1AX, CKS1B, HSP90AB1, ACTG1, S100A11, maspin, ANXA3, eEF2, P4HB, and HKDC1. ELISA results showed that five TAAbs including anti-CKS1B, anti-S100A11, anti-maspin, anti-ANXA3, and anti-eEF2 were potential diagnostic biomarkers during the diagnostic evaluation phase (all P < 0.05). The Random Forest model yielded an AUC of 0.82 (95% CI: 0.78-0.88) on the training set and 0.75 (95% CI: 0.68-0.82) on the test set, demonstrating the robustness of the results. Web-based implementations of CRC diagnostic tools are publicly accessible via weblink https://qzan.shinyapps.io/CRCPred/ .

CONCLUSIONS

A five biomarker panel can server as complementary biomarker to CEA and CA19-9 in CRC detection.

Multiparameter diagnostic model using S100A9, CCL5 and blood biomarkers for nasopharyngeal carcinoma

This study aimed to analyze S100A9 and CCL5 levels in patients with nasopharyngeal carcinoma (NPC) and evaluate their predictive value as blood-based indicators for NPC diagnosis. Serum S100A9 and CCL5 levels were measured in 123 patients newly diagnosed with NPC and 107 patients without NPC. Additionally, 38 patients (19 with NPC and 19 without) were recruited from Xiangya Hospital as an external validation cohort. Logistic regression was used to identify risk factors for NPC. Variable selection was conducted using least absolute shrinkage and selection operator (LASSO) regression. NPC prediction models were developed using four machine-learning algorithms, and their performance was evaluated with ROC curves. Calibration curves, decision curve analysis (DCA), and Shapley additive explanation plots were employed for further evaluation and interpretation. Serum S100A9 and CCL5 levels were significantly elevated in patients with NPC compared with patients without NPC. Multivariate logistic regression identified S100A9, CCL5, TP, and ALB as independent predictors of NPC. ROC analysis demonstrated that S100A9 had superior diagnostic performance compared to CCL5 and other blood indicators, effectively differentiating NPC from non-NPC cases. A machine-learning-based logistic regression model incorporating S100A9, CCL5, ALB, GLB, and PLR demonstrated a reliable diagnostic value for NPC, achieving an Area under the curve (AUC) of 0.877 in the training cohort. The calibration curve showed excellent agreement between predicted and actual probabilities; in contrast, the DCA curve highlighted strong clinical utility. The model also performed well in the external validation cohort, with an AUC of 0.817. Serum levels of S100A9, CCL5, and other indicators such as GLB, ALB, and PLR have diagnostic values for NPC. The logistic regression model based on these biomarkers demonstrated robust predictive performance and clinical utility for NPC diagnosis.

Where do we stand with screening for colorectal cancer and advanced adenoma based on serum protein biomarkers? A systematic review

Colorectal cancer (CRC) screening has been proven to reduce both mortality and the incidence of this disease. Most CRC screening programs are based on fecal immunochemical tests (FITs), which have a low participation rate. Searching for blood protein biomarkers can lead to the development of a more accepted screening test. The aim of this systematic review was to compare the diagnostic potential of the most promising serum protein biomarkers. A systematic review based on PRISMA guidelines was conducted in the PubMed and Web of Science databases between January 2010 and December 2023. Studies assessing blood protein biomarkers for CRC screening were included. The sensitivity, specificity, and area under the ROC curve of each biomarker were collected. Among 4685 screened studies, 94 were considered for analysis. Most of them were case-control studies, leading to an overestimation of the performance of candidate biomarkers. The performance of no protein biomarker or combination of biomarkers appears to match that of the FIT. Studies with a suitable design and population, testing new assay techniques, or based on algorithms combining FIT with serum tests are needed.

The Role of S100A6 in Human Diseases: Molecular Mechanisms and Therapeutic Potential

S100A6, also known as calcyclin, is a low-molecular-weight Ca2+-binding protein from the S100 family that contains two EF-hands. S100A6 is expressed in a variety of mammalian cells and tissues. It is also expressed in lung, colorectal, pancreatic, and liver cancers, as well as other cancers such as melanoma. S100A6 has many molecular functions related to cell proliferation, the cell cycle, cell differentiation, and the cytoskeleton. It is not only involved in tumor invasion, proliferation, and migration, but also the pathogenesis of other non-neoplastic diseases. In this review, we focus on the molecular mechanisms and potential therapeutic targets of S100A6 in tumors, nervous system diseases, leukemia, endometriosis, cardiovascular disease, osteoarthritis, and other related diseases.

S100A8 and S100A9 in Cancer

S100A8 and S100A9 are Ca²⁺ binding proteins that belong to the S100 family. Primarily expressed in neutrophils and monocytes, S100A8 and S100A9 play critical roles in modulating various inflammatory responses and inflammation-associated diseases. Forming a common heterodimer structure S100A8/A9, S100A8 and S100A9 are widely reported to participate in multiple signaling pathways in tumor cells. Meanwhile, S100A8/A9, S100A8, and S100A9, mainly as promoters, contribute to tumor development, growth and metastasis by interfering with tumor metabolism and the microenvironment. In recent years, the potential of S100A8/A9, S100A9, and S100A8 as tumor diagnostic or prognostic biomarkers has also been demonstrated. In addition, an increasing number of potential therapies targeting S100A8/A9 and related signaling pathways have emerged. In this review, we will first expound on the characteristics of S100A8/A9, S100A9, and S100A8 in-depth, focus on their interactions with tumor cells and microenvironments, and then discuss their clinical applications as biomarkers and therapeutic targets. We also highlight current limitations and look into the future of S100A8/A9 targeted anti-cancer therapy.

Proteomic Characterization of Colorectal Cancer Tissue from Patients Identifies Novel Putative Protein Biomarkers

Colorectal cancer (CRC) is one of the leading causes of cancer-related death over the world. There is a great need for biomarkers capable of early detection and as targets for treatment. Differential protein expression was investigated with two-dimensional gel electrophoresis (2D-PAGE) followed by identification with liquid chromatography–tandem mass spectrometry (LC-MS/MS) in CRC patient tissue from (i) the peripheral part of the tumor, (ii) the central part of the tumor as well as from (iii) a non-involved part of the colorectal tissue. The expression patterns of six identified proteins were further evaluated by one-dimensional Western blot (1D-WB) analysis of the CRC tissue. Proteins that were perturbed in expression level in the peripheral or in the central part of the tumor as compared with the non-involved part included S100A11, HNRNPF, HNRNPH1 or HNRNPH2, GSTP1, PKM and FABP1. These identified markers may have future diagnostic potential or may be novel treatment targets after further evaluation in larger patient cohorts.

Optimization of Blood Handling and Peripheral Blood Mononuclear Cell Cryopreservation of Low Cell Number Samples

Background: Rural/remote blood collection can cause delays in processing, reducing PBMC number, viability, cell composition and function. To mitigate these impacts, blood was stored at 4 °C prior to processing. Viable cell number, viability, immune phenotype, and Interferon-γ (IFN-γ) release were measured. Furthermore, the lowest protective volume of cryopreservation media and cell concentration was investigated. Methods: Blood from 10 individuals was stored for up to 10 days. Flow cytometry and IFN-γ ELISPOT were used to measure immune phenotype and function on thawed PBMC. Additionally, PBMC were cryopreserved in volumes ranging from 500 µL to 25 µL and concentration from 10 × 10⁶ cells/mL to 1.67 × 10⁶ cells/mL. Results: PBMC viability and viable cell number significantly reduced over time compared with samples processed immediately, except when stored for 24 h at RT. Monocytes and NK cells significantly reduced over time regardless of storage temperature. Samples with >24 h of RT storage had an increased proportion in Low-Density Neutrophils and T cells compared with samples stored at 4 °C. IFN-γ release was reduced after 24 h of storage, however not in samples stored at 4 °C for >24 h. The lowest protective volume identified was 150 µL with the lowest density of 6.67 × 10⁶ cells/mL. Conclusion: A sample delay of 24 h at RT does not impact the viability and total viable cell numbers. When long-term delays exist (>4 d) total viable cell number and cell viability losses are reduced in samples stored at 4 °C. Immune phenotype and function are slightly altered after 24 h of storage, further impacts of storage are reduced in samples stored at 4 °C.

ELK1‑mediated upregulation of lncRNA LBX2‑AS1 facilitates cell proliferation and invasion via regulating miR‑491‑5p/S100A11 axis in colorectal cancer

The aim of the present study was to investigate the role and regulatory mechanism of LBX2 antisense RNA 1 (LBX2-AS1) in colorectal cancer. Firstly, LBX2-AS1 expression was detected using reverse transcription-quantitative PCR in colorectal cancer tissues and cells, and its prognostic and diagnostic efficacy was assessed in a colorectal cancer cohort (n=145). Subcellular fractionation assay of LBX2-AS1 was performed. Secondly, the effects of LBX2-AS1 and microRNA (miR)-491-5p on colorectal cancer cell proliferation, apoptosis, migration and invasion were investigated by a series of functional assays. Thirdly, RNA immunoprecipitation, dual-luciferase reporter and gain and loss of function assays were carried out to analyze the interactions between ETS transcription factor ELK1 (ELK1) and LBX2-AS1, as well as LBX2-AS1, miR-491-5p and S100A11. The results showed that LBX2-AS1 was upregulated both in colorectal cancer tissues and cells, which was distributed in the cytoplasm and nucleus of colorectal cancer cells. Clinically, high LBX2-AS1 expression could be an independent prognostic factor for colorectal cancer. Furthermore, relative operating characteristic curve analysis showed that LBX2-AS1 was a sensitive diagnostic marker for colorectal cancer. Highly expressed ELK1, as a transcription factor, could bind to the two conserved sites in the promoter region of LBX2-AS1, thereby activating the transcription of LBX2-AS1. Silencing LBX2-AS1 markedly inhibited proliferative, migratory and invasive abilities of colorectal cancer cells. miR-491-5p expression was downregulated, while S100A11 expression was upregulated in colorectal cancer tissues and cells. Dual-luciferase reporter assays confirmed that LBX2-AS1 could block S100A11 degradation via competitively binding to miR-491-5p. Furthermore, LBX2-AS1 overexpression could notably reverse the inhibitory effect of miR-491-5p on proliferation and invasion of colorectal cancer cells. Taken together, LBX2-AS1 induced by transcription factor ELK1 may facilitate colorectal cancer cell proliferation and invasion via regulation of the miR-491-5p/S100A11 axis. Thus, LBX2-AS1 could be an underlying prognostic and diagnostic marker for colorectal cancer.

Establishment of a Potential Serum Biomarker Panel for the Diagnosis and Prognosis of Cholangiocarcinoma Using Decision Tree Algorithms

Potential biomarkers which include S100 calcium binding protein A9 (S100A9), mucin 5AC (MUC5AC), transforming growth factor β1 (TGF-β1), and angiopoietin-2 have previously been shown to be effective for cholangiocarcinoma (CCA) diagnosis. This study attempted to measure the sera levels of these biomarkers compared with carbohydrate antigen 19-9 (CA19-9). A total of 40 serum cases of CCA, gastrointestinal cancers (non-CCA), and healthy subjects were examined by using an enzyme-linked immunosorbent assay. The panel of biomarkers was evaluated for their accuracy in diagnosing CCA and subsequently used as inputs to construct the decision tree (DT) model as a basis for binary classification. The findings showed that serum levels of S100A9, MUC5AC, and TGF-β1 were dramatically enhanced in CCA patients. In addition, 95% sensitivity and 90% specificity for CCA differentiation from healthy cases, and 70% sensitivity and 83% specificity for CCA versus non-CCA cases was obtained by a panel incorporating all five candidate biomarkers. In CCA patients with low CA19-9 levels, S100A9 might well be a complementary marker for improved diagnostic accuracy. The high levels of TGF-β1 and angiopoietin-2 were both associated with severe tumor stages and metastasis, indicating that they could be used as a reliable prognostic biomarkers panel for CCA patients. Furthermore, the outcome of the CCA burden from the Classification and Regression Tree (CART) algorithm using serial CA19-9 and S100A9 showed high diagnostic efficiency. In conclusion, results have shown the efficacy of CCA diagnosis and prognosis of the novel CCA-biomarkers panel examined herein, which may prove be useful in clinical settings.

Tissue mRNA for S100A4, S100A6, S100A8, S100A9, S100A11 and S100P Proteins in Colorectal Neoplasia: A Pilot Study

S100 proteins are involved in the pathogenesis of sporadic colorectal carcinoma through different mechanisms. The aim of our study was to assess tissue mRNA encoding S100 proteins in patients with non-advanced and advanced colorectal adenoma. Mucosal biopsies were taken from the caecum, transverse colon and rectum during diagnostic and/or therapeutic colonoscopy. Another biopsy was obtained from adenomatous tissue in the advanced adenoma group. The tissue mRNA for each S100 protein (S100A4, S100A6, S100A8, S100A9, S100A11 and S100P) was investigated. Eighteen biopsies were obtained from the healthy mucosa in controls and the non-advanced adenoma group (six individuals in each group) and thirty biopsies in the advanced adenoma group (ten patients). Nine biopsies were obtained from advanced adenoma tissue (9/10 patients). Significant differences in mRNA investigated in the healthy mucosa were identified between (1) controls and the advanced adenoma group for S100A6 (p = 0.012), (2) controls and the non-advanced adenoma group for S100A8 (p = 0.033) and (3) controls and the advanced adenoma group for S100A11 (p = 0.005). In the advanced adenoma group, differences between the healthy mucosa and adenomatous tissue were found in S100A6 (p = 0.002), S100A8 (p = 0.002), S100A9 (p = 0.021) and S100A11 (p = 0.029). Abnormal mRNA expression for different S100 proteins was identified in the pathological adenomatous tissue as well as in the morphologically normal large intestinal mucosa.