Translational value of IDH1 and DNA methylation biomarkers in diagnosing lung cancers: a novel diagnostic panel of stage and histology-specificity

Construction and analysis of the invasive prediction model for pulmonary nodules: based on clinical, CT image and DNA methylation characteristics

Background

Accurately identifying whether pulmonary nodules are microinvasive adenocarcinoma or invasive carcinoma (MIA or IC) is clinically significant. This study aims to construct a predictive model for this.

Methods

Clinical, computed tomography (CT) image, and peripheral blood methylation data of 294 patients were collected. Based on postoperative pathology, they were divided into invasive (MIA or IC) and non-invasive groups. A quarter of the data was randomly selected as the validation set, and the rest was the training set. Screened significant indicators in training set and divided into three groups: clinical and image features, methylation features, and comprehensive features combining both. Logistic regression analyses were conducted respectively to construct models, and the model effect was verified in the validation set.

Results

There were six indicators in the comprehensive model (proportion of solid components, maximum CT value, SH3BP5_338_ CpG 4, PNPLA2_329_CpG 1, PNPLA2_329_CpG 4, and ARHGAP35 476_CpG_5). The area under the curve (AUC) of the training set and the validation set were 0.90 and 0.87, respectively. Prediction accuracies were 82% and 82%, sensitivities were 82% and 80%, specificities were 82% and 84%. The predictive effect of comprehensive model was better than that of the clinical and image feature model and the methylation feature model.

Conclusions

The invasiveness predictive model for pulmonary nodules constructed by combining clinical, CT image, and methylation features in this study has a relatively satisfactory effect and is worthy of further exploration and improvement.

Cell-free and extrachromosomal DNA profiling of small cell lung cancer

Small cell lung cancer (SCLC) is highly aggressive with poor prognosis. Despite a relative prevalence of circulating tumour DNA (ctDNA) in SCLC, liquid biopsies are not currently implemented, unlike non-SCLC where cell-free DNA (cfDNA) mutation profiling in the blood has utility for guiding targeted therapies and assessing minimal residual disease. cfDNA methylation profiling is highly sensitive for SCLC detection and holds promise for disease monitoring and molecular subtyping; cfDNA fragmentation profiling has also demonstrated clinical potential. Extrachromosomal DNA (ecDNA), that is often observed in SCLC, promotes tumour heterogeneity and chemotherapy resistance and can be detected in blood. We discuss how these cfDNA profiling modalities can be harnessed to expand the clinical applications of liquid biopsy in SCLC.

Data-mining-based biomarker evaluation and experimental validation of SHTN1 for bladder cancer

BACKGROUND

Gene therapy in bladder cancer (BLCA) remains an area ripe for exploration. Recent studies have highlighted the crucial role of SHTN1 in the initiation and progression of various cancers and SHTN1 may have interacted with the FGFR gene. However, its specific function in BLCA remains unclear.

MATERIALS AND METHODS

We investigated the association between SHTN1 expression and prognosis, immune infiltration, and the tumor microenvironment (TME) across multiple malignancies using 433 BLCA samples from The Cancer Genome Atlas (TCGA). Differential gene expression analysis, functional annotation via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed for SHTN1-related genes by using R packages. Immune response and TME scores, along with drug sensitivity profiles of SHTN1, were analyzed using R packages. Immunohistochemistry (IHC) and western blotting were conducted to assess SHTN1 expression in surgical specimens from BLCA patients.CCK8 assay and cells wound healing assay were performed.The bioinformatics was analyzed by R software. Significant differences were evaluated using unpaired t test.

RESULTS

SHTN1 expression levels were significantly elevated in BLCA associated with poor prognosis (p < 0.01). Receiver operating characteristic (ROC) curves and nomograms demonstrated the diagnostic and prognostic efficacy of SHTN1 in BLCA. Notably, SHTN1 expression was higher in high-grade BLCA compared to lower-grade (p = 5.6e-10), a finding corroborated by IHC and western blotting. Pathway enrichment analysis revealed significant involvement of the Neuroactive ligand-receptor interaction and Chemical carcinogenesis - DNA adducts signaling pathways among SHTN1 differentially expressed genes. In terms of immune infiltration, T cells CD8, T cells follicular helper, and dendritic cells were predominant in the SHTN1 low-expression group, whereas macrophages M0 and M2, and mast cells were predominant in the high-expression group. Multivariate Cox regression analysis identified SHTN1 as an independent prognostic factor for overall survival (HR = 2.93; 95 % CI = 1.40-6.13; p = 0.004).CCK8 and wound healing experiments showed that SHTN1 knockdown reduced the cell proliferation and migration. Western blot showed that the EMT pathway was clearly associated with SHTN1.

CONCLUSIONS

Our findings suggest that SHTN1 holds promise as a prognostic and diagnostic biomarker for BLCA. Moreover, it is closely associated with elevated immune infiltration and distinct characteristics of the tumor microenvironment in BLCA.

Circulating tumour DNA analysis for early detection of lung cancer: a systematic review

Background

Circulating tumor DNA (ctDNA) analysis has been applied in cancer diagnostics including lung cancer. Specifically for the early detection purpose, various modalities of ctDNA analysis have demonstrated their potentials. Such analyses have showed diverse performance across different studies.

Methods

We performed a systematic review of original studies published before 1 January 2023. Studies that evaluated ctDNA alone and in combination with other biomarkers for early detection of lung cancer were included.

Results

The systematic review analysis included 56 original studies that were aimed for early detection of lung cancer. There were 39 studies for lung cancer only and 17 for pan-cancer early detection. Cancer and control cases included were heterogenous across studies. Different molecular features of ctDNA have been evaluated, including 7 studies on cell-free DNA concentration, 17 on mutation, 29 on methylation, 5 on hydroxymethylation and 8 on fragmentation patterns. Among these 56 studies, 17 have utilised different combinations of the above-mentioned ctDNA features and/or circulation protein markers. For all the modalities, lower sensitivities were reported for the detection of early-stage cancer.

Conclusions

The systematic review suggested the clinical utility of ctDNA analysis for early detection of lung cancer, alone or in combination with other biomarkers. Future validation with standardised testing protocols would help integration into clinical care.

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives

The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA

Background

Lung cancer is the leading cause of cancer morbidity and mortality worldwide, however, the individualized treatment is still unsatisfactory. DNA methylation can affect gene regulation and may be one of the most valuable biomarkers in predicting the prognosis of lung adenocarcinoma. This study was aimed to identify methylation CpG sites that may be used to predict lung adenocarcinoma prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used to detect methylation CpG sites associated with lung adenocarcinoma prognosis and construct a methylation signature model. Then, a Chinese cohort was carried out to estimate the association between methylation and lung adenocarcinoma prognosis. Biological function studies, including demethylation treatment, cell proliferative capacity, and gene expression changes in lung adenocarcinoma cell lines, were further performed.

Results

In the TCGA set, three methylation CpG sites were selected that were associated with lung adenocarcinoma prognosis (cg14517217, cg15386964, and cg18878992). The risk of mortality was increased in lung adenocarcinoma patients with the gradual increase level of methylation signature based on three methylation sites levels (HR = 45.30, 95% CI = 26.69–66.83; p < 0.001). The C‐statistic value increased to 0.77 when age, gender, and other clinical variables were added to the signature to prediction model. A similar situation was confirmed in Chinese lung adenocarcinoma cohort. In the biological function studies, the proliferative capacity of cell lines was inhibited when the cells were demethylated with 5‐aza‐2'‐deoxycytidine (5‐aza‐2dC). The mRNA and protein expression levels of SEPT9 and HIST1H2BH (cg14517217 and cg15386964) were downregulated with different concentrations of 5‐aza‐2dC treatment, while cg18878992 showed the opposite result.

Conclusion

This study is the first to develop a three‐CpG‐based model for lung adenocarcinoma, which is a practical and useful tool for prognostic prediction that has been validated in a Chinese population.

The Neglected Role of Trichomonas tenax in Oral Diseases: A Systematic Review and Meta-analysis

PURPOSE

Trichomonas tenax (T. tenax) is a commensal flagellated protozoan found in periodontal microenvironment of the oral cavity, with a possible role in periodontal diseases. The purpose of the present systematic review and meta-analysis was to determine the worldwide prevalence of T. tenax infection and to show the neglected association of this parasitic infection with oral diseases.

METHODS

To find literatures published until August 2020, five English databases (PubMed, Scopus, Science Direct, Web of Science and Google Scholar) were explored. Finally, 65 papers were qualified to be included in the current study.

RESULTS

Our results revealed a global pooled prevalence of 17% (95% CI 14-22%) for T. tenax infection. The highest prevalence was estimated at 56% (42-69%) in Chile, while the lowest prevalence was related to Kenya with 3% (1-6%). The age-based analysis found that the infection was most common in 46-55 mean age group with 15% (0-100%). The overall prevalence regarding culture method, molecular method and direct method was 21% (12-32%), 19% (8-35%) and 17% (12-23%), respectively. Moreover, the subgroup analysis showed the pooled prevalence in patient with candidiasis [22% (3-52%)], gingivitis [21% (9-36%)] and periodontitis [27% (10-48%)].

CONCLUSION

Our study specified a connection between T. tenax protozoa and periodontitis disease. However, more epidemiological studies as well as clinical trials are needed to precisely identify this relation.