Serum Small Proline-Rich Protein 2A (SPRR2A) Is a Noninvasive Biomarker in Gastric Cancer

Advances in carcinoembryonic antigen detection: a review of clinical applications and standardization

Carcinoembryonic antigen (CEA) is among the earliest identified tumor markers and remains extensively utilized in the diagnosis and management of colorectal cancer. The detection of CEA presents considerable challenges in the field of analytical chemistry, given its complexity. The most prevalent detection approach is the immunoassay, including the chemiluminescence immunoassay commonly employed in clinical settings; however, discrepancies between various methods persist. Mass spectrometry-based techniques offer enhanced accuracy as they circumvent matrix interference. Nonetheless, the intricate nature of proteins continues to pose significant challenges. This paper reviews recent advancements in CEA detection technologies, examines their clinical application potential from two key platforms, and addresses the standardization process of CEA detection. This paper highlights the importance of developing rapid and precise methods for CEA analysis in complex matrices and their standardization.

Development and validation of a prediction model for gastric cancer: a single-center prospective study

OBJECTIVE

This study aimed to develop and validate a novel nomogram for diagnosing gastric cancer (GC).

METHODS

In this prospective analysis, 146 patients of Wenzhou Central Hospital were recruited for a GC group and a benign lesion group and were divided into a training set and an internal validation set in a ratio of 7:3. Clinical and analytical characteristics were collected and analyzed by logistic regression analysis. The performance of the predictive model was evaluated using the receiver operating characteristic curve, calibration curve, and decision curve analysis.

RESULTS

There were 5 variables, namely albumin, carcinoembryonic antigen, carbohydrate antigen 125, creatinine, and small proline-rich protein 2A, that were identified as the final parameters for the developed model. In the training and internal validation sets, the area under the curve of the model was 0.968 and 0.979, respectively, showing good diagnostic performance.

CONCLUSION

This study developed and validated a new nomogram based on 5 parameters. This model shows good diagnostic performance in distinguishing GC from benign lesion groups and has certain significance in clinical application.

Protein Biomarkers of Gastric Preneoplasia and Cancer Lesions in Blood: A Comprehensive Review

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. It is often associated with a bad prognosis because of its asymptomatic phenotype until advanced stages, highlighting the need for its prevention and early detection. GC development is preceded by the emergence of gastric preneoplasia lesions (GPNLs), namely atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia (DYS). GC is currently diagnosed by endoscopy, which is invasive and costly and has limited effectiveness for the detection of GPNLs. Therefore, the discovery of non-invasive biomarkers in liquid biopsies, such as blood samples, in order to identify the presence of gastric preneoplasia and/or cancer lesions at asymptomatic stages is of paramount interest. This comprehensive review provides an overview of recently identified plasma/serum proteins and their diagnostic performance for the prediction of GPNLs and early cancer lesions. Autoantibodies appear to be promising biomarkers for AG, IM and early gastric cancer detection, along with inflammation and immunity-related proteins and antibodies against H. pylori virulence factors. There is a lack of specific protein biomarkers with which to detect DYS. Despite the need for further investigation and validation, some emerging candidates could pave the way for the development of reliable, non-invasive diagnostic tests for the detection and prevention of GC.

Single-cell sequencing highlights heterogeneity and malignant progression in actinic keratosis and cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the second most frequent of the keratinocyte-derived malignancies with actinic keratosis (AK) as a precancerous lesion. To comprehensively delineate the underlying mechanisms for the whole progression from normal skin to AK to invasive cSCC, we performed single-cell RNA sequencing (scRNA-seq) to acquire the transcriptomes of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC, and their matched normal tissues, covering comprehensive clinical courses of cSCC. We identified diverse cell types, including important subtypes with different gene expression profiles and functions in major keratinocytes. In SCCIS, we discovered the malignant subtypes of basal cells with differential proliferative and migration potential. Differentially expressed genes (DEGs) analysis screened out multiple key driver genes including transcription factors along AK to cSCC progression. Immunohistochemistry (IHC)/immunofluorescence (IF) experiments and single-cell ATAC sequencing (scATAC-seq) data verified the expression changes of these genes. The functional experiments confirmed the important roles of these genes in regulating cell proliferation, apoptosis, migration, and invasion in cSCC tumor. Furthermore, we comprehensively described the tumor microenvironment (TME) landscape and potential keratinocyte-TME crosstalk in cSCC providing theoretical basis for immunotherapy. Together, our findings provide a valuable resource for deciphering the progression from AK to cSCC and identifying potential targets for anticancer treatment of cSCC.

Development and validation of prognostic index based on purine metabolism genes in patients with bladder cancer

Background

Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and is associated with significant morbidity and mortality worldwide. Dysregulation of tumor metabolic pathways is closely linked to the initiation and proliferation of BLCA. Tumor cells exhibit distinct metabolic activities compared to normal cells, and the purine metabolism pathway, responsible for providing essential components for DNA and RNA synthesis, is believed to play a crucial role. However, the precise involvement of Purine Metabolism Genes (PMGs) in the defense mechanism against BLCA remains elusive.

Methods

The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of PMGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and PMGs, unraveling their functional relevance and potential implications in BLCA.

Results

PMGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including CLDN6, CES1, SOST, SPRR2A, MYBPH, CGB5, and KRT1, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CRTAC1 was identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles.

Conclusion

PMGs have been implicated in the etiology and progression of bladder cancer (BLCA). Prognostic models corresponding to this malignancy aid in the accurate prediction of patient outcomes. Notably, exploring the potential therapeutic targets within the tumor microenvironment (TME) such as PMGs and immune cell infiltration holds promise for effective BLCA management, albeit necessitating further research. Moreover, the identification of a gene signature associated with purine Metabolism presents a credible and alternative approach for predicting BLCA, signifying a burgeoning avenue for targeted therapeutic investigations in the field of BLCA.

Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer

Background

Bladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood.

Methods

Predictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM.

Results

PyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections.

Conclusions

BLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets.

Beyond keratinocyte differentiation: emerging new biology of small proline-rich proteins

Small proline-rich proteins (SPRRPs) are traditionally known for their function in keratinocyte homeostasis. Recent evidence demonstrates their involvement in additional diverse physiological processes ranging from p53 signaling and direct prevention of DNA damage to bactericidal activities. We highlight these novel, intriguing roles of SPRRPs and discuss them in the context of relevant pathological conditions.

Biomarkers of gastric cancer: current advancement

Gastric cancer (GC) is one of the most prevalent malignant types worldwide, especially in East Asia. Due to its frequently advanced stage at diagnosis, the mortality from GC is high and the prognosis is still unsatisfactory. Thus, early detection using effective screening approaches is vital to decrease the morbidity and mortality of GC. Interestingly, biomarkers can be used for diagnosis, prediction of sensitivity to treatment, and prognosis in GC. The potential biomarkers detectable in liquid biopsies such as circulating tumor cells (CTCs), long non-coding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and exosomes reveal numerous information regarding the early prediction and the outcomes for GC patients. Additionally, using the novel serum biomarkers has opened up new opportunities for diagnosing and monitoring patients with GC. This review mainly summarizes the novel progress and approaches in GC biomarkers, which could be potentially used for early diagnosis and therapy monitoring. Meanwhile, we also discussed the advantages, disadvantages, and future perspectives of GC biomarkers.

Identification of potential metabolic biomarkers of rectal cancer and of the effect of neoadjuvant radiochemotherapy

We report a pilot study on the feasibility of determinations of circulating levels of paraoxonase-1 (PON1) and compounds related to energy metabolism as biomarkers for the evaluation of patients with rectal cancer (RC), and the effects produced by neoadjuvant radiochemotherapy (NRCT). We studied 32 patients treated with radiotherapy plus capecitabine concomitant chemotherapy and 48 control subjects. We identified pre-NRCT PON1 and α-ketoglutarate as the parameters that best discriminated between RC patients and the control group. Receiver operating characteristics analysis of the combination of the two parameters showed an area under the curve (AUC) of 0.918. Moreover, patients who presented a pathological complete response (pCR) to treatment had lower plasma pre-NRCT valine concentrations (AUC of 0.826). Patients who had a relapse had lower concentrations of succinate (AUC of 0.833). The results of the present study illustrate the usefulness of investigating alterations in oxidative stress and metabolism in RC. Due to the small number of patients studied, our results must be considered preliminary, but they suggest that the determination of circulating levels of PON1 and α-ketoglutarate might be a valuable tool for the early diagnosis of RC, while the determination of valine and succinate might effectively predict pCR and the appearance of relapse.