Transcriptomic and microRNA Expression Profiles Identify Biomarkers for Predicting Neo-Chemoradiotherapy Response in Esophageal Squamous Cell Carcinomas (ESCC)

Serum metabolomic profiling for predicting therapeutic response and toxicity in breast cancer neoadjuvant chemotherapy: a retrospective longitudinal study

BACKGROUND

Neoadjuvant chemotherapy (NACT) is the standard-of-care treatment for patients with locally advanced breast cancer (LABC), providing crucial benefits in tumor downstaging. Clinical parameters, such as molecular subtypes, influence the therapeutic impact of NACT. Moreover, severe adverse events delay the treatment process and reduce the effectiveness of therapy. Although metabolic changes during cancer treatment are crucial determinant factors in therapeutic responses and toxicities, related clinical research remains limited.

METHODS

One hundred paired blood samples were collected from 50 patients with LABC before and after a complete NACT treatment cycle. Untargeted metabolomics was used by liquid chromatography-mass spectrometry (LC-MS) to investigate the relationship between dynamically changing metabolites in serum and the responses and toxicities of NACT.

RESULTS

Firstly, we observed significant alterations in serum metabolite levels pre- and post-NACT, with a predominant enrichment in the sphingolipid and amino acid metabolism pathways. Second, pre-treatment serum metabolites successfully predicted the therapeutic response and hematotoxicities during NACT. In particular, molecular subtype variations in favorable treatment responses are linked to acyl carnitine levels. Finally, we discovered that the therapeutic effects of NACT could be attributed to essential amino acid metabolism.

CONCLUSION

This study elucidated the dynamic changes in metabolism during NACT treatment, providing a possibility for developing responsive metabolic signatures for personalized NACT treatment.

In Silico Identification of Dysregulated miRNAs Targeting KRAS Gene in Pancreatic Cancer

Pancreatic cancer (PC) is highly lethal, with KRAS mutations in up to 95% of cases. miRNAs inversely correlate with KRAS expression, indicating potential as biomarkers. This study identified miRNAs targeting KRAS and their impact on PC characteristics using in silico methods. dbDEMC identified dysregulated miRNAs in PC; TargetScan, miRDB, and PolymiRTS 3.0 identified miRNAs specific for the KRAS gene; and OncomiR evaluated the association of miRNAs with clinical characteristics and survival in PC. The correlation between miRNAs and KRAS was analysed using ENCORI/starBase. A total of 210 deregulated miRNAs were identified in PC (116 overexpressed and 94 underexpressed). In total, 16 of them were involved in the regulation of KRAS expression and 9 of these (hsa-miR-222-3p, hsa-miR-30a-5p, hsa-miR-30b-5p, hsa-miR-30e-5p, hsa-miR-377-3p, hsa-miR-495-3p, hsa-miR-654-3p, hsa-miR-877-5p and hsa-miR-885-5p) were associated with the clinical characteristics of the PC. Specifically, the overexpression of hsa-miR-30a-5p was associated with PC mortality, and hsa-miR-30b-5p, hsa-miR-377-3p, hsa-miR-495-3p, and hsa-miR-885-5p were associated with survival. Correlation analysis revealed that the expression of 10 miRNAs is correlated with KRAS expression. The dysregulated miRNAs identified in PC may regulate KRAS and some are associated with clinically relevant features, highlighting their potential as biomarkers and therapeutic targets in PC treatment. However, experimental validation is required for confirmation.

Recent advances in acid sensing by G protein coupled receptors

Changes in extracellular proton concentrations occur in a variety of tissues over a range of timescales under physiological conditions and also accompany virtually all pathologies, notably cancers, stroke, inflammation and trauma. Proton-activated, G protein coupled receptors are already partially active at physiological extracellular proton concentrations and their activity increases with rising proton concentrations. Their ability to monitor and report changes in extracellular proton concentrations and hence extracellular pH appears to be involved in a variety of processes, and it is likely to mirror and in some cases promote disease progression. Unsurprisingly, therefore, these pH-sensing receptors (pHR) receive increasing attention from researchers working in an expanding range of research areas, from cellular neurophysiology to systemic inflammatory processes. This review is looking at progress made in the field of pHRs over the past few years and also highlights outstanding issues.

Comprehensive analysis regarding the prognostic significance of downregulated ferroptosis-related gene AKR1C2 in gastric cancer and its underlying roles in immune response

Ferroptosis is a cell death form that has been reported to be involved in the progression of gastric cancer (GC). However, the underlying mechanism of ferroptosis in GC still needs to be further explored. This study conducted a survey regarding the biological functions of ferroptosis-related gene AKR1C2 in GC. Multiple bioinformatic platforms were applied to indicate that the expression level of AKR1C2 was downregulated in GC tissues, which displayed good prognostic value. Clinical statistics proved that AKR1C2 expression was correlated with several tumor characteristics of GC patients, such as characteristics of N-stage tumor or residual tumor. Additionally, LinkedOmics was employed to explore the co-expression network and molecular pathways of AKR1C2 in GC. Eventually, AKR1C2 was found to be involved in several immune-related signatures, such as immunostimulators, immunoinhibitors, chemokines and chemokine receptors. To sum up, these results may provide a novel insight into the significance and biological functions of ferroptosis-related gene AKR1C2 in GC tumorigenesis.

Development and validation of a prognostic model for esophageal carcinoma based on immune microenvironment using system bioinformatics

Esophageal cancer (EC) is an aggressive malignancy that accounts for numerous cancer-related deaths worldwide. The multimodal combination therapy approach can be potentially used to treat EC effectively. However, distinct biomarker of significant specificity are still needed to develop individualized treatment strategies and provide accurate prognostic predictions. Therefore, we aimed to investigate the associated genes subtypes identified were, IFN-γDominant, Inflammatory, Lymphocyte Depleted, etc. and construct a risk model based on these genes to predict the overall survival (OS) of patients suffering from EC. Three immune subtypes were defined in the Cancer Genome Atlas (TCGA) cohort with different tumor microenvironment (TME) and clinical outcomes based on radio-differentiated immune genes. Subsequently, a risk model of immune characteristics included the immune cell infiltration levels and pathway activity was developed based on the genomic changes between the subtypes. In the TCGA dataset, as well as in subgroup analysis with different stages, gender, age, and pathological type, a high-risk score was identified as an adverse factor for OS using the method of the univariate Cox regression analysis and tROC analysis. Furthermore, it was observed that the high-risk group was characterized by depleted immunophenotype, active cell metabolism, and a high tumor mutation burden (TMB). The low-risk group was characterized by high TME abundance and active immune function. Differences in the biological genotypes may account for the differences in the prognosis and treatment response. Extensive research was carried out, and the results revealed that the low-risk group exhibited a significant level of therapeutic advantage in the field of immunotherapy. A risk model was developed based on the immune characteristics. It can be used to optimize risk stratification for patients suffering from EC. The results can potentially help provide new perspectives on treatment methods.

Serum metabolic traits reveal therapeutic toxicities and responses of neoadjuvant chemoradiotherapy in patients with rectal cancer

Neoadjuvant chemoradiotherapy (nCRT) has become the standard treatment for patients with locally advanced rectal cancer (LARC). Therapeutic efficacy of nCRT is significantly affected by treatment-induced diarrhea and hematologic toxicities. Metabolic alternations in cancer therapy are key determinants to therapeutic toxicities and responses, but exploration in large-scale clinical studies remains limited. Here, we analyze 743 serum samples from 165 LARC patients recruited in a phase III clinical study using untargeted metabolomics and identify responsive metabolic traits over the course of nCRT. Pre-therapeutic serum metabolites successfully predict the chances of diarrhea and hematologic toxicities during nCRT. Particularly, levels of acyl carnitines are linked to sex disparity in nCRT-induced diarrhea. Finally, we show that differences in phenylalanine metabolism and essential amino acid metabolism may underlie distinct therapeutic responses of nCRT. This study illustrates the metabolic dynamics over the course of nCRT and provides potential to guide personalized nCRT treatment using responsive metabolic traits.

Next Generation Sequencing for Potential Regulated Genes and Micro-RNAs of Early Growth Response-1 in the Esophageal Squamous Cell Carcinoma

Esophageal cancer has a poor prognosis due to its aggressiveness and low survival rate. In Ease Asia, esophageal squamous cell carcinoma (ESCC) outnumbers esophageal adenocarcinoma (EAC). The ESCC patients still have high mortality despite modern surgical resection and neoadjuvant treatment. Determining patient and outcome prognostic factors is critical in ESCC treatment. In esophageal cancer, early growth response-1 (Egr-1) is a tumor suppressor gene, but the mechanism and associated genes are unknown. The study utilizes RNA interference method, the platform of Next Generation Sequencing (NGS) and bioinformatics analysis to investigate the influences after the Egr-1 gene slicing on the ESCC cells. The heat maps of differentially expressed mRNA and microRNAs were analyzed using the algorithm, Burrows-Wheller Aligner. The study showed that the expression of 51 mRNA and 26 microRNAs have significant changes in ESCC cells after Egr-1 knockdown. The KEGG enrichment analysis linked Egr-1-regulated genes and microRNAs. Egr-1 interactions with these genes and microRNAs may be important in tumor progression. In conclusions, this study provided the transcriptome patterns and relating pathway analysis for Egr-1 knockdown in ESCC cells. The mRNA and microRNAs altered by Egr-1 gene silencing might provide key information in the treatment of ESCC.

The Key Clinical Questions of Neoadjuvant Chemoradiotherapy for Resectable Esophageal Cancer—A Review

Over 50% of individuals with esophageal cancer (EC) present with advanced stages of the disease; therefore, their outcome following surgery alone is poor, with only 25%–36% being alive 5 years post-surgery. Based on the evidence that the CROSS and NEOCRTEC5010 trials provided, neoadjuvant chemoradiotherapy (nCRT) is now the standard therapy for patients with locally advanced EC. However, there are still many concerning clinical questions that remain controversial such as radiation dose, appropriate patient selection, the design of the radiation field, the time interval between chemoradiotherapy (CRT) and surgery, and esophageal retention. With immune checkpoint inhibitors (ICIs) rapidly becoming a mainstay of cancer therapy, along with radiation, chemotherapy, and surgery, the combination mode of immunotherapy is also becoming a hot topic of discussion. Here, we try to provide constructive suggestions to answer the perplexing problems and clinical concerns for the progress of nCRT for EC in the future.

Development of a prediction model for radiotherapy response among patients with head and neck squamous cell carcinoma based on the tumor immune microenvironment and hypoxia signature

INTRODUCTION

The immune system and hypoxia are major factors influencing radiosensitivity in patients with different cancer types. This study aimed at developing a model to predict radiotherapy response in patients with head and neck squamous cell carcinoma (HNSCC) based on the tumor immune microenvironment and hypoxia signature.

MATERIALS AND METHODS

We first evaluated the hypoxia status and tumor immune microenvironment in the Cancer Genome Atlas (TCGA) cohort by using transcriptomic data. Differentially expressed genes (DEGs) were identified between the "high immunity and low hypoxia" and "low immunity and high hypoxia" groups and those DEGs significantly associated with disease-specific survival in the univariate Cox regression analysis were selected as the prognostic DEGs. We selected the immune hypoxia-related genes (IHRGs) by intersecting prognostic DEGs with immune and hypoxia gene sets. We used the IHRGs to train a multivariate Cox regression model in the TCGA cohort, based on which we calculated the IHRG prognostic index (IHRGPI) for each patient and validated its efficacy in predicting radiotherapy response in the Gene Expression Omnibus cohorts. Furthermore, we explored potential mechanisms and effective combinational treatment strategies for different IHRGPI groups.

RESULTS

Five IHRGs were used to construct the IHRGPI, which was used to dichotomize the cohorts. The patients with lower IHRGPI showed a better radiotherapy response across different cohorts and endpoints, including overall survival, progression-free survival, and recurrence-free survival (p < 0.05). Patients with higher IHRGPI showed greater hypoxia and lesser immune cell infiltration. A lower IHRGPI indicated a better immunotherapy response, while a higher IHRGPI indicated a better chemotherapy response.

CONCLUSIONS

IHRGPI is promising for predicting radiotherapy response and guiding combinational treatment strategies in patients with HNSCC.

Bioinformatics-based identification of miRNAs, mRNA, and regulatory signaling pathways involved in esophageal squamous cell carcinoma

Aim

The current study analyzed the miRNA microarray dataset (GSE66274) and gene expression microarray dataset (GSE38129) with similar samples to achieve a better understanding of miRNA-mRNA interactions.

Background

The most common form of esophageal cancer is esophageal squamous cell carcinoma (ESCC). While, miRNAs are well recognized as having a critical regulatory role in human cancer, their responsibilities and mechanisms of miRNA-mRNA in ESCC are unknown.

Methods

Differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were identified using the LIMMA package in R. In total, 478 DEmRNA (224 upregulated and 254 downregulated) and 39 DEmiRNA (15 upregulated and 24 downregulated) were screened. The RNAInter database analyzed miRNA-mRNA interactions; then, the miRNA-mRNA network was visualized by Cytoscape software. ClusterProfiler packages were used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEmRNA as targets of DEmiRNAs.

Results

KEGG pathway analysis indicated that the p53 signaling pathway, ECM-receptor interaction, and AGE-RAGE signaling pathway were significant. Cellular response to amino acid stimulus, negative regulation of apoptotic signaling pathway, and endoderm formation were most prevalent in the biological process category. Additionally, the collagen-containing extracellular matrix, actomyosin complex collagen trimers, basement membrane, and extracellular matrix structural constituent were more enriched.

Conclusion

Overall, the present survey provides evidence that could support the prognosis of esophageal tumors in the future.